Study on transport properties of silicene monolayer under external field using NEGF method
Syaputra, Marhamni Wella, Sasfan Arman; Wungu, Triati Dewi Kencana; Purqon, Acep; Suprijadi
2015-09-30
We investigate the current-voltage (I-V) characteristics of a pristine monolayer silicene using non-equilibrium Green function (NEGF) method combining with density functional theory (DFT). This method succeeded in showing the relationship of I and V on silicene corresponding to the electronic characteristics such as density of states. The external field perpendicular to the silicene monolayer affects in increasing of the current. Under 0.2 eV external field, the current reaches the maximum peak at Vb = 0.3 eV with the increase is about 60% from what it is in zero external field.
3D NEGF quantum transport simulator for modeling ballistic transport in nano FinFETs
NASA Astrophysics Data System (ADS)
Khan, H. R.; Mamaluy, D.; Vasileska, D.
2008-03-01
Quantum effects play a dominant role in many of the state-of-the-art small size structures for which the applicability of the standard well-developed engineering tools based on a semi-classical transport description is very limited or even impossible. There are a number of methods developed by solid state theorists over the last several decades to address the issue of quantum transport. Among the most commonly used in nanostructure calculations schemes are the Wigner-function approach, the Pauli master equation, and the non-equilibrium Green's functions (NEGF). The growing popularity of the latest (sometimes referred to as the Keldysh or the Kadanoff-Baym) formalism is conditioned by its sound conceptual basis for the development of the new class of quantum transport simulators. We demonstrate in this work that the key to the successful application of the NEGF formalism to the 3D quantum transport problem in semiconductor nanostructures is the numerical efficiency of the contact block reduction (CBR) method. We also present some very important results from the 3D FinFET analysis, such as the importance of the third gate.
Performance analysis of junctionless carbon nanotube field effect transistors using NEGF formalism
NASA Astrophysics Data System (ADS)
Barbastegan, Saber; Shahhoseini, Ali
2016-04-01
This paper presents the simulation study of a junctionless carbon nanotube field effect transistor (JL-CNTFET) and a comparison is made with the conventional CNTFET using the atomistic scale simulation, within the non-equilibrium Green’s function (NEGF) formalism. In order to have a comprehensive analysis, both analog and digital parameters of the device are studied. Results have shown that JL-CNTFET with respect to C-CNTFET shows slightly higher ION/IOFF ratio about two times larger than that of C-CNTFET, smaller electric field along channel more than three order of magnitude and reduced tunneling current about 100 times. In addition, the investigation of analog properties of both devices has exhibited that junctionless structure has a transconductance about two times and an intrinsic gain of 15 dB larger than C-CNTFET in same bias condition which makes JL-CNTFET a promising candidate for low voltage analog applications.
A comparative study of NEGF and DDMS models in the GAA silicon nanowire transistor
NASA Astrophysics Data System (ADS)
Hosseini, Reza; Fathipour, Morteza; Faez, Rahim
2012-09-01
In this article, we have used quantum and semiclassical models to analyse the electrical characteristics of gate all around silicon nanowire transistor (GAA SNWT). A quantum mechanical transport approach based on non-equilibrium Green's function (NEGF) method with the use of mode space approach in the frame work of effective mass theory has been employed for this analysis. Semiclassical drift diffusion mode space (DDMS) approach has also been used for the simulation of GAA SNWT. We have studied the short-channel effects on the performance of GAA SNWT and evaluated the variation of the threshold voltage, the subthreshold slope (SS), the leakage current and the drain-induced barrier lowering (DIBL) when channel length gets shorter. The results showed that quantum mechanical effects increase the threshold voltage and decrease the leakage current, whereas it has also an impact on the SS and DIBL. We have also investigated the effects of high-κ materials as gate dielectric on the device performance.
Modified NEGF method for atomistic modeling of field emission from carbon nanotube
NASA Astrophysics Data System (ADS)
Monshipouri, Mahta; Behrooz, Milad; Abdi, Yaser
2017-09-01
A model to simulate the atomistic properties of the field emission (FE) from a zigzag-single walled carbon nanotube (Z-SWCNT) is presented. By a modification of the self-energy in non-equilibrium Green's function (NEGF) method, we simulated the field emission current, considering the quantum transport of electrons within the CNT. The paper involves investigation on the effect of the n index of the (n , 0) Z-SWCNT and the number of carbon dimers in the length direction as well as the anode-cathode separation on the FE current. Effect of additional gate voltage and substitutional impurities on the FE current is also studied. A comparison between the experimental data and simulation results are also included in the paper. The model can be used to consider different quantum effects of the atomistic emitter structure on the FE current.
NASA Astrophysics Data System (ADS)
Joy, Soumitra Roy; Bhowmick, Tonmoy Kumar; Hossain, Golam Md. Imran; Mohammedy, Farseem Mannan
Local Density of State (LDOS) and hence Density of State (DOS) at different energy levels of asymmetric conical shaped InAs/InGaAs quantum dots-in-a-well (DWELL) infrared photo-detector has been calculated through Non-Equilibrium Green's Function (NEGF) approach to explain the tri-band operation. Method of finite difference is used to solve the kinetic equation of Green's function and Self-energy is calculated in a recursive manner. Monotonic red shift of spectral response with incremental quantum well width is observed in terms of energy level difference, which is found in good agreement with previously reported experimental data, and the wavelengths corresponding to the peaks of responsivity is estimated from the DOS profile. Relative effect of changing the bottom quantum well width on ground and other higher state energy levels are also reported.
Zheng, K; Yang, Q; Tan, C J; Ye, H Y; Chen, X P
2017-07-19
Two new 2D materials, germanene and monolayer cadmium sulfide (CdS), have been theoretically predicted and experimentally fabricated recently. In this work, we conduct a systematic investigation of the geometry structure, electronic, optical, and transport properties of a CdS/germanene heterojunction by using density functional theory (DFT) combined with the nonequilibrium Green's function (NEGF) formalism. Despite the gapless nature of germanene, the CdS/germanene heterojunction is found to be a direct band gap semiconductor, with a band gap of 0.644 eV. In particular, applying external strain can effectively tune the electronic band structure and optical properties of the CdS/germanene bilayer in a wide range, and a semiconductor-metal transition can even be achieved. In addition, the transport property calculations show that the current-voltage (I-V) relation of the CdS/germanene bilayer exhibits sensitive responses to the applied strain with a marked change in the I-V relation. Such superior electronic, optical, and transport properties make the CdS/germanene heterobilayer a promising candidate for electronic and optical device applications.
Hot-carrier solar cell NEGF-based simulations
NASA Astrophysics Data System (ADS)
Cavassilas, Nicolas; Michelini, Fabienne; Bescond, Marc; Joie, Thibault
2016-03-01
Ultra thin absorbers for the hot carrier solar cell applications are promising. Indeed, in these ultimate absorbers electronphonon scattering are reduced and thickness can be lower than the electron mean-free-path. In this case carriers reach contact ballistically. However it is important that the contact permits to extract these carriers. This theoretical study is about the extraction of the photogenerated carriers and particularly the ballistic extraction without any scattering. We show that quantum interaction between the ultra-thin absorber and the contact can be used to enhance the extraction. Particularly, a contact composed of a quantum well into a double barrier permits to increase the current compared to a simple contact. This improvement is due to a quantum resonance. This result is interesting for the hot carrier solar cells but also for all the ultra-thin cells.
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.
NASA Technical Reports Server (NTRS)
Abrams, D.; Williams, C.
1999-01-01
This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases for which all know classical algorithms require exponential time.
NASA Astrophysics Data System (ADS)
Wolfe, William J.; Wood, David; Sorensen, Stephen E.
1996-12-01
This paper discusses automated scheduling as it applies to complex domains such as factories, transportation, and communications systems. The window-constrained-packing problem is introduced as an ideal model of the scheduling trade offs. Specific algorithms are compared in terms of simplicity, speed, and accuracy. In particular, dispatch, look-ahead, and genetic algorithms are statistically compared on randomly generated job sets. The conclusion is that dispatch methods are fast and fairly accurate; while modern algorithms, such as genetic and simulate annealing, have excessive run times, and are too complex to be practical.
Sobel, E.; Lange, K.; O`Connell, J.R.
1996-12-31
Haplotyping is the logical process of inferring gene flow in a pedigree based on phenotyping results at a small number of genetic loci. This paper formalizes the haplotyping problem and suggests four algorithms for haplotype reconstruction. These algorithms range from exhaustive enumeration of all haplotype vectors to combinatorial optimization by simulated annealing. Application of the algorithms to published genetic analyses shows that manual haplotyping is often erroneous. Haplotyping is employed in screening pedigrees for phenotyping errors and in positional cloning of disease genes from conserved haplotypes in population isolates. 26 refs., 6 figs., 3 tabs.
Grefenstette, J.J.
1994-12-31
Genetic algorithms solve problems by using principles inspired by natural population genetics: They maintain a population of knowledge structures that represent candidate solutions, and then let that population evolve over time through competition and controlled variation. GAs are being applied to a wide range of optimization and learning problems in many domains.
Schulz, Andreas S.; Shmoys, David B.; Williamson, David P.
1997-01-01
Increasing global competition, rapidly changing markets, and greater consumer awareness have altered the way in which corporations do business. To become more efficient, many industries have sought to model some operational aspects by gigantic optimization problems. It is not atypical to encounter models that capture 106 separate “yes” or “no” decisions to be made. Although one could, in principle, try all 2106 possible solutions to find the optimal one, such a method would be impractically slow. Unfortunately, for most of these models, no algorithms are known that find optimal solutions with reasonable computation times. Typically, industry must rely on solutions of unguaranteed quality that are constructed in an ad hoc manner. Fortunately, for some of these models there are good approximation algorithms: algorithms that produce solutions quickly that are provably close to optimal. Over the past 6 years, there has been a sequence of major breakthroughs in our understanding of the design of approximation algorithms and of limits to obtaining such performance guarantees; this area has been one of the most flourishing areas of discrete mathematics and theoretical computer science. PMID:9370525
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.
2013-01-01
approximation to the Tutte polynomial evaluated at 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 22-10-2012 13. SUPPLEMENTARY NOTES The views...over classical algorithms for additive approximation to the Tutte polynomial evaluated at certain roots of unity. This leads to an additive...Temperly-Leib algebras and approximations of tensor networks, and yield additive approximations to the Tutte polynomial . These are relevant to
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.
Stability of Bareiss algorithm
NASA Astrophysics Data System (ADS)
Bojanczyk, Adam W.; Brent, Richard P.; de Hoog, F. R.
1991-12-01
In this paper, we present a numerical stability analysis of Bareiss algorithm for solving a symmetric positive definite Toeplitz system of linear equations. We also compare Bareiss algorithm with Levinson algorithm and conclude that the former has superior numerical properties.
Algorithm Animation with Galant.
Stallmann, Matthias F
2017-01-01
Although surveys suggest positive student attitudes toward the use of algorithm animations, it is not clear that they improve learning outcomes. The Graph Algorithm Animation Tool, or Galant, challenges and motivates students to engage more deeply with algorithm concepts, without distracting them with programming language details or GUIs. Even though Galant is specifically designed for graph algorithms, it has also been used to animate other algorithms, most notably sorting algorithms.
Geist, G.A.; Howell, G.W.; Watkins, D.S.
1997-11-01
The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrowband, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the BR algorithm and gives numerical evidence that it works well in conjunction with the Lanczos process. On the biggest problems run so far, the BR algorithm beats the QR algorithm by a factor of 30--60 in computing time and a factor of over 100 in matrix storage space.
Margolis, C Z
1983-02-04
The clinical algorithm (flow chart) is a text format that is specially suited for representing a sequence of clinical decisions, for teaching clinical decision making, and for guiding patient care. A representative clinical algorithm is described in detail; five steps for writing an algorithm and seven steps for writing a set of algorithms are outlined. Five clinical education and patient care uses of algorithms are then discussed, including a map for teaching clinical decision making and protocol charts for guiding step-by-step care of specific problems. Clinical algorithms are compared as to their clinical usefulness with decision analysis. Three objections to clinical algorithms are answered, including the one that they restrict thinking. It is concluded that methods should be sought for writing clinical algorithms that represent expert consensus. A clinical algorithm could then be written for any area of medical decision making that can be standardized. Medical practice could then be taught more effectively, monitored accurately, and understood better.
Adaptive cockroach swarm algorithm
NASA Astrophysics Data System (ADS)
Obagbuwa, Ibidun C.; Abidoye, Ademola P.
2017-07-01
An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.
Current-voltage characteristics through dithienylcyclopentene: A NEGF-DFT study
NASA Astrophysics Data System (ADS)
Zahedi, Ehsan; Pangh, Abdolhakim
2014-07-01
The nonequilibrium Green's function technique combined with density functional theory were used to investigate the transport properties of 1,2-bis(5-methyl-[2,2‧-bithiophen]-4-yl)cyclopent-1-ene optical molecular switch. Both of its closed and open forms have two S-linkers and translated into the Gold junction with the (1 1 1) surfaces. I-V characteristics, differential conductance, on-off ratio, electronic transmission coefficients, spatial distribution of molecular projected self-consistent Hamiltonian (MPSH) orbitals and projected of the density of states spectrums corresponding to the closed and open forms have been calculated and analyzed. The influences of the delocalization degree of MPSH states in the bias window and coupling degree between molecule orbitals and electrodes levels, on the electronic transport of two systems were discussed in detail. Meantime, larger current through the closed form and negative differential resistance behavior were observed and considered.
NASA Astrophysics Data System (ADS)
Ghavami, Badie; Rastkar-Ebrahimzadeh, Alireza
2015-12-01
Electron transport and quantum conductance through an armchair graphene and its oxidised graphene-containing form were investigated by the density functional theory method and the implementation of the non-equilibrium Green function approach. The computed I - Vb(current as a function of bias voltage) characteristic of the studied systems showed the tunnelling phenomenon in bias and gate voltages considered. Along with the transport properties, electronic properties including density of states were calculated in the studied systems. A close examination of the results showed that the I - Vb curve for graphene behaved ? like at some bias voltages, while for the oxidised graphene-containing form, its trend was the same as that of a voltage dependent resistor (VDR-VARiable resISTOR), I∝Vβb, at the whole range of the applied bias.
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.
Software For Genetic Algorithms
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steve E.
1992-01-01
SPLICER computer program is genetic-algorithm software tool used to solve search and optimization problems. Provides underlying framework and structure for building genetic-algorithm application program. Written in Think C.
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.
Quantum algorithms: an overview
NASA Astrophysics Data System (ADS)
Montanaro, Ashley
2016-01-01
Quantum computers are designed to outperform standard computers by running quantum algorithms. Areas in which quantum algorithms can be applied include cryptography, search and optimisation, simulation of quantum systems and solving large systems of linear equations. Here we briefly survey some known quantum algorithms, with an emphasis on a broad overview of their applications rather than their technical details. We include a discussion of recent developments and near-term applications of quantum algorithms.
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.
NASA Astrophysics Data System (ADS)
Graf, Norman A.
2001-07-01
An object-oriented framework for undertaking clustering algorithm studies has been developed. We present here the definitions for the abstract Cells and Clusters as well as the interface for the algorithm. We intend to use this framework to investigate the interplay between various clustering algorithms and the resulting jet reconstruction efficiency and energy resolutions to assist in the design of the calorimeter detector.
License plate detection algorithm
NASA Astrophysics Data System (ADS)
Broitman, Michael; Klopovsky, Yuri; Silinskis, Normunds
2013-12-01
A novel algorithm for vehicle license plates localization is proposed. The algorithm is based on pixel intensity transition gradient analysis. Near to 2500 natural-scene gray-level vehicle images of different backgrounds and ambient illumination was tested. The best set of algorithm's parameters produces detection rate up to 0.94. Taking into account abnormal camera location during our tests and therefore geometrical distortion and troubles from trees this result could be considered as passable. Correlation between source data, such as license Plate dimensions and texture, cameras location and others, and parameters of algorithm were also defined.
Portfolios of Quantum Algorithms
NASA Astrophysics Data System (ADS)
Maurer, Sebastian M.; Hogg, Tad; Huberman, Bernardo A.
2001-12-01
Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can find the solution of hard problems only probabilistically. Thus the efficiency of the algorithms has to be characterized by both the expected time to completion and the associated variance. In order to minimize both the running time and its uncertainty, we show that portfolios of quantum algorithms analogous to those of finance can outperform single algorithms when applied to the NP-complete problems such as 3-satisfiability.
Distributed Minimum Hop Algorithms
1982-01-01
acknowledgement), node d starts iteration i+1, and otherwise the algorithm terminates. A detailed description of the algorithm is given in pidgin algol...precise behavior of the algorithm under these circumstances is described by the pidgin algol program in the appendix which is executed by each node. The...l) < N!(2) for each neighbor j, and thus by induction,J -1 N!(2-1) < n-i + (Z-1) + N!(Z-1), completing the proof. Algorithm Dl in Pidgin Algol It is
Derivation of Randomized Algorithms.
1985-10-01
81] randomized algorithm, 2)AKS deterministic algorithm[AKS83], 3) Column Sorting algorithm [Leighton 83], 4)FLASH SORT algorithm[Reif and Valiant 83...34 ) (for any a). This result immediately implies that r,. _ i- logN with 8 -’ probability > 1 - O(N - *) thus proving our claim. Lemma 3.3 A random SCX of...will be sampleselect, (LN/2J, N). With this modification, quicksort becomes atlgrithm samplesort, (X); if I Al 1 then r rnX; Choose a random subset SCX
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
The Training Effectiveness Algorithm.
ERIC Educational Resources Information Center
Cantor, Jeffrey A.
1988-01-01
Describes the Training Effectiveness Algorithm, a systematic procedure for identifying the cause of reported training problems which was developed for use in the U.S. Navy. A two-step review by subject matter experts is explained, and applications of the algorithm to other organizations and training systems are discussed. (Author/LRW)
Ultrametric Hierarchical Clustering Algorithms.
ERIC Educational Resources Information Center
Milligan, Glenn W.
1979-01-01
Johnson has shown that the single linkage and complete linkage hierarchical clustering algorithms induce a metric on the data known as the ultrametric. Johnson's proof is extended to four other common clustering algorithms. Two additional methods also produce hierarchical structures which can violate the ultrametric inequality. (Author/CTM)
Where genetic algorithms excel.
Baum, E B; Boneh, D; Garrett, C
2001-01-01
We analyze the performance of a genetic algorithm (GA) we call Culling, and a variety of other algorithms, on a problem we refer to as the Additive Search Problem (ASP). We show that the problem of learning the Ising perceptron is reducible to a noisy version of ASP. Noisy ASP is the first problem we are aware of where a genetic-type algorithm bests all known competitors. We generalize ASP to k-ASP to study whether GAs will achieve "implicit parallelism" in a problem with many more schemata. GAs fail to achieve this implicit parallelism, but we describe an algorithm we call Explicitly Parallel Search that succeeds. We also compute the optimal culling point for selective breeding, which turns out to be independent of the fitness function or the population distribution. We also analyze a mean field theoretic algorithm performing similarly to Culling on many problems. These results provide insight into when and how GAs can beat competing methods.
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.
NASA Astrophysics Data System (ADS)
Jiang, Ai-Hua; Huang, Xiu-Chang; Zhang, Zhen-Hua; Li, Jun; Zhang, Zhi-Yi; Hua, Hong-Xin
2010-11-01
Three new mutual information algorithms are raised for time delay in the phase space reconstruction process. Firstly, Cellucci's mutual information algorithm is analyzed based on partitioning plane, which is constructed by a pair of Lorenz series with the same size, into four and sixteen grids with equal distribution probability in elements on each axis. Then three new mutual information algorithms are promoted based on the original probability matrix that shows the distribution of points corresponding to the data pairs of Lorenz series on the plane, the matrix excluding the last column and the last row of the original one as well as the proportionally revised matrix from the original one. Synchronously, an algorithm to compute the probability matrix is also advanced by sorting two series and replacing each numerical value with its order number in its own series so as to judge the element in which data sets are located. The optimal time delay of the three new mutual information algorithms as well as the computing time is also compared when series sizes are different. Finally, after reconstructing phase space with the optimal time delay, comparison between the maximal Lyapunov exponent calculated by Rosenstein's algorithm from time series and that gained by Jacobi matrix from Lorenz equation is used to confirm the validity of the new mutual information algorithms. The results show that Cellucci's mutual information algorithm will lead to wrong optimal time delay when series size is not a multiple of elements. The three new algorithms, whose results are more steady when a large number of data pairs are used, can not only eliminate the default of Cellucci's algorithm but also is very speedy, and the time spent on calculations by three algorithms nearly enhances linearly with the increase in series size. Moreover, the algorithm using original probability distribution matrix is more accurate than the others when small size series are used, and is also faster than the
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.
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.
The Algorithm Selection Problem
NASA Technical Reports Server (NTRS)
Minton, Steve; Allen, John; Deiss, Ron (Technical Monitor)
1994-01-01
Work on NP-hard problems has shown that many instances of these theoretically computationally difficult problems are quite easy. The field has also shown that choosing the right algorithm for the problem can have a profound effect on the time needed to find a solution. However, to date there has been little work showing how to select the right algorithm for solving any particular problem. The paper refers to this as the algorithm selection problem. It describes some of the aspects that make this problem difficult, as well as proposes a technique for addressing it.
Inclusive Flavour Tagging Algorithm
NASA Astrophysics Data System (ADS)
Likhomanenko, Tatiana; Derkach, Denis; Rogozhnikov, Alex
2016-10-01
Identifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of B mesons in any proton-proton experiment.
NASA Astrophysics Data System (ADS)
Feigin, G.; Ben-Yosef, N.
1983-10-01
A thinning algorithm, of the banana-peel type, is presented. In each iteration pixels are attacked from all directions (there are no sub-iterations), and the deletion criteria depend on the 24 nearest neighbours.
Diagnostic Algorithm Benchmarking
NASA Technical Reports Server (NTRS)
Poll, Scott
2011-01-01
A poster for the NASA Aviation Safety Program Annual Technical Meeting. It describes empirical benchmarking on diagnostic algorithms using data from the ADAPT Electrical Power System testbed and a diagnostic software framework.
2016-06-07
ABSTRACT unclassified c . THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Date: 5 DEC 84 NAVAL UNDERWATER...algorithm. The FORTRAN 77 subroutines are listed alphabetically in APPENDIX C . SUMMARY Several new features have been incorporated into this version of...Correcting Algorithm, NUSC TM 781154, of 3 August 1978 (B) NUSC ( C ) (D) E. M. Podeszwa, Sound Speed Profiles for the Mediterranean Sea, NUSC TD
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.
Implementation of Parallel Algorithms
1993-06-30
their socia ’ relations or to achieve some goals. For example, we define a pair-wise force law of i epulsion and attraction for a group of identical...quantization based compression schemes. Photo-refractive crystals, which provide high density recording in real time, are used as our holographic media . The...of Parallel Algorithms (J. Reif, ed.). Kluwer Academic Pu’ ishers, 1993. (4) "A Dynamic Separator Algorithm", D. Armon and J. Reif. To appear in
Parallel Wolff Cluster Algorithms
NASA Astrophysics Data System (ADS)
Bae, S.; Ko, S. H.; Coddington, P. D.
The Wolff single-cluster algorithm is the most efficient method known for Monte Carlo simulation of many spin models. Due to the irregular size, shape and position of the Wolff clusters, this method does not easily lend itself to efficient parallel implementation, so that simulations using this method have thus far been confined to workstations and vector machines. Here we present two parallel implementations of this algorithm, and show that one gives fairly good performance on a MIMD parallel computer.
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
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.
NASA Technical Reports Server (NTRS)
Dongarra, Jack
1998-01-01
This exploratory study initiated our inquiry into algorithms and applications that would benefit by latency tolerant approach to algorithm building, including the construction of new algorithms where appropriate. In a multithreaded execution, when a processor reaches a point where remote memory access is necessary, the request is sent out on the network and a context--switch occurs to a new thread of computation. This effectively masks a long and unpredictable latency due to remote loads, thereby providing tolerance to remote access latency. We began to develop standards to profile various algorithm and application parameters, such as the degree of parallelism, granularity, precision, instruction set mix, interprocessor communication, latency etc. These tools will continue to develop and evolve as the Information Power Grid environment matures. To provide a richer context for this research, the project also focused on issues of fault-tolerance and computation migration of numerical algorithms and software. During the initial phase we tried to increase our understanding of the bottlenecks in single processor performance. Our work began by developing an approach for the automatic generation and optimization of numerical software for processors with deep memory hierarchies and pipelined functional units. Based on the results we achieved in this study we are planning to study other architectures of interest, including development of cost models, and developing code generators appropriate to these architectures.
Project resource reallocation algorithm
NASA Technical Reports Server (NTRS)
Myers, J. E.
1981-01-01
A methodology for adjusting baseline cost estimates according to project schedule changes is described. An algorithm which performs a linear expansion or contraction of the baseline project resource distribution in proportion to the project schedule expansion or contraction is presented. Input to the algorithm consists of the deck of cards (PACE input data) prepared for the baseline project schedule as well as a specification of the nature of the baseline schedule change. Output of the algorithm is a new deck of cards with all work breakdown structure block and element of cost estimates redistributed for the new project schedule. This new deck can be processed through PACE to produce a detailed cost estimate for the new schedule.
Detection of algorithmic trading
NASA Astrophysics Data System (ADS)
Bogoev, Dimitar; Karam, Arzé
2017-10-01
We develop a new approach to reflect the behavior of algorithmic traders. Specifically, we provide an analytical and tractable way to infer patterns of quote volatility and price momentum consistent with different types of strategies employed by algorithmic traders, and we propose two ratios to quantify these patterns. Quote volatility ratio is based on the rate of oscillation of the best ask and best bid quotes over an extremely short period of time; whereas price momentum ratio is based on identifying patterns of rapid upward or downward movement in prices. The two ratios are evaluated across several asset classes. We further run a two-stage Artificial Neural Network experiment on the quote volatility ratio; the first stage is used to detect the quote volatility patterns resulting from algorithmic activity, while the second is used to validate the quality of signal detection provided by our measure.
Andrews, Jeff; Likis, Frances E
2015-10-01
To aid authors in correctly naming their study design, to assist readers and reviewers who must decide what the design was for some published studies, and to provide consistency in evaluating the design of published studies, especially for those conducting systematic reviews and evidence synthesis. An annotated algorithm method is used to prompt serial questions and analysis to identify a single study design. The algorithm begins with a research article. Primary clinical research is divided into experimental and observational studies. Key determinants include identifying the study question and the population, intervention, comparison, and outcome. Experimental therapy and prognosis studies are subdivided into 4 design types. Observational therapy and prognosis studies are subdivided into 7 design types. Experimental diagnosis and screening studies are subdivided into 2 types. Observational diagnosis and screening studies are subdivided into 5 types. An annotated algorithm may be used by authors, readers, and reviewers to consistently determine the design of clinical research studies.
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.
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.
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.
Kernel Affine Projection Algorithms
NASA Astrophysics Data System (ADS)
Liu, Weifeng; Príncipe, José C.
2008-12-01
The combination of the famed kernel trick and affine projection algorithms (APAs) yields powerful nonlinear extensions, named collectively here, KAPA. This paper is a follow-up study of the recently introduced kernel least-mean-square algorithm (KLMS). KAPA inherits the simplicity and online nature of KLMS while reducing its gradient noise, boosting performance. More interestingly, it provides a unifying model for several neural network techniques, including kernel least-mean-square algorithms, kernel adaline, sliding-window kernel recursive-least squares (KRLS), and regularization networks. Therefore, many insights can be gained into the basic relations among them and the tradeoff between computation complexity and performance. Several simulations illustrate its wide applicability.
A MEDLINE categorization algorithm.
Darmoni, Stefan J; Névéol, Aurelie; Renard, Jean-Marie; Gehanno, Jean-Francois; Soualmia, Lina F; Dahamna, Badisse; Thirion, Benoit
2006-02-07
Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway. The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links. The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics. We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms/subheadings) pairs by NLM indexers. This
Improved Chaff Solution Algorithm
2009-03-01
Programme de démonstration de technologies (PDT) sur l’intégration de capteurs et de systèmes d’armes embarqués (SISWS), un algorithme a été élaboré...technologies (PDT) sur l’intégration de capteurs et de systèmes d’armes embarqués (SISWS), un algorithme a été élaboré pour déterminer automatiquement...0Z4 2. SECURITY CLASSIFICATION (Overall security classification of the document including special warning terms if applicable .) UNCLASSIFIED
Parallel Algorithms and Patterns
Robey, Robert W.
2016-06-16
This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.
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.
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)
Algorithm for reaction classification.
Kraut, Hans; Eiblmaier, Josef; Grethe, Guenter; Löw, Peter; Matuszczyk, Heinz; Saller, Heinz
2013-11-25
Reaction classification has important applications, and many approaches to classification have been applied. Our own algorithm tests all maximum common substructures (MCS) between all reactant and product molecules in order to find an atom mapping containing the minimum chemical distance (MCD). Recent publications have concluded that new MCS algorithms need to be compared with existing methods in a reproducible environment, preferably on a generalized test set, yet the number of test sets available is small, and they are not truly representative of the range of reactions that occur in real reaction databases. We have designed a challenging test set of reactions and are making it publicly available and usable with InfoChem's software or other classification algorithms. We supply a representative set of example reactions, grouped into different levels of difficulty, from a large number of reaction databases that chemists actually encounter in practice, in order to demonstrate the basic requirements for a mapping algorithm to detect the reaction centers in a consistent way. We invite the scientific community to contribute to the future extension and improvement of this data set, to achieve the goal of a common standard.
Static Analysis Numerical Algorithms
2016-04-01
and Honeywell Aerospace Advanced Technology to combine model-based development of complex avionics control software with static analysis of the...numerical algorithms, software verification, formal methods 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF PAGES...18 3.3.4. Tool Software Integration Architecture
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.
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''.
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…
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…
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.
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
Fast autodidactic adaptive equalization algorithms
NASA Astrophysics Data System (ADS)
Hilal, Katia
Autodidactic equalization by adaptive filtering is addressed in a mobile radio communication context. A general method, using an adaptive stochastic gradient Bussgang type algorithm, to deduce two low cost computation algorithms is given: one equivalent to the initial algorithm and the other having improved convergence properties thanks to a block criteria minimization. Two start algorithms are reworked: the Godard algorithm and the decision controlled algorithm. Using a normalization procedure, and block normalization, the performances are improved, and their common points are evaluated. These common points are used to propose an algorithm retaining the advantages of the two initial algorithms. This thus inherits the robustness of the Godard algorithm and the precision and phase correction of the decision control algorithm. The work is completed by a study of the stable states of Bussgang type algorithms and of the stability of the Godard algorithms, initial and normalized. The simulation of these algorithms, carried out in a mobile radio communications context, and under severe conditions on the propagation channel, gave a 75% reduction in the number of samples required for the processing in relation with the initial algorithms. The improvement of the residual error was of a much lower return. These performances are close to making possible the use of autodidactic equalization in the mobile radio system.
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.
A MEDLINE categorization algorithm
Darmoni, Stefan J; Névéol, Aurelie; Renard, Jean-Marie; Gehanno, Jean-Francois; Soualmia, Lina F; Dahamna, Badisse; Thirion, Benoit
2006-01-01
Background Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway. Methods The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links. Results The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics. Conclusion We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms
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
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…
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…
The cyclic reduction algorithm
NASA Astrophysics Data System (ADS)
Bini, Dario; Meini, Beatrice
2009-05-01
Cyclic reduction is an algorithm invented by G.H. Golub and R. W. Hockney in the mid 1960s for solving linear systems related to the finite differences discretization of the Poisson equation over a rectangle. Among the algorithms of Gene Golub, it is one of the most versatile and powerful ever created. Recently, it has been applied to solve different problems from different applicative areas. In this paper we survey the main features of cyclic reduction, relate it to properties of analytic functions, recall its extension to solving more general finite and infinite linear systems, and different kinds of nonlinear matrix equations, including algebraic Riccati equations, with applications to Markov chains, queueing models and transport theory. Some new results concerning the convergence properties of cyclic reduction and its applicability are proved under very weak assumptions. New formulae for overcoming breakdown are provided.
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.
Algorithms, games, and evolution
Chastain, Erick; Livnat, Adi; Papadimitriou, Christos; Vazirani, Umesh
2014-01-01
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. PMID:24979793
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.
ARPANET Routing Algorithm Improvements
1978-10-01
IMPROVEMENTS . .PFOnINI ORG. REPORT MUNDER -- ) _ .. .... 3940 7, AUT(c) .. .. .. CONTRACT Of GRANT NUMSlet e) SJ. M. /Mc~uillan E. C./Rosen I...8217), this problem may persist for a very long time, causing extremely bad performance throughout the whole network (for instance, if w’ reports that one of...algorithm may naturally tend to oscillate between bad routing paths and become itself a major contributor to network congestion. These examples show
1983-10-13
determining the solu- tion using the Moore - Penrose inverse . An expression for the mean square error is derived [8,9]. The expression indicates that...Proc. 10. "An Iterative Algorithm for Finding the Minimum Eigenvalue of a Class of Symmetric Matrices," D. Fuhrmann and B. Liu, submitted to 1984 IEEE...Int. Conf. Acous. Sp. 5V. Proc. 11. "Approximating the Eigenvectors of a Symmetric Toeplitz Matrix," by D. Fuhrmann and B. Liu, 1983 Allerton Conf. an
Algorithmic Complexity. Volume II.
1982-06-01
works, give an example, and discuss the inherent weaknesses and their causes. Electrical Network Analysis Knuth mentions the applicability of...of these 3 products of 2-coefficient 2 1 polynomials can be found by a repeated application of the 3 multiplication W Ascheme, only 3.3-9 scalar...see another application of this paradigm later. We now investigate the efficiency of the divide-and-conquer polynomial multiplication algorithm. Let M(n
NASA Astrophysics Data System (ADS)
Reda, Ibrahim; Andreas, Afshin
2015-04-01
The Solar Position Algorithm (SPA) calculates the solar zenith and azimuth angles in the period from the year -2000 to 6000, with uncertainties of +/- 0.0003 degrees based on the date, time, and location on Earth. SPA is implemented in C; in addition to being available for download, an online calculator using this code is available at http://www.nrel.gov/midc/solpos/spa.html.
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.
Irregular Applications: Architectures & Algorithms
Feo, John T.; Villa, Oreste; Tumeo, Antonino; Secchi, Simone
2012-02-06
Irregular applications are characterized by irregular data structures, control and communication patterns. Novel irregular high performance applications which deal with large data sets and require have recently appeared. Unfortunately, current high performance systems and software infrastructures executes irregular algorithms poorly. Only coordinated efforts by end user, area specialists and computer scientists that consider both the architecture and the software stack may be able to provide solutions to the challenges of modern irregular applications.
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.
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.
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.
Mammogram analysis using CNN algorithms
NASA Astrophysics Data System (ADS)
Liszka, Gyorgy; Roska, Tamas; Zarandy, Akos; Hegyesi, J.; Kek, L.; Rekeczky, Csaba
1995-05-01
Analogic CNN algorithms were developed and introduced to detect the major pathological signs of the breast cancer in x-ray mammogram images. The reported algorithms can detect the microcalcifications and the spiculi around a given tumor kernel.
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.
Baudoin, T; Grgić, M V; Zadravec, D; Geber, G; Tomljenović, D; Kalogjera, L
2013-12-01
ENT navigation has given new opportunities in performing Endoscopic Sinus Surgery (ESS) and improving surgical outcome of the patients` treatment. ESS assisted by a navigation system could be called Navigated Endoscopic Sinus Surgery (NESS). As it is generally accepted that the NESS should be performed only in cases of complex anatomy and pathology, it has not yet been established as a state-of-the-art procedure and thus not used on a daily basis. This paper presents an algorithm for use of a navigation system for basic ESS in the treatment of chronic rhinosinusitis (CRS). The algorithm includes five units that should be highlighted using a navigation system. They are as follows: 1) nasal vestibule unit, 2) OMC unit, 3) anterior ethmoid unit, 4) posterior ethmoid unit, and 5) sphenoid unit. Each unit has a shape of a triangular pyramid and consists of at least four reference points or landmarks. As many landmarks as possible should be marked when determining one of the five units. Navigated orientation in each unit should always precede any surgical intervention. The algorithm should improve the learning curve of trainees and enable surgeons to use the navigation system routinely and systematically.
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.
Stubbs, Allston Julius; Atilla, Halis Atil
2016-01-01
Summary Background Despite the rapid advancement of imaging and arthroscopic techniques about the hip joint, missed diagnoses are still common. As a deep joint and compared to the shoulder and knee joints, localization of hip symptoms is difficult. Hip pathology is not easily isolated and is often related to intra and extra-articular abnormalities. In light of these diagnostic challenges, we recommend an algorithmic approach to effectively diagnoses and treat hip pain. Methods In this review, hip pain is evaluated from diagnosis to treatment in a clear decision model. First we discuss emergency hip situations followed by the differentiation of intra and extra-articular causes of the hip pain. We differentiate the intra-articular hip as arthritic and non-arthritic and extra-articular pain as surrounding or remote tissue generated. Further, extra-articular hip pain is evaluated according to pain location. Finally we summarize the surgical treatment approach with an algorithmic diagram. Conclusion Diagnosis of hip pathology is difficult because the etiologies of pain may be various. An algorithmic approach to hip restoration from diagnosis to rehabilitation is crucial to successfully identify and manage hip pathologies. Level of evidence: V. PMID:28066734
Experimental data filtration algorithm
NASA Astrophysics Data System (ADS)
Oanta, E.; Tamas, R.; Danisor, A.
2017-08-01
Experimental data reduction is an important topic because the resulting information is used to calibrate the theoretical models and to verify the accuracy of their results. The paper presents some ideas used to extract a subset of points from the initial set of points which defines an experimentally acquired curve. The objective is to get a subset with significantly fewer points as the initial data set and which accurately defines a smooth curve that preserves the shape of the initial curve. Being a general study we used only data filtering criteria based geometric features that at a later stage may be related to upper level conditions specific to the phenomenon under investigation. Five algorithms were conceived and implemented in an original software consisting of more than 1800 computer code lines which has a flexible structure that allows us to easily update it using new algorithms. The software instrument was used to process the data of several case studies. Conclusions are drawn regarding the values of the parameters used in the algorithms to decide if a series of points may be considered either noise, or a relevant part of the curve. Being a general analysis, the result is a computer based trial-and-error method that efficiently solves this kind of problems.
Greedy algorithms in disordered systems
NASA Astrophysics Data System (ADS)
Duxbury, P. M.; Dobrin, R.
1999-08-01
We discuss search, minimal path and minimal spanning tree algorithms and their applications to disordered systems. Greedy algorithms solve these problems exactly, and are related to extremal dynamics in physics. Minimal cost path (Dijkstra) and minimal cost spanning tree (Prim) algorithms provide extremal dynamics for a polymer in a random medium (the KPZ universality class) and invasion percolation (without trapping) respectively.
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.
Grammar Rules as Computer Algorithms.
ERIC Educational Resources Information Center
Rieber, Lloyd
1992-01-01
One college writing teacher engaged his class in the revision of a computer program to check grammar, focusing on improvement of the algorithms for identifying inappropriate uses of the passive voice. Process and problems of constructing new algorithms, effects on student writing, and other algorithm applications are discussed. (MSE)
Verifying a Computer Algorithm Mathematically.
ERIC Educational Resources Information Center
Olson, Alton T.
1986-01-01
Presents an example of mathematics from an algorithmic point of view, with emphasis on the design and verification of this algorithm. The program involves finding roots for algebraic equations using the half-interval search algorithm. The program listing is included. (JN)
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.
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…
Selfish Gene Algorithm Vs Genetic Algorithm: A Review
NASA Astrophysics Data System (ADS)
Ariff, Norharyati Md; Khalid, Noor Elaiza Abdul; Hashim, Rathiah; Noor, Noorhayati Mohamed
2016-11-01
Evolutionary algorithm is one of the algorithms inspired by the nature. Within little more than a decade hundreds of papers have reported successful applications of EAs. In this paper, the Selfish Gene Algorithms (SFGA), as one of the latest evolutionary algorithms (EAs) inspired from the Selfish Gene Theory which is an interpretation of Darwinian Theory ideas from the biologist Richards Dawkins on 1989. In this paper, following a brief introduction to the Selfish Gene Algorithm (SFGA), the chronology of its evolution is presented. It is the purpose of this paper is to present an overview of the concepts of Selfish Gene Algorithm (SFGA) as well as its opportunities and challenges. Accordingly, the history, step involves in the algorithm are discussed and its different applications together with an analysis of these applications are evaluated.
Majorization in quantum adiabatic algorithms
Wei Zhaohui; Ji Zhengfeng; Ying Mingsheng
2006-10-15
The majorization theory has been applied to analyze the mathematical structure of quantum algorithms. An empirical conclusion by numerical simulations obtained in the previous literature indicates that step-by-step majorization seems to appear universally in quantum adiabatic algorithms. In this paper, a rigorous analysis of the majorization arrow in a special class of quantum adiabatic algorithms is carried out. In particular, we prove that for any adiabatic algorithm of this class, step-by-step majorization of the ground state holds exactly. For the actual state, we show that step-by-step majorization holds approximately, and furthermore that the longer the running time of the algorithm, the better the approximation.
A high performance graphics algorithm
North, M.J.; Zhao, S.
1994-07-01
Rendering images of complex collections of general objects in multidimensional space is typically very time consuming. The process of displaying such images is often a linear function of the number objects being considered. This behavior can become unacceptable when the number of objects to be considered is large. This paper describes an algorithm to address this problem. The graphics algorithm presented here is composed of a storage algorithm and a selection algorithm. Both of these components are described in relation to a specialized tree data structure. The storage algorithm is proven to exhibit O(n log n) average time behavior and the selection algorithm is proven to exhibit O(log n) average time behavior. This paper focuses on two dimensional images but natural extensions of the basic algorithms to higher dimensional spaces are also considered.
Join-Graph Propagation Algorithms
Mateescu, Robert; Kask, Kalev; Gogate, Vibhav; Dechter, Rina
2010-01-01
The paper investigates parameterized approximate message-passing schemes that are based on bounded inference and are inspired by Pearl's belief propagation algorithm (BP). We start with the bounded inference mini-clustering algorithm and then move to the iterative scheme called Iterative Join-Graph Propagation (IJGP), that combines both iteration and bounded inference. Algorithm IJGP belongs to the class of Generalized Belief Propagation algorithms, a framework that allowed connections with approximate algorithms from statistical physics and is shown empirically to surpass the performance of mini-clustering and belief propagation, as well as a number of other state-of-the-art algorithms on several classes of networks. We also provide insight into the accuracy of iterative BP and IJGP by relating these algorithms to well known classes of constraint propagation schemes. PMID:20740057
Constructive neural network learning algorithms
Parekh, R.; Yang, Jihoon; Honavar, V.
1996-12-31
Constructive Algorithms offer an approach for incremental construction of potentially minimal neural network architectures for pattern classification tasks. These algorithms obviate the need for an ad-hoc a-priori choice of the network topology. The constructive algorithm design involves alternately augmenting the existing network topology by adding one or more threshold logic units and training the newly added threshold neuron(s) using a stable variant of the perception learning algorithm (e.g., pocket algorithm, thermal perception, and barycentric correction procedure). Several constructive algorithms including tower, pyramid, tiling, upstart, and perception cascade have been proposed for 2-category pattern classification. These algorithms differ in terms of their topological and connectivity constraints as well as the training strategies used for individual neurons.
Algorithm performance evaluation
NASA Astrophysics Data System (ADS)
Smith, Richard N.; Greci, Anthony M.; Bradley, Philip A.
1995-03-01
Traditionally, the performance of adaptive antenna systems is measured using automated antenna array pattern measuring equipment. This measurement equipment produces a plot of the receive gain of the antenna array as a function of angle. However, communications system users more readily accept and understand bit error rate (BER) as a performance measure. The work reported on here was conducted to characterize adaptive antenna receiver performance in terms of overall communications system performance using BER as a performance measure. The adaptive antenna system selected for this work featured a linear array, least mean square (LMS) adaptive algorithm and a high speed phase shift keyed (PSK) communications modem.
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.
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.
Online Pairwise Learning Algorithms.
Ying, Yiming; Zhou, Ding-Xuan
2016-04-01
Pairwise learning usually refers to a learning task that involves a loss function depending on pairs of examples, among which the most notable ones are bipartite ranking, metric learning, and AUC maximization. In this letter we study an online algorithm for pairwise learning with a least-square loss function in an unconstrained setting of a reproducing kernel Hilbert space (RKHS) that we refer to as the Online Pairwise lEaRning Algorithm (OPERA). In contrast to existing works (Kar, Sriperumbudur, Jain, & Karnick, 2013 ; Wang, Khardon, Pechyony, & Jones, 2012 ), which require that the iterates are restricted to a bounded domain or the loss function is strongly convex, OPERA is associated with a non-strongly convex objective function and learns the target function in an unconstrained RKHS. Specifically, we establish a general theorem that guarantees the almost sure convergence for the last iterate of OPERA without any assumptions on the underlying distribution. Explicit convergence rates are derived under the condition of polynomially decaying step sizes. We also establish an interesting property for a family of widely used kernels in the setting of pairwise learning and illustrate the convergence results using such kernels. Our methodology mainly depends on the characterization of RKHSs using its associated integral operators and probability inequalities for random variables with values in a Hilbert space.
The evolutionary forest algorithm.
Leman, Scotland C; Uyenoyama, Marcy K; Lavine, Michael; Chen, Yuguo
2007-08-01
Gene genealogies offer a powerful context for inferences about the evolutionary process based on presently segregating DNA variation. In many cases, it is the distribution of population parameters, marginalized over the effectively infinite-dimensional tree space, that is of interest. Our evolutionary forest (EF) algorithm uses Monte Carlo methods to generate posterior distributions of population parameters. A novel feature is the updating of parameter values based on a probability measure defined on an ensemble of histories (a forest of genealogies), rather than a single tree. The EF algorithm generates samples from the correct marginal distribution of population parameters. Applied to actual data from closely related fruit fly species, it rapidly converged to posterior distributions that closely approximated the exact posteriors generated through massive computational effort. Applied to simulated data, it generated credible intervals that covered the actual parameter values in accordance with the nominal probabilities. A C++ implementation of this method is freely accessible at http://www.isds.duke.edu/~scl13
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.
Optimal Fungal Space Searching Algorithms.
Asenova, Elitsa; Lin, Hsin-Yu; Fu, Eileen; Nicolau, Dan V; Nicolau, Dan V
2016-10-01
Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.
NASA Astrophysics Data System (ADS)
Celis Gil, J. A.; Thijssen, J. M.
2017-08-01
A method is presented for predicting one-particle energies for a molecule in a junction with one metal electrode, using density functional theory methods. In contrast to previous studies, in which restricted spin configurations were analyzed, we take spin polarization into account. Furthermore, in addition to junctions in which the molecule is weakly coupled, our method is also capable of describing junctions in which the molecule is chemisorbed to the metal contact. We implemented a fully self-consistent scissor operator to correct the highest occupied molecular orbital-lowest unoccupied molecular orbital gap in transport calculations for single molecule junctions. We present results for various systems and compare our results with those obtained by other groups.
NASA Astrophysics Data System (ADS)
Leek, Meng Lee
The presence of slight azimuthal asymmetry in the initial shape of an underwater bubble entirely alters the final break-up dynamics. Vibrations in the cross-section shape of the bubble develop, grow relative to the average size of the bubble neck and bring about a coalescence mode of breakup in which distant regions along the air-water surface curve inwards and eventually collide with finite speed. Here we present boundary integral simulation results showing that these coalescence modes of breakups are interspersed with dynamics that give rise to sharp tips along the bubble surface. Our numerics show that when the initial condition is tuned towards some threshold value, the surface appears to evolve into a finite-time curvature singularity by developing sharp tips with infinite curvatures. However, starting with initial conditions at the threshold values, the surface evolution towards the curvature singularity is pre-empted by coalescence. We also show that the dynamics around the curvature singularity corresponds to a saddle-node evolution. In other words, an evolution towards a cross-section shape with sharp tips invariably later evolves away from it. The maximum curvature attained when the interface evolves towards the curvature singularity increases as the amplitude of the initial perturbation decreases. Taken together, the results suggest that the curvature singularity appears to be attained only in the limit that the initial perturbation amplitude approaches 0. For a phase space trajectory close to the curvature singularity, as the singularity is approached, the curvature of the sharp tip diverges approximately as (R-R c)-0.8, where R describes the average size of the horizontal cross-section of the bubble neck minimum and Rc corresponds to the onset of the singularity, and the velocity of the tip diverges approximately as (R-Rc) -0.4. In practice, these divergences imply that viscous drag and compressibility of the gas flow, two effects not included in our analysis, become significant as the interface evolves towards the curvature singularity.
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.
An overview of smart grid routing algorithms
NASA Astrophysics Data System (ADS)
Wang, Junsheng; OU, Qinghai; Shen, Haijuan
2017-08-01
This paper summarizes the typical routing algorithm in smart grid by analyzing the communication business and communication requirements of intelligent grid. Mainly from the two kinds of routing algorithm is analyzed, namely clustering routing algorithm and routing algorithm, analyzed the advantages and disadvantages of two kinds of typical routing algorithm in routing algorithm and applicability.
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.
One improved LSB steganography algorithm
NASA Astrophysics Data System (ADS)
Song, Bing; Zhang, Zhi-hong
2013-03-01
It is easy to be detected by X2 and RS steganalysis with high accuracy that using LSB algorithm to hide information in digital image. We started by selecting information embedded location and modifying the information embedded method, combined with sub-affine transformation and matrix coding method, improved the LSB algorithm and a new LSB algorithm was proposed. Experimental results show that the improved one can resist the X2 and RS steganalysis effectively.
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
2011-01-22
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.
Solar Occultation Retrieval Algorithm Development
NASA Technical Reports Server (NTRS)
Lumpe, Jerry D.
2004-01-01
This effort addresses the comparison and validation of currently operational solar occultation retrieval algorithms, and the development of generalized algorithms for future application to multiple platforms. initial development of generalized forward model algorithms capable of simulating transmission data from of the POAM II/III and SAGE II/III instruments. Work in the 2" quarter will focus on: completion of forward model algorithms, including accurate spectral characteristics for all instruments, and comparison of simulated transmission data with actual level 1 instrument data for specific occultation events.
Quantum algorithm for data fitting.
Wiebe, Nathan; Braun, Daniel; Lloyd, Seth
2012-08-03
We provide a new quantum algorithm that efficiently determines the quality of a least-squares fit over an exponentially large data set by building upon an algorithm for solving systems of linear equations efficiently [Harrow et al., Phys. Rev. Lett. 103, 150502 (2009)]. In many cases, our algorithm can also efficiently find a concise function that approximates the data to be fitted and bound the approximation error. In cases where the input data are pure quantum states, the algorithm can be used to provide an efficient parametric estimation of the quantum state and therefore can be applied as an alternative to full quantum-state tomography given a fault tolerant quantum computer.
Preconditioned quantum linear system algorithm.
Clader, B D; Jacobs, B C; Sprouse, C R
2013-06-21
We describe a quantum algorithm that generalizes the quantum linear system algorithm [Harrow et al., Phys. Rev. Lett. 103, 150502 (2009)] to arbitrary problem specifications. We develop a state preparation routine that can initialize generic states, show how simple ancilla measurements can be used to calculate many quantities of interest, and integrate a quantum-compatible preconditioner that greatly expands the number of problems that can achieve exponential speedup over classical linear systems solvers. To demonstrate the algorithm's applicability, we show how it can be used to compute the electromagnetic scattering cross section of an arbitrary target exponentially faster than the best classical algorithm.
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.
Research on Routing Selection Algorithm Based on Genetic Algorithm
NASA Astrophysics Data System (ADS)
Gao, Guohong; Zhang, Baojian; Li, Xueyong; Lv, Jinna
The hereditary algorithm is a kind of random searching and method of optimizing based on living beings natural selection and hereditary mechanism. In recent years, because of the potentiality in solving complicate problems and the successful application in the fields of industrial project, hereditary algorithm has been widely concerned by the domestic and international scholar. Routing Selection communication has been defined a standard communication model of IP version 6.This paper proposes a service model of Routing Selection communication, and designs and implements a new Routing Selection algorithm based on genetic algorithm.The experimental simulation results show that this algorithm can get more resolution at less time and more balanced network load, which enhances search ratio and the availability of network resource, and improves the quality of service.
Using DFX for Algorithm Evaluation
Beiriger, J.I.; Funkhouser, D.R.; Young, C.J.
1998-10-20
Evaluating whether or not a new seismic processing algorithm can improve the performance of the operational system can be problematic: it maybe difficult to isolate the comparable piece of the operational system it maybe necessary to duplicate ancillary timctions; and comparing results to the tuned, full-featured operational system maybe an unsat- isfactory basis on which to draw conclusions. Algorithm development and evaluation in an environment that more closely resembles the operational system can be achieved by integrating the algorithm with the custom user library of the Detection and Feature Extraction (DFX) code, developed by Science Applications kternational Corporation. This integration gives the seismic researcher access to all of the functionality of DFX, such as database access, waveform quality control, and station-specific tuning, and provides a more meaningfid basis for evaluation. The goal of this effort is to make the DFX environment more accessible to seismic researchers for algorithm evalua- tion. Typically, anew algorithm will be developed as a C-language progmm with an ASCII test parameter file. The integration process should allow the researcher to focus on the new algorithm developmen~ with minimum attention to integration issues. Customizing DFX, however, requires soflsvare engineering expertise, knowledge of the Scheme and C programming languages, and familiarity with the DFX source code. We use a C-language spatial coherence processing algorithm with a parameter and recipe file to develop a general process for integrating and evaluating a new algorithm in the DFX environment. To aid in configuring and managing the DFX environment, we develop a simple parameter management tool. We also identifi and examine capabilities that could simplify the process further, thus reducing the barriers facing researchers in using DFX..These capabilities include additional parameter manage- ment features, a Scheme-language template for algorithm testing, a
Modular algorithm concept evaluation tool (MACET) sensor fusion algorithm testbed
NASA Astrophysics Data System (ADS)
Watson, John S.; Williams, Bradford D.; Talele, Sunjay E.; Amphay, Sengvieng A.
1995-07-01
Target acquisition in a high clutter environment in all-weather at any time of day represents a much needed capability for the air-to-surface strike mission. A considerable amount of the research at the Armament Directorate at Wright Laboratory, Advanced Guidance Division WL/MNG, has been devoted to exploring various seeker technologies, including multi-spectral sensor fusion, that may yield a cost efficient system with these capabilities. Critical elements of any such seekers are the autonomous target acquisition and tracking algorithms. These algorithms allow the weapon system to operate independently and accurately in realistic battlefield scenarios. In order to assess the performance of the multi-spectral sensor fusion algorithms being produced as part of the seeker technology development programs, the Munition Processing Technology Branch of WL/MN is developing an algorithm testbed. This testbed consists of the Irma signature prediction model, data analysis workstations, such as the TABILS Analysis and Management System (TAMS), and the Modular Algorithm Concept Evaluation Tool (MACET) algorithm workstation. All three of these components are being enhanced to accommodate multi-spectral sensor fusion systems. MACET is being developed to provide a graphical interface driven simulation by which to quickly configure algorithm components and conduct performance evaluations. MACET is being developed incrementally with each release providing an additional channel of operation. To date MACET 1.0, a passive IR algorithm environment, has been delivered. The second release, MACET 1.1 is presented in this paper using the MMW/IR data from the Advanced Autonomous Dual Mode Seeker (AADMS) captive flight demonstration. Once completed, the delivered software from past algorithm development efforts will be converted to the MACET library format, thereby providing an on-line database of the algorithm research conducted to date.
Error analysis of corner cutting algorithms
NASA Astrophysics Data System (ADS)
Mainar, E.; Peña, J. M.
1999-10-01
Corner cutting algorithms are used in different fields and, in particular, play a relevant role in Computer Aided Geometric Design. Evaluation algorithms such as the de Casteljau algorithm for polynomials and the de Boor-Cox algorithm for B-splines are examples of corner cutting algorithms. Here backward and forward error analysis of corner cutting algorithms are performed. The running error is also analyzed and as a consequence the general algorithm is modified to include the computation of an error bound.
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.
"Noiseless" Data-Compression Algorithm
NASA Technical Reports Server (NTRS)
Rice, R. F.; Lee, J. J.
1986-01-01
Gamma-ray spectrometer data compressed to enable more frequent sampling. Proposed data-compression algorithm efficiently represents gamma-ray spectrometer spectra at any spectrum collection interval from 5 seconds to 5 minutes. Data representations "noiseless" (Data exactly constructed). Techniques useful in designing datacompression algorithms for other spectral instruments, which have varying data-rate requirements.
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.
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).
Algorithms on ensemble quantum computers.
Boykin, P Oscar; Mor, Tal; Roychowdhury, Vwani; Vatan, Farrokh
2010-06-01
In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified, as the common strategy of delaying the measurements usually does not resolve this ensemble-measurement problem. Here we present several new strategies for resolving this problem. Based on these strategies we provide new versions of some of the most important quantum algorithms, versions that are suitable for implementing on ensemble quantum computers, e.g., on liquid NMR quantum computers. These algorithms are Shor's factorization algorithm, Grover's search algorithm (with several marked items), and an algorithm for quantum fault-tolerant computation. The first two algorithms are simply modified using a randomizing and a sorting strategies. For the last algorithm, we develop a classical-quantum hybrid strategy for removing measurements. We use it to present a novel quantum fault-tolerant scheme. More explicitly, we present schemes for fault-tolerant measurement-free implementation of Toffoli and σ(z)(¼) as these operations cannot be implemented "bitwise", and their standard fault-tolerant implementations require measurement.
The improved differential demon algorithm.
Yang, Jinzhu; Deng, Meili; Cao, Peng; Tan, Wenjun; Sun, Qi; Lu, Lin; Zhao, Dazhe
2017-07-20
Differential demon is a fast and efficient registration algorithm. It drives the floating image to deform using the force based on the gradient between the reference and floating image. But it will cause abnormal deformation when the driving force approaches zero,which limits its practical applications. This paper proposed an improved differential demon algorithm, which aimed to enhance the registration performance of the existing demon algorithm. Firstly, we review the original differential demon algorithm. Then, we propose an improved differential demon algorithm and the process of mathematical deduction. Finally, we use experiment to prove that the improved differential demon algorithm is effective and it can improve the accuracy of registration. We tested our method on data sets provided by Xuanwu Hospital Capital Medical University. The registration performance proved to be better than the original demon algorithm in terms of mutual information, normalized correlation coefficient, mean square error and iteration number. Experiment results demonstrate the superiority of method proposed in this paper to the original demon algorithm.
Berry, K.; Dayton, S.
1996-10-28
Citibank was using a data collection system to create a one-time-only mailing history on prospective credit card customers that was becoming dated in its time to market requirements and as such was in need of performance improvements. To compound problems with their existing system, the assurance of the quality of the data matching process was manpower intensive and needed to be automated. Analysis, design, and prototyping capabilities involving information technology were areas of expertise provided by DOE-LMES Data Systems Research and Development (DSRD) program. The goal of this project was for Data Systems Research and Development (DSRD) to analyze the current Citibank credit card offering system and suggest and prototype technology improvements that would result in faster processing with quality as good as the current system. Technologies investigated include: a high-speed network of reduced instruction set computing (RISC) processors for loosely coupled parallel processing, tightly coupled, high performance parallel processing, higher order computer languages such as `C`, fuzzy matching algorithms applied to very large data files, relational database management system, and advanced programming techniques.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Yildiz, Yesna O.; Abraham, Douglas Q.; Agaian, Sos; Panetta, Karen
2008-04-01
Automated Explosive Detection Systems (EDS) utilizing Computed Tomography (CT) performs a series of X-ray scans of the luggage being checked, then various 2D projection images of the luggage are generated from the collected data set and sometimes 3D volumetric images of the luggage are generated in addition. Automatic explosives determination as to the presence of an explosive in the luggage is determined through extensive data manipulation of the 2D and 3D image sets, the results are then forwarded to a human interface for final review. The final determination as to whether the luggage contains an explosive and needs to be searched manually is performed by trained TSA (Transportation Security Administration) screeners following an approved TSA protocol. The TSA protocol has the screeners visually inspect the projection images and the renderings of the automated explosive results from detection to determine if the luggage needs to be suspected and consequently searched. Unlike conventional X-ray systems, the user interface for EDS systems are usually designed to display one bag at a time. However, in airport environments, there is usually more than one bag being processed. Therefore, segmentation is a crucial part of higher quality screening. If the screeners have to manually manipulate (zoom, pan, separate) the image, this increases overall screening time and decreases screener efficiency. This paper presents a novel image segmentation technique that is geared towards, though not exclusive to, automated explosive detection systems. The goal of this algorithm is to correctly separate each bag image to provide a higher quality screening process while reducing the overall screening time and luggage search rates.
The Dropout Learning Algorithm.
Baldi, Pierre; Sadowski, Peter
2014-05-01
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.
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
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.
Quantum algorithm for linear regression
NASA Astrophysics Data System (ADS)
Wang, Guoming
2017-07-01
We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.
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.
Subaperture stitching algorithms: A comparison
NASA Astrophysics Data System (ADS)
Chen, Shanyong; Xue, Shuai; Wang, Guilin; Tian, Ye
2017-05-01
With the research focus of subaperture stitching interferometry shifting from flat wavefronts to aspheric ones, a variety of algorithms for stitching optimization have been proposed. We try to category and compare the algorithms in this paper by their modeling of misalignment-induced subaperture aberrations which are of low orders. A simple way is to relate the aberrations to misalignment by linear approximation with small angle assumption. But it can not exactly model the induced aberrations of aspheres. In general, the induced aberrations can be fitted to free polynomials and then removed from subaperture measurements. However, it is at the risk of mixing up the surface error and the induced aberrations. The misalignment actually introduces different terms of aberrations with certain proportions. The interrelation is then determined through analytical modeling or ray tracing. The analytical model-based algorithm and the ray tracing-based algorithm both are tedious, aperture shape-related and surface type-specific. While the configuration space-based algorithm we proposed numerically calculates the surface height change under rigid body transformation, it is generally applicable to various surface types and different aperture shapes. Simulations and experiments are presented to compare the stitching results when different algorithms are applied to null cylindrical subapertures measured with a computer generated hologram. The configuration space-based algorithm shows superior flexibility and accuracy.
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.
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.
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.
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).
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.
Do You Understand Your Algorithms?
ERIC Educational Resources Information Center
Pickreign, Jamar; Rogers, Robert
2006-01-01
This article discusses relationships between the development of an understanding of algorithms and algebraic thinking. It also provides some sample activities for middle school teachers of mathematics to help promote students' algebraic thinking. (Contains 11 figures.)
APL simulation of Grover's algorithm
NASA Astrophysics Data System (ADS)
Lipovaca, Samir
2012-02-01
Grover's algorithm is a fast quantum search algorithm. Classically, to solve the search problem for a search space of size N we need approximately N operations. Grover's algorithm offers a quadratic speedup. Since present quantum computers are not robust enough for code writing and execution, to experiment with Grover's algorithm, we will simulate it using the APL programming language. The APL programming language is especially suited for this task. For example, to compute Walsh-Hadamard transformation matrix for N quantum states via a tensor product of N Hadamard matrices we need to iterate N-1 times only one line of the code. Initial study indicates the quantum mechanical amplitude of the solution is almost independent of the search space size and rapidly reaches 0.999 values with slight variations at higher decimal places.
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)
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)
Recursive Algorithm For Linear Regression
NASA Technical Reports Server (NTRS)
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
A retrodictive stochastic simulation algorithm
Vaughan, T.G. Drummond, P.D.; Drummond, A.J.
2010-05-20
In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.
The Structure of Parallel Algorithms.
1979-08-01
parallel architectures and parallel algorithms see [Anderson and Jensen 75, Stone 75, Kung 76, Enslow 77, Kuck 77, Ramamoorthy and Li 77, Sameh 77, Heller...the Routing Time on a Parallel Computer with a Fixed Interconnection Network, In Kuck., D. J., Lawrie, D.H. and Sameh , A.H., editor, High Speed...Letters 5(4):107-112, October 1976. [ Sameh 77] Sameh , A.H. Numerical Parallel Algorithms -- A Survey. In Hifh Speed Computer and AlgorLthm Organization
Inversion Algorithms for Geophysical Problems
1987-12-16
ktdud* Sccumy Oass/Kjoon) Inversion Algorithms for Geophysical Problems (U) 12. PERSONAL AUTHOR(S) Lanzano, Paolo 13 «. TYPE OF REPORT Final 13b...spectral density. 20. DISTRIBUTION/AVAILABILITY OF ABSTRACT 13 UNCLASSIFIED/UNLIMITED D SAME AS RPT n OTIC USERS 22a. NAME OF RESPONSIBLE...Research Laboratory ’^^ SSZ ’.Washington. DC 20375-5000 NRLrMemorandum Report-6138 Inversion Algorithms for Geophysical Problems p. LANZANO Space
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
Label Ranking Algorithms: A Survey
NASA Astrophysics Data System (ADS)
Vembu, Shankar; Gärtner, Thomas
Label ranking is a complex prediction task where the goal is to map instances to a total order over a finite set of predefined labels. An interesting aspect of this problem is that it subsumes several supervised learning problems, such as multiclass prediction, multilabel classification, and hierarchical classification. Unsurprisingly, there exists a plethora of label ranking algorithms in the literature due, in part, to this versatile nature of the problem. In this paper, we survey these algorithms.
Programming the gradient projection algorithm
NASA Technical Reports Server (NTRS)
Hargrove, A.
1983-01-01
The gradient projection method of numerical optimization which is applied to problems having linear constraints but nonlinear objective functions is described and analyzed. The algorithm is found to be efficient and thorough for small systems, but requires the addition of auxiliary methods and programming for large scale systems with severe nonlinearities. In order to verify the theoretical results a digital computer is used to simulate the algorithm.
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.
Topics in Geodetic Algorithm Research.
1986-08-15
given. These include classical integral evaluation methods, least-squares collocation, 4ASC’r GEOFAST technique, and Fourier transform methods. Also...8217 ..... ...... 10,’ so ~10 - 10 FREOUNCY m Figure 1-2 Research on Geodetic Algorithms chapter introduces the classical integral evaluation methods, as well as least... integral evaluation methods, least-squares colloca- tion, TASC’s GEOFAST algorithm, and other Fourier transform and frequency domain approaches. 2.1
Extrapolation of acenocoumarol pharmacogenetic algorithms.
Jiménez-Varo, Enrique; Cañadas-Garre, Marisa; Garcés-Robles, Víctor; Gutiérrez-Pimentel, María José; Calleja-Hernández, Miguel Ángel
2015-11-01
Acenocoumarol (ACN) has a narrow therapeutic range that is especially difficult to control at the start of its administration. Various dosing pharmacogenetic-guided dosing algorithms have been developed, but further work on their external validation is required. The aim of this study was to evaluate the extrapolation of pharmacogenetic algorithms for ACN as an alternative to the development of a specific algorithm for a given population. The predictive performance, deviation, accuracy, and clinical significance of five pharmacogenetic algorithms (EU-PACT, Borobia, Rathore, Markatos, Krishna Kumar) were compared in 189 stable ACN patients representing all indications for anticoagulant treatment. The correlation between the dose predictions of the five pharmacogenetic models ranged from 7.7 to 70.6% and the percentage of patients with a correct prediction (deviation ≤20% from actual ACN dose) ranged from 5.9 to 40.7%. EU-PACT and Borobia pharmacogenetic dosing algorithms were the most accurate in our setting and evidenced the best clinical performance. Among the five models studied, the EU-PACT and Borobia pharmacogenetic dosing algorithms demonstrated the best potential for extrapolation. Copyright © 2015 Elsevier Inc. All rights reserved.
Multimodal Estimation of Distribution Algorithms.
Yang, Qiang; Chen, Wei-Neng; Li, Yun; Chen, C L Philip; Xu, Xiang-Min; Zhang, Jun
2016-02-15
Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.
Rotational Invariant Dimensionality Reduction Algorithms.
Lai, Zhihui; Xu, Yong; Yang, Jian; Shen, Linlin; Zhang, David
2016-06-30
A common intrinsic limitation of the traditional subspace learning methods is the sensitivity to the outliers and the image variations of the object since they use the L₂ norm as the metric. In this paper, a series of methods based on the L₂,₁-norm are proposed for linear dimensionality reduction. Since the L₂,₁-norm based objective function is robust to the image variations, the proposed algorithms can perform robust image feature extraction for classification. We use different ideas to design different algorithms and obtain a unified rotational invariant (RI) dimensionality reduction framework, which extends the well-known graph embedding algorithm framework to a more generalized form. We provide the comprehensive analyses to show the essential properties of the proposed algorithm framework. This paper indicates that the optimization problems have global optimal solutions when all the orthogonal projections of the data space are computed and used. Experimental results on popular image datasets indicate that the proposed RI dimensionality reduction algorithms can obtain competitive performance compared with the previous L₂ norm based subspace learning algorithms.
Multithreaded Algorithms for Graph Coloring
Catalyurek, Umit V.; Feo, John T.; Gebremedhin, Assefaw H.; Halappanavar, Mahantesh; Pothen, Alex
2012-10-21
Graph algorithms are challenging to parallelize when high performance and scalability are primary goals. Low concurrency, poor data locality, irregular access pattern, and high data access to computation ratio are among the chief reasons for the challenge. The performance implication of these features is exasperated on distributed memory machines. More success is being achieved on shared-memory, multi-core architectures supporting multithreading. We consider a prototypical graph problem, coloring, and show how a greedy algorithm for solving it can be e*ectively parallelized on multithreaded architectures. We present in particular two di*erent parallel algorithms. The first relies on speculation and iteration, and is suitable for any shared-memory, multithreaded system. The second uses data ow principles and is targeted at the massively multithreaded Cray XMT system. We benchmark the algorithms on three di*erent platforms and demonstrate scalable runtime performance. In terms of quality of solution, both algorithms use nearly the same number of colors as the serial algorithm.
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.
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
An Extended Bayesian-FBP Algorithm.
Zeng, Gengsheng L; Divkovic, Zeljko
2016-02-01
Recently we developed a Bayesian-FBP (Filtered Backprojection) algorithm for CT image reconstruction. This algorithm is also referred to as the FBP-MAP (FBP Maximum a Posteriori) algorithm. This non-iterative Bayesian algorithm has been applied to real-time MRI, in which the k-space is under-sampled. This current paper investigates the possibility to extend this Bayesian-FBP algorithm by introducing more controlling parameters. Thus, our original Bayesian-FBP algorithm became a special case of the extended Bayesian-FBP algorithm. A cardiac patient data set is used in this paper to evaluate the extended Bayesian-FBP algorithm, and the result from a well-establish iterative algorithm with L1-norms is used as the gold standard. If the parameters are selected properly, the extended Bayesian-FBP algorithm can outperform the original Bayesian-FBP algorithm.
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)).
Fourier Lucas-Kanade algorithm.
Lucey, Simon; Navarathna, Rajitha; Ashraf, Ahmed Bilal; Sridharan, Sridha
2013-06-01
In this paper, we propose a framework for both gradient descent image and object alignment in the Fourier domain. Our method centers upon the classical Lucas & Kanade (LK) algorithm where we represent the source and template/model in the complex 2D Fourier domain rather than in the spatial 2D domain. We refer to our approach as the Fourier LK (FLK) algorithm. The FLK formulation is advantageous when one preprocesses the source image and template/model with a bank of filters (e.g., oriented edges, Gabor, etc.) as 1) it can handle substantial illumination variations, 2) the inefficient preprocessing filter bank step can be subsumed within the FLK algorithm as a sparse diagonal weighting matrix, 3) unlike traditional LK, the computational cost is invariant to the number of filters and as a result is far more efficient, and 4) this approach can be extended to the Inverse Compositional (IC) form of the LK algorithm where nearly all steps (including Fourier transform and filter bank preprocessing) can be precomputed, leading to an extremely efficient and robust approach to gradient descent image matching. Further, these computational savings translate to nonrigid object alignment tasks that are considered extensions of the LK algorithm, such as those found in Active Appearance Models (AAMs).
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.
Metal detector depth estimation algorithms
NASA Astrophysics Data System (ADS)
Marble, Jay; McMichael, Ian
2009-05-01
This paper looks at depth estimation techniques using electromagnetic induction (EMI) metal detectors. Four algorithms are considered. The first utilizes a vertical gradient sensor configuration. The second is a dual frequency approach. The third makes use of dipole and quadrapole receiver configurations. The fourth looks at coils of different sizes. Each algorithm is described along with its associated sensor. Two figures of merit ultimately define algorithm/sensor performance. The first is the depth of penetration obtainable. (That is, the maximum detection depth obtainable.) This describes the performance of the method to achieve detection of deep targets. The second is the achievable statistical depth resolution. This resolution describes the precision with which depth can be estimated. In this paper depth of penetration and statistical depth resolution are qualitatively determined for each sensor/algorithm. A scientific method is used to make these assessments. A field test was conducted using 2 lanes with emplaced UXO. The first lane contains 155 shells at increasing depths from 0" to 48". The second is more realistic containing objects of varying size. The first lane is used for algorithm training purposes, while the second is used for testing. The metal detectors used in this study are the: Geonics EM61, Geophex GEM5, Minelab STMR II, and the Vallon VMV16.
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.
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
Conflict-Aware Scheduling Algorithm
NASA Technical Reports Server (NTRS)
Wang, Yeou-Fang; Borden, Chester
2006-01-01
conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.
Multipath Binomial Congestion Control Algorithms
NASA Astrophysics Data System (ADS)
Le, Tuan Anh; Hong, Choong Seon; Lee, Sungwon
Nowadays portable devices with multiple wireless interfaces and using multimedia services are becoming more popular on the Internet. This paper describes a family of multipath binomial congestion control algorithms for audio/video streaming, where a low variant of transmission rate is important. We extend the fluid model of binomial algorithms for single-path transmission to support the concurrent transmission of packets across multiple paths. We focus on the extension of two particular algorithms, SQRT and IIAD, for multiple paths, called MPSQRT and MPIIAD, respectively. Additionally, we apply the design technique (using the multipath fluid model) for multipath TCP (MPTCP) into the extension of SQRT and IIAD, called fbMPSQRT and fbMPIIAD, respectively. Both two approaches ensure that multipath binomial congestion control algorithms achieve load-balancing, throughput improvement, and fairness to single-path binomial algorithms at shared bottlenecks. Through the simulations and comparison with the uncoordinated protocols MPSQRT/MPIIAD, fbMPSQRT/fbMPIIAD and MPTCP, we find that our extended multipath transport protocols can preserve lower latency and transmission rate variance than MPTCP, fairly share with single-path SQRT/IIAD, MPTCP and TCP, and also can achieve throughput improvements and load-balancing equivalent to those of MPTCP under various scenarios and network conditions.
Fast Algorithms for Exact Exchange
NASA Astrophysics Data System (ADS)
Manzer, Samuel Fenton
This thesis describes several new theoretical developments that facilitate the computation of the exact exchange energy, a vital component of accurate molecular simulations. The primary technique on which these developments are based is the resolution of the identity approximation, particularly the pair atomic resolution of the identity approximation (PARI). We prove that computation of exact exchange using the PARI approximation is variationally stable, and provide benchmarks of the performance and accuracy of our implementation. We then show that the most commonly used SCF convergence acceleration algorithm, DIIS, enables the design of a new fast exchange algorithm that we designate as occ-RI-K. Next, we combine the preceding occ-RI-K algorithm with the PARI approximation to create a linear-scaling exact exchange algorithm for the specific case of large weakly-interacting systems. Finally, we discuss our development of a high-level, object-oriented software library for block-sparse tensor operations. This library provides the underlying implementation for all of the algorithms discussed in this thesis.
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.
Parallel job-scheduling algorithms
Rodger, S.H.
1989-01-01
In this thesis, we consider solving job scheduling problems on the CREW PRAM model. We show how to adapt Cole's pipeline merge technique to yield several efficient parallel algorithms for a number of job scheduling problems and one optimal parallel algorithm for the following job scheduling problem: Given a set of n jobs defined by release times, deadlines and processing times, find a schedule that minimizes the maximum lateness of the jobs and allows preemption when the jobs are scheduled to run on one machine. In addition, we present the first NC algorithm for the following job scheduling problem: Given a set of n jobs defined by release times, deadlines and unit processing times, determine if there is a schedule of jobs on one machine, and calculate the schedule if it exists. We identify the notion of a canonical schedule, which is the type of schedule our algorithm computes if there is a schedule. Our algorithm runs in O((log n){sup 2}) time and uses O(n{sup 2}k{sup 2}) processors, where k is the minimum number of distinct offsets of release times or deadlines.
Model Based Filtered Backprojection Algorithm: A Tutorial
2014-01-01
Purpose People have been wandering for a long time whether a filtered backprojection (FBP) algorithm is able to incorporate measurement noise in image reconstruction. The purpose of this tutorial is to develop such an FBP algorithm that is able to minimize an objective function with an embedded noise model. Methods An objective function is first set up to model measurement noise and to enforce some constraints so that the resultant image has some pre-specified properties. An iterative algorithm is used to minimize the objective function, and then the result of the iterative algorithm is converted into the Fourier domain, which in turn leads to an FBP algorithm. The model based FBP algorithm is almost the same as the conventional FBP algorithm, except for the filtering step. Results The model based FBP algorithm has been applied to low-dose x-ray CT, nuclear medicine, and real-time MRI applications. Compared with the conventional FBP algorithm, the model based FBP algorithm is more effective in reducing noise. Even though an iterative algorithm can achieve the same noise-reducing performance, the model based FBP algorithm is much more computationally efficient. Conclusions The model based FBP algorithm is an efficient and effective image reconstruction tool. In many applications, it can replace the state-of-the-art iterative algorithms, which usually have a heavy computational cost. The model based FBP algorithm is linear and it has advantages over a nonlinear iterative algorithm in parametric image reconstruction and noise analysis. PMID:25574421
Using Alternative Multiplication Algorithms to "Offload" Cognition
ERIC Educational Resources Information Center
Jazby, Dan; Pearn, Cath
2015-01-01
When viewed through a lens of embedded cognition, algorithms may enable aspects of the cognitive work of multi-digit multiplication to be "offloaded" to the environmental structure created by an algorithm. This study analyses four multiplication algorithms by viewing different algorithms as enabling cognitive work to be distributed…
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…
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…
Selecting optimum algorithms for image processing
NASA Technical Reports Server (NTRS)
Jaroe, R. R.; Hodges, J.; Atkinson, R. E.; Gaggini, B.; Callas, L.; Peterson, J.
1981-01-01
Collection of registration, compression, and classification algorithms allows users to evaluate approaches and select best one for particular application. Program includes six registration algorithms, six compression algorithms, and two classification algorithms. Package also includes routines for evaluating effects of processing on image data. Collection is written in FORTRAN IV for batch execution.
Genetic-based unit commitment algorithm
Maifeld, T.T.; Sheble, G.B.
1996-08-01
This paper presents a new unit commitment scheduling algorithm. The proposed algorithm consist of using a genetic algorithm with domain specific mutation operators. The proposed algorithm can easily accommodate any constraint that can be true costed. Robustness of the proposed algorithm is demonstrated by comparison to a Lagrangian relaxation unit commitment algorithm on three different utilities. Results show the proposed algorithm finds good unit commitment schedules in a reasonable amount of computation time. Included in the appendix is an explanation of the true costing approach.
Old And New Algorithms For Toeplitz Systems
NASA Astrophysics Data System (ADS)
Brent, Richard P.
1988-02-01
Toeplitz linear systems and Toeplitz least squares problems commonly arise in digital signal processing. In this paper we survey some old, "well known" algorithms and some recent algorithms for solving these problems. We concentrate our attention on algorithms which can be implemented efficiently on a variety of parallel machines (including pipelined vector processors and systolic arrays). We distinguish between algorithms which require inner products, and algorithms which avoid inner products, and thus are better suited to parallel implementation on some parallel architectures. Finally, we mention some "asymptotically fast" 0(n(log n)2) algorithms and compare them with 0(n2) algorithms.
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.
Learning with the ratchet algorithm.
Hush, D. R.; Scovel, James C.
2003-01-01
This paper presents a randomized algorithm called Ratchet that asymptotically minimizes (with probability 1) functions that satisfy a positive-linear-dependent (PLD) property. We establish the PLD property and a corresponding realization of Ratchet for a generalized loss criterion for both linear machines and linear classifiers. We describe several learning criteria that can be obtained as special cases of this generalized loss criterion, e.g. classification error, classification loss and weighted classification error. We also establish the PLD property and a corresponding realization of Ratchet for the Neyman-Pearson criterion for linear classifiers. Finally we show how, for linear classifiers, the Ratchet algorithm can be derived as a modification of the Pocket algorithm.
Next Generation Suspension Dynamics Algorithms
Schunk, Peter Randall; Higdon, Jonathon; Chen, Steven
2014-12-01
This research project has the objective to extend the range of application, improve the efficiency and conduct simulations with the Fast Lubrication Dynamics (FLD) algorithm for concentrated particle suspensions in a Newtonian fluid solvent. The research involves a combination of mathematical development, new computational algorithms, and application to processing flows of relevance in materials processing. The mathematical developments clarify the underlying theory, facilitate verification against classic monographs in the field and provide the framework for a novel parallel implementation optimized for an OpenMP shared memory environment. The project considered application to consolidation flows of major interest in high throughput materials processing and identified hitherto unforeseen challenges in the use of FLD in these applications. Extensions to the algorithm have been developed to improve its accuracy in these applications.
Optimizing connected component labeling algorithms
Wu, Kesheng; Otoo, Ekow; Shoshani, Arie
2005-01-16
This paper presents two new strategies that can be used to greatly improve the speed of connected component labeling algorithms. To assign a label to a new object, most connected component labeling algorithms use a scanning step that examines some of its neighbors. The first strategy exploits the dependencies among them to reduce the number of neighbors examined. When considering 8-connected components in a 2D image, this can reduce the number of neighbors examined from four to one in many cases. The second strategy uses an array to store the equivalence information among the labels. This replaces the pointer based rooted trees used to store the same equivalence information. It reduces the memory required and also produces consecutive final labels. Using an array instead of the pointer based rooted trees speeds up the connected component labeling algorithms by a factor of 5 {approx} 100 in our tests on random binary images.
NASA Astrophysics Data System (ADS)
Lyu, Shanxiang; Ling, Cong
2017-09-01
There exists two issues among popular lattice reduction (LR) algorithms that should cause our concern. The first one is Korkine Zolotarev (KZ) and Lenstra Lenstra Lovasz (LLL) algorithms may increase the lengths of basis vectors. The other is KZ reduction suffers much worse performance than Minkowski reduction in terms of providing short basis vectors, despite its superior theoretical upper bounds. To address these limitations, we improve the size reduction steps in KZ and LLL to set up two new efficient algorithms, referred to as boosted KZ and LLL, for solving the shortest basis problem (SBP) with exponential and polynomial complexity, respectively. Both of them offer better actual performance than their classic counterparts, and the performance bounds for KZ are also improved. We apply them to designing integer-forcing (IF) linear receivers for multi-input multi-output (MIMO) communications. Our simulations confirm their rate and complexity advantages.
Optimizing connected component labeling algorithms
NASA Astrophysics Data System (ADS)
Wu, Kesheng; Otoo, Ekow; Shoshani, Arie
2005-04-01
This paper presents two new strategies that can be used to greatly improve the speed of connected component labeling algorithms. To assign a label to a new object, most connected component labeling algorithms use a scanning step that examines some of its neighbors. The first strategy exploits the dependencies among them to reduce the number of neighbors examined. When considering 8-connected components in a 2D image, this can reduce the number of neighbors examined from four to one in many cases. The second strategy uses an array to store the equivalence information among the labels. This replaces the pointer based rooted trees used to store the same equivalence information. It reduces the memory required and also produces consecutive final labels. Using an array instead of the pointer based rooted trees speeds up the connected component labeling algorithms by a factor of 5 ~ 100 in our tests on random binary images.
The Dynamic Ordered Dither Algorithm
NASA Astrophysics Data System (ADS)
Crinon, R. J.; Jenq, Y. C.
1986-12-01
Ordered dither is a popular method for printing/displaying continuous tone images on bi-level devices such as laser printers, ink-jet printers and liquid crystal flat panels; the success of this algorithm comes from its simplicity and its non recursive nature. A major contention about this technique is its poor performance for rendering sharp edges. To alleviate this problem, we propose a new half-toning method called the dynamic ordered dither algorithm; it is an adaptive scheme based on the standard ordered dither operation preceded by an adaptive high pass filter. The dynamic ordered dither algorithm yields a far better edge rendition while keeping the good properties of the standard dithering process, namely the preservation of the object location, the good color reproduction and the possibility to use parallel archi-tectures for processing pictures in real time.
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.
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.
Deceptiveness and genetic algorithm dynamics
Liepins, G.E. ); Vose, M.D. )
1990-01-01
We address deceptiveness, one of at least four reasons genetic algorithms can fail to converge to function optima. We construct fully deceptive functions and other functions of intermediate deceptiveness. For the fully deceptive functions of our construction, we generate linear transformations that induce changes of representation to render the functions fully easy. We further model genetic algorithm selection recombination as the interleaving of linear and quadratic operators. Spectral analysis of the underlying matrices allows us to draw preliminary conclusions about fixed points and their stability. We also obtain an explicit formula relating the nonuniform Walsh transform to the dynamics of genetic search. 21 refs.
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.
Enhanced variants of IDE algorithm
NASA Astrophysics Data System (ADS)
Bujok, Petr
2017-07-01
The performance of a new mechanism applied on a differential evolution algorithm with an individual-dependent mechanism (IDE) is studied experimentally. Three new IDE variants are proposed and compared with the original IDE variant. The performance of all studied algorithms was compared on each problem of CEC 2015 test suite. The newly proposed IDE variants mostly outperformed the original IDE variant significantly. The results show that the best results are for the newly proposed IDE variant with an enhanced mutation scheme and IDE with the control of the population diversity.
Adaptive-feedback control algorithm.
Huang, Debin
2006-06-01
This paper is motivated by giving the detailed proofs and some interesting remarks on the results the author obtained in a series of papers [Phys. Rev. Lett. 93, 214101 (2004); Phys. Rev. E 71, 037203 (2005); 69, 067201 (2004)], where an adaptive-feedback algorithm was proposed to effectively stabilize and synchronize chaotic systems. This note proves in detail the strictness of this algorithm from the viewpoint of mathematics, and gives some interesting remarks for its potential applications to chaos control & synchronization. In addition, a significant comment on synchronization-based parameter estimation is given, which shows some techniques proposed in literature less strict and ineffective in some cases.
An algorithm for haplotype analysis
Lin, Shili; Speed, T.P.
1997-12-01
This paper proposes an algorithm for haplotype analysis based on a Monte Carlo method. Haplotype configurations are generated according to the distribution of joint haplotypes of individuals in a pedigree given their phenotype data, via a Markov chain Monte Carlo algorithm. The haplotype configuration which maximizes this conditional probability distribution can thus be estimated. In addition, the set of haplotype configurations with relatively high probabilities can also be estimated as possible alternatives to the most probable one. This flexibility enables geneticists to choose the haplotype configurations which are most reasonable to them, allowing them to include their knowledge of the data under analysis. 18 refs., 2 figs., 1 tab.
Gossip algorithms in quantum networks
NASA Astrophysics Data System (ADS)
Siomau, Michael
2017-01-01
Gossip algorithms is a common term to describe protocols for unreliable information dissemination in natural networks, which are not optimally designed for efficient communication between network entities. We consider application of gossip algorithms to quantum networks and show that any quantum network can be updated to optimal configuration with local operations and classical communication. This allows to speed-up - in the best case exponentially - the quantum information dissemination. Irrespective of the initial configuration of the quantum network, the update requiters at most polynomial number of local operations and classical communication.
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.
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.
Aerocapture Guidance Algorithm Comparison Campaign
NASA Technical Reports Server (NTRS)
Rousseau, Stephane; Perot, Etienne; Graves, Claude; Masciarelli, James P.; Queen, Eric
2002-01-01
The aerocapture is a promising technique for the future human interplanetary missions. The Mars Sample Return was initially based on an insertion by aerocapture. A CNES orbiter Mars Premier was developed to demonstrate this concept. Mainly due to budget constraints, the aerocapture was cancelled for the French orbiter. A lot of studies were achieved during the three last years to develop and test different guidance algorithms (APC, EC, TPC, NPC). This work was shared between CNES and NASA, with a fruitful joint working group. To finish this study an evaluation campaign has been performed to test the different algorithms. The objective was to assess the robustness, accuracy, capability to limit the load, and the complexity of each algorithm. A simulation campaign has been specified and performed by CNES, with a similar activity on the NASA side to confirm the CNES results. This evaluation has demonstrated that the numerical guidance principal is not competitive compared to the analytical concepts. All the other algorithms are well adapted to guaranty the success of the aerocapture. The TPC appears to be the more robust, the APC the more accurate, and the EC appears to be a good compromise.
SMAP's Radar OBP Algorithm Development
NASA Technical Reports Server (NTRS)
Le, Charles; Spencer, Michael W.; Veilleux, Louise; Chan, Samuel; He, Yutao; Zheng, Jason; Nguyen, Kayla
2009-01-01
An approach for algorithm specifications and development is described for SMAP's radar onboard processor with multi-stage demodulation and decimation bandpass digital filter. Point target simulation is used to verify and validate the filter design with the usual radar performance parameters. Preliminary FPGA implementation is also discussed.
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…
Genetic Algorithms: A gentle introduction
Jong, K.D.
1994-12-31
Information is presented on genetic algorithms in outline form. The following topics are discussed: how are new samples generated, a genotypic viewpoint, a phenotypic viewpoint, an optimization viewpoint, an intuitive view, parameter optimization problems, evolving production rates, genetic programming, GAs and NNs, formal analysis, Lemmas and theorems, discrete Walsh transforms, deceptive problems, Markov chain analysis, and PAC learning analysis.
Fission Reaction Event Yield Algorithm
Hagmann, Christian; Verbeke, Jerome; Vogt, Ramona; Roundrup, Jorgen
2016-05-31
FREYA (Fission Reaction Event Yield Algorithm) is a code that simulated the decay of a fissionable nucleus at specified excitation energy. In its present form, FREYA models spontaneous fission and neutron-induced fission up to 20 MeV. It includes the possibility of neutron emission from the nuclear prior to its fussion (nth chance fission).
The minimal time detection algorithm
NASA Technical Reports Server (NTRS)
Kim, Sungwan
1995-01-01
An aerospace vehicle may operate throughout a wide range of flight environmental conditions that affect its dynamic characteristics. Even when the control design incorporates a degree of robustness, system parameters may drift enough to cause its performance to degrade below an acceptable level. The object of this paper is to develop a change detection algorithm so that we can build a highly adaptive control system applicable to aircraft systems. The idea is to detect system changes with minimal time delay. The algorithm developed is called Minimal Time-Change Detection Algorithm (MT-CDA) which detects the instant of change as quickly as possible with false-alarm probability below a certain specified level. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well as theory indicates though there is a difficulty in deciding the exact amount of change in some situations. One of MT-CDA distinguishing properties is that detection delay of MT-CDA is superior to that of Whiteness Test.
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
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.
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…
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…
Listless zerotree image compression algorithm
NASA Astrophysics Data System (ADS)
Lian, Jing; Wang, Ke
2006-09-01
In this paper, an improved zerotree structure and a new coding procedure are adopted, which improve the reconstructed image qualities. Moreover, the lists in SPIHT are replaced by flag maps, and lifting scheme is adopted to realize wavelet transform, which lowers the memory requirements and speeds up the coding process. Experimental results show that the algorithm is more effective and efficient compared with SPIHT.
Cognitive Algorithms for Signal Processing
2011-03-18
63] L. I. Perlovsky and R. Kozma. Eds. Neurodynamics of Higher-Level Cognition and Consciousness. Heidelberg, Germany: Springer-Verlag, 2007. [64...AFRL-RY-HS-TR-2011-0013 ________________________________________________________________________ Cognitive Algorithms for Signal Processing...in more details in [46]. ..................................... 16 1 Abstract Processes in the mind: perception, cognition
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.
Tracking algorithms for multiagent systems.
Meng, Deyuan; Jia, Yingmin; Du, Junping; Yu, Fashan
2013-10-01
This paper is devoted to the consensus tracking issue on multiagent systems. Instead of enabling the networked agents to reach an agreement asymptotically as the time tends to infinity, the consensus tracking between agents is considered to be derived on a finite time interval as accurately as possible. We thus propose a learning algorithm with a gain operator to be determined. If the gain operator is designed in the form of a polynomial expression, a necessary and sufficient condition is obtained for the networked agents to accomplish the consensus tracking objective, regardless of the relative degree of the system model of agents. Moreover, the H∞ analysis approach is introduced to help establish conditions in terms of linear matrix inequalities (LMIs) such that the resulting processes of the presented learning algorithm can be guaranteed to monotonically converge in an iterative manner. The established LMI conditions can also enable the iterative learning processes to converge with an exponentially fast speed. In addition, we extend the learning algorithm to address the relative formation problem for multiagent systems. Numerical simulations are performed to demonstrate the effectiveness of learning algorithms in achieving both consensus tracking and relative formation objectives for the networked agents.
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.
Randomized approximate nearest neighbors algorithm
Jones, Peter Wilcox; Osipov, Andrei; Rokhlin, Vladimir
2011-01-01
We present a randomized algorithm for the approximate nearest neighbor problem in d-dimensional Euclidean space. Given N points {xj} in , the algorithm attempts to find k nearest neighbors for each of xj, 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·k2·(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 {xj} for an arbitrary point . 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 {xj} and illustrate its performance via several numerical examples. PMID:21885738
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…
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…
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. © The Author(s) 2015.
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…
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.
Algorithms, modelling and VO₂ kinetics.
Capelli, Carlo; Carlo, Capelli; Cautero, Michela; Michela, Cautero; Pogliaghi, Silvia; Silvia, Pogliaghi
2011-03-01
This article summarises the pros and cons of different algorithms developed for estimating breath-by-breath (B-by-B) alveolar O(2) transfer (VO 2A) in humans. VO 2A is the difference between O(2) uptake at the mouth and changes in alveolar O(2) stores (∆ VO(2s)), which for any given breath, are equal to the alveolar volume change at constant FAO2/FAiO2 ∆VAi plus the O(2) alveolar fraction change at constant volume [V Ai-1(F Ai - F Ai-1) O2, where V (Ai-1) is the alveolar volume at the beginning of a breath. Therefore, VO 2A can be determined B-by-B provided that V (Ai-1) is: (a) set equal to the subject's functional residual capacity (algorithm of Auchincloss, A) or to zero; (b) measured (optoelectronic plethysmography, OEP); (c) selected according to a procedure that minimises B-by-B variability (algorithm of Busso and Robbins, BR). Alternatively, the respiratory cycle can be redefined as the time between equal FO(2) in two subsequent breaths (algorithm of Grønlund, G), making any assumption of V (Ai-1) unnecessary. All the above methods allow an unbiased estimate of VO2 at steady state, albeit with different precision. Yet the algorithms "per se" affect the parameters describing the B-by-B kinetics during exercise transitions. Among these approaches, BR and G, by increasing the signal-to-noise ratio of the measurements, reduce the number of exercise repetitions necessary to study VO2 kinetics, compared to A approach. OEP and G (though technically challenging and conceptually still debated), thanks to their ability to track ∆VO(2s) changes during the early phase of exercise transitions, appear rather promising for investigating B-by-B gas exchange.
Genetic algorithms for protein threading.
Yadgari, J; Amir, A; Unger, R
1998-01-01
Despite many years of efforts, a direct prediction of protein structure from sequence is still not possible. As a result, in the last few years researchers have started to address the "inverse folding problem": Identifying and aligning a sequence to the fold with which it is most compatible, a process known as "threading". In two meetings in which protein folding predictions were objectively evaluated, it became clear that threading as a concept promises a real breakthrough, but that much improvement is still needed in the technique itself. Threading is a NP-hard problem, and thus no general polynomial solution can be expected. Still a practical approach with demonstrated ability to find optimal solutions in many cases, and acceptable solutions in other cases, is needed. We applied the technique of Genetic Algorithms in order to significantly improve the ability of threading algorithms to find the optimal alignment of a sequence to a structure, i.e. the alignment with the minimum free energy. A major progress reported here is the design of a representation of the threading alignment as a string of fixed length. With this representation validation of alignments and genetic operators are effectively implemented. Appropriate data structure and parameters have been selected. It is shown that Genetic Algorithm threading is effective and is able to find the optimal alignment in a few test cases. Furthermore, the described algorithm is shown to perform well even without pre-definition of core elements. Existing threading methods are dependent on such constraints to make their calculations feasible. But the concept of core elements is inherently arbitrary and should be avoided if possible. While a rigorous proof is hard to submit yet an, we present indications that indeed Genetic Algorithm threading is capable of finding consistently good solutions of full alignments in search spaces of size up to 10(70).
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.
Birkhoffian symplectic algorithms derived from Hamiltonian symplectic algorithms
NASA Astrophysics Data System (ADS)
Xin-Lei, Kong; Hui-Bin, Wu; Feng-Xiang, Mei
2016-01-01
In this paper, we focus on the construction of structure preserving algorithms for Birkhoffian systems, based on existing symplectic schemes for the Hamiltonian equations. The key of the method is to seek an invertible transformation which drives the Birkhoffian equations reduce to the Hamiltonian equations. When there exists such a transformation, applying the corresponding inverse map to symplectic discretization of the Hamiltonian equations, then resulting difference schemes are verified to be Birkhoffian symplectic for the original Birkhoffian equations. To illustrate the operation process of the method, we construct several desirable algorithms for the linear damped oscillator and the single pendulum with linear dissipation respectively. All of them exhibit excellent numerical behavior, especially in preserving conserved quantities. Project supported by the National Natural Science Foundation of China (Grant No. 11272050), the Excellent Young Teachers Program of North China University of Technology (Grant No. XN132), and the Construction Plan for Innovative Research Team of North China University of Technology (Grant No. XN129).
Treatment algorithms in refractory partial epilepsy.
Jobst, Barbara C
2009-09-01
An algorithm is a "step-by-step procedure for solving a problem or accomplishing some end....in a finite number of steps." (Merriam-Webster, 2009). Medical algorithms are decision trees to help with diagnostic and therapeutic decisions. For the treatment of epilepsy there is no generally accepted treatment algorithm, as individual epilepsy centers follow different diagnostic and therapeutic guidelines. This article presents two algorithms to guide decisions in the treatment of refractory partial epilepsy. The treatment algorithm describes a stepwise diagnostic and therapeutic approach to intractable medial temporal and neocortical epilepsy. The surgical algorithm guides decisions in the surgical treatment of neocortical epilepsy.
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.
On Quantum Algorithm for Exptime Problem
NASA Astrophysics Data System (ADS)
Iriyama, S.; Ohya, M.
2011-01-01
There exists a quantum algorithm with chaos dynamics solving an NP-complete problem in polynomial time, called OMV SAT algorithm. The language class EXPTIME is larger class than NP, there is no classical algorithm to solve it in polynomial time. In this paper we propose a quantum algorithm for one of the problems in EXPTIME, Pebble Game, and compare the computational complexity of it with the classical one. We show that a quantum algorithm with Oracle solves it in polynomial time while a classical algorithm with same Oracle does in exponential time.
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.
Space complexity of estimation of distribution algorithms.
Gao, Yong; Culberson, Joseph
2005-01-01
In this paper, we investigate the space complexity of the Estimation of Distribution Algorithms (EDAs), a class of sampling-based variants of the genetic algorithm. By analyzing the nature of EDAs, we identify criteria that characterize the space complexity of two typical implementation schemes of EDAs, the factorized distribution algorithm and Bayesian network-based algorithms. Using random additive functions as the prototype, we prove that the space complexity of the factorized distribution algorithm and Bayesian network-based algorithms is exponential in the problem size even if the optimization problem has a very sparse interaction structure.
Algorithmic methods in diffraction microscopy
NASA Astrophysics Data System (ADS)
Thibault, Pierre
Recent diffraction imaging techniques use properties of coherent sources (most notably x-rays and electrons) to transfer a portion of the imaging task to computer algorithms. "Diffraction microscopy" is a method which consists in reconstructing the image of a specimen from its diffraction pattern. Because only the amplitude of a wavefield incident on a detector is measured, reconstruction of the image entails to recovering the lost phases. This extension of the 'phase problem" commonly met in crystallography is solved only if additional information is available. The main topic of this thesis is the development of algorithmic techniques in diffraction microscopy. In addition to introducing new methods, it is meant to be a review of the algorithmic aspects of the field of diffractive imaging. An overview of the scattering approximations used in the interpretation of diffraction datasets is first given, as well as a numerical propagation tool useful in conditions where known approximations fail. Concepts central to diffraction microscopy---such as oversampling---are then introduced and other similar imaging techniques described. A complete description of iterative reconstruction algorithms follows, with a special emphasis on the difference map, the algorithm used in this thesis. The formalism, based on constraint sets and projection onto these sets, is then defined and explained. Simple projections commonly used in diffraction imaging are then described. The various ways experimental realities can affect reconstruction methods will then be enumerated. Among the diverse sources of algorithmic difficulties, one finds that noise, missing data and partial coherence are typically the most important. Other related difficulties discussed are the detrimental effects of crystalline domains in a specimen, and the convergence problems occurring when the support of a complex-valued specimen is not well known. The last part of this thesis presents reconstruction results; an
Innovations in Lattice QCD Algorithms
Konstantinos Orginos
2006-06-25
Lattice QCD calculations demand a substantial amount of computing power in order to achieve the high precision results needed to better understand the nature of strong interactions, assist experiment to discover new physics, and predict the behavior of a diverse set of physical systems ranging from the proton itself to astrophysical objects such as neutron stars. However, computer power alone is clearly not enough to tackle the calculations we need to be doing today. A steady stream of recent algorithmic developments has made an important impact on the kinds of calculations we can currently perform. In this talk I am reviewing these algorithms and their impact on the nature of lattice QCD calculations performed today.
Algorithms for Lightweight Key Exchange.
Alvarez, Rafael; Caballero-Gil, Cándido; Santonja, Juan; Zamora, Antonio
2017-06-27
Public-key cryptography is too slow for general purpose encryption, with most applications limiting its use as much as possible. Some secure protocols, especially those that enable forward secrecy, make a much heavier use of public-key cryptography, increasing the demand for lightweight cryptosystems that can be implemented in low powered or mobile devices. This performance requirements are even more significant in critical infrastructure and emergency scenarios where peer-to-peer networks are deployed for increased availability and resiliency. We benchmark several public-key key-exchange algorithms, determining those that are better for the requirements of critical infrastructure and emergency applications and propose a security framework based on these algorithms and study its application to decentralized node or sensor networks.
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.
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.
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.
Algorithms for intravenous insulin delivery.
Braithwaite, Susan S; Clement, Stephen
2008-08-01
This review aims to classify algorithms for intravenous insulin infusion according to design. Essential input data include the current blood glucose (BG(current)), the previous blood glucose (BG(previous)), the test time of BG(current) (test time(current)), the test time of BG(previous) (test time(previous)), and the previous insulin infusion rate (IR(previous)). Output data consist of the next insulin infusion rate (IR(next)) and next test time. The classification differentiates between "IR" and "MR" algorithm types, both defined as a rule for assigning an insulin infusion rate (IR), having a glycemic target. Both types are capable of assigning the IR for the next iteration of the algorithm (IR(next)) as an increasing function of BG(current), IR(previous), and rate-of-change of BG with respect to time, each treated as an independent variable. Algorithms of the IR type directly seek to define IR(next) as an incremental adjustment to IR(previous). At test time(current), under an IR algorithm the differences in values of IR(next) that might be assigned depending upon the value of BG(current) are not necessarily continuously dependent upon, proportionate to, or commensurate with either the IR(previous) or the rate-of-change of BG. Algorithms of the MR type create a family of IR functions of BG differing according to maintenance rate (MR), each being an iso-MR curve. The change of IR(next) with respect to BG(current) is a strictly increasing function of MR. At test time(current), algorithms of the MR type use IR(previous) and the rate-of-change of BG to define the MR, multiplier, or column assignment, which will be used for patient assignment to the right iso-MR curve and as precedent for IR(next). Bolus insulin therapy is especially effective when used in proportion to carbohydrate load to cover anticipated incremental transitory enteral or parenteral carbohydrate exposure. Specific distinguishing algorithm design features and choice of parameters may be important to
Constrained Multiobjective Biogeography Optimization Algorithm
Mo, Hongwei; Xu, Zhidan; Xu, Lifang; Wu, Zhou; Ma, Haiping
2014-01-01
Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate diverse feasible individuals in order to promote the diversity of individuals on Pareto front. Infeasible individuals nearby feasible region are evolved to feasibility by recombining with their nearest nondominated feasible individuals. The convergence of CMBOA is proved by using probability theory. The performance of CMBOA is evaluated on a set of 6 benchmark problems and experimental results show that the CMBOA performs better than or similar to the classical NSGA-II and IS-MOEA. PMID:25006591
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.
Global Positioning System Navigation Algorithms
1977-05-01
Historical Remarks on Navigation In Greek mythology , Odysseus sailed safely by the Sirens only to encounter the monsters Scylla and Charybdis...TNED 000 00 1(.7 BIBLIOGRAPHY 1. Pinsent, John. Greek Mythology . Paul Hamlyn, London, 1969. 2. Kline, Morris. Mathematical Thought from Ancient to...Algorithms 20. ABS AACT (Continue an reverse sid* If necessary and identify by block nttrnber) The Global Positioning System (CPS) will be a constellation of
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.
QCCM Center for Quantum Algorithms
2008-10-17
Quantum lower bounds for the Goldreich-Levin problem M. Adcock, R. Cleve, K. Iwama, R. Putra , and S. Yamashita Information Processing Letters, 97(5), 208...Improved Algorithms for Quantum Identification of Boolean Oracles. Andris Ambainis, Kazuo Iwama, Akinori Kawachi, Rudy Raymond Harry Putra , Shigeru...Iwama, Akinori Kawachi, Rudy Raymond Harry Putra , Shigeru Yamashita Quantum Computation and Information: From Theory to Experiment, Topics in Applied
Algorithms for optimal redundancy allocation
Vandenkieboom, J.; Youngblood, R.
1993-01-01
Heuristic and exact methods for solving the redundancy allocation problem are compared to an approach based on genetic algorithms. The various methods are applied to the bridge problem, which has been used as a benchmark in earlier work on optimization methods. Comparisons are presented in terms of the best configuration found by each method, and the computation effort which was necessary in order to find it.
Efficient GPS Position Determination Algorithms
2007-06-01
Dilution of Precision ( GDOP ) conditions. The novel differential GPS algorithm for a network of users that has been developed in this research uses a...performance is achieved, even under high Geometric Dilution of Precision ( GDOP ) conditions. The second part of this research investigates a...respect to the receiver produces high Geometric Dilution of Precision ( GDOP ), which can adversely affect GPS position solutions [1]. Four
Gram-Schmidt Adaptive Algorithms.
1980-03-01
Calahan et al. 1976; Liles and Demmel 1978; Blakely 1977; Berra and Singhania 1976; Sameh and Kuck 1975]. Sameh and Kuck [1975, 1977a, 1977b, 1978] have...Griffiss Air Force Base, New York, November 1976; A. H. Sameh and D. J. Kuck, Linear System Solvers for Parallel Computers, Department of Computer...Sciences, Report No. UIUCDCS-R-75-701, University of Illinois at Urbana-Champaign, February 1975. A. H. Sameh , "Numerical Parallel Algorithms--A Survey
Network Games and Approximation Algorithms
2008-01-03
I also spend time during the last three years writing a textbook on Algorithm Design (with Jon Kleinberg) that had now been adopted by a number of...Minimum-Size Bounded-Capacity Cut (MSBCC) problem, in which we are given a graph with an identified source and seek to find a cut minimizing the number ...Distributed Computing (Special Issue PODC 05) Volume 19, Number 4, 2007, 255-266. http://www.springerlink.com/content/x 148746507861 np7/ ?p
Halftoning and Image Processing Algorithms
1999-02-01
screening techniques with the quality advantages of error diffusion in the half toning of color maps, and on color image enhancement for halftone ...image quality. Our goals in this research were to advance the understanding in image science for our new halftone algorithm and to contribute to...image retrieval and noise theory for such imagery. In the field of color halftone printing, research was conducted on deriving a theoretical model of our
Numerical Algorithms and Parallel Tasking.
1984-07-01
34 Principal Investigator, Virginia Klema, Research Staff, George Cybenko and Elizabeth Ducot . During the period, May 15, 1983 through May 14, 1984...Virginia Klema and Elizabeth Ducot have been supported for four months, and George Cybenko has been supported for one month. During this time system...algorithms or applications is the responsibility of the user. Virginia Klema and Elizabeth Ducot presented a description of the concurrent computing
Algorithmic deformation of matrix factorisations
NASA Astrophysics Data System (ADS)
Carqueville, Nils; Dowdy, Laura; Recknagel, Andreas
2012-04-01
Branes and defects in topological Landau-Ginzburg models are described by matrix factorisations. We revisit the problem of deforming them and discuss various deformation methods as well as their relations. We have implemented these algorithms and apply them to several examples. Apart from explicit results in concrete cases, this leads to a novel way to generate new matrix factorisations via nilpotent substitutions, and to criteria whether boundary obstructions can be lifted by bulk deformations.
Asynchronous Distributed Flow Control Algorithms.
1984-10-01
SCHEDULE IS. DISTRIBUTION STATEMENT (of this Report) Approved for public release; distribution unlimited. I?. DISTRIBUTION STATEMENT (of the abstract...model for asynchronous computation developed by Bertsekas [14] to get some results relating to general-asynchronous distributed algo- rithms with update...to get some results relating to general asynchronous distributed algorithms with update protocols. These results are used to give an alternate proof of
Principles for Developing Algorithmic Instruction.
1978-12-01
information-processing theories to test their applicability with instruction directed by learning algorithms. A version of a logical, or familiar, and a...intent of our research was to borrow~ from information-processing theory factors which are known to affect learning in a predictable manner and to apply... learning studies where processing theories are tested by minute performance or latency differences. -~ It is not surprising that differences are seldom found
Algorithms for Automated DNA Assembly
2010-01-01
polyketide synthase gene cluster. Proc. Natl Acad. Sci. USA, 101, 15573–15578. 16. Shetty,R.P., Endy,D. and Knight,T.F. Jr (2008) Engineering BioBrick vectors...correct theoretical construction scheme is de- veloped manually, it is likely to be suboptimal by any number of cost metrics. Modular, robust and...to an exhaustive search on a small synthetic dataset and our results show that our algorithms can quickly find an optimal solution. Comparison with
Parallel Algorithms for Image Analysis.
1982-06-01
8217 _ _ _ _ _ _ _ 4. TITLE (aid Subtitle) S. TYPE OF REPORT & PERIOD COVERED PARALLEL ALGORITHMS FOR IMAGE ANALYSIS TECHNICAL 6. PERFORMING O4G. REPORT NUMBER TR-1180...Continue on reverse side it neceesary aid Identlfy by block number) Image processing; image analysis ; parallel processing; cellular computers. 20... IMAGE ANALYSIS TECHNICAL 6. PERFORMING ONG. REPORT NUMBER TR-1180 - 7. AUTHOR(&) S. CONTRACT OR GRANT NUMBER(s) Azriel Rosenfeld AFOSR-77-3271 9
Routh's algorithm - A centennial survey
NASA Technical Reports Server (NTRS)
Barnett, S.; Siljak, D. D.
1977-01-01
One hundred years have passed since the publication of Routh's fundamental work on determining the stability of constant linear systems. The paper presents an outline of the algorithm and considers such aspects of it as the distribution of zeros and applications of it that relate to the greatest common divisor, the abscissa of stability, continued fractions, canonical forms, the nonnegativity of polynomials and polynomial matrices, the absolute stability, optimality and passivity of dynamic systems, and the stability of two-dimensional circuits.
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.
Algorithm Helps Monitor Engine Operation
NASA Technical Reports Server (NTRS)
Eckerling, Sherry J.; Panossian, Hagop V.; Kemp, Victoria R.; Taniguchi, Mike H.; Nelson, Richard L.
1995-01-01
Real-Time Failure Control (RTFC) algorithm part of automated monitoring-and-shutdown system being developed to ensure safety and prevent major damage to equipment during ground tests of main engine of space shuttle. Includes redundant sensors, controller voting logic circuits, automatic safe-limit logic circuits, and conditional-decision logic circuits, all monitored by human technicians. Basic principles of system also applicable to stationary powerplants and other complex machinery systems.
Consensus Algorithms Over Fading Channels
2010-10-01
studying the effect of fading and collisions on the performance of wireless consensus gossiping and in comparing its cost (measured in terms of number of...not assumed to be symmetric under A2. III. RELATED WORK There has been a resurgence of interest in characterizing consen- sus and gossip algorithms...tree, and then distribute the consensus value, with a finite number of exchanges. The price paid is clearly that of finding the appropriate routing
Multilevel Algorithms for Nonlinear Optimization
1994-06-01
NASA Contractor Report 194940 ICASE Report No. 94-53 AD-A284 318 * ICASE MULTILEVEL ALGORITHMSDDTIC FOR NONLINEAR OPTIMIZATION ELECTESEP 1 4 1994 F...Association SOperated b MULTILEVEL ALGORITHMS FOR NONLINEAR OPTIMIZATION Natalia Alexandrov Accesion For ICASE C Mail Stop 132C NTIS CRA&ID C TAB 1Q...ABSTRACT Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that
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.
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.
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
Introductory Students, Conceptual Understanding, and Algorithmic Success.
ERIC Educational Resources Information Center
Pushkin, David B.
1998-01-01
Addresses the distinction between conceptual and algorithmic learning and the clarification of what is meant by a second-tier student. Explores why novice learners in chemistry and physics are able to apply algorithms without significant conceptual understanding. (DDR)
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.
Introductory Students, Conceptual Understanding, and Algorithmic Success.
ERIC Educational Resources Information Center
Pushkin, David B.
1998-01-01
Addresses the distinction between conceptual and algorithmic learning and the clarification of what is meant by a second-tier student. Explores why novice learners in chemistry and physics are able to apply algorithms without significant conceptual understanding. (DDR)
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.
Comparison of turbulence mitigation algorithms
NASA Astrophysics Data System (ADS)
Kozacik, Stephen T.; Paolini, Aaron; Sherman, Ariel; Bonnett, James; Kelmelis, Eric
2017-07-01
When capturing imagery over long distances, atmospheric turbulence often degrades the data, especially when observation paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms has different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for postprocessing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005. We will compare techniques from the literature with our commercially available, real-time, GPU-accelerated turbulence mitigation software. These comparisons will be made using real (not synthetic), experimentally obtained data for a variety of conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation. Additionally, we will present a technique for quantitatively comparing turbulence mitigation algorithms using real images of radial resolution targets.
Improved LMS algorithm for adaptive beamforming
NASA Technical Reports Server (NTRS)
Godara, Lal C.
1990-01-01
Two adaptive algorithms which make use of all the available samples to estimate the required gradient are proposed and studied. The first algorithm is referred to as the recursive LMS (least mean squares) and is applicable to a general array. The second algorithm is referred to as the improved LMS algorithm and exploits the Toeplitz structure of the ACM (array correlation matrix); it can be used only for an equispaced linear array.
The Cartan algorithm in five dimensions
NASA Astrophysics Data System (ADS)
McNutt, D. D.; Coley, A. A.; Forget, A.
2017-03-01
In this paper, we introduce an algorithm to determine the equivalence of five dimensional spacetimes, which generalizes the Karlhede algorithm for four dimensional general relativity. As an alternative to the Petrov type classification, we employ the alignment classification to algebraically classify the Weyl tensor. To illustrate the algorithm, we discuss three examples: the singly rotating Myers-Perry solution, the Kerr (Anti-) de Sitter solution, and the rotating black ring solution. We briefly discuss some applications of the Cartan algorithm in five dimensions.
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.
Efficient Algorithm for Rectangular Spiral Search
NASA Technical Reports Server (NTRS)
Brugarolas, Paul; Breckenridge, William
2008-01-01
An algorithm generates grid coordinates for a computationally efficient spiral search pattern covering an uncertain rectangular area spanned by a coordinate grid. The algorithm does not require that the grid be fixed; the algorithm can search indefinitely, expanding the grid and spiral, as needed, until the target of the search is found. The algorithm also does not require memory of coordinates of previous points on the spiral to generate the current point on the spiral.
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.
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.
Code for Dinic's maximum flow algorithm. [MAXFLO
Slater, P.J.
1981-11-01
This report is a guide for the users of a subroutine for finding the maximum value of a source to sink flow in a network. The code, MAXFLO, implements an algorithm of E.A. Dinic which is a path augmenting flow algorithm with modifications on the basic maximum flow algorithm of Ford and Fulkerson. Dinic's algorithm was chosen for implementation because comparative studies indicated that this would provide the smallest average run time for a maximum flow computation.
Storage capacity of the Tilinglike Learning Algorithm
NASA Astrophysics Data System (ADS)
Buhot, Arnaud; Gordon, Mirta B.
2001-02-01
The storage capacity of an incremental learning algorithm for the parity machine, the Tilinglike Learning Algorithm, is analytically determined in the limit of a large number of hidden perceptrons. Different learning rules for the simple perceptron are investigated. The usual Gardner-Derrida rule leads to a storage capacity close to the upper bound, which is independent of the learning algorithm considered.
An algorithm on distributed mining association rules
NASA Astrophysics Data System (ADS)
Xu, Fan
2005-12-01
With the rapid development of the Internet/Intranet, distributed databases have become a broadly used environment in various areas. It is a critical task to mine association rules in distributed databases. The algorithms of distributed mining association rules can be divided into two classes. One is a DD algorithm, and another is a CD algorithm. A DD algorithm focuses on data partition optimization so as to enhance the efficiency. A CD algorithm, on the other hand, considers a setting where the data is arbitrarily partitioned horizontally among the parties to begin with, and focuses on parallelizing the communication. A DD algorithm is not always applicable, however, at the time the data is generated, it is often already partitioned. In many cases, it cannot be gathered and repartitioned for reasons of security and secrecy, cost transmission, or sheer efficiency. A CD algorithm may be a more appealing solution for systems which are naturally distributed over large expenses, such as stock exchange and credit card systems. An FDM algorithm provides enhancement to CD algorithm. However, CD and FDM algorithms are both based on net-structure and executing in non-shareable resources. In practical applications, however, distributed databases often are star-structured. This paper proposes an algorithm based on star-structure networks, which are more practical in application, have lower maintenance costs and which are more practical in the construction of the networks. In addition, the algorithm provides high efficiency in communication and good extension in parallel computation.
Are Mathematical Understanding and Algorithmic Performance Related?
ERIC Educational Resources Information Center
Nesher, Pearla
An algorithm is first defined by an example of making pancakes and then through discussion of how computers operate. The understanding that human beings bring to a task is contrasted with this algorithmic processing. In the second section, the question of understanding is related to learning algorithmic performance, with counting used as the…
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.
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.
Approximate algorithms for fast optimal attitude computation
NASA Technical Reports Server (NTRS)
Shuster, M. D.
1978-01-01
Fast accurate algorithms are presented for computing an optimal attitude which minimizes a quadratic loss function. These algorithms compute an optimal rotation which carries a set of reference vectors into a set of corresponding observation vectors. Simplifications of these algorithms are obtained for the case of small rotation angles. Applications to the Magsat mission 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.
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…
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.
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…
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.
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
Empirical Studies of the Value of Algorithm Animation in Algorithm Understanding
1993-08-01
A series of studies is presented using algorithm animation to teach computer algorithms . These studies are organized into three components: eliciting...lecture with experimenter-preprepared data sets. This work has implications for the design and use of animated algorithms in teaching computer algorithms and
An Optimal Class Association Rule Algorithm
NASA Astrophysics Data System (ADS)
Jean Claude, Turiho; Sheng, Yang; Chuang, Li; Kaia, Xie
Classification and association rule mining algorithms are two important aspects of data mining. Class association rule mining algorithm is a promising approach for it involves the use of association rule mining algorithm to discover classification rules. This paper introduces an optimal class association rule mining algorithm known as OCARA. It uses optimal association rule mining algorithm and the rule set is sorted by priority of rules resulting into a more accurate classifier. It outperforms the C4.5, CBA, RMR on UCI eight data sets, which is proved by experimental results.
Towards General Algorithms for Grammatical Inference
NASA Astrophysics Data System (ADS)
Clark, Alexander
Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of strings, and a set of features or tests that constrain various inference rules. Using this general framework, which we cast as a process of logical inference, we re-analyse Angluin's famous lstar algorithm and several recent algorithms for the inference of context-free grammars and multiple context-free grammars. Finally, to illustrate the advantages of this approach, we extend it to the inference of functional transductions from positive data only, and we present a new algorithm for the inference of finite state transducers.
Efficient demultiplexing algorithm for noncontiguous carriers
NASA Technical Reports Server (NTRS)
Thanawala, A. A.; Kwatra, S. C.; Jamali, M. M.; Budinger, J.
1992-01-01
A channel separation algorithm for the frequency division multiple access/time division multiplexing (FDMA/TDM) scheme is presented. It is shown that implementation using this algorithm can be more effective than the fast Fourier transform (FFT) algorithm when only a small number of carriers need to be selected from many, such as satellite Earth terminals. The algorithm is based on polyphase filtering followed by application of a generalized Walsh-Hadamard transform (GWHT). Comparison of the transform technique used in this algorithm with discrete Fourier transform (DFT) and FFT is given. Estimates of the computational rates and power requirements to implement this system are also given.
Genetic algorithms using SISAL parallel programming language
Tejada, S.
1994-05-06
Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.
Evolutionary algorithms for the satisfiability problem.
Gottlieb, Jens; Marchiori, Elena; Rossi, Claudio
2002-01-01
Several evolutionary algorithms have been proposed for the satisfiability problem. We review the solution representations suggested in literature and choose the most promising one - the bit string representation - for further evaluation. An empirical comparison on commonly used benchmarks is presented for the most successful evolutionary algorithms and for WSAT, a prominent local search algorithm for the satisfiability problem. The key features of successful evolutionary algorithms are identified, thereby providing useful methodological guidelines for designing new heuristics. Our results indicate that evolutionary algorithms are competitive to WSAT.
Transient noise suppression algorithm in speech system
NASA Astrophysics Data System (ADS)
Cao, Keyu; Wang, Mingjiang
2017-08-01
In this paper, I mainly introduce the algorithm of transient noise suppression in speech system. Firstly, it divides into impulsive noise and other types of transient noise according to the characteristics of transient noise. In the impulse noise suppression algorithm, I mainly use the averaging energy threshold method to detect the impulse noise, and then I use the amplitude threshold method to reduce the impulse noise which was detected. In the other types of transient noise suppression algorithm, I mainly use the Optimally Modified-Log Spectral Amplitude estimation (OM-LSA) algorithm and the Minimum Control Recursive Average (MCRA) algorithm to suppress the transient noise.
The Rational Hybrid Monte Carlo algorithm
NASA Astrophysics Data System (ADS)
Clark, Michael
2006-12-01
The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.
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.
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.
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.
The global Minmax k-means algorithm.
Wang, Xiaoyan; Bai, Yanping
2016-01-01
The global k-means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k-means to minimize the sum of the intra-cluster variances. However the global k-means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k-means algorithm. In this paper, we modified the global k-means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k-means clustering error method to global k-means algorithm to overcome the effect of bad initialization, proposed the global Minmax k-means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k-means algorithm, the global k-means algorithm and the MinMax k-means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.
Filtering algorithm for dotted interferences
NASA Astrophysics Data System (ADS)
Osterloh, K.; Bücherl, T.; Lierse von Gostomski, Ch.; Zscherpel, U.; Ewert, U.; Bock, S.
2011-09-01
An algorithm has been developed to remove reliably dotted interferences impairing the perceptibility of objects within a radiographic image. This particularly is a major challenge encountered with neutron radiographs collected at the NECTAR facility, Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II): the resulting images are dominated by features resembling a snow flurry. These artefacts are caused by scattered neutrons, gamma radiation, cosmic radiation, etc. all hitting the detector CCD directly in spite of a sophisticated shielding. This makes such images rather useless for further direct evaluations. One approach to resolve this problem of these random effects would be to collect a vast number of single images, to combine them appropriately and to process them with common image filtering procedures. However, it has been shown that, e.g. median filtering, depending on the kernel size in the plane and/or the number of single shots to be combined, is either insufficient or tends to blur sharp lined structures. This inevitably makes a visually controlled processing image by image unavoidable. Particularly in tomographic studies, it would be by far too tedious to treat each single projection by this way. Alternatively, it would be not only more comfortable but also in many cases the only reasonable approach to filter a stack of images in a batch procedure to get rid of the disturbing interferences. The algorithm presented here meets all these requirements. It reliably frees the images from the snowy pattern described above without the loss of fine structures and without a general blurring of the image. It consists of an iterative, within a batch procedure parameter free filtering algorithm aiming to eliminate the often complex interfering artefacts while leaving the original information untouched as far as possible.
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.
Privacy Preservation in Distributed Subgradient Optimization Algorithms.
Lou, Youcheng; Yu, Lean; Wang, Shouyang; Yi, Peng
2017-07-31
In this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, we first show that the distributed subgradient synchronous homogeneous-stepsize algorithm is not privacy preserving in the sense that the malicious agent can asymptotically discover other agents' subgradients by transmitting untrue estimates to its neighbors. Then a distributed subgradient asynchronous heterogeneous-stepsize projection algorithm is proposed and accordingly its convergence and optimality is established. In contrast to the synchronous homogeneous-stepsize algorithm, in the new algorithm agents make their optimization updates asynchronously with heterogeneous stepsizes. The introduced two mechanisms of projection operation and asynchronous heterogeneous-stepsize optimization can guarantee that agents' privacy can be effectively protected.
Quantum algorithm for support matrix machines
NASA Astrophysics Data System (ADS)
Duan, Bojia; Yuan, Jiabin; Liu, Ying; Li, Dan
2017-09-01
We propose a quantum algorithm for support matrix machines (SMMs) that efficiently addresses an image classification problem by introducing a least-squares reformulation. This algorithm consists of two core subroutines: a quantum matrix inversion (Harrow-Hassidim-Lloyd, HHL) algorithm and a quantum singular value thresholding (QSVT) algorithm. The two algorithms can be implemented on a universal quantum computer with complexity O[log(npq) ] and O[log(pq)], respectively, where n is the number of the training data and p q is the size of the feature space. By iterating the algorithms, we can find the parameters for the SMM classfication model. Our analysis shows that both HHL and QSVT algorithms achieve an exponential increase of speed over their classical counterparts.
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.
Optimal Multistage Algorithm for Adjoint Computation
Aupy, Guillaume; Herrmann, Julien; Hovland, Paul; Robert, Yves
2016-01-01
We reexamine the work of Stumm and Walther on multistage algorithms for adjoint computation. We provide an optimal algorithm for this problem when there are two levels of checkpoints, in memory and on disk. Previously, optimal algorithms for adjoint computations were known only for a single level of checkpoints with no writing and reading costs; a well-known example is the binomial checkpointing algorithm of Griewank and Walther. Stumm and Walther extended that binomial checkpointing algorithm to the case of two levels of checkpoints, but they did not provide any optimality results. We bridge the gap by designing the first optimal algorithm in this context. We experimentally compare our optimal algorithm with that of Stumm and Walther to assess the difference in performance.
A hybrid algorithm with GA and DAEM
NASA Astrophysics Data System (ADS)
Wan, HongJie; Deng, HaoJiang; Wang, XueWei
2013-03-01
Although the expectation-maximization (EM) algorithm has been widely used for finding maximum likelihood estimation of parameters in probabilistic models, it has the problem of trapping by local maxima. To overcome this problem, the deterministic annealing EM (DAEM) algorithm was once proposed and had achieved better performance than EM algorithm, but it is not very effective at avoiding local maxima. In this paper, a solution is proposed by integrating GA and DAEM into one procedure to further improve the solution quality. The population based search of genetic algorithm will produce different solutions and thus can increase the search space of DAEM. Therefore, the proposed algorithm will reach better solution than just using DAEM. The algorithm retains the property of DAEM and gets the better solution by genetic operation. Experiment results on Gaussian mixture model parameter estimation demonstrate that the proposed algorithm can achieve better performance.
MM Algorithms for Some Discrete Multivariate Distributions.
Zhou, Hua; Lange, Kenneth
2010-09-01
The MM (minorization-maximization) principle is a versatile tool for constructing optimization algorithms. Every EM algorithm is an MM algorithm but not vice versa. This article derives MM algorithms for maximum likelihood estimation with discrete multivariate distributions such as the Dirichlet-multinomial and Connor-Mosimann distributions, the Neerchal-Morel distribution, the negative-multinomial distribution, certain distributions on partitions, and zero-truncated and zero-inflated distributions. These MM algorithms increase the likelihood at each iteration and reliably converge to the maximum from well-chosen initial values. Because they involve no matrix inversion, the algorithms are especially pertinent to high-dimensional problems. To illustrate the performance of the MM algorithms, we compare them to Newton's method on data used to classify handwritten digits.
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.
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
Algorithm Sorts Groups Of Data
NASA Technical Reports Server (NTRS)
Evans, J. D.
1987-01-01
For efficient sorting, algorithm finds set containing minimum or maximum most significant data. Sets of data sorted as desired. Sorting process simplified by reduction of each multielement set of data to single representative number. First, each set of data expressed as polynomial with suitably chosen base, using elements of set as coefficients. Most significant element placed in term containing largest exponent. Base selected by examining range in value of data elements. Resulting series summed to yield single representative number. Numbers easily sorted, and each such number converted back to original set of data by successive division. Program written in BASIC.
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.
Public traffic transfer algorithm design
NASA Astrophysics Data System (ADS)
Yin, Kui-Ying; Jin, Lin; Qian, Bo; Fang, Kai
The route relationship matrix M is employed in this paper to indicate relationship between routes. The travel solutions for bus stations are obtained by matrix operation. Through the data mining to the history record of transportation information, the road transportation status at specific time interval can be predicted. Based on the predication, the best travel solutions can be found. The algorithm fully uses history transportation information, optimizes the travel solutions according to the time consumed. It can satisfy the time requirement of traveler and is very useful.
Sensor network algorithms and applications.
Trigoni, Niki; Krishnamachari, Bhaskar
2012-01-13
A sensor network is a collection of nodes with processing, communication and sensing capabilities deployed in an area of interest to perform a monitoring task. There has now been about a decade of very active research in the area of sensor networks, with significant accomplishments made in terms of both designing novel algorithms and building exciting new sensing applications. This Theme Issue provides a broad sampling of the central challenges and the contributions that have been made towards addressing these challenges in the field, and illustrates the pervasive and central role of sensor networks in monitoring human activities and the environment.
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.
Cluster Algorithm Special Purpose Processor
NASA Astrophysics Data System (ADS)
Talapov, A. L.; Shchur, L. N.; Andreichenko, V. B.; Dotsenko, Vl. S.
We describe a Special Purpose Processor, realizing the Wolff algorithm in hardware, which is fast enough to study the critical behaviour of 2D Ising-like systems containing more than one million spins. The processor has been checked to produce correct results for a pure Ising model and for Ising model with random bonds. Its data also agree with the Nishimori exact results for spin glass. Only minor changes of the SPP design are necessary to increase the dimensionality and to take into account more complex systems such as Potts models.
The Complexity of Parallel Algorithms,
1985-11-01
Much of this work was done in collaboration with my advisor, Ernst Mayr . He was also supported in part by ONR contract N00014-85-C-0731. F ’. Table...Helinbold and Mayr in their algorithn to compute an optimal two processor schedule [HM2]. One of the promising developments in parallel algorithms is that...lei can be solved by it fast parallel algorithmmmi if the nmlmmmibers are smiall. llehmibold and Mayr JIlM I] have slhowm that. if Ole job timies are
An efficient parallel termination detection algorithm
Baker, A. H.; Crivelli, S.; Jessup, E. R.
2004-05-27
Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Of these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.
Enhanced algorithms for stochastic programming
Krishna, A.S.
1993-09-01
In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions used in this method. We have concluded that approximating the recourse function by a computationally inexpensive piecewise-linear function is highly efficient. This reduced the problem from finding the mean of a computationally expensive functions to finding that of a computationally inexpensive function. Then we implemented various variance reduction techniques to estimate the mean of a piecewise-linear function. This method achieved similar variance reductions in orders of magnitude less time than, when we directly applied variance-reduction techniques directly on the given problem. In solving a stochastic linear program, the expected value problem is usually solved before a stochastic solution and also to speed-up the algorithm by making use of the information obtained from the solution of the expected value problem. We have devised a new decomposition scheme to improve the convergence of this algorithm.
Quantum Algorithms for Fermionic Simulations
NASA Astrophysics Data System (ADS)
Ortiz, Gerardo
2001-06-01
The probabilistic simulation of quantum systems in classical computers is known to be limited by the so-called sign or phase problem, a problem believed to be of exponential complexity. This ``disease" manifests itself by the exponentially hard task of estimating the expectation value of an observable with a given error. Therefore, probabilistic simulations on a classical computer do not seem to qualify as a practical computational scheme for general quantum many-body problems. The limiting factors, for whatever reasons, are negative or complex-valued probabilities whether the simulations are done in real or imaginary time. In 1981 Richard Feynman raised some provocative questions in connection to the ``exact imitation'' of such systems using a special device named a ``quantum computer.'' Feynman hesitated about the possibility of imitating fermion systems using such a device. Here we address some of his concerns and, in particular, investigate the simulation of fermionic systems. We show how quantum algorithms avoid the sign problem by reducing the complexity from exponential to polynomial. Our demonstration is based upon the use of isomorphisms of *-algebras (spin-particle transformations) which connect different models of quantum computation. In particular, we present fermionic models (the fabled ``Grassmann Chip''); but, of course, these models are not the only ones since our spin-particle connections allow us to introduce more ``esoteric'' models of computation. We present specific quantum algorithms that illustrate the main points of our algebraic approach.
Ligand Identification Scoring Algorithm (LISA)
Zheng, Zheng; Merz, Kenneth M.
2011-01-01
A central problem in de novo drug design is determining the binding affinity of a ligand with a receptor. A new scoring algorithm is presented that estimates the binding affinity of a protein-ligand complex given a three-dimensional structure. The method, LISA (Ligand Identification Scoring Algorithm), uses an empirical scoring function to describe the binding free energy. Interaction terms have been designed to account for van der Waals (VDW) contacts, hydrogen bonding, desolvation effects and metal chelation to model the dissociation equilibrium constants using a linear model. Atom types have been introduced to differentiate the parameters for VDW, H-bonding interactions and metal chelation between different atom pairs. A training set of 492 protein-ligand complexes was selected for the fitting process. Different test sets have been examined to evaluate its ability to predict experimentally measured binding affinities. By comparing with other well known scoring functions, the results show that LISA has advantages over many existing scoring functions in simulating protein-ligand binding affinity, especially metalloprotein-ligand binding affinity. Artificial Neural Network (ANN) was also used in order to demonstrate that the energy terms in LISA are well designed and do not require extra cross terms. PMID:21561101
POLDER level-1 processing algorithms
NASA Astrophysics Data System (ADS)
Hagolle, Olivier; Guerry, Agnes; Cunin, Laurent; Millet, Bruno; Perbos, Jacqueline; Laherrere, Jean-Marc; Bret-Dibat, Thierry; Poutier, Laurent
1996-06-01
POLDER (polarization and directionality of the Earth reflectances) is a French instrument that will be flown on- board ADEOS (advanced earth observing satellite) polar orbiting satellite, scheduled to be launched in August 1996. POLDER is a multispectral imaging radiometer/polarimeter designed to collect global and repetitive observations of the solar radiation reflected by the Earth/atmosphere system, with a wide field of view (2400 km) and a moderate geometric resolution (6 km). The instrument concept is based on telecentric optics, on a rotating wheel carrying 15 spectral filters and polarizers, and on a bidimensional CCD detector array. In addition to the classical measurement and mapping characteristics of a narrow-band imaging radiometer, POLDER has a unique ability to measure polarized reflectances at three different polarization angles (for three of its eight visible and near-infrared spectral bands), and to observe target reflectances from 14 different viewing directions during a single satellite pass. All the data transmitted by POLDER are processed in the POLDER Processing Centre. Level 1 products include geometrically and radiometrically corrected data, level 2 products are elementary geophysical products created from a single satellite pass, and level 3 products are geophysical synthesis from several passes of the satellite. This paper presents the radiometrical and geometrical algorithms of the level 1 processing: new algorithms developed for the removal of sensor artefacts (smearing, stray light), for the radiometrical mode inversion (normalized radiance and polarization parameter extraction), and for the geometrical projection of the data on a unique grid are explained.
The Aquarius Salinity Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Meissner, Thomas; Wentz, Frank; Hilburn, Kyle; Lagerloef, Gary; Le Vine, David
2012-01-01
The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.
Filter selection using genetic algorithms
NASA Astrophysics Data System (ADS)
Patel, Devesh
1996-03-01
Convolution operators act as matched filters for certain types of variations found in images and have been extensively used in the analysis of images. However, filtering through a bank of N filters generates N filtered images, consequently increasing the amount of data considerably. Moreover, not all these filters have the same discriminatory capabilities for the individual images, thus making the task of any classifier difficult. In this paper, we use genetic algorithms to select a subset of relevant filters. Genetic algorithms represent a class of adaptive search techniques where the processes are similar to natural selection of biological evolution. The steady state model (GENITOR) has been used in this paper. The reduction of filters improves the performance of the classifier (which in this paper is the multi-layer perceptron neural network) and furthermore reduces the computational requirement. In this study we use the Laws filters which were proposed for the analysis of texture images. Our aim is to recognize the different textures on the images using the reduced filter set.
Ligand Identification Scoring Algorithm (LISA).
Zheng, Zheng; Merz, Kenneth M
2011-06-27
A central problem in de novo drug design is determining the binding affinity of a ligand with a receptor. A new scoring algorithm is presented that estimates the binding affinity of a protein-ligand complex given a three-dimensional structure. The method, LISA (Ligand Identification Scoring Algorithm), uses an empirical scoring function to describe the binding free energy. Interaction terms have been designed to account for van der Waals (VDW) contacts, hydrogen bonding, desolvation effects, and metal chelation to model the dissociation equilibrium constants using a linear model. Atom types have been introduced to differentiate the parameters for VDW, H-bonding interactions, and metal chelation between different atom pairs. A training set of 492 protein-ligand complexes was selected for the fitting process. Different test sets have been examined to evaluate its ability to predict experimentally measured binding affinities. By comparing with other well-known scoring functions, the results show that LISA has advantages over many existing scoring functions in simulating protein-ligand binding affinity, especially metalloprotein-ligand binding affinity. Artificial Neural Network (ANN) was also used in order to demonstrate that the energy terms in LISA are well designed and do not require extra cross terms.
Novel algorithm for iris localization
NASA Astrophysics Data System (ADS)
Wang, Yunxin; Liu, Tiegen; Liu, Li
2007-11-01
With the emerging security demands, biometric identification technology has attracted more and more attention in recent years, and iris recognition is one of the most reliable biometric technologies. Iris localization is a crucial part in the iris recognition, which is quite time-consuming and easily disturbed by various noises, especially the eyelashes. A novel iris localization method is proposed in this paper. In the location of inner iris boundary, the gray curves of a row and a column with the pupil edge are used to estimate the coarse center and radius of pupil, which can reject the eyelash noises. The experiments show this coarse location method has better accuracy and speed than the common gray projection. Edge points of pupil are extracted by a gradient operator and fitted as the iris inner boundary. In the location of outer iris boundary, the image binarization is use to mark most noises, and then the outer iris boundary is extracted by integro-differential operator from the coarseness to fine. Performance experiments have been done, and the results show that about 0.175 second at speed and 99.5% at precision are reached by developed algorithm. In comparison with other classical methods, this algorithm has faster speed and better robustness.
Effects of visualization on algorithm comprehension
NASA Astrophysics Data System (ADS)
Mulvey, Matthew
Computer science students are expected to learn and apply a variety of core algorithms which are an essential part of the field. Any one of these algorithms by itself is not necessarily extremely complex, but remembering the large variety of algorithms and the differences between them is challenging. To address this challenge, we present a novel algorithm visualization tool designed to enhance students understanding of Dijkstra's algorithm by allowing them to discover the rules of the algorithm for themselves. It is hoped that a deeper understanding of the algorithm will help students correctly select, adapt and apply the appropriate algorithm when presented with a problem to solve, and that what is learned here will be applicable to the design of other visualization tools designed to teach different algorithms. Our visualization tool is currently in the prototype stage, and this thesis will discuss the pedagogical approach that informs its design, as well as the results of some initial usability testing. Finally, to clarify the direction for further development of the tool, four different variations of the prototype were implemented, and the instructional effectiveness of each was assessed by having a small sample participants use the different versions of the prototype and then take a quiz to assess their comprehension of the algorithm.
Firefly Mating Algorithm for Continuous Optimization Problems
Ritthipakdee, Amarita; Premasathian, Nol; Jitkongchuen, Duangjai
2017-01-01
This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima. PMID:28808442
A Probabilistic Cell Tracking Algorithm
NASA Astrophysics Data System (ADS)
Steinacker, Reinhold; Mayer, Dieter; Leiding, Tina; Lexer, Annemarie; Umdasch, Sarah
2013-04-01
The research described below was carried out during the EU-Project Lolight - development of a low cost, novel and accurate lightning mapping and thunderstorm (supercell) tracking system. The Project aims to develop a small-scale tracking method to determine and nowcast characteristic trajectories and velocities of convective cells and cell complexes. The results of the algorithm will provide a higher accuracy than current locating systems distributed on a coarse scale. Input data for the developed algorithm are two temporally separated lightning density fields. Additionally a Monte Carlo method minimizing a cost function is utilizied which leads to a probabilistic forecast for the movement of thunderstorm cells. In the first step the correlation coefficients between the first and the second density field are computed. Hence, the first field is shifted by all shifting vectors which are physically allowed. The maximum length of each vector is determined by the maximum possible speed of thunderstorm cells and the difference in time for both density fields. To eliminate ambiguities in determination of directions and velocities, the so called Random Walker of the Monte Carlo process is used. Using this method a grid point is selected at random. Moreover, one vector out of all predefined shifting vectors is suggested - also at random but with a probability that is related to the correlation coefficient. If this exchange of shifting vectors reduces the cost function, the new direction and velocity are accepted. Otherwise it is discarded. This process is repeated until the change of cost functions falls below a defined threshold. The Monte Carlo run gives information about the percentage of accepted shifting vectors for all grid points. In the course of the forecast, amplifications of cell density are permitted. For this purpose, intensity changes between the investigated areas of both density fields are taken into account. Knowing the direction and speed of thunderstorm
A generalized hybrid algorithm for bioluminescence tomography
Shi, Shengkun; Mao, Heng
2013-01-01
Bioluminescence tomography (BLT) is a promising optical molecular imaging technique on the frontier of biomedical optics. In this paper, a generalized hybrid algorithm has been proposed based on the graph cuts algorithm and gradient-based algorithms. The graph cuts algorithm is adopted to estimate a reliable source support without prior knowledge, and different gradient-based algorithms are sequentially used to acquire an accurate and fine source distribution according to the reconstruction status. Furthermore, multilevel meshes for the internal sources are used to speed up the computation and improve the accuracy of reconstruction. Numerical simulations have been performed to validate this proposed algorithm and demonstrate its high performance in the multi-source situation even if the detection noises, optical property errors and phantom structure errors are involved in the forward imaging. PMID:23667787
Adaptive link selection algorithms for distributed estimation
NASA Astrophysics Data System (ADS)
Xu, Songcen; de Lamare, Rodrigo C.; Poor, H. Vincent
2015-12-01
This paper presents adaptive link selection algorithms for distributed estimation and considers their application to wireless sensor networks and smart grids. In particular, exhaustive search-based least mean squares (LMS) / recursive least squares (RLS) link selection algorithms and sparsity-inspired LMS / RLS link selection algorithms that can exploit the topology of networks with poor-quality links are considered. The proposed link selection algorithms are then analyzed in terms of their stability, steady-state, and tracking performance and computational complexity. In comparison with the existing centralized or distributed estimation strategies, the key features of the proposed algorithms are as follows: (1) more accurate estimates and faster convergence speed can be obtained and (2) the network is equipped with the ability of link selection that can circumvent link failures and improve the estimation performance. The performance of the proposed algorithms for distributed estimation is illustrated via simulations in applications of wireless sensor networks and smart grids.
Quantum random-walk search algorithm
Shenvi, Neil; Whaley, K. Birgitta; Kempe, Julia
2003-05-01
Quantum random walks on graphs have been shown to display many interesting properties, including exponentially fast hitting times when compared with their classical counterparts. However, it is still unclear how to use these novel properties to gain an algorithmic speedup over classical algorithms. In this paper, we present a quantum search algorithm based on the quantum random-walk architecture that provides such a speedup. It will be shown that this algorithm performs an oracle search on a database of N items with O({radical}(N)) calls to the oracle, yielding a speedup similar to other quantum search algorithms. It appears that the quantum random-walk formulation has considerable flexibility, presenting interesting opportunities for development of other, possibly novel quantum algorithms.
An Algorithmic Framework for Multiobjective Optimization
Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.
2013-01-01
Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization. PMID:24470795
Algorithms in radiology and medical imaging.
Athanasoulis, C A; Lee, A K
1987-08-01
As a tool in clinical decision making, algorithms deserve careful consideration. The potential use or abuse of algorithms in rationing health care renders such consideration essential. In radiology and medical imaging, algorithms have been applied as teaching tools in the conference room setting. These teaching decision trees, however, may not be applicable in the clinical situation. If an algorithmic approach to clinical radiology is pursued, several issues should be considered. Specifically, the application, design, designer, economics, and universality of the algorithms must be addressed. As an alternative to the wide dissemination of clinical algorithms, the authors propose the development of consensus opinions among specialists and the promulgation of the principle of radiologist-consultant-decision maker. A decision team is preferable to a decision tree.
Tilted cone beam VCT reconstruction algorithm
NASA Astrophysics Data System (ADS)
Hsieh, Jiang; Tang, Xiangyang
2005-04-01
Reconstruction algorithms for volumetric CT have been the focus of many studies. Several exact and approximate reconstruction algorithms have been proposed for step-and-shoot and helical scanning trajectories to combat cone beam related artifacts. In this paper, we present a closed form cone beam reconstruction formula for tilted gantry data acquisition. Although several algorithms were proposed to compensate for errors induced by the gantry tilt, none of the algorithms addresses the case in which the cone beam geometry is first rebinned to a set of parallel beams prior to the filtered backprojection. Because of the rebinning process, the amount of iso-center adjustment depends not only on the projection angle and tilt angle, but also on the reconstructed pixel location. The proposed algorithm has been tested extensively on both 16 and 64 slice VCT with phantoms and clinical data. The efficacy of the algorithm is clearly demonstrated by the experiments.
A new cloud algorithm for gome data
NASA Astrophysics Data System (ADS)
Grzegorski, M.; Beierle, S.; Friedeburg, C.; Hollwedel, J.; Khokhar, F.; Kühl, S.; Platt, U.; Wenig, M.; Wilms-Grabe, W.; Wagner, T.
2003-04-01
The Global Ozone Monitoring Experiment (GOME) on the ERS-2 satellite allows the measurement of many tropospheric trace gases (e.g. NO_2, SO_2, BrO, HCHO, H_2O) using the DOAS technique. Cloud algorithms are essential for the accurate retrieval of the tropospheric vertical column density of these trace gases. A new algorithm using PMD-data is presented. The results are validated through comparison with other algorithms (e.g. FRESCO, CRUSA). Problems found in existing algorithms such as overestimated cloud fractions over desert regions and negative values over oceans are significantly improved with the new algorithm. Also other possible errorsources like the systematic intensity decrease across the subpixels influences the calculation of the cloud fractions. The new algorithm tries to correct this effect.
The EM algorithm in medical imaging.
Kay, J
1997-03-01
This article outlines the statistical developments that have taken place in the use of the EM algorithm in emission and transmission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data for both the emission and transmission cases and define the relevant probability models. This leads to the use of the method of maximum likelihood as a means of estimating the relevant unknown parameters within a given region of a patient's body and to the use of the EM algorithm to compute the reconstruction. Various different types of EM algorithm are discussed, including the SAGE algorithms of Fessler and Hero. The limitations of the EM algorithm, per se, are covered and the need for regularization is stressed. A number of different methods for penalizing the likelihood are described and a number of algorithms for the computation of the penalized EM reconstruction are discussed.
A boundary finding algorithm and its applications
NASA Technical Reports Server (NTRS)
Gupta, J. N.; Wintz, P. A.
1975-01-01
An algorithm for locating gray level and/or texture edges in digitized pictures is presented. The algorithm is based on the concept of hypothesis testing. The digitized picture is first subdivided into subsets of picture elements, e.g., 2 x 2 arrays. The algorithm then compares the first- and second-order statistics of adjacent subsets; adjacent subsets having similar first- and/or second-order statistics are merged into blobs. By continuing this process, the entire picture is segmented into blobs such that the picture elements within each blob have similar characteristics. The boundaries between the blobs comprise the boundaries. The algorithm always generates closed boundaries. The algorithm was developed for multispectral imagery of the earth's surface. Application of this algorithm to various image processing techniques such as efficient coding, information extraction (terrain classification), and pattern recognition (feature selection) are included.
Runtime support for parallelizing data mining algorithms
NASA Astrophysics Data System (ADS)
Jin, Ruoming; Agrawal, Gagan
2002-03-01
With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.
Visualizing output for a data learning algorithm
NASA Astrophysics Data System (ADS)
Carson, Daniel; Graham, James; Ternovskiy, Igor
2016-05-01
This paper details the process we went through to visualize the output for our data learning algorithm. We have been developing a hierarchical self-structuring learning algorithm based around the general principles of the LaRue model. One example of a proposed application of this algorithm would be traffic analysis, chosen because it is conceptually easy to follow and there is a significant amount of already existing data and related research material with which to work with. While we choose the tracking of vehicles for our initial approach, it is by no means the only target of our algorithm. Flexibility is the end goal, however, we still need somewhere to start. To that end, this paper details our creation of the visualization GUI for our algorithm, the features we included and the initial results we obtained from our algorithm running a few of the traffic based scenarios we designed.
ENAS-RIF algorithm for image restoration
NASA Astrophysics Data System (ADS)
Yang, Yang; Yang, Zhen-wen; Shen, Tian-shuang; Chen, Bo
2012-11-01
mage of objects is inevitably encountered by space-based working in the atmospheric turbulence environment, such as those used in astronomy, remote sensing and so on. The observed images are seriously blurred. The restoration is required for reconstruction turbulence degraded images. In order to enhance the performance of image restoration, a novel enhanced nonnegativity and support constants recursive inverse filtering(ENAS-RIF) algorithm was presented, which was based on the reliable support region and enhanced cost function. Firstly, the Curvelet denoising algorithm was used to weaken image noise. Secondly, the reliable object support region estimation was used to accelerate the algorithm convergence. Then, the average gray was set as the gray of image background pixel. Finally, an object construction limit and the logarithm function were add to enhance algorithm stability. The experimental results prove that the convergence speed of the novel ENAS-RIF algorithm is faster than that of NAS-RIF algorithm and it is better in image restoration.
LDRD Report: Scheduling Irregular Algorithms
Boman, Erik G.
2014-10-01
This LDRD project was a campus exec fellowship to fund (in part) Donald Nguyen’s PhD research at UT-Austin. His work has focused on parallel programming models, and scheduling irregular algorithms on shared-memory systems using the Galois framework. Galois provides a simple but powerful way for users and applications to automatically obtain good parallel performance using certain supported data containers. The naïve user can write serial code, while advanced users can optimize performance by advanced features, such as specifying the scheduling policy. Galois was used to parallelize two sparse matrix reordering schemes: RCM and Sloan. Such reordering is important in high-performance computing to obtain better data locality and thus reduce run times.
Novel MRC algorithms using GPGPU
NASA Astrophysics Data System (ADS)
Kato, Kokoro; Taniguchi, Yoshiyuki; Inoue, Tadao; Kadota, Kazuya
2012-06-01
GPGPU (General Purpose Graphic Processor Unit) has been attracting many engineers and scientists who develop their own software for massive numerical computation. With hundreds of core-processors and tens of thousands of threads operating concurrently, GPGPU programs can run significantly fast if their software architecture is well optimized. The basic program model used in GPGPU is SIMD (Single Instruction Multiple Data stream), and one must adapt his programming model to SIMD. However, conditional branching is fundamentally not allowed in SIMD and this limitation is quite challenging to apply GPGPU to photomask related software such as MDP or MRC. In this paper unique methods are proposed to utilize GPU for MRC operation. We explain novel algorithms of mask layout verification by GPGPU.
An algorithm for visual fields.
Trobe, J D; Acosta, P C
1980-01-01
The authors present an algorithm, or sequential strategy, for the performance and interpretation of visual fields. Based on the principle that particular areas of the visual field are relatively vulnerable and that particular defect configurations are relatively more diagnostic, the strategy proposes certain "core maneuvers" for all initial examinations, followed by selective exploration of the vertical meridian "rectangle" and central "keyhole." This constitutes the "qualitative" portion of perimetry and combines threshold kinetic and suprathreshold static techniques. If time and patience permit, qualitative perimetry is followed by quantiative definition of defect size, depth and slope, using the requisite number of stimuli. This approach may be adapted to all visual field instruments. The interpretation of the field defects is based on assessing their localizing features.
Energy functions for regularization algorithms
NASA Technical Reports Server (NTRS)
Delingette, H.; Hebert, M.; Ikeuchi, K.
1991-01-01
Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.
Online Planning Algorithms for POMDPs
Ross, Stéphane; Pineau, Joelle; Paquet, Sébastien; Chaib-draa, Brahim
2009-01-01
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP is often intractable except for small problems due to their complexity. Here, we focus on online approaches that alleviate the computational complexity by computing good local policies at each decision step during the execution. Online algorithms generally consist of a lookahead search to find the best action to execute at each time step in an environment. Our objectives here are to survey the various existing online POMDP methods, analyze their properties and discuss their advantages and disadvantages; and to thoroughly evaluate these online approaches in different environments under various metrics (return, error bound reduction, lower bound improvement). Our experimental results indicate that state-of-the-art online heuristic search methods can handle large POMDP domains efficiently. PMID:19777080
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.
Anaphora Resolution Algorithm for Sanskrit
NASA Astrophysics Data System (ADS)
Pralayankar, Pravin; Devi, Sobha Lalitha
This paper presents an algorithm, which identifies different types of pronominal and its antecedents in Sanskrit, an Indo-European language. The computational grammar implemented here uses very familiar concepts such as clause, subject, object etc., which are identified with the help of morphological information and concepts such as precede and follow. It is well known that natural languages contain anaphoric expressions, gaps and elliptical constructions of various kinds and that understanding of natural languages involves assignment of interpretations to these elements. Therefore, it is only to be expected that natural language understanding systems must have the necessary mechanism to resolve the same. The method we adopt here for resolving the anaphors is by exploiting the morphological richness of the language. The system is giving encouraging results when tested with a small corpus.
Online Planning Algorithms for POMDPs.
Ross, Stéphane; Pineau, Joelle; Paquet, Sébastien; Chaib-Draa, Brahim
2008-07-01
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP is often intractable except for small problems due to their complexity. Here, we focus on online approaches that alleviate the computational complexity by computing good local policies at each decision step during the execution. Online algorithms generally consist of a lookahead search to find the best action to execute at each time step in an environment. Our objectives here are to survey the various existing online POMDP methods, analyze their properties and discuss their advantages and disadvantages; and to thoroughly evaluate these online approaches in different environments under various metrics (return, error bound reduction, lower bound improvement). Our experimental results indicate that state-of-the-art online heuristic search methods can handle large POMDP domains efficiently.
Improved Heat-Stress Algorithm
NASA Technical Reports Server (NTRS)
Teets, Edward H., Jr.; Fehn, Steven
2007-01-01
NASA Dryden presents an improved and automated site-specific algorithm for heat-stress approximation using standard atmospheric measurements routinely obtained from the Edwards Air Force Base weather detachment. Heat stress, which is the net heat load a worker may be exposed to, is officially measured using a thermal-environment monitoring system to calculate the wet-bulb globe temperature (WBGT). This instrument uses three independent thermometers to measure wet-bulb, dry-bulb, and the black-globe temperatures. By using these improvements, a more realistic WBGT estimation value can now be produced. This is extremely useful for researchers and other employees who are working on outdoor projects that are distant from the areas that the Web system monitors. Most importantly, the improved WBGT estimations will make outdoor work sites safer by reducing the likelihood of heat stress.
Algorithms for tensor network renormalization
NASA Astrophysics Data System (ADS)
Evenbly, G.
2017-01-01
We discuss in detail algorithms for implementing tensor network renormalization (TNR) for the study of classical statistical and quantum many-body systems. First, we recall established techniques for how the partition function of a 2 D classical many-body system or the Euclidean path integral of a 1 D quantum system can be represented as a network of tensors, before describing how TNR can be implemented to efficiently contract the network via a sequence of coarse-graining transformations. The efficacy of the TNR approach is then benchmarked for the 2 D classical statistical and 1 D quantum Ising models; in particular the ability of TNR to maintain a high level of accuracy over sustained coarse-graining transformations, even at a critical point, is demonstrated.
[A simple algorithm for anemia].
Egyed, Miklós
2014-03-09
The author presents a novel algorithm for anaemia based on the erythrocyte haemoglobin content. The scheme is based on the aberrations of erythropoiesis and not on the pathophysiology of anaemia. The hemoglobin content of one erytrocyte is between 28-35 picogram. Any disturbance in hemoglobin synthesis can lead to a lower than 28 picogram hemoglobin content of the erythrocyte which will lead to hypochromic anaemia. In contrary, disturbances of nucleic acid metabolism will result in a hemoglobin content greater than 36 picogram, and this will result in hyperchromic anaemia. Normochromic anemia, characterised by hemoglobin content of erythrocytes between 28 and 35 picogram, is the result of alteration in the proliferation of erythropoeisis. Based on these three categories of anaemia, a unique system can be constructed, which can be used as a model for basic laboratory investigations and work-up of anaemic patients.
Neuberger's double-pass algorithm
NASA Astrophysics Data System (ADS)
Chiu, Ting-Wai; Hsieh, Tung-Han
2003-12-01
We analyze Neuberger’s double-pass algorithm for the matrix-vector multiplication R(H)ṡY [where R(H) is (n-1,n)th degree rational polynomial of positive definite operator H], and show that the number of floating-point operations is independent of the degree n, provided that the number of sites is much larger than the number of iterations in the conjugate gradient. This implies that the matrix-vector product (H)-1/2Y≃R(n-1,n)(H)ṡY can be approximated to very high precision with sufficiently large n, without noticeably extra costs. Further, we show that there exists a threshold nT such that the double-pass is faster than the single pass for n>nT, where nT≃12 25 for most platforms.
[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.
Algorithms for Labeling Focus Regions.
Fink, M; Haunert, Jan-Henrik; Schulz, A; Spoerhase, J; Wolff, A
2012-12-01
In this paper, we investigate the problem of labeling point sites in focus regions of maps or diagrams. This problem occurs, for example, when the user of a mapping service wants to see the names of restaurants or other POIs in a crowded downtown area but keep the overview over a larger area. Our approach is to place the labels at the boundary of the focus region and connect each site with its label by a linear connection, which is called a leader. In this way, we move labels from the focus region to the less valuable context region surrounding it. In order to make the leader layout well readable, we present algorithms that rule out crossings between leaders and optimize other characteristics such as total leader length and distance between labels. This yields a new variant of the boundary labeling problem, which has been studied in the literature. Other than in traditional boundary labeling, where leaders are usually schematized polylines, we focus on leaders that are either straight-line segments or Bezier curves. Further, we present algorithms that, given the sites, find a position of the focus region that optimizes the above characteristics. We also consider a variant of the problem where we have more sites than space for labels. In this situation, we assume that the sites are prioritized by the user. Alternatively, we take a new facility-location perspective which yields a clustering of the sites. We label one representative of each cluster. If the user wishes, we apply our approach to the sites within a cluster, giving details on demand.
Advanced spectral signature discrimination algorithm
NASA Astrophysics Data System (ADS)
Chakravarty, Sumit; Cao, Wenjie; Samat, Alim
2013-05-01
This paper presents a novel approach to the task of hyperspectral signature analysis. Hyperspectral signature analysis has been studied a lot in literature and there has been a lot of different algorithms developed which endeavors to discriminate between hyperspectral signatures. There are many approaches for performing the task of hyperspectral signature analysis. Binary coding approaches like SPAM and SFBC use basic statistical thresholding operations to binarize a signature which are then compared using Hamming distance. This framework has been extended to techniques like SDFC wherein a set of primate structures are used to characterize local variations in a signature together with the overall statistical measures like mean. As we see such structures harness only local variations and do not exploit any covariation of spectrally distinct parts of the signature. The approach of this research is to harvest such information by the use of a technique similar to circular convolution. In the approach we consider the signature as cyclic by appending the two ends of it. We then create two copies of the spectral signature. These three signatures can be placed next to each other like the rotating discs of a combination lock. We then find local structures at different circular shifts between the three cyclic spectral signatures. Texture features like in SDFC can be used to study the local structural variation for each circular shift. We can then create different measure by creating histogram from the shifts and thereafter using different techniques for information extraction from the histograms. Depending on the technique used different variant of the proposed algorithm are obtained. Experiments using the proposed technique show the viability of the proposed methods and their performances as compared to current binary signature coding techniques.
Dynamic Shortest Path Algorithms for Hypergraphs
2012-01-01
geometric hypergraphs and the Enron email data set. The latter illustrates the application of the proposed algorithms in social networks for identifying...analyze the time complexity of the proposed algorithms and perform simulation experiments for both random geometric hypergraphs and the Enron email data...geometric hypergraph model and a real data set of a social network ( Enron email data set), we study the average performance of these two algorithms in
QRS Detection Algorithm for Telehealth Electrocardiogram Recordings.
Khamis, Heba; Weiss, Robert; Xie, Yang; Chang, Chan-Wei; Lovell, Nigel H; Redmond, Stephen J
2016-07-01
QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a "UNSW" QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG. The UNSW algorithm generates a feature signal containing information about ECG amplitude and derivative, which is filtered according to its frequency content and an adaptive threshold is applied. The algorithm was tested on clinical and telehealth ECG and the QRS detection performance is compared to the Pan-Tompkins (PT) and Gutiérrez-Rivas (GR) algorithm. For the MIT-BIH Arrhythmia database (virtually artifact free, clinical ECG), the overall sensitivity (Se) and positive predictivity (+P) of the UNSW algorithm was >99%, which was comparable to PT and GR. When applied to the MIT-BIH noise stress test database (clinical ECG with added calibrated noise) after artifact masking, all three algorithms had overall Se >99%, and the UNSW algorithm had higher +P (98%, p < 0.05) than PT and GR. For 250 telehealth ECG records (unsupervised recordings; dry metal electrodes), the UNSW algorithm had 98% Se and 95% +P which was superior to PT (+P: p < 0.001) and GR (Se and +P: p < 0.001). This is the first study to describe a QRS detection algorithm for telehealth data and evaluate it on clinical and telehealth ECG with superior results to published algorithms. The UNSW algorithm could be used to manage increasing telehealth ECG analysis workloads.
Validation of Core Temperature Estimation Algorithm
2016-01-20
qualitatively expected behavior. Field data were taken from a study of 33 young male military personnel who tested six prototype uniforms over the...developer used to evaluate the algorithm. USARIEM has evaluated the algorithm accuracy on over 52,000 core temperature measurements from nine laboratory...were carried over from the previous time resulting in a continuation of the algorithm as if no gap existed. For time gaps of greater than 10 minutes
Angelic Hierarchical Planning: Optimal and Online Algorithms
2008-12-06
describe an alternative “satisficing” algorithm, AHSS . 4.1 Abstract Lookahead Trees Our ALT data structures support our search algorithms by efficiently...Angelic Hierarchical Satisficing Search ( AHSS ), which at- tempts to find a plan that reaches the goal with at most some pre-specified cost α. AHSS can be...much more efficient than AHA*, since it can commit to a plan without first proving its optimality. At each step, AHSS (see Algorithm 3) begins by
Genetic Algorithms Viewed as Anticipatory Systems
NASA Astrophysics Data System (ADS)
Mocanu, Irina; Kalisz, Eugenia; Negreanu, Lorina
2010-11-01
This paper proposes a new version of genetic algorithms—the anticipatory genetic algorithm AGA. The performance evaluation included in the paper shows that AGA is superior to traditional genetic algorithm from both speed and accuracy points of view. The paper also presents how this algorithm can be applied to solve a complex problem: image annotation, intended to be used in content based image retrieval systems.
Testing block subdivision algorithms on block designs
NASA Astrophysics Data System (ADS)
Wiseman, Natalie; Patterson, Zachary
2016-01-01
Integrated land use-transportation models predict future transportation demand taking into account how households and firms arrange themselves partly as a function of the transportation system. Recent integrated models require parcels as inputs and produce household and employment predictions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within blocks. Evaluating block subdivision algorithms is done by way of generating parcels and comparing them to those in a parcel database. Three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from Montreal, Canada. While the authors who developed each of the algorithms have evaluated them, they have used their own metrics and block types to evaluate their own algorithms. This makes it difficult to compare their strengths and weaknesses. The contribution of this paper is in resolving this difficulty with the aim of finding a better algorithm suited to subdividing each block type. The proposed hypothesis is that given the different approaches that block subdivision algorithms take, it's likely that different algorithms are better adapted to subdividing different block types. To test this, a standardized block type classification is used that consists of mutually exclusive and comprehensive categories. A statistical method is used for finding a better algorithm and the probability it will perform well for a given block type. Results suggest the oriented bounding box algorithm performs better for warped non-uniform sites, as well as gridiron and fragmented uniform sites. It also produces more similar parcel areas and widths. The Generalized Parcel Divider 1 algorithm performs better for gridiron non-uniform sites. The Straight Skeleton algorithm performs better for loop and lollipop networks as well as fragmented non-uniform and warped uniform sites. It also produces more similar parcel shapes and patterns.
Tests of Radar Rainfall Retrieval Algorithms
NASA Technical Reports Server (NTRS)
Durden, Stephen L.
1999-01-01
The NASA/JPL Airborne Rain Mapping Radar (ARMAR) operates at 14 GHz. ARMAR flew on the NASA DC-8 aircraft during Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE), collecting data in oceanic mesoscale convective systems, similar to those now being observed by the Tropical Rainfall Measuring Mission (TRMM) satellite, which includes a 14-GHz precipitation radar. Several algorithms for retrieving rain rate from downward looking radars are in existence. These can be categorized as deterministic and stochastic. Deterministic algorithms use the path integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the attenuation-rainfall (k-R) relation, while another corrects the reflectivity rainfall (ZR) relation. Stochastic algorithms apply an Extended Kalman Filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. We find that the stochastic algorithm with PIA is the most robust algorithm with regard to incorrect assumptions about the drop-size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA. The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions. The underestimation is illustrated in the diagram. The algorithm labeled D IS initially assumes a DSD that is appropriate for stratiform. rain, while the rain is most likely convective. The PIA constraint causes the k-R relation to be adjusted, resulting in a much lower rain rate than the other algorithms. Additional information is contained in the original.
A Traffic Motion Object Extraction Algorithm
NASA Astrophysics Data System (ADS)
Wu, Shaofei
2015-12-01
A motion object extraction algorithm based on the active contour model is proposed. Firstly, moving areas involving shadows are segmented with the classical background difference algorithm. Secondly, performing shadow detection and coarse removal, then a grid method is used to extract initial contours. Finally, the active contour model approach is adopted to compute the contour of the real object by iteratively tuning the parameter of the model. Experiments show the algorithm can remove the shadow and keep the integrity of a moving object.
Genetic algorithms for DNA sequence assembly.
Parsons, R; Forrest, S; Burks, C
1993-01-01
This paper describes a genetic algorithm application to the DNA sequence assembly problem. The genetic algorithm uses a sorted order representation for representing the orderings of fragments. Two different fitness functions, both based on pairwise overlap strengths between fragments, are tested. The paper concludes that the genetic algorithm is a promising method for fragment assembly problems, achieving usable solutions quickly, but that the current fitness functions are flawed and that other representations might be more appropriate.
Evolving evolutionary algorithms using linear genetic programming.
Oltean, Mihai
2005-01-01
A new model for evolving Evolutionary Algorithms is proposed in this paper. The model is based on the Linear Genetic Programming (LGP) technique. Every LGP chromosome encodes an EA which is used for solving a particular problem. Several Evolutionary Algorithms for function optimization, the Traveling Salesman Problem and the Quadratic Assignment Problem are evolved by using the considered model. Numerical experiments show that the evolved Evolutionary Algorithms perform similarly and sometimes even better than standard approaches for several well-known benchmarking problems.
Research in Complexity Theory and Combinatorial Algorithms
1980-01-01
other hand, when k = 1, the problem is obvious polynomial . Somewhere in between, there exists a boundary separating the two classes of problems. As to...input to an algorithm that solved the SHP), the complexity of the problem is not yet comipletely settled. For example, polynomial algorithms for solving...possible. B. Eberle [Ebe] discovered a polynomial time algorithm, O(!Vl4), that yields G with its radius upperbounded by I(r2 + r). .* L . - - T - I - ’U
MRCK_3D contact detonation algorithm
Rougier, Esteban; Munjiza, Antonio
2010-01-01
Large-scale Combined Finite-Discrete Element Methods (FEM-DEM) and Discrete Element Methods (DEM) simulations involving contact of a large number of separate bod ies need an efficient, robust and flexible contact detection algorithm. In this work the MRCK-3D search algorithm is outlined and its main CPU perfonnances are evaluated. One of the most important aspects of this newly developed search algorithm is that it is applicable to systems consisting of many bodies of different shapes and sizes.
Algorithm for Compressing Time-Series Data
NASA Technical Reports Server (NTRS)
Hawkins, S. Edward, III; Darlington, Edward Hugo
2012-01-01
An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").
Accurate Singular Values and Differential QD Algorithms
1992-07-01
name stands for the complex absolute value of z + iy. In numerical computing (e.g. Eispack), an alternative name for cabs is pythag. Algorithm 1 (oqd...ubiquitous phrase ’at most’ qualifying errors and modifications. Our algorithms still do not admit a pure backward error analysis , the computed output h...Loan. Matrix Computations . Johns Hopkins University Press, Baltimore, 1989. [121 P. Henrici . The quotient-difference algorithm. Nat. Bur. Standards Appl
Efficient algorithms for periodic Hermite spline interpolation
NASA Astrophysics Data System (ADS)
Plonka, G.; Tasche, M.
1992-04-01
Periodic Hermite spline interpolants on an equidistant lattice are represented by the Bezier technique as well as by the B-spline method. Circulant matrices are used to derive new explicit formulas for the periodic Hermite splines of degree m and defect r (1 ≤ r ≤ m) . Applying the known de Casteljau algorithm and the de Boor algorithm, respectively, we obtain new efficient real algorithms for periodic Hermite spline interpolation.
Unitary Quantum Lattice Algorithms for Turbulence
2016-05-23
evolution of the ground state of a Bose- Einstein condensate – whether in a magnetic or optical trap. The algorithm consists of interleaved collide...qubit unitary lattice algorithm is developed for the mean field evolution of the ground state of a Bose-Einstein condensate – whether in a magnetic or...optical trap. The algorithm consists of interleaved collide-stream operators which in diffusion ordering recovers the spinor Gross Pitaevskii equations
Robustness of Tree Extraction Algorithms from LIDAR
NASA Astrophysics Data System (ADS)
Dumitru, M.; Strimbu, B. M.
2015-12-01
Forest inventory faces a new era as unmanned aerial systems (UAS) increased the precision of measurements, while reduced field effort and price of data acquisition. A large number of algorithms were developed to identify various forest attributes from UAS data. The objective of the present research is to assess the robustness of two types of tree identification algorithms when UAS data are combined with digital elevation models (DEM). The algorithms use as input photogrammetric point cloud, which are subsequent rasterized. The first type of algorithms associate tree crown with an inversed watershed (subsequently referred as watershed based), while the second type is based on simultaneous representation of tree crown as an individual entity, and its relation with neighboring crowns (subsequently referred as simultaneous representation). A DJI equipped with a SONY a5100 was used to acquire images over an area from center Louisiana. The images were processed with Pix4D, and a photogrammetric point cloud with 50 points / m2 was attained. DEM was obtained from a flight executed in 2013, which also supplied a LIDAR point cloud with 30 points/m2. The algorithms were tested on two plantations with different species and crown class complexities: one homogeneous (i.e., a mature loblolly pine plantation), and one heterogeneous (i.e., an unmanaged uneven-aged stand with mixed species pine -hardwoods). Tree identification on photogrammetric point cloud reveled that simultaneous representation algorithm outperforms watershed algorithm, irrespective stand complexity. Watershed algorithm exhibits robustness to parameters, but the results were worse than majority sets of parameters needed by the simultaneous representation algorithm. The simultaneous representation algorithm is a better alternative to watershed algorithm even when parameters are not accurately estimated. Similar results were obtained when the two algorithms were run on the LIDAR point cloud.
Java implementation of Class Association Rule algorithms
Tamura, Makio
2007-08-30
Java implementation of three Class Association Rule mining algorithms, NETCAR, CARapriori, and clustering based rule mining. NETCAR algorithm is a novel algorithm developed by Makio Tamura. The algorithm is discussed in a paper: UCRL-JRNL-232466-DRAFT, and would be published in a peer review scientific journal. The software is used to extract combinations of genes relevant with a phenotype from a phylogenetic profile and a phenotype profile. The phylogenetic profiles is represented by a binary matrix and a phenotype profile is represented by a binary vector. The present application of this software will be in genome analysis, however, it could be applied more generally.
Generation of attributes for learning algorithms
Hu, Yuh-Jyh; Kibler, D.
1996-12-31
Inductive algorithms rely strongly on their representational biases. Constructive induction can mitigate representational inadequacies. This paper introduces the notion of a relative gain measure and describes a new constructive induction algorithm (GALA) which is independent of the learning algorithm. Unlike most previous research on constructive induction, our methods are designed as preprocessing step before standard machine learning algorithms are applied. We present the results which demonstrate the effectiveness of GALA on artificial and real domains for several learners: C4.5, CN2, perceptron and backpropagation.
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.
Automatic control algorithm effects on energy production
NASA Technical Reports Server (NTRS)
Mcnerney, G. M.
1981-01-01
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
A new frame-based registration algorithm
NASA Technical Reports Server (NTRS)
Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Sumanaweera, T. S.; Yen, S. Y.; Napel, S.
1998-01-01
This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required.
Solving Maximal Clique Problem through Genetic Algorithm
NASA Astrophysics Data System (ADS)
Rajawat, Shalini; Hemrajani, Naveen; Menghani, Ekta
2010-11-01
Genetic algorithm is one of the most interesting heuristic search techniques. It depends basically on three operations; selection, crossover and mutation. The outcome of the three operations is a new population for the next generation. Repeating these operations until the termination condition is reached. All the operations in the algorithm are accessible with today's molecular biotechnology. The simulations show that with this new computing algorithm, it is possible to get a solution from a very small initial data pool, avoiding enumerating all candidate solutions. For randomly generated problems, genetic algorithm can give correct solution within a few cycles at high probability.
Fast convolution algorithms for SAR processing
NASA Astrophysics Data System (ADS)
dall, Jorgen
Most high resolution SAR processors apply the Fast Fourier Transform (FFT) to implement convolution by a matched filter impulse response. However, a lower computational complexity is attainable with other algorithms which accordingly have the potential of offering faster and/or simpler processors. Thirteen different fast transform and convolution algorithms are presented, and their characteristics are compared with the fundamental requirements imposed on the algorithms by various SAR processing schemes. The most promising algorithm is based on a Fermat Number Transform (FNT). SAR-580 and SEASAT SAR images have been successfully processed with the FNT, and in this connection the range curvature correction, noise properties and processing speed are discussed.
Ascent guidance algorithm using lidar wind measurements
NASA Technical Reports Server (NTRS)
Cramer, Evin J.; Bradt, Jerre E.; Hardtla, John W.
1990-01-01
The formulation of a general nonlinear programming guidance algorithm that incorporates wind measurements in the computation of ascent guidance steering commands is discussed. A nonlinear programming (NLP) algorithm that is designed to solve a very general problem has the potential to address the diversity demanded by future launch systems. Using B-splines for the command functional form allows the NLP algorithm to adjust the shape of the command profile to achieve optimal performance. The algorithm flexibility is demonstrated by simulation of ascent with dynamic loading constraints through a set of random wind profiles with and without wind sensing capability.
Iterative phase retrieval algorithms. I: optimization.
Guo, Changliang; Liu, Shi; Sheridan, John T
2015-05-20
Two modified Gerchberg-Saxton (GS) iterative phase retrieval algorithms are proposed. The first we refer to as the spatial phase perturbation GS algorithm (SPP GSA). The second is a combined GS hybrid input-output algorithm (GS/HIOA). In this paper (Part I), it is demonstrated that the SPP GS and GS/HIO algorithms are both much better at avoiding stagnation during phase retrieval, allowing them to successfully locate superior solutions compared with either the GS or the HIO algorithms. The performances of the SPP GS and GS/HIO algorithms are also compared. Then, the error reduction (ER) algorithm is combined with the HIO algorithm (ER/HIOA) to retrieve the input object image and the phase, given only some knowledge of its extent and the amplitude in the Fourier domain. In Part II, the algorithms developed here are applied to carry out known plaintext and ciphertext attacks on amplitude encoding and phase encoding double random phase encryption systems. Significantly, ER/HIOA is then used to carry out a ciphertext-only attack on AE DRPE systems.
Ascent guidance algorithm using lidar wind measurements
NASA Technical Reports Server (NTRS)
Cramer, Evin J.; Bradt, Jerre E.; Hardtla, John W.
1990-01-01
The formulation of a general nonlinear programming guidance algorithm that incorporates wind measurements in the computation of ascent guidance steering commands is discussed. A nonlinear programming (NLP) algorithm that is designed to solve a very general problem has the potential to address the diversity demanded by future launch systems. Using B-splines for the command functional form allows the NLP algorithm to adjust the shape of the command profile to achieve optimal performance. The algorithm flexibility is demonstrated by simulation of ascent with dynamic loading constraints through a set of random wind profiles with and without wind sensing capability.
A new frame-based registration algorithm
NASA Technical Reports Server (NTRS)
Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Sumanaweera, T. S.; Yen, S. Y.; Napel, S.
1998-01-01
This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required.
A simple greedy algorithm for reconstructing pedigrees.
Cowell, Robert G
2013-02-01
This paper introduces a simple greedy algorithm for searching for high likelihood pedigrees using micro-satellite (STR) genotype information on a complete sample of related individuals. The core idea behind the algorithm is not new, but it is believed that putting it into a greedy search setting, and specifically the application to pedigree learning, is novel. The algorithm does not require age or sex information, but this information can be incorporated if desired. The algorithm is applied to human and non-human genetic data and in a simulation study.
Overview of an Algorithm Plugin Package (APP)
NASA Astrophysics Data System (ADS)
Linda, M.; Tilmes, C.; Fleig, A. J.
2004-12-01
Science software that runs operationally is fundamentally different than software that runs on a scientist's desktop. There are complexities in hosting software for automated production that are necessary and significant. Identifying common aspects of these complexities can simplify algorithm integration. We use NASA's MODIS and OMI data production systems as examples. An Algorithm Plugin Package (APP) is science software that is combined with algorithm-unique elements that permit the algorithm to interface with, and function within, the framework of a data processing system. The framework runs algorithms operationally against large quantities of data. The extra algorithm-unique items are constrained by the design of the data processing system. APPs often include infrastructure that is vastly similar. When the common elements in APPs are identified and abstracted, the cost of APP development, testing, and maintenance will be reduced. This paper is an overview of the extra algorithm-unique pieces that are shared between MODAPS and OMIDAPS APPs. Our exploration of APP structure will help builders of other production systems identify their common elements and reduce algorithm integration costs. Our goal is to complete the development of a library of functions and a menu of implementation choices that reflect common needs of APPs. The library and menu will reduce the time and energy required for science developers to integrate algorithms into production systems.
One cutting plane algorithm using auxiliary functions
NASA Astrophysics Data System (ADS)
Zabotin, I. Ya; Kazaeva, K. E.
2016-11-01
We propose an algorithm for solving a convex programming problem from the class of cutting methods. The algorithm is characterized by the construction of approximations using some auxiliary functions, instead of the objective function. Each auxiliary function bases on the exterior penalty function. In proposed algorithm the admissible set and the epigraph of each auxiliary function are embedded into polyhedral sets. In connection with the above, the iteration points are found by solving linear programming problems. We discuss the implementation of the algorithm and prove its convergence.
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.
Monte Carlo algorithm for free energy calculation.
Bi, Sheng; Tong, Ning-Hua
2015-07-01
We propose a Monte Carlo algorithm for the free energy calculation based on configuration space sampling. An upward or downward temperature scan can be used to produce F(T). We implement this algorithm for the Ising model on a square lattice and triangular lattice. Comparison with the exact free energy shows an excellent agreement. We analyze the properties of this algorithm and compare it with the Wang-Landau algorithm, which samples in energy space. This method is applicable to general classical statistical models. The possibility of extending it to quantum systems is discussed.
Introduction to Cluster Monte Carlo Algorithms
NASA Astrophysics Data System (ADS)
Luijten, E.
This chapter provides an introduction to cluster Monte Carlo algorithms for classical statistical-mechanical systems. A brief review of the conventional Metropolis algorithm is given, followed by a detailed discussion of the lattice cluster algorithm developed by Swendsen and Wang and the single-cluster variant introduced by Wolff. For continuum systems, the geometric cluster algorithm of Dress and Krauth is described. It is shown how their geometric approach can be generalized to incorporate particle interactions beyond hardcore repulsions, thus forging a connection between the lattice and continuum approaches. Several illustrative examples are discussed.
Improved algorithm for hyperspectral data dimension determination
NASA Astrophysics Data System (ADS)
CHEN, Jie; DU, Lei; LI, Jing; HAN, Yachao; GAO, Zihong
2017-02-01
The correlation between adjacent bands of hyperspectral image data is relatively strong. However, signal coexists with noise and the HySime (hyperspectral signal identification by minimum error) algorithm which is based on the principle of least squares is designed to calculate the estimated noise value and the estimated signal correlation matrix value. The algorithm is effective with accurate noise value but ineffective with estimated noise value obtained from spectral dimension reduction and de-correlation process. This paper proposes an improved HySime algorithm based on noise whitening process. It carries out the noise whitening, instead of removing noise pixel by pixel, process on the original data first, obtains the noise covariance matrix estimated value accurately, and uses the HySime algorithm to calculate the signal correlation matrix value in order to improve the precision of results. With simulated as well as real data experiments in this paper, results show that: firstly, the improved HySime algorithm are more accurate and stable than the original HySime algorithm; secondly, the improved HySime algorithm results have better consistency under the different conditions compared with the classic noise subspace projection algorithm (NSP); finally, the improved HySime algorithm improves the adaptability of non-white image noise with noise whitening process.
Approximate learning algorithm in Boltzmann machines.
Yasuda, Muneki; Tanaka, Kazuyuki
2009-11-01
Boltzmann machines can be regarded as Markov random fields. For binary cases, they are equivalent to the Ising spin model in statistical mechanics. Learning systems in Boltzmann machines are one of the NP-hard problems. Thus, in general we have to use approximate methods to construct practical learning algorithms in this context. In this letter, we propose new and practical learning algorithms for Boltzmann machines by using the belief propagation algorithm and the linear response approximation, which are often referred as advanced mean field methods. Finally, we show the validity of our algorithm using numerical experiments.
NASA Astrophysics Data System (ADS)
Nagao, Toshiyasu; Takeuchi, Akihiro; Nakamura, Kenji
2011-03-01
There are a number of reports on seismic quiescence phenomena before large earthquakes. The RTL algorithm is a weighted coefficient statistical method that takes into account the magnitude, occurrence time, and place of earthquake when seismicity pattern changes before large earthquakes are being investigated. However, we consider the original RTL algorithm to be overweighted on distance. In this paper, we introduce a modified RTL algorithm, called the RTM algorithm, and apply it to three large earthquakes in Japan, namely, the Hyogo-ken Nanbu earthquake in 1995 ( M JMA7.3), the Noto Hanto earthquake in 2007 ( M JMA 6.9), and the Iwate-Miyagi Nairiku earthquake in 2008 ( M JMA 7.2), as test cases. Because this algorithm uses several parameters to characterize the weighted coefficients, multiparameter sets have to be prepared for the tests. The results show that the RTM algorithm is more sensitive than the RTL algorithm to seismic quiescence phenomena. This paper represents the first step in a series of future analyses of seismic quiescence phenomena using the RTM algorithm. At this moment, whole surveyed parameters are empirically selected for use in the method. We have to consider the physical meaning of the "best fit" parameter, such as the relation of ACFS, among others, in future analyses.
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity.
A Support Vector Machine Blind Equalization Algorithm Based on Immune Clone Algorithm
NASA Astrophysics Data System (ADS)
Yecai, Guo; Rui, Ding
Aiming at affecting of the parameter selection method of support vector machine(SVM) on its application in blind equalization algorithm, a SVM constant modulus blind equalization algorithm based on immune clone selection algorithm(CSA-SVM-CMA) is proposed. In this proposed algorithm, the immune clone algorithm is used to optimize the parameters of the SVM on the basis advantages of its preventing evolutionary precocious, avoiding local optimum, and fast convergence. The proposed algorithm can improve the parameter selection efficiency of SVM constant modulus blind equalization algorithm(SVM-CMA) and overcome the defect of the artificial setting parameters. Accordingly, the CSA-SVM-CMA has faster convergence rate and smaller mean square error than the SVM-CMA. Computer simulations in underwater acoustic channels have proved the validity of the algorithm.
A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389
Control algorithms for dynamic attenuators
Hsieh, Scott S.; Pelc, Norbert J.
2014-06-15
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
Control algorithms for dynamic attenuators
Hsieh, Scott S.; Pelc, Norbert J.
2014-01-01
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not require a priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms
NASA Technical Reports Server (NTRS)
Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)
2000-01-01
In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.
Localization Algorithms of Underwater Wireless Sensor Networks: A Survey
Han, Guangjie; Jiang, Jinfang; Shu, Lei; Xu, Yongjun; Wang, Feng
2012-01-01
In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs. PMID:22438752
New pole placement algorithm - Polynomial matrix approach
NASA Technical Reports Server (NTRS)
Shafai, B.; Keel, L. H.
1990-01-01
A simple and direct pole-placement algorithm is introduced for dynamical systems having a block companion matrix A. The algorithm utilizes well-established properties of matrix polynomials. Pole placement is achieved by appropriately assigning coefficient matrices of the corresponding matrix polynomial. This involves only matrix additions and multiplications without requiring matrix inversion. A numerical example is given for the purpose of illustration.
Algorithmic Mechanism Design of Evolutionary Computation
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm. PMID:26257777
Trees, bialgebras and intrinsic numerical algorithms
NASA Technical Reports Server (NTRS)
Crouch, Peter; Grossman, Robert; Larson, Richard
1990-01-01
Preliminary work about intrinsic numerical integrators evolving on groups is described. Fix a finite dimensional Lie group G; let g denote its Lie algebra, and let Y(sub 1),...,Y(sub N) denote a basis of g. A class of numerical algorithms is presented that approximate solutions to differential equations evolving on G of the form: dot-x(t) = F(x(t)), x(0) = p is an element of G. The algorithms depend upon constants c(sub i) and c(sub ij), for i = 1,...,k and j is less than i. The algorithms have the property that if the algorithm starts on the group, then it remains on the group. In addition, they also have the property that if G is the abelian group R(N), then the algorithm becomes the classical Runge-Kutta algorithm. The Cayley algebra generated by labeled, ordered trees is used to generate the equations that the coefficients c(sub i) and c(sub ij) must satisfy in order for the algorithm to yield an rth order numerical integrator and to analyze the resulting algorithms.
Global Optimality of the Successive Maxbet Algorithm.
ERIC Educational Resources Information Center
Hanafi, Mohamed; ten Berge, Jos M. F.
2003-01-01
It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)
Kalman plus weights: a time scale algorithm
NASA Technical Reports Server (NTRS)
Greenhall, C. A.
2001-01-01
KPW is a time scale algorithm that combines Kalman filtering with the basic time scale equation (BTSE). A single Kalman filter that estimates all clocks simultaneously is used to generate the BTSE frequency estimates, while the BTSE weights are inversely proportional to the white FM variances of the clocks. Results from simulated clock ensembles are compared to previous simulation results from other algorithms.
Faster Algorithms on Branch and Clique Decompositions
NASA Astrophysics Data System (ADS)
Bodlaender, Hans L.; van Leeuwen, Erik Jan; van Rooij, Johan M. M.; Vatshelle, Martin
We combine two techniques recently introduced to obtain faster dynamic programming algorithms for optimization problems on graph decompositions. The unification of generalized fast subset convolution and fast matrix multiplication yields significant improvements to the running time of previous algorithms for several optimization problems. As an example, we give an O^{*}(3^{ω/2k}) time algorithm for Minimum Dominating Set on graphs of branchwidth k, improving on the previous O *(4 k ) algorithm. Here ω is the exponent in the running time of the best matrix multiplication algorithm (currently ω< 2.376). For graphs of cliquewidth k, we improve from O *(8 k ) to O *(4 k ). We also obtain an algorithm for counting the number of perfect matchings of a graph, given a branch decomposition of width k, that runs in time O^{*}(2^{ω/2k}). Generalizing these approaches, we obtain faster algorithms for all so-called [ρ,σ]-domination problems on branch decompositions if ρ and σ are finite or cofinite. The algorithms presented in this paper either attain or are very close to natural lower bounds for these problems.
Quantum Algorithm for Linear Programming Problems
NASA Astrophysics Data System (ADS)
Joag, Pramod; Mehendale, Dhananjay
The quantum algorithm (PRL 103, 150502, 2009) solves a system of linear equations with exponential speedup over existing classical algorithms. We show that the above algorithm can be readily adopted in the iterative algorithms for solving linear programming (LP) problems. The first iterative algorithm that we suggest for LP problem follows from duality theory. It consists of finding nonnegative solution of the equation forduality condition; forconstraints imposed by the given primal problem and for constraints imposed by its corresponding dual problem. This problem is called the problem of nonnegative least squares, or simply the NNLS problem. We use a well known method for solving the problem of NNLS due to Lawson and Hanson. This algorithm essentially consists of solving in each iterative step a new system of linear equations . The other iterative algorithms that can be used are those based on interior point methods. The same technique can be adopted for solving network flow problems as these problems can be readily formulated as LP problems. The suggested quantum algorithm cansolveLP problems and Network Flow problems of very large size involving millions of variables.
Initial borehole acoustic televiewer data processing algorithms
Moore, T.K.
1988-06-01
With the development of a new digital televiewer, several algorithms have been developed in support of off-line data processing. This report describes the initial set of utilities developed to support data handling as well as data display. Functional descriptions, implementation details, and instructions for use of the seven algorithms are provided. 5 refs., 33 figs., 1 tab.
Evolutionary algorithms dynamics represented by contact sequences
NASA Astrophysics Data System (ADS)
Skanderova, Lenka
2017-07-01
Population-based evolutionary algorithms are popular to solve difficult optimization problems in the various areas of research as well as real-world problems. In this work, we discuss a new approach of the analysis of the evolutionary algorithm which is based on the idea to represent the evolution of the population as the contact sequence.
Efficient Learning Algorithms with Limited Information
ERIC Educational Resources Information Center
De, Anindya
2013-01-01
The thesis explores efficient learning algorithms in settings which are more restrictive than the PAC model of learning (Valiant) in one of the following two senses: (i) The learning algorithm has a very weak access to the unknown function, as in, it does not get labeled samples for the unknown function (ii) The error guarantee required from the…
Efficient algorithms for molecular sequence analysis.
Karlin, S; Morris, M; Ghandour, G; Leung, M Y
1988-01-01
Efficient (linear time) algorithms are described for identifying global molecular sequence features allowing for errors including repeats, matches between sequences, dyad symmetry pairings, and other sequence patterns. A multiple sequence alignment algorithm is also described. Specific applications are given to hepatitis B viruses and the J5-C (J, joining; C, constant) region of the immunoglobulin kappa gene. PMID:3124111
A Runge-Kutta Nystrom algorithm.
NASA Technical Reports Server (NTRS)
Bettis, D. G.
1973-01-01
A Runge-Kutta algorithm of order five is presented for the solution of the initial value problem where the system of ordinary differential equations is of second order and does not contain the first derivative. The algorithm includes the Fehlberg step control procedure.
Algorithmic Case Pedagogy, Learning and Gender
ERIC Educational Resources Information Center
Bromley, Robert; Huang, Zhenyu
2015-01-01
Great investment has been made in developing algorithmically-based cases within online homework management systems. This has been done because publishers are convinced that textbook adoption decisions are influenced by the incorporation of these systems within their products. These algorithmic assignments are thought to promote learning while…
Excursion-Set-Mediated Genetic Algorithm
NASA Technical Reports Server (NTRS)
Noever, David; Baskaran, Subbiah
1995-01-01
Excursion-set-mediated genetic algorithm (ESMGA) is embodiment of method of searching for and optimizing computerized mathematical models. Incorporates powerful search and optimization techniques based on concepts analogous to natural selection and laws of genetics. In comparison with other genetic algorithms, this one achieves stronger condition for implicit parallelism. Includes three stages of operations in each cycle, analogous to biological generation.
Explaining the Cross-Multiplication Algorithm
ERIC Educational Resources Information Center
Handa, Yuichi
2009-01-01
Many high-school mathematics teachers have likely been asked by a student, "Why does the cross-multiplication algorithm work?" It is a commonly used algorithm when dealing with proportion problems, conversion of units, or fractional linear equations. For most teachers, the explanation usually involves the idea of finding a common denominator--one…
Algorithm for genome contig assembly. Final report
1995-09-01
An algorithm was developed for genome contig assembly which extended the range of data types that could be included in assembly and which ran on the order of a hundred times faster than the algorithm it replaced. Maps of all existing cosmid clone and YAC data at the Human Genome Information Resource were assembled using ICA. The resulting maps are summarized.
The Porter Stemming Algorithm: Then and Now
ERIC Educational Resources Information Center
Willett, Peter
2006-01-01
Purpose: In 1980, Porter presented a simple algorithm for stemming English language words. This paper summarises the main features of the algorithm, and highlights its role not just in modern information retrieval research, but also in a range of related subject domains. Design/methodology/approach: Review of literature and research involving use…
Synthesis of an algorithm for interference immunity
NASA Astrophysics Data System (ADS)
Kartsan, I. N.; Tyapkin, V. N.; Dmitriev, D. D.; Goncharov, A. E.; Zelenkov, P. V.; Kovalev, I. V.
2016-11-01
This paper discusses the synthesis of an algorithm for adaptive interference nulling of an 8-element phased antenna array. An adaptive beamforming system has been built on the basis of the algorithm. The paper discusses results of experimental functioning of navigation satellite systems user equipment fitted with an adaptive phased antenna array in interference environments.
Algorithmic Mechanism Design of Evolutionary Computation.
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.
Pitch-Learning Algorithm For Speech Encoders
NASA Technical Reports Server (NTRS)
Bhaskar, B. R. Udaya
1988-01-01
Adaptive algorithm detects and corrects errors in sequence of estimates of pitch period of speech. Algorithm operates in conjunction with techniques used to estimate pitch period. Used in such parametric and hybrid speech coders as linear predictive coders and adaptive predictive coders.
QPSO-based adaptive DNA computing algorithm.
Karakose, Mehmet; Cigdem, Ugur
2013-01-01
DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm.
The [Gamma] Algorithm and Some Applications
ERIC Educational Resources Information Center
Castillo, Enrique; Jubete, Francisco
2004-01-01
In this paper the power of the [gamma] algorithm for obtaining the dual of a given cone and some of its multiple applications is discussed. The meaning of each sequential tableau appearing during the process is interpreted. It is shown that each tableau contains the generators of the dual cone of a given cone and that the algorithm updates the…
Efficient Learning Algorithms with Limited Information
ERIC Educational Resources Information Center
De, Anindya
2013-01-01
The thesis explores efficient learning algorithms in settings which are more restrictive than the PAC model of learning (Valiant) in one of the following two senses: (i) The learning algorithm has a very weak access to the unknown function, as in, it does not get labeled samples for the unknown function (ii) The error guarantee required from the…
The Porter Stemming Algorithm: Then and Now
ERIC Educational Resources Information Center
Willett, Peter
2006-01-01
Purpose: In 1980, Porter presented a simple algorithm for stemming English language words. This paper summarises the main features of the algorithm, and highlights its role not just in modern information retrieval research, but also in a range of related subject domains. Design/methodology/approach: Review of literature and research involving use…
Excursion-Set-Mediated Genetic Algorithm
NASA Technical Reports Server (NTRS)
Noever, David; Baskaran, Subbiah
1995-01-01
Excursion-set-mediated genetic algorithm (ESMGA) is embodiment of method of searching for and optimizing computerized mathematical models. Incorporates powerful search and optimization techniques based on concepts analogous to natural selection and laws of genetics. In comparison with other genetic algorithms, this one achieves stronger condition for implicit parallelism. Includes three stages of operations in each cycle, analogous to biological generation.
Force-Control Algorithm for Surface Sampling
NASA Technical Reports Server (NTRS)
Acikmese, Behcet; Quadrelli, Marco B.; Phan, Linh
2008-01-01
A G-FCON algorithm is designed for small-body surface sampling. It has a linearization component and a feedback component to enhance performance. The algorithm regulates the contact force between the tip of a robotic arm attached to a spacecraft and a surface during sampling.
Advancing-Front Algorithm For Delaunay Triangulation
NASA Technical Reports Server (NTRS)
Merriam, Marshal L.
1993-01-01
Efficient algorithm performs Delaunay triangulation to generate unstructured grids for use in computing two-dimensional flows. Once grid generated, one can optionally call upon additional subalgorithm that removes diagonal lines from quadrilateral cells nearly rectangular. Resulting approximately rectangular grid reduces cost per iteration of flow-computing algorithm.
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.
Alocomotino Control Algorithm for Robotic Linkage Systems
Dohner, Jeffrey L.
2016-10-01
This dissertation describes the development of a control algorithm that transitions a robotic linkage system between stabilized states producing responsive locomotion. The developed algorithm is demonstrated using a simple robotic construction consisting of a few links with actuation and sensing at each joint. Numerical and experimental validation is presented.
Novel algorithm for management of acute epididymitis.
Hongo, Hiroshi; Kikuchi, Eiji; Matsumoto, Kazuhiro; Yazawa, Satoshi; Kanao, Kent; Kosaka, Takeo; Mizuno, Ryuichi; Miyajima, Akira; Saito, Shiro; Oya, Mototsugu
2017-01-01
To identify predictive factors for the severity of epididymitis and to develop an algorithm guiding decisions on how to manage patients with this disease. A retrospective study was carried out on 160 epididymitis patients at Keio University Hospital. We classified cases into severe and non-severe groups, and compared clinical findings at the first visit. Based on statistical analyses, we developed an algorithm for predicting severe cases. We validated the algorithm by applying it to an external cohort of 96 patients at Tokyo Medical Center. The efficacy of the algorithm was investigated by a decision curve analysis. A total of 19 patients (11.9%) had severe epididymitis. Patient characteristics including older age, previous history of diabetes mellitus and fever, as well as laboratory data including a higher white blood cell count, C-reactive protein level and blood urea nitrogen level were independently associated with severity. A predictive algorithm was created with the ability to classify epididymitis cases into three risk groups. In the Keio University Hospital cohort, 100%, 23.5%, and 3.4% of cases in the high-, intermediate-, and low-risk groups, respectively, became severe. The specificity of the algorithm for predicting severe epididymitis proved to be 100% in the Keio University Hospital cohort and 98.8% in the Tokyo Medical Center cohort. The decision curve analysis also showed the high efficacy of the algorithm. This algorithm might aid in decision-making for the clinical management of acute epididymitis. © 2016 The Japanese Urological Association.
Genetic algorithms and the immune system
Forrest, S. . Dept. of Computer Science); Perelson, A.S. )
1990-01-01
Using genetic algorithm techniques we introduce a model to examine the hypothesis that antibody and T cell receptor genes evolved so as to encode the information needed to recognize schemas that characterize common pathogens. We have implemented the algorithm on the Connection Machine for 16,384 64-bit antigens and 512 64-bit antibodies. 8 refs.
IUS guidance algorithm gamma guide assessment
NASA Technical Reports Server (NTRS)
Bray, R. E.; Dauro, V. A.
1980-01-01
The Gamma Guidance Algorithm which controls the inertial upper stage is described. The results of an independent assessment of the algorithm's performance in satisfying the NASA missions' targeting objectives are presented. The results of a launch window analysis for a Galileo mission, and suggested improvements are included.
Derivative Free Gradient Projection Algorithms for Rotation
ERIC Educational Resources Information Center
Jennrich, Robert I.
2004-01-01
A simple modification substantially simplifies the use of the gradient projection (GP) rotation algorithms of Jennrich (2001, 2002). These algorithms require subroutines to compute the value and gradient of any specific rotation criterion of interest. The gradient can be difficult to derive and program. It is shown that using numerical gradients…
Statistical Methods in Algorithm Design and Analysis.
ERIC Educational Resources Information Center
Weide, Bruce W.
The use of statistical methods in the design and analysis of discrete algorithms is explored. The introductory chapter contains a literature survey and background material on probability theory. In Chapter 2, probabilistic approximation algorithms are discussed with the goal of exposing and correcting some oversights in previous work. Chapter 3…
Formation Algorithms and Simulation Testbed
NASA Technical Reports Server (NTRS)
Wette, Matthew; Sohl, Garett; Scharf, Daniel; Benowitz, Edward
2004-01-01
Formation flying for spacecraft is a rapidly developing field that will enable a new era of space science. For one of its missions, the Terrestrial Planet Finder (TPF) project has selected a formation flying interferometer design to detect earth-like planets orbiting distant stars. In order to advance technology needed for the TPF formation flying interferometer, the TPF project has been developing a distributed real-time testbed to demonstrate end-to-end operation of formation flying with TPF-like functionality and precision. This is the Formation Algorithms and Simulation Testbed (FAST) . This FAST was conceived to bring out issues in timing, data fusion, inter-spacecraft communication, inter-spacecraft sensing and system-wide formation robustness. In this paper we describe the FAST and show results from a two-spacecraft formation scenario. The two-spacecraft simulation is the first time that precision end-to-end formation flying operation has been demonstrated in a distributed real-time simulation environment.
The algorithmic origins of life.
Walker, Sara Imari; Davies, Paul C W
2013-02-01
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.
3D dose computation algorithms
NASA Astrophysics Data System (ADS)
Knöös, T.
2017-05-01
The calculation of absorbed dose within patients during external photon beam radiotherapy is reviewed. This includes the modelling of the radiation source i.e. in most cases a linear accelerator (beam modelling) and examples of dose calculation algorithms applied within the patient i.e. the dose engine. For the first part - the beam modelling, the different sources in the treatment head as target, filters and collimators etc are discussed as well as their importance for the photon and electron fluence reaching the patient. The consequences of removing the flattening filter, which several vendors now have made commercially available, is also shown. The pros and cons regarding different dose engines ability to consider density changes within the patient will is covered (type a and b models). Engines covered are, for example, pencil-beam models, collapsed cone superposition/-convolution models and combinations of these, as well as a glimpse on Monte Carlo methods for radiotherapy. The different models’ ability to calculate dose to medium (tissue) and or water is. Finally, the role of commissioning data especially measurements in today’s model based dose calculation is presented.
Firmware algorithms for PINGU experiment
NASA Astrophysics Data System (ADS)
Pankova, Daria; Anderson, Tyler; IceCube Collaboration
2017-01-01
PINGU is a future low energy extension for the IceCube experiment. It will be implemented as several additional closer positioned stings of digital optical modules (DOMs) inside the main detector volume. PINGU would be able to register neutrinos with energies as low as few GeV. One of the proposed designs for the new PINGU DOMs is an updated version of IceCube DOMs with newer electronic components, particularly a better more modern FPGA. With those improvements it is desirable to run some waveform feature extraction directly on the DOM, thus decreasing amount of data sent over the detector's bandwidth-limited cable. In order to use the existing feature extraction package for this purpose the signal waveform needs to be prepared by subtracting of a variable baseline from it. The baseline shape is dependant mostly on the environment temperature, which causes the long term drift of the signal, and the induction used in signal readout electronics, which modifies the signal shape. Algorithms have been selected to counter those baseline variances, modeled and partly implemented in FPGA fabric. The simulation shows good agreement between initial signal and the ``corrected'' version.
Genetic algorithms for route discovery.
Gelenbe, Erol; Liu, Peixiang; Lainé, Jeremy
2006-12-01
Packet routing in networks requires knowledge about available paths, which can be either acquired dynamically while the traffic is being forwarded, or statically (in advance) based on prior information of a network's topology. This paper describes an experimental investigation of path discovery using genetic algorithms (GAs). We start with the quality-of-service (QoS)-driven routing protocol called "cognitive packet network" (CPN), which uses smart packets (SPs) to dynamically select routes in a distributed autonomic manner based on a user's QoS requirements. We extend it by introducing a GA at the source routers, which modifies and filters the paths discovered by the CPN. The GA can combine the paths that were previously discovered to create new untested but valid source-to-destination paths, which are then selected on the basis of their "fitness." We present an implementation of this approach, where the GA runs in background mode so as not to overload the ingress routers. Measurements conducted on a network test bed indicate that when the background-traffic load of the network is light to medium, the GA can result in improved QoS. When the background-traffic load is high, it appears that the use of the GA may be detrimental to the QoS experienced by users as compared to CPN routing because the GA uses less timely state information in its decision making.
Advanced algorithms for information science
Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.
1998-12-31
This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression.
Petascale algorithms for reactor hydrodynamics.
Fischer, P.; Lottes, J.; Pointer, W. D.; Siegel, A.
2008-01-01
We describe recent algorithmic developments that have enabled large eddy simulations of reactor flows on up to P = 65, 000 processors on the IBM BG/P at the Argonne Leadership Computing Facility. Petascale computing is expected to play a pivotal role in the design and analysis of next-generation nuclear reactors. Argonne's SHARP project is focused on advanced reactor simulation, with a current emphasis on modeling coupled neutronics and thermal-hydraulics (TH). The TH modeling comprises a hierarchy of computational fluid dynamics approaches ranging from detailed turbulence computations, using DNS (direct numerical simulation) and LES (large eddy simulation), to full core analysis based on RANS (Reynolds-averaged Navier-Stokes) and subchannel models. Our initial study is focused on LES of sodium-cooled fast reactor cores. The aim is to leverage petascale platforms at DOE's Leadership Computing Facilities (LCFs) to provide detailed information about heat transfer within the core and to provide baseline data for less expensive RANS and subchannel models.
Gear Tooth Wear Detection Algorithm
NASA Technical Reports Server (NTRS)
Delgado, Irebert R.
2015-01-01
Vibration-based condition indicators continue to be developed for Health Usage Monitoring of rotorcraft gearboxes. Testing performed at NASA Glenn Research Center have shown correlations between specific condition indicators and specific types of gear wear. To speed up the detection and analysis of gear teeth, an image detection program based on the Viola-Jones algorithm was trained to automatically detect spiral bevel gear wear pitting. The detector was tested using a training set of gear wear pictures and a blind set of gear wear pictures. The detector accuracy for the training set was 75 percent while the accuracy for the blind set was 15 percent. Further improvements on the accuracy of the detector are required but preliminary results have shown its ability to automatically detect gear tooth wear. The trained detector would be used to quickly evaluate a set of gear or pinion pictures for pits, spalls, or abrasive wear. The results could then be used to correlate with vibration or oil debris data. In general, the program could be retrained to detect features of interest from pictures of a component taken over a period of time.
Towards Robust Image Matching Algorithms
NASA Astrophysics Data System (ADS)
Parsons, Timothy J.
1984-12-01
The rapid advance in digital electronics during recent years has enabled the real-time hardware implementation of many basic image processing techniques and these methods are finding increasing use in both commercial and military applications where a superiority to existing systems can be demonstrated. The potential superiority of an entirely passive, automatic image processing based navigation system over the less accurate and active navigation systems based on radar, for example "TERCOM", is evident. By placing a sensor on board an aircraft or missile together with the appropriate processing power and enough memory to store a reference image or a map of the planned route, large scale features extracted from the scene available to the sensor can be compared with the same feature stored in memory. The difference between the aircraft's actual position and its desired position can then be evaluated and the appropriate navigational correction undertaken. This paper summaries work carried out at British Aerospace Hatfield to investigate various classes of algorithms and solutions which would render a robust image matching system viable for such an automatic system flying at low level with a thermal I.R. sensor.
Efficient multiple-way graph partitioning algorithms
Dasdan, A.; Aykanat, C.
1995-12-01
Graph partitioning deals with evenly dividing a graph into two or more parts such that the total weight of edges interconnecting these parts, i.e., cutsize, is minimized. Graph partitioning has important applications in VLSI layout, mapping, and sparse Gaussian elimination. Since graph partitioning problem is NP-hard, we should resort to polynomial-time algorithms to obtain a good solution, or hopefully a near-optimal solution. Kernighan-Lin (KL) propsoed a 2-way partitioning algorithms. Fiduccia-Mattheyses (FM) introduced a faster version of KL algorithm. Sanchis (FMS) generalized FM algorithm to a multiple-way partitioning algorithm. Simulated Annealing (SA) is one of the most successful approaches that are not KL-based.
Algorithms for radio networks with dynamic topology
NASA Astrophysics Data System (ADS)
Shacham, Nachum; Ogier, Richard; Rutenburg, Vladislav V.; Garcia-Luna-Aceves, Jose
1991-08-01
The objective of this project was the development of advanced algorithms and protocols that efficiently use network resources to provide optimal or nearly optimal performance in future communication networks with highly dynamic topologies and subject to frequent link failures. As reflected by this report, we have achieved our objective and have significantly advanced the state-of-the-art in this area. The research topics of the papers summarized include the following: efficient distributed algorithms for computing shortest pairs of disjoint paths; minimum-expected-delay alternate routing algorithms for highly dynamic unreliable networks; algorithms for loop-free routing; multipoint communication by hierarchically encoded data; efficient algorithms for extracting the maximum information from event-driven topology updates; methods for the neural network solution of link scheduling and other difficult problems arising in communication networks; and methods for robust routing in networks subject to sophisticated attacks.
Algorithms for improved performance in cryptographic protocols.
Schroeppel, Richard Crabtree; Beaver, Cheryl Lynn
2003-11-01
Public key cryptographic algorithms provide data authentication and non-repudiation for electronic transmissions. The mathematical nature of the algorithms, however, means they require a significant amount of computation, and encrypted messages and digital signatures possess high bandwidth. Accordingly, there are many environments (e.g. wireless, ad-hoc, remote sensing networks) where public-key requirements are prohibitive and cannot be used. The use of elliptic curves in public-key computations has provided a means by which computations and bandwidth can be somewhat reduced. We report here on the research conducted in an LDRD aimed to find even more efficient algorithms and to make public-key cryptography available to a wider range of computing environments. We improved upon several algorithms, including one for which a patent has been applied. Further we discovered some new problems and relations on which future cryptographic algorithms may be based.
A Learning Algorithm for Multimodal Grammar Inference.
D'Ulizia, A; Ferri, F; Grifoni, P
2011-12-01
The high costs of development and maintenance of multimodal grammars in integrating and understanding input in multimodal interfaces lead to the investigation of novel algorithmic solutions in automating grammar generation and in updating processes. Many algorithms for context-free grammar inference have been developed in the natural language processing literature. An extension of these algorithms toward the inference of multimodal grammars is necessary for multimodal input processing. In this paper, we propose a novel grammar inference mechanism that allows us to learn a multimodal grammar from its positive samples of multimodal sentences. The algorithm first generates the multimodal grammar that is able to parse the positive samples of sentences and, afterward, makes use of two learning operators and the minimum description length metrics in improving the grammar description and in avoiding the over-generalization problem. The experimental results highlight the acceptable performances of the algorithm proposed in this paper since it has a very high probability of parsing valid sentences.
Algorithms for security in robotics and networks
NASA Astrophysics Data System (ADS)
Simov, Borislav Hristov
The dissertation presents algorithms for robotics and security. The first chapter gives an overview of the area of visibility-based pursuit-evasion. The following two chapters introduce two specific algorithms in that area. The algorithms are based on research done together with Dr. Giora Slutzki and Dr. Steven LaValle. Chapter 2 presents a polynomial-time algorithm for clearing a polygon by a single 1-searcher. The result is extended to a polynomial-time algorithm for a pair of 1-searchers in Chapter 3. Chapters 4 and 5 contain joint research with Dr. Srini Tridandapani, Dr. Jason Jue and Dr. Michael Borella in the area of computer networks. Chapter 4 presents a method of providing privacy over an insecure channel which does not require encryption. Chapter 5 gives approximate bounds for the link utilization in multicast traffic.
Evolutionary development of path planning algorithms
Hage, M
1998-09-01
This paper describes the use of evolutionary software techniques for developing both genetic algorithms and genetic programs. Genetic algorithms are evolved to solve a specific problem within a fixed and known environment. While genetic algorithms can evolve to become very optimized for their task, they often are very specialized and perform poorly if the environment changes. Genetic programs are evolved through simultaneous training in a variety of environments to develop a more general controller behavior that operates in unknown environments. Performance of genetic programs is less optimal than a specially bred algorithm for an individual environment, but the controller performs acceptably under a wider variety of circumstances. The example problem addressed in this paper is evolutionary development of algorithms and programs for path planning in nuclear environments, such as Chernobyl.
MM Algorithms for Geometric and Signomial Programming.
Lange, Kenneth; Zhou, Hua
2014-02-01
This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.
A Parallel Rendering Algorithm for MIMD Architectures
NASA Technical Reports Server (NTRS)
Crockett, Thomas W.; Orloff, Tobias
1991-01-01
Applications such as animation and scientific visualization demand high performance rendering of complex three dimensional scenes. To deliver the necessary rendering rates, highly parallel hardware architectures are required. The challenge is then to design algorithms and software which effectively use the hardware parallelism. A rendering algorithm targeted to distributed memory MIMD architectures is described. For maximum performance, the algorithm exploits both object-level and pixel-level parallelism. The behavior of the algorithm is examined both analytically and experimentally. Its performance for large numbers of processors is found to be limited primarily by communication overheads. An experimental implementation for the Intel iPSC/860 shows increasing performance from 1 to 128 processors across a wide range of scene complexities. It is shown that minimal modifications to the algorithm will adapt it for use on shared memory architectures as well.
Algorithm refinement for the stochastic Burgers' equation
Bell, John B.; Foo, Jasmine; Garcia, Alejandro L. . E-mail: algarcia@algarcia.org
2007-04-10
In this paper, we develop an algorithm refinement (AR) scheme for an excluded random walk model whose mean field behavior is given by the viscous Burgers' equation. AR hybrids use the adaptive mesh refinement framework to model a system using a molecular algorithm where desired while allowing a computationally faster continuum representation to be used in the remainder of the domain. The focus in this paper is the role of fluctuations on the dynamics. In particular, we demonstrate that it is necessary to include a stochastic forcing term in Burgers' equation to accurately capture the correct behavior of the system. The conclusion we draw from this study is that the fidelity of multiscale methods that couple disparate algorithms depends on the consistent modeling of fluctuations in each algorithm and on a coupling, such as algorithm refinement, that preserves this consistency.
An efficient quantum algorithm for spectral estimation
NASA Astrophysics Data System (ADS)
Steffens, Adrian; Rebentrost, Patrick; Marvian, Iman; Eisert, Jens; Lloyd, Seth
2017-03-01
We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of exponentially damped sinusoids. Our algorithm provides a quantum speedup in a natural regime where the sampling rate is much higher than the number of sinusoid components. Along the way, we develop techniques that are expected to be useful for other quantum algorithms as well—consecutive phase estimations to efficiently make products of asymmetric low rank matrices classically accessible and an alternative method to efficiently exponentiate non-Hermitian matrices. Our algorithm features an efficient quantum–classical division of labor: the time-critical steps are implemented in quantum superposition, while an interjacent step, requiring much fewer parameters, can operate classically. We show that frequencies and damping factors can be obtained in time logarithmic in the number of sampling points, exponentially faster than known classical algorithms.
Learning theory of distributed spectral algorithms
NASA Astrophysics Data System (ADS)
Guo, Zheng-Chu; Lin, Shao-Bo; Zhou, Ding-Xuan
2017-07-01
Spectral algorithms have been widely used and studied in learning theory and inverse problems. This paper is concerned with distributed spectral algorithms, for handling big data, based on a divide-and-conquer approach. We present a learning theory for these distributed kernel-based learning algorithms in a regression framework including nice error bounds and optimal minimax learning rates achieved by means of a novel integral operator approach and a second order decomposition of inverse operators. Our quantitative estimates are given in terms of regularity of the regression function, effective dimension of the reproducing kernel Hilbert space, and qualification of the filter function of the spectral algorithm. They do not need any eigenfunction or noise conditions and are better than the existing results even for the classical family of spectral algorithms.
MM Algorithms for Geometric and Signomial Programming
Lange, Kenneth; Zhou, Hua
2013-01-01
This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates. PMID:24634545
Marshall Rosenbluth and the Metropolis algorithm
Gubernatis, J.E.
2005-05-15
The 1953 publication, 'Equation of State Calculations by Very Fast Computing Machines' by N. Metropolis, A. W. Rosenbluth and M. N. Rosenbluth, and M. Teller and E. Teller [J. Chem. Phys. 21, 1087 (1953)] marked the beginning of the use of the Monte Carlo method for solving problems in the physical sciences. The method described in this publication subsequently became known as the Metropolis algorithm, undoubtedly the most famous and most widely used Monte Carlo algorithm ever published. As none of the authors made subsequent use of the algorithm, they became unknown to the large simulation physics community that grew from this publication and their roles in its development became the subject of mystery and legend. At a conference marking the 50th anniversary of the 1953 publication, Marshall Rosenbluth gave his recollections of the algorithm's development. The present paper describes the algorithm, reconstructs the historical context in which it was developed, and summarizes Marshall's recollections.
Passive microwave algorithm development and evaluation
NASA Technical Reports Server (NTRS)
Petty, Grant W.
1995-01-01
The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.
A region labeling algorithm based on block
NASA Astrophysics Data System (ADS)
Wang, Jing
2009-10-01
The time performance of region labeling algorithm is important for image process. However, common region labeling algorithms cannot meet the requirements of real-time image processing. In this paper, a technique using block to record the connective area is proposed. By this technique, connective closure and information related to the target can be computed during a one-time image scan. It records the edge pixel's coordinate, including outer side edges and inner side edges, as well as the label, and then it can calculate connecting area's shape center, area and gray. Compared to others, this block based region labeling algorithm is more efficient. It can well meet the time requirements of real-time processing. Experiment results also validate the correctness and efficiency of the algorithm. Experiment results show that it can detect any connecting areas in binary images, which contains various complex and quaint patterns. The block labeling algorithm is used in a real-time image processing program now.
Theoretical convergence guarantees for cooperative coevolutionary algorithms.
Panait, Liviu
2010-01-01
Cooperative coevolutionary algorithms have the potential to significantly speed up the search process by dividing the space into parts that can each be conquered separately. However, recent research presented theoretical and empirical arguments that these algorithms tend to converge to suboptimal solutions in the search space, and are thus not fit for optimization tasks. This paper details an extended formal model for cooperative coevolutionary algorithms, and uses it to explore possible reasons these algorithms converge to optimal or suboptimal solutions. We demonstrate that, under specific conditions, this theoretical model will converge to the globally optimal solution. The proofs provide the underlying theoretical foundation for a better application of cooperative coevolutionary algorithms. We demonstrate the practical advantages of applying ideas from this theoretical work to a simple problem domain.
A Parametric k-Means Algorithm
Tarpey, Thaddeus
2007-01-01
Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692
Efficient hybrid algorithms for collisional plasma simulation
NASA Astrophysics Data System (ADS)
Dimits, A. M.; Cohen, B. I.; Caflisch, R. E.; Wang, C. M.; Huang, Y.
2009-11-01
We report on the development of efficient hybrid simulation algorithms for plasma systems that span a wide range of collisionality. Investigations of their performance, using ion-sheath and electron-transport test problems, are presented. In these schemes the distribution function is decomposed of into kinetic and fluid components. The fluid component is treated via Eulerian fluid simulation methods. In one class of algorithms, the kinetic component is treated using a combination of fixed-weight particle-in-cell (PIC) and binary Monte-Carlo collision methods. Particles are created by sampling from the fluid component, and paired for collisions with the kinetic particles. In the other class of algorithms, the kinetic component is treated using evolving-weight delta-f-PIC schemes and collision-field algorithms. The performance these algorithms depends strongly on the particular sets of criteria for (a) exchange between the particle and fluid components and (b) creation, destruction, and retention of the simulation particles.
A new algorithm for coding geological terminology
NASA Astrophysics Data System (ADS)
Apon, W.
The Geological Survey of The Netherlands has developed an algorithm to convert the plain geological language of lithologic well logs into codes suitable for computer processing and link these to existing plotting programs. The algorithm is based on the "direct method" and operates in three steps: (1) searching for defined word combinations and assigning codes; (2) deleting duplicated codes; (3) correcting incorrect code combinations. Two simple auxiliary files are used. A simple PC demonstration program is included to enable readers to experiment with this algorithm. The Department of Quarternary Geology of the Geological Survey of The Netherlands possesses a large database of shallow lithologic well logs in plain language and has been using a program based on this algorithm for about 3 yr. Erroneous codes resulting from using this algorithm are less than 2%.
Automatic ionospheric layers detection: Algorithms analysis
NASA Astrophysics Data System (ADS)
Molina, María G.; Zuccheretti, Enrico; Cabrera, Miguel A.; Bianchi, Cesidio; Sciacca, Umberto; Baskaradas, James
2016-03-01
Vertical sounding is a widely used technique to obtain ionosphere measurements, such as an estimation of virtual height versus frequency scanning. It is performed by high frequency radar for geophysical applications called ;ionospheric sounder; (or ;ionosonde;). Radar detection depends mainly on targets characteristics. While several targets behavior and correspondent echo detection algorithms have been studied, a survey to address a suitable algorithm for ionospheric sounder has to be carried out. This paper is focused on automatic echo detection algorithms implemented in particular for an ionospheric sounder, target specific characteristics were studied as well. Adaptive threshold detection algorithms are proposed, compared to the current implemented algorithm, and tested using actual data obtained from the Advanced Ionospheric Sounder (AIS-INGV) at Rome Ionospheric Observatory. Different cases of study have been selected according typical ionospheric and detection conditions.
A Parametric k-Means Algorithm.
Tarpey, Thaddeus
2007-04-01
The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm.
GOES-R Algorithm Working Group (AWG)
NASA Astrophysics Data System (ADS)
Daniels, Jaime; Goldberg, Mitch; Wolf, Walter; Zhou, Lihang; Lowe, Kenneth
2009-08-01
For the next-generation of GOES-R instruments to meet stated performance requirements, state-of-the-art algorithms will be needed to convert raw instrument data to calibrated radiances and derived geophysical parameters (atmosphere, land, ocean, and space weather). The GOES-R Program Office (GPO) assigned the NOAA/NESDIS Center for Satellite Research and Applications (STAR) the responsibility for technical leadership and management of GOES-R algorithm development and calibration/validation. STAR responded with the creation of the GOES-R Algorithm Working Group (AWG) to manage and coordinate development and calibration/validation activities for GOES-R proxy data and geophysical product algorithms. The AWG consists of 15 application teams that bring expertise in product algorithms that span atmospheric, land, oceanic, and space weather disciplines. Each AWG teams will develop new scientific Level- 2 algorithms for GOES-R and will also leverage science developments from other communities (other government agencies, universities and industry), and heritage approaches from current operational GOES and POES product systems. All algorithms will be demonstrated and validated in a scalable operational demonstration environment. All software developed by the AWG will adhere to new standards established within NOAA/NESDIS. The AWG Algorithm Integration Team (AIT) has the responsibility for establishing the system framework, integrating the product software from each team into this framework, enforcing the established software development standards, and preparing system deliveries. The AWG will deliver an Algorithm Theoretical Basis Document (ATBD) for each GOES-R geophysical product as well as Delivered Algorithm Packages (DAPs) to the GPO.
Exploration of new multivariate spectral calibration algorithms.
Van Benthem, Mark Hilary; Haaland, David Michael; Melgaard, David Kennett; Martin, Laura Elizabeth; Wehlburg, Christine Marie; Pell, Randy J.; Guenard, Robert D.
2004-03-01
A variety of multivariate calibration algorithms for quantitative spectral analyses were investigated and compared, and new algorithms were developed in the course of this Laboratory Directed Research and Development project. We were able to demonstrate the ability of the hybrid classical least squares/partial least squares (CLSIPLS) calibration algorithms to maintain calibrations in the presence of spectrometer drift and to transfer calibrations between spectrometers from the same or different manufacturers. These methods were found to be as good or better in prediction ability as the commonly used partial least squares (PLS) method. We also present the theory for an entirely new class of algorithms labeled augmented classical least squares (ACLS) methods. New factor selection methods are developed and described for the ACLS algorithms. These factor selection methods are demonstrated using near-infrared spectra collected from a system of dilute aqueous solutions. The ACLS algorithm is also shown to provide improved ease of use and better prediction ability than PLS when transferring calibrations between near-infrared calibrations from the same manufacturer. Finally, simulations incorporating either ideal or realistic errors in the spectra were used to compare the prediction abilities of the new ACLS algorithm with that of PLS. We found that in the presence of realistic errors with non-uniform spectral error variance across spectral channels or with spectral errors correlated between frequency channels, ACLS methods generally out-performed the more commonly used PLS method. These results demonstrate the need for realistic error structure in simulations when the prediction abilities of various algorithms are compared. The combination of equal or superior prediction ability and the ease of use of the ACLS algorithms make the new ACLS methods the preferred algorithms to use for multivariate spectral calibrations.
Annealed Importance Sampling Reversible Jump MCMC algorithms
Karagiannis, Georgios; Andrieu, Christophe
2013-03-20
It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappings underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.
Recent Advancements in Lightning Jump Algorithm Work
NASA Technical Reports Server (NTRS)
Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.
2010-01-01
In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).
Enghauser, Michael
2015-02-01
The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.
Enghauser, Michael
2016-02-01
The goal of the Domestic Nuclear Detection Office (DNDO) Algorithm Improvement Program (AIP) is to facilitate gamma-radiation detector nuclide identification algorithm development, improvement, and validation. Accordingly, scoring criteria have been developed to objectively assess the performance of nuclide identification algorithms. In addition, a Microsoft Excel spreadsheet application for automated nuclide identification scoring has been developed. This report provides an overview of the equations, nuclide weighting factors, nuclide equivalencies, and configuration weighting factors used by the application for scoring nuclide identification algorithm performance. Furthermore, this report presents a general overview of the nuclide identification algorithm scoring application including illustrative examples.
NASA Astrophysics Data System (ADS)
Zheng, Genrang; Lin, ZhengChun
The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.
Zhong, Liyun; Li, Hongyan; Tao, Tao; Zhang, Zhun; Lu, Xiaoxu
2011-11-07
To reach the limiting resolution of a digital holographic system and improve the displaying quality of the reconstructed image, the subdivision convolution algorithm and the subdivision Fresnel algorithm are presented, respectively. The obtained results show that the lateral size of the reconstructed image obtained by two kinds of subdivision algorithms is the same in the central region of the reconstructed image-plane; moreover, the size of the central region is in proportional to the recording distance. Importantly, in the central region of the reconstructed image-plane, the reconstruction can be performed by the subdivision Fresnel algorithm instead of the subdivision convolution algorithm effectively, and, based on these subdivision approaches, both the displaying quality and the resolution of the reconstructed image can be improved significantly. Furthermore, in the reconstruction of the digital hologram with the large numerical aperture, the computer's memory consumed and the calculating time resulting from the subdivision Fresnel algorithm is significantly less than those from the subdivision convolution algorithm.
A new algorithm for attitude-independent magnetometer calibration
NASA Technical Reports Server (NTRS)
Alonso, Roberto; Shuster, Malcolm D.
1994-01-01
A new algorithm is developed for inflight magnetometer bias determination without knowledge of the attitude. This algorithm combines the fast convergence of a heuristic algorithm currently in use with the correct treatment of the statistics and without discarding data. The algorithm performance is examined using simulated data and compared with previous algorithms.
Learning Algorithm for the Uniform Graph Partitioning Problem
NASA Astrophysics Data System (ADS)
Chua, C. B.; Chen, Kan
We study the uniform graph partitioning problem using the learning algorithm proposed by one of us. We discuss the characteristics of the learning algorithm and compare the performance of the algorithm empirically with the Kernighan-Lin algorithm on a range of instances. Even with a simple implementation, the learning algorithm is capable of producing very good results.
SAGE II inversion algorithm. [Stratospheric Aerosol and Gas Experiment
NASA Technical Reports Server (NTRS)
Chu, W. P.; Mccormick, M. P.; Lenoble, J.; Brogniez, C.; Pruvost, P.
1989-01-01
The operational Stratospheric Aerosol and Gas Experiment II multichannel data inversion algorithm is described. Aerosol and ozone retrievals obtained with the algorithm are discussed. The algorithm is compared to an independently developed algorithm (Lenoble, 1989), showing that the inverted aerosol and ozone profiles from the two algorithms are similar within their respective uncertainties.
Parallelization of Edge Detection Algorithm using MPI on Beowulf Cluster
NASA Astrophysics Data System (ADS)
Haron, Nazleeni; Amir, Ruzaini; Aziz, Izzatdin A.; Jung, Low Tan; Shukri, Siti Rohkmah
In this paper, we present the design of parallel Sobel edge detection algorithm using Foster's methodology. The parallel algorithm is implemented using MPI message passing library and master/slave algorithm. Every processor performs the same sequential algorithm but on different part of the image. Experimental results conducted on Beowulf cluster are presented to demonstrate the performance of the parallel algorithm.
ALGORITHM FOR SORTING GROUPED DATA
NASA Technical Reports Server (NTRS)
Evans, J. D.
1994-01-01
It is often desirable to sort data sets in ascending or descending order. This becomes more difficult for grouped data, i.e., multiple sets of data, where each set of data involves several measurements or related elements. The sort becomes increasingly cumbersome when more than a few elements exist for each data set. In order to achieve an efficient sorting process, an algorithm has been devised in which the maximum most significant element is found, and then compared to each element in succession. The program was written to handle the daily temperature readings of the Voyager spacecraft, particularly those related to the special tracking requirements of Voyager 2. By reducing each data set to a single representative number, the sorting process becomes very easy. The first step in the process is to reduce the data set of width 'n' to a data set of width '1'. This is done by representing each data set by a polynomial of length 'n' based on the differences of the maximum and minimum elements. These single numbers are then sorted and converted back to obtain the original data sets. Required input data are the name of the data file to read and sort, and the starting and ending record numbers. The package includes a sample data file, containing 500 sets of data with 5 elements in each set. This program will perform a sort of the 500 data sets in 3 - 5 seconds on an IBM PC-AT with a hard disk; on a similarly equipped IBM PC-XT the time is under 10 seconds. This program is written in BASIC (specifically the Microsoft QuickBasic compiler) for interactive execution and has been implemented on the IBM PC computer series operating under PC-DOS with a central memory requirement of approximately 40K of 8 bit bytes. A hard disk is desirable for speed considerations, but is not required. This program was developed in 1986.
Beard reconstruction: A surgical algorithm.
Ninkovic, M; Heidekrueger, P I; Ehrl, D; von Spiegel, F; Broer, P N
2016-06-01
Facial defects with loss of hair-bearing regions can be caused by trauma, infection, tumor excision, or burn injury. The presented analysis evaluates a series of different surgical approaches with a focus on male beard reconstruction, emphasizing the role of tissue expansion of regional and free flaps. Locoregional and free flap reconstructions were performed in 11 male patients with 14 facial defects affecting the hair-bearing bucco-mandibular or perioral region. In order to minimize donor-site morbidity and obtain large amounts of thin, pliable, hair-bearing tissue, pre-expansion was performed in five of 14 patients. Eight of 14 patients were treated with locoregional flap reconstructions and six with free flap reconstructions. Algorithms regarding pre- and intraoperative decision making are discussed and long-term (mean follow-up 1.5 years) results analyzed. Major complications, including tissue expander infection with the need for removal or exchange, partial or full flap loss, occurred in 0% (0/8) of patients with locoregional flaps and in 17% (1/6) of patients undergoing free flap reconstructions. Secondary refinement surgery was performed in 25% (2/8) of locoregional flaps and in 67% (4/6) of free flaps. Both locoregional and distant tissue transfers play a role in beard reconstruction, while pre-expansion remains an invaluable tool. Paying attention to the presented principles and considering the significance of aesthetic facial subunits, range of motion, aesthetics, and patient satisfaction were improved long term in all our patients while minimizing donor-site morbidity. Copyright © 2016 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.
ALGORITHM FOR SORTING GROUPED DATA
NASA Technical Reports Server (NTRS)
Evans, J. D.
1994-01-01
It is often desirable to sort data sets in ascending or descending order. This becomes more difficult for grouped data, i.e., multiple sets of data, where each set of data involves several measurements or related elements. The sort becomes increasingly cumbersome when more than a few elements exist for each data set. In order to achieve an efficient sorting process, an algorithm has been devised in which the maximum most significant element is found, and then compared to each element in succession. The program was written to handle the daily temperature readings of the Voyager spacecraft, particularly those related to the special tracking requirements of Voyager 2. By reducing each data set to a single representative number, the sorting process becomes very easy. The first step in the process is to reduce the data set of width 'n' to a data set of width '1'. This is done by representing each data set by a polynomial of length 'n' based on the differences of the maximum and minimum elements. These single numbers are then sorted and converted back to obtain the original data sets. Required input data are the name of the data file to read and sort, and the starting and ending record numbers. The package includes a sample data file, containing 500 sets of data with 5 elements in each set. This program will perform a sort of the 500 data sets in 3 - 5 seconds on an IBM PC-AT with a hard disk; on a similarly equipped IBM PC-XT the time is under 10 seconds. This program is written in BASIC (specifically the Microsoft QuickBasic compiler) for interactive execution and has been implemented on the IBM PC computer series operating under PC-DOS with a central memory requirement of approximately 40K of 8 bit bytes. A hard disk is desirable for speed considerations, but is not required. This program was developed in 1986.
Distributed sensor data compression algorithm
NASA Astrophysics Data System (ADS)
Ambrose, Barry; Lin, Freddie
2006-04-01
Theoretically it is possible for two sensors to reliably send data at rates smaller than the sum of the necessary data rates for sending the data independently, essentially taking advantage of the correlation of sensor readings to reduce the data rate. In 2001, Caltech researchers Michelle Effros and Qian Zhao developed new techniques for data compression code design for correlated sensor data, which were published in a paper at the 2001 Data Compression Conference (DCC 2001). These techniques take advantage of correlations between two or more closely positioned sensors in a distributed sensor network. Given two signals, X and Y, the X signal is sent using standard data compression. The goal is to design a partition tree for the Y signal. The Y signal is sent using a code based on the partition tree. At the receiving end, if ambiguity arises when using the partition tree to decode the Y signal, the X signal is used to resolve the ambiguity. We have extended this work to increase the efficiency of the code search algorithms. Our results have shown that development of a highly integrated sensor network protocol that takes advantage of a correlation in sensor readings can result in 20-30% sensor data transport cost savings. In contrast, the best possible compression using state-of-the-art compression techniques that did not take into account the correlation of the incoming data signals achieved only 9-10% compression at most. This work was sponsored by MDA, but has very widespread applicability to ad hoc sensor networks, hyperspectral imaging sensors and vehicle health monitoring sensors for space applications.
Least significant qubit algorithm for quantum images
NASA Astrophysics Data System (ADS)
Sang, Jianzhi; Wang, Shen; Li, Qiong
2016-11-01
To study the feasibility of the classical image least significant bit (LSB) information hiding algorithm on quantum computer, a least significant qubit (LSQb) information hiding algorithm of quantum image is proposed. In this paper, we focus on a novel quantum representation for color digital images (NCQI). Firstly, by designing the three qubits comparator and unitary operators, the reasonability and feasibility of LSQb based on NCQI are presented. Then, the concrete LSQb information hiding algorithm is proposed, which can realize the aim of embedding the secret qubits into the least significant qubits of RGB channels of quantum cover image. Quantum circuit of the LSQb information hiding algorithm is also illustrated. Furthermore, the secrets extracting algorithm and circuit are illustrated through utilizing control-swap gates. The two merits of our algorithm are: (1) it is absolutely blind and (2) when extracting secret binary qubits, it does not need any quantum measurement operation or any other help from classical computer. Finally, simulation and comparative analysis show the performance of our algorithm.
Passive MMW algorithm performance characterization using MACET
NASA Astrophysics Data System (ADS)
Williams, Bradford D.; Watson, John S.; Amphay, Sengvieng A.
1997-06-01
As passive millimeter wave sensor technology matures, algorithms which are tailored to exploit the benefits of this technology are being developed. The expedient development of such algorithms requires an understanding of not only the gross phenomenology, but also specific quirks and limitations inherent in sensors and the data gathering methodology specific to this regime. This level of understanding is approached as the technology matures and increasing amounts of data become available for analysis. The Armament Directorate of Wright Laboratory, WL/MN, has spearheaded the advancement of passive millimeter-wave technology in algorithm development tools and modeling capability as well as sensor development. A passive MMW channel is available within WL/MNs popular multi-channel modeling program Irma, and a sample passive MMW algorithm is incorporated into the Modular Algorithm Concept Evaluation Tool, an algorithm development and evaluation system. The Millimeter Wave Analysis of Passive Signatures system provides excellent data collection capability in the 35, 60, and 95 GHz MMW bands. This paper exploits these assets for the study of the PMMW signature of a High Mobility Multi- Purpose Wheeled Vehicle in the three bands mentioned, and the effect of camouflage upon this signature and autonomous target recognition algorithm performance.
An algorithmic approach to crustal deformation analysis
NASA Technical Reports Server (NTRS)
Iz, Huseyin Baki
1987-01-01
In recent years the analysis of crustal deformation measurements has become important as a result of current improvements in geodetic methods and an increasing amount of theoretical and observational data provided by several earth sciences. A first-generation data analysis algorithm which combines a priori information with current geodetic measurements was proposed. Relevant methods which can be used in the algorithm were discussed. Prior information is the unifying feature of this algorithm. Some of the problems which may arise through the use of a priori information in the analysis were indicated and preventive measures were demonstrated. The first step in the algorithm is the optimal design of deformation networks. The second step in the algorithm identifies the descriptive model of the deformation field. The final step in the algorithm is the improved estimation of deformation parameters. Although deformation parameters are estimated in the process of model discrimination, they can further be improved by the use of a priori information about them. According to the proposed algorithm this information must first be tested against the estimates calculated using the sample data only. Null-hypothesis testing procedures were developed for this purpose. Six different estimators which employ a priori information were examined. Emphasis was put on the case when the prior information is wrong and analytical expressions for possible improvements under incompatible prior information were derived.
Algorithm Optimally Allocates Actuation of a Spacecraft
NASA Technical Reports Server (NTRS)
Motaghedi, Shi
2007-01-01
A report presents an algorithm that solves the following problem: Allocate the force and/or torque to be exerted by each thruster and reaction-wheel assembly on a spacecraft for best performance, defined as minimizing the error between (1) the total force and torque commanded by the spacecraft control system and (2) the total of forces and torques actually exerted by all the thrusters and reaction wheels. The algorithm incorporates the matrix vector relationship between (1) the total applied force and torque and (2) the individual actuator force and torque values. It takes account of such constraints as lower and upper limits on the force or torque that can be applied by a given actuator. The algorithm divides the aforementioned problem into two optimization problems that it solves sequentially. These problems are of a type, known in the art as semi-definite programming problems, that involve linear matrix inequalities. The algorithm incorporates, as sub-algorithms, prior algorithms that solve such optimization problems very efficiently. The algorithm affords the additional advantage that the solution requires the minimum rate of consumption of fuel for the given best performance.
Improved wavefront reconstruction algorithm from slope measurements
NASA Astrophysics Data System (ADS)
Phuc, Phan Huy; Manh, Nguyen The; Rhee, Hyug-Gyo; Ghim, Young-Sik; Yang, Ho-Soon; Lee, Yun-Woo
2017-03-01
In this paper, we propose a wavefront reconstruction algorithm from slope measurements based on a zonal method. In this algorithm, the slope measurement sampling geometry used is the Southwell geometry, in which the phase values and the slope data are measured at the same nodes. The proposed algorithm estimates the phase value at a node point using the slope measurements of eight points around the node, as doing so is believed to result in better accuracy with regard to the wavefront. For optimization of the processing time, a successive over-relaxation method is applied to iteration loops. We use a trial-and-error method to determine the best relaxation factor for each type of wavefront in order to optimize the iteration time and, thus, the processing time of the algorithm. Specifically, for a circularly symmetric wavefront, the convergence rate of the algorithm can be improved by using the result of a Fourier Transform as an initial value for the iteration. Various simulations are presented to demonstrate the improvements realized when using the proposed algorithm. Several experimental measurements of deflectometry are also processed by using the proposed algorithm.