Pervaho: A specialized middleware for mobile context-aware applications

The concept of context-awareness offers a great potential for the future of mobile applications. In order to be developed in an optimal way, mobile context-aware applications need appropriate middleware services. This paper introduces Pervaho, an integrated middleware aimed specifically at supporting the development and testing of mobile context-aware applications. To illustrate the use of Pervaho, we walk through the development of a concrete mobile application and show how it can be built on top of Pervaho’s location-based publish/subscribe service. We also illustrate how a specialized mobility testing tool significantly simplifies the process of testing proximity-based semantics. We then present the implementation of Pervaho, which is based on a set of communication protocols geared at mesh networks. Finally, we provide a performance analysis of our implementation.     

A color-based face tracking algorithm for enhancing interaction with mobile devices

A color-based face tracking algorithm is proposed to be used as a human-computer interaction tool on mobile devices. The solution provides a natural means of interaction enabling a motion parallax effect in applications. The algorithm considers the characteristics of mobile use-constrained computational resources and varying environmental conditions. The solution is based on color comparisons and works on images gathered from the front camera of a device. In addition to color comparisons, the coherency of the facial pixels is considered in the algorithm. Several applications are also demonstrated in this work, which use the face position to determine the viewpoint in a virtual scene, or for browsing large images. The accuracy of the system is tested under different environmental conditions such as lighting and background, and the performance of the system is measured in different types of mobile devices. According to these measurements the system allows for accurate (7% RMS error) face tracking in real time (20–100 fps).     

Simultaneous design of optimal gait pattern and controller for a bipedal robot

Nowadays, biped robotics becomes an interesting topic for many control researchers. The biped robot is more adaptable than the other mobile robots in a varied environment and can have more diverse possibilities in planning the motion. However, it falls down easily and its control for stable walking is difficult. Therefore, generation of a desired walking pattern for the biped robot in the presence of some model uncertainties is an important problem. The proposed walking pattern should be also achievable by the designed controller. To achieve this aim and to reach the best control performance, the walking pattern and controller should be designed simultaneously rather than separately. In the present study, an optimal walking pattern is proposed to be tracked by a designed sliding mode controller. In this respect, a genetic algorithm (GA) is utilized to determine the walking pattern parameters and controller coefficients simultaneously. Here, high stability, minimum energy consumption, good mobility properties, and actuator limitations are considered as the important indexes in optimization. Simulation results indicate the efficiency of the proposed scheme in walking the understudy biped robot.     

A Dual-Petrov-Galerkin Method for the Kawahara-Type Equations

An efficient and accurate numerical scheme is proposed, analyzed and implemented for the Kawahara and modified Kawahara equations which model many physical phenomena such as gravity-capillary waves and magneto-sound propagation in plasmas. The scheme consists of dual-Petrov-Galerkin method in space and Crank-Nicholson-leap-frog in time such that at each time step only a sparse banded linear system needs to be solved. Theoretical analysis and numerical results are presented to show that the proposed numerical is extremely accurate and efficient for Kawahara type equations and other fifth-order nonlinear equations. This work is partially supported by the National Science Council of the Republic of China under the grant NSC 94-2115-M-126-004 and 95-2115-M-126-003. This work is partially supported by NSF grant DMS-0610646.     

Comments on ‘A multi-model adaptive predictor for stochastic processes with Markov switching parameters’

A prediction algorithm proposed by Qi Xiao-Jiang (1986) is shown to be non-optimal.     

A delayed force-reflecting haptic controller for master–slave neurosurgical robots

This paper presents a new force-reflecting control system for master–slave haptic devices. This controller has been implemented and tested on the robotic systems for minimally invasive neurosurgery developed by our Research Group. Robot-assisted surgery is a very valuable treatment, since it allows benefits of high precision, accuracy, and repeatability of robotic devices. The proposed controller is meant to be used for master–slave haptic robotic surgery, but it can be used for any device that provides haptic feedback. The new controller merges the paradigms of force reflection (FR) control and delayed reference control. Unlike the FR control, the proposed solution enhances the safety since it does not allow an unwanted motion of the slave device once the operator releases the haptic controller. Experimental tests are provided to show the capabilities and the performance of the controller. Closed-loop stability is investigated both theoretically and experimentally. The analytic results on stability impose a limit on the ratio between the measured contact force and the sampling frequency of the closed-loop controller.     

A hybrid metaheuristic case-based reasoning system for nurse rostering

In this paper we present a novel Case-Based Reasoning (CBR) system called CABAROST (CAsed-BAsed ROSTering) which was developed for personnel scheduling problems. CBR is used to capture and store examples of personnel manager behaviour which are then used to solve future problems. Previous examples of constraint violations in schedules and the repairs that were used to solve the violations are stored as cases. The sequence in which violations are repaired can have a great impact on schedule quality. A novel memetic algorithm is proposed which evolves good quality sequences of repairs generated by CABAROST. The algorithm was tested on instances of the real-world nurse rostering problem at the Queens Medical Centre NHS Trust in Nottingham.     

Image Fusion for Enhanced Visualization: A Variational Approach

We present a variational model to perform the fusion of an arbitrary number of images while preserving the salient information and enhancing the contrast for visualization. We propose to use the structure tensor to simultaneously describe the geometry of all the inputs. The basic idea is that the fused image should have a structure tensor which approximates the structure tensor obtained from the multiple inputs. At the same time, the fused image should appear ‘natural’ and ‘sharp’ to a human interpreter. We therefore propose to combine the geometry merging of the inputs with perceptual enhancement and intensity correction. This is performed through a minimization functional approach which implicitly takes into account a set of human vision characteristics.     

A high dynamic range rendering pipeline for interactive applications

Realistic images can be computed at interactive frame rates for Computer Graphics applications. Meanwhile, High Dynamic Range (HDR) rendering has a growing success in video games and virtual reality applications, as it improves the image quality and the player’s immersion feeling. In this paper, we propose a new method, based on a physical lighting model, to compute in real time a HDR illumination in virtual environments. Our method allows to re-use existing virtual environments as input, and computes HDR images in photometric units. Then, from these HDR images, displayable 8-bit images are rendered with a tone mapping operator and displayed on a standard display device. The HDR computation and the tone mapping are implemented in OpenSceneGraph with pixel shaders. The lighting model, together with a perceptual tone mapping, improves the perceptual realism of the rendered images at low cost. The method is illustrated with a practical application where the dynamic range of the virtual environment is a key rendering issue: night-time driving simulation.     

A Prolate-Element Method for Nonlinear PDEs on the Sphere

A p-type spectral-element method using prolate spheroidal wave functions (PSWFs) as basis functions, termed as the prolate-element method, is developed for solving partial differential equations (PDEs) on the sphere. The gridding on the sphere is based on a projection of the prolate-Gauss-Lobatto points by using the cube-sphere transform, which is free of singularity and leads to quasi-uniform grids. Various numerical results demonstrate that the proposed prolate-element method enjoys some remarkable advantages over the polynomial-based element method: (i) it can significantly relax the time step size constraint of an explicit time-marching scheme, and (ii) it can increase the accuracy and enhance the resolution.     

A self-tuning controller for systems with unknown or varying time delays†

A SISO self-tuning controller with a Smith-predictor type of time delay compensator (STC-TDC) is proposed to handle open-loop stable processes with unknown or varying time delays. Two numerical examples comparing PI control, the standard STC of Clarke and Gawthrop, the self-tuning Dahlin algorithm of Vogel and Edgar, and the STC-TDC show that the new approach performs best for both set-point and load changes when process time delay changes occur. A third example shows that the STC-TDC matches the extended stability characteristics of the alternative approach due to Kurz and Goedecke but is computationally much simpler.     

A recursive genetic framework for evolutionary decision-making in problems with high dynamism

Communication and coordination are the main cores for reaching a constructive agreement among multi-agent systems (MASs). Dividing the overall performance of MAS to individual agents may lead to group learning as opposed to individual learning, which is one of the weak points of MASs. This paper proposes a recursive genetic framework for solving problems with high dynamism. In this framework, a combination of genetic algorithm and multi-agent capabilities is utilised to accelerate team learning and accurate credit assignment. The argumentation feature is used to accomplish agent learning and the negotiation features of MASs are used to achieve a credit assignment. The proposed framework is quite general and its recursive hierarchical structure could be extended. We have dedicated one special controlling module for increasing convergence time. Due to the complexity of blackjack, we have applied it as a possible test bed to evaluate the system’s performance. The learning rate of agents is measured as well as their credit assignment. The analysis of the obtained results led us to believe that our robust framework with the proposed negotiation operator is a promising methodology to solve similar problems in other areas with high dynamism.     

A High Order Compact Scheme for the Pure-Streamfunction Formulation of the Navier-Stokes Equations

In this paper we continue the study, which was initiated in (Ben-Artzi et al. in Math. Model. Numer. Anal. 35(2):313–303, 2001; Fishelov et al. in Lecture Notes in Computer Science, vol. 2667, pp. 809–817, 2003; Ben-Artzi et al. in J. Comput. Phys. 205(2):640–664, 2005 and SIAM J. Numer. Anal. 44(5):1997–2024, 2006) of the numerical resolution of the pure streamfunction formulation of the time-dependent two-dimensional Navier-Stokes equation. Here we focus on enhancing our second-order scheme, introduced in the last three afore-mentioned articles, to fourth order accuracy. We construct fourth order approximations for the Laplacian, the biharmonic and the nonlinear convective operators. The scheme is compact (nine-point stencil) for the Laplacian and the biharmonic operators, which are both treated implicitly in the time-stepping scheme. The approximation of the convective term is compact in the no-leak boundary conditions case and is nearly compact (thirteen points stencil) in the case of general boundary conditions. However, we stress that in any case no unphysical boundary condition was applied to our scheme. Numerical results demonstrate that the fourth order accuracy is actually obtained for several test-cases.     

A new environment for education? The computer in the home

This paper derives from an interdisciplinary research project which is studying the engagement of young people with different aspects of techno-popular culture. The focus is on the young person and the significance of digital technologies in their lives as a whole. Drawing on cultural studies research we are investigating the ways in which the contexts for computer use are structured by the different discourses present within the family, and the ways in which these discourses may provide a framing context for children’s interactions with digital technology. Drawing on socio-cultural research we take the view that learning is learning to do something with a cultural or cognitive tool. Our analysis of data from case studies of 16 families shows that the context of home computer use amongst young people is far from a simple and uniform phenomenon and is structured by the different discourses present within the family. What young people learn through interaction with computers is thus as much framed by the context of use as by the affordance of the technology.     

A parameterized shared-memory scheme for parameterized metaheuristics

This paper presents a parameterized shared-memory scheme for parameterized metaheuristics. The use of a parameterized metaheuristic facilitates experimentation with different metaheuristics and hybridation/combinations to adapt them to the particular problem we are working with. Due to the large number of experiments necessary for the metaheuristic selection and tuning, parallelism should be used to reduce the execution time. To obtain parallel versions of the metaheuristics and to adapt them to the characteristics of the parallel system, a unified parameterized shared-memory scheme is developed. Given a particular computational system and fixed parameters for the sequential metaheuristic, the appropriate selection of parameters in the unified parallel scheme eases the development of parallel efficient metaheuristics.     

A combined CLP-MILP approach for scheduling commodities in a pipeline

This paper addresses the problem of developing an optimization model to aid the operational scheduling in a real-world pipeline scenario. The pipeline connects refinery and harbor, conveying different types of commodities (gasoline, diesel, kerosene, etc.). An optimization model was developed to determine pipeline scheduling with improved efficiency. This model combines constraint logic programming (CLP) and mixed integer linear programming (MILP) in a CLP-MILP approach. The proposed model uses decomposition strategies, continuous time representation, intervals that indicate time constraints (time windows), and a series of operational issues, such as the seasonal and hourly cost of electric energy (on-peak demand hours). Real cases were solved in a matter of seconds. The computational results have demonstrated that the model is able to define new operational points to the pipeline, providing significant cost savings. Indeed the CLP-MILP model is an efficient tool to aid operational decision-making within this real-world pipeline scenario.     

Schooling Is the Problem: A Plaidoyer for Its Deinstitutionalization

Abstract:

Education appears to be in a perpetual crisis. In this article, I suggest that one of the key contributing factors in educational crisis is the institution of schooling, which re/produces the failures to learn and, thereby, contributes to the re/production of inequities that it (schooling) is supposed to overcome. Ideologies and practices intended to bring about equity through schooling re/produce societal inequity. I show how activity theory allows us to understand that the origin of inequities lies in societal relations, which are relations of ruling. The implications are that a real change of schooling does not come from this or that curricular change but in a reformation of schooling as societal activity generally and science and mathematics education specifically. In ending, I suggest using the deinstitutionalization of psychiatric care as a model for rethinking schooling. Thus, as Bazzul (this issue), I make the beginning of a plaidoyer for redrawing the lines of society by rethinking the very institution of schooling rather than its curriculum contents and practices.     

A Cartesian Embedded Boundary Method for the Compressible Navier-Stokes Equations

We here generalize the embedded boundary method that was developed for boundary discretizations of the wave equation in second order formulation in Kreiss et al. (SIAM J. Numer. Anal. 40(5):1940–1967, 2002) and for the Euler equations of compressible fluid flow in Sjögreen and Peterson (Commun. Comput. Phys. 2:1199–1219, 2007), to the compressible Navier-Stokes equations. We describe the method and we implement it on a parallel computer. The implementation is tested for accuracy and correctness. The ability of the embedded boundary technique to resolve boundary layers is investigated by computing skin-friction profiles along the surfaces of the embedded objects. The accuracy is assessed by comparing the computed skin-friction profiles with those obtained by a body fitted discretization.     

A Spectral Stochastic Semi-Lagrangian Method for Convection-Diffusion Equations with Uncertainty

Real life convection-diffusion problems are characterized by their inherent or externally induced uncertainties in the design parameters. This paper presents a spectral stochastic finite element semi-Lagrangian method for numerical solution of convection-diffusion equations with uncertainty. Using the spectral decomposition, the stochastic variational problem is reformulated to a set of deterministic variational problems to be solved for each Wiener polynomial chaos. To obtain the chaos coefficients in the corresponding deterministic convection-diffusion equations, we implement a semi-Lagrangian method in the finite element framework. Once this representation is computed, statistics of the numerical solution can be easily evaluated. These numerical techniques associate the geometrical flexibility of the finite element method with the ability offered by the semi-Lagrangian method to solve convection-dominated problems using time steps larger than its Eulerian counterpart. Numerical results are shown for a convection-diffusion problem driven with stochastic velocity and for an incompressible viscous flow problem with a random force. In both examples, the proposed method demonstrates its ability to better maintain the shape of the solution in the presence of uncertainties and steep gradients.