Merging Procedure Research Articles

A Gaussian-Sum Based Cubature Kalman Filter for Bearings-Only Tracking

Herein is presented an efficient nonlinear filtering algorithm called the Gaussian-sum cubature Kalman filter (GSCKF) for the bearings-only tracking problem. It is developed based on the recently proposed cubature Kalman filter and is built within a Gaussian-sum framework. The new algorithm consists of a splitting and merging procedure when a high degree of nonlinearity is detected. Simulation results show that the proposed algorithm demonstrates comparable performance to the particle filter (PF) with significantly reduced computational cost.

Nested Modeling of Hazards in the National Airspace System

Highly complex and coupled nature of the National Airspace System makes it challenging to understand the safety implications of changes to its operations. A comprehensive assessment of the hazards associated with the introduction of new technologies must involve modeling of interactions among aircraft behavior, supporting infrastructure, and the operational procedures. The traditional approach to risk assessment does not focus on the relative timing of relevant events. The likelihoods of those events are computed externally, usually by means of physics-based simulations, which, while increasingly realistic in capturing physical phenomena, are limited to describing only few relevant interactions to keep the overall complexity tractable. This paper discusses an intermediate layer of analysis with enough fidelity to capture time-dependent coupling among relevant entities of the system that is compact enough to track a large number of those relevant entities simultaneously. To this end, Stochastic Petri nets are used to analyze the conflict resolution between the merging flows of air traffic for optimized-profile-descent approaches. Stochastic Petri nets are coupled with agent-based simulation, and the efficiency of the merging procedures and their sensitivity to wind conditions and the traffic patterns are analyzed. Finally, compact modeling of two off-nominal scenarios related to future procedures is discussed.

Retrieval of Chlorophyll a Concentration with Multi-sensor Data by GSM01 Merging Algorithm

Chlorophyll a concentration, which can be routinely measured by ocean color remote sensing at large scale, is one of the most important indicators to evaluate water quality. The standard inversion algorithms based on empirical model, however, often overestimate chlorophyll a concentration in caseⅡwaters. After tuning key parameters of a typical semi-analytical model called GSM01(Garver- Siegel-Maritorena-01), multi-sensor reflectance data of East China Sea acquired on May 11, 2008, which were from Aqua MODIS, Terra MODIS and SeaWiFS, were merged together to retrieve chlorophyll a concentration. The retrieved result was compared with that of the adaptive weighted averaging method and validated by field survey data. Result showed that retrieval of chlorophyll a concentration with multi-sensor data by GSM01 merging algorithm has four advantages:(1) the range of the retrieved values with GSM01 was basically consistent with the in-situ measurements. Because the influence of water's absorption and scattering on remote sensing reflectance was taken into account by GSM01model, overestimation of chlorophyll a concentration due to high concentrated suspended particulates near the coast was thus avoided.(2) More input bands(from original 6 for single senor to final 18 for multi-sensor in this case) were involved in the merging procedure, the freedom degree of model solution as well as the accuracy of the retrieval was thus improved. In addition, the spatial consistency of the result is ensured by minimizing root mean square error between the measured values and the retrieved values from different remote sensing data source.(3) Instead of merging the chlorophyll a concentration data, which were input of the adaptive weighted averaging method, the GSM01-based method directly merges the original ocean color remote sensing reflectance data, which can better prevent the propagation of error. And(4) the GSM01-based method shows more flexibility because the input reflectance bands can be specified as required.

Modified two-dimensional digital image correlation method with capability of merging of data distributed in time

In this article an analysis of two-dimensional (2D) digital image correlation (DIC) data captured over a long period of time is presented, where the case of a 2D DIC setup is not fixed in the same position between consecutive measurements. An implementation of the data merging procedure is described and a proof of concept is provided using example measurements for both: a numerical model and a physical model. An evaluation of the accuracy of the method and main sources of errors are also presented. The developed method can be used for long-term monitoring of different kinds of objects, which is particularly important for the use of DIC technique in application, e.g., building engineering, building control, or power engineering.

Automatic merging of tetrahedral meshes

SUMMARYA generic algorithm is proposed to merge arbitrary solid tetrahedral meshes automatically into one single valid finite element mesh. The intersection segments in the form of distinct nonoverlapping loops between the boundary surfaces of the given solid objects are determined by the robust neighbor tracing technique. Each intersected triangle on the boundary surface will be triangulated to incorporate the intersection segments onto the boundary surface of the objects. The tetrahedra on the boundary surface associated with the intersected triangular facets are each divided into as many tetrahedra as the number of subtriangles on the triangulated facet. There is a natural partition of the boundary surfaces of the solid objects by the intersection loops into a number of zones. Volumes of intersection can now be identified by collected bounding surfaces from the surface patches of the partition. Whereas mesh compatibility has already been established on the boundary of the solid objects, mesh compatibility has yet to be restored on the bounding surfaces of the regions of intersection. Tetrahedra intersected by the cut surfaces are removed, and new tetrahedra can be generated to fill the volumes bounded by the cut surfaces and the portion of cavity boundary connected to the cut surfaces to restore mesh compatibility at the cut surfaces. Upon restoring compatibility on the bounding surfaces of the regions of intersection, the objects are ready to be merged together as all regions of intersection can be detached freely from the objects. All operations, besides the determination of intersections structurally in the form of loops, are virtually topological, and no parameter and tolerance is needed in the entire merging process. Examples are presented to show the steps and the details of the mesh merging procedure. Copyright © 2012 John Wiley & Sons, Ltd.

Merging meets matching in MC@NLO

Abstract The next-to-leading order accuracy for MC@NLO results exclusive in J light jets is achieved if the computation is based on matrix elements that feature J and J + 1 QCD partons. The simultaneous prediction of observables which are exclusive in different light-jet multiplicities cannot simply be obtained by summing the above results over the relevant range in J; rather, a suitable merging procedure must be defined. We address the problem of such a merging, and propose a solution that can be easily incorporated into existing MC@NLO implementations. We use the automated aMC@NLO framework to illustrate how the method works in practice, by considering the production at the 8 TeV LHC of a Standard Model Higgs in association with up to J = 2 jets, and of an e + ν e pair or a $ t\overline{t} $ pair in association with up to J = 1 jet.

Edge-Guided Multiscale Segmentation of Satellite Multispectral Imagery

This paper presents a new approach to multiscale segmentation of satellite multispectral imagery using edge information. The Canny edge detector is applied to perform multispectral edge detection. The detected edge features are then utilized in a multiscale segmentation loop, and the merge procedure for adjacent image objects is controlled by a separability criterion that combines edge information with segmentation scale. The significance of the edge is measured by adjacent partitioned regions to perform edge assessment. The present method is based on a half-partition structure, which is composed of three steps: single edge detection, separated pixel grouping, and significant feature calculation. The spectral distance of the half-partitions separated by the edge is calculated, compared, and integrated into the edge information. The results show that the proposed approach works well on satellite multispectral images of a coastal area.

Exploring trade-offs between VMAT dose quality and delivery efficiency using a network optimization approach

To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called vmerge, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. vmerge begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the ‘ideal’ dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard vmerge algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the merging heuristics against the Pareto approximation validates that heuristic approaches are capable of achieving high-quality merged plans that lie close to the Pareto frontier.

Multivariable constrained process control via Lyapunov R-functions

This paper proposes a smooth control Lyapunov function with maximal controlled domain of attraction for the state-feedback control of constrained uncertain linear systems describing the dynamics of multivariable processes. Constructive algorithms are shown to build such a control Lyapunov function within a merging procedure due to the so-called R-functions. Robustness with respect to polytopic model uncertainties and disturbance rejection are also discussed. The controlled dynamics of two chemical reactions are simulated to show the benefits of the proposed strategy.

On the Switching Activity and Static Test Compaction of Multicycle Scan-Based Tests

Multicycle (multipattern) scan-based tests contain multiple clock cycles between scan operations. Each such clock cycle defines a pattern of the test. Multipattern tests require fewer clock cycles for test application compared with single-pattern or two-pattern tests for the same target faults. In addition, this paper demonstrates that patterns appearing later in a test typically have lower switching activity than patterns appearing earlier in the test. Based on these observations, the paper presents a static test compaction procedure for multipattern tests that targets a reduction in switching activity while reducing the number of clock cycles required for test application. The procedure is based on an operation called test merging. Merging of a test pair causes the patterns from both tests to appear in a single test. By placing the patterns from a test with a high switching activity at the end of a merged test, their switching activity can be reduced. The proposed procedure combines the test merging procedure with a procedure that modifies a test set so as to reduce its switching activity. Through this procedure it takes advantage of the opportunities created by test merging to reduce the switching activity of patterns that appear later in a test.

„Combined Firm Data for Germany" – Possibilities and Consequences of Merging Firm Data from Different Data Producers

Abstract In the project “Combined firm data for Germany” (KombiFiD) firm data from different institutions were merged and made available for research for the first time. The institutions involved in the project faced considerable challenges both due to the narrow legal limits underlying such a merging procedure and as a result of the partial lack of a unique identifier. This paper provides an overview of the objectives associated with the project and its progress. JEL Classification: C81

Reconstruction of coarse depth estimates using hierarchical image partitions

This paper presents a novel depth map enhancement method which takes as inputs a single view and an associated coarse depth estimate. The depth estimate is reconstructed according to the region boundaries proposed within a set of image partitions of the associated view. Image partitions are determined through a color-based region merging procedure and organized within a hierarchy. Novel depth estimates are computed according to plane-fitting procedures using the proposed regions as support and selected coarse depth estimates. The use of partition hierarchies provides an efficient mechanism for evaluating plane-fitting results over various scales and, in this way, reduce the dependency of the results on the quality of a single color-based segmentation. Experimental results on publicly available test sequences illustrate the potential of the algorithm in significantly improving low quality depth estimates.

Mentha: the interactome browser

Motivations. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". We have developed mentha, a new resource that addresses this problem. mentha archives evidence about PPI in the human proteome ‒ evidence collected from different PPI sources ‒ and offers a series of tools to analyse these data. Users can search the database using a web search engine that returns interaction information for any protein of interest displaying it in the context of the "global interactome". A graphical application to represent this information helps scientists browse the collected data in order to ease and to inspire new experiments and outlooks. Methods. All the remote protein-protein interaction (PPI) databases that are relevant to this project, namely Mint, IntAct, BioGRID, DIP and MatrixDB, are members of the IMEx consortium. IMEx databases adopt a common format and use controlled vocabularies that facilitates data integration. In addition they implement PSICQUIC, a project whose aim is to standardise the access to molecular interaction databases. PSICQUIC defines a list of common fields for each database, and specifies a standard web service with a well-defined list of methods. All the PPI databases are queried using the PSICQUIC protocol. mentha is assembled by a merging procedure that runs weekly and that creates non-redundant data. The information archived in the queried PPI databases is manually curated and annotated with controlled vocabularies. PPI evidence is represented with fixed sets of identifiers such as UniProt IDs and PMIDs. Most of the time proteins are represented with a UniProt identifiers. For any identifier different from UniProt, a sub-procedure gathers all the identifiers and tries to map them using a service offered by UniProt. The merging procedure behind mentha builds a non-redundant database that collects protein interactions from the aforementioned databases, together with their detailed annotation: interaction type, experimental methods and literature references. Results. This approach has generated a consistent interactome (graph) that can be used in various analyses as demonstrated by its use in other projects carried out in our group. Most importantly, the procedure assigns to each interaction a reliability score ‒ the MINT score ‒ that takes into account all the supporting evidence. The user can decide to explore a high confidence interactome or a larger one, accepting more false positives. The application and the web site that have been developed are designed to make the data stored in mentha accessible to all users. All the information contained in the local database is accessible through a web server. The Graphical Application embodies a wide selection of functionalities that help the user navigate and interact with a network of interest. The graphical application, formally a Java web applet, can be embedded in a web page such as iGoogle or even a scientific paper just by feeding it with an SDA, a DOI, or with UniProt IDs. Availability http://mentha.uniroma2.it/

Adaptive regional feature extraction for very high spatial resolution image classification

An object-oriented, multiscale feature extraction approach is proposed for the land-cover classification of high spatial resolution images. The approach provides more discriminative features by considering the spatial context information from different segmentation levels. It consists of three successive substeps: segmentation by mean-shift algorithm, an iteratively merging process controlled by merging cost function and range-of-scale parameter, and feature extraction from linked multilevel image partitions. The mean-shift method is to get boundary-preserved and spectrally homogeneous over-segmentation regions. Then, a family of nested image partitions is constructed by a merging procedure. Meanwhile, every region of the finest scale is linked to image objects of its superlevels. Finally, every region in the finest scale is treated as a basic analysis unit, and the feature vectors are created by stacking statistics from the region and their superlevels. A support vector machine is used as a classifier and the method on two widely used high spatial resolution data sets over Pavia City, Italy, are evaluated. Compared with results reported in many papers, the result indicates superior accuracy.

Evolutionary algorithm to traveling salesman problems

This paper proposed an improved version of the Particle Swarm Optimization (PSO) approach to solve Traveling Salesman Problems (TSP). This evolutionary algorithm includes two phases. The first phase includes Fuzzy C-Means clustering, a rule-based route permutation, a random swap strategy and a cluster merge procedure. This approach firstly generates an initial non-crossing route, such that the TSP can be solved more efficiently by the proposed PSO algorithm. The use of sub-cluster also reduces the complexity and achieves better performance for problems with a large number of cities. The proposed Genetic-based PSO procedure is then applied to solve the TSP with better efficiency in the second phase. The proposed Genetic-based PSO procedure is applied to TSPs with better efficiency. Fixed runtime performance was used to demonstrate the efficiency of the proposed algorithm for the cases with a large number of cities.

Measuring empirical discrepancy in image segmentation results

A methodology for comparison of boundary and segmentation images based on Precision-Recall graphs is presented in this study. The proposed methodology compares the location of edge pixels between an image under test and an ideal reference, in order to obtain a precise normalised similarity measure. This approach also deals with the case when multiple references are available using a merging procedure. Small displacement errors in edge pixel location are handled using a tolerance radius, which introduces the problem of multiple matching between test and reference edge pixels. This problem is addressed as a bipartite graph, solved by using the Hopcroft-Karp algorithm to obtain the maximum number of unique matchings. Experiments have been carried out in order to determine the performance of this evaluation approach.

Robust extraction of fuzzy rules with artificial neural network based on fuzzy inference system

The paper presents a method of parameters estimation for artificial neural network based on fuzzy inference system (ANNBFIS). It is based on deterministic annealing, e-insensitive learning by solving a system of linear inequalities and robust fuzzy c-means clustering. The proposed algorithm allows to improve the neuro-fuzzy modelling quality by increasing the generalisation ability and outliers robustness. To find the unknown number of fuzzy rules we proposed the procedure of robust clusters merging. The performance of the learning method is demonstrated through the benchmark sunspot prediction problem.

Merging for Particle-Mesh Complex Particle Kinetic modeling of the multiple plasma beams

We suggest a merging procedure for the Particle-Mesh Complex Particle Kinetic (PMCPK) method in case of inter-penetrating flow (multiple plasma beams). We examine the standard particle-in-cell (PIC) and the PMCPK methods in the case of particle acceleration by shock surfing for a wide range of the control numerical parameters. The plasma dynamics is described by a hybrid (particle-ion–fluid-electron) model. Note that one may need a mesh if modeling with the computation of an electromagnetic field. Our calculations use specified, time-independent electromagnetic fields for the shock, rather than self-consistently generated fields. While a particle-mesh method is a well-verified approach, the CPK method seems to be a good approach for multiscale modeling that includes multiple regions with various particle/fluid plasma behavior. However, the CPK method is still in need of a verification for studying the basic plasma phenomena: particle heating and acceleration by collisionless shocks, magnetic field reconnection, beam dynamics, etc.

Application of a radar-rainfall uncertainty model to the NWS multi-sensor precipitation estimator products

Given the increasing interest in using radar-based rainfall estimates in hydrologic studies, efforts are critically needed to assess the applicability of recently-proposed methods that focus on quantitative modelling of radar-rainfall uncertainties. The current study reports on the implementation and assessment of an empirically-based approach (known as product-error driven (PED) method) for modelling uncertainties in radar-based rainfall products. In this study, the PED method is applied to a suite of operational radar-based products produced by the U.S. National Weather Service (NWS) Multi-Sensor Precipitation Estimator (MPE) algorithm. The tested MPE products range from a radar-only product, to other products that include various degrees of mean-field and local bias adjustments and gauge-radar optimal merging procedures. Data from an independent dense rain gauge cluster located in south-west Louisiana is used as a proxy for the unknown surface rainfall rates. The focus is on assessing the transferability of the PED across different radar-rainfall products and geographical regions, and the generality of the distributional and parametric assumptions of the PED method. The study also provides insight on the critical issue of the sampling variability and data requirements that govern the implementation, interpretation and possible future enhancements of the radar-error modelling methods.

Interactive image segmentation by matching attributed relational graphs

A model-based graph matching approach is proposed for interactive image segmentation. It starts from an over-segmentation of the input image, exploiting color and spatial information among regions to propagate the labels from the regions marked by the user-provided seeds to the entire image. The region merging procedure is performed by matching two graphs: the input graph, representing the entire image; and the model graph, representing only the marked regions. The optimization is based on discrete search using deformed graphs to efficiently evaluate the spatial information. Note that by using a model-based approach, different interactive segmentation problems can be tackled: binary and multi-label segmentation of single images as well as of multiple similar images. Successful results for all these cases are presented, in addition to a comparison between our binary segmentation results and those obtained with state-of-the-art approaches. An implementation is available at http://structuralsegm.sourceforge.net/ . ► It starts from an oversegmentation to propagate the labels by region merging. ► It is trivially extensible from binary to multi-label segmentation. ► Spatial relations are exploited besides color information. ► It can be combined with the connectivity constraint to reduce the user effort. ► By including a boundary refinement step, it produced state-of-the-art results.