Youssef Mesri

Frédéric Alauzet

Alain Dervieux

A fixed-point mesh-adaptive shape design algorithm applied to sonic boom reduction

Keywords: Computational Fluid Dynamics, Mesh adaptation, shape design

This paper presents a combination of mesh adaptation and shape design optimization. The optimization loop is based on an Euler model and an adjoint-based gradient descent algorithm. Mesh adaptation provides here, a control of accuracy of the numerical solution by modifying the domain discretization according to size and stretching directions. A novel algorithm is designed for coupling mesh adaptation and shape optimization. Application of this algorithm to sonic boom mitigation is presented and compared to a more natural approach.

Introduction

Shape Design based on Optimal Control and adjoint state is becoming a frequent practice in industry (see [START_REF] Nadarajah | Optimum shape design for unsteady three-dimensional viscous flows using a non-linear domain method[END_REF][START_REF] Farhat | A shape optimization for reducing the sonic boom initial pressure rise[END_REF][START_REF] Vàzquez | Multilevel Optimization of a supersonic aircraft[END_REF] and [START_REF] Beux | Shape Design in Aerodynamics, Parameterization and sensitivity[END_REF]). Using it assumes some confidence in the High-Fidelity simulation tool involved in the optimization platform. In CFD, this confidence relies on the increasing robustness and accuracy of CFD solvers. However in some particular cases, the accuracy strongly depends on the ability of the solver to capture small scales. Because of these, secondorder convergence to exact solution is difficult and anisotropic mesh adaptation is understood as a mean for obtaining a higher order of convergence.

The particular mesh adaptative method which we want to use is described in details in [START_REF] Alauzet | Multi-dimensional continuous metric for mesh adaptation[END_REF]. It is generally refered as a Hessian-based anisotropic unstructured mesh adaptation and applied a fixed point iteration in order to converge the coupling between approximate solution and its adapted mesh. The fast and reliable mesh reconstruction involved in this algorithm does not introduce an important computer cost, but, at the contrary, contributes to a strong acceleration to attaining an adapted solution, enjoying the benefit of mesh refinement inside iterative flow convergence. The mesh adaptation algorithm chosen here has been observed as producing second-order convergence to exact solutions for a rather small number of discrete unknowns.

Mesh-adaptation for Optimal Control is a topic addressed by several authors, in particular for the choice of error estimators. Indeed, when the optimization problem is solved up to the complete satisfaction of the optimality system, it is natural to consider the optimum parameter, here the shape, as the target unknown and to build an adaptation strategy dedicated to get the lowest error on this unknown. See for example [START_REF] Becker | Adaptive Finite Elements for Optimal Control problems[END_REF]. In some other cases, the optimum system is not enough solved and a strategy looking for a good evaluation of the functional is reasonably prefered. This is the option considered here.

A typical example of phenomenon which is better solved with mesh adaptation is the sonic boom emission. Sonic boom basic modelisation is nothing else but the compressible Navier-Stokes equations. Unfortunately, for sonic boom this system would need to be solved in such level of accuracy that shock structure be accurately described and propagated from the aircraft to the ground at a distance of more than 15,000 meters. This, in practice, is out of reach whith today's computers. Simplified models are generally applied, or, for a higher accuracy, a near field Euler or Navier-Stokes High Fidelity model is coupled with a simplified, and much less computer demanding, "boom propagation" model.

Shape design in sonic boom mitigation is the next step. In case of an evaluation of sonic boom using mesh adaptation, the design will need combining shape and mesh deformation, see [START_REF] Maute | Sonic boom mitigation vis shape optimization using an adjoint method and application to a supersonic fighter aircraft[END_REF] [START_REF] Nadarajah | Adjoint-Based Sonic Boom Reduction for Wing-Body Configurations in Supersonic Flow[END_REF]. In the HISAC project, see for example [START_REF] Alauzet | Multi-model and multi-scale optimization strategies[END_REF], several strategies have been investigated. Among them, mesh adaptation has been introduced in design in order to accurately evaluate the near field production and propagation of the complex shock structure producing the boom. This idea is not new, see for example [START_REF] Choi | Numerical and Mesh Resolution Requirements for Accurate Sonic Boom Prediction of Complete Aircraft Configurations[END_REF].

When applied to sonic boom applications, the ratio of error between an poorly adapted mesh and the mesh adaptation produced by this method can be several order of magnitude. As a consequence, starting from the couple formed by an adapted mesh and the corresponding numerical flow solution, applying a slight variation of the design parameter (here the shape) will change the flow in such a way that the former adapted mesh cannot be used for obtaining an accurate evaluation of the new flow. This can be explained as follows: the shocks of new flow are outside previous mesh refinements, and error on boom evaluation functional is larger that the effect of shape perturbation. This point makes delicate the use of the mesh-adaptive solver inside an optimization loop.

In this paper, we consider the research by a descent method of an optimum in combination with this mesh adaptation algorithm. In other words, we want to reach by a progressive descent a shape that is optimal when the objective function is evaluated on a mesh that is strongly adapted to the optimal flow. We emphasize that the final mesh is not known in advance, but, instead, built at the same time we optimize. Further, since the adaptation mechanism involves topology changes (face swapping for example), we cannot define a fixed discrete optimization problem. Instead, we propose to approximatively solve the continuous optimality condition with a mesh adaptative method involving a descent step on a frozen mesh that is adapted to the whole descent..

Out standpoint is inspired by the unsteady fixed point adaptation algorithm studied in [START_REF] Alauzet | Transient fixed point based unstructured mesh adaptation[END_REF]. This latter algorithm determines a mesh adapted to the whole set of transient states of an adaptation sub-interval [T i , T i+1 ] of time interval [T 0 , T n ]. We advance in time by subcycling with a time step ∆t much smaller than the adaptation subinterval T i+1 -T i ). Inside [T i , T i+1 ], the mesh is implicitly adapted with the whole set of instantaneous solutions. For this purpose, a fixed point iteration is applied several times over the time levels of sub-interval [T i , T i+1 ] until convergence.

Let us examine the extension of this idea to a gradient loop. A gradient loop consists of to embedded loops. In an external loop, a state, an adjoint and a gradient are evaluated. Then starts a research of a better control in the direction of gradient. In a genuine descent algorithm (and also in more modern Sequential Quadratic Programming), a central condition is the verification that to the better control corresponds a smaller functional. This holds only if mesh is adapted to the diffeernt context of the descent step. What we propose in this paper is a fixed point iteration applied over the steps of each directional descent phase inside a gradient loop. After defining the new composite adaptation/optimization algorithm, we verify by a few numerical optimizations that the proposed concept is indeed useful to solve the addressed issue.

The plan of the paper is as follows. In next section, we formulate the minimization problem to solve. Section 3 presents the two numerical techniques to couple, viz. optimization and mesh adaptation, and propose a way to couple them. Section 4 presents the numerical application.

2 Optimization/Adaptation model

Continuous model

Given a set of admissible shapes Γ ad , a continuous optimal shape design problem writes:

min γ∈Γ ad j(γ) (1)
where j(γ) = J(γ, W (γ)) and W (γ) is the solution of a state equation, a PDE posed on a domain Ω γ with a shape parametrized by the control variable γ:

Ψ(γ, W (γ)) = 0 . (2)
The solution W (γ) of ( 2) is computed through an approximation W (M, γ) with some error depending of a field M defined on Ω γ :

E(γ, M) = || W (M, γ) -W (γ)|| (3)
Then we minimize the approximate functional:

j(M, γ) = J(γ, W (M, γ)) (4)
under conditions on approximation error. We would prefer to choose once for all a particular M such that E(M) = 0 to avoid the approximation error. But this choice is not possible, because it would take an infinite time on a computer. We consider having a maximum CPU effort, measured by the fact that the complexity of the approximation c(M) (typically the number of mesh nodes) is specified to a fixed number N . Then two options can be considered. A natural option ( [START_REF] Becker | Adaptive Finite Elements for Optimal Control problems[END_REF]) is to look for the couple (M + , γ + ) which offers the best approximation of the continuous optimal shape:

(M + , γ + ) such that |γ + -γ opt | = M in .
In the industrial practice, the option minimizing the error in flow variable evaluation can be preferred. We express it in terms of the error estimate ( 3):

(M * , γ * ) such that M * = ArgM inE(γ * , M) j(M, γ * ) ≤ j(M, γ) .
Where the ArgM in is taken for a complexity N . The research of a minimum of j will be based on a descent algorithm. Descent algorithms may take the historical form of the steepest gradient or the form of Sequential Quadratic Programming (SQP). In both cases, a first part of the algorithm is devoted to build a correction, and a second part is devoted to adapt the correction to make it match a simplified quadratic model. A central condition for the success of second part is that we have a reliable descent direction. The algorithm discussed in this paper is designed in order to satisfy this condition by using an exact gradient approach.

Shape design numerical model

The state equation under study is the 3D steady Euler system, expressed in terms of conservative variables W = (ρ, ρU, E), where ρ is the fluid density, U is velocity and E its total energy per volume unit. Triplet (F, G, H) denotes the usual conservative Euler fluxes. In order to optimize the shape without handling a variable computational domain, the variation of the shape is taken into account by a transpiration condition. The state equation then writes:

∀ φ, (Ψ(γ, W ), φ) = - Ω0 (F (W ) ∂φ ∂x + G(W ) ∂φ ∂y + H(W ) ∂φ ∂z ) dΩ 0 + ∂Ω0 p (n 0 x φ 2 + n 0 y φ 3 + n 0 z φ 4 ) d∂Ω 0 + ∂Ω0 q(γ)(W 1 φ 1 + W 2 φ 2 + W 3 φ 3 + W 4 φ 4 + (W 5 + p)φ 5 ) d∂Ω 0 = 0 . (5)
Where p = p(W ) is the pressure of fluid (perfect gas law is assumed), and, according to the transpiration condition formulation, the slip boundary term of the flux Ψ(W ) is defined on a fixed reference geometry Ω 0 of normal exterior n 0 by:

q(γ) = U . (n 0 -n γ )
in which n γ is the exterior normal to varying domain Ω γ . This discrete Euler system, denoted

Ψ h (γ, W h ) = 0 , (6)
is builts by means of a vertex-centered Mixed-Element-Volume approximation on unstructured tetrahedrisations. The consistent part is a Galerkin formulation. The stabilizing part relies on a Roe Riemann solver combined with a MUSCL reconstruction with limiters defined as in [START_REF] Cournède | Positivity statements for a Mixed-Element-Volume scheme on fixed and moving grids[END_REF]. This produces a space accuracy of order two. Let us mention that for solution of the steady system, an explicit multi-stage pseudo-time integration which does not influence the spatial accuracy is applied. For a given γ, we denote by W h (γ) the solution of (6). We evaluate the cost function at a plane z = -R, where R is a multiple of the aircraft length (i.e. R = L, R = 2L, R = 3L etc.). This plane is discretised as the intersection between tetrahedra and the plane represented by the equation z = -R. The cost function is computed over intersection points between mesh and a plane. The cost function is defined by: is the desired or target pressure value specified at the face if ac. One way to control the initial pressure rise is to define on an interval [x a , x b ] a target pressure chosen equal to farfield pressure p ∞ .

j(γ) = J(γ, W h (γ)) = ( if ac |if ac|(P if ac (W h (γ)) -P target if ac ) 2 )/n f
The functional minimum we are looking for is the solution of the following Karush-Kuhn-Tucker (KKT) system:

                       Ψ h (γ, W h ) = 0 (State) ∂J ∂W (γ, W h ) - ∂Ψ h ∂W h (γ, W h ) * • Π = 0 (Adjoint state) ∂J ∂γ (γ, W h ) - ∂Ψ h ∂γ (γ, W h ) * • Π = j (γ) = 0 (Optimality) (7)
The demonstration platform used in this paper takes into account several methodological contributions. Shape parameterization and multilevel preconditioning methods where elaborated in [START_REF] Marco | An additive multilevel preconditioning method and its application to unstructured meshes[END_REF], [START_REF] Vàzquez | Multilevel Optimization of a supersonic aircraft[END_REF], [START_REF] Courty | Multilevel functional Preconditioning for shape optimisation[END_REF]. The residual for adjoint state Π and the functional gradient software are developed with the help of reverse Automatic Differentiation, see [START_REF] Hascoët | Automatic Differentiation for Optimum Design, applied to Sonic Boom reduction[END_REF]. Efficient strategies for adjoint state solving are proposed in [START_REF] Martinelli | Sensitivity Evaluation in Aerodynamic Optimal Design[END_REF]. Comparisons with another platform and some mutual method enrichment are discussed in [START_REF] Alauzet | Multi-model and multi-scale optimization strategies[END_REF].

Mesh adaptation model

With the introduction of mesh adaptation in a design loop, a first question is risen: what do we want to compute accurately? Let us discuss the three following standard options: (a)-we adapt for a better flow evaluation, (b)-we adapt for a better functional evaluation, (c)-we adapt for a better evaluation of optimal design. Option (c) seems the most theoretically convenient, but in practice, the optimality system is not well solved, and the optimal design is not well known. Further, with our particular application, the optimisation is difficult with cost evaluation that do not use an accurate mesh adaptation. Then an external loop as in option (a) is very difficult to apply. Then options (b) and (c) seem more realistic. Option (b) is of high interest. It is still in infancy for anisotropic mesh adaptation and we shall discuss it in a forthcoming paper. Then option (a) is considered here.

The mesh adaptation method relies on a continuous theory and a fixed point discrete algorithm.

Continuous metric theory ([1]

): the mesh is represented by a continuous field, the metric M, with a density d M . The integral N = Ω d M dΩ of density over the computational domain represents the total number of nodes. The adapted metric M L 2 is the metric of number of nodes N which minimises a continuous model for the L 2 P 1 -interpolation error for a flow variable, typically the Mach number.

XXX

The mesh adaptation algorithm is built in order to compute a mesh and a numerical flow. Both are implicitly coupled since flow is computed on the mesh and mesh is specifically adapted to flow. This coupling is attained by iterating a fixed-point algorithm. At each stage, a numerical solution is computed on the current mesh with the Euler flow solver and has to be analyzed by means of an error estimate. The considered error estimate aims at minimizing the interpolation error in norm L 2 , independently of the problem at hand. From the continuous metric theory in [START_REF] Alauzet | Multi-dimensional continuous metric for mesh adaptation[END_REF], an analytical expression of the L 2 -optimal metric M L 2 is exhibited that minimizes the interpolation error in norm L 2 . Let u be an analytic solution defined on computational domain Ω and let N denotes the desired number of vertices for the mesh, the aims is to create the "best" mesh H, i.e., the optimal continuous metric M, to minimize the interpolation error u -Π h u 2 in L 2 norm. Π h u denotes the linear interpolate of u on H. The local interpolation error in the neighborhood of the vertex a is written:

e M (a) = n i=1 h 2 i ∂ 2 u ∂α i 2 , (8)
where h i stand for metric sizes and ∂ 2 u ∂αi 2 represents the eigenvalues of the Hessian of the variable u. Now, we are looking for a function M that minimizes, for a given number N of vertices, the L p norm of this error. To this end, we have to solve the following problem:

min M E(M) = min M Ω (e M (x)) 2 dx = min h i Ω n i=1 h 2 i (x) ∂ 2 u ∂α i 2 (x) 2 dx, (9)
under the constraint:

C(M) = Ω n i=1 h -1 i (x) dx = Ω d(x) dx = N. (10)
The resulting optimal metric solution of the Problem ( 9) and [START_REF] Hascoët | Automatic Differentiation for Optimum Design, applied to Sonic Boom reduction[END_REF] for the L 2 norm in three dimensions reads:

M L 2 = D L 2 (det |H u |) -1 7 R -1 u |Λ| R u with D L 2 = N 2 3   Ω 3 i=1 ∂ 2 u ∂α i 2 2 7   -2 3 . ( 11
)
Mesh adaptative algorithm: The sensor u will be for us the Mach number. The Hessian of it is reconstructed from the numerical solution by a double L 2 projection ( [START_REF] Alauzet | Multi-dimensional continuous metric for mesh adaptation[END_REF]) and we derive an approximation of the metric. Next, an adapted mesh is generated with respect to this metric where the aim is to generate a mesh such that all edges have a length equal (or close to) unity in the prescribed metric and such that all elements are almost regular. The volume mesh is adapted by local mesh modifications of the previous mesh (the mesh is not regenerated) using mesh operations: vertex insertion, edge and face swap, collapse and node displacement. The vertex insertion procedure uses an anisotropic generalization of the Delaunay kernel. Finally, the solution is linearly interpolated on the new mesh. In a static adaptation, this procedure is repeated up to convergence. Process is considered as converged in Step 7 when the difference between two metrics is small. In practice, this fixed point iterates about 5 times. Computing expenses can be reduced by saving and transferring flow arrays between remeshings. It is shown in [START_REF] Loseille | Achievement of global second order mesh convergence for discontinuous flows with adapted unstructured meshes[END_REF] that for flow calculation, this mesh adaptive loop produces second-order accurate Mach number outputs. XXX

Coupling in discrete case

We discuss now the strategy for combining a high-level mesh adaptation and the solution of the KKT system [START_REF] Cournède | Positivity statements for a Mixed-Element-Volume scheme on fixed and moving grids[END_REF]. We first describe the two main ingredients of this combination.

Minimizing for a fixed mesh

Assuming we are applying a steepest descent algorithm, we use an exact gradient of the discrete functional in order to keep a reliable descent direction. The following sequence can be applied to shape design without changing the computational mesh, thanks to the transpiration condition:

Gradient and line search:

-compute the flow (state equation), -compute the adjoint state, -compute the (exact)gradient of functional, -descent: update shape control variable.

Mesh adaptation for a fixed control

Coupled iteration

The flow changes when the shape is changed and adapted mesh needs be changed too . We shall refer to static adaptation when only one shape and one flow are concerned, and to dynamic adaptation else. We distinguish two level of coupling between adaptation and optimization:

Weak coupling between optimization and adaptation:

It relies on a static anisotropic adaptation loop applied at beginning of every gradient step.

Algorithm 1: static adaptation/gradient step:

Input: M 0 , γ 0 Output: M, γ opt , the converged mesh and optimal shape 1-Do 2-Do 2.1-compute on current mesh the flow (state equation),

2.2-compute the metrics for flow in steps 2,

build a new mesh specified by the new metric and by a fixed number N of nodes, While adaptation is not converged.

3-compute on current mesh the adjoint state, 4-compute on current mesh the (exact) gradient of functional, 5-perform descent: update shape control variable the descent direction, While control is not optimized.

Strong coupling:

A mesh that is accurately adapted to a flow will be much less accurate when used for computing an -even slightlydifferent flow. Then starting a line search with a mesh adapted to the first flow may result in poor evaluation of the other flows and a poor evaluation of the descent step length. To avoid this, we adapt the transient fixed point adaptation method introduced in [START_REF] Alauzet | Transient fixed point based unstructured mesh adaptation[END_REF]. In the fixed-point adaptation/gradient loop, the mesh is adapted to the k-th gradient+search step by adapting it to all the flows of this step:

-to each flow correspond an optimal metric, -the intersection of all these metrics is computed, -the adapted mesh is built from this intersection metric.

Algorithm 2: dynamic adaptation/gradient step:

Input: M 0 , γ 0 Output: M, γ opt , the converged mesh and optimal shape 1-Do The fixed point adaptation/gradient step is then itself included in the gradient loop. It is necessary to fix either the number of nodes or a certain level of accuracy in order to have, in the fixed-point process a well-posed problem with respect to the metric. It is possible to imagine to vary this number of nodes from one gradient step to the other. A uniform accuracy between time steps is a sound option in the case for an unsteady process,this is not necessary in the case of optimisation (we could try to incerase progressively accuracy.

In the experiments presented in the sequel, we simply have fixed N .

Improved shape representation:

The use of a transpiration condition is useful for the application of the descent with a fixed mesh. But it may introduce inaccuracies in the numerical description of the shape being computed. In particular, transpiration approximation is known as producing an inaccurate flow when the amplitude of the shape perturbation to account for in terms of surface displacement and orientation is not small. Now, the progression towards optimal shape is generally combined with an non-negligible increasing of the amplitude. In [START_REF] Vàzquez | A methodology for the shape optimization of flexible wings[END_REF], it is proposed to recover flow accuracy by updating the mesh at the end of every optimization step. The new mesh is fitted to the shape. This is obtained by a mesh deformation system relying on a spring analogy introduced in [START_REF] Degand | A three-dimensional torsional spring analogy method for unstructured dynamic meshes[END_REF]. This combines two advantages, first the flow at the beginning of each optimization iteration is evaluated without transpiration, and, second, this also holds for the optimum context when shape update is converging to zero. In that case, in the set of three optimality conditions, state and adjoint are not affected by the transpiration simplification. Only the stationarity of functional ("gradient is zero" in case of non-constraint) is influenced by the transpiration approximation. This strategy is summarized in Algorithm 3: Algorithm 3: dynamic adaptation/gradient step with mesh deformation:

Input: M 0 , γ 0 Output: M, γ opt , the converged mesh and optimal shape 1-Do 2-Do 2.1-compute on current mesh the flow (state equation), 2.2-compute on current mesh the adjoint state, 2.3-compute on current mesh the (exact)gradient of functional, 2.4-perform descent: update shape control variable 2.5-compute the intersection of metrics for each intermediate flow in steps 2.1-2.3, 2.6-build a new mesh specified by the intersected metric and by a fixed number N of nodes, While adaptation is not converged.

Compute a deformed mesh conforming the new shape While control is not optimized. Finally, the optimization/adaptation platform can be represented as in figure 1.

Applications to problem under study

Preliminary optimization computations have been applied to an HISAC test case (figure ??). We describe in Table 1, the initial configuration used to perform the pseudo-strong and the strong coupling computations. Both strategies use mesh deformation introduced in Algorithm 3. Further details can be found in [START_REF] Mesri | Gestion et Contrôle des maillages non structurés Anisotropes, Applications en Aérodynamique[END_REF]. Table 1: simulation parameters Applications are based on optimizing for minimum initial shock pressure rise (ISPR) using transpiration conditions and torsional springs deformation. Minimizing the ISPR leads not only to the lowest ISPR but also to the lowest maximum overpressure.

Application of pseudo-strongly coupled scheme to coarse meshes:

A pseudo-strongly coupled scheme consists in using slightly the mesh adaptation process in the optimization platform, which means that we apply just a single time the mesh adaptation process by iteration of optimization. The aim of this exercise is to measure the impact of mesh adaptation in shape optimization platforms. Figures below, represent some comparisons between the original and the optimized configurations.

Figure ?? shows the horizontal cuts of pressure value at z = -30m in order to compare the initial flow and the final flow after optimization. We observe that the first shock localization of initial flow is slightly reduced. Figure 2 shows on the right the evaluation of functional during the coupled loop. The oscillations observed in the functional curve are associated to the re-meshing stage. On the other hand one notes that with the last iteration, a brutal descent of the function. This behavior lets us to raise questions about the certainty of the functional computation. On the left of the figure 2 we depict the progress obtained on the near-field pressure after optimization. The red line (green line) corresponds to the initial (final) near-field pressure respectively. Figure 3 shows the reduction obtained after propagation of the near-field pressure to the ground. Figure ?? shows the final pressure distribution and adapted mesh respectively.

Figure 4 shows from the left to the right a comparison between the original and the optimized shapes at the nose tip respectively.

Application of strongly coupled scheme to coarse meshes:

A strongly coupled scheme consists in using a sufficiently converged fixed-point mesh adaptation process in the optimization loop. Figure ?? shows the horizontal cuts of pressure value at z = -30m in order to compare the initial flow and the final flow after optimization. We observe that the first shock localization of initial flow is well reduced. Figure 5 shows on the right the evaluation of functional during the coupled loop. The oscillations observed in the functional curve are associated to the mesh adaptation phase which is devoted to find the best adapted mesh and then ensure the good evaluation of the functional. This mesh adaptation influence over global optimization loop gives us a computation certainty along optimization cycle. On the left of the figure 5 we depict the progress obtained on the near-field pressure after optimization. The red line (green line) corresponds to the initial (final) near-field pressure respectively. Figure 6 shows the reduction obtained after propagation of the near-field pressure to the ground. Figure ?? shows the final pressure distribution and adapted mesh respectively.

Figure 7 shows from the left to the right a comparison between the original and the optimized shapes at the nose tip respectively. We summarize the ground signatures obtained with the pseudo-strong coupling and the strong coupling strategies in the following table:

Application of strong coupling with finer meshes

We recompute the above optimum with a finer specification of the number of nodes. This number is now fixed to 100,000 nodes. Strong coupling, fine mesh: Optimization of the HISAC shape with a mesh size of 100Kcells

Strong coupling, fine mesh: Optimized shape: adapted mesh Optimized shape

Concluding remarks

We have addressed a design problem in which mesh adaptation is mandatory. It can be considered as an equality constraint, in complement of the state system. Observing that this constraint is strongly nonlinear, we studies fixed point strategies in order to couple more or less strongly the adaptation process and the optimisation loop. This has been applied to a sonic boom mitigation study. Some of our numerical experiments show that when choosing strong coupling, the optimization can be successfully performed.

In the presented application, mesh adapted optimisation brings information of higher quality than before. We are expecting an extra improvement by introducing a goal-oriented adaptation criterion.

  Figure 1: Strong coupling platform

3 :

 3 l f ront = 25 and l back = 35. 2: Pseudo-strong coupling. Left: Comparison of the near-field signatures for the original and the optimized configurations, right: cost function evaluation around coupled mesh adaptation and optimization loop.

Figure 3 :Figure 4 :

 34 Figure 3: Pseudo-strong coupling: comparison of the ground signatures for the original and the optimized configurations.

3 :

 3 l f ront = 25 and l back = 35.

Figure 5 :

 5 Figure 5: Strong coupling: Left: Comparison of the near-field signatures for the original and the optimized configurations, right: cost function evaluation around coupled mesh adaptation and optimization loop.

Figure 6 :Figure 7 :

 67 Figure 6: Strong coupling: Left: comparison of the ground signatures for the original and the optimized configurations, right: comparison of the near-field signatures for the original and the optimized configurations

  acwhere |if ac| is the area of the face if ac, this face is obtained by intersection of a mesh element and the plane, then the resulting face is or a triangle or a quadrilateral. n f ac is the number of intersected faces. Denoting by P (W h ) the pressure field corresponding to W h (γ), P if ac (W h ) is obtained by P 1 interpolation of P (W h ) on intersection face if ac.

	P target if ac

Table 2 :

 2 Initial shock pressure rise in Pascal for different strategies.These results suggest that coupling strategies are suited for minimizing the ISPR. The sonic boom is reduced in both cases by creating a blunt nose (figs.4 and 7). In particular the strong coupling strategy is more efficient than the pseudo-strong coupling strategy. Indeed, the gain reached by SC (strong coupling) is about 20% and the gain reached by PSC (pseudo-strong coupling) does not exceed the 12%.

					pressure analysis at z=-30
		0.285 0.286						pressure before pressure after
		0.284
		0.283
		0.282
	pressure	0.28 0.281
		0.279
		0.278
		0.277
		0.276
		0.275	25	30	35	40	45	50	55	60	65
					x-axis probe under the aircraft at z=-30
	Pressure comparison

Acknowledgements

We acknowledge for the support of this work by FP6-HISAC European project.


Maria A Wimmer
email: wimmer@uni-koblenz.de

Rüdiger Grimm
email: grimm@uni-koblenz.de

Nico Jahn
email: jahn@uni-koblenz.de

J Felix Hampe
email: hampe@uni-koblenz.de

Mobile Participation: Exploring Mobile Tools in E-Participation

Keywords: Mobile participation, mPart, e-participation, mPart tools, mPart-API framework

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Mobile phones have reached a penetration of 125 % in Europe in 2009. Also the smartphone penetration is growing more and more. However, main use of mobile and in particular smartphone technology is currently recognized in private consumer use. While different attempts of introducing mobile technology in government contexts are known for nearly a decade (so-called m-government), mobile features are not so extensively exploited in e-participation contexts. This is astonishing especially since eparticipation is striving for reaching out widely to citizens, and mobile technology is widespread in many developed and even in some developing countries. Some e-participation projects have begun to allow smartphones to have access to their communication services. However, these are only a few, and the integration is rather ad-hoc. There is no standard strategy or architecture to build up mobile participation with respect to important requirements such as user-friendliness, scalability, security, and seamless cooperation with other participation means. We will use the acronym 'mPart' in short for 'm-participation' or 'mobile participation'.

In order to allow mPart tools to be integrated in a flexible way in different eparticipation contexts, we suggest an architecture that separates the user functions from an underlying communication infrastructure, especially from the Internet. The architecture is based on an mPart-API framework that provides well defined interfaces to the user tools as well as secure communication channels on top of the underlying infrastructure. The architecture provides a reference framework for integrating various mPart tools into a common architectural environment.

The paper is structured as follows: Chapter 2 investigates the state of the art of eparticipation literature. Chapter 3 provides an overview of related work on important mPart projects and their tools. Chapter 4 outlines the project and mPart applications with related research aims of an interdisciplinary project on communication, media and politics. The mPart tools we developed are described in chapter 5, together with a report of initial responses by users. Conclusions and an outlook on further research are given in chapter 6.

Setting Grounds for Mobile Participation: Foundations and Related Work on E-Participation

As a generic and widespread understanding, e-participation is referred to as the use of Information and Communication Technologies (ICT) in political participation (see e.g. [11, 12, 18, 23]). Macintosh argues that innovative tools and technology provide people with the capacity to participate and influence political decision-making [10].

Scholars investigating e-participation have made an attempt to structure and systematize the field of study through frameworks (e.g. [18, 23]) and differentiation among separate e-participation areas, such as information provision, consultation, deliberation, mediation, petitioning, spatial planning, participatory budgeting, etc. (see e.g. 26, 27]). An important evolution of the field has been observed since the revolution of the Internet as a participatory web, where everyone can communicate through Web 2.0 technologies [7]. The potential of using electronic means to reach the wider citizenry opened up new possibilities for political participation via electronic means [13]. Since then, a number of e-participation tools have been developed in various projects through the support of the European Commission and through governments of different countries. An assessment of such programs and projects to spur innovation and to advance solutions for citizen participation via online means in different eparticipation areas is e.g. available in [16, 23, 28]. Also, the United Nations have defined an e-participation index along their annual e-government surveys, which 'assesses the quality and usefulness of information and services provided by a country for the purpose of engaging its citizens in public policy making' [START_REF] Abramowicz | GOV (USability-drivEn open platform for MobilE GOVernment)[END_REF] . The index evaluates the capacity and willingness of a State to explore 'deliberative, participatory decision-making in public policy' and whether a State reaches the objectives of 'its own socially inclusive governance program' [START_REF] Bertot | Social Media Technology and Government Transparency[END_REF] . In the 2012 survey, Germany scored 0.7632, while Netherlands and South Korea reached the maximum of 1.000 [26, p. 134].

E-participation is also driven by technology development to support citizen participation in political decision-making. A categorization of ICT tools supporting eparticipation endeavors is e.g. given in [21, 23]. Tambouris et al distinguish e.g. among rather simple tools such as weblogs and web portals and more sophisticated consultation platforms, argument visualization tools and natural language interfaces. Technologies include e.g. messaging, semantic web, filtering methods and ontologies. In a study the authors performed 2007 on nineteen EC funded research projects of the field seven projects using mobile technologies have been identified [23]. Half a decade later, social media on the one hand and the use of mobile technologies on the other hand, have become prime means for interaction among citizens and governments in e-government and e-participation initiatives [START_REF] Biocca | Continuous Response Measurement (CRM). A Computerized Tool for Research on the Cognitive Processing of Communication Messages[END_REF] . Recent EUROSTAT data indicate that more than half of the Internet users in Europe post to social media [START_REF] Brend'amour | Generisches Framework für die mobile Kommunikation von anonymisierten Gruppen (generic framework for mobile communication of anonymizated groups)[END_REF] .

While mobile government has reached attention as an extension or supplement of e-government [24], mobile participation has so far not reached wide attention as a concept. We therefore define mobile participation (or m-participation, in short mPart), as an extension of the concepts of e-participation -relying on above described foundations of e-participation. mPart refers to the extensive use of mobile technologies and mobile applications in e-participation contexts. Nowadays, Internet, broadband access and mobile phones are more widespread in Europe. In 2012, Eurostat reports an internet penetration in households of 76 % in EU27, with Germany reaching 85 %; broadband access being recorded with 82 % in EU27 and 82 % in Germany [START_REF] Charalabidis | Participative Public Policy Making Through Multiple Social Media Platforms Utilization[END_REF] . Statistics on mobile phone penetration showed already in 2009 a penetration of 125 % in EU27 and of 137 % in Germany [START_REF]Empowering Open and Collaborative Governance. Technologies and Methods for Online Citizen Engagement in Public Policy Making[END_REF] . Also the use of smartphones is catching up quickly -47.6% of people in the EU5 (UK, Spain, Italy, France and Germany) are reported to use a smartphone in Q1 2012, with Germany scoring last among these top 5 with 41%. [START_REF] Effing | Social Media and Political Participation: Are Facebook, Twitter and YouTube Democratizing Our Political Systems?[END_REF] Hence, the provision of mobile applications to engage citizens in policy processes and democratic decision-making of States through mobile phones and smartphones is a natural and consequent evolution. To set the grounds for mobile participation, the next section investigates the use of mobile applications, tools and technologies in e-participation contexts of existing projects.

3

The Government compiling interests and roles of relevant stakeholders and correlating their roles and interests in distinct service and business scenarios, and (3) Recommendations for Service Planning including aspects of technology, standards and business operation to serve as an example for "others" when planning similar services [1, 15]. After use-me.gov, several projects have investigated the usage of mobile technology for providing on-the-spot information to governments such as damages on infrastructure in cities, where photos are made with mobile phones and are then sent to government sites via MMS or emails through smartphones or through uploads to a web site. The most known project in this regard is FixMyStreet in UK [START_REF] Emmer | Changing Political Communication and Participation in Germany[END_REF] . Also in Germany, similar examples exist such as Märker Brandenburg [START_REF] Goldberg | Pseudonymous communications infrastructure for the internet[END_REF] or "Sag's uns" of the city of Cologne, which is part of the city's mobile app [START_REF] Ergazakis | A State-of-The-Art Review of Applied Forms and Areas, Tools and Technologies for e-Participation[END_REF] . The main features of the mobile part of these solutions are MMS or email communication to a government site with a server in the backend to integrate the mobile communication entries into the government solution of complaints management. Some sites are now beginning to integrate mobile access via smartphones (e.g. Cologne's app).

Besides reporting on damages in public spaces and other misconceptions on infrastructures of a city, cities are also launching mobile apps to provide information about the city and for tourists via smartphones. Examples to name but a few are: the Cologne service app, which provides up-to-date information and options for contacting the city with questions or feedback by the citizens [START_REF] Macintosh | Characterizing e-participation in policy-making[END_REF] ; various apps for visitors to the London city (either for download before visiting or accessible through numerous free wireless networks in the city of London) [START_REF] Macintosh | E-Democracy and E-Participation Research in Europe[END_REF] ; or the Stuttgart App, which provides citizens and visitors with relevant information about the city and its tourism and traffic, as well as some e-government services [START_REF] Maier | Web 2.0 -Moderatorenrechte für alle? Gibt es eine E-Partizipation 2.0 im Web 2.0?[END_REF] .

With the evolution of open government data, a vast amount of mobile apps have evolved to provide users of smartphones information about cities or particular aspects of public interest. A good example of providing such mobile apps based on open government data is apps for Vienna with the objective to providing citizens, tourists and businesses with relevant information [START_REF]Real-Time Response Measurement in the Social Sciences[END_REF] . To spur the developments of the use of open government data in Germany, a contest was launched to bring forward mobile apps for informing citizens and businesses on issues of interest. The Apps4Deutschland brought forward 77 apps (among which many are for smartphones) providing useful information and services to citizens and other users by building on open government data sets [START_REF] Olmstead | TheUSE-ME.GOV (USability-drivEn open platform for MobilE GOVernment)[END_REF] . There are many more examples where governments are providing their data to enable added-value services via smartphones to citizens. An overview of examples in the US is e.g. given in [2].

It is to be noted that most of afore mentioned solutions are largely targeting egovernment contexts, while the use of mobile apps and tools in the context of eparticipation is still rare. Examples of such projects are Padgets and urbanAPI, which are briefly introduced hereafter (both funded in framework program 7 of the EC).

PADGETS (Policy Gadgets Mashing Underlying Group Knowledge in Web 2.0 Media) [START_REF] Panopoulou | eParticipation Initiatives in Europe: Learning from Practitioners[END_REF] introduces the concept of Policy Gadgets (Padgets). These are applications on top of web 2.0 technology to describe and control the interaction between a user's web software and others. The project targets integration of this concept in the established social media platforms to acquire a large number of people and uses social platforms for new services. It thereby also integrates smartphone technology for the interaction among citizens and policy makers [5]. urbanAPI (Urban Agile Policy Implementation) targets and uses virtual representations of planning decisions. Models of the real world display ideas about spatial planning. These models are 3D-models of blocks of houses and 2D-maps for visual representation of socioeconomic activity and a region-wide development simulation addressing urban growth and change. Mobile communication services allow the exploration of communication traces, describing human sojourn and activity patterns. [START_REF] Payne | An inkblot for attitudes: Affect misattribution as implicit measurement[END_REF] To conclude, searching for projects of e-participation employing mobile technology shows that this development is still in its infancy. The few projects we came across do employ mobile technology, even though not all fully focus on e-participation. Moreover, there is no standard strategy or architecture to build up mobile participation with respect of different challenges such as user-friendliness, acceptance, extensibility, scalability, seamless cooperation with other participation means, etc. To date, mobile tools are integrated rather in an ad-hoc manner However, the penetration of mobile phones and the trends towards more mobile access to services demands for much more research and investment in developing tools and applications for mobile participation. The State of Rhineland-Palatinate has therefore launched a project where different research disciplines are to work together to foster developments of mobile participation among others. The project is introduced in the next chapter.

4

The The initiative is divided into ten sub-projects, which all help to achieve the accomplishment of the overall research focus. These ten sub-projects are:

1. "Political communication via smartphone" targeting the question of how political information is consumed by the citizen in everyday life. 2. "Para-social Relationship to political actors" studying the impact of trust in the popularity of politicians. 3. "Mobile participation of citizens with protection of privacy" designing tools and services for mobile participation systems that respect privacy and security needs in order to allow the users to trust the technical system for mobile participation. 4. "Televised Debates in Germany" studying recipients real-time feedback while watching televised debates. Research targets are knowledge about politicians' argumentation templates and the impact at recipients' side. 5. "Mobilization of right-wing parties against Europe" focusing on the impact of right-wing parties activities on citizens. 6. "Personalization of political communication" investigating the change of relevance of a single political person and a whole party. 7. "Moral misbehavior of politicians" addressing the sacrifice of cooperativeness empowered by politicians' behavior and reports of them. 8. "Representation, Democracy and Trust" examining the type and relevance of interaction relationships, based on Web 2.0 technology, between a representative and citizens. 9. "Statistical and semantic analysis of political communication in social media" aiming to develop computer-based methods, which push transparency in political communication.

10. "Usage motives for of social media" targeting motives of political information and communication in social media and studying the reliability of political information in social media.

The mobile participation tools and applications developed along the initiative support the projects 3) "Mobile participation of citizens with protection of privacy", 4) "Televised Debates in Germany", 5) "Mobilization of right-wing parties against Europe" and 6) "Personalization of political communication". Other sub-projects outside our research focus are also supported by realizing smartphone-based test infrastructures with the use of a survey tool and special measurement tools under our development, which are described in the next chapter.

mPart Tools in E-Participation Contexts

In this section, we specify the mPart tools under our development and examine the advantages over existing mPart tools. We differentiate between mPart tools themselves, which are directly used for participation as described in subsection 5.2, software components cooperating with an underlying infrastructure as outlined in subsection 5.3, and online survey tools used for research in other projects of our research focus as depicted in subsection 5.4. How these features work together is outlined in the overall mPart system architecture in subsection 5.1.

mPart System Architecture

In order to achieve a flexible and maintainable software architecture, the mPart system architecture is separated in a framework of components ( as e.g. argued in [19, p. 394]), which are grouped and related to one another by well-defined interfaces as shown in fig. 1. The specification of the interface architecture of the mPart-API-Framework can be used for a basic evaluation of some generic properties like a generic approach, flexibility for anonymous usage and for different authentication and authorization functions, for extensibility by more modules, and for independence of enddevice connections like e.g. trusted servers and simple-transport clients (see subsection 5.3). A major advantage of the architecture is that it is open for the developer community, because it supports an easy integration of new modules and special mPart tool implementations. It is also meant to be a generic framework that can be extended and adapted to special needs.

To ease system maintenance and especially to control the security features, "mPart tools" are separated from the "mPart-API framework": While mPart tools are directly invoked by users, the components of the mPart-API framework build an underlying communication infrastructure with related security and privacy support services. Some of these tools, like a mobile survey tool and a helper to secure users' privacy, enable participation directly. Others, like online survey tools, are special research tools to support researchers in their subprojects. They will work on top of the common mPart tools.

mPart Tools

In this subsection, we outline the set of mPart tools developed within our project: Mobile Survey: To run a survey is an efficient way to analyze the opinion of a bigger group of individuals, like the public opinion. A related survey tool is an essential mPart tool. We are developing an own survey system, which is already used by our project partners to collect research data. A first implementation was done by the student project "mPartOnCampus". They developed an approach for a participation platform for the relatives of our university, where we find also a complex political system. The main advantages of developing an own implementation, instead of using one from a third party, are the possibility to fulfill special requirements and integration in an application, which works on top of our own developed underlying infrastructure. For example, LimeSurvey [START_REF] Phang | A framework of ICT exploitation for e-participation initiatives[END_REF] is an often used survey tool. It lacks a usable interface for mobile devices and for special needs, like retriggering survey participants, when a study is ongoing over time.

Mobile Consultation: Consultation in the context of e-participation is described by Macintosh as "a two-way relationship in which citizens provide feedback to government. It is based on the prior definition of information. Governments define the issues for consultation, set the questions and manage the process, while citizens are invited to contribute their views and opinions" [11]. Consultation has been classified as an e-participation area and a number of tools have emerged to support public consultation in political decision-making (general consultation, policy consultation or consultation in lawmaking) (see e.g. [16, 18, 23, 28]). Since existing projects on consultation in political decision-making barely use mobile devices, we have developed a mobile consultation tool, which enables consultation with respect of specific consultation needs. Among others these could be the request for feedback regarding measures taken or the discussion about measures to take in the future. The mobile survey implementation will as well be used as a tool within the mobile consultation tool. First prototypes for such a tool have been implemented in the project "mPartOnCampus" at the University of Koblenz-Landau. The tool will be advanced in iterative steps.

Privacy Navigator: Security requires both, functional support by a well-designed working system, and user awareness based on a sufficient knowledge about the risks and a cautious way of acting. A typical example is trust into website operators. Although a channel between a visitor of a website and a webserver is protected end-to-end by SSL and certificate validation is supported by a browser, the user could circumvent the protection and manually accept untrustworthy websites. The Privacy Navigator supports user awareness of security and privacy. It offers a contextsensitive adaptation of the user and its issue to adequately secure communication channels, by choosing the channel type on the basis of the type of participation, a pragmatic analysis of the participation issue and of course additional user inputs. The design follows a simple scale for intensity of privacy, which is understood by unskilled users. Our research aim is twofold: firstly we implement the Privacy Navigator in all mPart tools in order to learn an effective way of privacy enhancing technology for mPart functions. Secondly, we will study the way of change in user behavior in order to learn how users trust the system.

mPart-API Framework

mPart tools do not directly use common Internet channels. We interpose an underlying infrastructure between the mPart tools and the Internet, as shown in fig. 1, encapsulated by the mPart-API framework. The mPart-API framework's tasks are 1. decouple the user functions of the mPart tools from an underlying communication infrastructure, especially from the Internet, 11. establish secure communication channels on top of the underlying infrastructure, 12. provide well defined interfaces, which are used by the mPart tools or other nodes of the mPart-API framework.

The mPart-API framework is composed of a set of interface specifications, used for implementation of the collaborating nodes and agents within the mPart system. Nodes are transmitting via machines that build an overlay network. In some cases they use other overlay networks between an underlying communication structure and themselves to establish communication channels. The design of the system allows an easy integration of new modules, which can establish communication channels on top of other communication structures.

A prototypical implementation of the framework shows the effectiveness of the architecture with an implementation on top of different communication networks. For example, I2P [START_REF] Reussner | Handbuch der Softwarearchitektur[END_REF] is an overlay network for anonymous communication and thus supports the privacy of the communication partners. [4] used an implementation of I2P, which is encapsulated in a generalized communication module within the mPart-API-Framework, to realize a so called Trusted Server. A Trusted Server contains a whole implementation of the mPart-API, thus it is a part of the underlying mPart-Infrastructure, consisting of many cooperating mPart nodes. It can be used as a gateway for Mobile Clients or other applications, which have no (No-Transport-Client) or no complete (Simple-Transport-Client) implementation of the mPart-API, as shown in fig. 2. We evaluated the usability of the Trusted Server within the student project "mPartOnCampus".

Online Survey Tools

In some subprojects of disciplines within our research focus (psychology, political theory and communication sciences), computer-aided measurement tools are used by a test-lab setup to measure human behavior by capturing user input. The following software tools are developed for this purpose: Affective Misattribution Procedure: A psychological hypothesis supposes that recipients can be influenced by unconsciously consumed information [17]. The subprojects 5) "Mobilization of right-wing parties against Europe" and 6) "Personalization of political communication" aim to prove this effect by measuring a change of behavior. By their measurement they want to determine, which context-sensitive information results in a certain change of behavior. One method to examine this effect is the Affective Misattribution Procedure (AMP) described in [8]. We realized an AMP tool with connectivity to different survey systems, so that this procedure can be used directly in the context of a running survey.

Real Time Response Measurement: The concept of Real Time Response Measurement means immediate capturing of recipients' perception while consuming information. This method is explained and analyzed in [14]. The test environment of the subproject 4) "Televised Debates in Germany" is going to be the TV duel of the chancellor candidates in Germany in September 2013. It is suspected that investigation of data in a laboratory environment affects measurement of direct perception [3]. Our invention is the execution of such tests in a natural reception situation, e.g. respondents participate from their home being on the sofa. We will create a mobile app that provides a proper user interface for such measurements. It is expected that the study in this real-life environment will omit unwanted side-effect of a test-lab atmosphere and will make the test-results more reliable.

All our mPart tools are currently under development. As mentioned above, the online survey tools will be used by the subprojects 5) and 6) and by other projects outside our research focus. For the time being, they are used in a first test phase by the developers. We have received first feed-back reports by the users within our research project. They report that our mPart survey tools are running more stable and produce more reliable response data than the older Flash tools they used before. For example, they appreciate that our AMP has an online interface for integration in other survey systems like, for example, the GfK system [START_REF] Scherer | E-participation and enterprise architecture frameworks: An analysis[END_REF] , which implemented the surveys. Also with respect to RTR, the applicants report that their first impressions promise superior user convenience and more reliable results. A particular advantage is that larger sample sizes can be handled with less effort. This is an indication, that we will be able to fulfill the requirements flexibility, robustness and performance. In the next project phase, a systematic evaluation will be performed including quantitative test methods.

Conclusions

The paper at hand shows that a few projects have already started to integrate the use of smartphones in e-participation applications. However, this happens in an ad-hoc way without a strategic design. We have presented an architecture that allows a flexible integration of mPart tools in an mPart-API framework. The framework offers infrastructure services such as overlay networks for anonymous communication (if needed) or authorization services (if needed) etc. through a standardized API to mPart tools. The framework is generic to enable extension of the mPart toolset with further implementations.

Examples of mPart tools under development are introduced with first reports by users (researchers in the overall multi-disciplinary project KoMePol).

Beside the technical development of the framework and the tools, our next important steps are to perform a systematic evaluation of the existing tools against the requirements: user-friendliness, acceptance, extensibility, scalability, and seamless cooperation with other participation means; and to extend the architecture with adding complementary mPart tools. Further research will be conducted to amend the architecture towards a comprehensive reference architecture for mobile participation.

  Research Initiative 'Communication, Media and Politics' and its mPart Project in the State Rhineland-Palatinate In the period of 2012-2015, the State Rhineland-Palatinate is supporting a new research strand at the University of Koblenz-Landau, which addresses "Communication, Media and Politics" (KoMePol). The initiative brings together different research disciplines to study various concepts of the use of media in politics and how communication is impacted by the use of a particular media type. Finally, modern ICT and the use of mobile communication facilities are explored and studied in e-participation contexts. The initiative is also investigating the building of trust in communicating via innovative media in political contexts (directly or indirectly). The participation of social science, political theory and psychology allows to do research on trust in political systems and their actors. The participation of computer science and communication theory enables studying phenomena of trust in computer systems and communication via mobile devices, mobile communication infrastructures and open networks.

Fig. 1 .

 1 Fig. 1. Layers of the mPart System

Fig. 2 .

 2 Fig. 2. mPart Usage Scenario -an implementation of the mPart-API

Use of Mobile Technology in Government Projects: an Investigation of the Current State of Projects Mobile

  technology has been explored in several projects of e-government and eparticipation. Among the first projects funded in the scope of framework program 6 of the EC, use-me.gov researched mobile government solutions around 2005. Its aim was to advance three crucial developments for mobile solutions: (1) an Open Service Platform for Mobile Government meeting the most critical usability, interoperability and scalability requirements as well as supporting shared use between public organizations and respective departments, (2) Comprehensive Business Models for Mobile

http://unpan3.un.org/egovkb/egovernment_overview/eparticipation.htm (last access:

24/03/2013)

http://www.fixmystreet.com/ (last access 28/03/2013)

http://maerker.brandenburg.de/brandenburg (last access 28/03/2013)

http://www.stadt-koeln.de/1/verwaltung/10425/ (last access 28/03/2013)

Ibid.

http://www.visitlondon.com/traveller-information/getting-around-london/london-maps-andguides/apps (last access 28/03/2013)

[START_REF] Maier | Web 2.0 -Moderatorenrechte für alle? Gibt es eine E-Partizipation 2.0 im Web 2.0?[END_REF] http://www.stuttgart.de/item/show/168768 (last access 28/03/2013)

http://data.wien.gv.at/apps/ (last access 28/03/2013)

http://apps4deutschland.de/category/apps/ (last access 28/03/2013)

http://www.padgets.eu (last access 25/03/2013)

http://www.urbanapi.eu (last access 2013-06-03)

http://www.limesurvey.org -last seen on 2012-13-03

http://www.i2p2.de -last seen

2013-08-03

http://www.gfk.com (last access 2012-26-03)

Acknowledgement: This work was partially funded by the KoMePol project, which is funded by the Research Initiative (Stage II) of the State Rhineland-Palatinate. The authors express their gratitude for this interdisciplinary research opportunity.


Efthimios Tambouris
email: tambouris@uom.gr

Targeted Policy Making by Transforming Social Networks

Keywords:

Current economic conditions press governments worldwide to develop more efficient policies with significantly lower budgets. A possible way to achieve this is by exploiting online social networks. The tremendous impact of social networks in everyday life (e.g. obesity, financial situation, smoking etc.) is now well established in the literature. However, up to now, the impact of online social networks in policy making has not been thoroughly investigated. We claim that policies, in addition to their traditional aims, should also aim to improve the online connections of target population as this will enable more targeted thus more efficient and effective policy making. In this paper, we present this idea, relate it to traditional policy making lifecycles, and investigate relevant technological aspects. We anticipate this work will contribute to the on-going discussion on the pros and cons of exploiting online social networks in policy making.

Introduction

Today, a large number of economic, social, health and other policies are not sufficiently successful. In many case, funding and social benefits do not reach those is real need. Even when they do so, they still fail to assist beneficiaries to permanently overcome their problems. As an example, many policies for promoting entrepreneurship provide funds for young entrepreneurs taking into account pre-defined criteria e.g. age, business idea etc. Additional funds may be also provided for supporting entrepreneurs in their first steps in terms of open lectures and workshops. These approaches however are expensive and in many cases have limited only effectiveness in terms of successful new businesses and economic growth. At the same time, current conditions and especially the economic crisis press governments worldwide to develop more efficient policies with significantly lower budgets [1]. A straightforward way to achieve this is to develop more targeted policies, i.e. policies that reach and affect the target population in a cost-effective and efficient manner. To this end, policy modelling can assist in evaluating different approaches and forecasting the effect of policies.

Yet, an unexplored idea is to exploit the full potential of social networks and particularly online ones (e.g. those created in social networking sites). The fact that social networks have tremendous impact in a number of everyday areas (e.g. obesity, financial situation, smoking etc.) is now well established in the literature. The heavily influential book "Connected" in its final pages suggests that in order to reduce social inequalities we should also consider the personal connections of those we wish to assist [START_REF] Christakis | Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives[END_REF]. As an example it is stated that we could reduce crime by improving the connections of potential criminals. But is this actually true? And if so, how social network analysis can be exploited in actual policy making?

During the last few years, an increasing number of research projects are investigating the potential of online social networks in policy making. For example, Padgets (e.g. [START_REF] Charalabidis | Participative Public Policy Making Through Multiple Social Media Platforms Utilization[END_REF]) developed a central system that publishes various types of policy-related content (e.g., short text long text, images, video) and micro-applications in multiple social media and collects back data on citizens' interactions (e.g., views, comments, ratings, votes, etc.). The platform also offers analytics, opinion mining and forecasting future trends through simulation modelling to support policy making. WeGov project (e.g. [START_REF] Wandhofer | WeGov analysis tools to connect policy makers with citizens online[END_REF]) developed an online toolbox for policy makers to engage with citizens on social networking sites (SNS). It provides three broad categories of functions, enabling the policy maker to (i) search for discussions, topics and opinions from different SNS; (iii) analyse and summarize these discussions to determine the themes and important posts; and (iii) inject information into the SNS. The topics and opinions analysis identify groups of words that represent the topics within a discussion. The prediction of user activity shows posts that are going to generate more attention and the modelling of user behaviour analysis classifies users according to their behaviour and interactions within the SNS. The on-going NOMAD project (e.g. [START_REF] Karkaletsis | Social networks as a resource for policy formulation[END_REF]) aims to develop a technical platform that enables government agencies to search for content on a public policy under formulation in various social media and other sources (e.g. blogs and micro-blogs, news sharing sites, online forums, etc.). The gathered content is processed to extract arguments, opinions, issues and proposals on the particular policy, identify their sentiments (positive or negative) and finally summarise and visualise them.

In summary, current projects (such as Padgets and NOMAD) mainly aim to facilitate open and transparent discussions between policy makers and citizens through online social networks. WeGov goes further to classify users' behaviour. None however aims to transform online social networks.

The main objective of this paper is two-fold: First, to introduce an approach that enables exploiting online social networks in order to improve targeted policy making. Second, to present a high-level technological view of this approach, including how it fits a traditional policy making lifecycle, relevant high-level requirements and architecture, and a usage scenario.

The rest of this paper is structured as followed. In Section 2, the methodology is presented. In Section 3, the main principles of the proposed approach for targeted policy making are outlined while in Section 4 the relevant steps in a policy making lifecycle are provided. In Section 5, high-level requirements and a high-level architecture of a platform to support targeted policy making are presented. In Section 6, a usage scenario is presented on the envisaged use of the approach. Finally, in Section 7, conclusions are drawn and future work is presented.

Methodology

The overall methodology that is followed in this paper is influenced from the principles of software engineering and systems analysis and design. For example, an approach to systems analysis and design suggests one should start with a briefly described idea and then perform a feasibility study including technical, financial and organizational feasibility [START_REF] Tegarden | Systems Analysis and Design with UML[END_REF]. The technical feasibility aims to answer the question "can we build it?", the economic feasibility aims to answer the question "should we build it?" and the organizational feasibility aims to answer the question "if we build it, will they come?" In addition, architectural models, e.g. [START_REF] Kruchten | Architectural Blueprints-The "4+1" View Model of Software Architecture[END_REF], have been proposed to describe the architecture of software systems based on the use of different viewpoints, such as logical, development, process, physical, and scenarios. Finally, usage scenarios have been proposed as a starting point for software development [START_REF] Rosenberg | Use Case Driven Object Modeling with UML[END_REF].

In this paper, we concentrate on presenting the driving idea as well as a high-level technological view to support it. In this respect, we follow a four-step approach.

First, we present the overall vision and approach towards targeted policy making (section 3). This clarifies the main idea proposed in this paper at a conceptual level.

Second, we outline how our idea fits a traditional policy making lifecycle (section 4). This enables putting our ideas in context of policy making but also deriving the high-level requirements of the necessary technical infrastructure to support targeted policy making. It should be noted that the ideas presented in this paper rely heavily on new technological developments and innovations. Hence, we chose to focus on technical aspects to also facilitate conducting a first technical feasibility study.

Third, we present high-level requirements and architecture (section 5) for the necessary technical infrastructure to support targeted policy making. Once again, these aim at evaluating the technological feasibility of our approach rather than providing detailed development guidelines.

Finally, we present a hypothetical usage scenario (section 6). This enables better clarifying the vision of targeted policy making and the role of the technical infrastructure in supporting it.

It should be noted that other equally interesting questions arise from introducing the idea of exploiting online social networks for targeted policy making. Some of these include an evaluation of the relevant benefits and pitfalls (e.g. using a SWOT analysis), the legal and ethical issues that may arise from introducing such policy interventions, the economic feasibility as well as issues related to acceptance by stakeholders etc. All these issues however are outside the scope of this paper. Nevertheless, we will come back to some of these in the last section.

Towards Targeted Policy Making

The main idea behind this paper is that policy interventions should not only be based on the characteristics of a person or a group (such as age, income, skin colour etc.) but also on the position of a person in a relevant social network.

We introduce the term policy social networks to refer to social networks where nodes and links are important to a particular policy. We claim that policies should not only try to understand and exploit but also transform policy social networks and we aim to investigate that by doing so, policies will achieve their goals in a more efficient and effective manner. If our hypothesis is true then e.g. an entrepreneurship policy that changes the structure of the relevant policy social network will be more efficient than a traditional policy. In other words, policies enabling to improve the connections of potential entrepreneurs will be more successful.

Thus, the main assumption behind this paper is that "targeted policies that involve understanding, exploiting and transforming policy social networks are potentially more efficient and effective than those that do not do so".

We believe it is important to scientifically investigate whether the hypothesis is actually true. Indeed, the potential of social network analysis in policy making has not been systematically examined [START_REF] Wellman | Social Network Analysis: An Introduction[END_REF] despite the efforts in various relevant but currently disparate scientific areas, e.g. agent-based simulation [START_REF] Macal | Agent-based modelling and simulation[END_REF].

If this assumption is proven right, then policy making could become more targeted (even personalised) and thus potentially more efficient and cost-effective. Policy interventions could have maximum impact with less cost as they will no longer be horizontal but rather very much targeted by exploiting and even transforming relevant policy social networks to have desirable characteristics, such as improved connections.

As an example we consider promoting entrepreneurship, a policy particularly important due to the debt crisis [START_REF] Roudini | Global Economic Crisis and Entrepreneurship Development[END_REF] [START_REF]Entrepreneurship at a Glance[END_REF]. Here, the policy social network may contain nodes such as potential entrepreneurs, successful and unsuccessful entrepreneurs, venture capitalists, angel investors etc. and links may represent connections such as ones in Facebook and LinkedIn but also in real life. We claim relevant policies should aim to improve the connections of potential entrepreneurs and provide incentives for beneficiaries to do the same. Here, policy analysis might show that in young entrepreneurship, it is essential for new entrepreneurs to exchange ideas with successful businessmen and venture capitalists. The analysis might also show that currently, the social network of potential entrepreneurs in one region is isolated from such other groups. We therefore need to first of all represent this policy social network (see fig. 1A). There is therefore a need to develop and possibly simulate various alternatives aiming to change the structure of the network to facilitate improved communications. A technological platform is needed to exploit social media (such as twitter, LinkedIn and Facebook) trying to propose connections between entrepreneurs in the region with successful businessmen and venture capitalists. As an example, the platform might include software agents in Twitter that will (a) understand that entrepreneurs do not follow successful businessmen and venture capitalists, and (b) try to establish such connections e.g. by sending introductory invitation tweets. This will change their social network which will now have the desirable characteristics and measures values e.g. in terms of new connections that will enable ideas on entrepreneurship to flow to new entrepreneurs (see fig. 1B). In fig. 1B the new lines represent new connections (e.g. realised through follow in Twitter) that were introduced by the platform to implement the targeted policy interventions. These connections were deemed essential for new entrepreneurs to acquire the needed position in the network in order to succeed.

Targeted Policy Making Lifecycle

In this section we present the enhancements needed in a traditional policy making lifecycle to incorporate and exploit Policy Social Networks (PSN) for more targeted policy making. These enhancements provide an upper level description of the requirements of a relevant supporting technical infrastructure to assist in targeted policy making.

Fig. 2. Traditional policy making lifecycle

The policy-making lifecycle is usually defined as a 5-levels process [START_REF] Macintosh | Characterizing E-Participation in Policy-Making[END_REF] including: 1. The agenda-setting stage, referring to establishing the need for a policy change and defining what the problem to be addressed is. 2. The analysis stage, referring to exploring the challenges and opportunities regarding an agenda item, gathering evidence and knowledge on it as well as citizen opinions, understanding the context and developing alternative options. 3. The creation stage, referring to drafting of a policy document but also including formal consultations, pilots' studies, etc., if relevant. 4. The implementation stage, referring to the development and implementation of the relevant legislation and/or regulations. 5. The monitoring stage, referring to closely following policy in action and evaluating its impact.

Actually, the traditional lifecycle is a circle (from monitoring back to agenda setting) but we present it here as a sequence for simplicity. In traditional policy lifecycles, policy modelling is restricted mainly to evaluating alternatives and forecasting policies (or the lack of any policy) impact on the population. Different approaches have been followed for this purpose including, for example, agent-based simulation and mathematical epidemiology modelling.

In this paper, we suggest integrating and exploiting the concept of Policy Social Networks (PSN) in the policy lifecycle. For this purpose, contributions to each of the policy-making stages are required as follows:

• To the analysis stage, a new way to define and explore different policy options by exploiting trends and knowledge gathered from the policy's social network and by simulating different policy alternatives is required. • To the policy creation and implementation stage, an environment for defining and implementing a policy alternative by performing certain interventions on the PSN and actively transforming its structure and other characteristics is required. • To the monitoring stage, an environment for closely monitoring policy implementation and its impact on the social interconnections of the targeted subpopulation is required.

Understand & depict initial PSN

Define & simulate alternative policies

Implement policies

Monitor policies

Fine--tune selected PSN parameters The proposed enhanced targeted policy making lifecycle consists of 5 steps (fig.

3):

Step 1: Understanding and depicting the policy social network (PSN). This step initially involves the understanding of the policy area and the definition of all important (influential) parameters and network characteristics relevant to the selected policy area. Furthermore, this step involves the definition of the selected policy's social network (PSN) for a targeted population and its depiction both topologically and numerically by measuring its most important characteristics. Essentially, in this step, the policy maker obtains an overall understanding of the social networks' potential in the selected policy area and gets acquainted with the relevant policy social network (PSN) and its characteristics.

Step 2: Definition and simulation of alternative policies. This step initially refers to the definition of different alternative policies by modifying the relevant PSN metrics and connections, thus designing target social networks that will have desirable policy characteristics and network measures' values to achieve the desired policy goal. Then, one or more alternative policies are being simulated providing to the user a depiction of the final PSN after policy alternatives' implementation. Essentially, in this step, the policy maker explores alternative policy options and experiments with their impact by simulating the transformation of PSN for each option. Thus, the policy maker can take an informed decision on which policy alternative(s) to actually implement.

Step 3: Fine-tuning of the selected PSN. This step refers to selecting one of the alternative policies and refining its technicalities (e.g. finalise PSN metric changes needed to achieve target PSN) making it thus ready for implementation. Essentially, in this step, the policy maker selects one of the alternative policies explored in the previous steps and decides on suitable PSN interventions to be performed.

Step 4: Implementation of policies. This step refers to actual implementation of the selected policy alternative by modifying the relevant PSN connections, according to the decisions made in the previous step. Essentially, in this step, the policy maker applies the decided social network interventions to the current PSN in order to change it towards the target PSN. For example, the policy maker may propose specific, new connections to users so that PSN's density and central nodes are increased.

Step 5: Monitoring of policies. This step refers to evaluating the impact of implemented policies through real-time monitoring of PSN's topology and metrics and comparing progress of implemented policy vis-a-vis expected outcomes from prior simulation. Here, the policy maker can monitor PSN's transformation and conclude whether the expected impact of the implemented policy has been achieved. If not, the policy maker may decide to perform additional interventions to the PSN. Alternatively, the policy maker may decide to implement other policy alternatives, in which case the process makes a loop returning to step 2 and continuing from there on.

Towards a Platform to Support Targeted Policy Making

This section presents two artefacts towards a platform to support targeted policy making: high-level requirements and architecture.

Based on the analysis of the previous section, fig. 4 presents the main functionality expected from a supporting technical platform (i.e. platform). For this purpose, UML use case diagrams notation is employed. In UML use case diagrams, the stickman (called actor) represents a user of a system that can be either a human or another system, while the oval (called use case) represents an essential functionality of a system. A connection between the two suggests a user triggers or is involved in a specific functionality.

A relevant high-level architecture is depicted in fig. 5. This architecture can be used to illustrate the technical feasibility of the requirements presented above but also as a guideline for subsequent detailed architectures and ultimate prototype implementations. Some information on the architecture's main components follows.

The Social Network Connectors enable the connection of the platform with existing online social networks (e.g. Facebook, twitter and LinkedIn) thus feeding the platform with up-to-date information regarding the PSN under investigation e.g. connections and contacts of the nodes of interest, etc. The Social Network Interaction layer provides the mechanisms and tools for the secure retrieval of data related to the PSN (the policy maker can define the target population and the type of network data that will be retrieved for the scenario under investigation) from the existing online social network and for the alignment, transformation, anonymisation and semantic interconnection of this heterogeneous network data to a common reference format. Finally, this layer provides the mechanisms and tools required for transforming social networks through effective socialcomputational network interventions.

The Policy Application and Simulation layer implements the social network analysis and monitoring mechanism for representing the social network structure and calculating the values of its metrics. This will enable policy makers to understand the current state of the network and identify important metrics that could be improved through network interventions. The platform should also offer a recommendation mechanism to propose the most effective improvements (network interventions) related to the policy. The recommendations are based on identified social network patterns that define the "ideal" structure/characteristics of a social network. Moreover, the system analyses the PSN data and detects the current trends in the network, thus assist the policy maker to select the best policy. The layer should also provide mechanisms for: (i) initiating simulations to derive expected results of different potential policies and (ii) applying various social-computational network interventions to transform the network. Last, the layer should support a mechanism for identifying social network patterns in social relationships and how these may be related to metrics or behaviours. The Adaptable Dashboard Front-ends layer supports the user-centric focus of the platform and enables the easy, personalised access of users to the visualisation, simulation and intervention functionalities.

High-level requirements and architecture are first only steps towards platform development. However, they are sufficient for an initial technical feasibility study. They also provide the basis for further refinement towards platform implementation according to the principles of iterative and incremental software engineering.

Usage Scenario

In this section, we present a usage scenario to better illustrate the foreseen use of the ideas presented above. It should be noted that this scenario is based on the principles and high-level architecture presented above. Thus, no actual platform has been implemented yet. The scenario aims to facilitate a better understanding of the proposed approach and relevant requirements e.g. within a phase of system analysis. Maria, a policy maker, wants to apply a policy in order to improve the entrepreneurship among young people. Due to economic constraints she cannot apply horizontal strategies, but she has to apply more targeted and efficient policy interventions.

Initially, Maria launches the platform dashboard (fig. 6) to define the targeted Policy Social Network (PSN) (i.e. the targeted population of the policy). The platform offers tools and mechanisms that help Maria define the basic characteristics of the PSN. When the PSN is defined, Maria can see a visual representation of the social network showing the relations between the individual social entities of the network through the "Current Policy Social Network" tool of the dashboard. In this case, relations can be follow relationships in Twitter. The visualisation allows Maria to observe that a group of potential entrepreneurs in the PSN is probably isolated from other relevant groups, thus information and ideas do not "flow" to this part of the network. Additionally, the platform computes and displays a set of relevant metrics, through the "Current Policy Social Network" tool of the dashboard. This allows Maria to monitor the status of the online social network. These metrics are divided into network-level metrics (e.g. network density, centralization, hierarchy and symmetry, connectivity and complexity) and node-level metrics (e.g. centrality indices and ego-network indices). The former allow Maria to identify e.g. persons in positions of prominence while the latter allow the exploration of the social environment of a given individual.

In order to apply the policy, Maria has to select the most efficient network interventions. Due to the complexity of the social network the number of potential network interventions is large, thus making difficult the selection of the most appropriate and efficient. The platform offers an "Intervention recommendation" mechanism at the dashboard that recommends network interventions based on identified PSN patterns and on the metrics values of the current network. Specifically, the platform recommends the establishment of new connections (by sending introductory invitation tweets in Twitter) between budding entrepreneur of the isolated network and experienced entrepreneurs. Moreover, the platform analyses the PSN data and detects the current trends in the social network, thus assist the policy maker to select the best policy.

Before applying the policy to the social network, Maria wants to see the effects of the intervention to the social network. The platform enables Maria to simulate the policy in the PSN using the "Policy simulation" tool at the dashboard and measure the effects of the policy. This allows her to experiment with different policies and measure the results in a simulation environment (e.g. how did the PSN change after the transformation? What are the metrics values of the resulted PSN? etc.) before applying the policy to the real world social network.

The simulation results assist Maria to identify the most efficient policy strategy i.e. the one that has the best simulation results. Then, Maria applies the policy through the platform by transforming the social network, e.g. by sending introductory tweets to targeted persons. Finally, the platform enables Maria to monitor the results of the policy using the "Policy monitoring and evaluation" tool of the dashboard (e.g. to monitor if the suggested interventions have been adopted and the network metrics have been improved) and compare them with the expected results coming from the simulation process e.g. has the network structure improved the same at the real world and at the simulation? what type of differences exists? why these differences occur?

Conclusion and Future Work

In this paper we suggest that online social networks should be exploited for more targeted policy making. This can potentially increase the efficiency and effectiveness of policy making. For this purpose, we introduce the term policy social networks to refer to social networks where nodes and links are important to a particular policy. Therefore, the main assumption behind this paper is that "targeted policies that involve understanding, exploiting and transforming policy social networks are potentially more efficient and effective than those that do not do so". We also present the amendments needed in a traditional policy making lifecycle in order to incorporate these ideas. This analysis reveals that a sophisticated technical infrastructure is essential to support the use of policy social networks within the policy making processes. It also reveals the high-level requirements of such technical infrastructure. We subsequent outline a high-level architecture for such infrastructure that can be used to investigate its technical feasibility and also as a guide for subsequent implementation. This is followed by a usage scenario to illustrate the policy making process and the use of the relevant technical infrastructure.

Although we believe the ideas presented in this paper seem promising we do not claim they have been investigated thoroughly in all their aspects. Indeed, further work is needed in various directions.

First, there is a need to more thoroughly investigate the idea of exploiting online social networks for targeted policy making. Indeed, analysing and using data from online social networks might be undesirable from a legal and/or ethical perspective. This can be due, for example, provisions related to data protection, such as those imposed by Directive 95/46/EC in the European Union. Furthermore, the idea that policy making will be based on data resting within private companies and governed by their access policies might not be appealing. Finally, one might claim that new meth-ods of fraud might emerge if, for example, one develops an artificial social network just to enable him to become beneficiary of a particular public service or benefit. Thus, additional research is needed in these directions. In any case, our position is that these ideas should be used with cause and to supplement rather than replace traditional policy intervention methods.

Second, research is needed in the technical aspects of these ideas. Here, development and evaluation of a prototype is an essential ingredient of future work needed in the area.

Fig. 1 .

 1 Fig. 1. A. Before policy intervention B. After policy intervention

Fig. 3 .

 3 Fig. 3. Targeted policy making lifecycle

Fig. 4 .

 4 Fig. 4. High-level requirements (using UML use case diagram)

Fig. 5 .

 5 Fig. 5. High-level architecture

Fig. 6 .

 6 Fig. 6. Mockup of platform dashboard

Acknowledgements. I would like to thank the colleagues at Information Systems laboratory and particularly Eleni Panopoulou and Dimitrios Zeginis for fruitful discussions and feedback on this paper's ideas. I would also like to thank the anonymous referees for their useful comments and insights. Although some comments could not be integrated in this work, mainly due to space limitation, they will certainly influence my future research in the area.


Dalia Marcela

Rojas Castro

Arnaud Revel

Michel Ménard

Artificial Neural Network-Based Control Architecture: a Simultaneous Top-down and Bottom-up Approach to Autonomous Robot Navigation

Keywords: Neural control architecture, robot navigation, hybrid (topdown and bottom-up) approach, neural path planning

come

 [dalia_marcela.rojas_castro,arnaud.revel,michel.menard]@univ-lr.fr Abstract. This paper presents an artificial neural network-based control architecture allowing autonomous mobile robot indoor navigation by emulating the cognition process of a human brain when navigating in an unknown environment. The proposed architecture is based on a simultaneous top-down and bottom up approach, which combines the a priori knowledge of the environment gathered from a previously examined floor plan with the visual information acquired in real time. Thus, in order to take the right decision during navigation, the robot is able to process both set of information, compare them in real time and react accordingly. The architecture is composed of two modules: a) A deliberative module, corresponding to the processing chain in charge of extracting a sequence of navigation signs expected to be found in the environment, generating an optimal path plan to reach the goal,computing and memorizing the sequence of signs [1]. The path planning stage allowing the computation of the sign sequence is based on a neural implementation of the resistive grid. b) A reactive module, integrating the said sequence information in order to use it to control online navigation and learning sensory-motor associations. It follows a perception-action mechanism that constantly evolves because of the dynamic interaction between the robot and its environment. It is composed of three layers: one layer using a cognitive mechanism and the other two using a reflex mechanism. Experimental results obtained from the physical implementation of the architecture in an indoor environment show the feasibility of this approach. Research work supported by European regional development Funds (Contract35053) and the Poitou Charente Region.

  1. Rojas Castro, D. M., A. Revel, and M. Menard. "Document image analysis by a mobile robot for autonomous indoor navigation." Document Analysis and Recognition (ICDAR), 2015 13th International Conference on. IEEE, 2015.