Universal single level implicit algorithm for gasdynamics
NASA Technical Reports Server (NTRS)
Lombard, C. K.; Venkatapthy, E.
1984-01-01
A single level effectively explicit implicit algorithm for gasdynamics is presented. The method meets all the requirements for unconditionally stable global iteration over flows with mixed supersonic and supersonic zones including blunt body flow and boundary layer flows with strong interaction and streamwise separation. For hyperbolic (supersonic flow) regions the method is automatically equivalent to contemporary space marching methods. For elliptic (subsonic flow) regions, rapid convergence is facilitated by alternating direction solution sweeps which bring both sets of eigenvectors and the influence of both boundaries of a coordinate line equally into play. Point by point updating of the data with local iteration on the solution procedure at each spatial step as the sweeps progress not only renders the method single level in storage but, also, improves nonlinear accuracy to accelerate convergence by an order of magnitude over related two level linearized implicit methods. The method derives robust stability from the combination of an eigenvector split upwind difference method (CSCM) with diagonally dominant ADI(DDADI) approximate factorization and computed characteristic boundary approximations.
Simplified space vector PWM algorithm for five-level inverter
NASA Astrophysics Data System (ADS)
Lalili, D.; Berkouk, E. M.; Boudjema, F.; Lourci, N.; Taleb, T.; Petzold, J.
2007-12-01
In this work, we present an algorithm for the space vector pulse width modulation (SVPWM) applied to five-level diode clamped inverter. In this algorithm, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. This idea allows us to generalize the two-level SVPWM algorithm into the case of five-level inverter.
A three-level BDDC algorithm for Mortar discretizations
Kim, H.; Tu, X.
2007-12-09
In this paper, a three-level BDDC algorithm is developed for the solutions of large sparse algebraic linear systems arising from the mortar discretization of elliptic boundary value problems. The mortar discretization is considered on geometrically non-conforming subdomain partitions. In two-level BDDC algorithms, the coarse problem needs to be solved exactly. However, its size will increase with the increase of the number of the subdomains. To overcome this limitation, the three-level algorithm solves the coarse problem inexactly while a good rate of convergence is maintained. This is an extension of previous work, the three-level BDDC algorithms for standard finite element discretization. Estimates of the condition numbers are provided for the three-level BDDC method and numerical experiments are also discussed.
The Algorithm Theoretical Basis Document for Level 1A Processing
NASA Technical Reports Server (NTRS)
Jester, Peggy L.; Hancock, David W., III
2012-01-01
The first process of the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software converts the Level 0 data into the Level 1A Data Products. The Level 1A Data Products are the time ordered instrument data converted from counts to engineering units. This document defines the equations that convert the raw instrument data into engineering units. Required scale factors, bias values, and coefficients are defined in this document. Additionally, required quality assurance and browse products are defined in this document.
Re-Computation of Numerical Results Contained in NACA Report No. 496
NASA Technical Reports Server (NTRS)
Perry, Boyd, III
2015-01-01
An extensive examination of NACA Report No. 496 (NACA 496), "General Theory of Aerodynamic Instability and the Mechanism of Flutter," by Theodore Theodorsen, is described. The examination included checking equations and solution methods and re-computing interim quantities and all numerical examples in NACA 496. The checks revealed that NACA 496 contains computational shortcuts (time- and effort-saving devices for engineers of the time) and clever artifices (employed in its solution methods), but, unfortunately, also contains numerous tripping points (aspects of NACA 496 that have the potential to cause confusion) and some errors. The re-computations were performed employing the methods and procedures described in NACA 496, but using modern computational tools. With some exceptions, the magnitudes and trends of the original results were in fair-to-very-good agreement with the re-computed results. The exceptions included what are speculated to be computational errors in the original in some instances and transcription errors in the original in others. Independent flutter calculations were performed and, in all cases, including those where the original and re-computed results differed significantly, were in excellent agreement with the re-computed results. Appendix A contains NACA 496; Appendix B contains a Matlab(Reistered) program that performs the re-computation of results; Appendix C presents three alternate solution methods, with examples, for the two-degree-of-freedom solution method of NACA 496; Appendix D contains the three-degree-of-freedom solution method (outlined in NACA 496 but never implemented), with examples.
A two-level detection algorithm for optical fiber vibration
NASA Astrophysics Data System (ADS)
Bi, Fukun; Ren, Xuecong; Qu, Hongquan; Jiang, Ruiqing
2015-09-01
Optical fiber vibration is detected by the coherent optical time domain reflection technique. In addition to the vibration signals, the reflected signals include clutters and noises, which lead to a high false alarm rate. The "cell averaging" constant false alarm rate algorithm has a high computing speed, but its detection performance will be declined in nonhomogeneous environments such as multiple targets. The "order statistics" constant false alarm rate algorithm has a distinct advantage in multiple target environments, but it has a lower computing speed. An intelligent two-level detection algorithm is presented based on "cell averaging" constant false alarm rate and "order statistics" constant false alarm rate which work in serial way, and the detection speed of "cell averaging" constant false alarm rate and performance of "order statistics" constant false alarm rate are conserved, respectively. Through the adaptive selection, the "cell averaging" is applied in homogeneous environments, and the two-level detection algorithm is employed in nonhomogeneous environments. Our Monte Carlo simulation results demonstrate that considering different signal noise ratios, the proposed algorithm gives better detection probability than that of "order statistics".
A Three-level BDDC algorithm for saddle point problems
Tu, X.
2008-12-10
BDDC algorithms have previously been extended to the saddle point problems arising from mixed formulations of elliptic and incompressible Stokes problems. In these two-level BDDC algorithms, all iterates are required to be in a benign space, a subspace in which the preconditioned operators are positive definite. This requirement can lead to large coarse problems, which have to be generated and factored by a direct solver at the beginning of the computation and they can ultimately become a bottleneck. An additional level is introduced in this paper to solve the coarse problem approximately and to remove this difficulty. This three-level BDDC algorithm keeps all iterates in the benign space and the conjugate gradient methods can therefore be used to accelerate the convergence. This work is an extension of the three-level BDDC methods for standard finite element discretization of elliptic problems and the same rate of convergence is obtained for the mixed formulation of the same problems. Estimate of the condition number for this three-level BDDC methods is provided and numerical experiments are discussed.
On the multi-level solution algorithm for Markov chains
Horton, G.
1996-12-31
We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.
Level-treewidth property, exact algorithms and approximation schemes
Marathe, M.V.; Hunt, H.B.; Stearns, R.E.
1997-06-01
Informally, a class of graphs Q is said to have the level-treewidth property (LT-property) if for every G {element_of} Q there is a layout (breadth first ordering) L{sub G} such that the subgraph induced by the vertices in k-consecutive levels in the layout have treewidth O(f (k)), for some function f. We show that several important and well known classes of graphs including planar and bounded genus graphs, (r, s)-civilized graphs, etc, satisfy the LT-property. Building on the recent work, we present two general types of results for the class of graphs obeying the LT-property. (1) All problems in the classes MPSAT, TMAX and TMIN have polynomial time approximation schemes. (2) The problems considered in Eppstein have efficient polynomial time algorithms. These results can be extended to obtain polynomial time approximation algorithms and approximation schemes for a number of PSPACE-hard combinatorial problems specified using different kinds of succinct specifications studied in. Many of the results can also be extended to {delta}-near genus and {delta}-near civilized graphs, for any fixed {delta}. Our results significantly extend the work in and affirmatively answer recent open questions.
Level-1 pixel based tracking trigger algorithm for LHC upgrade
NASA Astrophysics Data System (ADS)
Moon, C.-S.; Savoy-Navarro, A.
2015-10-01
The Pixel Detector is the innermost detector of the tracking system of the Compact Muon Solenoid (CMS) experiment at CERN Large Hadron Collider (LHC) . It precisely determines the interaction point (primary vertex) of the events and the possible secondary vertexes due to heavy flavours (b and c quarks); it is part of the overall tracking system that allows reconstructing the tracks of the charged particles in the events and combined with the magnetic field to measure their momentum. The pixel detector allows measuring the tracks in the region closest to the interaction point. The Level-1 (real-time) pixel based tracking trigger is a novel trigger system that is currently being studied for the LHC upgrade. An important goal is developing real-time track reconstruction algorithms able to cope with very high rates and high flux of data in a very harsh environment. The pixel detector has an especially crucial role in precisely identifying the primary vertex of the rare physics events from the large pile-up (PU) of events. The goal of adding the pixel information already at the real-time level of the selection is to help reducing the total level-1 trigger rate while keeping an high selection capability. This is quite an innovative and challenging objective for the experiments upgrade for the High Luminosity LHC (HL-LHC) . The special case here addressed is the CMS experiment. This document describes exercises focusing on the development of a fast pixel track reconstruction where the pixel track matches with a Level-1 electron object using a ROOT-based simulation framework.
Areibi, Shawki; Yang, Zhen
2004-01-01
Combining global and local search is a strategy used by many successful hybrid optimization approaches. Memetic Algorithms (MAs) are Evolutionary Algorithms (EAs) that apply some sort of local search to further improve the fitness of individuals in the population. Memetic Algorithms have been shown to be very effective in solving many hard combinatorial optimization problems. This paper provides a forum for identifying and exploring the key issues that affect the design and application of Memetic Algorithms. The approach combines a hierarchical design technique, Genetic Algorithms, constructive techniques and advanced local search to solve VLSI circuit layout in the form of circuit partitioning and placement. Results obtained indicate that Memetic Algorithms based on local search, clustering and good initial solutions improve solution quality on average by 35% for the VLSI circuit partitioning problem and 54% for the VLSI standard cell placement problem. PMID:15355604
Areibi, Shawki; Yang, Zhen
2004-01-01
Combining global and local search is a strategy used by many successful hybrid optimization approaches. Memetic Algorithms (MAs) are Evolutionary Algorithms (EAs) that apply some sort of local search to further improve the fitness of individuals in the population. Memetic Algorithms have been shown to be very effective in solving many hard combinatorial optimization problems. This paper provides a forum for identifying and exploring the key issues that affect the design and application of Memetic Algorithms. The approach combines a hierarchical design technique, Genetic Algorithms, constructive techniques and advanced local search to solve VLSI circuit layout in the form of circuit partitioning and placement. Results obtained indicate that Memetic Algorithms based on local search, clustering and good initial solutions improve solution quality on average by 35% for the VLSI circuit partitioning problem and 54% for the VLSI standard cell placement problem.
Heuristic-based scheduling algorithm for high level synthesis
NASA Technical Reports Server (NTRS)
Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye
1992-01-01
A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.
Level set algorithms comparison for multi-slice CT left ventricle segmentation
NASA Astrophysics Data System (ADS)
Medina, Ruben; La Cruz, Alexandra; Ordoñes, Andrés.; Pesántez, Daniel; Morocho, Villie; Vanegas, Pablo
2015-12-01
The comparison of several Level Set algorithms is performed with respect to 2D left ventricle segmentation in Multi-Slice CT images. Five algorithms are compared by calculating the Dice coefficient between the resulting segmentation contour and a reference contour traced by a cardiologist. The algorithms are also tested on images contaminated with Gaussian noise for several values of PSNR. Additionally an algorithm for providing the initialization shape is proposed. This algorithm is based on a combination of mathematical morphology tools with watershed and region growing algorithms. Results on the set of test images are promising and suggest the extension to 3{D MSCT database segmentation.
Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D
2015-04-01
Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis."
Qualls, Joseph; Russomanno, David J.
2011-01-01
The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demonstrate the efficacy of the ontological problem-solving architecture, a family of persistence surveillance sensor systems and algorithms has been instantiated in a prototype environment to demonstrate the assignment of systems to subtasks of high-level missions. PMID:22164081
Signal window minimum average error algorithm for multi-phase level computer-generated holograms
NASA Astrophysics Data System (ADS)
El Bouz, Marwa; Heggarty, Kevin
2000-06-01
This paper extends the article "Signal window minimum average error algorithm for computer-generated holograms" (JOSA A 1998) to multi-phase level CGHs. We show that using the same rule for calculating the complex error diffusion weights, iterative-algorithm-like low-error signal windows can be obtained for any window shape or position (on- or off-axis) and any number of CGH phase levels. Important algorithm parameters such as amplitude normalisation level and phase freedom diffusers are described and investigated to optimize the algorithm. We show that, combined with a suitable diffuser, the algorithm makes feasible the calculation of high performance CGHs far larger than currently practical with iterative algorithms yet now realisable with modern fabrication techniques. Preliminary experimental optical reconstructions are presented.
A multi-level solution algorithm for steady-state Markov chains
NASA Technical Reports Server (NTRS)
Horton, Graham; Leutenegger, Scott T.
1993-01-01
A new iterative algorithm, the multi-level algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial differential equations. Initial results of numerical experiments are reported, showing significant reductions in computation time, often an order of magnitude or more, relative to the Gauss-Seidel and optimal SOR algorithms for a variety of test problems. The multi-level method is compared and contrasted with the iterative aggregation-disaggregation algorithm of Takahashi.
The new Sunspot Number: re-calibration, re-computation and implications for the solar cycle
NASA Astrophysics Data System (ADS)
Clette, Frédéric; Lefèvre, Laure
2015-08-01
Our knowledge of the long-term behaviour of the solar cycle and the occurrence of Grand Minima rest largely on the 400-year sunspot record, currently in the form of two time series: the Sunspot Number and the Group Number. Recently, a full revision of those two series allowed to identify and correct various inhomogeneities, thereby also eliminating most of the discrepancies between those two parallel series.We report here about the changes in those two series and one of the main implications: the absence of a progressive rise of solar activity from the Maunder Minimum to a modern maximum in the 20th century. We also focus in particular on the important corrections applied over the last 50 years, in particular a variable drift in the scale of the Specola Solare station (Locarno) that defined the long-term scale of the International Sunspot Number over the last 35 years, i.e. over the period when modern measurements of solar irradiance and solar wind particles can be correlated with the Sunspot Number for building long-term backward reconstructions of those physical parameters. Taking advantage of the archive of the World Data Center SILSO (270 stations, 550,000 observations), we could entirely re-compute the Sunspot Number. We describe the properties of the new resulting series and the new method developed to build a more stable multi-station reference for the Sunspot Number.We conclude on the release of the new reference Sunspot Number and the simultaneous adoption of new conventions and standards (error estimates, version tracking and documenting). We also consider the next steps that will allow future progresses in the characterisation of the solar cycle: the digitisation of historical drawings and the creation of image-based sunspot indices that will allow adding spatial information, to extend the one-dimensional information brought by the Sunspot Number.
Al Hosani, E; Soleimani, M
2016-06-28
Multiphase flow imaging is a very challenging and critical topic in industrial process tomography. In this article, simulation and experimental results of reconstructing the permittivity profile of multiphase material from data collected in electrical capacitance tomography (ECT) are presented. A multiphase narrowband level set algorithm is developed to reconstruct the interfaces between three- or four-phase permittivity values. The level set algorithm is capable of imaging multiphase permittivity by using one set of ECT measurement data, so-called absolute value ECT reconstruction, and this is tested with high-contrast and low-contrast multiphase data. Simulation and experimental results showed the superiority of this algorithm over classical pixel-based image reconstruction methods. The multiphase level set algorithm and absolute ECT reconstruction are presented for the first time, to the best of our knowledge, in this paper and critically evaluated. This article is part of the themed issue 'Supersensing through industrial process tomography'. PMID:27185966
Al Hosani, E; Soleimani, M
2016-06-28
Multiphase flow imaging is a very challenging and critical topic in industrial process tomography. In this article, simulation and experimental results of reconstructing the permittivity profile of multiphase material from data collected in electrical capacitance tomography (ECT) are presented. A multiphase narrowband level set algorithm is developed to reconstruct the interfaces between three- or four-phase permittivity values. The level set algorithm is capable of imaging multiphase permittivity by using one set of ECT measurement data, so-called absolute value ECT reconstruction, and this is tested with high-contrast and low-contrast multiphase data. Simulation and experimental results showed the superiority of this algorithm over classical pixel-based image reconstruction methods. The multiphase level set algorithm and absolute ECT reconstruction are presented for the first time, to the best of our knowledge, in this paper and critically evaluated. This article is part of the themed issue 'Supersensing through industrial process tomography'.
The Desired Sensation Level Multistage Input/Output Algorithm
Scollie, Susan; Seewald, Richard; Cornelisse, Leonard; Moodie, Sheila; Bagatto, Marlene; Laurnagaray, Diana; Beaulac, Steve; Pumford, John
2005-01-01
The Desired Sensation Level (DSL) Method was revised to support hearing instrument fitting for infants, young children, and adults who use modern hearing instrument technologies, including multichannel compression, expansion, and multimemory capability. The aims of this revision are to maintain aspects of the previous versions of the DSL Method that have been supported by research, while extending the method to account for adult-child differences in preference and listening requirements. The goals of this version (5.0) include avoiding loudness discomfort, selecting a frequency response that meets audibility requirements, choosing compression characteristics that appropriately match technology to the user's needs, and accommodating the overall prescription to meet individual needs for use in various listening environments. This review summarizes the status of research on the use of the DSL Method with pediatric and adult populations and presents a series of revisions that have been made during the generation of DSL v5.0. This article concludes with case examples that illustrate key differences between the DSL v4.1 and DSL v5.0 prescriptions. PMID:16424945
NASA Astrophysics Data System (ADS)
Niwa, Keiichi; Hayashida, Tomohiro; Sakawa, Masatoshi; Yang, Yishen
2010-10-01
We consider two-level programming problems in which there are one decision maker (the leader) at the upper level and two or more decision makers (the followers) at the lower level and decision variables of the leader and the followers are 0-1 variables. We assume that there is coordination among the followers while between the leader and the group of all the followers, there is no motivation to cooperate each other, and fuzzy goals for objective functions of the leader and the followers are introduced so as to take fuzziness of their judgments into consideration. The leader maximizes the degree of satisfaction (the value of the membership function) and the followers choose in concert in order to maximize a minimum among their degrees of satisfaction. We propose a modified computational method that solves problems related to the computational method based on the genetic algorithm (the existing method) for obtaining the Stackelberg solution. Specifically, the distributed genetic algorithm is introduced with respect to the upper level genetic algorithm, which handles decision variables for the leader in order to shorten the computational time of the existing method. Parallelization of the lower level genetic algorithm is also performed along with parallelization of the upper level genetic algorithm. In order to demonstrate the effectiveness of the proposed computational method, numerical experiments are carried out.
Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data
NASA Technical Reports Server (NTRS)
Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.
2011-01-01
The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.
An adaptive multi-level simulation algorithm for stochastic biological systems
Lester, C. Giles, M. B.; Baker, R. E.; Yates, C. A.
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 Monte 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
An adaptive multi-level simulation algorithm for stochastic biological systems
NASA Astrophysics Data System (ADS)
Lester, C.; Yates, C. A.; Giles, M. B.; Baker, R. E.
2015-01-01
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 Monte 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
An improved bi-level algorithm for partitioning dynamic grid hierarchies.
Deiterding, Ralf (California Institute of Technology, Pasadena, CA); Johansson, Henrik (Uppsala University, Uppsala, Sweden); Steensland, Johan; Ray, Jaideep
2006-05-01
Structured adaptive mesh refinement methods are being widely used for computer simulations of various physical phenomena. Parallel implementations potentially offer realistic simulations of complex three-dimensional applications. But achieving good scalability for large-scale applications is non-trivial. Performance is limited by the partitioner's ability to efficiently use the underlying parallel computer's resources. Designed on sound SAMR principles, Nature+Fable is a hybrid, dedicated SAMR partitioning tool that brings together the advantages of both domain-based and patch-based techniques while avoiding their drawbacks. But the original bi-level partitioning approach in Nature+Fable is insufficient as it for realistic applications regards frequently occurring bi-levels as ''impossible'' and fails. This document describes an improved bi-level partitioning algorithm that successfully copes with all possible bi-levels. The improved algorithm uses the original approach side-by-side with a new, complementing approach. By using a new, customized classification method, the improved algorithm switches automatically between the two approaches. This document describes the algorithms, discusses implementation issues, and presents experimental results. The improved version of Nature+Fable was found to be able to handle realistic applications and also to generate less imbalances, similar box count, but more communication as compared to the native, domain-based partitioner in the SAMR framework AMROC.
NASA Astrophysics Data System (ADS)
Niaz, Mansoor; Robinson, William R.
1993-06-01
It has been shown previously that many students solve chemistry problems using only algorithmic strategies and do not understand the chemical concepts on which the problems are based. It is plausible to suggest that if the information is presented in differing formats, the cognitive demand of a problem changes. The main objective of this study is to investigate the degree to which cognitive variables, such as developmental level, mental capacity, and disembedding ability explain student performance on problems which: (1) could be addressed by algorithms or (2) require conceptual understanding. All conceptual problems used in this study were based on a figurative format. The results obtained show that in all four problems requiring algorithmic strategies, developmental level of the students is the best predictor of success. This could be attributed to the fact that these are basically computational problems, requiring mathematical transformations. Although all three problems requiring conceptual understanding had an important aspect in common (the figurative format), in all three the best predictor of success is a different cognitive variable. It was concluded that: (1) the ability to solve computational problems (based on algorithms) is not the major factor in predicting success in solving problems that require conceptual understanding; (2) solving problems based on algorithmic strategies requires formal operational reasoning to a certain degree; and (3) student difficulty in solving problems that require conceptual understanding could be attributed to different cognitive variables.
NASA Astrophysics Data System (ADS)
Schämann, M.; Bücker, M.; Hessel, S.; Langmann, U.
2008-05-01
High data rates combined with high mobility represent a challenge for the design of cellular devices. Advanced algorithms are required which result in higher complexity, more chip area and increased power consumption. However, this contrasts to the limited power supply of mobile devices. This presentation discusses the application of an HSDPA receiver which has been optimized regarding power consumption with the focus on the algorithmic and architectural level. On algorithmic level the Rake combiner, Prefilter-Rake equalizer and MMSE equalizer are compared regarding their BER performance. Both equalizer approaches provide a significant increase of performance for high data rates compared to the Rake combiner which is commonly used for lower data rates. For both equalizer approaches several adaptive algorithms are available which differ in complexity and convergence properties. To identify the algorithm which achieves the required performance with the lowest power consumption the algorithms have been investigated using SystemC models regarding their performance and arithmetic complexity. Additionally, for the Prefilter Rake equalizer the power estimations of a modified Griffith (LMS) and a Levinson (RLS) algorithm have been compared with the tool ORINOCO supplied by ChipVision. The accuracy of this tool has been verified with a scalable architecture of the UMTS channel estimation described both in SystemC and VHDL targeting a 130 nm CMOS standard cell library. An architecture combining all three approaches combined with an adaptive control unit is presented. The control unit monitors the current condition of the propagation channel and adjusts parameters for the receiver like filter size and oversampling ratio to minimize the power consumption while maintaining the required performance. The optimization strategies result in a reduction of the number of arithmetic operations up to 70% for single components which leads to an estimated power reduction of up to 40
An algorithm based on sea level pressure fluctuations to identify major Baltic inflow events
NASA Astrophysics Data System (ADS)
Schimanke, Semjon; Dieterich, Christian; Markus Meier, H. E.
2014-05-01
The Baltic Sea is one of world largest brackish water areas with an estuarine like circulation. It is connected to the world ocean through the narrow Danish straits limiting the exchange of water masses. The deep water of the Baltic Sea is mainly renewed by so called major Baltic inflows which are an important feature to sustain the sensitive steady state of the Baltic Sea. We introduce an algorithm to identify atmospheric variability favourable for major Baltic inflows. The algorithm is based on sea level pressure fields as the only parameter. Characteristic sea level pressure pattern fluctuations include a precursory phase of 30 days and 10 days of inflow period. The algorithm identifies successfully the majority of observed major Baltic inflows between 1961--2010. In addition, the algorithm finds some occurrences which cannot be related to observed inflows. In these cases with favourable atmospheric conditions inflows were precluded by contemporaneously existing saline water masses or strong freshwater supply. No event is registered during the stagnation period 1983-1993 indicating that the lack of inflows is a consequence of missing favourable atmospheric variability. The only striking inflow which is not identified by the algorithm is the event in January 2003. We demonstrate that this is due to the special evolution of sea level pressure fields which are not comparable with any other event. Finally, the algorithm is applied to an ensemble of scenario simulations. The result indicates that the number of atmospheric events favourable for major Baltic inflows increases slightly in all scenarios. Possible explanations as for instance more frequent atmospheric blockings or changes in the NAO will be discussed.
A parallel algorithm for switch-level timing simulation on a hypercube multiprocessor
NASA Technical Reports Server (NTRS)
Rao, Hariprasad Nannapaneni
1989-01-01
The parallel approach to speeding up simulation is studied, specifically the simulation of digital LSI MOS circuitry on the Intel iPSC/2 hypercube. The simulation algorithm is based on RSIM, an event driven switch-level simulator that incorporates a linear transistor model for simulating digital MOS circuits. Parallel processing techniques based on the concepts of Virtual Time and rollback are utilized so that portions of the circuit may be simulated on separate processors, in parallel for as large an increase in speed as possible. A partitioning algorithm is also developed in order to subdivide the circuit for parallel processing.
The algorithm and implementation of EMCCD automatic gain adjustment based on fixed gray level
NASA Astrophysics Data System (ADS)
Luo, Le; Chen, Qian; He, Wei-Ji; Lu, Zhen-Xi
2015-10-01
The image quality and resolution will be affected, if the multiplication gain value of EMCCD imaging system is too low or too high. This paper presents the algorithm of EMCCD automatic gain adjustment based on fixed gray level. The algorithm takes the average brightness of the image as a measure of image quality. It calculates the multiplication gain adjustment value through the calculation of average brightness of current frame image, combining the two gray level threshold values and the system exposure function, so that the next frame image will achieve the ideal brightness value. On the basis of the algorithm, this paper builds a multiplication gain adjustment control circuit and a multiplication gain resistor lookup table. Then, we can achieve automatic adjustment of multiplication gain by changing the resistance value of the digital potentiometer in the circuit. Experimental results show that the image quality can be effectively improved, by using the algorithm of automatic gain adjustment based on fixed gray level. After adjustment, the brightness of the image is moderate, contrast enhanced, and the details more clear.
An algorithm for the grain-level modelling of a dry sand particulate system
NASA Astrophysics Data System (ADS)
Fang, Qin; Zhang, Jinhua; Chen, Li; Liu, Jinchun; Fan, Junyu; Zhang, Yadong
2014-07-01
This paper is composed of two parts: the generation of the sand particulate system and insights into the grain-level response under static and dynamic loadings. First, the algorithms for the generation of sand particles are presented, considering the randomness in their shape and distribution. Improvements to the robustness of the algorithms are obtained using controlling parameters. Second, we employ the take-and-place algorithm, placing sand grains into the specimen and checking how they overlap to form the initial model. In order to improve the porosity of the specimen, we develop the compaction algorithm: self-compaction by gravity and artificial compaction by mechanical vibration and pressure. The steps for the generation of a finite element grid are also introduced. Third, the grain-level configurations of the dry sand particulate system (aspects such as porosity, friction and contact) are taken into account in modelling. Results show that the grain-level responses of grains, i.e. deformation, fracture and damage of sand grains, impose significant effects on the mechanical behavior of dry sand under static and dynamic loadings.
A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution
Shi, Yonggang; Karl, William Clem
2010-01-01
In this paper, we present a complete and practical algorithm for the approximation of level-set-based curve evolution suitable for real-time implementation. In particular, we propose a two-cycle algorithm to approximate level-set-based curve evolution without the need of solving partial differential equations (PDEs). Our algorithm is applicable to a broad class of evolution speeds that can be viewed as composed of a data-dependent term and a curve smoothness regularization term. We achieve curve evolution corresponding to such evolution speeds by separating the evolution process into two different cycles: one cycle for the data-dependent term and a second cycle for the smoothness regularization. The smoothing term is derived from a Gaussian filtering process. In both cycles, the evolution is realized through a simple element switching mechanism between two linked lists, that implicitly represents the curve using an integer valued level-set function. By careful construction, all the key evolution steps require only integer operations. A consequence is that we obtain significant computation speedups compared to exact PDE-based approaches while obtaining excellent agreement with these methods for problems of practical engineering interest. In particular, the resulting algorithm is fast enough for use in real-time video processing applications, which we demonstrate through several image segmentation and video tracking experiments. PMID:18390371
An Evolutionary Algorithm with Double-Level Archives for Multiobjective Optimization.
Chen, Ni; Chen, Wei-Neng; Gong, Yue-Jiao; Zhan, Zhi-Hui; Zhang, Jun; Li, Yun; Tan, Yu-Song
2015-09-01
Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a whole or as several decomposed single-objective sub-problems. Though the problem decomposition approach generally converges faster through optimizing all the sub-problems simultaneously, there are two issues not fully addressed, i.e., distribution of solutions often depends on a priori problem decomposition, and the lack of population diversity among sub-problems. In this paper, a MOEA with double-level archives is developed. The algorithm takes advantages of both the multiobjective-problem-level and the sub-problem-level approaches by introducing two types of archives, i.e., the global archive and the sub-archive. In each generation, self-reproduction with the global archive and cross-reproduction between the global archive and sub-archives both breed new individuals. The global archive and sub-archives communicate through cross-reproduction, and are updated using the reproduced individuals. Such a framework thus retains fast convergence, and at the same time handles solution distribution along Pareto front (PF) with scalability. To test the performance of the proposed algorithm, experiments are conducted on both the widely used benchmarks and a set of truly disconnected problems. The results verify that, compared with state-of-the-art MOEAs, the proposed algorithm offers competitive advantages in distance to the PF, solution coverage, and search speed. PMID:25343775
NASA Technical Reports Server (NTRS)
Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.
1994-01-01
The EOS Moderate Resolution Imaging Spectrometer (MODIS) is being developed by NASA for flight on the Earth Observing System (EOS) series of satellites, the first of which (EOS-AM-1) is scheduled for launch in 1998. This document describes the algorithms and their theoretical basis for the MODIS Level 1B characterization, calibration, and geolocation algorithms which must produce radiometrically, spectrally, and spatially calibrated data with sufficient accuracy so that Global change research programs can detect minute changes in biogeophysical parameters. The document first describes the geolocation algorithm which determines geodetic latitude, longitude, and elevation of each MODIS pixel and the determination of geometric parameters for each observation (satellite zenith angle, satellite azimuth, range to the satellite, solar zenith angle, and solar azimuth). Next, the utilization of the MODIS onboard calibration sources, which consist of the Spectroradiometric Calibration Assembly (SRCA), Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), and the Blackbody (BB), is treated. Characterization of these sources and integration of measurements into the calibration process is described. Finally, the use of external sources, including the Moon, instrumented sites on the Earth (called vicarious calibration), and unsupervised normalization sites having invariant reflectance and emissive properties is treated. Finally, algorithms for generating utility masks needed for scene-based calibration are discussed. Eight appendices are provided, covering instrument design and additional algorithm details.
A Genetic Algorithm for the Bi-Level Topological Design of Local Area Networks
Camacho-Vallejo, José-Fernando; Mar-Ortiz, Julio; López-Ramos, Francisco; Rodríguez, Ricardo Pedraza
2015-01-01
Local access networks (LAN) are commonly used as communication infrastructures which meet the demand of a set of users in the local environment. Usually these networks consist of several LAN segments connected by bridges. The topological LAN design bi-level problem consists on assigning users to clusters and the union of clusters by bridges in order to obtain a minimum response time network with minimum connection cost. Therefore, the decision of optimally assigning users to clusters will be made by the leader and the follower will make the decision of connecting all the clusters while forming a spanning tree. In this paper, we propose a genetic algorithm for solving the bi-level topological design of a Local Access Network. Our solution method considers the Stackelberg equilibrium to solve the bi-level problem. The Stackelberg-Genetic algorithm procedure deals with the fact that the follower’s problem cannot be optimally solved in a straightforward manner. The computational results obtained from two different sets of instances show that the performance of the developed algorithm is efficient and that it is more suitable for solving the bi-level problem than a previous Nash-Genetic approach. PMID:26102502
A Genetic Algorithm for the Bi-Level Topological Design of Local Area Networks.
Camacho-Vallejo, José-Fernando; Mar-Ortiz, Julio; López-Ramos, Francisco; Rodríguez, Ricardo Pedraza
2015-01-01
Local access networks (LAN) are commonly used as communication infrastructures which meet the demand of a set of users in the local environment. Usually these networks consist of several LAN segments connected by bridges. The topological LAN design bi-level problem consists on assigning users to clusters and the union of clusters by bridges in order to obtain a minimum response time network with minimum connection cost. Therefore, the decision of optimally assigning users to clusters will be made by the leader and the follower will make the decision of connecting all the clusters while forming a spanning tree. In this paper, we propose a genetic algorithm for solving the bi-level topological design of a Local Access Network. Our solution method considers the Stackelberg equilibrium to solve the bi-level problem. The Stackelberg-Genetic algorithm procedure deals with the fact that the follower's problem cannot be optimally solved in a straightforward manner. The computational results obtained from two different sets of instances show that the performance of the developed algorithm is efficient and that it is more suitable for solving the bi-level problem than a previous Nash-Genetic approach.
An algorithm for solving the system-level problem in multilevel optimization
NASA Technical Reports Server (NTRS)
Balling, R. J.; Sobieszczanski-Sobieski, J.
1994-01-01
A multilevel optimization approach which is applicable to nonhierarchic coupled systems is presented. The approach includes a general treatment of design (or behavior) constraints and coupling constraints at the discipline level through the use of norms. Three different types of norms are examined: the max norm, the Kreisselmeier-Steinhauser (KS) norm, and the 1(sub p) norm. The max norm is recommended. The approach is demonstrated on a class of hub frame structures which simulate multidisciplinary systems. The max norm is shown to produce system-level constraint functions which are non-smooth. A cutting-plane algorithm is presented which adequately deals with the resulting corners in the constraint functions. The algorithm is tested on hub frames with increasing number of members (which simulate disciplines), and the results are summarized.
Use of the particle swarm optimization algorithm for second order design of levelling networks
NASA Astrophysics Data System (ADS)
Yetkin, Mevlut; Inal, Cevat; Yigit, Cemal Ozer
2009-08-01
The weight problem in geodetic networks can be dealt with as an optimization procedure. This classic problem of geodetic network optimization is also known as second-order design. The basic principles of geodetic network optimization are reviewed. Then the particle swarm optimization (PSO) algorithm is applied to a geodetic levelling network in order to solve the second-order design problem. PSO, which is an iterative-stochastic search algorithm in swarm intelligence, emulates the collective behaviour of bird flocking, fish schooling or bee swarming, to converge probabilistically to the global optimum. Furthermore, it is a powerful method because it is easy to implement and computationally efficient. Second-order design of a geodetic levelling network using PSO yields a practically realizable solution. It is also suitable for non-linear matrix functions that are very often encountered in geodetic network optimization. The fundamentals of the method and a numeric example are given.
A heuristic re-mapping algorithm reducing inter-level communication in SAMR applications.
Steensland, Johan; Ray, Jaideep
2003-07-01
This paper aims at decreasing execution time for large-scale structured adaptive mesh refinement (SAMR) applications by proposing a new heuristic re-mapping algorithm and experimentally showing its effectiveness in reducing inter-level communication. Tests were done for five different SAMR applications. The overall goal is to engineer a dynamically adaptive meta-partitioner capable of selecting and configuring the most appropriate partitioning strategy at run-time based on current system and application state. Such a metapartitioner can significantly reduce execution times for general SAMR applications. Computer simulations of physical phenomena are becoming increasingly popular as they constitute an important complement to real-life testing. In many cases, such simulations are based on solving partial differential equations by numerical methods. Adaptive methods are crucial to efficiently utilize computer resources such as memory and CPU. But even with adaption, the simulations are computationally demanding and yield huge data sets. Thus parallelization and the efficient partitioning of data become issues of utmost importance. Adaption causes the workload to change dynamically, calling for dynamic (re-) partitioning to maintain efficient resource utilization. The proposed heuristic algorithm reduced inter-level communication substantially. Since the complexity of the proposed algorithm is low, this decrease comes at a relatively low cost. As a consequence, we draw the conclusion that the proposed re-mapping algorithm would be useful to lower overall execution times for many large SAMR applications. Due to its usefulness and its parameterization, the proposed algorithm would constitute a natural and important component of the meta-partitioner.
An Overview of GPM At-Launch Level 2 Precipitation Algorithms (Invited)
NASA Astrophysics Data System (ADS)
Munchak, S. J.; Meneghini, R.; Kummerow, C. D.; Olson, W. S.
2013-12-01
The Global Precipitation Measurement core satellite will carry the most advanced array of precipitation sensing instruments yet flown in space, the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). Algorithms to convert the measurements from these instruments to precipitation rates have been developed and tested with data from aircraft instruments, physical model simulations, and existing satellites. These algorithms build upon the heritage of the Tropical Rainfall Measuring Mission (TRMM) algorithms to take advantage of the additional frequencies probed by GMI and DPR. As with TRMM, three instrument-specific level 2 precipitation products will be available: Radar-only, radiometer-only, and combined radar-radiometer. The radar-only product will be further subdivided into three subproducts: Ku-band-only (245 km swath), Ka-band-only (120 km swath with enhanced sensitivity), and Ku-Ka (120 km swath). The dual-frequency algorithm will provide enhanced estimation of rainfall rates and microphysical parameters such as mean raindrop size and phase identification relative to single-frequency products. The GMI precipitation product will be based upon a Bayesian algorithm that seeks to match observed brightness against those in a database. After launch, this database will be populated with observations from the GPM Core Observatory, but the at-launch database consists of profiles observed by TRMM, CloudSat, ground radars, and is augmented by model data fields to facilitate the generation of databases at non-observed frequencies. Ancillary data is used to subset the database by surface temperature, column water vapor, and surface type. This algorithm has been tested with data from the Special Sensor Microwave Imager/Sounder and comparisons with ground-based radar mosaic rainfall (NMQ) will be presented. The combined GMI-DPR algorithm uses an ensemble filtering approach to create and adjust many solutions (owing to different assumptions about the
NASA Astrophysics Data System (ADS)
Funabiki, Shigeyuki; Tanaka, Toshihiko; Fujii, Toshinori
A new optimization method of the electric power leveling system using an SMES is proposed. The SMES is parallelly connected with rolling mills in steel works. The leveling control is based on fuzzy reasoning. The SMES capacity and the scaling factors of the fuzzy controller will be optimized so that the power leveling control can be achieved and then the total cost of the added SMES cost and reduced contract electricity rate becomes lower. The optimization is carried out using the genetic algorithm and the cost reduction of 7.76 billion yen can be achieved. It is confirmed by the power leveling simulation that the proposed optimization method is very effective for designing the power leveling system.
Weighted least-squares algorithm for phase unwrapping based on confidence level in frequency domain
NASA Astrophysics Data System (ADS)
Wang, Shaohua; Yu, Jie; Yang, Cankun; Jiao, Shuai; Fan, Jun; Wan, Yanyan
2015-12-01
Phase unwrapping is a key step in InSAR (Synthetic Aperture Radar Interferometry) processing, and its result may directly affect the accuracy of DEM (Digital Elevation Model) and ground deformation. However, the decoherence phenomenon such as shadows and layover, in the area of severe land subsidence where the terrain is steep and the slope changes greatly, will cause error transmission in the differential wrapped phase information, leading to inaccurate unwrapping phase. In order to eliminate the effect of the noise and reduce the effect of less sampling which caused by topographical factors, a weighted least-squares method based on confidence level in frequency domain is used in this study. This method considered to express the terrain slope in the interferogram as the partial phase frequency in range and azimuth direction, then integrated them into the confidence level. The parameter was used as the constraints of the nonlinear least squares phase unwrapping algorithm, to smooth the un-requirements unwrapped phase gradient and improve the accuracy of phase unwrapping. Finally, comparing with interferometric data of the Beijing subsidence area obtained from TerraSAR verifies that the algorithm has higher accuracy and stability than the normal weighted least-square phase unwrapping algorithms, and could consider to terrain factors.
NASA Astrophysics Data System (ADS)
Zhao, Tao; Hwang, Feng-Nan; Cai, Xiao-Chuan
2016-07-01
We consider a quintic polynomial eigenvalue problem arising from the finite volume discretization of a quantum dot simulation problem. The problem is solved by the Jacobi-Davidson (JD) algorithm. Our focus is on how to achieve the quadratic convergence of JD in a way that is not only efficient but also scalable when the number of processor cores is large. For this purpose, we develop a projected two-level Schwarz preconditioned JD algorithm that exploits multilevel domain decomposition techniques. The pyramidal quantum dot calculation is carefully studied to illustrate the efficiency of the proposed method. Numerical experiments confirm that the proposed method has a good scalability for problems with hundreds of millions of unknowns on a parallel computer with more than 10,000 processor cores.
A conflict-free, path-level parallelization approach for sequential simulation algorithms
NASA Astrophysics Data System (ADS)
Rasera, Luiz Gustavo; Machado, Péricles Lopes; Costa, João Felipe C. L.
2015-07-01
Pixel-based simulation algorithms are the most widely used geostatistical technique for characterizing the spatial distribution of natural resources. However, sequential simulation does not scale well for stochastic simulation on very large grids, which are now commonly found in many petroleum, mining, and environmental studies. With the availability of multiple-processor computers, there is an opportunity to develop parallelization schemes for these algorithms to increase their performance and efficiency. Here we present a conflict-free, path-level parallelization strategy for sequential simulation. The method consists of partitioning the simulation grid into a set of groups of nodes and delegating all available processors for simulation of multiple groups of nodes concurrently. An automated classification procedure determines which groups are simulated in parallel according to their spatial arrangement in the simulation grid. The major advantage of this approach is that it does not require conflict resolution operations, and thus allows exact reproduction of results. Besides offering a large performance gain when compared to the traditional serial implementation, the method provides efficient use of computational resources and is generic enough to be adapted to several sequential algorithms.
NASA Technical Reports Server (NTRS)
Leutenegger, Scott T.; Horton, Graham
1994-01-01
Recently the Multi-Level algorithm was introduced as a general purpose solver for the solution of steady state Markov chains. In this paper, we consider the performance of the Multi-Level algorithm for solving Nearly Completely Decomposable (NCD) Markov chains, for which special-purpose iteractive aggregation/disaggregation algorithms such as the Koury-McAllister-Stewart (KMS) method have been developed that can exploit the decomposability of the the Markov chain. We present experimental results indicating that the general-purpose Multi-Level algorithm is competitive, and can be significantly faster than the special-purpose KMS algorithm when Gauss-Seidel and Gaussian Elimination are used for solving the individual blocks.
Utilization of PSO algorithm in estimation of water level change of Lake Beysehir
NASA Astrophysics Data System (ADS)
Buyukyildiz, Meral; Tezel, Gulay
2015-12-01
In this study, unlike backpropagation algorithm which gets local best solutions, the usefulness of particle swarm optimization (PSO) algorithm, a population-based optimization technique with a global search feature, inspired by the behavior of bird flocks, in determination of parameters of support vector machines (SVM) and adaptive network-based fuzzy inference system (ANFIS) methods was investigated. For this purpose, the performances of hybrid PSO-ɛ support vector regression (PSO-ɛSVR) and PSO-ANFIS models were studied to estimate water level change of Lake Beysehir in Turkey. The change in water level was also estimated using generalized regression neural network (GRNN) method, an iterative training procedure. Root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2) were used to compare the obtained results. Efforts were made to estimate water level change (L) using different input combinations of monthly inflow-lost flow (I), precipitation (P), evaporation (E), and outflow (O). According to the obtained results, the other methods except PSO-ANN generally showed significantly similar performances to each other. PSO-ɛSVR method with the values of minMAE = 0.0052 m, maxMAE = 0.04 m, and medianMAE = 0.0198 m; minRMSE = 0.0070 m, maxRMSE = 0.0518 m, and medianRMSE = 0.0241 m; minR 2 = 0.9169, maxR 2 = 0.9995, medianR 2 = 0.9909 for the I-P-E-O combination in testing period became superior in forecasting water level change of Lake Beysehir than the other methods. PSO-ANN models were the least successful models in all combinations.
Status of the MODIS Level 1B Algorithms and Calibration Tables
NASA Technical Reports Server (NTRS)
Xiong, X; Salomonson, V V; Kuyper, J; Tan, L; Chiang, K; Sun, J; Barnes, W L
2005-01-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and Aqua satellites, launched in December 1999 and May 2002, respectively. The MODIS Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) reflectance factors for the sensor's reflective solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the MODIS L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the MODIS collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.
Terra and Aqua moderate-resolution imaging spectroradiometer collection 6 level 1B algorithm
NASA Astrophysics Data System (ADS)
Toller, Gary; Xiong, Xiaoxiong; Sun, Junqiang; Wenny, Brian N.; Geng, Xu; Kuyper, James; Angal, Amit; Chen, Hongda; Madhavan, Sriharsha; Wu, Aisheng
2013-01-01
The moderate-resolution imaging spectroradiometer (MODIS) was launched on the Terra spacecraft on Dec.18, 1999 and on Aquaon May 4, 2002. The data acquired by these instruments have contributed to the long-term climate data record for more than a decade and represent a key component of NASA's Earth observing system. Each MODIS instrument observes nearly the whole Earth each day, enabling the scientific characterization of the land, ocean, and atmosphere. The MODIS Level 1B (L1B) algorithms input uncalibrated geo-located observations and convert instrument response into calibrated reflectance and radiance, which are used to generate science data products. The instrument characterization needed to run the L1B code is currently implemented using time-dependent lookup tables. The MODIS characterization support team, working closely with the MODIS Science Team, has improved the product quality with each data reprocessing. We provide an overview of the new L1B algorithm release, designated collection 6. Recent improvements made as a consequence of on-orbit calibration, on-orbit analyses, and operational considerations are described. Instrument performance and the expected impact of L1B changes on the collection 6 L1B products are discussed.
TES Level 1 Algorithms: Interferogram Processing, Geolocation, Radiometric, and Spectral Calibration
NASA Technical Reports Server (NTRS)
Worden, Helen; Beer, Reinhard; Bowman, Kevin W.; Fisher, Brendan; Luo, Mingzhao; Rider, David; Sarkissian, Edwin; Tremblay, Denis; Zong, Jia
2006-01-01
The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.
Level 1 In-Flight Radiometric Calibration and Characterization Algorithm Theoretical Basis
NASA Technical Reports Server (NTRS)
Bruegge, C.; Chrien, N.; Diner, D.
2000-01-01
This Algorithm Theoretical Basis (ATB) document describes the algorithms which operate at the Multi-angle Imaging SpectroRadiometer (MISR) Science Computing Facility (SCF) as part of the In-flight Radiometric Calibration and characterization (IFRCC) subsystem.
An overview of the CATS level 1 processing algorithms and data products
NASA Astrophysics Data System (ADS)
Yorks, J. E.; McGill, M. J.; Palm, S. P.; Hlavka, D. L.; Selmer, P. A.; Nowottnick, E. P.; Vaughan, M. A.; Rodier, S. D.; Hart, W. D.
2016-05-01
The Cloud-Aerosol Transport System (CATS) is an elastic backscatter lidar that was launched on 10 January 2015 to the International Space Station (ISS). CATS provides both space-based technology demonstrations for future Earth Science missions and operational science measurements. This paper outlines the CATS Level 1 data products and processing algorithms. Initial results and validation data demonstrate the ability to accurately detect optically thin atmospheric layers with 1064 nm nighttime backscatter as low as 5.0E-5 km-1 sr-1. This sensitivity, along with the orbital characteristics of the ISS, enables the use of CATS data for cloud and aerosol climate studies. The near-real-time downlinking and processing of CATS data are unprecedented capabilities and provide data that have applications such as forecasting of volcanic plume transport for aviation safety and aerosol vertical structure that will improve air quality health alerts globally.
Yu, Zhenhua; Fu, Xiao; Cai, Yuanli; Vuran, Mehmet C
2011-01-01
A reliable energy-efficient multi-level routing algorithm in wireless sensor networks is proposed. The proposed algorithm considers the residual energy, number of the neighbors and centrality of each node for cluster formation, which is critical for well-balanced energy dissipation of the network. In the algorithm, a knowledge-based inference approach using fuzzy Petri nets is employed to select cluster heads, and then the fuzzy reasoning mechanism is used to compute the degree of reliability in the route sprouting tree from cluster heads to the base station. Finally, the most reliable route among the cluster heads can be constructed. The algorithm not only balances the energy load of each node but also provides global reliability for the whole network. Simulation results demonstrate that the proposed algorithm effectively prolongs the network lifetime and reduces the energy consumption. PMID:22163802
SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation
NASA Technical Reports Server (NTRS)
Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann
2011-01-01
ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.
CT liver volumetry using geodesic active contour segmentation with a level-set algorithm
NASA Astrophysics Data System (ADS)
Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard
2010-03-01
Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.
Level 3 trigger algorithm and Hardware Platform for the HADES experiment
NASA Astrophysics Data System (ADS)
Kirschner, Daniel Georg; Agakishiev, Geydar; Liu, Ming; Perez, Tiago; Kühn, Wolfgang; Pechenov, Vladimir; Spataro, Stefano
2009-01-01
A next generation real time trigger method to improve the enrichment of lepton events in the High Acceptance DiElectron Spectrometer (HADES) trigger system has been developed. In addition, a flexible Hardware Platform (Gigabit Ethernet-Multi-Node, GE-MN) was developed to implement and test the trigger method. The trigger method correlates the ring information of the HADES Ring Imaging Cherenkov (RICH) detector with the fired wires (drift cells) of the HADES Mini Drift Chamber (MDC) detector. It is demonstrated that this Level 3 trigger method can enhance the number of events which contain leptons by a factor of up to 50 at efficiencies above 80%. The performance of the correlation method in terms of the events analyzed per second has been studied with the GE-MN prototype in a lab test setup by streaming previously recorded experiment data to the module. This paper is a compilation from Kirschner [Level 3 trigger algorithm and Hardware Platform for the HADES experiment, Ph.D. Thesis, II. Physikalisches Institut der Justus-Liebig-Universität Gießen, urn:nbn:de:hebis:26-opus-50784, October 2007 [1
Intelligence System for Diagnosis Level of Coronary Heart Disease with K-Star Algorithm
Kusnanto, Hari; Herianto, Herianto
2016-01-01
Objectives Coronary heart disease is the leading cause of death worldwide, and it is important to diagnose the level of the disease. Intelligence systems for diagnosis proved can be used to support diagnosis of the disease. Unfortunately, most of the data available between the level/type of coronary heart disease is unbalanced. As a result system performance is low. Methods This paper proposes an intelligence systems for the diagnosis of the level of coronary heart disease taking into account the problem of data imbalance. The first stage of this research was preprocessing, which included resampled non-stratified random sampling (R), the synthetic minority over-sampling technique (SMOTE), clean data out of range attribute (COR), and remove duplicate (RD). The second step was the sharing of data for training and testing using a k-fold cross-validation model and training multiclass classification by the K-star algorithm. The third step was performance evaluation. The proposed system was evaluated using the performance parameters of sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), area under the curve (AUC) and F-measure. Results The results showed that the proposed system provides an average performance with sensitivity of 80.1%, specificity of 95%, PPV of 80.1%, NPV of 95%, AUC of 87.5%, and F-measure of 80.1%. Performance of the system without consideration of data imbalance provide showed sensitivity of 53.1%, specificity of 88,3%, PPV of 53.1%, NPV of 88.3%, AUC of 70.7%, and F-measure of 53.1%. Conclusions Based on these results it can be concluded that the proposed system is able to deliver good performance in the category of classification. PMID:26893948
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui
2016-01-01
The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the
NASA Astrophysics Data System (ADS)
Smarda, M.; Alexopoulou, E.; Mazioti, A.; Kordolaimi, S.; Ploussi, A.; Priftis, K.; Efstathopoulos, E.
2015-09-01
Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our department's 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions.
End-to-End Design, Development and Testing of GOES-R Level 1 and 2 Algorithms
NASA Astrophysics Data System (ADS)
Zaccheo, T.; Copeland, A.; Steinfelt, E.; Van Rompay, P.; Werbos, A.
2012-12-01
GOES-R is the next generation of the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellite (GOES) System, and it represents a new technological era in operational geostationary environmental satellite systems. GOES-R will provide advanced products, based on government-supplied algorithms, which describe the state of the atmosphere, land, and oceans over the Western Hemisphere. The Harris GOES-R Core Ground Segment (GS) Team will provide the ground processing software and infrastructure needed to produce and distribute these data products. As part of this effort, new or updated Level 1b and Level 2+ algorithms will be deployed in the GOES-R Product Generation (PG) Element. In this work, we describe the general approach currently being employed to migrate these Level 1b (L1b) and Level 2+ (L2+) GOES-R PG algorithms from government-provided scientific descriptions to their implementation as integrated software, and provide an overview of how Product Generation software works with the other elements of the Ground Segment to produce Level 1/Level 2+ end-products. In general, GOES-R L1b algorithms ingest reformatted raw sensor data and ancillary information to produce geo-located GOES-R L1b data, and GOES-R L2+ algorithms ingest L1b data and other ancillary/auxiliary/intermediate information to produce L2+ products such as aerosol optical depth, rainfall rate, derived motion winds, and snow cover. In this presentation we provide an overview of the Algorithm development life cycle, the common Product Generation software architecture, and the common test strategies used to verify/validate the scientific implementation. This work will highlight the Software Integration and Test phase of the software life-cycle and the suite of automated test/analysis tools developed to insure the implemented algorithms meet desired reproducibility. As part of this discussion we will summarize the results of our algorithm testing to date
Density-matrix renormalization group algorithm with multi-level active space.
Ma, Yingjin; Wen, Jing; Ma, Haibo
2015-07-21
The density-matrix renormalization group (DMRG) method, which can deal with a large active space composed of tens of orbitals, is nowadays widely used as an efficient addition to traditional complete active space (CAS)-based approaches. In this paper, we present the DMRG algorithm with a multi-level (ML) control of the active space based on chemical intuition-based hierarchical orbital ordering, which is called as ML-DMRG with its self-consistent field (SCF) variant ML-DMRG-SCF. Ground and excited state calculations of H2O, N2, indole, and Cr2 with comparisons to DMRG references using fixed number of kept states (M) illustrate that ML-type DMRG calculations can obtain noticeable efficiency gains. It is also shown that the orbital re-ordering based on hierarchical multiple active subspaces may be beneficial for reducing computational time for not only ML-DMRG calculations but also DMRG ones with fixed M values. PMID:26203012
NASA Astrophysics Data System (ADS)
von Fischer, Joseph; Salo, Jessica; Griebenow, Claire; Bischak, Linde; Cooley, Daniel; Ham, Jay; Schumacher, Russ
2013-04-01
Methane (CH4) is an important greenhouse gas that has 70x greater heat forcing per molecule than CO2 over its ~10 year atmospheric residence time. Given this short residence time, there has been a surge of interest in mitigating anthropogenic CH4 sources because they will have a more immediate effect on warming rates. Recent observations of CH4 concentrations around the city of Boston reveal that natural gas distribution systems can have a very large number of leaks. However, there are a number of conceptual and practical challenges associated with interpretation of CH4 data gathered by car at the street level. In this presentation, we detail our efforts to develop an "algorithm" or set of standard practices for interpreting these patterns based on our own findings. At the most basic, we have evaluated approaches for vehicle driving patterns and management of the raw data. We also identify techniques for evaluating data quality and discerning when elevated CH4 may be due to other vehicles (e.g., CNG-powered city buses). We then compare methods for identifying "peaks" in CH4 concentration, and we discuss several approaches for relating concentration, space and wind data to emission rates. Finally, we provide some considerations for how the data from individual peaks might be aggregated to larger spatial scales.
Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.
Thompson, Aidan Patrick; Schultz, Peter Andrew; Crozier, Paul; Moore, Stan Gerald; Swiler, Laura Painton; Stephens, John Adam; Trott, Christian Robert; Foiles, Stephen Martin; Tucker, Garritt J.
2014-09-01
This report summarizes the result of LDRD project 12-0395, titled "Automated Algorithms for Quantum-level Accuracy in Atomistic Simulations." During the course of this LDRD, we have developed an interatomic potential for solids and liquids called Spectral Neighbor Analysis Poten- tial (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The SNAP coef- ficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. Global optimization methods in the DAKOTA software package are used to seek out good choices of hyperparameters that define the overall structure of the SNAP potential. FitSnap.py, a Python-based software pack- age interfacing to both LAMMPS and DAKOTA is used to formulate the linear regression problem, solve it, and analyze the accuracy of the resultant SNAP potential. We describe a SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties. Most significantly, in contrast to existing tantalum potentials, SNAP correctly predicts the Peierls barrier for screw dislocation motion. We also present results from SNAP potentials generated for indium phosphide (InP) and silica (SiO 2 ). We describe efficient algorithms for calculating SNAP forces and energies in molecular dynamics simulations using massively parallel computers
Bieberle, M.; Hampel, U.
2015-01-01
Tomographic image reconstruction is based on recovering an object distribution from its projections, which have been acquired from all angular views around the object. If the angular range is limited to less than 180° of parallel projections, typical reconstruction artefacts arise when using standard algorithms. To compensate for this, specialized algorithms using a priori information about the object need to be applied. The application behind this work is ultrafast limited-angle X-ray computed tomography of two-phase flows. Here, only a binary distribution of the two phases needs to be reconstructed, which reduces the complexity of the inverse problem. To solve it, a new reconstruction algorithm (LSR) based on the level-set method is proposed. It includes one force function term accounting for matching the projection data and one incorporating a curvature-dependent smoothing of the phase boundary. The algorithm has been validated using simulated as well as measured projections of known structures, and its performance has been compared to the algebraic reconstruction technique and a binary derivative of it. The validation as well as the application of the level-set reconstruction on a dynamic two-phase flow demonstrated its applicability and its advantages over other reconstruction algorithms. PMID:25939623
Initial condition for efficient mapping of level set algorithms on many-core architectures
NASA Astrophysics Data System (ADS)
Tornai, Gábor János; Cserey, György
2014-12-01
In this paper, we investigated the effect of adding more small curves to the initial condition which determines the required number of iterations of a fast level set (LS) evolution. As a result, we discovered two new theorems and developed a proof on the worst case of the required number of iterations. Furthermore, we found that these kinds of initial conditions fit well to many-core architectures. To show this, we have included two case studies which are presented on different platforms. One runs on a graphical processing unit (GPU) and the other is executed on a cellular nonlinear network universal machine (CNN-UM). With the new initial conditions, the steady-state solutions of the LS are reached in less than eight iterations depending on the granularity of the initial condition. These dense iterations can be calculated very quickly on many-core platforms according to the two case studies. In the case of the proposed dense initial condition on GPU, there is a significant speedup compared to the sparse initial condition in all cases since our dense initial condition together with the algorithm utilizes the properties of the underlying architecture. Therefore, greater performance gain can be achieved (up to 18 times speedup compared to the sparse initial condition on GPU). Additionally, we have validated our concept against numerically approximated LS evolution of standard flows (mean curvature, Chan-Vese, geodesic active regions). The dice indexes between the fast LS evolutions and the evolutions of the numerically approximated partial differential equations are in the range of 0.99±0.003.
Improving Limit Surface Search Algorithms in RAVEN Using Acceleration Schemes: Level II Milestone
Alfonsi, Andrea; Rabiti, Cristian; Mandelli, Diego; Cogliati, Joshua Joseph; Sen, Ramazan Sonat; Smith, Curtis Lee
2015-07-01
The RAVEN code is becoming a comprehensive tool to perform Probabilistic Risk Assessment (PRA); Uncertainty Quantification (UQ) and Propagation; and Verification and Validation (V&V). The RAVEN code is being developed to support the Risk-Informed Safety Margin Characterization (RISMC) pathway by developing an advanced set of methodologies and algorithms for use in advanced risk analysis. The RISMC approach uses system simulator codes applied to stochastic analysis tools. The fundamental idea behind this coupling approach to perturb (by employing sampling strategies) timing and sequencing of events, internal parameters of the system codes (i.e., uncertain parameters of the physics model) and initial conditions to estimate values ranges and associated probabilities of figures of merit of interest for engineering and safety (e.g. core damage probability, etc.). This approach applied to complex systems such as nuclear power plants requires performing a series of computationally expensive simulation runs. The large computational burden is caused by the large set of (uncertain) parameters characterizing those systems. Consequently, exploring the uncertain/parametric domain, with a good level of confidence, is generally not affordable, considering the limited computational resources that are currently available. In addition, the recent tendency to develop newer tools, characterized by higher accuracy and larger computational resources (if compared with the presently used legacy codes, that have been developed decades ago), has made this issue even more compelling. In order to overcome to these limitations, the strategy for the exploration of the uncertain/parametric space needs to use at best the computational resources focusing the computational effort in those regions of the uncertain/parametric space that are “interesting” (e.g., risk-significant regions of the input space) with respect the targeted Figures Of Merit (FOM): for example, the failure of the system
NASA Astrophysics Data System (ADS)
You, Seung-Han; Cho, Young Man; Hahn, Jin-Oh
2013-04-01
This study presents a component-level failure detection and identification (FDI) algorithm for a cascade mechanical system subsuming a plant driven by an actuator unit. The novelty of the FDI algorithm presented in this study is that it is able to discriminate failure occurring in the actuator unit, the sensor measuring the output of the actuator unit, and the plant driven by the actuator unit. The proposed FDI algorithm exploits the measurement of the actuator unit output together with its estimates generated by open-loop (OL) and closed-loop (CL) estimators to enable FDI at the component's level. In this study, the OL estimator is designed based on the system identification of the actuator unit. The CL estimator, which is guaranteed to be stable against variations in the plant, is synthesized based on the dynamics of the entire cascade system. The viability of the proposed algorithm is demonstrated using a hardware-in-the-loop simulation (HILS), which shows that it can detect and identify target failures reliably in the presence of plant uncertainties.
ERIC Educational Resources Information Center
Laakso, Mikko-Jussi; Myller, Niko; Korhonen, Ari
2009-01-01
In this paper, two emerging learning and teaching methods have been studied: collaboration in concert with algorithm visualization. When visualizations have been employed in collaborative learning, collaboration introduces new challenges for the visualization tools. In addition, new theories are needed to guide the development and research of the…
ERIC Educational Resources Information Center
Niaz, Mansoor; Robinson, William R.
It has been shown previously that many students solve chemistry problems using only algorithmic strategies and do not understand the chemical concepts on which the problems are based. It is plausible to suggest that if the information is presented in differing formats the cognitive demand of a problem changes. The main objective of this study…
NASA Astrophysics Data System (ADS)
Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.
2016-04-01
Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the
NASA Astrophysics Data System (ADS)
Gao, Min; Huang, Shutao; Zhong, Xia
2010-11-01
The establishment of multi-source database was designed to promote the informatics process of the geological disposal of High-level Radioactive Waste, the integration of multi-dimensional and multi-source information and its application are related to computer software and hardware. Based on the analysis of data resources in Beishan area, Gansu Province, and combined with GIS technologies and methods. This paper discusses the technical ideas of how to manage, fully share and rapidly retrieval the information resources in this area by using open source code GDAL and Quadtree algorithm, especially in terms of the characteristics of existing data resources, spatial data retrieval algorithm theory, programming design and implementation of the ideas.
NASA Astrophysics Data System (ADS)
Gao, Min; Huang, Shutao; Zhong, Xia
2009-09-01
The establishment of multi-source database was designed to promote the informatics process of the geological disposal of High-level Radioactive Waste, the integration of multi-dimensional and multi-source information and its application are related to computer software and hardware. Based on the analysis of data resources in Beishan area, Gansu Province, and combined with GIS technologies and methods. This paper discusses the technical ideas of how to manage, fully share and rapidly retrieval the information resources in this area by using open source code GDAL and Quadtree algorithm, especially in terms of the characteristics of existing data resources, spatial data retrieval algorithm theory, programming design and implementation of the ideas.
Sentinel-2 Level 2A Prototype Processor: Architecture, Algorithms And First Results
NASA Astrophysics Data System (ADS)
Muller-Wilm, Uwe; Louis, Jerome; Richter, Rudolf; Gascon, Ferran; Niezette, Marc
2013-12-01
Sen2Core is a prototype processor for Sentinel-2 Level 2A product processing and formatting. The processor is developed for and with ESA and performs the tasks of Atmospheric Correction and Scene Classification of Level 1C input data. Level 2A outputs are: Bottom-Of- Atmosphere (BOA) corrected reflectance images, Aerosol Optical Thickness-, Water Vapour-, Scene Classification maps and Quality indicators, including cloud and snow probabilities. The Level 2A Product Formatting performed by the processor follows the specification of the Level 1C User Product.
NASA Astrophysics Data System (ADS)
Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak
2010-02-01
This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.
On-line algorithm for ground-level ozone prediction with a mobile station
NASA Astrophysics Data System (ADS)
Kocijan, Juš; Gradišar, Dejan; Božnar, Marija Zlata; Grašič, Boštjan; Mlakar, Primož
2016-04-01
It is important to be able to predict high concentrations of tropospheric ozone and to inform the population about any violations of air-quality standards, as defined by international regulations. Although first-principle models that cover large geographical regions and different atmospheric layers are improving constantly, they typically still only cover geographical regions with a relatively low resolution. Such model predictions can be problematic for the micro-locations of a complex terrain, i.e., a terrain with a large geographical diversity or urban terrain. For such micro-locations, statistical models can be utilised. This paper presents a modelling and prediction algorithm that can be used in, or in accordance with, a mobile air-quality measurement station. Such a mobile station would enable the set-up of a statistical model and a relatively rapid access to the model's predictions for a specific geographical micro-location without a large quantity of historical of measurements. Uncertainty information about the model's predictions is also usually required. In addition, such a model can adapt to long-term changes, such as climate changes. In the paper we propose Gaussian-process models for the described modelling and prediction. In particular, we selected evolving Gaussian-process models that update on-line with the incoming measurement data. The proposed algorithm for the mobile air-quality measurement and the forecasting station is evaluated on measurements from five locations in Slovenia with different topographical and geographical properties. The obtained evaluation results confirm the feasibility of the concept.
Improvements in dark water, low light-level AOD retrievals in MISR operational algorithm
NASA Astrophysics Data System (ADS)
Witek, M. L.; Diner, D. J.; Garay, M. J.; Xu, F.
2015-12-01
Satellite remote sensing of aerosols is taking bold steps towards higher spatial resolutions, as evidenced by the newly released MODIS 3 km product and the soon to be released MISR 4.4 km product. Finer horizontal resolution allows for a better aerosol characterization in proximity to clouds—which is important for studying indirect aerosol effects—but also poses additional challenges due to various cloud artifact effects. It is therefore imperative to refine satellite algorithms to correctly interpret aerosol behavior in the proximity of clouds. For instance, MISR aerosol optical depth (AOD) retrievals frequently overestimate AODs in pristine oceanic areas, in particular close to Antarctica, as evidenced by comparison with Maritime Aerosol Network (MAN) observations. We trace the origin of this overestimation to stray light, or veiling light, being scattered more or less uniformly over the camera's field of view and reducing the contrast of the primary image. We found that the MISR-MODIS radiance difference in dark areas correlates with average scene brightness within the whole MISR camera field of view. A simple, single parameter model is proposed to effect the corrections. Collocated MISR/MODIS pixels are used to fit the parameter in the MISR nadir camera. For the off-nadir cameras two alternative approaches are employed that are based on MISR radiances and radiative transfer model calculations. These two methods are prone to higher uncertainties, but suggest somewhat increasing correction values for the longer focal length cameras. Finally, the empirical corrections applied in the operational MISR retrieval algorithm substantially decrease AODs in analyzed cases, and lead to closer agreement with MAN and MODIS, proving the efficacy of the developed procedure.
Umarova, Zhanat; Botayeva, Saule; Yegenova, Aliya; Usenova, Aisaule
2015-05-15
In the given article, the main thermodynamic aspects of the issue of modeling diffusion transfer in molecular sieves have been formulated. Dissipation function is used as a basic notion. The differential equation, connecting volume flow with the change of the concentration of catchable component has been derived. As a result, the expression for changing the concentration of the catchable component and the coefficient of membrane detecting has been received. As well, the system approach to describing the process of gases separation in ultra porous membranes has been realized and micro and meso-levels of mathematical modeling have been distinguished. The non-ideality of the shared system is primarily taken into consideration at the micro-level and the departure from the diffusion law of Fick has been taken into account. The calculation method of selectivity considering fractal structure of membranes has been developed at the meso level. The calculation algorithm and its software implementation have been suggested.
NASA Astrophysics Data System (ADS)
Baron, P.; Urban, J.; Sagawa, H.; Möller, J.; Murtagh, D. P.; Mendrok, J.; Dupuy, E.; Sato, T. O.; Ochiai, S.; Suzuki, K.; Manabe, T.; Nishibori, T.; Kikuchi, K.; Sato, R.; Takayanagi, M.; Murayama, Y.; Shiotani, M.; Kasai, Y.
2011-06-01
This paper describes the algorithms of the level-2 research (L2r) processing chain developed for the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES). The chain has been developed in parallel to the operational chain for conducting researches on calibration and retrieval algorithms. L2r chain products are available to the scientific community. The objective of version 2 is the retrieval of the vertical distribution of trace gases in the altitude range of 18-90 km. An theoretical error analysis is conducted to estimate the retrieval feasibility of key parameters of the processing: line-of-sight elevation tangent altitudes (or angles), temperature and O3 profiles. The line-of-sight tangent altitudes are retrieved between 20 and 50 km from the strong ozone (O3) line at 625.371 GHz, with low correlation with the O3 volume-mixing ratio and temperature retrieved profiles. Neglecting the non-linearity of the radiometric gain in the calibration procedure is the main systematic error. It is large for the retrieved temperature (between 5-10 K). Therefore, atmospheric pressure can not be derived from the retrieved temperature, and, then, in the altitude range where the line-of-sight tangent altitudes are retrieved, the retrieved trace gases profiles are found to be better represented on pressure levels than on altitude levels. The error analysis for the retrieved HOCl profile demonstrates that best results for inverting weak lines can be obtained by using narrow spectral windows. Future versions of the L2r algorithms will improve the temperature/pressure retrievals and also provide information in the upper tropospheric/lower stratospheric region (e.g., water vapor, ice content, O3) and on stratospheric and mesospheric line-of-sight winds.
NASA Astrophysics Data System (ADS)
Ribeiro, Vitor B.; Silva, Flávio A.; Oliveira, Julio C. R. F.; Franz, Lucas V.; Schneider, Eduardo O.; Moretti, Cleber; Ranzini, Stenio M.
2013-01-01
Today and next generation optical coherent systems rely more and more in DSP algorithms to improve capacity, spectral efficiency and fiber impairments mitigation. The amount of signal processing is remarkable, and because of that ASICs are preferable in order to comply with cost, power consumption and size, required in OIF 100G optical module standards. One important step in the ASIC development process is the validation of the DSP algorithms mathematical models in a high level language that consider HW characteristics and constrains. In this work we present, compare and evaluate in experimental data the mathematical model developed in Matlab and the SystemC model developed in C++. The DSP algorithms functionalities implemented were orthonormalization, CD equalizer, clock recovery, dynamic equalizer, frequency offset and phase estimation. The SystemC model considers clock signals, reset/enable structures, parallelization, finite fixed-point operations and structures that are closer to the ASIC HW implementation; due to these restrictions the performance is not as good as the mathematical modeling. The DSP algorithms models are evaluated in two 112 Gbit/s DP-QPSK experimental scenarios. In the first scenario the models are evaluated in back-to-back with ASE noise loading; in the second scenario the models are compared in a 226km optical fiber recirculation loop, with 80x112 Gbit/s DP-QPSK channels (8.96 Tbit/s). In the back-to-back experiment the OSNR penalty from the mathematical model to the SystemC model is only 1,0dB and in the recirculation loop the maximum reach is 2,600 km and 2,200 km for the Matlab and SystemC models respectively.
NASA Astrophysics Data System (ADS)
Quan, Haiyang; Wu, Fan; Hou, Xi
2015-10-01
New method for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution is proposed. It is based on basic iterative scheme and accelerates the Gauss-Seidel method by introducing an acceleration parameter. This modified Successive Over-relaxation (SOR) is effective for solving the rotationally asymmetric components with pixel-level spatial resolution, without the usage of a fitting procedure. Compared to the Jacobi and Gauss-Seidel method, the modified SOR method with an optimal relaxation factor converges much faster and saves more computational costs and memory space without reducing accuracy. It has been proved by real experimental results.
ERIC Educational Resources Information Center
Végh, Ladislav
2016-01-01
The first data structure that first-year undergraduate students learn during the programming and algorithms courses is the one-dimensional array. For novice programmers, it might be hard to understand different algorithms on arrays (e.g. searching, mirroring, sorting algorithms), because the algorithms dynamically change the values of elements. In…
NASA Astrophysics Data System (ADS)
Siddeq, M. M.; Rodrigues, M. A.
2015-09-01
Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.
Comparison of algorithms for the calculation of molecular vibrational level densities
NASA Astrophysics Data System (ADS)
Hansen, K.
2008-05-01
Level densities of vibrational degrees of freedom are calculated numerically with formulas based on the inversion of the canonical vibrational partition function. The calculated level densities are compared with other approximate equations from literature and with the exact Beyer-Swinehart values, for which a simplified but equivalent version is given. All approximate equations agree at high excitation energies, but our results are vastly superior at low energies for large molecules. The results presented here are therefore of particular relevance for thermal processes of very large molecules, e.g., of biological nature, for which the exact state counting can be prohibitively slow. Furthermore, it is valid for situations where anharmonic motion significantly influences the thermal properties.
NASA Astrophysics Data System (ADS)
Baron, P.; Urban, J.; Sagawa, H.; Möller, J.; Murtagh, D. P.; Mendrok, J.; Dupuy, E.; Sato, T. O.; Ochiai, S.; Suzuki, K.; Manabe, T.; Nishibori, T.; Kikuchi, K.; Sato, R.; Takayanagi, M.; Murayama, Y.; Shiotani, M.; Kasai, Y.
2011-10-01
This paper describes the algorithms of the level-2 research (L2r) processing chain developed for the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES). The chain has been developed in parallel to the operational chain for conducting researches on calibration and retrieval algorithms. L2r chain products are available to the scientific community. The objective of version 2 is the retrieval of the vertical distribution of trace gases in the altitude range of 18-90 km. A theoretical error analysis is conducted to estimate the retrieval feasibility of key parameters of the processing: line-of-sight elevation tangent altitudes (or angles), temperature and ozone profiles. While pointing information is often retrieved from molecular oxygen lines, there is no oxygen line in the SMILES spectra, so the strong ozone line at 625.371 GHz has been chosen. The pointing parameters and the ozone profiles are retrieved from the line wings which are measured with high signal to noise ratio, whereas the temperature profile is retrieved from the optically thick line center. The main systematic component of the retrieval error was found to be the neglect of the non-linearity of the radiometric gain in the calibration procedure. This causes a temperature retrieval error of 5-10 K. Because of these large temperature errors, it is not possible to construct a reliable hydrostatic pressure profile. However, as a consequence of the retrieval of pointing parameters, pressure induced errors are significantly reduced if the retrieved trace gas profiles are represented on pressure levels instead of geometric altitude levels. Further, various setups of trace gas retrievals have been tested. The error analysis for the retrieved HOCl profile demonstrates that best results for inverting weak lines can be obtained by using narrow spectral windows.
Chapman, Brian E; Lee, Sean; Kang, Hyunseok Peter; Chapman, Wendy W
2011-10-01
In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state of the diagnosis (uncertainty present or absent), the temporal state of an identified pulmonary embolus (acute or chronic), and the technical quality state of the exam (diagnostic or not diagnostic). Gold standard answers for each question were determined from the consensus classifications of three human annotators. peFinder results were compared to naive Bayes' classifiers using unigrams and bigrams. The sensitivities (and positive predictive values) for peFinder were 0.98(0.83), 0.86(0.96), 0.94(0.93), and 0.60(0.90) for disease state, quality state, certainty state, and temporal state respectively, compared to 0.68(0.77), 0.67(0.87), 0.62(0.82), and 0.04(0.25) for the naive Bayes' classifier using unigrams, and 0.75(0.79), 0.52(0.69), 0.59(0.84), and 0.04(0.25) for the naive Bayes' classifier using bigrams. PMID:21459155
NASA Astrophysics Data System (ADS)
Pegueroles, Josep R.; Alins, Juan J.; de la Cruz, Luis J.; Mata, Jorge
2001-07-01
MPEG family codecs generate variable-bit-rate (VBR) compressed video with significant multiple-time-scale bit rate variability. Smoothing techniques remove the periodic fluctuations generated by the codification modes. However, global efficiency concerning network resource allocation remains low due to scene-time-scale variability. RCBR techniques provide suitable means to achieving higher efficiency. Among all RCBR techniques described in literature, 2RCBR mechanism seems to be especially suitable for video-on demand. The method takes advantage of the knowledge of the stored video to calculate the renegotiation intervals and of the client buffer memory to perform work-ahead buffering techniques. 2RCBR achieves 100% bandwidth global efficiency with only two renegotiation levels. The algorithm is based on the study of the second derivative of the cumulative video sequence to find out sharp-sloped inflection points that point out changes in the scene complexity. Due to its nature, 2RCBR becomes very adequate to deliver MPEG2 scalable sequences into the network cause it can assure a constant bit rate to the base MPEG2 layer and use the higher rate intervals to deliver the enhanced MPEG2 layer. However, slight changes in the algorithm parameters must be introduced to attain an optimal behavior. This is verified by means of simulations on MPEG2 video patterns.
A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization
Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.; Laska, Jason A.; Sullivan, Blair D.
2016-10-20
This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less
A cascadic monotonic time-discretized algorithm for finite-level quantum control computation
NASA Astrophysics Data System (ADS)
Ditz, P.; Borzi`, A.
2008-03-01
A computer package (CNMS) is presented aimed at the solution of finite-level quantum optimal control problems. This package is based on a recently developed computational strategy known as monotonic schemes. Quantum optimal control problems arise in particular in quantum optics where the optimization of a control representing laser pulses is required. The purpose of the external control field is to channel the system's wavefunction between given states in its most efficient way. Physically motivated constraints, such as limited laser resources, are accommodated through appropriately chosen cost functionals. Program summaryProgram title: CNMS Catalogue identifier: ADEB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADEB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 770 No. of bytes in distributed program, including test data, etc.: 7098 Distribution format: tar.gz Programming language: MATLAB 6 Computer: AMD Athlon 64 × 2 Dual, 2:21 GHz, 1:5 GB RAM Operating system: Microsoft Windows XP Word size: 32 Classification: 4.9 Nature of problem: Quantum control Solution method: Iterative Running time: 60-600 sec
NASA Astrophysics Data System (ADS)
Pirayesh Neghab, Mohammadali; Haji, Rasoul
This study considers a two-level supply chain system consisting of one warehouse and a number of identical retailers. In this system, we incorporate transportation costs into inventory replenishment decisions. The transportation cost contains a fixed cost and a variable cost. We assume that the demand rate at each retailer is known and the demand is confined to a single item. First, we derive the total cost which is the sum of the holding and ordering cost at the warehouse and retailers as well as the transportation cost from the warehouse to retailers. Then, we propose a search algorithm to find the economic order quantities for the warehouse and retailers which minimize the total cost.
Fernandes, Edite M. G. P.
2015-01-01
This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as ‘erf’, is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. PMID:25875591
None, None
2015-09-28
Coulomb interaction between charged particles inside a bunch is one of the most importance collective effects in beam dynamics, becoming even more significant as the energy of the particle beam is lowered to accommodate analytical and low-Z material imaging purposes such as in the time resolved Ultrafast Electron Microscope (UEM) development currently underway at Michigan State University. In addition, space charge effects are the key limiting factor in the development of ultrafast atomic resolution electron imaging and diffraction technologies and are also correlated with an irreversible growth in rms beam emittance due to fluctuating components of the nonlinear electron dynamics.more » In the short pulse regime used in the UEM, space charge effects also lead to virtual cathode formation in which the negative charge of the electrons emitted at earlier times, combined with the attractive surface field, hinders further emission of particles and causes a degradation of the pulse properties. Space charge and virtual cathode effects and their remediation are core issues for the development of the next generation of high-brightness UEMs. Since the analytical models are only applicable for special cases, numerical simulations, in addition to experiments, are usually necessary to accurately understand the space charge effect. In this paper we will introduce a grid-free differential algebra based multiple level fast multipole algorithm, which calculates the 3D space charge field for n charged particles in arbitrary distribution with an efficiency of O(n), and the implementation of the algorithm to a simulation code for space charge dominated photoemission processes.« less
None, None
2015-09-28
Coulomb interaction between charged particles inside a bunch is one of the most importance collective effects in beam dynamics, becoming even more significant as the energy of the particle beam is lowered to accommodate analytical and low-Z material imaging purposes such as in the time resolved Ultrafast Electron Microscope (UEM) development currently underway at Michigan State University. In addition, space charge effects are the key limiting factor in the development of ultrafast atomic resolution electron imaging and diffraction technologies and are also correlated with an irreversible growth in rms beam emittance due to fluctuating components of the nonlinear electron dynamics. In the short pulse regime used in the UEM, space charge effects also lead to virtual cathode formation in which the negative charge of the electrons emitted at earlier times, combined with the attractive surface field, hinders further emission of particles and causes a degradation of the pulse properties. Space charge and virtual cathode effects and their remediation are core issues for the development of the next generation of high-brightness UEMs. Since the analytical models are only applicable for special cases, numerical simulations, in addition to experiments, are usually necessary to accurately understand the space charge effect. In this paper we will introduce a grid-free differential algebra based multiple level fast multipole algorithm, which calculates the 3D space charge field for n charged particles in arbitrary distribution with an efficiency of O(n), and the implementation of the algorithm to a simulation code for space charge dominated photoemission processes.
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
Algorithms for projecting a point onto a level surface of a continuous function on a compact set
NASA Astrophysics Data System (ADS)
Arutyunova, N. K.; Dulliev, A. M.; Zabotin, V. I.
2014-09-01
Given an equation f( x) = 0, the problem of finding its solution nearest to a given point is considered. In contrast to the authors' previous works dealing with this problem, exact algorithms are proposed assuming that the function f is continuous on a compact set. The convergence of the algorithms is proved, and their performance is illustrated with test examples.
Pantic, Igor; Dimitrijevic, Draga; Nesic, Dejan; Petrovic, Danica
2016-10-01
We demonstrate that a proapoptotic chemical agent, oxidopamine, induces dose dependent changes in chromatin textural patterns which can be quantified using the Gray level co-occurrence matrix (GLCM) method. Peripheral blood (heparin-pretreated) samples were treated with oxidopamine (6-OHDA, 6-hydroxydopamine) to achieve effective concentrations of 100, 200 and 300µM. The samples were smeared on microscope slides and fixated in methanol. The smears were stained using a modification of Feulgen method for DNA visualization. For each stained smear, a sample of 30 lymphocyte chromatin structures were visualized and analyzed. This way, textural parameters for a total of 120 nuclei micrographs were calculated. For each chromatin structure, five different GLCM features were calculated: angular second moment, GLCM entropy, inverse difference moment, GLCM correlation, and GLCM variance. Oxidopamine induced the rise of the values of GLCM entropy and variance, and the reduction of angular second moment, correlation, and inverse difference moment. The trends for GLCM parameter changes were found to be highly significant (p<0.001). These results indicate that GLCM mathematical algorithm might be successfully used in detection and evaluation of discrete early apoptotic structural changes in Feulgen-stained chromatin of peripheral blood lymphocytes that are not detectable using conventional microscopy/cell biology techniques.
Pantic, Igor; Dimitrijevic, Draga; Nesic, Dejan; Petrovic, Danica
2016-10-01
We demonstrate that a proapoptotic chemical agent, oxidopamine, induces dose dependent changes in chromatin textural patterns which can be quantified using the Gray level co-occurrence matrix (GLCM) method. Peripheral blood (heparin-pretreated) samples were treated with oxidopamine (6-OHDA, 6-hydroxydopamine) to achieve effective concentrations of 100, 200 and 300µM. The samples were smeared on microscope slides and fixated in methanol. The smears were stained using a modification of Feulgen method for DNA visualization. For each stained smear, a sample of 30 lymphocyte chromatin structures were visualized and analyzed. This way, textural parameters for a total of 120 nuclei micrographs were calculated. For each chromatin structure, five different GLCM features were calculated: angular second moment, GLCM entropy, inverse difference moment, GLCM correlation, and GLCM variance. Oxidopamine induced the rise of the values of GLCM entropy and variance, and the reduction of angular second moment, correlation, and inverse difference moment. The trends for GLCM parameter changes were found to be highly significant (p<0.001). These results indicate that GLCM mathematical algorithm might be successfully used in detection and evaluation of discrete early apoptotic structural changes in Feulgen-stained chromatin of peripheral blood lymphocytes that are not detectable using conventional microscopy/cell biology techniques. PMID:27424557
NASA Astrophysics Data System (ADS)
Wei, Chiang; Yeh, Hui-Chung; Chen, Yen-Chang
2015-04-01
This study assessed the classification of landslide areas by Genetic Algorithm of Operation Tree (GAOT) of Chen-Yu-Lan River upstream watershed of National Taiwan University Experimental Forest (NTUEF) after the Typhoon Morakot in 2009 using remotely and geological data. Landslides of 624.5 ha which accounting for 1.9% of total area were delineated with the threshold of slope (22°) and area size (1 hectare), 48 landslide sites were located in the upstream Chen-Yu-Lan watershed using FORMOSAT-II satellite imagery, the aerial photo and GIS related coverage. The five risk levels of these landslide areas was classified by the area, elevation, slope order, aspect, erosion order and geological factor order using the Simplicity Method suggested in the Technical Regulations for Soil and Water Conservation of Taiwan. If all the landslide sites were considered, the accuracy of classification using GAOT is 97.9%, superior than the K-means, Ward method, Shared Nearest Neighbor method, Maximum Likelihood Classifier and Bayesian Classifier; if 36 sites were used as training samples and the rest 12 sites were tested, the accuracy still can reach 81.3%. More geological data, anthropogenic influence and hydrological factors may be necessary for clarifying the landside area and the results benefit the assessment for future correction and management of the authorities.
Burgot, G; Burgot, J L
2000-10-01
The principles of two algorithms allowing the calculations of the concentration and activity levels of the different species during acid-base titrations in water are described. They simulate titrations at constant and variable ionic strengths respectively. They are designed so acid and base strengths, their concentrations and the titrant volume added can be chosen freely. The calculations are based on rigorous equations with a general scope. They are sufficiently compact to be processed on pocket calculators. The algorithms can easily simulate pH-metric, spectrophotometric, conductometric and calorimetric titrations, and hence allow determining concentrations and some physico-chemical constants related to the occurring chemical systems.
NASA Technical Reports Server (NTRS)
Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward
2011-01-01
The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November 2009, provides global maps of soil moisture and ocean salinity by measuring the L-band (1.4 GHz) emission of the Earth's surface with a spatial resolution of 40-50 km.Uncertainty in the retrieval of soilmoisture over large heterogeneous areas such as SMOS pixels is expected, due to the non-linearity of the relationship between soil moisture and the microwave emission. The current baseline soilmoisture retrieval algorithm adopted by SMOS and implemented in the SMOS Level 2 (SMOS L2) processor partially accounts for the sub-pixel heterogeneity of the land surface, by modelling the individual contributions of different pixel fractions to the overall pixel emission. This retrieval approach is tested in this study using airborne L-band data over an area the size of a SMOS pixel characterised by a mix Eucalypt forest and moderate vegetation types (grassland and crops),with the objective of assessing its ability to correct for the soil moisture retrieval error induced by the land surface heterogeneity. A preliminary analysis using a traditional uniform pixel retrieval approach shows that the sub-pixel heterogeneity of land cover type causes significant errors in soil moisture retrieval (7.7%v/v RMSE, 2%v/v bias) in pixels characterised by a significant amount of forest (40-60%). Although the retrieval approach adopted by SMOS partially reduces this error, it is affected by errors beyond the SMOS target accuracy, presenting in particular a strong dry bias when a fraction of the pixel is occupied by forest (4.1%v/v RMSE,-3.1%v/v bias). An extension to the SMOS approach is proposed that accounts for the heterogeneity of vegetation optical depth within the SMOS pixel. The proposed approach is shown to significantly reduce the error in retrieved soil moisture (2.8%v/v RMSE, -0.3%v/v bias) in pixels characterised by a critical amount of forest (40-60%), at the limited cost of only a crude estimate of the
NASA Technical Reports Server (NTRS)
Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Acker, James G. (Editor); Campbell, Janet W.; Blaisdell, John M.; Darzi, Michael
1995-01-01
The level-3 data products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are statistical data sets derived from level-2 data. Each data set will be based on a fixed global grid of equal-area bins that are approximately 9 x 9 sq km. Statistics available for each bin include the sum and sum of squares of the natural logarithm of derived level-2 geophysical variables where sums are accumulated over a binning period. Operationally, products with binning periods of 1 day, 8 days, 1 month, and 1 year will be produced and archived. From these accumulated values and for each bin, estimates of the mean, standard deviation, median, and mode may be derived for each geophysical variable. This report contains two major parts: the first (Section 2) is intended as a users' guide for level-3 SeaWiFS data products. It contains an overview of level-0 to level-3 data processing, a discussion of important statistical considerations when using level-3 data, and details of how to use the level-3 data. The second part (Section 3) presents a comparative statistical study of several binning algorithms based on CZCS and moored fluorometer data. The operational binning algorithms were selected based on the results of this study.
NASA Astrophysics Data System (ADS)
Bressan, L.; Tinti, S.
2012-05-01
Real-time detection of a tsunami on instrumental sea-level records is quite an important task for a Tsunami Warning System (TWS), and in case of alert conditions for an ongoing tsunami it is often performed by visual inspection in operational warning centres. In this paper we stress the importance of automatic detection algorithms and apply the TEDA (Tsunami Early Detection Algorithm) to identify tsunami arrivals of the 2011 Tohoku tsunami in a real-time virtual exercise. TEDA is designed to work at station level, that is on sea-level data of a single station, and was calibrated on data from the Adak island, Alaska, USA, tide-gauge station. Using the parameters' configuration devised for the Adak station, the TEDA has been applied to 123 coastal sea-level records from the coasts of the Pacific Ocean, which enabled us to evaluate the efficiency and sensitivity of the algorithm on a wide range of background conditions and of signal-to-noise ratios. The result is that TEDA is able to detect quickly the majority of the tsunami signals and therefore proves to have the potential for being a valid tool in the operational TWS practice.
NASA Astrophysics Data System (ADS)
Bosse, Stefan; Behrmann, Thomas
2011-06-01
We propose and demonstrate a design methodology for embedded systems satisfying low power requirements suitable for self-powered sensor and actuator nodes. This design methodology focuses on 1. smart energy management at runtime and 2. application-specific System-On- Chip (SoC) design at design time, contributing to low-power systems on both algorithmic and technology level. Smart energy management is performed spatially at runtime by a behaviour-based or state-action-driven selection from a set of different (implemented) algorithms classified by their demand of computation power, and temporally by varying data processing rates. It can be shown that power/energy consumption of an application-specific SoC design depends strongly on computation complexity. Signal and control processing is modelled on abstract level using signal flow diagrams. These signal flow graphs are mapped to Petri Nets to enable direct high-level synthesis of digital SoC circuits using a multi-process architecture with the Communicating-Sequential-Process model on execution level. Power analysis using simulation techniques on gatelevel provides input for the algorithmic selection during runtime of the system, leading to a closed-loop design flow. Additionally, the signal-flow approach enables power management by varying the signal flow and data processing rates depending on actual energy consumption, estimated energy deposit, and required Quality-of-Service.
Spurr, Robert; Loyola, Diego; Thomas, Werner; Balzer, Wolfgang; Mikusch, Eberhard; Aberle, Bernd; Slijkhuis, Sander; Ruppert, Thomas; van Roozendael, Michel; Lambert, Jean-Christopher; Soebijanta, Trisnanto
2005-11-20
The global ozone monitoring experiment (GOME) was launched in April 1995, and the GOME data processor (GDP) retrieval algorithm has processed operational total ozone amounts since July 1995. GDP level 1-to-2 is based on the two-step differential optical absorption spectroscopy (DOAS) approach, involving slant column fitting followed by air mass factor (AMF) conversions to vertical column amounts. We present a major upgrade of this algorithm to version 3.0. GDP 3.0 was implemented in July 2002, and the 9-year GOME data record from July 1995 to December 2004 has been processed using this algorithm. The key component in GDP 3.0 is an iterative approach to AMF calculation, in which AMFs and corresponding vertical column densities are adjusted to reflect the true ozone distribution as represented by the fitted DOAS effective slant column. A neural network ensemble is used to optimize the fast and accurate parametrization of AMFs. We describe results of a recent validation exercise for the operational version of the total ozone algorithm; in particular, seasonal and meridian errors are reduced by a factor of 2. On a global basis, GDP 3.0 ozone total column results lie between -2% and +4% of ground-based values for moderate solar zenith angles lower than 70 degrees. A larger variability of about +5% and -8% is observed for higher solar zenith angles up to 90 degrees.
NASA Astrophysics Data System (ADS)
Ouyang, Huei-Tau
2016-08-01
The forecasting of inundation levels during typhoons requires that multiple objectives be taken into account, including the forecasting capacity with regard to variations in water level throughout the entire weather event, the accuracy that can be attained in forecasting peak water levels, and the time at which peak water levels are likely to occur. This paper proposed a means of forecasting inundation levels in real time using monitoring data from a water-level gauging network. ARMAX was used to construct water-level forecast models for each gauging station using input variables including cumulative rainfall and water-level data from other gauging stations in the network. Analysis of the correlation between cumulative rainfall and water-level data makes it possible to obtain the appropriate accumulation duration of rainfall and the time lags associated with each gauging station. Analyses on cross-site water levels as well as on cumulative rainfall enable the identification of associate sites pertaining to each gauging station that share high correlations with regard to water level and low mutual information with regard to cumulative rainfall. Water-level data from the identified associate sites are used as a second input variable for the water-level forecast model of the target site. Three indices were considered in the selection of an optimal model: the coefficient of efficiency (CE), error in the stage of peak water level (ESP), and relative time shift (RTS). A multi-objective genetic algorithm was employed to derive an optimal Pareto set of models capable of performing well in the three objectives. A case study was conducted on the Xinnan area of Yilan County, Taiwan, in which optimal water-level forecast models were established for each of the four water-level gauging stations in the area. Test results demonstrate that the model best able to satisfy ESP exhibited significant time shift, whereas the models best able to satisfy CE and RTS provide accurate
La Ruche, G.; Lorougnon, F.; Digbeu, N.
1995-01-01
In the acquired immunodeficiency syndrome (AIDS) era, adequate management of sexually transmitted diseases (STDs) is a primary concern in Africa. Assessed in this study is the clinical efficacy and feasibility of WHO-recommended therapeutic algorithms for genital discharges and ulcers, diagnosed without laboratory tests, for use at the primary health care level. Drugs were sold on a cost-recovery basis and included intramuscular ceftriaxone and oral ciprofloxacin for single-dose therapy of gonorrhoea and chancroid. During April 1993 in 10 peripheral health care centres in Abidjan, Côte d'Ivoire, a total of 207 patients were followed up, including 89 cases of male urethritis, 92 cases of vaginal discharges and 26 cases of genital ulcers; clinical success, assessed 7 days after the onset of therapy, was, respectively, 92%, 87%, and 100%. Less than 10% of the 207 patients were referred to the next care level, an acceptable rate from a public health point of view. Medical adherence to the algorithms was excellent for urethral discharges and genital ulcers but poor for vaginal discharges, partly because of intentional therapeutic modifications, without detriment to success. For drugs, the average cost per cure was 1546 francs CFA (US$ 5.60) (maximum, 2980 francs CFA (US$ 10.70). Effective and affordable treatments for STDs are necessary for their realistic case management in Africa. PMID:7614662
Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla
2015-01-01
Abstract. Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as w, Δt, z, α, μ, α1, and α2, play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method. PMID:26158101
NASA Astrophysics Data System (ADS)
Troitskaya, Yuliya; Lebedev, Sergey; Soustova, Irina; Rybushkina, Galina; Papko, Vladislav; Baidakov, Georgy; Panyutin, Andrey
One of the recent applications of satellite altimetry originally designed for measurements of the sea level [1] is associated with remote investigation of the water level of inland waters: lakes, rivers, reservoirs [2-7]. The altimetry data re-tracking algorithms developed for open ocean conditions (e.g. Ocean-1,2) [1] often cannot be used in these cases, since the radar return is significantly contaminated by reflection from the land. The problem of minimization of errors in the water level retrieval for inland waters from altimetry measurements can be resolved by re-tracking satellite altimetry data. Recently, special re-tracking algorithms have been actively developed for re-processing altimetry data in the coastal zone when reflection from land strongly affects echo shapes: threshold re-tracking, The other methods of re-tracking (threshold re-tracking, beta-re-tracking, improved threshold re-tracking) were developed in [9-11]. The latest development in this field is PISTACH product [12], in which retracking bases on the classification of typical forms of telemetric waveforms in the coastal zones and inland water bodies. In this paper a novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. It was proposed in [13, 14], where the algorithm for assessing water level in inland water bodies and in the coastal zone of the ocean with an error of about 10-15 cm was constructed. The algorithm includes four consecutive steps: - constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; - solving a direct problem by calculating the reflected waveforms within the framework of the model; - imposing restrictions and validity criteria for the algorithm based on waveform modelling; - solving the inverse problem by retrieving a tracking point
Semioptimal practicable algorithmic cooling
NASA Astrophysics Data System (ADS)
Elias, Yuval; Mor, Tal; Weinstein, Yossi
2011-04-01
Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon’s entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.
Fisher, Jason C.
2013-01-01
Long-term groundwater monitoring networks can provide essential information for the planning and management of water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. A network design tool, distributed as an R package, was developed to determine which wells to exclude from a monitoring network because they add little or no beneficial information. A kriging-based genetic algorithm method was used to optimize the monitoring network. The algorithm was used to find the set of wells whose removal leads to the smallest increase in the weighted sum of the (1) mean standard error at all nodes in the kriging grid where the water table is estimated, (2) root-mean-squared-error between the measured and estimated water-level elevation at the removed sites, (3) mean standard deviation of measurements across time at the removed sites, and (4) mean measurement error of wells in the reduced network. The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The network design tool was applied to optimize two observation well networks monitoring the water table of the eastern Snake River Plain aquifer, Idaho; these networks include the 2008 Federal-State Cooperative water-level monitoring network (Co-op network) with 166 observation wells, and the 2008 U.S. Geological Survey-Idaho National Laboratory water-level monitoring network (USGS-INL network) with 171 wells. Each water-level monitoring network was optimized five times: by removing (1) 10, (2) 20, (3) 40, (4) 60, and (5) 80 observation wells from the original network. An examination of the trade-offs associated with changes in the number of wells to remove indicates that 20 wells can be removed from the Co-op network with a relatively small degradation of the estimated water table map, and 40 wells
Rajković, Nemanja; Kolarević, Daniela; Kanjer, Ksenija; Milošević, Nebojša T; Nikolić-Vukosavljević, Dragica; Radulovic, Marko
2016-10-01
Breast cancer prognosis is a subject undergoing intense study due to its high clinical relevance for effective therapeutic management and a great patient interest in disease progression. Prognostic value of fractal and gray level co-occurrence matrix texture analysis algorithms has been previously established on tumour histology images, but without any direct performance comparison. Therefore, this study was designed to compare the prognostic power of the monofractal, multifractal and co-occurrence algorithms on the same set of images. The investigation was retrospective, with 51 patients selected on account of non-metastatic IBC diagnosis, stage IIIB. Image analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Bootstrap-corrected Cox proportional hazards regression P-values indicated a significant association with metastasis outcome of at least one of the features within each group. AUC values were far better for co-occurrence (0.66-0.77) then for fractal features (0.60-0.64). Correction by the split-sample cross-validation likewise indicated the generalizability only for the co-occurrence features, with their classification accuracies ranging between 67 and 72 %, while accuracies of monofractal and multifractal features were reduced to nearly random 52-55 %. These findings indicate for the first time that the prognostic value of texture analysis of tumour histology is less dependent on the morphological complexity of the image as measured by fractal analysis, but predominantly on the spatial distribution of the gray pixel intensities as calculated by the co-occurrence features. PMID:27549346
Rajković, Nemanja; Kolarević, Daniela; Kanjer, Ksenija; Milošević, Nebojša T; Nikolić-Vukosavljević, Dragica; Radulovic, Marko
2016-10-01
Breast cancer prognosis is a subject undergoing intense study due to its high clinical relevance for effective therapeutic management and a great patient interest in disease progression. Prognostic value of fractal and gray level co-occurrence matrix texture analysis algorithms has been previously established on tumour histology images, but without any direct performance comparison. Therefore, this study was designed to compare the prognostic power of the monofractal, multifractal and co-occurrence algorithms on the same set of images. The investigation was retrospective, with 51 patients selected on account of non-metastatic IBC diagnosis, stage IIIB. Image analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Bootstrap-corrected Cox proportional hazards regression P-values indicated a significant association with metastasis outcome of at least one of the features within each group. AUC values were far better for co-occurrence (0.66-0.77) then for fractal features (0.60-0.64). Correction by the split-sample cross-validation likewise indicated the generalizability only for the co-occurrence features, with their classification accuracies ranging between 67 and 72 %, while accuracies of monofractal and multifractal features were reduced to nearly random 52-55 %. These findings indicate for the first time that the prognostic value of texture analysis of tumour histology is less dependent on the morphological complexity of the image as measured by fractal analysis, but predominantly on the spatial distribution of the gray pixel intensities as calculated by the co-occurrence features.
Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi
2010-05-15
Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
Genetic Algorithms and Local Search
NASA Technical Reports Server (NTRS)
Whitley, Darrell
1996-01-01
The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.
Wang, Lin; Qu, Hui; Chen, Tao; Yan, Fang-Ping
2013-01-01
The integration with different decisions in the supply chain is a trend, since it can avoid the suboptimal decisions. In this paper, we provide an effective intelligent algorithm for a modified joint replenishment and location-inventory problem (JR-LIP). The problem of the JR-LIP is to determine the reasonable number and location of distribution centers (DCs), the assignment policy of customers, and the replenishment policy of DCs such that the overall cost is minimized. However, due to the JR-LIP's difficult mathematical properties, simple and effective solutions for this NP-hard problem have eluded researchers. To find an effective approach for the JR-LIP, a hybrid self-adapting differential evolution algorithm (HSDE) is designed. To verify the effectiveness of the HSDE, two intelligent algorithms that have been proven to be effective algorithms for the similar problems named genetic algorithm (GA) and hybrid DE (HDE) are chosen to compare with it. Comparative results of benchmark functions and randomly generated JR-LIPs show that HSDE outperforms GA and HDE. Moreover, a sensitive analysis of cost parameters reveals the useful managerial insight. All comparative results show that HSDE is more stable and robust in handling this complex problem especially for the large-scale problem. PMID:24453822
Liu, Yaolin; Wang, Hua; Ji, Yingli; Liu, Zhongqiu; Zhao, Xiang
2012-08-01
Comprehensive land-use planning (CLUP) at the county level in China must include land-use zoning. This is specifically stipulated by the China Land Management Law and aims to achieve strict control on the usages of land. The land-use zoning problem is treated as a multi-objective optimization problem (MOOP) in this article, which is different from the traditional treatment. A particle swarm optimization (PSO) based model is applied to the problem and is developed to maximize the attribute differences between land-use zones, the spatial compactness, the degree of spatial harmony and the ecological benefits of the land-use zones. This is subject to some constraints such as: the quantity limitations for varying land-use zones, regulations assigning land units to a certain land-use zone, and the stipulation of a minimum parcel area in a land-use zoning map. In addition, a crossover and mutation operator from a genetic algorithm is adopted to avoid the prematurity of PSO. The results obtained for Yicheng, a county in central China, using different objective weighting schemes, are compared and suggest that: (1) the fundamental demand for attribute difference between land-use zones leads to a mass of fragmentary land-use zones; (2) the spatial pattern of land-use zones is remarkably optimized when a weight is given to the sub-objectives of spatial compactness and the degree of spatial harmony, simultaneously, with a reduction of attribute difference between land-use zones; (3) when a weight is given to the sub-objective of ecological benefits of the land-use zones, the ecological benefits get a slight increase also at the expense of a reduction in attribute difference between land-use zones; (4) the pursuit of spatial harmony or spatial compactness may have a negative effect on each other; (5) an increase in the ecological benefits may improve the spatial compactness and spatial harmony of the land-use zones; (6) adjusting the weights assigned to each sub-objective can
NOSS Altimeter Detailed Algorithm specifications
NASA Technical Reports Server (NTRS)
Hancock, D. W.; Mcmillan, J. D.
1982-01-01
The details of the algorithms and data sets required for satellite radar altimeter data processing are documented in a form suitable for (1) development of the benchmark software and (2) coding the operational software. The algorithms reported in detail are those established for altimeter processing. The algorithms which required some additional development before documenting for production were only scoped. The algorithms are divided into two levels of processing. The first level converts the data to engineering units and applies corrections for instrument variations. The second level provides geophysical measurements derived from altimeter parameters for oceanographic users.
NASA Technical Reports Server (NTRS)
Guenther, Bruce W.; Godden, Gerald D.; Xiong, Xiao-Xiong; Knight, Edward J.; Qiu, Shi-Yue; Montgomery, Harry; Hopkins, M. M.; Khayat, Mohammad G.; Hao, Zhi-Dong; Smith, David E. (Technical Monitor)
2000-01-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) radiometric calibration product is described for the thermal emissive and the reflective solar bands. Specific sensor design characteristics are identified to assist in understanding how the calibration algorithm software product is designed. The reflected solar band software products of radiance and reflectance factor both are described. The product file format is summarized and the MODIS Characterization Support Team (MCST) Homepage location for the current file format is provided.
Tactical Synthesis Of Efficient Global Search Algorithms
NASA Technical Reports Server (NTRS)
Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.
2009-01-01
Algorithm synthesis transforms a formal specification into an efficient algorithm to solve a problem. Algorithm synthesis in Specware combines the formal specification of a problem with a high-level algorithm strategy. To derive an efficient algorithm, a developer must define operators that refine the algorithm by combining the generic operators in the algorithm with the details of the problem specification. This derivation requires skill and a deep understanding of the problem and the algorithmic strategy. In this paper we introduce two tactics to ease this process. The tactics serve a similar purpose to tactics used for determining indefinite integrals in calculus, that is suggesting possible ways to attack the problem.
NASA Technical Reports Server (NTRS)
Barth, Timothy J.; Lomax, Harvard
1987-01-01
The past decade has seen considerable activity in algorithm development for the Navier-Stokes equations. This has resulted in a wide variety of useful new techniques. Some examples for the numerical solution of the Navier-Stokes equations are presented, divided into two parts. One is devoted to the incompressible Navier-Stokes equations, and the other to the compressible form.
Computer algorithm for coding gain
NASA Technical Reports Server (NTRS)
Dodd, E. E.
1974-01-01
Development of a computer algorithm for coding gain for use in an automated communications link design system. Using an empirical formula which defines coding gain as used in space communications engineering, an algorithm is constructed on the basis of available performance data for nonsystematic convolutional encoding with soft-decision (eight-level) Viterbi decoding.
NASA Astrophysics Data System (ADS)
Ahmed, Oumer S.; Franklin, Steven E.; Wulder, Michael A.; White, Joanne C.
2015-03-01
Many forest management activities, including the development of forest inventories, require spatially detailed forest canopy cover and height data. Among the various remote sensing technologies, LiDAR (Light Detection and Ranging) offers the most accurate and consistent means for obtaining reliable canopy structure measurements. A potential solution to reduce the cost of LiDAR data, is to integrate transects (samples) of LiDAR data with frequently acquired and spatially comprehensive optical remotely sensed data. Although multiple regression is commonly used for such modeling, often it does not fully capture the complex relationships between forest structure variables. This study investigates the potential of Random Forest (RF), a machine learning technique, to estimate LiDAR measured canopy structure using a time series of Landsat imagery. The study is implemented over a 2600 ha area of industrially managed coastal temperate forests on Vancouver Island, British Columbia, Canada. We implemented a trajectory-based approach to time series analysis that generates time since disturbance (TSD) and disturbance intensity information for each pixel and we used this information to stratify the forest land base into two strata: mature forests and young forests. Canopy cover and height for three forest classes (i.e. mature, young and mature and young (combined)) were modeled separately using multiple regression and Random Forest (RF) techniques. For all forest classes, the RF models provided improved estimates relative to the multiple regression models. The lowest validation error was obtained for the mature forest strata in a RF model (R2 = 0.88, RMSE = 2.39 m and bias = -0.16 for canopy height; R2 = 0.72, RMSE = 0.068% and bias = -0.0049 for canopy cover). This study demonstrates the value of using disturbance and successional history to inform estimates of canopy structure and obtain improved estimates of forest canopy cover and height using the RF algorithm.
Evolutionary pattern search algorithms
Hart, W.E.
1995-09-19
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimental analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.
Routing Algorithm Exploits Spatial Relations
NASA Technical Reports Server (NTRS)
Okino, Clayton; Jennings, Esther
2004-01-01
A recently developed routing algorithm for broadcasting in an ad hoc wireless communication network takes account of, and exploits, the spatial relationships among the locations of nodes, in addition to transmission power levels and distances between the nodes. In contrast, most prior algorithms for discovering routes through ad hoc networks rely heavily on transmission power levels and utilize limited graph-topology techniques that do not involve consideration of the aforesaid spatial relationships. The present algorithm extracts the relevant spatial-relationship information by use of a construct denoted the relative-neighborhood graph (RNG).
In-Trail Procedure (ITP) Algorithm Design
NASA Technical Reports Server (NTRS)
Munoz, Cesar A.; Siminiceanu, Radu I.
2007-01-01
The primary objective of this document is to provide a detailed description of the In-Trail Procedure (ITP) algorithm, which is part of the Airborne Traffic Situational Awareness In-Trail Procedure (ATSA-ITP) application. To this end, the document presents a high level description of the ITP Algorithm and a prototype implementation of this algorithm in the programming language C.
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
Tomasz Plawski, J. Hovater
2010-09-01
A digital low level radio frequency (RF) system typically incorporates either a heterodyne or direct sampling technique, followed by fast ADCs, then an FPGA, and finally a transmitting DAC. This universal platform opens up the possibilities for a variety of control algorithm implementations. The foremost concern for an RF control system is cavity field stability, and to meet the required quality of regulation, the chosen control system needs to have sufficient feedback gain. In this paper we will investigate the effectiveness of the regulation for three basic control system algorithms: I&Q (In-phase and Quadrature), Amplitude & Phase and digital SEL (Self Exciting Loop) along with the example of the Jefferson Lab 12 GeV cavity field control system.
NASA Astrophysics Data System (ADS)
Gravirov, V. V.; Kislov, K. V.
2009-12-01
The chief hazard posed by earthquakes consists in their suddenness. The number of earthquakes annually recorded is in excess of 100,000; of these, over 1000 are strong ones. Great human losses usually occur because no devices exist for advance warning of earthquakes. It is therefore high time that mobile information automatic systems should be developed for analysis of seismic information at high levels of manmade noise. The systems should be operated in real time with the minimum possible computational delays and be able to make fast decisions. The chief statement of the project is that sufficiently complete information about an earthquake can be obtained in real time by examining its first onset as recorded by a single seismic sensor or a local seismic array. The essential difference from the existing systems consists in the following: analysis of local seismic data at high levels of manmade noise (that is, when the noise level may be above the seismic signal level), as well as self-contained operation. The algorithms developed during the execution of the project will be capable to be used with success for individual personal protection kits and for warning the population in earthquake-prone areas over the world. The system being developed for this project uses P and S waves as well. The difference in the velocities of these seismic waves permits a technique to be developed for identifying a damaging earthquake. Real time analysis of first onsets yields the time that remains before surface waves arrive and the damage potential of these waves. Estimates show that, when the difference between the earthquake epicenter and the monitored site is of order 200 km, the time difference between the arrivals of P waves and surface waves will be about 30 seconds, which is quite sufficient to evacuate people from potentially hazardous space, insertion of moderators at nuclear power stations, pipeline interlocking, transportation stoppage, warnings issued to rescue services
A multilevel system of algorithms for detecting and isolating signals in a background of noise
NASA Technical Reports Server (NTRS)
Gurin, L. S.; Tsoy, K. A.
1978-01-01
Signal information is processed with the help of algorithms, and then on the basis of such processing, a part of the information is subjected to further processing with the help of more precise algorithms. Such a system of algorithms is studied, a comparative evaluation of a series of lower level algorithms is given, and the corresponding algorithms of higher level are characterized.
Distilling the Verification Process for Prognostics Algorithms
NASA Technical Reports Server (NTRS)
Roychoudhury, Indranil; Saxena, Abhinav; Celaya, Jose R.; Goebel, Kai
2013-01-01
The goal of prognostics and health management (PHM) systems is to ensure system safety, and reduce downtime and maintenance costs. It is important that a PHM system is verified and validated before it can be successfully deployed. Prognostics algorithms are integral parts of PHM systems. This paper investigates a systematic process of verification of such prognostics algorithms. To this end, first, this paper distinguishes between technology maturation and product development. Then, the paper describes the verification process for a prognostics algorithm as it moves up to higher maturity levels. This process is shown to be an iterative process where verification activities are interleaved with validation activities at each maturation level. In this work, we adopt the concept of technology readiness levels (TRLs) to represent the different maturity levels of a prognostics algorithm. It is shown that at each TRL, the verification of a prognostics algorithm depends on verifying the different components of the algorithm according to the requirements laid out by the PHM system that adopts this prognostics algorithm. Finally, using simplified examples, the systematic process for verifying a prognostics algorithm is demonstrated as the prognostics algorithm moves up TRLs.
A synthesized heuristic task scheduling algorithm.
Dai, Yanyan; Zhang, Xiangli
2014-01-01
Aiming at the static task scheduling problems in heterogeneous environment, a heuristic task scheduling algorithm named HCPPEFT is proposed. In task prioritizing phase, there are three levels of priority in the algorithm to choose task. First, the critical tasks have the highest priority, secondly the tasks with longer path to exit task will be selected, and then algorithm will choose tasks with less predecessors to schedule. In resource selection phase, the algorithm is selected task duplication to reduce the interresource communication cost, besides forecasting the impact of an assignment for all children of the current task permits better decisions to be made in selecting resources. The algorithm proposed is compared with STDH, PEFT, and HEFT algorithms through randomly generated graphs and sets of task graphs. The experimental results show that the new algorithm can achieve better scheduling performance.
Library of Continuation Algorithms
2005-03-01
LOCA (Library of Continuation Algorithms) is scientific software written in C++ that provides advanced analysis tools for nonlinear systems. In particular, it provides parameter continuation algorithms. bifurcation tracking algorithms, and drivers for linear stability analysis. The algorithms are aimed at large-scale applications that use Newtons method for their nonlinear solve.
Evolutionary Algorithm for Optimal Vaccination Scheme
NASA Astrophysics Data System (ADS)
Parousis-Orthodoxou, K. J.; Vlachos, D. S.
2014-03-01
The following work uses the dynamic capabilities of an evolutionary algorithm in order to obtain an optimal immunization strategy in a user specified network. The produced algorithm uses a basic genetic algorithm with crossover and mutation techniques, in order to locate certain nodes in the inputted network. These nodes will be immunized in an SIR epidemic spreading process, and the performance of each immunization scheme, will be evaluated by the level of containment that provides for the spreading of the disease.
Understanding Algorithms in Different Presentations
ERIC Educational Resources Information Center
Csernoch, Mária; Biró, Piroska; Abari, Kálmán; Máth, János
2015-01-01
Within the framework of the Testing Algorithmic and Application Skills project we tested first year students of Informatics at the beginning of their tertiary education. We were focusing on the students' level of understanding in different programming environments. In the present paper we provide the results from the University of Debrecen, the…
NASA Technical Reports Server (NTRS)
Rabideau, Gregg R.; Chien, Steve A.
2010-01-01
AVA v2 software selects goals for execution from a set of goals that oversubscribe shared resources. The term goal refers to a science or engineering request to execute a possibly complex command sequence, such as image targets or ground-station downlinks. Developed as an extension to the Virtual Machine Language (VML) execution system, the software enables onboard and remote goal triggering through the use of an embedded, dynamic goal set that can oversubscribe resources. From the set of conflicting goals, a subset must be chosen that maximizes a given quality metric, which in this case is strict priority selection. A goal can never be pre-empted by a lower priority goal, and high-level goals can be added, removed, or updated at any time, and the "best" goals will be selected for execution. The software addresses the issue of re-planning that must be performed in a short time frame by the embedded system where computational resources are constrained. In particular, the algorithm addresses problems with well-defined goal requests without temporal flexibility that oversubscribes available resources. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. Thereby enabling shorter response times and greater autonomy for the system under control.
Algorithm and program for information processing with the filin apparatus
NASA Technical Reports Server (NTRS)
Gurin, L. S.; Morkrov, V. S.; Moskalenko, Y. I.; Tsoy, K. A.
1979-01-01
The reduction of spectral radiation data from space sources is described. The algorithm and program for identifying segments of information obtained from the Film telescope-spectrometer on the Salyut-4 are presented. The information segments represent suspected X-ray sources. The proposed algorithm is an algorithm of the lowest level. Following evaluation, information free of uninformative segments is subject to further processing with algorithms of a higher level. The language used is FORTRAN 4.
Compression algorithm for multideterminant wave functions.
Weerasinghe, Gihan L; Ríos, Pablo López; Needs, Richard J
2014-02-01
A compression algorithm is introduced for multideterminant wave functions which can greatly reduce the number of determinants that need to be evaluated in quantum Monte Carlo calculations. We have devised an algorithm with three levels of compression, the least costly of which yields excellent results in polynomial time. We demonstrate the usefulness of the compression algorithm for evaluating multideterminant wave functions in quantum Monte Carlo calculations, whose computational cost is reduced by factors of between about 2 and over 25 for the examples studied. We have found evidence of sublinear scaling of quantum Monte Carlo calculations with the number of determinants when the compression algorithm is used.
A parallel algorithm for global routing
NASA Technical Reports Server (NTRS)
Brouwer, Randall J.; Banerjee, Prithviraj
1990-01-01
A Parallel Hierarchical algorithm for Global Routing (PHIGURE) is presented. The router is based on the work of Burstein and Pelavin, but has many extensions for general global routing and parallel execution. Main features of the algorithm include structured hierarchical decomposition into separate independent tasks which are suitable for parallel execution and adaptive simplex solution for adding feedthroughs and adjusting channel heights for row-based layout. Alternative decomposition methods and the various levels of parallelism available in the algorithm are examined closely. The algorithm is described and results are presented for a shared-memory multiprocessor implementation.
Some nonlinear space decomposition algorithms
Tai, Xue-Cheng; Espedal, M.
1996-12-31
Convergence of a space decomposition method is proved for a general convex programming problem. The space decomposition refers to methods that decompose a space into sums of subspaces, which could be a domain decomposition or a multigrid method for partial differential equations. Two algorithms are proposed. Both can be used for linear as well as nonlinear elliptic problems and they reduce to the standard additive and multiplicative Schwarz methods for linear elliptic problems. Two {open_quotes}hybrid{close_quotes} algorithms are also presented. They converge faster than the additive one and have better parallelism than the multiplicative method. Numerical tests with a two level domain decomposition for linear, nonlinear and interface elliptic problems are presented for the proposed algorithms.
Realization of a scalable Shor algorithm.
Monz, Thomas; Nigg, Daniel; Martinez, Esteban A; Brandl, Matthias F; Schindler, Philipp; Rines, Richard; Wang, Shannon X; Chuang, Isaac L; Blatt, Rainer
2016-03-01
Certain algorithms for quantum computers are able to outperform their classical counterparts. In 1994, Peter Shor came up with a quantum algorithm that calculates the prime factors of a large number vastly more efficiently than a classical computer. For general scalability of such algorithms, hardware, quantum error correction, and the algorithmic realization itself need to be extensible. Here we present the realization of a scalable Shor algorithm, as proposed by Kitaev. We factor the number 15 by effectively employing and controlling seven qubits and four "cache qubits" and by implementing generalized arithmetic operations, known as modular multipliers. This algorithm has been realized scalably within an ion-trap quantum computer and returns the correct factors with a confidence level exceeding 99%. PMID:26941315
Reasoning about systolic algorithms
Purushothaman, S.
1986-01-01
Systolic algorithms are a class of parallel algorithms, with small grain concurrency, well suited for implementation in VLSI. They are intended to be implemented as high-performance, computation-bound back-end processors and are characterized by a tesselating interconnection of identical processing elements. This dissertation investigates the problem of providing correctness of systolic algorithms. The following are reported in this dissertation: (1) a methodology for verifying correctness of systolic algorithms based on solving the representation of an algorithm as recurrence equations. The methodology is demonstrated by proving the correctness of a systolic architecture for optimal parenthesization. (2) The implementation of mechanical proofs of correctness of two systolic algorithms, a convolution algorithm and an optimal parenthesization algorithm, using the Boyer-Moore theorem prover. (3) An induction principle for proving correctness of systolic arrays which are modular. Two attendant inference rules, weak equivalence and shift transformation, which capture equivalent behavior of systolic arrays, are also presented.
Algorithm-development activities
NASA Technical Reports Server (NTRS)
Carder, Kendall L.
1994-01-01
The task of algorithm-development activities at USF continues. The algorithm for determining chlorophyll alpha concentration, (Chl alpha) and gelbstoff absorption coefficient for SeaWiFS and MODIS-N radiance data is our current priority.
NASA Astrophysics Data System (ADS)
Neta, B.; Mansager, B.
1992-08-01
Audio information concerning targets generally includes direction, frequencies, and energy levels. One use of audio cueing is to use direction information to help determine where more sensitive visual direction and acquisition sensors should be directed. Generally, use of audio cueing will shorten times required for visual detection, although there could be circumstances where the audio information is misleading and degrades visual performance. Audio signatures can also be useful for helping classify the emanating platform, as well as to provide estimates of its velocity. The Janus combat simulation is the premier high resolution model used by the Army and other agencies to conduct research. This model has a visual detection model which essentially incorporates algorithms as described by Hartman(1985). The model in its current form does not have any sound cueing capability. This report is part of a research effort to investigate the utility of developing such a capability.
INSENS classification algorithm report
Hernandez, J.E.; Frerking, C.J.; Myers, D.W.
1993-07-28
This report describes a new algorithm developed for the Imigration and Naturalization Service (INS) in support of the INSENS project for classifying vehicles and pedestrians using seismic data. This algorithm is less sensitive to nuisance alarms due to environmental events than the previous algorithm. Furthermore, the algorithm is simple enough that it can be implemented in the 8-bit microprocessor used in the INSENS system.
Accurate Finite Difference Algorithms
NASA Technical Reports Server (NTRS)
Goodrich, John W.
1996-01-01
Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.
POSE Algorithms for Automated Docking
NASA Technical Reports Server (NTRS)
Heaton, Andrew F.; Howard, Richard T.
2011-01-01
POSE (relative position and attitude) can be computed in many different ways. Given a sensor that measures bearing to a finite number of spots corresponding to known features (such as a target) of a spacecraft, a number of different algorithms can be used to compute the POSE. NASA has sponsored the development of a flash LIDAR proximity sensor called the Vision Navigation Sensor (VNS) for use by the Orion capsule in future docking missions. This sensor generates data that can be used by a variety of algorithms to compute POSE solutions inside of 15 meters, including at the critical docking range of approximately 1-2 meters. Previously NASA participated in a DARPA program called Orbital Express that achieved the first automated docking for the American space program. During this mission a large set of high quality mated sensor data was obtained at what is essentially the docking distance. This data set is perhaps the most accurate truth data in existence for docking proximity sensors in orbit. In this paper, the flight data from Orbital Express is used to test POSE algorithms at 1.22 meters range. Two different POSE algorithms are tested for two different Fields-of-View (FOVs) and two different pixel noise levels. The results of the analysis are used to predict future performance of the POSE algorithms with VNS data.
Algorithms Could Automate Cancer Diagnosis
NASA Technical Reports Server (NTRS)
Baky, A. A.; Winkler, D. G.
1982-01-01
Five new algorithms are a complete statistical procedure for quantifying cell abnormalities from digitized images. Procedure could be basis for automated detection and diagnosis of cancer. Objective of procedure is to assign each cell an atypia status index (ASI), which quantifies level of abnormality. It is possible that ASI values will be accurate and economical enough to allow diagnoses to be made quickly and accurately by computer processing of laboratory specimens extracted from patients.
Reasoning about systolic algorithms
Purushothaman, S.; Subrahmanyam, P.A.
1988-12-01
The authors present a methodology for verifying correctness of systolic algorithms. The methodology is based on solving a set of Uniform Recurrence Equations obtained from a description of systolic algorithms as a set of recursive equations. They present an approach to mechanically verify correctness of systolic algorithms, using the Boyer-Moore theorem proven. A mechanical correctness proof of an example from the literature is also presented.
Hyperspectral image compressive projection algorithm
NASA Astrophysics Data System (ADS)
Rice, Joseph P.; Allen, David W.
2009-05-01
We describe a compressive projection algorithm and experimentally assess its performance when used with a Hyperspectral Image Projector (HIP). The HIP is being developed by NIST for system-level performance testing of hyperspectral and multispectral imagers. It projects a two-dimensional image into the unit under test (UUT), whereby each pixel can have an independently programmable arbitrary spectrum. To efficiently project a single frame of dynamic realistic hyperspectral imagery through the collimator into the UUT, a compression algorithm has been developed whereby the series of abundance images and corresponding endmember spectra that comprise the image cube of that frame are first computed using an automated endmember-finding algorithm such as the Sequential Maximum Angle Convex Cone (SMACC) endmember model. Then these endmember spectra are projected sequentially on the HIP spectral engine in sync with the projection of the abundance images on the HIP spatial engine, during the singleframe exposure time of the UUT. The integrated spatial image captured by the UUT is the endmember-weighted sum of the abundance images, which results in the formation of a datacube for that frame. Compressive projection enables a much smaller set of broadband spectra to be projected than monochromatic projection, and thus utilizes the inherent multiplex advantage of the HIP spectral engine. As a result, radiometric brightness and projection frame rate are enhanced. In this paper, we use a visible breadboard HIP to experimentally assess the compressive projection algorithm performance.
Competing Sudakov veto algorithms
NASA Astrophysics Data System (ADS)
Kleiss, Ronald; Verheyen, Rob
2016-07-01
We present a formalism to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The formal analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance in a semi-realistic setting and show that there are significantly faster alternatives to the commonly used algorithms.
A novel algorithm for Bluetooth ECG.
Pandya, Utpal T; Desai, Uday B
2012-11-01
In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.
A segmentation algorithm for noisy images
Xu, Y.; Olman, V.; Uberbacher, E.C.
1996-12-31
This paper presents a 2-D image segmentation algorithm and addresses issues related to its performance on noisy images. The algorithm segments an image by first constructing a minimum spanning tree representation of the image and then partitioning the spanning tree into sub-trees representing different homogeneous regions. The spanning tree is partitioned in such a way that the sum of gray-level variations over all partitioned subtrees is minimized under the constraints that each subtree has at least a specified number of pixels and two adjacent subtrees have significantly different ``average`` gray-levels. Two types of noise, transmission errors and Gaussian additive noise. are considered and their effects on the segmentation algorithm are studied. Evaluation results have shown that the segmentation algorithm is robust in the presence of these two types of noise.
Algorithm That Synthesizes Other Algorithms for Hashing
NASA Technical Reports Server (NTRS)
James, Mark
2010-01-01
An algorithm that includes a collection of several subalgorithms has been devised as a means of synthesizing still other algorithms (which could include computer code) that utilize hashing to determine whether an element (typically, a number or other datum) is a member of a set (typically, a list of numbers). Each subalgorithm synthesizes an algorithm (e.g., a block of code) that maps a static set of key hashes to a somewhat linear monotonically increasing sequence of integers. The goal in formulating this mapping is to cause the length of the sequence thus generated to be as close as practicable to the original length of the set and thus to minimize gaps between the elements. The advantage of the approach embodied in this algorithm is that it completely avoids the traditional approach of hash-key look-ups that involve either secondary hash generation and look-up or further searching of a hash table for a desired key in the event of collisions. This algorithm guarantees that it will never be necessary to perform a search or to generate a secondary key in order to determine whether an element is a member of a set. This algorithm further guarantees that any algorithm that it synthesizes can be executed in constant time. To enforce these guarantees, the subalgorithms are formulated to employ a set of techniques, each of which works very effectively covering a certain class of hash-key values. These subalgorithms are of two types, summarized as follows: Given a list of numbers, try to find one or more solutions in which, if each number is shifted to the right by a constant number of bits and then masked with a rotating mask that isolates a set of bits, a unique number is thereby generated. In a variant of the foregoing procedure, omit the masking. Try various combinations of shifting, masking, and/or offsets until the solutions are found. From the set of solutions, select the one that provides the greatest compression for the representation and is executable in the
On mesh rezoning algorithms for parallel platforms
Plaskacz, E.J.
1995-07-01
A mesh rezoning algorithm for finite element simulations in a parallel-distributed environment is described. The cornerstones of the algorithm are: the parallel computation of distortion norms on the element and subdomain level, the exchange of the individual subdomain norms to form a subdomain distortion vector, the classification of subdomains and the rezoning behavior prescribed within each subdomain as a response to its own classification and the classification of neighboring subdomains.
Totally parallel multilevel algorithms
NASA Technical Reports Server (NTRS)
Frederickson, Paul O.
1988-01-01
Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.
Vectorized algorithms for spiking neural network simulation.
Brette, Romain; Goodman, Dan F M
2011-06-01
High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages. PMID:21395437
MUSIC algorithms for rebar detection
NASA Astrophysics Data System (ADS)
Solimene, Raffaele; Leone, Giovanni; Dell'Aversano, Angela
2013-12-01
The MUSIC (MUltiple SIgnal Classification) algorithm is employed to detect and localize an unknown number of scattering objects which are small in size as compared to the wavelength. The ensemble of objects to be detected consists of both strong and weak scatterers. This represents a scattering environment challenging for detection purposes as strong scatterers tend to mask the weak ones. Consequently, the detection of more weakly scattering objects is not always guaranteed and can be completely impaired when the noise corrupting data is of a relatively high level. To overcome this drawback, here a new technique is proposed, starting from the idea of applying a two-stage MUSIC algorithm. In the first stage strong scatterers are detected. Then, information concerning their number and location is employed in the second stage focusing only on the weak scatterers. The role of an adequate scattering model is emphasized to improve drastically detection performance in realistic scenarios.
Algorithm refinement for fluctuating hydrodynamics
Williams, Sarah A.; Bell, John B.; Garcia, Alejandro L.
2007-07-03
This paper introduces an adaptive mesh and algorithmrefinement method for fluctuating hydrodynamics. This particle-continuumhybrid simulates the dynamics of a compressible fluid with thermalfluctuations. The particle algorithm is direct simulation Monte Carlo(DSMC), a molecular-level scheme based on the Boltzmann equation. Thecontinuum algorithm is based on the Landau-Lifshitz Navier-Stokes (LLNS)equations, which incorporate thermal fluctuations into macroscopichydrodynamics by using stochastic fluxes. It uses a recently-developedsolver for LLNS, based on third-order Runge-Kutta. We present numericaltests of systems in and out of equilibrium, including time-dependentsystems, and demonstrate dynamic adaptive refinement by the computationof a moving shock wave. Mean system behavior and second moment statisticsof our simulations match theoretical values and benchmarks well. We findthat particular attention should be paid to the spectrum of the flux atthe interface between the particle and continuum methods, specificallyfor the non-hydrodynamic (kinetic) time scales.
Function-Based Algorithms for Biological Sequences
ERIC Educational Resources Information Center
Mohanty, Pragyan Sheela P.
2015-01-01
Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…
Improved Bat Algorithm Applied to Multilevel Image Thresholding
2014-01-01
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
Rempp, Florian; Mahler, Guenter; Michel, Mathias
2007-09-15
We introduce a scheme to perform the cooling algorithm, first presented by Boykin et al. in 2002, for an arbitrary number of times on the same set of qbits. We achieve this goal by adding an additional SWAP gate and a bath contact to the algorithm. This way one qbit may repeatedly be cooled without adding additional qbits to the system. By using a product Liouville space to model the bath contact we calculate the density matrix of the system after a given number of applications of the algorithm.
NASA Astrophysics Data System (ADS)
Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.
2013-01-01
A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.
NASA Technical Reports Server (NTRS)
Chan, Hak-Wai; Yan, Tsun-Yee
1989-01-01
Algorithm developed for optimal routing of packets of data along links of multilink, multinode digital communication network. Algorithm iterative and converges to cost-optimal assignment independent of initial assignment. Each node connected to other nodes through links, each containing number of two-way channels. Algorithm assigns channels according to message traffic leaving and arriving at each node. Modified to take account of different priorities among packets belonging to different users by using different delay constraints or imposing additional penalties via cost function.
NASA Astrophysics Data System (ADS)
Ahmed, Yasser A.; Afifi, Hossam; Rubino, Gerardo
1999-05-01
This paper present a new algorithm for stereo matching. The main idea is to decompose the original problem into independent hierarchical and more elementary problems that can be solved faster without any complicated mathematics using BBD. To achieve that, we use a new image feature called 'continuity feature' instead of classical noise. This feature can be extracted from any kind of images by a simple process and without using a searching technique. A new matching technique is proposed to match the continuity feature. The new algorithm resolves the main disadvantages of feature based stereo matching algorithms.
Variable depth recursion algorithm for leaf sequencing
Siochi, R. Alfredo C.
2007-02-15
The processes of extraction and sweep are basic segmentation steps that are used in leaf sequencing algorithms. A modified version of a commercial leaf sequencer changed the way that the extracts are selected and expanded the search space, but the modification maintained the basic search paradigm of evaluating multiple solutions, each one consisting of up to 12 extracts and a sweep sequence. While it generated the best solutions compared to other published algorithms, it used more computation time. A new, faster algorithm selects one extract at a time but calls itself as an evaluation function a user-specified number of times, after which it uses the bidirectional sweeping window algorithm as the final evaluation function. To achieve a performance comparable to that of the modified commercial leaf sequencer, 2-3 calls were needed, and in all test cases, there were only slight improvements beyond two calls. For the 13 clinical test maps, computation speeds improved by a factor between 12 and 43, depending on the constraints, namely the ability to interdigitate and the avoidance of the tongue-and-groove under dose. The new algorithm was compared to the original and modified versions of the commercial leaf sequencer. It was also compared to other published algorithms for 1400, random, 15x15, test maps with 3-16 intensity levels. In every single case the new algorithm provided the best solution.
Updated treatment algorithm of pulmonary arterial hypertension.
Galiè, Nazzareno; Corris, Paul A; Frost, Adaani; Girgis, Reda E; Granton, John; Jing, Zhi Cheng; Klepetko, Walter; McGoon, Michael D; McLaughlin, Vallerie V; Preston, Ioana R; Rubin, Lewis J; Sandoval, Julio; Seeger, Werner; Keogh, Anne
2013-12-24
The demands on a pulmonary arterial hypertension (PAH) treatment algorithm are multiple and in some ways conflicting. The treatment algorithm usually includes different types of recommendations with varying degrees of scientific evidence. In addition, the algorithm is required to be comprehensive but not too complex, informative yet simple and straightforward. The type of information in the treatment algorithm are heterogeneous including clinical, hemodynamic, medical, interventional, pharmacological and regulatory recommendations. Stakeholders (or users) including physicians from various specialties and with variable expertise in PAH, nurses, patients and patients' associations, healthcare providers, regulatory agencies and industry are often interested in the PAH treatment algorithm for different reasons. These are the considerable challenges faced when proposing appropriate updates to the current evidence-based treatment algorithm.The current treatment algorithm may be divided into 3 main areas: 1) general measures, supportive therapy, referral strategy, acute vasoreactivity testing and chronic treatment with calcium channel blockers; 2) initial therapy with approved PAH drugs; and 3) clinical response to the initial therapy, combination therapy, balloon atrial septostomy, and lung transplantation. All three sections will be revisited highlighting information newly available in the past 5 years and proposing updates where appropriate. The European Society of Cardiology grades of recommendation and levels of evidence will be adopted to rank the proposed treatments. PMID:24355643
Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425
Algorithmic synthesis using Python compiler
NASA Astrophysics Data System (ADS)
Cieszewski, Radoslaw; Romaniuk, Ryszard; Pozniak, Krzysztof; Linczuk, Maciej
2015-09-01
This paper presents a python to VHDL compiler. The compiler interprets an algorithmic description of a desired behavior written in Python and translate it to VHDL. FPGA combines many benefits of both software and ASIC implementations. Like software, the programmed circuit is flexible, and can be reconfigured over the lifetime of the system. FPGAs have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. This can be achieved by using many computational resources at the same time. Creating parallel programs implemented in FPGAs in pure HDL is difficult and time consuming. Using higher level of abstraction and High-Level Synthesis compiler implementation time can be reduced. The compiler has been implemented using the Python language. This article describes design, implementation and results of created tools.
2013-07-29
The OpenEIS Algorithm package seeks to provide a low-risk path for building owners, service providers and managers to explore analytical methods for improving building control and operational efficiency. Users of this software can analyze building data, and learn how commercial implementations would provide long-term value. The code also serves as a reference implementation for developers who wish to adapt the algorithms for use in commercial tools or service offerings.
The Superior Lambert Algorithm
NASA Astrophysics Data System (ADS)
der, G.
2011-09-01
Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most
The hierarchical algorithms--theory and applications
NASA Astrophysics Data System (ADS)
Su, Zheng-Yao
scan scheme applicable to problem domains of any high dimension and of arbitrary geometry (scan is an important primitive of parallel computing). In addition, from implementation results, the hierarchical cluster labeling algorithm has proved to work equally well on MIMD machines, though originally designed for SIMD machines.Based on this success, we further study the hierarchical structure hidden in the algorithm. Hierarchical structure is a conceptual framework frequently used in building models for the study of a great variety of problems. This structure serves not only to describe the complexity of the system at different levels, but also to achieve some goals targeted by the problem, i.e., an algorithm to solve the problem. In this regard, we investigate the similarities and differences between this algorithm and others, including the FFT and the Barnes-Hut method, in terms of their hierarchical structures.
Carroll, T.; Joshi, U.; Auchincloss, P.
1989-04-01
CDF is currently taking data at a luminosity of 10{sup 30} cm{sup -2} sec{sup -1} using a four level event filtering scheme. The fourth level, LEVEL3, uses ACP (Fermilab`s Advanced Computer Program) designed 32 bit VME based parallel processors (1) capable of executing algorithms written in FORTRAN. LEVEL3 currently rejects about 50% of the events.
Local multiplicative Schwarz algorithms for convection-diffusion equations
NASA Technical Reports Server (NTRS)
Cai, Xiao-Chuan; Sarkis, Marcus
1995-01-01
We develop a new class of overlapping Schwarz type algorithms for solving scalar convection-diffusion equations discretized by finite element or finite difference methods. The preconditioners consist of two components, namely, the usual two-level additive Schwarz preconditioner and the sum of some quadratic terms constructed by using products of ordered neighboring subdomain preconditioners. The ordering of the subdomain preconditioners is determined by considering the direction of the flow. We prove that the algorithms are optimal in the sense that the convergence rates are independent of the mesh size, as well as the number of subdomains. We show by numerical examples that the new algorithms are less sensitive to the direction of the flow than either the classical multiplicative Schwarz algorithms, and converge faster than the additive Schwarz algorithms. Thus, the new algorithms are more suitable for fluid flow applications than the classical additive or multiplicative Schwarz algorithms.
Algorithm for Detecting Significant Locations from Raw GPS Data
NASA Astrophysics Data System (ADS)
Kami, Nobuharu; Enomoto, Nobuyuki; Baba, Teruyuki; Yoshikawa, Takashi
We present a fast algorithm for probabilistically extracting significant locations from raw GPS data based on data point density. Extracting significant locations from raw GPS data is the first essential step of algorithms designed for location-aware applications. Assuming that a location is significant if users spend a certain time around that area, most current algorithms compare spatial/temporal variables, such as stay duration and a roaming diameter, with given fixed thresholds to extract significant locations. However, the appropriate threshold values are not clearly known in priori and algorithms with fixed thresholds are inherently error-prone, especially under high noise levels. Moreover, for N data points, they are generally O(N 2) algorithms since distance computation is required. We developed a fast algorithm for selective data point sampling around significant locations based on density information by constructing random histograms using locality sensitive hashing. Evaluations show competitive performance in detecting significant locations even under high noise levels.
Temperature Corrected Bootstrap Algorithm
NASA Technical Reports Server (NTRS)
Comiso, Joey C.; Zwally, H. Jay
1997-01-01
A temperature corrected Bootstrap Algorithm has been developed using Nimbus-7 Scanning Multichannel Microwave Radiometer data in preparation to the upcoming AMSR instrument aboard ADEOS and EOS-PM. The procedure first calculates the effective surface emissivity using emissivities of ice and water at 6 GHz and a mixing formulation that utilizes ice concentrations derived using the current Bootstrap algorithm but using brightness temperatures from 6 GHz and 37 GHz channels. These effective emissivities are then used to calculate surface ice which in turn are used to convert the 18 GHz and 37 GHz brightness temperatures to emissivities. Ice concentrations are then derived using the same technique as with the Bootstrap algorithm but using emissivities instead of brightness temperatures. The results show significant improvement in the area where ice temperature is expected to vary considerably such as near the continental areas in the Antarctic, where the ice temperature is colder than average, and in marginal ice zones.
Power spectral estimation algorithms
NASA Technical Reports Server (NTRS)
Bhatia, Manjit S.
1989-01-01
Algorithms to estimate the power spectrum using Maximum Entropy Methods were developed. These algorithms were coded in FORTRAN 77 and were implemented on the VAX 780. The important considerations in this analysis are: (1) resolution, i.e., how close in frequency two spectral components can be spaced and still be identified; (2) dynamic range, i.e., how small a spectral peak can be, relative to the largest, and still be observed in the spectra; and (3) variance, i.e., how accurate the estimate of the spectra is to the actual spectra. The application of the algorithms based on Maximum Entropy Methods to a variety of data shows that these criteria are met quite well. Additional work in this direction would help confirm the findings. All of the software developed was turned over to the technical monitor. A copy of a typical program is included. Some of the actual data and graphs used on this data are also included.
Optical rate sensor algorithms
NASA Astrophysics Data System (ADS)
Uhde-Lacovara, Jo A.
1989-12-01
Optical sensors, in particular Charge Coupled Device (CCD) arrays, will be used on Space Station to track stars in order to provide inertial attitude reference. Algorithms are presented to derive attitude rate from the optical sensors. The first algorithm is a recursive differentiator. A variance reduction factor (VRF) of 0.0228 was achieved with a rise time of 10 samples. A VRF of 0.2522 gives a rise time of 4 samples. The second algorithm is based on the direct manipulation of the pixel intensity outputs of the sensor. In 1-dimensional simulations, the derived rate was with 0.07 percent of the actual rate in the presence of additive Gaussian noise with a signal to noise ratio of 60 dB.
Optical rate sensor algorithms
NASA Technical Reports Server (NTRS)
Uhde-Lacovara, Jo A.
1989-01-01
Optical sensors, in particular Charge Coupled Device (CCD) arrays, will be used on Space Station to track stars in order to provide inertial attitude reference. Algorithms are presented to derive attitude rate from the optical sensors. The first algorithm is a recursive differentiator. A variance reduction factor (VRF) of 0.0228 was achieved with a rise time of 10 samples. A VRF of 0.2522 gives a rise time of 4 samples. The second algorithm is based on the direct manipulation of the pixel intensity outputs of the sensor. In 1-dimensional simulations, the derived rate was with 0.07 percent of the actual rate in the presence of additive Gaussian noise with a signal to noise ratio of 60 dB.
New Effective Multithreaded Matching Algorithms
Manne, Fredrik; Halappanavar, Mahantesh
2014-05-19
Matching is an important combinatorial problem with a number of applications in areas such as community detection, sparse linear algebra, and network alignment. Since computing optimal matchings can be very time consuming, several fast approximation algorithms, both sequential and parallel, have been suggested. Common to the algorithms giving the best solutions is that they tend to be sequential by nature, while algorithms more suitable for parallel computation give solutions of less quality. We present a new simple 1 2 -approximation algorithm for the weighted matching problem. This algorithm is both faster than any other suggested sequential 1 2 -approximation algorithm on almost all inputs and also scales better than previous multithreaded algorithms. We further extend this to a general scalable multithreaded algorithm that computes matchings of weight comparable with the best sequential algorithms. The performance of the suggested algorithms is documented through extensive experiments on different multithreaded architectures.
Mapped Landmark Algorithm for Precision Landing
NASA Technical Reports Server (NTRS)
Johnson, Andrew; Ansar, Adnan; Matthies, Larry
2007-01-01
A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.
Sampling Within k-Means Algorithm to Cluster Large Datasets
Bejarano, Jeremy; Bose, Koushiki; Brannan, Tyler; Thomas, Anita; Adragni, Kofi; Neerchal, Nagaraj; Ostrouchov, George
2011-08-01
Due to current data collection technology, our ability to gather data has surpassed our ability to analyze it. In particular, k-means, one of the simplest and fastest clustering algorithms, is ill-equipped to handle extremely large datasets on even the most powerful machines. Our new algorithm uses a sample from a dataset to decrease runtime by reducing the amount of data analyzed. We perform a simulation study to compare our sampling based k-means to the standard k-means algorithm by analyzing both the speed and accuracy of the two methods. Results show that our algorithm is significantly more efficient than the existing algorithm with comparable accuracy. Further work on this project might include a more comprehensive study both on more varied test datasets as well as on real weather datasets. This is especially important considering that this preliminary study was performed on rather tame datasets. Also, these datasets should analyze the performance of the algorithm on varied values of k. Lastly, this paper showed that the algorithm was accurate for relatively low sample sizes. We would like to analyze this further to see how accurate the algorithm is for even lower sample sizes. We could find the lowest sample sizes, by manipulating width and confidence level, for which the algorithm would be acceptably accurate. In order for our algorithm to be a success, it needs to meet two benchmarks: match the accuracy of the standard k-means algorithm and significantly reduce runtime. Both goals are accomplished for all six datasets analyzed. However, on datasets of three and four dimension, as the data becomes more difficult to cluster, both algorithms fail to obtain the correct classifications on some trials. Nevertheless, our algorithm consistently matches the performance of the standard algorithm while becoming remarkably more efficient with time. Therefore, we conclude that analysts can use our algorithm, expecting accurate results in considerably less time.
Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Choudhary, Alok Nidhi
1989-01-01
Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.
Automatic design of decision-tree algorithms with evolutionary algorithms.
Barros, Rodrigo C; Basgalupp, Márcio P; de Carvalho, André C P L F; Freitas, Alex A
2013-01-01
This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. The automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. The proposed hyper-heuristic evolutionary algorithm, HEAD-DT, is extensively tested using 20 public UCI datasets and 10 microarray gene expression datasets. The algorithms automatically designed by HEAD-DT are compared with traditional decision-tree induction algorithms, such as C4.5 and CART. Experimental results show that HEAD-DT is capable of generating algorithms which are significantly more accurate than C4.5 and CART.
Fractal Landscape Algorithms for Environmental Simulations
NASA Astrophysics Data System (ADS)
Mao, H.; Moran, S.
2014-12-01
Natural science and geographical research are now able to take advantage of environmental simulations that more accurately test experimental hypotheses, resulting in deeper understanding. Experiments affected by the natural environment can benefit from 3D landscape simulations capable of simulating a variety of terrains and environmental phenomena. Such simulations can employ random terrain generation algorithms that dynamically simulate environments to test specific models against a variety of factors. Through the use of noise functions such as Perlin noise, Simplex noise, and diamond square algorithms, computers can generate simulations that model a variety of landscapes and ecosystems. This study shows how these algorithms work together to create realistic landscapes. By seeding values into the diamond square algorithm, one can control the shape of landscape. Perlin noise and Simplex noise are also used to simulate moisture and temperature. The smooth gradient created by coherent noise allows more realistic landscapes to be simulated. Terrain generation algorithms can be used in environmental studies and physics simulations. Potential studies that would benefit from simulations include the geophysical impact of flash floods or drought on a particular region and regional impacts on low lying area due to global warming and rising sea levels. Furthermore, terrain generation algorithms also serve as aesthetic tools to display landscapes (Google Earth), and simulate planetary landscapes. Hence, it can be used as a tool to assist science education. Algorithms used to generate these natural phenomena provide scientists a different approach in analyzing our world. The random algorithms used in terrain generation not only contribute to the generating the terrains themselves, but are also capable of simulating weather patterns.
The evaluation of the OSGLR algorithm for restructurable controls
NASA Technical Reports Server (NTRS)
Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.
1986-01-01
The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.
Predictive Caching Using the TDAG Algorithm
NASA Technical Reports Server (NTRS)
Laird, Philip; Saul, Ronald
1992-01-01
We describe how the TDAG algorithm for learning to predict symbol sequences can be used to design a predictive cache store. A model of a two-level mass storage system is developed and used to calculate the performance of the cache under various conditions. Experimental simulations provide good confirmation of the model.
NASA Technical Reports Server (NTRS)
Tielking, John T.
1989-01-01
Two algorithms for obtaining static contact solutions are described in this presentation. Although they were derived for contact problems involving specific structures (a tire and a solid rubber cylinder), they are sufficiently general to be applied to other shell-of-revolution and solid-body contact problems. The shell-of-revolution contact algorithm is a method of obtaining a point load influence coefficient matrix for the portion of shell surface that is expected to carry a contact load. If the shell is sufficiently linear with respect to contact loading, a single influence coefficient matrix can be used to obtain a good approximation of the contact pressure distribution. Otherwise, the matrix will be updated to reflect nonlinear load-deflection behavior. The solid-body contact algorithm utilizes a Lagrange multiplier to include the contact constraint in a potential energy functional. The solution is found by applying the principle of minimum potential energy. The Lagrange multiplier is identified as the contact load resultant for a specific deflection. At present, only frictionless contact solutions have been obtained with these algorithms. A sliding tread element has been developed to calculate friction shear force in the contact region of the rolling shell-of-revolution tire model.
Comprehensive eye evaluation algorithm
NASA Astrophysics Data System (ADS)
Agurto, C.; Nemeth, S.; Zamora, G.; Vahtel, M.; Soliz, P.; Barriga, S.
2016-03-01
In recent years, several research groups have developed automatic algorithms to detect diabetic retinopathy (DR) in individuals with diabetes (DM), using digital retinal images. Studies have indicated that diabetics have 1.5 times the annual risk of developing primary open angle glaucoma (POAG) as do people without DM. Moreover, DM patients have 1.8 times the risk for age-related macular degeneration (AMD). Although numerous investigators are developing automatic DR detection algorithms, there have been few successful efforts to create an automatic algorithm that can detect other ocular diseases, such as POAG and AMD. Consequently, our aim in the current study was to develop a comprehensive eye evaluation algorithm that not only detects DR in retinal images, but also automatically identifies glaucoma suspects and AMD by integrating other personal medical information with the retinal features. The proposed system is fully automatic and provides the likelihood of each of the three eye disease. The system was evaluated in two datasets of 104 and 88 diabetic cases. For each eye, we used two non-mydriatic digital color fundus photographs (macula and optic disc centered) and, when available, information about age, duration of diabetes, cataracts, hypertension, gender, and laboratory data. Our results show that the combination of multimodal features can increase the AUC by up to 5%, 7%, and 8% in the detection of AMD, DR, and glaucoma respectively. Marked improvement was achieved when laboratory results were combined with retinal image features.
NASA Technical Reports Server (NTRS)
Nobbs, Steven G.
1995-01-01
An overview of the performance seeking control (PSC) algorithm and details of the important components of the algorithm are given. The onboard propulsion system models, the linear programming optimization, and engine control interface are described. The PSC algorithm receives input from various computers on the aircraft including the digital flight computer, digital engine control, and electronic inlet control. The PSC algorithm contains compact models of the propulsion system including the inlet, engine, and nozzle. The models compute propulsion system parameters, such as inlet drag and fan stall margin, which are not directly measurable in flight. The compact models also compute sensitivities of the propulsion system parameters to change in control variables. The engine model consists of a linear steady state variable model (SSVM) and a nonlinear model. The SSVM is updated with efficiency factors calculated in the engine model update logic, or Kalman filter. The efficiency factors are used to adjust the SSVM to match the actual engine. The propulsion system models are mathematically integrated to form an overall propulsion system model. The propulsion system model is then optimized using a linear programming optimization scheme. The goal of the optimization is determined from the selected PSC mode of operation. The resulting trims are used to compute a new operating point about which the optimization process is repeated. This process is continued until an overall (global) optimum is reached before applying the trims to the controllers.
The Xmath Integration Algorithm
ERIC Educational Resources Information Center
Bringslid, Odd
2009-01-01
The projects Xmath (Bringslid and Canessa, 2002) and dMath (Bringslid, de la Villa and Rodriguez, 2007) were supported by the European Commission in the so called Minerva Action (Xmath) and The Leonardo da Vinci programme (dMath). The Xmath eBook (Bringslid, 2006) includes algorithms into a wide range of undergraduate mathematical issues embedded…
Quantum gate decomposition algorithms.
Slepoy, Alexander
2006-07-01
Quantum computing algorithms can be conveniently expressed in a format of a quantum logical circuits. Such circuits consist of sequential coupled operations, termed ''quantum gates'', or quantum analogs of bits called qubits. We review a recently proposed method [1] for constructing general ''quantum gates'' operating on an qubits, as composed of a sequence of generic elementary ''gates''.
2005-03-30
The Robotic Follow Algorithm enables allows any robotic vehicle to follow a moving target while reactively choosing a route around nearby obstacles. The robotic follow behavior can be used with different camera systems and can be used with thermal or visual tracking as well as other tracking methods such as radio frequency tags.
Data Structures and Algorithms.
ERIC Educational Resources Information Center
Wirth, Niklaus
1984-01-01
Built-in data structures are the registers and memory words where binary values are stored; hard-wired algorithms are the fixed rules, embodied in electronic logic circuits, by which stored data are interpreted as instructions to be executed. Various topics related to these two basic elements of every computer program are discussed. (JN)
ERIC Educational Resources Information Center
Drake, Michael
2011-01-01
One debate that periodically arises in mathematics education is the issue of how to teach calculation more effectively. "Modern" approaches seem to initially favour mental calculation, informal methods, and the development of understanding before introducing written forms, while traditionalists tend to champion particular algorithms. The debate is…
Benchmarking monthly homogenization algorithms
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.
2011-08-01
The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data
MOPITT V7 Level 1 & Level 2 Release Announcement
Atmospheric Science Data Center
2016-08-02
MOPITT V7 Level 1 & Level 2 Release Announcement Wednesday, August 10, 2016 ... Infrared Radiances) • MOP01 - MOPITT Level 1 Radiances Several significant retrieval algorithm and product ... Featured improvements in the V7 retrieval products include (1) the representation of changing atmospheric concentrations of N2O, (2) ...
Mapping robust parallel multigrid algorithms to scalable memory architectures
NASA Technical Reports Server (NTRS)
Overman, Andrea; Vanrosendale, John
1993-01-01
The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids or anisotropic operators. The usual cure for this is the use of line or plane relaxation. However, multigrid algorithms based on line and plane relaxation have limited and awkward parallelism and are quite difficult to map effectively to highly parallel architectures. Newer multigrid algorithms that overcome anisotropy through the use of multiple coarse grids rather than relaxation are better suited to massively parallel architectures because they require only simple point-relaxation smoothers. In this paper, we look at the parallel implementation of a V-cycle multiple semicoarsened grid (MSG) algorithm on distributed-memory architectures such as the Intel iPSC/860 and Paragon computers. The MSG algorithms provide two levels of parallelism: parallelism within the relaxation or interpolation on each grid and across the grids on each multigrid level. Both levels of parallelism must be exploited to map these algorithms effectively to parallel architectures. This paper describes a mapping of an MSG algorithm to distributed-memory architectures that demonstrates how both levels of parallelism can be exploited. The result is a robust and effective multigrid algorithm for distributed-memory machines.
Mapping robust parallel multigrid algorithms to scalable memory architectures
NASA Technical Reports Server (NTRS)
Overman, Andrea; Vanrosendale, John
1993-01-01
The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids or anisotropic operators. The usual cure for this is the use of line or plane relaxation. However, multigrid algorithms based on line and plane relaxation have limited and awkward parallelism and are quite difficult to map effectively to highly parallel architectures. Newer multigrid algorithms that overcome anisotropy through the use of multiple coarse grids rather than line relaxation are better suited to massively parallel architectures because they require only simple point-relaxation smoothers. The parallel implementation of a V-cycle multiple semi-coarsened grid (MSG) algorithm or distributed-memory architectures such as the Intel iPSC/860 and Paragon computers is addressed. The MSG algorithms provide two levels of parallelism: parallelism within the relaxation or interpolation on each grid and across the grids on each multigrid level. Both levels of parallelism must be exploited to map these algorithms effectively to parallel architectures. A mapping of an MSG algorithm to distributed-memory architectures that demonstrate how both levels of parallelism can be exploited is described. The results is a robust and effective multigrid algorithm for distributed-memory machines.
A general algorithm for the construction of contour plots
NASA Technical Reports Server (NTRS)
Johnson, W.; Silva, F.
1981-01-01
An algorithm is described that performs the task of drawing equal level contours on a plane, which requires interpolation in two dimensions based on data prescribed at points distributed irregularly over the plane. The approach is described in detail. The computer program that implements the algorithm is documented and listed.
Applying a Genetic Algorithm to Reconfigurable Hardware
NASA Technical Reports Server (NTRS)
Wells, B. Earl; Weir, John; Trevino, Luis; Patrick, Clint; Steincamp, Jim
2004-01-01
This paper investigates the feasibility of applying genetic algorithms to solve optimization problems that are implemented entirely in reconfgurable hardware. The paper highlights the pe$ormance/design space trade-offs that must be understood to effectively implement a standard genetic algorithm within a modem Field Programmable Gate Array, FPGA, reconfgurable hardware environment and presents a case-study where this stochastic search technique is applied to standard test-case problems taken from the technical literature. In this research, the targeted FPGA-based platform and high-level design environment was the Starbridge Hypercomputing platform, which incorporates multiple Xilinx Virtex II FPGAs, and the Viva TM graphical hardware description language.
Algorithmic cooling in liquid-state nuclear magnetic resonance
NASA Astrophysics Data System (ADS)
Atia, Yosi; Elias, Yuval; Mor, Tal; Weinstein, Yossi
2016-01-01
Algorithmic cooling is a method that employs thermalization to increase qubit purification level; namely, it reduces the qubit system's entropy. We utilized gradient ascent pulse engineering, an optimal control algorithm, to implement algorithmic cooling in liquid-state nuclear magnetic resonance. Various cooling algorithms were applied onto the three qubits of C132-trichloroethylene, cooling the system beyond Shannon's entropy bound in several different ways. In particular, in one experiment a carbon qubit was cooled by a factor of 4.61. This work is a step towards potentially integrating tools of NMR quantum computing into in vivo magnetic-resonance spectroscopy.
Reactive Collision Avoidance Algorithm
NASA Technical Reports Server (NTRS)
Scharf, Daniel; Acikmese, Behcet; Ploen, Scott; Hadaegh, Fred
2010-01-01
The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on
Wire Detection Algorithms for Navigation
NASA Technical Reports Server (NTRS)
Kasturi, Rangachar; Camps, Octavia I.
2002-01-01
In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. Two approaches were explored for this purpose. The first approach involved a technique for sub-pixel edge detection and subsequent post processing, in order to reduce the false alarms. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter. The second approach involved the use of an example-based learning scheme namely, Support Vector Machines. The purpose of this approach was to explore the feasibility of an example-based learning based approach for the task of detecting wires from their images. Support Vector Machines (SVMs) have emerged as a promising pattern classification tool and have been used in various applications. It was found that this approach is not suitable for very thin wires and of course, not suitable at all for sub-pixel thick wires. High dimensionality of the data as such does not present a major problem for SVMs. However it is desirable to have a large number of training examples especially for high dimensional data. The main difficulty in using SVMs (or any other example-based learning
An efficient algorithm for function optimization: modified stem cells algorithm
NASA Astrophysics Data System (ADS)
Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad
2013-03-01
In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).
Algorithm Visualization System for Teaching Spatial Data Algorithms
ERIC Educational Resources Information Center
Nikander, Jussi; Helminen, Juha; Korhonen, Ari
2010-01-01
TRAKLA2 is a web-based learning environment for data structures and algorithms. The system delivers automatically assessed algorithm simulation exercises that are solved using a graphical user interface. In this work, we introduce a novel learning environment for spatial data algorithms, SDA-TRAKLA2, which has been implemented on top of the…
NASA Technical Reports Server (NTRS)
Arenstorf, Norbert S.; Jordan, Harry F.
1987-01-01
A barrier is a method for synchronizing a large number of concurrent computer processes. After considering some basic synchronization mechanisms, a collection of barrier algorithms with either linear or logarithmic depth are presented. A graphical model is described that profiles the execution of the barriers and other parallel programming constructs. This model shows how the interaction between the barrier algorithms and the work that they synchronize can impact their performance. One result is that logarithmic tree structured barriers show good performance when synchronizing fixed length work, while linear self-scheduled barriers show better performance when synchronizing fixed length work with an imbedded critical section. The linear barriers are better able to exploit the process skew associated with critical sections. Timing experiments, performed on an eighteen processor Flex/32 shared memory multiprocessor, that support these conclusions are detailed.
Algorithms, games, and evolution.
Chastain, Erick; Livnat, Adi; Papadimitriou, Christos; Vazirani, Umesh
2014-07-22
Even the most seasoned students of evolution, starting with Darwin himself, have occasionally expressed amazement that the mechanism of natural selection has produced the whole of Life as we see it around us. There is a computational way to articulate the same amazement: "What algorithm could possibly achieve all this in a mere three and a half billion years?" In this paper we propose an answer: We demonstrate that in the regime of weak selection, the standard equations of population genetics describing natural selection in the presence of sex become identical to those of a repeated game between genes played according to multiplicative weight updates (MWUA), an algorithm known in computer science to be surprisingly powerful and versatile. MWUA maximizes a tradeoff between cumulative performance and entropy, which suggests a new view on the maintenance of diversity in evolution.
Factorization using the quadratic sieve algorithm
Davis, J.A.; Holdridge, D.B.
1983-12-01
Since the cryptosecurity of the RSA two key cryptoalgorithm is no greater than the difficulty of factoring the modulus (product of two secret primes), a code that implements the Quadratic Sieve factorization algorithm on the CRAY I computer has been developed at the Sandia National Laboratories to determine as sharply as possible the current state-of-the-art in factoring. Because all viable attacks on RSA thus far proposed are equivalent to factorization of the modulus, sharper bounds on the computational difficulty of factoring permit improved estimates for the size of RSA parameters needed for given levels of cryptosecurity. Analysis of the Quadratic Sieve indicates that it may be faster than any previously published general purpose algorithm for factoring large integers. The high speed of the CRAY I coupled with the capability of the CRAY to pipeline certain vectorized operations make this algorithm (and code) the front runner in current factoring techniques.
Factorization using the quadratic sieve algorithm
Davis, J.A.; Holdridge, D.B.
1983-01-01
Since the cryptosecurity of the RSA two key cryptoalgorithm is no greater than the difficulty of factoring the modulus (product of two secret primes), a code that implements the Quadratic Sieve factorization algorithm on the CRAY I computer has been developed at the Sandia National Laboratories to determine as sharply as possible the current state-of-the-art in factoring. Because all viable attacks on RSA thus far proposed are equivalent to factorization of the modulus, sharper bounds on the computational difficulty of factoring permit improved estimates for the size of RSA parameters needed for given levels of cryptosecurity. Analysis of the Quadratic Sieve indicates that it may be faster than any previously published general purpose algorithm for factoring large integers. The high speed of the CRAY I coupled with the capability of the CRAY to pipeline certain vectorized operations make this algorithm (and code) the front runner in current factoring techniques.
New convergence estimates for multigrid algorithms
Bramble, J.H.; Pasciak, J.E.
1987-10-01
In this paper, new convergence estimates are proved for both symmetric and nonsymmetric multigrid algorithms applied to symmetric positive definite problems. Our theory relates the convergence of multigrid algorithms to a ''regularity and approximation'' parameter ..cap alpha.. epsilon (0, 1) and the number of relaxations m. We show that for the symmetric and nonsymmetric ..nu.. cycles, the multigrid iteration converges for any positive m at a rate which deteriorates no worse than 1-cj/sup -(1-//sup ..cap alpha..//sup )///sup ..cap alpha../, where j is the number of grid levels. We then define a generalized ..nu.. cycle algorithm which involves exponentially increasing (for example, doubling) the number of smoothings on successively coarser grids. We show that the resulting symmetric and nonsymmetric multigrid iterations converge for any ..cap alpha.. with rates that are independent of the mesh size. The theory is presented in an abstract setting which can be applied to finite element multigrid and finite difference multigrid methods.
Algorithm for fixed-range optimal trajectories
NASA Technical Reports Server (NTRS)
Lee, H. Q.; Erzberger, H.
1980-01-01
An algorithm for synthesizing optimal aircraft trajectories for specified range was developed and implemented in a computer program written in FORTRAN IV. The algorithm, its computer implementation, and a set of example optimum trajectories for the Boeing 727-100 aircraft are described. The algorithm optimizes trajectories with respect to a cost function that is the weighted sum of fuel cost and time cost. The optimum trajectory consists at most of a three segments: climb, cruise, and descent. The climb and descent profiles are generated by integrating a simplified set of kinematic and dynamic equations wherein the total energy of the aircraft is the independent or time like variable. At each energy level the optimum airspeeds and thrust settings are obtained as the values that minimize the variational Hamiltonian. Although the emphasis is on an off-line, open-loop computation, eventually the most important application will be in an on-board flight management system.
Two algorithms for fitting constrained marginal models
Evans, R.J.; Forcina, A.
2013-01-01
The two main algorithms that have been considered for fitting constrained marginal models to discrete data, one based on Lagrange multipliers and the other on a regression model, are studied in detail. It is shown that the updates produced by the two methods are identical, but that the Lagrangian method is more efficient in the case of identically distributed observations. A generalization is given of the regression algorithm for modelling the effect of exogenous individual-level covariates, a context in which the use of the Lagrangian algorithm would be infeasible for even moderate sample sizes. An extension of the method to likelihood-based estimation under L1-penalties is also considered. PMID:23794772
A danger-theory-based immune network optimization algorithm.
Zhang, Ruirui; Li, Tao; Xiao, Xin; Shi, Yuanquan
2013-01-01
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times.
A controllable sensor management algorithm capable of learning
NASA Astrophysics Data System (ADS)
Osadciw, Lisa A.; Veeramacheneni, Kalyan K.
2005-03-01
Sensor management technology progress is challenged by the geographic space it spans, the heterogeneity of the sensors, and the real-time timeframes within which plans controlling the assets are executed. This paper presents a new sensor management paradigm and demonstrates its application in a sensor management algorithm designed for a biometric access control system. This approach consists of an artificial intelligence (AI) algorithm focused on uncertainty measures, which makes the high level decisions to reduce uncertainties and interfaces with the user, integrated cohesively with a bottom up evolutionary algorithm, which optimizes the sensor network"s operation as determined by the AI algorithm. The sensor management algorithm presented is composed of a Bayesian network, the AI algorithm component, and a swarm optimization algorithm, the evolutionary algorithm. Thus, the algorithm can change its own performance goals in real-time and will modify its own decisions based on observed measures within the sensor network. The definition of the measures as well as the Bayesian network determine the robustness of the algorithm and its utility in reacting dynamically to changes in the global system.
Adaptive continuous twisting algorithm
NASA Astrophysics Data System (ADS)
Moreno, Jaime A.; Negrete, Daniel Y.; Torres-González, Victor; Fridman, Leonid
2016-09-01
In this paper, an adaptive continuous twisting algorithm (ACTA) is presented. For double integrator, ACTA produces a continuous control signal ensuring finite time convergence of the states to zero. Moreover, the control signal generated by ACTA compensates the Lipschitz perturbation in finite time, i.e. its value converges to the opposite value of the perturbation. ACTA also keeps its convergence properties, even in the case that the upper bound of the derivative of the perturbation exists, but it is unknown.
Quantum defragmentation algorithm
Burgarth, Daniel; Giovannetti, Vittorio
2010-08-15
In this addendum to our paper [D. Burgarth and V. Giovannetti, Phys. Rev. Lett. 99, 100501 (2007)] we prove that during the transformation that allows one to enforce control by relaxation on a quantum system, the ancillary memory can be kept at a finite size, independently from the fidelity one wants to achieve. The result is obtained by introducing the quantum analog of defragmentation algorithms which are employed for efficiently reorganizing classical information in conventional hard disks.
Basic cluster compression algorithm
NASA Technical Reports Server (NTRS)
Hilbert, E. E.; Lee, J.
1980-01-01
Feature extraction and data compression of LANDSAT data is accomplished by BCCA program which reduces costs associated with transmitting, storing, distributing, and interpreting multispectral image data. Algorithm uses spatially local clustering to extract features from image data to describe spectral characteristics of data set. Approach requires only simple repetitive computations, and parallel processing can be used for very high data rates. Program is written in FORTRAN IV for batch execution and has been implemented on SEL 32/55.
NOSS altimeter algorithm specifications
NASA Technical Reports Server (NTRS)
Hancock, D. W.; Forsythe, R. G.; Mcmillan, J. D.
1982-01-01
A description of all algorithms required for altimeter processing is given. Each description includes title, description, inputs/outputs, general algebraic sequences and data volume. All required input/output data files are described and the computer resources required for the entire altimeter processing system were estimated. The majority of the data processing requirements for any radar altimeter of the Seasat-1 type are scoped. Additions and deletions could be made for the specific altimeter products required by other projects.
NASA Astrophysics Data System (ADS)
Evertz, Hans Gerd
1998-03-01
Exciting new investigations have recently become possible for strongly correlated systems of spins, bosons, and fermions, through Quantum Monte Carlo simulations with the Loop Algorithm (H.G. Evertz, G. Lana, and M. Marcu, Phys. Rev. Lett. 70, 875 (1993).) (For a recent review see: H.G. Evertz, cond- mat/9707221.) and its generalizations. A review of this new method, its generalizations and its applications is given, including some new results. The Loop Algorithm is based on a formulation of physical models in an extended ensemble of worldlines and graphs, and is related to Swendsen-Wang cluster algorithms. It performs nonlocal changes of worldline configurations, determined by local stochastic decisions. It overcomes many of the difficulties of traditional worldline simulations. Computer time requirements are reduced by orders of magnitude, through a corresponding reduction in autocorrelations. The grand-canonical ensemble (e.g. varying winding numbers) is naturally simulated. The continuous time limit can be taken directly. Improved Estimators exist which further reduce the errors of measured quantities. The algorithm applies unchanged in any dimension and for varying bond-strengths. It becomes less efficient in the presence of strong site disorder or strong magnetic fields. It applies directly to locally XYZ-like spin, fermion, and hard-core boson models. It has been extended to the Hubbard and the tJ model and generalized to higher spin representations. There have already been several large scale applications, especially for Heisenberg-like models, including a high statistics continuous time calculation of quantum critical exponents on a regularly depleted two-dimensional lattice of up to 20000 spatial sites at temperatures down to T=0.01 J.
Genetic Algorithm for Optimization: Preprocessor and Algorithm
NASA Technical Reports Server (NTRS)
Sen, S. K.; Shaykhian, Gholam A.
2006-01-01
Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.
[Algorithm for treating preoperative anemia].
Bisbe Vives, E; Basora Macaya, M
2015-06-01
Hemoglobin optimization and treatment of preoperative anemia in surgery with a moderate to high risk of surgical bleeding reduces the rate of transfusions and improves hemoglobin levels at discharge and can also improve postoperative outcomes. To this end, we need to schedule preoperative visits sufficiently in advance to treat the anemia. The treatment algorithm we propose comes with a simple checklist to determine whether we should refer the patient to a specialist or if we can treat the patient during the same visit. With the blood count test and additional tests for iron metabolism, inflammation parameter and glomerular filtration rate, we can decide whether to start the treatment with intravenous iron alone or erythropoietin with or without iron. With significant anemia, a visit after 15 days might be necessary to observe the response and supplement the treatment if required. The hemoglobin objective will depend on the type of surgery and the patient's characteristics.
Large scale tracking algorithms.
Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett; Karelitz, David B.; Pitts, Todd Alan; Zollweg, Joshua David; Anderson, Dylan Z.; Nandy, Prabal; Whitlow, Gary L.; Bender, Daniel A.; Byrne, Raymond Harry
2015-01-01
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
Symbalisty, E.M.D.; Zinn, J.; Whitaker, R.W.
1995-09-01
This paper describes the history, physics, and algorithms of the computer code RADFLO and its extension HYCHEM. RADFLO is a one-dimensional, radiation-transport hydrodynamics code that is used to compute early-time fireball behavior for low-altitude nuclear bursts. The primary use of the code is the prediction of optical signals produced by nuclear explosions. It has also been used to predict thermal and hydrodynamic effects that are used for vulnerability and lethality applications. Another closely related code, HYCHEM, is an extension of RADFLO which includes the effects of nonequilibrium chemistry. Some examples of numerical results will be shown, along with scaling expressions derived from those results. We describe new computations of the structures and luminosities of steady-state shock waves and radiative thermal waves, which have been extended to cover a range of ambient air densities for high-altitude applications. We also describe recent modifications of the codes to use a one-dimensional analog of the CAVEAT fluid-dynamics algorithm in place of the former standard Richtmyer-von Neumann algorithm.
Evaluating super resolution algorithms
NASA Astrophysics Data System (ADS)
Kim, Youn Jin; Park, Jong Hyun; Shin, Gun Shik; Lee, Hyun-Seung; Kim, Dong-Hyun; Park, Se Hyeok; Kim, Jaehyun
2011-01-01
This study intends to establish a sound testing and evaluation methodology based upon the human visual characteristics for appreciating the image restoration accuracy; in addition to comparing the subjective results with predictions by some objective evaluation methods. In total, six different super resolution (SR) algorithms - such as iterative back-projection (IBP), robust SR, maximum a posteriori (MAP), projections onto convex sets (POCS), a non-uniform interpolation, and frequency domain approach - were selected. The performance comparison between the SR algorithms in terms of their restoration accuracy was carried out through both subjectively and objectively. The former methodology relies upon the paired comparison method that involves the simultaneous scaling of two stimuli with respect to image restoration accuracy. For the latter, both conventional image quality metrics and color difference methods are implemented. Consequently, POCS and a non-uniform interpolation outperformed the others for an ideal situation, while restoration based methods appear more accurate to the HR image in a real world case where any prior information about the blur kernel is remained unknown. However, the noise-added-image could not be restored successfully by any of those methods. The latest International Commission on Illumination (CIE) standard color difference equation CIEDE2000 was found to predict the subjective results accurately and outperformed conventional methods for evaluating the restoration accuracy of those SR algorithms.
An Algorithm for Autonomous Formation Obstacle Avoidance
NASA Astrophysics Data System (ADS)
Cruz, Yunior I.
The level of human interaction with Unmanned Aerial Systems varies greatly from remotely piloted aircraft to fully autonomous systems. In the latter end of the spectrum, the challenge lies in designing effective algorithms to dictate the behavior of the autonomous agents. A swarm of autonomous Unmanned Aerial Vehicles requires collision avoidance and formation flight algorithms to negotiate environmental challenges it may encounter during the execution of its mission, which may include obstacles and chokepoints. In this work, a simple algorithm is developed to allow a formation of autonomous vehicles to perform point to point navigation while avoiding obstacles and navigating through chokepoints. Emphasis is placed on maintaining formation structures. Rather than breaking formation and individually navigating around the obstacle or through the chokepoint, vehicles are required to assemble into appropriately sized/shaped sub-formations, bifurcate around the obstacle or negotiate the chokepoint, and reassemble into the original formation at the far side of the obstruction. The algorithm receives vehicle and environmental properties as inputs and outputs trajectories for each vehicle from start to the desired ending location. Simulation results show that the algorithm safely routes all vehicles past the obstruction while adhering to the aforementioned requirements. The formation adapts and successfully negotiates the obstacles and chokepoints in its path while maintaining proper vehicle separation.
Connected-Health Algorithm: Development and Evaluation.
Vlahu-Gjorgievska, Elena; Koceski, Saso; Kulev, Igor; Trajkovik, Vladimir
2016-04-01
Nowadays, there is a growing interest towards the adoption of novel ICT technologies in the field of medical monitoring and personal health care systems. This paper proposes design of a connected health algorithm inspired from social computing paradigm. The purpose of the algorithm is to give a recommendation for performing a specific activity that will improve user's health, based on his health condition and set of knowledge derived from the history of the user and users with similar attitudes to him. The algorithm could help users to have bigger confidence in choosing their physical activities that will improve their health. The proposed algorithm has been experimentally validated using real data collected from a community of 1000 active users. The results showed that the recommended physical activity, contributed towards weight loss of at least 0.5 kg, is found in the first half of the ordered list of recommendations, generated by the algorithm, with the probability > 0.6 with 1 % level of significance. PMID:26922593
SLAP lesions: a treatment algorithm.
Brockmeyer, Matthias; Tompkins, Marc; Kohn, Dieter M; Lorbach, Olaf
2016-02-01
Tears of the superior labrum involving the biceps anchor are a common entity, especially in athletes, and may highly impair shoulder function. If conservative treatment fails, successful arthroscopic repair of symptomatic SLAP lesions has been described in the literature particularly for young athletes. However, the results in throwing athletes are less successful with a significant amount of patients who will not regain their pre-injury level of performance. The clinical results of SLAP repairs in middle-aged and older patients are mixed, with worse results and higher revision rates as compared to younger patients. In this population, tenotomy or tenodesis of the biceps tendon is a viable alternative to SLAP repairs in order to improve clinical outcomes. The present article introduces a treatment algorithm for SLAP lesions based upon the recent literature as well as the authors' clinical experience. The type of lesion, age of patient, concomitant lesions, and functional requirements, as well as sport activity level of the patient, need to be considered. Moreover, normal variations and degenerative changes in the SLAP complex have to be distinguished from "true" SLAP lesions in order to improve results and avoid overtreatment. The suggestion for a treatment algorithm includes: type I: conservative treatment or arthroscopic debridement, type II: SLAP repair or biceps tenotomy/tenodesis, type III: resection of the instable bucket-handle tear, type IV: SLAP repair (biceps tenotomy/tenodesis if >50 % of biceps tendon is affected), type V: Bankart repair and SLAP repair, type VI: resection of the flap and SLAP repair, and type VII: refixation of the anterosuperior labrum and SLAP repair.
Design of robust systolic algorithms
Varman, P.J.; Fussell, D.S.
1983-01-01
A primary reason for the susceptibility of systolic algorithms to faults is their strong dependence on the interconnection between the processors in a systolic array. A technique to transform any linear systolic algorithm into an equivalent pipelined algorithm that executes on arbitrary trees is presented. 5 references.
Multipartite entanglement in quantum algorithms
Bruss, D.; Macchiavello, C.
2011-05-15
We investigate the entanglement features of the quantum states employed in quantum algorithms. In particular, we analyze the multipartite entanglement properties in the Deutsch-Jozsa, Grover, and Simon algorithms. Our results show that for these algorithms most instances involve multipartite entanglement.
Two Meanings of Algorithmic Mathematics.
ERIC Educational Resources Information Center
Maurer, Stephen B.
1984-01-01
Two mathematical topics are interpreted from the viewpoints of traditional (performing algorithms) and contemporary (creating algorithms and thinking in terms of them for solving problems and developing theory) algorithmic mathematics. The two topics are Horner's method for evaluating polynomials and Gauss's method for solving systems of linear…
Algorithm for Constructing Contour Plots
NASA Technical Reports Server (NTRS)
Johnson, W.; Silva, F.
1984-01-01
General computer algorithm developed for construction of contour plots. algorithm accepts as input data values at set of points irregularly distributed over plane. Algorithm based on interpolation scheme: points in plane connected by straight-line segments to form set of triangles. Program written in FORTRAN IV.
The clinical algorithm nosology: a method for comparing algorithmic guidelines.
Pearson, S D; Margolis, C Z; Davis, S; Schreier, L K; Gottlieb, L K
1992-01-01
Concern regarding the cost and quality of medical care has led to a proliferation of competing clinical practice guidelines. No technique has been described for determining objectively the degree of similarity between alternative guidelines for the same clinical problem. The authors describe the development of the Clinical Algorithm Nosology (CAN), a new method to compare one form of guideline: the clinical algorithm. The CAN measures overall design complexity independent of algorithm content, qualitatively describes the clinical differences between two alternative algorithms, and then scores the degree of similarity between them. CAN algorithm design-complexity scores correlated highly with clinicians' estimates of complexity on an ordinal scale (r = 0.86). Five pairs of clinical algorithms addressing three topics (gallstone lithotripsy, thyroid nodule, and sinusitis) were selected for interrater reliability testing of the CAN clinical-similarity scoring system. Raters categorized the similarity of algorithm pathways in alternative algorithms as "identical," "similar," or "different." Interrater agreement was achieved on 85/109 scores (80%), weighted kappa statistic, k = 0.73. It is concluded that the CAN is a valid method for determining the structural complexity of clinical algorithms, and a reliable method for describing differences and scoring the similarity between algorithms for the same clinical problem. In the future, the CAN may serve to evaluate the reliability of algorithm development programs, and to support providers and purchasers in choosing among alternative clinical guidelines.
Improved multiprocessor garbage collection algorithms
Newman, I.A.; Stallard, R.P.; Woodward, M.C.
1983-01-01
Outlines the results of an investigation of existing multiprocessor garbage collection algorithms and introduces two new algorithms which significantly improve some aspects of the performance of their predecessors. The two algorithms arise from different starting assumptions. One considers the case where the algorithm will terminate successfully whatever list structure is being processed and assumes that the extra data space should be minimised. The other seeks a very fast garbage collection time for list structures that do not contain loops. Results of both theoretical and experimental investigations are given to demonstrate the efficacy of the algorithms. 7 references.
De Groot, A.J.
1989-01-01
In this dissertation the author considered the design of bit - level systolic arrays where the basic computational unit consists of a simple one - bit logic unit, so that the systolic process is carried out at the level of individual bits. In order to pursue the foregoing research, several areas have been studied. First, the concept of systolic processing has been investigated. Several important algorithms were investigated and put into systolic form using graph-theoretic methods. The bit-level, word-level and block-level systolic arrays which have been designed for these algorithms exhibit linear speedup with respect to the number of processors and exhibit efficiency close to 100%, even with low interprocessor communication bandwidth. Block-level systolic arrays deal with blocks of data with block-level operations and communications. Block-level systolic arrays improve cell efficiency and are more efficient than their word-level counterparts. A comparison of bit-level, word-level and block-level systolic arrays was performed. In order to verify the foregoing theory and analysis a systolic processor called the SPRINT was developed to provide and environment where bit-level, word-level and block-level systolic algorithms could be confirmed by direct implementation rather than by computer simulation. The SPRINT is a supercomputer class, 64-element multiprocessor with a reconfigurable interconnection network. The theory has been confirmed by the execution on the SPRINT of the bit-level, word-level, and block-level systolic algorithms presented in the dissertation.
Fast algorithms for transport models. Final report
Manteuffel, T.A.
1994-10-01
This project has developed a multigrid in space algorithm for the solution of the S{sub N} equations with isotropic scattering in slab geometry. The algorithm was developed for the Modified Linear Discontinuous (MLD) discretization in space which is accurate in the thick diffusion limit. It uses a red/black two-cell {mu}-line relaxation. This relaxation solves for all angles on two adjacent spatial cells simultaneously. It takes advantage of the rank-one property of the coupling between angles and can perform this inversion in O(N) operations. A version of the multigrid in space algorithm was programmed on the Thinking Machines Inc. CM-200 located at LANL. It was discovered that on the CM-200 a block Jacobi type iteration was more efficient than the block red/black iteration. Given sufficient processors all two-cell block inversions can be carried out simultaneously with a small number of parallel steps. The bottleneck is the need for sums of N values, where N is the number of discrete angles, each from a different processor. These are carried out by machine intrinsic functions and are well optimized. The overall algorithm has computational complexity O(log(M)), where M is the number of spatial cells. The algorithm is very efficient and represents the state-of-the-art for isotropic problems in slab geometry. For anisotropic scattering in slab geometry, a multilevel in angle algorithm was developed. A parallel version of the multilevel in angle algorithm has also been developed. Upon first glance, the shifted transport sweep has limited parallelism. Once the right-hand-side has been computed, the sweep is completely parallel in angle, becoming N uncoupled initial value ODE`s. The author has developed a cyclic reduction algorithm that renders it parallel with complexity O(log(M)). The multilevel in angle algorithm visits log(N) levels, where shifted transport sweeps are performed. The overall complexity is O(log(N)log(M)).
Algorithms for physical segregation of coal
NASA Astrophysics Data System (ADS)
Ganguli, Rajive
The capability for on-line measurement of the quality characteristics of conveyed coal now enables mine operators to take advantage of the inherent heterogeneity of those streams and split them into wash and no-wash stocks. Relative to processing the entire stream, this reduces the amount of coal that must be washed at the mine and thereby reduces processing costs, recovery losses, and refuse generation levels. In this dissertation, two classes of segregation algorithms, using time series models and moving windows are developed and demonstrated using field and simulated data. In all of the developed segregation algorithms, a "cut-off" ash value was computed for coal scanned on the running conveyor belt by the ash analyzer. It determined if the coal was sent to the wash pile or to the nowash pile. Forecasts from time series models, at various lead times ahead, were used in one class of the developed algorithms, to determine the cut-off ash levels. The time series models were updated from time to time to reflect changes in process. Statistical Process Control (SPC) techniques were used to determine if an update was necessary at a given time. When an update was deemed necessary, optimization techniques were used to determine the next best set of model parameters. In the other class of segregation algorithms, "few" of the immediate past observations were used to determine the cut-off ash value. These "few" observations were called the window width . The window width was kept constant in some variants of this class of algorithms. The other variants of this class were an improvement over the fixed window width algorithms. Here, the window widths were varied rather than kept constant. In these cases, SPC was used to determine the window width at any instant. Statistics of the empirical distribution and the normal distribution were used in computation of the cut-off ash value in all the variants of this class of algorithms. The good performance of the developed algorithms
NASA Technical Reports Server (NTRS)
Vardi, A.
1984-01-01
The representation min t s.t. F(I)(x). - t less than or equal to 0 for all i is examined. An active set strategy is designed of functions: active, semi-active, and non-active. This technique will help in preventing zigzagging which often occurs when an active set strategy is used. Some of the inequality constraints are handled with slack variables. Also a trust region strategy is used in which at each iteration there is a sphere around the current point in which the local approximation of the function is trusted. The algorithm is implemented into a successful computer program. Numerical results are provided.
Parallel algorithm development
Adams, T.F.
1996-06-01
Rapid changes in parallel computing technology are causing significant changes in the strategies being used for parallel algorithm development. One approach is simply to write computer code in a standard language like FORTRAN 77 or with the expectation that the compiler will produce executable code that will run in parallel. The alternatives are: (1) to build explicit message passing directly into the source code; or (2) to write source code without explicit reference to message passing or parallelism, but use a general communications library to provide efficient parallel execution. Application of these strategies is illustrated with examples of codes currently under development.
MLP iterative construction algorithm
NASA Astrophysics Data System (ADS)
Rathbun, Thomas F.; Rogers, Steven K.; DeSimio, Martin P.; Oxley, Mark E.
1997-04-01
The MLP Iterative Construction Algorithm (MICA) designs a Multi-Layer Perceptron (MLP) neural network as it trains. MICA adds Hidden Layer Nodes one at a time, separating classes on a pair-wise basis, until the data is projected into a linear separable space by class. Then MICA trains the Output Layer Nodes, which results in an MLP that achieves 100% accuracy on the training data. MICA, like Backprop, produces an MLP that is a minimum mean squared error approximation of the Bayes optimal discriminant function. Moreover, MICA's training technique yields novel feature selection technique and hidden node pruning technique
A Polynomial Time, Numerically Stable Integer Relation Algorithm
NASA Technical Reports Server (NTRS)
Ferguson, Helaman R. P.; Bailey, Daivd H.; Kutler, Paul (Technical Monitor)
1998-01-01
Let x = (x1, x2...,xn be a vector of real numbers. X is said to possess an integer relation if there exist integers a(sub i) not all zero such that a1x1 + a2x2 + ... a(sub n)Xn = 0. Beginning in 1977 several algorithms (with proofs) have been discovered to recover the a(sub i) given x. The most efficient of these existing integer relation algorithms (in terms of run time and the precision required of the input) has the drawback of being very unstable numerically. It often requires a numeric precision level in the thousands of digits to reliably recover relations in modest-sized test problems. We present here a new algorithm for finding integer relations, which we have named the "PSLQ" algorithm. It is proved in this paper that the PSLQ algorithm terminates with a relation in a number of iterations that is bounded by a polynomial in it. Because this algorithm employs a numerically stable matrix reduction procedure, it is free from the numerical difficulties, that plague other integer relation algorithms. Furthermore, its stability admits an efficient implementation with lower run times oil average than other algorithms currently in Use. Finally, this stability can be used to prove that relation bounds obtained from computer runs using this algorithm are numerically accurate.
Optimal multisensor decision fusion of mine detection algorithms
NASA Astrophysics Data System (ADS)
Liao, Yuwei; Nolte, Loren W.; Collins, Leslie M.
2003-09-01
Numerous detection algorithms, using various sensor modalities, have been developed for the detection of mines in cluttered and noisy backgrounds. The performance for each detection algorithm is typically reported in terms of the Receiver Operating Characteristic (ROC), which is a plot of the probability of detection versus false alarm as a function of the threshold setting on the output decision variable of each algorithm. In this paper we present multi-sensor decision fusion algorithms that combine the local decisions of existing detection algorithms for different sensors. This offers, in certain situations, an expedient, attractive and much simpler alternative to "starting over" with the redesign of a new algorithm which fuses multiple sensors at the data level. The goal in our multi-sensor decision fusion approach is to exploit complimentary strengths of existing multi-sensor algorithms so as to achieve performance (ROC) that exceeds the performance of any sensor algorithm operating in isolation. Our approach to multi-sensor decision fusion is based on optimal signal detection theory, using the likelihood ratio. We consider the optimal fusion of local decisions for two sensors, GPR (ground penetrating radar) and MD (metal detector). A new robust algorithm for decision fusion is presented that addresses the problem that the statistics of the training data is not likely to exactly match the statistics of the test data. ROC's are presented and compared for real data.
NASA Technical Reports Server (NTRS)
Merceret, Francis; Lane, John; Immer, Christopher; Case, Jonathan; Manobianco, John
2005-01-01
The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.
Automated Vectorization of Decision-Based Algorithms
NASA Technical Reports Server (NTRS)
James, Mark
2006-01-01
Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.
Algorithms and programming tools for image processing on the MPP, introduction. Thesis
NASA Technical Reports Server (NTRS)
1985-01-01
The programming tools and parallel algorithms created for the Massively Parallel Processor (MPP) located at the NASA Goddard Space Center are discussed. A user-friendly environment for high level language parallel algorithm development was developed. The issues involved in implementing certain algorithms on the MPP were researched. The expected results were compared with the actual results.
Study of image matching algorithm and sub-pixel fitting algorithm in target tracking
NASA Astrophysics Data System (ADS)
Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu
2015-03-01
Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image
The algorithmic origins of life
Walker, Sara Imari; Davies, Paul C. W.
2013-01-01
Although it has been notoriously difficult to pin down precisely what is it that makes life so distinctive and remarkable, there is general agreement that its informational aspect is one key property, perhaps the key property. The unique informational narrative of living systems suggests that life may be characterized by context-dependent causal influences, and, in particular, that top-down (or downward) causation—where higher levels influence and constrain the dynamics of lower levels in organizational hierarchies—may be a major contributor to the hierarchal structure of living systems. Here, we propose that the emergence of life may correspond to a physical transition associated with a shift in the causal structure, where information gains direct and context-dependent causal efficacy over the matter in which it is instantiated. Such a transition may be akin to more traditional physical transitions (e.g. thermodynamic phase transitions), with the crucial distinction that determining which phase (non-life or life) a given system is in requires dynamical information and therefore can only be inferred by identifying causal architecture. We discuss some novel research directions based on this hypothesis, including potential measures of such a transition that may be amenable to laboratory study, and how the proposed mechanism corresponds to the onset of the unique mode of (algorithmic) information processing characteristic of living systems. PMID:23235265
Control Algorithms For Liquid-Cooled Garments
NASA Technical Reports Server (NTRS)
Drew, B.; Harner, K.; Hodgson, E.; Homa, J.; Jennings, D.; Yanosy, J.
1988-01-01
Three algorithms developed for control of cooling in protective garments. Metabolic rate inferred from temperatures of cooling liquid outlet and inlet, suitably filtered to account for thermal lag of human body. Temperature at inlet adjusted to value giving maximum comfort at inferred metabolic rate. Applicable to space suits, used for automatic control of cooling in suits worn by workers in radioactive, polluted, or otherwise hazardous environments. More effective than manual control, subject to frequent, overcompensated adjustments as level of activity varies.
STAR Algorithm Integration Team - Facilitating operational algorithm development
NASA Astrophysics Data System (ADS)
Mikles, V. J.
2015-12-01
The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.
Algorithm aversion: people erroneously avoid algorithms after seeing them err.
Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade
2015-02-01
Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.
Teaching Algorithm Efficiency at CS1 Level: A Different Approach
ERIC Educational Resources Information Center
Gal-Ezer, Judith; Vilner, Tamar; Zur, Ela
2004-01-01
Realizing the importance of teaching efficiency at early stages of the program of study in computer science (CS) on one hand, and the difficulties encountered when introducing this concept on the other, we advocate a different didactic approach in the introductory CS course (CS1). This paper describes the approach as it is used at the Open…
Implicit level set algorithms for modelling hydraulic fracture propagation.
Peirce, A
2016-10-13
Hydraulic fractures are tensile cracks that propagate in pre-stressed solid media due to the injection of a viscous fluid. Developing numerical schemes to model the propagation of these fractures is particularly challenging due to the degenerate, hypersingular nature of the coupled integro-partial differential equations. These equations typically involve a singular free boundary whose velocity can only be determined by evaluating a distinguished limit. This review paper describes a class of numerical schemes that have been developed to use the multiscale asymptotic behaviour typically encountered near the fracture boundary as multiple physical processes compete to determine the evolution of the fracture. The fundamental concepts of locating the free boundary using the tip asymptotics and imposing the tip asymptotic behaviour in a weak form are illustrated in two quite different formulations of the governing equations. These formulations are the displacement discontinuity boundary integral method and the extended finite-element method. Practical issues are also discussed, including new models for proppant transport able to capture 'tip screen-out'; efficient numerical schemes to solve the coupled nonlinear equations; and fast methods to solve resulting linear systems. Numerical examples are provided to illustrate the performance of the numerical schemes. We conclude the paper with open questions for further research. This article is part of the themed issue 'Energy and the subsurface'. PMID:27597787
Implicit level set algorithms for modelling hydraulic fracture propagation.
Peirce, A
2016-10-13
Hydraulic fractures are tensile cracks that propagate in pre-stressed solid media due to the injection of a viscous fluid. Developing numerical schemes to model the propagation of these fractures is particularly challenging due to the degenerate, hypersingular nature of the coupled integro-partial differential equations. These equations typically involve a singular free boundary whose velocity can only be determined by evaluating a distinguished limit. This review paper describes a class of numerical schemes that have been developed to use the multiscale asymptotic behaviour typically encountered near the fracture boundary as multiple physical processes compete to determine the evolution of the fracture. The fundamental concepts of locating the free boundary using the tip asymptotics and imposing the tip asymptotic behaviour in a weak form are illustrated in two quite different formulations of the governing equations. These formulations are the displacement discontinuity boundary integral method and the extended finite-element method. Practical issues are also discussed, including new models for proppant transport able to capture 'tip screen-out'; efficient numerical schemes to solve the coupled nonlinear equations; and fast methods to solve resulting linear systems. Numerical examples are provided to illustrate the performance of the numerical schemes. We conclude the paper with open questions for further research. This article is part of the themed issue 'Energy and the subsurface'.
Highly Scalable Matching Pursuit Signal Decomposition Algorithm
NASA Technical Reports Server (NTRS)
Christensen, Daniel; Das, Santanu; Srivastava, Ashok N.
2009-01-01
Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the
ICESat-2 / ATLAS Flight Science Receiver Algorithms
NASA Astrophysics Data System (ADS)
Mcgarry, J.; Carabajal, C. C.; Degnan, J. J.; Mallama, A.; Palm, S. P.; Ricklefs, R.; Saba, J. L.
2013-12-01
NASA's Advanced Topographic Laser Altimeter System (ATLAS) will be the single instrument on the ICESat-2 spacecraft which is expected to launch in 2016 with a 3 year mission lifetime. The ICESat-2 orbital altitude will be 500 km with a 92 degree inclination and 91-day repeat tracks. ATLAS is a single photon detection system transmitting at 532nm with a laser repetition rate of 10 kHz and a 6 spot pattern on the Earth's surface. Without some method of eliminating solar background noise in near real-time, the volume of ATLAS telemetry would far exceed the normal X-band downlink capability. To reduce the data volume to an acceptable level a set of onboard Receiver Algorithms has been developed. These Algorithms limit the daily data volume by distinguishing surface echoes from the background noise and allow the instrument to telemeter only a small vertical region about the signal. This is accomplished through the use of an onboard Digital Elevation Model (DEM), signal processing techniques, and an onboard relief map. Similar to what was flown on the ATLAS predecessor GLAS (Geoscience Laser Altimeter System) the DEM provides minimum and maximum heights for each 1 degree x 1 degree tile on the Earth. This information allows the onboard algorithm to limit its signal search to the region between minimum and maximum heights (plus some margin for errors). The understanding that the surface echoes will tend to clump while noise will be randomly distributed led us to histogram the received event times. The selection of the signal locations is based on those histogram bins with statistically significant counts. Once the signal location has been established the onboard Digital Relief Map (DRM) is used to determine the vertical width of the telemetry band about the signal. The ATLAS Receiver Algorithms are nearing completion of the development phase and are currently being tested using a Monte Carlo Software Simulator that models the instrument, the orbit and the environment
Multisensor data fusion algorithm development
Yocky, D.A.; Chadwick, M.D.; Goudy, S.P.; Johnson, D.K.
1995-12-01
This report presents a two-year LDRD research effort into multisensor data fusion. We approached the problem by addressing the available types of data, preprocessing that data, and developing fusion algorithms using that data. The report reflects these three distinct areas. First, the possible data sets for fusion are identified. Second, automated registration techniques for imagery data are analyzed. Third, two fusion techniques are presented. The first fusion algorithm is based on the two-dimensional discrete wavelet transform. Using test images, the wavelet algorithm is compared against intensity modulation and intensity-hue-saturation image fusion algorithms that are available in commercial software. The wavelet approach outperforms the other two fusion techniques by preserving spectral/spatial information more precisely. The wavelet fusion algorithm was also applied to Landsat Thematic Mapper and SPOT panchromatic imagery data. The second algorithm is based on a linear-regression technique. We analyzed the technique using the same Landsat and SPOT data.
NASA Technical Reports Server (NTRS)
Memarsadeghi, Nargess
2011-01-01
More efficient versions of an interpolation method, called kriging, have been introduced in order to reduce its traditionally high computational cost. Written in C++, these approaches were tested on both synthetic and real data. Kriging is a best unbiased linear estimator and suitable for interpolation of scattered data points. Kriging has long been used in the geostatistic and mining communities, but is now being researched for use in the image fusion of remotely sensed data. This allows a combination of data from various locations to be used to fill in any missing data from any single location. To arrive at the faster algorithms, sparse SYMMLQ iterative solver, covariance tapering, Fast Multipole Methods (FMM), and nearest neighbor searching techniques were used. These implementations were used when the coefficient matrix in the linear system is symmetric, but not necessarily positive-definite.
Fighting Censorship with Algorithms
NASA Astrophysics Data System (ADS)
Mahdian, Mohammad
In countries such as China or Iran where Internet censorship is prevalent, users usually rely on proxies or anonymizers to freely access the web. The obvious difficulty with this approach is that once the address of a proxy or an anonymizer is announced for use to the public, the authorities can easily filter all traffic to that address. This poses a challenge as to how proxy addresses can be announced to users without leaking too much information to the censorship authorities. In this paper, we formulate this question as an interesting algorithmic problem. We study this problem in a static and a dynamic model, and give almost tight bounds on the number of proxy servers required to give access to n people k of whom are adversaries. We will also discuss how trust networks can be used in this context.
Ozone Uncertainties Study Algorithm (OUSA)
NASA Technical Reports Server (NTRS)
Bahethi, O. P.
1982-01-01
An algorithm to carry out sensitivities, uncertainties and overall imprecision studies to a set of input parameters for a one dimensional steady ozone photochemistry model is described. This algorithm can be used to evaluate steady state perturbations due to point source or distributed ejection of H2O, CLX, and NOx, besides, varying the incident solar flux. This algorithm is operational on IBM OS/360-91 computer at NASA/Goddard Space Flight Center's Science and Applications Computer Center (SACC).
Sequence comparisons via algorithmic mutual information.
Milosavljević, A
1994-01-01
One of the main problems in DNA and protein sequence comparisons is to decide whether observed similarity of two sequences should be explained by their relatedness or by mere presence of some shared internal structure, e.g., shared internal tandem repeats. The standard methods that are based on statistics or classical information theory can be used to discover either internal structure or mutual sequence similarity, but cannot take into account both. Consequently, currently used methods for sequence comparison employ "masking" techniques that simply eliminate sequences that exhibit internal repetitive structure prior to sequence comparisons. The "masking" approach precludes discovery of homologous sequences of moderate or low complexity, which abound at both DNA and protein levels. As a solution to this problem, we propose a general method that is based on algorithmic information theory and minimal length encoding. We show that algorithmic mutual information factors out the sequence similarity that is due to shared internal structure and thus enables discovery of truly related sequences. We extend that recently developed algorithmic significance method (Milosavljević & Jurka 1993) to show that significance depends exponentially on algorithmic mutual information.
Obstacle Detection Algorithms for Rotorcraft Navigation
NASA Technical Reports Server (NTRS)
Kasturi, Rangachar; Camps, Octavia I.; Huang, Ying; Narasimhamurthy, Anand; Pande, Nitin; Ahumada, Albert (Technical Monitor)
2001-01-01
In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter.
Convergence behavior of a new DSMC algorithm.
Gallis, Michail A.; Rader, Daniel John; Torczynski, John Robert; Bird, Graeme A.
2008-10-01
The convergence rate of a new direct simulation Monte Carlo (DSMC) method, termed 'sophisticated DSMC', is investigated for one-dimensional Fourier flow. An argon-like hard-sphere gas at 273.15K and 266.644Pa is confined between two parallel, fully accommodating walls 1mm apart that have unequal temperatures. The simulations are performed using a one-dimensional implementation of the sophisticated DSMC algorithm. In harmony with previous work, the primary convergence metric studied is the ratio of the DSMC-calculated thermal conductivity to its corresponding infinite-approximation Chapman-Enskog theoretical value. As discretization errors are reduced, the sophisticated DSMC algorithm is shown to approach the theoretical values to high precision. The convergence behavior of sophisticated DSMC is compared to that of original DSMC. The convergence of the new algorithm in a three-dimensional implementation is also characterized. Implementations using transient adaptive sub-cells and virtual sub-cells are compared. The new algorithm is shown to significantly reduce the computational resources required for a DSMC simulation to achieve a particular level of accuracy, thus improving the efficiency of the method by a factor of 2.
An effective one-dimensional anisotropic fingerprint enhancement algorithm
NASA Astrophysics Data System (ADS)
Ye, Zhendong; Xie, Mei
2012-01-01
Fingerprint identification is one of the most important biometric technologies. The performance of the minutiae extraction and the speed of the fingerprint verification system rely heavily on the quality of the input fingerprint images, so the enhancement of the low fingerprint is a critical and difficult step in a fingerprint verification system. In this paper we proposed an effective algorithm for fingerprint enhancement. Firstly we use normalization algorithm to reduce the variations in gray level values along ridges and valleys. Then we utilize the structure tensor approach to estimate each pixel of the fingerprint orientations. At last we propose a novel algorithm which combines the advantages of onedimensional Gabor filtering method and anisotropic method to enhance the fingerprint in recoverable region. The proposed algorithm has been evaluated on the database of Fingerprint Verification Competition 2004, and the results show that our algorithm performs within less time.
An effective one-dimensional anisotropic fingerprint enhancement algorithm
NASA Astrophysics Data System (ADS)
Ye, Zhendong; Xie, Mei
2011-12-01
Fingerprint identification is one of the most important biometric technologies. The performance of the minutiae extraction and the speed of the fingerprint verification system rely heavily on the quality of the input fingerprint images, so the enhancement of the low fingerprint is a critical and difficult step in a fingerprint verification system. In this paper we proposed an effective algorithm for fingerprint enhancement. Firstly we use normalization algorithm to reduce the variations in gray level values along ridges and valleys. Then we utilize the structure tensor approach to estimate each pixel of the fingerprint orientations. At last we propose a novel algorithm which combines the advantages of onedimensional Gabor filtering method and anisotropic method to enhance the fingerprint in recoverable region. The proposed algorithm has been evaluated on the database of Fingerprint Verification Competition 2004, and the results show that our algorithm performs within less time.
Messy genetic algorithms: Recent developments
Kargupta, H.
1996-09-01
Messy genetic algorithms define a rare class of algorithms that realize the need for detecting appropriate relations among members of the search domain in optimization. This paper reviews earlier works in messy genetic algorithms and describes some recent developments. It also describes the gene expression messy GA (GEMGA)--an {Omicron}({Lambda}{sup {kappa}}({ell}{sup 2} + {kappa})) sample complexity algorithm for the class of order-{kappa} delineable problems (problems that can be solved by considering no higher than order-{kappa} relations) of size {ell} and alphabet size {Lambda}. Experimental results are presented to demonstrate the scalability of the GEMGA.
DNABIT Compress - Genome compression algorithm.
Rajarajeswari, Pothuraju; Apparao, Allam
2011-01-01
Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.
Approximate Algorithms for Computing Spatial Distance Histograms with Accuracy Guarantees
Grupcev, Vladimir; Yuan, Yongke; Tu, Yi-Cheng; Huang, Jin; Chen, Shaoping; Pandit, Sagar; Weng, Michael
2014-01-01
Particle simulation has become an important research tool in many scientific and engineering fields. Data generated by such simulations impose great challenges to database storage and query processing. One of the queries against particle simulation data, the spatial distance histogram (SDH) query, is the building block of many high-level analytics, and requires quadratic time to compute using a straightforward algorithm. Previous work has developed efficient algorithms that compute exact SDHs. While beating the naive solution, such algorithms are still not practical in processing SDH queries against large-scale simulation data. In this paper, we take a different path to tackle this problem by focusing on approximate algorithms with provable error bounds. We first present a solution derived from the aforementioned exact SDH algorithm, and this solution has running time that is unrelated to the system size N. We also develop a mathematical model to analyze the mechanism that leads to errors in the basic approximate algorithm. Our model provides insights on how the algorithm can be improved to achieve higher accuracy and efficiency. Such insights give rise to a new approximate algorithm with improved time/accuracy tradeoff. Experimental results confirm our analysis. PMID:24693210
An enhanced fast scanning algorithm for image segmentation
NASA Astrophysics Data System (ADS)
Ismael, Ahmed Naser; Yusof, Yuhanis binti
2015-12-01
Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.
Approximate Algorithms for Computing Spatial Distance Histograms with Accuracy Guarantees.
Grupcev, Vladimir; Yuan, Yongke; Tu, Yi-Cheng; Huang, Jin; Chen, Shaoping; Pandit, Sagar; Weng, Michael
2012-09-01
Particle simulation has become an important research tool in many scientific and engineering fields. Data generated by such simulations impose great challenges to database storage and query processing. One of the queries against particle simulation data, the spatial distance histogram (SDH) query, is the building block of many high-level analytics, and requires quadratic time to compute using a straightforward algorithm. Previous work has developed efficient algorithms that compute exact SDHs. While beating the naive solution, such algorithms are still not practical in processing SDH queries against large-scale simulation data. In this paper, we take a different path to tackle this problem by focusing on approximate algorithms with provable error bounds. We first present a solution derived from the aforementioned exact SDH algorithm, and this solution has running time that is unrelated to the system size N. We also develop a mathematical model to analyze the mechanism that leads to errors in the basic approximate algorithm. Our model provides insights on how the algorithm can be improved to achieve higher accuracy and efficiency. Such insights give rise to a new approximate algorithm with improved time/accuracy tradeoff. Experimental results confirm our analysis.
An adaptive mesh refinement algorithm for the discrete ordinates method
Jessee, J.P.; Fiveland, W.A.; Howell, L.H.; Colella, P.; Pember, R.B.
1996-03-01
The discrete ordinates form of the radiative transport equation (RTE) is spatially discretized and solved using an adaptive mesh refinement (AMR) algorithm. This technique permits the local grid refinement to minimize spatial discretization error of the RTE. An error estimator is applied to define regions for local grid refinement; overlapping refined grids are recursively placed in these regions; and the RTE is then solved over the entire domain. The procedure continues until the spatial discretization error has been reduced to a sufficient level. The following aspects of the algorithm are discussed: error estimation, grid generation, communication between refined levels, and solution sequencing. This initial formulation employs the step scheme, and is valid for absorbing and isotopically scattering media in two-dimensional enclosures. The utility of the algorithm is tested by comparing the convergence characteristics and accuracy to those of the standard single-grid algorithm for several benchmark cases. The AMR algorithm provides a reduction in memory requirements and maintains the convergence characteristics of the standard single-grid algorithm; however, the cases illustrate that efficiency gains of the AMR algorithm will not be fully realized until three-dimensional geometries are considered.
Efficient iterative image reconstruction algorithm for dedicated breast CT
NASA Astrophysics Data System (ADS)
Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan
2016-03-01
Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.
Quantum Image Encryption Algorithm Based on Quantum Image XOR Operations
NASA Astrophysics Data System (ADS)
Gong, Li-Hua; He, Xiang-Tao; Cheng, Shan; Hua, Tian-Xiang; Zhou, Nan-Run
2016-07-01
A novel encryption algorithm for quantum images based on quantum image XOR operations is designed. The quantum image XOR operations are designed by using the hyper-chaotic sequences generated with the Chen's hyper-chaotic system to control the control-NOT operation, which is used to encode gray-level information. The initial conditions of the Chen's hyper-chaotic system are the keys, which guarantee the security of the proposed quantum image encryption algorithm. Numerical simulations and theoretical analyses demonstrate that the proposed quantum image encryption algorithm has larger key space, higher key sensitivity, stronger resistance of statistical analysis and lower computational complexity than its classical counterparts.
Data-adaptive algorithms for calling alleles in repeat polymorphisms.
Stoughton, R; Bumgarner, R; Frederick, W J; McIndoe, R A
1997-01-01
Data-adaptive algorithms are presented for separating overlapping signatures of heterozygotic allele pairs in electrophoresis data. Application is demonstrated for human microsatellite CA-repeat polymorphisms in LiCor 4000 and ABI 373 data. The algorithms allow overlapping alleles to be called correctly in almost every case where a trained observer could do so, and provide a fast automated objective alternative to human reading of the gels. The algorithm also supplies an indication of confidence level which can be used to flag marginal cases for verification by eye, or as input to later stages of statistical analysis. PMID:9059812
Efficient scalable algorithms for hierarchically semiseparable matrices
Wang, Shen; Xia, Jianlin; Situ, Yingchong; Hoop, Maarten V. de
2011-09-14
Hierarchically semiseparable (HSS) matrix algorithms are emerging techniques in constructing the superfast direct solvers for both dense and sparse linear systems. Here, we develope a set of novel parallel algorithms for the key HSS operations that are used for solving large linear systems. These include the parallel rank-revealing QR factorization, the HSS constructions with hierarchical compression, the ULV HSS factorization, and the HSS solutions. The HSS tree based parallelism is fully exploited at the coarse level. The BLACS and ScaLAPACK libraries are used to facilitate the parallel dense kernel operations at the ne-grained level. We have appplied our new parallel HSS-embedded multifrontal solver to the anisotropic Helmholtz equations for seismic imaging, and were able to solve a linear system with 6.4 billion unknowns using 4096 processors, in about 20 minutes. The classical multifrontal solver simply failed due to high demand of memory. To our knowledge, this is the first successful demonstration of employing the HSS algorithms in solving the truly large-scale real-world problems. Our parallel strategies can be easily adapted to the parallelization of the other rank structured methods.
Algorithm Engineering - An Attempt at a Definition
NASA Astrophysics Data System (ADS)
Sanders, Peter
This paper defines algorithm engineering as a general methodology for algorithmic research. The main process in this methodology is a cycle consisting of algorithm design, analysis, implementation and experimental evaluation that resembles Popper’s scientific method. Important additional issues are realistic models, algorithm libraries, benchmarks with real-world problem instances, and a strong coupling to applications. Algorithm theory with its process of subsequent modelling, design, and analysis is not a competing approach to algorithmics but an important ingredient of algorithm engineering.
Algorithm Calculates Cumulative Poisson Distribution
NASA Technical Reports Server (NTRS)
Bowerman, Paul N.; Nolty, Robert C.; Scheuer, Ernest M.
1992-01-01
Algorithm calculates accurate values of cumulative Poisson distribution under conditions where other algorithms fail because numbers are so small (underflow) or so large (overflow) that computer cannot process them. Factors inserted temporarily to prevent underflow and overflow. Implemented in CUMPOIS computer program described in "Cumulative Poisson Distribution Program" (NPO-17714).
Interpolation algorithms for machine tools
Burleson, R.R.
1981-08-01
There are three types of interpolation algorithms presently used in most numerical control systems: digital differential analyzer, pulse-rate multiplier, and binary-rate multiplier. A method for higher order interpolation is in the experimental stages. The trends point toward the use of high-speed micrprocessors to perform these interpolation algorithms.
FORTRAN Algorithm for Image Processing
NASA Technical Reports Server (NTRS)
Roth, Don J.; Hull, David R.
1987-01-01
FORTRAN computer algorithm containing various image-processing analysis and enhancement functions developed. Algorithm developed specifically to process images of developmental heat-engine materials obtained with sophisticated nondestructive evaluation instruments. Applications of program include scientific, industrial, and biomedical imaging for studies of flaws in materials, analyses of steel and ores, and pathology.
Algorithm for Autonomous Landing
NASA Technical Reports Server (NTRS)
Kuwata, Yoshiaki
2011-01-01
Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.
Panniculitides, an algorithmic approach.
Zelger, B
2013-08-01
The issue of inflammatory diseases of subcutis and its mimicries is generally considered a difficult field of dermatopathology. Yet, in my experience, with appropriate biopsies and good clinicopathological correlation, a specific diagnosis of panniculitides can usually be made. Thereby, knowledge about some basic anatomic and pathological issues is essential. Anatomy differentiates within the panniculus between the fatty lobules separated by fibrous septa. Pathologically, inflammation of panniculus is defined and recognized by an inflammatory process which leads to tissue damage and necrosis. Several types of fat necrosis are observed: xanthomatized macrophages in lipophagic necrosis; granular fat necrosis and fat micropseudocysts in liquefactive fat necrosis; mummified adipocytes in "hyalinizing" fat necrosis with/without saponification and/or calcification; and lipomembranous membranes in membranous fat necrosis. In an algorithmic approach the recognition of an inflammatory process recognized by features as elaborated above is best followed in three steps: recognition of pattern, second of subpattern, and finally of presence and composition of inflammatory cells. Pattern differentiates a mostly septal or mostly lobular distribution at scanning magnification. In the subpattern category one looks for the presence or absence of vasculitis, and, if this is the case, the size and the nature of the involved blood vessel: arterioles and small arteries or veins; capillaries or postcapillary venules. The third step will be to identify the nature of the cells present in the inflammatory infiltrate and, finally, to look for additional histopathologic features that allow for a specific final diagnosis in the language of clinical dermatology of disease involving the subcutaneous fat.
Cubit Adaptive Meshing Algorithm Library
2004-09-01
CAMAL (Cubit adaptive meshing algorithm library) is a software component library for mesh generation. CAMAL 2.0 includes components for triangle, quad and tetrahedral meshing. A simple Application Programmers Interface (API) takes a discrete boundary definition and CAMAL computes a quality interior unstructured grid. The triangle and quad algorithms may also import a geometric definition of a surface on which to define the grid. CAMALs triangle meshing uses a 3D space advancing front method, the quadmore » meshing algorithm is based upon Sandias patented paving algorithm and the tetrahedral meshing algorithm employs the GHS3D-Tetmesh component developed by INRIA, France.« less
Testing an earthquake prediction algorithm
Kossobokov, V.G.; Healy, J.H.; Dewey, J.W.
1997-01-01
A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known as M8. The M8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.
Decision Making Algorithm for Adult Spinal Deformity Surgery
Kim, Yongjung J.; Cheh, Gene; Cho, Samuel K.; Rhim, Seung-Chul
2016-01-01
Adult spinal deformity (ASD) is one of the most challenging spinal disorders associated with broad range of clinical and radiological presentation. Correct selection of fusion levels in surgical planning for the management of adult spinal deformity is a complex task. Several classification systems and algorithms exist to assist surgeons in determining the appropriate levels to be instrumented. In this study, we describe our new simple decision making algorithm and selection of fusion level for ASD surgery in terms of adult idiopathic idiopathic scoliosis vs. degenerative scoliosis. PMID:27446511
Transitionless driving on adiabatic search algorithm
Oh, Sangchul; Kais, Sabre
2014-12-14
We study quantum dynamics of the adiabatic search algorithm with the equivalent two-level system. Its adiabatic and non-adiabatic evolution is studied and visualized as trajectories of Bloch vectors on a Bloch sphere. We find the change in the non-adiabatic transition probability from exponential decay for the short running time to inverse-square decay in asymptotic running time. The scaling of the critical running time is expressed in terms of the Lambert W function. We derive the transitionless driving Hamiltonian for the adiabatic search algorithm, which makes a quantum state follow the adiabatic path. We demonstrate that a uniform transitionless driving Hamiltonian, approximate to the exact time-dependent driving Hamiltonian, can alter the non-adiabatic transition probability from the inverse square decay to the inverse fourth power decay with the running time. This may open up a new but simple way of speeding up adiabatic quantum dynamics.
Pure field theories and MACSYMA algorithms
NASA Technical Reports Server (NTRS)
Ament, W. S.
1977-01-01
A pure field theory attempts to describe physical phenomena through singularity-free solutions of field equations resulting from an action principle. The physics goes into forming the action principle and interpreting specific results. Algorithms for the intervening mathematical steps are sketched. Vacuum general relativity is a pure field theory, serving as model and providing checks for generalizations. The fields of general relativity are the 10 components of a symmetric Riemannian metric tensor; those of the Einstein-Straus generalization are the 16 components of a nonsymmetric. Algebraic properties are exploited in top level MACSYMA commands toward performing some of the algorithms of that generalization. The light cone for the theory as left by Einstein and Straus is found and simplifications of that theory are discussed.
Algorithmic advances in stochastic programming
Morton, D.P.
1993-07-01
Practical planning problems with deterministic forecasts of inherently uncertain parameters often yield unsatisfactory solutions. Stochastic programming formulations allow uncertain parameters to be modeled as random variables with known distributions, but the size of the resulting mathematical programs can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We consider two classes of decomposition-based stochastic programming algorithms. The first type of algorithm addresses problems with a ``manageable`` number of scenarios. The second class incorporates Monte Carlo sampling within a decomposition algorithm. We develop and empirically study an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs within a prespecified tolerance. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of ``real-world`` multistage stochastic hydroelectric scheduling problems. Recently, there has been an increased focus on decomposition-based algorithms that use sampling within the optimization framework. These approaches hold much promise for solving stochastic programs with many scenarios. A critical component of such algorithms is a stopping criterion to ensure the quality of the solution. With this as motivation, we develop a stopping rule theory for algorithms in which bounds on the optimal objective function value are estimated by sampling. Rules are provided for selecting sample sizes and terminating the algorithm under which asymptotic validity of confidence interval statements for the quality of the proposed solution can be verified. Issues associated with the application of this theory to two sampling-based algorithms are considered, and preliminary empirical coverage results are presented.
A distributed Canny edge detector: algorithm and FPGA implementation.
Xu, Qian; Varadarajan, Srenivas; Chakrabarti, Chaitali; Karam, Lina J
2014-07-01
The Canny edge detector is one of the most widely used edge detection algorithms due to its superior performance. Unfortunately, not only is it computationally more intensive as compared with other edge detection algorithms, but it also has a higher latency because it is based on frame-level statistics. In this paper, we propose a mechanism to implement the Canny algorithm at the block level without any loss in edge detection performance compared with the original frame-level Canny algorithm. Directly applying the original Canny algorithm at the block-level leads to excessive edges in smooth regions and to loss of significant edges in high-detailed regions since the original Canny computes the high and low thresholds based on the frame-level statistics. To solve this problem, we present a distributed Canny edge detection algorithm that adaptively computes the edge detection thresholds based on the block type and the local distribution of the gradients in the image block. In addition, the new algorithm uses a nonuniform gradient magnitude histogram to compute block-based hysteresis thresholds. The resulting block-based algorithm has a significantly reduced latency and can be easily integrated with other block-based image codecs. It is capable of supporting fast edge detection of images and videos with high resolutions, including full-HD since the latency is now a function of the block size instead of the frame size. In addition, quantitative conformance evaluations and subjective tests show that the edge detection performance of the proposed algorithm is better than the original frame-based algorithm, especially when noise is present in the images. Finally, this algorithm is implemented using a 32 computing engine architecture and is synthesized on the Xilinx Virtex-5 FPGA. The synthesized architecture takes only 0.721 ms (including the SRAM READ/WRITE time and the computation time) to detect edges of 512 × 512 images in the USC SIPI database when clocked at 100
A distributed Canny edge detector: algorithm and FPGA implementation.
Xu, Qian; Varadarajan, Srenivas; Chakrabarti, Chaitali; Karam, Lina J
2014-07-01
The Canny edge detector is one of the most widely used edge detection algorithms due to its superior performance. Unfortunately, not only is it computationally more intensive as compared with other edge detection algorithms, but it also has a higher latency because it is based on frame-level statistics. In this paper, we propose a mechanism to implement the Canny algorithm at the block level without any loss in edge detection performance compared with the original frame-level Canny algorithm. Directly applying the original Canny algorithm at the block-level leads to excessive edges in smooth regions and to loss of significant edges in high-detailed regions since the original Canny computes the high and low thresholds based on the frame-level statistics. To solve this problem, we present a distributed Canny edge detection algorithm that adaptively computes the edge detection thresholds based on the block type and the local distribution of the gradients in the image block. In addition, the new algorithm uses a nonuniform gradient magnitude histogram to compute block-based hysteresis thresholds. The resulting block-based algorithm has a significantly reduced latency and can be easily integrated with other block-based image codecs. It is capable of supporting fast edge detection of images and videos with high resolutions, including full-HD since the latency is now a function of the block size instead of the frame size. In addition, quantitative conformance evaluations and subjective tests show that the edge detection performance of the proposed algorithm is better than the original frame-based algorithm, especially when noise is present in the images. Finally, this algorithm is implemented using a 32 computing engine architecture and is synthesized on the Xilinx Virtex-5 FPGA. The synthesized architecture takes only 0.721 ms (including the SRAM READ/WRITE time and the computation time) to detect edges of 512 × 512 images in the USC SIPI database when clocked at 100
Lossless compression algorithm for multispectral imagers
NASA Astrophysics Data System (ADS)
Gladkova, Irina; Grossberg, Michael; Gottipati, Srikanth
2008-08-01
Multispectral imaging is becoming an increasingly important tool for monitoring the earth and its environment from space borne and airborne platforms. Multispectral imaging data consists of visible and IR measurements from a scene across space and spectrum. Growing data rates resulting from faster scanning and finer spatial and spectral resolution makes compression an increasingly critical tool to reduce data volume for transmission and archiving. Research for NOAA NESDIS has been directed to finding for the characteristics of satellite atmospheric Earth science Imager sensor data what level of Lossless compression ratio can be obtained as well as appropriate types of mathematics and approaches that can lead to approaching this data's entropy level. Conventional lossless do not achieve the theoretical limits for lossless compression on imager data as estimated from the Shannon entropy. In a previous paper, the authors introduce a lossless compression algorithm developed for MODIS as a proxy for future NOAA-NESDIS satellite based Earth science multispectral imagers such as GOES-R. The algorithm is based on capturing spectral correlations using spectral prediction, and spatial correlations with a linear transform encoder. In decompression, the algorithm uses a statistically computed look up table to iteratively predict each channel from a channel decompressed in the previous iteration. In this paper we present a new approach which fundamentally differs from our prior work. In this new approach, instead of having a single predictor for each pair of bands we introduce a piecewise spatially varying predictor which significantly improves the compression results. Our new algorithm also now optimizes the sequence of channels we use for prediction. Our results are evaluated by comparison with a state of the art wavelet based image compression scheme, Jpeg2000. We present results on the 14 channel subset of the MODIS imager, which serves as a proxy for the GOES-R imager. We
Algorithms for bilevel optimization
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Dennis, J. E., Jr.
1994-01-01
General multilevel nonlinear optimization problems arise in design of complex systems and can be used as a means of regularization for multi-criteria optimization problems. Here, for clarity in displaying our ideas, we restrict ourselves to general bi-level optimization problems, and we present two solution approaches. Both approaches use a trust-region globalization strategy, and they can be easily extended to handle the general multilevel problem. We make no convexity assumptions, but we do assume that the problem has a nondegenerate feasible set. We consider necessary optimality conditions for the bi-level problem formulations and discuss results that can be extended to obtain multilevel optimization formulations with constraints at each level.
Periprosthetic joint infections: a clinical practice algorithm
VOLPE, LUIGI; INDELLI, PIER FRANCESCO; LATELLA, LEONARDO; POLI, PAOLO; YAKUPOGLU, JALE; MARCUCCI, MASSIMILIANO
2014-01-01
Purpose periprosthetic joint infection (PJI) accounts for 25% of failed total knee arthroplasties (TKAs) and 15% of failed total hip arthroplasties (THAs). The purpose of the present study was to design a multidisciplinary diagnostic algorithm to detect a PJI as cause of a painful TKA or THA. Methods from April 2010 to October 2012, 111 patients with suspected PJI were evaluated. The study group comprised 75 females and 36 males with an average age of 71 years (range, 48 to 94 years). Eighty-four patients had a painful THA, while 27 reported a painful TKA. The stepwise diagnostic algorithm, applied in all the patients, included: measurement of serum C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) levels; imaging studies, including standard radiological examination, standard technetium-99m-methylene diphosphonate (MDP) bone scan (if positive, confirmation by LeukoScan was obtained); and joint aspiration with analysis of synovial fluid. Results following application of the stepwise diagnostic algorithm, 24 out of our 111 screened patients were classified as having a suspected PJI (21.7%). CRP and ESR levels were negative in 84 and positive in 17 cases; 93.7% of the patients had a positive technetium-labeled bone scan, and 23% a positive LeukoScan. Preoperative synovial fluid analysis was positive in 13.5%; analysis of synovial fluid obtained by preoperative aspiration showed a leucocyte count of > 3000 cells μ/l in 52% of the patients. Conclusions the present study showed that the diagnosis of PJI requires the application of a multimodal diagnostic protocol in order to avoid complications related to surgical revision of a misdiagnosed “silent” PJI. Level of evidence Level IV, therapeutic case series. PMID:25750905
Scheduling with genetic algorithms
NASA Technical Reports Server (NTRS)
Fennel, Theron R.; Underbrink, A. J., Jr.; Williams, George P. W., Jr.
1994-01-01
In many domains, scheduling a sequence of jobs is an important function contributing to the overall efficiency of the operation. At Boeing, we develop schedules for many different domains, including assembly of military and commercial aircraft, weapons systems, and space vehicles. Boeing is under contract to develop scheduling systems for the Space Station Payload Planning System (PPS) and Payload Operations and Integration Center (POIC). These applications require that we respect certain sequencing restrictions among the jobs to be scheduled while at the same time assigning resources to the jobs. We call this general problem scheduling and resource allocation. Genetic algorithms (GA's) offer a search method that uses a population of solutions and benefits from intrinsic parallelism to search the problem space rapidly, producing near-optimal solutions. Good intermediate solutions are probabalistically recombined to produce better offspring (based upon some application specific measure of solution fitness, e.g., minimum flowtime, or schedule completeness). Also, at any point in the search, any intermediate solution can be accepted as a final solution; allowing the search to proceed longer usually produces a better solution while terminating the search at virtually any time may yield an acceptable solution. Many processes are constrained by restrictions of sequence among the individual jobs. For a specific job, other jobs must be completed beforehand. While there are obviously many other constraints on processes, it is these on which we focussed for this research: how to allocate crews to jobs while satisfying job precedence requirements and personnel, and tooling and fixture (or, more generally, resource) requirements.
The Dropout Learning Algorithm
Baldi, Pierre; Sadowski, Peter
2014-01-01
Dropout is a recently introduced algorithm for training neural network by randomly dropping units during training to prevent their co-adaptation. A mathematical analysis of some of the static and dynamic properties of dropout is provided using Bernoulli gating variables, general enough to accommodate dropout on units or connections, and with variable rates. The framework allows a complete analysis of the ensemble averaging properties of dropout in linear networks, which is useful to understand the non-linear case. The ensemble averaging properties of dropout in non-linear logistic networks result from three fundamental equations: (1) the approximation of the expectations of logistic functions by normalized geometric means, for which bounds and estimates are derived; (2) the algebraic equality between normalized geometric means of logistic functions with the logistic of the means, which mathematically characterizes logistic functions; and (3) the linearity of the means with respect to sums, as well as products of independent variables. The results are also extended to other classes of transfer functions, including rectified linear functions. Approximation errors tend to cancel each other and do not accumulate. Dropout can also be connected to stochastic neurons and used to predict firing rates, and to backpropagation by viewing the backward propagation as ensemble averaging in a dropout linear network. Moreover, the convergence properties of dropout can be understood in terms of stochastic gradient descent. Finally, for the regularization properties of dropout, the expectation of the dropout gradient is the gradient of the corresponding approximation ensemble, regularized by an adaptive weight decay term with a propensity for self-consistent variance minimization and sparse representations. PMID:24771879
Efficient implementation of the adaptive scale pixel decomposition algorithm
NASA Astrophysics Data System (ADS)
Zhang, L.; Bhatnagar, S.; Rau, U.; Zhang, M.
2016-08-01
Context. Most popular algorithms in use to remove the effects of a telescope's point spread function (PSF) in radio astronomy are variants of the CLEAN algorithm. Most of these algorithms model the sky brightness using the delta-function basis, which results in undesired artefacts when used to image extended emission. The adaptive scale pixel decomposition (Asp-Clean) algorithm models the sky brightness on a scale-sensitive basis and thus gives a significantly better imaging performance when imaging fields that contain both resolved and unresolved emission. Aims: However, the runtime cost of Asp-Clean is higher than that of scale-insensitive algorithms. In this paper, we identify the most expensive step in the original Asp-Clean algorithm and present an efficient implementation of it, which significantly reduces the computational cost while keeping the imaging performance comparable to the original algorithm. The PSF sidelobe levels of modern wide-band telescopes are significantly reduced, allowing us to make approximations to reduce the computational cost, which in turn allows for the deconvolution of larger images on reasonable timescales. Methods: As in the original algorithm, scales in the image are estimated through function fitting. Here we introduce an analytical method to model extended emission, and a modified method for estimating the initial values used for the fitting procedure, which ultimately leads to a lower computational cost. Results: The new implementation was tested with simulated EVLA data and the imaging performance compared well with the original Asp-Clean algorithm. Tests show that the current algorithm can recover features at different scales with lower computational cost.
Conservative Patch Algorithm and Mesh Sequencing for PAB3D
NASA Technical Reports Server (NTRS)
Pao, S. P.; Abdol-Hamid, K. S.
2005-01-01
A mesh-sequencing algorithm and a conservative patched-grid-interface algorithm (hereafter Patch Algorithm ) have been incorporated into the PAB3D code, which is a computer program that solves the Navier-Stokes equations for the simulation of subsonic, transonic, or supersonic flows surrounding an aircraft or other complex aerodynamic shapes. These algorithms are efficient, flexible, and have added tremendously to the capabilities of PAB3D. The mesh-sequencing algorithm makes it possible to perform preliminary computations using only a fraction of the grid cells (provided the original cell count is divisible by an integer) along any grid coordinate axis, independently of the other axes. The patch algorithm addresses another critical need in multi-block grid situation where the cell faces of adjacent grid blocks may not coincide, leading to errors in calculating fluxes of conserved physical quantities across interfaces between the blocks. The patch algorithm, based on the Stokes integral formulation of the applicable conservation laws, effectively matches each of the interfacial cells on one side of the block interface to the corresponding fractional cell area pieces on the other side. This approach is comprehensive and unified such that all interface topology is automatically processed without user intervention. This algorithm is implemented in a preprocessing code that creates a cell-by-cell database that will maintain flux conservation at any level of full or reduced grid density as the user may choose by way of the mesh-sequencing algorithm. These two algorithms have enhanced the numerical accuracy of the code, reduced the time and effort for grid preprocessing, and provided users with the flexibility of performing computations at any desired full or reduced grid resolution to suit their specific computational requirements.
A fast algorithm for sparse matrix computations related to inversion
NASA Astrophysics Data System (ADS)
Li, S.; Wu, W.; Darve, E.
2013-06-01
We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green's functions Gr and G< for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round-off errors
Portable Health Algorithms Test System
NASA Technical Reports Server (NTRS)
Melcher, Kevin J.; Wong, Edmond; Fulton, Christopher E.; Sowers, Thomas S.; Maul, William A.
2010-01-01
A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.
Efficient bit-level, word-level, and block-level systolic arrays for matrix-matrix multiplication
De Groot, A.J.; Parker, S.R.; Johansson, E.M.
1988-02-01
This paper investigates the mapping of matrix-matrix multiplication onto bit level, word level and block level systolic arrays. Highly efficient and regular bit level, word level and block level systolic arrays are described. Efficiencies of many block level and word level systolic arrays reported in this paper approach 100/percent/, three times the efficiencies of systolic arrays reported previously. Bit level systolic arrays reported in this paper require less computation time than do bit level systolic arrays reported previously and, for special matrices, require less cells. Execution times of block level systolic algorithms on sixty-four-element multiprocessor agree with theory.
Linearization algorithms for line transfer
Scott, H.A.
1990-11-06
Complete linearization is a very powerful technique for solving multi-line transfer problems that can be used efficiently with a variety of transfer formalisms. The linearization algorithm we describe is computationally very similar to ETLA, but allows an effective treatment of strongly-interacting lines. This algorithm has been implemented (in several codes) with two different transfer formalisms in all three one-dimensional geometries. We also describe a variation of the algorithm that handles saturable laser transport. Finally, we present a combination of linearization with a local approximate operator formalism, which has been implemented in two dimensions and is being developed in three dimensions. 11 refs.
Review of jet reconstruction algorithms
NASA Astrophysics Data System (ADS)
Atkin, Ryan
2015-10-01
Accurate jet reconstruction is necessary for understanding the link between the unobserved partons and the jets of observed collimated colourless particles the partons hadronise into. Understanding this link sheds light on the properties of these partons. A review of various common jet algorithms is presented, namely the Kt, Anti-Kt, Cambridge/Aachen, Iterative cones and the SIScone, highlighting their strengths and weaknesses. If one is interested in studying jets, the Anti-Kt algorithm is the best choice, however if ones interest is in the jet substructures then the Cambridge/Aachen algorithm would be the best option.
A universal symmetry detection algorithm.
Maurer, Peter M
2015-01-01
Research on symmetry detection focuses on identifying and detecting new types of symmetry. The paper presents an algorithm that is capable of detecting any type of permutation-based symmetry, including many types for which there are no existing algorithms. General symmetry detection is library-based, but symmetries that can be parameterized, (i.e. total, partial, rotational, and dihedral symmetry), can be detected without using libraries. In many cases it is faster than existing techniques. Furthermore, it is simpler than most existing techniques, and can easily be incorporated into existing software. The algorithm can also be used with virtually any type of matrix-based symmetry, including conjugate symmetry.
Multiprojection algorithms with generalized projections
Censor, J.; Elfving, T.
1994-12-31
Generalized distances give raise to generalized projections onto convex sets. An important question is whether or not one can use, within the same projection algorithm, different types of such generalized projections. This question has practical consequences in the areas of signal detection and image recovery, in situations that can be formulated mathematically as convex feasibility problems. We show here that a simultaneous multiprojection algorithmic scheme converges. Different specific multiprojection algorithms can be derived from our scheme by a judicious choice of the Bregman functions which govern the process. As a by-product of the investigation we also obtain block-iterative schemes for certain kinds of linearly constrained optimization problems.
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Dynamic Programming Algorithm vs. Genetic Algorithm: Which is Faster?
NASA Astrophysics Data System (ADS)
Petković, Dušan
The article compares two different approaches for the optimization problem of large join queries (LJQs). Almost all commercial database systems use a form of the dynamic programming algorithm to solve the ordering of join operations for large join queries, i.e. joins with more than dozen join operations. The property of the dynamic programming algorithm is that the execution time increases significantly in the case, where the number of join operations in a query is large. Genetic algorithms (GAs), as a data mining technique, have been shown as a promising technique in solving the ordering of join operations in LJQs. Using the existing implementation of GA, we compare the dynamic programming algorithm implemented in commercial database systems with the corresponding GA module. Our results show that the use of a genetic algorithm is a better solution for optimization of large join queries, i.e., that such a technique outperforms the implementations of the dynamic programming algorithm in conventional query optimization components for very large join queries.
A finite element algorithm for high-lying eigenvalues with Neumann and Dirichlet boundary conditions
NASA Astrophysics Data System (ADS)
Báez, G.; Méndez-Sánchez, R. A.; Leyvraz, F.; Seligman, T. H.
2014-01-01
We present a finite element algorithm that computes eigenvalues and eigenfunctions of the Laplace operator for two-dimensional problems with homogeneous Neumann or Dirichlet boundary conditions, or combinations of either for different parts of the boundary. We use an inverse power plus Gauss-Seidel algorithm to solve the generalized eigenvalue problem. For Neumann boundary conditions the method is much more efficient than the equivalent finite difference algorithm. We checked the algorithm by comparing the cumulative level density of the spectrum obtained numerically with the theoretical prediction given by the Weyl formula. We found a systematic deviation due to the discretization, not to the algorithm itself.
Belief network algorithms: A study of performance
Jitnah, N.
1996-12-31
This abstract gives an overview of the work. We present a survey of Belief Network algorithms and propose a domain characterization system to be used as a basis for algorithm comparison and for predicting algorithm performance.
Algorithms for verbal autopsies: a validation study in Kenyan children.
Quigley, M. A.; Armstrong Schellenberg, J. R.; Snow, R. W.
1996-01-01
The verbal autopsy (VA) questionnaire is a widely used method for collecting information on cause-specific mortality where the medical certification of deaths in childhood is incomplete. This paper discusses review by physicians and expert algorithms as approaches to ascribing cause of deaths from the VA questionnaire and proposes an alternative, data-derived approach. In this validation study, the relatives of 295 children who had died in hospital were interviewed using a VA questionnaire. The children were assigned causes of death using data-derived algorithms obtained under logistic regression and using expert algorithms. For most causes of death, the data-derived algorithms and expert algorithms yielded similar levels of diagnostic accuracy. However, a data-derived algorithm for malaria gave a sensitivity of 71% (95% Cl: 58-84%), which was significantly higher than the sensitivity of 47% obtained under an expert algorithm. The need for exploring this and other ways in which the VA technique can be improved are discussed. The implications of less-than-perfect sensitivity and specificity are explored using numerical examples. Misclassification bias should be taken into consideration when planning and evaluating epidemiological studies. PMID:8706229
Multikernel least mean square algorithm.
Tobar, Felipe A; Kung, Sun-Yuan; Mandic, Danilo P
2014-02-01
The multikernel least-mean-square algorithm is introduced for adaptive estimation of vector-valued nonlinear and nonstationary signals. This is achieved by mapping the multivariate input data to a Hilbert space of time-varying vector-valued functions, whose inner products (kernels) are combined in an online fashion. The proposed algorithm is equipped with novel adaptive sparsification criteria ensuring a finite dictionary, and is computationally efficient and suitable for nonstationary environments. We also show the ability of the proposed vector-valued reproducing kernel Hilbert space to serve as a feature space for the class of multikernel least-squares algorithms. The benefits of adaptive multikernel (MK) estimation algorithms are illuminated in the nonlinear multivariate adaptive prediction setting. Simulations on nonlinear inertial body sensor signals and nonstationary real-world wind signals of low, medium, and high dynamic regimes support the approach. PMID:24807027
Parallel algorithms for matrix computations
Plemmons, R.J.
1990-01-01
The present conference on parallel algorithms for matrix computations encompasses both shared-memory systems and distributed-memory systems, as well as combinations of the two, to provide an overall perspective on parallel algorithms for both dense and sparse matrix computations in solving systems of linear equations, dense or structured problems related to least-squares computations, eigenvalue computations, singular-value computations, and rapid elliptic solvers. Specific issues addressed include the influence of parallel and vector architectures on algorithm design, computations for distributed-memory architectures such as hypercubes, solutions for sparse symmetric positive definite linear systems, symbolic and numeric factorizations, and triangular solutions. Also addressed are reference sources for parallel and vector numerical algorithms, sources for machine architectures, and sources for programming languages.
Fibonacci Numbers and Computer Algorithms.
ERIC Educational Resources Information Center
Atkins, John; Geist, Robert
1987-01-01
The Fibonacci Sequence describes a vast array of phenomena from nature. Computer scientists have discovered and used many algorithms which can be classified as applications of Fibonacci's sequence. In this article, several of these applications are considered. (PK)
The Origins of Counting Algorithms
Cantlon, Jessica F.; Piantadosi, Steven T.; Ferrigno, Stephen; Hughes, Kelly D.; Barnard, Allison M.
2015-01-01
Humans’ ability to ‘count’ by verbally labeling discrete quantities is unique in animal cognition. The evolutionary origins of counting algorithms are not understood. We report that non-human primates exhibit a cognitive ability that is algorithmically and logically similar to human counting. Monkeys were given the task of choosing between two food caches. Monkeys saw one cache baited with some number of food items, one item at a time. Then, a second cache was baited with food items, one at a time. At the point when the second set approximately outnumbered the first set, monkeys spontaneously moved to choose the second set even before it was completely baited. Using a novel Bayesian analysis, we show that monkeys used an approximate counting algorithm to increment and compare quantities in sequence. This algorithm is structurally similar to formal counting in humans and thus may have been an important evolutionary precursor to human counting. PMID:25953949
Description of the AILS Alerting Algorithm
NASA Technical Reports Server (NTRS)
Samanant, Paul; Jackson, Mike
2000-01-01
This document provides a complete description of the Airborne Information for Lateral Spacing (AILS) alerting algorithms. The purpose of AILS is to provide separation assurance between aircraft during simultaneous approaches to closely spaced parallel runways. AILS will allow independent approaches to be flown in such situations where dependent approaches were previously required (typically under Instrument Meteorological Conditions (IMC)). This is achieved by providing multiple levels of alerting for pairs of aircraft that are in parallel approach situations. This document#s scope is comprehensive and covers everything from general overviews, definitions, and concepts down to algorithmic elements and equations. The entire algorithm is presented in complete and detailed pseudo-code format. This can be used by software programmers to program AILS into a software language. Additional supporting information is provided in the form of coordinate frame definitions, data requirements, calling requirements as well as all necessary pre-processing and post-processing requirements. This is important and required information for the implementation of AILS into an analysis, a simulation, or a real-time system.
An iterative algorithm for finite element analysis
NASA Astrophysics Data System (ADS)
Laouafa, F.; Royis, P.
2004-03-01
In this paper, we state in a new form the algebraic problem arising from the one-field displacement finite element method (FEM). The displacement approach, in this discrete form, can be considered as the dual approach (force or equilibrium) with subsidiary constraints. This approach dissociates the nonlinear operator to the linear ones and their sizes are linear functions of integration rule which is of interest in the case of reduced integration. This new form of the problem leads to an inexpensive improvement of FEM computations, which acts at local, elementary and global levels. We demonstrate the numerical performances of this approach which is independent of the mesh structure. Using the GMRES algorithm we build, for nonsymmetric problems, a new algorithm based upon the discretized field of strain. The new algorithms proposed are more closer to the mechanical problem than the classical ones because all fields appear during the resolution process. The sizes of the different operators arising in these new forms are linear functions of integration rule, which is of great interest in the case of reduced integration.
NASA Astrophysics Data System (ADS)
Rao, Sailesh K.; Kollath, T.
1986-07-01
In this paper, we show that every systolic array executes a Regular Iterative Algorithm with a strongly separating hyperplane and conversely, that every such algorithm can be implemented on a systolic array. This characterization provides us with an unified framework for describing the contributions of other authors. It also exposes the relevance of many fundamental concepts that were introduced in the sixties by Hennie, Waite and Karp, Miller and Winograd, to the present day concern of systolic array
Genetic algorithms as discovery programs
Hilliard, M.R.; Liepins, G.
1986-01-01
Genetic algorithms are mathematical counterparts to natural selection and gene recombination. As such, they have provided one of the few significant breakthroughs in machine learning. Used with appropriate reward functions and apportionment of credit, they have been successfully applied to gas pipeline operation, x-ray registration and mathematical optimization problems. This paper discusses the basics of genetic algorithms, describes a few successes, and reports on current progress at Oak Ridge National Laboratory in applications to set covering and simulated robots.
An Efficient Pattern Matching Algorithm
NASA Astrophysics Data System (ADS)
Sleit, Azzam; Almobaideen, Wesam; Baarah, Aladdin H.; Abusitta, Adel H.
In this study, we present an efficient algorithm for pattern matching based on the combination of hashing and search trees. The proposed solution is classified as an offline algorithm. Although, this study demonstrates the merits of the technique for text matching, it can be utilized for various forms of digital data including images, audio and video. The performance superiority of the proposed solution is validated analytically and experimentally.
Monitoring and Commissioning Verification Algorithms for CHP Systems
Brambley, Michael R.; Katipamula, Srinivas; Jiang, Wei
2008-03-31
This document provides the algorithms for CHP system performance monitoring and commissioning verification (CxV). It starts by presenting system-level and component-level performance metrics, followed by descriptions of algorithms for performance monitoring and commissioning verification, using the metric presented earlier. Verification of commissioning is accomplished essentially by comparing actual measured performance to benchmarks for performance provided by the system integrator and/or component manufacturers. The results of these comparisons are then automatically interpreted to provide conclusions regarding whether the CHP system and its components have been properly commissioned and where problems are found, guidance is provided for corrections. A discussion of uncertainty handling is then provided, which is followed by a description of how simulations models can be used to generate data for testing the algorithms. A model is described for simulating a CHP system consisting of a micro-turbine, an exhaust-gas heat recovery unit that produces hot water, a absorption chiller and a cooling tower. The process for using this model for generating data for testing the algorithms for a selected set of faults is described. The next section applies the algorithms developed to CHP laboratory and field data to illustrate their use. The report then concludes with a discussion of the need for laboratory testing of the algorithms on a physical CHP systems and identification of the recommended next steps.
The prototype SMOS soil moisture Algorithm
NASA Astrophysics Data System (ADS)
Kerr, Y.; Waldteufel, P.; Richaume, P.; Cabot, F.; Wigneron, J. P.; Ferrazzoli, P.; Mahmoodi, A.; Delwart, S.
2009-04-01
The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, to be launched in September 2007. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 will consists mainly of angular brightness temperatures while level 2 will consist of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The consortium of institutes preparing the Soil moisture algorithm is led by CESBIO (Centre d'Etudes Spatiales de la BIOsphère) and Service d'Aéronomie and consists of the institutes represented by the authors. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric
Retrieval Algorithms for the Halogen Occultation Experiment
NASA Technical Reports Server (NTRS)
Thompson, Robert E.; Gordley, Larry L.
2009-01-01
The Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite (UARS) provided high quality measurements of key middle atmosphere constituents, aerosol characteristics, and temperature for 14 years (1991-2005). This report is an outline of the Level 2 retrieval algorithms, and it also describes the great care that was taken in characterizing the instrument prior to launch and throughout its mission life. It represents an historical record of the techniques used to analyze the data and of the steps that must be considered for the development of a similar experiment for future satellite missions.
Concepts and algorithms in digital photogrammetry
NASA Technical Reports Server (NTRS)
Schenk, T.
1994-01-01
Despite much progress in digital photogrammetry, there is still a considerable lack of understanding of theories and methods which would allow a substantial increase in the automation of photogrammetric processes. The purpose of this paper is to raise awareness that the automation problem is one that cannot be solved in a bottom-up fashion by a trial-and-error approach. We present a short overview of concepts and algorithms used in digital photogrammetry. This is followed by a more detailed presentation of perceptual organization, a typical middle-level task.
Linear antenna array optimization using flower pollination algorithm.
Saxena, Prerna; Kothari, Ashwin
2016-01-01
Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance. PMID:27066339
Parallel algorithms for computation of the manipulator inertia matrix
NASA Technical Reports Server (NTRS)
Amin-Javaheri, Masoud; Orin, David E.
1989-01-01
The development of an O(log2N) parallel algorithm for the manipulator inertia matrix is presented. It is based on the most efficient serial algorithm which uses the composite rigid body method. Recursive doubling is used to reformulate the linear recurrence equations which are required to compute the diagonal elements of the matrix. It results in O(log2N) levels of computation. Computation of the off-diagonal elements involves N linear recurrences of varying-size and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log2N) algorithm is presented in both equation and graphic forms which clearly show the parallelism inherent in the algorithm.
Quantum Image Encryption Algorithm Based on Image Correlation Decomposition
NASA Astrophysics Data System (ADS)
Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun
2015-02-01
A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.
Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.
He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej
2011-12-01
Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.
Algorithms for propagating uncertainty across heterogeneous domains
Cho, Heyrim; Yang, Xiu; Venturi, D.; Karniadakis, George E.
2015-12-30
We address an important research area in stochastic multi-scale modeling, namely the propagation of uncertainty across heterogeneous domains characterized by partially correlated processes with vastly different correlation lengths. This class of problems arise very often when computing stochastic PDEs and particle models with stochastic/stochastic domain interaction but also with stochastic/deterministic coupling. The domains may be fully embedded, adjacent or partially overlapping. The fundamental open question we address is the construction of proper transmission boundary conditions that preserve global statistical properties of the solution across different subdomains. Often, the codes that model different parts of the domains are black-box and hence a domain decomposition technique is required. No rigorous theory or even effective empirical algorithms have yet been developed for this purpose, although interfaces defined in terms of functionals of random fields (e.g., multi-point cumulants) can overcome the computationally prohibitive problem of preserving sample-path continuity across domains. The key idea of the different methods we propose relies on combining local reduced-order representations of random fields with multi-level domain decomposition. Specifically, we propose two new algorithms: The first one enforces the continuity of the conditional mean and variance of the solution across adjacent subdomains by using Schwarz iterations. The second algorithm is based on PDE-constrained multi-objective optimization, and it allows us to set more general interface conditions. The effectiveness of these new algorithms is demonstrated in numerical examples involving elliptic problems with random diffusion coefficients, stochastically advected scalar fields, and nonlinear advection-reaction problems with random reaction rates.
Recursive Branching Simulated Annealing Algorithm
NASA Technical Reports Server (NTRS)
Bolcar, Matthew; Smith, J. Scott; Aronstein, David
2012-01-01
This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal
Optimization of multilayer cylindrical cloaks using genetic algorithms and NEWUOA
NASA Astrophysics Data System (ADS)
Sakr, Ahmed A.; Abdelmageed, Alaa K.
2016-06-01
The problem of minimizing the scattering from a multilayer cylindrical cloak is studied. Both TM and TE polarizations are considered. A two-stage optimization procedure using genetic algorithms and NEWUOA (new unconstrained optimization algorithm) is adopted for realizing the cloak using homogeneous isotropic layers. The layers are arranged such that they follow a repeated pattern of alternating DPS and DNG materials. The results show that a good level of invisibility can be realized using a reasonable number of layers. Maintaining the cloak performance over a finite range of frequencies without sacrificing the level of invisibility is achieved.
NASA Astrophysics Data System (ADS)
Gori, Valentina
2014-05-01
The CMS experiment has been designed with a 2-level trigger system: the Level 1 Trigger, implemented on custom-designed electronics, and the High Level Trigger (HLT), a streamlined version of the CMS offline reconstruction software running on a computer farm. A software trigger system requires a tradeoff between the complexity of the algorithms running on the available computing power, the sustainable output rate, and the selection efficiency. Here we will present the performance of the main triggers used during the 2012 data taking, ranging from simpler single-object selections to more complex algorithms combining different objects, and applying analysis-level reconstruction and selection. We will discuss the optimisation of the triggers and the specific techniques to cope with the increasing LHC pile-up, reducing its impact on the physics performance.
NASA Astrophysics Data System (ADS)
Trocino, Daniele
2014-06-01
The CMS experiment has been designed with a two-level trigger system: the Level-1 Trigger, implemented in custom-designed electronics, and the High-Level Trigger (HLT), a streamlined version of the CMS offline reconstruction software running on a computer farm. A software trigger system requires a tradeoff between the complexity of the algorithms running with the available computing power, the sustainable output rate, and the selection efficiency. We present the performance of the main triggers used during the 2012 data taking, ranging from simple single-object selections to more complex algorithms combining different objects, and applying analysis-level reconstruction and selection. We discuss the optimisation of the trigger and the specific techniques to cope with the increasing LHC pile-up, reducing its impact on the physics performance.
A comparative analysis of biclustering algorithms for gene expression data.
Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V
2013-05-01
The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters.
Chang, C.Y.
1986-01-01
New results on efficient forms of decoding convolutional codes based on Viterbi and stack algorithms using systolic array architecture are presented. Some theoretical aspects of systolic arrays are also investigated. First, systolic array implementation of Viterbi algorithm is considered, and various properties of convolutional codes are derived. A technique called strongly connected trellis decoding is introduced to increase the efficient utilization of all the systolic array processors. The issues dealing with the composite branch metric generation, survivor updating, overall system architecture, throughput rate, and computations overhead ratio are also investigated. Second, the existing stack algorithm is modified and restated in a more concise version so that it can be efficiently implemented by a special type of systolic array called systolic priority queue. Three general schemes of systolic priority queue based on random access memory, shift register, and ripple register are proposed. Finally, a systematic approach is presented to design systolic arrays for certain general classes of recursively formulated algorithms.
Analysis and applications of a general boresight algorithm for the DSS-13 beam waveguide antenna
NASA Technical Reports Server (NTRS)
Alvarez, L. S.
1992-01-01
A general antenna beam boresight algorithm is presented. Equations for axial pointing error, peak received signal level, and antenna half-power beamwidth are given. A pointing error variance equation is derived that illustrates the dependence of the measurement estimation performance on the various algorithm inputs, including RF signal level uncertainty. Plots showing pointing error uncertainty as function of algorithm inputs are presented. Insight gained from the performance analysis is discussed in terms of its application to the areas of antenna controller and receiver interfacing, pointing error compensation, and antenna calibrations. Current and planned applications of the boresight algorithm, including its role in the upcoming Ka-band downlink experiment (KABLE), are highlighted.
Level-3 Calorimetric Resolution available for the Level-1 and Level-2 CDF Triggers
Canepa, Anadi; Casarsa, M.; Cavaliere, V.; Cortiana, Giorgio; Donati, S.; Flanagan, G.; Greco, V.; Giannetti, P.; Frisch, H.; Krop, D.; Liu, T.; /Fermilab /INFN, Pisa
2008-06-01
As the Tevatron luminosity increases sophisticated selections are required to be efficient in selecting rare events among a very huge background. To cope with this problem, CDF has pushed the offline calorimeter algorithm reconstruction resolution up to Level 2 and, when possible, even up to Level 1, increasing efficiency and, at the same time, keeping under control the rates. The CDF Run II Level 2 calorimeter trigger is implemented in hardware and is based on a simple algorithm that was used in Run I. This system has worked well for Run II at low luminosity. As the Tevatron instantaneous luminosity increases, the limitation due to this simple algorithm starts to become clear: some of the most important jet and MET (Missing ET) related triggers have large growth terms in cross section at higher luminosity. In this paper, we present an upgrade of the Level 2 Calorimeter system which makes the calorimeter trigger tower information available directly to a CPU allowing more sophisticated algorithms to be implemented in software. Both Level 2 jets and MET can be made nearly equivalent to offline quality, thus significantly improving the performance and flexibility of the jet and MET related triggers. However in order to fully take advantage of the new L2 triggering capabilities having at Level 1 the same L2 MET resolution is necessary. The new Level-1 MET resolution is calculated by dedicated hardware. This paper describes the design, the hardware and software implementation and the performance of the upgraded calorimeter trigger system both at Level 2 and Level 1.
GPU Accelerated Event Detection Algorithm
2011-05-25
Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but alsomore » model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.« less
Mathematical algorithms for approximate reasoning
NASA Technical Reports Server (NTRS)
Murphy, John H.; Chay, Seung C.; Downs, Mary M.
1988-01-01
Most state of the art expert system environments contain a single and often ad hoc strategy for approximate reasoning. Some environments provide facilities to program the approximate reasoning algorithms. However, the next generation of expert systems should have an environment which contain a choice of several mathematical algorithms for approximate reasoning. To meet the need for validatable and verifiable coding, the expert system environment must no longer depend upon ad hoc reasoning techniques but instead must include mathematically rigorous techniques for approximate reasoning. Popular approximate reasoning techniques are reviewed, including: certainty factors, belief measures, Bayesian probabilities, fuzzy logic, and Shafer-Dempster techniques for reasoning. A group of mathematically rigorous algorithms for approximate reasoning are focused on that could form the basis of a next generation expert system environment. These algorithms are based upon the axioms of set theory and probability theory. To separate these algorithms for approximate reasoning various conditions of mutual exclusivity and independence are imposed upon the assertions. Approximate reasoning algorithms presented include: reasoning with statistically independent assertions, reasoning with mutually exclusive assertions, reasoning with assertions that exhibit minimum overlay within the state space, reasoning with assertions that exhibit maximum overlay within the state space (i.e. fuzzy logic), pessimistic reasoning (i.e. worst case analysis), optimistic reasoning (i.e. best case analysis), and reasoning with assertions with absolutely no knowledge of the possible dependency among the assertions. A robust environment for expert system construction should include the two modes of inference: modus ponens and modus tollens. Modus ponens inference is based upon reasoning towards the conclusion in a statement of logical implication, whereas modus tollens inference is based upon reasoning away
Improved autonomous star identification algorithm
NASA Astrophysics Data System (ADS)
Luo, Li-Yan; Xu, Lu-Ping; Zhang, Hua; Sun, Jing-Rong
2015-06-01
The log-polar transform (LPT) is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm. Project supported by the National Natural Science Foundation of China (Grant Nos. 61172138 and 61401340), the Open Research Fund of the Academy of Satellite Application, China (Grant No. 2014_CXJJ-DH_12), the Fundamental Research Funds for the Central Universities, China (Grant Nos. JB141303 and 201413B), the Natural Science Basic Research Plan in Shaanxi Province, China (Grant No. 2013JQ8040), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130203120004), and the Xi’an Science and Technology Plan, China (Grant. No CXY1350(4)).
GPU Accelerated Event Detection Algorithm
2011-05-25
Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but also model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.
Adaptive Routing Algorithm in Wireless Communication Networks Using Evolutionary Algorithm
NASA Astrophysics Data System (ADS)
Yan, Xuesong; Wu, Qinghua; Cai, Zhihua
At present, mobile communications traffic routing designs are complicated because there are more systems inter-connecting to one another. For example, Mobile Communication in the wireless communication networks has two routing design conditions to consider, i.e. the circuit switching and the packet switching. The problem in the Packet Switching routing design is its use of high-speed transmission link and its dynamic routing nature. In this paper, Evolutionary Algorithms is used to determine the best solution and the shortest communication paths. We developed a Genetic Optimization Process that can help network planners solving the best solutions or the best paths of routing table in wireless communication networks are easily and quickly. From the experiment results can be noted that the evolutionary algorithm not only gets good solutions, but also a more predictable running time when compared to sequential genetic algorithm.
Algorithms, complexity, and the sciences.
Papadimitriou, Christos
2014-11-11
Algorithms, perhaps together with Moore's law, compose the engine of the information technology revolution, whereas complexity--the antithesis of algorithms--is one of the deepest realms of mathematical investigation. After introducing the basic concepts of algorithms and complexity, and the fundamental complexity classes P (polynomial time) and NP (nondeterministic polynomial time, or search problems), we discuss briefly the P vs. NP problem. We then focus on certain classes between P and NP which capture important phenomena in the social and life sciences, namely the Nash equlibrium and other equilibria in economics and game theory, and certain processes in population genetics and evolution. Finally, an algorithm known as multiplicative weights update (MWU) provides an algorithmic interpretation of the evolution of allele frequencies in a population under sex and weak selection. All three of these equivalences are rife with domain-specific implications: The concept of Nash equilibrium may be less universal--and therefore less compelling--than has been presumed; selection on gene interactions may entail the maintenance of genetic variation for longer periods than selection on single alleles predicts; whereas MWU can be shown to maximize, for each gene, a convex combination of the gene's cumulative fitness in the population and the entropy of the allele distribution, an insight that may be pertinent to the maintenance of variation in evolution.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms.
SDR Input Power Estimation Algorithms
NASA Technical Reports Server (NTRS)
Nappier, Jennifer M.; Briones, Janette C.
2013-01-01
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
SDR input power estimation algorithms
NASA Astrophysics Data System (ADS)
Briones, J. C.; Nappier, J. M.
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Algorithms for automated DNA assembly
Densmore, Douglas; Hsiau, Timothy H.-C.; Kittleson, Joshua T.; DeLoache, Will; Batten, Christopher; Anderson, J. Christopher
2010-01-01
Generating a defined set of genetic constructs within a large combinatorial space provides a powerful method for engineering novel biological functions. However, the process of assembling more than a few specific DNA sequences can be costly, time consuming and error prone. Even if a correct theoretical construction scheme is developed manually, it is likely to be suboptimal by any number of cost metrics. Modular, robust and formal approaches are needed for exploring these vast design spaces. By automating the design of DNA fabrication schemes using computational algorithms, we can eliminate human error while reducing redundant operations, thus minimizing the time and cost required for conducting biological engineering experiments. Here, we provide algorithms that optimize the simultaneous assembly of a collection of related DNA sequences. We compare our algorithms to an exhaustive search on a small synthetic dataset and our results show that our algorithms can quickly find an optimal solution. Comparison with random search approaches on two real-world datasets show that our algorithms can also quickly find lower-cost solutions for large datasets. PMID:20335162
Algorithm for Rapid Searching Among Star-Catalog Entries
NASA Technical Reports Server (NTRS)
Liebe, Carl Christian
2006-01-01
An algorithm searches a star catalog to identify guide stars within the field of view of a telescope or camera. The algorithm is fast: the number of computations needed to perform the search is approximately proportional to the logarithm of the number of stars in the catalog. The algorithm requires the prior organization of the star catalog into a hierarchy utilizing independent spherical coverings (see figure), such that each successively higher level contains fewer elements. In the lowest and most numerous level of the hierarchy, the elements are individual stars in the star catalog. The next higher level contains a spherical covering (a constellation of n points on a sphere that minimizes the maximum distance of any point on the sphere from the closest one of the n points), the next higher level contains a smaller spherical covering, and so forth, ending at the highest level, which contains one element representing the point of entry into the search structure. With necessary exceptions at the lowest and highest levels, each element at each level is labeled in terms of the element to which it is linked in the next higher level and the first element to which it is linked in the next lower level. Each element is also labeled in terms of (1) its coordinates on the celestial sphere and (2) the largest angular distance to any element in any lower level in the hierarchy. The elements at all levels of the hierarchy are numbered on a single list, such that the elements of each constellation at each level are numbered consecutively. The algorithm is recursive. The input required to start the algorithm comprises the coordinates of a point on the celestial sphere. Attention is then focused on individual elements of the hierarchy, starting from the topmost one, as follows: The angle between the input point and the element under consideration is calculated. If the calculated angle is larger than the sum of (1) the predetermined angle to the most distant element plus (2) the
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…
Operator induced multigrid algorithms using semirefinement
NASA Technical Reports Server (NTRS)
Decker, Naomi; Vanrosendale, John
1989-01-01
A variant of multigrid, based on zebra relaxation, and a new family of restriction/prolongation operators is described. Using zebra relaxation in combination with an operator-induced prolongation leads to fast convergence, since the coarse grid can correct all error components. The resulting algorithms are not only fast, but are also robust, in the sense that the convergence rate is insensitive to the mesh aspect ratio. This is true even though line relaxation is performed in only one direction. Multigrid becomes a direct method if an operator-induced prolongation is used, together with the induced coarse grid operators. Unfortunately, this approach leads to stencils which double in size on each coarser grid. The use of an implicit three point restriction can be used to factor these large stencils, in order to retain the usual five or nine point stencils, while still achieving fast convergence. This algorithm achieves a V-cycle convergence rate of 0.03 on Poisson's equation, using 1.5 zebra sweeps per level, while the convergence rate improves to 0.003 if optimal nine point stencils are used. Numerical results for two and three dimensional model problems are presented, together with a two level analysis explaining these results.
Operator induced multigrid algorithms using semirefinement
NASA Technical Reports Server (NTRS)
Decker, Naomi Henderson; Van Rosendale, John
1989-01-01
A variant of multigrid, based on zebra relaxation, and a new family of restriction/prolongation operators is described. Using zebra relaxation in combination with an operator-induced prolongation leads to fast convergence, since the coarse grid can correct all error components. The resulting algorithms are not only fast, but are also robust, in the sense that the convergence rate is insensitive to the mesh aspect ratio. This is true even though line relaxation is performed in only one direction. Multigrid becomes a direct method if an operator-induced prolongation is used, together with the induced coarse grid operators. Unfortunately, this approach leads to stencils which double in size on each coarser grid. The use of an implicit three point restriction can be used to factor these large stencils, in order to retain the usual five or nine point stencils, while still achieving fast convergence. This algorithm achieves a V-cycle convergence rate of 0.03 on Poisson's equation, using 1.5 zebra sweeps per level, while the convergence rate improves to 0.003 if optimal nine point stencils are used. Numerical results for two- and three-dimensional model problems are presented, together with a two level analysis explaining these results.
Algorithmic requirements for swarm intelligence in differently coupled collective systems.
Stradner, Jürgen; Thenius, Ronald; Zahadat, Payam; Hamann, Heiko; Crailsheim, Karl; Schmickl, Thomas
2013-05-01
Swarm systems are based on intermediate connectivity between individuals and dynamic neighborhoods. In natural swarms self-organizing principles bring their agents to that favorable level of connectivity. They serve as interesting sources of inspiration for control algorithms in swarm robotics on the one hand, and in modular robotics on the other hand. In this paper we demonstrate and compare a set of bio-inspired algorithms that are used to control the collective behavior of swarms and modular systems: BEECLUST, AHHS (hormone controllers), FGRN (fractal genetic regulatory networks), and VE (virtual embryogenesis). We demonstrate how such bio-inspired control paradigms bring their host systems to a level of intermediate connectivity, what delivers sufficient robustness to these systems for collective decentralized control. In parallel, these algorithms allow sufficient volatility of shared information within these systems to help preventing local optima and deadlock situations, this way keeping those systems flexible and adaptive in dynamic non-deterministic environments. PMID:23805030
Analysis of multigrid algorithms for nonsymmetric and indefinite elliptic problems
Bramble, J.H.; Pasciak, J.E.; Xu, J.
1988-10-01
We prove some new estimates for the convergence of multigrid algorithms applied to nonsymmetric and indefinite elliptic boundary value problems. We provide results for the so-called 'symmetric' multigrid schemes. We show that for the variable V-script-cycle and the W-script-cycle schemes, multigrid algorithms with any amount of smoothing on the finest grid converge at a rate that is independent of the number of levels or unknowns, provided that the initial grid is sufficiently fine. We show that the V-script-cycle algorithm also converges (under appropriate assumptions on the coarsest grid) but at a rate which may deteriorate as the number of levels increases. This deterioration for the V-script-cycle may occur even in the case of full elliptic regularity. Finally, the results of numerical experiments are given which illustrate the convergence behavior suggested by the theory.
Shape determination and placement algorithms for hierarchical integrated circuit layout
NASA Astrophysics Data System (ADS)
Slutz, E. A.
Algorithms for the automatic layout of integrated circuits are presented. The algorithms use a hierarchical decomposition of the circuit structure. Since this reduces the complexity of the design, it is an aid to the designer as well as the means of making possible the automated approach to layout. The layout method consists of two phases: a top-down phase during which the shapes of the components at each level are determined, followed by a bottomup phase where a final placement and routing for each level is computed. The data structure used to model the chip surface is central to the algorithms. This data structure is presented along with the alternative structures. Four basic operations of adding components, deleting components, sizing, and building the structure for a given placement are described. A file format for capturing integrated circuit design information is also described.
Firefly Algorithm for Structural Search.
Avendaño-Franco, Guillermo; Romero, Aldo H
2016-07-12
The problem of computational structure prediction of materials is approached using the firefly (FF) algorithm. Starting from the chemical composition and optionally using prior knowledge of similar structures, the FF method is able to predict not only known stable structures but also a variety of novel competitive metastable structures. This article focuses on the strengths and limitations of the algorithm as a multimodal global searcher. The algorithm has been implemented in software package PyChemia ( https://github.com/MaterialsDiscovery/PyChemia ), an open source python library for materials analysis. We present applications of the method to van der Waals clusters and crystal structures. The FF method is shown to be competitive when compared to other population-based global searchers. PMID:27232694
Automated DNA Base Pair Calling Algorithm
1999-07-07
The procedure solves the problem of calling the DNA base pair sequence from two channel electropherogram separations in an automated fashion. The core of the program involves a peak picking algorithm based upon first, second, and third derivative spectra for each electropherogram channel, signal levels as a function of time, peak spacing, base pair signal to noise sequence patterns, frequency vs ratio of the two channel histograms, and confidence levels generated during the run. Themore » ratios of the two channels at peak centers can be used to accurately and reproducibly determine the base pair sequence. A further enhancement is a novel Gaussian deconvolution used to determine the peak heights used in generating the ratio.« less
Computational Algorithms for Device-Circuit Coupling
KEITER, ERIC R.; HUTCHINSON, SCOTT A.; HOEKSTRA, ROBERT J.; RANKIN, ERIC LAMONT; RUSSO, THOMAS V.; WATERS, LON J.
2003-01-01
Circuit simulation tools (e.g., SPICE) have become invaluable in the development and design of electronic circuits. Similarly, device-scale simulation tools (e.g., DaVinci) are commonly used in the design of individual semiconductor components. Some problems, such as single-event upset (SEU), require the fidelity of a mesh-based device simulator but are only meaningful when dynamically coupled with an external circuit. For such problems a mixed-level simulator is desirable, but the two types of simulation generally have different (sometimes conflicting) numerical requirements. To address these considerations, we have investigated variations of the two-level Newton algorithm, which preserves tight coupling between the circuit and the partial differential equations (PDE) device, while optimizing the numerics for both.
Synthesis of Greedy Algorithms Using Dominance Relations
NASA Technical Reports Server (NTRS)
Nedunuri, Srinivas; Smith, Douglas R.; Cook, William R.
2010-01-01
Greedy algorithms exploit problem structure and constraints to achieve linear-time performance. Yet there is still no completely satisfactory way of constructing greedy algorithms. For example, the Greedy Algorithm of Edmonds depends upon translating a problem into an algebraic structure called a matroid, but the existence of such a translation can be as hard to determine as the existence of a greedy algorithm itself. An alternative characterization of greedy algorithms is in terms of dominance relations, a well-known algorithmic technique used to prune search spaces. We demonstrate a process by which dominance relations can be methodically derived for a number of greedy algorithms, including activity selection, and prefix-free codes. By incorporating our approach into an existing framework for algorithm synthesis, we demonstrate that it could be the basis for an effective engineering method for greedy algorithms. We also compare our approach with other characterizations of greedy algorithms.
HEATR project: ATR algorithm parallelization
NASA Astrophysics Data System (ADS)
Deardorf, Catherine E.
1998-09-01
High Performance Computing (HPC) Embedded Application for Target Recognition (HEATR) is a project funded by the High Performance Computing Modernization Office through the Common HPC Software Support Initiative (CHSSI). The goal of CHSSI is to produce portable, parallel, multi-purpose, freely distributable, support software to exploit emerging parallel computing technologies and enable application of scalable HPC's for various critical DoD applications. Specifically, the CHSSI goal for HEATR is to provide portable, parallel versions of several existing ATR detection and classification algorithms to the ATR-user community to achieve near real-time capability. The HEATR project will create parallel versions of existing automatic target recognition (ATR) detection and classification algorithms and generate reusable code that will support porting and software development process for ATR HPC software. The HEATR Team has selected detection/classification algorithms from both the model- based and training-based (template-based) arena in order to consider the parallelization requirements for detection/classification algorithms across ATR technology. This would allow the Team to assess the impact that parallelization would have on detection/classification performance across ATR technology. A field demo is included in this project. Finally, any parallel tools produced to support the project will be refined and returned to the ATR user community along with the parallel ATR algorithms. This paper will review: (1) HPCMP structure as it relates to HEATR, (2) Overall structure of the HEATR project, (3) Preliminary results for the first algorithm Alpha Test, (4) CHSSI requirements for HEATR, and (5) Project management issues and lessons learned.
Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms
Pacheco, Maria P.; Pfau, Thomas; Sauter, Thomas
2016-01-01
Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. PMID:26834640
Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms.
Pacheco, Maria P; Pfau, Thomas; Sauter, Thomas
2015-01-01
Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms.
PPP Sliding Window Algorithm and Its Application in Deformation Monitoring.
Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming
2016-01-01
Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts. PMID:27241172
PPP Sliding Window Algorithm and Its Application in Deformation Monitoring
Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming
2016-01-01
Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts. PMID:27241172
Improving Polyp Detection Algorithms for CT Colonography: Pareto Front Approach.
Huang, Adam; Li, Jiang; Summers, Ronald M; Petrick, Nicholas; Hara, Amy K
2010-03-21
We investigated a Pareto front approach to improving polyp detection algorithms for CT colonography (CTC). A dataset of 56 CTC colon surfaces with 87 proven positive detections of 53 polyps sized 4 to 60 mm was used to evaluate the performance of a one-step and a two-step curvature-based region growing algorithm. The algorithmic performance was statistically evaluated and compared based on the Pareto optimal solutions from 20 experiments by evolutionary algorithms. The false positive rate was lower (p<0.05) by the two-step algorithm than by the one-step for 63% of all possible operating points. While operating at a suitable sensitivity level such as 90.8% (79/87) or 88.5% (77/87), the false positive rate was reduced by 24.4% (95% confidence intervals 17.9-31.0%) or 45.8% (95% confidence intervals 40.1-51.0%) respectively. We demonstrated that, with a proper experimental design, the Pareto optimization process can effectively help in fine-tuning and redesigning polyp detection algorithms.
PPP Sliding Window Algorithm and Its Application in Deformation Monitoring
NASA Astrophysics Data System (ADS)
Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming
2016-05-01
Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts.
Auto-focus algorithm based on statistical blur estimation
NASA Astrophysics Data System (ADS)
Kulkarni, Prajit
2013-03-01
Conventional auto-focus techniques in movable-lens camera systems use a measure of image sharpness to determine the lens position that brings the scene into focus. This paper presents a novel wavelet-domain approach to determine the position of best focus. In contrast to current techniques, the proposed algorithm estimates the level of blur in the captured image at each lens position. Image blur is quantified by fitting a Generalized Gaussian Density (GGD) curve to a high-pass version of the image using second-order statistics. The system then moves the lens to the position that yields the least measure of image blur. The algorithm overcomes shortcomings of sharpness-based approaches, namely, the application of large band-pass filters, sensitivity to image noise and need for calibration under different imaging conditions. Since noise has no effect on the proposed blur metric, the algorithm works with a short filter and is devoid of parameter tuning. Furthermore, the algorithm could be simplified to use a single high-pass filter to reduce complexity. These advantages, along with the optimization presented in the paper, make the proposed algorithm very attractive for hardware implementation on cell phones. Experiments prove that the algorithm performs well in the presence of noise as well as resolution and data scaling.
An Efficient Reachability Analysis Algorithm
NASA Technical Reports Server (NTRS)
Vatan, Farrokh; Fijany, Amir
2008-01-01
A document discusses a new algorithm for generating higher-order dependencies for diagnostic and sensor placement analysis when a system is described with a causal modeling framework. This innovation will be used in diagnostic and sensor optimization and analysis tools. Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in-situ platforms. This algorithm will serve as a power tool for technologies that satisfy a key requirement of autonomous spacecraft, including science instruments and in-situ missions.
A generalized memory test algorithm
NASA Technical Reports Server (NTRS)
Milner, E. J.
1982-01-01
A general algorithm for testing digital computer memory is presented. The test checks that (1) every bit can be cleared and set in each memory work, and (2) bits are not erroneously cleared and/or set elsewhere in memory at the same time. The algorithm can be applied to any size memory block and any size memory word. It is concise and efficient, requiring the very few cycles through memory. For example, a test of 16-bit-word-size memory requries only 384 cycles through memory. Approximately 15 seconds were required to test a 32K block of such memory, using a microcomputer having a cycle time of 133 nanoseconds.
A swaying object detection algorithm
NASA Astrophysics Data System (ADS)
Wang, Shidong; Rong, Jianzhong; Zhou, Dechuang; Wang, Jian
2013-07-01
Moving object detection is a most important preliminary step in video analysis. Some moving objects such as spitting steam, fire and smoke have unique motion feature whose lower position keep basically unchanged and the upper position move back and forth. Based on this unique motion feature, a swaying object detection algorithm is presented in this paper. Firstly, fuzzy integral was adopted to integrate color features for extracting moving objects from video frames. Secondly, a swaying identification algorithm based on centroid calculation was used to distinguish the swaying object from other moving objects. Experiments show that the proposed method is effective to detect swaying object.
ALGORITHM DEVELOPMENT FOR SPATIAL OPERATORS.
Claire, Robert W.
1984-01-01
An approach is given that develops spatial operators about the basic geometric elements common to spatial data structures. In this fashion, a single set of spatial operators may be accessed by any system that reduces its operands to such basic generic representations. Algorithms based on this premise have been formulated to perform operations such as separation, overlap, and intersection. Moreover, this generic approach is well suited for algorithms that exploit concurrent properties of spatial operators. The results may provide a framework for a geometry engine to support fundamental manipulations within a geographic information system.
Born approximation, scattering, and algorithm
NASA Astrophysics Data System (ADS)
Martinez, Alex; Hu, Mengqi; Gu, Haicheng; Qiao, Zhijun
2015-05-01
In the past few decades, there were many imaging algorithms designed in the case of the absence of multiple scattering. Recently, we discussed an algorithm for removing high order scattering components from collected data. This paper is a continuation of our previous work. First, we investigate the current state of multiple scattering in SAR. Then, we revise our method and test it. Given an estimate of our target reflectivity, we compute the multi scattering effects in the target region for various frequencies. Furthermore, we propagate this energy through free space towards our antenna, and remove it from the collected data.
Parallel algorithms for unconstrained optimizations by multisplitting
He, Qing
1994-12-31
In this paper a new parallel iterative algorithm for unconstrained optimization using the idea of multisplitting is proposed. This algorithm uses the existing sequential algorithms without any parallelization. Some convergence and numerical results for this algorithm are presented. The experiments are performed on an Intel iPSC/860 Hyper Cube with 64 nodes. It is interesting that the sequential implementation on one node shows that if the problem is split properly, the algorithm converges much faster than one without splitting.
Blind Alley Aware ACO Routing Algorithm
NASA Astrophysics Data System (ADS)
Yoshikawa, Masaya; Otani, Kazuo
2010-10-01
The routing problem is applied to various engineering fields. Many researchers study this problem. In this paper, we propose a new routing algorithm which is based on Ant Colony Optimization. The proposed algorithm introduces the tabu search mechanism to escape the blind alley. Thus, the proposed algorithm enables to find the shortest route, even if the map data contains the blind alley. Experiments using map data prove the effectiveness in comparison with Dijkstra algorithm which is the most popular conventional routing algorithm.
Two Algorithms for Processing Electronic Nose Data
NASA Technical Reports Server (NTRS)
Young, Rebecca; Linnell, Bruce
2007-01-01
Two algorithms for processing the digitized readings of electronic noses, and computer programs to implement the algorithms, have been devised in a continuing effort to increase the utility of electronic noses as means of identifying airborne compounds and measuring their concentrations. One algorithm identifies the two vapors in a two-vapor mixture and estimates the concentration of each vapor (in principle, this algorithm could be extended to more than two vapors). The other algorithm identifies a single vapor and estimates its concentration.
Formalization of algorithms for relational database machines
Ryvkin, V.M.; Komarov, P.I.; Nazarov, A.S.
1986-11-01
This paper applies the apparatus of algorithmic algebras to formalize the mapping of the relational algebra language into the internal database processor language. The apparatus is a popular tool for formal structured description of parallel algorithms. The MUL'TIPROTSESSIST automatic parallel program design system using systems of algorithmic algebras may be applied to automate the design of database machine operating algorithms in experimental research and to formalize the parallel organization of interpretation algorithms for the relational algebraic operations.
NASA Technical Reports Server (NTRS)
Roth, J. P.
1972-01-01
Methods for development of logic design together with algorithms for failure testing, a method for design of logic for ultra-large-scale integration, extension of quantum calculus to describe the functional behavior of a mechanism component-by-component and to computer tests for failures in the mechanism using the diagnosis algorithm, and the development of an algorithm for the multi-output 2-level minimization problem are discussed.
Two Level Parallel Grammatical Evolution
NASA Astrophysics Data System (ADS)
Ošmera, Pavel
This paper describes a Two Level Parallel Grammatical Evolution (TLPGE) that can evolve complete programs using a variable length linear genome to govern the mapping of a Backus Naur Form grammar definition. To increase the efficiency of Grammatical Evolution (GE) the influence of backward processing was tested and a second level with differential evolution was added. The significance of backward coding (BC) and the comparison with standard coding of GEs is presented. The new method is based on parallel grammatical evolution (PGE) with a backward processing algorithm, which is further extended with a differential evolution algorithm. Thus a two-level optimization method was formed in attempt to take advantage of the benefits of both original methods and avoid their difficulties. Both methods used are discussed and the architecture of their combination is described. Also application is discussed and results on a real-word application are described.
Sensitivity Analysis for Hierarchical Models Employing "t" Level-1 Assumptions.
ERIC Educational Resources Information Center
Seltzer, Michael; Novak, John; Choi, Kilchan; Lim, Nelson
2002-01-01
Examines the ways in which level-1 outliers can impact the estimation of fixed effects and random effects in hierarchical models (HMs). Also outlines and illustrates the use of Markov Chain Monte Carlo algorithms for conducting sensitivity analyses under "t" level-1 assumptions, including algorithms for settings in which the degrees of freedom at…
PSLQ: An Algorithm to Discover Integer Relations
Bailey, David H.; Borwein, J. M.
2009-04-03
Let x = (x{sub 1}, x{sub 2} {hor_ellipsis}, x{sub n}) be a vector of real or complex numbers. x is said to possess an integer relation if there exist integers a{sub i}, not all zero, such that a{sub 1}x{sub 1} + a{sub 2}x{sub 2} + {hor_ellipsis} + a{sub n}x{sub n} = 0. By an integer relation algorithm, we mean a practical computational scheme that can recover the vector of integers ai, if it exists, or can produce bounds within which no integer relation exists. As we will see in the examples below, an integer relation algorithm can be used to recognize a computed constant in terms of a formula involving known constants, or to discover an underlying relation between quantities that can be computed to high precision. At the present time, the most effective algorithm for integer relation detection is the 'PSLQ' algorithm of mathematician-sculptor Helaman Ferguson [10, 4]. Some efficient 'multi-level' implementations of PSLQ, as well as a variant of PSLQ that is well-suited for highly parallel computer systems, are given in [4]. PSLQ constructs a sequence of integer-valued matrices B{sub n} that reduces the vector y = xB{sub n}, until either the relation is found (as one of the columns of B{sub n}), or else precision is exhausted. At the same time, PSLQ generates a steadily growing bound on the size of any possible relation. When a relation is found, the size of smallest entry of the vector y abruptly drops to roughly 'epsilon' (i.e. 10{sup -p}, where p is the number of digits of precision). The size of this drop can be viewed as a 'confidence level' that the relation is real and not merely a numerical artifact - a drop of 20 or more orders of magnitude almost always indicates a real relation. Very high precision arithmetic must be used in PSLQ. If one wishes to recover a relation of length n, with coefficients of maximum size d digits, then the input vector x must be specified to at least nd digits, and one must employ nd-digit floating-point arithmetic. Maple and
Rapid algorithm prototyping and implementation for power quality measurement
NASA Astrophysics Data System (ADS)
Kołek, Krzysztof; Piątek, Krzysztof
2015-12-01
This article presents a Model-Based Design (MBD) approach to rapidly implement power quality (PQ) metering algorithms. Power supply quality is a very important aspect of modern power systems and will become even more important in future smart grids. In this case, maintaining the PQ parameters at the desired level will require efficient implementation methods of the metering algorithms. Currently, the development of new, advanced PQ metering algorithms requires new hardware with adequate computational capability and time intensive, cost-ineffective manual implementations. An alternative, considered here, is an MBD approach. The MBD approach focuses on the modelling and validation of the model by simulation, which is well-supported by a Computer-Aided Engineering (CAE) packages. This paper presents two algorithms utilized in modern PQ meters: a phase-locked loop based on an Enhanced Phase Locked Loop (EPLL), and the flicker measurement according to the IEC 61000-4-15 standard. The algorithms were chosen because of their complexity and non-trivial development. They were first modelled in the MATLAB/Simulink package, then tested and validated in a simulation environment. The models, in the form of Simulink diagrams, were next used to automatically generate C code. The code was compiled and executed in real-time on the Zynq Xilinx platform that combines a reconfigurable Field Programmable Gate Array (FPGA) with a dual-core processor. The MBD development of PQ algorithms, automatic code generation, and compilation form a rapid algorithm prototyping and implementation path for PQ measurements. The main advantage of this approach is the ability to focus on the design, validation, and testing stages while skipping over implementation issues. The code generation process renders production-ready code that can be easily used on the target hardware. This is especially important when standards for PQ measurement are in constant development, and the PQ issues in emerging smart
Rapidly re-computable EEG (electroencephalography) forward models for realistic head shapes
Ermer, J. J.; Mosher, J. C.; Baillet, S.; Leahy, R. M.
2001-01-01
Solution of the EEG source localization (inverse) problem utilizing model-based methods typically requires a significant number of forward model evaluations. For subspace based inverse methods like MUSIC [6], the total number of forward model evaluations can often approach an order of 10{sup 3} or 10{sup 4}. Techniques based on least-squares minimization may require significantly more evaluations. The observed set of measurements over an M-sensor array is often expressed as a linear forward spatio-temporal model of the form: F = GQ + N (1) where the observed forward field F (M-sensors x N-time samples) can be expressed in terms of the forward model G, a set of dipole moment(s) Q (3xP-dipoles x N-time samples) and additive noise N. Because of their simplicity, ease of computation, and relatively good accuracy, multi-layer spherical models [7] (or fast approximations described in [1], [7]) have traditionally been the 'forward model of choice' for approximating the human head. However, approximation of the human head via a spherical model does have several key drawbacks. By its very shape, the use of a spherical model distorts the true distribution of passive currents in the skull cavity. Spherical models also require that the sensor positions be projected onto the fitted sphere (Fig. 1), resulting in a distortion of the true sensor-dipole spatial geometry (and ultimately the computed surface potential). The use of a single 'best-fitted' sphere has the added drawback of incomplete coverage of the inner skull region, often ignoring areas such as the frontal cortex. In practice, this problem is typically countered by fitting additional sphere(s) to those region(s) not covered by the primary sphere. The use of these additional spheres results in added complication to the forward model. Using high-resolution spatial information obtained via X-ray CT or MR imaging, a realistic head model can be formed by tessellating the head into a set of contiguous regions (typically the scalp, outer skull, and inner skull surfaces). Since accurate in vivo determination of internal conductivities is currently not currently possible, the head is typically assumed to consist of a set of contiguous isotropic regions, each with constant conductivity.
Chen, S; Wu, Y; Luk, B L
1999-01-01
The paper presents a two-level learning method for radial basis function (RBF) networks. A regularized orthogonal least squares (ROLS) algorithm is employed at the lower level to construct RBF networks while the two key learning parameters, the regularization parameter and the RBF width, are optimized using a genetic algorithm (GA) at the upper level. Nonlinear time series modeling and prediction is used as an example to demonstrate the effectiveness of this hierarchical learning approach.
Decoding the brain's algorithm for categorization from its neural implementation.
Mack, Michael L; Preston, Alison R; Love, Bradley C
2013-10-21
Acts of cognition can be described at different levels of analysis: what behavior should characterize the act, what algorithms and representations underlie the behavior, and how the algorithms are physically realized in neural activity [1]. Theories that bridge levels of analysis offer more complete explanations by leveraging the constraints present at each level [2-4]. Despite the great potential for theoretical advances, few studies of cognition bridge levels of analysis. For example, formal cognitive models of category decisions accurately predict human decision making [5, 6], but whether model algorithms and representations supporting category decisions are consistent with underlying neural implementation remains unknown. This uncertainty is largely due to the hurdle of forging links between theory and brain [7-9]. Here, we tackle this critical problem by using brain response to characterize the nature of mental computations that support category decisions to evaluate two dominant, and opposing, models of categorization. We found that brain states during category decisions were significantly more consistent with latent model representations from exemplar [5] rather than prototype theory [10, 11]. Representations of individual experiences, not the abstraction of experiences, are critical for category decision making. Holding models accountable for behavior and neural implementation provides a means for advancing more complete descriptions of the algorithms of cognition. PMID:24094852
Coupled cluster algorithms for networks of shared memory parallel processors
NASA Astrophysics Data System (ADS)
Bentz, Jonathan L.; Olson, Ryan M.; Gordon, Mark S.; Schmidt, Michael W.; Kendall, Ricky A.
2007-05-01
As the popularity of using SMP systems as the building blocks for high performance supercomputers increases, so too increases the need for applications that can utilize the multiple levels of parallelism available in clusters of SMPs. This paper presents a dual-layer distributed algorithm, using both shared-memory and distributed-memory techniques to parallelize a very important algorithm (often called the "gold standard") used in computational chemistry, the single and double excitation coupled cluster method with perturbative triples, i.e. CCSD(T). The algorithm is presented within the framework of the GAMESS [M.W. Schmidt, K.K. Baldridge, J.A. Boatz, S.T. Elbert, M.S. Gordon, J.J. Jensen, S. Koseki, N. Matsunaga, K.A. Nguyen, S. Su, T.L. Windus, M. Dupuis, J.A. Montgomery, General atomic and molecular electronic structure system, J. Comput. Chem. 14 (1993) 1347-1363]. (General Atomic and Molecular Electronic Structure System) program suite and the Distributed Data Interface [M.W. Schmidt, G.D. Fletcher, B.M. Bode, M.S. Gordon, The distributed data interface in GAMESS, Comput. Phys. Comm. 128 (2000) 190]. (DDI), however, the essential features of the algorithm (data distribution, load-balancing and communication overhead) can be applied to more general computational problems. Timing and performance data for our dual-level algorithm is presented on several large-scale clusters of SMPs.
Biclustering Protein Complex Interactions with a Biclique FindingAlgorithm
Ding, Chris; Zhang, Anne Ya; Holbrook, Stephen
2006-12-01
Biclustering has many applications in text mining, web clickstream mining, and bioinformatics. When data entries are binary, the tightest biclusters become bicliques. We propose a flexible and highly efficient algorithm to compute bicliques. We first generalize the Motzkin-Straus formalism for computing the maximal clique from L{sub 1} constraint to L{sub p} constraint, which enables us to provide a generalized Motzkin-Straus formalism for computing maximal-edge bicliques. By adjusting parameters, the algorithm can favor biclusters with more rows less columns, or vice verse, thus increasing the flexibility of the targeted biclusters. We then propose an algorithm to solve the generalized Motzkin-Straus optimization problem. The algorithm is provably convergent and has a computational complexity of O(|E|) where |E| is the number of edges. It relies on a matrix vector multiplication and runs efficiently on most current computer architectures. Using this algorithm, we bicluster the yeast protein complex interaction network. We find that biclustering protein complexes at the protein level does not clearly reflect the functional linkage among protein complexes in many cases, while biclustering at protein domain level can reveal many underlying linkages. We show several new biologically significant results.
Quartic Rotation Criteria and Algorithms.
ERIC Educational Resources Information Center
Clarkson, Douglas B.; Jennrich, Robert I.
1988-01-01
Most of the current analytic rotation criteria for simple structure in factor analysis are summarized and identified as members of a general symmetric family of quartic criteria. A unified development of algorithms for orthogonal and direct oblique rotation using arbitrary criteria from this family is presented. (Author/TJH)
Adaptive protection algorithm and system
Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA
2009-04-28
An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.
Algorithms, complexity, and the sciences
Papadimitriou, Christos
2014-01-01
Algorithms, perhaps together with Moore’s law, compose the engine of the information technology revolution, whereas complexity—the antithesis of algorithms—is one of the deepest realms of mathematical investigation. After introducing the basic concepts of algorithms and complexity, and the fundamental complexity classes P (polynomial time) and NP (nondeterministic polynomial time, or search problems), we discuss briefly the P vs. NP problem. We then focus on certain classes between P and NP which capture important phenomena in the social and life sciences, namely the Nash equlibrium and other equilibria in economics and game theory, and certain processes in population genetics and evolution. Finally, an algorithm known as multiplicative weights update (MWU) provides an algorithmic interpretation of the evolution of allele frequencies in a population under sex and weak selection. All three of these equivalences are rife with domain-specific implications: The concept of Nash equilibrium may be less universal—and therefore less compelling—than has been presumed; selection on gene interactions may entail the maintenance of genetic variation for longer periods than selection on single alleles predicts; whereas MWU can be shown to maximize, for each gene, a convex combination of the gene’s cumulative fitness in the population and the entropy of the allele distribution, an insight that may be pertinent to the maintenance of variation in evolution. PMID:25349382
Associative Algorithms for Computational Creativity
ERIC Educational Resources Information Center
Varshney, Lav R.; Wang, Jun; Varshney, Kush R.
2016-01-01
Computational creativity, the generation of new, unimagined ideas or artifacts by a machine that are deemed creative by people, can be applied in the culinary domain to create novel and flavorful dishes. In fact, we have done so successfully using a combinatorial algorithm for recipe generation combined with statistical models for recipe ranking…
Coagulation algorithms with size binning
NASA Technical Reports Server (NTRS)
Statton, David M.; Gans, Jason; Williams, Eric
1994-01-01
The Smoluchowski equation describes the time evolution of an aerosol particle size distribution due to aggregation or coagulation. Any algorithm for computerized solution of this equation requires a scheme for describing the continuum of aerosol particle sizes as a discrete set. One standard form of the Smoluchowski equation accomplishes this by restricting the particle sizes to integer multiples of a basic unit particle size (the monomer size). This can be inefficient when particle concentrations over a large range of particle sizes must be calculated. Two algorithms employing a geometric size binning convention are examined: the first assumes that the aerosol particle concentration as a function of size can be considered constant within each size bin; the second approximates the concentration as a linear function of particle size within each size bin. The output of each algorithm is compared to an analytical solution in a special case of the Smoluchowski equation for which an exact solution is known . The range of parameters more appropriate for each algorithm is examined.
Key Concepts in Informatics: Algorithm
ERIC Educational Resources Information Center
Szlávi, Péter; Zsakó, László
2014-01-01
"The system of key concepts contains the most important key concepts related to the development tasks of knowledge areas and their vertical hierarchy as well as the links of basic key concepts of different knowledge areas." (Vass 2011) One of the most important of these concepts is the algorithm. In everyday life, when learning or…
Document Organization Using Kohonen's Algorithm.
ERIC Educational Resources Information Center
Guerrero Bote, Vicente P.; Moya Anegon, Felix de; Herrero Solana, Victor
2002-01-01
Discussion of the classification of documents from bibliographic databases focuses on a method of vectorizing reference documents from LISA (Library and Information Science Abstracts) which permits their topological organization using Kohonen's algorithm. Analyzes possibilities of this type of neural network with respect to the development of…
The origins of counting algorithms.
Cantlon, Jessica F; Piantadosi, Steven T; Ferrigno, Stephen; Hughes, Kelly D; Barnard, Allison M
2015-06-01
Humans' ability to count by verbally labeling discrete quantities is unique in animal cognition. The evolutionary origins of counting algorithms are not understood. We report that nonhuman primates exhibit a cognitive ability that is algorithmically and logically similar to human counting. Monkeys were given the task of choosing between two food caches. First, they saw one cache baited with some number of food items, one item at a time. Then, a second cache was baited with food items, one at a time. At the point when the second set was approximately equal to the first set, the monkeys spontaneously moved to choose the second set even before that cache was completely baited. Using a novel Bayesian analysis, we show that the monkeys used an approximate counting algorithm for comparing quantities in sequence that is incremental, iterative, and condition controlled. This proto-counting algorithm is structurally similar to formal counting in humans and thus may have been an important evolutionary precursor to human counting. PMID:25953949
Threshold extended ID3 algorithm
NASA Astrophysics Data System (ADS)
Kumar, A. B. Rajesh; Ramesh, C. Phani; Madhusudhan, E.; Padmavathamma, M.
2012-04-01
Information exchange over insecure networks needs to provide authentication and confidentiality to the database in significant problem in datamining. In this paper we propose a novel authenticated multiparty ID3 Algorithm used to construct multiparty secret sharing decision tree for implementation in medical transactions.
Algorithm Visualization in Teaching Practice
ERIC Educational Resources Information Center
Törley, Gábor
2014-01-01
This paper presents the history of algorithm visualization (AV), highlighting teaching-methodology aspects. A combined, two-group pedagogical experiment will be presented as well, which measured the efficiency and the impact on the abstract thinking of AV. According to the results, students, who learned with AV, performed better in the experiment.
Multilevel algorithms for nonlinear optimization
NASA Technical Reports Server (NTRS)
Alexandrov, Natalia; Dennis, J. E., Jr.
1994-01-01
Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that naturally occur in blocks. We propose a class of multilevel optimization methods motivated by the structure and number of constraints and by the expense of the derivative computations for MDO. The algorithms are an extension to the nonlinear programming problem of the successful class of local Brown-Brent algorithms for nonlinear equations. Our extensions allow the user to partition constraints into arbitrary blocks to fit the application, and they separately process each block and the objective function, restricted to certain subspaces. The methods use trust regions as a globalization strategy, and they have been shown to be globally convergent under reasonable assumptions. The multilevel algorithms can be applied to all classes of MDO formulations. Multilevel algorithms for solving nonlinear systems of equations are a special case of the multilevel optimization methods. In this case, they can be viewed as a trust-region globalization of the Brown-Brent class.
An Algorithm for Suffix Stripping
ERIC Educational Resources Information Center
Porter, M. F.
2006-01-01
Purpose: The automatic removal of suffixes from words in English is of particular interest in the field of information retrieval. This work was originally published in Program in 1980 and is republished as part of a series of articles commemorating the 40th anniversary of the journal. Design/methodology/approach: An algorithm for suffix stripping…
Randomized approximate nearest neighbors algorithm.
Jones, Peter Wilcox; Osipov, Andrei; Rokhlin, Vladimir
2011-09-20
We present a randomized algorithm for the approximate nearest neighbor problem in d-dimensional Euclidean space. Given N points {x(j)} in R(d), the algorithm attempts to find k nearest neighbors for each of x(j), where k is a user-specified integer parameter. The algorithm is iterative, and its running time requirements are proportional to T·N·(d·(log d) + k·(d + log k)·(log N)) + N·k(2)·(d + log k), with T the number of iterations performed. The memory requirements of the procedure are of the order N·(d + k). A by-product of the scheme is a data structure, permitting a rapid search for the k nearest neighbors among {x(j)} for an arbitrary point x ∈ R(d). The cost of each such query is proportional to T·(d·(log d) + log(N/k)·k·(d + log k)), and the memory requirements for the requisite data structure are of the order N·(d + k) + T·(d + N). The algorithm utilizes random rotations and a basic divide-and-conquer scheme, followed by a local graph search. We analyze the scheme's behavior for certain types of distributions of {x(j)} and illustrate its performance via several numerical examples.
Some Practical Payments Clearance Algorithms
NASA Astrophysics Data System (ADS)
Kumlander, Deniss
The globalisation of corporations' operations has produced a huge volume of inter-company invoices. Optimisation of those known as payment clearance can produce a significant saving in costs associated with those transfers and handling. The paper revises some common and so practical approaches to the payment clearance problem and proposes some novel algorithms based on graphs theory and heuristic totals' distribution.
Evaluating and comparing algorithms for respiratory motion prediction.
Ernst, F; Dürichen, R; Schlaefer, A; Schweikard, A
2013-06-01
In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm-which is one of the algorithms currently used in the CyberKnife-is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient's respiratory
Evaluating and comparing algorithms for respiratory motion prediction.
Ernst, F; Dürichen, R; Schlaefer, A; Schweikard, A
2013-06-01
In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm-which is one of the algorithms currently used in the CyberKnife-is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient's respiratory
Linear Bregman algorithm implemented in parallel GPU
NASA Astrophysics Data System (ADS)
Li, Pengyan; Ke, Jue; Sui, Dong; Wei, Ping
2015-08-01
At present, most compressed sensing (CS) algorithms have poor converging speed, thus are difficult to run on PC. To deal with this issue, we use a parallel GPU, to implement a broadly used compressed sensing algorithm, the Linear Bregman algorithm. Linear iterative Bregman algorithm is a reconstruction algorithm proposed by Osher and Cai. Compared with other CS reconstruction algorithms, the linear Bregman algorithm only involves the vector and matrix multiplication and thresholding operation, and is simpler and more efficient for programming. We use C as a development language and adopt CUDA (Compute Unified Device Architecture) as parallel computing architectures. In this paper, we compared the parallel Bregman algorithm with traditional CPU realized Bregaman algorithm. In addition, we also compared the parallel Bregman algorithm with other CS reconstruction algorithms, such as OMP and TwIST algorithms. Compared with these two algorithms, the result of this paper shows that, the parallel Bregman algorithm needs shorter time, and thus is more convenient for real-time object reconstruction, which is important to people's fast growing demand to information technology.
Development of microwave rainfall retrieval algorithm for climate applications
NASA Astrophysics Data System (ADS)
KIM, J. H.; Shin, D. B.
2014-12-01
With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.
NASA Technical Reports Server (NTRS)
Delaat, J. C.; Merrill, W. C.
1983-01-01
A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.
Mental Computation or Standard Algorithm? Children's Strategy Choices on Multi-Digit Subtractions
ERIC Educational Resources Information Center
Torbeyns, Joke; Verschaffel, Lieven
2016-01-01
This study analyzed children's use of mental computation strategies and the standard algorithm on multi-digit subtractions. Fifty-eight Flemish 4th graders of varying mathematical achievement level were individually offered subtractions that either stimulated the use of mental computation strategies or the standard algorithm in one choice and two…
Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm
2014-01-01
The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to compute the objective function values for each generation. Two case studies were given to illustrate the application of proposed approach. Optimum shape parameters of 2D bushing model were determined by shape optimization using differential evolution algorithm. PMID:25276848
AN ALGORITHM FOR PARALLEL SN SWEEPS ON UNSTRUCTURED MESHES
S. D. PAUTZ
2000-12-01
We develop a new algorithm for performing parallel S{sub n} sweeps on unstructured meshes. The algorithm uses a low-complexity list ordering heuristic to determine a sweep ordering on any partitioned mesh. For typical problems and with ''normal'' mesh partitionings we have observed nearly linear speedups on up to 126 processors. This is an important and desirable result, since although analyses of structured meshes indicate that parallel sweeps will not scale with normal partitioning approaches, we do not observe any severe asymptotic degradation in the parallel efficiency with modest ({le}100) levels of parallelism. This work is a fundamental step in the development of parallel S{sub n} methods.
Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description
Schmidt, Gail; Jenkerson, Calli; Masek, Jeffrey; Vermote, Eric; Gao, Feng
2013-01-01
The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from LandsatThematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product.The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record.This report discusses the LEDAPS algorithm, which was implemented by the USGS.
Algorithm-based analysis of collective decoherence in quantum computation
NASA Astrophysics Data System (ADS)
Utsunomiya, Shoko; Master, Cyrus P.; Yamamoto, Yoshihisa
2007-02-01
In a quantum computer, qubits are often stored in identical two-level systems separated by a distance shorter than the characteristic wavelength of the reservoirs that are responsible for decoherence. In this case the collective qubit-reservoir interaction, rather than the individual qubit-reservoir interaction, may determine the decoherence properties. We study the collective decoherence behavior in between each step in certain quantum algorithms and propose a simple alternative of implementing quantum algorithms using a quantum trajectory that is close to a decoherence-free subspace that avoids unstable Dicke's superradiant states and Schrödinger's cat state.
Generalized monotonically convergent algorithms for solving quantum optimal control problems
NASA Astrophysics Data System (ADS)
Ohtsuki, Yukiyoshi; Turinici, Gabriel; Rabitz, Herschel
2004-03-01
A wide range of cost functionals that describe the criteria for designing optimal pulses can be reduced to two basic functionals by the introduction of product spaces. We extend previous monotonically convergent algorithms to solve the generalized pulse design equations derived from those basic functionals. The new algorithms are proved to exhibit monotonic convergence. Numerical tests are implemented in four-level model systems employing stationary and/or nonstationary targets in the absence and/or presence of relaxation. Trajectory plots that conveniently present the global nature of the convergence behavior show that slow convergence may often be attributed to "trapping" and that relaxation processes may remove such unfavorable behavior.
Generalized monotonically convergent algorithms for solving quantum optimal control problems.
Ohtsuki, Yukiyoshi; Turinici, Gabriel; Rabitz, Herschel
2004-03-22
A wide range of cost functionals that describe the criteria for designing optimal pulses can be reduced to two basic functionals by the introduction of product spaces. We extend previous monotonically convergent algorithms to solve the generalized pulse design equations derived from those basic functionals. The new algorithms are proved to exhibit monotonic convergence. Numerical tests are implemented in four-level model systems employing stationary and/or nonstationary targets in the absence and/or presence of relaxation. Trajectory plots that conveniently present the global nature of the convergence behavior show that slow convergence may often be attributed to "trapping" and that relaxation processes may remove such unfavorable behavior. PMID:15267426
Robust message authentication code algorithm for digital audio recordings
NASA Astrophysics Data System (ADS)
Zmudzinski, Sascha; Steinebach, Martin
2007-02-01
Current systems and protocols for integrity and authenticity verification of media data do not distinguish between legitimate signal transformation and malicious tampering that manipulates the content. Furthermore, they usually provide no localization or assessment of the relevance of such manipulations with respect to human perception or semantics. We present an algorithm for a robust message authentication code (RMAC) to verify the integrity of audio recodings by means of robust audio fingerprinting and robust perceptual hashing. Experimental results show that the proposed algorithm provides both a high level of distinction between perceptually different audio data and a high robustness against signal transformations that do not change the perceived information.
AN ALGORITHM FOR PARALLEL SN SWEEPS ON UNSTRUCTURED MESHES
S. D. PAUTZ
2001-03-01
We develop a new algorithm for performing parallel S{sub n} sweeps on unstructured meshes. The algorithm uses a low-complexity list ordering heuristic to determine a sweep ordering on any partitioned mesh. For typical problems and with ''normal'' mesh partitionings we have observed nearly linear speedups on up to 126 processors. This is an important and desirable result, since although analyses of structured meshes indicate that parallel sweeps will not scale with normal partitioning approaches, we do not observe any severe asymptotic degradation in the parallel efficiency with modest ({le} 100) levels of parallelism. This work is a fundamental step in the development of parallel S{sub n} methods.
Why is Boris algorithm so good?
Qin, Hong; Zhang, Shuangxi; Xiao, Jianyuan; Liu, Jian; Sun, Yajuan; Tang, William M.
2013-08-15
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this paper, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Why is Boris Algorithm So Good?
et al, Hong Qin
2013-03-03
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this letter, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Higher-order force gradient symplectic algorithms
NASA Astrophysics Data System (ADS)
Chin, Siu A.; Kidwell, Donald W.
2000-12-01
We show that a recently discovered fourth order symplectic algorithm, which requires one evaluation of force gradient in addition to three evaluations of the force, when iterated to higher order, yielded algorithms that are far superior to similarly iterated higher order algorithms based on the standard Forest-Ruth algorithm. We gauge the accuracy of each algorithm by comparing the step-size independent error functions associated with energy conservation and the rotation of the Laplace-Runge-Lenz vector when solving a highly eccentric Kepler problem. For orders 6, 8, 10, and 12, the new algorithms are approximately a factor of 103, 104, 104, and 105 better.
Speech Enhancement based on Compressive Sensing Algorithm
NASA Astrophysics Data System (ADS)
Sulong, Amart; Gunawan, Teddy S.; Khalifa, Othman O.; Chebil, Jalel
2013-12-01
There are various methods, in performance of speech enhancement, have been proposed over the years. The accurate method for the speech enhancement design mainly focuses on quality and intelligibility. The method proposed with high performance level. A novel speech enhancement by using compressive sensing (CS) is a new paradigm of acquiring signals, fundamentally different from uniform rate digitization followed by compression, often used for transmission or storage. Using CS can reduce the number of degrees of freedom of a sparse/compressible signal by permitting only certain configurations of the large and zero/small coefficients, and structured sparsity models. Therefore, CS is significantly provides a way of reconstructing a compressed version of the speech in the original signal by taking only a small amount of linear and non-adaptive measurement. The performance of overall algorithms will be evaluated based on the speech quality by optimise using informal listening test and Perceptual Evaluation of Speech Quality (PESQ). Experimental results show that the CS algorithm perform very well in a wide range of speech test and being significantly given good performance for speech enhancement method with better noise suppression ability over conventional approaches without obvious degradation of speech quality.
Algorithm design of liquid lens inspection system
NASA Astrophysics Data System (ADS)
Hsieh, Lu-Lin; Wang, Chun-Chieh
2008-08-01
In mobile lens domain, the glass lens is often to be applied in high-resolution requirement situation; but the glass zoom lens needs to be collocated with movable machinery and voice-coil motor, which usually arises some space limits in minimum design. In high level molding component technology development, the appearance of liquid lens has become the focus of mobile phone and digital camera companies. The liquid lens sets with solid optical lens and driving circuit has replaced the original components. As a result, the volume requirement is decreased to merely 50% of the original design. Besides, with the high focus adjusting speed, low energy requirement, high durability, and low-cost manufacturing process, the liquid lens shows advantages in the competitive market. In the past, authors only need to inspect the scrape defect made by external force for the glass lens. As to the liquid lens, authors need to inspect the state of four different structural layers due to the different design and structure. In this paper, authors apply machine vision and digital image processing technology to administer inspections in the particular layer according to the needs of users. According to our experiment results, the algorithm proposed can automatically delete non-focus background, extract the region of interest, find out and analyze the defects efficiently in the particular layer. In the future, authors will combine the algorithm of the system with automatic-focus technology to implement the inside inspection based on the product inspective demands.
Implementation of FFT Algorithm using DSP TMS320F28335 for Shunt Active Power Filter
NASA Astrophysics Data System (ADS)
Patel, Pinkal Jashvantbhai; Patel, Rajesh M.; Patel, Vinod
2016-07-01
This work presents simulation, analysis and experimental verification of Fast Fourier Transform (FFT) algorithm for shunt active power filter based on three-level inverter. Different types of filters can be used for elimination of harmonics in the power system. In this work, FFT algorithm for reference current generation is discussed. FFT control algorithm is verified using PSIM simulation results with DLL block and C-code. Simulation results are compared with experimental results for FFT algorithm using DSP TMS320F28335 for shunt active power filter application.
A scalable and practical one-pass clustering algorithm for recommender system
NASA Astrophysics Data System (ADS)
Khalid, Asra; Ghazanfar, Mustansar Ali; Azam, Awais; Alahmari, Saad Ali
2015-12-01
KMeans clustering-based recommendation algorithms have been proposed claiming to increase the scalability of recommender systems. One potential drawback of these algorithms is that they perform training offline and hence cannot accommodate the incremental updates with the arrival of new data, making them unsuitable for the dynamic environments. From this line of research, a new clustering algorithm called One-Pass is proposed, which is a simple, fast, and accurate. We show empirically that the proposed algorithm outperforms K-Means in terms of recommendation and training time while maintaining a good level of accuracy.
Level Set Method for Positron Emission Tomography
Chan, Tony F.; Li, Hongwei; Lysaker, Marius; Tai, Xue-Cheng
2007-01-01
In positron emission tomography (PET), a radioactive compound is injected into the body to promote a tissue-dependent emission rate. Expectation maximization (EM) reconstruction algorithms are iterative techniques which estimate the concentration coefficients that provide the best fitted solution, for example, a maximum likelihood estimate. In this paper, we combine the EM algorithm with a level set approach. The level set method is used to capture the coarse scale information and the discontinuities of the concentration coefficients. An intrinsic advantage of the level set formulation is that anatomical information can be efficiently incorporated and used in an easy and natural way. We utilize a multiple level set formulation to represent the geometry of the objects in the scene. The proposed algorithm can be applied to any PET configuration, without major modifications. PMID:18354724
Blood or urine tests can determine the levels of various hormones in the body. This includes reproductive hormones, thyroid hormones, adrenal hormones, pituitary hormones, and many others. For more information, see: ...
A comparison of iterative algorithms and a mixed approach for in-line x-ray phase retrieval
Meng, Fanbo; Zhang, Da; Wu, Xizeng; Liu, Hong
2009-01-01
Previous studies have shown that iterative in-line x-ray phase retrieval algorithms may have higher precision than direct retrieval algorithms. This communication compares three iterative phase retrieval algorithms in terms of accuracy and efficiency using computer simulations. We found the Fourier transformation based algorithm (FT) is of the fastest convergence, while the Poisson-solver based algorithm (PS) has higher precision. The traditional Gerchberg-Saxton algorithm (GS) is very slow and sometimes does not converge in our tests. Then a mixed FT-PS algorithm is presented to achieve both high efficiency and high accuracy. The mixed algorithm is tested using simulated images with different noise level and experimentally obtained images of a piece of chicken breast muscle. PMID:20161234
A comparison of iterative algorithms and a mixed approach for in-line x-ray phase retrieval.
Meng, Fanbo; Zhang, Da; Wu, Xizeng; Liu, Hong
2009-08-15
Previous studies have shown that iterative in-line x-ray phase retrieval algorithms may have higher precision than direct retrieval algorithms. This communication compares three iterative phase retrieval algorithms in terms of accuracy and efficiency using computer simulations. We found the Fourier transformation based algorithm (FT) is of the fastest convergence, while the Poisson-solver based algorithm (PS) has higher precision. The traditional Gerchberg-Saxton algorithm (GS) is very slow and sometimes does not converge in our tests. Then a mixed FT-PS algorithm is presented to achieve both high efficiency and high accuracy. The mixed algorithm is tested using simulated images with different noise level and experimentally obtained images of a piece of chicken breast muscle.
Systolic algorithms and their implementation
Kung, H.T.
1984-01-01
Very high performance computer systems must rely heavily on parallelism since there are severe physical and technological limits on the ultimate speed of any single processor. The systolic array concept developed in the last several years allows effective use of a very large number of processors in parallel. This article illustrates the basic ideas by reviewing a systolic array design for matrix triangularization and describing its use in the on-the-fly updating of Cholesky decomposition of covariance matrices-a crucial computation in adaptive signal processing. Following this are discussions on issues related to the hardware implementation of systolic algorithms in general, and some guidelines for designing systolic algorithms that will be convenient for implementation. 33 references.
NASA Technical Reports Server (NTRS)
Loewenstein, M.; Greenblatt. B. J.; Jost, H.; Podolske, J. R.; Elkins, Jim; Hurst, Dale; Romanashkin, Pavel; Atlas, Elliott; Schauffler, Sue; Donnelly, Steve; Condon, Estelle (Technical Monitor)
2000-01-01
De-nitrification and excess re-nitrification was widely observed by ER-2 instruments in the Arctic vortex during SOLVE in winter/spring 2000. Analyses of these events requires a knowledge of the initial or pre-vortex state of the sampled air masses. The canonical relationship of NOy to the long-lived tracer N2O observed in the unperturbed stratosphere is generally used for this purpose. In this paper we will attempt to establish the current unperturbed NOy:N2O relationship (NOy* algorithm) using the ensemble of extra-vortex data from in situ instruments flying on the ER-2 and DC-8, and from the Mark IV remote measurements on the OMS balloon. Initial analysis indicates a change in the SOLVE NOy* from the values predicted by the 1994 Northern Hemisphere NOy* algorithm which was derived from the observations in the ASHOE/MAESA campaign.
A fast meteor detection algorithm
NASA Astrophysics Data System (ADS)
Gural, P.
2016-01-01
A low latency meteor detection algorithm for use with fast steering mirrors had been previously developed to track and telescopically follow meteors in real-time (Gural, 2007). It has been rewritten as a generic clustering and tracking software module for meteor detection that meets both the demanding throughput requirements of a Raspberry Pi while also maintaining a high probability of detection. The software interface is generalized to work with various forms of front-end video pre-processing approaches and provides a rich product set of parameterized line detection metrics. Discussion will include the Maximum Temporal Pixel (MTP) compression technique as a fast thresholding option for feeding the detection module, the detection algorithm trade for maximum processing throughput, details on the clustering and tracking methodology, processing products, performance metrics, and a general interface description.
Authenticated algorithms for Byzantine agreement
Dolev, D.; Strong, H.R.
1983-11-01
Reaching agreement in a distributed system in the presence of fault processors is a central issue for reliable computer systems. Using an authentication protocol, one can limit the undetected behavior of faulty processors to a simple failure to relay messages to all intended targets. In this paper the authors show that, in spite of such an ability to limit faulty behavior, and no matter what message types or protocols are allowed, reaching (Byzantine) agreement requires at least t+1 phases or rounds of information exchange, where t is an upper bound on the number of faulty processors. They present algorithms for reaching agreement based on authentication that require a total number of messages sent by correctly operating processors that is polynomial in both t and the number of processors, n. The best algorithm uses only t+1 phases and o(nt) messages. 9 references.
Molecular beacon sequence design algorithm.
Monroe, W Todd; Haselton, Frederick R
2003-01-01
A method based on Web-based tools is presented to design optimally functioning molecular beacons. Molecular beacons, fluorogenic hybridization probes, are a powerful tool for the rapid and specific detection of a particular nucleic acid sequence. However, their synthesis costs can be considerable. Since molecular beacon performance is based on its sequence, it is imperative to rationally design an optimal sequence before synthesis. The algorithm presented here uses simple Microsoft Excel formulas and macros to rank candidate sequences. This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.
Evaluating and comparing algorithms for respiratory motion prediction
NASA Astrophysics Data System (ADS)
Ernst, F.; Dürichen, R.; Schlaefer, A.; Schweikard, A.
2013-06-01
In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm—which is one of the algorithms currently used in the CyberKnife—is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient
Iterative projection algorithms in protein crystallography. II. Application.
Lo, Victor L; Kingston, Richard L; Millane, Rick P
2015-07-01
Iterative projection algorithms (IPAs) are a promising tool for protein crystallographic phase determination. Although related to traditional density-modification algorithms, IPAs have better convergence properties, and, as a result, can effectively overcome the phase problem given modest levels of structural redundancy. This is illustrated by applying IPAs to determine the electron densities of two protein crystals with fourfold non-crystallographic symmetry, starting with only the experimental diffraction amplitudes, a low-resolution molecular envelope and the position of the non-crystallographic axes. The algorithm returns electron densities that are sufficiently accurate for model building, allowing automated recovery of the known structures. This study indicates that IPAs should find routine application in protein crystallography, being capable of reconstructing electron densities starting with very little initial phase information. PMID:26131900
SeaWiFS Science Algorithm Flow Chart
NASA Technical Reports Server (NTRS)
Darzi, Michael
1998-01-01
This flow chart describes the baseline science algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Processing System (SDPS). As such, it includes only processing steps used in the generation of the operational products that are archived by NASA's Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC). It is meant to provide the reader with a basic understanding of the scientific algorithm steps applied to SeaWiFS data. It does not include non-science steps, such as format conversions, and places the greatest emphasis on the geophysical calculations of the level-2 processing. Finally, the flow chart reflects the logic sequences and the conditional tests of the software so that it may be used to evaluate the fidelity of the implementation of the scientific algorithm. In many cases however, the chart may deviate from the details of the software implementation so as to simplify the presentation.
Study of genetic direct search algorithms for function optimization
NASA Technical Reports Server (NTRS)
Zeigler, B. P.
1974-01-01
The results are presented of a study to determine the performance of genetic direct search algorithms in solving function optimization problems arising in the optimal and adaptive control areas. The findings indicate that: (1) genetic algorithms can outperform standard algorithms in multimodal and/or noisy optimization situations, but suffer from lack of gradient exploitation facilities when gradient information can be utilized to guide the search. (2) For large populations, or low dimensional function spaces, mutation is a sufficient operator. However for small populations or high dimensional functions, crossover applied in about equal frequency with mutation is an optimum combination. (3) Complexity, in terms of storage space and running time, is significantly increased when population size is increased or the inversion operator, or the second level adaptation routine is added to the basic structure.
The strobe algorithms for multi-source warehouse consistency
Zhuge, Yue; Garcia-Molina, H.; Wiener, J.L.
1996-12-31
A warehouse is a data repository containing integrated information for efficient querying and analysis. Maintaining the consistency of warehouse data is challenging, especially if the data sources are autonomous and views of the data at the warehouse span multiple sources. Transactions containing multiple updates at one or more sources, e.g., batch updates, complicate the consistency problem. In this paper we identify and discuss three fundamental transaction processing scenarios for data warehousing. We define four levels of consistency for warehouse data and present a new family of algorithms, the Strobe family, that maintain consistency as the warehouse is updated, under the various warehousing scenarios. All of the algorithms are incremental and can handle a continuous and overlapping stream of updates from the sources. Our implementation shows that the algorithms are practical and realistic choices for a wide variety of update scenarios.
Iterative projection algorithms in protein crystallography. II. Application.
Lo, Victor L; Kingston, Richard L; Millane, Rick P
2015-07-01
Iterative projection algorithms (IPAs) are a promising tool for protein crystallographic phase determination. Although related to traditional density-modification algorithms, IPAs have better convergence properties, and, as a result, can effectively overcome the phase problem given modest levels of structural redundancy. This is illustrated by applying IPAs to determine the electron densities of two protein crystals with fourfold non-crystallographic symmetry, starting with only the experimental diffraction amplitudes, a low-resolution molecular envelope and the position of the non-crystallographic axes. The algorithm returns electron densities that are sufficiently accurate for model building, allowing automated recovery of the known structures. This study indicates that IPAs should find routine application in protein crystallography, being capable of reconstructing electron densities starting with very little initial phase information.
Astronomical observation tasks short-term scheduling using PDDS algorithm
NASA Astrophysics Data System (ADS)
Kornilov, M. V.
2016-07-01
A concept of the ground-based optical astronomical observation efficiency is considered in this paper. We believe that a telescope efficiency can be increased by properly allocating observation tasks with respect to the current environment state and probability to obtain the data with required properties under the current conditions. An online observations scheduling is assumed to be an essential part for raising the efficiency. The short-term online scheduling is treated as the discrete optimisation problems which are stated using several abstraction levels. The optimisation problems are solved using the parallel depth-bounded discrepancy search (PDDS) algorithm by Moisan et al. (2014). Some aspects of the algorithm performance are discussed. The presented algorithm is a core of open-source chelyabinsk C++ library which is planned to be used at 2.5 m telescope of Sternberg Astronomical Institute of Lomonosov Moscow State University.
Virus evolutionary genetic algorithm for task collaboration of logistics distribution
NASA Astrophysics Data System (ADS)
Ning, Fanghua; Chen, Zichen; Xiong, Li
2005-12-01
In order to achieve JIT (Just-In-Time) level and clients' maximum satisfaction in logistics collaboration, a Virus Evolutionary Genetic Algorithm (VEGA) was put forward under double constraints of logistics resource and operation sequence. Based on mathematic description of a multiple objective function, the algorithm was designed to schedule logistics tasks with different due dates and allocate them to network members. By introducing a penalty item, make span and customers' satisfaction were expressed in fitness function. And a dynamic adaptive probability of infection was used to improve performance of local search. Compared to standard Genetic Algorithm (GA), experimental result illustrates the performance superiority of VEGA. So the VEGA can provide a powerful decision-making technique for optimizing resource configuration in logistics network.
Fourier and Walsh digital filtering algorithms for distance protection
Altuve F., H.J.; Diaz V., I.; Vazquez M., E.
1996-02-01
Filtering requirements for distance relays are very critical, because they must estimate precisely and quickly the electrical distance to the fault, even with highly distorted input signals. A number of digital filtering algorithms for distance relays have been proposed and some of them are in use in practical relays; however, power system evolution increases the corruption level of signals and imposes the necessity of continuing the research efforts in this area. In the present paper a comparative evaluation of different digital filtering algorithms for distance protection is performed. An evaluation method is proposed, which gives a comprehensive information about filter transient behavior on a wide frequency range of noise. The discussion is focused in well-known algorithms based on Fourier and Walsh transforms, and includes a recently proposed combined sine-cosine filter.
Fourier and Walsh digital filtering algorithms for distance protection
Altuve F., H.J.; Diaz V., I.; Vazquez M., E.
1995-12-31
Filtering requirements for distance relays are very critical, because they must estimate precisely and quickly the electrical distance to the fault, even with highly distorted input signals. A number of digital filtering algorithms for distance relays have been proposed and some of them are in use in practical relays; however, power system evolution increases the corruption level of signals and imposes the necessity of continuing the research efforts in this area. In the present paper a comparative evaluation of different digital filtering algorithms for distance protection is performed. An evaluation method is proposed, which gives a comprehensive information about filter transient behavior on a wide frequency range of noise. The discussion is focused in well-known algorithms based on Fourier and Walsh transforms, and includes a recently proposed combined sine-cosine filter.
Parallel grid generation algorithm for distributed memory computers
NASA Technical Reports Server (NTRS)
Moitra, Stuti; Moitra, Anutosh
1994-01-01
A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.
Control algorithm implementation for a redundant degree of freedom manipulator
NASA Technical Reports Server (NTRS)
Cohan, Steve
1991-01-01
This project's purpose is to develop and implement control algorithms for a kinematically redundant robotic manipulator. The manipulator is being developed concurrently by Odetics Inc., under internal research and development funding. This SBIR contract supports algorithm conception, development, and simulation, as well as software implementation and integration with the manipulator hardware. The Odetics Dexterous Manipulator is a lightweight, high strength, modular manipulator being developed for space and commercial applications. It has seven fully active degrees of freedom, is electrically powered, and is fully operational in 1 G. The manipulator consists of five self-contained modules. These modules join via simple quick-disconnect couplings and self-mating connectors which allow rapid assembly/disassembly for reconfiguration, transport, or servicing. Each joint incorporates a unique drive train design which provides zero backlash operation, is insensitive to wear, and is single fault tolerant to motor or servo amplifier failure. The sensing system is also designed to be single fault tolerant. Although the initial prototype is not space qualified, the design is well-suited to meeting space qualification requirements. The control algorithm design approach is to develop a hierarchical system with well defined access and interfaces at each level. The high level endpoint/configuration control algorithm transforms manipulator endpoint position/orientation commands to joint angle commands, providing task space motion. At the same time, the kinematic redundancy is resolved by controlling the configuration (pose) of the manipulator, using several different optimizing criteria. The center level of the hierarchy servos the joints to their commanded trajectories using both linear feedback and model-based nonlinear control techniques. The lowest control level uses sensed joint torque to close torque servo loops, with the goal of improving the manipulator dynamic behavior
Vecharynski, Eugene; Yang, Chao; Pask, John E.
2015-06-01
We present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimal block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer.
IMAGE ANALYSIS ALGORITHMS FOR DUAL MODE IMAGING SYSTEMS
Robinson, Sean M.; Jarman, Kenneth D.; Miller, Erin A.; Misner, Alex C.; Myjak, Mitchell J.; Pitts, W. Karl; Seifert, Allen; Seifert, Carolyn E.; Woodring, Mitchell L.
2010-06-11
The level of detail discernable in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes where information barriers are mandatory. However, if a balance can be struck between sufficient information barriers and feature extraction to verify or identify objects of interest, imaging may significantly advance verification efforts. This paper describes the development of combined active (conventional) radiography and passive (auto) radiography techniques for imaging sensitive items assuming that comparison images cannot be furnished. Three image analysis algorithms are presented, each of which reduces full image information to non-sensitive feature information and ultimately is intended to provide only a yes/no response verifying features present in the image. These algorithms are evaluated on both their technical performance in image analysis and their application with or without an explicitly constructed information barrier. The first algorithm reduces images to non-invertible pixel intensity histograms, retaining only summary information about the image that can be used in template comparisons. This one-way transform is sufficient to discriminate between different image structures (in terms of area and density) without revealing unnecessary specificity. The second algorithm estimates the attenuation cross-section of objects of known shape based on transition characteristics around the edge of the object’s image. The third algorithm compares the radiography image with the passive image to discriminate dense, radioactive material from point sources or inactive dense material. By comparing two images and reporting only a single statistic from the combination thereof, this algorithm can operate entirely behind an information barrier stage. Together with knowledge of the radiography system, the use of these algorithms in combination can be used to improve verification capability to inspection regimes and improve
Observations on student misconceptions—A case study of the Build Heap Algorithm
NASA Astrophysics Data System (ADS)
Seppälä, Otto; Malmi, Lauri; Korhonen, Ari
2006-09-01
Data structures and algorithms are core issues in computer programming. However, learning them is challenging for most students and many of them have various types of misconceptions on how algorithms work. In this study, we discuss the problem of identifying misconceptions on the principles of how algorithms work. Our context is algorithm simulation exercises, where students simulate the steps of a given algorithm by manipulating data structure visualizations on a computer screen by using a mouse. Thus, contrasting to “typical” data structures and algorithms courses, these exercises are designed to work on an abstraction level higher than that of the actual implementation.We have analyzed the recorded simulation sequences to infer existing misconceptions from students' answers, and then implemented the corresponding variations of the target algorithm to find out how many of students' answers consistently follow each variation. The results suggest that many students are aware of the ultimate goal of the algorithm but have not studied the algorithm itself well enough. This often leads to different misconceptions that can be modeled and recognized using our approach. The results presented here concern the Build Heap algorithm, but the approach is of general value.
Systolic systems: algorithms and complexity
Chang, J.H.
1986-01-01
This thesis has two main contributions. The first is the design of efficient systolic algorithms for solving recurrence equations, dynamic programming problems, scheduling problems, as well as new systolic implementation of data structures such as stacks, queues, priority queues, and dictionary machines. The second major contribution is the investigation of the computational power of systolic arrays in comparison to sequential models and other models of parallel computation.
Relative-Error-Covariance Algorithms
NASA Technical Reports Server (NTRS)
Bierman, Gerald J.; Wolff, Peter J.
1991-01-01
Two algorithms compute error covariance of difference between optimal estimates, based on data acquired during overlapping or disjoint intervals, of state of discrete linear system. Provides quantitative measure of mutual consistency or inconsistency of estimates of states. Relative-error-covariance concept applied, to determine degree of correlation between trajectories calculated from two overlapping sets of measurements and construct real-time test of consistency of state estimates based upon recently acquired data.
Summing It All Up: Pre-1900 Algorithms.
ERIC Educational Resources Information Center
Pearson, Eleanor S.
1986-01-01
Computational algorithms from American textbooks copyrighted prior to 1900 are presented--some that convey the concept, some just for special cases, and some just for fun. Algorithms for each operation with whole numbers are presented and analyzed. (MNS)
Spaceborne SAR Imaging Algorithm for Coherence Optimized.
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446
Algorithmic complexity and entanglement of quantum states.
Mora, Caterina E; Briegel, Hans J
2005-11-11
We define the algorithmic complexity of a quantum state relative to a given precision parameter, and give upper bounds for various examples of states. We also establish a connection between the entanglement of a quantum state and its algorithmic complexity.
An algorithm for generating abstract syntax trees
NASA Technical Reports Server (NTRS)
Noonan, R. E.
1985-01-01
The notion of an abstract syntax is discussed. An algorithm is presented for automatically deriving an abstract syntax directly from a BNF grammar. The implementation of this algorithm and its application to the grammar for Modula are discussed.
Spaceborne SAR Imaging Algorithm for Coherence Optimized.
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.
Spaceborne SAR Imaging Algorithm for Coherence Optimized
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446
Teaching Multiplication Algorithms from Other Cultures
ERIC Educational Resources Information Center
Lin, Cheng-Yao
2007-01-01
This article describes a number of multiplication algorithms from different cultures around the world: Hindu, Egyptian, Russian, Japanese, and Chinese. Students can learn these algorithms and better understand the operation and properties of multiplication.
Concurrent algorithms for transient FE analysis
NASA Technical Reports Server (NTRS)
Ortiz, M.; Nour-Omid, B.
1989-01-01
Information on concurrent algorithms for transient finite element analysis is given in viewgraph form. Information is given on concurrent dynamic algorithms, interprocessor communication, the performance of the BAR problem on the 32 Processor Hypercube, computational efficiency and accuracy analysis.
Comparative study of heart sound localization algorithms
NASA Astrophysics Data System (ADS)
Moukadem, A.; Dieterlen, A.; Hueber, N.; Brandt, C.; Raymond, P.
2011-05-01
The purpose of this document is to present a comparative study of five algorithms of heart sound localization, one of which, is a method based on radial basis function networks applied in a novel approach. The advantages and disadvantages of each method are evaluated according to a data base of 50 subjects in which there are 25 healthy subjects selected from the University Hospital of Strasbourg (HUS) and from theMARS500 project (Moscow) and 25 subjects with cardiac pathologies selected from the HUS. This study is made under the control of an experienced cardiologist. The performance of each method is evaluated by calculating the area under a receiver operating curve (AUC) and the robustness is shown against different levels of additive white Gaussian noise.
Algorithmic Strategies in Combinatorial Chemistry
GOLDMAN,DEBORAH; ISTRAIL,SORIN; LANCIA,GIUSEPPE; PICCOLBONI,ANTONIO; WALENZ,BRIAN
2000-08-01
Combinatorial Chemistry is a powerful new technology in drug design and molecular recognition. It is a wet-laboratory methodology aimed at ``massively parallel'' screening of chemical compounds for the discovery of compounds that have a certain biological activity. The power of the method comes from the interaction between experimental design and computational modeling. Principles of ``rational'' drug design are used in the construction of combinatorial libraries to speed up the discovery of lead compounds with the desired biological activity. This paper presents algorithms, software development and computational complexity analysis for problems arising in the design of combinatorial libraries for drug discovery. The authors provide exact polynomial time algorithms and intractability results for several Inverse Problems-formulated as (chemical) graph reconstruction problems-related to the design of combinatorial libraries. These are the first rigorous algorithmic results in the literature. The authors also present results provided by the combinatorial chemistry software package OCOTILLO for combinatorial peptide design using real data libraries. The package provides exact solutions for general inverse problems based on shortest-path topological indices. The results are superior both in accuracy and computing time to the best software reports published in the literature. For 5-peptoid design, the computation is rigorously reduced to an exhaustive search of about 2% of the search space; the exact solutions are found in a few minutes.
On the Multilevel Solution Algorithm for Markov Chains
NASA Technical Reports Server (NTRS)
Horton, Graham
1997-01-01
We discuss the recently introduced multilevel algorithm for the steady-state solution of Markov chains. The method is based on an aggregation principle which is well established in the literature and features a multiplicative coarse-level correction. Recursive application of the aggregation principle, which uses an operator-dependent coarsening, yields a multi-level method which has been shown experimentally to give results significantly faster than the typical methods currently in use. When cast as a multigrid-like method, the algorithm is seen to be a Galerkin-Full Approximation Scheme with a solution-dependent prolongation operator. Special properties of this prolongation lead to the cancellation of the computationally intensive terms of the coarse-level equations.
SCORPIUS algorithm benchmarks on the image understanding architecture machine
NASA Astrophysics Data System (ADS)
Bogdanowicz, Julius F.; Nash, J. Gregory; Shu, David B.
1992-04-01
Many Hughes tactical and strategic programs need high performance image processing. For example, photo-interpretation applications can require up to four orders of magnitude speedup over conventional computer architectures. Therefore, parallel processing systems are needed to help close the processing gap. Vision applications can usually be decomposed into three levels of processing called high, intermediate, and low level vision. Each processing level typically requires different types of numeric/symbolic computation, processing task granularities, and communications bandwidths. No parallel processing system is commercially available that is optimized for the entire range of computations. To meet these processing challenges, the image understanding architecture (IUA) has been developed by Hughes in collaboration with the University of Massachusetts. The IUA is a heterogeneous, hierarchical, associative parallel processor that is organized in three levels corresponding to the vision problem. Its lowest level consists of a large content addressable array parallel processor. This array of 'per pixel' bit serial processors is used for fixed point, low level numeric, and symbolic computations. The middle level is an interface communications array processor (ICAP). ICAP is an array of digital signal processing chips from TI TMS320Cx line, used for high speed number crunching. The highest level is the symbolic processing array. It is an array of general purpose microprocessors in which the artificial intelligence content of the image understanding software resides. A set of benchmarks from the DARPA/ORD sponsored SCORPIUS program were developed using the IUA. The set of algorithms included low level image processing as well as high level matching algorithms. Benchmark performance on the second generation IUA hardware is over four orders of magnitude faster than equivalent algorithms implemented on a DEC VAX 8650. The first generation hardware is operational. Development
Algorithms and Requirements for Measuring Network Bandwidth
Jin, Guojun
2002-12-08
This report unveils new algorithms for actively measuring (not estimating) available bandwidths with very low intrusion, computing cross traffic, thus estimating the physical bandwidth, provides mathematical proof that the algorithms are accurate, and addresses conditions, requirements, and limitations for new and existing algorithms for measuring network bandwidths. The paper also discusses a number of important terminologies and issues for network bandwidth measurement, and introduces a fundamental parameter -Maximum Burst Size that is critical for implementing algorithms based on multiple packets.
The performance of asynchronous algorithms on hypercubes
Womble, D.E.
1988-12-01
Many asynchronous algorithms have been developed for parallel computers. Most implementations of asynchronous algorithms, however, have been for shared memory machines. In this paper, we study the implementation and performance of some common asynchronous algorithms on the NCUBE/ten, a 1024 node hypercube. In addition, we summarize existing theoretical work and discuss some classes of algorithms that can be made asynchronous and some that cannot. 16 refs., 3 figs.
TVFMCATS. Time Variant Floating Mean Counting Algorithm
Huffman, R.K.
1999-05-01
This software was written to test a time variant floating mean counting algorithm. The algorithm was developed by Westinghouse Savannah River Company and a provisional patent has been filed on the algorithm. The test software was developed to work with the Val Tech model IVB prototype version II count rate meter hardware. The test software was used to verify the algorithm developed by WSRC could be correctly implemented with the vendor`s hardware.
Time Variant Floating Mean Counting Algorithm
Huffman, Russell Kevin
1999-06-03
This software was written to test a time variant floating mean counting algorithm. The algorithm was developed by Westinghouse Savannah River Company and a provisional patent has been filed on the algorithm. The test software was developed to work with the Val Tech model IVB prototype version II count rate meter hardware. The test software was used to verify the algorithm developed by WSRC could be correctly implemented with the vendor''s hardware.
Algorithmic approach to intelligent robot mobility
Kauffman, S.
1983-05-01
This paper presents Sutherland's algorithm, plus an alternative algorithm, which allows mobile robots to move about intelligently in environments resembling the rooms and hallways in which we move around. The main hardware requirements for a robot to use the algorithms presented are mobility and an ability to sense distances with some type of non-contact scanning device. This article does not discuss the actual robot construction. The emphasis is on heuristics and algorithms. 1 reference.
An algorithm for segmenting range imagery
Roberts, R.S.
1997-03-01
This report describes the technical accomplishments of the FY96 Cross Cutting and Advanced Technology (CC&AT) project at Los Alamos National Laboratory. The project focused on developing algorithms for segmenting range images. The image segmentation algorithm developed during the project is described here. In addition to segmenting range images, the algorithm can fuse multiple range images thereby providing true 3D scene models. The algorithm has been incorporated into the Rapid World Modelling System at Sandia National Laboratory.
An artificial intelligent algorithm for tumor detection in screening mammogram.
Zheng, L; Chan, A K
2001-07-01
Cancerous tumor mass is one of the major types of breast cancer. When cancerous masses are embedded in and camouflaged by varying densities of parenchymal tissue structures, they are very difficult to be visually detected on mammograms. This paper presents an algorithm that combines several artificial intelligent techniques with the discrete wavelet transform (DWT) for detection of masses in mammograms. The AI techniques include fractal dimension analysis, multiresolution markov random field, dogs-and-rabbits algorithm, and others. The fractal dimension analysis serves as a preprocessor to determine the approximate locations of the regions suspicious for cancer in the mammogram. The dogs-and-rabbits clustering algorithm is used to initiate the segmentation at the LL subband of a three-level DWT decomposition of the mammogram. A tree-type classification strategy is applied at the end to determine whether a given region is suspicious for cancer. We have verified the algorithm with 322 mammograms in the Mammographic Image Analysis Society Database. The verification results show that the proposed algorithm has a sensitivity of 97.3% and the number of false positive per image is 3.92.
Improved algorithm for solving nonlinear parabolized stability equations
NASA Astrophysics Data System (ADS)
Zhao, Lei; Zhang, Cun-bo; Liu, Jian-xin; Luo, Ji-sheng
2016-08-01
Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. Project supported by the National Natural Science Foundation of China (Grant Nos. 11332007 and 11402167).
FPGA implementation of sparse matrix algorithm for information retrieval
NASA Astrophysics Data System (ADS)
Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio
2005-06-01
Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.
Mesh Algorithms for PDE with Sieve I: Mesh Distribution
Knepley, Matthew G.; Karpeev, Dmitry A.
2009-01-01
We have developed a new programming framework, called Sieve, to support parallel numerical partial differential equation(s) (PDE) algorithms operating over distributed meshes. We have also developed a reference implementation of Sieve in C++ as a library of generic algorithms operating on distributed containers conforming to the Sieve interface. Sieve makes instances of the incidence relation, or arrows, the conceptual first-class objects represented in the containers. Further, generic algorithms acting on this arrow container are systematically used to provide natural geometric operations on the topology and also, through duality, on the data. Finally, coverings and duality are used to encode notmore » only individual meshes, but all types of hierarchies underlying PDE data structures, including multigrid and mesh partitions. In order to demonstrate the usefulness of the framework, we show how the mesh partition data can be represented and manipulated using the same fundamental mechanisms used to represent meshes. We present the complete description of an algorithm to encode a mesh partition and then distribute a mesh, which is independent of the mesh dimension, element shape, or embedding. Moreover, data associated with the mesh can be similarly distributed with exactly the same algorithm. The use of a high level of abstraction within the Sieve leads to several benefits in terms of code reuse, simplicity, and extensibility. We discuss these benefits and compare our approach to other existing mesh libraries.« less
Improved algorithm for solving nonlinear parabolized stability equations
NASA Astrophysics Data System (ADS)
Zhao, Lei; Zhang, Cun-bo; Liu, Jian-xin; Luo, Ji-sheng
2016-08-01
Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. Project supported by the National Natural Science Foundation of China (Grant Nos. 11332007 and 11402167).
Effective FCM noise clustering algorithms in medical images.
Kannan, S R; Devi, R; Ramathilagam, S; Takezawa, K
2013-02-01
The main motivation of this paper is to introduce a class of robust non-Euclidean distance measures for the original data space to derive new objective function and thus clustering the non-Euclidean structures in data to enhance the robustness of the original clustering algorithms to reduce noise and outliers. The new objective functions of proposed algorithms are realized by incorporating the noise clustering concept into the entropy based fuzzy C-means algorithm with suitable noise distance which is employed to take the information about noisy data in the clustering process. This paper presents initial cluster prototypes using prototype initialization method, so that this work tries to obtain the final result with less number of iterations. To evaluate the performance of the proposed methods in reducing the noise level, experimental work has been carried out with a synthetic image which is corrupted by Gaussian noise. The superiority of the proposed methods has been examined through the experimental study on medical images. The experimental results show that the proposed algorithms perform significantly better than the standard existing algorithms. The accurate classification percentage of the proposed fuzzy C-means segmentation method is obtained using silhouette validity index.
Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci
NASA Astrophysics Data System (ADS)
Kosmale, Miriam; Popp, Thomas
2016-04-01
Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.
Algorithmic Processes for Increasing Design Efficiency.
ERIC Educational Resources Information Center
Terrell, William R.
1983-01-01
Discusses the role of algorithmic processes as a supplementary method for producing cost-effective and efficient instructional materials. Examines three approaches to problem solving in the context of developing training materials for the Naval Training Command: application of algorithms, quasi-algorithms, and heuristics. (EAO)
Learning Intelligent Genetic Algorithms Using Japanese Nonograms
ERIC Educational Resources Information Center
Tsai, Jinn-Tsong; Chou, Ping-Yi; Fang, Jia-Cen
2012-01-01
An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and…
Improvements of HITS Algorithms for Spam Links
NASA Astrophysics Data System (ADS)
Asano, Yasuhito; Tezuka, Yu; Nishizeki, Takao
The HITS algorithm proposed by Kleinberg is one of the representative methods of scoring Web pages by using hyperlinks. In the days when the algorithm was proposed, most of the pages given high score by the algorithm were really related to a given topic, and hence the algorithm could be used to find related pages. However, the algorithm and the variants including Bharat's improved HITS, abbreviated to BHITS, proposed by Bharat and Henzinger cannot be used to find related pages any more on today's Web, due to an increase of spam links. In this paper, we first propose three methods to find “linkfarms,” that is, sets of spam links forming a densely connected subgraph of a Web graph. We then present an algorithm, called a trust-score algorithm, to give high scores to pages which are not spam pages with a high probability. Combining the three methods and the trust-score algorithm with BHITS, we obtain several variants of the HITS algorithm. We ascertain by experiments that one of them, named TaN+BHITS using the trust-score algorithm and the method of finding linkfarms by employing name servers, is most suitable for finding related pages on today's Web. Our algorithms take time and memory no more than those required by the original HITS algorithm, and can be executed on a PC with a small amount of main memory.
A Robustly Stabilizing Model Predictive Control Algorithm
NASA Technical Reports Server (NTRS)
Ackmece, A. Behcet; Carson, John M., III
2007-01-01
A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.
An adaptive algorithm for noise rejection.
Lovelace, D E; Knoebel, S B
1978-01-01
An adaptive algorithm for the rejection of noise artifact in 24-hour ambulatory electrocardiographic recordings is described. The algorithm is based on increased amplitude distortion or increased frequency of fluctuations associated with an episode of noise artifact. The results of application of the noise rejection algorithm on a high noise population of test tapes are discussed.
New Results in Astrodynamics Using Genetic Algorithms
NASA Technical Reports Server (NTRS)
Coverstone-Carroll, V.; Hartmann, J. W.; Williams, S. N.; Mason, W. J.
1998-01-01
Generic algorithms have gained popularity as an effective procedure for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a brief survey of the use of genetic algorithms to solve astrodynamics problems is presented and is followed by new results obtained from applying a Pareto genetic algorithm to the optimization of low-thrust interplanetary spacecraft missions.
Verification of IEEE Compliant Subtractive Division Algorithms
NASA Technical Reports Server (NTRS)
Miner, Paul S.; Leathrum, James F., Jr.
1996-01-01
A parameterized definition of subtractive floating point division algorithms is presented and verified using PVS. The general algorithm is proven to satisfy a formal definition of an IEEE standard for floating point arithmetic. The utility of the general specification is illustrated using a number of different instances of the general algorithm.
Optimisation of nonlinear motion cueing algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Asadi, Houshyar; Mohamed, Shady; Rahim Zadeh, Delpak; Nahavandi, Saeid
2015-04-01
Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching
ERIC Educational Resources Information Center
Bautista, Nazan
2014-01-01
A national survey reports that 42% of mainstream teachers have English language learners (ELLs) in their classrooms, but only 12.5% say they have been prepared to work with them (National Center for Education Statistics 2002). This article supplies a framework to address the cognitive demands of ELLs with varying proficiency levels, guided by the…
Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo
2016-01-01
Purpose To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Methods Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Results Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Conclusions Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features. PMID:27741289
An Algorithm for the Mixed Transportation Network Design Problem.
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
Optimization of reliability allocation strategies through use of genetic algorithms
Campbell, J.E.; Painton, L.A.
1996-08-01
This paper examines a novel optimization technique called genetic algorithms and its application to the optimization of reliability allocation strategies. Reliability allocation should occur in the initial stages of design, when the objective is to determine an optimal breakdown or allocation of reliability to certain components or subassemblies in order to meet system specifications. The reliability allocation optimization is applied to the design of a cluster tool, a highly complex piece of equipment used in semiconductor manufacturing. The problem formulation is presented, including decision variables, performance measures and constraints, and genetic algorithm parameters. Piecewise ``effort curves`` specifying the amount of effort required to achieve a certain level of reliability for each component of subassembly are defined. The genetic algorithm evolves or picks those combinations of ``effort`` or reliability levels for each component which optimize the objective of maximizing Mean Time Between Failures while staying within a budget. The results show that the genetic algorithm is very efficient at finding a set of robust solutions. A time history of the optimization is presented, along with histograms or the solution space fitness, MTBF, and cost for comparative purposes.
An Algorithm for the Mixed Transportation Network Design Problem
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately. PMID:27626803
An Algorithm for the Mixed Transportation Network Design Problem.
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately. PMID:27626803
Parallelized dilate algorithm for remote sensing image.
Zhang, Suli; Hu, Haoran; Pan, Xin
2014-01-01
As an important algorithm, dilate algorithm can give us more connective view of a remote sensing image which has broken lines or objects. However, with the technological progress of satellite sensor, the resolution of remote sensing image has been increasing and its data quantities become very large. This would lead to the decrease of algorithm running speed or cannot obtain a result in limited memory or time. To solve this problem, our research proposed a parallelized dilate algorithm for remote sensing Image based on MPI and MP. Experiments show that our method runs faster than traditional single-process algorithm.
Alternative learning algorithms for feedforward neural networks
Vitela, J.E.
1996-03-01
The efficiency of the back propagation algorithm to train feed forward multilayer neural networks has originated the erroneous belief among many neural networks users, that this is the only possible way to obtain the gradient of the error in this type of networks. The purpose of this paper is to show how alternative algorithms can be obtained within the framework of ordered partial derivatives. Two alternative forward-propagating algorithms are derived in this work which are mathematically equivalent to the BP algorithm. This systematic way of obtaining learning algorithms illustrated with this particular type of neural networks can also be used with other types such as recurrent neural networks.
Problem solving with genetic algorithms and Splicer
NASA Technical Reports Server (NTRS)
Bayer, Steven E.; Wang, Lui
1991-01-01
Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.
Is there a best hyperspectral detection algorithm?
NASA Astrophysics Data System (ADS)
Manolakis, D.; Lockwood, R.; Cooley, T.; Jacobson, J.
2009-05-01
A large number of hyperspectral detection algorithms have been developed and used over the last two decades. Some algorithms are based on highly sophisticated mathematical models and methods; others are derived using intuition and simple geometrical concepts. The purpose of this paper is threefold. First, we discuss the key issues involved in the design and evaluation of detection algorithms for hyperspectral imaging data. Second, we present a critical review of existing detection algorithms for practical hyperspectral imaging applications. Finally, we argue that the "apparent" superiority of sophisticated algorithms with simulated data or in laboratory conditions, does not necessarily translate to superiority in real-world applications.
Dynamic programming and graph algorithms in computer vision.
Felzenszwalb, Pedro F; Zabih, Ramin
2011-04-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.
Modeling and Algorithmic Approaches to Constitutively-Complex, Microstructured Fluids
Miller, Gregory H.; Forest, Gregory
2014-05-01
We present a new multiscale model for complex fluids based on three scales: microscopic, kinetic, and continuum. We choose the microscopic level as Kramers' bead-rod model for polymers, which we describe as a system of stochastic differential equations with an implicit constraint formulation. The associated Fokker-Planck equation is then derived, and adiabatic elimination removes the fast momentum coordinates. Approached in this way, the kinetic level reduces to a dispersive drift equation. The continuum level is modeled with a finite volume Godunov-projection algorithm. We demonstrate computation of viscoelastic stress divergence using this multiscale approach.
Color sorting algorithm based on K-means clustering algorithm
NASA Astrophysics Data System (ADS)
Zhang, BaoFeng; Huang, Qian
2009-11-01
In the process of raisin production, there were a variety of color impurities, which needs be removed effectively. A new kind of efficient raisin color-sorting algorithm was presented here. First, the technology of image processing basing on the threshold was applied for the image pre-processing, and then the gray-scale distribution characteristic of the raisin image was found. In order to get the chromatic aberration image and reduce some disturbance, we made the flame image subtraction that the target image data minus the background image data. Second, Haar wavelet filter was used to get the smooth image of raisins. According to the different colors and mildew, spots and other external features, the calculation was made to identify the characteristics of their images, to enable them to fully reflect the quality differences between the raisins of different types. After the processing above, the image were analyzed by K-means clustering analysis method, which can achieve the adaptive extraction of the statistic features, in accordance with which, the image data were divided into different categories, thereby the categories of abnormal colors were distinct. By the use of this algorithm, the raisins of abnormal colors and ones with mottles were eliminated. The sorting rate was up to 98.6%, and the ratio of normal raisins to sorted grains was less than one eighth.
Empirical study of parallel LRU simulation algorithms
NASA Technical Reports Server (NTRS)
Carr, Eric; Nicol, David M.
1994-01-01
This paper reports on the performance of five parallel algorithms for simulating a fully associative cache operating under the LRU (Least-Recently-Used) replacement policy. Three of the algorithms are SIMD, and are implemented on the MasPar MP-2 architecture. Two other algorithms are parallelizations of an efficient serial algorithm on the Intel Paragon. One SIMD algorithm is quite simple, but its cost is linear in the cache size. The two other SIMD algorithm are more complex, but have costs that are independent on the cache size. Both the second and third SIMD algorithms compute all stack distances; the second SIMD algorithm is completely general, whereas the third SIMD algorithm presumes and takes advantage of bounds on the range of reference tags. Both MIMD algorithm implemented on the Paragon are general and compute all stack distances; they differ in one step that may affect their respective scalability. We assess the strengths and weaknesses of these algorithms as a function of problem size and characteristics, and compare their performance on traces derived from execution of three SPEC benchmark programs.
New algorithms for binary wavefront optimization
NASA Astrophysics Data System (ADS)
Zhang, Xiaolong; Kner, Peter
2015-03-01
Binary amplitude modulation promises to allow rapid focusing through strongly scattering media with a large number of segments due to the faster update rates of digital micromirror devices (DMDs) compared to spatial light modulators (SLMs). While binary amplitude modulation has a lower theoretical enhancement than phase modulation, the faster update rate should more than compensate for the difference - a factor of π2 /2. Here we present two new algorithms, a genetic algorithm and a transmission matrix algorithm, for optimizing the focus with binary amplitude modulation that achieve enhancements close to the theoretical maximum. Genetic algorithms have been shown to work well in noisy environments and we show that the genetic algorithm performs better than a stepwise algorithm. Transmission matrix algorithms allow complete characterization and control of the medium but require phase control either at the input or output. Here we introduce a transmission matrix algorithm that works with only binary amplitude control and intensity measurements. We apply these algorithms to binary amplitude modulation using a Texas Instruments Digital Micromirror Device. Here we report an enhancement of 152 with 1536 segments (9.90%×N) using a genetic algorithm with binary amplitude modulation and an enhancement of 136 with 1536 segments (8.9%×N) using an intensity-only transmission matrix algorithm.
Hierarchical artificial bee colony algorithm for RFID network planning optimization.
Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong
2014-01-01
This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200
An Autonomous Onboard Targeting Algorithm Using Finite Thrust Maneuvers
NASA Technical Reports Server (NTRS)
Scarritt, Sara K.; Marchand, Belinda G.; Weeks, Michael W.
2009-01-01
In earlier investigations, the adaptation and implementation of a modified two-level corrections process as the onboard targeting algorithm for the Trans-Earth Injection phase of Orion is presented. The objective of that targeting algorithm is to generate the times of ignition and magnitudes of the required maneuvers such that the desired state at entry interface is achieved. In an actual onboard flight software implementation, these times of ignition and maneuvers are relayed onto Flight Control for command and execution. Although this process works well when the burn durations or burn arcs are small, this might not be the case during a contingency situation when lower thrust engines are employed to perform the maneuvers. Therefore, a new version of the modified two-level corrections process is formulated to handle the case of finite burn arcs. This paper presents the development and formulation of that finite burn modified two-level corrections process which can again be used as an onboard targeting algorithm for the Trans-Earth Injection phase of Orion. Additionally, performance results and a comparison between the two methods are presented. The finite burn two-level corrector formulation presented here ensures the entry constraints at entry interface are still met without violating the available fuel budget, while still accounting for much longer burn times in its design.
Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization
Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong
2014-01-01
This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200
Hierarchical artificial bee colony algorithm for RFID network planning optimization.
Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong
2014-01-01
This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.
Algorithms versus architectures for computational chemistry
NASA Technical Reports Server (NTRS)
Partridge, H.; Bauschlicher, C. W., Jr.
1986-01-01
The algorithms employed are computationally intensive and, as a result, increased performance (both algorithmic and architectural) is required to improve accuracy and to treat larger molecular systems. Several benchmark quantum chemistry codes are examined on a variety of architectures. While these codes are only a small portion of a typical quantum chemistry library, they illustrate many of the computationally intensive kernels and data manipulation requirements of some applications. Furthermore, understanding the performance of the existing algorithm on present and proposed supercomputers serves as a guide for future programs and algorithm development. The algorithms investigated are: (1) a sparse symmetric matrix vector product; (2) a four index integral transformation; and (3) the calculation of diatomic two electron Slater integrals. The vectorization strategies are examined for these algorithms for both the Cyber 205 and Cray XMP. In addition, multiprocessor implementations of the algorithms are looked at on the Cray XMP and on the MIT static data flow machine proposed by DENNIS.
A compilation of jet finding algorithms
Flaugher, B.; Meier, K.
1992-12-31
Technical descriptions of jet finding algorithms currently in use in p{anti p} collider experiments (CDF, UA1, UA2), e{sup +}e{sup {minus}} experiments and Monte-Carlo event generators (LUND programs, ISAJET) have been collected. For the hadron collider experiments, the clustering methods fall into two categories: cone algorithms and nearest-neighbor algorithms. In addition, UA2 has employed a combination of both methods for some analysis. While there are clearly differences between the cone and nearest-neighbor algorithms, the authors have found that there are also differences among the cone algorithms in the details of how the centroid of a cone cluster is located and how the E{sub T} and P{sub T} of the jet are defined. The most commonly used jet algorithm in electron-positron experiments is the JADE-type cluster algorithm. Five various incarnations of this approach have been described.
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.
ALFA: Automated Line Fitting Algorithm
NASA Astrophysics Data System (ADS)
Wesson, R.
2015-12-01
ALFA fits emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. It uses a catalog of lines which may be present to construct synthetic spectra, the parameters of which are then optimized by means of a genetic algorithm. Uncertainties are estimated using the noise structure of the residuals. An emission line spectrum containing several hundred lines can be fitted in a few seconds using a single processor of a typical contemporary desktop or laptop PC. Data cubes in FITS format can be analysed using multiple processors, and an analysis of tens of thousands of deep spectra obtained with instruments such as MUSE will take a few hours.
Algorithms for skiascopy measurement automatization
NASA Astrophysics Data System (ADS)
Fomins, Sergejs; Trukša, Renārs; KrūmiĆa, Gunta
2014-10-01
Automatic dynamic infrared retinoscope was developed, which allows to run procedure at a much higher rate. Our system uses a USB image sensor with up to 180 Hz refresh rate equipped with a long focus objective and 850 nm infrared light emitting diode as light source. Two servo motors driven by microprocessor control the rotation of semitransparent mirror and motion of retinoscope chassis. Image of eye pupil reflex is captured via software and analyzed along the horizontal plane. Algorithm for automatic accommodative state analysis is developed based on the intensity changes of the fundus reflex.