Refinement Algorithm Research Articles

ACCURATE OPTICAL TARGET POSE DETERMINATION FOR APPLICATIONS IN AERIAL PHOTOGRAMMETRY

We propose a new design for an optical coded target based on concentric circles and a position and orientation determination algorithm optimized for high distances compared to the target size. If two ellipses are fitted on the edge pixels corresponding to the outer and inner circles, quasi-analytical methods are known to obtain the coordinates of the projection of the circles center. We show the limits of these methods for quasi-frontal target orientations and in presence of noise and we propose an iterative refinement algorithm based on a geometric invariant. Next, we introduce a closed form, computationally inexpensive, solution to obtain the target position and orientation given the projected circle center and the parameters of the outer circle projection. The viability of the approach is demonstrated based on aerial pictures taken by an UAV from elevations between 10 to 100 m. We obtain a distance RMS below 0.25 % under 50 m and below 1 % under 100 m with a target size of 90 cm, part of which is a deterministic bias introduced by image exposure.

Multi-Story Indoor Floor Plan Reconstruction via Mobile Crowdsensing

The lack of floor plans is a critical reason behind the current sporadic availability of indoor localization service. Service providers have to go through effort-intensive and time-consuming business negotiations with building operators, or hire dedicated personnel to gather such data. In this paper, we propose Jigsaw, a floor plan reconstruction system that leverages crowdsensed data from mobile users. It extracts the position, size, and orientation information of individual landmark objects from images taken by users. It also obtains the spatial relation between adjacent landmark objects from inertial sensor data, then computes the coordinates and orientations of these objects on an initial floor plan. By combining user mobility traces and locations where images are taken, it produces complete floor plans with hallway connectivity, room sizes, and shapes. It also identifies different types of connection areas (e.g., escalators and stairs) between stories, and employs a refinement algorithm to correct detection errors. Our experiments on three stories of two large shopping malls show that the 90-percentile errors of positions and orientations of landmark objects are about $1\sim 2m$ and $5\sim 9^\circ$ , while the hallway connectivity and connection areas between stories are 100 percent correct.

An adaptive multi-spline refinement algorithm in simulation based sailboat trajectory optimization using onboard multi-core computer systems

Abstract A new dynamic programming based parallel algorithm adapted to on-board heterogeneous computers for simulation based trajectory optimization is studied in the context of “high-performance sailing”. The algorithm uses a new discrete space of continuously differentiable functions called the multi-splines as its search space representation. A basic version of the algorithm is presented in detail (pseudo-code, time and space complexity, search space auto-adaptation properties). Possible extensions of the basic algorithm are also described. The presented experimental results show that contemporary heterogeneous on-board computers can be effectively used for solving simulation based trajectory optimization problems. These computers can be considered micro high performance computing (HPC) platforms-they offer high performance while remaining energy and cost efficient. The simulation based approach can potentially give highly accurate results since the mathematical model that the simulator is built upon may be as complex as required. The approach described is applicable to many trajectory optimization problems due to its black-box represented performance measure and use of OpenCL.

Continuous adjoint-based error estimation and its application to adaptive discontinuous Galerkin method

Abstract An adaptive mesh refinement algorithm based on a continuous adjoint approach is developed. Both the primal equation and the adjoint equation are approximated with the discontinuous Galerkin (DG) method. The proposed adaptive algorithm is used in compressible Euler equations. Numerical tests are made to show the superiority of the proposed adaptive algorithm.

FIR Filter Design by Convex Optimization Using Directed Iterative Rank Refinement Algorithm

The advances in convex optimization techniques have offered new formulations of design with improved control over the performance of FIR filters. By using lifting techniques, the design of a length- $L$ FIR filter can be formulated as a convex semidefinite program (SDP) in terms of an $L\times L$ matrix that must be rank-1. Although this formulation provides means for introducing highly flexible design constraints on the magnitude and phase responses of the filter, convex solvers implementing interior point methods almost never provide a rank-1 solution matrix. To obtain a rank-1 solution, we propose a novel Directed Iterative Rank Refinement (DIRR) algorithm, where at each iteration a matrix is obtained by solving a convex optimization problem. The semidefinite cost function of that convex optimization problem favors a solution matrix whose dominant singular vector is on a direction determined in the previous iterations. Analytically it is shown that the DIRR iterations provide monotonic improvement, and the global optimum is a fixed point of the iterations. Over a set of design examples it is illustrated that the DIRR requires only a few iterations to converge to an approximately rank-1 solution matrix. The effectiveness of the proposed method and its flexibility are also demonstrated for the cases where in addition to the magnitude constraints, the constraints on the phase and group delay of filter are placed on the designed filter.

Algorithms of Two-Dimensional X-Ray Diffraction

ABSTRACTX-ray diffraction pattern collected with two-dimensional detector contains the scattering intensity distribution as a function of two orthogonal angles. One is the Bragg angle 2θ and the other is the azimuthal angle about the incident x-ray beam, denoted by γ. A 2D diffraction pattern can be integrated to a conventional diffraction pattern and evaluated by most exiting software and algorithms for conventional applications, such as, phase identification, structure refinement and 2θ-profile analysis. However, the materials structure information associated to the intensity distribution along γ direction is lost through the integration. The diffraction vector approach has been approved to be the genuine theory in 2D data analysis. The unit diffraction vector used for 2D analysis is a function of both 2θ and γ. The unit diffraction vector for all the pixels in the 2D pattern can be expressed either in the laboratory coordinates or in the sample coordinates. The vector components can then be used to derive fundamental equations for many applications, including stress, texture, crystal orientation and crystal size evaluation.

Adaptive finite element modeling of direct current resistivity in 2-D generally anisotropic structures

In this paper, we present an adaptive finite element (FE) algorithm for direct current (DC) resistivity modeling in 2-D generally anisotropic conductivity structures. Our algorithm is implemented on an unstructured triangular mesh that readily accommodates complex structures such as topography and dipping layers and so on. We implement a self-adaptive, goal-oriented grid refinement algorithm in which the finite element analysis is performed on a sequence of refined grids. The grid refinement process is guided by an a posteriori error estimator. The problem is formulated in terms of total potentials where mixed boundary conditions are incorporated. This type of boundary condition is superior to the Dirichlet type of conditions and improves numerical accuracy considerably according to model calculations. We have verified the adaptive finite element algorithm using a two-layered earth with azimuthal anisotropy. The FE algorithm with incorporation of mixed boundary conditions achieves high accuracy. The relative error between the numerical and analytical solutions is less than 1% except in the vicinity of the current source location, where the relative error is up to 2.4%. A 2-D anisotropic model is used to demonstrate the effects of anisotropy upon the apparent resistivity in DC soundings.

A parallel adaptive viscoelastic flow solver with template based dynamic mesh refinement

A parallel adaptive mesh refinement algorithm has been incorporated into the side-centered finite volume method [Sahin, A stable unstructured finite volume method for parallel large-scale viscoelastic fluid flow calculations. J. Non-Newtonian Fluid Mech., 166 (2011) 779–791] in order to obtain highly accurate numerical results for viscoelastic fluid flow problems. The present recursive mesh refinement algorithm is based on a conformal refinement of unstructured quadrilateral/hexahedral elements with templates based on 1:3 refinement of edges. In order to transfer cell-centered data between source and target meshes, a second-order conservative interpolation (remapping) technique similar to the work of Menon and Schmidt [Supermesh construction for conservative interpolation on unstructured meshes: An extension to cell–centered finite-volume variables. Comput. Methods Appl. Mech. Eng., 200 (2011), 2797–2804] are employed and the approach has been extended for side-centered data. The proposed framework has been applied to the classical benchmark problem of an Oldroyd-B fluid past a confined circular cylinder in a rectangular channel and a sphere falling in a circular tube. The calculations confirm that high accuracy can be achieved with the present adaptive mesh refinement.

A High-Speed Vision-Based Sensor for Dynamic Vibration Analysis Using Fast Motion Extraction Algorithms.

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.

On the linear independence of truncated hierarchical generating systems

Motivated by the necessity to perform adaptive refinement in geometric design and numerical simulation, the construction of hierarchical splines from generating systems spanning nested spaces has been recently studied in several publications. Linear independence can be guaranteed with the help of the local linear independence of the spline basis at each level. The present paper extends this framework in several ways. Firstly, we consider spline functions that are defined on domain manifolds, while the existing constructions are limited to domains that are open subsets of Rd. Secondly, we generalize the approach to generating systems containing functions which are not necessarily non-negative. Thirdly, we present a more general approach to guarantee linear independence and present a refinement algorithm that maintains this property. The three extensions of the framework are then used in several relevant applications: doubly hierarchical B-splines, hierarchical Zwart-Powell elements, and three different types of hierarchical subdivision splines.

Dynamics of internal jets in the merging of two droplets of unequal sizes

The head-on collision, merging and internal mixing dynamics of two unequal-sized droplets were experimentally studied and interpreted, using water, $n$-decane and $n$-tetradecane to identify the distinguishing effects of surface tension and liquid viscosity on the merging and mixing patterns. It is shown that, upon merging of water and $n$-decane droplets, mushroom-like jets of dissimilar characteristics develop within the merged mass for small and large values of the impact Weber number (We), and that such jets are not developed for intermediate values of We. Furthermore, such jet-like mixing patterns were not observed for droplets of $n$-tetradecane, which has smaller surface tension and larger viscosity as compared to water. A regime nomogram relating the Ohnesorge and symmetric Weber numbers is constructed, providing a unified interpretation of the internal mixing patterns. Numerical simulations based on an improved volume-of-fluid method and an adaptive mesh refinement algorithm provide auxiliary diagnoses of the flow fields and the observed phenomena.

A novel flexible activity refinement approach for improving workflow process flexibility

Flexible activity refinement plays an important role in improving process flexibility and addressing uncertainties of business processes. However, it is still a challenge to refine flexible activities, and the existing researches on flexible activity refinement such as the refinement principles and methods, and their combination with factors such as constraints and contexts is still lacking. Aiming at this, a novel dynamic refinement approach for flexible activities is proposed, which combines both vertical decomposition and horizontal extension refinements, with the impact of constraints and contexts considered. In particular, we summarize five typical refinement categories, and present a set of activity refinement rules based on them. Furthermore, the decomposition refinement, including the activity decomposition principles, the related rules for trigger event delivering and execution condition transferring is discussed in detail. The extension refinement, which realizes the horizontal refinement, can be integrated with other kinds of refinement and uses constraints to specify activity selection, activity temporal relationships, etc. Then, a tree-like activity refinement graph (ARG) is proposed to represent the refinement process, based on which the refinement cost and refinement degree can be computed to benefit the finding of the potential optimal refinement path. As a further implementation of the proposed refinement approach, a general refinement algorithm is described. Finally, a case study of urolithiasis therapy process and its application are given, and the results indicate the effectiveness of our proposals.

The influence of incident shock Mach number on radial incident shock wave focusing

Experiments and numerical simulations were carried out to investigate radial incident shock focusing on a test section where the planar incident shock wave was divided into two identical ones. A conventional shock tube was used to generate the planar shock. Incident shock Mach number of 1.51, 1.84 and 2.18 were tested. CCD camera was used to obtain the schlieren photos of the flow field. Third-order, three step strong-stability-preserving (SSP) Runge-Kutta method, third-order weighed essential non-oscillation (WENO) scheme and adaptive mesh refinement (AMR) algorithm were adopted to simulate the complicated flow fields characterized by shock wave interaction. Good agreement between experimental and numerical results was observed. Complex shock wave configurations and interactions (such as shock reflection, shock-vortex interaction and shock focusing) were observed in both the experiments and numerical results. Some new features were observed and discussed. The differences of structure of flow field and the variation trends of pressure were compared and analyzed under the condition of different Mach numbers while shock wave focusing.

Automatic clustering algorithms for indoor site selection in LTE

Small cell systems are a cost-effective solution to provide adequate coverage inside buildings. Nonetheless, the addition of any indoor site requires evaluating the trade-off between the coverage and capacity gain provided by the new site and its monetary cost. In this paper, a new automatic indoor site selection algorithm based on clustering techniques is presented. The algorithm calculates the number of antennas, radio heads, and baseband units needed for the area under study. Then, a clustering algorithm groups several radio heads of different buildings in a single pooled baseband unit, reducing deployment costs. The proposed clustering algorithm is based on a local refinement algorithm, whose starting point considers a new baseband unit for every new site, and then, possible reallocation to existing units is checked. To assess the method, the proposed indoor site selection algorithm is included in a network planning tool. The algorithm is tested in a real heterogeneous network scenario, taking into account vendor specifications and operator constraints. Results show that the use of the proposed clustering algorithm can reduce the total network cost by up to 58 % in a real scenario.

Counter-Transitivity in Argument Ranking Semantics

The principle of counter-transitivity plays a vital role in argumentation. It states that an argument is strong when its attackers are weak, and is weak when its attackers are strong. In this work, we develop a formal theory about the argument ranking semantics based on this principle. Three approaches, quantity-based, quality-based and the unity of them, are defined to implement the principle. Then, we show an iterative refinement algorithm for capturing the ranking on arguments based on the recursive nature of the principle.

Randomized path planning for tasks requiring the release and regrasp of objects

This paper presents a randomized planning algorithm for manipulation tasks that require the robot to release and regrasp an object in different robot postures. Such problems arise, for example, in robotic suturing and knot tying, and in assembly tasks where parts must be guided through complex environments. Formulating the problem as one of planning on a foliated manifold, we present a randomized planning algorithm that, unlike existing methods, involves sampling and tree propagation primarily in the task space manifold; such an approach significantly improves computational efficiency by reducing the number of projections to the constraint manifold, without incurring any significant increases in the number of release-regrasp sequences. We also propose a post-processing topological exploration algorithm and path refinement procedure for reducing the number of release-regrasp sequences in a solution path, independent of the algorithm used to generate the path. Experiments involving spatial open chains with up to 10 degrees of freedom, operating in complex obstacle-filled environments, show that our algorithm considerably outperforms existing algorithms in terms of computation time, path length, and the number of release-regrasp operations.

Assessment of the Suomi NPP VIIRS Land Surface Albedo Data Using Station Measurements and High-Resolution Albedo Maps

Land surface albedo (LSA), one of the Visible Infrared Imaging Radiometer Suite (VIIRS) environmental data records (EDRs), is a fundamental component for linking the land surface and the climate system by regulating shortwave energy exchange between the land and the atmosphere. Currently, the improved bright pixel sub-algorithm (BPSA) is a unique algorithm employed by VIIRS to routinely generate LSA EDR from VIIRS top-of-atmosphere (TOA) observations. As a product validation procedure, LSA EDR reached validated (V1 stage) maturity in December 2014. This study summarizes recent progress in algorithm refinement, and presents comprehensive validation and evaluation results of VIIRS LSA by using extensive field measurements, Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product, and Landsat-retrieved albedo maps. Results indicate that: (1) by testing the updated desert-specific look-up-table (LUT) that uses a stricter standard to select the training data specific for desert aerosol type in our local environment, it is found that the VIIRS LSA retrieval accuracy is improved over a desert surface and the absolute root mean square error (RMSE) is reduced from 0.036 to 0.023, suggesting the potential of the updated desert LUT to the improve the VIIRS LSA product accuracy; (2) LSA retrieval on snow-covered surfaces is more accurate if the newly developed snow-specific LUT (RMSE = 0.082) replaces the generic LUT (RMSE = 0.093) that is employed in the current operational LSA EDR production; (3) VIIRS LSA is also comparable to high-resolution Landsat albedo retrieval (RMSE < 0.04), although Landsat albedo has a slightly higher accuracy, probably owing to higher spatial resolution with less impacts of mixed pixel; (4) VIIRS LSA retrievals agree well with the MODIS albedo product over various land surface types, with overall RMSE of lower than 0.05 and the overall bias as low as 0.025, demonstrating the comparable data quality between VIIRS and the MODIS LSA product.

Frame buffer-less stream processor for accurate real-time interest point detection

A high performance HW accelerator is proposed to extract and refine the Interest Points from images, by accurately calculating the Difference-of-Gaussian and using refinement algorithms from the SIFT method. Unique features of the accelerator consist in an accuracy comparable to the CDVS Test Model, reference software; in the capability to process the incoming pixel in streaming order to minimize the amount of embedded memory and avoid external frame buffers; in the possibility to configure the processor with different area/speed ratios. FPGA synthesis on a Xilinx XC7V2000T returns a maximum operation frequency up of 309MHz at the fastest corner. Standard cell synthesis with the STMICROELECTRONICS FDSOI 28nm technology, de-congestioned by the use of DPREG memories in place of SRAM, gives a maximum frequency of 1.2GHz and a power dissipation of about 1W at the typical conditions.

Higher Resolution with the Same Data - Tuning cryo-EM Refinement in Relion

Structure refinement used to be limited by crystallization or computational time. We have eliminated the computational burden of cryo-em by accelerating data processing through development of a new, GPU-enabled version of RELION, in collaboration with its ongoing development. The iterative refinement of bio-molecular structures from cryo-em image data, is therefore faster than ever before. However no systematic analysis has been published on the optimal use of input data in the final stages of high-resolution reconstruction. As a consequence, selective exclusion of available image data (at the discretion of the experimenter) represents the currently most efficient (and often used) way to increase the attained resolution. We show that a higher level of reconstructed detail can be achieved by incorporating new methods into existing cryo-em refinement algorithms, which aim to increase the density of high-resolution data used in the final reconstruction steps. Using a combination of tunable parameters and guided data exclusion, we show that these methods can both increase resolution, as well as reduce sensitivity on the input data. These measures facilitate an improvement to the cryo-em refinement method by a) making reconstructed detail more robust to the used data, and b) rendering the process less subjective. Since cryo-em is rapidly becoming a common tool in structural biology, this represents a necessary development for an enormously influential method over the coming years.

Abstraction refinement guided by a learnt probabilistic model

The core challenge in designing an effective static program analysis is to find a good program abstraction -- one that retains only details relevant to a given query. In this paper, we present a new approach for automatically finding such an abstraction. Our approach uses a pessimistic strategy, which can optionally use guidance from a probabilistic model. Our approach applies to parametric static analyses implemented in Datalog, and is based on counterexample-guided abstraction refinement. For each untried abstraction, our probabilistic model provides a probability of success, while the size of the abstraction provides an estimate of its cost in terms of analysis time. Combining these two metrics, probability and cost, our refinement algorithm picks an optimal abstraction. Our probabilistic model is a variant of the Erdos--Renyi random graph model, and it is tunable by what we call hyperparameters. We present a method to learn good values for these hyperparameters, by observing past runs of the analysis on an existing codebase. We evaluate our approach on an object sensitive pointer analysis for Java programs, with two client analyses (PolySite and Downcast).