Linear Phase FIR Low Pass Filter Design Based on Firefly Algorithm

In this paper, a linear phase Low Pass FIR filter is designed and proposed based on Firefly algorithm. We exploit the exploitation and exploration mechanism with a local search routine to improve the convergence and get higher speed computation. The optimum FIR filters are designed based on the Firefly method for which the finite word length is used to represent coefficients. Furthermore, Particle Swarm Optimization (PSO) and Differential Evolution algorithm (DE) will be used to show the solution. The results will be compared with PSO and DE methods. Firefly algorithm and Parks–McClellan (PM) algorithm are also compared in this paper thoroughly. The design goal is successfully achieved in all design examples using the Firefly algorithm. They are compared with that obtained by using the PSO and the DE algorithm. For the problem at hand, the simulation results show that the Firefly algorithm outperforms the PSO and DE methods in some of the presented design examples. It also performs well in a portion of the exhibited design examples particularly in speed and quality.

Analysis of UAS-S4 Éhecatl aerodynamic performance improvement using several configurations of a morphing wing technology

ABSTRACTThe paper presents the results of the aerodynamic optimisation of an Unmanned Aerial System's wing using a morphing approach. The shape deformation of the wing is achieved by placing actuator lines at several positions along its span. For each flight condition, the optimal displacements are found by using a combination of the new Artificial Bee Colony algorithm and a classical gradient-based search routine. The wing aerodynamic characteristics are calculated with an efficient nonlinear lifting line method coupled with a two-dimensional viscous flow solver. The optimisations are performed at angles of attack below the maximum lift angle, with the aim of improving the Hydra Technologies UAS-S4 wing lift-to-drag ratio. Several configurations of the morphing wing are proposed, each with a different number of actuation lines, and the improvements obtained by these configurations are analysed and compared.

Localization of Windows and Doors in 3d Point Clouds of Facades

In this paper, we present a fully automatic approach to localize the outlines of facade objects (windows and doors) in 3D point clouds of facades. We introduce an approach to search for the main facade wall and locate the facade objects within a probabilistic framework. Our search routine is based on Monte Carlo Simulation (MC-Simulation). Templates containing control points of curves are used to approximate the possible shapes of windows and doors. These are interpolated using parametric B-spline curves. These templates are scored in a sliding window style over the entire facade using a likelihood function in a probabilistic matching procedure. This produces many competing results for which a two layered model selection based on Bayes factor is applied. A major thrust in our work is the introduction of a 2D shape-space of similar shapes under affine transform in this architectural scene. This transforms the initial parametric B-splines curves representing the outlines of objects to curves of affine similarity in a strongly reduced dimensionality thus facilitating the generation of competing hypotheses within the search space. A further computational speedup is achieved through the clustering of the search space to disjoint regions, thus enabling a parallel implementation. We obtain state-of-the results on self-acquired data sets. The robustness of our algorithm is evaluated on 3D point clouds from image matching and LiDAR data of diverse quality.

Designing an IP Link Topology for a Metro Area Backbone Network

Massive increases in IP (Internet Protocol) traffic have led to rapid deployment of IP-based networks in metropolitan (metro) areas. In order to facilitate this deployment, computer-based design tools are needed. One of the most difficult decisions that engineers face in designing an IP network is choosing the IP link topology (i.e., the set of router-to-router connections). This is especially complicated when it is also necessary to route these IP links over an underlying physical network of optical fibers. In this paper, the authors describe a new heuristic for simultaneously designing a backbone IP link topology for a metro area network, and routing these IP links over a given physical network. The IP network must be designed for survivability in the event of a network failure (i.e., the loss of a physical link, router or IP link). Initially, they employ a Construction Heuristic that explicitly considers the number of router-to-router connections that would be carried over each physical link. In this way it seeks to minimize the impact of any single physical link failure. An optional Local Search routine then attempts to improve on the solution by a sequence of topology changes. IP link routings are adjusted at each topology change. This heuristic is readily able to be incorporated into an interactive design tool. Some computational experience is described.

A theoretical study on formation shear radial profiling in well-bonded cased boreholes using sonic dispersion data based on a parameterized perturbation model

Interpretation of sonic data can be challenging in the presence of a steel casing that has a strong influence on elastic waves propagating along a borehole. The cement annulus behind the casing together with drilling-induced near-wellbore alteration causes radial heterogeneity in the propagating medium. It is necessary to study the influence of such heterogeneities on borehole waves and estimate the radial extent of near-wellbore alteration in terms of radial variation of velocities away from the casing. To this end, we based our study on the model of a fluid-filled well-bonded cased borehole surrounded by a cylindrically layered formation. The formation is isotropic and purely elastic, and can be either fast or slow. Borehole monopole and dipole dispersions for this kind of model can be obtained from a root finding mode-search routine. A modified perturbation model based on Hamilton’s principle is used to predict changes in borehole dispersions caused by formation heterogeneities. A two-layer formation model as the reference state is introduced, which always provides normal dispersive reference dispersion for calculations of perturbation integrals for fast and slow formations. Radial variations of the formation shear velocity can be expressed in terms of a parametric exponential profile. Consequently, estimation of these parameters in the assumed profile yields the radial variation of the formation shear slowness away from the casing. Numerical results using synthetic examples are presented to demonstrate the validity of this radial profiling methodology.

Spectral-method algorithm for modeling dispersion of acoustic modes in elastic cylindrical structures

A new spectral-method algorithm can be used to study wave propagation in cylindrically layered fluid and elastic structures. The cylindrical structure is discretized with Chebyshev points in the radial direction, whereas differentiation matrices are used to approximate the differential operators. We express the problem of determining modal dispersions as a generalized eigenvalue problem that can be solved readily for all eigenvalues corresponding to various axial wavenumbers. Modal dispersions of guided modes can then be expressed in terms of axial wavenumbers as a function of frequency. The associated eigenvectors are related to the displacement potentials that can be used to calcu-late radial distributions of modal amplitudes as well as stress components at a given frequency. The workflow includes input parameters and the construction of differentiation matrices and boundary conditions that yield the generalized eigenvalue problem. Results from this algorithm for a fluid-filled borehole surrounded by an elastic formation agree very well with those from a root-finding search routine. Computational efficiency of the algorithm has been demonstrated on a four-layer completion model used in a hydrocarbon-producing well. Even though the algorithm is numerically unstable at very low frequencies, it produces reliable and accurate results for multilayered cylindrical structures at moderate frequencies that are of interest in estimating formation properties using modal dispersions.

The role of symmetries in adiabatic quantum algorithms

Exploiting the similarity between adiabatic quantum algorithms and quantum phase transitions, we argue that second-order transitions -- typically associated with broken or restored symmetries -- should be advantageous in comparison to first-order transitions. Guided by simple examples we construct an alternative adiabatic algorithm for the NP-complete problem {\em Exact Cover 3}. We show numerically that its average performance (for the considered cases up to $\ord\{20\}$ qubits) is better than that of the conventional scheme. The run-time of adiabatic algorithms is not just determined by the minimum value of the fundamental energy gap (between the ground state and the exited states), but also by its curvature at the critical point. The proposed symmetry-restoring adiabatic quantum algorithm only contains contributions linear and quadratic in the Pauli matrices and can be generalized to other problem Hamiltonians which are decomposed of terms involving one and two qubits. We show how the factoring problem can be cast into such a quadratic form. These findings suggest that adiabatic quantum algorithms can solve a large class of NP problems much faster than the Grover search routine (which corresponds to a first-order transition and yields a quadratic enhancement only).

Gate location optimization scheme for plastic injection molding

Gate location of injection molding is vital to achieve high quality plastic part. The determination of gate location is an important issue in mold design. A computationally efficient scheme based on flow path is proposed to locate the optimum gate for achieving balanced flow. The range of filling time is employed as objective function. Comparisons were made between the flow path search scheme and the existing adjacent node evaluation scheme, and between the objective function of the range of filling time and the existing standard deviation of filling time. The two examples investigated indicated that the search routine based on the concept of flow path is more efficient computationally and the range of filling time is a better objective function to reflect the uniformity of fill.