FileName
stringlengths 17
17
| Abstract
stringlengths 163
6.01k
| Title
stringlengths 12
421
|
|---|---|---|
S001044851300239X | This article presents a generalized B -spline surface subdivision scheme of arbitrary order with a tension parameter. We first propose a tensor-product subdivision scheme that produces k u × k v order generalized B -spline limit surfaces. Generalized B -spline surface is the unified and extended form of B -splines, trigonometric B -splines and hyperbolic B -splines (Fang et al. 2010). The tensor product subdivision scheme can be used to generate various surfaces of revolution, including those generated by classical analytic curves that can be exactly represented by generalized B -spline curves. By extending a bi-order (say k ) tensor-product scheme to meshes of arbitrary topology, we further propose a generalized surface subdivision scheme with a tension parameter. Several well-known subdivision schemes, including Doo–Sabin subdivision, Catmull–Clark subdivision, and two other subdivision schemes proposed by Morin et al. (2001) and Stam (2001), become special cases of the generalized subdivision scheme. The tension parameter can be used to adjust the shape of subdivision surfaces. The scheme produces higher order C k − 2 continuous limit surfaces except at extraordinary points where the continuity is C 1 . Convenient and hierarchical methods are also presented for embedding sharp features and semi-sharp features on the resulting limit surfaces. | A generalized surface subdivision scheme of arbitrary order with a tension parameter |
S001044851400061X | Axisymmetry and planar reflective symmetry properties of mechanical components can be used throughout a product development process to restructure the modeling process of a component, simplify the computation of tool path trajectories, assembly trajectories, etc. To this end, the restructured geometric model of such components must be at least as accurate as the manufacturing processes used to produce them, likewise their symmetry properties must be extracted with the same level of accuracy to preserve the accuracy of their geometric model. The proposed symmetry analysis is performed on a B-Rep CAD model through a divide-and-conquer approach over the boundary of a component with faces as atomic entities. As a result, it is possible to identify rapidly all global symmetry planes and axisymmetry as well as local symmetries. Also, the corresponding algorithm is fast enough to be inserted in CAD/CAM operators as part of interactive modeling processes, it performs at the same level of tolerance than geometric modelers and it is independent of the face and edge parameterizations. | Fast global and partial reflective symmetry analyses using boundary surfaces of mechanical components |
S0020019014001987 | We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in O ( n log n ) time and O ( n ) space, where n denotes the number of vertices of the polygon. | A simple algorithm for computing positively weighted straight skeletons of monotone polygons |
S0045782513000479 | This article presents a novel approach to collision detection based on distance fields. A novel interpolation ensures stability of the distances in the vicinity of complex geometries. An assumed gradient formulation is introduced leading to a C 1 -continuous distance function. The gap function is re-expressed allowing penalty and Lagrange multiplier formulations. The article introduces a node-to-element integration for first order elements, but also discusses signed distances, partial updates, intermediate surfaces, mortar methods and higher order elements. The algorithm is fast, simple and robust for complex geometries and self contact. The computed tractions conserve linear and angular momentum even in infeasible contact. Numerical examples illustrate the new algorithm in three dimensions. | Distance fields on unstructured grids: Stable interpolation, assumed gradients, collision detection and gap function |
S0045782513001448 | Incompressible smoothed particle hydrodynamics generally requires particle distribution smoothing to give stable and accurate simulations with noise-free pressures. The diffusion-based smoothing algorithm of Lind et al. (J. Comp. Phys. 231 (2012) 1499–1523) has proved effective for a range of impulsive flows and propagating waves. Here we apply this to body–water slam and wave–body impact problems and discover that temporal pressure noise can occur for these applications (while spatial noise is effectively eliminated). This is due to the free-surface treatment as a discontinuous boundary. Treating this as a continuous very thin boundary within the pressure solver is shown to effectively cure this problem. The particle smoothing algorithm is further generalised so that a non-dimensional diffusion coefficient is applied which suits a given time step and particle spacing. We model the particular problems of cylinder and wedge slam into still water. We also model wave-body impact by setting up undisturbed wave propagation within a periodic domain several wavelengths long and inserting the body. In this case, the loads become cyclic after one wave period and are in good agreement with experiment. This approach is more efficient than the conventional wave flume approach with a wavemaker which requires many wavelengths and a beach absorber. Results are accurate and virtually noise-free, spatially and temporally. Convergence is demonstrated. Although these test cases are two-dimensional with simple geometries, the approach is quite general and may be readily extended to three dimensions. | Incompressible smoothed particle hydrodynamics (SPH) with reduced temporal noise and generalised Fickian smoothing applied to body–water slam and efficient wave–body interaction |
S0045782513001473 | We propose a new hybrid algorithm for incompressible micro and nanoflows that applies to non-isothermal steady-state flows and does not require the calculation of the Irving–Kirkwood stress tensor or heat flux vector. The method is validated by simulating the flow in a channel under the effect of a gravity-like force with bounding walls at two different temperatures and velocities. The model shows very accurate results compared to benchmark full MD simulations. In the temperature results, in particular, the contribution of viscous dissipation is correctly evaluated. | A Laplacian-based algorithm for non-isothermal atomistic-continuum hybrid simulation of micro and nano-flows |
S0045782514000607 | The Lagrange Multiplier (LM) and penalty methods are commonly used to enforce incompressibility and compressibility in models of cardiac mechanics. In this paper we show how both formulations may be equivalently thought of as a weakly penalized system derived from the statically condensed Perturbed Lagrangian formulation, which may be directly discretized maintaining the simplicity of penalty formulations with the convergence characteristics of LM techniques. A modified Shamanskii–Newton–Raphson scheme is introduced to enhance the nonlinear convergence of the weakly penalized system and, exploiting its equivalence, modifications are developed for the penalty form. Focusing on accuracy, we proceed to study the convergence behavior of these approaches using different interpolation schemes for both a simple test problem and more complex models of cardiac mechanics. Our results illustrate the well-known influence of locking phenomena on the penalty approach (particularly for lower order schemes) and its effect on accuracy for whole-cycle mechanics. Additionally, we verify that direct discretization of the weakly penalized form produces similar convergence behavior to mixed formulations while avoiding the use of an additional variable. Combining a simple structure which allows the solution of computationally challenging problems with good convergence characteristics, the weakly penalized form provides an accurate and efficient alternative to incompressibility and compressibility in cardiac mechanics. | A displacement-based finite element formulation for incompressible and nearly-incompressible cardiac mechanics |
S0045782514001492 | Discrete element methods can be based on either penalties or impulses to resolve collisions. A generic impulse based method, the energy tracking method (ETM), is described to resolve collisions between multiple non-convex bodies in three dimensions. As opposed to the standard sequential impulse method (SQM) and simultaneous impulse method (SMM), which also apply impulses to avoid penetration, the energy tracking method changes the relative velocity between two colliding bodies iteratively yet simultaneously. Its main novelty is that impulses are applied gradually at multi-point contacts, and energy changes at the contact points are tracked to ensure conservation. Three main steps are involved in the propagation of the impulses during the single- and multi-contact resolution: compression, restitution-related energy loss, and separation. Numerical tests show that the energy tracking method captures the energy conservation property of perfectly elastic single- and multi-point collisions. ETM exhibits improved angular velocity estimation, as compared to SMM and SQM, as demonstrated by two numerical examples that model multi-point contact between box-shaped objects. Angles of repose estimated for multi-object pack repositioning of spheres, cubes, and crosses are in good agreement with the reported experimental values. | An impulse-based energy tracking method for collision resolution |
S0045782514002291 | We consider the extension of the Nitsche method to the case of fluid–structure interaction problems on unfitted meshes. We give a stability analysis for the space semi-discretized problem and show how this estimate may be used to derive optimal error estimates for smooth solutions, irrespectively of the mesh/interface intersection. We also discuss different strategies for the time discretization, using either fully implicit or explicit coupling (loosely coupled) schemes. Some numerical examples illustrate the theoretical discussion. | An unfitted Nitsche method for incompressible fluid–structure interaction using overlapping meshes |
S0045782514002874 | In level set methods for structural topology and shape optimization, the level set function gradients at the design interface need to be controlled in order to ensure stability of the optimization process. One popular way to do this is to enforce the level set function to be a signed distance function by periodically using initialization schemes, which is commonly known as re-initialization. However, such re-initialization schemes are time-consuming, as additional partial differential equations need to be solved in every iteration step. Furthermore, the use of re-initialization brings some undesirable problems; for example, it may move the zero level set away from the expected position. This paper presents a level set method with distance-suppression scheme for structural topology and shape optimization. An energy functional is introduced into the level set equation to maintain the level set function to close to a signed distance function near the structural boundaries, meanwhile forcing the level set function to be a constant at locations far away from the structural boundaries. As a result, the present method not only can avoid the need for re-initialization but also can simplify the setting of the initial level set function. The validity of the proposed method is tested on the mean compliance minimization problem and the compliant mechanisms synthesis problem. Different aspects of the proposed method are demonstrated on a number of benchmarks from the literature of structural optimization. | Structural topology and shape optimization using a level set method with distance-suppression scheme |
S0045782514004812 | Issues related to space–time adaptivity for a class of nonlinear and time-dependent problems are discussed. The dG(k)-methods are adopted for the time integration, and the a posteriori error control is based on the appropriate dual problem in space–time. One key ingredient is to decouple the error generation in space and time with a hierarchical decomposition of the discrete space of dual solutions. The main idea put forward in the paper is to increase the computational efficiency of the adaptive scheme by avoiding recursive adaptations of the whole time-mesh; rather, the space-mesh and the time-step defining each finite space–time slab are defined in a truly sequential fashion. The proposed adaptive strategy is applied to the coupled consolidation problem in geomechanics involving large deformations. Its performance is investigated with the aid of a numerical example in 2D. 1. Compute z h | S n ( k ) based on z h ( t n − 1 − ) that was computed for the previous time slab S n − 1 . Then, solve for the enhanced dual solution z ̃ ∗ | S n ( k ) from the decoupled dual problem A n ∗ ( z h ( k ) ; δ z ∗ , z ̃ ∗ ( k ) ) = L n ∗ ( z h ( k ) ; δ z ∗ , z ̃ H ∗ ( t n + ) ) , whereby it is noted that z ̃ ∗ ( t n + ) has been replaced by the background dual solution z ̃ H ∗ ( t n + ) as the load (or data) for the current space–time slab. Compute the error contributions E n , SOL ( k ) , E ( s ) n , FEM ( k ) , etc. Check the stopping criterion in (68): If E n ( k ) ≤ TOL Δ t n ( k ) T then exit and take a new time step. Refine the space-mesh, the time interval or both: If α − E ( t ) n , FEM ( k ) ≤ E ( s ) n , FEM ( k ) ≤ α + E ( t ) n , FEM ( k ) then refine in space and time uniformly. Else if α + E ( t ) n , FEM ( k ) ≤ E ( s ) n , FEM ( k ) then refine in space: M h , n ( k ) → M h , n ( k + 1 ) , I n ( k ) = I n ( k + 1 ) Else if E ( s ) n , FEM ( k ) ≤ α − E ( t ) n , FEM ( k ) then refine in time: I n ( k ) → I n ( k + 1 ) , M h , n ( k ) = M h , n ( k + 1 ) | A sequential-adaptive strategy in space–time with application to consolidation of porous media |
S0045782516000037 | In this paper, a discontinuous Galerkin method for a nonlinear shear-flexible shell theory is proposed that is suitable for both thick and thin shell analysis. The proposed method extends recent work on Reissner–Mindlin plates to avoid locking without the use of projection operators, such as mixed methods or reduced integration techniques. Instead, the flexibility inherent to discontinuous Galerkin methods in the choice of approximation spaces is exploited to satisfy the thin plate compatibility conditions a priori. A benefit of this approach is that only generalized displacements appear as unknowns. We take advantage of this to craft the method in terms of a discrete energy minimization principle, thereby restoring the Rayleigh–Ritz approach. In addition to providing a straightforward and elegant derivation of the discrete equilibrium equations, the variational character of the method could afford numerous advantages in terms of mesh adaptation and available solution techniques. The proposed method is exercised on a set of benchmarks and example problems to assess its performance numerically, and to test for shear and membrane locking. | A discontinuous Galerkin method for nonlinear shear-flexible shells |
S0045782516000050 | We extend the hierarchical multiscale design framework of Nakshatrala et al. (2013) to nonlinear elastodynamics wherein we use topology optimization to design material micro-structures to achieve desired energy propagation in nonlinear elastic material systems subjected to impact loading. As in Part I, a well-posed topology optimization problem is obtained via (a) relaxation to design the macroscale which requires homogenization theory to relate the macroscopic homogenized response to its micro-structure and (b) via restriction to design the microscale to obtain a well-defined micro-structural length scale. It is assumed that the primary wavelengths of interest are much longer than the micro-structural length scale and hence the effective properties are computed using the static homogenization theory. An adjoint sensitivity analysis is performed to compute the derivatives of the objective function with respect to the micro-structural design parameters and a gradient-based optimization algorithm is used to update the design. The numerical implementation of the computationally challenging terminal-value adjoint problems is discussed and a structural design example for tailored energy propagation is provided. | Nonlinear structural design using multiscale topology optimization. Part II: Transient formulation |
S0045782516300068 | A novel non-intrusive reduced order model (NIROM) for fluid–structure interaction (FSI) has been developed. The model is based on proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation method. The method is independent of the governing equations, therefore, it does not require modifications to the source code. This is the first time that a NIROM was constructed for FSI phenomena using POD and RBF interpolation method. Another novelty of this work is the first implementation of the FSI NIROM under the framework of an unstructured mesh finite element multi-phase model (Fluidity) and a combined finite-discrete element method based solid model (Y2D). The capability of this new NIROM for FSI is numerically illustrated in three coupling simulations: a one-way coupling case (flow past a cylinder), a two-way coupling case (a free-falling cylinder in water) and a vortex-induced vibration of an elastic beam test case. It is shown that the FSI NIROM results in a large CPU time reduction by several orders of magnitude while the dominant details of the high fidelity model are captured. | Non-intrusive reduced order modelling of fluid–structure interactions |
S0045782516300111 | This work is concerned with the development of an efficient and robust isogeometric Reissner–Mindlin shell formulation for the mechanical simulation of thin-walled structures. Such structures are usually defined by non-uniform rational B-splines (NURBS) surfaces in industrial design software. The usage of isogeometric shell elements can avoid costly conversions from NURBS surfaces to other surface or volume geometry descriptions. The shell formulation presented in this contribution uses a continuous orthogonal rotation described by Rodrigues’ tensor in every integration point to compute the current director vector. The rotational state is updated in a multiplicative manner. Large deformations and finite rotations can be described accurately. The proposed formulation is robust in terms of stable convergence behavior in the nonlinear equilibrium iteration for large load steps and geometries with large and arbitrary curvature, and in terms of insensitivity to shell intersections with kinks under small angles. Three different integration schemes and their influence on accuracy and computational costs are assessed. The efficiency and robustness of the proposed isogeometric shell formulation is shown with the help of several examples. Accuracy and efficiency is compared to an isogeometric shell formulation with the more common discrete rotational concept and to Lagrange-based finite element shell formulations. The competitiveness of the proposed isogeometric shell formulation in terms of computational costs to attain a pre-defined error level is shown. | An efficient and robust rotational formulation for isogeometric Reissner–Mindlin shell elements |
S0045782516300214 | While the interest in higher-order models in physics and mechanics grows, their numerical simulation still poses a challenge, especially for arbitrary shaped three-dimensional domains. This contribution presents the mathematical framework as well as the application to different problems in the field of material science, fracture mechanics and diffusion problems. All models under consideration require at least C 1 continuity, which prevents the application of standard finite element analysis and local mesh refinements. Introducing isogeometric analysis (IGA) for the discretization in a finite element framework enables us to deal with these requirements. Moreover, a general hierarchical refinement scheme based on a subdivision projection is presented here for one, two and three dimensional simulations. This technique allows to enhance the approximation space using finer splines on each level but preserves the partition of unity as well as the continuity properties of the original discretization. Using this mathematical framework, the improved convergence of a Kuramoto–Sivashinsky model, a mesh-adapted thermal diffusion simulation and computations of a priori unknown crack propagation in different fracture modes underline the versatility of the presented hierarchical refinement scheme. | Isogeometric analysis and hierarchical refinement for higher-order phase-field models |
S0045782516300287 | This work proposes a hybrid modelling technique for efficient analysis of poroelastic materials, which are widely used for noise reduction in acoustic problems. By combining the finite element method and the wave based method in a direct manner, the proposed hybrid technique maximises the advantages and compensates the drawbacks of both numerical methods. The considered poroelastic domain described by Biot’s theory is divided into two groups of domains according to their geometrical characteristics and boundary conditions. The group with complex geometries and/or boundary conditions leading to singularities is discretised into a large number of small finite elements. The other group consisting of large, geometrically moderate poroelastic domains is partitioned into wave based subdomains where the field variables are expanded with analytical poroelastic wave functions. Both groups modelled by the finite element method and the wave based method, respectively, are combined in a hybrid framework in this work to ensure their interacting dynamic behaviours. The properties of the hybrid model are investigated and are compared to existing modelling methods for some numerical examples. The proposed direct hybrid modelling technique provides stable predictions and exhibits fast convergence performances for the analysis of poroelastic materials, especially when singularities arise in the poroelastic domain. | A direct hybrid finite element–wave based modelling technique for efficient analysis of poroelastic materials in steady-state acoustic problems |
S0045782516300354 | In this work, we present a statistical treatment of stress-life (S-N) data drawn from a collection of records of fatigue experiments that were performed on 75S-T6 aluminum alloys. Our main objective is to predict the fatigue life of materials by providing a systematic approach to model calibration, model selection and model ranking with reference to S-N data. To this purpose, we consider fatigue-limit models and random fatigue-limit models that are specially designed to allow the treatment of the run-outs (right-censored data). We first fit the models to the data by maximum likelihood methods and estimate the quantiles of the life distribution of the alloy specimen. To assess the robustness of the estimation of the quantile functions, we obtain bootstrap confidence bands by stratified resampling with respect to the cycle ratio. We then compare and rank the models by classical measures of fit based on information criteria. We also consider a Bayesian approach that provides, under the prior distribution of the model parameters selected by the user, their simulation-based posterior distributions. We implement and apply Bayesian model comparison methods, such as Bayes factor ranking and predictive information criteria based on cross-validation techniques under various a priori scenarios. | Bayesian inference and model comparison for metallic fatigue data |
S0045782516300524 | The avascular multiphase model for tumor growth, developed by the authors in previous works, is enhanced to include angiogenesis. The original model comprises the extracellular matrix (ECM) as porous solid phase and three fluid phases: living and necrotic tumor cells (TCs), host cells (HCs), and the interstitial fluid. In this paper we add transport of tumor angiogenic factor (TAF) and of endothelial cells. The density of the endothelial cells represents the newly created vessels in a smeared manner. Co-opted blood vessels can be added as line element with flow or can be taken into account as boundary condition. The model is hence of the continuum–discrete type. Two examples show the potential of the newly enhanced model. The first deals with growth of a 2D tumor spheroid in a square tissue domain. From a blood vessel, posed on one side of the domain, angiogenesis takes place through the migration of endothelial cells from the vessel to the tumor. The second one is the simulation of cutaneous melanoma growth with the diffusion of TAF from the living tumor cells and the consequent development of a new vessel network, represented by the endothelial cells density. The introduction of angiogenesis will allow for simulating the delivery of chemotherapeutic and nanoparticle-mediated agents to the vascular tumor, and for evaluation of the therapeutic effect. Equation Equations Thermodynamically Constrained Averaging Theory Coefficient in the pressure–saturations relationship Nonlinear coefficient of the discretized capacity matrix Rate of strain tensor Effective diffusion coefficient for the species i dissolved in the phase l Endothelial cells Discretized source term associated to the primary variable v Nonlinear coefficient of the discretized conduction matrix Compressibility of the phase i ( i = s , t , h and l ) Intrinsic permeability tensor of the ECM Relative permeability of the phase α Vector of shape functions related to the primary variable v Pressure in the phase α Pressure difference between fluid phases i and j Saturation degree of the phase α Effective stress tensor of the solid phase s Total stress tensor of the solid phase s Yield limit of the solid phase which defines the boundary of elastic domain Tumor angiogenic factors Displacement vector of the solid phase s Velocity vector of the phase α Solution vector Biot’s coefficient Growth coefficient Necrosis coefficient Nutrient consumption coefficient related to growth Nutrient consumption coefficient not related to growth Porosity Volume fraction of the phase α Viscosity parameter of the solid phase Dynamic viscosity of the phase α Density of the phase α Interfacial tension between fluid phases i and j Adhesion of the phase α Mass fraction of necrotic cells in the tumor cells phase Nutrient mass fraction in the interstitial fluid Critical nutrient mass fraction for growth Reference nutrient mass fraction in the environment TAF mass fraction in the interstitial fluid Critical TAF mass fraction Endothelial cells mass fraction in the interstitial fluid Critical endothelial cells mass fraction for the death of the endothelial cells Coefficient for uptake of TAF by endothelial cells Degradation rate coefficient for TAF demise Coefficient for TAF and endothelial cells production Coefficient for new oxygen brought by the new capillary network Inter-phase mass transfer Reaction term i.e. intra-phase mass transfer Critical value Nutrient Host cell phase Interstitial fluid Solid Tumor cell phase Phase indicator with α = t , h , l , or s TAF Endothelial cells Oxygen | Simulation of angiogenesis in a multiphase tumor growth model |
S0045782516300639 | The numerical manifold method (NMM) surmounting the mesh dependence has successfully solved very complicated problems involving small deformation and large movement, but had few applications to large deformation and large rotation problems because the false volume expansion and other issues exist. In this study it is shown that the false volume expansion in NMM can be excellently resolved by using the S–R (strain–rotation) decomposition theorem which can precisely reflect complex physical behaviors occurring in the process of large rotation and large deformation. The numerical methods based on the S–R decomposition theorem have been limited to the static analysis of large deformations. To remove this limitation, a new formulation taking into account dynamical features is proposed based on the weak form of momentum conservation law. Under the framework of NMM, the generalized- α method is employed to discretize the temporal variables. The updates of variables are described using the updated co-moving coordinate system. Thus, a new method named S–R-D-based NMM is established. The new formulation can be implemented in any other partition of unity based methods as well, so as to improve the performances of such methods in the analysis of dynamic large deformations. Global reference system Co-moving coordinate system Position vector of a point before deformation Position vector of a point after deformation Displacement vector of a point Velocity vector of a point Acceleration vector of a point Specified vector of a point Specified traction vector of a point Force per unit volume Basis vector corresponding to initial co-moving coordinate system Basis vector corresponding to the co-moving coordinate system after deformation Transformation function between g i 0 and g i Kronecker-delta Displacement derivative Christoffel symbol of the second kind Strain tensor Linear strain tensor Nonlinear strain tensor Local mean rotation tensor Unit vector of the rotation axis Mean rotation angle Area coordinates of any point ( x , y ) Partition of unity function Star coordinates Area of a triangular mesh covering one manifold element Parameters in terms of star coordinates Constants with regard to a k , b k , c k , k = 1 , 2 , 3 Stress Material tensor Material density Time Time increment or time step size Virtual work of inertia force Virtual work of constraint force of specified displacement Virtual work of external force Penalty parameter Displacement vector of a manifold element Velocity vector of a manifold element Acceleration vector of a manifold element Interpolation matrix Strain vector of a manifold element Linear strain vector of a manifold element Nonlinear strain vector of a manifold element Linear strain–displacement matrix Nonlinear strain–displacement matrix Element stiffness matrix Mass matrix of a manifold element Equivalent force vector of a manifold element Algorithmic parameters of generalized- α Spectral radius of generalized- α | S–R decomposition based numerical manifold method |
S0045782516300834 | This work proposes a stochastic shape optimization method for continuous structures using the level-set method. Such a method aims to minimize the expected compliance and its variance as measures of the structural robustness. The behavior of continuous structures is modeled by linear elasticity equations with uncertain loading and material. This uncertainty can be modeled using random variables with different probability distributions as well as random fields. The proper problem formulation is ensured by the proof of the existence colorrev of solution under certain geometrical constraints on the set of admissible shapes. The proposed method addresses the stochastic linear elasticity problem in its weak form obtaining the explicit expressions for the continuous shape derivatives. Some numerical examples are presented to show the effectiveness of the proposed approach. | Robust shape optimization of continuous structures via the level set method |
S0045782516300895 | This work evaluates the performance of a NURBS-based isogeometric finite element formulation for solving stationary acoustic problems in two dimensions. An initial assessment is made by studying eigenvalue problems for a square and a circular domain. The spectral approximation properties of NURBS functions of varying order are compared to those of conventional polynomials and are found to be superior, yielding more accurate representations of eigenvalues as well as eigenmodes. The higher smoothness of NURBS shape functions yields better approximations over an extended frequency range when compared to conventional polynomials. Two numerical case studies, including a geometrically complex domain, are used to benchmark the method versus the traditional finite element method. A convergence analysis confirms the higher efficiency of the isogeometric method on a per-degree-of-freedom basis. Simulations over a wider frequency range also illustrate that the method suffers less from the dispersion effects that deteriorate the acoustic response towards higher frequencies. The tensor product structure of NURBS, however, also imposes practical considerations when modelling a complex geometry consisting of multiple patches. | A performance study of NURBS-based isogeometric analysis for interior two-dimensional time-harmonic acoustics |
S0045782516300901 | Discontinuous deformation analysis (DDA) is a numerical method for analyzing dynamic behaviors of an assemblage of distinct blocks, with the block displacements as the basic variables. The contact conditions are approximately satisfied by the open–close iteration, which needs to fix or remove repeatedly the virtual springs between blocks in contact. The results from DDA are strongly dependent upon stiffness of these virtual springs. Excessively hard or soft springs all incur numerical problems. This is believed to be the biggest obstacle to more extensive application of DDA. To avoid the introduction of virtual springs, huge efforts have been made with little progress related to low efficiency in solution. In this study, the contact forces, instead of the block displacements, are taken as the basic variables. Stemming from the equations of momentum conservation of each block, the block displacements can be expressed in terms of the contact forces acting on the block. From the contact conditions a finite-dimensional quasi-variational inequality is derived with the contact forces as the independent variables. On the basis of the projection–contraction algorithm for the standard finite-dimensional variational inequalities, an iteration algorithm, called the compatibility iteration, is designed for the quasi-variational inequality. The main processes can be highly parallelized with no need to assemble the global stiffness matrix. A number of numerical tests, including those very challenging, suggest that the proposed procedure has reached practical level in accuracy, robustness and efficiency, and the goal to abandon completely virtual springs has been reached. 6-dimensional generalized force vector, in Eq. (4) 6 × 2 n i matrix formed by all the local frames at block Ω i , Eq. (8) 6 × 2 matrix of the j th contact local frame at block Ω i , Eq. (9) cohesion at the k th contact, Eq. (33) incremental displacement vector of block Ω i , Eq. (1) time interval of a time step, Eq. (10) Young’s modulus, in all the examples 6 × 6 stiffness matrix of block Ω i , Eq. (7) tolerance of contact force vector p in the compatibility iteration x direction normal strain of block Ω i , Eq. (7) y direction normal strain of block Ω i , Eq. (1) 6 × 2 n i flexibility matrix, Eq. (15) 6-dimensional flexibility vector, Eq. (16) vector-valued gap function, in Eq. (38) acceleration of gravity, in all the examples a part of normal gap of the contact-pair formed by an edge of Ω i and a vertex of Ω j , in Eq. (24) a part of tangential slide of the contact-pair formed by an edge of Ω i and a vertex of Ω j , in Eq. (31) normal gap of the k th contact, Eq. (18) tangential slide of the k th contact, Eq. (27) shear strain component of block Ω i , Eq. (1) 6 × 6 equivalent stiffness matrix of block Ω i , Eq. (12) allowable maximum displacement within a time step, in all the example density of block, Eq. (6) 6 × 6 mass matrix of block Ω i , Eq. (6) friction coefficient at the k th contact, Eq. (33) the number of contact-pairs within a time step, in Section 4 unit normal vector of local frame [ n , τ ] of a contact-pair 2 n i - and 2 n j - and dimensional vectors in calculating normal gap g k n of the k th contact-pair, in Eq. (23) the number of contact-pairs at block Ω i , Eq. (5) Poisson’s ratio, in all the examples region occupied by the i th block contact force vector, Eq. (35) normal contact force of the k th contact, Eq. (25) tangential contact force of the k th contact, Eq. (32) 6-dimensional equivalent block force vector of block Ω i , Eq. (13) rotation angle of block Ω i around point ( x 0 , y 0 ) , Eq. (1) 2 × 6 shape function matrix of block Ω i , Eq. (3) unit normal vector of local frame [ n , τ ] of a contact-pair 2 n i - and 2 n j - and dimensional vectors in calculating tangential slide g k τ of the k th contact-pair, in Eq. (30) shear strength corresponding to normal contact force p k n , in Eq. (33) velocity vector of block Ω i at the end of a time step, Eq. (17) velocity vector of block Ω i at the beginning of a time step, Eq. (17) coordinates of an arbitrary point in block Ω i , Eq. (2) coordinates of a reference point in block Ω i , Eq. (1) constraint for the contact forces, in Eq. (36) | Dual form of discontinuous deformation analysis |
S0045782516300913 | This contribution presents Bézier extraction of truncated hierarchical B -splines and the application of the approach to adaptive isogeometric analysis. The developed procedures allow for the implementation of hierarchical B -splines and NURBS without the need for an explicit truncation of the basis. Moreover, standard procedures of adaptive finite element analysis for error estimation and marking of elements are directly applicable due to the strict use of an element viewpoint. Starting from a multi-level nested mesh that results from uniform h -refinement, standard Bézier extraction is applied to active elements that contribute to the hierarchical approximation. This results in a multi-level system of equations without communication between individual hierarchy levels. A hierarchical subdivision operator is developed to recover this communication by transforming the multi-level system of equations into a hierarchical system of equations. It is demonstrated that this approach implicitly defines the truncated hierarchical basis in terms of a simple matrix multiplication. In this way, the implementation effort is reduced to a minimum as shape function routines and Bézier extraction procedures remain unchanged compared to standard isogeometric analysis. The convergence and the computational efficiency of the approach are examined in three different demonstration problems of heat conduction, linear elasticity, and the phase-field modelling of brittle fracture. | Bézier extraction and adaptive refinement of truncated hierarchical NURBS |
S0045782516300925 | Recently, new families of mixed finite elements have been proposed to address the analysis of linear elastic bodies on regular grids adopting a limited number of degrees of freedom per element. A two-dimensional mixed discretization is implemented to formulate an alternative topology optimization problem where stresses play the role of main variables and both compressible and incompressible materials can be dealt with. The structural compliance is computed through the evaluation of the complementary energy, whereas the enforcement of stress constraints is straightforward. Numerical simulations investigate the features of the proposed approach: comparisons with a conventional displacement-based scheme are provided for compressible materials; stress-constrained solutions for structures made of incompressible media are introduced. | Topology optimization with mixed finite elements on regular grids |
S0045782516300950 | This paper addresses the use of isogeometric analysis to solve solid mechanics problems involving nearly incompressible materials. The present work is focused on extension of two-field mixed variational formulations in both small and large strains to isogeometric analysis. Inf–sup stable displacement–pressure combinations for mixed formulations are developed based on the subdivision property of NURBS. Stability and convergence properties of the proposed displacement–pressure combinations are illustrated by computing numerical inf–sup constants and error norms. The performance of the proposed formulations is assessed by studying several benchmark examples involving nearly incompressible and incompressible elastic and elasto-plastic materials in both small and large strain regime. | Subdivision based mixed methods for isogeometric analysis of linear and nonlinear nearly incompressible materials |
S0045782516300974 | In this work, we intend to address the limitation of our earlier particle method, namely the Moving Particle Pressure Mesh (MPPM) method in handling arbitrary-shaped flow boundaries. The application of the Cartesian pressure mesh system adopted in our original MPPM method, which serves as the main key in recovering the divergence-free velocity condition for incompressible flow in the framework of particle method, is rather limited to rectangular flow domain. Here, the hybrid unstructured pressure mesh is adopted to remove the geometrical constraint of our earlier MPPM method. Coupled with the moving particle strategy in the Moving Particle Semi-implicit (MPS) method, the new method is named as the Unstructured Moving Particle Pressure Mesh (UMPPM) method in the current work. A consistent Laplacian model, namely the Consistent Particle Method (CPM) recently reported in the open literature is incorporated as well in the framework of UMPPM for discretizing the viscous term on the scattered particle cloud, while its implicit form is solved in the current work for overall robustness. Finally, we shall verify our UMPPM method with a series of benchmark solutions (for isothermal and non-isothermal flows) available from the literatures, including those obtained from the commercial code. It is appealing to find that the numerical solutions of UMPPM compare well with the benchmark solutions. In some cases, the accuracy of our UMPPM is better than that of the existing particle method such as Smoothed Particle Hydrodynamics (SPH). | Unstructured Moving Particle Pressure Mesh (UMPPM) method for incompressible isothermal and non-isothermal flow computation |
S0045782516301001 | We develop a fractional extension of a mass-conserving Allen–Cahn phase field model that describes the mixture of two incompressible fluids. The fractional order controls the sharpness of the interface, which is typically diffusive in integer-order phase-field models. The model is derived based on an energy variational formulation. An additional constraint is employed to make the Allen–Cahn formulation mass-conserving and comparable to the Cahn–Hilliard formulation but at reduced cost. The spatial discretization is based on a Petrov–Galerkin spectral method whereas the temporal discretization is based on a stabilized ADI scheme both for the phase-field equation and for the Navier–Stokes equation. We demonstrate the spectral accuracy of the method with fabricated smooth solutions and also the ability to control the interface thickness between two fluids with different viscosity and density in simulations of two-phase flow in a pipe and of a rising bubble. We also demonstrate that using a formulation with variable fractional order we can deal simultaneously with both erroneous boundary effects and sharpening of the interface at no extra resolution. | A fractional phase-field model for two-phase flows with tunable sharpness: Algorithms and simulations |
S0045782516301049 | In this paper we present a multi-fidelity (MF) extension of non-intrusive polynomial chaos based on regression (point collocation) for uncertainty quantification purposes. The proposed method uses the principle of a global correction function from a previous similar method that uses spectral projection to estimate the coefficients. Due to its usage of regression to estimate the coefficients, the present method offers high flexibility in the sampling and generation of the polynomial basis. The method takes advantage of a nested sampling plan to create the samples for the low-fidelity (LF) and correction expansions where the high-fidelity (HF) samples are a subset of the LF ones. To build the polynomial basis, a total order or hyperbolic truncation strategy is used with a highly flexible combination of the LF and correction polynomial expansions. The method is demonstrated on some artificial test problems and aerodynamic problems of the Euler flow around an airfoil and common three-dimensional research models. In order to derive the strategies for successful MF approximation, the effect of the correlation and the errors between the LF and HF functions is also studied. The results show that high correlation and moderately low errors are important to improve the MF approximation’s accuracy. On a common research model problem, the MF approach with partially-converged simulations as the LF samples can successfully reduce the computational cost to about 40% for similar accuracy compared to an approach using a single HF expansion. | Multi-fidelity non-intrusive polynomial chaos based on regression |
S0045782516301128 | The present work is dedicated to the detection of Lagrangian Coherent Structures (LCSs) in viscous flows through the Finite-Time Lyapunov Exponents (FTLEs) which have been addressed by several works in the recent literature. Here, a novel numerical technique is presented in the context of the Smoothed Particle Hydrodynamics (SPH) models. Thanks to the Lagrangian character of SPH, the trajectory of each fluid particle is explicitly tracked over the whole simulation. This allows for a direct evaluation of the FTLE field supplying a new way for the data analysis of complex flows. The evaluation of FTLE can be either implemented as a post-processing or nested into the SPH scheme conveniently. In the numerical results, three test-cases are presented giving a proof of concept for different conditions. The last test-case regards a naval engineering problem for which the present algorithm is successfully used to capture the submerged vortical tunnels caused by the splashing bow wave. | Detection of Lagrangian Coherent Structures in the SPH framework |
S0045782516301281 | Variational Multiscale (VMS) Finite Element Methods (FEMs) are robust for the development of general formulations for the solution of multiphysics and multiscale transport problems. To obtain a tractable and computationally efficient model, VMS methods often rely on a residual-based algebraic approximation of the sub-grid scales (small or unresolved features of the solution field not captured by the discretization) using a so-called intrinsic time scales matrix, which depends on the problem’s overall differential operator and represents the main model parameter. A novel technique for approximating the intrinsic time scales matrix for generic transport problems in a relatively inexpensive manner (e.g., does not rely on eigenvalue computations) is presented. The method is denoted Transport-Equivalent Scaling (TES) and is based on the monolithic casting of the transport problem as a system of transient–advective–diffusive–reactive (TADR) equations and a subsequent scaling of the coefficient matrices such to preserve each type of transport flux. An algebraic VMS formulation incorporating the TES method is complemented with a discontinuity-capturing (DC) approach and implemented within a FEM solver for the solution of TADR problems. The solution of the global discrete system is accomplished using a generalized-alpha time-stepper together with a globalized inexact Newton–Krylov nonlinear solver. The effectiveness of the TES formulation is verified with the simulation of benchmark incompressible, compressible, and magnetohydrodynamic flow problems. The results demonstrate that the TES method seamlessly handles incompressible–compressible flows in a unified manner (e.g., without assessing the compressibility of the flow). The convergence process using the TES approach and a more standard approximation for the intrinsic time scales, as well as the effect of the DC approach, are also investigated. Analysis of the intrinsic time scales for a one-dimensional incompressible flow model reveals the similitudes and differences between the TES formulation and other conventional methods. | Algebraic approximation of sub-grid scales for the variational multiscale modeling of transport problems |
S0045782516301323 | An efficient and reliable stress computation algorithm is presented, which is based on implicit integration of the local evolution equations of multiplicative finite-strain plasticity/viscoplasticity. The algorithm is illustrated by an example involving a combined nonlinear isotropic/kinematic hardening; numerous backstress tensors are employed for a better description of the material behavior. The considered material model exhibits the so-called weak invariance under arbitrary isochoric changes of the reference configuration, and the presented algorithm retains this useful property. Even more: the weak invariance serves as a guide in constructing this algorithm. The constraint of inelastic incompressibility is exactly preserved as well. The proposed method is first-order accurate. Concerning the accuracy of the stress computation, the new algorithm is comparable to the Euler Backward method with a subsequent correction of incompressibility (EBMSC) and the classical exponential method (EM). Regarding the computational efficiency, the new algorithm is superior to the EBMSC and EM. Some accuracy tests are presented using parameters of the aluminum alloy 5754-O and the 42CrMo4 steel. FEM solutions of two boundary value problems using MSC.MARC are presented to show the correctness of the numerical implementation. | Efficient implicit integration for finite-strain viscoplasticity with a nested multiplicative split |
S0045782516301347 | This paper explores the application of maximum-entropy methods (max-ent) to time harmonic acoustic problems. Max-ent basis functions are mesh-free approximants that are constructed observing an equivalence between basis functions and discrete probability distributions and applying Jaynes’s maximum entropy principle. They are C ∞ -continuous and therefore they are particularly suited for the resolution of Helmholtz problems, where classical finite element methods show a poor accuracy in the high frequency region. In addition, it was recently shown that max-ent approximants can be blended with isogeometric basis functions on the boundary of the domain. This preserves the correct representation of the boundary like in Isogeometric Analysis, with the advantage that the discretization of the interior of the domain is straightforward. In this paper the max-ent mathematical formulation is reviewed and then some numerical applications are studied, including a 2D car cavity geometry defined by B-spline curves. In all cases, if the same nodal discretization is used, finite elements results are significantly improved. | Maximum-entropy methods for time-harmonic acoustics |
S0045782516301372 | This paper presents a novel topology optimization method for designing structures with multiphase embedded components under minimum distance constraints in the level set framework. By using the level set representation for both the component layout and the host structure topology, the shapes of the components can be easily preserved, and optimal structural topologies with smooth boundary/material interface can be obtained. With the purpose of preventing the components moving too close to each other, a minimum distance constraint based on virtual boundary offset is proposed. Different from existing distance detection methods relying on explicit topology representation, the proposed constraint is imposed as a unified integral form, for which the design sensitivity can be readily obtained. Moreover, this constraint is effective for detecting the distance between any complex-shaped components. Several numerical examples are presented to demonstrate the validity and effectiveness of the proposed method. | Structural topology optimization with minimum distance control of multiphase embedded components by level set method |
S0045782516301517 | In this work, a novel comparative method for highly brittle materials such as aragonite crystals is proposed, which provides an efficient and accurate in-sight understanding for multi-scale fracture modeling. In particular, physically-motivated molecular dynamics (MD) simulations are performed to model quasi-static brittle crack propagation on the nano-scale and followingly compared to macroscopic modeling of fracture using the phase-field modeling (PFM) technique. A link between the two modeling schemes is later proposed by deriving PFM parameters from the MD atomistic simulations. Thus, in this combined approach, MD simulations provide a more realistic meaning and physical estimation of the PFM parameters. The proposed computational approach, that encompasses mechanics on discrete and continuum levels, can assist multi-scale modeling and easing, for instance, the simulation of biological materials and the design of new materials. | A comparative molecular dynamics-phase-field modeling approach to brittle fracture |
S0045782516302626 | Non-Uniform Rational B-splines (NURBS) and T-splines can have some drawbacks when modelling damage and fracture. The use of Powell–Sabin B-splines, which are based on triangles, can by-pass these drawbacks. Herein, smeared as well as discrete approaches to fracture in quasi-brittle materials using Powell–Sabin B-splines are considered. For the smeared formulation, an implicit fourth-order gradient damage model is adopted. Since quadratic Powell–Sabin B-splines employ C 1 -continuous basis functions throughout the domain, they are well-suited for solving the fourth order partial differential equation that emerges in this higher order damage model. Moreover, they can be generated from an arbitrary triangulation without user intervention. Since Powell–Sabin B-splines are generated from a classical triangulation, they are not necessarily boundary-fitting and in that case they are not isogeometric in the strict sense. For discrete fracture approaches, the degree of continuity of T-splines is reduced to C 0 at the crack tip. Hence, stresses need to be evaluated and weighted at the integration points in the vicinity of the crack tip in order to decide when the critical stress is reached. In practice, stress fields are highly irregular around crack tips. Furthermore, aligning a T-spline mesh with the new crack segment can be difficult. Powell–Sabin B-splines also remedy these drawbacks as they are C 1 -continuous at the crack tip and stresses can be directly computed, which vastly increases the accuracy and simplifies the implementation. Moreover, re-meshing is more straightforward using Powell–Sabin B-splines. A current limitation is that, in three dimensions, there is no procedure (yet) for constructing Powell–Sabin B-splines on arbitrary tetrahedral meshes. | Powell–Sabin B-splines for smeared and discrete approaches to fracture in quasi-brittle materials |
S0045790613002474 | Industrial image processing tasks, especially in the domain of optical metrology, are becoming more and more complex. While in recent years standard PC components were sufficient to fulfill the requirements, special architectures have to be used to build high-speed image processing systems today. For example, for adaptive optical systems in large scale telescopes, the latency between capturing an image and steering the mirrors is critical for the quality of the resulting images. Commonly, the applied image processing algorithms consist of several tasks with different granularities and complexities. Therefore, we combined the advantages of multicore CPUs, GPUs, and FPGAs to build a heterogeneous image processing pipeline for adaptive optical systems by presenting new architectures and algorithms. Each architecture is well-suited to solve a particular task efficiently, which is proven by a detailed evaluation. With the developed pipeline it is possible to achieve a high throughput and to reduce the latency of the whole steering system significantly. | Fast image processing for optical metrology utilizing heterogeneous computer architectures |
S0045790613002504 | With the development of the 6LoWPAN standard, sensors can be natively integrated into the IP world, becoming tiny information providers that are directly addressable by any Internet-connected party. To protect the information gathered by sensors from any potential attacker on the Internet, it is essential to have trustworthy real-time information about the legitimacy of every attempt to interact with a sensor. Our approach to address this issue is Ladon, a new security protocol specifically tailored to the characteristics of low capacity devices. In this paper, we study the performance of Ladon, showing that it successfully meets the requirements of the targeted environments. To that end, we evaluate the delay and energy consumption of the execution of Ladon. The obtained results show that the cost of Ladon is bounded, even in situations of high packet loss rates (20–80%) and comparable to that of other protocols that implement fewer security features. | Analytical evaluation of a time- and energy-efficient security protocol for IP-enabled sensors |
S0045790614000391 | In cognitive radio networks, it is well known that the cooperative spectrum sensing can overcome damaging effects of fading and shadowing. However, it also increases the amount of energy consumption which is a critical factor in low powered wireless communications. In this paper based on bi-threshold energy detection, we maximize the network throughput such that the energy consumption is below a predefined value and also sufficient protection of primary users against interference is guaranteed. Convex optimization analysis is presented to jointly obtain the optimal values of sensing time and detection thresholds. Simulation results show that the proposed method is very flexible such that a good tradeoff between achievable throughput and energy efficiency can be established, while it often outperforms the conventional sensing method significantly. | Optimized energy limited cooperative spectrum sensing in cognitive radio networks |
S0045790614000457 | With reference to a network consisting of sensor nodes connected by wireless links, we approach the problem of the distribution of the cryptographic keys. We present a solution based on communication channels connecting sequences of adjacent nodes. All the nodes in a channel share the same key. This result is obtained by propagating the key connecting the first two nodes to all the other nodes in the channel. The key propagation mechanism is also used for key replacement, as is required, for instance, in group communication to support forms of forward and backward secrecy, when a node leaves a group or a new node is added to an existing group. | Key propagation in wireless sensor networks |
S0045790614000688 | When wireless sensor networks (WSNs) are deployed in areas inaccessible by human beings, security becomes extremely important, as they are prone to different types of malicious attacks. We propose a scheme to build a security mechanism in a query-processing paradigm within WSNs with clustered architecture. This work aims to preserve the basic security features such as confidentiality and integrity as well as to protect from replay attack in presence of mote class attacker. Considering the limitations of such an attacker, the probability of attacking cluster head and member nodes is higher than attacking the base station. Paying attention to this fact, in all communication between cluster head and member nodes, the key is neither transmitted nor pre-deployed. Performance of the scheme is evaluated and compared through qualitative and quantitative analyses; results show the present scheme’s dominance over the competing schemes. | A lightweight security scheme for query processing in clustered wireless sensor networks |
S0045790614000706 | Thresholding is a popular image segmentation method that converts a grayscale image into a binary image. In this paper, we propose a cloud model-based framework for range-constrained thresholding with uncertainty, and improve four traditional methods. The method involves four major steps, including representing the image using cloud model, estimating the automatic threshold for gray level ranges of object and background, implementing image transformation to focus on mid-region of the image, and determining the binary threshold within the constrained gray level range. Cloud model can effectively represent various visual properties of the image, such as intensity-based class uncertainty, intra-class homogeneity, and between-class contrast. The approach is validated both quantitatively and qualitatively. Compared with the traditional state-of-art algorithms on a variety of synthetic and real images, with or without noisy, as well as laser cladding images, the experimental results suggest that the presented method is efficient and effective. | Cloud model-based method for range-constrained thresholding |
S0045790614001347 | Cognitive radio (CR) technology can solve the problems of spectrum scarcity and low spectrum utilization. However, random behavior of the primary user (PU) appears to be an enormous challenge. In this paper, we propose a PU behavior aware joint channel selection and allocation scheme. In the first step, the channels are ranked based on statistics of the PU usage whereas in the second phase, a proportional fair oriented channel allocation scheme is employed to allocate channels among CRs. We also introduce the concept of a time-varying framing process (TVFP) that minimizes the overall data transmission time. Simulation results show that the proposed scheme outperforms existing schemes in terms of the transmission-time and the number of collisions with the PUs. In addition, it helps to save a significant amount of transmission power. Moreover, it provides a significantly higher system throughput as compared to the existing schemes. | Primary user behavior aware spectrum allocation scheme for cognitive radio networks |
S0045790614001669 | Having a direct effect on network lifetime, balanced energy consumption is one of the key challenges in wireless networks. In this paper, we investigate the effects of node mobility on energy balancing in wireless networks. We construct a Linear Programming (LP) framework that jointly captures data routing, mobility, and energy dissipation aspects. We explore the design space by performing numerical analysis using the developed LP framework. Our results show that mobility has significant effects on the energy dissipation trends of wireless nodes. Mobility can improve the energy balancing up to a certain level, however extreme mobility may lead to a degradation in energy balancing of wireless networks. | Effects of node mobility on energy balancing in wireless networks |
S0045790614001761 | The number of wireless sensor network deployments for real-life applications has rapidly increased in recent years. However, power consumption is a critical problem affecting the lifetime of wireless sensor networks (WSNs). A number of techniques have been proposed to solve this power problem. Among the proposed techniques, data compression scheme is one that can be used to reduce the volume of data to be transmitted. This paper therefore proposes a fast and efficient lossless adaptive compression scheme (FELACS) for WSNs. FELACS was proposed to enable a fast and low memory compression algorithm for WSNs. FELACS generates its coding tables on the fly and compresses data very fast. FELACS is lightweight, robust to packet losses and has very low complexity. FELACS achieved compression rates of 4.11 bits per sample. In addition, it achieved power savings up to 70.61% using the real-world test datasets. | Fast and efficient lossless adaptive compression scheme for wireless sensor networks |
S0045790614001840 | Virtual fixtures can be used in haptic-enabled hydraulic telemanipulators to facilitate certain tasks. Using this concept, however, the operator may tend to move the master fast due to relying on the virtual fixture. As a result, the slave manipulator could start to lag due to latency in the hydraulic actuation control system. This paper describes how to mitigate the position errors between master and slave robots by overlaying an augmentation force on the master that is collinear but opposite of the master instantaneous velocity. The magnitude of this force is proportional to the position error at the slave end-effector. Experiments, conducted on a teleoperated hydraulic manipulator to perform several live-line maintenance tasks, show that the augmented scheme exhibits less position error at the slave side, better task quality, but longer task completion time as compared to the virtual fixture alone. | An augmented virtual fixture to improve task performance in robot-assisted live-line maintenance |
S0045790614001888 | The main constraint of wireless sensor networks (WSNs) is the limited and generally irreplaceable power source of the sensor nodes. Therefore, designing energy saving routing algorithm is one of the most focused research issues. In this paper, we propose an energy aware routing algorithm for cluster based WSNs. The algorithm is based on a clever strategy of cluster head (CH) selection, residual energy of the CHs and the intra-cluster distance for cluster formation. To facilitate data routing, a directed virtual backbone of CHs is constructed which is rooted at the sink. The proposed algorithm is also shown to balance energy consumption of the CHs during data routing process. We prove that the algorithm achieves constant message and linear time complexity. We test the proposed algorithm extensively. The experimental results show that the algorithm outperforms other existing algorithms in terms of network lifetime, energy consumption and other parameters. | Energy-aware routing algorithm for wireless sensor networks |
S0045790614001918 | Cognitive radio is an emerging technology in wireless communications for dynamically accessing under-utilized spectrum resources. In order to maximize the network utilization, vacant channels are assigned to cognitive users without interference to primary users. This is performed in the spectrum allocation (SA) module of the cognitive radio cycle. Spectrum allocation is a NP hard problem, thus the algorithmic time complexity increases with the cognitive radio network parameters. This paper addresses this by solving the SA problem using Differential Evolution (DE) algorithm and compared its quality of solution and time complexity with Particle Swarm Optimization (PSO) and Firefly algorithms. In addition to this, an Intellectual Property (IP) of DE based SA algorithm is developed and it is interfaced with PowerPC440 processor of Xilinx Virtex-5 FPGA via Auxiliary Processor Unit (APU) to accelerate the execution speed of spectrum allocation task. The acceleration of this coprocessor is compared with the equivalent floating and fixed point arithmetic implementation of the algorithm in the PowerPC440 processor. The simulation results show that the DE algorithm improves quality of solution and time complexity by 29.9% and 242.32%, 19.04% and 46.3% compared to PSO and Firefly algorithms. Furthermore, the implementation results show that the coprocessor accelerates the SA task by 76.79–105× and 5.19–6.91× compared to floating and fixed point implementation of the algorithm in PowerPC processor. It is also observed that the power consumption of the coprocessor is 26.5mW. | Field programmable gate array implementation of spectrum allocation technique for cognitive radio networks |
S0045790614002109 | Compressed sensing recovers a sparse signal from a small set of linear, nonadaptive measurements. A sparse signal can be represented by compressed measurements with a reduced number of projections on a set of random vectors. In this paper, a multiscale compressed sensing based processing is investigated for an electrocardiogram signal which yields coded measurements. In case of an electrocardiogram (ECG) signal, the coded measurements are expected to retain the clinical information. To achieve this, compressed sensing based processing is applied at each wavelet scale and measurements are coded using Huffman coder. The measurements at each scale use random sensing matrix with independent identically distributed (i.i.d.) entries formed by sampling a Gaussian distribution. The proposed method is evaluated using pathological ECG signals from the CSE database, synthetic and normal ECGs. It helps preserve the pathological information and clinical components in compressed signal. The compressed signal quality is evaluated using standard distortion measures and mean opinion score (MOS). The MOS values for the signals range from 5 % to 8.3 % with a wavelet energy based diagnostic distortion (WEDD) value of 9.46 % which falls under the excellent category. | Coding ECG beats using multiscale compressed sensing based processing |
S0045790614002110 | In this study, the Quality of Service (QoS) needed to support service continuity in heterogeneous networks is achieved by a Distributed Multi-Agent Scheme (DMAS) based on cooperation concepts and an awareness algorithm. A set of problem solving agents autonomously process local tasks and cooperatively interoperate via an in-cloud blackboard system to provide QoS and mobility information. A Q-Learning awareness algorithm calculates the exceptive rewards of a handoff to all access networks. These rewards are then used by problem solving agents to determine what actions must be performed. Agents located in the integrated IMS-4G-Cloud networks handle service continuity by using a handoff mechanism. Through operations and cooperation among active agents, these phases select a policy for predictive and anticipated IP Multimedia Subsystem (IMS) handoff management. Compared with conventional IMS handoff management, the proposed DMAS scheme achieves shorter handoff delay and better QoS for real-time service applications. | Distributed multi-agent scheme support for service continuity in IMS-4G-Cloud networks |
S0045790614002146 | This paper presents a novel scheme to implement blind image watermarking based on the feature parameters extracted from a composite domain including the discrete wavelet transform (DWT), singular value decomposition (SVD), and discrete cosine transform (DCT). Multiple bits can be embedded into a single image block by adjusting designated parameters via a progressive quantization index modulation technique. The quantization with respect to the feature parameters obtained in the DWT–SVD–DCT domain leads to efficient watermark extraction without referring to the original image. Experimental results show that the embedded watermarks exhibit exceptional robustness against image compression using JPEG and JPEG2000 coding standards. | Exploring DWT–SVD–DCT feature parameters for robust multiple watermarking against JPEG and JPEG2000 compression |
S0045790614002195 | MapReduce is considered the key behind the success of cloud computing because it not only makes a cluster highly scalable but also allows applications to use resources in a cluster. However, MapReduce achieves this simplicity at the expense of flexibility for data partitioning, localization, and processing procedures by handling all issues on behalf of application developers. Unfortunately, MapReduce currently has no solution capable of giving application developers flexibility in customizing data partitioning, localization, and processing procedures. To address the aforementioned flexibility constraints of MapReduce, we propose an architecture called Flexible Architecture for Cluster Evolution (FACE) which is both language-independent and platform-independent. FACE allows a MapReduce cluster to be designed to match various application requirements by customizing data partitioning, localization, and processing procedures. We compare the performance of FACE with that of a general MapReduce system and then demonstrate performance improvements with our implemented procedures. | Flexible architecture for cluster evolution in cloud computing |
S0045790614002213 | A fundamental challenge in the design of Wireless Sensor Network (WSNs) is the proper utilization of resources that are scarce. The critical challenge is to maximize the bandwidth utilization in data gathering and forwarding from sensor nodes to the sink. The main design objective is to utilize the available bandwidth efficiently. The proposed Bandwidth Efficient Cluster-based Data Aggregation (BECDA) algorithm presents the solution for the effective data gathering with in-network aggregation. It considers the network with heterogeneous nodes in terms of energy and mobile sink to aggregate the data packets. The optimal approach is achieved by intra and inter-cluster aggregation on the randomly distributed nodes with the variable data generation rate. The proposed algorithm uses the correlation of data within the packet for applying the aggregation function on the data generated by nodes. BECDA shows significant improvement in PDR (67.44% and 26.79%) and throughput (41.25% and 26.16%) as compared to the state-of-the-art solutions. | Bandwidth efficient cluster-based data aggregation for Wireless Sensor Network |
S0045790614002328 | This work presents an analysis on efficiency of solar energy harvesting circuits focused on low power, low voltage sensor platforms. Two different approaches were tested in order to operate a solar panel closely to its maximum power point. The first circuit precisely matches the solar cells with the batteries. The second one is based on a Maximum Power Point Tracker (MPPT) chip. The paper addresses the circuits’ design and evaluation. Two tests were performed outdoors, under two different irradiance conditions. Although the MPPT chip may be efficient for a variety of low power devices, experiments have shown that it did not extract more energy from the environment than the directly coupled circuit. A mathematical energy consumption analysis shows that, in both cases, the directly coupled circuit is more efficient. Therefore, this work shows that there is still a lack of industry solutions for low power, low voltage, solar harvesting circuits. | Experimental analysis of solar energy harvesting circuits efficiency for low power applications |
S0045790614002353 | Widely deployed real-time embedded systems can improve the performance of industrial applications, but these systems also face the critical challenge of providing high quality security in an unpredictable network environment. We measure the time and energy consumptions of commonly used cryptographic algorithms on a real embedded platform and introduce a method to quantify the security risk of real-time applications. We propose a Dynamic Security Risk Management (DSRM) mechanism to manage the aperiodic real-time tasks for networked industrial applications. Inspired by the feedback design philosophy, DSRM is designed as a two-level control mechanism. The upper-level component makes efforts to admit or reject the arrival tasks and assigns the reasonable security level for each admitted task. With three proportional feedback controllers at the lower level, the security level of each ready task can be adjusted adaptively according to the dynamic environments. Simulation results show the superiority of the proposed mechanism. | Dynamic security management for real-time embedded applications in industrial networks |
S0045790614002377 | Glossy is a reliable and low latency flooding mechanism designed primarily for distributed communication in wireless sensor networks (WSN). Glossy achieves its superior performance over tree-based wireless sensor networks by exploiting identical concurrent transmissions. WSNs are subject to wireless attacks aimed to disrupt the legitimate network operations. Real-world deployments require security and the current Glossy implementation has no built-in security mechanisms. In this paper, we explore the effectiveness of several attacks that attempt to break constructive interference in Glossy. Our results show that Glossy is quite robust to approaches where attackers do not respect the timing constraints necessary to create constructive interference. Changing the packet content, however, has a severe effect on the packet reception rate that is even more detrimental than other physical layer denial-of-service attacks such as jamming. We also discuss potential countermeasures to address these security threats and vulnerabilities. | An experimental study of attacks on the availability of Glossy |
S0045790614002390 | This paper presents a new approach for verifying user identity in pervasive environments using a non-intrusive behaviour tracking technique that offers minimum interruption to the user’s activities. The technique, termed Non-intrusive Identity Assertion System (NIAS), uses knowledge of how the user uses the environment’s services to infer their identity. The technique monitors user behaviour through identifying certain types of activity without the need for detailed tracking of user behaviour, thus minimising intrusion on the user’s normal activities. The technique was evaluated using a simulated environment to assess its reliability. Simulation results show that the technique can be applied in various situations such as strict and relaxed security settings by applying different security policies. They also show that the technique is particularly effective where the environment has a mixture of high and low security resources in which case reliability could exceed 99%. | Discreet verification of user identity in pervasive computing environments using a non-intrusive technique |
S0045790614002407 | An important issue to be addressed when data are to be published is data privacy. In this paper, the problem of data privacy based on a prominent privacy model, ( k , e ) -Anonymous, is addressed. Our scenario is that when a new dataset is to be released, there may be, at the same time, datasets that were released elsewhere. A problem arises because some attackers might obtain multiple versions of the same dataset and compare them with the newly released dataset. Although the privacy of all of the datasets has been well-preserved individually, such a comparison can lead to a privacy breach, which is a so-called “incremental privacy breach”. To address this problem effectively, we first study the characteristics of the effects of multiple dataset releases with a theoretical approach. It has been found that a privacy breach that is subjected to an increment occurs when there is overlap between any parts of the new dataset with any parts of an existing dataset. Based on our proposed studies, a polynomial-time algorithm is proposed. This algorithm needs to consider only one previous version of the dataset, and it can also skip computing the overlapping partitions. Thus, the computational complexity of the proposed algorithm is reduced from O ( n m ) to only O ( pn 3 ) where p is the number of partitions, n is the number of tuples, and m is the number of released datasets. At the same time, the privacy of all of the released datasets as well as the optimal solution can be always guaranteed. In addition, experiment results that illustrate the efficiency of our algorithm on real-world datasets are presented. | An incremental privacy-preservation algorithm for the (k, e)-Anonymous model |
S0045790614002419 | Independent fine-grain web services can be integrated to a value-added coarse-grain service through service composition technologies in Service Oriented Architecture. With the advent of cloud computing, more and more web services in cloud may provide the same function but differ in performance. In addition, the development of cloud computing presents a geographically distributed manner, which elevates the impact of the network on the QoS of composited web services. Therefore, a significant research problem in service composition is how to select the best candidate service from a set of functionally equivalent services in terms of a service level agreement (SLA). In this paper, we propose a composition model that takes both QoS of services and cloud network environment into consideration. We also propose a web service composition approach based on genetic algorithm for geo-distributed cloud and service providers who want to minimize the SLA violations. | A genetic-based approach to web service composition in geo-distributed cloud environment |
S0045790614002560 | Botnets continue to be used by attackers to perform various malicious activities on the Internet. Over the past years, many botnet detection techniques have been proposed; however, most of them cannot detect botnets in an early stage of their lifecycle, or they often depend on a specific command and control protocol. In this paper, we propose BotGrab, a general botnet detection system that considers both malicious activities and the history of coordinated group activities in the network to identify bot-infected hosts. BotGrab tracks suspected hosts participating in some coordinated group activities and calculates a negative reputation score for each of them based on the history of their participation in these activities. A suspected host will be identified as being bot-infected if it has a high negative reputation score or performs some malicious activities while having a low negative reputation score. We demonstrate the effectiveness of BotGrab to detect various botnets including HTTP-, IRC-, and P2P-based botnets using a testbed network consisting of some bot-infected hosts. | BotGrab: A negative reputation system for botnet detection |
S0045790614002572 | This paper focuses on the spectrum sensing mechanisms, which could improve network throughput through the sensing strategy optimization and cooperative spectrum sensing methods. In order to guarantee an integrated and effective research, we take the whole channel scenarios into consideration, i.e., Single Secondary user with Single and Multiple Channels (SSSC and SSMC), Multiple Secondary users with Single and Multiple Channels (MSSC and MSMC). Moreover, according to the specific feature of each scenario, different sensing methods are adopted, i.e., optimal sensing period to maximize network throughput for SSSC, a novel sensing method to minimize searching time for SSMC, partial cooperative spectrum sensing mechanism for MSMC, and setting a spectrum pool in the fusion center to record the channel states for MSMC. Simulation results demonstrate that our methods can improve spectrum efficiency, network throughput and channel utilization, especially when the spectrum is utilized inadequately. | Interference-aware spectrum sensing mechanisms in cognitive radio networks |
S0045790614002584 | Openflow, a novel Software Defined Network (SDN) technology, is developing rapidly and has already been utilized in many fields. It facilitates decoupling between the control and forwarding plane, enabling users to code the network functions easily and replace the traditional high-cost network functions devices. The FlowTable of Openflow, its base of operating the network packets, consists of many flow entries and is stored in the Ternary Content Addressable Memories (TCAMs) of the Openflow switch. When the FlowTable occupies the entire storage space of the Openflow switch and more flow entries are added, the delete operation on the TCAMs increases, and the latency and loss of packets deteriorates – this is the primary issue. In order to solve this problem, this paper proposes a distributed storage framework which stores the FlowTable in multiple Openflow switches, equipped with small TCAMs. To conclude, this paper simulates the algorithms used in the framework and builds a testbed. The experimental results prove the framework’s feasibility and successful performance. | A distributed storage framework of FlowTable in software defined network |
S0045790614002596 | A wireless ad hoc network consists of a set of wireless devices. The wireless devices are capable of communicating with each other without the assistance of base stations. Space Division Multiple Access (SDMA) is a new technology designed to optimize the performance of current and future mobile communication systems. In this paper, an SDMA-based MAC protocol (S-MAC) for wireless ad hoc networks with smart antennas is proposed. The proposed protocol exploits the SDMA system to allow reception of more than one packet from spatially separated transmitters. Using SDMA technology provides collision-free access to the communication medium based on the location of a node. The proposed protocol solves the hidden terminal problem, the exposed terminal problem, and the deafness problem. Simulation results demonstrate the effectiveness of the proposed S-MAC in improving throughput and increasing spatial channel reuse. | An SDMA-based MAC protocol for wireless ad hoc networks with smart antennas |
S0045790614002614 | Online induction machine faults diagnosis is a concern to guarantee the overall production process efficiency. Nowadays, the industry demands the integration of smart wireless sensors networks (WSN) to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can produce sever damages. The origin of most recurrent faults in rotary machines is in the components: stator, rotor, bearing and others. This work presents a novel methodology for the online faults diagnosis in induction motors. This technique uses the smart WSN to obtain the machine condition based on the motor stator current analysis. The implementation of the proposed smart sensor methodology allows the system to perform online fault detection in a fully automated way. Simulation results presented show the efficiency of the proposed method to detect simple and multiple faults in induction machine. It provides detailed analysis to address challenges in designing and deploying WSNs in industrial environments, and its reliability. | Smart wireless sensor networks for online faults diagnosis in induction machine |
S0045790614002626 | Smart Grid makes use of Information and Communications Technology (ICT) infrastructures for the management of the generation, transmission and consumption of electrical energy to increase the efficiency of remote control and automation systems. One of the most widely accepted standards for power system communication is IEC 61850, which defines services and protocols with different requirements that need to be fulfilled with traffic engineering techniques. In this paper, we discuss the implementation of a novel management framework to meet these requirements through control and monitoring tools that provide a global view of the network. With this purpose, we provide an overview of relevant Software Defined Networking (SDN) related approaches, and we describe an architecture based on OpenFlow that establishes different types of flows according to their needs and the network status. We present the implementation of the architecture and evaluate its capabilities using the Mininet network emulator. | Using Software Defined Networking to manage and control IEC 61850-based systems |
S0045790614002663 | Active authentication is the process of continuously verifying a user based on their on-going interaction with a computer. In this study, we consider a representative collection of behavioral biometrics: two low-level modalities of keystroke dynamics and mouse movement, and a high-level modality of stylometry. We develop a sensor for each modality and organize the sensors as a parallel binary decision fusion architecture. We consider several applications for this authentication system, with a particular focus on secure distributed communication. We test our approach on a dataset collected from 67 users, each working individually in an office environment for a period of approximately one week. We are able to characterize the performance of the system with respect to intruder detection time and robustness to adversarial attacks, and to quantify the contribution of each modality to the overall performance. | Multi-modal decision fusion for continuous authentication |
S0045790614002687 | This paper focuses on the design of a novel low power twelve transistor static random access memory (12T SRAM) cell. In the proposed structure two voltage sources are used, one connected with the bit line and the other one connected with the bitbar line in order to reduce the swing voltage at the output nodes of the bit and the bitbar lines, respectively. Reduction in swing voltage reduces the dynamic power dissipation when the SRAM cell is in working mode. Low threshold voltage (LVT) transmission gate (TG) and two high threshold voltage (HVT) sleep transistors are used for applying the charge recycling technique. The charge recycling technique reduces leakage current when the transistors change its state from sleep to active (OFF to ON condition) and active to sleep (ON to OFF condition) modes. Reduction in leakage current causes the reduction in static power dissipation. Stability of the proposed SRAM has also improved due to the reduction in swing voltage. Simulation results of power dissipation, access time, current leakage, stability and power delay product of the proposed SRAM cell have been determined and compared with those of some other existing models of SRAM cell. Simulation has been done in 45nm CMOS environment. Microwind 3.1 is used for schematic design and layout design purpose. | A design of low swing and multi threshold voltage based low power 12T SRAM cell |
S0045790614002705 | Previous distributed file systems aim at storing very large data sets. Their architectures are often designed to support large-scale data-intensive applications, which cannot cope with massive daily users who want to store their data on the Internet. In this paper, CSTORE is proposed to support mass data storage for a large number of users. The user-independent metadata management can ensure data security through assigning an independent namespace to every user. Operating logs are applied to synchronize simultaneous sessions of the same user and resolve conflicts. We also implement a block-level deduplication strategy based on our three-level mapping hash method for the large quantity of repeated data. The migration and rank extension on the hash rules are defined to achieve load balancing and capacity expansion. Performance measurements under a variety of workloads show that CSTORE offers the better scalability and performance than other public cloud storage systems. | CSTORE: A desktop-oriented distributed public cloud storage system |
S0045790614002717 | Service composition is an evolving approach that increases the number of applications of cloud computing by reusing existing services. However, the available methods focus on generating composite services from a single cloud, which limits the benefits that are derived from other clouds. This paper proposes a novel COMbinatorial optimization algorithm for cloud service COMposition (COM2) that can efficiently utilize multiple clouds. The proposed algorithm ensures that the cloud with the maximum number of services will always be selected before other clouds, which increases the possibility of fulfilling service requests with minimal overhead. The experimental results demonstrate that the COM2 successfully competes with previous multiple cloud service composition algorithms by examining a small number of services—which directly relates to execution time—without compromising the number of combined clouds. | A combinatorial optimization algorithm for multiple cloud service composition |
S0045790614002729 | A fault detection method based on dynamic kernel slow feature analysis (DKSFA) is presented in the paper. SFA is a new feature extraction technology which can find a group of slowly varying feature outputs from the high-dimensional inputs. In order to analyze the nonlinear dynamic characteristics of the process data, DKSFA is presented which applies the augmented matrix to consider the dynamic characteristic and uses kernel slow feature analysis (KSFA) to extract the nonlinear slow features hidden in the observed data. For the purpose of fault detection, the D monitoring statistic index is built based on DKSFA model and its confidence limit is computed by kernel density estimation. Simulations on a nonlinear system and Tennessee Eastman (TE) benchmark process show that the proposed method has a better fault detection performance compared with the conventional (kernel principal component analysis) KPCA-based method. | Process fault detection based on dynamic kernel slow feature analysis |
S0045790614002845 | This study presents a new weak signal detection method based on the van der Pol–Duffing oscillator. The principle of the proposed method is described. A weak signal is detected through the transition from the chaotic to the periodic state. Numerical simulation shows that the van der Pol–Duffing oscillator is sensitive to a weak signal under strong noise conditions. Several aspects of the proposed method, including the noise influence, influence of different frequency signals, and influence of the phase shift, are studied in detail. Results indicate that the application of the van der Pol–Duffing oscillator to weak signal detection is feasible. | Application of van der Pol–Duffing oscillator in weak signal detection |
S0045790614003036 | Biometric-based personal authentication is receiving a widespread interest in the area of research due to its high applicability in a wide range of security applications. Among these, hand-based biometric systems are considered to be more successful in terms of accuracy and computational complexity. In hand-based biometrics, finger knuckle surface is considered as one of the emerging potential biometric traits for personal authentication. This is due to its stable and unique inherent patterns present in the outer surface of the finger back knuckle region. Further, this finger knuckle has a high potentiality towards discriminating individuals with high accuracy. In this paper, we present a review of various system models that are implemented for personal authentication using finger knuckle biometrics. Furthermore, the challenges that could arise during the implementation of the large scale real time biometric system with finger knuckle print are explored. | Finger knuckle biometrics – A review |
S0045790614003073 | In this paper, an Android based home automation system that allows multiple users to control the appliances by an Android application or through a web site is presented. The system has three hardware components: a local device to transfer signals to home appliances, a web server to store customer records and support services to the other components, and a mobile smart device running Android application. Distributed cloud platforms and Google services are used to support messaging between the components. The prototype implementation of the proposed system is evaluated based on the criteria considered after the requirement analysis for an adequate home automation system. The paper presents the outcomes of a survey carried out regarding the properties of home automation systems, and also the evaluation results of the experimental tests conducted with volunteers on running prototype. | A cloud based and Android supported scalable home automation system |
S0045790614003097 | Collaboration between mobile nodes is significant in Mobile Ad Hoc Networks (MANETs). The great challenges of MANETs are their vulnerabilities to various security attacks. Because of the lack of centralized administration, secure routing is challenging in MANETs. Effective secure routing is quite essential to protect nodes from anonymous behaviours. Game theory is currently employed as a tool to analyse, formulate and solve selfishness issues in MANETs. This work uses a Dynamic Bayesian Signalling Game to analyse strategy profiles for regular and malicious nodes. We calculate the Payoff to nodes for motivating the particular nodes involved in misbehaviour. Regular nodes monitor continuously to evaluate their neighbours by using the belief evaluation and belief updating system of the Bayes rule. Simulation results show that the proposed scheme could significantly minimize the misbehaving activities of malicious nodes and thereby enhance secure routing. | Enhancing secure routing in Mobile Ad Hoc Networks using a Dynamic Bayesian Signalling Game model |
S0045790614003103 | In this paper, a locality aware NoC communication architecture is proposed. The architecture may reduce the energy consumption and latency in MultiProcessor Systems on Chips (MPSoCs). It consists of two network layers which one layer is dedicated to the packets transmitted to near destinations and the other layer is used for the packets transmitted to far destinations. The actual physical channel width connecting the cores is divided between the two layers. The locality is defined based on the number of hops between the nodes. The relative significances of the two types of communications determine the optimum ratio for the channel width division. To assess the efficiency of the proposed method, we compare its communication latency with that of conventional one for different channel widths, communication traffic profiles, and mesh sizes. | An efficient network on-chip architecture based on isolating local and non-local communications |
S0045790614003115 | Supervisory control and data acquisition (SCADA) systems currently use the polling technique for monitoring electric utility networks. Unfortunately, conventional SCADA systems do not suit the needs of smart grids in terms of the required data rate. Polling-based wireless networks can extend the capabilities of SCADA systems as they provide low cost transceivers and bounded packet delay. However, the harsh environment of power stations negatively impacts the performance of wireless links. This paper introduces a field measurement-based study that focuses on the effect of power system noise and transients on packet delivery reliability of Zigbee and WiFi polling-based wireless networks. Extensive experiments show that the electromagnetic interference emitted from high voltage substations, during normal operation conditions, do not significantly affect wireless communication in the gigahertz range. Moreover, we analytically and experimentally demonstrate that abnormal operation conditions of power systems may negatively impact the reliability of packet delivery in polling-based wireless networks. Furthermore, we show that this negative impact can be mitigated by following some proposed technical considerations regarding the wireless standard, the operating frequency, the location, and the number of wireless transceivers used. | Considerations for packet delivery reliability over polling-based wireless networks in smart grids |
S0045790614003127 | A memory efficient field programmable gate array (FPGA) method is described that facilitates the processing of the continuous wavelet transform (CWT) arithmetic operations. The CWT computations were performed in Fourier space and implemented on FPGA following several optimization schemes. First, the adapted wavelet function was stored in a lookup table instead of computing the equation each time. Second, the utilization of FPGA memory was highly optimized by only storing the nonzero values of the wavelet function. This reduces 89% of the memory storage and allows fitting the entire design into the FPGA. Third, the design decreases the number of multiplications and shortens the time to produce the CWT coefficients. The proposed design was tested using EEG data and demonstrated to be suitable for extracting features from the event related potentials. Fourth, wavelet function scales were eliminated which saves further resources. The achieved computation speed allows for real time CWT application. | Optimized FPGA based continuous wavelet transform |
S0045790614003152 | Advanced medical diagnosing and research requires precise information which can be obtained from measured electrophysiological data, e.g., electroencephalogram (EEG) and electrocardiograph (ECG). However, they are often contaminated with noise and a variety of bioelectric signals called artefacts, e.g., electromyography (EMG). These noise and artefacts which need to be reduced make it difficult to distinguish normal from abnormal physiological activity. Electromagnetic contamination of recorded signals represents a major source of noise in electrophysiology and impairs the use of recordings for research. In this paper we present an effective method for cancelling 50Hz (or 60Hz) interference using a radial basis function (RBF) Wiener hybrid filter. One of the main points of this paper is the hybridization of the RBF filter and a Wiener filter to make full use of both merits. The effectiveness and validity of those filters are verified by applying them to ECG and EEG recordings. The results show that the proposed method is able to reduce powerline interference (PLI) from the noisy ECG and EEG signals more accurately and consistently in comparison to some of the state of-the-art methods and this method can be efficiently used with very low signal-to-noise ratios, while preserving original signal waveform. | A new method for removal of powerline interference in ECG and EEG recordings |
S0045790614003164 | Backside illuminated pixel structure is proposed and evaluated as the building block for the image sensor being used as epiretinal prosthesis implant. The image sensor pixel is designed with the parameters of 90nm technology node of standard CMOS (Complementary Metal Oxide Semiconductor) process. The image sensor is consisted of a p-sub/n-well structure as the photosensitive area with the pixel pitch of 20μm. The maximum fill factor is observed due to separation of photosensitive area with the readout transistor surface in backside illumination technology. 90% quantum efficiency at 600nm wavelength and the dark current of 74.6nA/cm2 at room temperature is achieved for the optimized pixel. The application of deep backside Deep Trench Isolation (DTI), with high depth n-well doping profiles, results in a significant reduction of crosstalk (5.6% total crosstalk). | Design and optimization of backside illuminated image sensor for epiretinal implants |
S0045790614003188 | Networks-on-Chip (NoCs) have emerged as a promising solution for the communication crisis in today’s high-performance Multi-Processor System-on-Chip (MPSoC) architectures. Routing methods have a prominent role in taking advantage of the potential benefits offered by NoCs. As a result, designing high-performance and efficient routing algorithms is highly desirable. In this paper, the Hamiltonian-based Odd–Even (HOE) turn model is proposed for both unicast and multicast routing in wormhole-switched 2D mesh networks. HOE is able to maximize the degree of adaptiveness by minimizing the number of prohibited turns, such that the algorithm remains deadlock-free without adding virtual channels. By increasing the number of alternative minimal paths, the hotspots are less likely to be created and the traffic is efficiently distributed throughout the network. The simulation results in terms of latency and power consumption indicate the better performance of the proposed method in comparison with the existing routing methods. | The Hamiltonian-based odd–even turn model for maximally adaptive routing in 2D mesh networks-on-chip |
S0045790614003218 | XACML (eXtensible Access Control Markup Language) policies, which are widely adopted for defining and controlling dynamic access among Web/cloud services, are becoming more complex in order to handle the significant growth in communication and cooperation between individuals and composed services. However, the large size and complexity of these policies raise many concerns related to their correctness in terms of flaws, conflicts and redundancies presence. This paper addresses this problem through introducing a novel set and semantics based scheme that provides accurate and efficient analysis of XACML policies. First, our approach resolves the complexity of policies by elaborating an intermediate set-based representation to which the elements of XACML are automatically converted. Second, it allows to detect flaws, conflicts and redundancies between rules by offering new mechanisms to analyze the meaning of policy rules through semantics verification by inference rule structure and deductive logic. All the approach components and algorithms realizing the proposed analysis semantics have been implemented in one development framework. Experiments carried out on synthetic and real-life XACML policies explore the relevance of our analysis algorithms with acceptable overhead. Please visit http://www.azzammourad.org/#projects to download the framework. | Semantics-based approach for detecting flaws, conflicts and redundancies in XACML policies |
S0045790615000051 | Blood travels throughout the body and thus its flow is modulated by changes in body condition. As a consequence, the wrist pulse signal contains important information about the status of the human body. In this work we have employed signal processing techniques to extract important information from these signals. Radial artery pulse pressure signals are acquired at wrist position noninvasively for several subjects for two cases of interest, viz. before and after exercise, and before and after lunch. Further analysis is performed by fitting a bi-modal Gaussian model to the data and extracting spatial features from the fit. The spatial features show statistically significant (p <0.001) changes between the groups for both the cases, which indicates that they are effective in distinguishing the changes taking place due to exercise or food intake. Recursive cluster elimination based support vector machine classifier is used to classify between the groups. A high classification accuracy of 99.71% is achieved for the exercise case and 99.94% is achieved for the lunch case. This paper demonstrates the utility of certain spatial features in studying wrist pulse signals obtained under various experimental conditions. The ability of the spatial features in distinguishing changing body conditions can be potentially used for various healthcare applications. | Study of wrist pulse signals using time domain spatial features |
S0045790615000063 | Wavelet packet (WP) acoustic features are found to be very promising in unvoiced phoneme classification task but they are less effective to capture periodic information from voiced speech. This motivated us to develop a wavelet packet based feature extraction technique that signifies both the periodic and aperiodic information. This method is based on parallel distributed processing technique inspired by the human speech perception process. This front end feature processing technique employs Equivalent Rectangular Bandwidth (ERB) filter like wavelet speech feature extraction method called Wavelet ERB Sub-band based Periodicity and Aperiodicity Decomposition (WERB-SPADE). Winer filter is used at front end to minimize the noise for further processing. The speech signal is filtered by 24 band ERB like wavelet filter banks, and then the output of each sub-band is processed through comb filter. Each comb filter is designed individually for each sub-band to decompose the signal into periodic and aperiodic features. Thus it carries the periodic information without losing certain important information like formant transition incorporated in aperiodic features. Hindi phoneme classification experiments with a standard HMM recognizer under both clean-training and multi-training condition is conducted. This technique shows significant improvement in voiced phoneme class without affecting the performance of unvoiced phoneme class. | Hindi phoneme classification using Wiener filtered wavelet packet decomposed periodic and aperiodic acoustic feature |
S0045790615000075 | In this paper a new approach of edge-based quantization for the compression of gray scale images using an Adaptive Block Truncation Coding technique (ABTC-EQ) is proposed, to improve the compression ratio (CR) with high picture quality. Quantization is done based on the edge information contained in each block of pixels of the image. Conventional BTC method retains the visual quality of the reconstructed image but it shows some artifacts near the edges. In conventional BTC and variants, same quantization is done for all pixel values with different block sizes so that CR is static for images with a fixed block size. But in the case of proposed method since the quantization is done based on the edge information, CR become dynamic and consequently achieves better visual quality with better CR. The experimental analysis based on subjective and quantitative analysis proved that the proposed method outperforms other BTC variants. | Adaptive block truncation coding technique using edge-based quantization approach |
S0045790615000099 | Data compression is a challenging process with important practical applications. Specialized techniques for lossy and lossless data compression have been the subject of numerous investigations during last several decades. Previously, we studied the use of the pseudo-distance technique (PDT) in lossless compression of color-mapped images and its parallel implementation. In this paper we present a new technique (PDT2) to improve compression gain of PDT. We also present a parallelized implementation of the new technique, which results in substantial gains in compression time while providing the desired compression efficiency. We demonstrate that on non-dithered images PDT2 outperforms PDT by 22.4% and PNG by 29.3%. On dithered images, PDT2 achieves compression gains of 7.1% over PDT and 23.8% over PNG. We also show that the parallel implementation of PDT2, while compromising compression less than 0.3%, achieves near linear speedup and utilization of Intel Hyper-Threading technology on supported systems improves speedup on average 18%. | The pseudo-distance technique for parallel lossless compression of color-mapped images |
S0045790615000105 | Detecting covert information in images by means of steganalysis techniques has become increasingly necessary due to the amount of data being transmitted mainly through the Internet. However, these techniques are computationally expensive and not much attention has been paid to reduce their cost by means of available parallel computational platforms. This article presents two computational models for the Subtractive Pixel Adjacency Model (SPAM) which has shown the best detection rates among several assessed steganalysis techniques. A hardware architecture tailored for reconfigurable fabrics is presented achieving high performance and fulfilling hard real-time constraints. On the other hand, a parallel computational model for the CUDA architecture is also proposed. This model presents high performance during the first stage but it faces a bottleneck during the second stage of the SPAM process. Both computational models are analyzed in detail in terms of their algorithmic structure and performance results. To the best of Authors’ knowledge these are the first design proposals to accelerate the SPAM model calculation. | An analysis of computational models for accelerating the subtractive pixel adjacency model computation |
S0045790615000130 | Wireless sensor networks are formed by a large number of sensor nodes which are commonly known as motes. In the past few years, several reliable, congestion controlled and energy efficient transport layer protocols in wireless sensor networks have been developed and proposed in the literature. In this paper, we have presented a hybrid and dynamic reliable transport protocol which provides the mechanism to dynamically assign the timing parameters to the nodes as well as enhance the protocol performance by using a hybrid Acknowledgement/Negative Acknowledgement scheme. The performance of proposed protocol is tested under TinyOS Simulator varying different parameters and protocol settings and found that proposed protocol is able to program all the nodes when given proper pump/fetch ratios, is able to solve the booting sensor nodes problem by being able to wait till all the nodes finished booting and solves the all-packets-lost problem by acknowledging the receipt of its first packet delivered that is the inform message. | A hybrid and dynamic reliable transport protocol for wireless sensor networks |
S0045790615000142 | This paper investigates an optimal adaptive rate and power transmission algorithms for Orthogonal Frequency Division Multiplexing (OFDM) – based Cognitive Radio (CR) systems. The aim was to study the problem of maximizing the overall rate achieved by the Secondary User (SU), while keeping the interference powers introduced by the SU on the spectrum band of Primary User’s (PU) below the specified thresholds and considering the total transmit power budget constraints. In addition, the novel suboptimal power allocation algorithm was proposed and consequently the maximum modulation level according to allocated power based on maximizing the overall achievable rate was obtained. The performance of the proposed suboptimal algorithm is compared with the optimal and existing algorithms including uniform loading and water filling algorithms. Numerical results revealed that the proposed suboptimal algorithm had a better performance than the uniform loading and water filling algorithms. | Optimal and suboptimal adaptive algorithms for rate and power transmission in OFDM-based Cognitive Radio systems |
S0045790615000166 | Orthogonal Frequency Division Multiplexing (OFDM) system has lead to significant advancement in wireless communication systems. In OFDM system multi-carriers are present. During modulation the sub-carriers are added together with same phase which increases the value of Peak-to-Average Power Ratio (PAPR). High PAPR leads to more interference and reduced resolution of analog to digital converter (A/D) and digital to analog converter (D/A). The Partial Transmit Sequence (PTS) is a popular technique used for PAPR reduction in OFDM systems. The modified PTS technique proposed in this paper overcomes the drawbacks of Original PTS (O-PTS) by making use of Group Phase Weighting Factor (GPW) and Recursive Phase Weighting Factor (RPW) along with All Pass Filtering. Simulations show that the proposed scheme performs very well in terms of PAPR and achieves almost the same Bit Error Rate (BER) performance under Rayleigh fading channel. | Peak-power reduction using improved partial transmit sequence in orthogonal frequency division multiplexing systems |
S0045790615000178 | Wireless multimedia sensor networks (WMSNs) are capable of retrieving audio, image and video data in addition to scalar sensor data. The lifetime of these networks is mainly dependent on the communication and computational energy consumption of the node. In this paper, compressed sensing (CS)-based image transmission is proposed to reduce the energy consumption considerably with acceptable image quality. A unique encoding algorithm is formulated for the CS measurements attained with the Bernoulli measurement matrix. The proposed CS method produces better results at a lower sparsity range. Experimental analysis is performed using the Atmega 128 processor of Mica2 to compute the execution time and energy consumption in the hardware platform. The proposed CS method has a considerable reduction in energy consumption and better image quality than the conventional CS method. The simulation results show the efficiency of the proposed method. | Energy-efficient image transmission in wireless multimedia sensor networks using block-based Compressive Sensing |
S0045790615000191 | Diabetic retinopathy is a condition that occurs in individuals with several years of diabetes mellitus and causes a characteristic group of lesions in the retina and progressively damages it. Detecting retinal fundus diseases in advance helps ophthalmologists to apply proper treatments that may cure the disease or decrease its severity and thus protect patients from vision loss. Diabetic retinopathy is usually diagnosed by ophthalmologists using dilated images that are captured by pouring a chemical solution into the patient’s eye, which causes inconvenience and irritation to the patient. In this paper, we propose a method to detect lesion exudates automatically with the aid of a non-dilated retinal fundus image to help ophthalmologists diagnose the disease. The exudates from the low contrast images are detected and localised using a neighbourhood based segmentation technique. A support vector machine (SVM) and probabilistic neural network (PNN) classifiers are proposed to assess the severity of the disease, and the results are compared with the same segmentation technique. The average classification accuracy for the SVM and PNN classifiers are determined to be 97.89% and 94.76%, respectively. | Investigation of the severity level of diabetic retinopathy using supervised classifier algorithms |
S0045790615000208 | The main goal of this paper is to propose and implement an experimental fully automatic face recognition system which will be used to annotate photographs during insertion into a database. Its main strength is to successfully process photos of a great number of different individuals taken in a totally uncontrolled environment. The system is available for research purposes for free. It uses our previously proposed SIFT based Kepenekci approach for the face recognition, because it outperforms a number of efficient face recognition approaches on three large standard corpora (namely FERET, AR and LFW). The next goal is proposing a new corpus creation algorithm that extracts the faces from the database and creates a facial corpus. We show that this algorithm is beneficial in a preprocessing step of our system in order to create good quality face models. We further compare the performance of our SIFT based Kepenekci approach with the original Kepenekci method on the created corpus. This comparison proves that our approach significantly outperforms the original one. The last goal is to propose two novel supervised confidence measure methods based on a posterior class probability and a multi-layer perceptron to identify incorrectly recognized faces. These faces are then removed from the recognition results. We experimentally validated that the proposed confidence measures are very efficient and thus suitable for our task. | Automatic face recognition system based on the SIFT features |
S0045790615000221 | Government agencies and many non-governmental organizations often need to publish sensitive data that contain information about individuals. The sensitive data or private data is an important source of information for the agencies like government and non-governmental organization for research and allocation of public funds, medical research and trend analysis. The important problem here is publishing data without revealing the sensitive information of individuals. This sensitive or private information of any individual is essential to several data repositories like medical data, census data, voter registration data, social network data and customer data. In this paper a personalized anonymization approach is proposed which preserves the privacy while the sensitive data is published. The main contributions of this paper are three folds: (i) the definition of the data collection and publication process, (ii) the privacy framework model and (iii) personalized anonymization approach. The experimental analysis is presented at the end; it shows this approach performs better over the distinct l-diversity measure, probabilistic l-diversity measure and k-anonymity with t-closeness measure. | An approach for prevention of privacy breach and information leakage in sensitive data mining |
S0045790615000233 | In this paper we discuss the application of two-dimensional linear cellular automata (CA) rules with the help of fuzzy heuristic membership function to the problems of edge detection in image processing applications. We proposed an efficient and simple thresholding technique of edge detection based on fuzzy cellular automata transition rules optimized by Particle Swarm Optimization method (PSO). Finally, we present some results of the proposed linear rules for edge detection to the selected 22 images from the Berkeley Segmentation Dataset (BSDS) and compare with some classical Sobel and Canny results. Also, Baddeley Delta Metric (BDM) is used for the performance index to compare the results. | Edge detection with fuzzy cellular automata transition function optimized by PSO |
S0045790615000245 | In this article, we investigate the performance of a coded multiple-input multiple-output (MIMO) multi-carrier (MC) system in underwater communication, where acoustic interference and ambient noise are the two major channel impairments. The channel model considered in this work is based on the shallow water model that has eleven paths. In our work, the acoustic signal is spread with the aid of a high rate spreading sequence to alleviate the effects of acoustic interference. At the receiver, non-linear detectors based on Zero-Forcing (ZF) and Minimum-Mean-Square-Error (MMSE) are employed for signal detection. The simulation results reveal that the system under consideration with the MMSE detector provides better performance in terms of the achievable bit error rate than the system with the ZF detector while achieving higher data rates. | Performance analysis of turbo-coded MIMO–OFDM system for underwater communication |
S0045790615000257 | The world of home automation is an exciting field that has exploded with new technologies and today is known as an area where “The internet of things” (IoT) vision becomes reality. The primary advantages that stem from this concept include how each device forms a small part of the Internet, by which the advanced system is able to interact and communicate, maximizes safety, security, comfort, convenience and energy-savings. This paper proposes an implementation of Sensor Web node as a part of IoT using a Raspberry Pi – inexpensive, fully customizable and programmable small computer with support for a large number of peripherals and network communication. Using this technology, in an example of monitoring and determining the confidence of fire in building, a full system, based on Sensor Web elements, is created and developed starting from a scratch. The given example confirms the advantage of Raspberry Pi – flexibility and extensive possibility of its usage. | Raspberry Pi as a Sensor Web node for home automation |
S0045790615000269 | This paper presents an analysis of a mobile manipulator movement executing a pick-up task. The robot has to reach a target point with its end-effector. The configuration of the manipulator and the pose of the mobile robot define the inputs of the problem. The random profile approach is applied to deal with the aforementioned issue. The trajectory which minimizes the execution time of the task is generated. Furthermore, the manipulability index is introduced in the optimization process in order to allow a comfortable configuration of the manipulator to reach the target-point. The obtained results in free and cluttered environments are presented and discussed. The feasibility of the computed trajectories is also validated against experimentation, in the case of the RobuTER mobile robot carrying the Ultra-Light Manipulator. | Motion analysis of a mobile manipulator executing pick-up tasks |
S0045790615000270 | The main challenge in image denoising is, how to preserve the information such as edges and textures to get satisfactory visual quality when improving the signal to noise ratio. In this paper, we propose a hybrid filter bank for denoising based on wavelet filter bank and quincunx diamond filter bank. The noisy image is decomposed into different subbands of frequency and orientation using DMeyer wavelet. The quincunx diamond filter bank is designed from finite impulse response (FIR) filters using Kaiser window, which is applied on the detail subband of wavelet filter bank. The directional subband coefficients are modeled with Gaussian scale mixture model (GSM). The Bayes least squares estimator is used to obtain the denoised detail coefficients from the noisy image decomposition. Experimental results show that the new method performs spatial averaging without smoothing edges, and thereby enhances the visual quality and peak signal-to-noise-ratio. | Image denoising in hybrid wavelet and quincunx diamond filter bank domain based on Gaussian scale mixture model |
S0045790615000282 | Provisioning of appropriate resources to cloud workloads depends on the Quality of Service (QoS) requirements of cloud workloads. Based on application requirements of cloud users, discovery and allocation of best workload – resource pair is an optimization problem. Acceptable QoS cannot be provided to the cloud users until provisioning of resources is offered as a crucial ability. QoS parameters based resource provisioning technique is therefore required for efficient provisioning of resources. In this paper, QoS metric based resource provisioning technique has been proposed. The proposed technique caters to provisioned resource distribution and scheduling of resources. The main aim of this research work is to analyze the workloads, categorize them on the basis of common patterns and then provision the cloud workloads before actual scheduling. The experimental results demonstrate that QoS metric based resource provisioning technique is efficient in reducing execution time and execution cost of cloud workloads along with other QoS parameters. | Q-aware: Quality of service based cloud resource provisioning |
S0045790615000294 | Increasingly, companies are adopting service-oriented architectures to respond to rapid changes in the market. Even though there are excellent tools and frameworks for service-oriented architecture adoption and service development, the latest adaptation to context has not been properly dealt with yet. Current approaches are mostly focused on solving context-aware issues for web applications only, focusing mainly on client-side adaptation, and there is a clear lack of context taxonomies which facilitate context-aware applications. In our previous work we proposed Model-Driven Adaptable Services (MoDAS): a methodology and tool for the development of context-aware services. In this paper, we propose two key improvements on MoDAS: firstly, leveraging the proposal’s abstraction level, facilitating the use of a larger collection of contexts through the definition of an extensible context taxonomy by means of a metamodel; secondly, providing additional opportunities for code generation. | A metamodel and taxonomy to facilitate context-aware service adaptation |
End of preview. Expand
in Dataset Viewer.
README.md exists but content is empty.
- Downloads last month
- 22