Search

Abstract An extension of the well-known delayed resonator concept is proposed with the objective to enhance its robustness in vibration suppression under guaranteeing stability of the overall set up. The novel resonator feedback is based on an acceleration measurements passing through a delay of polynomial distribution. The feedback design is formulated as an optimization problem over the parameter set formed by the polynomial coefficients and the gain of the delay free part. The first objective is to minimize the sensitivity of the resonator performance with respect to variations of the excitation frequency, i.e. to widen its frequency stop-band centered at the nominal excitation frequency. The second, equally significant objective is to guarantee that this does not lead to instability of the overall mechanical system coupled with the absorber and to ensure sufficient stability margin. The arising non-convex and non-smooth optimization problem is widely discussed and a penalty method is developed, where the unconstrained problem in every iteration step is solved using available software tools for optimization and spectral design of time delay systems. The proposed design technique is validated by simulations for two case study examples. [ABSTRACT FROM AUTHOR]

A novel power-split powertrain is proposed for the electric vehicles (EVs), which consists of dual propelling motor and one planetary gear set. The original motor is replaced by two downsize motor without changing the total power. The power distribution between the two downsize motors is determined by the parameters specifications of planetary gear set, which ensures the dual input powertrain has at least the same drivability performance as conventional single input powertrain. The planetary gear set is used to realize the power-split function by adjusting the gear ratio continuously to improve overall motor efficiency. The multibody dynamic model of the planetary gear set is built, considering the effect of inertia of all components. Based on the efficiency maps of the two motors, an energy management optimization model is built to minimize the consumed power of motors and transmission at each instant. The acceleration of sun gear and mechanical power of planetary gear set are constrained to avoid the large impact of transmission. A penalty factor is introduced in the objective function to realize the robust control of motor speed. Three driving cycles are used to demonstrate the improvement of energy efficiency compared to the traditional EVs with single-speed transmission. [ABSTRACT FROM AUTHOR]

We describe an effective and efficient strategy building steganography detector for patch synthesis based steganography, one case of which is reversible texture synthesis based steganography method proposed by Wu et al. (2015). By exploiting the observation that steganography destroys optimization of matching extent between the synthetic patch and optimal candidate patch, we reconstruct the two patches from an overlapped region to extract the existence of optimality, which are distinct between cover and stego images, to form features. Support vector machine (SVM) is implemented for classification. Meanwhile, a variant of Wu et al.’s steganographic method is proposed with reinforced security, by padding redundant regions carrying no message around the periphery of the synthesized image and generating additional candidate patches to increase capacity. Experiments demonstrate that the modified algorithm offers not only better resistance against the state-of-the-art steganalysis methods and steganalytic attack we developed, but also a larger embedding capacity. [ABSTRACT FROM AUTHOR]

Consider the task of recovering an unknown n -vector from phaseless linear measurements. This nonconvex problem may be convexified into a semidefinite rank-one matrix recovery problem, known as PhaseLift. Under a linear number of Gaussian measurements, PhaseLift recovers the unknown vector exactly with high probability. Under noisy measurements, the solution to a variant of PhaseLift has error proportional to the ℓ 1 norm of the noise. In the present paper, we study the robustness of this variant of PhaseLift to gross, arbitrary corruptions. We prove that PhaseLift can tolerate noise and a small, fixed fraction of gross errors, even in the highly underdetermined regime where there are only O ( n ) measurements. The lifted phase retrieval problem can be viewed as a rank-one robust Principal Component Analysis (PCA) problem under generic rank-one measurements. From this perspective, the proposed convex program is simpler than the semidefinite version of the sparse-plus-low-rank formulation standard in the robust PCA literature. Specifically, the rank penalization through a trace term is unnecessary, and the resulting optimization program has no parameters that need to be chosen. [ABSTRACT FROM AUTHOR]

Shimmy vibration is the oscillatory motion of the fork–wheel assembly about the steering axis. It represents one of the major problem of aircraft landing gear because it can lead to excessive wear, discomfort as well as safety concerns. Based on the nonlinear model of the mechanics of a single wheel nose landing gear (NLG), electromechanical actuator and tire elasticity, a robust active controller capable of damping shimmy vibration is designed and investigated in this study. A novel Decline Population Swarm Optimization ( P D SO ) procedure is introduced and used to select the optimal parameters for the controller. The P D SO procedure is based on a decline demographic model and shows high global search capability with reduced computational costs. The open and closed loop system behavior is analyzed under different case studies of aeronautical interest and the effects of torsional free play on the nose landing gear response are also studied. Plant parameters probabilistic uncertainties are then taken into account to assess the active controller robustness using a stochastic approach. [ABSTRACT FROM AUTHOR]

This paper considers the problem of recovering the delays and amplitudes of a weighted superposition of pulses. This problem is motivated by a variety of applications, such as ultrasound and radar. We show that for univariate and bivariate stream of pulses, one can recover the delays and weights to any desired accuracy by solving a tractable convex optimization problem, provided that a pulse-dependent separation condition is satisfied. The main result of this paper states that the recovery is robust to additive noise or model mismatch. [ABSTRACT FROM AUTHOR]

Load identification becomes essential when direct measurement of structure loads is unavailable. In this paper, a method for localization and identification of impact is proposed. The location of impact is first determined with an error functional indicator using the Complex Method. The identification of impact history is then considered a constrained optimization problem. The solution of the problem is found using Gradient Projection Method. Both numerical and experiment results proved the validity of the proposed method. The identification process is faster and more robust with the techniques introduced. Further discussion and advice for implementation are also provided. [ABSTRACT FROM AUTHOR]

A linear quadratic regulator based optimization problem is formulated in order to minimize the broad-band low-frequency domain vibration and acoustic response of a baffled simply supported plate by means of multiple optimally tuned mass–spring–damper systems. To this end, we propose a robust method to obtain a (stable) state–space model describing the far-field radiated sound power, also known as the radiation filter. The Kirchhoff plate equation, which describes the plate vibrations, is discretized based on the Rayleigh–Ritz method. The resulting state–space models of the plate and the mass–springdamper systems are coupled to the radiation filter. Finally, the optimal spring stiffness and damping values of each mass–spring–damper system are successfully obtained by minimizing the kinetic energy or the far-field radiated sound power of the plate for low computational cost. In general, the results indicate that tuned mass-spring-damper systems have great potential to reduce the broadband low frequency vibration and acoustic response of vibro-acoustic systems. From the results, it can be concluded that there are fundamental differences between the optimal TMD systems if one minimizes the kinetic energy or the far-field radiated sound power. [ABSTRACT FROM AUTHOR]

We introduce a new methodology for inferring the accuracy of computational simulations through the practice of solution verification. We demonstrate this methodology on examples from computational heat transfer, fluid dynamics and radiation transport. Our methodology is suited to both well- and ill-behaved sequences of simulations. Our approach to the analysis of these sequences of simulations incorporates expert judgment into the process directly via a flexible optimization framework, and the application of robust statistics. The expert judgment is systematically applied as constraints to the analysis, and together with the robust statistics guards against over-emphasis on anomalous analysis results. We have named our methodology Robust Verification . Our methodology is based on utilizing multiple constrained optimization problems to solve the verification model in a manner that varies the analysis' underlying assumptions. Constraints applied in the analysis can include expert judgment regarding convergence rates (bounds and expectations) as well as bounding values for physical quantities (e.g., positivity of energy or density). This approach then produces a number of error models, which are then analyzed through robust statistical techniques (median instead of mean statistics). This provides self-contained, data and expert informed error estimation including uncertainties for both the solution itself and order of convergence. Our method produces high quality results for the well-behaved cases relatively consistent with existing practice. The methodology can also produce reliable results for ill-behaved circumstances predicated on appropriate expert judgment. We demonstrate the method and compare the results with standard approaches used for both code and solution verification on well-behaved and ill-behaved simulations. [ABSTRACT FROM AUTHOR]

With the correction of the level set function by the use of Lagrangian maker particles, the particle level method has been proven to be an accurate and robust scheme to capture the evolution of moving interface [1] . In this work, together with the later improved version [2] , the drawbacks of the particle correction procedure in the original particle level set method were investigated in detail and an optimized particle correction procedure was developed to improve the accuracy and robustness of the implicitly represented moving interface. A refined grid point level set value selection process has been proposed and shown to effectively improve the interface location accuracy through a set of standard advection test cases when using a fast first order accurate semi-Lagrangian solver firstly proposed in [3] . With the implementation of our enhanced level set value selection procedure during the particle correction stage, it was observed that the particle reseeding was not required, which allowed for faster runtime performance of the fast particle level set method without compromising interface position accuracy. [ABSTRACT FROM AUTHOR]

Info-Gap Decision Theory is adopted to assess the robustness of a technique aimed at identifying the optimal excitation signal to be used for active sensing approaches to damage detection. Here the term "active sensing" refers to procedures where a known input is applied to the structure to enhance the damage detection process. Given limited system response measurements and ever-present physical limits on the level of excitation, the ultimate goal of the mentioned technique is to improve the detectability of damage by increasing the difference between measured outputs of the undamaged and damaged systems. In particular, a two degree-of-freedom mass-spring-damper system characterized by the presence of a nonlinear stiffness is considered. Uncertainty is introduced to the system in the form of deviations of its parameters (mass, stiffness, damping ratio) from their nominal values. Variations in the performance of the mentioned technique are then evaluated both in terms of changes in the estimated difference between the responses of the damaged and undamaged systems and in terms of deviations of the identified optimal input signal from its nominal estimation. Finally, plots of the performances of the analyzed algorithm for different levels of uncertainty are obtained, enabling a clear evaluation of the risks connected with designing excitation signals for damage detection, when the parameters that dictate system behavior (e.g. stiffness, mass) are poorly characterized or improperly modeled. [ABSTRACT FROM AUTHOR]

Foraging, either solitarily or collectively, is a necessary behavior for survival that is demonstrated by many organisms. Foraging can be collectively optimized by utilizing communication between the organisms. Examples of such communication range from high level strategic foraging by animal groups to rudimentary signaling among unicellular organisms. Here we systematically study the simplest form of communication via long range repulsive interactions between multiple diffusing Brownian searchers on a one-dimensional lattice. We show that the mean first passage time for any one of them to reach a fixed target depends non-monotonically on the range of the interaction and can be optimized for a repulsive range that is comparable to the average spacing between searchers. Our results suggest that even the most rudimentary form of collective searching does in fact lower the search time for the foragers suggesting robust mechanisms for search optimization in cellular communities. [ABSTRACT FROM AUTHOR]

This article studies two regularized robust estimators of scatter matrices proposed (and proved to be well defined) in parallel in Chen et al. (2011) and Pascal et al. (2013), based on Tyler’s robust M-estimator (Tyler, 1987) and on Ledoit and Wolf’s shrinkage covariance matrix estimator (Ledoit and Wolf, 2004). These hybrid estimators have the advantage of conveying (i) robustness to outliers or impulsive samples and (ii) small sample size adequacy to the classical sample covariance matrix estimator. We consider here the case of i.i.d. elliptical zero mean samples in the regime where both sample and population sizes are large. We demonstrate that, under this setting, the estimators under study asymptotically behave similar to well-understood random matrix models. This characterization allows us to derive optimal shrinkage strategies to estimate the population scatter matrix, improving significantly upon the empirical shrinkage method proposed in Chen et al. (2011). [ABSTRACT FROM AUTHOR]

Conventional local preserving projection (LPP) is sensitive to outliers because its objective function is based on the L2-norm distance criterion and suffers from the small sample size (SSS) problem. To improve the robustness of LPP against outliers, LPP-L1 uses L1-norm distance metric. However, LPP-L1 does not work ideally when there are larger outliers. We propose a more robust version of LPP, called LPP-MCC, which formulates the objective problem based on maximum correntropy criterion (MCC). The objective problem is efficiently solved via a half-quadratic optimization procedure and the complicated non-linear optimization procedure can thereby be reduced to a simple quadratic optimization at each iteration. Moreover, LPP-MCC avoids the SSS problem because the generalized eigenvalues computation is not involved in the optimization procedure. The experimental results on both synthetic and real-world databases demonstrate that the proposed method can outperform LPP and LPP-L1 when there are large outliers in the training data. [ABSTRACT FROM AUTHOR]

Highlights: [•] We optimize a multiple-quantum filter sequence for lactate editing. [•] Pulses derived from optimal control achieve robust excitation of lactate. [•] The optimized pulses achieve also robust suppression of unwanted signals. [•] The overall editing efficiency in inhomogeneous fields is increased. [Copyright &y& Elsevier]

Abstract: This paper presents the combination of topology optimization and optimal control method to find the optimal match between the material topology and control. In the presented method, the material topology is determined using the SIMP (Solid Isotropic Material with Penalization) method, which has been popularly used in topology optimization. In the SIMP method, the design variable is relaxed and bounded in the interval , and the evolution of the design variable is usually implemented by the method of moving asymptotes (MMA), which can be used to deal with optimization problem with multiple integral constraints and bound constraint of the design variable. In the combination of topology optimization and optimal control method, the control variable appears along with the design variable. In order to evolve the control variable and design variable using MMA simultaneously, the control variable is regularized using a bound constraint and the corresponding bound constraint is projected onto the interval , which is the same as the bound constraint of the design variable. The optimization problem is analyzed using the adjoint method to obtain the adjoint sensitivity. During the optimization procedure, the design and control variables are filtered by the Helmholtz filters to ensure the smoothness of the distribution. To ensure the minimum scale length and remove the gray area in the material topology, the filtered design variable is projected by the threshold method. The feasibility and robustness of the combination of these two methods are demonstrated by several test problems, including heat transfer, fluid flow and compliance minimization. [Copyright &y& Elsevier]

Abstract: This paper presents a technique that allows to untangle high-order/curvilinear meshes. The technique makes use of unconstrained optimization where element Jacobians are constrained to lie in a prescribed range through moving log-barriers. The untangling procedure starts from a possibly invalid curvilinear mesh and moves mesh vertices with the objective of producing elements that all have bounded Jacobians. Bounds on Jacobians are computed using the results of Johnen et al. (2012, 2013) [1,2]. The technique is applicable to any kind of polynomial element, for surface, volume, hybrid or boundary layer meshes. A series of examples demonstrate both the robustness and the efficiency of the technique. The final example, involving a time explicit computation, shows that it is possible to control the stable time step of the computation for curvilinear meshes through an alternative element deformation measure. [Copyright &y& Elsevier]

Abstract: Active appearance models (AAMs) are useful for face tracking for the advantages of detailed face interpretation, accurate alignment and high efficiency. However, they are sensitive to initial parameters and may easily be stuck in local minima due to the gradient-descent optimization, which makes the AAM based face tracker unstable in the presence of large pose deviation and fast motion. In this paper, we propose to combine the view-based AAMs with two novel temporal filters to overcome the limitations. First, we build a new view space based on the shape parameters of AAMs, instead of the model parameters controlling both the shape and appearance, for the purpose of pose estimation. Then the Kalman filter is used to simultaneously update the pose and shape parameters for a better fitting of each frame. Second, we propose a temporal matching filter which is twofold. The inter-frame local appearance constraint is incorporated into AAM fitting, where the mechanism of the active shape model (ASM) is also implemented in a unified framework to find more accurate matching points. Moreover, we propose to initialize the shape with correspondences found by a random forest based local feature matching. By introducing the local information and temporal correspondences, the twofold temporal matching filter improves the tracking stability when confronted with fast appearance changes. Experimental results show that our algorithm is more pose robust than basic AAMs and some state-of-art AAM based methods, and that it can also handle large expressions and non-extreme illumination changes in test video sequences. [Copyright &y& Elsevier]

Abstract: The photorealistic modeling of large-scale objects, such as urban scenes, requires the combination of range sensing technology and digital photography. In this paper, we attack the key problem of camera pose estimation, in an automatic and efficient way. First, the camera orientation is recovered by matching vanishing points (extracted from 2D images) with 3D directions (derived from a 3D range model). Then, a hypothesis-and-test algorithm computes the camera positions with respect to the 3D range model by matching corresponding 2D and 3D linear features. The camera positions are further optimized by minimizing a line-to-line distance. The advantage of our method over earlier work has to do with the fact that we do not need to rely on extracted planar facades, or other higher-order features; we are utilizing low-level linear features. That makes this method more general, robust, and efficient. We have also developed a user-interface for allowing users to accurately texture-map 2D images onto 3D range models at interactive rates. We have tested our system in a large variety of urban scenes. [Copyright &y& Elsevier]

Abstract: This paper presents a new approach to robust multi-objective and multi-level optimization of the design of complex mechanical structures. The optimization is at two levels: system and elements. At system-level, the robust multi-objective problem has four cost functions: on the one hand the minimization of the global mass and displacement at a fixed point of the mechanical structure, and on the other hand the maximization of both the robustness and the displacement of the mass. At element-level the robust multi-objective problem has two cost functions: minimization of the element mass and maximization of its robustness. A robust condensation technique, based on an enriched Karhunen–Loève condensation, is used for complex structures which require a large finite element model. In contrast to existing formulations, this new approach takes into account uncertainties in the design parameters at system-level and element-level. It also allows for the task sharing which is commonly used in structural engineering. [Copyright &y& Elsevier]

Abstract: Several high breakdown robust estimators have been developed to solve computer vision problems involving parametric modeling and segmentation of multi-structured data. Since the cost functions of these estimators are not differentiable functions of parameters, they are commonly optimized by random sampling. This random search can be computationally cumbersome in cases involving segmentation of multiple structures. This paper introduces a high breakdown M-estimator (called HBM for short) with a differentiable cost function that can be directly optimized by iteratively reweighted least squares regression. The fast convergence and high breakdown point of HBM make this estimator an outstanding choice for segmentation of multi-structured data. The results of a number of experiments on range image segmentation and fundamental matrix estimation problems are presented. Those experiments involve both synthetic and real image data and benchmark the performance of HBM estimator both in terms of accurate segmentation of numerous structures in the data and convergence speed in comparison against a number of modern robust estimators developed for computer vision applications (e.g. pbM and ASKC). The results show that HBM outperforms other estimators in terms of computation time while exhibiting similar or better accuracy of estimation and segmentation. [Copyright &y& Elsevier]

Abstract: We present a novel method to solve the sign ambiguity for phase demodulation from a single interferometric image that possibly contains closed fringes. The problem is formulated in a Markov random field (MRF) energy minimization framework with the assumption of phase gradient orientation continuity. The binary pairwise objective function is non-submodular and therefore its minimization is an NP-hard problem, for which we devise a multigrid hierarchy of quadratic pseudoboolean optimization problems that can be improved iteratively to approximate the optimal solution. We name the method MSARI algorithm, for Markov based sign ambiguity resolution in interferometry. Compared with traditional path-following phase demodulation methods, the new approach does not require any heuristic scanning strategy, is not subject to the propagation of error, and the extension to three dimensional fringe patterns is straightforward. A set of experiments with synthetic data and real prelens tear film interferometric images of the human eye demonstrate the effectiveness and robustness of the proposed algorithm as compared with existing state-of-the-art phase demodulation methods. [Copyright &y& Elsevier]

Abstract: Discriminative classifiers are a popular approach to solving classification problems. However, one of the problems with these approaches, in particular kernel based classifiers such as support vector machines (SVMs), is that they are hard to adapt to mismatches between the training and test data. This paper describes a scheme for overcoming this problem for speech recognition in noise by adapting the kernel rather than the SVM decision boundary. Generative kernels, defined using generative models, are one type of kernel that allows SVMs to handle sequence data. By compensating the parameters of the generative models for each noise condition noise-specific generative kernels can be obtained. These can be used to train a noise-independent SVM on a range of noise conditions, which can then be used with a test-set noise kernel for classification. The noise-specific kernels used in this paper are based on Vector Taylor Series (VTS) model-based compensation. VTS allows all the model parameters to be compensated and the background noise to be estimated in a maximum likelihood fashion. A brief discussion of VTS, and the optimisation of the mismatch function representing the impact of noise on the clean speech, is also included. Experiments using these VTS-based test-set noise kernels were run on the AURORA 2 continuous digit task. The proposed SVM rescoring scheme yields large gains in performance over the VTS compensated models. [Copyright &y& Elsevier]

Abstract: The partial quadratic eigenvalue assignment problem (PQEVAP) concerns reassigning a few undesired eigenvalues of a quadratic matrix pencil to suitably chosen locations and keeping the other large number of eigenvalues and eigenvectors unchanged (no spill-over). The problem naturally arises in controlling dangerous vibrations in structures by means of active feedback control design. For practical viability, the design must be robust, which requires that the norms of the feedback matrices and the condition number of the closed-loop eigenvectors are as small as possible. The problem of computing feedback matrices that satisfy the above two practical requirements is known as the Robust Partial Quadratic Eigenvalue Assignment Problem (RPQEVAP). In this paper, we formulate the RPQEVAP as an unconstrained minimization problem with the cost function involving the condition number of the closed-loop eigenvector matrix and two feedback norms. Since only a small number of eigenvalues of the open-loop quadratic pencil are computable using the state-of-the-art matrix computational techniques and/or measurable in a vibration laboratory, it is imperative that the problem is solved using these small number of eigenvalues and the corresponding eigenvectors. To this end, a class of the feedback matrices are obtained in parametric form, parameterized by a single parametric matrix, and the cost function and the required gradient formulas for the optimization problem are developed in terms of the small number of eigenvalues that are reassigned and their corresponding eigenvectors. The problem is solved directly in quadratic setting without transforming it to a standard first-order control problem and most importantly, the significant “no spill-over property” of the closed-loop eigenvalues and eigenvectors is established by means of a mathematical result. These features make the proposed method practically applicable even for very large structures. Results on numerical experiments show that the proposed method considerably reduces both feedback norms and the sensitivity of the closed-loop eigenvalues. A study on robustness of the system responses of the method under small perturbations show that the responses of the perturbed closed-loop system are compatible with perturbations. [Copyright &y& Elsevier]

Abstract: A trajectory piecewise linearization (TPWL) procedure for the reduced-order modeling of two-phase flow in subsurface formations is developed and applied. The method represents new pressure and saturation states using linear expansions around states previously simulated and saved during a series of preprocessing training runs. The linearized representation is projected into a low-dimensional space, with the projection matrix constructed through proper orthogonal decomposition of the states determined during the training runs. The TPWL model is applied to two example problems, containing 24,000 and 79,200 grid blocks, which are characterized by heterogeneous permeability descriptions. Extensive test simulations are performed for both models. It is shown that the TPWL model provides accurate results when the controls (bottom hole pressures of the production wells in this case) applied in test simulations are within the general range of the controls applied in the training runs, even though the well pressure schedules for the test runs can differ significantly from those of the training runs. This indicates that the TPWL model displays a reasonable degree of robustness. Runtime speedups using the procedure are very significant–a factor of 100–2000 (depending on model size and whether or not mass balance error is computed at every time step) for the cases considered. The preprocessing overhead required by the TPWL procedure is the equivalent of about four high-fidelity simulations. Finally, the TPWL procedure is applied to a computationally demanding multiobjective optimization problem, for which the Pareto front is determined. Limited high-fidelity simulations demonstrate the accuracy and applicability of TPWL for this optimization. Future work should focus on error estimation and on stabilizing the method for large models with significant density differences between phases. [Copyright &y& Elsevier]

Abstract: In this work, we propose a cross-layer solution to robust video multicast in erasure networks based on random linear network coding (RLNC) in the network layer and video interleaving (VI) in the application layer, and call it the joint RLNC-VI scheme. In the RLNC implementation, we partition one video coding unit (VCU) into several priority levels using scalable properties of H.264/SVC video. Packets from the same priority level of several VCUs form one RLNC generation, and unequal protection is applied to different generations. RLNC provides redundancy for video packets in the network layer and has proved to be useful in a multicast environment. Then, we propose a new packet-level interleaving scheme, called the RLNC-facilitated interleaving scheme, where each received packet corresponds to a new constraint on source packets. As a result, it can facilitate the RLNC decoding at the destination node. Furthermore, we study the problem of optimal interleaving design, which selects the optimal interleaving degree and the optimal redundancy of each generation. The tradeoff between delay and received video quality due to the choice of different VCUs is also examined. It is shown by simulation results that the proposed RLNC-VI scheme outperforms the pure RLNC method for robust video multicast in erasure networks. This can be explained by two reasons. First, the VI scheme distributes the impact of the loss (or erasure) of one VCU into partial data loss over multiple neighboring VCUs. Second, the original video content can be easily recovered with spatial/temporal error concealment (EC) in the joint RLNC-VI scheme. [Copyright &y& Elsevier]

Abstract: In order to reduce vibrations or sound levels in industrial vibroacoustic problems, the low-cost and efficient way consists in introducing visco- and poro-elastic materials either on the structure or on cavity walls. Depending on the frequency range of interest, several numerical approaches can be used to estimate the behavior of the coupled problem. In the context of low frequency applications related to acoustic cavities with surrounding vibrating structures, the finite elements method (FEM) is one of the most efficient techniques. Nevertheless, industrial problems lead to large FE models which are time-consuming in updating or optimization processes. A classical way to reduce calculation time is the component mode synthesis (CMS) method, whose classical formulation is not always efficient to predict dynamical behavior of structures including visco-elastic and/or poro-elastic patches. Then, to ensure an efficient prediction, the fluid and structural bases used for the model reduction need to be updated as a result of changes in a parametric optimization procedure. For complex models, this leads to prohibitive numerical costs in the optimization phase or for management and propagation of uncertainties in the stochastic vibroacoustic problem. In this paper, the formulation of an alternative CMS method is proposed and compared to classical (u,p) CMS method: the Ritz basis is completed with static residuals associated to visco-elastic and poro-elastic behaviors. This basis is also enriched by the static response of residual forces due to structural modifications, resulting in a so-called robust basis, also adapted to Monte Carlo simulations for uncertainties propagation using reduced models. [Copyright &y& Elsevier]

Abstract: Nonlinear shape models have been shown to improve the robustness and flexibility of contour-based object segmentation when there are appearance ambiguities between the object and the background. In this paper, we focus on a new search strategy for the shape regularized active contour (ShRAC) model, which adopts existing nonlinear shape models to segment objects that are similar to a set of training shapes. The search for optimal contour is performed by a coarse-to-fine algorithm that iterates between combinatorial search and gradient-based local optimization. First, multi-solution dynamic programming (MSDP) is used to generate initial candidates by minimizing only the image energy. In the second step, a combination of image energy and shape energy is minimized starting from these initial candidates using a local optimization method and the best one is selected. To generate diverse initial candidates while reducing invalid shapes, we apply two pruning methods to the search space of MSDP. Our search strategy combines the advantages of global combinatorial search and local optimization, and has shown excellent robustness to local minima caused by distracting suboptimal solutions. Experimental results on segmentation of different anatomical structures using ShRAC, as well as preliminary results on human silhouette segmentation are provided. [Copyright &y& Elsevier]

Abstract: The problems of robust stabilization and robust control with maximal decay rate are investigated for discrete-time stochastic systems with time-varying norm-bounded parameter uncertainties. For the robust stabilization problem, an optimal state feedback controller is designed, which ensures that the closed-loop system is robustly stochastically stable with maximal decay rate, while for the robust control problem, the designed state feedback controller guarantees that the resulting closed-loop system is with a specified performance level, besides robust stochastic stability with maximal decay rate. The method based on the convex optimization and linear matrix inequality is developed to solve these problems. Two examples are provided to show the effectiveness of the proposed approach. [Copyright &y& Elsevier]

Abstract: Recent advances in forward error correction and scalable video coding enable new approaches for robust, distributed streaming in Mobile Ad Hoc Networks (MANETs). This paper presents an approach for distribution of real time video by uncoordinated peer-to-peer relay or source nodes in an overlay network on top of a MANET. The approach proposed here allows for distributed, rate-distortion optimized transmission-rate allocation for competing scalable video streams at relay nodes in the overlay network. The approach has the desirable feature of path/source diversity that can be used for enhancing reliability in connectivity to serving nodes and/or attaining a higher throughput. The distributed approach reduces signaling overhead as well as avoiding scalability issues that come with centralized processing in MANETs. Results show a significant performance gain over both single-server systems and previously proposed multi-source systems. [Copyright &y& Elsevier]

Abstract: There is an acute need for a functional assay allowing the investigation of efflux pumps. A dedicated procedure was previously developed, but although it was unambiguous, it suffered from a lack of reproducibility. We describe an optimization of the procedure that makes the assay much more robust. [Copyright &y& Elsevier]