Extending the scope of pooled analyses of individual patient biomarker data from heterogeneous laboratory platforms and cohorts using merging algorithms.

PubMed

Burke, Órlaith; Benton, Samantha; Szafranski, Pawel; von Dadelszen, Peter; Buhimschi, S Catalin; Cetin, Irene; Chappell, Lucy; Figueras, Francesc; Galindo, Alberto; Herraiz, Ignacio; Holzman, Claudia; Hubel, Carl; Knudsen, Ulla; Kronborg, Camilla; Laivuori, Hannele; Lapaire, Olav; McElrath, Thomas; Moertl, Manfred; Myers, Jenny; Ness, Roberta B; Oliveira, Leandro; Olson, Gayle; Poston, Lucilla; Ris-Stalpers, Carrie; Roberts, James M; Schalekamp-Timmermans, Sarah; Schlembach, Dietmar; Steegers, Eric; Stepan, Holger; Tsatsaris, Vassilis; van der Post, Joris A; Verlohren, Stefan; Villa, Pia M; Williams, David; Zeisler, Harald; Redman, Christopher W G; Staff, Anne Cathrine

2016-01-01

A common challenge in medicine, exemplified in the analysis of biomarker data, is that large studies are needed for sufficient statistical power. Often, this may only be achievable by aggregating multiple cohorts. However, different studies may use disparate platforms for laboratory analysis, which can hinder merging. Using circulating placental growth factor (PlGF), a potential biomarker for hypertensive disorders of pregnancy (HDP) such as preeclampsia, as an example, we investigated how such issues can be overcome by inter-platform standardization and merging algorithms. We studied 16,462 pregnancies from 22 study cohorts. PlGF measurements (gestational age ⩾20 weeks) analyzed on one of four platforms: R&D Systems, AlereTriage, RocheElecsys or AbbottArchitect, were available for 13,429 women. Two merging algorithms, using Z-Score and Multiple of Median transformations, were applied. Best reference curves (BRC), based on merged, transformed PlGF measurements in uncomplicated pregnancy across six gestational age groups, were estimated. Identification of HDP by these PlGF-BRCs was compared to that of platform-specific curves. We demonstrate the feasibility of merging PlGF concentrations from different analytical platforms. Overall BRC identification of HDP performed at least as well as platform-specific curves. Our method can be extended to any set of biomarkers obtained from different laboratory platforms in any field. Merged biomarker data from multiple studies will improve statistical power and enlarge our understanding of the pathophysiology and management of medical syndromes. Copyright © 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

Surface Hold Advisor Using Critical Sections

NASA Technical Reports Server (NTRS)

Law, Caleb Hoi Kei (Inventor); Hsiao, Thomas Kun-Lung (Inventor); Mittler, Nathan C. (Inventor); Couluris, George J. (Inventor)

2013-01-01

The Surface Hold Advisor Using Critical Sections is a system and method for providing hold advisories to surface controllers to prevent gridlock and resolve crossing and merging conflicts among vehicles traversing a vertex-edge graph representing a surface traffic network on an airport surface. The Advisor performs pair-wise comparisons of current position and projected path of each vehicle with other surface vehicles to detect conflicts, determine critical sections, and provide hold advisories to traffic controllers recommending vehicles stop at entry points to protected zones around identified critical sections. A critical section defines a segment of the vertex-edge graph where vehicles are in crossing or merging or opposite direction gridlock contention. The Advisor detects critical sections without reference to scheduled, projected or required times along assigned vehicle paths, and generates hold advisories to prevent conflicts without requiring network path direction-of-movement rules and without requiring rerouting, rescheduling or other network optimization solutions.

The use of Merging and Aggregation Operators for MRDB Data Feeding

NASA Astrophysics Data System (ADS)

Kozioł, Krystian; Lupa, Michał

2013-12-01

This paper presents the application of two generalization operators - merging and displacement - in the process of automatic data feeding in a multiresolution data base of topographic objects from large-scale data-bases (1 : 500-1 : 5000). An ordered collection of objects makes a layer of development that in the process of generalization is subjected to the processes of merging and displacement in order to maintain recognizability in the reduced scale of the map. The solution to the above problem is the algorithms described in the work; these algorithms use the standard recognition of drawings (Chrobak 2010), independent of the user. A digital cartographic generalization process is a set of consecutive operators where merging and aggregation play a key role. The proper operation has a significant impact on the qualitative assessment of data generalization

A Round Robin evaluation of AMSR-E soil moisture retrievals

NASA Astrophysics Data System (ADS)

Mittelbach, Heidi; Hirschi, Martin; Nicolai-Shaw, Nadine; Gruber, Alexander; Dorigo, Wouter; de Jeu, Richard; Parinussa, Robert; Jones, Lucas A.; Wagner, Wolfgang; Seneviratne, Sonia I.

2014-05-01

Large-scale and long-term soil moisture observations based on remote sensing are promising data sets to investigate and understand various processes of the climate system including the water and biochemical cycles. Currently, the ESA Climate Change Initiative for soil moisture develops and evaluates a consistent global long-term soil moisture data set, which is based on merging passive and active remotely sensed soil moisture. Within this project an inter-comparison of algorithms for AMSR-E and ASCAT Level 2 products was conducted separately to assess the performance of different retrieval algorithms. Here we present the inter-comparison of AMSR-E Level 2 soil moisture products. These include the public data sets from University of Montana (UMT), Japan Aerospace and Space Exploration Agency (JAXA), VU University of Amsterdam (VUA; two algorithms) and National Aeronautics and Space Administration (NASA). All participating algorithms are applied to the same AMSR-E Level 1 data set. Ascending and descending paths of scaled surface soil moisture are considered and evaluated separately in daily and monthly resolution over the 2007-2011 time period. Absolute values of soil moisture as well as their long-term anomalies (i.e. removing the mean seasonal cycle) and short-term anomalies (i.e. removing a five weeks moving average) are evaluated. The evaluation is based on conventional measures like correlation and unbiased root-mean-square differences as well as on the application of the triple collocation method. As reference data set, surface soil moisture of 75 quality controlled soil moisture sites from the International Soil Moisture Network (ISMN) are used, which cover a wide range of vegetation density and climate conditions. For the application of the triple collocation method, surface soil moisture estimates from the Global Land Data Assimilation System are used as third independent data set. We find that the participating algorithms generally display a better performance for the descending compared to the ascending paths. A first classification of the sites defined by geographical locations show that the algorithms have a very similar average performance. Further classifications of the sites by land cover types and climate regions will be conducted which might result in a more diverse performance of the algorithms.

Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network.

PubMed

Newton, Katherine M; Peissig, Peggy L; Kho, Abel Ngo; Bielinski, Suzette J; Berg, Richard L; Choudhary, Vidhu; Basford, Melissa; Chute, Christopher G; Kullo, Iftikhar J; Li, Rongling; Pacheco, Jennifer A; Rasmussen, Luke V; Spangler, Leslie; Denny, Joshua C

2013-06-01

Genetic studies require precise phenotype definitions, but electronic medical record (EMR) phenotype data are recorded inconsistently and in a variety of formats. To present lessons learned about validation of EMR-based phenotypes from the Electronic Medical Records and Genomics (eMERGE) studies. The eMERGE network created and validated 13 EMR-derived phenotype algorithms. Network sites are Group Health, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University. By validating EMR-derived phenotypes we learned that: (1) multisite validation improves phenotype algorithm accuracy; (2) targets for validation should be carefully considered and defined; (3) specifying time frames for review of variables eases validation time and improves accuracy; (4) using repeated measures requires defining the relevant time period and specifying the most meaningful value to be studied; (5) patient movement in and out of the health plan (transience) can result in incomplete or fragmented data; (6) the review scope should be defined carefully; (7) particular care is required in combining EMR and research data; (8) medication data can be assessed using claims, medications dispensed, or medications prescribed; (9) algorithm development and validation work best as an iterative process; and (10) validation by content experts or structured chart review can provide accurate results. Despite the diverse structure of the five EMRs of the eMERGE sites, we developed, validated, and successfully deployed 13 electronic phenotype algorithms. Validation is a worthwhile process that not only measures phenotype performance but also strengthens phenotype algorithm definitions and enhances their inter-institutional sharing.

A method for automatic grain segmentation of multi-angle cross-polarized microscopic images of sandstone

NASA Astrophysics Data System (ADS)

Jiang, Feng; Gu, Qing; Hao, Huizhen; Li, Na; Wang, Bingqian; Hu, Xiumian

2018-06-01

Automatic grain segmentation of sandstone is to partition mineral grains into separate regions in the thin section, which is the first step for computer aided mineral identification and sandstone classification. The sandstone microscopic images contain a large number of mixed mineral grains where differences among adjacent grains, i.e., quartz, feldspar and lithic grains, are usually ambiguous, which make grain segmentation difficult. In this paper, we take advantage of multi-angle cross-polarized microscopic images and propose a method for grain segmentation with high accuracy. The method consists of two stages, in the first stage, we enhance the SLIC (Simple Linear Iterative Clustering) algorithm, named MSLIC, to make use of multi-angle images and segment the images as boundary adherent superpixels. In the second stage, we propose the region merging technique which combines the coarse merging and fine merging algorithms. The coarse merging merges the adjacent superpixels with less evident boundaries, and the fine merging merges the ambiguous superpixels using the spatial enhanced fuzzy clustering. Experiments are designed on 9 sets of multi-angle cross-polarized images taken from the three major types of sandstones. The results demonstrate both the effectiveness and potential of the proposed method, comparing to the available segmentation methods.

Aerosol correction for remotely sensed sea surface temperatures from the National Oceanic and Atmospheric Administration advanced very high resolution radiometer

NASA Astrophysics Data System (ADS)

Nalli, Nicholas R.; Stowe, Larry L.

2002-10-01

This research presents the first-phase derivation and implementation of daytime aerosol correction algorithms for remotely sensed sea surface temperature (SST) from the advanced very high resolution radiometer (AVHRR) instrument flown onboard NOAA polar orbiting satellites. To accomplish this, a long-term (1990-1998), global AVHRR-buoy match-up database was created by merging the NOAA/NASA Pathfinder Atmospheres and Pathfinder Oceans data sets. The merged data set is unique in that it includes daytime estimates of aerosol optical depth (AOD) derived from AVHRR channel 1 (0.63 μm) under global conditions of significant aerosol loading. Histograms of retrieved AOD reveal monomodal, lognormal distributions for both tropospheric and stratospheric aerosol modes. It is then shown empirically that the SST depression caused under each aerosol mode can be expressed as a linear function in two predictors, these being the slant path AOD retrieved from AVHRR channel 1 along with the ratio of channels 1 and 2 normalized reflectances. On the basis of these relationships, parametric equations are derived to provide an aerosol correction for retrievals from the daytime NOAA operational multichannel and nonlinear SST algorithms. Separate sets of coefficients are utilized for two aerosol modes: tropospheric (i.e., dust, smoke, haze) and stratospheric/tropospheric (i.e., following a major volcanic eruption). The equations are shown to significantly reduce retrieved SST bias using an independent set of match-ups. Eliminating aerosol-induced bias in both real-time and retrospective processing will enhance the utility of the AVHRR SST for the general user community and in climate research.

Smell Detection Agent Based Optimization Algorithm

NASA Astrophysics Data System (ADS)

Vinod Chandra, S. S.

2016-09-01

In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

Automatic extraction of numeric strings in unconstrained handwritten document images

NASA Astrophysics Data System (ADS)

Haji, M. Mehdi; Bui, Tien D.; Suen, Ching Y.

2011-01-01

Numeric strings such as identification numbers carry vital pieces of information in documents. In this paper, we present a novel algorithm for automatic extraction of numeric strings in unconstrained handwritten document images. The algorithm has two main phases: pruning and verification. In the pruning phase, the algorithm first performs a new segment-merge procedure on each text line, and then using a new regularity measure, it prunes all sequences of characters that are unlikely to be numeric strings. The segment-merge procedure is composed of two modules: a new explicit character segmentation algorithm which is based on analysis of skeletal graphs and a merging algorithm which is based on graph partitioning. All the candidate sequences that pass the pruning phase are sent to a recognition-based verification phase for the final decision. The recognition is based on a coarse-to-fine approach using probabilistic RBF networks. We developed our algorithm for the processing of real-world documents where letters and digits may be connected or broken in a document. The effectiveness of the proposed approach is shown by extensive experiments done on a real-world database of 607 documents which contains handwritten, machine-printed and mixed documents with different types of layouts and levels of noise.

Developing a hybrid dictionary-based bio-entity recognition technique.

PubMed

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Developing a hybrid dictionary-based bio-entity recognition technique

PubMed Central

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

NASA Astrophysics Data System (ADS)

Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam

2017-04-01

The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.

Aerosol Correction for Remotely Sensed Sea Surface Temperatures From the NOAA AVHRR: Phase II

NASA Astrophysics Data System (ADS)

Nalli, N. R.; Ignatov, A.

2002-05-01

For over two decades, the National Oceanic and Atmospheric Administration (NOAA) has produced global retrievals of sea surface temperature (SST) using infrared (IR) data from the Advanced Very High Resolution Radiometer (AVHRR). The standard multichannel retrieval algorithms are derived from regression analyses of AVHRR window channel brightness temperatures against in situ buoy measurements under non-cloudy conditions thus providing a correction for IR attenuation due to molecular water vapor absorption. However, for atmospheric conditions with elevated aerosol levels (e.g., arising from dust, biomass burning and volcanic eruptions), such algorithms lead to significant negative biases in SST because of IR attenuation arising from aerosol absorption and scattering. This research presents the development of a 2nd-phase aerosol correction algorithm for daytime AVHRR SST. To accomplish this, a long-term (1990-1998), global AVHRR-buoy matchup database was created by merging the Pathfinder Atmospheres (PATMOS) and Oceans (PFMDB) data sets. The merged data are unique in that they include multi-year, global daytime estimates of aerosol optical depth (AOD) derived from AVHRR channels 1 and 2 (0.63 and 0.83 μ m, respectively), along with an effective Angstrom exponent derived from the AOD retrievals (Ignatov and Nalli, 2002). Recent enhancements in the aerosol data constitute an improvement over the Phase I algorithm (Nalli and Stowe, 2002) which relied only on channel 1 AOD and the ratio of normalized reflectance from channels 1 and 2. The Angstrom exponent and channel 2 AOD provide important statistical information about the particle size distribution of the aerosol. The SST bias can be parametrically expressed as a function of observed AVHRR channels 1 and 2 slant-path AOD, normalized reflectance ratio and the Angstrom exponent. Based upon these empirical relationships, aerosol correction equations are then derived for the daytime multichannel and nonlinear SST (MCSST and NLSST) algorithms. Separate sets of coefficients are utilized for two aerosol modes, these being stratospheric/tropospheric (e.g., volcanic aerosol) and tropospheric (e.g., dust, smoke). The algorithms are subsequently applied to retrospective PATMOS data to demonstrate the potential for climate applications. The minimization of cold biases in the AVHRR SST, as demonstrated in this work, should improve its overall utility for the general user community.

Seamless Merging of Hypertext and Algorithm Animation

ERIC Educational Resources Information Center

Karavirta, Ville

2009-01-01

Online learning material that students use by themselves is one of the typical usages of algorithm animation (AA). Thus, the integration of algorithm animations into hypertext is seen as an important topic today to promote the usage of algorithm animation in teaching. This article presents an algorithm animation viewer implemented purely using…

Technical Note: Improving the VMERGE treatment planning algorithm for rotational radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaddy, Melissa R., E-mail: mrgaddy@ncsu.edu; Papp,

2016-07-15

Purpose: The authors revisit the VMERGE treatment planning algorithm by Craft et al. [“Multicriteria VMAT optimization,” Med. Phys. 39, 686–696 (2012)] for arc therapy planning and propose two changes to the method that are aimed at improving the achieved trade-off between treatment time and plan quality at little additional planning time cost, while retaining other desirable properties of the original algorithm. Methods: The original VMERGE algorithm first computes an “ideal,” high quality but also highly time consuming treatment plan that irradiates the patient from all possible angles in a fine angular grid with a highly modulated beam and then makesmore » this plan deliverable within practical treatment time by an iterative fluence map merging and sequencing algorithm. We propose two changes to this method. First, we regularize the ideal plan obtained in the first step by adding an explicit constraint on treatment time. Second, we propose a different merging criterion that comprises of identifying and merging adjacent maps whose merging results in the least degradation of radiation dose. Results: The effect of both suggested modifications is evaluated individually and jointly on clinical prostate and paraspinal cases. Details of the two cases are reported. Conclusions: In the authors’ computational study they found that both proposed modifications, especially the regularization, yield noticeably improved treatment plans for the same treatment times than what can be obtained using the original VMERGE method. The resulting plans match the quality of 20-beam step-and-shoot IMRT plans with a delivery time of approximately 2 min.« less

Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Cao, Lu; Chen, Qiwei

2018-03-01

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

An Elementary Algorithm for Autonomous Air Terminal Merging and Interval Management

NASA Technical Reports Server (NTRS)

White, Allan L.

2017-01-01

A central element of air traffic management is the safe merging and spacing of aircraft during the terminal area flight phase. This paper derives and examines an algorithm for the merging and interval managing problem for Standard Terminal Arrival Routes. It describes a factor analysis for performance based on the distribution of arrivals, the operating period of the terminal, and the topology of the arrival routes; then presents results from a performance analysis and from a safety analysis for a realistic topology based on typical routes for a runway at Phoenix International Airport. The heart of the safety analysis is a statistical derivation on how to conduct a safety analysis for a local simulation when the safety requirement is given for the entire airspace.

A real time sorting algorithm to time sort any deterministic time disordered data stream

NASA Astrophysics Data System (ADS)

Saini, J.; Mandal, S.; Chakrabarti, A.; Chattopadhyay, S.

2017-12-01

In new generation high intensity high energy physics experiments, millions of free streaming high rate data sources are to be readout. Free streaming data with associated time-stamp can only be controlled by thresholds as there is no trigger information available for the readout. Therefore, these readouts are prone to collect large amount of noise and unwanted data. For this reason, these experiments can have output data rate of several orders of magnitude higher than the useful signal data rate. It is therefore necessary to perform online processing of the data to extract useful information from the full data set. Without trigger information, pre-processing on the free streaming data can only be done with time based correlation among the data set. Multiple data sources have different path delays and bandwidth utilizations and therefore the unsorted merged data requires significant computational efforts for real time manifestation of sorting before analysis. Present work reports a new high speed scalable data stream sorting algorithm with its architectural design, verified through Field programmable Gate Array (FPGA) based hardware simulation. Realistic time based simulated data likely to be collected in an high energy physics experiment have been used to study the performance of the algorithm. The proposed algorithm uses parallel read-write blocks with added memory management and zero suppression features to make it efficient for high rate data-streams. This algorithm is best suited for online data streams with deterministic time disorder/unsorting on FPGA like hardware.

Method of modifying a volume mesh using sheet extraction

DOEpatents

Borden, Michael J [Albuquerque, NM; Shepherd, Jason F [Albuquerque, NM

2007-02-20

A method and machine-readable medium provide a technique to modify a hexahedral finite element volume mesh using dual generation and sheet extraction. After generating a dual of a volume stack (mesh), a predetermined algorithm may be followed to modify the volume mesh of hexahedral elements. The predetermined algorithm may include the steps of determining a sheet of hexahedral mesh elements, generating nodes for merging, and merging the nodes to delete the sheet of hexahedral mesh elements and modify the volume mesh.

Algorithms for Large-Scale Astronomical Problems

DTIC Science & Technology

2013-08-01

implemented as a succession of Hadoop MapReduce jobs and sequential programs written in Java . The sampling and splitting stages are implemented as...one MapReduce job, the partitioning and clustering phases make up another job. The merging stage is implemented as a stand-alone Java program. The...Merging. The merging stage is implemented as a sequential Java program that reads the files with the shell information, which were generated by

The Challenge of Wider Library Units: Merging Libraries and Developing Taxing Districts May Be a Way to Stabilize Funding, but the Path Is Not Always Clear

ERIC Educational Resources Information Center

Hennen, Thomas J., Jr.

2004-01-01

Last year, Louisville, KY, grew overnight from the country's 64th largest city to the 16th largest, the result of the merger of the city with Jefferson County. Pittsburgh and Buffalo, NY, are among other communities discussing city-county mergers. Many smaller communities are considering merging services, such as police and fire, or consolidating…

Delineating wetland catchments and modeling hydrologic ...

EPA Pesticide Factsheets

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that

Automatic tracking of dynamical evolutions of oceanic mesoscale eddies with satellite observation data

NASA Astrophysics Data System (ADS)

Sun, Liang; Li, Qiu-Yang

2017-04-01

The oceanic mesoscale eddies play a major role in ocean climate system. To analyse spatiotemporal dynamics of oceanic mesoscale eddies, the Genealogical Evolution Model (GEM) based on satellite data is developed, which is an efficient logical model used to track dynamic evolution of mesoscale eddies in the ocean. It can distinguish different dynamic processes (e.g., merging and splitting) within a dynamic evolution pattern, which is difficult to accomplish using other tracking methods. To this end, a mononuclear eddy detection method was firstly developed with simple segmentation strategies, e.g. watershed algorithm. The algorithm is very fast by searching the steepest descent path. Second, the GEM uses a two-dimensional similarity vector (i.e. a pair of ratios of overlap area between two eddies to the area of each eddy) rather than a scalar to measure the similarity between eddies, which effectively solves the ''missing eddy" problem (temporarily lost eddy in tracking). Third, for tracking when an eddy splits, GEM uses both "parent" (the original eddy) and "child" (eddy split from parent) and the dynamic processes are described as birth and death of different generations. Additionally, a new look-ahead approach with selection rules effectively simplifies computation and recording. All of the computational steps are linear and do not include iteration. Given the pixel number of the target region L, the maximum number of eddies M, the number N of look-ahead time steps, and the total number of time steps T, the total computer time is O (LM(N+1)T). The tracking of each eddy is very smooth because we require that the snapshots of each eddy on adjacent days overlap one another. Although eddy splitting or merging is ubiquitous in the ocean, they have different geographic distribution in the Northern Pacific Ocean. Both the merging and splitting rates of the eddies are high, especially at the western boundary, in currents and in "eddy deserts". GEM is useful not only for satellite-based observational data but also for numerical simulation outputs. It is potentially useful for studying dynamic processes in other related fields, e.g., the dynamics of cyclones in meteorology.

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

A Fast-Time Simulation Environment for Airborne Merging and Spacing Research

NASA Technical Reports Server (NTRS)

Bussink, Frank J. L.; Doble, Nathan A.; Barmore, Bryan E.; Singer, Sharon

2005-01-01

As part of NASA's Distributed Air/Ground Traffic Management (DAG-TM) effort, NASA Langley Research Center is developing concepts and algorithms for merging multiple aircraft arrival streams and precisely spacing aircraft over the runway threshold. An airborne tool has been created for this purpose, called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR). To evaluate the performance of AMSTAR and complement human-in-the-loop experiments, a simulation environment has been developed that enables fast-time studies of AMSTAR operations. The environment is based on TMX, a multiple aircraft desktop simulation program created by the Netherlands National Aerospace Laboratory (NLR). This paper reviews the AMSTAR concept, discusses the integration of the AMSTAR algorithm into TMX and the enhancements added to TMX to support fast-time AMSTAR studies, and presents initial simulation results.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Path planning on satellite images for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Yang, Joe-Ming; Tseng, Chien-Ming; Tseng, P. S.

2015-01-01

In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A* algorithm (FAA*), an advanced A* algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.

Path connectivity based spectral defragmentation in flexible bandwidth networks.

PubMed

Wang, Ying; Zhang, Jie; Zhao, Yongli; Zhang, Jiawei; Zhao, Jie; Wang, Xinbo; Gu, Wanyi

2013-01-28

Optical networks with flexible bandwidth provisioning have become a very promising networking architecture. It enables efficient resource utilization and supports heterogeneous bandwidth demands. In this paper, two novel spectrum defragmentation approaches, i.e. Maximum Path Connectivity (MPC) algorithm and Path Connectivity Triggering (PCT) algorithm, are proposed based on the notion of Path Connectivity, which is defined to represent the maximum variation of node switching ability along the path in flexible bandwidth networks. A cost-performance-ratio based profitability model is given to denote the prons and cons of spectrum defragmentation. We compare these two proposed algorithms with non-defragmentation algorithm in terms of blocking probability. Then we analyze the differences of defragmentation profitability between MPC and PCT algorithms.

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

PubMed

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Constrained VPH+: a local path planning algorithm for a bio-inspired crawling robot with customized ultrasonic scanning sensor.

PubMed

Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan

This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.

Design requirements and development of an airborne descent path definition algorithm for time navigation

NASA Technical Reports Server (NTRS)

Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.

1986-01-01

The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.

Merging Sounder and Imager Data for Improved Cloud Depiction on SNPP and JPSS.

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Holz, R.; Li, Y.; Platnick, S. E.; Wanzong, S.

2017-12-01

Under the NOAA GOES-R Algorithm Working Group (AWG) Program, NOAA supports the development of an Infrared (IR) Optimal Estimation (OE) Cloud Height Algorithm (ACHA). ACHA is an enterprise solution that supports many geostationary and polar orbiting imager sensors. ACHA is operational at NOAA on SNPP VIIRS and has been adopted as the cloud height algorithm for the NASA NPP Atmospheric Suite of products. Being an OE algorithm, ACHA is flexible and capable of using additional observations and constraints. We have modified ACHA to use sounder (CriS) observations to improve the cloud detection, typing and height estimation. Specifically, these improvements include retrievals in multi-layer scenarios and improved performance in polar regions. This presentation will describe the process for merging VIIRS and CrIS and a demonstration of the improvements.

Calculating Least Risk Paths in 3d Indoor Space

NASA Astrophysics Data System (ADS)

Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.

2013-08-01

Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms, vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

PubMed Central

Kok, Kai Yit; Rajendran, Parvathy

2016-01-01

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

Monitoring weaving sections

DOT National Transportation Integrated Search

2001-10-01

Traffic control in highway weaving sections is complicated since vehicles are crossing paths, changing lanes, or merging with through traffic as they enter or exit an expressway. There are two types of weaving sections: (a) single weaving sections wh...

Richardson-Lucy deconvolution as a general tool for combining images with complementary strengths.

PubMed

Ingaramo, Maria; York, Andrew G; Hoogendoorn, Eelco; Postma, Marten; Shroff, Hari; Patterson, George H

2014-03-17

We use Richardson-Lucy (RL) deconvolution to combine multiple images of a simulated object into a single image in the context of modern fluorescence microscopy techniques. RL deconvolution can merge images with very different point-spread functions, such as in multiview light-sheet microscopes,1, 2 while preserving the best resolution information present in each image. We show that RL deconvolution is also easily applied to merge high-resolution, high-noise images with low-resolution, low-noise images, relevant when complementing conventional microscopy with localization microscopy. We also use RL deconvolution to merge images produced by different simulated illumination patterns, relevant to structured illumination microscopy (SIM)3, 4 and image scanning microscopy (ISM). The quality of our ISM reconstructions is at least as good as reconstructions using standard inversion algorithms for ISM data, but our method follows a simpler recipe that requires no mathematical insight. Finally, we apply RL deconvolution to merge a series of ten images with varying signal and resolution levels. This combination is relevant to gated stimulated-emission depletion (STED) microscopy, and shows that merges of high-quality images are possible even in cases for which a non-iterative inversion algorithm is unknown. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies

PubMed Central

2017-01-01

The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems. PMID:29121100

Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

NASA Astrophysics Data System (ADS)

Pasquato, Mario; Chung, Chul

2016-05-01

Context. Machine-learning (ML) solves problems by learning patterns from data with limited or no human guidance. In astronomy, ML is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims: We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify globular clusters (GCs) that may have a history of merging from observational data. Methods: We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After carrying out dimensionality reduction on the feature space, the resulting datapoints are fed in to various classification algorithms. Using repeated random subsampling validation, we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations. Results: The three algorithms we considered (C5.0 trees, k-nearest neighbour, and support-vector machines) all achieve a test misclassification rate of about 10% without parameter tuning, with support-vector machines slightly outperforming the others. The first principal component of feature space correlates with cluster concentration. If we exclude it from the regression, the performance of the algorithms is only slightly reduced.

A Minimum Path Algorithm Among 3D-Polyhedral Objects

NASA Astrophysics Data System (ADS)

Yeltekin, Aysin

1989-03-01

In this work we introduce a minimum path theorem for 3D case. We also develop an algorithm based on the theorem we prove. The algorithm will be implemented on the software package we develop using C language. The theorem we introduce states that; "Given the initial point I, final point F and S be the set of finite number of static obstacles then an optimal path P from I to F, such that PA S = 0 is composed of straight line segments which are perpendicular to the edge segments of the objects." We prove the theorem as well as we develop the following algorithm depending on the theorem to find the minimum path among 3D-polyhedral objects. The algorithm generates the point Qi on edge ei such that at Qi one can find the line which is perpendicular to the edge and the IF line. The algorithm iteratively provides a new set of initial points from Qi and exploits all possible paths. Then the algorithm chooses the minimum path among the possible ones. The flowchart of the program as well as the examination of its numerical properties are included.

Departure Trajectory Synthesis and the Intercept Problem

NASA Technical Reports Server (NTRS)

Bolender, Michael A.; Slater, G. L.

1997-01-01

Two areas of the departure problem in air traffic control are discussed. The first topic is the generation of climb-out trajectories to a fix. The trajectories would be utilized by a scheduling algorithm to allocate runways, sequence the proposed departures, and assign a departure time. The second area is concerned with finding horizontal trajectories to merge aircraft from the TRACON to an open slot in the en-route environment. Solutions are presented for the intercept problem for two cases: (1) the aircraft is traveling at the speed of the aircraft in the jetway; (2) the merging aircraft has to accelerate to reach the speed of the aircraft in the en-route stream. An algorithm is given regarding the computation of a solution for the latter case. For the former, a set of equations is given that allows us to numerically solve for the coordinate where the merge will occur.

Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

PubMed

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-03-19

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

A parallel algorithm for finding the shortest exit paths in mines

NASA Astrophysics Data System (ADS)

Jastrzab, Tomasz; Buchcik, Agata

2017-11-01

In the paper we study the problem of finding the shortest exit path in an underground mine in case of emergency. Since emergency situations, such as underground fires, can put the miners' lives at risk, the ability to quickly determine the safest exit path is crucial. We propose a parallel algorithm capable of finding the shortest path between the safe exit point and any other point in the mine. The algorithm is also able to take into account the characteristics of individual miners, to make the path determination more reliable.

Automated flight path planning for virtual endoscopy.

PubMed

Paik, D S; Beaulieu, C F; Jeffrey, R B; Rubin, G D; Napel, S

1998-05-01

In this paper, a novel technique for rapid and automatic computation of flight paths for guiding virtual endoscopic exploration of three-dimensional medical images is described. While manually planning flight paths is a tedious and time consuming task, our algorithm is automated and fast. Our method for positioning the virtual camera is based on the medial axis transform but is much more computationally efficient. By iteratively correcting a path toward the medial axis, the necessity of evaluating simple point criteria during morphological thinning is eliminated. The virtual camera is also oriented in a stable viewing direction, avoiding sudden twists and turns. We tested our algorithm on volumetric data sets of eight colons, one aorta and one bronchial tree. The algorithm computed the flight paths in several minutes per volume on an inexpensive workstation with minimal computation time added for multiple paths through branching structures (10%-13% per extra path). The results of our algorithm are smooth, centralized paths that aid in the task of navigation in virtual endoscopic exploration of three-dimensional medical images.

A Graph-Embedding Approach to Hierarchical Visual Word Mergence.

PubMed

Wang, Lei; Liu, Lingqiao; Zhou, Luping

2017-02-01

Appropriately merging visual words are an effective dimension reduction method for the bag-of-visual-words model in image classification. The approach of hierarchically merging visual words has been extensively employed, because it gives a fully determined merging hierarchy. Existing supervised hierarchical merging methods take different approaches and realize the merging process with various formulations. In this paper, we propose a unified hierarchical merging approach built upon the graph-embedding framework. Our approach is able to merge visual words for any scenario, where a preferred structure and an undesired structure are defined, and, therefore, can effectively attend to all kinds of requirements for the word-merging process. In terms of computational efficiency, we show that our algorithm can seamlessly integrate a fast search strategy developed in our previous work and, thus, well maintain the state-of-the-art merging speed. To the best of our survey, the proposed approach is the first one that addresses the hierarchical visual word mergence in such a flexible and unified manner. As demonstrated, it can maintain excellent image classification performance even after a significant dimension reduction, and outperform all the existing comparable visual word-merging methods. In a broad sense, our work provides an open platform for applying, evaluating, and developing new criteria for hierarchical word-merging tasks.

Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.

PubMed

Lin, Lanny; Goodrich, Michael A

2014-12-01

During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Lane, Charles R.

2017-07-01

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

Identification of anomalous motion of thunderstorms using daily rainfall fields

NASA Astrophysics Data System (ADS)

Moral, Anna del; Llasat, María del Carmen; Rigo, Tomeu

2017-03-01

Most of the adverse weather phenomena in Catalonia (northeast Iberian Peninsula) are caused by convective events, which can produce heavy rains, large hailstones, strong winds, lightning and/or tornadoes. These thunderstorms usually have marked paths. However, their trajectories can vary sharply at any given time, completely changing direction from the path they have previously followed. Furthermore, some thunderstorms split or merge with each other, creating new formations with different behaviour. In order to identify the potentially anomalous movements that some thunderstorms make, this paper presents a two-step methodology using a database with 8 years of daily rainfall fields data for the Catalonia region (2008-2015). First, it classifies daily rainfall fields between days with "no rain", "non-potentially convective rain" and "potentially convective rain", based on daily accumulated precipitation and extension thresholds. Second, it categorises convective structures within rainfall fields and briefly identifies their main features, distinguishing whether there were any anomalous thunderstorm movements in each case. This methodology has been applied to the 2008-2015 period, and the main climatic features of convective and non-convective days were obtained. The methodology can be exported to other regions that do not have the necessary radar-based algorithms to detect convective cells, but where there is a good rain gauge network in place.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, Animesh, E-mail: animesh@zedat.fu-berlin.de; Delle Site, Luigi, E-mail: dellesite@fu-berlin.de

Quantum effects due to the spatial delocalization of light atoms are treated in molecular simulation via the path integral technique. Among several methods, Path Integral (PI) Molecular Dynamics (MD) is nowadays a powerful tool to investigate properties induced by spatial delocalization of atoms; however, computationally this technique is very demanding. The above mentioned limitation implies the restriction of PIMD applications to relatively small systems and short time scales. One of the possible solutions to overcome size and time limitation is to introduce PIMD algorithms into the Adaptive Resolution Simulation Scheme (AdResS). AdResS requires a relatively small region treated at pathmore » integral level and embeds it into a large molecular reservoir consisting of generic spherical coarse grained molecules. It was previously shown that the realization of the idea above, at a simple level, produced reasonable results for toy systems or simple/test systems like liquid parahydrogen. Encouraged by previous results, in this paper, we show the simulation of liquid water at room conditions where AdResS, in its latest and more accurate Grand-Canonical-like version (GC-AdResS), is merged with two of the most relevant PIMD techniques available in the literature. The comparison of our results with those reported in the literature and/or with those obtained from full PIMD simulations shows a highly satisfactory agreement.« less

Gap filling of 3-D microvascular networks by tensor voting.

PubMed

Risser, L; Plouraboue, F; Descombes, X

2008-05-01

We present a new algorithm which merges discontinuities in 3-D images of tubular structures presenting undesirable gaps. The application of the proposed method is mainly associated to large 3-D images of microvascular networks. In order to recover the real network topology, we need to fill the gaps between the closest discontinuous vessels. The algorithm presented in this paper aims at achieving this goal. This algorithm is based on the skeletonization of the segmented network followed by a tensor voting method. It permits to merge the most common kinds of discontinuities found in microvascular networks. It is robust, easy to use, and relatively fast. The microvascular network images were obtained using synchrotron tomography imaging at the European Synchrotron Radiation Facility. These images exhibit samples of intracortical networks. Representative results are illustrated.

Evaluating progressive-rendering algorithms in appearance design tasks.

PubMed

Jiawei Ou; Karlik, Ondrej; Křivánek, Jaroslav; Pellacini, Fabio

2013-01-01

Progressive rendering is becoming a popular alternative to precomputational approaches to appearance design. However, progressive algorithms create images exhibiting visual artifacts at early stages. A user study investigated these artifacts' effects on user performance in appearance design tasks. Novice and expert subjects performed lighting and material editing tasks with four algorithms: random path tracing, quasirandom path tracing, progressive photon mapping, and virtual-point-light rendering. Both the novices and experts strongly preferred path tracing to progressive photon mapping and virtual-point-light rendering. None of the participants preferred random path tracing to quasirandom path tracing or vice versa; the same situation held between progressive photon mapping and virtual-point-light rendering. The user workflow didn’t differ significantly with the four algorithms. The Web Extras include a video showing how four progressive-rendering algorithms converged (at http://youtu.be/ck-Gevl1e9s), the source code used, and other supplementary materials.

Synthesizer: Expediting synthesis studies from context-free data with information retrieval techniques.

PubMed

Gandy, Lisa M; Gumm, Jordan; Fertig, Benjamin; Thessen, Anne; Kennish, Michael J; Chavan, Sameer; Marchionni, Luigi; Xia, Xiaoxin; Shankrit, Shambhavi; Fertig, Elana J

2017-01-01

Scientists have unprecedented access to a wide variety of high-quality datasets. These datasets, which are often independently curated, commonly use unstructured spreadsheets to store their data. Standardized annotations are essential to perform synthesis studies across investigators, but are often not used in practice. Therefore, accurately combining records in spreadsheets from differing studies requires tedious and error-prone human curation. These efforts result in a significant time and cost barrier to synthesis research. We propose an information retrieval inspired algorithm, Synthesize, that merges unstructured data automatically based on both column labels and values. Application of the Synthesize algorithm to cancer and ecological datasets had high accuracy (on the order of 85-100%). We further implement Synthesize in an open source web application, Synthesizer (https://github.com/lisagandy/synthesizer). The software accepts input as spreadsheets in comma separated value (CSV) format, visualizes the merged data, and outputs the results as a new spreadsheet. Synthesizer includes an easy to use graphical user interface, which enables the user to finish combining data and obtain perfect accuracy. Future work will allow detection of units to automatically merge continuous data and application of the algorithm to other data formats, including databases.

On three dimensional object recognition and pose-determination: An abstraction based approach. Ph.D. Thesis - Michigan Univ. Final Report

NASA Technical Reports Server (NTRS)

Quek, Kok How Francis

1990-01-01

A method of computing reliable Gaussian and mean curvature sign-map descriptors from the polynomial approximation of surfaces was demonstrated. Such descriptors which are invariant under perspective variation are suitable for hypothesis generation. A means for determining the pose of constructed geometric forms whose algebraic surface descriptors are nonlinear in terms of their orienting parameters was developed. This was done by means of linear functions which are capable of approximating nonlinear forms and determining their parameters. It was shown that biquadratic surfaces are suitable companion linear forms for cylindrical approximation and parameter estimation. The estimates provided the initial parametric approximations necessary for a nonlinear regression stage to fine tune the estimates by fitting the actual nonlinear form to the data. A hypothesis-based split-merge algorithm for extraction and pose determination of cylinders and planes which merge smoothly into other surfaces was developed. It was shown that all split-merge algorithms are hypothesis-based. A finite-state algorithm for the extraction of the boundaries of run-length regions was developed. The computation takes advantage of the run list topology and boundary direction constraints implicit in the run-length encoding.

Synthesizer: Expediting synthesis studies from context-free data with information retrieval techniques

PubMed Central

Gumm, Jordan; Fertig, Benjamin; Thessen, Anne; Kennish, Michael J.; Chavan, Sameer; Marchionni, Luigi; Xia, Xiaoxin; Shankrit, Shambhavi; Fertig, Elana J.

2017-01-01

Scientists have unprecedented access to a wide variety of high-quality datasets. These datasets, which are often independently curated, commonly use unstructured spreadsheets to store their data. Standardized annotations are essential to perform synthesis studies across investigators, but are often not used in practice. Therefore, accurately combining records in spreadsheets from differing studies requires tedious and error-prone human curation. These efforts result in a significant time and cost barrier to synthesis research. We propose an information retrieval inspired algorithm, Synthesize, that merges unstructured data automatically based on both column labels and values. Application of the Synthesize algorithm to cancer and ecological datasets had high accuracy (on the order of 85–100%). We further implement Synthesize in an open source web application, Synthesizer (https://github.com/lisagandy/synthesizer). The software accepts input as spreadsheets in comma separated value (CSV) format, visualizes the merged data, and outputs the results as a new spreadsheet. Synthesizer includes an easy to use graphical user interface, which enables the user to finish combining data and obtain perfect accuracy. Future work will allow detection of units to automatically merge continuous data and application of the algorithm to other data formats, including databases. PMID:28437440

A fast 3D region growing approach for CT angiography applications

NASA Astrophysics Data System (ADS)

Ye, Zhen; Lin, Zhongmin; Lu, Cheng-chang

2004-05-01

Region growing is one of the most popular methods for low-level image segmentation. Many researches on region growing have focused on the definition of the homogeneity criterion or growing and merging criterion. However, one disadvantage of conventional region growing is redundancy. It requires a large memory usage, and the computation-efficiency is very low especially for 3D images. To overcome this problem, a non-recursive single-pass 3D region growing algorithm named SymRG is implemented and successfully applied to 3D CT angiography (CTA) applications for vessel segmentation and bone removal. The method consists of three steps: segmenting one-dimensional regions of each row; doing region merging to adjacent rows to obtain the region segmentation of each slice; and doing region merging to adjacent slices to obtain the final region segmentation of 3D images. To improve the segmentation speed for very large volume 3D CTA images, this algorithm is applied repeatedly to newly updated local cubes. The next new cube can be estimated by checking isolated segmented regions on all 6 faces of the current local cube. This local non-recursive 3D region-growing algorithm is memory-efficient and computation-efficient. Clinical testings of this algorithm on Brain CTA show this technique could effectively remove whole skull, most of the bones on the skull base, and reveal the cerebral vascular structures clearly.

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Buluc, Aydn; Pothen, Alex

It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting pathmore » is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.« less

Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting

DOE PAGES

Azad, Ariful; Buluc, Aydn; Pothen, Alex

2016-03-24

It is difficult to obtain high performance when computing matchings on parallel processors because matching algorithms explicitly or implicitly search for paths in the graph, and when these paths become long, there is little concurrency. In spite of this limitation, we present a new algorithm and its shared-memory parallelization that achieves good performance and scalability in computing maximum cardinality matchings in bipartite graphs. This algorithm searches for augmenting paths via specialized breadth-first searches (BFS) from multiple source vertices, hence creating more parallelism than single source algorithms. Algorithms that employ multiple-source searches cannot discard a search tree once no augmenting pathmore » is discovered from the tree, unlike algorithms that rely on single-source searches. We describe a novel tree-grafting method that eliminates most of the redundant edge traversals resulting from this property of multiple-source searches. We also employ the recent direction-optimizing BFS algorithm as a subroutine to discover augmenting paths faster. Our algorithm compares favorably with the current best algorithms in terms of the number of edges traversed, the average augmenting path length, and the number of iterations. Here, we provide a proof of correctness for our algorithm. Our NUMA-aware implementation is scalable to 80 threads of an Intel multiprocessor and to 240 threads on an Intel Knights Corner coprocessor. On average, our parallel algorithm runs an order of magnitude faster than the fastest algorithms available. The performance improvement is more significant on graphs with small matching number.« less

Stereo-vision-based terrain mapping for off-road autonomous navigation

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-05-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as nogo regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Huertas, Andres; Matthies, Larry H.

2009-01-01

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

Path Planning Method in Multi-obstacle Marine Environment

NASA Astrophysics Data System (ADS)

Zhang, Jinpeng; Sun, Hanxv

2017-12-01

In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.

Modified multiblock partial least squares path modeling algorithm with backpropagation neural networks approach

NASA Astrophysics Data System (ADS)

Yuniarto, Budi; Kurniawan, Robert

2017-03-01

PLS Path Modeling (PLS-PM) is different from covariance based SEM, where PLS-PM use an approach based on variance or component, therefore, PLS-PM is also known as a component based SEM. Multiblock Partial Least Squares (MBPLS) is a method in PLS regression which can be used in PLS Path Modeling which known as Multiblock PLS Path Modeling (MBPLS-PM). This method uses an iterative procedure in its algorithm. This research aims to modify MBPLS-PM with Back Propagation Neural Network approach. The result is MBPLS-PM algorithm can be modified using the Back Propagation Neural Network approach to replace the iterative process in backward and forward step to get the matrix t and the matrix u in the algorithm. By modifying the MBPLS-PM algorithm using Back Propagation Neural Network approach, the model parameters obtained are relatively not significantly different compared to model parameters obtained by original MBPLS-PM algorithm.

ELASTIC NET FOR COX'S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM.

PubMed

Wu, Yichao

2012-01-01

For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox's proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox's proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1989-01-01

Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.

A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

PubMed

Moschini, Ugo; Meijster, Arnold; Wilkinson, Michael H F

2018-03-01

Max-trees, or component trees, are graph structures that represent the connected components of an image in a hierarchical way. Nowadays, many application fields rely on images with high-dynamic range or floating point values. Efficient sequential algorithms exist to build trees and compute attributes for images of any bit depth. However, we show that the current parallel algorithms perform poorly already with integers at bit depths higher than 16 bits per pixel. We propose a parallel method combining the two worlds of flooding and merging max-tree algorithms. First, a pilot max-tree of a quantized version of the image is built in parallel using a flooding method. Later, this structure is used in a parallel leaf-to-root approach to compute efficiently the final max-tree and to drive the merging of the sub-trees computed by the threads. We present an analysis of the performance both on simulated and actual 2D images and 3D volumes. Execution times are about better than the fastest sequential algorithm and speed-up goes up to on 64 threads.

Routing and spectrum assignment based on ant colony optimization of minimum consecutiveness loss in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Tian, Qinghua; Zhang, Qi; Rao, Lan; Tian, Feng; Luo, Biao; Liu, Yingjun; Tang, Bao

2016-10-01

Elastic Optical Networks are considered to be a promising technology for future high-speed network. In this paper, we propose a RSA algorithm based on the ant colony optimization of minimum consecutiveness loss (ACO-MCL). Based on the effect of the spectrum consecutiveness loss on the pheromone in the ant colony optimization, the path and spectrum of the minimal impact on the network are selected for the service request. When an ant arrives at the destination node from the source node along a path, we assume that this path is selected for the request. We calculate the consecutiveness loss of candidate-neighbor link pairs along this path after the routing and spectrum assignment. Then, the networks update the pheromone according to the value of the consecutiveness loss. We save the path with the smallest value. After multiple iterations of the ant colony optimization, the final selection of the path is assigned for the request. The algorithms are simulated in different networks. The results show that ACO-MCL algorithm performs better in blocking probability and spectrum efficiency than other algorithms. Moreover, the ACO-MCL algorithm can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness. Compared with other algorithms, the ACO-MCL algorithm can reduce the blocking rate by at least 5.9% in heavy load.

Path generation algorithm for UML graphic modeling of aerospace test software

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Chen, Chao

2018-03-01

Aerospace traditional software testing engineers are based on their own work experience and communication with software development personnel to complete the description of the test software, manual writing test cases, time-consuming, inefficient, loopholes and more. Using the high reliability MBT tools developed by our company, the one-time modeling can automatically generate test case documents, which is efficient and accurate. UML model to describe the process accurately express the need to rely on the path is reached, the existing path generation algorithm are too simple, cannot be combined into a path and branch path with loop, or too cumbersome, too complicated arrangement generates a path is meaningless, for aerospace software testing is superfluous, I rely on our experience of ten load space, tailor developed a description of aerospace software UML graphics path generation algorithm.

Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

PubMed Central

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-01-01

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

Using State Merging and State Pruning to Address the Path Explosion Problem Faced by Symbolic Execution

DTIC Science & Technology

2014-06-19

urgent and compelling. Recent efforts in this area automate program analysis techniques using model checking and symbolic execution [2, 5–7]. These...bounded model checking tool for x86 binary programs developed at the Air Force Institute of Technology (AFIT). Jiseki creates a bit-vector logic model based...assume there are n different paths through the function foo . The program could potentially call the function foo a bound number of times, resulting in n

Soldier detection using unattended acoustic and seismic sensors

NASA Astrophysics Data System (ADS)

Naz, P.; Hengy, S.; Hamery, P.

2012-06-01

During recent military conflicts, as well as for security interventions, the urban zone has taken a preponderant place. Studies have been initiated in national and in international programs to stimulate the technical innovations for these specific scenarios. For example joint field experiments have been organized by the NATO group SET-142 to evaluate the capability for the detection and localization of snipers, mortars or artillery guns using acoustic devices. Another important operational need corresponds to the protection of military sites or buildings. In this context, unattended acoustic and seismic sensors are envisaged to contribute to the survey of specific points by the detection of approaching enemy soldiers. This paper describes some measurements done in an anechoic chamber and in free field to characterize typical sounds generated by the soldier activities (walking, crawling, weapon handling, radio communication, clothing noises...). Footstep, speech and some specific impulsive sounds are detectable at various distances from the source. Such detection algorithms may be easily merged with the existing weapon firing detection algorithms to provide a more generic "battlefield acoustic" early warning system. Results obtained in various conditions (grassy terrain, gravel path, road, forest) will be presented. A method to extrapolate the distances of detection has been developed, based on an acoustic propagation model and applied to the laboratory measurements.

Algorithms and Sensors for Small Robot Path Following

NASA Technical Reports Server (NTRS)

Hogg, Robert W.; Rankin, Arturo L.; Roumeliotis, Stergios I.; McHenry, Michael C.; Helmick, Daniel M.; Bergh, Charles F.; Matthies, Larry

2002-01-01

Tracked mobile robots in the 20 kg size class are under development for applications in urban reconnaissance. For efficient deployment, it is desirable for teams of robots to be able to automatically execute path following behaviors, with one or more followers tracking the path taken by a leader. The key challenges to enabling such a capability are (l) to develop sensor packages for such small robots that can accurately determine the path of the leader and (2) to develop path following algorithms for the subsequent robots. To date, we have integrated gyros, accelerometers, compass/inclinometers, odometry, and differential GPS into an effective sensing package. This paper describes the sensor package, sensor processing algorithm, and path tracking algorithm we have developed for the leader/follower problem in small robots and shows the result of performance characterization of the system. We also document pragmatic lessons learned about design, construction, and electromagnetic interference issues particular to the performance of state sensors on small robots.

Unsupervised tattoo segmentation combining bottom-up and top-down cues

NASA Astrophysics Data System (ADS)

Allen, Josef D.; Zhao, Nan; Yuan, Jiangbo; Liu, Xiuwen

2011-06-01

Tattoo segmentation is challenging due to the complexity and large variance in tattoo structures. We have developed a segmentation algorithm for finding tattoos in an image. Our basic idea is split-merge: split each tattoo image into clusters through a bottom-up process, learn to merge the clusters containing skin and then distinguish tattoo from the other skin via top-down prior in the image itself. Tattoo segmentation with unknown number of clusters is transferred to a figureground segmentation. We have applied our segmentation algorithm on a tattoo dataset and the results have shown that our tattoo segmentation system is efficient and suitable for further tattoo classification and retrieval purpose.

Merging NLO multi-jet calculations with improved unitarization

NASA Astrophysics Data System (ADS)

Bellm, Johannes; Gieseke, Stefan; Plätzer, Simon

2018-03-01

We present an algorithm to combine multiple matrix elements at LO and NLO with a parton shower. We build on the unitarized merging paradigm. The inclusion of higher orders and multiplicities reduce the scale uncertainties for observables sensitive to hard emissions, while preserving the features of inclusive quantities. The combination allows further soft and collinear emissions to be predicted by the all-order parton-shower approximation. We inspect the impact of terms that are formally but not parametrically negligible. We present results for a number of collider observables where multiple jets are observed, either on their own or in the presence of additional uncoloured particles. The algorithm is implemented in the event generator Herwig.

A modified PATH algorithm rapidly generates transition states comparable to those found by other well established algorithms

PubMed Central

Chandrasekaran, Srinivas Niranj; Das, Jhuma; Dokholyan, Nikolay V.; Carter, Charles W.

2016-01-01

PATH rapidly computes a path and a transition state between crystal structures by minimizing the Onsager-Machlup action. It requires input parameters whose range of values can generate different transition-state structures that cannot be uniquely compared with those generated by other methods. We outline modifications to estimate these input parameters to circumvent these difficulties and validate the PATH transition states by showing consistency between transition-states derived by different algorithms for unrelated protein systems. Although functional protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. PMID:26958584

Trajectory Generation and Path Planning for Autonomous Aerobots

NASA Technical Reports Server (NTRS)

Sharma, Shivanjli; Kulczycki, Eric A.; Elfes, Alberto

2007-01-01

This paper presents global path planning algorithms for the Titan aerobot based on user defined waypoints in 2D and 3D space. The algorithms were implemented using information obtained through a planner user interface. The trajectory planning algorithms were designed to accurately represent the aerobot's characteristics, such as minimum turning radius. Additionally, trajectory planning techniques were implemented to allow for surveying of a planar area based solely on camera fields of view, airship altitude, and the location of the planar area's perimeter. The developed paths allow for planar navigation and three-dimensional path planning. These calculated trajectories are optimized to produce the shortest possible path while still remaining within realistic bounds of airship dynamics.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis.

PubMed

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M

2016-07-14

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x'; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

NASA Astrophysics Data System (ADS)

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M.

2016-07-01

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x'; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

Data parallel sorting for particle simulation

NASA Technical Reports Server (NTRS)

Dagum, Leonardo

1992-01-01

Sorting on a parallel architecture is a communications intensive event which can incur a high penalty in applications where it is required. In the case of particle simulation, only integer sorting is necessary, and sequential implementations easily attain the minimum performance bound of O (N) for N particles. Parallel implementations, however, have to cope with the parallel sorting problem which, in addition to incurring a heavy communications cost, can make the minimun performance bound difficult to attain. This paper demonstrates how the sorting problem in a particle simulation can be reduced to a merging problem, and describes an efficient data parallel algorithm to solve this merging problem in a particle simulation. The new algorithm is shown to be optimal under conditions usual for particle simulation, and its fieldwise implementation on the Connection Machine is analyzed in detail. The new algorithm is about four times faster than a fieldwise implementation of radix sort on the Connection Machine.

Automated cloud screening of AVHRR imagery using split-and-merge clustering

NASA Technical Reports Server (NTRS)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Extraction of edge-based and region-based features for object recognition

NASA Astrophysics Data System (ADS)

Coutts, Benjamin; Ravi, Srinivas; Hu, Gongzhu; Shrikhande, Neelima

1993-08-01

One of the central problems of computer vision is object recognition. A catalogue of model objects is described as a set of features such as edges and surfaces. The same features are extracted from the scene and matched against the models for object recognition. Edges and surfaces extracted from the scenes are often noisy and imperfect. In this paper algorithms are described for improving low level edge and surface features. Existing edge extraction algorithms are applied to the intensity image to obtain edge features. Initial edges are traced by following directions of the current contour. These are improved by using corresponding depth and intensity information for decision making at branch points. Surface fitting routines are applied to the range image to obtain planar surface patches. An algorithm of region growing is developed that starts with a coarse segmentation and uses quadric surface fitting to iteratively merge adjacent regions into quadric surfaces based on approximate orthogonal distance regression. Surface information obtained is returned to the edge extraction routine to detect and remove fake edges. This process repeats until no more merging or edge improvement can take place. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested using the merging criteria. Results appeared quite encouraging.

Greedy algorithms in disordered systems

NASA Astrophysics Data System (ADS)

Duxbury, P. M.; Dobrin, R.

1999-08-01

We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.

Bringing Algorithms to Life: Cooperative Computing Activities Using Students as Processors.

ERIC Educational Resources Information Center

Bachelis, Gregory F.; And Others

1994-01-01

Presents cooperative computing activities in which each student plays the role of a switch or processor and acts out algorithms. Includes binary counting, finding the smallest card in a deck, sorting by selection and merging, adding and multiplying large numbers, and sieving for primes. (16 references) (Author/MKR)

ELASTIC NET FOR COX’S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM

PubMed Central

Wu, Yichao

2012-01-01

For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox’s proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox’s proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems. PMID:23226932

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Research on Taxiway Path Optimization Based on Conflict Detection

PubMed Central

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485

Research on Taxiway Path Optimization Based on Conflict Detection.

PubMed

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems

NASA Astrophysics Data System (ADS)

Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui

2017-07-01

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.

Autonomous Navigation by a Mobile Robot

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand

2005-01-01

ROAMAN is a computer program for autonomous navigation of a mobile robot on a long (as much as hundreds of meters) traversal of terrain. Developed for use aboard a robotic vehicle (rover) exploring the surface of a remote planet, ROAMAN could also be adapted to similar use on terrestrial mobile robots. ROAMAN implements a combination of algorithms for (1) long-range path planning based on images acquired by mast-mounted, wide-baseline stereoscopic cameras, and (2) local path planning based on images acquired by body-mounted, narrow-baseline stereoscopic cameras. The long-range path-planning algorithm autonomously generates a series of waypoints that are passed to the local path-planning algorithm, which plans obstacle-avoiding legs between the waypoints. Both the long- and short-range algorithms use an occupancy-grid representation in computations to detect obstacles and plan paths. Maps that are maintained by the long- and short-range portions of the software are not shared because substantial localization errors can accumulate during any long traverse. ROAMAN is not guaranteed to generate an optimal shortest path, but does maintain the safety of the rover.

Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

Mapping chemicals in air using an environmental CAT scanning system: evaluation of algorithms

NASA Astrophysics Data System (ADS)

Samanta, A.; Todd, L. A.

A new technique is being developed which creates near real-time maps of chemical concentrations in air for environmental and occupational environmental applications. This technique, we call Environmental CAT Scanning, combines the real-time measuring technique of open-path Fourier transform infrared spectroscopy with the mapping capabilitites of computed tomography to produce two-dimensional concentration maps. With this system, a network of open-path measurements is obtained over an area; measurements are then processed using a tomographic algorithm to reconstruct the concentrations. This research focussed on the process of evaluating and selecting appropriate reconstruction algorithms, for use in the field, by using test concentration data from both computer simultation and laboratory chamber studies. Four algorithms were tested using three types of data: (1) experimental open-path data from studies that used a prototype opne-path Fourier transform/computed tomography system in an exposure chamber; (2) synthetic open-path data generated from maps created by kriging point samples taken in the chamber studies (in 1), and; (3) synthetic open-path data generated using a chemical dispersion model to create time seires maps. The iterative algorithms used to reconstruct the concentration data were: Algebraic Reconstruction Technique without Weights (ART1), Algebraic Reconstruction Technique with Weights (ARTW), Maximum Likelihood with Expectation Maximization (MLEM) and Multiplicative Algebraic Reconstruction Technique (MART). Maps were evaluated quantitatively and qualitatively. In general, MART and MLEM performed best, followed by ARTW and ART1. However, algorithm performance varied under different contaminant scenarios. This study showed the importance of using a variety of maps, particulary those generated using dispersion models. The time series maps provided a more rigorous test of the algorithms and allowed distinctions to be made among the algorithms. A comprehensive evaluation of algorithms, for the environmental application of tomography, requires the use of a battery of test concentration data before field implementation, which models reality and tests the limits of the algorithms.

Synthetic aperture radar/LANDSAT MSS image registration

NASA Technical Reports Server (NTRS)

Maurer, H. E. (Editor); Oberholtzer, J. D. (Editor); Anuta, P. E. (Editor)

1979-01-01

Algorithms and procedures necessary to merge aircraft synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) imagery were determined. The design of a SAR/LANDSAT data merging system was developed. Aircraft SAR images were registered to the corresponding LANDSAT MSS scenes and were the subject of experimental investigations. Results indicate that the registration of SAR imagery with LANDSAT MSS imagery is feasible from a technical viewpoint, and useful from an information-content viewpoint.

Bayesian approach for peak detection in two-dimensional chromatography.

PubMed

Vivó-Truyols, Gabriel

2012-03-20

A new method for peak detection in two-dimensional chromatography is presented. In a first step, the method starts with a conventional one-dimensional peak detection algorithm to detect modulated peaks. In a second step, a sophisticated algorithm is constructed to decide which of the individual one-dimensional peaks have been originated from the same compound and should then be arranged in a two-dimensional peak. The merging algorithm is based on Bayesian inference. The user sets prior information about certain parameters (e.g., second-dimension retention time variability, first-dimension band broadening, chromatographic noise). On the basis of these priors, the algorithm calculates the probability of myriads of peak arrangements (i.e., ways of merging one-dimensional peaks), finding which of them holds the highest value. Uncertainty in each parameter can be accounted by adapting conveniently its probability distribution function, which in turn may change the final decision of the most probable peak arrangement. It has been demonstrated that the Bayesian approach presented in this paper follows the chromatographers' intuition. The algorithm has been applied and tested with LC × LC and GC × GC data and takes around 1 min to process chromatograms with several thousands of peaks.

A Clustering Algorithm for Ecological Stream Segment Identification from Spatially Extensive Digital Databases

NASA Astrophysics Data System (ADS)

Brenden, T. O.; Clark, R. D.; Wiley, M. J.; Seelbach, P. W.; Wang, L.

2005-05-01

Remote sensing and geographic information systems have made it possible to attribute variables for streams at increasingly detailed resolutions (e.g., individual river reaches). Nevertheless, management decisions still must be made at large scales because land and stream managers typically lack sufficient resources to manage on an individual reach basis. Managers thus require a method for identifying stream management units that are ecologically similar and that can be expected to respond similarly to management decisions. We have developed a spatially-constrained clustering algorithm that can merge neighboring river reaches with similar ecological characteristics into larger management units. The clustering algorithm is based on the Cluster Affinity Search Technique (CAST), which was developed for clustering gene expression data. Inputs to the clustering algorithm are the neighbor relationships of the reaches that comprise the digital river network, the ecological attributes of the reaches, and an affinity value, which identifies the minimum similarity for merging river reaches. In this presentation, we describe the clustering algorithm in greater detail and contrast its use with other methods (expert opinion, classification approach, regular clustering) for identifying management units using several Michigan watersheds as a backdrop.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

PubMed

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path

PubMed Central

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective. PMID:27490901

From the physics of interacting polymers to optimizing routes on the London Underground

PubMed Central

Yeung, Chi Ho; Saad, David; Wong, K. Y. Michael

2013-01-01

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise. PMID:23898198

From the physics of interacting polymers to optimizing routes on the London Underground.

PubMed

Yeung, Chi Ho; Saad, David; Wong, K Y Michael

2013-08-20

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise.

Trajectory generation for an on-road autonomous vehicle

NASA Astrophysics Data System (ADS)

Horst, John; Barbera, Anthony

2006-05-01

We describe an algorithm that generates a smooth trajectory (position, velocity, and acceleration at uniformly sampled instants of time) for a car-like vehicle autonomously navigating within the constraints of lanes in a road. The technique models both vehicle paths and lane segments as straight line segments and circular arcs for mathematical simplicity and elegance, which we contrast with cubic spline approaches. We develop the path in an idealized space, warp the path into real space and compute path length, generate a one-dimensional trajectory along the path length that achieves target speeds and positions, and finally, warp, translate, and rotate the one-dimensional trajectory points onto the path in real space. The algorithm moves a vehicle in lane safely and efficiently within speed and acceleration maximums. The algorithm functions in the context of other autonomous driving functions within a carefully designed vehicle control hierarchy.

Optimal solution for travelling salesman problem using heuristic shortest path algorithm with imprecise arc length

NASA Astrophysics Data System (ADS)

Bakar, Sumarni Abu; Ibrahim, Milbah

2017-08-01

The shortest path problem is a popular problem in graph theory. It is about finding a path with minimum length between a specified pair of vertices. In any network the weight of each edge is usually represented in a form of crisp real number and subsequently the weight is used in the calculation of shortest path problem using deterministic algorithms. However, due to failure, uncertainty is always encountered in practice whereby the weight of edge of the network is uncertain and imprecise. In this paper, a modified algorithm which utilized heuristic shortest path method and fuzzy approach is proposed for solving a network with imprecise arc length. Here, interval number and triangular fuzzy number in representing arc length of the network are considered. The modified algorithm is then applied to a specific example of the Travelling Salesman Problem (TSP). Total shortest distance obtained from this algorithm is then compared with the total distance obtained from traditional nearest neighbour heuristic algorithm. The result shows that the modified algorithm can provide not only on the sequence of visited cities which shown to be similar with traditional approach but it also provides a good measurement of total shortest distance which is lesser as compared to the total shortest distance calculated using traditional approach. Hence, this research could contribute to the enrichment of methods used in solving TSP.

A computational geometry approach to pore network construction for granular packings

NASA Astrophysics Data System (ADS)

van der Linden, Joost H.; Sufian, Adnan; Narsilio, Guillermo A.; Russell, Adrian R.; Tordesillas, Antoinette

2018-03-01

Pore network construction provides the ability to characterize and study the pore space of inhomogeneous and geometrically complex granular media in a range of scientific and engineering applications. Various approaches to the construction have been proposed, however subtle implementational details are frequently omitted, open access to source code is limited, and few studies compare multiple algorithms in the context of a specific application. This study presents, in detail, a new pore network construction algorithm, and provides a comprehensive comparison with two other, well-established Delaunay triangulation-based pore network construction methods. Source code is provided to encourage further development. The proposed algorithm avoids the expensive non-linear optimization procedure in existing Delaunay approaches, and is robust in the presence of polydispersity. Algorithms are compared in terms of structural, geometrical and advanced connectivity parameters, focusing on the application of fluid flow characteristics. Sensitivity of the various networks to permeability is assessed through network (Stokes) simulations and finite-element (Navier-Stokes) simulations. Results highlight strong dependencies of pore volume, pore connectivity, throat geometry and fluid conductance on the degree of tetrahedra merging and the specific characteristics of the throats targeted by the merging algorithm. The paper concludes with practical recommendations on the applicability of the three investigated algorithms.

A two-stage path planning approach for multiple car-like robots based on PH curves and a modified harmony search algorithm

NASA Astrophysics Data System (ADS)

Zeng, Wenhui; Yi, Jin; Rao, Xiao; Zheng, Yun

2017-11-01

In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the task's completion time. Accordingly, a new approach based on Pythagorean Hodograph (PH) curves and Modified Harmony Search algorithm is proposed to solve the two-stage path-planning problem subject to kinematic constraints such as velocity, acceleration, and minimum turning radius. First, a method of path planning based on PH curves for a single robot is proposed. Second, a mathematical model of the two-stage path-planning problem for multiple car-like robots with variable motion subject to kinematic constraints is constructed that the first-stage minimizes the total length of all paths and the second-stage minimizes the task's completion time. Finally, a modified harmony search algorithm is applied to solve the two-stage optimization problem. A set of experiments demonstrate the effectiveness of the proposed approach.

Four-dimensional guidance algorithms for aircraft in an air traffic control environment

NASA Technical Reports Server (NTRS)

Pecsvaradi, T.

1975-01-01

Theoretical development and computer implementation of three guidance algorithms are presented. From a small set of input parameters the algorithms generate the ground track, altitude profile, and speed profile required to implement an experimental 4-D guidance system. Given a sequence of waypoints that define a nominal flight path, the first algorithm generates a realistic, flyable ground track consisting of a sequence of straight line segments and circular arcs. Each circular turn is constrained by the minimum turning radius of the aircraft. The ground track and the specified waypoint altitudes are used as inputs to the second algorithm which generates the altitude profile. The altitude profile consists of piecewise constant flight path angle segments, each segment lying within specified upper and lower bounds. The third algorithm generates a feasible speed profile subject to constraints on the rate of change in speed, permissible speed ranges, and effects of wind. Flight path parameters are then combined into a chronological sequence to form the 4-D guidance vectors. These vectors can be used to drive the autopilot/autothrottle of the aircraft so that a 4-D flight path could be tracked completely automatically; or these vectors may be used to drive the flight director and other cockpit displays, thereby enabling the pilot to track a 4-D flight path manually.

Optimization of Ocean Color Algorithms: Application to Satellite Data Merging

NASA Technical Reports Server (NTRS)

Ritorena, Stephane; Siegel, David A.; Morel, Andre

2004-01-01

The objective of the program is to develop and validate a procedure for ocean color data merging, which is one of the major goals of the SIMBIOS project. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances L((sub wN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) It works with single or multiple data sources regardless of their specific bands; 2) It exploits band redundancies and band differences; 3) It accounts for uncertainties in the L((sub wN)(lambda)) data; 4) It provides uncertainty estimates for the retrieved variables.

A Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2007-01-01

This document describes an algorithm for the generation of a four dimensional aircraft trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival Route (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. Wind data at each waypoint are also inputs into this algorithm. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint.

Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity

NASA Astrophysics Data System (ADS)

Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.

2017-12-01

The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for obtaining inter-sensor climate data record continuity.

Evolvable Neuronal Paths: A Novel Basis for Information and Search in the Brain

PubMed Central

Fernando, Chrisantha; Vasas, Vera; Szathmáry, Eörs; Husbands, Phil

2011-01-01

We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard ‘genetic’ informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain. PMID:21887266

Short paths in expander graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleinberg, J.; Rubinfeld, R.

Graph expansion has proved to be a powerful general tool for analyzing the behavior of routing algorithms and the interconnection networks on which they run. We develop new routing algorithms and structural results for bounded-degree expander graphs. Our results are unified by the fact that they are all based upon, and extend, a body of work asserting that expanders are rich in short, disjoint paths. In particular, our work has consequences for the disjoint paths problem, multicommodify flow, and graph minor containment. We show: (i) A greedy algorithm for approximating the maximum disjoint paths problem achieves a polylogarithmic approximation ratiomore » in bounded-degree expanders. Although our algorithm is both deterministic and on-line, its performance guarantee is an improvement over previous bounds in expanders. (ii) For a multicommodily flow problem with arbitrary demands on a bounded-degree expander, there is a (1 + {epsilon})-optimal solution using only flow paths of polylogarithmic length. It follows that the multicommodity flow algorithm of Awerbuch and Leighton runs in nearly linear time per commodity in expanders. Our analysis is based on establishing the following: given edge weights on an expander G, one can increase some of the weights very slightly so the resulting shortest-path metric is smooth - the min-weight path between any pair of nodes uses a polylogarithmic number of edges. (iii) Every bounded-degree expander on n nodes contains every graph with O(n/log{sup O(1)} n) nodes and edges as a minor.« less

An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

PubMed

Li, Bai; Gong, Li-gang; Yang, Wen-lun

2014-01-01

Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

Analysis and Simulation of the Simplified Aircraft-Based Paired Approach Concept With the ALAS Alerting Algorithm in Conjunction With Echelon and Offset Strategies

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo; Madden, Michael M.; Butler, Rickey W.; Perry, Raleigh B.

2014-01-01

This report presents analytical and simulation results of an investigation into proposed operational concepts for closely spaced parallel runways, including the Simplified Aircraft-based Paired Approach (SAPA) with alerting and an escape maneuver, MITRE?s echelon spacing and no escape maneuver, and a hybrid concept aimed at lowering the visibility minima. We found that the SAPA procedure can be used at 950 ft separations or higher with next-generation avionics and that 1150 ft separations or higher is feasible with current-rule compliant ADS-B OUT. An additional 50 ft reduction in runway separation for the SAPA procedure is possible if different glideslopes are used. For the echelon concept we determined that current generation aircraft cannot conduct paired approaches on parallel paths using echelon spacing on runways less than 1400 ft apart and next-generation aircraft will not be able to conduct paired approach on runways less than 1050 ft apart. The hybrid concept added alerting and an escape maneuver starting 1 NM from the threshold when flying the echelon concept. This combination was found to be effective, but the probability of a collision can be seriously impacted if the turn component of the escape maneuver has to be disengaged near the ground (e.g. 300 ft or below) due to airport buildings and surrounding terrain. We also found that stabilizing the approach path in the straight-in segment was only possible if the merge point was at least 1.5 to 2 NM from the threshold unless the total system error can be sufficiently constrained on the offset path and final turn.

Nearby Search Indekos Based Android Using A Star (A*) Algorithm

NASA Astrophysics Data System (ADS)

Siregar, B.; Nababan, EB; Rumahorbo, JA; Andayani, U.; Fahmi, F.

2018-03-01

Indekos or rented room is a temporary residence for months or years. Society of academicians who come from out of town need a temporary residence, such as Indekos or rented room during their education, teaching, or duties. They are often found difficulty in finding a Indekos because lack of information about the Indekos. Besides, new society of academicians don’t recognize the areas around the campus and desire the shortest path from Indekos to get to the campus. The problem can be solved by implementing A Star (A*) algorithm. This algorithm is one of the shortest path algorithm to a finding shortest path from campus to the Indekos application, where the faculties in the campus as the starting point of the finding. Determination of the starting point used in this study aims to allow students to determine the starting point in finding the Indekos. The mobile based application facilitates the finding anytime and anywhere. Based on the experimental results, A* algorithm can find the shortest path with 86,67% accuracy.

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent.

PubMed

Simon, Noah; Friedman, Jerome; Hastie, Trevor; Tibshirani, Rob

2011-03-01

We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of ℓ 1 and ℓ 2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a regularization path. We demonstrate the efficacy of our algorithm on real and simulated data sets, and find considerable speedup between our algorithm and competing methods.

Automated and Cooperative Vehicle Merging at Highway On-Ramps

DOE PAGES

Rios-Torres, Jackeline; Malikopoulos, Andreas A.

2016-08-05

Recognition of necessities of connected and automated vehicles (CAVs) is gaining momentum. CAVs can improve both transportation network efficiency and safety through control algorithms that can harmonically use all existing information to coordinate the vehicles. This paper addresses the problem of optimally coordinating CAVs at merging roadways to achieve smooth traffic flow without stop-and-go driving. Here we present an optimization framework and an analytical closed-form solution that allows online coordination of vehicles at merging zones. The effectiveness of the efficiency of the proposed solution is validated through a simulation, and it is shown that coordination of vehicles can significantly reducemore » both fuel consumption and travel time.« less

A Revised Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2010-01-01

This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates descent Mach values that are different from the cruise Mach values. Wind data at each waypoint are also inputs into this algorithm. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint.

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.

PubMed

Altarelli, Fabrizio; Braunstein, Alfredo; Dall'Asta, Luca; De Bacco, Caterina; Franz, Silvio

2015-01-01

We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by incorporating under a unique framework both traffic optimization and total path length minimization. The computation of the cavity equations can be performed efficiently by exploiting a mapping of a generalized edge-disjoint path problem on a star graph onto a weighted maximum matching problem. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behavior of both the number of paths to be accommodated and their minimum total length.

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing

PubMed Central

2015-01-01

We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by incorporating under a unique framework both traffic optimization and total path length minimization. The computation of the cavity equations can be performed efficiently by exploiting a mapping of a generalized edge-disjoint path problem on a star graph onto a weighted maximum matching problem. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behavior of both the number of paths to be accommodated and their minimum total length. PMID:26710102

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Bayard, David S.; Kohen, Hamid

1997-01-01

This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

PubMed Central

Jiang, Peng; Li, Deshi; Sun, Tao

2017-01-01

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region. PMID:28925960

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs.

PubMed

Wang, Xiaoliang; Jiang, Peng; Li, Deshi; Sun, Tao

2017-09-19

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

An adaptive multi-level simulation algorithm for stochastic biological systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lester, C., E-mail: lesterc@maths.ox.ac.uk; Giles, M. B.; Baker, R. E.

2015-01-14

Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, “Multi-level Montemore » Carlo for continuous time Markov chains, with applications in biochemical kinetics,” SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the efficiency of our method using a number of examples.« less

Image-based path planning for automated virtual colonoscopy navigation

NASA Astrophysics Data System (ADS)

Hong, Wei

2008-03-01

Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.

Development and validation of an electronic phenotyping algorithm for chronic kidney disease

PubMed Central

Nadkarni, Girish N; Gottesman, Omri; Linneman, James G; Chase, Herbert; Berg, Richard L; Farouk, Samira; Nadukuru, Rajiv; Lotay, Vaneet; Ellis, Steve; Hripcsak, George; Peissig, Peggy; Weng, Chunhua; Bottinger, Erwin P

2014-01-01

Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular disease and end stage renal disease. CKD is frequently undiagnosed and patients are unaware, hampering intervention. A tool for accurate and timely identification of CKD from electronic medical records (EMR) could improve healthcare quality and identify patients for research. As members of eMERGE (electronic medical records and genomics) Network, we developed an automated phenotyping algorithm that can be deployed to identify rapidly diabetic and/or hypertensive CKD cases and controls in health systems with EMRs It uses diagnostic codes, laboratory results, medication and blood pressure records, and textual information culled from notes. Validation statistics demonstrated positive predictive values of 96% and negative predictive values of 93.3. Similar results were obtained on implementation by two independent eMERGE member institutions. The algorithm dramatically outperformed identification by ICD-9-CM codes with 63% positive and 54% negative predictive values, respectively. PMID:25954398

Stereo Image Dense Matching by Integrating Sift and Sgm Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Y.; Song, Y.; Lu, J.

2018-05-01

Semi-global matching(SGM) performs the dynamic programming by treating the different path directions equally. It does not consider the impact of different path directions on cost aggregation, and with the expansion of the disparity search range, the accuracy and efficiency of the algorithm drastically decrease. This paper presents a dense matching algorithm by integrating SIFT and SGM. It takes the successful matching pairs matched by SIFT as control points to direct the path in dynamic programming with truncating error propagation. Besides, matching accuracy can be improved by using the gradient direction of the detected feature points to modify the weights of the paths in different directions. The experimental results based on Middlebury stereo data sets and CE-3 lunar data sets demonstrate that the proposed algorithm can effectively cut off the error propagation, reduce disparity search range and improve matching accuracy.

Do Poor Students Benefit from China's Merger Program? Transfer Path and Educational Performance

ERIC Educational Resources Information Center

Chen, Xinxin; Yi, Hongmei; Zhang, Linxiu; Mo, Di; Chu, James; Rozelle, Scott

2014-01-01

Aiming to provide better education facilities and improve the educational attainment of poor rural students, China's government has been merging remote rural primary schools into centralized village, town, or county schools since the late 1990s. To accompany the policy, boarding facilities have been constructed that allow (mandate) primary…

A Novel Dual Separate Paths (DSP) Algorithm Providing Fault-Tolerant Communication for Wireless Sensor Networks.

PubMed

Tien, Nguyen Xuan; Kim, Semog; Rhee, Jong Myung; Park, Sang Yoon

2017-07-25

Fault tolerance has long been a major concern for sensor communications in fault-tolerant cyber physical systems (CPSs). Network failure problems often occur in wireless sensor networks (WSNs) due to various factors such as the insufficient power of sensor nodes, the dislocation of sensor nodes, the unstable state of wireless links, and unpredictable environmental interference. Fault tolerance is thus one of the key requirements for data communications in WSN applications. This paper proposes a novel path redundancy-based algorithm, called dual separate paths (DSP), that provides fault-tolerant communication with the improvement of the network traffic performance for WSN applications, such as fault-tolerant CPSs. The proposed DSP algorithm establishes two separate paths between a source and a destination in a network based on the network topology information. These paths are node-disjoint paths and have optimal path distances. Unicast frames are delivered from the source to the destination in the network through the dual paths, providing fault-tolerant communication and reducing redundant unicast traffic for the network. The DSP algorithm can be applied to wired and wireless networks, such as WSNs, to provide seamless fault-tolerant communication for mission-critical and life-critical applications such as fault-tolerant CPSs. The analyzed and simulated results show that the DSP-based approach not only provides fault-tolerant communication, but also improves network traffic performance. For the case study in this paper, when the DSP algorithm was applied to high-availability seamless redundancy (HSR) networks, the proposed DSP-based approach reduced the network traffic by 80% to 88% compared with the standard HSR protocol, thus improving network traffic performance.

Applications and development of new algorithms for displacement analysis using InSAR time series

NASA Astrophysics Data System (ADS)

Osmanoglu, Batuhan

Time series analysis of Synthetic Aperture Radar Interferometry (InSAR) data has become an important scientific tool for monitoring and measuring the displacement of Earth's surface due to a wide range of phenomena, including earthquakes, volcanoes, landslides, changes in ground water levels, and wetlands. Time series analysis is a product of interferometric phase measurements, which become ambiguous when the observed motion is larger than half of the radar wavelength. Thus, phase observations must first be unwrapped in order to obtain physically meaningful results. Persistent Scatterer Interferometry (PSI), Stanford Method for Persistent Scatterers (StaMPS), Short Baselines Interferometry (SBAS) and Small Temporal Baseline Subset (STBAS) algorithms solve for this ambiguity using a series of spatio-temporal unwrapping algorithms and filters. In this dissertation, I improve upon current phase unwrapping algorithms, and apply the PSI method to study subsidence in Mexico City. PSI was used to obtain unwrapped deformation rates in Mexico City (Chapter 3),where ground water withdrawal in excess of natural recharge causes subsurface, clay-rich sediments to compact. This study is based on 23 satellite SAR scenes acquired between January 2004 and July 2006. Time series analysis of the data reveals a maximum line-of-sight subsidence rate of 300mm/yr at a high enough resolution that individual subsidence rates for large buildings can be determined. Differential motion and related structural damage along an elevated metro rail was evident from the results. Comparison of PSI subsidence rates with data from permanent GPS stations indicate root mean square (RMS) agreement of 6.9 mm/yr, about the level expected based on joint data uncertainty. The Mexico City results suggest negligible recharge, implying continuing degradation and loss of the aquifer in the third largest metropolitan area in the world. Chapters 4 and 5 illustrate the link between time series analysis and three-dimensional (3-D) phase unwrapping. Chapter 4 focuses on the unwrapping path. Unwrapping algorithms can be divided into two groups, path-dependent and path-independent algorithms. Path-dependent algorithms use local unwrapping functions applied pixel-by-pixel to the dataset. In contrast, path-independent algorithms use global optimization methods such as least squares, and return a unique solution. However, when aliasing and noise are present, path-independent algorithms can underestimate the signal in some areas due to global fitting criteria. Path-dependent algorithms do not underestimate the signal, but, as the name implies, the unwrapping path can affect the result. Comparison between existing path algorithms and a newly developed algorithm based on Fisher information theory was conducted. Results indicate that Fisher information theory does indeed produce lower misfit results for most tested cases. Chapter 5 presents a new time series analysis method based on 3-D unwrapping of SAR data using extended Kalman filters. Existing methods for time series generation using InSAR data employ special filters to combine two-dimensional (2-D) spatial unwrapping with one-dimensional (1-D) temporal unwrapping results. The new method, however, combines observations in azimuth, range and time for repeat pass interferometry. Due to the pixel-by-pixel characteristic of the filter, the unwrapping path is selected based on a quality map. This unwrapping algorithm is the first application of extended Kalman filters to the 3-D unwrapping problem. Time series analyses of InSAR data are used in a variety of applications with different characteristics. Consequently, it is difficult to develop a single algorithm that can provide optimal results in all cases, given that different algorithms possess a unique set of strengths and weaknesses. Nonetheless, filter-based unwrapping algorithms such as the one presented in this dissertation have the capability of joining multiple observations into a uniform solution, which is becoming an important feature with continuously growing datasets.

a Line-Based 3d Roof Model Reconstruction Algorithm: Tin-Merging and Reshaping (tmr)

NASA Astrophysics Data System (ADS)

Rau, J.-Y.

2012-07-01

Three-dimensional building model is one of the major components of a cyber-city and is vital for the realization of 3D GIS applications. In the last decade, the airborne laser scanning (ALS) data is widely used for 3D building model reconstruction and object extraction. Instead, based on 3D roof structural lines, this paper presents a novel algorithm for automatic roof models reconstruction. A line-based roof model reconstruction algorithm, called TIN-Merging and Reshaping (TMR), is proposed. The roof structural line, such as edges, eaves and ridges, can be measured manually from aerial stereo-pair, derived by feature line matching or inferred from ALS data. The originality of the TMR algorithm for 3D roof modelling is to perform geometric analysis and topology reconstruction among those unstructured lines and then reshapes the roof-type using elevation information from the 3D structural lines. For topology reconstruction, a line constrained Delaunay Triangulation algorithm is adopted where the input structural lines act as constraint and their vertex act as input points. Thus, the constructed TINs will not across the structural lines. Later at the stage of Merging, the shared edge between two TINs will be check if the original structural line exists. If not, those two TINs will be merged into a polygon. Iterative checking and merging of any two neighboured TINs/Polygons will result in roof polygons on the horizontal plane. Finally, at the Reshaping stage any two structural lines with fixed height will be used to adjust a planar function for the whole roof polygon. In case ALS data exist, the Reshaping stage can be simplified by adjusting the point cloud within the roof polygon. The proposed scheme reduces the complexity of 3D roof modelling and makes the modelling process easier. Five test datasets provided by ISPRS WG III/4 located at downtown Toronto, Canada and Vaihingen, Germany are used for experiment. The test sites cover high rise buildings and residential area with diverse roof type. For performance evaluation, the adopted roof structural lines are manually measured from the provided stereo-pair. Experimental results indicate a nearly 100% success rate for topology reconstruction was achieved provided that the 3D structural lines can be enclosed as polygons. On the other hand, the success rate at the Reshaping stage is dependent on the complexity of the rooftop structure. Thus, a visual inspection and semi-automatic adjustment of roof-type is suggested and implemented to complete the roof modelling. The results demonstrate that the proposed scheme is robust and reliable with a high degree of completeness, correctness, and quality, even when a group of connected buildings with multiple layers and mixed roof types is processed.

Optimization of Ocean Color Algorithms: Application to Satellite Data Merging

NASA Technical Reports Server (NTRS)

Maritorena, Stephane; Siegel, David A.; Morel, Andre

2003-01-01

The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project. The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage. The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global Ocean the merging of Ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances (L(sub WN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the (L(sub WN)(lambda)) data and, 4) it provides uncertainty estimates for the retrieved variables.

Quality of service routing in wireless ad hoc networks

NASA Astrophysics Data System (ADS)

Sane, Sachin J.; Patcha, Animesh; Mishra, Amitabh

2003-08-01

An efficient routing protocol is essential to guarantee application level quality of service running on wireless ad hoc networks. In this paper we propose a novel routing algorithm that computes a path between a source and a destination by considering several important constraints such as path-life, availability of sufficient energy as well as buffer space in each of the nodes on the path between the source and destination. The algorithm chooses the best path from among the multiples paths that it computes between two endpoints. We consider the use of control packets that run at a priority higher than the data packets in determining the multiple paths. The paper also examines the impact of different schedulers such as weighted fair queuing, and weighted random early detection among others in preserving the QoS level guarantees. Our extensive simulation results indicate that the algorithm improves the overall lifetime of a network, reduces the number of dropped packets, and decreases the end-to-end delay for real-time voice application.

The application of Markov decision process in restaurant delivery robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Hu, Zhen; Wang, Ying

2017-05-01

As the restaurant delivery robot is often in a dynamic and complex environment, including the chairs inadvertently moved to the channel and customers coming and going. The traditional path planning algorithm is not very ideal. To solve this problem, this paper proposes the Markov dynamic state immediate reward (MDR) path planning algorithm according to the traditional Markov decision process. First of all, it uses MDR to plan a global path, then navigates along this path. When the sensor detects there is no obstructions in front state, increase its immediate state reward value; when the sensor detects there is an obstacle in front, plan a global path that can avoid obstacle with the current position as the new starting point and reduce its state immediate reward value. This continues until the target is reached. When the robot learns for a period of time, it can avoid those places where obstacles are often present when planning the path. By analyzing the simulation experiment, the algorithm has achieved good results in the global path planning under the dynamic environment.

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

User's manual for SYNC: A FORTRAN program for merging and time-synchronizing data

NASA Technical Reports Server (NTRS)

Maine, R. E.

1981-01-01

The FORTRAN 77 computer program SYNC for merging and time synchronizing data is described. The program SYNC reads one or more input files which contain either synchronous data frames or time-tagged data points, which can be compressed. The program decompresses and time synchronizes the data, correcting for any channel time skews. Interpolation and hold last value synchronization algorithms are available. The output from SYNC is a file of time synchronized data frames at any requested sample rate.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Surface temperature dataset for North America obtained by application of optimal interpolation algorithm merging tree-ring chronologies and climate model output

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Nie, Suping; Zhao, Zongci; Huang, Jianbin; Wang, Shaowu; Tian, Qinhua

2017-02-01

A new dataset of surface temperature over North America has been constructed by merging climate model results and empirical tree-ring data through the application of an optimal interpolation algorithm. Errors of both the Community Climate System Model version 4 (CCSM4) simulation and the tree-ring reconstruction were considered to optimize the combination of the two elements. Variance matching was used to reconstruct the surface temperature series. The model simulation provided the background field, and the error covariance matrix was estimated statistically using samples from the simulation results with a running 31-year window for each grid. Thus, the merging process could continue with a time-varying gain matrix. This merging method (MM) was tested using two types of experiment, and the results indicated that the standard deviation of errors was about 0.4 °C lower than the tree-ring reconstructions and about 0.5 °C lower than the model simulation. Because of internal variabilities and uncertainties in the external forcing data, the simulated decadal warm-cool periods were readjusted by the MM such that the decadal variability was more reliable (e.g., the 1940-1960s cooling). During the two centuries (1601-1800 AD) of the preindustrial period, the MM results revealed a compromised spatial pattern of the linear trend of surface temperature, which is in accordance with the phase transition of the Pacific decadal oscillation and Atlantic multidecadal oscillation. Compared with pure CCSM4 simulations, it was demonstrated that the MM brought a significant improvement to the decadal variability of the gridded temperature via the merging of temperature-sensitive tree-ring records.

Selective epidemic vaccination under the performant routing algorithms

NASA Astrophysics Data System (ADS)

Bamaarouf, O.; Alweimine, A. Ould Baba; Rachadi, A.; EZ-Zahraouy, H.

2018-04-01

Despite the extensive research on traffic dynamics and epidemic spreading, the effect of the routing algorithms strategies on the traffic-driven epidemic spreading has not received an adequate attention. It is well known that more performant routing algorithm strategies are used to overcome the congestion problem. However, our main result shows unexpectedly that these algorithms favor the virus spreading more than the case where the shortest path based algorithm is used. In this work, we studied the virus spreading in a complex network using the efficient path and the global dynamic routing algorithms as compared to shortest path strategy. Some previous studies have tried to modify the routing rules to limit the virus spreading, but at the expense of reducing the traffic transport efficiency. This work proposed a solution to overcome this drawback by using a selective vaccination procedure instead of a random vaccination used often in the literature. We found that the selective vaccination succeeded in eradicating the virus better than a pure random intervention for the performant routing algorithm strategies.

Quantum Adiabatic Algorithms and Large Spin Tunnelling

NASA Technical Reports Server (NTRS)

Boulatov, A.; Smelyanskiy, V. N.

2003-01-01

We provide a theoretical study of the quantum adiabatic evolution algorithm with different evolution paths proposed in this paper. The algorithm is applied to a random binary optimization problem (a version of the 3-Satisfiability problem) where the n-bit cost function is symmetric with respect to the permutation of individual bits. The evolution paths are produced, using the generic control Hamiltonians H (r) that preserve the bit symmetry of the underlying optimization problem. In the case where the ground state of H(0) coincides with the totally-symmetric state of an n-qubit system the algorithm dynamics is completely described in terms of the motion of a spin-n/2. We show that different control Hamiltonians can be parameterized by a set of independent parameters that are expansion coefficients of H (r) in a certain universal set of operators. Only one of these operators can be responsible for avoiding the tunnelling in the spin-n/2 system during the quantum adiabatic algorithm. We show that it is possible to select a coefficient for this operator that guarantees a polynomial complexity of the algorithm for all problem instances. We show that a successful evolution path of the algorithm always corresponds to the trajectory of a classical spin-n/2 and provide a complete characterization of such paths.

Structure-guided Protein Transition Modeling with a Probabilistic Roadmap Algorithm.

PubMed

Maximova, Tatiana; Plaku, Erion; Shehu, Amarda

2016-07-07

Proteins are macromolecules in perpetual motion, switching between structural states to modulate their function. A detailed characterization of the precise yet complex relationship between protein structure, dynamics, and function requires elucidating transitions between functionally-relevant states. Doing so challenges both wet and dry laboratories, as protein dynamics involves disparate temporal scales. In this paper we present a novel, sampling-based algorithm to compute transition paths. The algorithm exploits two main ideas. First, it leverages known structures to initialize its search and define a reduced conformation space for rapid sampling. This is key to address the insufficient sampling issue suffered by sampling-based algorithms. Second, the algorithm embeds samples in a nearest-neighbor graph where transition paths can be efficiently computed via queries. The algorithm adapts the probabilistic roadmap framework that is popular in robot motion planning. In addition to efficiently computing lowest-cost paths between any given structures, the algorithm allows investigating hypotheses regarding the order of experimentally-known structures in a transition event. This novel contribution is likely to open up new venues of research. Detailed analysis is presented on multiple-basin proteins of relevance to human disease. Multiscaling and the AMBER ff14SB force field are used to obtain energetically-credible paths at atomistic detail.

Comparison of some evolutionary algorithms for optimization of the path synthesis problem

NASA Astrophysics Data System (ADS)

Grabski, Jakub Krzysztof; Walczak, Tomasz; Buśkiewicz, Jacek; Michałowska, Martyna

2018-01-01

The paper presents comparison of the results obtained in a mechanism synthesis by means of some selected evolutionary algorithms. The optimization problem considered in the paper as an example is the dimensional synthesis of the path generating four-bar mechanism. In order to solve this problem, three different artificial intelligence algorithms are employed in this study.

An Algorithm for the Hierarchical Organization of Path Diagrams and Calculation of Components of Expected Covariance.

ERIC Educational Resources Information Center

Boker, Steven M.; McArdle, J. J.; Neale, Michael

2002-01-01

Presents an algorithm for the production of a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged. The algorithm, which relies on the matrix equations of J. McArdle and R. McDonald (1984), calculates the individual path components of expected covariance between variables and…

A Comparison of Hybrid Approaches for Turbofan Engine Gas Path Fault Diagnosis

NASA Astrophysics Data System (ADS)

Lu, Feng; Wang, Yafan; Huang, Jinquan; Wang, Qihang

2016-09-01

A hybrid diagnostic method utilizing Extended Kalman Filter (EKF) and Adaptive Genetic Algorithm (AGA) is presented for performance degradation estimation and sensor anomaly detection of turbofan engine. The EKF is used to estimate engine component performance degradation for gas path fault diagnosis. The AGA is introduced in the integrated architecture and applied for sensor bias detection. The contributions of this work are the comparisons of Kalman Filters (KF)-AGA algorithms and Neural Networks (NN)-AGA algorithms with a unified framework for gas path fault diagnosis. The NN needs to be trained off-line with a large number of prior fault mode data. When new fault mode occurs, estimation accuracy by the NN evidently decreases. However, the application of the Linearized Kalman Filter (LKF) and EKF will not be restricted in such case. The crossover factor and the mutation factor are adapted to the fitness function at each generation in the AGA, and it consumes less time to search for the optimal sensor bias value compared to the Genetic Algorithm (GA). In a word, we conclude that the hybrid EKF-AGA algorithm is the best choice for gas path fault diagnosis of turbofan engine among the algorithms discussed.

Rock climbing: A local-global algorithm to compute minimum energy and minimum free energy pathways.

PubMed

Templeton, Clark; Chen, Szu-Hua; Fathizadeh, Arman; Elber, Ron

2017-10-21

The calculation of minimum energy or minimum free energy paths is an important step in the quantitative and qualitative studies of chemical and physical processes. The computations of these coordinates present a significant challenge and have attracted considerable theoretical and computational interest. Here we present a new local-global approach to study reaction coordinates, based on a gradual optimization of an action. Like other global algorithms, it provides a path between known reactants and products, but it uses a local algorithm to extend the current path in small steps. The local-global approach does not require an initial guess to the path, a major challenge for global pathway finders. Finally, it provides an exact answer (the steepest descent path) at the end of the calculations. Numerical examples are provided for the Mueller potential and for a conformational transition in a solvated ring system.

Flight Path Synthesis and HUD Scaling for V/STOL Terminal Area Operations

DOT National Transportation Integrated Search

1995-04-01

A two circle horizontal flightpath synthesis algorithm for Vertical/Short : Takeoff and Landing (V/STOL) terminal area operations is presented. This : algorithm provides a flight-path that is tangential to the aircraft's velocity : vector at the inst...

Robot path planning algorithm based on symbolic tags in dynamic environment

NASA Astrophysics Data System (ADS)

Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.

2017-09-01

The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.

Shortest path problem on a grid network with unordered intermediate points

NASA Astrophysics Data System (ADS)

Saw, Veekeong; Rahman, Amirah; Eng Ong, Wen

2017-10-01

We consider a shortest path problem with single cost factor on a grid network with unordered intermediate points. A two stage heuristic algorithm is proposed to find a feasible solution path within a reasonable amount of time. To evaluate the performance of the proposed algorithm, computational experiments are performed on grid maps of varying size and number of intermediate points. Preliminary results for the problem are reported. Numerical comparisons against brute forcing show that the proposed algorithm consistently yields solutions that are within 10% of the optimal solution and uses significantly less computation time.

A Simulation Testbed for Airborne Merging and Spacing

NASA Technical Reports Server (NTRS)

Santos, Michel; Manikonda, Vikram; Feinberg, Art; Lohr, Gary

2008-01-01

The key innovation in this effort is the development of a simulation testbed for airborne merging and spacing (AM&S). We focus on concepts related to airports with Super Dense Operations where new airport runway configurations (e.g. parallel runways), sequencing, merging, and spacing are some of the concepts considered. We focus on modeling and simulating a complementary airborne and ground system for AM&S to increase efficiency and capacity of these high density terminal areas. From a ground systems perspective, a scheduling decision support tool generates arrival sequences and spacing requirements that are fed to the AM&S system operating on the flight deck. We enhanced NASA's Airspace Concept Evaluation Systems (ACES) software to model and simulate AM&S concepts and algorithms.

Multiple object tracking using the shortest path faster association algorithm.

PubMed

Xi, Zhenghao; Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

PubMed Central

Liu, Heping; Liu, Huaping; Yang, Bin

2014-01-01

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time. PMID:25215322

Binary partition tree analysis based on region evolution and its application to tree simplification.

PubMed

Lu, Huihai; Woods, John C; Ghanbari, Mohammed

2007-04-01

Pyramid image representations via tree structures are recognized methods for region-based image analysis. Binary partition trees can be applied which document the merging process with small details found at the bottom levels and larger ones close to the root. Hindsight of the merging process is stored within the tree structure and provides the change histories of an image property from the leaf to the root node. In this work, the change histories are modelled by evolvement functions and their second order statistics are analyzed by using a knee function. Knee values show the reluctancy of each merge. We have systematically formulated these findings to provide a novel framework for binary partition tree analysis, where tree simplification is demonstrated. Based on an evolvement function, for each upward path in a tree, the tree node associated with the first reluctant merge is considered as a pruning candidate. The result is a simplified version providing a reduced solution space and still complying with the definition of a binary tree. The experiments show that image details are preserved whilst the number of nodes is dramatically reduced. An image filtering tool also results which preserves object boundaries and has applications for segmentation.

Managing Network Partitions in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Shafaat, Tallat M.; Ghodsi, Ali; Haridi, Seif

Structured overlay networks form a major class of peer-to-peer systems, which are touted for their abilities to scale, tolerate failures, and self-manage. Any long-lived Internet-scale distributed system is destined to face network partitions. Consequently, the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems. This makes it a crucial requirement for building any structured peer-to-peer systems to be resilient to network partitions. Although the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems, it has hardly been studied in the context of structured peer-to-peer systems. Structured overlays have mainly been studied under churn (frequent joins/failures), which as a side effect solves the problem of network partitions, as it is similar to massive node failures. Yet, the crucial aspect of network mergers has been ignored. In fact, it has been claimed that ring-based structured overlay networks, which constitute the majority of the structured overlays, are intrinsically ill-suited for merging rings. In this chapter, we motivate the problem of network partitions and mergers in structured overlays. We discuss how a structured overlay can automatically detect a network partition and merger. We present an algorithm for merging multiple similar ring-based overlays when the underlying network merges. We examine the solution in dynamic conditions, showing how our solution is resilient to churn during the merger, something widely believed to be difficult or impossible. We evaluate the algorithm for various scenarios and show that even when falsely detecting a merger, the algorithm quickly terminates and does not clutter the network with many messages. The algorithm is flexible as the tradeoff between message complexity and time complexity can be adjusted by a parameter.

Hybrid clustering based fuzzy structure for vibration control - Part 1: A novel algorithm for building neuro-fuzzy system

NASA Astrophysics Data System (ADS)

Nguyen, Sy Dzung; Nguyen, Quoc Hung; Choi, Seung-Bok

2015-01-01

This paper presents a new algorithm for building an adaptive neuro-fuzzy inference system (ANFIS) from a training data set called B-ANFIS. In order to increase accuracy of the model, the following issues are executed. Firstly, a data merging rule is proposed to build and perform a data-clustering strategy. Subsequently, a combination of clustering processes in the input data space and in the joint input-output data space is presented. Crucial reason of this task is to overcome problems related to initialization and contradictory fuzzy rules, which usually happen when building ANFIS. The clustering process in the input data space is accomplished based on a proposed merging-possibilistic clustering (MPC) algorithm. The effectiveness of this process is evaluated to resume a clustering process in the joint input-output data space. The optimal parameters obtained after completion of the clustering process are used to build ANFIS. Simulations based on a numerical data, 'Daily Data of Stock A', and measured data sets of a smart damper are performed to analyze and estimate accuracy. In addition, convergence and robustness of the proposed algorithm are investigated based on both theoretical and testing approaches.

Adaptive structured dictionary learning for image fusion based on group-sparse-representation

NASA Astrophysics Data System (ADS)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

On Channel-Discontinuity-Constraint Routing in Wireless Networks☆

PubMed Central

Sankararaman, Swaminathan; Efrat, Alon; Ramasubramanian, Srinivasan; Agarwal, Pankaj K.

2011-01-01

Multi-channel wireless networks are increasingly deployed as infrastructure networks, e.g. in metro areas. Network nodes frequently employ directional antennas to improve spatial throughput. In such networks, between two nodes, it is of interest to compute a path with a channel assignment for the links such that the path and link bandwidths are the same. This is achieved when any two consecutive links are assigned different channels, termed as “Channel-Discontinuity-Constraint” (CDC). CDC-paths are also useful in TDMA systems, where, preferably, consecutive links are assigned different time-slots. In the first part of this paper, we develop a t-spanner for CDC-paths using spatial properties; a sub-network containing O(n/θ) links, for any θ > 0, such that CDC-paths increase in cost by at most a factor t = (1−2 sin (θ/2))−2. We propose a novel distributed algorithm to compute the spanner using an expected number of O(n log n) fixed-size messages. In the second part, we present a distributed algorithm to find minimum-cost CDC-paths between two nodes using O(n2) fixed-size messages, by developing an extension of Edmonds’ algorithm for minimum-cost perfect matching. In a centralized implementation, our algorithm runs in O(n2) time improving the previous best algorithm which requires O(n3) running time. Moreover, this running time improves to O(n/θ) when used in conjunction with the spanner developed. PMID:24443646

Application of ant colony algorithm in path planning of the data center room robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Ma, Jianming; Wang, Ying

2017-05-01

According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.

Generalized gradient algorithm for trajectory optimization

NASA Technical Reports Server (NTRS)

Zhao, Yiyuan; Bryson, A. E.; Slattery, R.

1990-01-01

The generalized gradient algorithm presented and verified as a basis for the solution of trajectory optimization problems improves the performance index while reducing path equality constraints, and terminal equality constraints. The algorithm is conveniently divided into two phases, of which the first, 'feasibility' phase yields a solution satisfying both path and terminal constraints, while the second, 'optimization' phase uses the results of the first phase as initial guesses.

Connecting Satellite-Based Precipitation Estimates to Users

NASA Technical Reports Server (NTRS)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

Structural factoring approach for analyzing stochastic networks

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.; Shier, Douglas R.

1991-01-01

The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

The force control and path planning of electromagnetic induction-based massage robot.

PubMed

Wang, Wendong; Zhang, Lei; Li, Jinzhe; Yuan, Xiaoqing; Shi, Yikai; Jiang, Qinqin; He, Lijing

2017-07-20

Massage robot is considered as an effective physiological treatment to relieve fatigue, improve blood circulation, relax muscle tone, etc. The simple massage equipment quickly spread into market due to low cost, but they are not widely accepted due to restricted massage function. Complicated structure and high cost caused difficulties for developing multi-function massage equipment. This paper presents a novel massage robot which can achieve tapping, rolling, kneading and other massage operations, and proposes an improved reciprocating path planning algorithm to improve massage effect. The number of coil turns, the coil current and the distance between massage head and yoke were chosen to investigate the influence on massage force by finite element method. The control system model of the wheeled massage robot was established, including control subsystem of the motor, path algorithm control subsystem, parameter module of the massage robot and virtual reality interface module. The improved reciprocating path planning algorithm was proposed to improve regional coverage rate and massage effect. The influence caused by coil current, the number of coil turns and the distance between massage head and yoke were simulated in Maxwell. It indicated that coil current has more important influence compared to the other two factors. The path planning simulation of the massage robot was completed in Matlab, and the results show that the improved reciprocating path planning algorithm achieved higher coverage rate than the traditional algorithm. With the analysis of simulation results, it can be concluded that the number of coil turns and the distance between the moving iron core and the yoke could be determined prior to coil current, and the force can be controllable by optimizing structure parameters of massage head and adjusting coil current. Meanwhile, it demonstrates that the proposed algorithm could effectively improve path coverage rate during massage operations, therefore the massage effect can be improved.

Hubble Views Two Galaxies Merging

NASA Image and Video Library

2017-12-08

This image, taken with the Wide Field Planetary Camera 2 on board the NASA/ESA Hubble Space Telescope, shows the galaxy NGC 6052, located around 230 million light-years away in the constellation of Hercules. It would be reasonable to think of this as a single abnormal galaxy, and it was originally classified as such. However, it is in fact a “new” galaxy in the process of forming. Two separate galaxies have been gradually drawn together, attracted by gravity, and have collided. We now see them merging into a single structure. As the merging process continues, individual stars are thrown out of their original orbits and placed onto entirely new paths, some very distant from the region of the collision itself. Since the stars produce the light we see, the “galaxy” now appears to have a highly chaotic shape. Eventually, this new galaxy will settle down into a stable shape, which may not resemble either of the two original galaxies. Image credit: ESA/Hubble & NASA, Acknowledgement: Judy Schmidt

Navier-Stokes structure of merged layer flow on the spherical nose of a space vehicle

NASA Technical Reports Server (NTRS)

Jain, A. C.; Woods, G. H.

1988-01-01

Hypersonic merged layer flow on the forepart of a spherical surface of a space vehicle has been investigated on the basis of the full steady-state Navier-Stokes equations using slip and temperature jump boundary conditions at the surface and free-stream conditions far from the surface. The shockwave-like structure was determined as part of the computations. Using an equivalent body concept, computations were carried out under conditions that the Aeroassist Flight Experiment (AFE) Vehicle would encounter at 15 and 20 seconds in its flight path. Emphasis was placed on understanding the basic nature of the flow structure under low density conditions. Particular attention was paid to the understanding of the structure of the outer shockwave-like region as the fluid expands around the sphere. Plots were drawn for flow profiles and surface characteristics to understand the role of dissipation processes in the merged layer of the spherical nose of the vehicle.

Evaluation of a New Backtrack Free Path Planning Algorithm for Manipulators

NASA Astrophysics Data System (ADS)

Islam, Md. Nazrul; Tamura, Shinsuke; Murata, Tomonari; Yanase, Tatsuro

This paper evaluates a newly proposed backtrack free path planning algorithm (BFA) for manipulators. BFA is an exact algorithm, i.e. it is resolution complete. Different from existing resolution complete algorithms, its computation time and memory space are proportional to the number of arms. Therefore paths can be calculated within practical and predetermined time even for manipulators with many arms, and it becomes possible to plan complicated motions of multi-arm manipulators in fully automated environments. The performance of BFA is evaluated for 2-dimensional environments while changing the number of arms and obstacle placements. Its performance under locus and attitude constraints is also evaluated. Evaluation results show that the computation volume of the algorithm is almost the same as the theoretical one, i.e. it increases linearly with the number of arms even in complicated environments. Moreover BFA achieves the constant performance independent of environments.

Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator

PubMed Central

Mohamd Shoukry, Alaa; Gani, Showkat

2017-01-01

Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions; however, they give good approximation usually in time. The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. The genetic algorithm depends on selection criteria, crossover, and mutation operators. To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations. In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance. This approach has been linked with path representation, which is the most natural way to represent a legal tour. Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements. PMID:29209364

Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator.

PubMed

Hussain, Abid; Muhammad, Yousaf Shad; Nauman Sajid, M; Hussain, Ijaz; Mohamd Shoukry, Alaa; Gani, Showkat

2017-01-01

Genetic algorithms are evolutionary techniques used for optimization purposes according to survival of the fittest idea. These methods do not ensure optimal solutions; however, they give good approximation usually in time. The genetic algorithms are useful for NP-hard problems, especially the traveling salesman problem. The genetic algorithm depends on selection criteria, crossover, and mutation operators. To tackle the traveling salesman problem using genetic algorithms, there are various representations such as binary, path, adjacency, ordinal, and matrix representations. In this article, we propose a new crossover operator for traveling salesman problem to minimize the total distance. This approach has been linked with path representation, which is the most natural way to represent a legal tour. Computational results are also reported with some traditional path representation methods like partially mapped and order crossovers along with new cycle crossover operator for some benchmark TSPLIB instances and found improvements.

A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model. PMID:23193383

A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.

A bat algorithm with mutation for UCAV path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

Real-time path planning and autonomous control for helicopter autorotation

NASA Astrophysics Data System (ADS)

Yomchinda, Thanan

Autorotation is a descending maneuver that can be used to recover helicopters in the event of total loss of engine power; however it is an extremely difficult and complex maneuver. The objective of this work is to develop a real-time system which provides full autonomous control for autorotation landing of helicopters. The work includes the development of an autorotation path planning method and integration of the path planner with a primary flight control system. The trajectory is divided into three parts: entry, descent and flare. Three different optimization algorithms are used to generate trajectories for each of these segments. The primary flight control is designed using a linear dynamic inversion control scheme, and a path following control law is developed to track the autorotation trajectories. Details of the path planning algorithm, trajectory following control law, and autonomous autorotation system implementation are presented. The integrated system is demonstrated in real-time high fidelity simulations. Results indicate feasibility of the capability of the algorithms to operate in real-time and of the integrated systems ability to provide safe autorotation landings. Preliminary simulations of autonomous autorotation on a small UAV are presented which will lead to a final hardware demonstration of the algorithms.

Genetic Algorithm for Solving Fuzzy Shortest Path Problem in a Network with mixed fuzzy arc lengths

NASA Astrophysics Data System (ADS)

Mahdavi, Iraj; Tajdin, Ali; Hassanzadeh, Reza; Mahdavi-Amiri, Nezam; Shafieian, Hosna

2011-06-01

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model.

Mobile transporter path planning

NASA Technical Reports Server (NTRS)

Baffes, Paul; Wang, Lui

1990-01-01

The use of a genetic algorithm (GA) for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the space station which must be able to reach any point of the structure autonomously. Elements of the genetic algorithm are explored in both a theoretical and experimental sense. Specifically, double crossover, greedy crossover, and tournament selection techniques are examined. Additionally, the use of local optimization techniques working in concert with the GA are also explored. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

Application of particle swarm optimization in path planning of mobile robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

NASA Astrophysics Data System (ADS)

Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment.

PubMed

Zhang, Bo; Duan, Haibin

2017-01-01

Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.

Bayesian Fusion of Color and Texture Segmentations

NASA Technical Reports Server (NTRS)

Manduchi, Roberto

2000-01-01

In many applications one would like to use information from both color and texture features in order to segment an image. We propose a novel technique to combine "soft" segmentations computed for two or more features independently. Our algorithm merges models according to a mean entropy criterion, and allows to choose the appropriate number of classes for the final grouping. This technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.)

Uncovering the overlapping community structure of complex networks by maximal cliques

NASA Astrophysics Data System (ADS)

Li, Junqiu; Wang, Xingyuan; Cui, Yaozu

2014-12-01

In this paper, a unique algorithm is proposed to detect overlapping communities in the un-weighted and weighted networks with considerable accuracy. The maximal cliques, overlapping vertex, bridge vertex and isolated vertex are introduced. First, all the maximal cliques are extracted by the algorithm based on the deep and bread searching. Then two maximal cliques can be merged into a larger sub-graph by some given rules. In addition, the proposed algorithm successfully finds overlapping vertices and bridge vertices between communities. Experimental results using some real-world networks data show that the performance of the proposed algorithm is satisfactory.

The indexing ambiguity in serial femtosecond crystallography (SFX) resolved using an expectation maximization algorithm.

PubMed

Liu, Haiguang; Spence, John C H

2014-11-01

Crystallographic auto-indexing algorithms provide crystal orientations and unit-cell parameters and assign Miller indices based on the geometric relations between the Bragg peaks observed in diffraction patterns. However, if the Bravais symmetry is higher than the space-group symmetry, there will be multiple indexing options that are geometrically equivalent, and hence many ways to merge diffraction intensities from protein nanocrystals. Structure factor magnitudes from full reflections are required to resolve this ambiguity but only partial reflections are available from each XFEL shot, which must be merged to obtain full reflections from these 'stills'. To resolve this chicken-and-egg problem, an expectation maximization algorithm is described that iteratively constructs a model from the intensities recorded in the diffraction patterns as the indexing ambiguity is being resolved. The reconstructed model is then used to guide the resolution of the indexing ambiguity as feedback for the next iteration. Using both simulated and experimental data collected at an X-ray laser for photosystem I in the P63 space group (which supports a merohedral twinning indexing ambiguity), the method is validated.

Study of Double-Weighted Graph Model and Optimal Path Planning for Tourist Scenic Area Oriented Intelligent Tour Guide

NASA Astrophysics Data System (ADS)

Shi, Y.; Long, Y.; Wi, X. L.

2014-04-01

When tourists visiting multiple tourist scenic spots, the travel line is usually the most effective road network according to the actual tour process, and maybe the travel line is different from planned travel line. For in the field of navigation, a proposed travel line is normally generated automatically by path planning algorithm, considering the scenic spots' positions and road networks. But when a scenic spot have a certain area and have multiple entrances or exits, the traditional described mechanism of single point coordinates is difficult to reflect these own structural features. In order to solve this problem, this paper focuses on the influence on the process of path planning caused by scenic spots' own structural features such as multiple entrances or exits, and then proposes a doubleweighted Graph Model, for the weight of both vertexes and edges of proposed Model can be selected dynamically. And then discusses the model building method, and the optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from the proposed model and algorithm is more reasonable, and the travelling order and distance would be further optimized.

Human resource recommendation algorithm based on ensemble learning and Spark

NASA Astrophysics Data System (ADS)

Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

2017-08-01

Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

Planning Flight Paths of Autonomous Aerobots

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Sharma, Shivanjli

2009-01-01

Algorithms for planning flight paths of autonomous aerobots (robotic blimps) to be deployed in scientific exploration of remote planets are undergoing development. These algorithms are also adaptable to terrestrial applications involving robotic submarines as well as aerobots and other autonomous aircraft used to acquire scientific data or to perform surveying or monitoring functions.

Validation Studies of the Accuracy of Various SO2 Gas Retrievals in the Thermal InfraRed (8-14 μm)

NASA Astrophysics Data System (ADS)

Gabrieli, A.; Wright, R.; Lucey, P. G.; Porter, J. N.; Honniball, C.; Garbeil, H.; Wood, M.

2016-12-01

Quantifying hazardous SO2 in the atmosphere and in volcanic plumes is important for public health and volcanic eruption prediction. Remote sensing measurements of spectral radiance of plumes contain information on the abundance of SO2. However, in order to convert such measurements into SO2 path-concentrations, reliable inversion algorithms are needed. Various techniques can be employed to derive SO2 path-concentrations. The first approach employs a Partial Least Square Regression model trained using MODTRAN5 simulations for a variety of plume and atmospheric conditions. Radiances at many spectral wavelengths (8-14 μm) were used in the algorithm. The second algorithm uses measurements inside and outside the SO2 plume. Measurements in the plume-free region (background sky) make it possible to remove background atmospheric conditions and any instrumental effects. After atmospheric and instrumental effects are removed, MODTRAN5 is used to fit the SO2 spectral feature and obtain SO2 path-concentrations. The two inversion algorithms described above can be compared with the inversion algorithm for SO2 retrievals developed by Prata and Bernardo (2014). Their approach employs three wavelengths to characterize the plume temperature, the atmospheric background, and the SO2 path-concentration. The accuracy of these various techniques requires further investigation in terms of the effects of different atmospheric background conditions. Validating these inversion algorithms is challenging because ground truth measurements are very difficult. However, if the three separate inversion algorithms provide similar SO2 path-concentrations for actual measurements with various background conditions, then this increases confidence in the results. Measurements of sky radiance when looking through SO2 filled gas cells were collected with a Thermal Hyperspectral Imager (THI) under various atmospheric background conditions. These data were processed using the three inversion approaches, which were tested for convergence on the known SO2 gas cell path-concentrations. For this study, the inversion algorithms were modified to account for the gas cell configuration. Results from these studies will be presented, as well as results from SO2 gas plume measurements at Kīlauea volcano, Hawai'i.

Object-oriented and pixel-based classification approach for land cover using airborne long-wave infrared hyperspectral data

NASA Astrophysics Data System (ADS)

Marwaha, Richa; Kumar, Anil; Kumar, Arumugam Senthil

2015-01-01

Our primary objective was to explore a classification algorithm for thermal hyperspectral data. Minimum noise fraction is applied to thermal hyperspectral data and eight pixel-based classifiers, i.e., constrained energy minimization, matched filter, spectral angle mapper (SAM), adaptive coherence estimator, orthogonal subspace projection, mixture-tuned matched filter, target-constrained interference-minimized filter, and mixture-tuned target-constrained interference minimized filter are tested. The long-wave infrared (LWIR) has not yet been exploited for classification purposes. The LWIR data contain emissivity and temperature information about an object. A highest overall accuracy of 90.99% was obtained using the SAM algorithm for the combination of thermal data with a colored digital photograph. Similarly, an object-oriented approach is applied to thermal data. The image is segmented into meaningful objects based on properties such as geometry, length, etc., which are grouped into pixels using a watershed algorithm and an applied supervised classification algorithm, i.e., support vector machine (SVM). The best algorithm in the pixel-based category is the SAM technique. SVM is useful for thermal data, providing a high accuracy of 80.00% at a scale value of 83 and a merge value of 90, whereas for the combination of thermal data with a colored digital photograph, SVM gives the highest accuracy of 85.71% at a scale value of 82 and a merge value of 90.

Parameter optimization on the convergence surface of path simulations

NASA Astrophysics Data System (ADS)

Chandrasekaran, Srinivas Niranj

Computational treatments of protein conformational changes tend to focus on the trajectories themselves, despite the fact that it is the transition state structures that contain information about the barriers that impose multi-state behavior. PATH is an algorithm that computes a transition pathway between two protein crystal structures, along with the transition state structure, by minimizing the Onsager-Machlup action functional. It is rapid but depends on several unknown input parameters whose range of different values can potentially generate different transition-state structures. Transition-state structures arising from different input parameters cannot be uniquely compared with those generated by other methods. I outline modifications that I have made to the PATH algorithm that estimates these input parameters in a manner that circumvents these difficulties, and describe two complementary tests that validate the transition-state structures found by the PATH algorithm. First, I show that although the PATH algorithm and two other approaches to computing transition pathways produce different low-energy structures connecting the initial and final ground-states with the transition state, all three methods agree closely on the configurations of their transition states. Second, I show that the PATH transition states are close to the saddle points of free-energy surfaces connecting initial and final states generated by replica-exchange Discrete Molecular Dynamics simulations. I show that aromatic side-chain rearrangements create similar potential energy barriers in the transition-state structures identified by PATH for a signaling protein, a contractile protein, and an enzyme. Finally, I observed, but cannot account for, the fact that trajectories obtained for all-atom and Calpha-only simulations identify transition state structures in which the Calpha atoms are in essentially the same positions. The consistency between transition-state structures derived by different algorithms for unrelated protein systems argues that although functionally important protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. In the end, I outline the strategies that could enhance the efficiency and applicability of PATH.

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

Optimization Of Ocean Color Algorithms: Application To Satellite And In Situ Data Merging. Chapter 9

NASA Technical Reports Server (NTRS)

Maritorena, Stephane; Siegel, David A.; Morel, Andre

2003-01-01

The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project (McClain et al., 1995). The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage (Gregg et al., 1998; Gregg & Woodward, 1998). The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global ocean the merging of ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program (see e.g. Kwiatkowska & Fargion, 2003, Franz et al., 2003). As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized waterleaving radiances (LwN( )) from single or multiple sensors and uses them in the inversion of a semianalytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the LwN( ) data and, 4) it provides uncertainty estimates for the retrieved variables.

Ancient village fire escape path planning based on improved ant colony algorithm

NASA Astrophysics Data System (ADS)

Xia, Wei; Cao, Kang; Hu, QianChuan

2017-06-01

The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.

A Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts: Third Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2012-01-01

This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates constant radius turns and cruise altitude waypoints with calibrated airspeed, versus Mach, constraints. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint. Wind data at each of these waypoints are also used for the calculation of ground speed and turn radius.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Keller, James F.

This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent surveillance applications but few directly address dynamic maneuver constraints. The key feature of C1 is a two stage sequential solution that discretizes the problem so that graph search techniques can be combined with parametric polynomial curve generation. A method to abstract the kino-dynamics of the aerial platforms is then presented so that a graph search solution can be adapted for this application. An A* Traveling Salesman Problem (TSP) algorithm is developed to search the discretized space using the abstract distance metric to acquire more data or avoid obstacles. Results of the graph search are then transcribed into smooth paths based on vehicle maneuver constraints. A complete solution for a single vehicle periodic tour of the area is developed using the results of the graph search algorithm. To execute the mission, we present a simultaneous arrival algorithm (C2) to coordinate execution by multiple vehicles to satisfy data refresh requirements and to ensure there are no collisions at any of the path intersections. We present a toolbox of spline-based algorithms (C3) to streamline the development of C2 continuous paths with numerical stability. These tools are applied to an aerial persistent surveillance application to illustrate their utility. Comparisons with other parametric polynomial approaches are highlighted to underscore the benefits of the B-spline framework. Performance limits with respect to feasibility constraints are documented.

Applying Semantic Web Concepts to Support Net-Centric Warfare Using the Tactical Assessment Markup Language (TAML)

DTIC Science & Technology

2006-06-01

SPARQL SPARQL Protocol and RDF Query Language SQL Structured Query Language SUMO Suggested Upper Merged Ontology SW... Query optimization algorithms are implemented in the Pellet reasoner in order to ensure querying a knowledge base is efficient . These algorithms...memory as a treelike structure in order for the data to be queried . XML Query (XQuery) is the standard language used when querying XML

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

NASA Astrophysics Data System (ADS)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

Simulation and validation of concentrated subsurface lateral flow paths in an agricultural landscape

NASA Astrophysics Data System (ADS)

Zhu, Q.; Lin, H. S.

2009-08-01

The importance of soil water flow paths to the transport of nutrients and contaminants has long been recognized. However, effective means of detecting concentrated subsurface flow paths in a large landscape are still lacking. The flow direction and accumulation algorithm based on single-direction flow algorithm (D8) in GIS hydrologic modeling is a cost-effective way to simulate potential concentrated flow paths over a large area once relevant data are collected. This study tested the D8 algorithm for simulating concentrated lateral flow paths at three interfaces in soil profiles in a 19.5-ha agricultural landscape in central Pennsylvania, USA. These interfaces were (1) the interface between surface plowed layers of Ap1 and Ap2 horizons, (2) the interface with subsoil water-restricting clay layer where clay content increased to over 40%, and (3) the soil-bedrock interface. The simulated flow paths were validated through soil hydrologic monitoring, geophysical surveys, and observable soil morphological features. The results confirmed that concentrated subsurface lateral flow occurred at the interfaces with the clay layer and the underlying bedrock. At these two interfaces, the soils on the simulated flow paths were closer to saturation and showed more temporally unstable moisture dynamics than those off the simulated flow paths. Apparent electrical conductivity in the soil on the simulated flow paths was elevated and temporally unstable as compared to those outside the simulated paths. The soil cores collected from the simulated flow paths showed significantly higher Mn content at these interfaces than those away from the simulated paths. These results suggest that (1) the D8 algorithm is useful in simulating possible concentrated subsurface lateral flow paths if used with appropriate threshold value of contributing area and sufficiently detailed digital elevation model (DEM); (2) repeated electromagnetic surveys can reflect the temporal change of soil water storage and thus is a useful indicator of possible subsurface flow path over a large area; and (3) observable Mn distribution in soil profiles can be used as a simple indicator of water flow paths in soils and over the landscape; however, it does require sufficient soil sampling (by excavation or augering) to possibly infer landscape-scale subsurface flow paths. In areas where subsurface interface topography varies similarly with surface topography, surface DEM can be used to simulate potential subsurface lateral flow path reasonably so the cost associated with obtaining depth to subsurface water-restricting layer can be minimized.

Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

PubMed

Fesharaki, Nooshin Jafari; Pourghassem, Hossein

2013-07-01

Due to the daily mass production and the widespread variation of medical X-ray images, it is necessary to classify these for searching and retrieving proposes, especially for content-based medical image retrieval systems. In this paper, a medical X-ray image hierarchical classification structure based on a novel merging and splitting scheme and using shape and texture features is proposed. In the first level of the proposed structure, to improve the classification performance, similar classes with regard to shape contents are grouped based on merging measures and shape features into the general overlapped classes. In the next levels of this structure, the overlapped classes split in smaller classes based on the classification performance of combination of shape and texture features or texture features only. Ultimately, in the last levels, this procedure is also continued forming all the classes, separately. Moreover, to optimize the feature vector in the proposed structure, we use orthogonal forward selection algorithm according to Mahalanobis class separability measure as a feature selection and reduction algorithm. In other words, according to the complexity and inter-class distance of each class, a sub-space of the feature space is selected in each level and then a supervised merging and splitting scheme is applied to form the hierarchical classification. The proposed structure is evaluated on a database consisting of 2158 medical X-ray images of 18 classes (IMAGECLEF 2005 database) and accuracy rate of 93.6% in the last level of the hierarchical structure for an 18-class classification problem is obtained.

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

ERIC Educational Resources Information Center

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

Large Scale Ice Water Path and 3-D Ice Water Content

DOE Data Explorer

Liu, Guosheng

2008-01-15

Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.

Identification and correction of road courses by merging successive segments and using improved attributes

NASA Astrophysics Data System (ADS)

Bulatov, Dimitri; Häufel, Gisela; Pohl, Melanie

2016-10-01

Both in military and civil applications, there is an urgent need for a highly up-to-date road data, which should be ideally semantically structured (into main roads, walking paths, escape ways, etc.) with application-driven attributes, such as road width, road type, surface condition and many others. A vectorization algorithm processing aerial images recently acquired yields an up-to-date road vector data, which are, however, often represented by wriggly, noisy polylines without semantics. The reasons for zigzagged street courses are insufficiencies in the intermediate results of sensor data processing (orthophotos, elevation maps) and occlusions caused by trees, buildings, and others. In the current contribution, an improved computation of geometric attributes will be explained which makes a difference between straight and circular (or elliptic) polylines. Using improved attributes, the candidates for polylines having identical course and sharing a junction are determined. From such candidates, we form chains of polylines. These chains correspond better to the intuitive perception of the term street than the previously used road polylines, because, even after being interrupted by narrower side roads, a chain maintains its label. The generalization of chains with simultaneously adjusting positions of junctions is evidently performed. We apply a generalization with the purpose-based modification of a well-known polyline simplification algorithm once chain-wise and once polyline-wise in order to show - by means of qualitative results - the advantages of the chain-wise generalization.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

NASA Astrophysics Data System (ADS)

Selva Bhuvaneswari, K.; Geetha, P.

2017-05-01

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.

A statistical-based scheduling algorithm in automated data path synthesis

NASA Technical Reports Server (NTRS)

Jeon, Byung Wook; Lursinsap, Chidchanok

1992-01-01

In this paper, we propose a new heuristic scheduling algorithm based on the statistical analysis of the cumulative frequency distribution of operations among control steps. It has a tendency of escaping from local minima and therefore reaching a globally optimal solution. The presented algorithm considers the real world constraints such as chained operations, multicycle operations, and pipelined data paths. The result of the experiment shows that it gives optimal solutions, even though it is greedy in nature.

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

NASA Astrophysics Data System (ADS)

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

2012-01-01

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

The profile algorithm for microwave delay estimation from water vapor radiometer data

NASA Technical Reports Server (NTRS)

Robinson, Steven E.

1988-01-01

A new algorithm has been developed for the estimation of tropospheric microwave path delays from water vapor radiometer (WVR) data, which does not require site and weather dependent empirical parameters to produce accuracy better than 0.3 cm of delay. Instead of taking the conventional linear approach, the new algorithm first uses the observables with an emission model to determine an approximate form of the vertical water vapor distribution, which is then explicitly integrated to estimate wet path delays in a second step. The intrinsic accuracy of this algorithm, excluding uncertainties caused by the radiometers and the emission model, has been examined for two channel WVR data using path delays and corresponding simulated observables computed from archived radiosonde data. It is found that annual rms errors for a wide range of sites average 0.18 cm in the absence of clouds, 0.22 cm in cloudy weather, and 0.19 cm overall. In clear weather, the new algorithm's accuracy is comparable to the best that can be obtained from conventional linear algorithms, while in cloudy weather it offers a 35 percent improvement.

A new algorithm for microwave delay estimation from water vapor radiometer data

NASA Technical Reports Server (NTRS)

Robinson, S. E.

1986-01-01

A new algorithm has been developed for the estimation of tropospheric microwave path delays from water vapor radiometer (WVR) data, which does not require site and weather dependent empirical parameters to produce high accuracy. Instead of taking the conventional linear approach, the new algorithm first uses the observables with an emission model to determine an approximate form of the vertical water vapor distribution which is then explicitly integrated to estimate wet path delays, in a second step. The intrinsic accuracy of this algorithm has been examined for two channel WVR data using path delays and stimulated observables computed from archived radiosonde data. It is found that annual RMS errors for a wide range of sites are in the range from 1.3 mm to 2.3 mm, in the absence of clouds. This is comparable to the best overall accuracy obtainable from conventional linear algorithms, which must be tailored to site and weather conditions using large radiosonde data bases. The new algorithm's accuracy and flexibility are indications that it may be a good candidate for almost all WVR data interpretation.

A Bat Algorithm with Mutation for UCAV Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518

Floyd-warshall algorithm to determine the shortest path based on android

NASA Astrophysics Data System (ADS)

Ramadiani; Bukhori, D.; Azainil; Dengen, N.

2018-04-01

The development of technology has made all areas of life easier now, one of which is the ease of obtaining geographic information. The use of geographic information may vary according to need, for example, the digital map learning, navigation systems, observations area, and much more. With the support of adequate infrastructure, almost no one will ever get lost to a destination even to foreign places or that have never been visited before. The reasons why many institutions and business entities use technology to improve services to consumers and to streamline the production process undertaken and so forth. Speaking of the efficient, there are many elements related to efficiency in navigation systems, and one of them is the efficiency in terms of distance. The shortest distance determination algorithm required in this research is used Floyd-Warshall Algorithm. Floyd-Warshall algorithm is the algorithm to find the fastest path and the shortest distance between 2 nodes, while the program is intended to find the path of more than 2 nodes.

Algorithms for constructing optimal paths and statistical analysis of passenger traffic

NASA Astrophysics Data System (ADS)

Trofimov, S. P.; Druzhinina, N. G.; Trofimova, O. G.

2018-01-01

Several existing information systems of urban passenger transport (UPT) are considered. Author’s UPT network model is presented. To a passenger a new service is offered that is the best path from one stop to another stop at a specified time. The algorithm and software implementation for finding the optimal path are presented. The algorithm uses the current UPT schedule. The article also describes the algorithm of statistical analysis of trip payments by the electronic E-cards. The algorithm allows obtaining the density of passenger traffic during the day. This density is independent of the network topology and UPT schedules. The resulting density of the traffic flow can solve a number of practical problems. In particular, the forecast for the overflow of passenger transport in the «rush» hours, the quantitative comparison of different topologies transport networks, constructing of the best UPT timetable. The efficiency of the proposed integrated approach is demonstrated by the example of the model town with arbitrary dimensions.

Multi-chord fiber-coupled interferometer with a long coherence length laser

NASA Astrophysics Data System (ADS)

Merritt, Elizabeth C.; Lynn, Alan G.; Gilmore, Mark A.; Hsu, Scott C.

2012-03-01

This paper describes a 561 nm laser heterodyne interferometer that provides time-resolved measurements of line-integrated plasma electron density within the range of 1015-1018 cm-2. Such plasmas are produced by railguns on the plasma liner experiment, which aims to produce μs-, cm-, and Mbar-scale plasmas through the merging of 30 plasma jets in a spherically convergent geometry. A long coherence length, 320 mW laser allows for a strong, sub-fringe phase-shift signal without the need for closely matched probe and reference path lengths. Thus, only one reference path is required for all eight probe paths, and an individual probe chord can be altered without altering the reference or other probe path lengths. Fiber-optic decoupling of the probe chord optics on the vacuum chamber from the rest of the system allows the probe paths to be easily altered to focus on different spatial regions of the plasma. We demonstrate that sub-fringe resolution capability allows the interferometer to operate down to line-integrated densities of the order of 5 × 1015 cm-2.

Merging of multi-string BWTs with applications

PubMed Central

Holt, James; McMillan, Leonard

2014-01-01

Motivation: The throughput of genomic sequencing has increased to the point that is overrunning the rate of downstream analysis. This, along with the desire to revisit old data, has led to a situation where large quantities of raw, and nearly impenetrable, sequence data are rapidly filling the hard drives of modern biology labs. These datasets can be compressed via a multi-string variant of the Burrows–Wheeler Transform (BWT), which provides the side benefit of searches for arbitrary k-mers within the raw data as well as the ability to reconstitute arbitrary reads as needed. We propose a method for merging such datasets for both increased compression and downstream analysis. Results: We present a novel algorithm that merges multi-string BWTs in O(LCS×N) time where LCS is the length of their longest common substring between any of the inputs, and N is the total length of all inputs combined (number of symbols) using O(N×log2(F)) bits where F is the number of multi-string BWTs merged. This merged multi-string BWT is also shown to have a higher compressibility compared with the input multi-string BWTs separately. Additionally, we explore some uses of a merged multi-string BWT for bioinformatics applications. Availability and implementation: The MSBWT package is available through PyPI with source code located at https://code.google.com/p/msbwt/. Contact: holtjma@cs.unc.edu PMID:25172922

Simulation Results for Airborne Precision Spacing along Continuous Descent Arrivals

NASA Technical Reports Server (NTRS)

Barmore, Bryan E.; Abbott, Terence S.; Capron, William R.; Baxley, Brian T.

2008-01-01

This paper describes the results of a fast-time simulation experiment and a high-fidelity simulator validation with merging streams of aircraft flying Continuous Descent Arrivals through generic airspace to a runway at Dallas-Ft Worth. Aircraft made small speed adjustments based on an airborne-based spacing algorithm, so as to arrive at the threshold exactly at the assigned time interval behind their Traffic-To-Follow. The 40 aircraft were initialized at different altitudes and speeds on one of four different routes, and then merged at different points and altitudes while flying Continuous Descent Arrivals. This merging and spacing using flight deck equipment and procedures to augment or implement Air Traffic Management directives is called Flight Deck-based Merging and Spacing, an important subset of a larger Airborne Precision Spacing functionality. This research indicates that Flight Deck-based Merging and Spacing initiated while at cruise altitude and well prior to the Terminal Radar Approach Control entry can significantly contribute to the delivery of aircraft at a specified interval to the runway threshold with a high degree of accuracy and at a reduced pilot workload. Furthermore, previously documented work has shown that using a Continuous Descent Arrival instead of a traditional step-down descent can save fuel, reduce noise, and reduce emissions. Research into Flight Deck-based Merging and Spacing is a cooperative effort between government and industry partners.

The transcultural diabetes nutrition algorithm toolkit: survey and content validation in the United States, Mexico, and Taiwan.

PubMed

Hamdy, Osama; Marchetti, Albert; Hegazi, Refaat A; Mechanick, Jeffrey I

2014-06-01

Evidence demonstrates that medical nutrition therapy (MNT) in prediabetes and type 2 diabetes (T2D) improves glycemic control and reduces diabetes risks and complications. Consequently, MNT is included in current clinical practice guidelines. Guideline recommendations, however, are frequently limited by their complexity, contradictions, personal and cultural rigidity, and compromised portability. The transcultural Diabetes Nutrition Algorithm (tDNA) was developed to overcome these limitations. To facilitate tDNA uptake and usage, an instructional Patient Algorithm Therapy (PATh) toolkit was created. Content validation of tDNA-PATh is needed before widespread implementation. Healthcare providers (n=837) in Mexico (n=261), Taiwan (n=250), and the United States (n=326) were questioned about challenges implementing MNT in clinical practice and the projected utilization and impact of tDNA-PATh. To assess the international portability and applicability of tDNA-PATh, the survey was conducted in countries with distinct ethnic and cultural attributes. Potential respondents were screened for professional and practice demographics related to diabetes. The questionnaire was administered electronically after respondents were exposed to core tDNA-PATh components. Overall, 61% of respondents thought that tDNA-PATh could help overcome MNT implementation challenges, 91% indicated positive impressions, 83% believed they would adopt tDNA-PATh, and 80% thought tDNA-PATh would be fairly easy to implement. tDNA-PATh appears to be an effective culturally sensitive tool to foster MNT in clinical practice. By providing simple culturally specific instructions, tDNA-PATh may help to overcome current impediments to implementing recommended lifestyle modifications. Specific guidance provided by tDNA-PATh, together with included patient education materials, may increase healthcare provider efficiency.

How Certain are We of the Uncertainties in Recent Ozone Profile Trend Assessments of Merged Limbo Ccultation Records? Challenges and Possible Ways Forward

NASA Technical Reports Server (NTRS)

Hubert, Daan; Lambert, Jean-Christopher; Verhoelst, Tijl; Granville, Jose; Keppens, Arno; Baray, Jean-Luc; Cortesi, Ugo; Degenstein, D. A.; Froidevaux, Lucien; Godin-Beekmann, Sophie;

Efficient Merge and Insert Operations for Binary Heaps and Trees

NASA Technical Reports Server (NTRS)

Kuszmaul, Christopher Lee; Woo, Alex C. (Technical Monitor)

2000-01-01

Binary heaps and binary search trees merge efficiently. We introduce a new amortized analysis that allows us to prove the cost of merging either binary heaps or balanced binary trees is O(l), in the amortized sense. The standard set of other operations (create, insert, delete, extract minimum, in the case of binary heaps, and balanced binary trees, as well as a search operation for balanced binary trees) remain with a cost of O(log n). For binary heaps implemented as arrays, we show a new merge algorithm that has a single operation cost for merging two heaps, a and b, of O(absolute value of a + min(log absolute value of b log log absolute value of b. log absolute value of a log absolute value of b). This is an improvement over O(absolute value of a + log absolute value of a log absolute value of b). The cost of the new merge is so low that it can be used in a new structure which we call shadow heaps. to implement the insert operation to a tunable efficiency. Shadow heaps support the insert operation for simple priority queues in an amortized time of O(f(n)) and other operations in time O((log n log log n)/f (n)), where 1 less than or equal to f (n) less than or equal to log log n. More generally, the results here show that any data structure with operations that change its size by at most one, with the exception of a merge (aka meld) operation, can efficiently amortize the cost of the merge under conditions that are true for most implementations of binary heaps and search trees.

Path Planning Algorithms for the Adaptive Sensor Fleet

NASA Technical Reports Server (NTRS)

Stoneking, Eric; Hosler, Jeff

2005-01-01

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

Label-based routing for a family of small-world Farey graphs.

PubMed

Zhai, Yinhu; Wang, Yinhe

2016-05-11

We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure.

Label-based routing for a family of small-world Farey graphs

NASA Astrophysics Data System (ADS)

Zhai, Yinhu; Wang, Yinhe

2016-05-01

We introduce an informative labelling method for vertices in a family of Farey graphs, and deduce a routing algorithm on all the shortest paths between any two vertices in Farey graphs. The label of a vertex is composed of the precise locating position in graphs and the exact time linking to graphs. All the shortest paths routing between any pair of vertices, which number is exactly the product of two Fibonacci numbers, are determined only by their labels, and the time complexity of the algorithm is O(n). It is the first algorithm to figure out all the shortest paths between any pair of vertices in a kind of deterministic graphs. For Farey networks, the existence of an efficient routing protocol is of interest to design practical communication algorithms in relation to dynamical processes (including synchronization and structural controllability) and also to understand the underlying mechanisms that have shaped their particular structure.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

Congestion patterns of electric vehicles with limited battery capacity.

PubMed

Jing, Wentao; Ramezani, Mohsen; An, Kun; Kim, Inhi

2018-01-01

The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm.

Cooperative organic mine avoidance path planning

NASA Astrophysics Data System (ADS)

McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David

2005-06-01

The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.

Congestion patterns of electric vehicles with limited battery capacity

PubMed Central

2018-01-01

The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm. PMID:29543875

A maximally stable extremal region based scene text localization method

NASA Astrophysics Data System (ADS)

Xiao, Chengqiu; Ji, Lixin; Gao, Chao; Li, Shaomei

2015-07-01

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

Traffic engineering and regenerator placement in GMPLS networks with restoration

NASA Astrophysics Data System (ADS)

Yetginer, Emre; Karasan, Ezhan

2002-07-01

In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.

Speed and path control for conflict-free flight in high air traffic demand in terminal airspace

NASA Astrophysics Data System (ADS)

Rezaei, Ali

To accommodate the growing air traffic demand, flights will need to be planned and navigated with a much higher level of precision than today's aircraft flight path. The Next Generation Air Transportation System (NextGen) stands to benefit significantly in safety and efficiency from such movement of aircraft along precisely defined paths. Air Traffic Operations (ATO) relying on such precision--the Precision Air Traffic Operations or PATO--are the foundation of high throughput capacity envisioned for the future airports. In PATO, the preferred method is to manage the air traffic by assigning a speed profile to each aircraft in a given fleet in a given airspace (in practice known as (speed control). In this research, an algorithm has been developed, set in the context of a Hybrid Control System (HCS) model, that determines whether a speed control solution exists for a given fleet of aircraft in a given airspace and if so, computes this solution as a collective speed profile that assures separation if executed without deviation. Uncertainties such as weather are not considered but the algorithm can be modified to include uncertainties. The algorithm first computes all feasible sequences (i.e., all sequences that allow the given fleet of aircraft to reach destinations without violating the FAA's separation requirement) by looking at all pairs of aircraft. Then, the most likely sequence is determined and the speed control solution is constructed by a backward trajectory generation, starting with the aircraft last out and proceeds to the first out. This computation can be done for different sequences in parallel which helps to reduce the computation time. If such a solution does not exist, then the algorithm calculates a minimal path modification (known as path control) that will allow separation-compliance speed control. We will also prove that the algorithm will modify the path without creating a new separation violation. The new path will be generated by adding new waypoints in the airspace. As a byproduct, instead of minimal path modification, one can use the aircraft arrival time schedule to generate the sequence in which the aircraft reach their destinations.

Social network analysis using k-Path centrality method

NASA Astrophysics Data System (ADS)

Taniarza, Natya; Adiwijaya; Maharani, Warih

2018-03-01

k-Path centrality is deemed as one of the effective methods to be applied in centrality measurement in which the influential node is estimated as the node that is being passed by information path frequently. Regarding this, k-Path centrality has been employed in the analysis of this paper specifically by adapting random-algorithm approach in order to: (1) determine the influential user’s ranking in a social media Twitter; and (2) ascertain the influence of parameter α in the numeration of k-Path centrality. According to the analysis, the findings showed that the method of k-Path centrality with random-algorithm approach can be used to determine user’s ranking which influences in the dissemination of information in Twitter. Furthermore, the findings also showed that parameter α influenced the duration and the ranking results: the less the α value, the longer the duration, yet the ranking results were more stable.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

On load paths and load bearing topology from finite element analysis

NASA Astrophysics Data System (ADS)

Kelly, D.; Reidsema, C.; Lee, M.

2010-06-01

Load paths can be mapped from vector plots of 'pointing stress vectors'. They define a path along which a component of load remains constant as it traverses the solution domain. In this paper the theory for the paths is first defined. Properties of the plots that enable a designer to interpret the structural behavior from the contours are then identified. Because stress is a second order tensor defined on an orthogonal set of axes, the vector plots define separate paths for load transfer in each direction of the set of axes. An algorithm is therefore presented that combines the vectors to define a topology to carry the loads. The algorithm is shown to straighten the paths reducing bending moments and removing stress concentration. Application to a bolted joint, a racing car body and a yacht hull demonstrate the usefulness of the plots.

End-to-end simulation of bunch merging for a muon collider

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bao, Yu; Stratakis, Diktys; Hanson, Gail G.

2015-05-03

Muon accelerator beams are commonly produced indirectly through pion decay by interaction of a charged particle beam with a target. Efficient muon capture requires the muons to be first phase-rotated by rf cavities into a train of 21 bunches with much reduced energy spread. Since luminosity is proportional to the square of the number of muons per bunch, it is crucial for a Muon Collider to use relatively few bunches with many muons per bunch. In this paper we will describe a bunch merging scheme that should achieve this goal. We present for the first time a complete end-to-end simulationmore » of a 6D bunch merger for a Muon Collider. The 21 bunches arising from the phase-rotator, after some initial cooling, are merged in longitudinal phase space into seven bunches, which then go through seven paths with different lengths and reach the final collecting "funnel" at the same time. The final single bunch has a transverse and a longitudinal emittance that matches well with the subsequent 6D rectilinear cooling scheme.« less

Laboratory plasma physics experiments using merging supersonic plasma jets

DOE PAGES

Hsu, S. C.; Moser, A. L.; Merritt, E. C.; ...

2015-04-01

We describe a laboratory plasma physics experiment at Los Alamos National Laboratory that uses two merging supersonic plasma jets formed and launched by pulsed-power-driven railguns. The jets can be formed using any atomic species or mixture available in a compressed-gas bottle and have the following nominal initial parameters at the railgun nozzle exit: n e ≈ n i ~ 10¹⁶ cm⁻³, T e ≈ T i ≈ 1.4 eV, V jet ≈ 30–100 km/s, mean chargemore » $$\\bar{Z}$$ ≈ 1, sonic Mach number M s ≡ V jet/C s > 10, jet diameter = 5 cm, and jet length ≈ 20 cm. Experiments to date have focused on the study of merging-jet dynamics and the shocks that form as a result of the interaction, in both collisional and collisionless regimes with respect to the inter-jet classical ion mean free path, and with and without an applied magnetic field. However, many other studies are also possible, as discussed in this paper.« less

Laboratory plasma physics experiments using merging supersonic plasma jets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hsu, S. C.; Moser, A. L.; Merritt, E. C.

We describe a laboratory plasma physics experiment at Los Alamos National Laboratory that uses two merging supersonic plasma jets formed and launched by pulsed-power-driven railguns. The jets can be formed using any atomic species or mixture available in a compressed-gas bottle and have the following nominal initial parameters at the railgun nozzle exit: n e ≈ n i ~ 10¹⁶ cm⁻³, T e ≈ T i ≈ 1.4 eV, V jet ≈ 30–100 km/s, mean chargemore » $$\\bar{Z}$$ ≈ 1, sonic Mach number M s ≡ V jet/C s > 10, jet diameter = 5 cm, and jet length ≈ 20 cm. Experiments to date have focused on the study of merging-jet dynamics and the shocks that form as a result of the interaction, in both collisional and collisionless regimes with respect to the inter-jet classical ion mean free path, and with and without an applied magnetic field. However, many other studies are also possible, as discussed in this paper.« less

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

NASA Astrophysics Data System (ADS)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

Results from Two Low Mass Cosmic Ray Experiments Flown on the HASP Platform

NASA Astrophysics Data System (ADS)

Fontenot, R. S.; Hollerman, W. A.; Tittsworth, M.; Fountain, W.; Christl, M.; Thibodaux, C.; Broussard, B. M.

2009-03-01

The High Altitude Student Payload (HASP) program is designed to carry twelve student experiments to an altitude of about 123,000 feet (˜37 km). In 2006, students participated in the first HASP launch to measure cosmic ray intensities using traditional film and absorbers. This 10 kg payload flew from Fort Sumner, New Mexico in early September 2006 and was a great success. In 2007, students participated in the second HASP flight to measure the cosmic ray intensity and flux using a traditional film and absorber stack with five layers of optically stimulated luminescent (OSL) dosimeters. Results from both payloads showed that the cosmic ray flux decreases as a function of payload depth. As the cosmic rays go through the stack, they deposit their energy in the payload material. Determining cosmic ray flux is a tedious task. It involves digitizing the film and determining the real cosmic ray density. For the first HASP payload, students used a program known as GlobalLab to count particles. For the second payload, the students decided to use a combination of the GREYCStoration image regularization algorithm, an embossing filter, and a depth-merging filter to reconstruct the paths of the cosmic rays.

Path planning algorithms for assembly sequence planning. [in robot kinematics

NASA Technical Reports Server (NTRS)

Krishnan, S. S.; Sanderson, Arthur C.

1991-01-01

Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.

Path statistics, memory, and coarse-graining of continuous-time random walks on networks

PubMed Central

Kion-Crosby, Willow; Morozov, Alexandre V.

2015-01-01

Continuous-time random walks (CTRWs) on discrete state spaces, ranging from regular lattices to complex networks, are ubiquitous across physics, chemistry, and biology. Models with coarse-grained states (for example, those employed in studies of molecular kinetics) or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics. However, existing methods for analyzing CTRWs on complex energy landscapes do not address these effects. Here we use statistical mechanics of the nonequilibrium path ensemble to characterize first-passage CTRWs on networks with arbitrary connectivity, energy landscape, and waiting time distributions. Our approach can be applied to calculating higher moments (beyond the mean) of path length, time, and action, as well as statistics of any conservative or non-conservative force along a path. For homogeneous networks, we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process with its discrete-time projection. For more general models, we obtain recursion relations, reminiscent of transfer matrix and exact enumeration techniques, to efficiently calculate path statistics numerically. We have implemented our algorithm in PathMAN (Path Matrix Algorithm for Networks), a Python script that users can apply to their model of choice. We demonstrate the algorithm on a few representative examples which underscore the importance of non-exponential distributions, memory, and coarse-graining in CTRWs. PMID:26646868

Effect of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths.

PubMed

Payne, Velma L; Medvedeva, Olga; Legowski, Elizabeth; Castine, Melissa; Tseytlin, Eugene; Jukic, Drazen; Crowley, Rebecca S

2009-11-01

Determine effects of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths. Determine if limited enforcement in a medical tutoring system inhibits students from learning the optimal and most efficient solution path. Describe the type of deviations from the optimal solution path that occur during tutoring, and how these deviations change over time. Determine if the size of the problem-space (domain scope), has an effect on learning gains when using a tutor with limited enforcement. Analyzed data mined from 44 pathology residents using SlideTutor-a Medical Intelligent Tutoring System in Dermatopathology that teaches histopathologic diagnosis and reporting skills based on commonly used diagnostic algorithms. Two subdomains were included in the study representing sub-algorithms of different sizes and complexities. Effects of the tutoring system on student errors, goal states and solution paths were determined. Students gradually increase the frequency of steps that match the tutoring system's expectation of expert performance. Frequency of errors gradually declines in all categories of error significance. Student performance frequently differs from the tutor-defined optimal path. However, as students continue to be tutored, they approach the optimal solution path. Performance in both subdomains was similar for both errors and goal differences. However, the rate at which students progress toward the optimal solution path differs between the two domains. Tutoring in superficial perivascular dermatitis, the larger and more complex domain was associated with a slower rate of approximation towards the optimal solution path. Students benefit from a limited-enforcement tutoring system that leverages diagnostic algorithms but does not prevent alternative strategies. Even with limited enforcement, students converge toward the optimal solution path.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Experimental and analytical study of secondary path variations in active engine mounts

NASA Astrophysics Data System (ADS)

Hausberg, Fabian; Scheiblegger, Christian; Pfeffer, Peter; Plöchl, Manfred; Hecker, Simon; Rupp, Markus

2015-03-01

Active engine mounts (AEMs) provide an effective solution to further improve the acoustic and vibrational comfort of passenger cars. Typically, adaptive feedforward control algorithms, e.g., the filtered-x-least-mean-squares (FxLMS) algorithm, are applied to cancel disturbing engine vibrations. These algorithms require an accurate estimate of the AEM active dynamic characteristics, also known as the secondary path, in order to guarantee control performance and stability. This paper focuses on the experimental and theoretical study of secondary path variations in AEMs. The impact of three major influences, namely nonlinearity, change of preload and component temperature, on the AEM active dynamic characteristics is experimentally analyzed. The obtained test results are theoretically investigated with a linear AEM model which incorporates an appropriate description for elastomeric components. A special experimental set-up extends the model validation of the active dynamic characteristics to higher frequencies up to 400 Hz. The theoretical and experimental results show that significant secondary path variations are merely observed in the frequency range of the AEM actuator's resonance frequency. These variations mainly result from the change of the component temperature. As the stability of the algorithm is primarily affected by the actuator's resonance frequency, the findings of this paper facilitate the design of AEMs with simpler adaptive feedforward algorithms. From a practical point of view it may further be concluded that algorithmic countermeasures against instability are only necessary in the frequency range of the AEM actuator's resonance frequency.

Kleinberg Complex Networks

DTIC Science & Technology

2014-10-21

linear combinations of paths. This project featured research on two classes of routing problems , namely traveling salesman problems and multicommodity...flows. One highlight of this research was our discovery of a polynomial-time algorithm for the metric traveling salesman s-t path problem whose...metric TSP would resolve one of the most venerable open problems in the theory of approximation algorithms. Our research on traveling salesman

Robot path planning using a genetic algorithm

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu

1988-01-01

Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.

A Spatial Cognitive Map and a Human-Like Memory Model Dedicated to Pedestrian Navigation in Virtual Urban Environments

NASA Astrophysics Data System (ADS)

Thomas, Romain; Donikian, Stéphane

Many articles dealing with agent navigation in an urban environment involve the use of various heuristics. Among them, one is prevalent: the search of the shortest path between two points. This strategy impairs the realism of the resulting behaviour. Indeed, psychological studies state that such a navigation behaviour is conditioned by the knowledge the subject has of its environment. Furthermore, the path a city dweller can follow may be influenced by many factors like his daily habits, or the path simplicity in term of minimum of direction changes. It appeared interesting to us to investigate how to mimic human navigation behavior with an autonomous agent. The solution we propose relies on an architecture based on a generic model of informed environment, a spatial cognitive map model merged with a human-like memory model, representing the agent's temporal knowledge of the environment, it gained along its experiences of navigation.

The Container Problem in Bubble-Sort Graphs

NASA Astrophysics Data System (ADS)

Suzuki, Yasuto; Kaneko, Keiichi

Bubble-sort graphs are variants of Cayley graphs. A bubble-sort graph is suitable as a topology for massively parallel systems because of its simple and regular structure. Therefore, in this study, we focus on n-bubble-sort graphs and propose an algorithm to obtain n-1 disjoint paths between two arbitrary nodes in time bounded by a polynomial in n, the degree of the graph plus one. We estimate the time complexity of the algorithm and the sum of the path lengths after proving the correctness of the algorithm. In addition, we report the results of computer experiments evaluating the average performance of the algorithm.

Cloud Computing Security Model with Combination of Data Encryption Standard Algorithm (DES) and Least Significant Bit (LSB)

NASA Astrophysics Data System (ADS)

Basri, M.; Mawengkang, H.; Zamzami, E. M.

2018-03-01

Limitations of storage sources is one option to switch to cloud storage. Confidentiality and security of data stored on the cloud is very important. To keep up the confidentiality and security of such data can be done one of them by using cryptography techniques. Data Encryption Standard (DES) is one of the block cipher algorithms used as standard symmetric encryption algorithm. This DES will produce 8 blocks of ciphers combined into one ciphertext, but the ciphertext are weak against brute force attacks. Therefore, the last 8 block cipher will be converted into 8 random images using Least Significant Bit (LSB) algorithm which later draws the result of cipher of DES algorithm to be merged into one.

An improved hierarchical A * algorithm in the optimization of parking lots

NASA Astrophysics Data System (ADS)

Wang, Yong; Wu, Junjuan; Wang, Ying

2017-08-01

In the parking lot parking path optimization, the traditional evaluation index is the shortest distance as the best index and it does not consider the actual road conditions. Now, the introduction of a more practical evaluation index can not only simplify the hardware design of the boot system but also save the software overhead. Firstly, we establish the parking lot network graph RPCDV mathematical model and all nodes in the network is divided into two layers which were constructed using different evaluation function base on the improved hierarchical A * algorithm which improves the time optimal path search efficiency and search precision of the evaluation index. The final results show that for different sections of the program attribute parameter algorithm always faster the time to find the optimal path.

Thread Graphs, Linear Rank-Width and Their Algorithmic Applications

NASA Astrophysics Data System (ADS)

Ganian, Robert

The introduction of tree-width by Robertson and Seymour [7] was a breakthrough in the design of graph algorithms. A lot of research since then has focused on obtaining a width measure which would be more general and still allowed efficient algorithms for a wide range of NP-hard problems on graphs of bounded width. To this end, Oum and Seymour have proposed rank-width, which allows the solution of many such hard problems on a less restricted graph classes (see e.g. [3,4]). But what about problems which are NP-hard even on graphs of bounded tree-width or even on trees? The parameter used most often for these exceptionally hard problems is path-width, however it is extremely restrictive - for example the graphs of path-width 1 are exactly paths.

Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model Generation for ns-3

DTIC Science & Technology

2015-12-01

through visiting the inferred automata o Fuzzing of an implementation by generating altered message formats We tested with 3 versions of Netzob. First...relationships. Afterwards, we used the Automata module to generate state machines using different functions: “generateChainedStateAutomata...The “generatePTAAutomata” takes as input several communication sessions and then identifies common paths and merges these into a single automata . The

Homotopy Algorithm for Fixed Order Mixed H2/H(infinity) Design

NASA Technical Reports Server (NTRS)

Whorton, Mark; Buschek, Harald; Calise, Anthony J.

1996-01-01

Recent developments in the field of robust multivariable control have merged the theories of H-infinity and H-2 control. This mixed H-2/H-infinity compensator formulation allows design for nominal performance by H-2 norm minimization while guaranteeing robust stability to unstructured uncertainties by constraining the H-infinity norm. A key difficulty associated with mixed H-2/H-infinity compensation is compensator synthesis. A homotopy algorithm is presented for synthesis of fixed order mixed H-2/H-infinity compensators. Numerical results are presented for a four disk flexible structure to evaluate the efficiency of the algorithm.

Planification de trajectoires pour placement automatise de fibres sur surfaces de geometries complexes

NASA Astrophysics Data System (ADS)

Hely, Clement

During the past 50 years, the use of composite materials drastically increase, mainly thanks to the interest of aeronautical industries for these strong and lightweight materials. To improve the productivity of composite materials manufacturing some of the largest aeronautics companies began to develop automated processes such as Automated Fibre Placement (AFP). The AFP workcells currently used by the industry were mainly developed for production of large, nearly flat, plates with low curvatures such as aircraft fuselages. However, the fields of aeronautics and sport goods production begin nowadays to show an interest for manufacturing of smaller and more complex parts. The aim of the project in which this research takes place is to design a new AFP workcell and to develop new techniques allowing production of parts with small size and complex geometry. The work presented in this thesis focuses on the path planning on multi-axial revolution surfaces, e.g. Y-shaped tubes of constant circular cross section. Several path planning algorithms will be presented aiming at the exhaustive coverage of a mandrel with pre-impregnated (prepreg) composite tape. The methodology used in two of these algorithms is to individually cover each branch of the Y-shaped part with paths deriving from a helix. In the first one, the helix will be cut at the boundary between a branch and the junction region (algorithm HD) while in the second (algorithm HA) the pseudo-helix path can be adjusted to follow this boundary. These two methods were shown to have some drawbacks compromising their practical use and possibly leading to parts with diminished mechanical properties. To avoid these drawbacks, two others algorithms were developed with a new methodology. With them, the aim is to cover two branches of the Y-shape with a continuous course (i.e. without cut). The first one uses a well known strategy which defines plies with a constant fibre orientation. Parallel paths are then computed to generate a full and uniform ply covering two branches. Once again this method suffers from a main drawback, namely that it can produce highly curved paths leading to manufacturing defects. To overcome this limitation, a last algorithm is proposed ensuring that the maximal curvature of a trajectory stays below a fixed threshold. However, fulfilling this constraint prevents to predict the complete shape of the path and to ensure a perfectly uniform coverage. It is thus proposed to generate an exhaustive set of trajectories having different shapes and covering all the part. Then, a selection algorithm is used to choose the ones which are best suited according to selection criteria. To help the definition of these criteria, a finite element analysis is conducted to give some insight concerning the best suited shapes for specific loading cases. Finally, simulations were carried out with a workcell constituted by a robotic manipulator associated with a rotary table to verify the feasibility of the paths generated by the different algorithms.

Comparison of Genetic Algorithm and Hill Climbing for Shortest Path Optimization Mapping

NASA Astrophysics Data System (ADS)

Fronita, Mona; Gernowo, Rahmat; Gunawan, Vincencius

2018-02-01

Traveling Salesman Problem (TSP) is an optimization to find the shortest path to reach several destinations in one trip without passing through the same city and back again to the early departure city, the process is applied to the delivery systems. This comparison is done using two methods, namely optimization genetic algorithm and hill climbing. Hill Climbing works by directly selecting a new path that is exchanged with the neighbour's to get the track distance smaller than the previous track, without testing. Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations. To simplify the process of determining the shortest path supported by the development of software that uses the google map API. Tests carried out as much as 20 times with the number of city 8, 16, 24 and 32 to see which method is optimal in terms of distance and time computation. Based on experiments conducted with a number of cities 3, 4, 5 and 6 producing the same value and optimal distance for the genetic algorithm and hill climbing, the value of this distance begins to differ with the number of city 7. The overall results shows that these tests, hill climbing are more optimal to number of small cities and the number of cities over 30 optimized using genetic algorithms.

A novel line segment detection algorithm based on graph search

NASA Astrophysics Data System (ADS)

Zhao, Hong-dan; Liu, Guo-ying; Song, Xu

2018-02-01

To overcome the problem of extracting line segment from an image, a method of line segment detection was proposed based on the graph search algorithm. After obtaining the edge detection result of the image, the candidate straight line segments are obtained in four directions. For the candidate straight line segments, their adjacency relationships are depicted by a graph model, based on which the depth-first search algorithm is employed to determine how many adjacent line segments need to be merged. Finally we use the least squares method to fit the detected straight lines. The comparative experimental results verify that the proposed algorithm has achieved better results than the line segment detector (LSD).

PCN-index derivation at World Data Center for Geomagnetism, Copenhagen, DTU Space

NASA Astrophysics Data System (ADS)

Stolle, C.; Matzka, J.

2012-04-01

The Polar Cap North (PCN) index is based on a correlation between geomagnetic disturbances at the Qaanaaq geomagnetic observatory (IAGA code THL) and the merging electric field derived from solar wind parameters. The index is therefore meant to provide a fast ground based single station indicator for variations in the merging electric field without being dependent on satellite observations. The PC index will be subject to an IAGA endorsement process during IAGA Scientific Assembly 2013. Actually the WDC provides near real time PC-indices and post-processed final PC-indices based on former developed algorithms. However, the coefficients used for calculating the PCN distributed by the WDC Copenhagen are presently not reproducible. In the frame of the IAGA endorsement, DTU Space tests new coefficients mainly based on published algorithms. This presentation will report on activities at the WDC Copenhagen and on the current status at DTU Space with respect to the preparation for the IAGA endorsement process of the PCN-index.

Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways

PubMed Central

Seyler, Sean L.; Kumar, Avishek; Thorpe, M. F.; Beckstein, Oliver

2015-01-01

Diverse classes of proteins function through large-scale conformational changes and various sophisticated computational algorithms have been proposed to enhance sampling of these macromolecular transition paths. Because such paths are curves in a high-dimensional space, it has been difficult to quantitatively compare multiple paths, a necessary prerequisite to, for instance, assess the quality of different algorithms. We introduce a method named Path Similarity Analysis (PSA) that enables us to quantify the similarity between two arbitrary paths and extract the atomic-scale determinants responsible for their differences. PSA utilizes the full information available in 3N-dimensional configuration space trajectories by employing the Hausdorff or Fréchet metrics (adopted from computational geometry) to quantify the degree of similarity between piecewise-linear curves. It thus completely avoids relying on projections into low dimensional spaces, as used in traditional approaches. To elucidate the principles of PSA, we quantified the effect of path roughness induced by thermal fluctuations using a toy model system. Using, as an example, the closed-to-open transitions of the enzyme adenylate kinase (AdK) in its substrate-free form, we compared a range of protein transition path-generating algorithms. Molecular dynamics-based dynamic importance sampling (DIMS) MD and targeted MD (TMD) and the purely geometric FRODA (Framework Rigidity Optimized Dynamics Algorithm) were tested along with seven other methods publicly available on servers, including several based on the popular elastic network model (ENM). PSA with clustering revealed that paths produced by a given method are more similar to each other than to those from another method and, for instance, that the ENM-based methods produced relatively similar paths. PSA applied to ensembles of DIMS MD and FRODA trajectories of the conformational transition of diphtheria toxin, a particularly challenging example, showed that the geometry-based FRODA occasionally sampled the pathway space of force field-based DIMS MD. For the AdK transition, the new concept of a Hausdorff-pair map enabled us to extract the molecular structural determinants responsible for differences in pathways, namely a set of conserved salt bridges whose charge-charge interactions are fully modelled in DIMS MD but not in FRODA. PSA has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing conformational transitions. PMID:26488417

Energy aware path planning in complex four dimensional environments

NASA Astrophysics Data System (ADS)

Chakrabarty, Anjan

This dissertation addresses the problem of energy-aware path planning for small autonomous vehicles. While small autonomous vehicles can perform missions that are too risky (or infeasible) for larger vehicles, the missions are limited by the amount of energy that can be carried on board the vehicle. Path planning techniques that either minimize energy consumption or exploit energy available in the environment can thus increase range and endurance. Path planning is complicated by significant spatial (and potentially temporal) variations in the environment. While the main focus is on autonomous aircraft, this research also addresses autonomous ground vehicles. Range and endurance of small unmanned aerial vehicles (UAVs) can be greatly improved by utilizing energy from the atmosphere. Wind can be exploited to minimize energy consumption of a small UAV. But wind, like any other atmospheric component , is a space and time varying phenomenon. To effectively use wind for long range missions, both exploration and exploitation of wind is critical. This research presents a kinematics based tree algorithm which efficiently handles the four dimensional (three spatial and time) path planning problem. The Kinematic Tree algorithm provides a sequence of waypoints, airspeeds, heading and bank angle commands for each segment of the path. The planner is shown to be resolution complete and computationally efficient. Global optimality of the cost function cannot be claimed, as energy is gained from the atmosphere, making the cost function inadmissible. However the Kinematic Tree is shown to be optimal up to resolution if the cost function is admissible. Simulation results show the efficacy of this planning method for a glider in complex real wind data. Simulation results verify that the planner is able to extract energy from the atmosphere enabling long range missions. The Kinematic Tree planning framework, developed to minimize energy consumption of UAVs, is applied for path planning in ground robots. In traditional path planning problem the focus is on obstacle avoidance and navigation. The optimal Kinematic Tree algorithm named Kinematic Tree* is shown to find optimal paths to reach the destination while avoiding obstacles. A more challenging path planning scenario arises for planning in complex terrain. This research shows how the Kinematic Tree* algorithm can be extended to find minimum energy paths for a ground vehicle in difficult mountainous terrain.

Extended shortest path selection for package routing of complex networks

NASA Astrophysics Data System (ADS)

Ye, Fan; Zhang, Lei; Wang, Bing-Hong; Liu, Lu; Zhang, Xing-Yi

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

Multiscale combination of climate model simulations and proxy records over the last millennium

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Nie, Suping; Zhao, Zongci; Huang, Jianbin; Tian, Qinhua

2018-05-01

To highlight the compatibility of climate model simulation and proxy reconstruction at different timescales, a timescale separation merging method combining proxy records and climate model simulations is presented. Annual mean surface temperature anomalies for the last millennium (851-2005 AD) at various scales over the land of the Northern Hemisphere were reconstructed with 2° × 2° spatial resolution, using an optimal interpolation (OI) algorithm. All target series were decomposed using an ensemble empirical mode decomposition method followed by power spectral analysis. Four typical components were obtained at inter-annual, decadal, multidecadal, and centennial timescales. A total of 323 temperature-sensitive proxy chronologies were incorporated after screening for each component. By scaling the proxy components using variance matching and applying a localized OI algorithm to all four components point by point, we obtained merged surface temperatures. Independent validation indicates that the most significant improvement was for components at the inter-annual scale, but this became less evident with increasing timescales. In mid-latitude land areas, 10-30% of grids were significantly corrected at the inter-annual scale. By assimilating the proxy records, the merged results reduced the gap in response to volcanic forcing between a pure reconstruction and simulation. Difficulty remained in verifying the centennial information and quantifying corresponding uncertainties, so additional effort should be devoted to this aspect in future research.

Calibration of neural networks using genetic algorithms, with application to optimal path planning

NASA Technical Reports Server (NTRS)

Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel

1987-01-01

Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.

Formal language constrained path problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrett, C.; Jacob, R.; Marathe, M.

1997-07-08

In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvablemore » efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.« less

A Path Algorithm for Constrained Estimation

PubMed Central

Zhou, Hua; Lange, Kenneth

2013-01-01

Many least-square problems involve affine equality and inequality constraints. Although there are a variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current article proposes a new path-following algorithm for quadratic programming that replaces hard constraints by what are called exact penalties. Similar penalties arise in l1 regularization in model selection. In the regularization setting, penalties encapsulate prior knowledge, and penalized parameter estimates represent a trade-off between the observed data and the prior knowledge. Classical penalty methods of optimization, such as the quadratic penalty method, solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties!are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path-following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in Lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the Lasso and generalized Lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well-chosen examples illustrate the mechanics and potential of path following. This article has supplementary materials available online. PMID:24039382

Augmented microscopy: real-time overlay of bright-field and near-infrared fluorescence images.

PubMed

Watson, Jeffrey R; Gainer, Christian F; Martirosyan, Nikolay; Skoch, Jesse; Lemole, G Michael; Anton, Rein; Romanowski, Marek

2015-10-01

Intraoperative applications of near-infrared (NIR) fluorescent contrast agents can be aided by instrumentation capable of merging the view of surgical field with that of NIR fluorescence. We demonstrate augmented microscopy, an intraoperative imaging technique in which bright-field (real) and electronically processed NIR fluorescence (synthetic) images are merged within the optical path of a stereomicroscope. Under luminance of 100,000 lx, representing typical illumination of the surgical field, the augmented microscope detects 189 nM concentration of indocyanine green and produces a composite of the real and synthetic images within the eyepiece of the microscope at 20 fps. Augmentation described here can be implemented as an add-on module to visualize NIR contrast agents, laser beams, or various types of electronic data within the surgical microscopes commonly used in neurosurgical, cerebrovascular, otolaryngological, and ophthalmic procedures.

Augmented microscopy: real-time overlay of bright-field and near-infrared fluorescence images

NASA Astrophysics Data System (ADS)

Watson, Jeffrey R.; Gainer, Christian F.; Martirosyan, Nikolay; Skoch, Jesse; Lemole, G. Michael, Jr.; Anton, Rein; Romanowski, Marek

2015-10-01

Intraoperative applications of near-infrared (NIR) fluorescent contrast agents can be aided by instrumentation capable of merging the view of surgical field with that of NIR fluorescence. We demonstrate augmented microscopy, an intraoperative imaging technique in which bright-field (real) and electronically processed NIR fluorescence (synthetic) images are merged within the optical path of a stereomicroscope. Under luminance of 100,000 lx, representing typical illumination of the surgical field, the augmented microscope detects 189 nM concentration of indocyanine green and produces a composite of the real and synthetic images within the eyepiece of the microscope at 20 fps. Augmentation described here can be implemented as an add-on module to visualize NIR contrast agents, laser beams, or various types of electronic data within the surgical microscopes commonly used in neurosurgical, cerebrovascular, otolaryngological, and ophthalmic procedures.

Coarse-grained representation of the quasi adiabatic propagator path integral for the treatment of non-Markovian long-time bath memory

NASA Astrophysics Data System (ADS)

Richter, Martin; Fingerhut, Benjamin P.

2017-06-01

The description of non-Markovian effects imposed by low frequency bath modes poses a persistent challenge for path integral based approaches like the iterative quasi-adiabatic propagator path integral (iQUAPI) method. We present a novel approximate method, termed mask assisted coarse graining of influence coefficients (MACGIC)-iQUAPI, that offers appealing computational savings due to substantial reduction of considered path segments for propagation. The method relies on an efficient path segment merging procedure via an intermediate coarse grained representation of Feynman-Vernon influence coefficients that exploits physical properties of system decoherence. The MACGIC-iQUAPI method allows us to access the regime of biological significant long-time bath memory on the order of hundred propagation time steps while retaining convergence to iQUAPI results. Numerical performance is demonstrated for a set of benchmark problems that cover bath assisted long range electron transfer, the transition from coherent to incoherent dynamics in a prototypical molecular dimer and excitation energy transfer in a 24-state model of the Fenna-Matthews-Olson trimer complex where in all cases excellent agreement with numerically exact reference data is obtained.

Multi-Instrument Manager Tool for Data Acquisition and Merging of Optical and Electrical Mobility Size Distributions

NASA Astrophysics Data System (ADS)

Tritscher, Torsten; Koched, Amine; Han, Hee-Siew; Filimundi, Eric; Johnson, Tim; Elzey, Sherrie; Avenido, Aaron; Kykal, Carsten; Bischof, Oliver F.

2015-05-01

Electrical mobility classification (EC) followed by Condensation Particle Counter (CPC) detection is the technique combined in Scanning Mobility Particle Sizers(SMPS) to retrieve nanoparticle size distributions in the range from 2.5 nm to 1 μm. The detectable size range of SMPS systems can be extended by the addition of an Optical Particle Sizer(OPS) that covers larger sizes from 300 nm to 10 μm. This optical sizing method reports an optical equivalent diameter, which is often different from the electrical mobility diameter measured by the standard SMPS technique. Multi-Instrument Manager (MIMTM) software developed by TSI incorporates algorithms that facilitate merging SMPS data sets with data based on optical equivalent diameter to compile single, wide-range size distributions. Here we present MIM 2.0, the next-generation of the data merging tool that offers many advanced features for data merging and post-processing. MIM 2.0 allows direct data acquisition with OPS and NanoScan SMPS instruments to retrieve real-time particle size distributions from 10 nm to 10 μm, which we show in a case study at a fireplace. The merged data can be adjusted using one of the merging options, which automatically determines an overall aerosol effective refractive index. As a result an indirect and average characterization of aerosol optical and shape properties is possible. The merging tool allows several pre-settings, data averaging and adjustments, as well as the export of data sets and fitted graphs. MIM 2.0 also features several post-processing options for SMPS data and differences can be visualized in a multi-peak sample over a narrow size range.

Tomographic reconstruction of tracer gas concentration profiles in a room with the use of a single OP-FTIR and two iterative algorithms: ART and PWLS.

PubMed

Park, D Y; Fessler, J A; Yost, M G; Levine, S P

2000-03-01

Computed tomographic (CT) reconstructions of air contaminant concentration fields were conducted in a room-sized chamber employing a single open-path Fourier transform infrared (OP-FTIR) instrument and a combination of 52 flat mirrors and 4 retroreflectors. A total of 56 beam path data were repeatedly collected for around 1 hr while maintaining a stable concentration gradient. The plane of the room was divided into 195 pixels (13 x 15) for reconstruction. The algebraic reconstruction technique (ART) failed to reconstruct the original concentration gradient patterns for most cases. These poor results were caused by the "highly underdetermined condition" in which the number of unknown values (156 pixels) exceeds that of known data (56 path integral concentrations) in the experimental setting. A new CT algorithm, called the penalized weighted least-squares (PWLS), was applied to remedy this condition. The peak locations were correctly positioned in the PWLS-CT reconstructions. A notable feature of the PWLS-CT reconstructions was a significant reduction of highly irregular noise peaks found in the ART-CT reconstructions. However, the peak heights were slightly reduced in the PWLS-CT reconstructions due to the nature of the PWLS algorithm. PWLS could converge on the original concentration gradient even when a fairly high error was embedded into some experimentally measured path integral concentrations. It was also found in the simulation tests that the PWLS algorithm was very robust with respect to random errors in the path integral concentrations. This beam geometry and the use of a single OP-FTIR scanning system, in combination with the PWLS algorithm, is a system applicable to both environmental and industrial settings.

Tomographic Reconstruction of Tracer Gas Concentration Profiles in a Room with the Use of a Single OP-FTIR and Two Iterative Algorithms: ART and PWLS.

PubMed

Park, Doo Y; Fessier, Jeffrey A; Yost, Michael G; Levine, Steven P

2000-03-01

Computed tomographic (CT) reconstructions of air contaminant concentration fields were conducted in a room-sized chamber employing a single open-path Fourier transform infrared (OP-FTIR) instrument and a combination of 52 flat mirrors and 4 retroreflectors. A total of 56 beam path data were repeatedly collected for around 1 hr while maintaining a stable concentration gradient. The plane of the room was divided into 195 pixels (13 × 15) for reconstruction. The algebraic reconstruction technique (ART) failed to reconstruct the original concentration gradient patterns for most cases. These poor results were caused by the "highly underdetermined condition" in which the number of unknown values (156 pixels) exceeds that of known data (56 path integral concentrations) in the experimental setting. A new CT algorithm, called the penalized weighted least-squares (PWLS), was applied to remedy this condition. The peak locations were correctly positioned in the PWLS-CT reconstructions. A notable feature of the PWLS-CT reconstructions was a significant reduction of highly irregular noise peaks found in the ART-CT reconstructions. However, the peak heights were slightly reduced in the PWLS-CT reconstructions due to the nature of the PWLS algorithm. PWLS could converge on the original concentration gradient even when a fairly high error was embedded into some experimentally measured path integral concentrations. It was also found in the simulation tests that the PWLS algorithm was very robust with respect to random errors in the path integral concentrations. This beam geometry and the use of a single OP-FTIR scanning system, in combination with the PWLS algorithm, is a system applicable to both environmental and industrial settings.

Ray-tracing method for creeping waves on arbitrarily shaped nonuniform rational B-splines surfaces.

PubMed

Chen, Xi; He, Si-Yuan; Yu, Ding-Feng; Yin, Hong-Cheng; Hu, Wei-Dong; Zhu, Guo-Qiang

2013-04-01

An accurate creeping ray-tracing algorithm is presented in this paper to determine the tracks of creeping waves (or creeping rays) on arbitrarily shaped free-form parametric surfaces [nonuniform rational B-splines (NURBS) surfaces]. The main challenge in calculating the surface diffracted fields on NURBS surfaces is due to the difficulty in determining the geodesic paths along which the creeping rays propagate. On one single parametric surface patch, the geodesic paths need to be computed by solving the geodesic equations numerically. Furthermore, realistic objects are generally modeled as the union of several connected NURBS patches. Due to the discontinuity of the parameter between the patches, it is more complicated to compute geodesic paths on several connected patches than on one single patch. Thus, a creeping ray-tracing algorithm is presented in this paper to compute the geodesic paths of creeping rays on the complex objects that are modeled as the combination of several NURBS surface patches. In the algorithm, the creeping ray tracing on each surface patch is performed by solving the geodesic equations with a Runge-Kutta method. When the creeping ray propagates from one patch to another, a transition method is developed to handle the transition of the creeping ray tracing across the border between the patches. This creeping ray-tracing algorithm can meet practical requirements because it can be applied to the objects with complex shapes. The algorithm can also extend the applicability of NURBS for electromagnetic and optical applications. The validity and usefulness of the algorithm can be verified from the numerical results.

Method and apparatus for eliminating unsuccessful tries in a search tree

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Chow, Edward (Inventor); Madan, Herb S. (Inventor)

1991-01-01

A circuit switching system in an M-ary, n-cube connected network completes a best-first path from an originating node to a destination node by latching valid legs of the path as the path is being sought out. Each network node is provided with a routing hyperswitch sub-network, (HSN) connected between that node and bidirectional high capacity communication channels of the n-cube network. The sub-networks are all controlled by routing algorithms which respond to message identification headings (headers) on messages to be routed along one or more routing legs. The header includes information embedded therein which is interpreted by each sub-network to route and historically update the header. A logic circuit, available at every node, implements the algorithm and automatically forwards or back-tracks the header in the network legs of various paths until a completed path is latched.

DiversePathsJ: diverse shortest paths for bioimage analysis.

PubMed

Uhlmann, Virginie; Haubold, Carsten; Hamprecht, Fred A; Unser, Michael

2018-02-01

We introduce a formulation for the general task of finding diverse shortest paths between two end-points. Our approach is not linked to a specific biological problem and can be applied to a large variety of images thanks to its generic implementation as a user-friendly ImageJ/Fiji plugin. It relies on the introduction of additional layers in a Viterbi path graph, which requires slight modifications to the standard Viterbi algorithm rules. This layered graph construction allows for the specification of various constraints imposing diversity between solutions. The software allows obtaining a collection of diverse shortest paths under some user-defined constraints through a convenient and user-friendly interface. It can be used alone or be integrated into larger image analysis pipelines. http://bigwww.epfl.ch/algorithms/diversepathsj. michael.unser@epfl.ch or fred.hamprecht@iwr.uni-heidelberg.de. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Sequential quadratic programming-based fast path planning algorithm subject to no-fly zone constraints

NASA Astrophysics Data System (ADS)

Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang

2016-08-01

Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.

Efficient computation paths for the systematic analysis of sensitivities

NASA Astrophysics Data System (ADS)

Greppi, Paolo; Arato, Elisabetta

2013-01-01

A systematic sensitivity analysis requires computing the model on all points of a multi-dimensional grid covering the domain of interest, defined by the ranges of variability of the inputs. The issues to efficiently perform such analyses on algebraic models are handling solution failures within and close to the feasible region and minimizing the total iteration count. Scanning the domain in the obvious order is sub-optimal in terms of total iterations and is likely to cause many solution failures. The problem of choosing a better order can be translated geometrically into finding Hamiltonian paths on certain grid graphs. This work proposes two paths, one based on a mixed-radix Gray code and the other, a quasi-spiral path, produced by a novel heuristic algorithm. Some simple, easy-to-visualize examples are presented, followed by performance results for the quasi-spiral algorithm and the practical application of the different paths in a process simulation tool.

Kinematic path planning for space-based robotics

NASA Astrophysics Data System (ADS)

Seereeram, Sanjeev; Wen, John T.

1998-01-01

Future space robotics tasks require manipulators of significant dexterity, achievable through kinematic redundancy and modular reconfigurability, but with a corresponding complexity of motion planning. Existing research aims for full autonomy and completeness, at the expense of efficiency, generality or even user friendliness. Commercial simulators require user-taught joint paths-a significant burden for assembly tasks subject to collision avoidance, kinematic and dynamic constraints. Our research has developed a Kinematic Path Planning (KPP) algorithm which bridges the gap between research and industry to produce a powerful and useful product. KPP consists of three key components: path-space iterative search, probabilistic refinement, and an operator guidance interface. The KPP algorithm has been successfully applied to the SSRMS for PMA relocation and dual-arm truss assembly tasks. Other KPP capabilities include Cartesian path following, hybrid Cartesian endpoint/intermediate via-point planning, redundancy resolution and path optimization. KPP incorporates supervisory (operator) input at any detail to influence the solution, yielding desirable/predictable paths for multi-jointed arms, avoiding obstacles and obeying manipulator limits. This software will eventually form a marketable robotic planner suitable for commercialization in conjunction with existing robotic CAD/CAM packages.

Statistical Analysis of the First Passage Path Ensemble of Jump Processes

NASA Astrophysics Data System (ADS)

von Kleist, Max; Schütte, Christof; Zhang, Wei

2018-02-01

The transition mechanism of jump processes between two different subsets in state space reveals important dynamical information of the processes and therefore has attracted considerable attention in the past years. In this paper, we study the first passage path ensemble of both discrete-time and continuous-time jump processes on a finite state space. The main approach is to divide each first passage path into nonreactive and reactive segments and to study them separately. The analysis can be applied to jump processes which are non-ergodic, as well as continuous-time jump processes where the waiting time distributions are non-exponential. In the particular case that the jump processes are both Markovian and ergodic, our analysis elucidates the relations between the study of the first passage paths and the study of the transition paths in transition path theory. We provide algorithms to numerically compute statistics of the first passage path ensemble. The computational complexity of these algorithms scales with the complexity of solving a linear system, for which efficient methods are available. Several examples demonstrate the wide applicability of the derived results across research areas.

Distribution path robust optimization of electric vehicle with multiple distribution centers

PubMed Central

Hao, Wei; He, Ruichun; Jia, Xiaoyan; Pan, Fuquan; Fan, Jing; Xiong, Ruiqi

2018-01-01

To identify electrical vehicle (EV) distribution paths with high robustness, insensitivity to uncertainty factors, and detailed road-by-road schemes, optimization of the distribution path problem of EV with multiple distribution centers and considering the charging facilities is necessary. With the minimum transport time as the goal, a robust optimization model of EV distribution path with adjustable robustness is established based on Bertsimas’ theory of robust discrete optimization. An enhanced three-segment genetic algorithm is also developed to solve the model, such that the optimal distribution scheme initially contains all road-by-road path data using the three-segment mixed coding and decoding method. During genetic manipulation, different interlacing and mutation operations are carried out on different chromosomes, while, during population evolution, the infeasible solution is naturally avoided. A part of the road network of Xifeng District in Qingyang City is taken as an example to test the model and the algorithm in this study, and the concrete transportation paths are utilized in the final distribution scheme. Therefore, more robust EV distribution paths with multiple distribution centers can be obtained using the robust optimization model. PMID:29518169

The application of Markov decision process with penalty function in restaurant delivery robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Hu, Zhen; Wang, Ying

2017-05-01

As the restaurant delivery robot is often in a dynamic and complex environment, including the chairs inadvertently moved to the channel and customers coming and going. The traditional Markov decision process path planning algorithm is not save, the robot is very close to the table and chairs. To solve this problem, this paper proposes the Markov Decision Process with a penalty term called MDPPT path planning algorithm according to the traditional Markov decision process (MDP). For MDP, if the restaurant delivery robot bumps into an obstacle, the reward it receives is part of the current status reward. For the MDPPT, the reward it receives not only the part of the current status but also a negative constant term. Simulation results show that the MDPPT algorithm can plan a more secure path.

PathNER: a tool for systematic identification of biological pathway mentions in the literature

PubMed Central

2013-01-01

Background Biological pathways are central to many biomedical studies and are frequently discussed in the literature. Several curated databases have been established to collate the knowledge of molecular processes constituting pathways. Yet, there has been little focus on enabling systematic detection of pathway mentions in the literature. Results We developed a tool, named PathNER (Pathway Named Entity Recognition), for the systematic identification of pathway mentions in the literature. PathNER is based on soft dictionary matching and rules, with the dictionary generated from public pathway databases. The rules utilise general pathway-specific keywords, syntactic information and gene/protein mentions. Detection results from both components are merged. On a gold-standard corpus, PathNER achieved an F1-score of 84%. To illustrate its potential, we applied PathNER on a collection of articles related to Alzheimer's disease to identify associated pathways, highlighting cases that can complement an existing manually curated knowledgebase. Conclusions In contrast to existing text-mining efforts that target the automatic reconstruction of pathway details from molecular interactions mentioned in the literature, PathNER focuses on identifying specific named pathway mentions. These mentions can be used to support large-scale curation and pathway-related systems biology applications, as demonstrated in the example of Alzheimer's disease. PathNER is implemented in Java and made freely available online at http://sourceforge.net/projects/pathner/. PMID:24555844

Optimizing Retransmission Threshold in Wireless Sensor Networks

PubMed Central

Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

2016-01-01

The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is OnΔ·max1≤i≤n{ui}, where ui is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based (1+pmin)-approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O(1)-approximation algorithm with time complexity O(1) is proposed. Experimental results show that the proposed algorithms have better performance. PMID:27171092

A novel communication mechanism based on node potential multi-path routing

NASA Astrophysics Data System (ADS)

Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen

2016-10-01

With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.

A portable back massage robot based on Traditional Chinese Medicine.

PubMed

Wang, Wendong; Liang, Chaohong; Zhang, Peng; Shi, Yikai

2018-05-30

A portable back massage robot which can complete the massage operations such as tapping, kneading and rolling was designed to improve the level of intelligence and massage effect. An efficient full covered path planning algorithm was put forward for a portable back massage robot to improve the coverage. Currently, massage robots has become one of important research focuses with the increasing requirements for healthcare. The massage robot is difficult to be widely accepted as there are problems of massage robot in control, structure, and coverage path planning. The 3D electromagnetic simulation model was established to optimize electromagnetic force. By analyzing the Traditional Chinese Medicine massage operation and the demands, the path planning algorithm models were established. The experimental platform of the massage robot was built. The simulation results show presented path planning algorithm is suitable for back massage, which ensures that the massage robot traverse the entire back area with improved massage coverage. The tested results show that the massage effect is best when the duty cycle is in the range of 1/8 to 1/2, and the massage force increases with the increase of the input voltage. The massage robot eventually achieved the desired massage effect, and the proposed efficient algorithm can effectively improve the coverage and promote the massage effect.

Improvement in Recursive Hierarchical Segmentation of Data

NASA Technical Reports Server (NTRS)

Tilton, James C.

2006-01-01

A further modification has been made in the algorithm and implementing software reported in Modified Recursive Hierarchical Segmentation of Data (GSC- 14681-1), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 51. That software performs recursive hierarchical segmentation of data having spatial characteristics (e.g., spectral-image data). The output of a prior version of the software contained artifacts, including spurious segmentation-image regions bounded by processing-window edges. The modification for suppressing the artifacts, mentioned in the cited article, was addition of a subroutine that analyzes data in the vicinities of seams to find pairs of regions that tend to lie adjacent to each other on opposite sides of the seams. Within each such pair, pixels in one region that are more similar to pixels in the other region are reassigned to the other region. The present modification provides for a parameter ranging from 0 to 1 for controlling the relative priority of merges between spatially adjacent and spatially non-adjacent regions. At 1, spatially-adjacent-/spatially- non-adjacent-region merges have equal priority. At 0, only spatially-adjacent-region merges (no spectral clustering) are allowed. Between 0 and 1, spatially-adjacent- region merges have priority over spatially- non-adjacent ones.

Learning to merge: a new tool for interactive mapping

NASA Astrophysics Data System (ADS)

Porter, Reid B.; Lundquist, Sheng; Ruggiero, Christy

2013-05-01

The task of turning raw imagery into semantically meaningful maps and overlays is a key area of remote sensing activity. Image analysts, in applications ranging from environmental monitoring to intelligence, use imagery to generate and update maps of terrain, vegetation, road networks, buildings and other relevant features. Often these tasks can be cast as a pixel labeling problem, and several interactive pixel labeling tools have been developed. These tools exploit training data, which is generated by analysts using simple and intuitive paint-program annotation tools, in order to tailor the labeling algorithm for the particular dataset and task. In other cases, the task is best cast as a pixel segmentation problem. Interactive pixel segmentation tools have also been developed, but these tools typically do not learn from training data like the pixel labeling tools do. In this paper we investigate tools for interactive pixel segmentation that also learn from user input. The input has the form of segment merging (or grouping). Merging examples are 1) easily obtained from analysts using vector annotation tools, and 2) more challenging to exploit than traditional labels. We outline the key issues in developing these interactive merging tools, and describe their application to remote sensing.

A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics.

PubMed

Hageman, Nathan S; Toga, Arthur W; Narr, Katherine L; Shattuck, David W

2009-03-01

We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color images of the DTI dataset.

A Diffusion Tensor Imaging Tractography Algorithm Based on Navier-Stokes Fluid Mechanics

PubMed Central

Hageman, Nathan S.; Toga, Arthur W.; Narr, Katherine; Shattuck, David W.

2009-01-01

We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color (DEC) images of the DTI dataset. PMID:19244007

Automated mapping of pharmacy orders from two electronic health record systems to RxNorm within the STRIDE clinical data warehouse.

PubMed

Hernandez, Penni; Podchiyska, Tanya; Weber, Susan; Ferris, Todd; Lowe, Henry

2009-11-14

The Stanford Translational Research Integrated Database Environment (STRIDE) clinical data warehouse integrates medication information from two Stanford hospitals that use different drug representation systems. To merge this pharmacy data into a single, standards-based model supporting research we developed an algorithm to map HL7 pharmacy orders to RxNorm concepts. A formal evaluation of this algorithm on 1.5 million pharmacy orders showed that the system could accurately assign pharmacy orders in over 96% of cases. This paper describes the algorithm and discusses some of the causes of failures in mapping to RxNorm.

Privacy-Preserving Relationship Path Discovery in Social Networks

NASA Astrophysics Data System (ADS)

Mezzour, Ghita; Perrig, Adrian; Gligor, Virgil; Papadimitratos, Panos

As social networks sites continue to proliferate and are being used for an increasing variety of purposes, the privacy risks raised by the full access of social networking sites over user data become uncomfortable. A decentralized social network would help alleviate this problem, but offering the functionalities of social networking sites is a distributed manner is a challenging problem. In this paper, we provide techniques to instantiate one of the core functionalities of social networks: discovery of paths between individuals. Our algorithm preserves the privacy of relationship information, and can operate offline during the path discovery phase. We simulate our algorithm on real social network topologies.

Multidimensional scaling for evolutionary algorithms--visualization of the path through search space and solution space using Sammon mapping.

PubMed

Pohlheim, Hartmut

2006-01-01

Multidimensional scaling as a technique for the presentation of high-dimensional data with standard visualization techniques is presented. The technique used is often known as Sammon mapping. We explain the mathematical foundations of multidimensional scaling and its robust calculation. We also demonstrate the use of this technique in the area of evolutionary algorithms. First, we present the visualization of the path through the search space of the best individuals during an optimization run. We then apply multidimensional scaling to the comparison of multiple runs regarding the variables of individuals and multi-criteria objective values (path through the solution space).

A Multi-Scale Settlement Matching Algorithm Based on ARG

NASA Astrophysics Data System (ADS)

Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

2016-06-01

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

Multi-hop path tracing of mobile robot with multi-range image

NASA Astrophysics Data System (ADS)

Choudhury, Ramakanta; Samal, Chandrakanta; Choudhury, Umakanta

2010-02-01

It is well known that image processing depends heavily upon image representation technique . This paper intends to find out the optimal path of mobile robots for a specified area where obstacles are predefined as well as modified. Here the optimal path is represented by using the Quad tree method. Since there has been rising interest in the use of quad tree, we have tried to use the successive subdivision of images into quadrants from which the quad tree is developed. In the quad tree, obstacles-free area and the partial filled area are represented with different notations. After development of quad tree the algorithm is used to find the optimal path by employing neighbor finding technique, with a view to move the robot from the source to destination. The algorithm, here , permeates through the entire tree, and tries to locate the common ancestor for computation. The computation and the algorithm, aim at easing the ability of the robot to trace the optimal path with the help of adjacencies between the neighboring nodes as well as determining such adjacencies in the horizontal, vertical and diagonal directions. In this paper efforts have been made to determine the movement of the adjacent block in the quad tree and to detect the transition between the blocks equal size and finally generate the result.

Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach

DTIC Science & Technology

2014-01-01

Paper DS-14-1028 to appear in the Special Issue on Stochastic Models, Control and Algorithms in Robotics, ASME Journal of Dynamic Systems...Measurement and Control Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach⋆ Devesh K. Jha† Yue Li† Thomas A. Wettergren‡† Asok...algorithm, called ν⋆, that was formulated in the framework of probabilistic finite state automata (PFSA) and language measure from a control -theoretic

On Parallel Push-Relabel based Algorithms for Bipartite Maximum Matching

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langguth, Johannes; Azad, Md Ariful; Halappanavar, Mahantesh

2014-07-01

We study multithreaded push-relabel based algorithms for computing maximum cardinality matching in bipartite graphs. Matching is a fundamental combinatorial (graph) problem with applications in a wide variety of problems in science and engineering. We are motivated by its use in the context of sparse linear solvers for computing maximum transversal of a matrix. We implement and test our algorithms on several multi-socket multicore systems and compare their performance to state-of-the-art augmenting path-based serial and parallel algorithms using a testset comprised of a wide range of real-world instances. Building on several heuristics for enhancing performance, we demonstrate good scaling for themore » parallel push-relabel algorithm. We show that it is comparable to the best augmenting path-based algorithms for bipartite matching. To the best of our knowledge, this is the first extensive study of multithreaded push-relabel based algorithms. In addition to a direct impact on the applications using matching, the proposed algorithmic techniques can be extended to preflow-push based algorithms for computing maximum flow in graphs.« less

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Benefit of adaptive FEC in shared backup path protected elastic optical network.

PubMed

Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang

2015-07-27

We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

Exact and Approximate Probabilistic Symbolic Execution

NASA Technical Reports Server (NTRS)

Luckow, Kasper; Pasareanu, Corina S.; Dwyer, Matthew B.; Filieri, Antonio; Visser, Willem

2014-01-01

Probabilistic software analysis seeks to quantify the likelihood of reaching a target event under uncertain environments. Recent approaches compute probabilities of execution paths using symbolic execution, but do not support nondeterminism. Nondeterminism arises naturally when no suitable probabilistic model can capture a program behavior, e.g., for multithreading or distributed systems. In this work, we propose a technique, based on symbolic execution, to synthesize schedulers that resolve nondeterminism to maximize the probability of reaching a target event. To scale to large systems, we also introduce approximate algorithms to search for good schedulers, speeding up established random sampling and reinforcement learning results through the quantification of path probabilities based on symbolic execution. We implemented the techniques in Symbolic PathFinder and evaluated them on nondeterministic Java programs. We show that our algorithms significantly improve upon a state-of- the-art statistical model checking algorithm, originally developed for Markov Decision Processes.

Accelerated Path-following Iterative Shrinkage Thresholding Algorithm with Application to Semiparametric Graph Estimation

PubMed Central

Zhao, Tuo; Liu, Han

2016-01-01

We propose an accelerated path-following iterative shrinkage thresholding algorithm (APISTA) for solving high dimensional sparse nonconvex learning problems. The main difference between APISTA and the path-following iterative shrinkage thresholding algorithm (PISTA) is that APISTA exploits an additional coordinate descent subroutine to boost the computational performance. Such a modification, though simple, has profound impact: APISTA not only enjoys the same theoretical guarantee as that of PISTA, i.e., APISTA attains a linear rate of convergence to a unique sparse local optimum with good statistical properties, but also significantly outperforms PISTA in empirical benchmarks. As an application, we apply APISTA to solve a family of nonconvex optimization problems motivated by estimating sparse semiparametric graphical models. APISTA allows us to obtain new statistical recovery results which do not exist in the existing literature. Thorough numerical results are provided to back up our theory. PMID:28133430

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

PubMed

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of these two fields results in a safe path planning algorithm, with a deterministic outcome, to navigate agents to their desired goals.

Contour Detection and Completion for Inpainting and Segmentation Based on Topological Gradient and Fast Marching Algorithms

PubMed Central

Auroux, Didier; Cohen, Laurent D.; Masmoudi, Mohamed

2011-01-01

We combine in this paper the topological gradient, which is a powerful method for edge detection in image processing, and a variant of the minimal path method in order to find connected contours. The topological gradient provides a more global analysis of the image than the standard gradient and identifies the main edges of an image. Several image processing problems (e.g., inpainting and segmentation) require continuous contours. For this purpose, we consider the fast marching algorithm in order to find minimal paths in the topological gradient image. This coupled algorithm quickly provides accurate and connected contours. We present then two numerical applications, to image inpainting and segmentation, of this hybrid algorithm. PMID:22194734

Improving the resolution for Lamb wave testing via a smoothed Capon algorithm

NASA Astrophysics Data System (ADS)

Cao, Xuwei; Zeng, Liang; Lin, Jing; Hua, Jiadong

2018-04-01

Lamb wave testing is promising for damage detection and evaluation in large-area structures. The dispersion of Lamb waves is often unavoidable, restricting testing resolution and making the signal hard to interpret. A smoothed Capon algorithm is proposed in this paper to estimate the accurate path length of each wave packet. In the algorithm, frequency domain whitening is firstly used to obtain the transfer function in the bandwidth of the excitation pulse. Subsequently, wavenumber domain smoothing is employed to reduce the correlation between wave packets. Finally, the path lengths are determined by distance domain searching based on the Capon algorithm. Simulations are applied to optimize the number of smoothing times. Experiments are performed on an aluminum plate consisting of two simulated defects. The results demonstrate that spatial resolution is improved significantly by the proposed algorithm.

Preliminary test results of a flight management algorithm for fuel conservative descents in a time based metered traffic environment. [flight tests of an algorithm to minimize fuel consumption of aircraft based on flight time

NASA Technical Reports Server (NTRS)

Knox, C. E.; Cannon, D. G.

1979-01-01

A flight management algorithm designed to improve the accuracy of delivering the airplane fuel efficiently to a metering fix at a time designated by air traffic control is discussed. The algorithm provides a 3-D path with time control (4-D) for a test B 737 airplane to make an idle thrust, clean configured descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path is calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithms and the results of the flight tests are discussed.

Augmented microscopy: real-time overlay of bright-field and near-infrared fluorescence images

PubMed Central

Watson, Jeffrey R.; Gainer, Christian F.; Martirosyan, Nikolay; Skoch, Jesse; Lemole, G. Michael; Anton, Rein; Romanowski, Marek

2015-01-01

Abstract. Intraoperative applications of near-infrared (NIR) fluorescent contrast agents can be aided by instrumentation capable of merging the view of surgical field with that of NIR fluorescence. We demonstrate augmented microscopy, an intraoperative imaging technique in which bright-field (real) and electronically processed NIR fluorescence (synthetic) images are merged within the optical path of a stereomicroscope. Under luminance of 100,000 lx, representing typical illumination of the surgical field, the augmented microscope detects 189 nM concentration of indocyanine green and produces a composite of the real and synthetic images within the eyepiece of the microscope at 20 fps. Augmentation described here can be implemented as an add-on module to visualize NIR contrast agents, laser beams, or various types of electronic data within the surgical microscopes commonly used in neurosurgical, cerebrovascular, otolaryngological, and ophthalmic procedures. PMID:26440760

Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations

NASA Technical Reports Server (NTRS)

Osher, Stanley; Sethian, James A.

1987-01-01

New numerical algorithms are devised (PSC algorithms) for following fronts propagating with curvature-dependent speed. The speed may be an arbitrary function of curvature, and the front can also be passively advected by an underlying flow. These algorithms approximate the equations of motion, which resemble Hamilton-Jacobi equations with parabolic right-hand-sides, by using techniques from the hyperbolic conservation laws. Non-oscillatory schemes of various orders of accuracy are used to solve the equations, providing methods that accurately capture the formation of sharp gradients and cusps in the moving fronts. The algorithms handle topological merging and breaking naturally, work in any number of space dimensions, and do not require that the moving surface be written as a function. The methods can be used also for more general Hamilton-Jacobi-type problems. The algorithms are demonstrated by computing the solution to a variety of surface motion problems.

Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks

NASA Astrophysics Data System (ADS)

Cui, Yaozu; Wang, Xingyuan; Eustace, Justine

2014-12-01

Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping community structure, our algorithm firstly extracts fully connected sub-graphs which are maximal sub-graphs from original networks. Then two maximal sub-graphs having the key pair-vertices can be merged into a new larger sub-graph using some belonging degree functions. Furthermore we extend the modularity function to evaluate the proposed algorithm. In addition, overlapping nodes between communities are founded successfully. Finally we report the comparison between the modularity and the computational complexity of the proposed algorithm with some other existing algorithms. The experimental results show that the proposed algorithm gives satisfactory results.

Perception for rugged terrain

NASA Technical Reports Server (NTRS)

Kweon, In SO; Hebert, Martial; Kanade, Takeo

1989-01-01

A three-dimensional perception system for building a geometrical description of rugged terrain environments from range image data is presented with reference to the exploration of the rugged terrain of Mars. An intermediate representation consisting of an elevation map that includes an explicit representation of uncertainty and labeling of the occluded regions is proposed. The locus method used to convert range image to an elevation map is introduced, along with an uncertainty model based on this algorithm. Both the elevation map and the locus method are the basis of a terrain matching algorithm which does not assume any correspondences between range images. The two-stage algorithm consists of a feature-based matching algorithm to compute an initial transform and an iconic terrain matching algorithm to merge multiple range images into a uniform representation. Terrain modeling results on real range images of rugged terrain are presented. The algorithms considered are a fundamental part of the perception system for the Ambler, a legged locomotor.

Application of Extended Kalman Filter in Persistant Scatterer Interferometry to Enhace the Accuracy of Unwrapping Process

NASA Astrophysics Data System (ADS)

Tavakkoli Estahbanat, A.; Dehghani, M.

2017-09-01

In interferometry technique, phases have been modulated between 0-2π. Finding the number of integer phases missed when they were wrapped is the main goal of unwrapping algorithms. Although the density of points in conventional interferometry is high, this is not effective in some cases such as large temporal baselines or noisy interferograms. Due to existing noisy pixels, not only it does not improve results, but also it leads to some unwrapping errors during interferogram unwrapping. In PS technique, because of the sparse PS pixels, scientists are confronted with a problem to unwrap phases. Due to the irregular data separation, conventional methods are sterile. Unwrapping techniques are divided in to path-independent and path-dependent in the case of unwrapping paths. A region-growing method which is a path-dependent technique has been used to unwrap PS data. In this paper an idea of EKF has been generalized on PS data. This algorithm is applied to consider the nonlinearity of PS unwrapping problem as well as conventional unwrapping problem. A pulse-pair method enhanced with singular value decomposition (SVD) has been used to estimate spectral shift from interferometric power spectral density in 7*7 local windows. Furthermore, a hybrid cost-map is used to manage the unwrapping path. This algorithm has been implemented on simulated PS data. To form a sparse dataset, A few points from regular grid are randomly selected and the RMSE of results and true unambiguous phases in presented to validate presented approach. The results of this algorithm and true unwrapped phases were completely identical.

Fuzzy logic and A* algorithm implementation on goat foraging games

NASA Astrophysics Data System (ADS)

Harsani, P.; Mulyana, I.; Zakaria, D.

2018-03-01

Goat foraging is one of the games that apply the search techniques within the scope of artificial intelligence. This game involves several actors including players and enemies. The method used in this research is fuzzy logic and Algorithm A*. Fuzzy logic is used to determine enemy behaviour. The A* algorithm is used to search for the shortest path. There are two input variables: the distance between the player and the enemy and the anger level of the goat. The output variable that has been defined is the enemy behaviour. The A* algorithm is used to determine the closest path between the player and the enemy and define the enemy's escape path to avoid the player. There are 4 types of enemies namely farmers, planters, farmers and sellers of plants. Players are goats that aims to find a meal that is a plant. In this game goats aim to spend grass in the garden in the form of a maze while avoiding the enemy. The game provides an application of artificial intelligence and is made in four difficulty levels.

Semiautomated Management Of Arriving Air Traffic

NASA Technical Reports Server (NTRS)

Erzberger, Heinz; Nedell, William

1992-01-01

System of computers, graphical workstations, and computer programs developed for semiautomated management of approach and arrival of numerous aircraft at airport. System comprises three subsystems: traffic-management advisor, used for controlling traffic into terminal area; descent advisor generates information integrated into plan-view display of traffic on monitor; and final-approach-spacing tool used to merge traffic converging on final approach path while making sure aircraft are properly spaced. Not intended to restrict decisions of air-traffic controllers.

Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm

NASA Astrophysics Data System (ADS)

Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.

This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).

IIR filtering based adaptive active vibration control methodology with online secondary path modeling using PZT actuators

NASA Astrophysics Data System (ADS)

Boz, Utku; Basdogan, Ipek

2015-12-01

Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation

PubMed Central

Yu, Hongyi

2018-01-01

A novel geolocation architecture, termed “Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)” is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér–Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML. PMID:29562601

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation.

PubMed

Du, Jianping; Wang, Ding; Yu, Wanting; Yu, Hongyi

2018-03-17

A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér-Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.

A Comparison of Two Path Planners for Planetary Rovers

NASA Technical Reports Server (NTRS)

Tarokh, M.; Shiller, Z.; Hayati, S.

1999-01-01

The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain. The second planner uses a global optimization method with a cost function that is the path distance divided by the velocity limit obtained from the consideration of the rover static and dynamic stability. A description of both methods is provided, and the results of paths produced are given which show the effectiveness of the path planners in finding near optimal paths. The features of the methods and their suitability and application for rover path planning are compared

Increasingly minimal bias routing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bataineh, Abdulla; Court, Thomas; Roweth, Duncan

2017-02-21

A system and algorithm configured to generate diversity at the traffic source so that packets are uniformly distributed over all of the available paths, but to increase the likelihood of taking a minimal path with each hop the packet takes. This is achieved by configuring routing biases so as to prefer non-minimal paths at the injection point, but increasingly prefer minimal paths as the packet proceeds, referred to herein as Increasing Minimal Bias (IMB).

MOD3D: a model for incorporating MODTRAN radiative transfer into 3D simulations

NASA Astrophysics Data System (ADS)

Berk, Alexander; Anderson, Gail P.; Gossage, Brett N.

2001-08-01

MOD3D, a rapid and accurate radiative transport algorithm, is being developed for application to 3D simulations. MOD3D couples to optical property databases generated by the MODTRAN4 Correlated-k (CK) band model algorithm. The Beer's Law dependence of the CK algorithm provides for proper coupling of illumination and line-of-sight paths. Full 3D spatial effects are modeled by scaling and interpolating optical data to local conditions. A C++ version of MOD3D has been integrated into JMASS for calculation of path transmittances, thermal emission and single scatter solar radiation. Results from initial validation efforts are presented.

Dijkstra Methode for Optimalize Recommendation System of Garbage Transportation Time in Surakarta City

NASA Astrophysics Data System (ADS)

Hartatik; Purbayu, A.; Triyono, L.

2018-03-01

Major problem that often occurs in waste transportation in each region is the route of garbage transportation. Determination of this route should become a major concern because it affects fuel consumption and also the working time from the employee. Therefore, in this research we will develop an application to optimize with pigeonhole and dijsktra algorithm. Pigeonhole algorithm is used to determine which garbage trucks should be taken in a particular TPS. Time optimization is done by determining the shortest path that can be skipped for each garbage truck. Data generated from Pigeonhole then used to determine the shortest path by using Dijkstra algorithm.

Home and Clinical Cardiovascular Care Center (H4C): a Framework for Integrating Body Sensor Networks and QTRU Cryptography System.

PubMed

Zakerolhosseini, Ali; Sokouti, Massoud; Pezeshkian, Massoud

2013-01-01

Quick responds to heart attack patients before arriving to hospital is a very important factor. In this paper, a combined model of Body Sensor Network and Personal Digital Access using QTRU cipher algorithm in Wifi networks is presented to efficiently overcome these life threatening attacks. The algorithm for optimizing the routing paths between sensor nodes and an algorithm for reducing the power consumption are also applied for achieving the best performance by this model. This system is consumes low power and has encrypting and decrypting processes. It also has an efficient routing path in a fast manner.

Home and Clinical Cardiovascular Care Center (H4C): a Framework for Integrating Body Sensor Networks and QTRU Cryptography System

PubMed Central

Zakerolhosseini, Ali; Sokouti, Massoud; Pezeshkian, Massoud

2013-01-01

Quick responds to heart attack patients before arriving to hospital is a very important factor. In this paper, a combined model of Body Sensor Network and Personal Digital Access using QTRU cipher algorithm in Wifi networks is presented to efficiently overcome these life threatening attacks. The algorithm for optimizing the routing paths between sensor nodes and an algorithm for reducing the power consumption are also applied for achieving the best performance by this model. This system is consumes low power and has encrypting and decrypting processes. It also has an efficient routing path in a fast manner. PMID:24252988

Variational nature, integration, and properties of Newton reaction path

NASA Astrophysics Data System (ADS)

Bofill, Josep Maria; Quapp, Wolfgang

2011-02-01

The distinguished coordinate path and the reduced gradient following path or its equivalent formulation, the Newton trajectory, are analyzed and unified using the theory of calculus of variations. It is shown that their minimum character is related to the fact that the curve is located in a valley region. In this case, we say that the Newton trajectory is a reaction path with the category of minimum energy path. In addition to these findings a Runge-Kutta-Fehlberg algorithm to integrate these curves is also proposed.

Variational nature, integration, and properties of Newton reaction path.

PubMed

Bofill, Josep Maria; Quapp, Wolfgang

2011-02-21

The distinguished coordinate path and the reduced gradient following path or its equivalent formulation, the Newton trajectory, are analyzed and unified using the theory of calculus of variations. It is shown that their minimum character is related to the fact that the curve is located in a valley region. In this case, we say that the Newton trajectory is a reaction path with the category of minimum energy path. In addition to these findings a Runge-Kutta-Fehlberg algorithm to integrate these curves is also proposed.

A concept for a fuel efficient flight planning aid for general aviation

NASA Technical Reports Server (NTRS)

Collins, B. P.; Haines, A. L.; Wales, C. J.

1982-01-01

A core equation for estimation of fuel burn from path profile data was developed. This equation was used as a necessary ingredient in a dynamic program to define a fuel efficient flight path. The resultant algorithm is oriented toward use by general aviation. The pilot provides a description of the desired ground track, standard aircraft parameters, and weather at selected waypoints. The algorithm then derives the fuel efficient altitudes and velocities at the waypoints.

Real-time video streaming using H.264 scalable video coding (SVC) in multihomed mobile networks: a testbed approach

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2011-03-01

Users of the next generation wireless paradigm known as multihomed mobile networks expect satisfactory quality of service (QoS) when accessing streamed multimedia content. The recent H.264 Scalable Video Coding (SVC) extension to the Advanced Video Coding standard (AVC), offers the facility to adapt real-time video streams in response to the dynamic conditions of multiple network paths encountered in multihomed wireless mobile networks. Nevertheless, preexisting streaming algorithms were mainly proposed for AVC delivery over multipath wired networks and were evaluated by software simulation. This paper introduces a practical, hardware-based testbed upon which we implement and evaluate real-time H.264 SVC streaming algorithms in a realistic multihomed wireless mobile networks environment. We propose an optimised streaming algorithm with multi-fold technical contributions. Firstly, we extended the AVC packet prioritisation schemes to reflect the three-dimensional granularity of SVC. Secondly, we designed a mechanism for evaluating the effects of different streamer 'read ahead window' sizes on real-time performance. Thirdly, we took account of the previously unconsidered path switching and mobile networks tunnelling overheads encountered in real-world deployments. Finally, we implemented a path condition monitoring and reporting scheme to facilitate the intelligent path switching. The proposed system has been experimentally shown to offer a significant improvement in PSNR of the received stream compared with representative existing algorithms.

Efficient shortest-path-tree computation in network routing based on pulse-coupled neural networks.

PubMed

Qu, Hong; Yi, Zhang; Yang, Simon X

2013-06-01

Shortest path tree (SPT) computation is a critical issue for routers using link-state routing protocols, such as the most commonly used open shortest path first and intermediate system to intermediate system. Each router needs to recompute a new SPT rooted from itself whenever a change happens in the link state. Most commercial routers do this computation by deleting the current SPT and building a new one using static algorithms such as the Dijkstra algorithm at the beginning. Such recomputation of an entire SPT is inefficient, which may consume a considerable amount of CPU time and result in a time delay in the network. Some dynamic updating methods using the information in the updated SPT have been proposed in recent years. However, there are still many limitations in those dynamic algorithms. In this paper, a new modified model of pulse-coupled neural networks (M-PCNNs) is proposed for the SPT computation. It is rigorously proved that the proposed model is capable of solving some optimization problems, such as the SPT. A static algorithm is proposed based on the M-PCNNs to compute the SPT efficiently for large-scale problems. In addition, a dynamic algorithm that makes use of the structure of the previously computed SPT is proposed, which significantly improves the efficiency of the algorithm. Simulation results demonstrate the effective and efficient performance of the proposed approach.

Software for Project-Based Learning of Robot Motion Planning

ERIC Educational Resources Information Center

Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.

2013-01-01

Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can…

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets

PubMed Central

Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.

2017-01-01

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787

Surface wave tomography of the European crust and upper mantle from ambient seismic noise

NASA Astrophysics Data System (ADS)

LU, Y.; Stehly, L.; Paul, A.

2017-12-01

We present a high-resolution 3-D Shear wave velocity model of the European crust and upper mantle derived from ambient seismic noise tomography. In this study, we collect 4 years of continuous vertical-component seismic recordings from 1293 broadband stations across Europe (10W-35E, 30N-75N). We analyze group velocity dispersion from 5s to 150s for cross-correlations of more than 0.8 million virtual source-receiver pairs. 2-D group velocity maps are estimated using adaptive parameterization to accommodate the strong heterogeneity of path coverage. 3-D velocity model is obtained by merging 1-D models inverted at each pixel through a two-step data-driven inversion algorithm: a non-linear Bayesian Monte Carlo inversion, followed by a linearized inversion. Resulting S-wave velocity model and Moho depth are compared with previous geophysical studies: 1) The crustal model and Moho depth show striking agreement with active seismic imaging results. Moreover, it even provides new valuable information such as a strong difference of the European Moho along two seismic profiles in the Western Alps (Cifalps and ECORS-CROP). 2) The upper mantle model displays strong similarities with published models even at 150km deep, which is usually imaged using earthquake records.

A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs

NASA Astrophysics Data System (ADS)

Gudmundsson, Snorri

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.

Sensory feedback in a bump attractor model of path integration.

PubMed

Poll, Daniel B; Nguyen, Khanh; Kilpatrick, Zachary P

2016-04-01

Mammalian spatial navigation systems utilize several different sensory information channels. This information is converted into a neural code that represents the animal's current position in space by engaging place cell, grid cell, and head direction cell networks. In particular, sensory landmark (allothetic) cues can be utilized in concert with an animal's knowledge of its own velocity (idiothetic) cues to generate a more accurate representation of position than path integration provides on its own (Battaglia et al. The Journal of Neuroscience 24(19):4541-4550 (2004)). We develop a computational model that merges path integration with feedback from external sensory cues that provide a reliable representation of spatial position along an annular track. Starting with a continuous bump attractor model, we explore the impact of synaptic spatial asymmetry and heterogeneity, which disrupt the position code of the path integration process. We use asymptotic analysis to reduce the bump attractor model to a single scalar equation whose potential represents the impact of asymmetry and heterogeneity. Such imperfections cause errors to build up when the network performs path integration, but these errors can be corrected by an external control signal representing the effects of sensory cues. We demonstrate that there is an optimal strength and decay rate of the control signal when cues appear either periodically or randomly. A similar analysis is performed when errors in path integration arise from dynamic noise fluctuations. Again, there is an optimal strength and decay of discrete control that minimizes the path integration error.

An Educational Development Tool Based on Principles of Formal Ontology

ERIC Educational Resources Information Center

Guzzi, Rodolfo; Scarpanti, Stefano; Ballista, Giovanni; Di Nicolantonio, Walter

2005-01-01

Computer science provides with virtual laboratories, places where one can merge real experiments with the formalism of algorithms and mathematics and where, with the advent of multimedia, sounds and movies can also be added. In this paper we present a method, based on principles of formal ontology, allowing one to develop interactive educational…

Automated Driftmeter Fused with Inertial Navigation

DTIC Science & Technology

2014-03-27

6 IMU Inertial Measurement Unit . . . . . . . . . . . . . . . . . . . . . . . 7 SLAM Simultaneous...timing lines to remain horizontal at all times, regardless of turbulence and within 20 degrees of roll , pitch, and yaw of the aircraft. It had two...introduced in 1960 [2]. The Kalman filter algorithm has been used to merge inertial navigational data from Inertial Measurement Units ( IMU ) with

A variational dynamic programming approach to robot-path planning with a distance-safety criterion

NASA Technical Reports Server (NTRS)

Suh, Suk-Hwan; Shin, Kang G.

1988-01-01

An approach to robot-path planning is developed by considering both the traveling distance and the safety of the robot. A computationally-efficient algorithm is developed to find a near-optimal path with a weighted distance-safety criterion by using a variational calculus and dynamic programming (VCDP) method. The algorithm is readily applicable to any factory environment by representing the free workspace as channels. A method for deriving these channels is also proposed. Although it is developed mainly for two-dimensional problems, this method can be easily extended to a class of three-dimensional problems. Numerical examples are presented to demonstrate the utility and power of this method.

A novel Iterative algorithm to text segmentation for web born-digital images

NASA Astrophysics Data System (ADS)

Xu, Zhigang; Zhu, Yuesheng; Sun, Ziqiang; Liu, Zhen

2015-07-01

Since web born-digital images have low resolution and dense text atoms, text region over-merging and miss detection are still two open issues to be addressed. In this paper a novel iterative algorithm is proposed to locate and segment text regions. In each iteration, the candidate text regions are generated by detecting Maximally Stable Extremal Region (MSER) with diminishing thresholds, and categorized into different groups based on a new similarity graph, and the texted region groups are identified by applying several features and rules. With our proposed overlap checking method the final well-segmented text regions are selected from these groups in all iterations. Experiments have been carried out on the web born-digital image datasets used for robust reading competition in ICDAR 2011 and 2013, and the results demonstrate that our proposed scheme can significantly reduce both the number of over-merge regions and the lost rate of target atoms, and the overall performance outperforms the best compared with the methods shown in the two competitions in term of recall rate and f-score at the cost of slightly higher computational complexity.

Improved assemblies using a source-agnostic pipeline for MetaGenomic Assembly by Merging (MeGAMerge) of contigs

DOE PAGES

Scholz, Matthew; Lo, Chien -Chi; Chain, Patrick S. G.

2014-10-01

Assembly of metagenomic samples is a very complex process, with algorithms designed to address sequencing platform-specific issues, (read length, data volume, and/or community complexity), while also faced with genomes that differ greatly in nucleotide compositional biases and in abundance. To address these issues, we have developed a post-assembly process: MetaGenomic Assembly by Merging (MeGAMerge). We compare this process to the performance of several assemblers, using both real, and in-silico generated samples of different community composition and complexity. MeGAMerge consistently outperforms individual assembly methods, producing larger contigs with an increased number of predicted genes, without replication of data. MeGAMerge contigs aremore » supported by read mapping and contig alignment data, when using synthetically-derived and real metagenomic data, as well as by gene prediction analyses and similarity searches. Ultimately, MeGAMerge is a flexible method that generates improved metagenome assemblies, with the ability to accommodate upcoming sequencing platforms, as well as present and future assembly algorithms.« less

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Generation, recognition, and consistent fusion of partial boundary representations from range images

NASA Astrophysics Data System (ADS)

Kohlhepp, Peter; Hanczak, Andrzej M.; Li, Gang

1994-10-01

This paper presents SOMBRERO, a new system for recognizing and locating 3D, rigid, non- moving objects from range data. The objects may be polyhedral or curved, partially occluding, touching or lying flush with each other. For data collection, we employ 2D time- of-flight laser scanners mounted to a moving gantry robot. By combining sensor and robot coordinates, we obtain 3D cartesian coordinates. Boundary representations (Brep's) provide view independent geometry models that are both efficiently recognizable and derivable automatically from sensor data. SOMBRERO's methods for generating, matching and fusing Brep's are highly synergetic. A split-and-merge segmentation algorithm with dynamic triangular builds a partial (21/2D) Brep from scattered data. The recognition module matches this scene description with a model database and outputs recognized objects, their positions and orientations, and possibly surfaces corresponding to unknown objects. We present preliminary results in scene segmentation and recognition. Partial Brep's corresponding to different range sensors or viewpoints can be merged into a consistent, complete and irredundant 3D object or scene model. This fusion algorithm itself uses the recognition and segmentation methods.

Multi-scales region segmentation for ROI separation in digital mammograms

NASA Astrophysics Data System (ADS)

Zhang, Dapeng; Zhang, Di; Li, Yue; Wang, Wei

2017-02-01

Mammography is currently the most effective imaging modality used by radiologists for the screening of breast cancer. Segmentation is one of the key steps in the process of developing anatomical models for calculation of safe medical dose of radiation. This paper explores the potential of the statistical region merging segmentation technique for Breast segmentation in digital mammograms. First, the mammograms are pre-processing for regions enhancement, then the enhanced images are segmented using SRM with multi scales, finally these segmentations are combined for region of interest (ROI) separation and edge detection. The proposed algorithm uses multi-scales region segmentation in order to: separate breast region from background region, region edge detection and ROIs separation. The experiments are performed using a data set of mammograms from different patients, demonstrating the validity of the proposed criterion. Results show that, the statistical region merging segmentation algorithm actually can work on the segmentation of medical image and more accurate than another methods. And the outcome shows that the technique has a great potential to become a method of choice for segmentation of mammograms.

Improving Strategies via SMT Solving

NASA Astrophysics Data System (ADS)

Gawlitza, Thomas Martin; Monniaux, David

We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widening operators for enforcing convergence within a finite number of iterations (ii) the use of merge operations (often, convex hulls) at the merge points of the control flow graph. It instead computes the least inductive invariant expressible in the domain at a restricted set of program points, and analyzes the rest of the code en bloc. We emphasize that we compute this inductive invariant precisely. For that we extend the strategy improvement algorithm of Gawlitza and Seidl [17]. If we applied their method directly, we would have to solve an exponentially sized system of abstract semantic equations, resulting in memory exhaustion. Instead, we keep the system implicit and discover strategy improvements using SAT modulo real linear arithmetic (SMT). For evaluating strategies we use linear programming. Our algorithm has low polynomial space complexity and performs for contrived examples in the worst case exponentially many strategy improvement steps; this is unsurprising, since we show that the associated abstract reachability problem is Π2 P -complete.

Abstract - Cooperative Research and Development Agreement between Ames National Laboratory and National Energy Technology Laboratory AGMT-0609

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryden, Mark; Tucker, David A.

The goal of this project is to develop a merged environment for simulation and analysis (MESA) at the National Energy Technology Laboratory’s (NETL) Hybrid Performance (Hyper) project laboratory. The MESA sensor lab developed as a component of this research will provide a development platform for investigating: 1) advanced control strategies, 2) testing and development of sensor hardware, 3) various modeling in-the-loop algorithms and 4) other advanced computational algorithms for improved plant performance using sensors, real-time models, and complex systems tools.

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models

PubMed Central

Murray-Watters, Alexander; Glymour, Clark

2016-01-01

Using Gebharter's (2014) representation, we consider aspects of the problem of discovering the structure of unmeasured sub-mechanisms when the variables in those sub-mechanisms have not been measured. Exploiting an early insight of Sober's (1998), we provide a correct algorithm for identifying latent, endogenous structure—sub-mechanisms—for a restricted class of structures. The algorithm can be merged with other methods for discovering causal relations among unmeasured variables, and feedback relations between measured variables and unobserved causes can sometimes be learned. PMID:27313331

LiveWire interactive boundary extraction algorithm based on Haar wavelet transform and control point set direction search

NASA Astrophysics Data System (ADS)

Cheng, Jun; Zhang, Jun; Tian, Jinwen

2015-12-01

Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n2] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.

A surface hopping algorithm for nonadiabatic minimum energy path calculations.

PubMed

Schapiro, Igor; Roca-Sanjuán, Daniel; Lindh, Roland; Olivucci, Massimo

2015-02-15

The article introduces a robust algorithm for the computation of minimum energy paths transiting along regions of near-to or degeneracy of adiabatic states. The method facilitates studies of excited state reactivity involving weakly avoided crossings and conical intersections. Based on the analysis of the change in the multiconfigurational wave function the algorithm takes the decision whether the optimization should continue following the same electronic state or switch to a different state. This algorithm helps to overcome convergence difficulties near degeneracies. The implementation in the MOLCAS quantum chemistry package is discussed. To demonstrate the utility of the proposed procedure four examples of application are provided: thymine, asulam, 1,2-dioxetane, and a three-double-bond model of the 11-cis-retinal protonated Schiff base. © 2015 Wiley Periodicals, Inc.

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

A Binary Array Asynchronous Sorting Algorithm with Using Petri Nets

NASA Astrophysics Data System (ADS)

Voevoda, A. A.; Romannikov, D. O.

2017-01-01

Nowadays the tasks of computations speed-up and/or their optimization are actual. Among the approaches on how to solve these tasks, a method applying approaches of parallelization and asynchronization to a sorting algorithm is considered in the paper. The sorting methods are ones of elementary methods and they are used in a huge amount of different applications. In the paper, we offer a method of an array sorting that based on a division into a set of independent adjacent pairs of numbers and their parallel and asynchronous comparison. And this one distinguishes the offered method from the traditional sorting algorithms (like quick sorting, merge sorting, insertion sorting and others). The algorithm is implemented with the use of Petri nets, like the most suitable tool for an asynchronous systems description.

Identification of limit cycles in multi-nonlinearity, multiple path systems

NASA Technical Reports Server (NTRS)

Mitchell, J. R.; Barron, O. L.

1979-01-01

A method of analysis which identifies limit cycles in autonomous systems with multiple nonlinearities and multiple forward paths is presented. The FORTRAN code for implementing the Harmonic Balance Algorithm is reported. The FORTRAN code is used to identify limit cycles in multiple path and nonlinearity systems while retaining the effects of several harmonic components.

Solution Path for Pin-SVM Classifiers With Positive and Negative $\\tau $ Values.

PubMed

Huang, Xiaolin; Shi, Lei; Suykens, Johan A K

2017-07-01

Applying the pinball loss in a support vector machine (SVM) classifier results in pin-SVM. The pinball loss is characterized by a parameter τ . Its value is related to the quantile level and different τ values are suitable for different problems. In this paper, we establish an algorithm to find the entire solution path for pin-SVM with different τ values. This algorithm is based on the fact that the optimal solution to pin-SVM is continuous and piecewise linear with respect to τ . We also show that the nonnegativity constraint on τ is not necessary, i.e., τ can be extended to negative values. First, in some applications, a negative τ leads to better accuracy. Second, τ = -1 corresponds to a simple solution that links SVM and the classical kernel rule. The solution for τ = -1 can be obtained directly and then be used as a starting point of the solution path. The proposed method efficiently traverses τ values through the solution path, and then achieves good performance by a suitable τ . In particular, τ = 0 corresponds to C-SVM, meaning that the traversal algorithm can output a result at least as good as C-SVM with respect to validation error.

Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited

NASA Astrophysics Data System (ADS)

Lee, Youngseok; Mukherjee, Biswanath

2004-03-01

Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.

Graphs and matroids weighted in a bounded incline algebra.

PubMed

Lu, Ling-Xia; Zhang, Bei

2014-01-01

Firstly, for a graph weighted in a bounded incline algebra (or called a dioid), a longest path problem (LPP, for short) is presented, which can be considered the uniform approach to the famous shortest path problem, the widest path problem, and the most reliable path problem. The solutions for LPP and related algorithms are given. Secondly, for a matroid weighted in a linear matroid, the maximum independent set problem is studied.

The Complexity of Parallel Algorithms,

DTIC Science & Technology

1985-11-01

programns have been written for se(luiential coiipn ters. Many p~eop~le want coimp ~ilers dihal. will c(nimpile t he, code for parallel machines, to avoid...between two vertices. We also rely on parallel algorithms for maintaining data structures and manipulating graphs. We do not go into the details of these...Jpatlis and maintain connected coimp ~onents. The routine is: - 35 .- ExtendPath(r, Q, V) begin P +-0; s 4- while there is a path in V - P from s to a vertex

Grasp planning under uncertainty

NASA Technical Reports Server (NTRS)

Erkmen, A. M.; Stephanou, H. E.

1989-01-01

The planning of dexterous grasps for multifingered robot hands operating in uncertain environments is covered. A sensor-based approach to the planning of a reach path prior to grasping is first described. An on-line, joint space finger path planning algorithm for the enclose phase of grasping was then developed. The algorithm minimizes the impact momentum of the hand. It uses a Preshape Jacobian matrix to map task-level hand preshape requirements into kinematic constraints. A master slave scheme avoids inter-finger collisions and reduces the dimensionality of the planning problem.

Interprocedural Analysis and the Verification of Concurrent Programs

DTIC Science & Technology

2009-01-01

SSPE ) problem is to compute a regular expression that represents paths(s, v) for all vertices v in the graph. The syntax of regular expressions is as...follows: r ::= ∅ | ε | e | r1 ∪ r2 | r1.r2 | r∗, where e stands for an edge in G. We can use any algorithm for SSPE to compute regular expressions for...a closed representation of loops provides an exponential speedup.2 Tarjan’s path-expression algorithm solves the SSPE problem efficiently. It uses

Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space.

PubMed

Kalathil, Shaeen; Elias, Elizabeth

2015-11-01

This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB) using canonic signed digit (CSD) coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational Search algorithm, Harmony Search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB.

Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space

PubMed Central

Kalathil, Shaeen; Elias, Elizabeth

2014-01-01

This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB) using canonic signed digit (CSD) coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational Search algorithm, Harmony Search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB. PMID:26644921

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

Quantifying Traversability of Terrain for a Mobile Robot

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Seraji, Homayoun; Werger, Barry

2005-01-01

A document presents an updated discussion on a method of autonomous navigation for a robotic vehicle navigating across rough terrain. The method involves, among other things, the use of a measure of traversability, denoted the fuzzy traversability index, which embodies the information about the slope and roughness of terrain obtained from analysis of images acquired by cameras mounted on the robot. The improvements presented in the report focus on the use of the fuzzy traversability index to generate a traversability map and a grid map for planning the safest path for the robot. Once grid traversability values have been computed, they are utilized for rejecting unsafe path segments and for computing a traversalcost function for ranking candidate paths, selected by a search algorithm, from a specified initial position to a specified final position. The output of the algorithm is a set of waypoints designating a path having a minimal-traversal cost.

Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path

PubMed Central

Jeon, Semi; Yoon, Inhye; Jang, Jinbeum; Yang, Seungji; Kim, Jisung; Paik, Joonki

2017-01-01

Acquisition of stabilized video is an important issue for various type of digital cameras. This paper presents an adaptive camera path estimation method using robust feature detection to remove shaky artifacts in a video. The proposed algorithm consists of three steps: (i) robust feature detection using particle keypoints between adjacent frames; (ii) camera path estimation and smoothing; and (iii) rendering to reconstruct a stabilized video. As a result, the proposed algorithm can estimate the optimal homography by redefining important feature points in the flat region using particle keypoints. In addition, stabilized frames with less holes can be generated from the optimal, adaptive camera path that minimizes a temporal total variation (TV). The proposed video stabilization method is suitable for enhancing the visual quality for various portable cameras and can be applied to robot vision, driving assistant systems, and visual surveillance systems. PMID:28208622

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

Descent graphs in pedigree analysis: applications to haplotyping, location scores, and marker-sharing statistics.

PubMed Central

Sobel, E.; Lange, K.

1996-01-01

The introduction of stochastic methods in pedigree analysis has enabled geneticists to tackle computations intractable by standard deterministic methods. Until now these stochastic techniques have worked by running a Markov chain on the set of genetic descent states of a pedigree. Each descent state specifies the paths of gene flow in the pedigree and the founder alleles dropped down each path. The current paper follows up on a suggestion by Elizabeth Thompson that genetic descent graphs offer a more appropriate space for executing a Markov chain. A descent graph specifies the paths of gene flow but not the particular founder alleles traveling down the paths. This paper explores algorithms for implementing Thompson's suggestion for codominant markers in the context of automatic haplotyping, estimating location scores, and computing gene-clustering statistics for robust linkage analysis. Realistic numerical examples demonstrate the feasibility of the algorithms. PMID:8651310

Path querying system on mobile devices

NASA Astrophysics Data System (ADS)

Lin, Xing; Wang, Yifei; Tian, Yuan; Wu, Lun

2006-01-01

Traditional approaches to path querying problems are not efficient and convenient under most circumstances. A more convenient and reliable approach to this problem has to be found. This paper is devoted to a path querying solution on mobile devices. By using an improved Dijkstra's shortest path algorithm and a natural language translating module, this system can help people find the shortest path between two places through their cell phones or other mobile devices. The chosen path is prompted in text of natural language, as well as a map picture. This system would be useful in solving best path querying problems and have potential to be a profitable business system.

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Properties of an adaptive feedback equalization algorithm.

PubMed

Engebretson, A M; French-St George, M

1993-01-01

This paper describes a new approach to feedback equalization for hearing aids. The method involves the use of an adaptive algorithm that estimates and tracks the characteristic of the hearing aid feedback path. The algorithm is described and the results of simulation studies and bench testing are presented.

Raman Lidar MERGE Value-Added Product

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newsom, Rob; Goldsmith, John; Sivaraman, Chitra

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Raman lidars (RLs) are semi-autonomous, land-based, laser remote sensing systems that provide height- and time-resolved measurements of water vapor mixing ratio, temperature, aerosol backscatter, extinction, and linear depolarization ratio from about 200 m to greater than 10 km AGL. These systems transmit at a wavelength of 355 nm with 300 mJ, ~5 ns pulses, and a pulse repetition frequency of 30 Hz. The receiver incorporates nine detection channels, including two water vapor channels at 408 nm, two nitrogen channels at 387 nm, three elastic channels, and twomore » rotational Raman channels for temperature profiling at 354 and 353 nm. Figure 1 illustrates the layout of the ARM RL receiver system. Backscattered light from the atmosphere enters the telescope and is directed into the receiver system (i.e., aft optics). This signal is then split between a narrow-field-of-view radiometer (NFOV) path (blue) and a wide-field-of-view zenith radiometer (WFOV) path (red). The WFOV (2 mrad) path contains three channels (water vapor, nitrogen, and unpolarized elastic), and the NFOV (0.3 mrad) path contains six channels (water vapor, nitrogen, parallel and perpendicular elastic, and two rotational Raman). All nine detection channels use Electron Tubes 9954B photomultiplier tubes (PMTs). The signals from each of the nine PMTs are acquired using transient data recorders from Licel GbR (Berlin, Germany). The Licel data recorders provide simultaneous measurements of both analog photomultiplier current and photon counts at height resolution of 7.5 m and a time resolution of 10 s. The analog signal provides good linearity in the strong signal regime, but poor sensitivity at low signal levels. Conversely, the photo counting signal provides good sensitivity in the weak signal regime, but is strongly nonlinear at higher signal levels. The advantage in recording both signals is that they can be combined (or merged) into a single signal with improved dynamic range. The process of combining the analog and photon counting data has become known as “gluing” (Whiteman et al., 2006).« less

Hierarchical image segmentation via recursive superpixel with adaptive regularity

NASA Astrophysics Data System (ADS)

Nakamura, Kensuke; Hong, Byung-Woo

2017-11-01

A fast and accurate segmentation algorithm in a hierarchical way based on a recursive superpixel technique is presented. We propose a superpixel energy formulation in which the trade-off between data fidelity and regularization is dynamically determined based on the local residual in the energy optimization procedure. We also present an energy optimization algorithm that allows a pixel to be shared by multiple regions to improve the accuracy and appropriate the number of segments. The qualitative and quantitative evaluations demonstrate that our algorithm, combining the proposed energy and optimization, outperforms the conventional k-means algorithm by up to 29.10% in F-measure. We also perform comparative analysis with state-of-the-art algorithms in the hierarchical segmentation. Our algorithm yields smooth regions throughout the hierarchy as opposed to the others that include insignificant details. Our algorithm overtakes the other algorithms in terms of balance between accuracy and computational time. Specifically, our method runs 36.48% faster than the region-merging approach, which is the fastest of the comparing algorithms, while achieving a comparable accuracy.

a Modified Genetic Algorithm for Finding Fuzzy Shortest Paths in Uncertain Networks

NASA Astrophysics Data System (ADS)

Heidari, A. A.; Delavar, M. R.

2016-06-01

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.

Numerically robust and efficient nonlocal electron transport in 2D DRACO simulations

NASA Astrophysics Data System (ADS)

Cao, Duc; Chenhall, Jeff; Moses, Greg; Delettrez, Jacques; Collins, Tim

2013-10-01

An improved implicit algorithm based on Schurtz, Nicolai and Busquet (SNB) algorithm for nonlocal electron transport is presented. Validation with direct drive shock timing experiments and verification with the Goncharov nonlocal model in 1D LILAC simulations demonstrate the viability of this efficient algorithm for producing 2D lagrangian radiation hydrodynamics direct drive simulations. Additionally, simulations provide strong incentive to further modify key parameters within the SNB theory, namely the ``mean free path.'' An example 2D polar drive simulation to study 2D effects of the nonlocal flux as well as mean free path modifications will also be presented. This research was supported by the University of Rochester Laboratory for Laser Energetics.

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors

PubMed Central

Las Fargeas, Jonathan; Kabamba, Pierre; Girard, Anouck

2015-01-01

This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios. PMID:25591168

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE PAGES

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

2017-01-01

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Hop Optimization and Relay Node Selection in Multi-hop Wireless Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Li, Xiaohua(Edward)

In this paper we propose an efficient approach to determine the optimal hops for multi-hop ad hoc wireless networks. Based on the assumption that nodes use successive interference cancellation (SIC) and maximal ratio combining (MRC) to deal with mutual interference and to utilize all the received signal energy, we show that the signal-to-interference-plus-noise ratio (SINR) of a node is determined only by the nodes before it, not the nodes after it, along a packet forwarding path. Based on this observation, we propose an iterative procedure to select the relay nodes and to calculate the path SINR as well as capacity of an arbitrary multi-hop packet forwarding path. The complexity of the algorithm is extremely low, and scaling well with network size. The algorithm is applicable in arbitrarily large networks. Its performance is demonstrated as desirable by simulations. The algorithm can be helpful in analyzing the performance of multi-hop wireless networks.

Robust mobility in human-populated environments

NASA Astrophysics Data System (ADS)

Gonzalez, Juan Pablo; Phillips, Mike; Neuman, Brad; Likhachev, Max

2012-06-01

Creating robots that can help humans in a variety of tasks requires robust mobility and the ability to safely navigate among moving obstacles. This paper presents an overview of recent research in the Robotics Collaborative Technology Alliance (RCTA) that addresses many of the core requirements for robust mobility in human-populated environments. Safe Interval Path Planning (SIPP) allows for very fast planning in dynamic environments when planning timeminimal trajectories. Generalized Safe Interval Path Planning extends this concept to trajectories that minimize arbitrary cost functions. Finally, generalized PPCP algorithm is used to generate plans that reason about the uncertainty in the predicted trajectories of moving obstacles and try to actively disambiguate the intentions of humans whenever necessary. We show how these approaches consider moving obstacles and temporal constraints and produce high-fidelity paths. Experiments in simulated environments show the performance of the algorithms under different controlled conditions, and experiments on physical mobile robots interacting with humans show how the algorithms perform under the uncertainties of the real world.

Fast marching methods for the continuous traveling salesman problem.

PubMed

Andrews, June; Sethian, J A

2007-01-23

We consider a problem in which we are given a domain, a cost function which depends on position at each point in the domain, and a subset of points ("cities") in the domain. The goal is to determine the cheapest closed path that visits each city in the domain once. This can be thought of as a version of the traveling salesman problem, in which an underlying known metric determines the cost of moving through each point of the domain, but in which the actual shortest path between cities is unknown at the outset. We describe algorithms for both a heuristic and an optimal solution to this problem. The complexity of the heuristic algorithm is at worst case M.N log N, where M is the number of cities, and N the size of the computational mesh used to approximate the solutions to the shortest paths problems. The average runtime of the heuristic algorithm is linear in the number of cities and O(N log N) in the size N of the mesh.

Improved transition path sampling methods for simulation of rare events

NASA Astrophysics Data System (ADS)

Chopra, Manan; Malshe, Rohit; Reddy, Allam S.; de Pablo, J. J.

2008-04-01

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.

Reconstruction for proton computed tomography by tracing proton trajectories: A Monte Carlo study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Tianfang; Liang Zhengrong; Singanallur, Jayalakshmi V.

Proton computed tomography (pCT) has been explored in the past decades because of its unique imaging characteristics, low radiation dose, and its possible use for treatment planning and on-line target localization in proton therapy. However, reconstruction of pCT images is challenging because the proton path within the object to be imaged is statistically affected by multiple Coulomb scattering. In this paper, we employ GEANT4-based Monte Carlo simulations of the two-dimensional pCT reconstruction of an elliptical phantom to investigate the possible use of the algebraic reconstruction technique (ART) with three different path-estimation methods for pCT reconstruction. The first method assumes amore » straight-line path (SLP) connecting the proton entry and exit positions, the second method adapts the most-likely path (MLP) theoretically determined for a uniform medium, and the third method employs a cubic spline path (CSP). The ART reconstructions showed progressive improvement of spatial resolution when going from the SLP [2 line pairs (lp) cm{sup -1}] to the curved CSP and MLP path estimates (5 lp cm{sup -1}). The MLP-based ART algorithm had the fastest convergence and smallest residual error of all three estimates. This work demonstrates the advantage of tracking curved proton paths in conjunction with the ART algorithm and curved path estimates.« less

Iterative blip-summed path integral for quantum dynamics in strongly dissipative environments

NASA Astrophysics Data System (ADS)

Makri, Nancy

2017-04-01

The iterative decomposition of the blip-summed path integral [N. Makri, J. Chem. Phys. 141, 134117 (2014)] is described. The starting point is the expression of the reduced density matrix for a quantum system interacting with a harmonic dissipative bath in the form of a forward-backward path sum, where the effects of the bath enter through the Feynman-Vernon influence functional. The path sum is evaluated iteratively in time by propagating an array that stores blip configurations within the memory interval. Convergence with respect to the number of blips and the memory length yields numerically exact results which are free of statistical error. In situations of strongly dissipative, sluggish baths, the algorithm leads to a dramatic reduction of computational effort in comparison with iterative path integral methods that do not implement the blip decomposition. This gain in efficiency arises from (i) the rapid convergence of the blip series and (ii) circumventing the explicit enumeration of between-blip path segments, whose number grows exponentially with the memory length. Application to an asymmetric dissipative two-level system illustrates the rapid convergence of the algorithm even when the bath memory is extremely long.

Path coloring on the Mesh

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabani, Y.

In the minimum path coloring problem, we are given a list of pairs of vertices of a graph. We are asked to connect each pair by a colored path. Paths of the same color must be edge disjoint. Our objective is to minimize the number of colors used. This problem was raised by Aggarwal et al and Raghavan and Upfal as a model for routing in all-optical networks. It is also related to questions in circuit routing. In this paper, we improve the O (ln N) approximation result of Kleinberg and Tardos for path coloring on the N x Nmore » mesh. We give an O(1) approximation algorithm to the number of colors needed, and a poly(ln ln N) approximation algorithm to the choice of paths and colors. To the best of our knowledge, these are the first sub-logarithmic bounds for any network other than trees, rings, or trees of rings. Our results are based on developing new techniques for randomized rounding. These techniques iteratively improve a fractional solution until it approaches integrality. They are motivated by the method used by Leighton, Maggs, and Rao for packet routing.« less

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors.

PubMed

Dasgupta, Rumpa; Yoon, Seokhoon

2017-04-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs' traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs' paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay.

Energy-Efficient Deadline-Aware Data-Gathering Scheme Using Multiple Mobile Data Collectors

PubMed Central

Dasgupta, Rumpa; Yoon, Seokhoon

2017-01-01

In wireless sensor networks, the data collected by sensors are usually forwarded to the sink through multi-hop forwarding. However, multi-hop forwarding can be inefficient due to the energy hole problem and high communications overhead. Moreover, when the monitored area is large and the number of sensors is small, sensors cannot send the data via multi-hop forwarding due to the lack of network connectivity. In order to address those problems of multi-hop forwarding, in this paper, we consider a data collection scheme that uses mobile data collectors (MDCs), which visit sensors and collect data from them. Due to the recent breakthroughs in wireless power transfer technology, MDCs can also be used to recharge the sensors to keep them from draining their energy. In MDC-based data-gathering schemes, a big challenge is how to find the MDCs’ traveling paths in a balanced way, such that their energy consumption is minimized and the packet-delay constraint is satisfied. Therefore, in this paper, we aim at finding the MDCs’ paths, taking energy efficiency and delay constraints into account. We first define an optimization problem, named the delay-constrained energy minimization (DCEM) problem, to find the paths for MDCs. An integer linear programming problem is formulated to find the optimal solution. We also propose a two-phase path-selection algorithm to efficiently solve the DCEM problem. Simulations are performed to compare the performance of the proposed algorithms with two heuristics algorithms for the vehicle routing problem under various scenarios. The simulation results show that the proposed algorithms can outperform existing algorithms in terms of energy efficiency and packet delay. PMID:28368300

Motion Planning and Synthesis of Human-Like Characters in Constrained Environments

NASA Astrophysics Data System (ADS)

Zhang, Liangjun; Pan, Jia; Manocha, Dinesh

We give an overview of our recent work on generating naturally-looking human motion in constrained environments with multiple obstacles. This includes a whole-body motion planning algorithm for high DOF human-like characters. The planning problem is decomposed into a sequence of low dimensional sub-problems. We use a constrained coordination scheme to solve the sub-problems in an incremental manner and a local path refinement algorithm to compute collision-free paths in tight spaces and satisfy the statically stable constraint on CoM. We also present a hybrid algorithm to generate plausible motion by combing the motion computed by our planner with mocap data. We demonstrate the performance of our algorithm on a 40 DOF human-like character and generate efficient motion strategies for object placement, bending, walking, and lifting in complex environments.

THE EVOLUTION OF PRIMORDIAL BINARY OPEN STAR CLUSTERS: MERGERS, SHREDDED SECONDARIES, AND SEPARATED TWINS

DOE Office of Scientific and Technical Information (OSTI.GOV)

De la Fuente Marcos, R.; De la Fuente Marcos, C., E-mail: raul@galaxy.suffolk.e

2010-08-10

The properties of the candidate binary star cluster population in the Magellanic Clouds and Milky Way are similar. The fraction of candidate binaries is {approx}10% and the pair separation histogram exhibits a bimodal distribution commonly attributed to their transient nature. However, if primordial pairs cannot survive for long as recognizable bound systems, how are they ending up? Here, we use simulations to confirm that merging, extreme tidal distortion, and ionization are possible depending on the initial orbital elements and mass ratio of the cluster pair. Merging is observed for initially close pairs but also for wider systems in nearly parabolicmore » orbits. Its characteristic timescale depends on the initial orbital semi-major axis, eccentricity, and cluster pair mass ratio, becoming shorter for closer, more eccentric equal mass pairs. Shredding of the less massive cluster and subsequent separation is observed in all pairs with appreciably different masses. Wide pairs evolve into separated twins characterized by the presence of tidal bridges and separations of 200-500 pc after one Galactic orbit. Most observed binary candidates appear to be following this evolutionary path which translates into the dominant peak (25-30 pc) in the observed pair separation distribution. The secondary peak at smaller separations (10-15 pc) can be explained as due to close pairs in almost circular orbits and/or undergoing merging. Merged clusters exhibit both peculiar radial density and velocity dispersion profiles shaped by synchronization and gravogyro instabilities. Simulations and observations show that long-term binary open cluster stability is unlikely.« less

A Portable Ground-Based Atmospheric Monitoring System (PGAMS) for the Calibration and Validation of Atmospheric Correction Algorithms Applied to Aircraft and Satellite Images

NASA Technical Reports Server (NTRS)

Schiller, Stephen; Luvall, Jeffrey C.; Rickman, Doug L.; Arnold, James E. (Technical Monitor)

2000-01-01

Detecting changes in the Earth's environment using satellite images of ocean and land surfaces must take into account atmospheric effects. As a result, major programs are underway to develop algorithms for image retrieval of atmospheric aerosol properties and atmospheric correction. However, because of the temporal and spatial variability of atmospheric transmittance it is very difficult to model atmospheric effects and implement models in an operational mode. For this reason, simultaneous in situ ground measurements of atmospheric optical properties are vital to the development of accurate atmospheric correction techniques. Presented in this paper is a spectroradiometer system that provides an optimized set of surface measurements for the calibration and validation of atmospheric correction algorithms. The Portable Ground-based Atmospheric Monitoring System (PGAMS) obtains a comprehensive series of in situ irradiance, radiance, and reflectance measurements for the calibration of atmospheric correction algorithms applied to multispectral. and hyperspectral images. The observations include: total downwelling irradiance, diffuse sky irradiance, direct solar irradiance, path radiance in the direction of the north celestial pole, path radiance in the direction of the overflying satellite, almucantar scans of path radiance, full sky radiance maps, and surface reflectance. Each of these parameters are recorded over a wavelength range from 350 to 1050 nm in 512 channels. The system is fast, with the potential to acquire the complete set of observations in only 8 to 10 minutes depending on the selected spatial resolution of the sky path radiance measurements

Effective bandwidth guaranteed routing schemes for MPLS traffic engineering

NASA Astrophysics Data System (ADS)

Wang, Bin; Jain, Nidhi

2001-07-01

In this work, we present online algorithms for dynamic routing bandwidth guaranteed label switched paths (LSPs) where LSP set-up requests (in terms of a pair of ingress and egress routers as well as its bandwidth requirement) arrive one by one and there is no a priori knowledge regarding future LSP set-up requests. In addition, we consider rerouting of LSPs in this work. Rerouting of LSPs has not been well studied in previous work on LSP routing. The need of LSP rerouting arises in a number of ways: occurrence of faults (link and/or node failures), re-optimization of existing LSPs' routes to accommodate traffic fluctuation, requests with higher priorities, and so on. We formulate the bandwidth guaranteed LSP routing with rerouting capability as a multi-commodity flow problem. The solution to this problem is used as the benchmark for comparing other computationally less costly algorithms studied in this paper. Furthermore, to more efficiently utilize the network resources, we propose online routing algorithms which route bandwidth demands over multiple paths at the ingress router to satisfy the customer requests while providing better service survivability. Traffic splitting and distribution over the multiple paths are carefully handled using table-based hashing schemes while the order of packets within a flow is preserved. Preliminary simulations are conducted to show the performance of different design choices and the effectiveness of the rerouting and multi-path routing algorithms in terms of LSP set-up request rejection probability and bandwidth blocking probability.

Open-path FTIR data reduction algorithm with atmospheric absorption corrections: the NONLIN code

NASA Astrophysics Data System (ADS)

Phillips, William; Russwurm, George M.

1999-02-01

This paper describes the progress made to date in developing, testing, and refining a data reduction computer code, NONLIN, that alleviates many of the difficulties experienced in the analysis of open path FTIR data. Among the problems that currently effect FTIR open path data quality are: the inability to obtain a true I degree or background, spectral interferences of atmospheric gases such as water vapor and carbon dioxide, and matching the spectral resolution and shift of the reference spectra to a particular field instrument. This algorithm is based on a non-linear fitting scheme and is therefore not constrained by many of the assumptions required for the application of linear methods such as classical least squares (CLS). As a result, a more realistic mathematical model of the spectral absorption measurement process can be employed in the curve fitting process. Applications of the algorithm have proven successful in circumventing open path data reduction problems. However, recent studies, by one of the authors, of the temperature and pressure effects on atmospheric absorption indicate there exist temperature and water partial pressure effects that should be incorporated into the NONLIN algorithm for accurate quantification of gas concentrations. This paper investigates the sources of these phenomena. As a result of this study a partial pressure correction has been employed in NONLIN computer code. Two typical field spectra are examined to determine what effect the partial pressure correction has on gas quantification.

Cold pool organization and the merging of convective updrafts in a Large Eddy Simulation

NASA Astrophysics Data System (ADS)

Glenn, I. B.; Krueger, S. K.

2016-12-01

Cold pool organization is a process that accelerates the transition from shallow to deep cumulus convection, and leads to higher deep convective cloud top heights. The mechanism by which cold pool organization enhances convection remains not well understood, but the basic idea is that since precipitation evaporation and a low equivalent potential temperature in the mid-troposphere lead to strong cold pools, the net cold pool effect can be accounted for in a cumulus parameterization as a relationship involving those factors. Understanding the actual physical mechanism at work will help quantify the strength of the relationship between cold pools and enhanced deep convection. One proposed mechanism of enhancement is that cold pool organization leads to reduced distances between updrafts, creating a local environment more conducive to convection as updrafts entrain parcels of air recently detrained by their neighbors. We take this hypothesis one step further and propose that convective updrafts actually merge, not just exchange recently processed air. Because entrainment and detrainment around an updraft draws nearby air in or pushes it out, respectively, they act like dynamic flow sources and sinks, drawing each other in or pushing each other away. The acceleration is proportional to the inverse square of the distance between two updrafts, so a small reduction in distance can make a big difference in the rate of merging. We have shown in previous research how merging can be seen as collisions between different updraft air parcels using Lagrangian Parcel Trajectories (LPTs) released in a Large Eddy Simulation (LES) during a period with organized deep convection. Now we use a Eulerian frame of reference to examine the updraft merging process during the transition from shallow to organized deep convection. We use a case based on the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) for our LES. We directly measure the rate of entrainment and the properties of the entrained air for all convective updrafts in the simulation. We use a tracking algorithm to define merging between convective updrafts. We will show the rate of merging as the transition between shallow and deep convection occurs and the different distributions of entrainment rate and ultimate detrainment height of merged and non-merged updrafts.

[An object-oriented remote sensing image segmentation approach based on edge detection].

PubMed

Tan, Yu-Min; Huai, Jian-Zhu; Tang, Zhong-Shi

2010-06-01

Satellite sensor technology endorsed better discrimination of various landscape objects. Image segmentation approaches to extracting conceptual objects and patterns hence have been explored and a wide variety of such algorithms abound. To this end, in order to effectively utilize edge and topological information in high resolution remote sensing imagery, an object-oriented algorithm combining edge detection and region merging is proposed. Susan edge filter is firstly applied to the panchromatic band of Quickbird imagery with spatial resolution of 0.61 m to obtain the edge map. Thanks to the resulting edge map, a two-phrase region-based segmentation method operates on the fusion image from panchromatic and multispectral Quickbird images to get the final partition result. In the first phase, a quad tree grid consisting of squares with sides parallel to the image left and top borders agglomerates the square subsets recursively where the uniform measure is satisfied to derive image object primitives. Before the merger of the second phrase, the contextual and spatial information, (e. g., neighbor relationship, boundary coding) of the resulting squares are retrieved efficiently by means of the quad tree structure. Then a region merging operation is performed with those primitives, during which the criterion for region merging integrates edge map and region-based features. This approach has been tested on the QuickBird images of some site in Sanxia area and the result is compared with those of ENVI Zoom Definiens. In addition, quantitative evaluation of the quality of segmentation results is also presented. Experiment results demonstrate stable convergence and efficiency.

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Janich, Karl W.

2005-01-01

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

Synthesis of Joint Volumes, Visualization of Paths, and Revision of Viewing Sequences in a Multi-dimensional Seismic Data Viewer

NASA Astrophysics Data System (ADS)

Chen, D. M.; Clapp, R. G.; Biondi, B.

2006-12-01

Ricksep is a freely-available interactive viewer for multi-dimensional data sets. The viewer is very useful for simultaneous display of multiple data sets from different viewing angles, animation of movement along a path through the data space, and selection of local regions for data processing and information extraction. Several new viewing features are added to enhance the program's functionality in the following three aspects. First, two new data synthesis algorithms are created to adaptively combine information from a data set with mostly high-frequency content, such as seismic data, and another data set with mainly low-frequency content, such as velocity data. Using the algorithms, these two data sets can be synthesized into a single data set which resembles the high-frequency data set on a local scale and at the same time resembles the low- frequency data set on a larger scale. As a result, the originally separated high and low-frequency details can now be more accurately and conveniently studied together. Second, a projection algorithm is developed to display paths through the data space. Paths are geophysically important because they represent wells into the ground. Two difficulties often associated with tracking paths are that they normally cannot be seen clearly inside multi-dimensional spaces and depth information is lost along the direction of projection when ordinary projection techniques are used. The new algorithm projects samples along the path in three orthogonal directions and effectively restores important depth information by using variable projection parameters which are functions of the distance away from the path. Multiple paths in the data space can be generated using different character symbols as positional markers, and users can easily create, modify, and view paths in real time. Third, a viewing history list is implemented which enables Ricksep's users to create, edit and save a recipe for the sequence of viewing states. Then, the recipe can be loaded into an active Ricksep session, after which the user can navigate to any state in the sequence and modify the sequence from that state. Typical uses of this feature are undoing and redoing viewing commands and animating a sequence of viewing states. The theoretical discussion are carried out and several examples using real seismic data are provided to show how these new Ricksep features provide more convenient, accurate ways to manipulate multi-dimensional data sets.

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

NASA Astrophysics Data System (ADS)

Chatzidakis, Stylianos; Liu, Zhengzhi; Hayward, Jason P.; Scaglione, John M.

2018-03-01

This work presents a generalized muon trajectory estimation algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguard verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstruction algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS is explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm's precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm root mean square (RMS) for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. The effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.

Application of modern control theory to scheduling and path-stretching maneuvers of aircraft in the near terminal area

NASA Technical Reports Server (NTRS)

Athans, M.

1974-01-01

A design concept of the dynamic control of aircraft in the near terminal area is discussed. An arbitrary set of nominal air routes, with possible multiple merging points, all leading to a single runway, is considered. The system allows for the automated determination of acceleration/deceleration of aircraft along the nominal air routes, as well as for the automated determination of path-stretching delay maneuvers. In addition to normal operating conditions, the system accommodates: (1) variable commanded separations over the outer marker to allow for takeoffs and between successive landings and (2) emergency conditions under which aircraft in distress have priority. The system design is based on a combination of three distinct optimal control problems involving a standard linear-quadratic problem, a parameter optimization problem, and a minimum-time rendezvous problem.

Fast algorithm of adaptive Fourier series

NASA Astrophysics Data System (ADS)

Gao, You; Ku, Min; Qian, Tao

2018-05-01

Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

2010-01-01

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms.

PubMed

Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Peissig, Peggy L; Denny, Joshua C; Kho, Abel N; Miller, Aaron; Pathak, Jyotishman

2012-01-01

The development of Electronic Health Record (EHR)-based phenotype selection algorithms is a non-trivial and highly iterative process involving domain experts and informaticians. To make it easier to port algorithms across institutions, it is desirable to represent them using an unambiguous formal specification language. For this purpose we evaluated the recently developed National Quality Forum (NQF) information model designed for EHR-based quality measures: the Quality Data Model (QDM). We selected 9 phenotyping algorithms that had been previously developed as part of the eMERGE consortium and translated them into QDM format. Our study concluded that the QDM contains several core elements that make it a promising format for EHR-driven phenotyping algorithms for clinical research. However, we also found areas in which the QDM could be usefully extended, such as representing information extracted from clinical text, and the ability to handle algorithms that do not consist of Boolean combinations of criteria.

A cluster merging method for time series microarray with production values.

PubMed

Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio

2014-09-01

A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.

Target-based calibration method for multifields of view measurement using multiple stereo digital image correlation systems

NASA Astrophysics Data System (ADS)

Dong, Shuai; Yu, Shanshan; Huang, Zheng; Song, Shoutan; Shao, Xinxing; Kang, Xin; He, Xiaoyuan

2017-12-01

Multiple digital image correlation (DIC) systems can enlarge the measurement field without losing effective resolution in the area of interest (AOI). However, the results calculated in substereo DIC systems are located in its local coordinate system in most cases. To stitch the data obtained by each individual system, a data merging algorithm is presented in this paper for global measurement of multiple stereo DIC systems. A set of encoded targets is employed to assist the extrinsic calibration, of which the three-dimensional (3-D) coordinates are reconstructed via digital close range photogrammetry. Combining the 3-D targets with precalibrated intrinsic parameters of all cameras, the extrinsic calibration is significantly simplified. After calculating in substereo DIC systems, all data can be merged into a universal coordinate system based on the extrinsic calibration. Four stereo DIC systems are applied to a four point bending experiment of a steel reinforced concrete beam structure. Results demonstrate high accuracy for the displacement data merging in the overlapping field of views (FOVs) and show feasibility for the distributed FOVs measurement.

Image Fusion of CT and MR with Sparse Representation in NSST Domain

PubMed Central

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. PMID:29250134

Image Fusion of CT and MR with Sparse Representation in NSST Domain.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan; Xia, Shunren

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

Richardson-Lucy deblurring for the star scene under a thinning motion path

NASA Astrophysics Data System (ADS)

Su, Laili; Shao, Xiaopeng; Wang, Lin; Wang, Haixin; Huang, Yining

2015-05-01

This paper puts emphasis on how to model and correct image blur that arises from a camera's ego motion while observing a distant star scene. Concerning the significance of accurate estimation of point spread function (PSF), a new method is employed to obtain blur kernel by thinning star motion path. In particular, how the blurred star image can be corrected to reconstruct the clear scene with a thinning motion blur model which describes the camera's path is presented. This thinning motion path to build blur kernel model is more effective at modeling the spatially motion blur introduced by camera's ego motion than conventional blind estimation of kernel-based PSF parameterization. To gain the reconstructed image, firstly, an improved thinning algorithm is used to obtain the star point trajectory, so as to extract the blur kernel of the motion-blurred star image. Then how motion blur model can be incorporated into the Richardson-Lucy (RL) deblurring algorithm, which reveals its overall effectiveness, is detailed. In addition, compared with the conventional estimated blur kernel, experimental results show that the proposed method of using thinning algorithm to get the motion blur kernel is of less complexity, higher efficiency and better accuracy, which contributes to better restoration of the motion-blurred star images.

Optimization of the transition path of the head hardening with using the genetic algorithms

NASA Astrophysics Data System (ADS)

Wróbel, Joanna; Kulawik, Adam

2016-06-01

An automated method of choice of the transition path of the head hardening in heat treatment process for the plane steel element is proposed in this communication. This method determines the points on the path of moving heat source using the genetic algorithms. The fitness function of the used algorithm is determined on the basis of effective stresses and yield point depending on the phase composition. The path of the hardening tool and also the area of the heat affected zone is determined on the basis of obtained points. A numerical model of thermal phenomena, phase transformations in the solid state and mechanical phenomena for the hardening process is implemented in order to verify the presented method. A finite element method (FEM) was used for solving the heat transfer equation and getting required temperature fields. The moving heat source is modeled with a Gaussian distribution and the water cooling is also included. The macroscopic model based on the analysis of the CCT and CHT diagrams of the medium-carbon steel is used to determine the phase transformations in the solid state. A finite element method is also used for solving the equilibrium equations giving us the stress field. The thermal and structural strains are taken into account in the constitutive relations.

Formation flight and collision avoidance for multiple UAVs based on modified tentacle algorithm in unstructured environments

PubMed Central

2017-01-01

This paper presents a method for formation flight and collision avoidance of multiple UAVs. Due to the shortcomings such as collision avoidance caused by UAV’s high-speed and unstructured environments, this paper proposes a modified tentacle algorithm to ensure the high performance of collision avoidance. Different from the conventional tentacle algorithm which uses inverse derivation, the modified tentacle algorithm rapidly matches the radius of each tentacle and the steering command, ensuring that the data calculation problem in the conventional tentacle algorithm is solved. Meanwhile, both the speed sets and tentacles in one speed set are reduced and reconstructed so as to be applied to multiple UAVs. Instead of path iterative optimization, the paper selects the best tentacle to obtain the UAV collision avoidance path quickly. The simulation results show that the method presented in the paper effectively enhances the performance of flight formation and collision avoidance for multiple high-speed UAVs in unstructured environments. PMID:28763498

Temperature and pressure determination of the tin melt boundary from a combination of pyrometry, spectral reflectance, and velocity measurements along release paths

NASA Astrophysics Data System (ADS)

La Lone, Brandon; Asimow, Paul; Fatyanov, Oleg; Hixson, Robert; Stevens, Gerald

2017-06-01

Plate impact experiments were conducted on tin samples backed by LiF windows to determine the tin melt curve. Thin copper flyers were used so that a release wave followed the 30-40 GPa shock wave in the tin. The release wave at the tin-LiF interface was about 300 ns long. Two sets of experiments were conducted. In one set, spectral emissivity was measured at six wavelengths using a flashlamp illuminated integrating sphere. In the other set, thermal radiance was measured at two wavelengths. The emissivity and thermal radiance measurements were combined to obtain temperature histories of the tin-LiF interface during the release. PDV was used to obtain stress histories. All measurements were combined to obtain temperature vs. stress release paths. A kink or steepening in the release paths indicate where the releases merge onto the melt boundary, and release paths originating from different shock stresses overlap on the melt boundary. Our temperature-stress release path measurements provide a continuous segment of the tin melt boundary that is in good agreement with some of the published melt curves. This work was done by National Security Technologies, LLC, under Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy, and supported by the Site-Directed Research and Development Program. DOE/NV/259463133.

A distributed geo-routing algorithm for wireless sensor networks.

PubMed

Joshi, Gyanendra Prasad; Kim, Sung Won

2009-01-01

Geographic wireless sensor networks use position information for greedy routing. Greedy routing works well in dense networks, whereas in sparse networks it may fail and require a recovery algorithm. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costly for resource constrained position-based wireless sensor networks (WSNs). In this paper, we propose a void avoidance algorithm (VAA), a novel idea based on upgrading virtual distance. VAA allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forwarding packets using only greedy routing. In VAA, the stuck node upgrades distance unless it finds a next hop node that is closer to the destination than it is. VAA guarantees packet delivery if there is a topologically valid path. Further, it is completely distributed, immediately responds to node failure or topology changes and does not require planarization of the network. NS-2 is used to evaluate the performance and correctness of VAA and we compare its performance to other protocols. Simulations show our proposed algorithm consumes less energy, has an efficient path and substantially less control overheads.

A divide-and-conquer algorithm for large-scale de novo transcriptome assembly through combining small assemblies from existing algorithms.

PubMed

Sze, Sing-Hoi; Parrott, Jonathan J; Tarone, Aaron M

2017-12-06

While the continued development of high-throughput sequencing has facilitated studies of entire transcriptomes in non-model organisms, the incorporation of an increasing amount of RNA-Seq libraries has made de novo transcriptome assembly difficult. Although algorithms that can assemble a large amount of RNA-Seq data are available, they are generally very memory-intensive and can only be used to construct small assemblies. We develop a divide-and-conquer strategy that allows these algorithms to be utilized, by subdividing a large RNA-Seq data set into small libraries. Each individual library is assembled independently by an existing algorithm, and a merging algorithm is developed to combine these assemblies by picking a subset of high quality transcripts to form a large transcriptome. When compared to existing algorithms that return a single assembly directly, this strategy achieves comparable or increased accuracy as memory-efficient algorithms that can be used to process a large amount of RNA-Seq data, and comparable or decreased accuracy as memory-intensive algorithms that can only be used to construct small assemblies. Our divide-and-conquer strategy allows memory-intensive de novo transcriptome assembly algorithms to be utilized to construct large assemblies.

Optimal guidance with obstacle avoidance for nap-of-the-earth flight

NASA Technical Reports Server (NTRS)

Pekelsma, Nicholas J.

1988-01-01

The development of automatic guidance is discussed for helicopter Nap-of-the-Earth (NOE) and near-NOE flight. It deals with algorithm refinements relating to automated real-time flight path planning and to mission planning. With regard to path planning, it relates rotorcraft trajectory characteristics to the NOE computation scheme and addresses real-time computing issues and both ride quality issues and pilot-vehicle interfaces. The automated mission planning algorithm refinements include route optimization, automatic waypoint generation, interactive applications, and provisions for integrating the results into the real-time path planning software. A microcomputer based mission planning workstation was developed and is described. Further, the application of Defense Mapping Agency (DMA) digital terrain to both the mission planning workstation and to automatic guidance is both discussed and illustrated.

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Scanning electron microscope fine tuning using four-bar piezoelectric actuated mechanism

NASA Astrophysics Data System (ADS)

Hatamleh, Khaled S.; Khasawneh, Qais A.; Al-Ghasem, Adnan; Jaradat, Mohammad A.; Sawaqed, Laith; Al-Shabi, Mohammad

2018-01-01

Scanning Electron Microscopes are extensively used for accurate micro/nano images exploring. Several strategies have been proposed to fine tune those microscopes in the past few years. This work presents a new fine tuning strategy of a scanning electron microscope sample table using four bar piezoelectric actuated mechanisms. The introduced paper presents an algorithm to find all possible inverse kinematics solutions of the proposed mechanism. In addition, another algorithm is presented to search for the optimal inverse kinematic solution. Both algorithms are used simultaneously by means of a simulation study to fine tune a scanning electron microscope sample table through a pre-specified circular or linear path of motion. Results of the study shows that, proposed algorithms were able to minimize the power required to drive the piezoelectric actuated mechanism by a ratio of 97.5% for all simulated paths of motion when compared to general non-optimized solution.

Development and test results of a flight management algorithm for fuel conservative descents in a time-based metered traffic environment

NASA Technical Reports Server (NTRS)

Knox, C. E.; Cannon, D. G.

1980-01-01

A simple flight management descent algorithm designed to improve the accuracy of delivering an airplane in a fuel-conservative manner to a metering fix at a time designated by air traffic control was developed and flight tested. This algorithm provides a three dimensional path with terminal area time constraints (four dimensional) for an airplane to make an idle thrust, clean configured (landing gear up, flaps zero, and speed brakes retracted) descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path was calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithm is described. The results of the flight tests flown with the Terminal Configured Vehicle airplane are presented.

Multi-jet Merging with NLO Matrix Elements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siegert, Frank; /Freiburg U.; Hoche, Stefan

2011-08-18

In the algorithm presented here, the ME+PS approach to merge samples of tree-level matrix elements into inclusive event samples is combined with the POWHEG method, which includes exact next-to-leading order matrix elements in the parton shower. The advantages of the method are discussed and the quality of its implementation in SHERPA is exemplified by results for e{sup +}e{sup -} annihilation into hadrons at LEP, for deep-inelastic lepton-nucleon scattering at HERA, for Drell-Yan lepton-pair production at the Tevatron and for W{sup +}W{sup -}-production at LHC energies. The simulation of hard QCD radiation in parton-shower Monte Carlos has seen tremendous progress overmore » the last years. It was largely stimulated by the need for more precise predictions at LHC energies where the large available phase space allows additional hard QCD radiation alongside known Standard Model processes or even signals from new physics. Two types of algorithms have been developed, which allow to improve upon the soft-collinear approximations made in the parton shower, such that hard radiation is simulated according to exact matrix elements. In the ME+PS approach [1] higher-order tree-level matrix elements for different final-state jet multiplicity are merged with each other and with subsequent parton shower emissions to generate an inclusive sample. Such a prescription is invaluable for analyses which are sensitive to final states with a large jet multiplicity. The only remaining deficiency of such tree-level calculations is the large uncertainty stemming from scale variations. The POWHEG method [2] solves this problem for the lowest multiplicity subprocess by combining full NLO matrix elements with the parton shower. While this leads to NLO accuracy in the inclusive cross section and the exact radiation pattern for the first emission, it fails to describe higher-order emissions with improved accuracy. Thus it is not sufficient if final states with high jet multiplicities are considered. With the complementary advantages of these two approaches, the question arises naturally whether it would be possible to combine them into an even more powerful one. Such a combined algorithm was independently developed in [5] and [6]. Here a summary of the algorithm is given and predictions from corresponding Monte-Carlo predictions are presented.« less

A technique for locating function roots and for satisfying equality constraints in optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1991-01-01

A new technique for locating simultaneous roots of a set of functions is described. The technique is based on the property of the Kreisselmeier-Steinhauser function which descends to a minimum at each root location. It is shown that the ensuing algorithm may be merged into any nonlinear programming method for solving optimization problems with equality constraints.

A technique for locating function roots and for satisfying equality constraints in optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.

1992-01-01

A new technique for locating simultaneous roots of a set of functions is described. The technique is based on the property of the Kreisselmeier-Steinhauser function which descends to a minimum at each root location. It is shown that the ensuing algorithm may be merged into any nonlinear programming method for solving optimization problems with equality constraints.

The MAGIC-5 CAD for nodule detection in low dose and thin slice lung CTs

NASA Astrophysics Data System (ADS)

Cerello, Piergiorgio; MAGIC-5 Collaboration

2010-11-01

Lung cancer is the leading cause of cancer-related mortality in developed countries. Only 10-15% of all men and women diagnosed with lung cancer live 5 years after the diagnosis. However, the 5-year survival rate for patients diagnosed in the early asymptomatic stage of the disease can reach 70%. Early-stage lung cancers can be diagnosed by detecting non-calcified small pulmonary nodules with computed tomography (CT). Computer-aided detection (CAD) could support radiologists in the analysis of the large amount of noisy images generated in screening programs, where low-dose and thin-slice settings are used. The MAGIC-5 project, funded by the Istituto Nazionale di Fisica Nucleare (INFN, Italy) and Ministero dell'Università e della Ricerca (MUR, Italy), developed a multi-method approach based on three CAD algorithms to be used in parallel with a merging of their results: the Channeler Ant Model (CAM), based on Virtual Ant Colonies, the Dot-Enhancement/Pleura Surface Normals/VBNA (DE-PSN-VBNA), and the Region Growing Volume Plateau (RGVP). Preliminary results show quite good performances, to be improved with the refining of the single algorithm and the added value of the results merging.

Research to Operations: From Point Positions, Earthquake and Tsunami Modeling to GNSS-augmented Tsunami Early Warning

NASA Astrophysics Data System (ADS)

Stough, T.; Green, D. S.

2017-12-01

This collaborative research to operations demonstration brings together the data and algorithms from NASA research, technology, and applications-funded projects to deliver relevant data streams, algorithms, predictive models, and visualization tools to the NOAA National Tsunami Warning Center (NTWC) and Pacific Tsunami Warning Center (PTWC). Using real-time GNSS data and models in an operational environment, we will test and evaluate an augmented capability for tsunami early warning. Each of three research groups collect data from a selected network of real-time GNSS stations, exchange data consisting of independently processed 1 Hz station displacements, and merge the output into a single, more accurate and reliable set. The resulting merged data stream is delivered from three redundant locations to the TWCs with a latency of 5-10 seconds. Data from a number of seismogeodetic stations with collocated GPS and accelerometer instruments are processed for displacements and seismic velocities and also delivered. Algorithms for locating and determining the magnitude of earthquakes as well as algorithms that compute the source function of a potential tsunami using this new data stream are included in the demonstration. The delivered data, algorithms, models and tools are hosted on NOAA-operated machines at both warning centers, and, once tested, the results will be evaluated for utility in improving the speed and accuracy of tsunami warnings. This collaboration has the potential to dramatically improve the speed and accuracy of the TWCs local tsunami information over the current seismometer-only based methods. In our first year of this work, we have established and deployed an architecture for data movement and algorithm installation at the TWC's. We are addressing data quality issues and porting algorithms into the TWCs operating environment. Our initial module deliveries will focus on estimating moment magnitude (Mw) from Peak Ground Displacement (PGD), within 2-3 minutes of the event, and coseismic displacements converging to static offsets. We will also develop visualizations of module outputs tailored to the operational environment. In the context of this work, we will also discuss this research to operations approach and other opportunities within the NASA Applied Science Disaster Program.

Architecture and design of optical path networks utilizing waveband virtual links

NASA Astrophysics Data System (ADS)

Ito, Yusaku; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi

2016-02-01

We propose a novel optical network architecture that uses waveband virtual links, each of which can carry several optical paths, to directly bridge distant node pairs. Future photonic networks should not only transparently cover extended areas but also expand fiber capacity. However, the traversal of many ROADM nodes impairs the optical signal due to spectrum narrowing. To suppress the degradation, the bandwidth of guard bands needs to be increased, which degrades fiber frequency utilization. Waveband granular switching allows us to apply broader pass-band filtering at ROADMs and to insert sufficient guard bands between wavebands with minimum frequency utilization offset. The scheme resolves the severe spectrum narrowing effect. Moreover, the guard band between optical channels in a waveband can be minimized, which increases the number of paths that can be accommodated per fiber. In the network, wavelength path granular routing is done without utilizing waveband virtual links, and it still suffers from spectrum narrowing. A novel network design algorithm that can bound the spectrum narrowing effect by limiting the number of hops (traversed nodes that need wavelength path level routing) is proposed in this paper. This algorithm dynamically changes the waveband virtual link configuration according to the traffic distribution variation, where optical paths that need many node hops are effectively carried by virtual links. Numerical experiments demonstrate that the number of necessary fibers is reduced by 23% compared with conventional optical path networks.

Real-time multiple-objective path search for in-vehicle route guidance systems

DOT National Transportation Integrated Search

1997-01-01

The application of multiple-objective route choice for in-vehicle route guidance systems is discussed. A bi-objective path search algorithm is presented and its use demonstrated. A concept of trip quality is introduced that is composed of two objecti...

Short-range quantitative precipitation forecasting using Deep Learning approaches

NASA Astrophysics Data System (ADS)

Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

Efficient sampling of parsimonious inversion histories with application to genome rearrangement in Yersinia.

PubMed

Miklós, István; Darling, Aaron E

2009-06-22

Inversions are among the most common mutations acting on the order and orientation of genes in a genome, and polynomial-time algorithms exist to obtain a minimal length series of inversions that transform one genome arrangement to another. However, the minimum length series of inversions (the optimal sorting path) is often not unique as many such optimal sorting paths exist. If we assume that all optimal sorting paths are equally likely, then statistical inference on genome arrangement history must account for all such sorting paths and not just a single estimate. No deterministic polynomial algorithm is known to count the number of optimal sorting paths nor sample from the uniform distribution of optimal sorting paths. Here, we propose a stochastic method that uniformly samples the set of all optimal sorting paths. Our method uses a novel formulation of parallel Markov chain Monte Carlo. In practice, our method can quickly estimate the total number of optimal sorting paths. We introduce a variant of our approach in which short inversions are modeled to be more likely, and we show how the method can be used to estimate the distribution of inversion lengths and breakpoint usage in pathogenic Yersinia pestis. The proposed method has been implemented in a program called "MC4Inversion." We draw comparison of MC4Inversion to the sampler implemented in BADGER and a previously described importance sampling (IS) technique. We find that on high-divergence data sets, MC4Inversion finds more optimal sorting paths per second than BADGER and the IS technique and simultaneously avoids bias inherent in the IS technique.

Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Birge, Brian

2013-01-01

The design priority for manned space exploration missions is almost always placed on human safety. Proposed manned surface exploration tasks (lunar, asteroid sample returns, Mars) have the possibility of astronauts traveling several kilometers away from a home base. Deviations from preplanned paths are expected while exploring. In a time-critical emergency situation, there is a need to develop an optimal home base return path. The return path may or may not be similar to the outbound path, and what defines optimal may change with, and even within, each mission. A novel path planning algorithm and prototype program was developed using biologically inspired particle swarm optimization (PSO) that generates an optimal path of traversal while avoiding obstacles. Applications include emergency path planning on lunar, Martian, and/or asteroid surfaces, generating multiple scenarios for outbound missions, Earth-based search and rescue, as well as human manual traversal and/or path integration into robotic control systems. The strategy allows for a changing environment, and can be re-tasked at will and run in real-time situations. Given a random extraterrestrial planetary or small body surface position, the goal was to find the fastest (or shortest) path to an arbitrary position such as a safe zone or geographic objective, subject to possibly varying constraints. The problem requires a workable solution 100% of the time, though it does not require the absolute theoretical optimum. Obstacles should be avoided, but if they cannot be, then the algorithm needs to be smart enough to recognize this and deal with it. With some modifications, it works with non-stationary error topologies as well.

Development of a prototype multi-processing interactive software invocation system

NASA Technical Reports Server (NTRS)

Berman, W. J.

1983-01-01

The Interactive Software Invocation System (NASA-ISIS) was first transported to the M68000 microcomputer, and then rewritten in the programming language Path Pascal. Path Pascal is a significantly enhanced derivative of Pascal, allowing concurrent algorithms to be expressed using the simple and elegant concept of Path Expressions. The primary results of this contract was to verify the viability of Path Pascal as a system's development language. The NASA-ISIS implementation using Path Pascal is a prototype of a large, interactive system in Path Pascal. As such, it is an excellent demonstration of the feasibility of using Path Pascal to write even more extensive systems. It is hoped that future efforts will build upon this research and, ultimately, that a full Path Pascal/ISIS Operating System (PPIOS) might be developed.

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

PubMed

Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando

2017-08-15

This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.

Sampling-Based Coverage Path Planning for Complex 3D Structures

DTIC Science & Technology

2012-09-01

one such task, in which a single robot must sweep its end effector over the entirety of a known workspace. For two-dimensional environments, optimal...structures. First, we introduce a new algorithm for planning feasible coverage paths. It is more computationally efficient in problems of complex geometry...iteratively shortens and smooths a feasible coverage path; robot configurations are adjusted without violating any coverage con- straints. Third, we propose

minepath.org: a free interactive pathway analysis web server.

PubMed

Koumakis, Lefteris; Roussos, Panos; Potamias, George

2017-07-03

( www.minepath.org ) is a web-based platform that elaborates on, and radically extends the identification of differentially expressed sub-paths in molecular pathways. Besides the network topology, the underlying MinePath algorithmic processes exploit exact gene-gene molecular relationships (e.g. activation, inhibition) and are able to identify differentially expressed pathway parts. Each pathway is decomposed into all its constituent sub-paths, which in turn are matched with corresponding gene expression profiles. The highly ranked, and phenotype inclined sub-paths are kept. Apart from the pathway analysis algorithm, the fundamental innovation of the MinePath web-server concerns its advanced visualization and interactive capabilities. To our knowledge, this is the first pathway analysis server that introduces and offers visualization of the underlying and active pathway regulatory mechanisms instead of genes. Other features include live interaction, immediate visualization of functional sub-paths per phenotype and dynamic linked annotations for the engaged genes and molecular relations. The user can download not only the results but also the corresponding web viewer framework of the performed analysis. This feature provides the flexibility to immediately publish results without publishing source/expression data, and get all the functionality of a web based pathway analysis viewer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

An improved approach for the segmentation of starch granules in microscopic images

PubMed Central

2010-01-01

Background Starches are the main storage polysaccharides in plants and are distributed widely throughout plants including seeds, roots, tubers, leaves, stems and so on. Currently, microscopic observation is one of the most important ways to investigate and analyze the structure of starches. The position, shape, and size of the starch granules are the main measurements for quantitative analysis. In order to obtain these measurements, segmentation of starch granules from the background is very important. However, automatic segmentation of starch granules is still a challenging task because of the limitation of imaging condition and the complex scenarios of overlapping granules. Results We propose a novel method to segment starch granules in microscopic images. In the proposed method, we first separate starch granules from background using automatic thresholding and then roughly segment the image using watershed algorithm. In order to reduce the oversegmentation in watershed algorithm, we use the roundness of each segment, and analyze the gradient vector field to find the critical points so as to identify oversegments. After oversegments are found, we extract the features, such as the position and intensity of the oversegments, and use fuzzy c-means clustering to merge the oversegments to the objects with similar features. Experimental results demonstrate that the proposed method can alleviate oversegmentation of watershed segmentation algorithm successfully. Conclusions We present a new scheme for starch granules segmentation. The proposed scheme aims to alleviate the oversegmentation in watershed algorithm. We use the shape information and critical points of gradient vector flow (GVF) of starch granules to identify oversegments, and use fuzzy c-mean clustering based on prior knowledge to merge these oversegments to the objects. Experimental results on twenty microscopic starch images demonstrate the effectiveness of the proposed scheme. PMID:21047380

Manual flying of curved precision approaches to landing with electromechanical instrumentation. A piloted simulation study

NASA Technical Reports Server (NTRS)

Knox, Charles E.

1993-01-01

A piloted simulation study was conducted to examine the requirements for using electromechanical flight instrumentation to provide situation information and flight guidance for manually controlled flight along curved precision approach paths to a landing. Six pilots were used as test subjects. The data from these tests indicated that flight director guidance is required for the manually controlled flight of a jet transport airplane on curved approach paths. Acceptable path tracking performance was attained with each of the three situation information algorithms tested. Approach paths with both multiple sequential turns and short final path segments were evaluated. Pilot comments indicated that all the approach paths tested could be used in normal airline operations.

Kinematics, controls, and path planning results for a redundant manipulator

NASA Technical Reports Server (NTRS)

Gretz, Bruce; Tilley, Scott W.

1989-01-01

The inverse kinematics solution, a modal position control algorithm, and path planning results for a 7 degree of freedom manipulator are presented. The redundant arm consists of two links with shoulder and elbow joints and a spherical wrist. The inverse kinematics problem for tip position is solved and the redundant joint is identified. It is also shown that a locus of tip positions exists in which there are kinematic limitations on self-motion. A computationally simple modal position control algorithm has been developed which guarantees a nearly constant closed-loop dynamic response throughout the workspace. If all closed-loop poles are assigned to the same location, the algorithm can be implemented with very little computation. To further reduce the required computation, the modal gains are updated only at discrete time intervals. Criteria are developed for the frequency of these updates. For commanding manipulator movements, a 5th-order spline which minimizes jerk provides a smooth tip-space path. Schemes for deriving a corresponding joint-space trajectory are discussed. Modifying the trajectory to avoid joint torque saturation when a tip payload is added is also considered. Simulation results are presented.

Optimization of IBF parameters based on adaptive tool-path algorithm

NASA Astrophysics Data System (ADS)

Deng, Wen Hui; Chen, Xian Hua; Jin, Hui Liang; Zhong, Bo; Hou, Jin; Li, An Qi

2018-03-01

As a kind of Computer Controlled Optical Surfacing(CCOS) technology. Ion Beam Figuring(IBF) has obvious advantages in the control of surface accuracy, surface roughness and subsurface damage. The superiority and characteristics of IBF in optical component processing are analyzed from the point of view of removal mechanism. For getting more effective and automatic tool path with the information of dwell time, a novel algorithm is proposed in this thesis. Based on the removal functions made through our IBF equipment and the adaptive tool-path, optimized parameters are obtained through analysis the residual error that would be created in the polishing process. A Φ600 mm plane reflector element was used to be a simulation instance. The simulation result shows that after four combinations of processing, the surface accuracy of PV (Peak Valley) value and the RMS (Root Mean Square) value was reduced to 4.81 nm and 0.495 nm from 110.22 nm and 13.998 nm respectively in the 98% aperture. The result shows that the algorithm and optimized parameters provide a good theoretical for high precision processing of IBF.

A Linear Kernel for Co-Path/Cycle Packing

NASA Astrophysics Data System (ADS)

Chen, Zhi-Zhong; Fellows, Michael; Fu, Bin; Jiang, Haitao; Liu, Yang; Wang, Lusheng; Zhu, Binhai

Bounded-Degree Vertex Deletion is a fundamental problem in graph theory that has new applications in computational biology. In this paper, we address a special case of Bounded-Degree Vertex Deletion, the Co-Path/Cycle Packing problem, which asks to delete as few vertices as possible such that the graph of the remaining (residual) vertices is composed of disjoint paths and simple cycles. The problem falls into the well-known class of 'node-deletion problems with hereditary properties', is hence NP-complete and unlikely to admit a polynomial time approximation algorithm with approximation factor smaller than 2. In the framework of parameterized complexity, we present a kernelization algorithm that produces a kernel with at most 37k vertices, improving on the super-linear kernel of Fellows et al.'s general theorem for Bounded-Degree Vertex Deletion. Using this kernel,and the method of bounded search trees, we devise an FPT algorithm that runs in time O *(3.24 k ). On the negative side, we show that the problem is APX-hard and unlikely to have a kernel smaller than 2k by a reduction from Vertex Cover.

Fast marching methods for the continuous traveling salesman problem

PubMed Central

Andrews, June; Sethian, J. A.

2007-01-01

We consider a problem in which we are given a domain, a cost function which depends on position at each point in the domain, and a subset of points (“cities”) in the domain. The goal is to determine the cheapest closed path that visits each city in the domain once. This can be thought of as a version of the traveling salesman problem, in which an underlying known metric determines the cost of moving through each point of the domain, but in which the actual shortest path between cities is unknown at the outset. We describe algorithms for both a heuristic and an optimal solution to this problem. The complexity of the heuristic algorithm is at worst case M·N log N, where M is the number of cities, and N the size of the computational mesh used to approximate the solutions to the shortest paths problems. The average runtime of the heuristic algorithm is linear in the number of cities and O(N log N) in the size N of the mesh. PMID:17220271

Fast marching methods for the continuous traveling salesman problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, J.; Sethian, J.A.

We consider a problem in which we are given a domain, a cost function which depends on position at each point in the domain, and a subset of points ('cities') in the domain. The goal is to determine the cheapest closed path that visits each city in the domain once. This can be thought of as a version of the Traveling Salesman Problem, in which an underlying known metric determines the cost of moving through each point of the domain, but in which the actual shortest path between cities is unknown at the outset. We describe algorithms for both amore » heuristic and an optimal solution to this problem. The order of the heuristic algorithm is at worst case M * N logN, where M is the number of cities, and N the size of the computational mesh used to approximate the solutions to the shortest paths problems. The average runtime of the heuristic algorithm is linear in the number of cities and O(N log N) in the size N of the mesh.« less

Shortest multiple disconnected path for the analysis of entanglements in two- and three-dimensional polymeric systems

NASA Astrophysics Data System (ADS)

Kröger, Martin

2005-06-01

We present an algorithm which returns a shortest path and related number of entanglements for a given configuration of a polymeric system in 2 or 3 dimensions. Rubinstein and Helfand, and later Everaers et al. introduced a concept to extract primitive paths for dense polymeric melts made of linear chains (a multiple disconnected multibead 'path'), where each primitive path is defined as a path connecting the (space-fixed) ends of a polymer under the constraint of non-interpenetration (excluded volume) between primitive paths of different chains, such that the multiple disconnected path fulfills a minimization criterion. The present algorithm uses geometrical operations and provides a—model independent—efficient approximate solution to this challenging problem. Primitive paths are treated as 'infinitely' thin (we further allow for finite thickness to model excluded volume), and tensionless lines rather than multibead chains, excluded volume is taken into account without a force law. The present implementation allows to construct a shortest multiple disconnected path (SP) for 2D systems (polymeric chain within spherical obstacles) and an optimal SP for 3D systems (collection of polymeric chains). The number of entanglements is then simply obtained from the SP as either the number of interior kinks, or from the average length of a line segment. Further, information about structure and potentially also the dynamics of entanglements is immediately available from the SP. We apply the method to study the 'concentration' dependence of the degree of entanglement in phantom chain systems. Program summaryTitle of program:Z Catalogue number:ADVG Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVG Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Silicon Graphics (Irix), Sun (Solaris), PC (Linux) Operating systems or monitors under which the program has been tested: UNIX, Linux Program language used: USANSI Fortran 77 and Fortran 90 Memory required to execute with typical data: 1 MByte No. of lines in distributed program, including test data, etc.: 10 660 No. of bytes in distributed program, including test data, etc.: 119 551 Distribution formet:tar.gz Nature of physical problem: The problem is to obtain primitive paths substantiating a shortest multiple disconnected path (SP) for a given polymer configuration (chains of particles, with or without additional single particles as obstacles for the 2D case). Primitive paths are here defined as in [M. Rubinstein, E. Helfand, J. Chem. Phys. 82 (1985) 2477; R. Everaers, S.K. Sukumaran, G.S. Grest, C. Svaneborg, A. Sivasubramanian, K. Kremer, Science 303 (2004) 823] as the shortest line (path) respecting 'topological' constraints (from neighboring polymers or point obstacles) between ends of polymers. There is a unique solution for the 2D case. For the 3D case it is unique if we construct a primitive path of a single chain embedded within fixed line obstacles [J.S.B. Mitchell, Geometric shortest paths and network optimization, in: J.-R. Sack, J. Urrutia (Eds.), Handbook of Computational Geometry, Elsevier, Amsterdam, 2000, pp. 633-701]. For a large 3D configuration made of several chains, short is meant to be the Euclidean shortest multiple disconnected path (SP) where primitive paths are constructed for all chains simultaneously. While the latter problem, in general, does not possess a unique solution, the algorithm must return a locally optimal solution, robust against minor displacements of the disconnected path and chain re-labeling. The problem is solved if the number of kinks (or entanglements Z), explicitly deduced from the SP, is quite insensitive to the exact conformation of the SP which allows to estimate Z with a small error. Efficient method of solution: Primitive paths are constructed from the given polymer configuration (a non-shortest multiple disconnected path, including obstacles, if present) by first replacing each polymer contour by a line with a number of 'kinks' (beads, nodes) and 'segments' (edges). To obtain primitive paths, defined to be uncrossable by any other objects (neighboring primitive paths, line or point obstacles), the algorithm minimizes the length of all primitive paths consecutively, until a final minimum Euclidean length of the SP is reached. Fast geometric operations rather than dynamical methods are used to minimize the contour lengths of the primitive paths. Neighbor lists are used to keep track of potentially intersecting segments of other chains. Periodic boundary conditions are employed. A finite small line thickness is used in order to make sure that entanglements are not 'lost' due to finite precision of representation of numbers. Restrictions on the complexity of the problem: For a single chain embedded within fixed line or point obstacles, the algorithm returns the exact SP. For more complex problems, the algorithm returns a locally optimal SP. Except for exotic, probably rare, configurations it turns out that different locally optimal SPs possess quite an identical number of nodes. In general, the problem constructing the SP is known to be NP-hard [J.S.B. Mitchell, Geometric shortest paths and network optimization, in: J.-R. Sack, J. Urrutia (Eds.), Handbook of Computational Geometry, Elsevier, Amsterdam, 2000, pp. 633-701], and we offer a solution which should suffice to analyze physical problems, and gives an estimate about the precision and uniqueness of the result (from a standard deviation by varying the parameter: cyclicswitch). The program is NOT restricted to handle systems for which segment lengths of the SP exceed half the box size. Typical running time: Typical running times are approximately two orders of magnitude shorter compared with the ones needed for a corresponding molecular dynamics approach, and scale mostly linearly with system size. We provide a benchmark table.

Online POMDP Algorithms for Very Large Observation Spaces

DTIC Science & Technology

2017-06-06

stochastic optimization: From sets to paths." In Advances in Neural Information Processing Systems, pp. 1585- 1593 . 2015. • Luo, Yuanfu, Haoyu Bai...and Wee Sun Lee. "Adaptive stochastic optimization: From sets to paths." In Advances in Neural Information Processing Systems, pp. 1585- 1593 . 2015

Distributed Method to Optimal Profile Descent

NASA Astrophysics Data System (ADS)

Kim, Geun I.

Current ground automation tools for Optimal Profile Descent (OPD) procedures utilize path stretching and speed profile change to maintain proper merging and spacing requirements at high traffic terminal area. However, low predictability of aircraft's vertical profile and path deviation during decent add uncertainty to computing estimated time of arrival, a key information that enables the ground control center to manage airspace traffic effectively. This paper uses an OPD procedure that is based on a constant flight path angle to increase the predictability of the vertical profile and defines an OPD optimization problem that uses both path stretching and speed profile change while largely maintaining the original OPD procedure. This problem minimizes the cumulative cost of performing OPD procedures for a group of aircraft by assigning a time cost function to each aircraft and a separation cost function to a pair of aircraft. The OPD optimization problem is then solved in a decentralized manner using dual decomposition techniques under inter-aircraft ADS-B mechanism. This method divides the optimization problem into more manageable sub-problems which are then distributed to the group of aircraft. Each aircraft solves its assigned sub-problem and communicate the solutions to other aircraft in an iterative process until an optimal solution is achieved thus decentralizing the computation of the optimization problem.

Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and other Meteorological Measurements

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Larry; Cecil, Dan; Bateman, Monte; Stano, Geoffrey; Goodman, Steve

2012-01-01

Objective of project is to refine, adapt and demonstrate the Lightning Jump Algorithm (LJA) for transition to GOES -R GLM (Geostationary Lightning Mapper) readiness and to establish a path to operations Ongoing work . reducing risk in GLM lightning proxy, cell tracking, LJA algorithm automation, and data fusion (e.g., radar + lightning).

Design Genetic Algorithm Optimization Education Software Based Fuzzy Controller for a Tricopter Fly Path Planning

ERIC Educational Resources Information Center

Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao

2016-01-01

In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…

Validating the accuracy of SO2 gas retrievals in the thermal infrared (8-14 μm)

NASA Astrophysics Data System (ADS)

Gabrieli, Andrea; Porter, John N.; Wright, Robert; Lucey, Paul G.

2017-11-01

Quantifying sulfur dioxide (SO2) in volcanic plumes is important for eruption predictions and public health. Ground-based remote sensing of spectral radiance of plumes contains information on the path-concentration of SO2. However, reliable inversion algorithms are needed to convert plume spectral radiance measurements into SO2 path-concentrations. Various techniques have been used for this purpose. Recent approaches have employed thermal infrared (TIR) imaging between 8 μm and 14 μm to provide two-dimensional mapping of plume SO2 path-concentration, using what might be described as "dual-view" techniques. In this case, the radiance (or its surrogate brightness temperature) is computed for portions of the image that correspond to the plume and compared with spectral radiance obtained for adjacent regions of the image that do not (i.e., "clear sky"). In this way, the contribution that the plume makes to the measured radiance can be isolated from the background atmospheric contribution, this residual signal being converted to an estimate of gas path-concentration via radiative transfer modeling. These dual-view approaches suffer from several issues, mainly the assumption of clear sky background conditions. At this time, the various inversion algorithms remain poorly validated. This paper makes two contributions. Firstly, it validates the aforementioned dual-view approaches, using hyperspectral TIR imaging data. Secondly, it introduces a new method to derive SO2 path-concentrations, which allows for single point SO2 path-concentration retrievals, suitable for hyperspectral imaging with clear or cloudy background conditions. The SO2 amenable lookup table algorithm (SO2-ALTA) uses the MODTRAN5 radiative transfer model to compute radiance for a variety (millions) of plume and atmospheric conditions. Rather than searching this lookup table to find the best fit for each measured spectrum, the lookup table was used to train a partial least square regression (PLSR) model. The coefficients of this model are used to invert measured radiance spectra to path-concentration on a pixel-by-pixel basis. In order to validate the algorithms, TIR hyperspectral measurements were carried out by measuring sky radiance when looking through gas cells filled with known amounts of SO2. SO2-ALTA was also tested on retrieving SO2 path-concentrations from the Kīlauea volcano, Hawai'i. For cloud-free conditions, all three techniques worked well. In cases where background clouds were present, then only SO2-ALTA was found to provide good results, but only under low atmospheric water vapor column amounts.

A hybrid algorithm for clustering of time series data based on affinity search technique.

PubMed

Aghabozorgi, Saeed; Ying Wah, Teh; Herawan, Tutut; Jalab, Hamid A; Shaygan, Mohammad Amin; Jalali, Alireza

2014-01-01

Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impracticality results in poor clustering accuracy in several systems. In this paper, a new hybrid clustering algorithm is proposed based on the similarity in shape of time series data. Time series data are first grouped as subclusters based on similarity in time. The subclusters are then merged using the k-Medoids algorithm based on similarity in shape. This model has two contributions: (1) it is more accurate than other conventional and hybrid approaches and (2) it determines the similarity in shape among time series data with a low complexity. To evaluate the accuracy of the proposed model, the model is tested extensively using syntactic and real-world time series datasets.

Probabilistic cosmological mass mapping from weak lensing shear

DOE PAGES

Schneider, M. D.; Ng, K. Y.; Dawson, W. A.; ...

2017-04-10

Here, we infer gravitational lensing shear and convergence fields from galaxy ellipticity catalogs under a spatial process prior for the lensing potential. We demonstrate the performance of our algorithm with simulated Gaussian-distributed cosmological lensing shear maps and a reconstruction of the mass distribution of the merging galaxy cluster Abell 781 using galaxy ellipticities measured with the Deep Lens Survey. Given interim posterior samples of lensing shear or convergence fields on the sky, we describe an algorithm to infer cosmological parameters via lens field marginalization. In the most general formulation of our algorithm we make no assumptions about weak shear ormore » Gaussian-distributed shape noise or shears. Because we require solutions and matrix determinants of a linear system of dimension that scales with the number of galaxies, we expect our algorithm to require parallel high-performance computing resources for application to ongoing wide field lensing surveys.« less

Probabilistic Cosmological Mass Mapping from Weak Lensing Shear

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schneider, M. D.; Dawson, W. A.; Ng, K. Y.

2017-04-10

We infer gravitational lensing shear and convergence fields from galaxy ellipticity catalogs under a spatial process prior for the lensing potential. We demonstrate the performance of our algorithm with simulated Gaussian-distributed cosmological lensing shear maps and a reconstruction of the mass distribution of the merging galaxy cluster Abell 781 using galaxy ellipticities measured with the Deep Lens Survey. Given interim posterior samples of lensing shear or convergence fields on the sky, we describe an algorithm to infer cosmological parameters via lens field marginalization. In the most general formulation of our algorithm we make no assumptions about weak shear or Gaussian-distributedmore » shape noise or shears. Because we require solutions and matrix determinants of a linear system of dimension that scales with the number of galaxies, we expect our algorithm to require parallel high-performance computing resources for application to ongoing wide field lensing surveys.« less

A Hybrid Algorithm for Clustering of Time Series Data Based on Affinity Search Technique

PubMed Central

Aghabozorgi, Saeed; Ying Wah, Teh; Herawan, Tutut; Jalab, Hamid A.; Shaygan, Mohammad Amin; Jalali, Alireza

2014-01-01

Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impracticality results in poor clustering accuracy in several systems. In this paper, a new hybrid clustering algorithm is proposed based on the similarity in shape of time series data. Time series data are first grouped as subclusters based on similarity in time. The subclusters are then merged using the k-Medoids algorithm based on similarity in shape. This model has two contributions: (1) it is more accurate than other conventional and hybrid approaches and (2) it determines the similarity in shape among time series data with a low complexity. To evaluate the accuracy of the proposed model, the model is tested extensively using syntactic and real-world time series datasets. PMID:24982966

Biplane reconstruction and visualization of virtual endoscopic and fluoroscopic views for interventional device navigation

NASA Astrophysics Data System (ADS)

Wagner, Martin G.; Strother, Charles M.; Schafer, Sebastian; Mistretta, Charles A.

2016-03-01

Biplane fluoroscopic imaging is an important tool for minimally invasive procedures for the treatment of cerebrovascular diseases. However, finding a good working angle for the C-arms of the angiography system as well as navigating based on the 2D projection images can be a difficult task. The purpose of this work is to propose a novel 4D reconstruction algorithm for interventional devices from biplane fluoroscopy images and to propose new techniques for a better visualization of the results. The proposed reconstruction methods binarizes the fluoroscopic images using a dedicated noise reduction algorithm for curvilinear structures and a global thresholding approach. A topology preserving thinning algorithm is then applied and a path search algorithm minimizing the curvature of the device is used to extract the 2D device centerlines. Finally, the 3D device path is reconstructed using epipolar geometry. The point correspondences are determined by a monotonic mapping function that minimizes the reconstruction error. The three dimensional reconstruction of the device path allows the rendering of virtual fluoroscopy images from arbitrary angles as well as 3D visualizations like virtual endoscopic views or glass pipe renderings, where the vessel wall is rendered with a semi-transparent material. This work also proposes a combination of different visualization techniques in order to increase the usability and spatial orientation for the user. A combination of synchronized endoscopic and glass pipe views is proposed, where the virtual endoscopic camera position is determined based on the device tip location as well as the previous camera position using a Kalman filter in order to create a smooth path. Additionally, vessel centerlines are displayed and the path to the target is highlighted. Finally, the virtual endoscopic camera position is also visualized in the glass pipe view to further improve the spatial orientation. The proposed techniques could considerably improve the workflow of minimally invasive procedures for the treatment of cerebrovascular diseases.

A 48Cycles/MB H.264/AVC Deblocking Filter Architecture for Ultra High Definition Applications

NASA Astrophysics Data System (ADS)

Zhou, Dajiang; Zhou, Jinjia; Zhu, Jiayi; Goto, Satoshi

In this paper, a highly parallel deblocking filter architecture for H.264/AVC is proposed to process one macroblock in 48 clock cycles and give real-time support to QFHD@60fps sequences at less than 100MHz. 4 edge filters organized in 2 groups for simultaneously processing vertical and horizontal edges are applied in this architecture to enhance its throughput. While parallelism increases, pipeline hazards arise owing to the latency of edge filters and data dependency of deblocking algorithm. To solve this problem, a zig-zag processing schedule is proposed to eliminate the pipeline bubbles. Data path of the architecture is then derived according to the processing schedule and optimized through data flow merging, so as to minimize the cost of logic and internal buffer. Meanwhile, the architecture's data input rate is designed to be identical to its throughput, while the transmission order of input data can also match the zig-zag processing schedule. Therefore no intercommunication buffer is required between the deblocking filter and its previous component for speed matching or data reordering. As a result, only one 24×64 two-port SRAM as internal buffer is required in this design. When synthesized with SMIC 130nm process, the architecture costs a gate count of 30.2k, which is competitive considering its high performance.

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

NASA Technical Reports Server (NTRS)

Tilton, James C.

2003-01-01

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

A one-way shooting algorithm for transition path sampling of asymmetric barriers

NASA Astrophysics Data System (ADS)

Brotzakis, Z. Faidon; Bolhuis, Peter G.

2016-10-01

We present a novel transition path sampling shooting algorithm for the efficient sampling of complex (biomolecular) activated processes with asymmetric free energy barriers. The method employs a fictitious potential that biases the shooting point toward the transition state. The method is similar in spirit to the aimless shooting technique by Peters and Trout [J. Chem. Phys. 125, 054108 (2006)], but is targeted for use with the one-way shooting approach, which has been shown to be more effective than two-way shooting algorithms in systems dominated by diffusive dynamics. We illustrate the method on a 2D Langevin toy model, the association of two peptides and the initial step in dissociation of a β-lactoglobulin dimer. In all cases we show a significant increase in efficiency.

MWRRET Value-Added Product: The Retrieval of Liquid Water Path and Precipitable Water Vapor from Microwave Radiometer (MWR) Datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

KL Gaustad; DD Turner

2007-09-30

This report provides a short description of the Atmospheric Radiation Measurement (ARM) microwave radiometer (MWR) RETrievel (MWRRET) Value-Added Product (VAP) algorithm. This algorithm utilizes complimentary physical and statistical retrieval methods and applies brightness temperature offsets to reduce spurious liquid water path (LWP) bias in clear skies resulting in significantly improved precipitable water vapor (PWV) and LWP retrievals. We present a general overview of the technique, input parameters, output products, and describe data quality checks. A more complete discussion of the theory and results is given in Turner et al. (2007b).

Concurrent computation of attribute filters on shared memory parallel machines.

PubMed

Wilkinson, Michael H F; Gao, Hui; Hesselink, Wim H; Jonker, Jan-Eppo; Meijster, Arnold

2008-10-01

Morphological attribute filters have not previously been parallelized, mainly because they are both global and non-separable. We propose a parallel algorithm that achieves efficient parallelism for a large class of attribute filters, including attribute openings, closings, thinnings and thickenings, based on Salembier's Max-Trees and Min-trees. The image or volume is first partitioned in multiple slices. We then compute the Max-trees of each slice using any sequential Max-Tree algorithm. Subsequently, the Max-trees of the slices can be merged to obtain the Max-tree of the image. A C-implementation yielded good speed-ups on both a 16-processor MIPS 14000 parallel machine, and a dual-core Opteron-based machine. It is shown that the speed-up of the parallel algorithm is a direct measure of the gain with respect to the sequential algorithm used. Furthermore, the concurrent algorithm shows a speed gain of up to 72 percent on a single-core processor, due to reduced cache thrashing.

Physarum can compute shortest paths.

PubMed

Bonifaci, Vincenzo; Mehlhorn, Kurt; Varma, Girish

2012-09-21

Physarum polycephalum is a slime mold that is apparently able to solve shortest path problems. A mathematical model has been proposed by Tero et al. (Journal of Theoretical Biology, 244, 2007, pp. 553-564) to describe the feedback mechanism used by the slime mold to adapt its tubular channels while foraging two food sources s(0) and s(1). We prove that, under this model, the mass of the mold will eventually converge to the shortest s(0)-s(1) path of the network that the mold lies on, independently of the structure of the network or of the initial mass distribution. This matches the experimental observations by Tero et al. and can be seen as an example of a "natural algorithm", that is, an algorithm developed by evolution over millions of years. Copyright © 2012 Elsevier Ltd. All rights reserved.

Information spread of emergency events: path searching on social networks.

PubMed

Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, Zheng, E-mail: 19994035@sina.com; Wang, Jun; Zhou, Bihua

2014-03-15

This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented tomore » tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.« less

Algorithm Estimates Microwave Water-Vapor Delay

NASA Technical Reports Server (NTRS)

Robinson, Steven E.

1989-01-01

Accuracy equals or exceeds conventional linear algorithms. "Profile" algorithm improved algorithm using water-vapor-radiometer data to produce estimates of microwave delays caused by water vapor in troposphere. Does not require site-specific and weather-dependent empirical parameters other than standard meteorological data, latitude, and altitude for use in conjunction with published standard atmospheric data. Basic premise of profile algorithm, wet-path delay approximated closely by solution to simplified version of nonlinear delay problem and generated numerically from each radiometer observation and simultaneous meteorological data.

Diagnostic and Remedial Learning Strategy Based on Conceptual Graphs

ERIC Educational Resources Information Center

Jong, BinShyan; Lin, TsongWuu; Wu, YuLung; Chan, Teyi

2004-01-01

Numerous scholars have applied conceptual graphs for explanatory purposes. This study devised the Remedial-Instruction Decisive path (RID path) algorithm for diagnosing individual student learning situation. This study focuses on conceptual graphs. According to the concepts learned by students and the weight values of relations among these…

Assessing the Performance of Human-Automation Collaborative Planning Systems

DTIC Science & Technology

2011-06-01

process- ing and incorporating vast amounts of incoming information into their solutions. How- ever, these algorithms are brittle and unable to account for...planning system, a descriptive Mission Performance measure may address the total travel time on the path or the cost of the path (e.g. total work...minimizing costs or collisions [4, 32, 33]. Error measures for such a path planning system may track how many collisions occur or how much threat

Two arm robot path planning in a static environment using polytopes and string stretching. Thesis

NASA Technical Reports Server (NTRS)

Schima, Francis J., III

1990-01-01

The two arm robot path planning problem has been analyzed and reduced into components to be simplified. This thesis examines one component in which two Puma-560 robot arms are simultaneously holding a single object. The problem is to find a path between two points around obstacles which is relatively fast and minimizes the distance. The thesis involves creating a structure on which to form an advanced path planning algorithm which could ideally find the optimum path. An actual path planning method is implemented which is simple though effective in most common situations. Given the limits of computer technology, a 'good' path is currently found. Objects in the workspace are modeled with polytopes. These are used because they can be used for rapid collision detection and still provide a representation which is adequate for path planning.

Computing the total atmospheric refraction for real-time optical imaging sensor simulation

NASA Astrophysics Data System (ADS)

Olson, Richard F.

2015-05-01

Fast and accurate computation of light path deviation due to atmospheric refraction is an important requirement for real-time simulation of optical imaging sensor systems. A large body of existing literature covers various methods for application of Snell's Law to the light path ray tracing problem. This paper provides a discussion of the adaptation to real time simulation of atmospheric refraction ray tracing techniques used in mid-1980's LOWTRAN releases. The refraction ray trace algorithm published in a LOWTRAN-6 technical report by Kneizys (et. al.) has been coded in MATLAB for development, and in C-language for simulation use. To this published algorithm we have added tuning parameters for variable path segment lengths, and extensions for Earth grazing and exoatmospheric "near Earth" ray paths. Model atmosphere properties used to exercise the refraction algorithm were obtained from tables published in another LOWTRAN-6 related report. The LOWTRAN-6 based refraction model is applicable to atmospheric propagation at wavelengths in the IR and visible bands of the electromagnetic spectrum. It has been used during the past two years by engineers at the U.S. Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) in support of several advanced imaging sensor simulations. Recently, a faster (but sufficiently accurate) method using Gauss-Chebyshev Quadrature integration for evaluating the refraction integral was adopted.

Lung fissure detection in CT images using global minimal paths

NASA Astrophysics Data System (ADS)

Appia, Vikram; Patil, Uday; Das, Bipul

2010-03-01

Pulmonary fissures separate human lungs into five distinct regions called lobes. Detection of fissure is essential for localization of the lobar distribution of lung diseases, surgical planning and follow-up. Treatment planning also requires calculation of the lobe volume. This volume estimation mandates accurate segmentation of the fissures. Presence of other structures (like vessels) near the fissure, along with its high variational probability in terms of position, shape etc. makes the lobe segmentation a challenging task. Also, false incomplete fissures and occurrence of diseases add to the complications of fissure detection. In this paper, we propose a semi-automated fissure segmentation algorithm using a minimal path approach on CT images. An energy function is defined such that the path integral over the fissure is the global minimum. Based on a few user defined points on a single slice of the CT image, the proposed algorithm minimizes a 2D energy function on the sagital slice computed using (a) intensity (b) distance of the vasculature, (c) curvature in 2D, (d) continuity in 3D. The fissure is the infimum energy path between a representative point on the fissure and nearest lung boundary point in this energy domain. The algorithm has been tested on 10 CT volume datasets acquired from GE scanners at multiple clinical sites. The datasets span through different pathological conditions and varying imaging artifacts.

Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Krozel, James A.

1988-01-01

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

DOE PAGES

Chatzidakis, Stylianos; Liu, Zhengzhi; Hayward, Jason P.; ...

2018-03-28

Here, this work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstructionmore » algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS are explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm’s precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm RMS for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. Finally, the effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.« less

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatzidakis, Stylianos; Liu, Zhengzhi; Hayward, Jason P.

Here, this work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstructionmore » algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS are explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm’s precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm RMS for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. Finally, the effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.« less

Planning Under Uncertainty: Methods and Applications

DTIC Science & Technology

2010-06-09

begun research into fundamental algorithms for optimization and re?optimization of continuous optimization problems (such as linear and quadratic... algorithm yields a 14.3% improvement over the original design while saving 68.2 % of the simulation evaluations compared to standard sample-path...They provide tools for building and justifying computational algorithms for such problems. Year. 2010 Month: 03 Final Research under this grant

Multiuser TOA Estimation Algorithm in DS-CDMA Sparse Channel for Radiolocation

NASA Astrophysics Data System (ADS)

Kim, Sunwoo

This letter considers multiuser time delay estimation in a sparse channel environment for radiolocation. The generalized successive interference cancellation (GSIC) algorithm is used to eliminate the multiple access interference (MAI). To adapt GSIC to sparse channels the alternating maximization (AM) algorithm is considered, and the continuous time delay of each path is estimated without requiring a priori known data sequences.

Efficient Sampling of Parsimonious Inversion Histories with Application to Genome Rearrangement in Yersinia

PubMed Central

Darling, Aaron E.

2009-01-01

Inversions are among the most common mutations acting on the order and orientation of genes in a genome, and polynomial-time algorithms exist to obtain a minimal length series of inversions that transform one genome arrangement to another. However, the minimum length series of inversions (the optimal sorting path) is often not unique as many such optimal sorting paths exist. If we assume that all optimal sorting paths are equally likely, then statistical inference on genome arrangement history must account for all such sorting paths and not just a single estimate. No deterministic polynomial algorithm is known to count the number of optimal sorting paths nor sample from the uniform distribution of optimal sorting paths. Here, we propose a stochastic method that uniformly samples the set of all optimal sorting paths. Our method uses a novel formulation of parallel Markov chain Monte Carlo. In practice, our method can quickly estimate the total number of optimal sorting paths. We introduce a variant of our approach in which short inversions are modeled to be more likely, and we show how the method can be used to estimate the distribution of inversion lengths and breakpoint usage in pathogenic Yersinia pestis. The proposed method has been implemented in a program called “MC4Inversion.” We draw comparison of MC4Inversion to the sampler implemented in BADGER and a previously described importance sampling (IS) technique. We find that on high-divergence data sets, MC4Inversion finds more optimal sorting paths per second than BADGER and the IS technique and simultaneously avoids bias inherent in the IS technique. PMID:20333186

A General, Adaptive, Roadmap-Based Algorithm for Protein Motion Computation.

PubMed

Molloy, Kevin; Shehu, Amarda

2016-03-01

Precious information on protein function can be extracted from a detailed characterization of protein equilibrium dynamics. This remains elusive in wet and dry laboratories, as function-modulating transitions of a protein between functionally-relevant, thermodynamically-stable and meta-stable structural states often span disparate time scales. In this paper we propose a novel, robotics-inspired algorithm that circumvents time-scale challenges by drawing analogies between protein motion and robot motion. The algorithm adapts the popular roadmap-based framework in robot motion computation to handle the more complex protein conformation space and its underlying rugged energy surface. Given known structures representing stable and meta-stable states of a protein, the algorithm yields a time- and energy-prioritized list of transition paths between the structures, with each path represented as a series of conformations. The algorithm balances computational resources between a global search aimed at obtaining a global view of the network of protein conformations and their connectivity and a detailed local search focused on realizing such connections with physically-realistic models. Promising results are presented on a variety of proteins that demonstrate the general utility of the algorithm and its capability to improve the state of the art without employing system-specific insight.

A distributed algorithm to maintain and repair the trail networks of arboreal ants.

PubMed

Chandrasekhar, Arjun; Gordon, Deborah M; Navlakha, Saket

2018-06-18

We study how the arboreal turtle ant (Cephalotes goniodontus) solves a fundamental computing problem: maintaining a trail network and finding alternative paths to route around broken links in the network. Turtle ants form a routing backbone of foraging trails linking several nests and temporary food sources. This species travels only in the trees, so their foraging trails are constrained to lie on a natural graph formed by overlapping branches and vines in the tangled canopy. Links between branches, however, can be ephemeral, easily destroyed by wind, rain, or animal movements. Here we report a biologically feasible distributed algorithm, parameterized using field data, that can plausibly describe how turtle ants maintain the routing backbone and find alternative paths to circumvent broken links in the backbone. We validate the ability of this probabilistic algorithm to circumvent simulated breaks in synthetic and real-world networks, and we derive an analytic explanation for why certain features are crucial to improve the algorithm's success. Our proposed algorithm uses fewer computational resources than common distributed graph search algorithms, and thus may be useful in other domains, such as for swarm computing or for coordinating molecular robots.

A Space-Time Signal Decomposition Algorithm for Downlink MIMO DS-CDMA Receivers

NASA Astrophysics Data System (ADS)

Wang, Yung-Yi; Fang, Wen-Hsien; Chen, Jiunn-Tsair

We propose a dimension reduction algorithm for the receiver of the downlink of direct-sequence code-division multiple access (DS-CDMA) systems in which both the transmitters and the receivers employ antenna arrays of multiple elements. To estimate the high order channel parameters, we develop a layered architecture using dimension-reduced parameter estimation algorithms to estimate the frequency-selective multipath channels. In the proposed architecture, to exploit the space-time geometric characteristics of multipath channels, spatial beamformers and constrained (or unconstrained) temporal filters are adopted for clustered-multipath grouping and path isolation. In conjunction with the multiple access interference (MAI) suppression techniques, the proposed architecture jointly estimates the direction of arrivals, propagation delays, and fading amplitudes of the downlink fading multipaths. With the outputs of the proposed architecture, the signals of interest can then be naturally detected by using path-wise maximum ratio combining. Compared to the traditional techniques, such as the Joint-Angle-and-Delay-Estimation (JADE) algorithm for DOA-delay joint estimation and the space-time minimum mean square error (ST-MMSE) algorithm for signal detection, computer simulations show that the proposed algorithm substantially mitigate the computational complexity at the expense of only slight performance degradation.

Aircraft path planning for optimal imaging using dynamic cost functions

NASA Astrophysics Data System (ADS)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

The metallicity and elemental abundance gradients of simulated galaxies and their environmental dependence

NASA Astrophysics Data System (ADS)

Taylor, Philip; Kobayashi, Chiaki

2017-11-01

The internal distribution of heavy elements, in particular the radial metallicity gradient, offers insight into the merging history of galaxies. Using our cosmological, chemodynamical simulations that include both detailed chemical enrichment and feedback from active galactic nuclei (AGN), we find that stellar metallicity gradients in the most massive galaxies (≳3 × 1010M⊙) are made flatter by mergers and are unable to regenerate due to the quenching of star formation by AGN feedback. The fitting range is chosen on a galaxy-by-galaxy basis in order to mask satellite galaxies. The evolutionary paths of the gradients can be summarized as follows: (I) creation of initial steep gradients by gas-rich assembly, (II) passive evolution by star formation and/or stellar accretion at outskirts, and (III) sudden flattening by mergers. There is a significant scatter in gradients at a given mass, which originates from the last path, and therefore from galaxy type. Some variation remains at given galaxy mass and type because of the complexity of merging events, and hence we find only a weak environmental dependence. Our early-type galaxies (ETGs), defined from the star formation main sequence rather than their morphology, are in excellent agreement with the observed stellar metallicity gradients of ETGs in the SAURON and ATLAS3D surveys. We find small positive [O/Fe] gradients of stars in our simulated galaxies, although they are smaller with AGN feedback. Gas-phase metallicity and [O/Fe] gradients also show variation, the origin of which is not as clear as for stellar populations.

The Chandra Source Catalog: Algorithms

NASA Astrophysics Data System (ADS)

McDowell, Jonathan; Evans, I. N.; Primini, F. A.; Glotfelty, K. J.; McCollough, M. L.; Houck, J. C.; Nowak, M. A.; Karovska, M.; Davis, J. E.; Rots, A. H.; Siemiginowska, A. L.; Hain, R.; Evans, J. D.; Anderson, C. S.; Bonaventura, N. R.; Chen, J. C.; Doe, S. M.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hall, D. M.; Harbo, P. N.; He, X.; Lauer, J.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Plummer, D. A.; Refsdal, B. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

Creation of the Chandra Source Catalog (CSC) required adjustment of existing pipeline processing, adaptation of existing interactive analysis software for automated use, and development of entirely new algorithms. Data calibration was based on the existing pipeline, but more rigorous data cleaning was applied and the latest calibration data products were used. For source detection, a local background map was created including the effects of ACIS source readout streaks. The existing wavelet source detection algorithm was modified and a set of post-processing scripts used to correct the results. To analyse the source properties we ran the SAO Traceray trace code for each source to generate a model point spread function, allowing us to find encircled energy correction factors and estimate source extent. Further algorithms were developed to characterize the spectral, spatial and temporal properties of the sources and to estimate the confidence intervals on count rates and fluxes. Finally, sources detected in multiple observations were matched, and best estimates of their merged properties derived. In this paper we present an overview of the algorithms used, with more detailed treatment of some of the newly developed algorithms presented in companion papers.

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

NASA Technical Reports Server (NTRS)

Manohar, M.; Ramapriyan, H. K.; Strong, J. P.

1988-01-01

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.

PubMed

Jiang, Wen Jun; Wittek, Peter; Zhao, Li; Gao, Shi Chao

2014-01-01

Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. The new feature enables real-time adaptive waveform detection using an algorithm of linear time complexity. It can also recognize notches in the waveform and it is inherently robust to baseline drift. An implementation of the algorithm on Android is available for free download. We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.

An Algorithm for the Retrieval of Droplet Number Concentration and Geometrical Thickness of Stratiform Marine Boundary Layer Clouds Applied to MODIS Radiometric Observations.

NASA Astrophysics Data System (ADS)

Schüller, Lothar; Bennartz, Ralf; Fischer, Jürgen; Brenguier, Jean-Louis

2005-01-01

Algorithms are now currently used for the retrieval of cloud optical thickness and droplet effective radius from multispectral radiance measurements. This paper extends their application to the retrieval of cloud droplet number concentration, cloud geometrical thickness, and liquid water path in shallow convective clouds, using an algorithm that was previously tested with airborne measurements of cloud radiances and validated against in situ measurements of the same clouds. The retrieval is based on a stratified cloud model of liquid water content and droplet spectrum. Radiance measurements in visible and near-infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is operated from the NASA platforms Terra and Aqua, are analyzed. Because of uncertainties in the simulation of the continental surface reflectance, the algorithm is presently limited to the monitoring of the microphysical structure of boundary layer clouds over the ocean. Two MODIS scenes of extended cloud fields over the North Atlantic Ocean trade wind region are processed. A transport and dispersion model (the Hybrid Single-Particle Lagrangian Integrated Trajectory Model, HYSPLIT4) is also used to characterize the origin of the air masses and hence their aerosol regimes. One cloud field formed in an air mass that was advected from southern Europe and North Africa. It shows high values of the droplet concentration when compared with the second cloud system, which developed in a more pristine environment. The more pristine case also exhibits a higher geometrical thickness and, thus, liquid water path, which counterbalances the expected cloud albedo increase of the polluted case. Estimates of cloud liquid water path are then compared with retrievals from the Special Sensor Microwave Imager (SSM/I). SSM/I-derived liquid water paths are in good agreement with the MODIS-derived values.

Tropical Rainfall Analysis Using TRMM in Combination With Other Satellite Gauge Data: Comparison with Global Precipitation Climatology Project (GPCP) Results

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George J.; Bolvin, David; Nelkin, Eric; Curtis, Scott

1999-01-01

This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1 deg x 1 deg latitude/longitude monthly scale based on multiple satellite sources and raingauge analysis. The procedure used to produce the GPCP data set is a stepwise approach which first combines the satellite low-orbit microwave and geosynchronous IR observations into a "multi-satellite" product and than merges that result with the raingauge analysis. Preliminary results produced with the still-stabilizing TRMM algorithms indicate that TRMM shows tighter spatial gradients in tropical rain maxima with higher peaks in the center of the maxima. The TRMM analyses will be used to evaluate the evolution of the 1998 ENSO variations, again in comparison with the GPCP analyses.

Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm

PubMed Central

Chuan, He; Dishan, Qiu; Jin, Liu

2012-01-01

The cooperative scheduling problem on high-altitude airships for imaging observation tasks is discussed. A constraint programming model is established by analyzing the main constraints, which takes the maximum task benefit and the minimum cruising distance as two optimization objectives. The cooperative scheduling problem of high-altitude airships is converted into a main problem and a subproblem by adopting hierarchy architecture. The solution to the main problem can construct the preliminary matching between tasks and observation resource in order to reduce the search space of the original problem. Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA). Then, a novel swarm intelligence algorithm named propagation algorithm (PA) is combined with the key node search algorithm (KNSA) to optimize the cruising path of each airship and determine the execution time interval of each task. Meanwhile, this paper also provides the realization approach of the above algorithm and especially makes a detailed introduction on the encoding rules, search models, and propagation mechanism of the PA. Finally, the application results and comparison analysis show the proposed models and algorithms are effective and feasible. PMID:23365522

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

2007-01-01

Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.

Multi Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

DTIC Science & Technology

2016-10-04

Multi- Robot Path Planning for Budgeted Active Perception with Self-Organising Maps Graeme Best1, Jan Faigl2 and Robert Fitch1 Abstract— We propose a...optimise paths for a multi- robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting...regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes

Regularization Paths for Conditional Logistic Regression: The clogitL1 Package.

PubMed

Reid, Stephen; Tibshirani, Rob

2014-07-01

We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso [Formula: see text] and elastic net penalties. The sequential strong rules of Tibshirani, Bien, Hastie, Friedman, Taylor, Simon, and Tibshirani (2012) are also used in the algorithm and it is shown that these offer a considerable speed up over the standard coordinate descent algorithm with warm starts. Once implemented, the algorithm is used in simulation studies to compare the variable selection and prediction performance of the conditional logistic regression model against that of its unconditional (standard) counterpart. We find that the conditional model performs admirably on datasets drawn from a suitable conditional distribution, outperforming its unconditional counterpart at variable selection. The conditional model is also fit to a small real world dataset, demonstrating how we obtain regularization paths for the parameters of the model and how we apply cross validation for this method where natural unconditional prediction rules are hard to come by.

Regularization Paths for Conditional Logistic Regression: The clogitL1 Package

PubMed Central

Reid, Stephen; Tibshirani, Rob

2014-01-01

We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso (ℓ1) and elastic net penalties. The sequential strong rules of Tibshirani, Bien, Hastie, Friedman, Taylor, Simon, and Tibshirani (2012) are also used in the algorithm and it is shown that these offer a considerable speed up over the standard coordinate descent algorithm with warm starts. Once implemented, the algorithm is used in simulation studies to compare the variable selection and prediction performance of the conditional logistic regression model against that of its unconditional (standard) counterpart. We find that the conditional model performs admirably on datasets drawn from a suitable conditional distribution, outperforming its unconditional counterpart at variable selection. The conditional model is also fit to a small real world dataset, demonstrating how we obtain regularization paths for the parameters of the model and how we apply cross validation for this method where natural unconditional prediction rules are hard to come by. PMID:26257587

Numerical evaluation of mobile robot navigation in static indoor environment via EGAOR Iteration

NASA Astrophysics Data System (ADS)

Dahalan, A. A.; Saudi, A.; Sulaiman, J.; Din, W. R. W.

2017-09-01

One of the key issues in mobile robot navigation is the ability for the robot to move from an arbitrary start location to a specified goal location without colliding with any obstacles while traveling, also known as mobile robot path planning problem. In this paper, however, we examined the performance of a robust searching algorithm that relies on the use of harmonic potentials of the environment to generate smooth and safe path for mobile robot navigation in a static known indoor environment. The harmonic potentials will be discretized by using Laplacian’s operator to form a system of algebraic approximation equations. This algebraic linear system will be computed via 4-Point Explicit Group Accelerated Over-Relaxation (4-EGAOR) iterative method for rapid computation. The performance of the proposed algorithm will then be compared and analyzed against the existing algorithms in terms of number of iterations and execution time. The result shows that the proposed algorithm performed better than the existing methods.

Spectrum-averaged Harmonic Path (SHAPA) algorithm for non-contact vital sign monitoring with ultra-wideband (UWB) radar.

PubMed

Van Nguyen; Javaid, Abdul Q; Weitnauer, Mary Ann

2014-01-01

We introduce the Spectrum-averaged Harmonic Path (SHAPA) algorithm for estimation of heart rate (HR) and respiration rate (RR) with Impulse Radio Ultrawideband (IR-UWB) radar. Periodic movement of human torso caused by respiration and heart beat induces fundamental frequencies and their harmonics at the respiration and heart rates. IR-UWB enables capture of these spectral components and frequency domain processing enables a low cost implementation. Most existing methods of identifying the fundamental component either in frequency or time domain to estimate the HR and/or RR lead to significant error if the fundamental is distorted or cancelled by interference. The SHAPA algorithm (1) takes advantage of the HR harmonics, where there is less interference, and (2) exploits the information in previous spectra to achieve more reliable and robust estimation of the fundamental frequency in the spectrum under consideration. Example experimental results for HR estimation demonstrate how our algorithm eliminates errors caused by interference and produces 16% to 60% more valid estimates.

An Aircraft Separation Algorithm with Feedback and Perturbation

NASA Technical Reports Server (NTRS)

White, Allan L.

2010-01-01

A separation algorithm is a set of rules that tell aircraft how to maneuver in order to maintain a minimum distance between them. This paper investigates demonstrating that separation algorithms satisfy the FAA requirement for the occurrence of incidents by means of simulation. Any demonstration that a separation algorithm, or any other aspect of flight, satisfies the FAA requirement is a challenge because of the stringent nature of the requirement and the complexity of airspace operations. The paper begins with a probability and statistical analysis of both the FAA requirement and demonstrating meeting it by a Monte Carlo approach. It considers the geometry of maintaining separation when one plane must change its flight path. It then develops a simple feedback control law that guides the planes on their paths. The presence of feedback control permits the introduction of perturbations, and the stochastic nature of the chosen perturbation is examined. The simulation program is described. This paper is an early effort in the realistic demonstration of a stringent requirement. Much remains to be done.

An improved least cost routing approach for WDM optical network without wavelength converters

NASA Astrophysics Data System (ADS)

Bonani, Luiz H.; Forghani-elahabad, Majid

2016-12-01

Routing and wavelength assignment (RWA) problem has been an attractive problem in optical networks, and consequently several algorithms have been proposed in the literature to solve this problem. The most known techniques for the dynamic routing subproblem are fixed routing, fixed-alternate routing, and adaptive routing methods. The first one leads to a high blocking probability (BP) and the last one includes a high computational complexity and requires immense backing from the control and management protocols. The second one suggests a trade-off between performance and complexity, and hence we consider it to improve in our work. In fact, considering the RWA problem in a wavelength routed optical network with no wavelength converter, an improved technique is proposed for the routing subproblem in order to decrease the BP of the network. Based on fixed-alternate approach, the first k shortest paths (SPs) between each node pair is determined. We then rearrange the SPs according to a newly defined cost for the links and paths. Upon arriving a connection request, the sorted paths are consecutively checked for an available wavelength according to the most-used technique. We implement our proposed algorithm and the least-hop fixed-alternate algorithm to show how the rearrangement of SPs contributes to a lower BP in the network. The numerical results demonstrate the efficiency of our proposed algorithm in comparison with the others, considering different number of available wavelengths.

Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms

NASA Astrophysics Data System (ADS)

Tleis, Mohamed; Verbeek, Fons J.

2014-04-01

Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.

Path integral Monte Carlo ground state approach: formalism, implementation, and applications

NASA Astrophysics Data System (ADS)

Yan, Yangqian; Blume, D.

2017-11-01

Monte Carlo techniques have played an important role in understanding strongly correlated systems across many areas of physics, covering a wide range of energy and length scales. Among the many Monte Carlo methods applicable to quantum mechanical systems, the path integral Monte Carlo approach with its variants has been employed widely. Since semi-classical or classical approaches will not be discussed in this review, path integral based approaches can for our purposes be divided into two categories: approaches applicable to quantum mechanical systems at zero temperature and approaches applicable to quantum mechanical systems at finite temperature. While these two approaches are related to each other, the underlying formulation and aspects of the algorithm differ. This paper reviews the path integral Monte Carlo ground state (PIGS) approach, which solves the time-independent Schrödinger equation. Specifically, the PIGS approach allows for the determination of expectation values with respect to eigen states of the few- or many-body Schrödinger equation provided the system Hamiltonian is known. The theoretical framework behind the PIGS algorithm, implementation details, and sample applications for fermionic systems are presented.

Blocking performance approximation in flexi-grid networks

NASA Astrophysics Data System (ADS)

Ge, Fei; Tan, Liansheng

2016-12-01

The blocking probability to the path requests is an important issue in flexible bandwidth optical communications. In this paper, we propose a blocking probability approximation method of path requests in flexi-grid networks. It models the bundled neighboring carrier allocation with a group of birth-death processes and provides a theoretical analysis to the blocking probability under variable bandwidth traffic. The numerical results show the effect of traffic parameters to the blocking probability of path requests. We use the first fit algorithm in network nodes to allocate neighboring carriers to path requests in simulations, and verify approximation results.

Path Planning for Robot based on Chaotic Artificial Potential Field Method

NASA Astrophysics Data System (ADS)

Zhang, Cheng

2018-03-01

Robot path planning in unknown environments is one of the hot research topics in the field of robot control. Aiming at the shortcomings of traditional artificial potential field methods, we propose a new path planning for Robot based on chaotic artificial potential field method. The path planning adopts the potential function as the objective function and introduces the robot direction of movement as the control variables, which combines the improved artificial potential field method with chaotic optimization algorithm. Simulations have been carried out and the results demonstrate that the superior practicality and high efficiency of the proposed method.

Algorithm for lens calculations in the geometrized Maxwell theory

NASA Astrophysics Data System (ADS)

Kulyabov, Dmitry S.; Korolkova, Anna V.; Sevastianov, Leonid A.; Gevorkyan, Migran N.; Demidova, Anastasia V.

2018-04-01

Nowadays the geometric approach in optics is often used to find out media parameters based on propagation paths of the rays because in this case it is a direct problem. However inverse problem in the framework of geometrized optics is usually not given attention. The aim of this work is to demonstrate the work of the proposed the algorithm in the framework of geometrized approach to optics for solving the problem of finding the propagation path of the electromagnetic radiation depending on environmental parameters. The methods of differential geometry are used for effective metrics construction for isotropic and anisotropic media. For effective metric space ray trajectories are obtained in the form of geodesic curves. The introduced algorithm is applied to well-known objects, Maxwell and Luneburg lenses. The similarity of results obtained by classical and geometric approach is demonstrated.

Modified Hyperspheres Algorithm to Trace Homotopy Curves of Nonlinear Circuits Composed by Piecewise Linear Modelled Devices

PubMed Central

Vazquez-Leal, H.; Jimenez-Fernandez, V. M.; Benhammouda, B.; Filobello-Nino, U.; Sarmiento-Reyes, A.; Ramirez-Pinero, A.; Marin-Hernandez, A.; Huerta-Chua, J.

2014-01-01

We present a homotopy continuation method (HCM) for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL) representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation. PMID:25184157

Test results of flight guidance for fuel conservative descents in a time-based metered air traffic environment. [terminal configured vehicle

NASA Technical Reports Server (NTRS)

Knox, C. E.; Person, L. H., Jr.

1981-01-01

The NASA developed, implemented, and flight tested a flight management algorithm designed to improve the accuracy of delivering an airplane in a fuel-conservative manner to a metering fix at a time designated by air traffic control. This algorithm provides a 3D path with time control (4D) for the TCV B-737 airplane to make an idle-thrust, clean configured (landing gear up, flaps zero, and speed brakes retracted) descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path is calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithms are described and flight test results are presented.

Inverse optimal self-tuning PID control design for an autonomous underwater vehicle

NASA Astrophysics Data System (ADS)

Rout, Raja; Subudhi, Bidyadhar

2017-01-01

This paper presents a new approach to path following control design for an autonomous underwater vehicle (AUV). A NARMAX model of the AUV is derived first and then its parameters are adapted online using the recursive extended least square algorithm. An adaptive Propotional-Integral-Derivative (PID) controller is developed using the derived parameters to accomplish the path following task of an AUV. The gain parameters of the PID controller are tuned using an inverse optimal control technique, which alleviates the problem of solving Hamilton-Jacobian equation and also satisfies an error cost function. Simulation studies were pursued to verify the efficacy of the proposed control algorithm. From the obtained results, it is envisaged that the proposed NARMAX model-based self-tuning adaptive PID control provides good path following performance even in the presence of uncertainty arising due to ocean current or hydrodynamic parameter.

Information Spread of Emergency Events: Path Searching on Social Networks

PubMed Central

Hu, Hongzhi; Wu, Tunan

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

NASA Technical Reports Server (NTRS)

Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan

2014-01-01

Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

NASA Technical Reports Server (NTRS)

Colby, Mitchell; Knudson, Matthew D.; Tumer, Kagan

2014-01-01

Dynamic environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal paths through these environments. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially with the number of agents in the system. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance.

Real-time path planning in dynamic virtual environments using multiagent navigation graphs.

PubMed

Sud, Avneesh; Andersen, Erik; Curtis, Sean; Lin, Ming C; Manocha, Dinesh

2008-01-01

We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multi-agent Navigation Graph (MaNG), which is constructed using first- and second-order Voronoi diagrams. The MaNG is used to perform route planning and proximity computations for each agent in real time. Moreover, we use the path information and proximity relationships for local dynamics computation of each agent by extending a social force model [Helbing05]. We compute the MaNG using graphics hardware and present culling techniques to accelerate the computation. We also address undersampling issues and present techniques to improve the accuracy of our algorithm. Our algorithm is used for real-time multi-agent planning in pursuit-evasion, terrain exploration and crowd simulation scenarios consisting of hundreds of moving agents, each with a distinct goal.

Scheduling and control strategies for the departure problem in air traffic control

NASA Astrophysics Data System (ADS)

Bolender, Michael Alan

Two problems relating to the departure problem in air traffic control automation are examined. The first problem that is addressed is the scheduling of aircraft for departure. The departure operations at a major US hub airport are analyzed, and a discrete event simulation of the departure operations is constructed. Specifically, the case where there is a single departure runway is considered. The runway is fed by two queues of aircraft. Each queue, in turn, is fed by a single taxiway. Two salient areas regarding scheduling are addressed. The first is the construction of optimal departure sequences for the aircraft that are queued. Several greedy search algorithms are designed to minimize the total time to depart a set of queued aircraft. Each algorithm has a different set of heuristic rules to resolve situations within the search space whenever two branches of the search tree with equal edge costs are encountered. These algorithms are then compared and contrasted with a genetic search algorithm in order to assess the performance of the heuristics. This is done in the context of a static departure problem where the length of the departure queue is fixed. A greedy algorithm which deepens the search whenever two branches of the search tree with non-unique costs are encountered is shown to outperform the other heuristic algorithms. This search strategy is then implemented in the discrete event simulation. A baseline performance level is established, and a sensitivity analysis is performed by implementing changes in traffic mix, routing, and miles-in-trail restrictions for comparison. It is concluded that to minimize the average time spent in the queue for different traffic conditions, a queue assignment algorithm is needed to maintain an even balance of aircraft in the queues. A necessary consideration is to base queue assignment upon traffic management restrictions such as miles-in-trail constraints. The second problem addresses the technical challenges associated with merging departure aircraft onto their filed routes in a congested airspace environment. Conflicts between departures and en route aircraft within the Center airspace are analyzed. Speed control, holding the aircraft; at an intermediate altitude, re-routing, and vectoring are posed as possible deconfliction maneuvers. A cost assessment of these merge strategies, which are based upon 4D fight management and conflict detection and resolution principles, is given. Several merge conflicts are studied and a cost for each resolution is computed. It is shown that vectoring tends to be the most expensive resolution technique. Altitude hold is simple, costs less than vectoring, but may require a long time for the aircraft to achieve separation. Re-routing is the simplest, and provides the most cost benefit since the aircraft flies a shorter distance than if it had followed its filed route. Speed control is shown to be ineffective as a means of increasing separation, but is effective for maintaining separation between aircraft. In addition, the affects of uncertainties on the cost are assessed. The analysis shows that cost is invariant with the decision time.