Glen R. Longhurst
2008-12-01
The TMAP Code was written at the Idaho National Engineering and Environmental Laboratory by Brad Merrill and James Jones in the late 1980s as a tool for safety analysis of systems involving tritium. Since then it was upgraded to TMAP4 and has been used in numerous applications including experiments supporting fusion safety, predictions for advanced systems such as the International Thermonuclear Experimental Reactor (ITER), and estimates involving tritium production technologies. Its further upgrade to TMAP2000 and now to TMAP7 was accomplished in response to several needs. TMAP and TMAP4 had the capacity to deal with only a single trap for diffusing gaseous species in solid structures. TMAP7 includes up to three separate traps and up to 10 diffusing species. The original code had difficulty dealing with heteronuclear molecule formation such as HD and DT under solution-law dependent diffusion boundary conditions. That difficulty has been overcome. TMAP7 automatically generates heteronuclear molecular partial pressures when solubilities and partial pressures of the homonuclear molecular species are provided for law-dependent diffusion boundary conditions. A further sophistication is the addition of non-diffusing surface species. Atoms such as oxygen or nitrogen or formation and decay or combination of hydroxyl radicals on metal surfaces are sometimes important in reactions with diffusing hydrogen isotopes but do not themselves diffuse appreciably in the material. TMAP7 will accommodate up to 30 such surface species, allowing the user to specify relationships between those surface concentrations and partial pressures of gaseous species above the surfaces or to form them dynamically by combining diffusion species or other surface species. Additionally, TMAP7 allows the user to include a surface binding energy and an adsorption barrier energy. The code includes asymmetrical diffusion between the surface sites and regular diffusion sites in the bulk. All of the
Longhurst, G.R.; Merrill, B.J.; Jones, J.L.
2000-10-31
The TMAP Code was written in the late 1980s as a tool for safety analysis of systems involving tritium. Since then it was upgraded to TMAP4 and used in numerous applications including experiments supporting fusion safety predictions for advanced systems such as the International Thermonuclear Experimental Reactor (ITER), and estimates involving tritium production technologies. Its further upgrade to TMAP2000 was accomplished in response to several needs. TMAP and TMAP4 had the capacity to deal with only a single trap for diffusing gaseous species in solid structures. TMAP2000 has been revised to include up to three separate traps and to keep track separately of each of up to 10 diffusing species in each of the traps. A difficulty in the original code dealing with heteronuclear molecule formation such as HD and DT has been removed. Under equilibrium boundary conditions such as Sieverts' law, TMAP2000 generates heteronuclear molecular partial pressures when solubilities and partial pressures of the homonuclear molecular species and the equilibrium stoichiometry are provided. A further sophistication is the addition of non-diffusing surface species and surface binding energy dynamics options. Atoms such as oxygen or nitrogen on metal surfaces are sometimes important in molecule formation with diffusing hydrogen isotopes but do not themselves diffuse appreciably in the material. TMAP2000 will accommodate up to 30 such surface species, allowing the user to specify relationships between those surface concentrations and populations of gaseous species above the surfaces. Additionally, TMAP2000 allows the user to include a surface binding energy and an adsorption barrier energy and includes asymmetrical diffusion between the surface sites and regular diffusion sites in the bulk. All of the previously existing features for heat transfer, flows between enclosures, and chemical reactions within the enclosures have been retained, but the allowed problem size and complexity have
Longhurst, Glen Reed; Merrill, Brad Johnson; Jones, James Litton
2000-10-01
The TMAP Code was written in the late 1980s as a tool for safety analysis of systems involving tritium. Since then it was upgraded to TMAP4 and used in numerous applications including experiments supporting fusion safety predictions for advanced systems such as the International Thermonuclear Experimental Reactor (ITER), and estimates involving tritium production technologies. Its further upgrade to TMAP2000 was accomplished in response to several needs. TMAP and TMAP4 had the capacity to deal with only a single trap for diffusing gaseous species in solid structures. TMAP2000 has been revised to include up to three separate traps and to keep track separately of each of up to 10 diffusing species in each of the traps. A difficulty in the original code dealing with heteronuclear molecule formation such as HD and DT has been removed. Under equilibrium boundary conditions such as Sieverts' law, TMAP2000 generates heteronuclear molecular partial pressures when solubilities and partial pressures of the homonuclear molecular species and the equilibrium stoichiometry are provided. A further sophistication is the addition of non-diffusing surface species and surface binding energy dynamics options. Atoms such as oxygen or nitrogen on metal surfaces are sometimes important in molecule formation with diffusing hydrogen isotopes but do not themselves diffuse appreciably in the material. TMAP2000 will accommodate up to 30 such surface species, allowing the user to specify relationships between those surface concentrations and populations of gaseous species above the surfaces. Additionally, TMAP2000 allows the user to include a surface binding energy and an adsorption barrier energy and includes asymmetrical diffusion between the surface sites and regular diffusion sites in the bulk. All of the previously existing features for heat transfer, flows between enclosures, and chemical reactions within the enclosures have been retained, but the allowed problem size and complexity have
Glen R. Longhurst
2006-09-01
The TMAP Code was written at the Idaho National Engineering and Environmental Laboratory by Brad Merrill and James Jones in the late 1980s as a tool for safety analysis of systems involving tritium. Since then it has been upgraded to TMAP4 and has been used in numerous applications including experiments supporting fusion safety, predictions for advanced systems such as the International Thermonuclear Experimental Reactor (ITER), and estimates involving tritium production technologies. Its further upgrade to TMAP2000 and now to TMAP7 was accomplished in response to several needs. TMAP and TMAP4 had the capacity to deal with only a single trap for diffusing gaseous species in solid structures. TMAP7 includes up to three separate traps and up to 10 diffusing species. The original code had difficulty dealing with heteronuclear molecule formation such as HD and DT. That has been removed. Under pre-specified boundary enclosure conditions and solution-law dependent diffusion boundary conditions, such as Sieverts' law, TMAP7 automatically generates heteronuclear molecular partial pressures when solubilities and partial pressures of the homonuclear molecular species are provided for law-dependent diffusion boundary conditions. A further sophistication is the addition of non-diffusing surface species. Atoms such as oxygen or nitrogen or formation and decay or combination of hydroxyl radicals on metal surfaces are sometimes important in reactions with diffusing hydrogen isotopes but do not themselves diffuse appreciably in the material. TMAP7 will accommodate up to 30 such surface species, allowing the user to specify relationships between those surface concentrations and partial pressures of gaseous species above the surfaces or to form them dynamically by combining diffusion species or other surface species. Additionally, TMAP7 allows the user to include a surface binding energy and an adsorption barrier energy. The code includes asymmetrical diffusion between the surface
Longhurst, G.R.; Holland, D.F.; Jones, J.L.; Merrill, B.J.
1992-06-12
The Tritium Migration Analysis Program, Version 4 (TMAP4) has been developed by the Fusion Safety Program at the Idaho National Engineering Laboratory (INEL) as a safety analysis code, mainly to analyze tritium retention and loss in fusion reactor structures and systems during normal operation and accident conditions. TMAP4 incorporates one-dimensional thermal- and mass-diffusive transport and trapping calculations through structures and zero dimensional fluid transport between enclosures and across the interface between enclosures and structures. A key feature is the ability to input problem definition parameters as constants, interpolation tables, or FORTRAN equations. The code is specifically intended for use under a DOS operating system on PC-type mini-computers, but it has also been run successfully on workstations and mainframe computer systems. Use of the equation-input feature requires access to a FORTRAN-77 compiler and a linker program.
Verification and Validation of TMAP7
James Ambrosek; James Ambrosek
2008-12-01
The Tritium Migration Analysis Program, Version 7 (TMAP7) code is an update of TMAP4, an earlier version that was verified and validated in support of the International Thermonuclear Experimental Reactor (ITER) program and of the intermediate version TMAP2000. It has undergone several revisions. The current one includes radioactive decay, multiple trap capability, more realistic treatment of heteronuclear molecular formation at surfaces, processes that involve surface-only species, and a number of other improvements. Prior to code utilization, it needed to be verified and validated to ensure that the code is performing as it was intended and that its predictions are consistent with physical reality. To that end, the demonstration and comparison problems cited here show that the code results agree with analytical solutions for select problems where analytical solutions are straightforward or with results from other verified and validated codes, and that actual experimental results can be accurately replicated using reasonable models with this code. These results and their documentation in this report are necessary steps in the qualification of TMAP7 for its intended service.
Verification and Validation of TMAP7
James Ambrosek; James Ambrosek
2005-12-01
The Tritium Migration Analysis Program, Version 7 (TMAP7) code is an update of TMAP4, an earlier version that was verified and validated in support of the International Thermonuclear Experimental Reactor (ITER) program and of the intermediate version TMAP2000. It has undergone several revisions. The current one includes radioactive decay, multiple trap capability, more realistic treatment of heteronuclear molecular formation at surfaces, processes that involve surface-only species, and a number of other improvements. Prior to code utilization, it needed to be verified and validated to ensure that the code is performing as it was intended and that its predictions are consistent with physical reality. To that end, the demonstration and comparison problems cited here show that the code results agree with analytical solutions for select problems where analytical solutions are straightforward or with results from other verified and validated codes, and that actual experimental results can be accurately replicated using reasonable models with this code. These results and their documentation in this report are necessary steps in the qualification of TMAP7 for its intended service.
Longhurst, G.R.; Holland, D.F.; Jones, J.L.; Merrill, B.J.
1992-06-12
The Tritium Migration Analysis Program, Version 4 (TMAP4) has been developed by the Fusion Safety Program at the Idaho National Engineering Laboratory (INEL) as a safety analysis code, mainly to analyze tritium retention and loss in fusion reactor structures and systems during normal operation and accident conditions. TMAP4 incorporates one-dimensional thermal- and mass-diffusive transport and trapping calculations through structures and zero dimensional fluid transport between enclosures and across the interface between enclosures and structures. A key feature is the ability to input problem definition parameters as constants, interpolation tables, or FORTRAN equations. The code is specifically intended for use under a DOS operating system on PC-type mini-computers, but it has also been run successfully on workstations and mainframe computer systems. Use of the equation-input feature requires access to a FORTRAN-77 compiler and a linker program.
Verification and validation of TMAP4
Longhurst, G.R.; Harms, S.L.; Marwil, E.S.; Miller, B.G.
1992-07-08
The Tritium Migration Analysis Program MODl/CY04 (TMAP4) was written to be used in analyzing experiments and for safety calculations that involve the injection, solution, diffusion, trapping, release, and other related processes experienced by hydrogen isotopes in materials. Because of the desire to make it suitable for analyzing safety issues, it is important that TMAP4 be certified (verified and validated) at Quality Assurance Level A. This report documents the work done to achieve that certification. The process includes assuring that the developed code meets the software requirements specified in the Software Quality Assurance Plan, verifying that the code functions in accordance with the written description and that it is self-consistent and internally correct, and validating that its computed results are in agreement with experimental data and/or known analytical solutions. Quality Level A certification for TMAP4 is specifically for implementation on an IBM PS/2 Model 70 operating under DOS 5.0. Certification for any other environment will require demonstration that all of the verification and validation tests documented here give the same results in the new environment.
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.
Cascade Error Projection Learning Algorithm
NASA Technical Reports Server (NTRS)
Duong, T. A.; Stubberud, A. R.; Daud, T.
1995-01-01
A detailed mathematical analysis is presented for a new learning algorithm termed cascade error projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters.
Projection Classification Based Iterative Algorithm
NASA Astrophysics Data System (ADS)
Zhang, Ruiqiu; Li, Chen; Gao, Wenhua
2015-05-01
Iterative algorithm has good performance as it does not need complete projection data in 3D image reconstruction area. It is possible to be applied in BGA based solder joints inspection but with low convergence speed which usually acts with x-ray Laminography that has a worse reconstruction image compared to the former one. This paper explores to apply one projection classification based method which tries to separate the object to three parts, i.e. solute, solution and air, and suppose that the reconstruction speed decrease from solution to two other parts on both side lineally. And then SART and CAV algorithms are improved under the proposed idea. Simulation experiment result with incomplete projection images indicates the fast convergence speed of the improved iterative algorithms and the effectiveness of the proposed method. Less the projection images, more the superiority is also founded.
TMAP: Tübingen NLTE Model-Atmosphere Package
NASA Astrophysics Data System (ADS)
Werner, Klaus; Dreizler, Stefan; Rauch, Thomas
2012-12-01
The Tübingen NLTE Model-Atmosphere Package (TMAP) is a tool to calculate stellar atmospheres in spherical or plane-parallel geometry in hydrostatic and radiative equilibrium allowing departures from local thermodynamic equilibrium (LTE) for the population of atomic levels. It is based on the Accelerated Lambda Iteration (ALI) method and is able to account for line blanketing by metals. All elements from hydrogen to nickel may be included in the calculation with model atoms which are tailored for the aims of the user.
HEATR project: ATR algorithm parallelization
NASA Astrophysics Data System (ADS)
Deardorf, Catherine E.
1998-09-01
High Performance Computing (HPC) Embedded Application for Target Recognition (HEATR) is a project funded by the High Performance Computing Modernization Office through the Common HPC Software Support Initiative (CHSSI). The goal of CHSSI is to produce portable, parallel, multi-purpose, freely distributable, support software to exploit emerging parallel computing technologies and enable application of scalable HPC's for various critical DoD applications. Specifically, the CHSSI goal for HEATR is to provide portable, parallel versions of several existing ATR detection and classification algorithms to the ATR-user community to achieve near real-time capability. The HEATR project will create parallel versions of existing automatic target recognition (ATR) detection and classification algorithms and generate reusable code that will support porting and software development process for ATR HPC software. The HEATR Team has selected detection/classification algorithms from both the model- based and training-based (template-based) arena in order to consider the parallelization requirements for detection/classification algorithms across ATR technology. This would allow the Team to assess the impact that parallelization would have on detection/classification performance across ATR technology. A field demo is included in this project. Finally, any parallel tools produced to support the project will be refined and returned to the ATR user community along with the parallel ATR algorithms. This paper will review: (1) HPCMP structure as it relates to HEATR, (2) Overall structure of the HEATR project, (3) Preliminary results for the first algorithm Alpha Test, (4) CHSSI requirements for HEATR, and (5) Project management issues and lessons learned.
Reimold, Matthias; Slifstein, Mark; Heinz, Andreas; Mueller-Schauenburg, Wolfgang; Bares, Roland
2006-06-01
Voxelwise statistical analysis has become popular in explorative functional brain mapping with fMRI or PET. Usually, results are presented as voxelwise levels of significance (t-maps), and for clusters that survive correction for multiple testing the coordinates of the maximum t-value are reported. Before calculating a voxelwise statistical test, spatial smoothing is required to achieve a reasonable statistical power. Little attention is being given to the fact that smoothing has a nonlinear effect on the voxel variances and thus the local characteristics of a t-map, which becomes most evident after smoothing over different types of tissue. We investigated the related artifacts, for example, white matter peaks whose position depend on the relative variance (variance over contrast) of the surrounding regions, and suggest improving spatial precision with 'masked contrast images': color-codes are attributed to the voxelwise contrast, and significant clusters (e.g., detected with statistical parametric mapping, SPM) are enlarged by including contiguous pixels with a contrast above the mean contrast in the original cluster, provided they satisfy P < 0.05. The potential benefit is demonstrated with simulations and data from a [11C]Carfentanil PET study. We conclude that spatial smoothing may lead to critical, sometimes-counterintuitive artifacts in t-maps, especially in subcortical brain regions. If significant clusters are detected, for example, with SPM, the suggested method is one way to improve spatial precision and may give the investigator a more direct sense of the underlying data. Its simplicity and the fact that no further assumptions are needed make it a useful complement for standard methods of statistical mapping. PMID:16208316
Cascade Error Projection: A New Learning Algorithm
NASA Technical Reports Server (NTRS)
Duong, T. A.; Stubberud, A. R.; Daud, T.; Thakoor, A. P.
1995-01-01
A new neural network architecture and a hardware implementable learning algorithm is proposed. The algorithm, called cascade error projection (CEP), handles lack of precision and circuit noise better than existing algorithms.
TMAP [Teleoperated Mobile Antiarmor Platform]: The Army`s near term entree to battlefield robotics
Simmons, R.K.
1988-05-01
TMAP is a remotely operated battlefield system consisting of a 750-pound all terrain vehicle, remotely operated by a solider over a fiber optic communication link 4 km long. Using state-of-the-art automation and robotic technology, Martin Marietta Aero and Naval Systems is developing a modular prototype system under contract to Sandia National Laboratories. The Army Material developer is the Missile Command (MICOM) at Huntsville, Alabama; the Combat Developer is the Infantry School (USAIS) at Ft. Benning, Georgia. With the weapons removed by Congress in December 1987, the O & O is being rewritten for a ``Tactical Multipurpose Automated Platform`` (TMAP) instead of the original Teleoperated Mobile Antiarmor Platform. With minimal modification the modular TMAP system can be used in many applications (eg., antiarmor or antiair weapons, mine detection, medical support). System acceptance and Army evaluation testing is scheduled for summer and fall of 1988. 9 figs., 2 tabs.
[Orthogonal Vector Projection Algorithm for Spectral Unmixing].
Song, Mei-ping; Xu, Xing-wei; Chang, Chein-I; An, Ju-bai; Yao, Li
2015-12-01
Spectrum unmixing is an important part of hyperspectral technologies, which is essential for material quantity analysis in hyperspectral imagery. Most linear unmixing algorithms require computations of matrix multiplication and matrix inversion or matrix determination. These are difficult for programming, especially hard for realization on hardware. At the same time, the computation costs of the algorithms increase significantly as the number of endmembers grows. Here, based on the traditional algorithm Orthogonal Subspace Projection, a new method called. Orthogonal Vector Projection is prompted using orthogonal principle. It simplifies this process by avoiding matrix multiplication and inversion. It firstly computes the final orthogonal vector via Gram-Schmidt process for each endmember spectrum. And then, these orthogonal vectors are used as projection vector for the pixel signature. The unconstrained abundance can be obtained directly by projecting the signature to the projection vectors, and computing the ratio of projected vector length and orthogonal vector length. Compared to the Orthogonal Subspace Projection and Least Squares Error algorithms, this method does not need matrix inversion, which is much computation costing and hard to implement on hardware. It just completes the orthogonalization process by repeated vector operations, easy for application on both parallel computation and hardware. The reasonability of the algorithm is proved by its relationship with Orthogonal Sub-space Projection and Least Squares Error algorithms. And its computational complexity is also compared with the other two algorithms', which is the lowest one. At last, the experimental results on synthetic image and real image are also provided, giving another evidence for effectiveness of the method. PMID:26964231
Jeon, Sang-Min; Choi, Bongkun; Hong, Kyung Uk; Kim, Eunhee; Seong, Yeon-Sun; Bae, Chang-Dae; Park, Joobae . E-mail: jbpark@med.skku.ac.kr
2006-09-15
Previously, we reported the cloning of a cytoskeleton-associated protein, TMAP/CKAP2, which was up-regulated in primary human gastric cancers. Although TMAP/CKAP2 has been found to be expressed in most cancer cell lines examined, the function of CKAP2 is not known. In this study, we found that TMAP/CKAP2 was not expressed in G0/G1 arrested HFFs, but that it was expressed in actively dividing cells. After initiating the cell cycle, TMAP/CKAP2 levels remained low throughout most of the G1 phase, but gradually increased between late G1 and G2/M. Knockdown of TMAP/CKAP2 reduced pRB phosphorylation and increased p27 expression, and consequently reduced HFF proliferation, whereas constitutive TMAP/CKAP2 expression increased pRB phosphorylation and enhanced proliferation. Our results show that this novel cytoskeleton-associated protein is expressed cell cycle dependently and that it is involved in cell proliferation.
Density equalizing map projections: A new algorithm
Merrill, D.W.; Selvin, S.; Mohr, M.S.
1992-02-01
In the study of geographic disease clusters, an alternative to traditional methods based on rates is to analyze case locations on a transformed map in which population density is everywhere equal. Although the analyst`s task is thereby simplified, the specification of the density equalizing map projection (DEMP) itself is not simple and continues to be the subject of considerable research. Here a new DEMP algorithm is described, which avoids some of the difficulties of earlier approaches. The new algorithm (a) avoids illegal overlapping of transformed polygons; (b) finds the unique solution that minimizes map distortion; (c) provides constant magnification over each map polygon; (d) defines a continuous transformation over the entire map domain; (e) defines an inverse transformation; (f) can accept optional constraints such as fixed boundaries; and (g) can use commercially supported minimization software. Work is continuing to improve computing efficiency and improve the algorithm.
Density equalizing map projections: A new algorithm
Merrill, D.W.; Selvin, S.; Mohr, M.S.
1992-02-01
In the study of geographic disease clusters, an alternative to traditional methods based on rates is to analyze case locations on a transformed map in which population density is everywhere equal. Although the analyst's task is thereby simplified, the specification of the density equalizing map projection (DEMP) itself is not simple and continues to be the subject of considerable research. Here a new DEMP algorithm is described, which avoids some of the difficulties of earlier approaches. The new algorithm (a) avoids illegal overlapping of transformed polygons; (b) finds the unique solution that minimizes map distortion; (c) provides constant magnification over each map polygon; (d) defines a continuous transformation over the entire map domain; (e) defines an inverse transformation; (f) can accept optional constraints such as fixed boundaries; and (g) can use commercially supported minimization software. Work is continuing to improve computing efficiency and improve the algorithm.
Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings
NASA Astrophysics Data System (ADS)
Slavakis, Konstantinos; Theodoridis, Sergios
2008-12-01
Very recently, a solution to the kernel-based online classification problem has been given by the adaptive projected subgradient method (APSM). The developed algorithm can be considered as a generalization of a kernel affine projection algorithm (APA) and the kernel normalized least mean squares (NLMS). Furthermore, sparsification of the resulting kernel series expansion was achieved by imposing a closed ball (convex set) constraint on the norm of the classifiers. This paper presents another sparsification method for the APSM approach to the online classification task by generating a sequence of linear subspaces in a reproducing kernel Hilbert space (RKHS). To cope with the inherent memory limitations of online systems and to embed tracking capabilities to the design, an upper bound on the dimension of the linear subspaces is imposed. The underlying principle of the design is the notion of projection mappings. Classification is performed by metric projection mappings, sparsification is achieved by orthogonal projections, while the online system's memory requirements and tracking are attained by oblique projections. The resulting sparsification scheme shows strong similarities with the classical sliding window adaptive schemes. The proposed design is validated by the adaptive equalization problem of a nonlinear communication channel, and is compared with classical and recent stochastic gradient descent techniques, as well as with the APSM's solution where sparsification is performed by a closed ball constraint on the norm of the classifiers.
Cascade Error Projection: An Efficient Hardware Learning Algorithm
NASA Technical Reports Server (NTRS)
Duong, T. A.
1995-01-01
A new learning algorithm termed cascade error projection (CEP) is presented. CEP is an adaption of a constructive architecture from cascade correlation and the dynamical stepsize of A/D conversion from the cascade back propagation algorithm.
Fast image matching algorithm based on projection characteristics
NASA Astrophysics Data System (ADS)
Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun
2011-06-01
Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.
An affine projection algorithm using grouping selection of input vectors
NASA Astrophysics Data System (ADS)
Shin, JaeWook; Kong, NamWoong; Park, PooGyeon
2011-10-01
This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.
Preconditioned Alternating Projection Algorithms for Maximum a Posteriori ECT Reconstruction.
Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng
2012-11-01
We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constrain involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the preconditioned alternating projection algorithm. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. PMID:23271835
Preconditioned Alternating Projection Algorithms for Maximum a Posteriori ECT Reconstruction
Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng
2012-01-01
We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constrain involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the preconditioned alternating projection algorithm. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. PMID:23271835
The Coastcolour project regional algorithm round robin exercise
NASA Astrophysics Data System (ADS)
Ruddick, K.; Brockmann, C.; Doerffer, R.; Lee, Z.; Brotas, V.; Fomferra, N.; Groom, S.; Krasemann, H.; Martinez-Vicente, V.; Sa, C.; Santer, R.; Sathyendranath, S.; Stelzer, K.; Pinnock, S.
2010-10-01
The MERIS instrument delivers a unique dataset of ocean colour measurements of the coastal zone, at 300m resolution and with a unique spectral band set. The motivation for the Coastcolour project is to fully exploit the potential of the MERIS instrument for remote sensing of the coastal zone. The general objective of the project is to develop, demonstrate, validate and intercompare different processing algorithms for MERIS over a global range of coastal water types in order to identify best practices. In this paper the Coastcolour project is presented in general and the Regional Algorithm Round Robin (RARR) exercise is described in detail. The RARR has the objective of determining the best approach to retrieval of chlorophyll a and other marine products (e.g. Inherent Optical Properties) for each of the Coastcolour coastal water test sites. Benchmark datasets of reflectances at MERIS bands will be distributed to algorithm provider participants for testing of both global (Coastcolour and other) algorithms and site-specific local algorithms. Results from all algorithms will be analysed and compared according to a uniform methodology. Participation of algorithm providers from outside the Coastcolour consortium is encouraged.
A unified evaluation of iterative projection algorithms for phase retrieval
Marchesini, S
2006-03-08
Iterative projection algorithms are successfully being used as a substitute of lenses to recombine, numerically rather than optically, light scattered by illuminated objects. Images obtained computationally allow aberration-free diffraction-limited imaging and allow new types of imaging using radiation for which no lenses exist. The challenge of this imaging technique is transferred from the lenses to the algorithms. We evaluate these new computational ''instruments'' developed for the phase retrieval problem, and discuss acceleration strategies.
OTG-snpcaller: An Optimized Pipeline Based on TMAP and GATK for SNP Calling from Ion Torrent Data
Huang, Wenpan; Xi, Feng; Lin, Lin; Zhi, Qihuan; Zhang, Wenwei; Tang, Y. Tom; Geng, Chunyu; Lu, Zhiyuan; Xu, Xun
2014-01-01
Because the new Proton platform from Life Technologies produced markedly different data from those of the Illumina platform, the conventional Illumina data analysis pipeline could not be used directly. We developed an optimized SNP calling method using TMAP and GATK (OTG-snpcaller). This method combined our own optimized processes, Remove Duplicates According to AS Tag (RDAST) and Alignment Optimize Structure (AOS), together with TMAP and GATK, to call SNPs from Proton data. We sequenced four sets of exomes captured by Agilent SureSelect and NimbleGen SeqCap EZ Kit, using Life Technology’s Ion Proton sequencer. Then we applied OTG-snpcaller and compared our results with the results from Torrent Variants Caller. The results indicated that OTG-snpcaller can reduce both false positive and false negative rates. Moreover, we compared our results with Illumina results generated by GATK best practices, and we found that the results of these two platforms were comparable. The good performance in variant calling using GATK best practices can be primarily attributed to the high quality of the Illumina sequences. PMID:24824529
An improved back projection algorithm of ultrasound tomography
NASA Astrophysics Data System (ADS)
Xiaozhen, Chen; Mingxu, Su; Xiaoshu, Cai
2014-04-01
Binary logic back projection algorithm is improved in this work for the development of fast ultrasound tomography system with a better effect of image reconstruction. The new algorithm is characterized by an extra logical value `2' and dual-threshold processing of collected raw data. To compare with the original algorithm, a numerical simulation was conducted by the verification of COMSOL simulations formerly, and then a set of ultrasonic tomography system is established to perform the experiments of one, two and three cylindrical objects. The object images are reconstructed through the inversion of signals matrix acquired by the transducer array after a preconditioning, while the corresponding spatial imaging errors can obviously indicate that the improved back projection method can achieve modified inversion effect.
A Turn-Projected State-Based Conflict Resolution Algorithm
NASA Technical Reports Server (NTRS)
Butler, Ricky W.; Lewis, Timothy A.
2013-01-01
State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.
An improved back projection algorithm of ultrasound tomography
Xiaozhen, Chen; Mingxu, Su; Xiaoshu, Cai
2014-04-11
Binary logic back projection algorithm is improved in this work for the development of fast ultrasound tomography system with a better effect of image reconstruction. The new algorithm is characterized by an extra logical value ‘2’ and dual-threshold processing of collected raw data. To compare with the original algorithm, a numerical simulation was conducted by the verification of COMSOL simulations formerly, and then a set of ultrasonic tomography system is established to perform the experiments of one, two and three cylindrical objects. The object images are reconstructed through the inversion of signals matrix acquired by the transducer array after a preconditioning, while the corresponding spatial imaging errors can obviously indicate that the improved back projection method can achieve modified inversion effect.
The PRISM project: Infrastructure and algorithms for parallel eigensolvers
Bischof, C.; Sun, X.; Huss-Lederman, S.; Tsao, A.
1993-12-31
The goal of the PRISM project is the development of infrastructure and algorithms for the parallel solution of eigenvalue problems. We are currently investigating a complete eigensolver based on the Invariant Subspace Decomposition Algorithm for dense symmetric matrices (SYISDA). After briefly reviewing the SYISDA approach, we discuss the algorithmic highlights of a distributed-memory implementation of an eigensolver based on this approach. These include a fast matrix-matrix multiplication algorithm, a new approach to parallel band reduction and tridiagonalization, and a harness for coordinating the divide-and-conquer parallelism in the problem. We also present performance results of these kernels as well as the overall SYISDA implementation on the Intel Touchstone Delta prototype and the IBM SP/1.
Secure 3D watermarking algorithm based on point set projection
NASA Astrophysics Data System (ADS)
Liu, Quan; Zhang, Xiaomei
2007-11-01
3D digital models greatly facilitate the distribution and storage of information. While its copyright protection problems attract more and more research interests. A novel secure digital watermarking algorithm for 3D models is proposed in this paper. In order to survive most attacks like rotation, cropping, smoothing, adding noise, etc, the projection of the model's point set is chosen as the carrier of the watermark in the presented algorithm, in which contains the copyright information as logos, text, and so on. Then projection of the model's point set onto x, y and z plane are calculated respectively. Before watermark embedding process, the original watermark is scrambled by a key. Each projection is singular value decomposed, and the scrambled watermark is embedded into the SVD(singular value decomposed) domain of the above x, y and z plane respectively. After that we use the watermarked x, y and z plane to recover the vertices of the model and the watermarked model is attained. Only the legal user can remove the watermark from the watermarked models using the private key. Experiments are presented in the paper to show that the proposed algorithm has good performance on various malicious attacks.
NASA Astrophysics Data System (ADS)
Liu, Jianming; Grant, Steven L.; Benesty, Jacob
2015-12-01
A new reweighted proportionate affine projection algorithm (RPAPA) with memory and row action projection (MRAP) is proposed in this paper. The reweighted PAPA is derived from a family of sparseness measures, which demonstrate performance similar to mu-law and the l 0 norm PAPA but with lower computational complexity. The sparseness of the channel is taken into account to improve the performance for dispersive system identification. Meanwhile, the memory of the filter's coefficients is combined with row action projections (RAP) to significantly reduce computational complexity. Simulation results demonstrate that the proposed RPAPA MRAP algorithm outperforms both the affine projection algorithm (APA) and PAPA, and has performance similar to l 0 PAPA and mu-law PAPA, in terms of convergence speed and tracking ability. Meanwhile, the proposed RPAPA MRAP has much lower computational complexity than PAPA, mu-law PAPA, and l 0 PAPA, etc., which makes it very appealing for real-time implementation.
Abejuela, Harmony Raylen; Osser, David N
2016-01-01
This revision of previous algorithms for the pharmacotherapy of generalized anxiety disorder was developed by the Psychopharmacology Algorithm Project at the Harvard South Shore Program. Algorithms from 1999 and 2010 and associated references were reevaluated. Newer studies and reviews published from 2008-14 were obtained from PubMed and analyzed with a focus on their potential to justify changes in the recommendations. Exceptions to the main algorithm for special patient populations, such as women of childbearing potential, pregnant women, the elderly, and those with common medical and psychiatric comorbidities, were considered. Selective serotonin reuptake inhibitors (SSRIs) are still the basic first-line medication. Early alternatives include duloxetine, buspirone, hydroxyzine, pregabalin, or bupropion, in that order. If response is inadequate, then the second recommendation is to try a different SSRI. Additional alternatives now include benzodiazepines, venlafaxine, kava, and agomelatine. If the response to the second SSRI is unsatisfactory, then the recommendation is to try a serotonin-norepinephrine reuptake inhibitor (SNRI). Other alternatives to SSRIs and SNRIs for treatment-resistant or treatment-intolerant patients include tricyclic antidepressants, second-generation antipsychotics, and valproate. This revision of the GAD algorithm responds to issues raised by new treatments under development (such as pregabalin) and organizes the evidence systematically for practical clinical application. PMID:27384395
Mohammad, Othman; Osser, David N
2014-01-01
This new algorithm for the pharmacotherapy of acute mania was developed by the Psychopharmacology Algorithm Project at the Harvard South Shore Program. The authors conducted a literature search in PubMed and reviewed key studies, other algorithms and guidelines, and their references. Treatments were prioritized considering three main considerations: (1) effectiveness in treating the current episode, (2) preventing potential relapses to depression, and (3) minimizing side effects over the short and long term. The algorithm presupposes that clinicians have made an accurate diagnosis, decided how to manage contributing medical causes (including substance misuse), discontinued antidepressants, and considered the patient's childbearing potential. We propose different algorithms for mixed and nonmixed mania. Patients with mixed mania may be treated first with a second-generation antipsychotic, of which the first choice is quetiapine because of its greater efficacy for depressive symptoms and episodes in bipolar disorder. Valproate and then either lithium or carbamazepine may be added. For nonmixed mania, lithium is the first-line recommendation. A second-generation antipsychotic can be added. Again, quetiapine is favored, but if quetiapine is unacceptable, risperidone is the next choice. Olanzapine is not considered a first-line treatment due to its long-term side effects, but it could be second-line. If the patient, whether mixed or nonmixed, is still refractory to the above medications, then depending on what has already been tried, consider carbamazepine, haloperidol, olanzapine, risperidone, and valproate first tier; aripiprazole, asenapine, and ziprasidone second tier; and clozapine third tier (because of its weaker evidence base and greater side effects). Electroconvulsive therapy may be considered at any point in the algorithm if the patient has a history of positive response or is intolerant of medications. PMID:25188733
An Overview of the JPSS Ground Project Algorithm Integration Process
NASA Astrophysics Data System (ADS)
Vicente, G. A.; Williams, R.; Dorman, T. J.; Williamson, R. C.; Shaw, F. J.; Thomas, W. M.; Hung, L.; Griffin, A.; Meade, P.; Steadley, R. S.; Cember, R. P.
2015-12-01
The smooth transition, implementation and operationalization of scientific software's from the National Oceanic and Atmospheric Administration (NOAA) development teams to the Join Polar Satellite System (JPSS) Ground Segment requires a variety of experiences and expertise. This task has been accomplished by a dedicated group of scientist and engineers working in close collaboration with the NOAA Satellite and Information Services (NESDIS) Center for Satellite Applications and Research (STAR) science teams for the JPSS/Suomi-NPOES Preparatory Project (S-NPP) Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) instruments. The presentation purpose is to describe the JPSS project process for algorithm implementation from the very early delivering stages by the science teams to the full operationalization into the Interface Processing Segment (IDPS), the processing system that provides Environmental Data Records (EDR's) to NOAA. Special focus is given to the NASA Data Products Engineering and Services (DPES) Algorithm Integration Team (AIT) functional and regression test activities. In the functional testing phase, the AIT uses one or a few specific chunks of data (granules) selected by the NOAA STAR Calibration and Validation (cal/val) Teams to demonstrate that a small change in the code performs properly and does not disrupt the rest of the algorithm chain. In the regression testing phase, the modified code is placed into to the Government Resources for Algorithm Verification, Integration, Test and Evaluation (GRAVITE) Algorithm Development Area (ADA), a simulated and smaller version of the operational IDPS. Baseline files are swapped out, not edited and the whole code package runs in one full orbit of Science Data Records (SDR's) using Calibration Look Up Tables (Cal LUT's) for the time of the orbit. The purpose of the regression test is to
Staff line detection and revision algorithm based on subsection projection and correlation algorithm
NASA Astrophysics Data System (ADS)
Yang, Yin-xian; Yang, Ding-li
2013-03-01
Staff line detection plays a key role in OMR technology, and is the precon-ditions of subsequent segmentation 1& recognition of music sheets. For the phenomena of horizontal inclination & curvature of staff lines and vertical inclination of image, which often occur in music scores, an improved approach based on subsection projection is put forward to realize the detection of original staff lines and revision in an effect to implement staff line detection more successfully. Experimental results show the presented algorithm can detect and revise staff lines fast and effectively.
Cascade Error Projection: A Learning Algorithm for Hardware Implementation
NASA Technical Reports Server (NTRS)
Duong, Tuan A.; Daud, Taher
1996-01-01
In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.
An Algorithm for Projecting Points onto a Patched CAD Model
Henshaw, W D
2001-05-29
We are interested in building structured overlapping grids for geometries defined by computer-aided-design (CAD) packages. Geometric information defining the boundary surfaces of a computation domain is often provided in the form of a collection of possibly hundreds of trimmed patches. The first step in building an overlapping volume grid on such a geometry is to build overlapping surface grids. A surface grid is typically built using hyperbolic grid generation; starting from a curve on the surface, a grid is grown by marching over the surface. A given hyperbolic grid will typically cover many of the underlying CAD surface patches. The fundamental operation needed for building surface grids is that of projecting a point in space onto the closest point on the CAD surface. We describe an fast algorithm for performing this projection, it will make use of a fairly coarse global triangulation of the CAD geometry. We describe how to build this global triangulation by first determining the connectivity of the CAD surface patches. This step is necessary since it often the case that the CAD description will contain no information specifying how a given patch connects to other neighboring patches. Determining the connectivity is difficult since the surface patches may contain mistakes such as gaps or overlaps between neighboring patches.
Korean Medication Algorithm Project for Bipolar Disorder: third revision
Woo, Young Sup; Lee, Jung Goo; Jeong, Jong-Hyun; Kim, Moon-Doo; Sohn, Inki; Shim, Se-Hoon; Jon, Duk-In; Seo, Jeong Seok; Shin, Young-Chul; Min, Kyung Joon; Yoon, Bo-Hyun; Bahk, Won-Myong
2015-01-01
Objective To constitute the third revision of the guidelines for the treatment of bipolar disorder issued by the Korean Medication Algorithm Project for Bipolar Disorder (KMAP-BP 2014). Methods A 56-item questionnaire was used to obtain the consensus of experts regarding pharmacological treatment strategies for the various phases of bipolar disorder and for special populations. The review committee included 110 Korean psychiatrists and 38 experts for child and adolescent psychiatry. Of the committee members, 64 general psychiatrists and 23 child and adolescent psychiatrists responded to the survey. Results The treatment of choice (TOC) for euphoric, mixed, and psychotic mania was the combination of a mood stabilizer (MS) and an atypical antipsychotic (AAP); the TOC for acute mild depression was monotherapy with MS or AAP; and the TOC for moderate or severe depression was MS plus AAP/antidepressant. The first-line maintenance treatment following mania or depression was MS monotherapy or MS plus AAP; the first-line treatment after mania was AAP monotherapy; and the first-line treatment after depression was lamotrigine (LTG) monotherapy, LTG plus MS/AAP, or MS plus AAP plus LTG. The first-line treatment strategy for mania in children and adolescents was MS plus AAP or AAP monotherapy. For geriatric bipolar patients, the TOC for mania was AAP/MS monotherapy, and the TOC for depression was AAP plus MS or AAP monotherapy. Conclusion The expert consensus in the KMAP-BP 2014 differed from that in previous publications; most notably, the preference for AAP was increased in the treatment of acute mania, depression, and maintenance treatment. There was increased expert preference for the use of AAP and LTG. The major limitation of the present study is that it was based on the consensus of Korean experts rather than on experimental evidence. PMID:25750530
Riemannian mean and space-time adaptive processing using projection and inversion algorithms
NASA Astrophysics Data System (ADS)
Balaji, Bhashyam; Barbaresco, Frédéric
2013-05-01
The estimation of the covariance matrix from real data is required in the application of space-time adaptive processing (STAP) to an airborne ground moving target indication (GMTI) radar. A natural approach to estimation of the covariance matrix that is based on the information geometry has been proposed. In this paper, the output of the Riemannian mean is used in inversion and projection algorithms. It is found that the projection class of algorithms can yield very significant gains, even when the gains due to inversion-based algorithms are marginal over standard algorithms. The performance of the projection class of algorithms does not appear to be overly sensitive to the projected subspace dimension.
Saad, Y.
1980-12-01
Many powerful methods for solving systems of equations can be regarded as projection methods. Most of the projection methods known for solving linear systems are orthogonal projection methods: but little attention has been given to the class of nonorthogonal (or oblique) projection methods, which is particularly attractive for large nonsymmetric systems. Some methods in the general setting of oblique projection methods are presented, and some theoretical results are given. Some experiments comparing the various algorithms are reported. 5 figures.
Affine Projection Algorithm with Improved Data-Selective Method Using the Condition Number
NASA Astrophysics Data System (ADS)
Ban, Sung Jun; Lee, Chang Woo; Kim, Sang Woo
Recently, a data-selective method has been proposed to achieve low misalignment in affine projection algorithm (APA) by keeping the condition number of an input data matrix small. We present an improved method, and a complexity reduction algorithm for the APA with the data-selective method. Experimental results show that the proposed algorithm has lower misalignment and a lower condition number for an input data matrix than both the conventional APA and the APA with the previous data-selective method.
ERIC Educational Resources Information Center
Emslie, Graham J.; Hughes, Carroll W.; Crismon, M. Lynn; Lopez, Molly; Pliszka, Steve; Toprac, Marcia G.; Boemer, Christine
2004-01-01
Objective: To evaluate the feasibility and impact on clinical response and function associated with the use of an algorithm-driven disease management program (ALGO) for children and adolescents treated for depression with or without attention-deficit/hyperactivity disorder (ADHD) in community mental health centers. Method: Interventions included…
Volkov transform generalized projection algorithm for attosecond pulse characterization
NASA Astrophysics Data System (ADS)
Keathley, P. D.; Bhardwaj, S.; Moses, J.; Laurent, G.; Kärtner, F. X.
2016-07-01
An algorithm for characterizing attosecond extreme ultraviolet pulses that is not bandwidth-limited, requires no interpolation of the experimental data, and makes no approximations beyond the strong-field approximation is introduced. This approach fully incorporates the dipole transition matrix element into the retrieval process. Unlike attosecond retrieval methods such as phase retrieval by omega oscillation filtering (PROOF), or improved PROOF, it simultaneously retrieves both the attosecond and infrared (IR) pulses, without placing fundamental restrictions on the IR pulse duration, intensity or bandwidth. The new algorithm is validated both numerically and experimentally, and is also found to have practical advantages. These include an increased robustness to noise, and relaxed requirements for the size of the experimental dataset and the intensity of the streaking pulse.
Filtered back-projection algorithm for Compton telescopes
Gunter, Donald L.
2008-03-18
A method for the conversion of Compton camera data into a 2D image of the incident-radiation flux on the celestial sphere includes detecting coincident gamma radiation flux arriving from various directions of a 2-sphere. These events are mapped by back-projection onto the 2-sphere to produce a convolution integral that is subsequently stereographically projected onto a 2-plane to produce a second convolution integral which is deconvolved by the Fourier method to produce an image that is then projected onto the 2-sphere.
Rios, A. B.; Valda, A.; Somacal, H.
2007-10-26
Usually tomographic procedure requires a set of projections around the object under study and a mathematical processing of such projections through reconstruction algorithms. An accurate reconstruction requires a proper number of projections (angular sampling) and a proper number of elements in each projection (linear sampling). However in several practical cases it is not possible to fulfill these conditions leading to the so-called problem of few projections. In this case, iterative reconstruction algorithms are more suitable than analytic ones. In this work we present a program written in C++ that provides an environment for two iterative algorithm implementations, one algebraic and the other statistical. The software allows the user a full definition of the acquisition and reconstruction geometries used for the reconstruction algorithms but also to perform projection and backprojection operations. A set of analysis tools was implemented for the characterization of the convergence process. We analyze the performance of the algorithms on numerical phantoms and present the reconstruction of experimental data with few projections coming from transmission X-ray and micro PIXE (Particle-Induced X-Ray Emission) images.
NASA Astrophysics Data System (ADS)
Muralidhar, Karthik; Li, Kwok Hung; George, Sapna
To attain good performance in an acoustic echo cancellation system, it is important to have a variable step size (VSS) algorithm as part of an adaptive filter. In this paper, we are concerned with the development of a VSS algorithm for a recently proposed subband affine projection (SAP) adaptive filter. Two popular VSS algorithms in the literature are the methods of delayed coefficients (DC) and variable regularization (VR). However, the merits and demerits of them are mutually exclusive. We propose a VSS algorithm* that is a hybrid of both methods and combines their advantages. An extensive study of the new algorithm in different scenarios like the presence double-talk (DT) during the transient phase of the adaptive filter, DT during steady state, and varying DT power is conducted and reasoning is given to support the observed behavior. The importance of the method of VR as part of a VSS algorithm is emphasized.
Zhang, Jinkai; Rivard, Benoit; Rogge, D.M.
2008-01-01
Spectral mixing is a problem inherent to remote sensing data and results in few image pixel spectra representing ″pure″ targets. Linear spectral mixture analysis is designed to address this problem and it assumes that the pixel-to-pixel variability in a scene results from varying proportions of spectral endmembers. In this paper we present a different endmember-search algorithm called the Successive Projection Algorithm (SPA). SPA builds on convex geometry and orthogonal projection common to other endmember search algorithms by including a constraint on the spatial adjacency of endmember candidate pixels. Consequently it can reduce the susceptibility to outlier pixels and generates realistic endmembers.This is demonstrated using two case studies (AVIRIS Cuprite cube and Probe-1 imagery for Baffin Island) where image endmembers can be validated with ground truth data. The SPA algorithm extracts endmembers from hyperspectral data without having to reduce the data dimensionality. It uses the spectral angle (alike IEA) and the spatial adjacency of pixels in the image to constrain the selection of candidate pixels representing an endmember. We designed SPA based on the observation that many targets have spatial continuity (e.g. bedrock lithologies) in imagery and thus a spatial constraint would be beneficial in the endmember search. An additional product of the SPA is data describing the change of the simplex volume ratio between successive iterations during the endmember extraction. It illustrates the influence of a new endmember on the data structure, and provides information on the convergence of the algorithm. It can provide a general guideline to constrain the total number of endmembers in a search.
WIDE-FIELD WIDE-BAND INTERFEROMETRIC IMAGING: THE WB A-PROJECTION AND HYBRID ALGORITHMS
Bhatnagar, S.; Rau, U.; Golap, K. E-mail: rurvashi@nrao.edu
2013-06-20
Variations of the antenna primary beam (PB) pattern as a function of time, frequency, and polarization form one of the dominant direction-dependent effects at most radio frequency bands. These gains may also vary from antenna to antenna. The A-Projection algorithm, published earlier, accounts for the effects of the narrow-band antenna PB in full polarization. In this paper, we present the wide-band A-Projection algorithm (WB A-Projection) to include the effects of wide bandwidth in the A-term itself and show that the resulting algorithm simultaneously corrects for the time, frequency, and polarization dependence of the PB. We discuss the combination of the WB A-Projection and the multi-term multi-frequency synthesis (MT-MFS) algorithm for simultaneous mapping of the sky brightness distribution and the spectral index distribution across a wide field of view. We also discuss the use of the narrow-band A-Projection algorithm in hybrid imaging schemes that account for the frequency dependence of the PB in the image domain.
Wide-field wide-band Interferometric Imaging: The WB A-Projection and Hybrid Algorithms
NASA Astrophysics Data System (ADS)
Bhatnagar, S.; Rau, U.; Golap, K.
2013-06-01
Variations of the antenna primary beam (PB) pattern as a function of time, frequency, and polarization form one of the dominant direction-dependent effects at most radio frequency bands. These gains may also vary from antenna to antenna. The A-Projection algorithm, published earlier, accounts for the effects of the narrow-band antenna PB in full polarization. In this paper, we present the wide-band A-Projection algorithm (WB A-Projection) to include the effects of wide bandwidth in the A-term itself and show that the resulting algorithm simultaneously corrects for the time, frequency, and polarization dependence of the PB. We discuss the combination of the WB A-Projection and the multi-term multi-frequency synthesis (MT-MFS) algorithm for simultaneous mapping of the sky brightness distribution and the spectral index distribution across a wide field of view. We also discuss the use of the narrow-band A-Projection algorithm in hybrid imaging schemes that account for the frequency dependence of the PB in the image domain.
NASA Astrophysics Data System (ADS)
Sekihara, Kensuke; Kawabata, Yuya; Ushio, Shuta; Sumiya, Satoshi; Kawabata, Shigenori; Adachi, Yoshiaki; Nagarajan, Srikantan S.
2016-06-01
Objective. In functional electrophysiological imaging, signals are often contaminated by interference that can be of considerable magnitude compared to the signals of interest. This paper proposes a novel algorithm for removing such interferences that does not require separate noise measurements. Approach. The algorithm is based on a dual definition of the signal subspace in the spatial- and time-domains. Since the algorithm makes use of this duality, it is named the dual signal subspace projection (DSSP). The DSSP algorithm first projects the columns of the measured data matrix onto the inside and outside of the spatial-domain signal subspace, creating a set of two preprocessed data matrices. The intersection of the row spans of these two matrices is estimated as the time-domain interference subspace. The original data matrix is projected onto the subspace that is orthogonal to this interference subspace. Main results. The DSSP algorithm is validated by using the computer simulation, and using two sets of real biomagnetic data: spinal cord evoked field data measured from a healthy volunteer and magnetoencephalography data from a patient with a vagus nerve stimulator. Significance. The proposed DSSP algorithm is effective for removing overlapped interference in a wide variety of biomagnetic measurements.
Sanz, J.L.; Dinstein, I.
1987-01-01
In this paper, some image transforms and features such as projections along linear patterns, convex hull approximations, Hough transform for line detection, diameter, moments, and principal components will be considered. Specifically, we present algorithms for computing these features which are suitable for implementation in image analysis pipeline architectures. In particular, random access memories and other dedicated hardware components which may be found in the implementation of classical techniques are not longer needed in our algorithms. The effectiveness of our approach is demonstrated by running some of the new algorithms in conventional short-pipelines for image analysis.
A penalty-projection algorithm for a monolithic fluid-structure interaction solver
NASA Astrophysics Data System (ADS)
Cerroni, D.; Manservisi, S.
2016-05-01
In this paper we propose a new iterative penalty-projection algorithm for a monolithic fluid-structure interaction solver. Projection methods, that split the computation of the velocity from the pressure, are very popular in fluid dynamics since the boundary errors generated by the projection method are localized mainly near the boundary layers where the incorrect pressure boundary conditions are imposed. However, when solid regions are taken into account, the pressure projected field cannot satisfy fully coupled boundary constraints imposed on external solid surfaces such as stress-free conditions, and, due to the rigidity of the medium, the boundary errors propagate deeply in the interior. In order to reduce the projection errors we propose a one-step penalty-projection method in the fluid domain and an iterative penalty-projection method in the solid region. This technique decouples the pressure-velocity degrees of freedom and, as a consequence, the computational cost. In order to verify the accuracy and robustness of the proposed method we compare the results between this splitting velocity-pressure algorithm and the coupled one. These numerical results show stability and robustness of the proposed algorithm with a strong reduction of the computational effort.
Designing of an environmental assessment algorithm for surface mining projects.
Mirmohammadi, Mirsaleh; Gholamnejad, Javad; Fattahpour, Vahidoddin; Seyedsadri, Pejman; Ghorbani, Yousef
2009-06-01
This paper depicts the method used to quantify the environmental impact of mining activities in surface mine projects. The affected environment was broken down into thirteen components, such as Human health and immunity, Surface water, Air quality, etc. The effect of twenty impacting factors from the mining and milling activities was then calculated for each Environmental Component. Environmental assessments are often performed by using matrix methods in which one dimension of the matrix is the "Impacting Factor" and the other one is the "Environmental Components". For the presented matrix method, each Impacting Factor was first given a magnitude between -10 and 10. These factors are used to set up a matrix named Impacting Factor Matrix, whose elements represent the Impacting Factor values. The effects of each Impacting Factor on each Environmental Component were then quantified by multiplying the Impacting Factor Matrix by Weighting Factor Matrix. The elements of the weighting factors matrix reflect the effects of each Impacting Factor on each Environmental Component. The outlined method was originally developed for a mining and milling operation in Iran, but it can successfully be used for mining ventures and more general industrial activities in other countries in accordance to their environmental regulations and laws. PMID:19286301
Improvement of wavelet threshold filtered back-projection image reconstruction algorithm
NASA Astrophysics Data System (ADS)
Ren, Zhong; Liu, Guodong; Huang, Zhen
2014-11-01
Image reconstruction technique has been applied into many fields including some medical imaging, such as X ray computer tomography (X-CT), positron emission tomography (PET) and nuclear magnetic resonance imaging (MRI) etc, but the reconstructed effects are still not satisfied because original projection data are inevitably polluted by noises in process of image reconstruction. Although some traditional filters e.g., Shepp-Logan (SL) and Ram-Lak (RL) filter have the ability to filter some noises, Gibbs oscillation phenomenon are generated and artifacts leaded by back-projection are not greatly improved. Wavelet threshold denoising can overcome the noises interference to image reconstruction. Since some inherent defects exist in the traditional soft and hard threshold functions, an improved wavelet threshold function combined with filtered back-projection (FBP) algorithm was proposed in this paper. Four different reconstruction algorithms were compared in simulated experiments. Experimental results demonstrated that this improved algorithm greatly eliminated the shortcomings of un-continuity and large distortion of traditional threshold functions and the Gibbs oscillation. Finally, the availability of this improved algorithm was verified from the comparison of two evaluation criterions, i.e. mean square error (MSE), peak signal to noise ratio (PSNR) among four different algorithms, and the optimum dual threshold values of improved wavelet threshold function was gotten.
Quantum Algorithm for Universal Implementation of the Projective Measurement of Energy
NASA Astrophysics Data System (ADS)
Nakayama, Shojun; Soeda, Akihito; Murao, Mio
2015-05-01
A projective measurement of energy (PME) on a quantum system is a quantum measurement determined by the Hamiltonian of the system. PME protocols exist when the Hamiltonian is given in advance. Unknown Hamiltonians can be identified by quantum tomography, but the time cost to achieve a given accuracy increases exponentially with the size of the quantum system. In this Letter, we improve the time cost by adapting quantum phase estimation, an algorithm designed for computational problems, to measurements on physical systems. We present a PME protocol without quantum tomography for Hamiltonians whose dimension and energy scale are given but which are otherwise unknown. Our protocol implements a PME to arbitrary accuracy without any dimension dependence on its time cost. We also show that another computational quantum algorithm may be used for efficient estimation of the energy scale. These algorithms show that computational quantum algorithms, with suitable modifications, have applications beyond their original context.
Rush, A J; Rago, W V; Crismon, M L; Toprac, M G; Shon, S P; Suppes, T; Miller, A L; Trivedi, M H; Swann, A C; Biggs, M M; Shores-Wilson, K; Kashner, T M; Pigott, T; Chiles, J A; Gilbert, D A; Altshuler, K Z
1999-05-01
This article provides an overview of the issues involved in developing, using, and evaluating specific medication guidelines for patients with psychiatric disorders. The potential advantages and disadvantages, as well as the essential elements in the structure of algorithms, are illustrated by experience to date with the Texas Medication Algorithm Project, a public-academic collaboration. Phase 1 entailed assembling research findings on the efficacy of medications for schizophrenic, bipolar, and major depressive disorders. This knowledge was evaluated for its quality and relevance, integrated with expert clinical judgment as well as input by practicing clinicians, family advocates, and patients. Phase 1 (the design and development of the algorithms) was followed by a feasibility test (Phase 2). Phase 3 is an ongoing evaluation comparing the clinical and economic effects of using specific medication guidelines (algorithms) versus treatment as usual in public sector patients with severe and persistent mental illnesses. PMID:10362434
A selective-update affine projection algorithm with selective input vectors
NASA Astrophysics Data System (ADS)
Kong, NamWoong; Shin, JaeWook; Park, PooGyeon
2011-10-01
This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.
An accelerated threshold-based back-projection algorithm for Compton camera image reconstruction
Mundy, Daniel W.; Herman, Michael G.
2011-01-15
Purpose: Compton camera imaging (CCI) systems are currently under investigation for radiotherapy dose reconstruction and verification. The ability of such a system to provide real-time images during dose delivery will be limited by the computational speed of the image reconstruction algorithm. In this work, the authors present a fast and simple method by which to generate an initial back-projected image from acquired CCI data, suitable for use in a filtered back-projection algorithm or as a starting point for iterative reconstruction algorithms, and compare its performance to the current state of the art. Methods: Each detector event in a CCI system describes a conical surface that includes the true point of origin of the detected photon. Numerical image reconstruction algorithms require, as a first step, the back-projection of each of these conical surfaces into an image space. The algorithm presented here first generates a solution matrix for each slice of the image space by solving the intersection of the conical surface with the image plane. Each element of the solution matrix is proportional to the distance of the corresponding voxel from the true intersection curve. A threshold function was developed to extract those pixels sufficiently close to the true intersection to generate a binary intersection curve. This process is repeated for each image plane for each CCI detector event, resulting in a three-dimensional back-projection image. The performance of this algorithm was tested against a marching algorithm known for speed and accuracy. Results: The threshold-based algorithm was found to be approximately four times faster than the current state of the art with minimal deficit to image quality, arising from the fact that a generically applicable threshold function cannot provide perfect results in all situations. The algorithm fails to extract a complete intersection curve in image slices near the detector surface for detector event cones having axes nearly
Feature selection and back-projection algorithms for nonline-of-sight laser-gated viewing
NASA Astrophysics Data System (ADS)
Laurenzis, Martin; Velten, Andreas
2014-11-01
We discuss new approaches to analyze laser-gated viewing data for nonline-of-sight vision with a frame-to-frame back-projection as well as feature selection algorithms. Although first back-projection approaches use time transients for each pixel, our method has the ability to calculate the projection of imaging data on the voxel space for each frame. Further, different data analysis algorithms and their sequential application were studied with the aim of identifying and selecting signals from different target positions. A slight modification of commonly used filters leads to a powerful selection of local maximum values. It is demonstrated that the choice of the filter has an impact on the selectivity i.e., multiple target detection as well as on the localization precision.
Developing a synergy algorithm for land surface temperature: the SEN4LST project
NASA Astrophysics Data System (ADS)
Sobrino, Jose A.; Jimenez, Juan C.; Ghent, Darren J.
2013-04-01
Land surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. An adequate characterization of LST distribution and its temporal evolution requires measurements with detailed spatial and temporal frequencies. With the advent of the Sentinel 2 (S2) and 3 (S3) series of satellites a unique opportunity exists to go beyond the current state of the art of single instrument algorithms. The Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project aims at developing techniques to fully utilize synergy between S2 and S3 instruments in order to improve LST retrievals. In the framework of the SEN4LST project, three LST retrieval algorithms were proposed using the thermal infrared bands of the Sea and Land Surface Temperature Retrieval (SLSTR) instrument on board the S3 platform: split-window (SW), dual-angle (DA) and a combined algorithm using both split-window and dual-angle techniques (SW-DA). One of the objectives of the project is to select the best algorithm to generate LST products from the synergy between S2/S3 instruments. In this sense, validation is a critical step in the selection process for the best performing candidate algorithm. A unique match-up database constructed at University of Leicester (UoL) of in situ observations from over twenty ground stations and corresponding brightness temperature (BT) and LST match-ups from multi-sensor overpasses is utilised for validating the candidate algorithms. Furthermore, their performance is also evaluated against the standard ESA LST product and the enhanced offline UoL LST product. In addition, a simulation dataset is constructed using 17 synthetic images of LST and the radiative transfer model MODTRAN carried under 66 different atmospheric conditions. Each candidate LST
softMip: a novel projection algorithm for ultra-low-dose computed tomography.
Meyer, Henning; Juran, Ralf; Rogalla, Patrik
2008-01-01
Two projection algorithms are currently available for viewing computed tomography (CT) data sets: average projection (AVG) and maximum intensity projection (MIP). Although AVG images feature good suppression of image noise but reduced edge sharpness, MIP images are characterized by good edge sharpness but also amplify image noise. Ultra-low-dose (ULD) CT has very low radiation exposure but has high image noise. Maximum intensity projection images of ULDCT data sets amplify image noise and are therefore unsuitable for image interpretation in the routine clinical setting. We developed a synthesis of both algorithms that tries to unite the respective advantages. The resulting softMip algorithm was implemented in C++ and installed on a workstation. Depending on the settings used, softMip images can represent any graduation between MIP and AVG. The new softMip algorithm was evaluated and compared with MIP and AVG in terms of image noise and edge sharpness in a series of phantom experiments performed on 7 different CT scanners. Furthermore, image quality of the transition from AVG to MIP by means of softMip was compared with the image quality of simply blending AVG and MIP. Images generated with softMip showed less image noise than MIP images (P < 0.0005) and higher edge sharpness than AVG images (P< 0.0005). The softMip transition from AVG to MIP had a better ratio of edge sharpness and image noise than blending (P < 0.0005). Our results suggest that softMip is a very promising projection procedure for postprocessing cross-sectional image data, especially ULDCT data sets. PMID:18520560
Non-iterative conductivity reconstruction algorithm using projected current density in MREIT
NASA Astrophysics Data System (ADS)
Nam, Hyun Soo; Park, Chunjae; In Kwon, Oh
2008-12-01
Magnetic resonance electrical impedance tomography (MREIT) is to visualize the current density and the conductivity distribution in an electrical object Ω using the measured magnetic flux data by an MRI scanner. MREIT uses only one component Bz of the magnetic flux density B = (Bx, By, Bz) generated by an injected electrical current into the object. In this paper, we propose a fast and direct non-iterative algorithm to reconstruct the internal conductivity distribution in Ω with the measured Bz data. To develop the algorithm, we investigate the relation between the projected current density JP, a uniquely determined component of J by the map from current J to measured Bz data and the isotropic conductivity. Three-dimensional numerical simulations and phantom experiments are studied to show the feasibility of the proposed method by comparing with those using the conventional iterative harmonic Bz algorithm.
NASA Astrophysics Data System (ADS)
Pokhrel, Damodar
Interstitial and intracavitary brachytherapy plays an essential role in management of several malignancies. However, the achievable accuracy of brachytherapy treatment for prostate and cervical cancer is limited due to the lack of intraoperative planning and adaptive replanning. A major problem in implementing TRUS-based intraoperative planning is an inability of TRUS to accurately localize individual seed poses (positions and orientations) relative to the prostate volume during or after the implantation. For the locally advanced cervical cancer patient, manual drawing of the source positions on orthogonal films can not localize the full 3D intracavitary brachytherapy (ICB) applicator geometry. A new iterative forward projection matching (IFPM) algorithm can explicitly localize each individual seed/applicator by iteratively matching computed projections of the post-implant patient with the measured projections. This thesis describes adaptation and implementation of a novel IFPM algorithm that addresses hitherto unsolved problems in localization of brachytherapy seeds and applicators. The prototype implementation of 3-parameter point-seed IFPM algorithm was experimentally validated using a set of a few cone-beam CT (CBCT) projections of both the phantom and post-implant patient's datasets. Geometric uncertainty due to gantry angle inaccuracy was incorporated. After this, IFPM algorithm was extended to 5-parameter elongated line-seed model which automatically reconstructs individual seed orientation as well as position. The accuracy of this algorithm was tested using both the synthetic-measured projections of clinically-realistic Model-6711 125I seed arrangements and measured projections of an in-house precision-machined prostate implant phantom that allows the orientations and locations of up to 100 seeds to be set to known values. The seed reconstruction error for simulation was less than 0.6 mm/3o. For the physical phantom experiments, IFPM absolute accuracy for
Multiple R&D Projects Scheduling Optimization with Improved Particle Swarm Algorithm
Liu, Mengqi; Shan, Miyuan; Wu, Juan
2014-01-01
For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment. PMID:25032232
Sun, Pengfei; Sun, Changku; Li, Wenqiang; Wang, Peng
2015-01-01
Pose estimation aims at measuring the position and orientation of a calibrated camera using known image features. The pinhole model is the dominant camera model in this field. However, the imaging precision of this model is not accurate enough for an advanced pose estimation algorithm. In this paper, a new camera model, called incident ray tracking model, is introduced. More importantly, an advanced pose estimation algorithm based on the perspective ray in the new camera model, is proposed. The perspective ray, determined by two positioning points, is an abstract mathematical equivalent of the incident ray. In the proposed pose estimation algorithm, called perspective-ray-based scaled orthographic projection with iteration (PRSOI), an approximate ray-based projection is calculated by a linear system and refined by iteration. Experiments on the PRSOI have been conducted, and the results demonstrate that it is of high accuracy in the six degrees of freedom (DOF) motion. And it outperforms three other state-of-the-art algorithms in terms of accuracy during the contrast experiment. PMID:26197272
The finite state projection algorithm for the solution of the chemical master equation.
Munsky, Brian; Khammash, Mustafa
2006-01-28
This article introduces the finite state projection (FSP) method for use in the stochastic analysis of chemically reacting systems. One can describe the chemical populations of such systems with probability density vectors that evolve according to a set of linear ordinary differential equations known as the chemical master equation (CME). Unlike Monte Carlo methods such as the stochastic simulation algorithm (SSA) or tau leaping, the FSP directly solves or approximates the solution of the CME. If the CME describes a system that has a finite number of distinct population vectors, the FSP method provides an exact analytical solution. When an infinite or extremely large number of population variations is possible, the state space can be truncated, and the FSP method provides a certificate of accuracy for how closely the truncated space approximation matches the true solution. The proposed FSP algorithm systematically increases the projection space in order to meet prespecified tolerance in the total probability density error. For any system in which a sufficiently accurate FSP exists, the FSP algorithm is shown to converge in a finite number of steps. The FSP is utilized to solve two examples taken from the field of systems biology, and comparisons are made between the FSP, the SSA, and tau leaping algorithms. In both examples, the FSP outperforms the SSA in terms of accuracy as well as computational efficiency. Furthermore, due to very small molecular counts in these particular examples, the FSP also performs far more effectively than tau leaping methods. PMID:16460146
A homotopy algorithm for digital optimal projection control GASD-HADOC
NASA Technical Reports Server (NTRS)
Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.
1993-01-01
The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.
Zdunek, Rafal; Cichocki, Andrzej
2008-01-01
Recently, a considerable growth of interest in projected gradient (PG) methods has been observed due to their high efficiency in solving large-scale convex minimization problems subject to linear constraints. Since the minimization problems underlying nonnegative matrix factorization (NMF) of large matrices well matches this class of minimization problems, we investigate and test some recent PG methods in the context of their applicability to NMF. In particular, the paper focuses on the following modified methods: projected Landweber, Barzilai-Borwein gradient projection, projected sequential subspace optimization (PSESOP), interior-point Newton (IPN), and sequential coordinate-wise. The proposed and implemented NMF PG algorithms are compared with respect to their performance in terms of signal-to-interference ratio (SIR) and elapsed time, using a simple benchmark of mixed partially dependent nonnegative signals. PMID:18628948
NASA Astrophysics Data System (ADS)
Kochanek, Anna
2015-12-01
The process of area development and planning in compliance with conditions outlined in the Zoning Scheme is significant because of the current rapid development of rural and urban areas. The verification of project documentation in terms of observing constant and nationally binding norms, legislation and local laws is based on certain standards. In order to streamline the process of verification undertaken by the relevant public authorities, it is necessary to create formal algorithms that will automate the existing method of control of architecture-building documentation. The objective of this article is algorithmisation of the project documentation verification allowing further streamlining and automation of the process.
NASA Astrophysics Data System (ADS)
Zhang, Xing; Wen, Gongjian
2015-10-01
Anomaly detection (AD) becomes increasingly important in hyperspectral imagery analysis with many practical applications. Local orthogonal subspace projection (LOSP) detector is a popular anomaly detector which exploits local endmembers/eigenvectors around the pixel under test (PUT) to construct background subspace. However, this subspace only takes advantage of the spectral information, but the spatial correlat ion of the background clutter is neglected, which leads to the anomaly detection result sensitive to the accuracy of the estimated subspace. In this paper, a local three dimensional orthogonal subspace projection (3D-LOSP) algorithm is proposed. Firstly, under the jointly use of both spectral and spatial information, three directional background subspaces are created along the image height direction, the image width direction and the spectral direction, respectively. Then, the three corresponding orthogonal subspaces are calculated. After that, each vector along three direction of the local cube is projected onto the corresponding orthogonal subspace. Finally, a composite score is given through the three direction operators. In 3D-LOSP, the anomalies are redefined as the target not only spectrally different to the background, but also spatially distinct. Thanks to the addition of the spatial information, the robustness of the anomaly detection result has been improved greatly by the proposed 3D-LOSP algorithm. It is noteworthy that the proposed algorithm is an expansion of LOSP and this ideology can inspire many other spectral-based anomaly detection methods. Experiments with real hyperspectral images have proved the stability of the detection result.
ERIC Educational Resources Information Center
Pliszka, Steven R.; Crismon, M. Lynn; Hughes, Carroll W.; Corners, C. Keith; Emslie, Graham J.; Jensen, Peter S.; McCracken, James T.; Swanson, James M.; Lopez, Molly
2006-01-01
Objective: In 1998, the Texas Department of Mental Health and Mental Retardation developed algorithms for medication treatment of attention-deficit/hyperactivity disorder (ADHD). Advances in the psychopharmacology of ADHD and results of a feasibility study of algorithm use in community mental health centers caused the algorithm to be modified and…
Evaluation of observation-driven evaporation algorithms: results of the WACMOS-ET project
NASA Astrophysics Data System (ADS)
Miralles, Diego G.; Jimenez, Carlos; Ershadi, Ali; McCabe, Matthew F.; Michel, Dominik; Hirschi, Martin; Seneviratne, Sonia I.; Jung, Martin; Wood, Eric F.; (Bob) Su, Z.; Timmermans, Joris; Chen, Xuelong; Fisher, Joshua B.; Mu, Quiaozen; Fernandez, Diego
2015-04-01
Terrestrial evaporation (ET) links the continental water, energy and carbon cycles. Understanding the magnitude and variability of ET at the global scale is an essential step towards reducing uncertainties in our projections of climatic conditions and water availability for the future. However, the requirement of global observational data of ET can neither be satisfied with our sparse global in-situ networks, nor with the existing satellite sensors (which cannot measure evaporation directly from space). This situation has led to the recent rise of several algorithms dedicated to deriving ET fields from satellite data indirectly, based on the combination of ET-drivers that can be observed from space (e.g. radiation, temperature, phenological variability, water content, etc.). These algorithms can either be based on physics (e.g. Priestley and Taylor or Penman-Monteith approaches) or be purely statistical (e.g., machine learning). However, and despite the efforts from different initiatives like GEWEX LandFlux (Jimenez et al., 2011; Mueller et al., 2013), the uncertainties inherent in the resulting global ET datasets remain largely unexplored, partly due to a lack of inter-product consistency in forcing data. In response to this need, the ESA WACMOS-ET project started in 2012 with the main objectives of (a) developing a Reference Input Data Set to derive and validate ET estimates, and (b) performing a cross-comparison, error characterization and validation exercise of a group of selected ET algorithms driven by this Reference Input Data Set and by in-situ forcing data. The algorithms tested are SEBS (Su et al., 2002), the Penman- Monteith approach from MODIS (Mu et al., 2011), the Priestley and Taylor JPL model (Fisher et al., 2008), the MPI-MTE model (Jung et al., 2010) and GLEAM (Miralles et al., 2011). In this presentation we will show the first results from the ESA WACMOS-ET project. The performance of the different algorithms at multiple spatial and temporal
A scalable projective scaling algorithm for l(p) loss with convex penalizations.
Zhou, Hongbo; Cheng, Qiang
2015-02-01
This paper presents an accurate, efficient, and scalable algorithm for minimizing a special family of convex functions, which have a lp loss function as an additive component. For this problem, well-known learning algorithms often have well-established results on accuracy and efficiency, but there exists rarely any report on explicit linear scalability with respect to the problem size. The proposed approach starts with developing a second-order learning procedure with iterative descent for general convex penalization functions, and then builds efficient algorithms for a restricted family of functions, which satisfy the Karmarkar's projective scaling condition. Under this condition, a light weight, scalable message passing algorithm (MPA) is further developed by constructing a series of simpler equivalent problems. The proposed MPA is intrinsically scalable because it only involves matrix-vector multiplication and avoids matrix inversion operations. The MPA is proven to be globally convergent for convex formulations; for nonconvex situations, it converges to a stationary point. The accuracy, efficiency, scalability, and applicability of the proposed method are verified through extensive experiments on sparse signal recovery, face image classification, and over-complete dictionary learning problems. PMID:25608289
NASA Astrophysics Data System (ADS)
Arevalillo-Herráez, Miguel; Gdeisat, Munther; Lilley, Francis; Burton, David R.
2016-07-01
In this paper, we present a novel algorithm to reduce the number of phase wraps in two dimensional signals in fringe projection profilometry. The technique operates in the spatial domain, and achieves a significant computational saving with regard to existing methods based on frequency shifting. The method works by estimating the modes of the first differences distribution in each axial direction. These are used to generate a tilted plane, which is subtracted from the entire phase map. Finally, the result is re-wrapped to obtain a phase map with fewer wraps. The method may be able to completely eliminate the phase wraps in many cases, or can achieve a significant phase wrap reduction that helps the subsequent unwrapping of the signal. The algorithm has been exhaustively tested across a large number of real and simulated signals, showing similar results compared to approaches operating in the frequency domain, but at significantly lower running times.
Position algorithm for monolithic scintillation crystals based on charge projection readout
NASA Astrophysics Data System (ADS)
Pani, R.; Bettiol, M.; Preziosi, E.; Cinti, M. N.; Borrazzo, C.; Pellegrini, R.; Di Castro, E.; Fabbri, A.
2016-01-01
Nuclear medicine imaging devices commonly use multi-element photo detection systems, composed of an array of N × N elements, each one providing an individual signal. Many strategies have been developed to reduce the number of readout channels, one of the main approaches is the Rows and Columns (R/C) projection logic. In this paper we proposed a modified version of Raised To the Power (RTP) algorithm adapted to R/C logic. In order to validate its efficiency a linear scanning irradiation on two 49× 49 mm2 LaBr3:Ce (0.5%) crystals with different thickness (4 mm and 10 mm) was carried out. Imaging performance analysis was made in terms of position linearity, Field-of-View (FoV) enlargement and spatial resolution. Imaging results from Anger Logic, RTP algorithm based on single element readout and RTP algorithm based on R/C readout were compared. A notable advantage of using RTP algorithms instead of Anger Logic was found: the FoV widens from about 30% to more than 70% of the detector area whereas the spatial resolution is highly improved, especially for off-center interactions, both for 4 mm-thick and 10 mm-thick crystals. Furthermore, imaging performance with the R/C readout is just slightly different from the single element one (FoV reduction less than 7% and SR worsening less than 10%). The R/C adapted RTP algorithm opens doors to high imaging performance with a substantial reduction of complexity and cost in the readout electronics.
Webb-Robertson, Bobbie-Jo M.; Jarman, Kristin H.; Harvey, Scott D.; Posse, Christian; Wright, Bob W.
2005-05-28
A fundamental problem in analysis of highly multivariate spectral or chromatographic data is reduction of dimensionality. Principal components analysis (PCA), concerned with explaining the variance-covariance structure of the data, is a commonly used approach to dimension reduction. Recently an attractive alternative to PCA, sequential projection pursuit (SPP), has been introduced. Designed to elicit clustering tendencies in the data, SPP may be more appropriate when performing clustering or classification analysis. However, the existing genetic algorithm (GA) implementation of SPP has two shortcomings, computation time and inability to determine the number of factors necessary to explain the majority of the structure in the data. We address both these shortcomings. First, we introduce a new SPP algorithm, a random scan sampling algorithm (RSSA), that significantly reduces computation time. We compare the computational burden of the RSS and GA implementation for SPP on a dataset containing Raman spectra of twelve organic compounds. Second, we propose a Bayes factor criterion, BFC, as an effective measure for selecting the number of factors needed to explain the majority of the structure in the data. We compare SPP to PCA on two datasets varying in type, size, and difficulty; in both cases SPP achieves a higher accuracy with a lower number of latent variables.
High-Resolution Snow Projections for Alaska: Regionally and seasonally specific algorithms
NASA Astrophysics Data System (ADS)
McAfee, S. A.; Walsh, J. E.; Rupp, S. T.
2012-12-01
The fate of Alaska's snow in a warmer world is of both scientific and practical concern. Snow projections are critical for understanding glacier mass balance, forest demographic changes, and for natural resource planning and decision making - such as hydropower facilities in southern and southeastern portions of the state and winter road construction and use in the northern portions. To meet this need, we have developed a set of regionally and seasonally specific statistical models relating long-term average snow-day fraction from average monthly temperature in Alaska. The algorithms were based on temperature data and on daily precipitation and snowfall occurrence for 104 stations from the Global Historical Climatology Network. Although numerous models exist for estimating snow fraction from temperature, the algorithms we present here provide substantial improvements for Alaska. There are fundamental differences in the synoptic conditions across the state, and specific algorithms can accommodate this variability in the relationship between average monthly temperature and typical conditions during snowfall, rainfall, and dry spells. In addition, this set of simple algorithms, unlike more complex physically based models, can be easily and efficiently applied to a large number of future temperature trajectories, facilitating scenario-based planning approaches. Model fits are quite good, with mean errors of the snow-day fractions at most stations within 0.1 of the observed values, which range from 0 to 1, although larger average errors do occur at some sites during the transition seasons. Errors at specific stations are often stable in terms of sign and magnitude across the snowy season, suggesting that site-specific conditions can drive consistent deviations from mean regional conditions. Applying these algorithms to the gridded temperature projections downscaled by the Scenarios Network for Alaska and Arctic Planning, allows us to provide decadal estimates of changes
NASA Astrophysics Data System (ADS)
Fang, Yi-Chin; Liu, Tung-Kuan; Wu, Bo-Wen; Chou, Jyh-Horng; MacDonald, John
2008-05-01
Following the development of a digitalized image optics system, chromatic aberration has become increasingly important especially in lateral color aberration. For rear projection television L-type lens, chromatic aberration plays the significant role because it is easily seen when facing bright screen. Basically, the elimination of axial chromatic and lateral color aberration for an optical lens depends on the choice of optical glass. DLS (damped least squares), a Ray-tracing-based method, is limited, owing to its inability to identify an enhanced optical system configuration. Genetic algorithms were applied to so-called global optimization but unfortunately so far the results show little success. Additionally, L-type optics with aspherical surface might complicate optimization due to being nonlinear response during optimization. As an alternative, this research proposes a new feasible chromatic aberration optimization process by using algorithms involving theories of geometric optics in a lens, real encoding, multiple dynamic crossover and random gene mutation techniques. In this research, rear projection television lens with aspherical surface and L-type lens are mainly discussed. Results and conclusions show that attempts to eliminate difficult axial and lateral color aberration are successful.
Optimal well locations using genetic algorithm for Tushki Project, Western Desert, Egypt
NASA Astrophysics Data System (ADS)
Khalaf, S.; Gad, M. I.
2014-10-01
Groundwater depletion is one of the most important problems threaten the national projects in Egypt. The optimal distribution of well locations and pumping rates mitigate this problem. In this paper, a trial to mitigate this problem in Tushki National Project, south western desert, Egypt was carried out via delineating the optimal well locations and optimal pumping rates. The methodology of combination between simulation and optimization techniques was applied. A linked simulation-optimization model for obtaining the optimum management of groundwater flow is used in this research. MODFLOW packages are used to simulate the groundwater flow system. This model is integrated with an optimization model OLGA (Optimal well Location using Genetic Algorithm technique) which is based on the genetic algorithm (GA). Two management cases were considered by running the model in Abu Simbel-Tushki area with adopted steady and transit calibrated parameters. The first case (fixed well location) is found that the optimum value of the objective function (maximum pumping rate). In the second case (flexible well location with the moving well option) locations of wells are to be decided by the OLGA model itself within a user defined region of the model grid until the optimal location is reached. Also, the prediction of the future changes in both head and flow were made in steady and transient states.
Field depth extension of 2D barcode scanner based on wavefront coding and projection algorithm
NASA Astrophysics Data System (ADS)
Zhao, Tingyu; Ye, Zi; Zhang, Wenzi; Huang, Weiwei; Yu, Feihong
2008-03-01
Wavefront coding (WFC) used in 2D barcode scanners can extend the depth of field into a great extent with simpler structure compared to the autofocus microscope system. With a cubic phase mask (CPM) employed in the STOP, blurred images will be obtained in charge coupled device (CCD), which can be restored by digital filters. Direct methods are used widely in real-time restoration with good computational efficiency but with details smoothed. Here, the results of direct method are firstly filtered by hard-threshold function. The positions of the steps can be detected by simple differential operators. With the positions corrected by projection algorithm, the exact barcode information is restored. A wavefront coding system with 7mm effective focal length and 6 F-number is designed as an example. Although with the different magnification, images of different object distances can be restored by one point spread function (PSF) with 200mm object distance. A QR code (Quickly Response Code) of 31mm X 27mm is used as a target object. The simulation results showed that the sharp imaging objective distance is from 80mm to 355mm. The 2D barcode scanner with wavefront coding extends field depth with simple structure, low cost and large manufacture tolerance. This combination of the direct filter and projection algorithm proposed here could get the exact 2D barcode information with good computational efficiency.
Gomes, Adriano de Araújo; Alcaraz, Mirta Raquel; Goicoechea, Hector C; Araújo, Mario Cesar U
2014-02-01
In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV-vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL. PMID:24456589
NASA Astrophysics Data System (ADS)
Shams Esfand Abadi, Mohammad; AbbasZadeh Arani, Seyed Ali Asghar
2011-12-01
This paper extends the recently introduced variable step-size (VSS) approach to the family of adaptive filter algorithms. This method uses prior knowledge of the channel impulse response statistic. Accordingly, optimal step-size vector is obtained by minimizing the mean-square deviation (MSD). The presented algorithms are the VSS affine projection algorithm (VSS-APA), the VSS selective partial update NLMS (VSS-SPU-NLMS), the VSS-SPU-APA, and the VSS selective regressor APA (VSS-SR-APA). In VSS-SPU adaptive algorithms the filter coefficients are partially updated which reduce the computational complexity. In VSS-SR-APA, the optimal selection of input regressors is performed during the adaptation. The presented algorithms have good convergence speed, low steady state mean square error (MSE), and low computational complexity features. We demonstrate the good performance of the proposed algorithms through several simulations in system identification scenario.
Pokhrel, Damodar; Murphy, Martin J.; Todor, Dorin A.; Weiss, Elisabeth; Williamson, Jeffrey F.
2010-09-15
Purpose: To experimentally validate a new algorithm for reconstructing the 3D positions of implanted brachytherapy seeds from postoperatively acquired 2D conebeam-CT (CBCT) projection images. Methods: The iterative forward projection matching (IFPM) algorithm finds the 3D seed geometry that minimizes the sum of the squared intensity differences between computed projections of an initial estimate of the seed configuration and radiographic projections of the implant. In-house machined phantoms, containing arrays of 12 and 72 seeds, respectively, are used to validate this method. Also, four {sup 103}Pd postimplant patients are scanned using an ACUITY digital simulator. Three to ten x-ray images are selected from the CBCT projection set and processed to create binary seed-only images. To quantify IFPM accuracy, the reconstructed seed positions are forward projected and overlaid on the measured seed images to find the nearest-neighbor distance between measured and computed seed positions for each image pair. Also, the estimated 3D seed coordinates are compared to known seed positions in the phantom and clinically obtained VariSeed planning coordinates for the patient data. Results: For the phantom study, seed localization error is (0.58{+-}0.33) mm. For all four patient cases, the mean registration error is better than 1 mm while compared against the measured seed projections. IFPM converges in 20-28 iterations, with a computation time of about 1.9-2.8 min/iteration on a 1 GHz processor. Conclusions: The IFPM algorithm avoids the need to match corresponding seeds in each projection as required by standard back-projection methods. The authors' results demonstrate {approx}1 mm accuracy in reconstructing the 3D positions of brachytherapy seeds from the measured 2D projections. This algorithm also successfully localizes overlapping clustered and highly migrated seeds in the implant.
MERIS burned area algorithm in the framework of the ESA Fire CCI Project
NASA Astrophysics Data System (ADS)
Oliva, P.; Calado, T.; Gonzalez, F.
2012-04-01
The Fire-CCI project aims at generating long and reliable time series of burned area (BA) maps based on existing information provided by European satellite sensors. In this context, a BA algorithm is currently being developed using the Medium Resolution Imaging Spectrometer (MERIS) sensor. The algorithm is being tested over a series of ten study sites with a area of 500x500 km2 each, for the period of 2003 to 2009. The study sites are located in Canada, Colombia, Brazil, Portugal, Angola, South Africa, Kazakhstan, Borneo, Russia and Australia and include a variety of vegetation types characterized by different fire regimes. The algorithm has to take into account several limiting aspects that range from the MERIS sensor characteristics (e.g. the lack of SWIR bands) to the noise presented in the data. In addition the lack of data in some areas caused either because of cloud contamination or because the sensor does not acquire full resolution data over the study area, provokes a limitation difficult to overcome. In order to overcome these drawbacks, the design of the BA algorithm is based on the analysis of maximum composites of spectral indices characterized by low values of temporal standard deviation in space and associated to MODIS hot spots. Accordingly, for each study site and year, composites of maximum values of BAI are computed and the corresponding Julian day of the maximum value and number of observations in the period are registered by pixel . Then we computed the temporal standard deviation for pixels with a number of observations greater than 10 using spatial matrices of 3x3 pixels. To classify the BAI values as burned or non-burned we extract statistics using the MODIS hot spots. A pixel is finally classified as burned if it satisfies the following conditions: i) it is associated to hot spots; ii) BAI maximum is higher than a certain threshold and iii) the standard deviation of the Julian day is less than a given number of days.
Quantum Monte Carlo algorithms for electronic structure at the petascale; the endstation project.
Kim, J; Ceperley, D M; Purwanto, W; Walter, E J; Krakauer, H; Zhang, S W; Kent, P.R. C; Hennig, R G; Umrigar, C; Bajdich, M; Kolorenc, J; Mitas, L; Srinivasan, A
2008-10-01
Over the past two decades, continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting of the properties of matter from fundamental principles. By solving the Schrodinger equation through a stochastic projection, it achieves the greatest accuracy and reliability of methods available for physical systems containing more than a few quantum particles. QMC enjoys scaling favorable to quantum chemical methods, with a computational effort which grows with the second or third power of system size. This accuracy and scalability has enabled scientific discovery across a broad spectrum of disciplines. The current methods perform very efficiently at the terascale. The quantum Monte Carlo Endstation project is a collaborative effort among researchers in the field to develop a new generation of algorithms, and their efficient implementations, which will take advantage of the upcoming petaflop architectures. Some aspects of these developments are discussed here. These tools will expand the accuracy, efficiency and range of QMC applicability and enable us to tackle challenges which are currently out of reach. The methods will be applied to several important problems including electronic and structural properties of water, transition metal oxides, nanosystems and ultracold atoms.
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.
AsteroidZoo: A New Zooniverse project to detect asteroids and improve asteroid detection algorithms
NASA Astrophysics Data System (ADS)
Beasley, M.; Lewicki, C. A.; Smith, A.; Lintott, C.; Christensen, E.
2013-12-01
We present a new citizen science project: AsteroidZoo. A collaboration between Planetary Resources, Inc., the Zooniverse Team, and the Catalina Sky Survey, we will bring the science of asteroid identification to the citizen scientist. Volunteer astronomers have proved to be a critical asset in identification and characterization of asteroids, especially potentially hazardous objects. These contributions, to date, have required that the volunteer possess a moderate telescope and the ability and willingness to be responsive to observing requests. Our new project will use data collected by the Catalina Sky Survey (CSS), currently the most productive asteroid survey, to be used by anyone with sufficient interest and an internet connection. As previous work by the Zooniverse has demonstrated, the capability of the citizen scientist is superb at classification of objects. Even the best automated searches require human intervention to identify new objects. These searches are optimized to reduce false positive rates and to prevent a single operator from being overloaded with requests. With access to the large number of people in Zooniverse, we will be able to avoid that problem and instead work to produce a complete detection list. Each frame from CSS will be searched in detail, generating a large number of new detections. We will be able to evaluate the completeness of the CSS data set and potentially provide improvements to the automated pipeline. The data corpus produced by AsteroidZoo will be used as a training environment for machine learning challenges in the future. Our goals include a more complete asteroid detection algorithm and a minimum computation program that skims the cream of the data suitable for implemention on small spacecraft. Our goal is to have the site become live in the Fall 2013.
NASA Astrophysics Data System (ADS)
Santos, Eugene, Jr.; Zhao, Qunhua; Pratto, Felicia; Pearson, Adam R.; McQueary, Bruce; Breeden, Andy; Krause, Lee
2007-04-01
Nowadays, there is an increasing demand for the military to conduct operations that are beyond traditional warfare. In these operations, analyzing and understanding those who are involved in the situation, how they are going to behave, and why they behave in certain ways is critical for success. The challenge lies in that behavior does not simply follow universal/fixed doctrines; it is significantly influenced by soft factors (i.e. cultural factors, societal norms, etc.). In addition, there is rarely just one isolated enemy; the behaviors and responses of all groups in the region, and the dynamics of the interaction among them composes an important part of the whole picture. The Dynamic Adversarial Gaming Algorithm (DAGA) project aims to provide a wargaming environment for automation of simulating dynamics of geopolitical crisis and eventually be applied to military simulation and training domain, and/or commercial gaming arena. The focus of DAGA is on modeling communities of interest (COIs), where various individuals, groups, and organizations as well as their interactions are captured. The framework should provide a context for COIs to interact with each other and influence others' behaviors. These behaviors must incorporate soft factors by modeling cultural knowledge. We do so by representing cultural variables and their influence on behavior using probabilistic networks. In this paper, we describe our COI modeling, the development of cultural networks, the interaction architecture, and a prototype of DAGA.
An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor.
Qu, Fangfang; Ren, Dong; Wang, Jihua; Zhang, Zhong; Lu, Na; Meng, Lei
2016-01-01
Spectral analysis technique based on near infrared (NIR) sensor is a powerful tool for complex information processing and high precision recognition, and it has been widely applied to quality analysis and online inspection of agricultural products. This paper proposes a new method to address the instability of small sample sizes in the successive projections algorithm (SPA) as well as the lack of association between selected variables and the analyte. The proposed method is an evaluated bootstrap ensemble SPA method (EBSPA) based on a variable evaluation index (EI) for variable selection, and is applied to the quantitative prediction of alcohol concentrations in liquor using NIR sensor. In the experiment, the proposed EBSPA with three kinds of modeling methods are established to test their performance. In addition, the proposed EBSPA combined with partial least square is compared with other state-of-the-art variable selection methods. The results show that the proposed method can solve the defects of SPA and it has the best generalization performance and stability. Furthermore, the physical meaning of the selected variables from the near infrared sensor data is clear, which can effectively reduce the variables and improve their prediction accuracy. PMID:26761015
An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor
Qu, Fangfang; Ren, Dong; Wang, Jihua; Zhang, Zhong; Lu, Na; Meng, Lei
2016-01-01
Spectral analysis technique based on near infrared (NIR) sensor is a powerful tool for complex information processing and high precision recognition, and it has been widely applied to quality analysis and online inspection of agricultural products. This paper proposes a new method to address the instability of small sample sizes in the successive projections algorithm (SPA) as well as the lack of association between selected variables and the analyte. The proposed method is an evaluated bootstrap ensemble SPA method (EBSPA) based on a variable evaluation index (EI) for variable selection, and is applied to the quantitative prediction of alcohol concentrations in liquor using NIR sensor. In the experiment, the proposed EBSPA with three kinds of modeling methods are established to test their performance. In addition, the proposed EBSPA combined with partial least square is compared with other state-of-the-art variable selection methods. The results show that the proposed method can solve the defects of SPA and it has the best generalization performance and stability. Furthermore, the physical meaning of the selected variables from the near infrared sensor data is clear, which can effectively reduce the variables and improve their prediction accuracy. PMID:26761015
Vecharynski, Eugene; Yang, Chao; Pask, John E.
2015-06-01
We present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimal block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer.
Workshop on algorithms for macromolecular modeling. Final project report, June 1, 1994--May 31, 1995
Leimkuhler, B.; Hermans, J.; Skeel, R.D.
1995-07-01
A workshop was held on algorithms and parallel implementations for macromolecular dynamics, protein folding, and structural refinement. This document contains abstracts and brief reports from that workshop.
NASA Astrophysics Data System (ADS)
Timofeew, Sergey; Eliseev, Vladimir; Tcherkassov, Oleg; Birukow, Valentin; Orbachevskyi, Leonid; Shamsutdinov, Uriy
1998-04-01
Some problems of creation of medical expert systems and the ways of their overcoming using artificial neural networks are discussed. The instrumental system for projecting neural network algorithms `Neural Architector', developed by the authors, is described. It allows to perform effective modeling of artificial neural networks and to analyze their work. The example of the application of the `Neural Architector' system in composing an expert system for diagnostics of pulmonological diseases is shown.
Cheng, Jun-Hu; Sun, Da-Wen; Pu, Hongbin
2016-04-15
The potential use of feature wavelengths for predicting drip loss in grass carp fish, as affected by being frozen at -20°C for 24 h and thawed at 4°C for 1, 2, 4, and 6 days, was investigated. Hyperspectral images of frozen-thawed fish were obtained and their corresponding spectra were extracted. Least-squares support vector machine and multiple linear regression (MLR) models were established using five key wavelengths, selected by combining a genetic algorithm and successive projections algorithm, and this showed satisfactory performance in drip loss prediction. The MLR model with a determination coefficient of prediction (R(2)P) of 0.9258, and lower root mean square error estimated by a prediction (RMSEP) of 1.12%, was applied to transfer each pixel of the image and generate the distribution maps of exudation changes. The results confirmed that it is feasible to identify the feature wavelengths using variable selection methods and chemometric analysis for developing on-line multispectral imaging. PMID:26617027
Xu, Wei-Heng; Feng, Zhong-Ke; Su, Zhi-Fang; Xu, Hui; Jiao, You-Quan; Deng, Ou
2014-02-01
Tree crown projection area and crown volume are the important parameters for the estimation of biomass, tridimensional green biomass and other forestry science applications. Using conventional measurements of tree crown projection area and crown volume will produce a large area of errors in the view of practical situations referring to complicated tree crown structures or different morphological characteristics. However, it is difficult to measure and validate their accuracy through conventional measurement methods. In view of practical problems which include complicated tree crown structure, different morphological characteristics, so as to implement the objective that tree crown projection and crown volume can be extracted by computer program automatically. This paper proposes an automatic untouched measurement based on terrestrial three-dimensional laser scanner named FARO Photon120 using plane scattered data point convex hull algorithm and slice segmentation and accumulation algorithm to calculate the tree crown projection area. It is exploited on VC+6.0 and Matlab7.0. The experiments are exploited on 22 common tree species of Beijing, China. The results show that the correlation coefficient of the crown projection between Av calculated by new method and conventional method A4 reaches 0.964 (p<0.01); and the correlation coefficient of tree crown volume between V(VC) derived from new method and V(C) by the formula of a regular body is 0.960 (p<0.001). The results also show that the average of V(C) is smaller than that of V(VC) at the rate of 8.03%, and the average of A4 is larger than that of A(V) at the rate of 25.5%. Assumed Av and V(VC) as ture values, the deviations of the new method could be attributed to irregularity of the crowns' silhouettes. Different morphological characteristics of tree crown led to measurement error in forest simple plot survey. Based on the results, the paper proposes that: (1) the use of eight-point or sixteen-point projection with
Implementation of a new algorithm for Density Equalizing Map Projections (DEMP)
Close, E.R.; Merrill, D.W.; Holmes, H.H.
1995-07-01
The purpose of the PAREP (Populations at Risk to Environmental Pollution) Project at Lawrence Berkeley National Laboratory (LBNL), an ongoing Department of Energy (DOE) project since 1978, is to develop resources (data, computing techniques, and biostatistical methodology) applicable to DOE`s needs. Specifically, the PAREP project has developed techniques for statistically analyzing disease distributions in the vicinity of supposed environmental hazards. Such techniques can be applied to assess the health risks in populations residing near DOE installations, provided adequate small-area health data are available. The FY 1994 task descriptions for the PAREP project were determined in discussions at LBNL on 11/2/93. The FY94 PAREP Work Authorization specified three major tasks: a prototype small area study, a feasibility study for obtaining small-area data, and preservation of the PAREP data archive. The complete FY94 work plan, and the subtasks accomplished to date, were included in the Cumulative FY94 progress report.
Soares, Sófacles Figueredo Carreiro; Galvão, Roberto Kawakami Harrop; Araújo, Mário César Ugulino; da Silva, Edvan Cirino; Pereira, Claudete Fernandes; de Andrade, Stéfani Iury Evangelista; Leite, Flaviano Carvalho
2011-03-01
This work proposes a modification to the successive projections algorithm (SPA) aimed at selecting spectral variables for multiple linear regression (MLR) in the presence of unknown interferents not included in the calibration data set. The modified algorithm favours the selection of variables in which the effect of the interferent is less pronounced. The proposed procedure can be regarded as an adaptive modelling technique, because the spectral features of the samples to be analyzed are considered in the variable selection process. The advantages of this new approach are demonstrated in two analytical problems, namely (1) ultraviolet-visible spectrometric determination of tartrazine, allure red and sunset yellow in aqueous solutions under the interference of erythrosine, and (2) near-infrared spectrometric determination of ethanol in gasoline under the interference of toluene. In these case studies, the performance of conventional MLR-SPA models is substantially degraded by the presence of the interferent. This problem is circumvented by applying the proposed Adaptive MLR-SPA approach, which results in prediction errors smaller than those obtained by three other multivariate calibration techniques, namely stepwise regression, full-spectrum partial-least-squares (PLS) and PLS with variables selected by a genetic algorithm. An inspection of the variable selection results reveals that the Adaptive approach successfully avoids spectral regions in which the interference is more intense. PMID:21338751
NASA Astrophysics Data System (ADS)
Huang, Q.; Zeng, G. L.; You, J.; Gullberg, G. T.
2005-05-01
In this paper, Novikov's inversion formula of the attenuated two-dimensional (2D) Radon transform is applied to the reconstruction of attenuated fan-beam projections acquired with equal detector spacing and of attenuated cone-beam projections acquired with a flat planar detector and circular trajectory. The derivation of the fan-beam algorithm is obtained by transformation from parallel-beam coordinates to fan-beam coordinates. The cone-beam reconstruction algorithm is an extension of the fan-beam reconstruction algorithm using Feldkamp-Davis-Kress's (FDK) method. Computer simulations indicate that the algorithm is efficient and is accurate in reconstructing slices close to the central slice of the cone-beam orbit plane. When the attenuation map is set to zero the implementation is equivalent to the FDK method. Reconstructed images are also shown for noise corrupted projections.
NASA Astrophysics Data System (ADS)
Michel, D.; Jiménez, C.; Miralles, D. G.; Jung, M.; Hirschi, M.; Ershadi, A.; Martens, B.; McCabe, M. F.; Fisher, J. B.; Mu, Q.; Seneviratne, S. I.; Wood, E. F.; Fernández-Prieto, D.
2015-10-01
The WACMOS-ET project has compiled a forcing data set covering the period 2005-2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run 4 established ET algorithms: the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman-Monteith algorithm from the MODIS evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in-situ meteorological data from 24 FLUXNET towers was used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed across several time scales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement to the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2 = 0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2 = 0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs re-sampled to a common grid to facilitate global estimates) confirmed the original findings.
NASA Astrophysics Data System (ADS)
Michel, D.; Jiménez, C.; Miralles, D. G.; Jung, M.; Hirschi, M.; Ershadi, A.; Martens, B.; McCabe, M. F.; Fisher, J. B.; Mu, Q.; Seneviratne, S. I.; Wood, E. F.; Fernández-Prieto, D.
2016-02-01
The WAter Cycle Multi-mission Observation Strategy - EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005-2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman-Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared to tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2 = 0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2 = 0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. An extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global estimates) confirmed the original
Fox, Andrew; Williams, Mathew; Richardson, Andrew D.; Cameron, David; Gove, Jeffrey H.; Quaife, Tristan; Ricciuto, Daniel M; Reichstein, Markus; Tomelleri, Enrico; Trudinger, Cathy; Van Wijk, Mark T.
2009-10-01
We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) ofCO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration,were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving>80% success rate and mean NEE confidence intervals <110 gCm-2 year-1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence
Sidje, R B; Vo, H D
2015-11-01
The mathematical framework of the chemical master equation (CME) uses a Markov chain to model the biochemical reactions that are taking place within a biological cell. Computing the transient probability distribution of this Markov chain allows us to track the composition of molecules inside the cell over time, with important practical applications in a number of areas such as molecular biology or medicine. However the CME is typically difficult to solve, since the state space involved can be very large or even countably infinite. We present a novel way of using the stochastic simulation algorithm (SSA) to reduce the size of the finite state projection (FSP) method. Numerical experiments that demonstrate the effectiveness of the reduction are included. PMID:26319118
Han, Wenhua; Shen, Xiaohui; Xu, Jun; Wang, Ping; Tian, Guiyun; Wu, Zhengyang
2014-01-01
Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection. PMID:25192314
Han, Wenhua; Shen, Xiaohui; Xu, Jun; Wang, Ping; Tian, Guiyun; Wu, Zhengyang
2014-01-01
Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection. PMID:25192314
An iterative algorithm for soft tissue reconstruction from truncated flat panel projections
NASA Astrophysics Data System (ADS)
Langan, D.; Claus, B.; Edic, P.; Vaillant, R.; De Man, B.; Basu, S.; Iatrou, M.
2006-03-01
The capabilities of flat panel interventional x-ray systems continue to expand, enabling a broader array of medical applications to be performed in a minimally invasive manner. Although CT is providing pre-operative 3D information, there is a need for 3D imaging of low contrast soft tissue during interventions in a number of areas including neurology, cardiac electro-physiology, and oncology. Unlike CT systems, interventional angiographic x-ray systems provide real-time large field of view 2D imaging, patient access, and flexible gantry positioning enabling interventional procedures. However, relative to CT, these C-arm flat panel systems have additional technical challenges in 3D soft tissue imaging including slower rotation speed, gantry vibration, reduced lateral patient field of view (FOV), and increased scatter. The reduced patient FOV often results in significant data truncation. Reconstruction of truncated (incomplete) data is known an "interior problem", and it is mathematically impossible to obtain an exact reconstruction. Nevertheless, it is an important problem in 3D imaging on a C-arm to address the need to generate a 3D reconstruction representative of the object being imaged with minimal artifacts. In this work we investigate the application of an iterative Maximum Likelihood Transmission (MLTR) algorithm to truncated data. We also consider truncated data with limited views for cardiac imaging where the views are gated by the electrocardiogram(ECG) to combat motion artifacts.
NASA Astrophysics Data System (ADS)
Michel, Dominik; Miralles, Diego; Jimenez, Carlos; Ershadi, Ali; McCabe, Matthew F.; Hirschi, Martin; Seneviratne, Sonia I.; Jung, Martin; Wood, Eric F.; (Bob) Su, Z.; Timmermans, Joris; Chen, Xuelong; Fisher, Joshua B.; Mu, Quiaozen; Fernandez, Diego
2015-04-01
Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts have recently aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which cannot be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). The WACMOS-ET project (http://wacmoset.estellus.eu) started in the year 2012 and constitutes an ESA contribution to the GEWEX initiative LandFlux. It focuses on advancing the development of ET estimates at global, regional and tower scales. WACMOS-ET aims at developing a Reference Input Data Set exploiting European Earth Observations assets and deriving ET estimates produced by a set of four ET algorithms covering the period 2005-2007. The algorithms used are the SEBS (Su et al., 2002), Penman-Monteith from MODIS (Mu et al., 2011), the Priestley and Taylor JPL model (Fisher et al., 2008) and GLEAM (Miralles et al., 2011). The algorithms are run with Fluxnet tower observations, reanalysis data (ERA-Interim), and satellite forcings. They are cross-compared and validated against in-situ data. In this presentation the performance of the different ET algorithms with respect to different temporal resolutions, hydrological regimes, land cover types (including grassland, cropland, shrubland, vegetation mosaic, savanna
Tests of a simple data merging algorithm for the GONG project
NASA Technical Reports Server (NTRS)
Williams, W. E.; Hill, F.
1992-01-01
The GONG (Global Oscillation Network Group) project proposes to reduce the impact of diurnal variations on helioseismic measurements by making long-term observations of solar images from six sites placed around the globe. The sun will be observed nearly constantly for three years, resulting in the acquisition of l+ terabyte of image data. To use the solar network to maximum advantage, the images from the sites must be combined into a single time series to determine mode frequencies, amplitudes, and line widths. Initial versions of combined, i.e., merged, time series were made using a simple weighted average of data from different sites taken simultaneously. In order to accurately assess the impact of the data merge on the helioseismic measurements, a set of artificial solar disk images was made using a standard solar model and containing a well known set of oscillation modes and frequencies. This undegraded data set and data products computed from it were used to judge the relative merits of various data merging schemes. The artificial solar disk images were subjected to various instrumental and atmospheric degradations, dependent on site and time, in order to create a set of images simulating those likely to be taken at the site. The degraded artificial solar disk images for the six observing sites were combined in various ways to form merged time series of images and mode coefficients. Various forms of a weighted average were used, including an equally-weighted average, an average with weights dependent upon air mass and averages with weights dependent on various quality assurance parameters. Both the undegraded solar disk image time series and several time series made up of various combinations of the degraded solar disk images from the six sites were subjected to standard helioseismic measurement processing. This processing consisted of coordinate remapping, detrending, spherical harmonic transformation, computation of power series for the oscillation mode
Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Kuncic, Zdenka; Keall, Paul J.
2014-01-01
Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR
Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka
2014-04-15
Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
NASA Astrophysics Data System (ADS)
Yigit, Enes; Demirci, Sevket; Özdemir, Caner; Tekbaş, Mustafa
2013-01-01
Two popular synthetic aperture radar (SAR) reconstruction algorithms, namely the back-projection (BP) and the frequency wavenumber (ω-k) algorithms, were tested and compared against each other, especially for their use in ground-based (GB) SAR applications directed to foreign object debris removal. For this purpose, an experimental setup in a semi-anechoic chamber room was accomplished to obtain near-field SAR images of objects on the ground. Then, the 90 to 95 GHz scattering data were acquired by using a stepped frequency continuous-wave radar operation. The performances of the setup and the imaging algorithms were then assessed by exploiting various metrics including point spread function, signal-to-clutter ratio, integrated side-lobe ratio, and computational complexity. Results demonstrate that although both algorithms produce almost accurate images of targets, the BP algorithm is shown to be superior to the ω-k algorithm due to its some inherent advantages specifically suited for short-range GB-SAR applications.
NASA Astrophysics Data System (ADS)
Kuttig, Jan; Steiding, Christian; Hupfer, Martin; Karolczak, Marek; Kolditz, Daniel
2015-09-01
In this study we compared various defect pixel correction methods for reducing artifact appearance within projection images used for computed tomography (CT) reconstructions. Defect pixel correction algorithms were examined with respect to their artifact behaviour within planar projection images as well as in volumetric CT reconstructions. We investigated four algorithms: nearest neighbour, linear and adaptive linear interpolation, and a frequency-selective spectral-domain approach. To characterise the quality of each algorithm in planar image data, we inserted line defects of varying widths and orientations into images. The structure preservation of each algorithm was analysed by corrupting and correcting the image of a slit phantom pattern and by evaluating its line spread function (LSF). The noise preservation was assessed by interpolating corrupted flat images and estimating the noise power spectrum (NPS) of the interpolated region. For the volumetric investigations, we examined the structure and noise preservation within a structured aluminium foam, a mid-contrast cone-beam phantom and a homogeneous Polyurethane (PUR) cylinder. The frequency-selective algorithm showed the best structure and noise preservation for planar data of the correction methods tested. For volumetric data it still showed the best noise preservation, whereas the structure preservation was outperformed by the linear interpolation. The frequency-selective spectral-domain approach in the correction of line defects is recommended for planar image data, but its abilities within high-contrast volumes are restricted. In that case, the application of a simple linear interpolation might be the better choice to correct line defects within projection images used for CT.
NASA Astrophysics Data System (ADS)
Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.
2008-04-01
The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set
NASA Astrophysics Data System (ADS)
Pawlowski, Jason M.; Ding, George X.
2014-04-01
A new model-based dose calculation algorithm is presented for kilovoltage x-rays and is tested for the cases of calculating the radiation dose from kilovoltage cone-beam CT (kV-CBCT) and 2D planar projected radiographs. This algorithm calculates the radiation dose to water-like media as the sum of primary and scattered dose components. The scatter dose is calculated by convolution of a newly introduced, empirically parameterized scatter dose kernel with the primary photon fluence. Several approximations are introduced to increase the scatter dose calculation efficiency: (1) the photon energy spectrum is approximated as monoenergetic; (2) density inhomogeneities are accounted for by implementing a global distance scaling factor in the scatter kernel; (3) kernel tilting is ignored. These approximations allow for efficient calculation of the scatter dose convolution with the fast Fourier transform. Monte Carlo simulations were used to obtain the model parameters. The accuracy of using this model-based algorithm was validated by comparing with the Monte Carlo method for calculating dose distributions for real patients resulting from radiotherapy image guidance procedures including volumetric kV-CBCT scans and 2D planar projected radiographs. For all patients studied, mean dose-to-water errors for kV-CBCT are within 0.3% with a maximum standard deviation error of 4.1%. Using a medium-dependent correction method to account for the effects of photoabsorption in bone on the dose distribution, mean dose-to-medium errors for kV-CBCT are within 3.6% for bone and 2.4% for soft tissues. This algorithm offers acceptable accuracy and has the potential to extend the applicability of model-based dose calculation algorithms from megavoltage to kilovoltage photon beams.
ERIC Educational Resources Information Center
Hughes, Carroll W.; Emslie, Graham J.; Crismon, M. Lynn; Posner, Kelly; Birmaher, Boris; Ryan, Neal; Jensen, Peter; Curry, John; Vitiello, Benedetto; Lopez, Molly; Shon, Steve P.; Pliszka, Steven R.; Trivedi, Madhukar H.
2007-01-01
Objective: To revise and update consensus guidelines for medication treatment algorithms for childhood major depressive disorder based on new scientific evidence and expert clinical consensus when evidence is lacking. Method: A consensus conference was held January 13-14, 2005, that included academic clinicians and researchers, practicing…
NASA Astrophysics Data System (ADS)
Thériault Lauzier, Pascal; Tang, Jie; Chen, Guang-Hong
2012-05-01
C-arm cone-beam CT could replace preoperative multi-detector CT scans in the cardiac interventional setting. However, cardiac gating results in view angle undersampling and the small size of the detector results in projection data truncation. These problems are incompatible with conventional tomographic reconstruction algorithms. In this paper, the prior image constrained compressed sensing (PICCS) reconstruction method was adapted to solve these issues. The performance of the proposed method was compared to that of FDK, FDK with extrapolated projection data (E-FDK), and total variation-based compressed sensing. A canine projection dataset acquired using a clinical C-arm imaging system supplied realistic cardiac motion and anatomy for this evaluation. Three different levels of truncation were simulated. The relative root mean squared error and the universal image quality index were used to quantify the reconstruction accuracy. Three main conclusions were reached. (1) The adapted version of the PICCS algorithm offered the highest image quality and reconstruction accuracy. (2) No meaningful variation in performance was observed when the amount of truncation was changed. (3) This study showed evidence that accurate interior tomography with an undersampled acquisition is possible for realistic objects if a prior image with minimal artifacts is available.
Hybrid-optimization algorithm for the management of a conjunctive-use project and well field design
Chiu, Y.-C.; Nishikawa, T.; Martin, P.
2012-01-01
Hi-Desert Water District (HDWD), the primary water-management agency in the Warren Groundwater Basin, California, plans to construct a waste water treatment plant to reduce future septic-tank effluent from reaching the groundwater system. The treated waste water will be reclaimed by recharging the groundwater basin via recharge ponds as part of a larger conjunctive-use strategy. HDWD wishes to identify the least-cost conjunctive-use strategies for managing imported surface water, reclaimed water, and local groundwater. As formulated, the mixed-integer nonlinear programming (MINLP) groundwater-management problem seeks to minimize water-delivery costs subject to constraints including potential locations of the new pumping wells, California State regulations, groundwater-level constraints, water-supply demand, available imported water, and pump/recharge capacities. In this study, a hybrid-optimization algorithm, which couples a genetic algorithm and successive-linear programming, is developed to solve the MINLP problem. The algorithm was tested by comparing results to the enumerative solution for a simplified version of the HDWD groundwater-management problem. The results indicate that the hybrid-optimization algorithm can identify the global optimum. The hybrid-optimization algorithm is then applied to solve a complex groundwater-management problem. Sensitivity analyses were also performed to assess the impact of varying the new recharge pond orientation, varying the mixing ratio of reclaimed water and pumped water, and varying the amount of imported water available. The developed conjunctive management model can provide HDWD water managers with information that will improve their ability to manage their surface water, reclaimed water, and groundwater resources. ?? 2011, National Ground Water Association.
Hybrid-optimization algorithm for the management of a conjunctive-use project and well field design
Chiu, Yung-Chia; Nishikawa, Tracy; Martin, Peter
2012-01-01
Hi-Desert Water District (HDWD), the primary water-management agency in the Warren Groundwater Basin, California, plans to construct a waste water treatment plant to reduce future septic-tank effluent from reaching the groundwater system. The treated waste water will be reclaimed by recharging the groundwater basin via recharge ponds as part of a larger conjunctive-use strategy. HDWD wishes to identify the least-cost conjunctiveuse strategies for managing imported surface water, reclaimed water, and local groundwater. As formulated, the mixed-integer nonlinear programming (MINLP) groundwater-management problem seeks to minimize water delivery costs subject to constraints including potential locations of the new pumping wells, California State regulations, groundwater-level constraints, water-supply demand, available imported water, and pump/recharge capacities. In this study, a hybrid-optimization algorithm, which couples a genetic algorithm and successive-linear programming, is developed to solve the MINLP problem. The algorithm was tested by comparing results to the enumerative solution for a simplified version of the HDWD groundwater-management problem. The results indicate that the hybrid-optimization algorithm can identify the global optimum. The hybrid-optimization algorithm is then applied to solve a complex groundwater-management problem. Sensitivity analyses were also performed to assess the impact of varying the new recharge pond orientation, varying the mixing ratio of reclaimed water and pumped water, and varying the amount of imported water available. The developed conjunctive management model can provide HDWD water managers with information that will improve their ability to manage their surface water, reclaimed water, and groundwater resources.
NASA Astrophysics Data System (ADS)
Sakaguchi, Toshimasa; Fujigaki, Motoharu; Murata, Yorinobu
2015-03-01
Accurate and wide-range shape measurement method is required in industrial field. The same technique is possible to be used for a shape measurement of a human body for the garment industry. Compact 3D shape measurement equipment is also required for embedding in the inspection system. A shape measurement by a phase shifting method can measure the shape with high spatial resolution because the coordinates can be obtained pixel by pixel. A key-device to develop compact equipment is a grating projector. Authors developed a linear LED projector and proposed a light source stepping method (LSSM) using the linear LED projector. The shape measurement euipment can be produced with low-cost and compact without any phase-shifting mechanical systems by using this method. Also it enables us to measure 3D shape in very short time by switching the light sources quickly. A phase unwrapping method is necessary to widen the measurement range with constant accuracy for phase shifting method. A general phase unwrapping method with difference grating pitches is often used. It is one of a simple phase unwrapping method. It is, however, difficult to apply the conventional phase unwrapping algorithm to the LSSM. Authors, therefore, developed an expansion unwrapping algorithm for the LSSM. In this paper, an expansion algorithm of measurement range suited for 3D shape measurement using two pitches of projected grating with the LSSM was evaluated.
NASA Technical Reports Server (NTRS)
Wehrbein, W. M.; Leovy, C. B.
1981-01-01
A Curtis matrix is used to compute cooling by the 15 micron and 10 micron bands of carbon dioxide. Escape of radiation to space and exchange the lower boundary are used for the 9.6 micron band of ozone. Voigt line shape, vibrational relaxation, line overlap, and the temperature dependence of line strength distributions and transmission functions are incorporated into the Curtis matrices. The distributions of the atmospheric constituents included in the algorithm, and the method used to compute the Curtis matrices are discussed as well as cooling or heating by the 9.6 micron band of ozone. The FORTRAN programs and subroutines that were developed are described and listed.
Mobashsher, Ahmed Toaha; Mahmoud, A; Abbosh, A M
2016-01-01
Intracranial hemorrhage is a medical emergency that requires rapid detection and medication to restrict any brain damage to minimal. Here, an effective wideband microwave head imaging system for on-the-spot detection of intracranial hemorrhage is presented. The operation of the system relies on the dielectric contrast between healthy brain tissues and a hemorrhage that causes a strong microwave scattering. The system uses a compact sensing antenna, which has an ultra-wideband operation with directional radiation, and a portable, compact microwave transceiver for signal transmission and data acquisition. The collected data is processed to create a clear image of the brain using an improved back projection algorithm, which is based on a novel effective head permittivity model. The system is verified in realistic simulation and experimental environments using anatomically and electrically realistic human head phantoms. Quantitative and qualitative comparisons between the images from the proposed and existing algorithms demonstrate significant improvements in detection and localization accuracy. The radiation and thermal safety of the system are examined and verified. Initial human tests are conducted on healthy subjects with different head sizes. The reconstructed images are statistically analyzed and absence of false positive results indicate the efficacy of the proposed system in future preclinical trials. PMID:26842761
NASA Astrophysics Data System (ADS)
Mobashsher, Ahmed Toaha; Mahmoud, A.; Abbosh, A. M.
2016-02-01
Intracranial hemorrhage is a medical emergency that requires rapid detection and medication to restrict any brain damage to minimal. Here, an effective wideband microwave head imaging system for on-the-spot detection of intracranial hemorrhage is presented. The operation of the system relies on the dielectric contrast between healthy brain tissues and a hemorrhage that causes a strong microwave scattering. The system uses a compact sensing antenna, which has an ultra-wideband operation with directional radiation, and a portable, compact microwave transceiver for signal transmission and data acquisition. The collected data is processed to create a clear image of the brain using an improved back projection algorithm, which is based on a novel effective head permittivity model. The system is verified in realistic simulation and experimental environments using anatomically and electrically realistic human head phantoms. Quantitative and qualitative comparisons between the images from the proposed and existing algorithms demonstrate significant improvements in detection and localization accuracy. The radiation and thermal safety of the system are examined and verified. Initial human tests are conducted on healthy subjects with different head sizes. The reconstructed images are statistically analyzed and absence of false positive results indicate the efficacy of the proposed system in future preclinical trials.
Goodarzi, Mohammad; Saeys, Wouter; de Araujo, Mario Cesar Ugulino; Galvão, Roberto Kawakami Harrop; Vander Heyden, Yvan
2014-01-23
Chalcones are naturally occurring aromatic ketones, which consist of an α-, β-unsaturated carbonyl system joining two aryl rings. These compounds are reported to exhibit several pharmacological activities, including antiparasitic, antibacterial, antifungal, anticancer, immunomodulatory, nitric oxide inhibition and anti-inflammatory effects. In the present work, a Quantitative Structure-Activity Relationship (QSAR) study is carried out to classify chalcone derivatives with respect to their antileishmanial activity (active/inactive) on the basis of molecular descriptors. For this purpose, two techniques to select descriptors are employed, the Successive Projections Algorithm (SPA) and the Genetic Algorithm (GA). The selected descriptors are initially employed to build Linear Discriminant Analysis (LDA) models. An additional investigation is then carried out to determine whether the results can be improved by using a non-parametric classification technique (One Nearest Neighbour, 1NN). In a case study involving 100 chalcone derivatives, the 1NN models were found to provide better rates of correct classification than LDA, both in the training and test sets. The best result was achieved by a SPA-1NN model with six molecular descriptors, which provided correct classification rates of 97% and 84% for the training and test sets, respectively. PMID:24090733
Mobashsher, Ahmed Toaha; Mahmoud, A.; Abbosh, A. M.
2016-01-01
Intracranial hemorrhage is a medical emergency that requires rapid detection and medication to restrict any brain damage to minimal. Here, an effective wideband microwave head imaging system for on-the-spot detection of intracranial hemorrhage is presented. The operation of the system relies on the dielectric contrast between healthy brain tissues and a hemorrhage that causes a strong microwave scattering. The system uses a compact sensing antenna, which has an ultra-wideband operation with directional radiation, and a portable, compact microwave transceiver for signal transmission and data acquisition. The collected data is processed to create a clear image of the brain using an improved back projection algorithm, which is based on a novel effective head permittivity model. The system is verified in realistic simulation and experimental environments using anatomically and electrically realistic human head phantoms. Quantitative and qualitative comparisons between the images from the proposed and existing algorithms demonstrate significant improvements in detection and localization accuracy. The radiation and thermal safety of the system are examined and verified. Initial human tests are conducted on healthy subjects with different head sizes. The reconstructed images are statistically analyzed and absence of false positive results indicate the efficacy of the proposed system in future preclinical trials. PMID:26842761
NASA Astrophysics Data System (ADS)
Tavakoli, Reza; Srinivasan, Sanjay; Wheeler, Mary
2015-04-01
The application of ensemble-based algorithms for history matching reservoir models has been steadily increasing over the past decade. However, the majority of implementations in the reservoir engineering have dealt only with production history matching. During geologic sequestration, the injection of large quantities of CO2 into the subsurface may alter the stress/strain field which in turn can lead to surface uplift or subsidence. Therefore, it is essential to couple multiphase flow and geomechanical response in order to predict and quantify the uncertainty of CO2 plume movement for long-term, large-scale CO2 sequestration projects. In this work, we simulate and estimate the properties of a reservoir that is being used to store CO2 as part of the In Salah Capture and Storage project in Algeria. The CO2 is separated from produced natural gas and is re-injected into downdip aquifer portion of the field from three long horizontal wells. The field observation data includes ground surface deformations (uplift) measured using satellite-based radar (InSAR), injection well locations and CO2 injection rate histories provided by the operators. We implement variations of ensemble Kalman filter and ensemble smoother algorithms for assimilating both injection rate data as well as geomechanical observations (surface uplift) into reservoir model. The preliminary estimation results of horizontal permeability and material properties such as Young Modulus and Poisson Ratio are consistent with available measurements and previous studies in this field. Moreover, the existence of high-permeability channels (fractures) within the reservoir; especially in the regions around the injection wells are confirmed. This estimation results can be used to accurately and efficiently predict and quantify the uncertainty in the movement of CO2 plume.
NASA Astrophysics Data System (ADS)
Barnard, L.; Scott, C. J.; Owens, M.; Lockwood, M.; Crothers, S. R.; Davies, J. A.; Harrison, R. A.
2015-10-01
Observations from the Heliospheric Imager (HI) instruments aboard the twin STEREO spacecraft have enabled the compilation of several catalogues of coronal mass ejections (CMEs), each characterizing the propagation of CMEs through the inner heliosphere. Three such catalogues are the Rutherford Appleton Laboratory (RAL)-HI event list, the Solar Stormwatch CME catalogue, and, presented here, the J-tracker catalogue. Each catalogue uses a different method to characterize the location of CME fronts in the HI images: manual identification by an expert, the statistical reduction of the manual identifications of many citizen scientists, and an automated algorithm. We provide a quantitative comparison of the differences between these catalogues and techniques, using 51 CMEs common to each catalogue. The time-elongation profiles of these CME fronts are compared, as are the estimates of the CME kinematics derived from application of three widely used single-spacecraft-fitting techniques. The J-tracker and RAL-HI profiles are most similar, while the Solar Stormwatch profiles display a small systematic offset. Evidence is presented that these differences arise because the RAL-HI and J-tracker profiles follow the sunward edge of CME density enhancements, while Solar Stormwatch profiles track closer to the antisunward (leading) edge. We demonstrate that the method used to produce the time-elongation profile typically introduces more variability into the kinematic estimates than differences between the various single-spacecraft-fitting techniques. This has implications for the repeatability and robustness of these types of analyses, arguably especially so in the context of space weather forecasting, where it could make the results strongly dependent on the methods used by the forecaster.
Michel, D.; Jimenez, C.; Miralles, D. G.; Jung, M.; Hirschi, M.; Ershadi, A.; Martens, B.; McCabe, M. F.; Fisher, J. B.; Mu, Q.; et al
2016-02-23
The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared tomore » tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements (R2 = 0.67), the agreement of the satellite-based ET estimates is only marginally lower (R2 = 0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. In conclusion, an extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global
Calzado, A; Geleijns, J; Joemai, R M S; Veldkamp, W J H
2014-01-01
Objective: To compare low-contrast detectability (LCDet) performance between a model [non–pre-whitening matched filter with an eye filter (NPWE)] and human observers in CT images reconstructed with filtered back projection (FBP) and iterative [adaptive iterative dose reduction three-dimensional (AIDR 3D; Toshiba Medical Systems, Zoetermeer, Netherlands)] algorithms. Methods: Images of the Catphan® phantom (Phantom Laboratories, New York, NY) were acquired with Aquilion ONE™ 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan) at five tube current levels (20–500 mA range) and reconstructed with FBP and AIDR 3D. Samples containing either low-contrast objects (diameters, 2–15 mm) or background were extracted and analysed by the NPWE model and four human observers in a two-alternative forced choice detection task study. Proportion correct (PC) values were obtained for each analysed object and used to compare human and model observer performances. An efficiency factor (η) was calculated to normalize NPWE to human results. Results: Human and NPWE model PC values (normalized by the efficiency, η = 0.44) were highly correlated for the whole dose range. The Pearson's product-moment correlation coefficients (95% confidence interval) between human and NPWE were 0.984 (0.972–0.991) for AIDR 3D and 0.984 (0.971–0.991) for FBP, respectively. Bland–Altman plots based on PC results showed excellent agreement between human and NPWE [mean absolute difference 0.5 ± 0.4%; range of differences (−4.7%, 5.6%)]. Conclusion: The NPWE model observer can predict human performance in LCDet tasks in phantom CT images reconstructed with FBP and AIDR 3D algorithms at different dose levels. Advances in knowledge: Quantitative assessment of LCDet in CT can accurately be performed using software based on a model observer. PMID:24837275
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.
NASA Astrophysics Data System (ADS)
Reale, M.; Lionello, P.
2012-04-01
This study considers the Mediterranean storm track and its link with severe precipitation events in the Mediterranean region as reproduced by different tracking algorithms. Data for tracking cyclones are provided by the IMILAST project ( http://www.proclim.ch/imilast/index.html ). Data for the analysis of precipitation are provided by ECA&D dataset (http://eca.knmi.nl/ hosted at the Netherland Royal meteorological institute). Most of methods identify the "Mediterranean storm track" characterized in all the cases by a prevailing southeastward direction, extending through Italy, down to the Albanian and Greek coasts. They also agree on locating the main cyclogenetic areas in the gulf of Genoa, North-West Africa and Iberia peninsula (in the Western Mediterranean), Cyprus and Black Sea areas (in the Eastern Mediterranean.) However, differences in patterns and in intensity of track features are large and related mainly to: i) how efficiently the schemes identify heat lows generated in summer and spring over Iberian peninsula , North-East Africa and Black Sea; ii) how the schemes locate the cyclogenesis occurring over Northern Italy and Cyprus areas (mainly in winter). A case of severe precipitations over Larnaca (Cyprus) has been analyzed in detail . Most of methods agree to identify a minimum close to Larnaca at the peak of the precipitation event, but differ in the reconstruction of the initial and final portions of the cyclone tracks. The differences observed in the tracks affect important descriptors of the cyclone life cycle, as it is shown by the different estimates of the speed at which cyclones move and their initial deepening rate.
NASA Technical Reports Server (NTRS)
Piepmeier, Jeffrey; Mohammed, Priscilla; De Amici, Giovanni; Kim, Edward; Peng, Jinzheng; Ruf, Christopher; Hanna, Maher; Yueh, Simon; Entekhabi, Dara
2016-01-01
The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm.
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 Astrophysics Data System (ADS)
Abrams, Daniel S.
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 (commonly found in ab initio physics and chemistry problems) for which all known classical algorithms require exponential time. Fast algorithms for simulating many body Fermi systems are also provided in both first and second quantized descriptions. An efficient quantum algorithm for anti-symmetrization is given as well as a detailed discussion of a simulation of the Hubbard model. In addition, quantum algorithms that calculate numerical integrals and various characteristics of stochastic processes are described. Two techniques are given, both of which obtain an exponential speed increase in comparison to the fastest known classical deterministic algorithms and a quadratic speed increase in comparison to classical Monte Carlo (probabilistic) methods. I derive a simpler and slightly faster version of Grover's mean algorithm, show how to apply quantum counting to the problem, develop some variations of these algorithms, and show how both (apparently distinct) approaches can be understood from the same unified framework. Finally, the relationship between physics and computation is explored in some more depth, and it is shown that computational complexity theory depends very sensitively on physical laws. In particular, it is shown that nonlinear quantum mechanics allows for the polynomial time solution of NP-complete and #P oracle problems. Using the Weinberg model as a simple example, the explicit construction of the necessary gates is derived from the underlying physics. Nonlinear quantum algorithms are also presented using Polchinski type nonlinearities which do not allow for superluminal communication. (Copies available exclusively from MIT Libraries, Rm. 14- 0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
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.
NASA Astrophysics Data System (ADS)
Shahriari, Mohammadreza
2016-03-01
The time-cost tradeoff problem is one of the most important and applicable problems in project scheduling area. There are many factors that force the mangers to crash the time. This factor could be early utilization, early commissioning and operation, improving the project cash flow, avoiding unfavorable weather conditions, compensating the delays, and so on. Since there is a need to allocate extra resources to short the finishing time of project and the project managers are intended to spend the lowest possible amount of money and achieve the maximum crashing time, as a result, both direct and indirect costs will be influenced in the project, and here, we are facing into the time value of money. It means that when we crash the starting activities in a project, the extra investment will be tied in until the end date of the project; however, when we crash the final activities, the extra investment will be tied in for a much shorter period. This study is presenting a two-objective mathematical model for balancing compressing the project time with activities delay to prepare a suitable tool for decision makers caught in available facilities and due to the time of projects. Also drawing the scheduling problem to real world conditions by considering nonlinear objective function and the time value of money are considered. The presented problem was solved using NSGA-II, and the effect of time compressing reports on the non-dominant set.
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.
Optical Sensor Based Corn Algorithm Evaluation
Technology Transfer Automated Retrieval System (TEKTRAN)
Optical sensor based algorithms for corn fertilization have developed by researchers in several states. The goal of this international research project was to evaluate these different algorithms and determine their robustness over a large geographic area. Concurrently the goal of this project was to...
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.
Anglada-Escude, Guillem; Butler, R. Paul
2012-06-01
Doppler spectroscopy has uncovered or confirmed all the known planets orbiting nearby stars. Two main techniques are used to obtain precision Doppler measurements at optical wavelengths. The first approach is the gas cell method, which consists of least-squares matching of the spectrum of iodine imprinted on the spectrum of the star. The second method relies on the construction of a stabilized spectrograph externally calibrated in wavelength. The most precise stabilized spectrometer in operation is the High Accuracy Radial velocity Planet Searcher (HARPS), operated by the European Southern Observatory in La Silla Observatory, Chile. The Doppler measurements obtained with HARPS are typically obtained using the cross-correlation function (CCF) technique. This technique consists of multiplying the stellar spectrum by a weighted binary mask and finding the minimum of the product as a function of the Doppler shift. It is known that CCF is suboptimal in exploiting the Doppler information in the stellar spectrum. Here we describe an algorithm to obtain precision radial velocity measurements using least-squares matching of each observed spectrum to a high signal-to-noise ratio template derived from the same observations. This algorithm is implemented in our software HARPS-TERRA (Template-Enhanced Radial velocity Re-analysis Application). New radial velocity measurements on a representative sample of stars observed by HARPS are used to illustrate the benefits of the proposed method. We show that, compared with CCF, template matching provides a significant improvement in accuracy, especially when applied to M dwarfs.
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.
Evaluating super resolution algorithms
NASA Astrophysics Data System (ADS)
Kim, Youn Jin; Park, Jong Hyun; Shin, Gun Shik; Lee, Hyun-Seung; Kim, Dong-Hyun; Park, Se Hyeok; Kim, Jaehyun
2011-01-01
This study intends to establish a sound testing and evaluation methodology based upon the human visual characteristics for appreciating the image restoration accuracy; in addition to comparing the subjective results with predictions by some objective evaluation methods. In total, six different super resolution (SR) algorithms - such as iterative back-projection (IBP), robust SR, maximum a posteriori (MAP), projections onto convex sets (POCS), a non-uniform interpolation, and frequency domain approach - were selected. The performance comparison between the SR algorithms in terms of their restoration accuracy was carried out through both subjectively and objectively. The former methodology relies upon the paired comparison method that involves the simultaneous scaling of two stimuli with respect to image restoration accuracy. For the latter, both conventional image quality metrics and color difference methods are implemented. Consequently, POCS and a non-uniform interpolation outperformed the others for an ideal situation, while restoration based methods appear more accurate to the HR image in a real world case where any prior information about the blur kernel is remained unknown. However, the noise-added-image could not be restored successfully by any of those methods. The latest International Commission on Illumination (CIE) standard color difference equation CIEDE2000 was found to predict the subjective results accurately and outperformed conventional methods for evaluating the restoration accuracy of those SR algorithms.
Fast algorithms for transport models
Manteuffel, T.A.
1992-12-01
The objective of this project is the development of numerical solution techniques for deterministic models of the transport of neutral and charged particles and the demonstration of their effectiveness in both a production environment and on advanced architecture computers. The primary focus is on various versions of the linear Boltzman equation. These equations are fundamental in many important applications. This project is an attempt to integrate the development of numerical algorithms with the process of developing production software. A major thrust of this reject will be the implementation of these algorithms on advanced architecture machines that reside at the Advanced Computing Laboratory (ACL) at Los Alamos National Laboratories (LANL).
NASA Astrophysics Data System (ADS)
di Paola, Francesco; Casella, Daniele; Dietrich, Stefano; Formenton, Marco; Mugnai, Alberto; Sanò, Paolo
2010-05-01
Within the EU FLASH project, instantaneous precipitation maps are generated also from MW images taken by cross-track scanners on operational satellites in sun-synchronous orbits, for each satellite pass. Before undertaking retrieval, the AMSU-A data are regridded at AMSU-B/MHS resolution using bilinear interpolation. The retrieval algorithm is based on a neural network trained by a pre-computed cloud-radiation database built from meteorological situations simulated by a cloud resolving model followed by a radiative transfer model. To fill the large temporal gaps between consecutive MW snapshots several combined microwave-infrared (MW-IR) algorithms have been proposed in the past. Their aim is the generation of High Resolution Precipitation Products (HRPP) using the IR measurements from geostationary satellites to enhance the spatial resolution and the temporal sampling of the intermittent rain fields estimated from passive MW sensors aboard low earth orbiting (LEO) satellites. The Precipitation Evolving Technique (PET) produces a quasi real time HRPP. PET drives the evolution (shape and intensity) of the last available MW-estimated rain field using iterative and statistical multi-scale pattern recognition procedure computed over two consecutives IR images. This allows effectively recognizing homogeneous cloud structures and their movements in the system by combining together the displacements occurring at each spatial scale. Since such an approach is spatially limited by the extension of the last MW swath coverage and it does not solve extinction and/or generation of precipitating cloud structures, so ad hoc calibration procedure completes the algorithm. In this paper, we show the results of the application of our latest version of PET to the analysis of some European severe storms.
ERIC Educational Resources Information Center
Grayson, Katherine
2007-01-01
In November 2006, the editors of "Campus Technology" launched their first-ever High-Resolution Projection Study, to find out if the latest in projector technology could really make a significant difference in teaching, learning, and educational innovation on US campuses. The author and her colleagues asked campus educators, technologists, and…
NASA Technical Reports Server (NTRS)
Gregory, Kyle J.; Hill, Joanne E. (Editor); Black, J. Kevin; Baumgartner, Wayne H.; Jahoda, Keith
2016-01-01
A fundamental challenge in a spaceborne application of a gas-based Time Projection Chamber (TPC) for observation of X-ray polarization is handling the large amount of data collected. The TPC polarimeter described uses the APV-25 Application Specific Integrated Circuit (ASIC) to readout a strip detector. Two dimensional photoelectron track images are created with a time projection technique and used to determine the polarization of the incident X-rays. The detector produces a 128x30 pixel image per photon interaction with each pixel registering 12 bits of collected charge. This creates challenging requirements for data storage and downlink bandwidth with only a modest incidence of photons and can have a significant impact on the overall mission cost. An approach is described for locating and isolating the photoelectron track within the detector image, yielding a much smaller data product, typically between 8x8 pixels and 20x20 pixels. This approach is implemented using a Microsemi RT-ProASIC3-3000 Field-Programmable Gate Array (FPGA), clocked at 20 MHz and utilizing 10.7k logic gates (14% of FPGA), 20 Block RAMs (17% of FPGA), and no external RAM. Results will be presented, demonstrating successful photoelectron track cluster detection with minimal impact to detector dead-time.
NASA Astrophysics Data System (ADS)
Gregory, Kyle J.; Hill, Joanne E.; Black, J. Kevin; Baumgartner, Wayne H.; Jahoda, Keith
2016-05-01
A fundamental challenge in a spaceborne application of a gas-based Time Projection Chamber (TPC) for observation of X-ray polarization is handling the large amount of data collected. The TPC polarimeter described uses the APV-25 Application Specific Integrated Circuit (ASIC) to readout a strip detector. Two dimensional photo- electron track images are created with a time projection technique and used to determine the polarization of the incident X-rays. The detector produces a 128x30 pixel image per photon interaction with each pixel registering 12 bits of collected charge. This creates challenging requirements for data storage and downlink bandwidth with only a modest incidence of photons and can have a significant impact on the overall mission cost. An approach is described for locating and isolating the photoelectron track within the detector image, yielding a much smaller data product, typically between 8x8 pixels and 20x20 pixels. This approach is implemented using a Microsemi RT-ProASIC3-3000 Field-Programmable Gate Array (FPGA), clocked at 20 MHz and utilizing 10.7k logic gates (14% of FPGA), 20 Block RAMs (17% of FPGA), and no external RAM. Results will be presented, demonstrating successful photoelectron track cluster detection with minimal impact to detector dead-time.
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.
NASA Astrophysics Data System (ADS)
Tamrat, Yalew; Hatleberg, Clancy
2007-04-01
In this paper, we present a Multi-Frequency Space-Time Orthogonal (MF-STOP) adaptive filtering approach for detection and discrimination of targets based on a two stage orthogonal projection whereby target parameters can be extracted in the presence of heavy clutter and noise. The proposed technique detects targets within heavy clutter tracked by a radar system. After targets are detected, motion information is extracted that can be used to discriminate threats such as reentry vehicles from other targets. Target detection is generated in stage one by a combination of Windowed Short Time Fast Fourier Transform (WSTFFT) processing and Principal Component Analysis (PCA). Target discrimination is done in a second stage via Partial Least Squares (PLS) using a training filter constructed from the stage one detection. The target is discriminated explicitly by metric criteria such as size or precession. These discriminate features do not have to be known a priori.
Kuo, Yu; Lin, Yi-Yang; Lee, Rheun-Chuan; Lin, Chung-Jung; Chiou, Yi-You; Guo, Wan-Yuo
2016-01-01
Abstract The purpose of this study was to compare the image noise-reducing abilities of iterative model reconstruction (IMR) with those of traditional filtered back projection (FBP) and statistical iterative reconstruction (IR) in abdominal computed tomography (CT) images This institutional review board-approved retrospective study enrolled 103 patients; informed consent was waived. Urinary bladder (n = 83) and renal cysts (n = 44) were used as targets for evaluating imaging quality. Raw data were retrospectively reconstructed using FBP, statistical IR, and IMR. Objective image noise and signal-to-noise ratio (SNR) were calculated and analyzed using one-way analysis of variance. Subjective image quality was evaluated and analyzed using Wilcoxon signed-rank test with Bonferroni correction. Objective analysis revealed a reduction in image noise for statistical IR compared with that for FBP, with no significant differences in SNR. In the urinary bladder group, IMR achieved up to 53.7% noise reduction, demonstrating a superior performance to that of statistical IR. IMR also yielded a significantly superior SNR to that of statistical IR. Similar results were obtained in the cyst group. Subjective analysis revealed reduced image noise for IMR, without inferior margin delineation or diagnostic confidence. IMR reduced noise and increased SNR to greater degrees than did FBP and statistical IR. Applying the IMR technique to abdominal CT imaging has potential for reducing the radiation dose without sacrificing imaging quality. PMID:27495078
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…
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.
Genetic algorithms at UC Davis/LLNL
Vemuri, V.R.
1993-12-31
A tutorial introduction to genetic algorithms is given. This brief tutorial should serve the purpose of introducing the subject to the novice. The tutorial is followed by a brief commentary on the term project reports that follow.
Advanced CHP Control Algorithms: Scope Specification
Katipamula, Srinivas; Brambley, Michael R.
2006-04-28
The primary objective of this multiyear project is to develop algorithms for combined heat and power systems to ensure optimal performance, increase reliability, and lead to the goal of clean, efficient, reliable and affordable next generation energy systems.
Schmidtlein, CR; Beattie, B; Humm, J; Li, S; Wu, Z; Xu, Y; Zhang, J; Shen, L; Vogelsang, L; Feiglin, D; Krol, A
2014-06-15
Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1st order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved
Spectral Representations of Uncertainty: Algorithms and Applications
George Em Karniadakis
2005-04-24
The objectives of this project were: (1) Develop a general algorithmic framework for stochastic ordinary and partial differential equations. (2) Set polynomial chaos method and its generalization on firm theoretical ground. (3) Quantify uncertainty in large-scale simulations involving CFD, MHD and microflows. The overall goal of this project was to provide DOE with an algorithmic capability that is more accurate and three to five orders of magnitude more efficient than the Monte Carlo simulation.
NYU Ultracomputer project. Final project summary, 1979-1993
Gottlieb, A.
1994-10-01
This report discusses the following on the Ultracomputer project: simulation studies; network analysis; prototype hardware; VSLI design; coordination algorithms; systems software; application software; and compiler development.
Comparison of cone beam artifacts reduction: two pass algorithm vs TV-based CS algorithm
NASA Astrophysics Data System (ADS)
Choi, Shinkook; Baek, Jongduk
2015-03-01
In a cone beam computed tomography (CBCT), the severity of the cone beam artifacts is increased as the cone angle increases. To reduce the cone beam artifacts, several modified FDK algorithms and compressed sensing based iterative algorithms have been proposed. In this paper, we used two pass algorithm and Gradient-Projection-Barzilai-Borwein (GPBB) algorithm to reduce the cone beam artifacts, and compared their performance using structural similarity (SSIM) index. In two pass algorithm, it is assumed that the cone beam artifacts are mainly caused by extreme-density(ED) objects, and therefore the algorithm reproduces the cone beam artifacts(i.e., error image) produced by ED objects, and then subtract it from the original image. GPBB algorithm is a compressed sensing based iterative algorithm which minimizes an energy function for calculating the gradient projection with the step size determined by the Barzilai- Borwein formulation, therefore it can estimate missing data caused by the cone beam artifacts. To evaluate the performance of two algorithms, we used testing objects consisting of 7 ellipsoids separated along the z direction and cone beam artifacts were generated using 30 degree cone angle. Even though the FDK algorithm produced severe cone beam artifacts with a large cone angle, two pass algorithm reduced the cone beam artifacts with small residual errors caused by inaccuracy of ED objects. In contrast, GPBB algorithm completely removed the cone beam artifacts and restored the original shape of the objects.
Pistonesi, Marcelo F; Di Nezio, María S; Centurión, María E; Lista, Adriana G; Fragoso, Wallace D; Pontes, Márcio J C; Araújo, Mário C U; Band, Beatriz S Fernández
2010-12-15
In this study, a novel, simple, and efficient spectrofluorimetric method to determine directly and simultaneously five phenolic compounds (hydroquinone, resorcinol, phenol, m-cresol and p-cresol) in air samples is presented. For this purpose, variable selection by the successive projections algorithm (SPA) is used in order to obtain simple multiple linear regression (MLR) models based on a small subset of wavelengths. For comparison, partial least square (PLS) regression is also employed in full-spectrum. The concentrations of the calibration matrix ranged from 0.02 to 0.2 mg L(-1) for hydroquinone, from 0.05 to 0.6 mg L(-1) for resorcinol, and from 0.05 to 0.4 mg L(-1) for phenol, m-cresol and p-cresol; incidentally, such ranges are in accordance with the Argentinean environmental legislation. To verify the accuracy of the proposed method a recovery study on real air samples of smoking environment was carried out with satisfactory results (94-104%). The advantage of the proposed method is that it requires only spectrofluorimetric measurements of samples and chemometric modeling for simultaneous determination of five phenols. With it, air is simply sampled and no pre-treatment sample is needed (i.e., separation steps and derivatization reagents are avoided) that means a great saving of time. PMID:21111140
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.
Hogan, Robin
2008-01-15
Cloudnet is a research project supported by the European Commission. This project aims to use data obtained quasi-continuously for the development and implementation of cloud remote sensing synergy algorithms. The use of active instruments (lidar and radar) results in detailed vertical profiles of important cloud parameters which cannot be derived from current satellite sensing techniques. A network of three already existing cloud remote sensing stations (CRS-stations) will be operated for a two year period, activities will be co-ordinated, data formats harmonised and analysis of the data performed to evaluate the representation of clouds in four major european weather forecast models.
Library of Continuation Algorithms
2005-03-01
LOCA (Library of Continuation Algorithms) is scientific software written in C++ that provides advanced analysis tools for nonlinear systems. In particular, it provides parameter continuation algorithms. bifurcation tracking algorithms, and drivers for linear stability analysis. The algorithms are aimed at large-scale applications that use Newtons method for their nonlinear solve.
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.
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.
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)).
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.
Reasoning about systolic algorithms
Purushothaman, S.
1986-01-01
Systolic algorithms are a class of parallel algorithms, with small grain concurrency, well suited for implementation in VLSI. They are intended to be implemented as high-performance, computation-bound back-end processors and are characterized by a tesselating interconnection of identical processing elements. This dissertation investigates the problem of providing correctness of systolic algorithms. The following are reported in this dissertation: (1) a methodology for verifying correctness of systolic algorithms based on solving the representation of an algorithm as recurrence equations. The methodology is demonstrated by proving the correctness of a systolic architecture for optimal parenthesization. (2) The implementation of mechanical proofs of correctness of two systolic algorithms, a convolution algorithm and an optimal parenthesization algorithm, using the Boyer-Moore theorem prover. (3) An induction principle for proving correctness of systolic arrays which are modular. Two attendant inference rules, weak equivalence and shift transformation, which capture equivalent behavior of systolic arrays, are also presented.
Algorithm-development activities
NASA Technical Reports Server (NTRS)
Carder, Kendall L.
1994-01-01
The task of algorithm-development activities at USF continues. The algorithm for determining chlorophyll alpha concentration, (Chl alpha) and gelbstoff absorption coefficient for SeaWiFS and MODIS-N radiance data is our current priority.
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.
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).
Software Management Environment (SME): Components and algorithms
NASA Technical Reports Server (NTRS)
Hendrick, Robert; Kistler, David; Valett, Jon
1994-01-01
This document presents the components and algorithms of the Software Management Environment (SME), a management tool developed for the Software Engineering Branch (Code 552) of the Flight Dynamics Division (FDD) of the Goddard Space Flight Center (GSFC). The SME provides an integrated set of visually oriented experienced-based tools that can assist software development managers in managing and planning software development projects. This document describes and illustrates the analysis functions that underlie the SME's project monitoring, estimation, and planning tools. 'SME Components and Algorithms' is a companion reference to 'SME Concepts and Architecture' and 'Software Engineering Laboratory (SEL) Relationships, Models, and Management Rules.'
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.
Novel biomedical tetrahedral mesh methods: algorithms and applications
NASA Astrophysics Data System (ADS)
Yu, Xiao; Jin, Yanfeng; Chen, Weitao; Huang, Pengfei; Gu, Lixu
2007-12-01
Tetrahedral mesh generation algorithm, as a prerequisite of many soft tissue simulation methods, becomes very important in the virtual surgery programs because of the real-time requirement. Aiming to speed up the computation in the simulation, we propose a revised Delaunay algorithm which makes a good balance of quality of tetrahedra, boundary preservation and time complexity, with many improved methods. Another mesh algorithm named Space-Disassembling is also presented in this paper, and a comparison of Space-Disassembling, traditional Delaunay algorithm and the revised Delaunay algorithm is processed based on clinical soft-tissue simulation projects, including craniofacial plastic surgery and breast reconstruction plastic surgery.
Semioptimal practicable algorithmic cooling
Elias, Yuval; Mor, Tal; Weinstein, Yossi
2011-04-15
Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon's entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.
Reasoning about systolic algorithms
Purushothaman, S.; Subrahmanyam, P.A.
1988-12-01
The authors present a methodology for verifying correctness of systolic algorithms. The methodology is based on solving a set of Uniform Recurrence Equations obtained from a description of systolic algorithms as a set of recursive equations. They present an approach to mechanically verify correctness of systolic algorithms, using the Boyer-Moore theorem proven. A mechanical correctness proof of an example from the literature is also presented.
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.
Competing Sudakov veto algorithms
NASA Astrophysics Data System (ADS)
Kleiss, Ronald; Verheyen, Rob
2016-07-01
We present a formalism to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The formal analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance in a semi-realistic setting and show that there are significantly faster alternatives to the commonly used algorithms.
A new reconstruction algorithm for Radon data
NASA Astrophysics Data System (ADS)
Xu, Y.; Tischenko, O.; Hoeschen, C.
2006-03-01
A new reconstruction algorithm for Radon data is introduced. We call the new algorithm OPED as it is based on Orthogonal Polynomial Expansion on the Disk. OPED is fundamentally different from the filtered back projection (FBP) method. It allows one to use fan beam geometry directly without any additional procedures such as interpolation or rebinning. It reconstructs high degree polynomials exactly and works for smooth functions without the assumption that functions are band- limited. Our initial tests indicate that the algorithm is stable, provides high resolution images, and has a small global error. Working with the geometry specified by the algorithm and a new mask, OPED could also lead to a reconstruction method that works with reduced x-ray dose (see the paper by Tischenko et al in these proceedings).
Advancements to the planogram frequency–distance rebinning algorithm
Champley, Kyle M; Raylman, Raymond R; Kinahan, Paul E
2010-01-01
In this paper we consider the task of image reconstruction in positron emission tomography (PET) with the planogram frequency–distance rebinning (PFDR) algorithm. The PFDR algorithm is a rebinning algorithm for PET systems with panel detectors. The algorithm is derived in the planogram coordinate system which is a native data format for PET systems with panel detectors. A rebinning algorithm averages over the redundant four-dimensional set of PET data to produce a three-dimensional set of data. Images can be reconstructed from this rebinned three-dimensional set of data. This process enables one to reconstruct PET images more quickly than reconstructing directly from the four-dimensional PET data. The PFDR algorithm is an approximate rebinning algorithm. We show that implementing the PFDR algorithm followed by the (ramp) filtered backprojection (FBP) algorithm in linogram coordinates from multiple views reconstructs a filtered version of our image. We develop an explicit formula for this filter which can be used to achieve exact reconstruction by means of a modified FBP algorithm applied to the stack of rebinned linograms and can also be used to quantify the errors introduced by the PFDR algorithm. This filter is similar to the filter in the planogram filtered backprojection algorithm derived by Brasse et al. The planogram filtered backprojection and exact reconstruction with the PFDR algorithm require complete projections which can be completed with a reprojection algorithm. The PFDR algorithm is similar to the rebinning algorithm developed by Kao et al. By expressing the PFDR algorithm in detector coordinates, we provide a comparative analysis between the two algorithms. Numerical experiments using both simulated data and measured data from a positron emission mammography/tomography (PEM/PET) system are performed. Images are reconstructed by PFDR+FBP (PFDR followed by 2D FBP reconstruction), PFDRX (PFDR followed by the modified FBP algorithm for exact
LCD motion blur: modeling, analysis, and algorithm.
Chan, Stanley H; Nguyen, Truong Q
2011-08-01
Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD model and an efficient deblurring algorithm are needed. However, existing LCD motion blur models are insufficient to reflect the limitation of human-eye-tracking system. Also, the spatiotemporal equivalence in LCD motion blur models has not been proven directly in the discrete 2-D spatial domain, although it is widely used. There are three main contributions of this paper: modeling, analysis, and algorithm. First, a comprehensive LCD motion blur model is presented, in which human-eye-tracking limits are taken into consideration. Second, a complete analysis of spatiotemporal equivalence is provided and verified using real video sequences. Third, an LCD motion blur reduction algorithm is proposed. The proposed algorithm solves an l(1)-norm regularized least-squares minimization problem using a subgradient projection method. Numerical results show that the proposed algorithm gives higher peak SNR, lower temporal error, and lower spatial error than motion-compensated inverse filtering and Lucy-Richardson deconvolution algorithm, which are two state-of-the-art LCD deblurring algorithms. PMID:21292596
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
Total variation projection with first order schemes.
Fadili, Jalal M; Peyre, Gabriel
2011-03-01
This article proposes a new algorithm to compute the projection on the set of images whose total variation is bounded by a constant. The projection is computed through a dual formulation that is solved by first order non-smooth optimization methods. This yields an iterative algorithm that applies iterative soft thresholding to the dual vector field, and for which we establish convergence rate on the primal iterates. This projection algorithm can then be used as a building block in a variety of applications such as solving inverse problems under a total variation constraint, or for texture synthesis. Numerical results are reported to illustrate the usefulness and potential applicability of our TV projection algorithm on various examples including denoising, texture synthesis, inpainting, deconvolution and tomography problems. We also show that our projection algorithm competes favorably with state-of-the-art TV projection methods in terms of convergence speed. PMID:20876024
Parallel scheduling algorithms
Dekel, E.; Sahni, S.
1983-01-01
Parallel algorithms are given for scheduling problems such as scheduling to minimize the number of tardy jobs, job sequencing with deadlines, scheduling to minimize earliness and tardiness penalties, channel assignment, and minimizing the mean finish time. The shared memory model of parallel computers is used to obtain fast algorithms. 26 references.
Developmental Algorithms Have Meaning!
ERIC Educational Resources Information Center
Green, John
1997-01-01
Adapts Stanic and McKillip's ideas for the use of developmental algorithms to propose that the present emphasis on symbolic manipulation should be tempered with an emphasis on the conceptual understanding of the mathematics underlying the algorithm. Uses examples from the areas of numeric computation, algebraic manipulation, and equation solving…
Use of evolutionary algorithms for telescope scheduling
NASA Astrophysics Data System (ADS)
Grim, Ruud; Jansen, Mischa; Baan, Arno; van Hemert, Jano; de Wolf, Hans
2002-07-01
LOFAR, a new radio telescope, will be designed to observe with up to 8 independent beams, thus allowing several simultaneous observations. Scheduling of multiple observations parallel in time, each having their own constraints, requires a more intelligent and flexible scheduling function then operated before. In support of the LOFAR radio telescope project, and in co-operation with Leiden University, Fokker Space has started a study to investigate the suitability of the use of evolutionary algorithms applied to complex scheduling problems. After a positive familiarization phase, we now examine the potential use of evolutionary algorithms via a demonstration project. Results of the familiarization phase, and the first results of the demonstration project are presented in this paper.
BALL - biochemical algorithms library 1.3
2010-01-01
Background The Biochemical Algorithms Library (BALL) is a comprehensive rapid application development framework for structural bioinformatics. It provides an extensive C++ class library of data structures and algorithms for molecular modeling and structural bioinformatics. Using BALL as a programming toolbox does not only allow to greatly reduce application development times but also helps in ensuring stability and correctness by avoiding the error-prone reimplementation of complex algorithms and replacing them with calls into the library that has been well-tested by a large number of developers. In the ten years since its original publication, BALL has seen a substantial increase in functionality and numerous other improvements. Results Here, we discuss BALL's current functionality and highlight the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics. Conclusions BALL is available for all major operating systems, including Linux, Windows, and MacOS X. It is available free of charge under the Lesser GNU Public License (LPGL). Parts of the code are distributed under the GNU Public License (GPL). BALL is available as source code and binary packages from the project web site at http://www.ball-project.org. Recently, it has been accepted into the debian project; integration into further distributions is currently pursued. PMID:20973958
NASA Astrophysics Data System (ADS)
Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.
2013-01-01
A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.
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.
Parallel algorithms and architectures
Albrecht, A.; Jung, H.; Mehlhorn, K.
1987-01-01
Contents of this book are the following: Preparata: Deterministic simulation of idealized parallel computers on more realistic ones; Convex hull of randomly chosen points from a polytope; Dataflow computing; Parallel in sequence; Towards the architecture of an elementary cortical processor; Parallel algorithms and static analysis of parallel programs; Parallel processing of combinatorial search; Communications; An O(nlogn) cost parallel algorithms for the single function coarsest partition problem; Systolic algorithms for computing the visibility polygon and triangulation of a polygonal region; and RELACS - A recursive layout computing system. Parallel linear conflict-free subtree access.
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.
Infrared algorithm development for ocean observations
NASA Technical Reports Server (NTRS)
Brown, Otis B.
1995-01-01
Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, involvement in field studies, production and evaluation of new computer networking strategies, and objective analysis approaches.
Graph algorithms in the titan toolkit.
McLendon, William Clarence, III; Wylie, Brian Neil
2009-10-01
Graph algorithms are a key component in a wide variety of intelligence analysis activities. The Graph-Based Informatics for Non-Proliferation and Counter-Terrorism project addresses the critical need of making these graph algorithms accessible to Sandia analysts in a manner that is both intuitive and effective. Specifically we describe the design and implementation of an open source toolkit for doing graph analysis, informatics, and visualization that provides Sandia with novel analysis capability for non-proliferation and counter-terrorism.
Thomas, Kamishia L
2016-01-01
Catheter-associated urinary tract infections (CAUTIs) are the most common hospital-acquired infections. The purpose of this quality improvement (QI) project was to successfully implement a nurse-led evidence-based practice change designed to reduce CAUTIs in a cardiac intensive care and step-down unit. The QI project was implemented using a convenience sample of patients admitted to the cardiac intensive care and step-down unit.Evaluation data were collected 3 months preimplementation and 9 months postimplementation. We used Wick's Check-Plan-Do-Check-Act model of continuous QI to guide the project. A statistically significant change in the number of CAUTIs (P = .009) and CAUTI occurrences (P = .005) was observed following the intervention. The number of indwelling catheter days and indwelling catheter utilization did not significantly differ following implementation of the intervention. Nurse compliance with the intervention was computed for each month; the average compliance rate was 91%. Findings from this project indicate that a nurse-led evidence-based practice project exerted a positive influence on CAUTI occurrences. PMID:26808302
Implementation and testing of algorithms for data fitting
NASA Astrophysics Data System (ADS)
Monahan, Alison; Engelhardt, Larry
2012-03-01
This poster will describe an undergraduate senior research project involving the creation and testing of a java class to implement the Nelder-Mead algorithm, which can be used for data fitting. The performance between the Nelder-Mead algorithm and the Levenberg-Marquardt algorithm will be compared using a variety of different data. The new class will be made available at http://www.compadre.org/osp/items/detail.cfm?ID=11593. At the time of the presentation, this project will be nearing completion; and I will discuss my progress, successes, and challenges.
A Simple Calculator Algorithm.
ERIC Educational Resources Information Center
Cook, Lyle; McWilliam, James
1983-01-01
The problem of finding cube roots when limited to a calculator with only square root capability is discussed. An algorithm is demonstrated and explained which should always produce a good approximation within a few iterations. (MP)
Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425
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.
Algorithmically specialized parallel computers
Snyder, L.; Jamieson, L.H.; Gannon, D.B.; Siegel, H.J.
1985-01-01
This book is based on a workshop which dealt with array processors. Topics considered include algorithmic specialization using VLSI, innovative architectures, signal processing, speech recognition, image processing, specialized architectures for numerical computations, and general-purpose computers.
2013-07-29
The OpenEIS Algorithm package seeks to provide a low-risk path for building owners, service providers and managers to explore analytical methods for improving building control and operational efficiency. Users of this software can analyze building data, and learn how commercial implementations would provide long-term value. The code also serves as a reference implementation for developers who wish to adapt the algorithms for use in commercial tools or service offerings.
The Superior Lambert Algorithm
NASA Astrophysics Data System (ADS)
der, G.
2011-09-01
Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most
Randomized Algorithms for Matrices and Data
NASA Astrophysics Data System (ADS)
Mahoney, Michael W.
2012-03-01
This chapter reviews recent work on randomized matrix algorithms. By “randomized matrix algorithms,” we refer to a class of recently developed random sampling and random projection algorithms for ubiquitous linear algebra problems such as least-squares (LS) regression and low-rank matrix approximation. These developments have been driven by applications in large-scale data analysis—applications which place very different demands on matrices than traditional scientific computing applications. Thus, in this review, we will focus on highlighting the simplicity and generality of several core ideas that underlie the usefulness of these randomized algorithms in scientific applications such as genetics (where these algorithms have already been applied) and astronomy (where, hopefully, in part due to this review they will soon be applied). The work we will review here had its origins within theoretical computer science (TCS). An important feature in the use of randomized algorithms in TCS more generally is that one must identify and then algorithmically deal with relevant “nonuniformity structure” in the data. For the randomized matrix algorithms to be reviewed here and that have proven useful recently in numerical linear algebra (NLA) and large-scale data analysis applications, the relevant nonuniformity structure is defined by the so-called statistical leverage scores. Defined more precisely below, these leverage scores are basically the diagonal elements of the projection matrix onto the dominant part of the spectrum of the input matrix. As such, they have a long history in statistical data analysis, where they have been used for outlier detection in regression diagnostics. More generally, these scores often have a very natural interpretation in terms of the data and processes generating the data. For example, they can be interpreted in terms of the leverage or influence that a given data point has on, say, the best low-rank matrix approximation; and this
NASA Astrophysics Data System (ADS)
Tom, C. N.; Davies, W. J.; Goycochea, J. F.
1993-09-01
The purpose of this project was to explore the use of polar processing techniques in SIGINT-related signal processing applications. An investigation of ways to apply the CORDIC arithmetic algorithm to signal processing problems, and an application of the TMC2330 Coordinate Transformer chip in a coprocessor or accelerator board for a Sun workstation are covered.
Sampling Within k-Means Algorithm to Cluster Large Datasets
Bejarano, Jeremy; Bose, Koushiki; Brannan, Tyler; Thomas, Anita; Adragni, Kofi; Neerchal, Nagaraj; Ostrouchov, George
2011-08-01
Due to current data collection technology, our ability to gather data has surpassed our ability to analyze it. In particular, k-means, one of the simplest and fastest clustering algorithms, is ill-equipped to handle extremely large datasets on even the most powerful machines. Our new algorithm uses a sample from a dataset to decrease runtime by reducing the amount of data analyzed. We perform a simulation study to compare our sampling based k-means to the standard k-means algorithm by analyzing both the speed and accuracy of the two methods. Results show that our algorithm is significantly more efficient than the existing algorithm with comparable accuracy. Further work on this project might include a more comprehensive study both on more varied test datasets as well as on real weather datasets. This is especially important considering that this preliminary study was performed on rather tame datasets. Also, these datasets should analyze the performance of the algorithm on varied values of k. Lastly, this paper showed that the algorithm was accurate for relatively low sample sizes. We would like to analyze this further to see how accurate the algorithm is for even lower sample sizes. We could find the lowest sample sizes, by manipulating width and confidence level, for which the algorithm would be acceptably accurate. In order for our algorithm to be a success, it needs to meet two benchmarks: match the accuracy of the standard k-means algorithm and significantly reduce runtime. Both goals are accomplished for all six datasets analyzed. However, on datasets of three and four dimension, as the data becomes more difficult to cluster, both algorithms fail to obtain the correct classifications on some trials. Nevertheless, our algorithm consistently matches the performance of the standard algorithm while becoming remarkably more efficient with time. Therefore, we conclude that analysts can use our algorithm, expecting accurate results in considerably less time.
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.
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.
A digitally reconstructed radiograph algorithm calculated from first principles
Staub, David; Murphy, Martin J.
2013-01-15
Purpose: To develop an algorithm for computing realistic digitally reconstructed radiographs (DRRs) that match real cone-beam CT (CBCT) projections with no artificial adjustments. Methods: The authors used measured attenuation data from cone-beam CT projection radiographs of different materials to obtain a function to convert CT number to linear attenuation coefficient (LAC). The effects of scatter, beam hardening, and veiling glare were first removed from the attenuation data. Using this conversion function the authors calculated the line integral of LAC through a CT along rays connecting the radiation source and detector pixels with a ray-tracing algorithm, producing raw DRRs. The effects of scatter, beam hardening, and veiling glare were then included in the DRRs through postprocessing. Results: The authors compared actual CBCT projections to DRRs produced with all corrections (scatter, beam hardening, and veiling glare) and to uncorrected DRRs. Algorithm accuracy was assessed through visual comparison of projections and DRRs, pixel intensity comparisons, intensity histogram comparisons, and correlation plots of DRR-to-projection pixel intensities. In general, the fully corrected algorithm provided a small but nontrivial improvement in accuracy over the uncorrected algorithm. The authors also investigated both measurement- and computation-based methods for determining the beam hardening correction, and found the computation-based method to be superior, as it accounted for nonuniform bowtie filter thickness. The authors benchmarked the algorithm for speed and found that it produced DRRs in about 0.35 s for full detector and CT resolution at a ray step-size of 0.5 mm. Conclusions: The authors have demonstrated a DRR algorithm calculated from first principles that accounts for scatter, beam hardening, and veiling glare in order to produce accurate DRRs. The algorithm is computationally efficient, making it a good candidate for iterative CT reconstruction techniques
NASA Astrophysics Data System (ADS)
Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing
2015-08-01
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).
A set-membership approach to blind channel equalization algorithm
NASA Astrophysics Data System (ADS)
Li, Yue-ming
2013-03-01
The constant modulus algorithm (CMA) has low computational complexity while presenting slow convergence and possible convergence to local minima, the CMA family of algorithms based on affine projection version (AP-CMA) alleviates the speed limitations of the CMA. However, the computational complexity has been a weak point in the implementation of AP-CMA. To reduce the computational complexity of the adaptive filtering algorithm, a new AP-CMA algorithm based on set membership (SM-AP-CMA) is proposed. The new algorithm combines a bounded error specification on the adaptive filter with the concept of data-reusing. Simulations confirmed that the convergence rate of the proposed algorithm is significantly faster; meanwhile, the excess mean square error can be maintained in a relatively low level and a substantial reduction in the number of updates when compared with its conventional counterpart.
Evaluating ACLS Algorithms for the International Space Station (ISS) - A Paradigm Revisited
NASA Technical Reports Server (NTRS)
Alexander, Dave; Brandt, Keith; Locke, James; Hurst, Victor, IV; Mack, Michael D.; Pettys, Marianne; Smart, Kieran
2007-01-01
The ISS may have communication gaps of up to 45 minutes during each orbit and therefore it is imperative to have medical protocols, including an effective ACLS algorithm, that can be reliably autonomously executed during flight. The aim of this project was to compare the effectiveness of the current ACLS algorithm with an improved algorithm having a new navigation format.
Parallel Implementation of Katsevich's FBP Algorithm
Guo, Xiaohu; Kong, Qiang; Zhou, Tie; Jiang, Ming
2006-01-01
For spiral cone-beam CT, parallel computing is an effective approach to resolving the problem of heavy computation burden. It is well known that the major computation time is spent in the backprojection step for either filtered-backprojection (FBP) or backprojected-filtration (BPF) algorithms. By the cone-beam cover method [1], the backprojection procedure is driven by cone-beam projections, and every cone-beam projection can be backprojected independently. Basing on this fact, we develop a parallel implementation of Katsevich's FBP algorithm. We do all the numerical experiments on a Linux cluster. In one typical experiment, the sequential reconstruction time is 781.3 seconds, while the parallel reconstruction time is 25.7 seconds with 32 processors. PMID:23165019
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
Optical rate sensor algorithms
NASA Technical Reports Server (NTRS)
Uhde-Lacovara, Jo A.
1989-01-01
Optical sensors, in particular Charge Coupled Device (CCD) arrays, will be used on Space Station to track stars in order to provide inertial attitude reference. Algorithms are presented to derive attitude rate from the optical sensors. The first algorithm is a recursive differentiator. A variance reduction factor (VRF) of 0.0228 was achieved with a rise time of 10 samples. A VRF of 0.2522 gives a rise time of 4 samples. The second algorithm is based on the direct manipulation of the pixel intensity outputs of the sensor. In 1-dimensional simulations, the derived rate was with 0.07 percent of the actual rate in the presence of additive Gaussian noise with a signal to noise ratio of 60 dB.
Temperature Corrected Bootstrap Algorithm
NASA Technical Reports Server (NTRS)
Comiso, Joey C.; Zwally, H. Jay
1997-01-01
A temperature corrected Bootstrap Algorithm has been developed using Nimbus-7 Scanning Multichannel Microwave Radiometer data in preparation to the upcoming AMSR instrument aboard ADEOS and EOS-PM. The procedure first calculates the effective surface emissivity using emissivities of ice and water at 6 GHz and a mixing formulation that utilizes ice concentrations derived using the current Bootstrap algorithm but using brightness temperatures from 6 GHz and 37 GHz channels. These effective emissivities are then used to calculate surface ice which in turn are used to convert the 18 GHz and 37 GHz brightness temperatures to emissivities. Ice concentrations are then derived using the same technique as with the Bootstrap algorithm but using emissivities instead of brightness temperatures. The results show significant improvement in the area where ice temperature is expected to vary considerably such as near the continental areas in the Antarctic, where the ice temperature is colder than average, and in marginal ice zones.
Power spectral estimation algorithms
NASA Technical Reports Server (NTRS)
Bhatia, Manjit S.
1989-01-01
Algorithms to estimate the power spectrum using Maximum Entropy Methods were developed. These algorithms were coded in FORTRAN 77 and were implemented on the VAX 780. The important considerations in this analysis are: (1) resolution, i.e., how close in frequency two spectral components can be spaced and still be identified; (2) dynamic range, i.e., how small a spectral peak can be, relative to the largest, and still be observed in the spectra; and (3) variance, i.e., how accurate the estimate of the spectra is to the actual spectra. The application of the algorithms based on Maximum Entropy Methods to a variety of data shows that these criteria are met quite well. Additional work in this direction would help confirm the findings. All of the software developed was turned over to the technical monitor. A copy of a typical program is included. Some of the actual data and graphs used on this data are also included.
Algorithmic Techniques for Massive Data Sets
Moses Charikar
2006-04-03
This report describes the progress made during the Early Career Principal Investigator (ECPI) project on Algorithmic Techniques for Large Data Sets. Research was carried out in the areas of dimension reduction, clustering and finding structure in data, aggregating information from different sources and designing efficient methods for similarity search for high dimensional data. A total of nine different research results were obtained and published in leading conferences and journals.
Programming parallel vision algorithms
Shapiro, L.G.
1988-01-01
Computer vision requires the processing of large volumes of data and requires parallel architectures and algorithms to be useful in real-time, industrial applications. The INSIGHT dataflow language was designed to allow encoding of vision algorithms at all levels of the computer vision paradigm. INSIGHT programs, which are relational in nature, can be translated into a graph structure that represents an architecture for solving a particular vision problem or a configuration of a reconfigurable computational network. The authors consider here INSIGHT programs that produce a parallel net architecture for solving low-, mid-, and high-level vision tasks.
New Effective Multithreaded Matching Algorithms
Manne, Fredrik; Halappanavar, Mahantesh
2014-05-19
Matching is an important combinatorial problem with a number of applications in areas such as community detection, sparse linear algebra, and network alignment. Since computing optimal matchings can be very time consuming, several fast approximation algorithms, both sequential and parallel, have been suggested. Common to the algorithms giving the best solutions is that they tend to be sequential by nature, while algorithms more suitable for parallel computation give solutions of less quality. We present a new simple 1 2 -approximation algorithm for the weighted matching problem. This algorithm is both faster than any other suggested sequential 1 2 -approximation algorithm on almost all inputs and also scales better than previous multithreaded algorithms. We further extend this to a general scalable multithreaded algorithm that computes matchings of weight comparable with the best sequential algorithms. The performance of the suggested algorithms is documented through extensive experiments on different multithreaded architectures.
Parallel vision algorithms. Annual technical report No. 1, 1 October 1986-30 September 1987
Ibrahim, H.A.; Kender, J.R.; Brown, L.G.
1987-10-01
The objective of this project is to develop and implement, on highly parallel computers, vision algorithms that combine stereo, texture, and multi-resolution techniques for determining local surface orientation and depth. Such algorithms will immediately serve as front-ends for autonomous land vehicle navigation systems. During the first year of the project, efforts have concentrated on two fronts. First, developing and testing the parallel programming environment that will be used to develop, implement and test the parallel vision algorithms. Second, developing and testing multi-resolution stereo, and texture algorithms. This report describes the status and progress on these two fronts. The authors describe first the programming environment developed, and mapping scheme that allows efficient use of the connection machine for pyramid (multi-resolution) algorithms. Second, they present algorithms and test results for multi-resolution stereo, and texture algorithms. Also the initial results of the starting efforts of integrating stereo and texture algorithms are presented.
Advanced Algorithms and Automation Tools for Discrete Ordinates Methods in Parallel Environments
Alireza Haghighat
2003-05-07
This final report discusses major accomplishments of a 3-year project under the DOE's NEER Program. The project has developed innovative and automated algorithms, codes, and tools for solving the discrete ordinates particle transport method efficiently in parallel environments. Using a number of benchmark and real-life problems, the performance and accuracy of the new algorithms have been measured and analyzed.
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.
Multivariate Spline Algorithms for CAGD
NASA Technical Reports Server (NTRS)
Boehm, W.
1985-01-01
Two special polyhedra present themselves for the definition of B-splines: a simplex S and a box or parallelepiped B, where the edges of S project into an irregular grid, while the edges of B project into the edges of a regular grid. More general splines may be found by forming linear combinations of these B-splines, where the three-dimensional coefficients are called the spline control points. Univariate splines are simplex splines, where s = 1, whereas splines over a regular triangular grid are box splines, where s = 2. Two simple facts render the development of the construction of B-splines: (1) any face of a simplex or a box is again a simplex or box but of lower dimension; and (2) any simplex or box can be easily subdivided into smaller simplices or boxes. The first fact gives a geometric approach to Mansfield-like recursion formulas that express a B-spline in B-splines of lower order, where the coefficients depend on x. By repeated recursion, the B-spline will be expressed as B-splines of order 1; i.e., piecewise constants. In the case of a simplex spline, the second fact gives a so-called insertion algorithm that constructs the new control points if an additional knot is inserted.
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.
ANL CT Reconstruction Algorithm for Utilizing Digital X-ray
2004-05-01
Reconstructs X-ray computed tomographic images from large data sets known as 16-bit binary sinograms when using a massively parallelized computer architecture such as a Beowuif cluster by parallelizing the X-ray CT reconstruction routine. The algorithm uses the concept of generation of an image from carefully obtained multiple 1-D or 2-D X-ray projections. The individual projections are filtered using a digital Fast Fourier Transform. The literature refers to this as filtered back projection.
NASA Astrophysics Data System (ADS)
Santer, Richard P.; Fell, Frank
2003-05-01
), combining satellite data, evaluation algorithms and value-adding ancillary digital information. This prevents the end user from investing funds into expensive equipment or to hire specialized personnel. The data processor shall be a generic tool, which may be applied to a large variety of operationally gathered satellite data. In the frame of SISCAL, the processor shall be applied to remotely sensed data of selected coastal areas and lakes in Central Europe and the Eastern Mediterranean, according to the needs of the end users within the SISCAL consortium. A number of measures are required to achieve the objective of the proposed project: (1) Identification and specification of the SISCAL end user needs for NRT water related data products accessible to EO techniques. (2) Selection of the most appropriate instruments, evaluation algorithms and ancillary data bases required to provide the identified data products. (3) Development of the actual Near-Real-Time data processor for the specified EO data products. (4) Development of the GIS processor adding ancillary digital information to the satellite images and providing the required geographical projections. (5) Development of a product retrieval and management system to handle ordering and distribution of data products between the SISCAL server and the end users, including payment and invoicing. (6) Evaluation of the derived data products in terms of accuracy and usefulness by comparison with available in-situ measurements and by making use of the local expertise of the end users. (7) Establishing an Internet server dedicated to internal communication between the consortium members as well as presenting the SISCAL project to a larger public. (8) Marketing activities, presentation of data processor to potential external customers, identification of their exact needs. The innovative aspect of the SISCAL project consists in the generation of NRT data products on water quality parameters from EO data. This article mainly deals
NASA Astrophysics Data System (ADS)
Santer, Richard P.; Fell, Frank
2003-05-01
), combining satellite data, evaluation algorithms and value-adding ancillary digital information. This prevents the end user from investing funds into expensive equipment or to hire specialized personnel. The data processor shall be a generic tool, which may be applied to a large variety of operationally gathered satellite data. In the frame of SISCAL, the processor shall be applied to remotely sensed data of selected coastal areas and lakes in Central Europe and the Eastern Mediterranean, according to the needs of the end users within the SISCAL consortium. A number of measures are required to achieve the objective of the proposed project: (1) Identification and specification of the SISCAL end user needs for NRT water related data products accessible to EO techniques. (2) Selection of the most appropriate instruments, evaluation algorithms and ancillary data bases required to provide the identified data products. (3) Development of the actual Near-Real-Time data processor for the specified EO data products. (4) Development of the GIS processor adding ancillary digital information to the satellite images and providing the required geographical projections. (5) Development of a product retrieval and management system to handle ordering and distribution of data products between the SISCAL server and the end users, including payment and invoicing. (6) Evaluation of the derived data products in terms of accuracy and usefulness by comparison with available in-situ measurements and by making use of the local expertise of the end users. (7) Establishing an Internet server dedicated to internal communication between the consortium members as well as presenting the SISCAL project to a larger public. (8) Marketing activities, presentation of data processor to potential external customers, identification of their exact needs. The innovative aspect of the SISCAL project consists in the generation of NRT data products on water quality parameters from EO data. This article mainly deals
2005-03-30
The Robotic Follow Algorithm enables allows any robotic vehicle to follow a moving target while reactively choosing a route around nearby obstacles. The robotic follow behavior can be used with different camera systems and can be used with thermal or visual tracking as well as other tracking methods such as radio frequency tags.
Data Structures and Algorithms.
ERIC Educational Resources Information Center
Wirth, Niklaus
1984-01-01
Built-in data structures are the registers and memory words where binary values are stored; hard-wired algorithms are the fixed rules, embodied in electronic logic circuits, by which stored data are interpreted as instructions to be executed. Various topics related to these two basic elements of every computer program are discussed. (JN)
General cardinality genetic algorithms
Koehler; Bhattacharyya; Vose
1997-01-01
A complete generalization of the Vose genetic algorithm model from the binary to higher cardinality case is provided. Boolean AND and EXCLUSIVE-OR operators are replaced by multiplication and addition over rings of integers. Walsh matrices are generalized with finite Fourier transforms for higher cardinality usage. Comparison of results to the binary case are provided. PMID:10021767
ERIC Educational Resources Information Center
Drake, Michael
2011-01-01
One debate that periodically arises in mathematics education is the issue of how to teach calculation more effectively. "Modern" approaches seem to initially favour mental calculation, informal methods, and the development of understanding before introducing written forms, while traditionalists tend to champion particular algorithms. The debate is…
ERIC Educational Resources Information Center
Siegenthaler, David
For 37 states in the United States, Project Wild has become an officially sanctioned, distributed and funded "environemtnal and conservation education program." For those who are striving to implement focused, sequential, learning programs, as well as those who wish to promote harmony through a non-anthropocentric world view, Project Wild may…
Influence of DBT reconstruction algorithm on power law spectrum coefficient
NASA Astrophysics Data System (ADS)
Vancamberg, Laurence; Carton, Ann-Katherine; Abderrahmane, Ilyes H.; Palma, Giovanni; Milioni de Carvalho, Pablo; Iordache, Rǎzvan; Muller, Serge
2015-03-01
In breast X-ray images, texture has been characterized by a noise power spectrum (NPS) that has an inverse power-law shape described by its slope β in the log-log domain. It has been suggested that the magnitude of the power-law spectrum coefficient β is related to mass lesion detection performance. We assessed β in reconstructed digital breast tomosynthesis (DBT) images to evaluate its sensitivity to different typical reconstruction algorithms including simple back projection (SBP), filtered back projection (FBP) and a simultaneous iterative reconstruction algorithm (SIRT 30 iterations). Results were further compared to the β coefficient estimated from 2D central DBT projections. The calculations were performed on 31 unilateral clinical DBT data sets and simulated DBT images from 31 anthropomorphic software breast phantoms. Our results show that β highly depends on the reconstruction algorithm; the highest β values were found for SBP, followed by reconstruction with FBP, while the lowest β values were found for SIRT. In contrast to previous studies, we found that β is not always lower in reconstructed DBT slices, compared to 2D projections and this depends on the reconstruction algorithm. All β values estimated in DBT slices reconstructed with SBP were larger than β values from 2D central projections. Our study also shows that the reconstruction algorithm affects the symmetry of the breast texture NPS; the NPS of clinical cases reconstructed with SBP exhibit the highest symmetry, while the NPS of cases reconstructed with SIRT exhibit the highest asymmetry.
NASA Technical Reports Server (NTRS)
Manning, Robert M.
1991-01-01
The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.
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.
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
Fast algorithms for transport models. Final report
Manteuffel, T.A.
1994-10-01
This project has developed a multigrid in space algorithm for the solution of the S{sub N} equations with isotropic scattering in slab geometry. The algorithm was developed for the Modified Linear Discontinuous (MLD) discretization in space which is accurate in the thick diffusion limit. It uses a red/black two-cell {mu}-line relaxation. This relaxation solves for all angles on two adjacent spatial cells simultaneously. It takes advantage of the rank-one property of the coupling between angles and can perform this inversion in O(N) operations. A version of the multigrid in space algorithm was programmed on the Thinking Machines Inc. CM-200 located at LANL. It was discovered that on the CM-200 a block Jacobi type iteration was more efficient than the block red/black iteration. Given sufficient processors all two-cell block inversions can be carried out simultaneously with a small number of parallel steps. The bottleneck is the need for sums of N values, where N is the number of discrete angles, each from a different processor. These are carried out by machine intrinsic functions and are well optimized. The overall algorithm has computational complexity O(log(M)), where M is the number of spatial cells. The algorithm is very efficient and represents the state-of-the-art for isotropic problems in slab geometry. For anisotropic scattering in slab geometry, a multilevel in angle algorithm was developed. A parallel version of the multilevel in angle algorithm has also been developed. Upon first glance, the shifted transport sweep has limited parallelism. Once the right-hand-side has been computed, the sweep is completely parallel in angle, becoming N uncoupled initial value ODE`s. The author has developed a cyclic reduction algorithm that renders it parallel with complexity O(log(M)). The multilevel in angle algorithm visits log(N) levels, where shifted transport sweeps are performed. The overall complexity is O(log(N)log(M)).
A limited-memory algorithm for bound-constrained optimization
Byrd, R.H.; Peihuang, L.; Nocedal, J. |
1996-03-01
An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited-memory BFGS matrix to approximate the Hessian of the objective function. We show how to take advantage of the form of the limited-memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.
Tomasz Plawski, J. Hovater
2010-09-01
A digital low level radio frequency (RF) system typically incorporates either a heterodyne or direct sampling technique, followed by fast ADCs, then an FPGA, and finally a transmitting DAC. This universal platform opens up the possibilities for a variety of control algorithm implementations. The foremost concern for an RF control system is cavity field stability, and to meet the required quality of regulation, the chosen control system needs to have sufficient feedback gain. In this paper we will investigate the effectiveness of the regulation for three basic control system algorithms: I&Q (In-phase and Quadrature), Amplitude & Phase and digital SEL (Self Exciting Loop) along with the example of the Jefferson Lab 12 GeV cavity field control system.
NASA Technical Reports Server (NTRS)
Arenstorf, Norbert S.; Jordan, Harry F.
1987-01-01
A barrier is a method for synchronizing a large number of concurrent computer processes. After considering some basic synchronization mechanisms, a collection of barrier algorithms with either linear or logarithmic depth are presented. A graphical model is described that profiles the execution of the barriers and other parallel programming constructs. This model shows how the interaction between the barrier algorithms and the work that they synchronize can impact their performance. One result is that logarithmic tree structured barriers show good performance when synchronizing fixed length work, while linear self-scheduled barriers show better performance when synchronizing fixed length work with an imbedded critical section. The linear barriers are better able to exploit the process skew associated with critical sections. Timing experiments, performed on an eighteen processor Flex/32 shared memory multiprocessor, that support these conclusions are detailed.
Algorithms, games, and evolution
Chastain, Erick; Livnat, Adi; Papadimitriou, Christos; Vazirani, Umesh
2014-01-01
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.
1989-01-01
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.
NASA Astrophysics Data System (ADS)
Deprit, André; Palacián, Jesúus; Deprit, Etienne
2001-03-01
The relegation algorithm extends the method of normalization by Lie transformations. Given a Hamiltonian that is a power series ℋ = ℋ0+ ɛℋ1+ ... of a small parameter ɛ, normalization constructs a map which converts the principal part ℋ0into an integral of the transformed system — relegation does the same for an arbitrary function ℋ[G]. If the Lie derivative induced by ℋ[G] is semi-simple, a double recursion produces the generator of the relegating transformation. The relegation algorithm is illustrated with an elementary example borrowed from galactic dynamics; the exercise serves as a standard against which to test software implementations. Relegation is also applied to the more substantial example of a Keplerian system perturbed by radiation pressure emanating from a rotating source.
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.
An efficient algorithm for function optimization: modified stem cells algorithm
NASA Astrophysics Data System (ADS)
Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad
2013-03-01
In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).
Algorithm Visualization System for Teaching Spatial Data Algorithms
ERIC Educational Resources Information Center
Nikander, Jussi; Helminen, Juha; Korhonen, Ari
2010-01-01
TRAKLA2 is a web-based learning environment for data structures and algorithms. The system delivers automatically assessed algorithm simulation exercises that are solved using a graphical user interface. In this work, we introduce a novel learning environment for spatial data algorithms, SDA-TRAKLA2, which has been implemented on top of the…
NASA Astrophysics Data System (ADS)
Yedidia, Jonathan S.
2011-11-01
Message-passing algorithms can solve a wide variety of optimization, inference, and constraint satisfaction problems. The algorithms operate on factor graphs that visually represent and specify the structure of the problems. After describing some of their applications, I survey the family of belief propagation (BP) algorithms, beginning with a detailed description of the min-sum algorithm and its exactness on tree factor graphs, and then turning to a variety of more sophisticated BP algorithms, including free-energy based BP algorithms, "splitting" BP algorithms that generalize "tree-reweighted" BP, and the various BP algorithms that have been proposed to deal with problems with continuous variables. The Divide and Concur (DC) algorithm is a projection-based constraint satisfaction algorithm that deals naturally with continuous variables, and converges to exact answers for problems where the solution sets of the constraints are convex. I show how it exploits the "difference-map" dynamics to avoid traps that cause more naive alternating projection algorithms to fail for non-convex problems, and explain that it is a message-passing algorithm that can also be applied to optimization problems. The BP and DC algorithms are compared, both in terms of their fundamental justifications and their strengths and weaknesses.
A vehicle detection algorithm based on deep belief network.
Wang, Hai; Cai, Yingfeng; Chen, Long
2014-01-01
Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN) is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets. PMID:24959617
Analysis of estimation algorithms for CDTI and CAS applications
NASA Technical Reports Server (NTRS)
Goka, T.
1985-01-01
Estimation algorithms for Cockpit Display of Traffic Information (CDTI) and Collision Avoidance System (CAS) applications were analyzed and/or developed. The algorithms are based on actual or projected operational and performance characteristics of an Enhanced TCAS II traffic sensor developed by Bendix and the Federal Aviation Administration. Three algorithm areas are examined and discussed. These are horizontal x and y, range and altitude estimation algorithms. Raw estimation errors are quantified using Monte Carlo simulations developed for each application; the raw errors are then used to infer impacts on the CDTI and CAS applications. Applications of smoothing algorithms to CDTI problems are also discussed briefly. Technical conclusions are summarized based on the analysis of simulation results.
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.
Quantum defragmentation algorithm
Burgarth, Daniel; Giovannetti, Vittorio
2010-08-15
In this addendum to our paper [D. Burgarth and V. Giovannetti, Phys. Rev. Lett. 99, 100501 (2007)] we prove that during the transformation that allows one to enforce control by relaxation on a quantum system, the ancillary memory can be kept at a finite size, independently from the fidelity one wants to achieve. The result is obtained by introducing the quantum analog of defragmentation algorithms which are employed for efficiently reorganizing classical information in conventional hard disks.
NASA Astrophysics Data System (ADS)
Nardi, Jerry
The Satellite Aided Search and Rescue (Sarsat) is designed to detect and locate distress beacons using satellite receivers. Algorithms used for calculating the positions of 406 MHz beacons and 121.5/243 MHz beacons are presented. The techniques for matching, resolving and averaging calculated locations from multiple satellite passes are also described along with results pertaining to single pass and multiple pass location estimate accuracy.
Algorithms for builder guidelines
Balcomb, J.D.; Lekov, A.B.
1989-06-01
The Builder Guidelines are designed to make simple, appropriate guidelines available to builders for their specific localities. Builders may select from passive solar and conservation strategies with different performance potentials. They can then compare the calculated results for their particular house design with a typical house in the same location. Algorithms used to develop the Builder Guidelines are described. The main algorithms used are the monthly solar ratio (SLR) method for winter heating, the diurnal heat capacity (DHC) method for temperature swing, and a new simplified calculation method (McCool) for summer cooling. This paper applies the algorithms to estimate the performance potential of passive solar strategies, and the annual heating and cooling loads of various combinations of conservation and passive solar strategies. The basis of the McCool method is described. All three methods are implemented in a microcomputer program used to generate the guideline numbers. Guidelines for Denver, Colorado, are used to illustrate the results. The structure of the guidelines and worksheet booklets are also presented. 5 refs., 3 tabs.
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.
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. PMID:24260766
Developing dataflow algorithms
Hiromoto, R.E. ); Bohm, A.P.W. . Dept. of Computer Science)
1991-01-01
Our goal is to study the performance of a collection of numerical algorithms written in Id which is available to users of Motorola's dataflow machine Monsoon. We will study the dataflow performance of these implementations first under the parallel profiling simulator Id World, and second in comparison with actual dataflow execution on the Motorola Monsoon. This approach will allow us to follow the computational and structural details of the parallel algorithms as implemented on dataflow systems. When running our programs on the Id World simulator we will examine the behaviour of algorithms at dataflow graph level, where each instruction takes one timestep and data becomes available at the next. This implies that important machine level phenomena such as the effect that global communication time may have on the computation are not addressed. These phenomena will be addressed when we run our programs on the Monsoon hardware. Potential ramifications for compilation techniques, functional programming style, and program efficiency are significant to this study. In a later stage of our research we will compare the efficiency of Id programs to programs written in other languages. This comparison will be of a rather qualitative nature as there are too many degrees of freedom in a language implementation for a quantitative comparison to be of interest. We begin our study by examining one routine that exhibit different computational characteristics. This routine and its corresponding characteristics is Fast Fourier Transforms; computational parallelism and data dependences between the butterfly shuffles.
A constrained optimization algorithm based on the simplex search method
NASA Astrophysics Data System (ADS)
Mehta, Vivek Kumar; Dasgupta, Bhaskar
2012-05-01
In this article, a robust method is presented for handling constraints with the Nelder and Mead simplex search method, which is a direct search algorithm for multidimensional unconstrained optimization. The proposed method is free from the limitations of previous attempts that demand the initial simplex to be feasible or a projection of infeasible points to the nonlinear constraint boundaries. The method is tested on several benchmark problems and the results are compared with various evolutionary algorithms available in the literature. The proposed method is found to be competitive with respect to the existing algorithms in terms of effectiveness and efficiency.
Algorithm implementation on the Navier-Stokes computer
NASA Technical Reports Server (NTRS)
Krist, Steven E.; Zang, Thomas A.
1987-01-01
The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.
An active set algorithm for nonlinear optimization with polyhedral constraints
NASA Astrophysics Data System (ADS)
Hager, William W.; Zhang, Hongchao
2016-08-01
A polyhedral active set algorithm PASA is developed for solving a nonlinear optimization problem whose feasible set is a polyhedron. Phase one of the algorithm is the gradient projection method, while phase two is any algorithm for solving a linearly constrained optimization problem. Rules are provided for branching between the two phases. Global convergence to a stationary point is established, while asymptotically PASA performs only phase two when either a nondegeneracy assumption holds, or the active constraints are linearly independent and a strong second-order sufficient optimality condition holds.
Ray-tracing-based reconstruction algorithms for digital breast tomosynthesis
NASA Astrophysics Data System (ADS)
Zhou, Weihua; Lu, Jianping; Zhou, Otto; Chen, Ying
2015-03-01
As a breast-imaging technique, digital breast tomosynthesis has great potential to improve the diagnosis of early breast cancer over mammography. Ray-tracing-based reconstruction algorithms, such as ray-tracing back projection, maximum-likelihood expectation maximization (MLEM), ordered-subset MLEM (OS-MLEM), and simultaneous algebraic reconstruction technique (SART), have been developed as reconstruction methods for different breast tomosynthesis systems. This paper provides a comparative study to investigate these algorithms by computer simulation and phantom study. Experimental results suggested that, among the four investigated reconstruction algorithms, OS-MLEM and SART performed better in interplane artifact removal with a fast speed convergence.
Exact fan-beam and 4{pi}-acquisition cone-beam SPECT algorithms with uniform attenuation correction
Tang Qiulin; Zeng, Gengsheng L.; Wu Jiansheng; Gullberg, Grant T.
2005-11-15
This paper presents analytical fan-beam and cone-beam reconstruction algorithms that compensate for uniform attenuation in single photon emission computed tomography. First, a fan-beam algorithm is developed by obtaining a relationship between the two-dimensional (2D) Fourier transform of parallel-beam projections and fan-beam projections. Using this relationship, 2D Fourier transforms of equivalent parallel-beam projection data are obtained from the fan-beam projection data. Then a quasioptimal analytical reconstruction algorithm for uniformly attenuated Radon data, developed by Metz and Pan, is used to reconstruct the image. A cone-beam algorithm is developed by extending the fan-beam algorithm to 4{pi} solid angle geometry. The cone-beam algorithm is also an exact algorithm.
The systems biology simulation core algorithm
2013-01-01
Background With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases. Results This article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database. Conclusions The formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code, binaries, and documentation can be freely obtained under the terms of the LGPL version 3 from http://simulation-core.sourceforge.net. Feature requests, bug reports, contributions, or any further discussion can be directed to the mailing list simulation-core-development@lists.sourceforge.net. PMID:23826941
Linear scaling algorithms: Progress and promise
Stechel, E.B.
1996-08-01
The goal of this laboratory-directed research and development (LDRD) project was to develop a new and efficient electronic structure algorithm that would scale linearly with system size. Since the start of the program this field has received much attention in the literature as well as in terms of focused symposia and at least one dedicated international workshop. The major success of this program is the development of a unique algorithm for minimization of the density functional energy which replaces the diagonalization of the Kohn-Sham hamiltonian with block diagonalization into explicit occupied and partially occupied (in metals) subspaces and an implicit unoccupied subspace. The progress reported here represents an important step toward the simultaneous goals of linear scaling, controlled accuracy, efficiency and transferability. The method is specifically designed to deal with localized, non-orthogonal basis sets to maximize transferability and state by state iteration to minimize any charge-sloshing instabilities and accelerate convergence. The computational demands of the algorithm do scale as the particle number, permitting applications to problems involving many inequivalent atoms. Our targeted goal is at least 10,000 inequivalent atoms on a teraflop computer. This report describes our algorithm, some proof-of-principle examples and a state of the field at the conclusion of this LDRD.
Design of robust systolic algorithms
Varman, P.J.; Fussell, D.S.
1983-01-01
A primary reason for the susceptibility of systolic algorithms to faults is their strong dependence on the interconnection between the processors in a systolic array. A technique to transform any linear systolic algorithm into an equivalent pipelined algorithm that executes on arbitrary trees is presented. 5 references.
High-performance combinatorial algorithms
Pinar, Ali
2003-10-31
Combinatorial algorithms have long played an important role in many applications of scientific computing such as sparse matrix computations and parallel computing. The growing importance of combinatorial algorithms in emerging applications like computational biology and scientific data mining calls for development of a high performance library for combinatorial algorithms. Building such a library requires a new structure for combinatorial algorithms research that enables fast implementation of new algorithms. We propose a structure for combinatorial algorithms research that mimics the research structure of numerical algorithms. Numerical algorithms research is nicely complemented with high performance libraries, and this can be attributed to the fact that there are only a small number of fundamental problems that underlie numerical solvers. Furthermore there are only a handful of kernels that enable implementation of algorithms for these fundamental problems. Building a similar structure for combinatorial algorithms will enable efficient implementations for existing algorithms and fast implementation of new algorithms. Our results will promote utilization of combinatorial techniques and will impact research in many scientific computing applications, some of which are listed.
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.
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.
Polynomial Algorithms for Item Matching.
ERIC Educational Resources Information Center
Armstrong, Ronald D.; Jones, Douglas H.
1992-01-01
Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)
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)
Fast algorithms for transport models. Technical progress report
Manteuffel, T.A.
1992-12-01
The objective of this project is the development of numerical solution techniques for deterministic models of the transport of neutral and charged particles and the demonstration of their effectiveness in both a production environment and on advanced architecture computers. The primary focus is on various versions of the linear Boltzman equation. These equations are fundamental in many important applications. This project is an attempt to integrate the development of numerical algorithms with the process of developing production software. A major thrust of this reject will be the implementation of these algorithms on advanced architecture machines that reside at the Advanced Computing Laboratory (ACL) at Los Alamos National Laboratories (LANL).
An Assessment of Current Satellite Precipitation Algorithms
NASA Technical Reports Server (NTRS)
Smith, Eric A.
2007-01-01
The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.
Algorithmic commonalities in the parallel environment
NASA Technical Reports Server (NTRS)
Mcanulty, Michael A.; Wainer, Michael S.
1987-01-01
The ultimate aim of this project was to analyze procedures from substantially different application areas to discover what is either common or peculiar in the process of conversion to the Massively Parallel Processor (MPP). Three areas were identified: molecular dynamic simulation, production systems (rule systems), and various graphics and vision algorithms. To date, only selected graphics procedures have been investigated. They are the most readily available, and produce the most visible results. These include simple polygon patch rendering, raycasting against a constructive solid geometric model, and stochastic or fractal based textured surface algorithms. Only the simplest of conversion strategies, mapping a major loop to the array, has been investigated so far. It is not entirely satisfactory.
Improved multiprocessor garbage collection algorithms
Newman, I.A.; Stallard, R.P.; Woodward, M.C.
1983-01-01
Outlines the results of an investigation of existing multiprocessor garbage collection algorithms and introduces two new algorithms which significantly improve some aspects of the performance of their predecessors. The two algorithms arise from different starting assumptions. One considers the case where the algorithm will terminate successfully whatever list structure is being processed and assumes that the extra data space should be minimised. The other seeks a very fast garbage collection time for list structures that do not contain loops. Results of both theoretical and experimental investigations are given to demonstrate the efficacy of the algorithms. 7 references.
Efficient multicomponent fuel algorithm
NASA Astrophysics Data System (ADS)
Torres, D. J.; O'Rourke, P. J.; Amsden, A. A.
2003-03-01
We derive equations for multicomponent fuel evaporation in airborne fuel droplets and wall films, and implement the model into KIVA-3V. Temporal and spatial variations in liquid droplet composition and temperature are not modelled but solved for by discretizing the interior of the droplet in an implicit and computationally efficient way. We find that an interior discretization is necessary to correctly compute the evolution of the droplet composition. The details of the one-dimensional numerical algorithm are described. Numerical simulations of multicomponent evaporation are performed for single droplets and compared to experimental data.
NASA Technical Reports Server (NTRS)
Vardi, A.
1984-01-01
The representation min t s.t. F(I)(x). - t less than or equal to 0 for all i is examined. An active set strategy is designed of functions: active, semi-active, and non-active. This technique will help in preventing zigzagging which often occurs when an active set strategy is used. Some of the inequality constraints are handled with slack variables. Also a trust region strategy is used in which at each iteration there is a sphere around the current point in which the local approximation of the function is trusted. The algorithm is implemented into a successful computer program. Numerical results are provided.
Reliability measure for segmenting algorithms
NASA Astrophysics Data System (ADS)
Alvarez, Robert E.
2004-05-01
Segmenting is a key initial step in many computer-aided detection (CAD) systems. Our purpose is to develop a method to estimate the reliability of segmenting algorithm results. We use a statistical shape model computed using principal component analysis. The model retains a small number of eigenvectors, or modes, that represent a large fraction of the variance. The residuals between the segmenting result and its projection into the space of retained modes are computed. The sum of the squares of residuals is transformed to a zero-mean, unit standard deviation Gaussian random variable. We also use the standardized scale parameter. The reliability measure is the probability that the transformed residuals and scale parameter are greater than the absolute value of the observed values. We tested the reliability measure with thirty chest x-ray images with "leave-out-one" testing. The Gaussian assumption was verified using normal probability plots. For each image, a statistical shape model was computed from the hand-digitized data of the rest of the images in the training set. The residuals and scale parameter with automated segment results for the image were used to compute the reliability measure in each case. The reliability measure was significantly lower for two images in the training set with unusual lung fields or processing errors. The data and Matlab scripts for reproducing the figures are at http://www.aprendtech.com/papers/relmsr.zip Errors detected by the new reliability measure can be used to adjust processing or warn the user.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Owen, Mark W.; Stubberud, Allen R.
2003-12-01
Highly maneuvering threats are a major concern for the Navy and the DoD and the technology discussed in this paper is intended to help address this issue. A neural extended Kalman filter algorithm has been embedded in an interacting multiple model architecture for target tracking. The neural extended Kalman filter algorithm is used to improve motion model prediction during maneuvers. With a better target motion mode, noise reduction can be achieved through a maneuver. Unlike the interacting multiple model architecture which uses a high process noise model to hold a target through a maneuver with poor velocity and acceleration estimates, a neural extended Kalman filter is used to predict corrections to the velocity and acceleration states of a target through a maneuver. The neural extended Kalman filter estimates the weights of a neural network, which in turn are used to modify the state estimate predictions of the filter as measurements are processed. The neural network training is performed on-line as data is processed. In this paper, the simulation results of a tracking problem using a neural extended Kalman filter embedded in an interacting multiple model tracking architecture are shown. Preliminary results on the 2nd Benchmark Problem are also given.
NASA Astrophysics Data System (ADS)
Owen, Mark W.; Stubberud, Allen R.
2004-01-01
Highly maneuvering threats are a major concern for the Navy and the DoD and the technology discussed in this paper is intended to help address this issue. A neural extended Kalman filter algorithm has been embedded in an interacting multiple model architecture for target tracking. The neural extended Kalman filter algorithm is used to improve motion model prediction during maneuvers. With a better target motion mode, noise reduction can be achieved through a maneuver. Unlike the interacting multiple model architecture which uses a high process noise model to hold a target through a maneuver with poor velocity and acceleration estimates, a neural extended Kalman filter is used to predict corrections to the velocity and acceleration states of a target through a maneuver. The neural extended Kalman filter estimates the weights of a neural network, which in turn are used to modify the state estimate predictions of the filter as measurements are processed. The neural network training is performed on-line as data is processed. In this paper, the simulation results of a tracking problem using a neural extended Kalman filter embedded in an interacting multiple model tracking architecture are shown. Preliminary results on the 2nd Benchmark Problem are also given.
Algorithms to Automate LCLS Undulator Tuning
Wolf, Zachary
2010-12-03
Automation of the LCLS undulator tuning offers many advantages to the project. Automation can make a substantial reduction in the amount of time the tuning takes. Undulator tuning is fairly complex and automation can make the final tuning less dependent on the skill of the operator. Also, algorithms are fixed and can be scrutinized and reviewed, as opposed to an individual doing the tuning by hand. This note presents algorithms implemented in a computer program written for LCLS undulator tuning. The LCLS undulators must meet the following specifications. The maximum trajectory walkoff must be less than 5 {micro}m over 10 m. The first field integral must be below 40 x 10{sup -6} Tm. The second field integral must be below 50 x 10{sup -6} Tm{sup 2}. The phase error between the electron motion and the radiation field must be less than 10 degrees in an undulator. The K parameter must have the value of 3.5000 {+-} 0.0005. The phase matching from the break regions into the undulator must be accurate to better than 10 degrees. A phase change of 113 x 2{pi} must take place over a distance of 3.656 m centered on the undulator. Achieving these requirements is the goal of the tuning process. Most of the tuning is done with Hall probe measurements. The field integrals are checked using long coil measurements. An analysis program written in Matlab takes the Hall probe measurements and computes the trajectories, phase errors, K value, etc. The analysis program and its calculation techniques were described in a previous note. In this note, a second Matlab program containing tuning algorithms is described. The algorithms to determine the required number and placement of the shims are discussed in detail. This note describes the operation of a computer program which was written to automate LCLS undulator tuning. The algorithms used to compute the shim sizes and locations are discussed.
ERIC Educational Resources Information Center
Textor, Martin R.
2005-01-01
The great educational value of projects is emphasized by contrasting negative aspects of the life of today's children with the goals of project work. This is illustrated by a project "Shopping." It is shown what children are learning in such projects and what the advantages of project work are. Relevant topic areas, criteria for selecting a…
An image processing algorithm for PPCR imaging
NASA Astrophysics Data System (ADS)
Cowen, Arnold R.; Giles, Anthony; Davies, Andrew G.; Workman, A.
1993-09-01
During 1990 The UK Department of Health installed two Photostimulable Phosphor Computed Radiography (PPCR) systems in the General Infirmary at Leeds with a view to evaluating the clinical and physical performance of the technology prior to its introduction into the NHS. An issue that came to light from the outset of the projects was the radiologists reservations about the influence of the standard PPCR computerized image processing on image quality and diagnostic performance. An investigation was set up by FAXIL to develop an algorithm to produce single format high quality PPCR images that would be easy to implement and allay the concerns of radiologists.
An innovative localisation algorithm for railway vehicles
NASA Astrophysics Data System (ADS)
Allotta, B.; D'Adamio, P.; Malvezzi, M.; Pugi, L.; Ridolfi, A.; Rindi, A.; Vettori, G.
2014-11-01
In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the Italian Sistema Controllo Marcia Treno (SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and an Inertial Measurements Unit (IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements
JPSS CGS Tools For Rapid Algorithm Updates
NASA Astrophysics Data System (ADS)
Smith, D. C.; Grant, K. D.
2011-12-01
The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather and environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will contribute the afternoon orbit component and ground processing system of the restructured National Polar-orbiting Operational Environmental Satellite System (NPOESS). As such, JPSS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the ground processing component of both POES and the Defense Meteorological Satellite Program (DMSP) replacement known as the Defense Weather Satellite System (DWSS), managed by the Department of Defense (DoD). The JPSS satellites will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for JPSS is known as the JPSS Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS). Both are developed by Raytheon Intelligence and Information Systems (IIS). The Interface Data Processing Segment will process NPOESS Preparatory Project, Joint Polar Satellite System and Defense Weather Satellite System satellite data to provide environmental data products to NOAA and DoD processing centers operated by the United States government. Under NPOESS, Northrop Grumman Aerospace Systems Algorithms and Data Products (A&DP) organization was responsible for the algorithms that produce the EDRs, including their quality aspects. For JPSS, that responsibility has transferred to NOAA's Center for Satellite Applications & Research (STAR). As the Calibration and Validation (Cal/Val) activities move forward following both the NPP launch and subsequent JPSS and DWSS launches, rapid algorithm updates may be required. Raytheon and
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.
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
Totally parallel multilevel algorithms for sparse elliptic systems
NASA Technical Reports Server (NTRS)
Frederickson, Paul O.
1989-01-01
The fastest known algorithms for the solution of a large elliptic boundary value problem on a massively parallel hypercube all require O(log(n)) floating point operations and O(log(n)) distance-1 communications, if massively parallel is defined to mean a number of processors proportional to the size n of the problem. The Totally Parallel Multilevel Algorithm (TPMA) that has, as special cases, four of these fast algorithms is described. These four algorithms are Parallel Superconvergent Multigrid (PSMG), Robust Multigrid, the Fast Fourier Transformation (FFT) based Spectral Algorithm, and Parallel Cyclic Reduction. The algorithm TPMA, when described recursively, has four steps: (1) project to a collection of interlaced, coarser problems at the next lower level; (2) apply TPMA, recursively, to each of these lower level problems, solving directly at the lowest level; (3) interpolate these approximate solutions to the finer grid, and to verage them to form an approximate solution on this grid; and (4) refine this approximate solution with a defect-correction step, using a local approximate inverse. Choice of the projection operator (P), the interpolation operator (Q), and the smoother (S) determines the class of problems on which TPMA is most effective. There are special cases in which the first three steps produce an exact solution, and the smoother is not needed (e.g., constant coefficient operators).
A Novel Latin Hypercube Algorithm via Translational Propagation
Pan, Guang; Ye, Pengcheng
2014-01-01
Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is directly related to the experimental designs used. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. However, the high cost in constructing them limits their use. In this paper, a methodology for creating novel Latin hypercube designs via translational propagation and successive local enumeration algorithm (TPSLE) is developed without using formal optimization. TPSLE algorithm is based on the inspiration that a near optimal Latin Hypercube design can be constructed by a simple initial block with a few points generated by algorithm SLE as a building block. In fact, TPSLE algorithm offers a balanced trade-off between the efficiency and sampling performance. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time and has acceptable space-filling and projective properties. PMID:25276844
A Novel Latin hypercube algorithm via translational propagation.
Pan, Guang; Ye, Pengcheng; Wang, Peng
2014-01-01
Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is directly related to the experimental designs used. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. However, the high cost in constructing them limits their use. In this paper, a methodology for creating novel Latin hypercube designs via translational propagation and successive local enumeration algorithm (TPSLE) is developed without using formal optimization. TPSLE algorithm is based on the inspiration that a near optimal Latin Hypercube design can be constructed by a simple initial block with a few points generated by algorithm SLE as a building block. In fact, TPSLE algorithm offers a balanced trade-off between the efficiency and sampling performance. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time and has acceptable space-filling and projective properties. PMID:25276844
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.
Trial encoding algorithms ensemble.
Cheng, Lipin Bill; Yeh, Ren Jye
2013-01-01
This paper proposes trial algorithms for some basic components in cryptography and lossless bit compression. The symmetric encryption is accomplished by mixing up randomizations and scrambling with hashing of the key playing an essential role. The digital signature is adapted from the Hill cipher with the verification key matrices incorporating un-invertible parts to hide the signature matrix. The hash is a straight running summation (addition chain) of data bytes plus some randomization. One simplified version can be burst error correcting code. The lossless bit compressor is the Shannon-Fano coding that is less optimal than the later Huffman and Arithmetic coding, but can be conveniently implemented without the use of a tree structure and improvable with bytes concatenation. PMID:27057475
Faster tomographic fan-beam back-projection using Cartesian axes pre-projection
NASA Astrophysics Data System (ADS)
Davis, G. R.
1998-02-01
The convolution back-projection algorithm is the most common method for reconstructing images from complete sets of fan-beam projections. For each pixel and for every projection, the interception point on the detector array must be determined and a weighted value from the appropriate point on the filtered back projection added. Thus the number of operations required is of order n2p, where n is the number of points per projection, and p the number of projections. This can mean a considerable computation time, even with modern, fast computer workstations. The complexity of each pixel operation (weighting and geometric computations) is reduced if the projection is first pre-projected onto one or other of the Cartesian axes. This has been demonstrated to reduce the computational time by a factor of 2, with no loss of accuracy, when compared with a highly optimised implementation of the conventional fan-beam back-projection algorithm.
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.
Projection-resolved optical coherence tomographic angiography
Zhang, Miao; Hwang, Thomas S.; Campbell, J. Peter; Bailey, Steven T.; Wilson, David J.; Huang, David; Jia, Yali
2016-01-01
Shadowgraphic projection artifacts from superficial vasculature interfere with the visualization of deeper vascular networks in optical coherence tomography angiography (OCT-A). We developed a novel algorithm to remove this artifact by resolving the ambiguity between in situ and projected flow signals. The algorithm identifies voxels with in situ flow as those where intensity-normalized decorrelation values are higher than all shallower voxels in the same axial scan line. This “projection-resolved” (PR) algorithm effectively suppressed the projection artifact on both en face and cross-sectional angiograms and enhanced depth resolution of vascular networks. In the human macula, the enhanced angiograms show three distinct vascular plexuses in the inner retina and no vessels in the outer retina. We demonstrate that PR OCT-A cleanly removes flow projection from the normally avascular outer retinal slab while preserving the density and continuity of the intermediate and deep retinal capillary plexuses. PMID:27231591
Ozone Uncertainties Study Algorithm (OUSA)
NASA Technical Reports Server (NTRS)
Bahethi, O. P.
1982-01-01
An algorithm to carry out sensitivities, uncertainties and overall imprecision studies to a set of input parameters for a one dimensional steady ozone photochemistry model is described. This algorithm can be used to evaluate steady state perturbations due to point source or distributed ejection of H2O, CLX, and NOx, besides, varying the incident solar flux. This algorithm is operational on IBM OS/360-91 computer at NASA/Goddard Space Flight Center's Science and Applications Computer Center (SACC).
Ozone Uncertainties Study Algorithm (OUSA)
NASA Astrophysics Data System (ADS)
Bahethi, O. P.
An algorithm to carry out sensitivities, uncertainties and overall imprecision studies to a set of input parameters for a one dimensional steady ozone photochemistry model is described. This algorithm can be used to evaluate steady state perturbations due to point source or distributed ejection of H2O, CLX, and NOx, besides, varying the incident solar flux. This algorithm is operational on IBM OS/360-91 computer at NASA/Goddard Space Flight Center's Science and Applications Computer Center (SACC).
Neurons to algorithms LDRD final report.
Rothganger, Fredrick H.; Aimone, James Bradley; Warrender, Christina E.; Trumbo, Derek
2013-09-01
Over the last three years the Neurons to Algorithms (N2A) LDRD project teams has built infrastructure to discover computational structures in the brain. This consists of a modeling language, a tool that enables model development and simulation in that language, and initial connections with the Neuroinformatics community, a group working toward similar goals. The approach of N2A is to express large complex systems like the brain as populations of a discrete part types that have specific structural relationships with each other, along with internal and structural dynamics. Such an evolving mathematical system may be able to capture the essence of neural processing, and ultimately of thought itself. This final report is a cover for the actual products of the project: the N2A Language Specification, the N2A Application, and a journal paper summarizing our methods.
Image reconstruction algorithms with wavelet filtering for optoacoustic imaging
NASA Astrophysics Data System (ADS)
Gawali, S.; Leggio, L.; Broadway, C.; González, P.; Sánchez, M.; Rodríguez, S.; Lamela, H.
2016-03-01
Optoacoustic imaging (OAI) is a hybrid biomedical imaging modality based on the generation and detection of ultrasound by illuminating the target tissue by laser light. Typically, laser light in visible or near infrared spectrum is used as an excitation source. OAI is based on the implementation of image reconstruction algorithms using the spatial distribution of optical absorption in tissues. In this work, we apply a time-domain back-projection (BP) reconstruction algorithm and a wavelet filtering for point and line detection, respectively. A comparative study between point detection and integrated line detection has been carried out by evaluating their effects on the image reconstructed. Our results demonstrate that the back-projection algorithm proposed is efficient for reconstructing high-resolution images of absorbing spheres embedded in a non-absorbing medium when it is combined with the wavelet filtering.
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.
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.
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.
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. PMID:23829722
Variable Selection using MM Algorithms
Hunter, David R.; Li, Runze
2009-01-01
Variable selection is fundamental to high-dimensional statistical modeling. Many variable selection techniques may be implemented by maximum penalized likelihood using various penalty functions. Optimizing the penalized likelihood function is often challenging because it may be nondifferentiable and/or nonconcave. This article proposes a new class of algorithms for finding a maximizer of the penalized likelihood for a broad class of penalty functions. These algorithms operate by perturbing the penalty function slightly to render it differentiable, then optimizing this differentiable function using a minorize-maximize (MM) algorithm. MM algorithms are useful extensions of the well-known class of EM algorithms, a fact that allows us to analyze the local and global convergence of the proposed algorithm using some of the techniques employed for EM algorithms. In particular, we prove that when our MM algorithms converge, they must converge to a desirable point; we also discuss conditions under which this convergence may be guaranteed. We exploit the Newton-Raphson-like aspect of these algorithms to propose a sandwich estimator for the standard errors of the estimators. Our method performs well in numerical tests. PMID:19458786
An accelerated and convergent iterative algorithm in image reconstruction
NASA Astrophysics Data System (ADS)
Yan, Jianhua; Yu, Jun
2007-05-01
Positron emission tomography (PET) is becoming increasingly important in the field of medicine and biology. The maximum-likelihood expectation-maximization (ML-EM) algorithm is becoming more important than filtered back-projection (FBP) algorithm which can incorporate various physical models into image reconstruction scheme. However, ML-EM converges slowly. In this paper, we propose a new algorithm named AC-ML-EM (accelerated and convergent maximum likelihood expectation maximization) by introducing gradually decreasing correction factor into ML-EM. AC-ML-EM has a higher speed of convergence. Through the experiments of computer simulated phantom data and real phantom data, AC-ML-EM is shown faster and better quantitatively than conventional ML-EM algorithm.
Managing and learning with multiple models: Objectives and optimization algorithms
Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.
2011-01-01
The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.
Valence-bond quantum Monte Carlo algorithms defined on trees.
Deschner, Andreas; Sørensen, Erik S
2014-09-01
We present a class of algorithms for performing valence-bond quantum Monte Carlo of quantum spin models. Valence-bond quantum Monte Carlo is a projective T=0 Monte Carlo method based on sampling of a set of operator strings that can be viewed as forming a treelike structure. The algorithms presented here utilize the notion of a worm that moves up and down this tree and changes the associated operator string. In quite general terms, we derive a set of equations whose solutions correspond to a whole class of algorithms. As specific examples of this class of algorithms, we focus on two cases. The bouncing worm algorithm, for which updates are always accepted by allowing the worm to bounce up and down the tree, and the driven worm algorithm, where a single parameter controls how far up the tree the worm reaches before turning around. The latter algorithm involves only a single bounce where the worm turns from going up the tree to going down. The presence of the control parameter necessitates the introduction of an acceptance probability for the update. PMID:25314561
Multicenter evaluation of signal enhancement algorithms for hearing aids.
Luts, Heleen; Eneman, Koen; Wouters, Jan; Schulte, Michael; Vormann, Matthias; Buechler, Michael; Dillier, Norbert; Houben, Rolph; Dreschler, Wouter A; Froehlich, Matthias; Puder, Henning; Grimm, Giso; Hohmann, Volker; Leijon, Arne; Lombard, Anthony; Mauler, Dirk; Spriet, Ann
2010-03-01
In the framework of the European HearCom project, promising signal enhancement algorithms were developed and evaluated for future use in hearing instruments. To assess the algorithms' performance, five of the algorithms were selected and implemented on a common real-time hardware/software platform. Four test centers in Belgium, The Netherlands, Germany, and Switzerland perceptually evaluated the algorithms. Listening tests were performed with large numbers of normal-hearing and hearing-impaired subjects. Three perceptual measures were used: speech reception threshold (SRT), listening effort scaling, and preference rating. Tests were carried out in two types of rooms. Speech was presented in multitalker babble arriving from one or three loudspeakers. In a pseudo-diffuse noise scenario, only one algorithm, the spatially preprocessed speech-distortion-weighted multi-channel Wiener filtering, provided a SRT improvement relative to the unprocessed condition. Despite the general lack of improvement in SRT, some algorithms were preferred over the unprocessed condition at all tested signal-to-noise ratios (SNRs). These effects were found across different subject groups and test sites. The listening effort scores were less consistent over test sites. For the algorithms that did not affect speech intelligibility, a reduction in listening effort was observed at 0 dB SNR. PMID:20329849
PCA-LBG-based algorithms for VQ codebook generation
NASA Astrophysics Data System (ADS)
Tsai, Jinn-Tsong; Yang, Po-Yuan
2015-04-01
Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.
Efficient iterative image reconstruction algorithm for dedicated breast CT
NASA Astrophysics Data System (ADS)
Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan
2016-03-01
Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.
ERIC Educational Resources Information Center
Patton, Bob
Vocational agriculture teachers in Oklahoma prepared the shop project drawings which comprise the document. Seventy-one projects, with lists of required materials, diagrams, and measurements, are included. Construction projects fall into six categories (number of projects in parentheses): Trailers (5), racks (3), livestock production projects…
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.
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.
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.
ERIC Educational Resources Information Center
Coscarelli, William C.
This study, part of an instructional development project, explores the effects of three different representations of functional algorithms in an introductory chemistry laboratory. Intact classes were randomly assigned to a flowchart, list, or standard prose representation of the procedures (algorithms). At the completion of 11 laboratory sessions,…
NASA Technical Reports Server (NTRS)
Schultz, Christopher J.; Carey, Larry; Cecil, Dan; Bateman, Monte; Stano, Geoffrey; Goodman, Steve
2012-01-01
Objective of project is to refine, adapt and demonstrate the Lightning Jump Algorithm (LJA) for transition to GOES -R GLM (Geostationary Lightning Mapper) readiness and to establish a path to operations Ongoing work . reducing risk in GLM lightning proxy, cell tracking, LJA algorithm automation, and data fusion (e.g., radar + lightning).
An algorithm for fast DNS cavitating flows simulations using homogeneous mixture approach
NASA Astrophysics Data System (ADS)
Žnidarčič, A.; Coutier-Delgosha, O.; Marquillie, M.; Dular, M.
2015-12-01
A new algorithm for fast DNS cavitating flows simulations is developed. The algorithm is based on Kim and Moin projection method form. Homogeneous mixture approach with transport equation for vapour volume fraction is used to model cavitation and various cavitation models can be used. Influence matrix and matrix diagonalisation technique enable fast parallel computations.
Testing Algorithmic Skills in Traditional and Non-Traditional Programming Environments
ERIC Educational Resources Information Center
Csernoch, Mária; Biró, Piroska; Máth, János; Abari, Kálmán
2015-01-01
The Testing Algorithmic and Application Skills (TAaAS) project was launched in the 2011/2012 academic year to test first year students of Informatics, focusing on their algorithmic skills in traditional and non-traditional programming environments, and on the transference of their knowledge of Informatics from secondary to tertiary education. The…
Content addressable memory project
NASA Technical Reports Server (NTRS)
Hall, Josh; Levy, Saul; Smith, D.; Wei, S.; Miyake, K.; Murdocca, M.
1991-01-01
The progress on the Rutgers CAM (Content Addressable Memory) Project is described. The overall design of the system is completed at the architectural level and described. The machine is composed of two kinds of cells: (1) the CAM cells which include both memory and processor, and support local processing within each cell; and (2) the tree cells, which have smaller instruction set, and provide global processing over the CAM cells. A parameterized design of the basic CAM cell is completed. Progress was made on the final specification of the CPS. The machine architecture was driven by the design of algorithms whose requirements are reflected in the resulted instruction set(s). A few of these algorithms are described.
Parallel vision algorithms. Annual technical report No. 2, 1 October 1987-28 December 1988
Ibrahim, H.A.; Kender, J.R.; Brown, L.G.
1989-01-01
This Second Annual Technical Report covers the project activities during the period from October 1, 1987 through December 31, 1988. The objective of this project is to develop and implement, on highly parallel computers, vision algorithms that combine stereo, texture, and multi-resolution techniques for determining local surface orientation and depth. Such algorithms can serve as front-end components of autonomous land-vehicle vision systems. During the second year of the project, efforts concentrated on the following: first, implementing and testing on the Connection Machine the parallel programming environment that will be used to develop, implement and test our parallel vision algorithms; second, implementing and testing primitives for the multi-resolution stereo and texture algorithms, in this environment. Also, efforts were continued to refine techniques used in the texture algorithms, and to develop a system that integrates information from several shape-from-texture methods. This report describes the status and progress of these efforts. The authors describe first the programming environment implementation, and how to use it. They summarize the results for multi-resolution based depth-interpolation algorithms on parallel architectures. Then, they present algorithms and test results for the texture algorithms. Finally, the results of the efforts of integrating information from various shape-from-texture algorithms are presented.
The Chopthin Algorithm for Resampling
NASA Astrophysics Data System (ADS)
Gandy, Axel; Lau, F. Din-Houn
2016-08-01
Resampling is a standard step in particle filters and more generally sequential Monte Carlo methods. We present an algorithm, called chopthin, for resampling weighted particles. In contrast to standard resampling methods the algorithm does not produce a set of equally weighted particles; instead it merely enforces an upper bound on the ratio between the weights. Simulation studies show that the chopthin algorithm consistently outperforms standard resampling methods. The algorithms chops up particles with large weight and thins out particles with low weight, hence its name. It implicitly guarantees a lower bound on the effective sample size. The algorithm can be implemented efficiently, making it practically useful. We show that the expected computational effort is linear in the number of particles. Implementations for C++, R (on CRAN), Python and Matlab are available.
CORDIC algorithms in four dimensions
NASA Astrophysics Data System (ADS)
Delosme, Jean-Marc; Hsiao, Shen-Fu
1990-11-01
CORDIC algorithms offer an attractive alternative to multiply-and-add based algorithms for the implementation of two-dimensional rotations preserving either norm: (x2 + 2) or (x2 _ y2)/2 Indeed these norms whose computation is a significant part of the evaluation of the two-dimensional rotations are computed much more easily by the CORDIC algorithms. However the part played by norm computations in the evaluation of rotations becomes quickly small as the dimension of the space increases. Thus in spaces of dimension 5 or more there is no practical alternative to multiply-and-add based algorithms. In the intermediate region dimensions 3 and 4 extensions of the CORDIC algorithms are an interesting option. The four-dimensional extensions are particularly elegant and are the main object of this paper.
Cubit Adaptive Meshing Algorithm Library
2004-09-01
CAMAL (Cubit adaptive meshing algorithm library) is a software component library for mesh generation. CAMAL 2.0 includes components for triangle, quad and tetrahedral meshing. A simple Application Programmers Interface (API) takes a discrete boundary definition and CAMAL computes a quality interior unstructured grid. The triangle and quad algorithms may also import a geometric definition of a surface on which to define the grid. CAMALs triangle meshing uses a 3D space advancing front method, the quadmore » meshing algorithm is based upon Sandias patented paving algorithm and the tetrahedral meshing algorithm employs the GHS3D-Tetmesh component developed by INRIA, France.« less
Testing an earthquake prediction algorithm
Kossobokov, V.G.; Healy, J.H.; Dewey, J.W.
1997-01-01
A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known as M8. The M8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.
An Artificial Immune Univariate Marginal Distribution Algorithm
NASA Astrophysics Data System (ADS)
Zhang, Qingbin; Kang, Shuo; Gao, Junxiang; Wu, Song; Tian, Yanping
Hybridization is an extremely effective way of improving the performance of the Univariate Marginal Distribution Algorithm (UMDA). Owing to its diversity and memory mechanisms, artificial immune algorithm has been widely used to construct hybrid algorithms with other optimization algorithms. This paper proposes a hybrid algorithm which combines the UMDA with the principle of general artificial immune algorithm. Experimental results on deceptive function of order 3 show that the proposed hybrid algorithm can get more building blocks (BBs) than the UMDA.
A Numerical Algorithm for the Solution of a Phase-Field Model of Polycrystalline Materials
Dorr, M R; Fattebert, J; Wickett, M E; Belak, J F; Turchi, P A
2008-12-04
We describe an algorithm for the numerical solution of a phase-field model (PFM) of microstructure evolution in polycrystalline materials. The PFM system of equations includes a local order parameter, a quaternion representation of local orientation and a species composition parameter. The algorithm is based on the implicit integration of a semidiscretization of the PFM system using a backward difference formula (BDF) temporal discretization combined with a Newton-Krylov algorithm to solve the nonlinear system at each time step. The BDF algorithm is combined with a coordinate projection method to maintain quaternion unit length, which is related to an important solution invariant. A key element of the Newton-Krylov algorithm is the selection of a preconditioner to accelerate the convergence of the Generalized Minimum Residual algorithm used to solve the Jacobian linear system in each Newton step. Results are presented for the application of the algorithm to 2D and 3D examples.
A fast algorithm for reconstruction of spectrally sparse signals in super-resolution
NASA Astrophysics Data System (ADS)
Cai, Jian-Feng; Liu, Suhui; Xu, Weiyu
2015-08-01
We propose a fast algorithm to reconstruct spectrally sparse signals from a small number of randomly observed time domain samples. Different from conventional compressed sensing where frequencies are discretized, we consider the super-resolution case where the frequencies can be any values in the normalized continuous frequency domain [0; 1). We first convert our signal recovery problem into a low rank Hankel matrix completion problem, for which we then propose an efficient feasible point algorithm named projected Wirtinger gradient algorithm(PWGA). The algorithm can be further accelerated by a scheme inspired by the fast iterative shrinkage-thresholding algorithm (FISTA). Numerical experiments are provided to illustrate the effectiveness of our proposed algorithm. Different from earlier approaches, our algorithm can solve problems of large scale efficiently.
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.
Comparison and analysis of nonlinear algorithms for compressed sensing in MRI.
Yu, Yeyang; Hong, Mingjian; Liu, Feng; Wang, Hua; Crozier, Stuart
2010-01-01
Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A systematic and comparative study of those commonly used algorithms is therefore essential for the implementation of CS in MRI. In this work, three typical algorithms, namely, the Gradient Projection For Sparse Reconstruction (GPSR) algorithm, Interior-point algorithm (l(1)_ls), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm are compared and investigated in three different imaging scenarios, brain, angiogram and phantom imaging. The algorithms' performances are characterized in terms of image quality and reconstruction speed. The theoretical results show that the performance of the CS algorithms is case sensitive; overall, the StOMP algorithm offers the best solution in imaging quality, while the GPSR algorithm is the most efficient one among the three methods. In the next step, the algorithm performances and characteristics will be experimentally explored. It is hoped that this research will further support the applications of CS in MRI. PMID:21097312
NASA Technical Reports Server (NTRS)
Kasturi, Rangachar; Camps, Octavia; Coraor, Lee
2000-01-01
The research reported here is a part of NASA's Synthetic Vision System (SVS) project for the development of a High Speed Civil Transport Aircraft (HSCT). One of the components of the SVS is a module for detection of potential obstacles in the aircraft's flight path by analyzing the images captured by an on-board camera in real-time. Design of such a module includes the selection and characterization of robust, reliable, and fast techniques and their implementation for execution in real-time. This report describes the results of our research in realizing such a design. It is organized into three parts. Part I. Data modeling and camera characterization; Part II. Algorithms for detecting airborne obstacles; and Part III. Real time implementation of obstacle detection algorithms on the Datacube MaxPCI architecture. A list of publications resulting from this grant as well as a list of relevant publications resulting from prior NASA grants on this topic are presented.
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
Wavelet periodicity detection algorithms
NASA Astrophysics Data System (ADS)
Benedetto, John J.; Pfander, Goetz E.
1998-10-01
This paper deals with the analysis of time series with respect to certain known periodicities. In particular, we shall present a fast method aimed at detecting periodic behavior inherent in noise data. The method is composed of three steps: (1) Non-noisy data are analyzed through spectral and wavelet methods to extract specific periodic patterns of interest. (2) Using these patterns, we construct an optimal piecewise constant wavelet designed to detect the underlying periodicities. (3) We introduce a fast discretized version of the continuous wavelet transform, as well as waveletgram averaging techniques, to detect occurrence and period of these periodicities. The algorithm is formulated to provide real time implementation. Our procedure is generally applicable to detect locally periodic components in signals s which can be modeled as s(t) equals A(t)F(h(t)) + N(t) for t in I, where F is a periodic signal, A is a non-negative slowly varying function, and h is strictly increasing with h' slowly varying, N denotes background activity. For example, the method can be applied in the context of epileptic seizure detection. In this case, we try to detect seizure periodics in EEG and ECoG data. In the case of ECoG data, N is essentially 1/f noise. In the case of EEG data and for t in I,N includes noise due to cranial geometry and densities. In both cases N also includes standard low frequency rhythms. Periodicity detection has other applications including ocean wave prediction, cockpit motion sickness prediction, and minefield detection.
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.
Algorithms + Observations = VStar
NASA Astrophysics Data System (ADS)
Benn, D.
2012-05-01
VStar is a multi-platform, free, open source application for visualizing and analyzing time-series data. It is primarily intended for use with variable star observations, permitting light curves and phase plots to be created, viewed in tabular form, and filtered. Period search and model creation are supported. Wavelet-based time-frequency analysis permits change in period over time to be investigated. Data can be loaded from the AAVSO International Database or files of various formats. vstar's feature set can be expanded via plug-ins, for example, to read Kepler mission data. This article explores vstar's beginnings from a conversation with Arne Henden in 2008 to its development since 2009 in the context of the AAVSO's Citizen Sky Project. Science examples are provided and anticipated future directions are outlined.
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.
Undergraduate computational physics projects on quantum computing
NASA Astrophysics Data System (ADS)
Candela, D.
2015-08-01
Computational projects on quantum computing suitable for students in a junior-level quantum mechanics course are described. In these projects students write their own programs to simulate quantum computers. Knowledge is assumed of introductory quantum mechanics through the properties of spin 1/2. Initial, more easily programmed projects treat the basics of quantum computation, quantum gates, and Grover's quantum search algorithm. These are followed by more advanced projects to increase the number of qubits and implement Shor's quantum factoring algorithm. The projects can be run on a typical laptop or desktop computer, using most programming languages. Supplementing resources available elsewhere, the projects are presented here in a self-contained format especially suitable for a short computational module for physics students.
Cluster algorithms and computational complexity
NASA Astrophysics Data System (ADS)
Li, Xuenan
Cluster algorithms for the 2D Ising model with a staggered field have been studied and a new cluster algorithm for path sampling has been worked out. The complexity properties of Bak-Seppen model and the Growing network model have been studied by using the Computational Complexity Theory. The dynamic critical behavior of the two-replica cluster algorithm is studied. Several versions of the algorithm are applied to the two-dimensional, square lattice Ising model with a staggered field. The dynamic exponent for the full algorithm is found to be less than 0.5. It is found that odd translations of one replica with respect to the other together with global flips are essential for obtaining a small value of the dynamic exponent. The path sampling problem for the 1D Ising model is studied using both a local algorithm and a novel cluster algorithm. The local algorithm is extremely inefficient at low temperature, where the integrated autocorrelation time is found to be proportional to the fourth power of correlation length. The dynamic exponent of the cluster algorithm is found to be zero and therefore proved to be much more efficient than the local algorithm. The parallel computational complexity of the Bak-Sneppen evolution model is studied. It is shown that Bak-Sneppen histories can be generated by a massively parallel computer in a time that is polylog in the length of the history, which means that the logical depth of producing a Bak-Sneppen history is exponentially less than the length of the history. The parallel dynamics for generating Bak-Sneppen histories is contrasted to standard Bak-Sneppen dynamics. The parallel computational complexity of the Growing Network model is studied. The growth of the network with linear kernels is shown to be not complex and an algorithm with polylog parallel running time is found. The growth of the network with gamma ≥ 2 super-linear kernels can be realized by a randomized parallel algorithm with polylog expected running time.
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).
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.
Infrared algorithm development for ocean observations with EOS/MODIS
NASA Technical Reports Server (NTRS)
Brown, Otis B.
1994-01-01
Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared retrievals. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, and participation in MODIS (project) related activities. Efforts in this contract period have focused on radiative transfer modeling and evaluation of atmospheric path radiance efforts on SST estimation, exploration of involvement in ongoing field studies, evaluation of new computer networking strategies, and objective analysis approaches.
Infrared Algorithm Development for Ocean Observations with EOS/MODIS
NASA Technical Reports Server (NTRS)
Brown, Otis B.
1997-01-01
Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.
Adaptive Multigrid Algorithm for the Lattice Wilson-Dirac Operator
Babich, R.; Brower, R. C.; Rebbi, C.; Brannick, J.; Clark, M. A.; Manteuffel, T. A.; McCormick, S. F.; Osborn, J. C.
2010-11-12
We present an adaptive multigrid solver for application to the non-Hermitian Wilson-Dirac system of QCD. The key components leading to the success of our proposed algorithm are the use of an adaptive projection onto coarse grids that preserves the near null space of the system matrix together with a simplified form of the correction based on the so-called {gamma}{sub 5}-Hermitian symmetry of the Dirac operator. We demonstrate that the algorithm nearly eliminates critical slowing down in the chiral limit and that it has weak dependence on the lattice volume.
Adaptive multigrid algorithm for the lattice Wilson-Dirac operator.
Babich, R; Brannick, J; Brower, R C; Clark, M A; Manteuffel, T A; McCormick, S F; Osborn, J C; Rebbi, C
2010-11-12
We present an adaptive multigrid solver for application to the non-Hermitian Wilson-Dirac system of QCD. The key components leading to the success of our proposed algorithm are the use of an adaptive projection onto coarse grids that preserves the near null space of the system matrix together with a simplified form of the correction based on the so-called γ5-Hermitian symmetry of the Dirac operator. We demonstrate that the algorithm nearly eliminates critical slowing down in the chiral limit and that it has weak dependence on the lattice volume. PMID:21231217
Liu, Li; Gao, Simon S.; Bailey, Steven T.; Huang, David; Li, Dengwang; Jia, Yali
2015-01-01
Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area. PMID:26417524
A computational study of routing algorithms for realistic transportation networks
Jacob, R.; Marathe, M.V.; Nagel, K.
1998-12-01
The authors carry out an experimental analysis of a number of shortest path (routing) algorithms investigated in the context of the TRANSIMS (Transportation Analysis and Simulation System) project. The main focus of the paper is to study how various heuristic and exact solutions, associated data structures affected the computational performance of the software developed especially for realistic transportation networks. For this purpose the authors have used Dallas Fort-Worth road network with very high degree of resolution. The following general results are obtained: (1) they discuss and experimentally analyze various one-one shortest path algorithms, which include classical exact algorithms studied in the literature as well as heuristic solutions that are designed to take into account the geometric structure of the input instances; (2) they describe a number of extensions to the basic shortest path algorithm. These extensions were primarily motivated by practical problems arising in TRANSIMS and ITS (Intelligent Transportation Systems) related technologies. Extensions discussed include--(i) time dependent networks, (ii) multi-modal networks, (iii) networks with public transportation and associated schedules. Computational results are provided to empirically compare the efficiency of various algorithms. The studies indicate that a modified Dijkstra`s algorithm is computationally fast and an excellent candidate for use in various transportation planning applications as well as ITS related technologies.
Star pattern recognition algorithm aided by inertial information
NASA Astrophysics Data System (ADS)
Liu, Bao; Wang, Ke-dong; Zhang, Chao
2011-08-01
Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.
A High Precision Terahertz Wave Image Reconstruction Algorithm
Guo, Qijia; Chang, Tianying; Geng, Guoshuai; Jia, Chengyan; Cui, Hong-Liang
2016-01-01
With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging features sources of array elements that are almost always supposed to be spherical wave radiators, including single antennae. As such, well-developed methodologies such as Range-Doppler Algorithm (RDA) are not directly applicable in such near-range situations. The Back Projection Algorithm (BPA) can provide products of high precision at the the cost of a high computational burden, while the Range Migration Algorithm (RMA) sacrifices the quality of images for efficiency. The Phase-shift Migration Algorithm (PMA) is a good alternative, the features of which combine both of the classical algorithms mentioned above. In this research, it is used for mechanical scanning, and is extended to array imaging for the first time. In addition, the performances of PMA are studied in detail in contrast to BPA and RMA. It is demonstrated in our simulations and experiments described herein that the algorithm can reconstruct images with high precision. PMID:27455269
A High Precision Terahertz Wave Image Reconstruction Algorithm.
Guo, Qijia; Chang, Tianying; Geng, Guoshuai; Jia, Chengyan; Cui, Hong-Liang
2016-01-01
With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging features sources of array elements that are almost always supposed to be spherical wave radiators, including single antennae. As such, well-developed methodologies such as Range-Doppler Algorithm (RDA) are not directly applicable in such near-range situations. The Back Projection Algorithm (BPA) can provide products of high precision at the the cost of a high computational burden, while the Range Migration Algorithm (RMA) sacrifices the quality of images for efficiency. The Phase-shift Migration Algorithm (PMA) is a good alternative, the features of which combine both of the classical algorithms mentioned above. In this research, it is used for mechanical scanning, and is extended to array imaging for the first time. In addition, the performances of PMA are studied in detail in contrast to BPA and RMA. It is demonstrated in our simulations and experiments described herein that the algorithm can reconstruct images with high precision. PMID:27455269
Wind farm optimization using evolutionary algorithms
NASA Astrophysics Data System (ADS)
Ituarte-Villarreal, Carlos M.
In recent years, the wind power industry has focused its efforts on solving the Wind Farm Layout Optimization (WFLO) problem. Wind resource assessment is a pivotal step in optimizing the wind-farm design and siting and, in determining whether a project is economically feasible or not. In the present work, three (3) different optimization methods are proposed for the solution of the WFLO: (i) A modified Viral System Algorithm applied to the optimization of the proper location of the components in a wind-farm to maximize the energy output given a stated wind environment of the site. The optimization problem is formulated as the minimization of energy cost per unit produced and applies a penalization for the lack of system reliability. The viral system algorithm utilized in this research solves three (3) well-known problems in the wind-energy literature; (ii) a new multiple objective evolutionary algorithm to obtain optimal placement of wind turbines while considering the power output, cost, and reliability of the system. The algorithm presented is based on evolutionary computation and the objective functions considered are the maximization of power output, the minimization of wind farm cost and the maximization of system reliability. The final solution to this multiple objective problem is presented as a set of Pareto solutions and, (iii) A hybrid viral-based optimization algorithm adapted to find the proper component configuration for a wind farm with the introduction of the universal generating function (UGF) analytical approach to discretize the different operating or mechanical levels of the wind turbines in addition to the various wind speed states. The proposed methodology considers the specific probability functions of the wind resource to describe their proper behaviors to account for the stochastic comportment of the renewable energy components, aiming to increase their power output and the reliability of these systems. The developed heuristic considers a
A comparison of three additive tree algorithms that rely on a least-squares loss criterion.
Smith, T J
1998-11-01
The performances of three additive tree algorithms which seek to minimize a least-squares loss criterion were compared. The algorithms included the penalty-function approach of De Soete (1983), the iterative projection strategy of Hubert & Arabie (1995) and the two-stage ADDTREE algorithm, (Corter, 1982; Sattath & Tversky, 1977). Model fit, comparability of structure, processing time and metric recovery were assessed. Results indicated that the iterative projection strategy consistently located the best-fitting tree, but also displayed a wider range and larger number of local optima. PMID:9854946
An Adaptive Data Collection Algorithm Based on a Bayesian Compressed Sensing Framework
Liu, Zhi; Zhang, Mengmeng; Cui, Jian
2014-01-01
For Wireless Sensor Networks, energy efficiency is always a key consideration in system design. Compressed sensing is a new theory which has promising prospects in WSNs. However, how to construct a sparse projection matrix is a problem. In this paper, based on a Bayesian compressed sensing framework, a new adaptive algorithm which can integrate routing and data collection is proposed. By introducing new target node selection metrics, embedding the routing structure and maximizing the differential entropy for each collection round, an adaptive projection vector is constructed. Simulations show that compared to reference algorithms, the proposed algorithm can decrease computation complexity and improve energy efficiency. PMID:24818659
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)
An onboard star identification algorithm
NASA Astrophysics Data System (ADS)
Ha, Kong; Femiano, Michael
The paper presents the autonomous Initial Stellar Acquisition (ISA) algorithm developed for the X-Ray Timing Explorer for prividing the attitude quaternion within the desired accuracy, based on the one-axis attitude knowledge (through the use of the Digital Sun Sensor, CCD Star Trackers, and the onboard star catalog, OSC). Mathematical analysis leads to an accurate measure of the performance of the algorithm as a function of various parameters, such as the probability of a tracked star being in the OSC, the sensor noise level, and the number of stars matched. It is shown that the simplicity, tractability, and robustness of the ISA algorithm, compared to a general three-axis attiude determination algorithm, make it a viable on-board solution.
Scheduling Jobs with Genetic Algorithms
NASA Astrophysics Data System (ADS)
Ferrolho, António; Crisóstomo, Manuel
Most scheduling problems are NP-hard, the time required to solve the problem optimally increases exponentially with the size of the problem. Scheduling problems have important applications, and a number of heuristic algorithms have been proposed to determine relatively good solutions in polynomial time. Recently, genetic algorithms (GA) are successfully used to solve scheduling problems, as shown by the growing numbers of papers. GA are known as one of the most efficient algorithms for solving scheduling problems. But, when a GA is applied to scheduling problems various crossovers and mutations operators can be applicable. This paper presents and examines a new concept of genetic operators for scheduling problems. A software tool called hybrid and flexible genetic algorithm (HybFlexGA) was developed to examine the performance of various crossover and mutation operators by computing simulations of job scheduling problems.
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.
Algorithmic complexity of a protein
NASA Astrophysics Data System (ADS)
Dewey, T. Gregory
1996-07-01
The information contained in a protein's amino acid sequence dictates its three-dimensional structure. To quantitate the transfer of information that occurs in the protein folding process, the Kolmogorov information entropy or algorithmic complexity of the protein structure is investigated. The algorithmic complexity of an object provides a means of quantitating its information content. Recent results have indicated that the algorithmic complexity of microstates of certain statistical mechanical systems can be estimated from the thermodynamic entropy. In the present work, it is shown that the algorithmic complexity of a protein is given by its configurational entropy. Using this result, a quantitative estimate of the information content of a protein's structure is made and is compared to the information content of the sequence. Additionally, the mutual information between sequence and structure is determined. It is seen that virtually all the information contained in the protein structure is shared with the sequence.
An onboard star identification algorithm
NASA Technical Reports Server (NTRS)
Ha, Kong; Femiano, Michael
1993-01-01
The paper presents the autonomous Initial Stellar Acquisition (ISA) algorithm developed for the X-Ray Timing Explorer for prividing the attitude quaternion within the desired accuracy, based on the one-axis attitude knowledge (through the use of the Digital Sun Sensor, CCD Star Trackers, and the onboard star catalog, OSC). Mathematical analysis leads to an accurate measure of the performance of the algorithm as a function of various parameters, such as the probability of a tracked star being in the OSC, the sensor noise level, and the number of stars matched. It is shown that the simplicity, tractability, and robustness of the ISA algorithm, compared to a general three-axis attiude determination algorithm, make it a viable on-board solution.
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.
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.
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.
Fully relativistic lattice Boltzmann algorithm
Romatschke, P.; Mendoza, M.; Succi, S.
2011-09-15
Starting from the Maxwell-Juettner equilibrium distribution, we develop a relativistic lattice Boltzmann (LB) algorithm capable of handling ultrarelativistic systems with flat, but expanding, spacetimes. The algorithm is validated through simulations of a quark-gluon plasma, yielding excellent agreement with hydrodynamic simulations. The present scheme opens the possibility of transferring the recognized computational advantages of lattice kinetic theory to the context of both weakly and ultrarelativistic systems.
NASA Astrophysics Data System (ADS)
El-Guibaly, Fayez; Sabaa, A.
1996-10-01
In this paper, we introduce modifications on the classic CORDIC algorithm to reduce the number of iterations, and hence the rounding noise. The modified algorithm needs, at most, half the number of iterations to achieve the same accuracy as the classical one. The modifications are applicable to linear, circular and hyperbolic CORDIC in both vectoring and rotation modes. Simulations illustrate the effect of the new modifications.
Localization algorithm for acoustic emission
NASA Astrophysics Data System (ADS)
Salinas, V.; Vargas, Y.; Ruzzante, J.; Gaete, L.
2010-01-01
In this paper, an iterative algorithm for localization of acoustic emission (AE) source is presented. The main advantage of the system is that it is independent of the 'ability' in the determination of signal level to triggering the signal by the researcher. The system was tested in cylindrical samples with an AE localized in a known position; the precision in the source determination was of about 2 mm, better than the precision obtained with classic localization algorithms (˜1 cm).
Concluding Report: Quantitative Tomography Simulations and Reconstruction Algorithms
Aufderheide, M B; Martz, H E; Slone, D M; Jackson, J A; Schach von Wittenau, A E; Goodman, D M; Logan, C M; Hall, J M
2002-02-01
In this report we describe the original goals and final achievements of this Laboratory Directed Research and Development project. The Quantitative was Tomography Simulations and Reconstruction Algorithms project (99-ERD-015) funded as a multi-directorate, three-year effort to advance the state of the art in radiographic simulation and tomographic reconstruction by improving simulation and including this simulation in the tomographic reconstruction process. Goals were to improve the accuracy of radiographic simulation, and to couple advanced radiographic simulation tools with a robust, many-variable optimization algorithm. In this project, we were able to demonstrate accuracy in X-Ray simulation at the 2% level, which is an improvement of roughly a factor of 5 in accuracy, and we have successfully coupled our simulation tools with the CCG (Constrained Conjugate Gradient) optimization algorithm, allowing reconstructions that include spectral effects and blurring in the reconstructions. Another result of the project was the assembly of a low-scatter X-Ray imaging facility for use in nondestructive evaluation applications. We conclude with a discussion of future work.
Algorithms for rapid outbreak detection: a research synthesis.
Buckeridge, David L; Burkom, Howard; Campbell, Murray; Hogan, William R; Moore, Andrew W
2005-04-01
The threat of bioterrorism has stimulated interest in enhancing public health surveillance to detect disease outbreaks more rapidly than is currently possible. To advance research on improving the timeliness of outbreak detection, the Defense Advanced Research Project Agency sponsored the Bio-event Advanced Leading Indicator Recognition Technology (BioALIRT) project beginning in 2001. The purpose of this paper is to provide a synthesis of research on outbreak detection algorithms conducted by academic and industrial partners in the BioALIRT project. We first suggest a practical classification for outbreak detection algorithms that considers the types of information encountered in surveillance analysis. We then present a synthesis of our research according to this classification. The research conducted for this project has examined how to use spatial and other covariate information from disparate sources to improve the timeliness of outbreak detection. Our results suggest that use of spatial and other covariate information can improve outbreak detection performance. We also identified, however, methodological challenges that limited our ability to determine the benefit of using outbreak detection algorithms that operate on large volumes of data. Future research must address challenges such as forecasting expected values in high-dimensional data and generating spatial and multivariate test data sets. PMID:15797000
CORDIC Algorithms: Theory And Extensions
NASA Astrophysics Data System (ADS)
Delosme, Jean-Marc
1989-11-01
Optimum algorithms for signal processing are notoriously costly to implement since they usually require intensive linear algebra operations to be performed at very high rates. In these cases a cost-effective solution is to design a pipelined or parallel architecture with special-purpose VLSI processors. One may often lower the hardware cost of such a dedicated architecture by using processors that implement CORDIC-like arithmetic algorithms. Indeed, with CORDIC algorithms, the evaluation and the application of an operation, such as determining a rotation that brings a vector onto another one and rotating other vectors by that amount, require the same time on identical processors and can be fully overlapped in most cases, thus leading to highly efficient implementations. We have shown earlier that a necessary condition for a CORDIC-type algorithm to exist is that the function to be implemented can be represented in terms of a matrix exponential. This paper refines this condition to the ability to represent , the desired function in terms of a rational representation of a matrix exponential. This insight gives us a powerful tool for the design of new CORDIC algorithms. This is demonstrated by rederiving classical CORDIC algorithms and introducing several new ones, for Jacobi rotations, three and higher dimensional rotations, etc.
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.
Myers, Timothy
2006-09-01
The use of protocols or care algorithms in medical facilities has increased in the managed care environment. The definition and application of care algorithms, with a particular focus on the treatment of acute bronchospasm, are explored in this review. The benefits and goals of using protocols, especially in the treatment of asthma, to standardize patient care based on clinical guidelines and evidence-based medicine are explained. Ideally, evidence-based protocols should translate research findings into best medical practices that would serve to better educate patients and their medical providers who are administering these protocols. Protocols should include evaluation components that can monitor, through some mechanism of quality assurance, the success and failure of the instrument so that modifications can be made as necessary. The development and design of an asthma care algorithm can be accomplished by using a four-phase approach: phase 1, identifying demographics, outcomes, and measurement tools; phase 2, reviewing, negotiating, and standardizing best practice; phase 3, testing and implementing the instrument and collecting data; and phase 4, analyzing the data and identifying areas of improvement and future research. The experiences of one medical institution that implemented an asthma care algorithm in the treatment of pediatric asthma are described. Their care algorithms served as tools for decision makers to provide optimal asthma treatment in children. In addition, the studies that used the asthma care algorithm to determine the efficacy and safety of ipratropium bromide and levalbuterol in children with asthma are described. PMID:16945065
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
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.
Engine Removal Projection Tool
Ferryman, Thomas A.; Matzke, Brett D.; Wilson, John E.; Sharp, Julia L.; Greitzer, Frank L.
2005-06-02
The US Navy has over 3500 gas turbine engines used throughout the surface fleet for propulsion and the generation of electrical power. Past data is used to forecast the number of engine removals for the next ten years and determine engine down times between removals. Currently this is done via a FORTRAN program created in the early 1970s. This paper presents results of R&D associated with creating a new algorithm and software program. We tested over 60 techniques on data spanning 20 years from over 3100 engines and 120 ships. Investigated techniques for the forecast basis including moving averages, empirical negative binomial, generalized linear models, Cox regression, and Kaplan Meier survival curves, most of which are documented in engineering, medical and scientific research literature. We applied those techniques to the data, and chose the best algorithm based on its performance on real-world data. The software uses the best algorithm in combination with user-friendly interfaces and intuitively understandable displays. The user can select a specific engine type, forecast time period, and op-tempo. Graphical displays and numerical tables present forecasts and uncertainty intervals. The technology developed for the project is applicable to other logistic forecasting challenges.
Chang, C.Y.
1986-01-01
New results on efficient forms of decoding convolutional codes based on Viterbi and stack algorithms using systolic array architecture are presented. Some theoretical aspects of systolic arrays are also investigated. First, systolic array implementation of Viterbi algorithm is considered, and various properties of convolutional codes are derived. A technique called strongly connected trellis decoding is introduced to increase the efficient utilization of all the systolic array processors. The issues dealing with the composite branch metric generation, survivor updating, overall system architecture, throughput rate, and computations overhead ratio are also investigated. Second, the existing stack algorithm is modified and restated in a more concise version so that it can be efficiently implemented by a special type of systolic array called systolic priority queue. Three general schemes of systolic priority queue based on random access memory, shift register, and ripple register are proposed. Finally, a systematic approach is presented to design systolic arrays for certain general classes of recursively formulated algorithms.
Comparative study of heart sound localization algorithms
NASA Astrophysics Data System (ADS)
Moukadem, A.; Dieterlen, A.; Hueber, N.; Brandt, C.; Raymond, P.
2011-05-01
The purpose of this document is to present a comparative study of five algorithms of heart sound localization, one of which, is a method based on radial basis function networks applied in a novel approach. The advantages and disadvantages of each method are evaluated according to a data base of 50 subjects in which there are 25 healthy subjects selected from the University Hospital of Strasbourg (HUS) and from theMARS500 project (Moscow) and 25 subjects with cardiac pathologies selected from the HUS. This study is made under the control of an experienced cardiologist. The performance of each method is evaluated by calculating the area under a receiver operating curve (AUC) and the robustness is shown against different levels of additive white Gaussian noise.
Component evaluation testing and analysis algorithms.
Hart, Darren M.; Merchant, Bion John
2011-10-01
The Ground-Based Monitoring R&E Component Evaluation project performs testing on the hardware components that make up Seismic and Infrasound monitoring systems. The majority of the testing is focused on the Digital Waveform Recorder (DWR), Seismic Sensor, and Infrasound Sensor. In order to guarantee consistency, traceability, and visibility into the results of the testing process, it is necessary to document the test and analysis procedures that are in place. Other reports document the testing procedures that are in place (Kromer, 2007). This document serves to provide a comprehensive overview of the analysis and the algorithms that are applied to the Component Evaluation testing. A brief summary of each test is included to provide the context for the analysis that is to be performed.
Nonlinearity calibrating algorithm for structured light illumination
NASA Astrophysics Data System (ADS)
Liu, Kai; Wang, Shuaijun; Lau, Daniel L.; Barner, Kenneth E.; Kiamilev, Fouad
2014-05-01
In structured light illumination (SLI), the nonlinear distortion of the optical devices dramatically ruins accuracy of three-dimensional reconstruction when using only a small number of projected patterns. We propose a universal algorithm to calibrate these device nonlinearities to accurately precompensate the patterns. Thus, no postprocessing is needed to correct for the distortions while the number of patterns can be reduced down to as few as possible. Theoretically, the proposed method can be applied to any SLI pattern strategy. Using a three-pattern SLI method, our experimental results will show a 25× to 60× reduction in surface variance for a flat target, depending upon any surface smoothing that might be applied to remove Gaussian noise.
UWB Tracking System Design with TDOA Algorithm
NASA Technical Reports Server (NTRS)
Ni, Jianjun; Arndt, Dickey; Ngo, Phong; Phan, Chau; Gross, Julia; Dusl, John; Schwing, Alan
2006-01-01
This presentation discusses an ultra-wideband (UWB) tracking system design effort using a tracking algorithm TDOA (Time Difference of Arrival). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A two-stage weighted least square method is chosen to solve the TDOA non-linear equations. Matlab simulations in both two-dimensional space and three-dimensional space show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. The error analysis reveals various ways to improve the tracking resolution. Lab experiments demonstrate the UWBTDOA tracking capability with fine resolution. This research effort is motivated by a prototype development project Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS).
Combat Air Identification Fusion Algorithm (CAIFA)
NASA Astrophysics Data System (ADS)
Butler, C. A.; Baker, Joni E.; Crowe, John A.; Kierstead, David P.; Mauro, Carl A.
2003-04-01
The Combat Air Identification Fusion Algorithm (CAIFA), developed by Daniel H. Wagner, Associates, is a prototype, inferential reasoning algorithm for air combat identification. Bayesian reasoning and updating techniques are used in CAIFA to fuse multi-source identification evidence to provide identity estimates-allegiance, nationality, platform type, and intent-of detected airborne objects in the air battle space, enabling positive and rapid Combat Identification (CID) decisions. CAIFA was developed for the Composite Combat Identification (CCID) project under the Office of Naval Research (ONR) Missile Defense (MD) Future Naval Capability (FNC) program. CAIFA processes identification (ID) attribute evidence generated by surveillance sensors and other information sources over time by updating the identity estimate for each target using Bayesian inference. CAIFA exploits the conditional interdependencies of attribute variables by constructing a context-dependent Bayesian Network (BN). This formulation offers a well-established, consistent approach for evidential reasoning, renders manageable the potentially large CID state space, and provides a flexible and extensible representation to accommodate requirements for model reconfiguration/restructuring. CAIFA enables reasoning across and at different levels of the Air Space Taxonomy.
ISINA: INTEGRAL Source Identification Network Algorithm
NASA Astrophysics Data System (ADS)
Scaringi, S.; Bird, A. J.; Clark, D. J.; Dean, A. J.; Hill, A. B.; McBride, V. A.; Shaw, S. E.
2008-11-01
We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. First, we introduce the data set and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky. Three independent random forests are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples. Based on observations with INTEGRAL, an ESA project with instruments and science data centre funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain), Czech Republic and Poland, and the participation of Russia and the USA. E-mail: simo@astro.soton.ac.uk
Libpsht: Algorithms for Efficient Spherical Harmonic Transforms
NASA Astrophysics Data System (ADS)
Reinecke, Martin
2010-10-01
Libpsht (or "library for Performing Spherical Harmonic Transforms") is a collection of algorithms for efficient conversion between spatial-domain and spectral-domain representations of data defined on the sphere. The package supports transforms of scalars as well as spin-1 and spin-2 quantities, and can be used for a wide range of pixelisations (including HEALPix, GLESP and ECP). It will take advantage of hardware features like multiple processor cores and floating-point vector operations, if available. Even without this additional acceleration, the employed algorithms are among the most efficient (in terms of CPU time as well as memory consumption) currently being used in the astronomical community. The library is written in strictly standard-conforming C90, ensuring portability to many different hard- and software platforms, and allowing straightforward integration with codes written in various programming languages like C, C++, Fortran, Python etc. Libpsht is distributed under the terms of the GNU General Public License (GPL) version 2. Development on this project has ended; its successor is libsharp (ascl:1402.033).
Template based illumination compensation algorithm for multiview video coding
NASA Astrophysics Data System (ADS)
Li, Xiaoming; Jiang, Lianlian; Ma, Siwei; Zhao, Debin; Gao, Wen
2010-07-01
Recently multiview video coding (MVC) standard has been finalized as an extension of H.264/AVC by Joint Video Team (JVT). In the project Joint Multiview Video Model (JMVM) for the standardization, illumination compensation (IC) is adopted as a useful tool. In this paper, a novel illumination compensation algorithm based on template is proposed. The basic idea of the algorithm is that the illumination of the current block has a strong correlation with its adjacent template. Based on this idea, firstly a template based illumination compensation method is presented, and then a template models selection strategy is devised to improve the illumination compensation performance. The experimental results show that the proposed algorithm can improve the coding efficiency significantly.
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
GPU Accelerated Event Detection Algorithm
2011-05-25
Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but alsomore » model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.« less
Demeyer, Sofie; Michoel, Tom; Fostier, Jan; Audenaert, Pieter; Pickavet, Mario; Demeester, Piet
2013-01-01
Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma/. PMID:23620730
Demeyer, Sofie; Michoel, Tom; Fostier, Jan; Audenaert, Pieter; Pickavet, Mario; Demeester, Piet
2013-01-01
Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma/. PMID:23620730
Nonlinear optimization with linear constraints using a projection method
NASA Technical Reports Server (NTRS)
Fox, T.
1982-01-01
Nonlinear optimization problems that are encountered in science and industry are examined. A method of projecting the gradient vector onto a set of linear contraints is developed, and a program that uses this method is presented. The algorithm that generates this projection matrix is based on the Gram-Schmidt method and overcomes some of the objections to the Rosen projection method.
Atmospheric Correction Algorithm for Hyperspectral Imagery
R. J. Pollina
1999-09-01
In December 1997, the US Department of Energy (DOE) established a Center of Excellence (Hyperspectral-Multispectral Algorithm Research Center, HyMARC) for promoting the research and development of algorithms to exploit spectral imagery. This center is located at the DOE Remote Sensing Laboratory in Las Vegas, Nevada, and is operated for the DOE by Bechtel Nevada. This paper presents the results to date of a research project begun at the center during 1998 to investigate the correction of hyperspectral data for atmospheric aerosols. Results of a project conducted by the Rochester Institute of Technology to define, implement, and test procedures for absolute calibration and correction of hyperspectral data to absolute units of high spectral resolution imagery will be presented. Hybrid techniques for atmospheric correction using image or spectral scene data coupled through radiative propagation models will be specifically addressed. Results of this effort to analyze HYDICE sensor data will be included. Preliminary results based on studying the performance of standard routines, such as Atmospheric Pre-corrected Differential Absorption and Nonlinear Least Squares Spectral Fit, in retrieving reflectance spectra show overall reflectance retrieval errors of approximately one to two reflectance units in the 0.4- to 2.5-micron-wavelength region (outside of the absorption features). These results are based on HYDICE sensor data collected from the Southern Great Plains Atmospheric Radiation Measurement site during overflights conducted in July of 1997. Results of an upgrade made in the model-based atmospheric correction techniques, which take advantage of updates made to the moderate resolution atmospheric transmittance model (MODTRAN 4.0) software, will also be presented. Data will be shown to demonstrate how the reflectance retrieval in the shorter wavelengths of the blue-green region will be improved because of enhanced modeling of multiple scattering effects.
A novel blinding digital watermark algorithm based on lab color space
NASA Astrophysics Data System (ADS)
Dong, Bing-feng; Qiu, Yun-jie; Lu, Hong-tao
2010-02-01
It is necessary for blinding digital image watermark algorithm to extract watermark information without any extra information except the watermarked image itself. But most of the current blinding watermark algorithms have the same disadvantage: besides the watermarked image, they also need the size and other information about the original image when extracting the watermark. This paper presents an innovative blinding color image watermark algorithm based on Lab color space, which does not have the disadvantages mentioned above. This algorithm first marks the watermark region size and position through embedding some regular blocks called anchor points in image spatial domain, and then embeds the watermark into the image. In doing so, the watermark information can be easily extracted after doing cropping and scale change to the image. Experimental results show that the algorithm is particularly robust against the color adjusting and geometry transformation. This algorithm has already been used in a copyright protecting project and works very well.
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Three-dimensional algorithms for grid restructuring in Free-Lagrangian calculations
NASA Technical Reports Server (NTRS)
Fritts, M.
1985-01-01
Grid restructuring algorithms which lower the price of three-dimensional Free-Lagrange calculations are presented. The algorithms are first given for the case of planar triangulated surfaces embedded in and spanning a three-dimensional region. The tetrahedra generated by this technique form a Delaunay mesh if the interplane spacing is comparable to the resolution within the planes. The algorithm can therefore be used for efficient determinations of Voronoi connections for initial grids. Modifications of the algorithm for the case of closely spaced surfaces are demonstrated in the context of restructuring algorithms which can accommodate colliding surfaces. Then, the restriction to planar surfaces is removed and regular surfaces are examined. The basic algorithm is the same, with an additional operation to project the vertices of one surface onto another. Finally, vertices on the surface are allowed to migrate anywhere in space.
A general-purpose contact detection algorithm for nonlinear structural analysis codes
Heinstein, M.W.; Attaway, S.W.; Swegle, J.W.; Mello, F.J.
1993-05-01
A new contact detection algorithm has been developed to address difficulties associated with the numerical simulation of contact in nonlinear finite element structural analysis codes. Problems including accurate and efficient detection of contact for self-contacting surfaces, tearing and eroding surfaces, and multi-body impact are addressed. The proposed algorithm is portable between dynamic and quasi-static codes and can efficiently model contact between a variety of finite element types including shells, bricks, beams and particles. The algorithm is composed of (1) a location strategy that uses a global search to decide which slave nodes are in proximity to a master surface and (2) an accurate detailed contact check that uses the projected motions of both master surface and slave node. In this report, currently used contact detection algorithms and their associated difficulties are discussed. Then the proposed algorithm and how it addresses these problems is described. Finally, the capability of the new algorithm is illustrated with several example problems.
SDR input power estimation algorithms
NASA Astrophysics Data System (ADS)
Briones, J. C.; Nappier, J. M.
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
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). PMID:23599053
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.
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.
Benchmarking image fusion algorithm performance
NASA Astrophysics Data System (ADS)
Howell, Christopher L.
2012-06-01
Registering two images produced by two separate imaging sensors having different detector sizes and fields of view requires one of the images to undergo transformation operations that may cause its overall quality to degrade with regards to visual task performance. This possible change in image quality could add to an already existing difference in measured task performance. Ideally, a fusion algorithm would take as input unaltered outputs from each respective sensor used in the process. Therefore, quantifying how well an image fusion algorithm performs should be base lined to whether the fusion algorithm retained the performance benefit achievable by each independent spectral band being fused. This study investigates an identification perception experiment using a simple and intuitive process for discriminating between image fusion algorithm performances. The results from a classification experiment using information theory based image metrics is presented and compared to perception test results. The results show an effective performance benchmark for image fusion algorithms can be established using human perception test data. Additionally, image metrics have been identified that either agree with or surpass the performance benchmark established.
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
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. PMID:25349382
Reconstruction algorithms for optoacoustic imaging based on fiber optic detectors
NASA Astrophysics Data System (ADS)
Lamela, Horacio; Díaz-Tendero, Gonzalo; Gutiérrez, Rebeca; Gallego, Daniel
2011-06-01
Optoacoustic Imaging (OAI), a novel hybrid imaging technology, offers high contrast, molecular specificity and excellent resolution to overcome limitations of the current clinical modalities for detection of solid tumors. The exact time-domain reconstruction formula produces images with excellent resolution but poor contrast. Some approximate time-domain filtered back-projection reconstruction algorithms have also been reported to solve this problem. A wavelet transform implementation filtering can be used to sharpen object boundaries while simultaneously preserving high contrast of the reconstructed objects. In this paper, several algorithms, based on Back Projection (BP) techniques, have been suggested to process OA images in conjunction with signal filtering for ultrasonic point detectors and integral detectors. We apply these techniques first directly to a numerical generated sample image and then to the laserdigitalized image of a tissue phantom, obtaining in both cases the best results in resolution and contrast for a waveletbased filter.
Firefly Algorithm for Structural Search.
Avendaño-Franco, Guillermo; Romero, Aldo H
2016-07-12
The problem of computational structure prediction of materials is approached using the firefly (FF) algorithm. Starting from the chemical composition and optionally using prior knowledge of similar structures, the FF method is able to predict not only known stable structures but also a variety of novel competitive metastable structures. This article focuses on the strengths and limitations of the algorithm as a multimodal global searcher. The algorithm has been implemented in software package PyChemia ( https://github.com/MaterialsDiscovery/PyChemia ), an open source python library for materials analysis. We present applications of the method to van der Waals clusters and crystal structures. The FF method is shown to be competitive when compared to other population-based global searchers. PMID:27232694
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.
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…
The Langley Parameterized Shortwave Algorithm (LPSA) for Surface Radiation Budget Studies. 1.0
NASA Technical Reports Server (NTRS)
Gupta, Shashi K.; Kratz, David P.; Stackhouse, Paul W., Jr.; Wilber, Anne C.
2001-01-01
An efficient algorithm was developed during the late 1980's and early 1990's by W. F. Staylor at NASA/LaRC for the purpose of deriving shortwave surface radiation budget parameters on a global scale. While the algorithm produced results in good agreement with observations, the lack of proper documentation resulted in a weak acceptance by the science community. The primary purpose of this report is to develop detailed documentation of the algorithm. In the process, the algorithm was modified whenever discrepancies were found between the algorithm and its referenced literature sources. In some instances, assumptions made in the algorithm could not be justified and were replaced with those that were justifiable. The algorithm uses satellite and operational meteorological data for inputs. Most of the original data sources have been replaced by more recent, higher quality data sources, and fluxes are now computed on a higher spatial resolution. Many more changes to the basic radiation scheme and meteorological inputs have been proposed to improve the algorithm and make the product more useful for new research projects. Because of the many changes already in place and more planned for the future, the algorithm has been renamed the Langley Parameterized Shortwave Algorithm (LPSA).
Limited angle C-arm tomosynthesis reconstruction algorithms
NASA Astrophysics Data System (ADS)
Malalla, Nuhad A. Y.; Xu, Shiyu; Chen, Ying
2015-03-01
In this paper, C-arm tomosynthesis with digital detector was investigated as a novel three dimensional (3D) imaging technique. Digital tomosythses is an imaging technique to provide 3D information of the object by reconstructing slices passing through the object, based on a series of angular projection views with respect to the object. C-arm tomosynthesis provides two dimensional (2D) X-ray projection images with rotation (-/+20 angular range) of both X-ray source and detector. In this paper, four representative reconstruction algorithms including point by point back projection (BP), filtered back projection (FBP), simultaneous algebraic reconstruction technique (SART) and maximum likelihood expectation maximization (MLEM) were investigated. Dataset of 25 projection views of 3D spherical object that located at center of C-arm imaging space was simulated from 25 angular locations over a total view angle of 40 degrees. With reconstructed images, 3D mesh plot and 2D line profile of normalized pixel intensities on focus reconstruction plane crossing the center of the object were studied with each reconstruction algorithm. Results demonstrated the capability to generate 3D information from limited angle C-arm tomosynthesis. Since C-arm tomosynthesis is relatively compact, portable and can avoid moving patients, it has been investigated for different clinical applications ranging from tumor surgery to interventional radiology. It is very important to evaluate C-arm tomosynthesis for valuable applications.
Evaluation of the VIIRS Land Algorithms at Land PEATE
NASA Technical Reports Server (NTRS)
Wolfe, Robert E.; Devadiga, Sadashiva; Ye, Gang; Masuoka, Edward J.; Schweiss, Robert J.
2010-01-01
The Land Product Evaluation and Algorithm Testing Element (Land PEATE), a component of the Science Data Segment of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), is being developed at the NASA Goddard Space Flight Center (GSFC). The primary task of the Land PEATE is to assess the quality of the Visible Infrared Imaging Radiometer Suite (VIIRS) Land data products made by the Interface Data Processing System (IDPS) using the Operational (OPS) Code during the NPP era and to recommend improvements to the algorithms in the IDPS OPS code. The Land PEATE uses a version of the MODIS Adaptive Processing System (MODAPS), NPPDAPS, that has been modified to produce products from the IDPS OPS code and software provided by the VIIRS Science Team, and uses the MODIS Land Data Operational Product Evaluation (LDOPE) team for evaluation of the data records generated by the NPPDAPS. Land PEATE evaluates the algorithms by comparing data products generated using different versions of the algorithm and also by comparing to heritage products generated from different instrument such as MODIS using various quality assessment tools developed at LDOPE. This paper describes the Land PEATE system and some of the approaches used by the Land PEATE for evaluating the VIIRS Land algorithms during the pre-launch period of the NPP mission and the proposed plan for long term monitoring of the quality of the VIIRS Land products post-launch.
Improved algorithm for solving nonlinear parabolized stability equations
NASA Astrophysics Data System (ADS)
Zhao, Lei; Zhang, Cun-bo; Liu, Jian-xin; Luo, Ji-sheng
2016-08-01
Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. Project supported by the National Natural Science Foundation of China (Grant Nos. 11332007 and 11402167).
Decryption of pure-position permutation algorithms.
Zhao, Xiao-Yu; Chen, Gang; Zhang, Dan; Wang, Xiao-Hong; Dong, Guang-Chang
2004-07-01
Pure position permutation image encryption algorithms, commonly used as image encryption investigated in this work are unfortunately frail under known-text attack. In view of the weakness of pure position permutation algorithm, we put forward an effective decryption algorithm for all pure-position permutation algorithms. First, a summary of the pure position permutation image encryption algorithms is given by introducing the concept of ergodic matrices. Then, by using probability theory and algebraic principles, the decryption probability of pure-position permutation algorithms is verified theoretically; and then, by defining the operation system of fuzzy ergodic matrices, we improve a specific decryption algorithm. Finally, some simulation results are shown. PMID:15495308
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.
Development and Testing of Data Mining Algorithms for Earth Observation
NASA Technical Reports Server (NTRS)
Glymour, Clark
2005-01-01
The new algorithms developed under this project included a principled procedure for classification of objects, events or circumstances according to a target variable when a very large number of potential predictor variables is available but the number of cases that can be used for training a classifier is relatively small. These "high dimensional" problems require finding a minimal set of variables -called the Markov Blanket-- sufficient for predicting the value of the target variable. An algorithm, the Markov Blanket Fan Search, was developed, implemented and tested on both simulated and real data in conjunction with a graphical model classifier, which was also implemented. Another algorithm developed and implemented in TETRAD IV for time series elaborated on work by C. Granger and N. Swanson, which in turn exploited some of our earlier work. The algorithms in question learn a linear time series model from data. Given such a time series, the simultaneous residual covariances, after factoring out time dependencies, may provide information about causal processes that occur more rapidly than the time series representation allow, so called simultaneous or contemporaneous causal processes. Working with A. Monetta, a graduate student from Italy, we produced the correct statistics for estimating the contemporaneous causal structure from time series data using the TETRAD IV suite of algorithms. Two economists, David Bessler and Kevin Hoover, have independently published applications using TETRAD style algorithms to the same purpose. These implementations and algorithmic developments were separately used in two kinds of studies of climate data: Short time series of geographically proximate climate variables predicting agricultural effects in California, and longer duration climate measurements of temperature teleconnections.
Algorithm for detecting energy diversion. [Appendix contains an annotated bibliography
Altschul, R.E.; Janky, D.G.; Scholz, F.W.; Tjoelker, R.A.; Tosch, T.J.; Tosch, T.J. )
1991-08-01
The objective of this project was to investigate those factors influencing energy consumption and to develop advanced statistical algorithms and a corresponding computer program to aid utilities in identifying energy diversion by analyzing patterns of energy consumption and other factors readily available to the utility. This final report documents the development of the algorithms, the methodologies used in analyzing their validity, and the advantages and disadvantages of these methods that resulted from these analyses. In the internal study, the algorithms appear to discriminate diverters from the rest of the population. Problems were found that decreased the efficiency of the algorithms during the field investigation. These included the quality of the data used by the algorithms, and the incomplete description of diverters. For the external study 300 potential diverters were submitted to the participating utility for field investigation. They found many cases of vacancies, seasonal use, two cases of tampering, several of suspect nature, irregularities in billing, and a number of meter problems. The code development was not undertaken due to the inconclusive nature of the results obtained in the external validation of the algorithms. Two final recommendations are presented. The first, to create better profiles for diverters and nondiverters, a large sample investigation of electric utility customers should be conducted. This would eliminate selection bias problems perceived to be present in current data. The second provides a list of action items that can be taken by the utilities, to improve both present detection methods and any algorithms that may be developed in the future. 64 refs., 39 figs., 32 figs.
Motion object tracking algorithm using multi-cameras
NASA Astrophysics Data System (ADS)
Kong, Xiaofang; Chen, Qian; Gu, Guohua
2015-09-01
Motion object tracking is one of the most important research directions in computer vision. Challenges in designing a robust tracking method are usually caused by partial or complete occlusions on targets. However, motion object tracking algorithm based on multiple cameras according to the homography relation in three views can deal with this issue effectively since the information combining from multiple cameras in different views can make the target more complete and accurate. In this paper, a robust visual tracking algorithm based on the homography relations of three cameras in different views is presented to cope with the occlusion. First of all, being the main contribution of this paper, the motion object tracking algorithm based on the low-rank matrix representation under the framework of the particle filter is applied to track the same target in the public region respectively in different views. The target model and the occlusion model are established and an alternating optimization algorithm is utilized to solve the proposed optimization formulation while tracking. Then, we confirm the plane in which the target has the largest occlusion weight to be the principal plane and calculate the homography to find out the mapping relations between different views. Finally, the images of the other two views are projected into the main plane. By making use of the homography relation between different views, the information of the occluded target can be obtained completely. The proposed algorithm has been examined throughout several challenging image sequences, and experiments show that it overcomes the failure of the motion tracking especially under the situation of the occlusion. Besides, the proposed algorithm improves the accuracy of the motion tracking comparing with other state-of-the-art 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.
Squint mode SAR processing algorithms
NASA Technical Reports Server (NTRS)
Chang, C. Y.; Jin, M.; Curlander, J. C.
1989-01-01
The unique characteristics of a spaceborne SAR (synthetic aperture radar) operating in a squint mode include large range walk and large variation in the Doppler centroid as a function of range. A pointing control technique to reduce the Doppler drift and a new processing algorithm to accommodate large range walk are presented. Simulations of the new algorithm for squint angles up to 20 deg and look angles up to 44 deg for the Earth Observing System (Eos) L-band SAR configuration demonstrate that it is capable of maintaining the resolution broadening within 20 percent and the ISLR within a fraction of a decibel of the theoretical value.
ALGORITHM DEVELOPMENT FOR SPATIAL OPERATORS.
Claire, Robert W.
1984-01-01
An approach is given that develops spatial operators about the basic geometric elements common to spatial data structures. In this fashion, a single set of spatial operators may be accessed by any system that reduces its operands to such basic generic representations. Algorithms based on this premise have been formulated to perform operations such as separation, overlap, and intersection. Moreover, this generic approach is well suited for algorithms that exploit concurrent properties of spatial operators. The results may provide a framework for a geometry engine to support fundamental manipulations within a geographic information system.
Born approximation, scattering, and algorithm
NASA Astrophysics Data System (ADS)
Martinez, Alex; Hu, Mengqi; Gu, Haicheng; Qiao, Zhijun
2015-05-01
In the past few decades, there were many imaging algorithms designed in the case of the absence of multiple scattering. Recently, we discussed an algorithm for removing high order scattering components from collected data. This paper is a continuation of our previous work. First, we investigate the current state of multiple scattering in SAR. Then, we revise our method and test it. Given an estimate of our target reflectivity, we compute the multi scattering effects in the target region for various frequencies. Furthermore, we propagate this energy through free space towards our antenna, and remove it from the collected data.
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.
ERIC Educational Resources Information Center
Meredith, Larry D.
Project Success consists of after-school, weekend, and summer educational programs geared toward minority and disadvantaged students to increase their numbers seeking postsecondary education from the Meadville, Pennsylvania area. The project is funded primarily through the Edinboro University of Pennsylvania, whose administration is committed to…
ERIC Educational Resources Information Center
Chemical and Engineering News, 1986
1986-01-01
Reports on Project SEED (Summer Educational Experience for the Disadvantaged) a project in which high school students from low-income families work in summer jobs in a variety of academic, industrial, and government research labs. The program introduces the students to career possibilities in chemistry and to the advantages of higher education.…
ERIC Educational Resources Information Center
Alvord, David J.; Tack, Leland R.; Dallam, Jerald W.
1998-01-01
Describes the development of Project EASIER, a collaborative electronic-data interchange for networking Iowa local school districts, education agencies, community colleges, universities, and the Department of Education. The primary goal of this project is to develop and implement a system for collection of student information for state and federal…
ERIC Educational Resources Information Center
Essexville-Hampton Public Schools, MI.
Described are components of Project FAST (Functional Analysis Systems Training) a nationally validated project to provide more effective educational and support services to learning disordered children and their regular elementary classroom teachers. The program is seen to be based on a series of modules of delivery systems ranging from mainstream…
Reconstruction algorithm improving the spatial resolution of Micro-CT
NASA Astrophysics Data System (ADS)
Fu, Jian; Wei, Dongbo; Li, Bing; Zhang, Lei
2008-03-01
X-ray Micro computed tomography (Micro-CT) enables nondestructive visualization of the internal structure of objects with high-resolution images and plays an important role for industrial nondestructive testing, material evaluation and medical researches. Because the micro focus is much smaller than the ordinary focus, the geometry un-sharpness of Micro-CT projection is several decuples less than that of ordinary CT systems. So the scan conditions with high geometry magnification can be adopted to acquire the projection data with high sampling frequency. Based on this feature, a new filter back projection reconstruction algorithm is researched to improve the spatial resolution of Micro-CT. This algorithm permits the reconstruction center at any point on the line connecting the focus and the rotation center. It can reconstruct CT images with different geometry magnification by adjusting the position of the reconstruction center. So it can make the best of the above feature to improve the spatial resolution of Micro-CT. The computer simulation and the CT experiment of a special spatial resolution phantom are executed to check the validity of this method. The results demonstrate the effect of the new algorithm. Analysis shows that the spatial resolution can be improved 50%.
A fast optimization algorithm for multicriteria intensity modulated proton therapy planning
Chen Wei; Craft, David; Madden, Thomas M.; Zhang, Kewu; Kooy, Hanne M.; Herman, Gabor T.
2010-09-15
Purpose: To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. Methods: The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. Results: The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK's interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. Conclusions: The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.
A fast optimization algorithm for multicriteria intensity modulated proton therapy planning
Chen, Wei; Craft, David; Madden, Thomas M.; Zhang, Kewu; Kooy, Hanne M.; Herman, Gabor T.
2010-01-01
Purpose: To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. Methods: The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. Results: The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK’s interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. Conclusions: The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization. PMID:20964213
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.
Blind Alley Aware ACO Routing Algorithm
NASA Astrophysics Data System (ADS)
Yoshikawa, Masaya; Otani, Kazuo
2010-10-01
The routing problem is applied to various engineering fields. Many researchers study this problem. In this paper, we propose a new routing algorithm which is based on Ant Colony Optimization. The proposed algorithm introduces the tabu search mechanism to escape the blind alley. Thus, the proposed algorithm enables to find the shortest route, even if the map data contains the blind alley. Experiments using map data prove the effectiveness in comparison with Dijkstra algorithm which is the most popular conventional routing algorithm.
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.
A Parallel Processing Algorithm for Gravity Inversion
NASA Astrophysics Data System (ADS)
Frasheri, Neki; Bushati, Salvatore; Frasheri, Alfred
2013-04-01
The paper presents results of using MPI parallel processing for the 3D inversion of gravity anomalies. The work is done under the FP7 project HP-SEE (http://www.hp-see.eu/). The inversion of geophysical anomalies remains a challenge, and the use of parallel processing can be a tool to achieve better results, "compensating" the complexity of the ill-posed problem of inversion with the increase of volume of calculations. We considered the gravity as the simplest case of physical fields and experimented an algorithm based in the methodology known as CLEAN and developed by Högbom in 1974. The 3D geosection was discretized in finite cuboid elements and represented by a 3D array of nodes, while the ground surface where the anomaly is observed as a 2D array of points. Starting from a geosection with mass density zero in all nodes, iteratively the algorithm defines the 3D node that offers the best anomaly shape that approximates the observed anomaly minimizing the least squares error; the mass density in the best 3D node is modified with a prefixed density step and the related effect subtracted from the observed anomaly; the process continues until some criteria is fulfilled. Theoretical complexity of he algorithm was evaluated on the basis of iterations and run-time for a geosection discretized in different scales. We considered the average number N of nodes in one edge of the 3D array. The order of number of iterations was evaluated O(N^3); and the order of run-time was evaluated O(N^8). We used several different methods for the identification of the 3D node which effect offers the best least squares error in approximating the observed anomaly: unweighted least squares error for the whole 2D array of anomalous points; weighting least squares error by the inverted value of observed anomaly over each 3D node; and limiting the area of 2D anomalous points where least squares are calculated over shallow 3D nodes. By comparing results from the inversion of single body and two
Linear array implementation of the EM algorithm for PET image reconstruction
Rajan, K.; Patnaik, L.M.; Ramakrishna, J.
1995-08-01
The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution back projection algorithms. However, the PET image reconstruction based on the EM algorithm is computationally burdensome for today`s single processor systems. In addition, a large memory is required for the storage of the image, projection data, and the probability matrix. Since the computations are easily divided into tasks executable in parallel, multiprocessor configurations are the ideal choice for fast execution of the EM algorithms. In tis study, the authors attempt to overcome these two problems by parallelizing the EM algorithm on a multiprocessor systems. The parallel EM algorithm on a linear array topology using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PE`s) has been implemented. The performance of the EM algorithm on a 386/387 machine, IBM 6000 RISC workstation, and on the linear array system is discussed and compared. The results show that the computational speed performance of a linear array using 8 DSP chips as PE`s executing the EM image reconstruction algorithm is about 15.5 times better than that of the IBM 6000 RISC workstation. The novelty of the scheme is its simplicity. The linear array topology is expandable with a larger number of PE`s. The architecture is not dependant on the DSP chip chosen, and the substitution of the latest DSP chip is straightforward and could yield better speed performance.
Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci
NASA Astrophysics Data System (ADS)
Kosmale, Miriam; Popp, Thomas
2016-04-01
Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.
Kim, Ye-seul; Park, Hye-suk; Lee, Haeng-Hwa; Choi, Young-Wook; Choi, Jae-Gu; Kim, Hak Hee; Kim, Hee-Joung
2016-02-01
Digital breast tomosynthesis (DBT) is a recently developed system for three-dimensional imaging that offers the potential to reduce the false positives of mammography by preventing tissue overlap. Many qualitative evaluations of digital breast tomosynthesis were previously performed by using a phantom with an unrealistic model and with heterogeneous background and noise, which is not representative of real breasts. The purpose of the present work was to compare reconstruction algorithms for DBT by using various breast phantoms; validation was also performed by using patient images. DBT was performed by using a prototype unit that was optimized for very low exposures and rapid readout. Three algorithms were compared: a back-projection (BP) algorithm, a filtered BP (FBP) algorithm, and an iterative expectation maximization (EM) algorithm. To compare the algorithms, three types of breast phantoms (homogeneous background phantom, heterogeneous background phantom, and anthropomorphic breast phantom) were evaluated, and clinical images were also reconstructed by using the different reconstruction algorithms. The in-plane image quality was evaluated based on the line profile and the contrast-to-noise ratio (CNR), and out-of-plane artifacts were evaluated by means of the artifact spread function (ASF). Parenchymal texture features of contrast and homogeneity were computed based on reconstructed images of an anthropomorphic breast phantom. The clinical images were studied to validate the effect of reconstruction algorithms. The results showed that the CNRs of masses reconstructed by using the EM algorithm were slightly higher than those obtained by using the BP algorithm, whereas the FBP algorithm yielded much lower CNR due to its high fluctuations of background noise. The FBP algorithm provides the best conspicuity for larger calcifications by enhancing their contrast and sharpness more than the other algorithms; however, in the case of small-size and low
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.
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
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.
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.
Adaptive color image watermarking algorithm
NASA Astrophysics Data System (ADS)
Feng, Gui; Lin, Qiwei
2008-03-01
As a major method for intellectual property right protecting, digital watermarking techniques have been widely studied and used. But due to the problems of data amount and color shifted, watermarking techniques on color image was not so widespread studied, although the color image is the principal part for multi-medium usages. Considering the characteristic of Human Visual System (HVS), an adaptive color image watermarking algorithm is proposed in this paper. In this algorithm, HSI color model was adopted both for host and watermark image, the DCT coefficient of intensity component (I) of the host color image was used for watermark date embedding, and while embedding watermark the amount of embedding bit was adaptively changed with the complex degree of the host image. As to the watermark image, preprocessing is applied first, in which the watermark image is decomposed by two layer wavelet transformations. At the same time, for enhancing anti-attack ability and security of the watermarking algorithm, the watermark image was scrambled. According to its significance, some watermark bits were selected and some watermark bits were deleted as to form the actual embedding data. The experimental results show that the proposed watermarking algorithm is robust to several common attacks, and has good perceptual quality at the same time.
Simultaneous stabilization using genetic algorithms
Benson, R.W.; Schmitendorf, W.E. . Dept. of Mechanical Engineering)
1991-01-01
This paper considers the problem of simultaneously stabilizing a set of plants using full state feedback. The problem is converted to a simple optimization problem which is solved by a genetic algorithm. Several examples demonstrate the utility of this method. 14 refs., 8 figs.
Detection Algorithms: FFT vs. KLT
NASA Astrophysics Data System (ADS)
Maccone, Claudio
Given the vast distances between the stars, we can anticipate that any received SETI signal will be exceedingly weak. How can we hope to extract (or even recognize) such signals buried well beneath the natural background noise with which they must compete? This chapter analyzes, compares, and contrasts the two dominant signal detection algorithms used by SETI scientists to recognize extremely weak candidate signals.
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.
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.
Nuclear models and exact algorithms
NASA Astrophysics Data System (ADS)
Bes, D. R.; Dobaczewski, J.; Draayer, J. P.; Szymański, Z.
1992-07-01
Discussion Group E on Nuclear Models and Exact Algorithms received contributions from the following individuals: L. Egido, S. Frauendorf, F. Iachello, P. Ring, H. Sagawa, W. Satula, N. C. Schmeing, M. Vincent, A. J. Zucker. The report that follows is an attempt by the leaders of the discussion to summarize the presentations and to give an impression of the subject matter.
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.
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.
Quartic Rotation Criteria and Algorithms.
ERIC Educational Resources Information Center
Clarkson, Douglas B.; Jennrich, Robert I.
1988-01-01
Most of the current analytic rotation criteria for simple structure in factor analysis are summarized and identified as members of a general symmetric family of quartic criteria. A unified development of algorithms for orthogonal and direct oblique rotation using arbitrary criteria from this family is presented. (Author/TJH)
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…
Knowledge-based tracking algorithm
NASA Astrophysics Data System (ADS)
Corbeil, Allan F.; Hawkins, Linda J.; Gilgallon, Paul F.
1990-10-01
This paper describes the Knowledge-Based Tracking (KBT) algorithm for which a real-time flight test demonstration was recently conducted at Rome Air Development Center (RADC). In KBT processing, the radar signal in each resolution cell is thresholded at a lower than normal setting to detect low RCS targets. This lower threshold produces a larger than normal false alarm rate. Therefore, additional signal processing including spectral filtering, CFAR and knowledge-based acceptance testing are performed to eliminate some of the false alarms. TSC's knowledge-based Track-Before-Detect (TBD) algorithm is then applied to the data from each azimuth sector to detect target tracks. In this algorithm, tentative track templates are formed for each threshold crossing and knowledge-based association rules are applied to the range, Doppler, and azimuth measurements from successive scans. Lastly, an M-association out of N-scan rule is used to declare a detection. This scan-to-scan integration enhances the probability of target detection while maintaining an acceptably low output false alarm rate. For a real-time demonstration of the KBT algorithm, the L-band radar in the Surveillance Laboratory (SL) at RADC was used to illuminate a small Cessna 310 test aircraft. The received radar signal wa digitized and processed by a ST-100 Array Processor and VAX computer network in the lab. The ST-100 performed all of the radar signal processing functions, including Moving Target Indicator (MTI) pulse cancelling, FFT Doppler filtering, and CFAR detection. The VAX computers performed the remaining range-Doppler clustering, beamsplitting and TBD processing functions. The KBT algorithm provided a 9.5 dB improvement relative to single scan performance with a nominal real time delay of less than one second between illumination and display.
Construction project selection with the use of fuzzy preference relation
NASA Astrophysics Data System (ADS)
Ibadov, Nabi
2016-06-01
In the article, author describes the problem of the construction project variant selection during pre-investment phase. As a solution, the algorithm basing on fuzzy preference relation is presented. The article provides an example of the algorithm used for selection of the best variant for construction project. The choice is made basing on criteria such as: net present value (NPV), level of technological difficulty, financing possibilities, and level of organizational difficulty.
An Effective CUDA Parallelization of Projection in Iterative Tomography Reconstruction.
Xie, Lizhe; Hu, Yining; Yan, Bin; Wang, Lin; Yang, Benqiang; Liu, Wenyuan; Zhang, Libo; Luo, Limin; Shu, Huazhong; Chen, Yang
2015-01-01
Projection and back-projection are the most computationally intensive parts in Computed Tomography (CT) reconstruction, and are essential to acceleration of CT reconstruction algorithms. Compared to back-projection, parallelization efficiency in projection is highly limited by racing condition and thread unsynchronization. In this paper, a strategy of Fixed Sampling Number Projection (FSNP) is proposed to ensure the operation synchronization in the ray-driven projection with Graphical Processing Unit (GPU). Texture fetching is also used utilized to further accelerate the interpolations in both projection and back-projection. We validate the performance of this FSNP approach using both simulated and real cone-beam CT data. Experimental results show that compare to the conventional approach, the proposed FSNP method together with texture fetching is 10~16 times faster than the conventional approach based on global memory, and thus leads to more efficient iterative algorithm in CT reconstruction. PMID:26618857
An Effective CUDA Parallelization of Projection in Iterative Tomography Reconstruction
Xie, Lizhe; Hu, Yining; Yan, Bin; Wang, Lin; Yang, Benqiang; Liu, Wenyuan; Zhang, Libo; Luo, Limin; Shu, Huazhong; Chen, Yang
2015-01-01
Projection and back-projection are the most computationally intensive parts in Computed Tomography (CT) reconstruction, and are essential to acceleration of CT reconstruction algorithms. Compared to back-projection, parallelization efficiency in projection is highly limited by racing condition and thread unsynchronization. In this paper, a strategy of Fixed Sampling Number Projection (FSNP) is proposed to ensure the operation synchronization in the ray-driven projection with Graphical Processing Unit (GPU). Texture fetching is also used utilized to further accelerate the interpolations in both projection and back-projection. We validate the performance of this FSNP approach using both simulated and real cone-beam CT data. Experimental results show that compare to the conventional approach, the proposed FSNP method together with texture fetching is 10~16 times faster than the conventional approach based on global memory, and thus leads to more efficient iterative algorithm in CT reconstruction. PMID:26618857
Final Report: Algorithms for Diffractive Microscopy
Elser, Veit
2010-10-08
The phenomenal coherence and brightness of x-ray free-electron laser light sources, such as the LCLS at SLAC, have the potential of revolutionizing the investigation of structure and dynamics in the nano-domain. However, this potential will go unrealized without a similar revolution in the way the data are analyzed. While it is true that the ambitious design parameters of the LCLS have been achieved, the prospects of realizing the most publicized goal of this instrument — the imaging of individual bio-particles — remains daunting. Even with 10{sup 12} photons per x-ray pulse, the feebleness of the scattering process represents a fundamental limit that no amount of engineering ingenuity can overcome. Large bio-molecules will scatter on the order of only 10{sup 3} photons per pulse into a detector with 106 pixels; the diffraction “images” will be virtually indistinguishable from noise. Averaging such noisy signals over many pulses is not possible because the particle orientation cannot be controlled. Each noisy laser snapshot is thus confounded by the unknown viewpoint of the particle. Given the heavy DOE investment in LCLS and the profound technical challenges facing single-particle imaging, the final two years of this project have concentrated on this effort. We are happy to report that we succeeded in developing an extremely efficient algorithm that can reconstruct the shapes of particles at even the extremes of noise expected in future LCLS experiments with single bio-particles. Since this is the most important outcome of this project, the major part of this report documents this accomplishment. The theoretical techniques that were developed for the single-particle imaging project have proved useful in other imaging problems that are described at the end of the report.
Self-Correcting HVAC Controls Project Final Report
Fernandez, Nicholas; Brambley, Michael R.; Katipamula, Srinivas; Cho, Heejin; Goddard, James K.; Dinh, Liem H.
2010-01-04
This document represents the final project report for the Self-Correcting Heating, Ventilating and Air-Conditioning (HVAC) Controls Project jointly funded by Bonneville Power Administration (BPA) and the U.S. Department of Energy (DOE) Building Technologies Program (BTP). The project, initiated in October 2008, focused on exploratory initial development of self-correcting controls for selected HVAC components in air handlers. This report, along with the companion report documenting the algorithms developed, Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units (Fernandez et al. 2009), document the work performed and results of this project.
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.
ERIC Educational Resources Information Center
Drake, Charles L.
1977-01-01
Describes activities of Geodynamics Project of the Federal Council on Science and Technology, such as the application of multichannel seismic-reflection techniques to study the nature of the deep crust and upper mantle. (MLH)
ERIC Educational Resources Information Center
Austin, Marion
1982-01-01
Project Soar, a Saturday enrichment program for gifted students (6-14 years old), allows students to work intensively in a single area of interest. Examples are cited of students' work in crewel embroidery, creative writing, and biochemistry. (CL)
ERIC Educational Resources Information Center
Diffily, Deborah
2001-01-01
Integrating curriculum is important in helping children make connections within and among areas. Presents a class project for kindergarten children which came out of the students' interests and desire to build a reptile exhibit. (ASK)
NASA Astrophysics Data System (ADS)
Schlifske, Daniel; Medeiros, Henry
2016-03-01
Modern CT image reconstruction algorithms rely on projection and back-projection operations to refine an image estimate in iterative image reconstruction. A widely-used state-of-the-art technique is distance-driven projection and back-projection. While the distance-driven technique yields superior image quality in iterative algorithms, it is a computationally demanding process. This has a detrimental effect on the relevance of the algorithms in clinical settings. A few methods have been proposed for enhancing the distance-driven technique in order to take advantage of modern computer hardware. This paper explores a two-dimensional extension of the branchless method proposed by Samit Basu and Bruno De Man. The extension of the branchless method is named "pre-integration" because it achieves a significant performance boost by integrating the data before the projection and back-projection operations. It was written with Nvidia's CUDA platform and carefully designed for massively parallel GPUs. The performance and the image quality of the pre-integration method were analyzed. Both projection and back-projection are significantly faster with preintegration. The image quality was analyzed using cone beam image reconstruction algorithms within Jeffrey Fessler's Image Reconstruction Toolbox. Images produced from regularized, iterative image reconstruction algorithms using the pre-integration method show no significant impact to image quality.
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.
Why is Boris algorithm so good?
Qin, Hong; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08543 ; Zhang, Shuangxi; Xiao, Jianyuan; Liu, Jian; Sun, Yajuan; Tang, William M.
2013-08-15
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this paper, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms
NASA Astrophysics Data System (ADS)
de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team
2011-12-01
The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for
Binocular self-calibration performed via adaptive genetic algorithm based on laser line imaging
NASA Astrophysics Data System (ADS)
Apolinar Muñoz Rodríguez, J.; Mejía Alanís, Francisco Carlos
2016-07-01
An accurate technique to perform binocular self-calibration by means of an adaptive genetic algorithm based on a laser line is presented. In this calibration, the genetic algorithm computes the vision parameters through simulated binary crossover (SBX). To carry it out, the genetic algorithm constructs an objective function from the binocular geometry of the laser line projection. Then, the SBX minimizes the objective function via chromosomes recombination. In this algorithm, the adaptive procedure determines the search space via line position to obtain the minimum convergence. Thus, the chromosomes of vision parameters provide the minimization. The approach of the proposed adaptive genetic algorithm is to calibrate and recalibrate the binocular setup without references and physical measurements. This procedure leads to improve the traditional genetic algorithms, which calibrate the vision parameters by means of references and an unknown search space. It is because the proposed adaptive algorithm avoids errors produced by the missing of references. Additionally, the three-dimensional vision is carried out based on the laser line position and vision parameters. The contribution of the proposed algorithm is corroborated by an evaluation of accuracy of binocular calibration, which is performed via traditional genetic algorithms.
Possible quantum algorithms for the Bollobas-Riordan-Tutte polynomial of a ribbon graph
NASA Astrophysics Data System (ADS)
Vélez, Mario; Ospina, Juan
2008-04-01
Three possible quantum algorithms, for the computation of the Bollobás-Riordan-Tutte polynomial of a given ribbon graph, are presented and discussed. The first possible algorithm is based on the spanning quasi-trees expansion for generalized Tutte polynomials of generalized graphs and on a quantum version of the Binary Decision Diagram (BDD) for quasi-trees . The second possible algorithm is based on the relation between the Kauffman bracket and the Tutte polynomial; and with an application of the recently introduced Aharonov-Arad-Eban-Landau quantum algorithm. The third possible algorithm is based on the relation between the HOMFLY polynomial and the Tutte polynomial; and with an application of the Wocjan-Yard quantum algorithm. It is claimed that these possible algorithms may be more efficient that the best known classical algorithms. These three algorithms may have interesting applications in computer science at general or in computational biology and bio-informatics in particular. A line for future research based on the categorification project is mentioned.
Advanced three-dimensional Eulerian hydrodynamic algorithm development
Rider, W.J.; Kothe, D.B.; Mosso, S.
1998-11-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The purpose of this project is to investigate, implement, and evaluate algorithms that have high potential for improving the robustness, fidelity and accuracy of three-dimensional Eulerian hydrodynamic simulations. Eulerian computations are necessary to simulate a number of important physical phenomena ranging from the molding process for metal parts to nuclear weapons safety issues to astrophysical phenomena such as that associated with a Type 2 supernovae. A number of algorithmic issues were explored in the course of this research including interface/volume tracking, surface physics integration, high resolution integration techniques, multilevel iterative methods, multimaterial hydrodynamics and coupling radiation with hydrodynamics. This project combines core strengths of several Laboratory divisions. The project has high institutional benefit given the renewed emphasis on numerical simulations in Science-Based Stockpile Stewardship and the Accelerated Strategic Computing Initiative and LANL`s tactical goals related to high performance computing and simulation.
Reconstruction of rainfall events responsible for landslides using an algorithm
NASA Astrophysics Data System (ADS)
Melillo, Massimo; Brunetti, Maria Teresa; Gariano, Stefano Luigi; Guzzetti, Fausto; Peruccacci, Silvia
2014-05-01
In Italy, intense or prolonged rainfall is the primary trigger of damaging landslides. The identification of the rainfall conditions responsible for the initiation of landslides is a crucial issue and may contribute to reduce landslide risk. Objective criteria for the identification of rainfall conditions that could initiate slope failures are still lacking or ambiguous. The reconstruction of rainfall events able to trigger past landslides is usually performed manually by expert investigators. Here, we propose an algorithm that reconstructs automatically rainfall events from a series of hourly rainfall data. The automatic reconstruction reproduces the actions performed by an expert investigator that adopts empirical rules to define rainfall conditions that presumably initiated the documented landslides. The algorithm, which is implemented in R (http://www.r-project.org), performs three actions on the data series: (i) removes isolated events with negligible amount of rainfall and random noise generated by the rain gauge; (ii) aggregates rainfall measurements in order to obtain a sequence of distinct rainfall events; (iii) identifies single or multiple rainfall conditions responsible for the slope failures. In particular, the algorithm calculates the duration, D, and the cumulated rainfall, E, for rainfall events, and for rainfall conditions that have resulted in landslides. A set of input parameters allows the automatic reconstruction of rainfall events in different physical settings and climatic conditions. We tested the algorithm using rainfall and landslide information available to us for Sicily, Southern Italy, in the period between January 2002 and December 2012. The algorithm reconstructed 13,537 rainfall events and 343 rainfall conditions as possible triggers of the 163 documented landslides. Most (87.7%) of the rainfall conditions obtained manually were reconstructed accurately. Use of the algorithm shall contribute to an objective and reproducible
Algorithms for computing and integrating physical maps using unique probes.
Jain, M; Myers, E W
1997-01-01
Current physical mapping projects based on STS-probes involve additional clues such as the fact that some probes are anchored to a known map and that others come from the ends of clones. Because of the disparate combinatorial contributions of these varied data items, it is difficult to design a "tailored" algorithm that incorporates them all. Moreover, it is inevitable that new experiments will provide new kinds of data, making obsolete any such algorithm. We show how to convert the physical mapping problem into a 0/1 linear programming (LP) problem. We further show how one can incorporate additional clues as additional constraints in the LP formulation. We give a simple relaxation of the 0/1 LP problem, which solves problems of the same scale as previously reported tailored algorithms, to equal or greater optimization levels. We also present a theorem proving that when the data is 100% accurate, then the relaxed and integer solutions coincide. The LP algorithm suffices to solve problems on the order of 80-100 probes--the typical size of the 2- or 3-connected contigs of Arratia et al. (1991). We give a heuristic algorithm which attempts to order and link the set of LP-solved contigs. Unlike previous work, this algorithm only links and orders contigs when the join is 90% or more likely to be correct. It is our view that there is no value in computing an optimal solution with respect to some criteria over very noisy data as this optimal solution rarely corresponds to the true solution. The paper involves extensive empirical trials over real and simulated data. PMID:9385539
Measurement-based quantum phase estimation algorithm for finding eigenvalues of non-unitary matrices
Wang Hefeng; Nori, Franco; Wu Lianao; Liu Yuxi
2010-12-15
We propose a quantum algorithm for finding eigenvalues of non-unitary matrices. We show how to construct, through interactions in a quantum system and projective measurements, a non-Hermitian or non-unitary matrix and obtain its eigenvalues and eigenvectors. This proposal combines ideas of frequent measurement, measured quantum Fourier transform, and quantum state tomography. It provides a generalization of the conventional phase estimation algorithm, which is limited to Hermitian or unitary matrices.
Higher-Order, Space-Time Adaptive Finite Volume Methods: Algorithms, Analysis and Applications
Minion, Michael
2014-04-29
The four main goals outlined in the proposal for this project were: 1. Investigate the use of higher-order (in space and time) finite-volume methods for fluid flow problems. 2. Explore the embedding of iterative temporal methods within traditional block-structured AMR algorithms. 3. Develop parallel in time methods for ODEs and PDEs. 4. Work collaboratively with the Center for Computational Sciences and Engineering (CCSE) at Lawrence Berkeley National Lab towards incorporating new algorithms within existing DOE application codes.
Systolic algorithms and their implementation
Kung, H.T.
1984-01-01
Very high performance computer systems must rely heavily on parallelism since there are severe physical and technological limits on the ultimate speed of any single processor. The systolic array concept developed in the last several years allows effective use of a very large number of processors in parallel. This article illustrates the basic ideas by reviewing a systolic array design for matrix triangularization and describing its use in the on-the-fly updating of Cholesky decomposition of covariance matrices-a crucial computation in adaptive signal processing. Following this are discussions on issues related to the hardware implementation of systolic algorithms in general, and some guidelines for designing systolic algorithms that will be convenient for implementation. 33 references.
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.
NASA Technical Reports Server (NTRS)
Loewenstein, M.; Greenblatt. B. J.; Jost, H.; Podolske, J. R.; Elkins, Jim; Hurst, Dale; Romanashkin, Pavel; Atlas, Elliott; Schauffler, Sue; Donnelly, Steve; Condon, Estelle (Technical Monitor)
2000-01-01
De-nitrification and excess re-nitrification was widely observed by ER-2 instruments in the Arctic vortex during SOLVE in winter/spring 2000. Analyses of these events requires a knowledge of the initial or pre-vortex state of the sampled air masses. The canonical relationship of NOy to the long-lived tracer N2O observed in the unperturbed stratosphere is generally used for this purpose. In this paper we will attempt to establish the current unperturbed NOy:N2O relationship (NOy* algorithm) using the ensemble of extra-vortex data from in situ instruments flying on the ER-2 and DC-8, and from the Mark IV remote measurements on the OMS balloon. Initial analysis indicates a change in the SOLVE NOy* from the values predicted by the 1994 Northern Hemisphere NOy* algorithm which was derived from the observations in the ASHOE/MAESA campaign.
A spectral canonical electrostatic algorithm
NASA Astrophysics Data System (ADS)
Webb, Stephen D.
2016-03-01
Studying single-particle dynamics over many periods of oscillations is a well-understood problem solved using symplectic integration. Such integration schemes derive their update sequence from an approximate Hamiltonian, guaranteeing that the geometric structure of the underlying problem is preserved. Simulating a self-consistent system over many oscillations can introduce numerical artifacts such as grid heating. This unphysical heating stems from using non-symplectic methods on Hamiltonian systems. With this guidance, we derive an electrostatic algorithm using a discrete form of Hamilton’s principle. The resulting algorithm, a gridless spectral electrostatic macroparticle model, does not exhibit the unphysical heating typical of most particle-in-cell methods. We present results of this using a two-body problem as an example of the algorithm’s energy- and momentum-conserving properties.
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
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
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.
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.
Optimisation algorithms for microarray biclustering.
Perrin, Dimitri; Duhamel, Christophe
2013-01-01
In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic Algorithms. We also introduce a new heuristic "Propagate", which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme, optimal or near-optimal solutions can be identified. PMID:24109756
A possible hypercomputational quantum algorithm
NASA Astrophysics Data System (ADS)
Sicard, Andres; Velez, Mario; Ospina, Juan
2005-05-01
The term 'hypermachine' denotes any data processing device (theoretical or that can be implemented) capable of carrying out tasks that cannot be performed by a Turing machine. We present a possible quantum algorithm for a classically non-computable decision problem, Hilbert's tenth problem; more specifically, we present a possible hypercomputation model based on quantum computation. Our algorithm is inspired by the one proposed by Tien D. Kieu, but we have selected the infinite square well instead of the (one-dimensional) simple harmonic oscillator as the underlying physical system. Our model exploits the quantum adiabatic process and the characteristics of the representation of the dynamical Lie algebra su(1,1) associated to the infinite square well.
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.
Daylighting simulation: methods, algorithms, and resources
Carroll, William L.
1999-12-01
This document presents work conducted as part of Subtask C, ''Daylighting Design Tools'', Subgroup C2, ''New Daylight Algorithms'', of the IEA SHC Task 21 and the ECBCS Program Annex 29 ''Daylight in Buildings''. The search for and collection of daylighting analysis methods and algorithms led to two important observations. First, there is a wide range of needs for different types of methods to produce a complete analysis tool. These include: Geometry; Light modeling; Characterization of the natural illumination resource; Materials and components properties, representations; and Usability issues (interfaces, interoperability, representation of analysis results, etc). Second, very advantageously, there have been rapid advances in many basic methods in these areas, due to other forces. They are in part driven by: The commercial computer graphics community (commerce, entertainment); The lighting industry; Architectural rendering and visualization for projects; and Academia: Course materials, research. This has led to a very rich set of information resources that have direct applicability to the small daylighting analysis community. Furthermore, much of this information is in fact available online. Because much of the information about methods and algorithms is now online, an innovative reporting strategy was used: the core formats are electronic, and used to produce a printed form only secondarily. The electronic forms include both online WWW pages and a downloadable .PDF file with the same appearance and content. Both electronic forms include live primary and indirect links to actual information sources on the WWW. In most cases, little additional commentary is provided regarding the information links or citations that are provided. This in turn allows the report to be very concise. The links are expected speak for themselves. The report consists of only about 10+ pages, with about 100+ primary links, but with potentially thousands of indirect links. For purposes of
DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks.
Estévez, Francisco José; Glösekötter, Peter; González, Jesús
2016-01-01
The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities. PMID:27347962
Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.
Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu
2015-08-01
This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm. PMID:25265622
ASYMPTOTICALLY OPTIMAL HIGH-ORDER ACCURATE ALGORITHMS FOR THE SOLUTION OF CERTAIN ELLIPTIC PDEs
Leonid Kunyansky, PhD
2008-11-26
The main goal of the project, "Asymptotically Optimal, High-Order Accurate Algorithms for the Solution of Certain Elliptic PDE's" (DE-FG02-03ER25577) was to develop fast, high-order algorithms for the solution of scattering problems and spectral problems of photonic crystals theory. The results we obtained lie in three areas: (1) asymptotically fast, high-order algorithms for the solution of eigenvalue problems of photonics, (2) fast, high-order algorithms for the solution of acoustic and electromagnetic scattering problems in the inhomogeneous media, and (3) inversion formulas and fast algorithms for the inverse source problem for the acoustic wave equation, with applications to thermo- and opto- acoustic tomography.
Martinez-Canales, Monica L.; Heaphy, Robert; Gramacy, Robert B.; Taddy, Matt; Chiesa, Michael L.; Thomas, Stephen W.; Swiler, Laura Painton; Hough, Patricia Diane; Lee, Herbert K. H.; Trucano, Timothy Guy; Gray, Genetha Anne
2006-11-01
This project focused on research and algorithmic development in optimization under uncertainty (OUU) problems driven by earth penetrator (EP) designs. While taking into account uncertainty, we addressed three challenges in current simulation-based engineering design and analysis processes. The first challenge required leveraging small local samples, already constructed by optimization algorithms, to build effective surrogate models. We used Gaussian Process (GP) models to construct these surrogates. We developed two OUU algorithms using 'local' GPs (OUU-LGP) and one OUU algorithm using 'global' GPs (OUU-GGP) that appear competitive or better than current methods. The second challenge was to develop a methodical design process based on multi-resolution, multi-fidelity models. We developed a Multi-Fidelity Bayesian Auto-regressive process (MF-BAP). The third challenge involved the development of tools that are computational feasible and accessible. We created MATLAB{reg_sign} and initial DAKOTA implementations of our algorithms.
A block-wise approximate parallel implementation for ART algorithm on CUDA-enabled GPU.
Fan, Zhongyin; Xie, Yaoqin
2015-01-01
Computed tomography (CT) has been widely used to acquire volumetric anatomical information in the diagnosis and treatment of illnesses in many clinics. However, the ART algorithm for reconstruction from under-sampled and noisy projection is still time-consuming. It is the goal of our work to improve a block-wise approximate parallel implementation for the ART algorithm on CUDA-enabled GPU to make the ART algorithm applicable to the clinical environment. The resulting method has several compelling features: (1) the rays are allotted into blocks, making the rays in the same block parallel; (2) GPU implementation caters to the actual industrial and medical application demand. We test the algorithm on a digital shepp-logan phantom, and the results indicate that our method is more efficient than the existing CPU implementation. The high computation efficiency achieved in our algorithm makes it possible for clinicians to obtain real-time 3D images. PMID:26405857
DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks
Estévez, Francisco José; Glösekötter, Peter; González, Jesús
2016-01-01
The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities. PMID:27347962
Systolic systems: algorithms and complexity
Chang, J.H.
1986-01-01
This thesis has two main contributions. The first is the design of efficient systolic algorithms for solving recurrence equations, dynamic programming problems, scheduling problems, as well as new systolic implementation of data structures such as stacks, queues, priority queues, and dictionary machines. The second major contribution is the investigation of the computational power of systolic arrays in comparison to sequential models and other models of parallel computation.
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.
Algorithms of NCG geometrical module
NASA Astrophysics Data System (ADS)
Gurevich, M. I.; Pryanichnikov, A. V.
2012-12-01
The methods and algorithms of the versatile NCG geometrical module used in the MCU code system are described. The NCG geometrical module is based on the Monte Carlo method and intended for solving equations of particle transport. The versatile combinatorial body method, the grid method, and methods of equalized cross sections and grain structures are used for description of the system geometry and calculation of trajectories.
Algorithms of NCG geometrical module
Gurevich, M. I.; Pryanichnikov, A. V.
2012-12-15
The methods and algorithms of the versatile NCG geometrical module used in the MCU code system are described. The NCG geometrical module is based on the Monte Carlo method and intended for solving equations of particle transport. The versatile combinatorial body method, the grid method, and methods of equalized cross sections and grain structures are used for description of the system geometry and calculation of trajectories.
Computed laminography and reconstruction algorithm
NASA Astrophysics Data System (ADS)
Que, Jie-Min; Cao, Da-Quan; Zhao, Wei; Tang, Xiao; Sun, Cui-Li; Wang, Yan-Fang; Wei, Cun-Feng; Shi, Rong-Jian; Wei, Long; Yu, Zhong-Qiang; Yan, Yong-Lian
2012-08-01
Computed laminography (CL) is an alternative to computed tomography if large objects are to be inspected with high resolution. This is especially true for planar objects. In this paper, we set up a new scanning geometry for CL, and study the algebraic reconstruction technique (ART) for CL imaging. We compare the results of ART with variant weighted functions by computer simulation with a digital phantom. It proves that ART algorithm is a good choice for the CL system.
Efficient algorithms for proximity problems
Wee, Y.C.
1989-01-01
Computational geometry is currently a very active area of research in computer science because of its applications to VLSI design, database retrieval, robotics, pattern recognition, etc. The author studies a number of proximity problems which are fundamental in computational geometry. Optimal or improved sequential and parallel algorithms for these problems are presented. Along the way, some relations among the proximity problems are also established. Chapter 2 presents an O(N log{sup 2} N) time divide-and-conquer algorithm for solving the all pairs geographic nearest neighbors problem (GNN) for a set of N sites in the plane under any L{sub p} metric. Chapter 3 presents an O(N log N) divide-and-conquer algorithm for computing the angle restricted Voronoi diagram for a set of N sites in the plane. Chapter 4 introduces a new data structure for the dynamic version of GNN. Chapter 5 defines a new formalism called the quasi-valid range aggregation. This formalism leads to a new and simple method for reducing non-range query-like problems to range queries and often to orthogonal range queries, with immediate applications to the attracted neighbor and the planar all-pairs nearest neighbors problem. Chapter 6 introduces a new approach for the construction of the Voronoi diagram. Using this approach, we design an O(log N) time O (N) processor algorithm for constructing the Voronoi diagram with L{sub 1} and L. metrics on a CREW PRAM machine. Even though the GNN and the Delaunay triangulation (DT) do not have an inclusion relation, we show, using some range type queries, how to efficiently construct DT from the GNN relations over a constant number of angular ranges.
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.
Algorithmic Strategies in Combinatorial Chemistry
GOLDMAN,DEBORAH; ISTRAIL,SORIN; LANCIA,GIUSEPPE; PICCOLBONI,ANTONIO; WALENZ,BRIAN
2000-08-01
Combinatorial Chemistry is a powerful new technology in drug design and molecular recognition. It is a wet-laboratory methodology aimed at ``massively parallel'' screening of chemical compounds for the discovery of compounds that have a certain biological activity. The power of the method comes from the interaction between experimental design and computational modeling. Principles of ``rational'' drug design are used in the construction of combinatorial libraries to speed up the discovery of lead compounds with the desired biological activity. This paper presents algorithms, software development and computational complexity analysis for problems arising in the design of combinatorial libraries for drug discovery. The authors provide exact polynomial time algorithms and intractability results for several Inverse Problems-formulated as (chemical) graph reconstruction problems-related to the design of combinatorial libraries. These are the first rigorous algorithmic results in the literature. The authors also present results provided by the combinatorial chemistry software package OCOTILLO for combinatorial peptide design using real data libraries. The package provides exact solutions for general inverse problems based on shortest-path topological indices. The results are superior both in accuracy and computing time to the best software reports published in the literature. For 5-peptoid design, the computation is rigorously reduced to an exhaustive search of about 2% of the search space; the exact solutions are found in a few minutes.
Algorithm validation using multicolor phantoms.
Samarov, Daniel V; Clarke, Matthew L; Lee, Ji Youn; Allen, David W; Litorja, Maritoni; Hwang, Jeeseong
2012-06-01
We present a framework for hyperspectral image (HSI) analysis validation, specifically abundance fraction estimation based on HSI measurements of water soluble dye mixtures printed on microarray chips. In our work we focus on the performance of two algorithms, the Least Absolute Shrinkage and Selection Operator (LASSO) and the Spatial LASSO (SPLASSO). The LASSO is a well known statistical method for simultaneously performing model estimation and variable selection. In the context of estimating abundance fractions in a HSI scene, the "sparse" representations provided by the LASSO are appropriate as not every pixel will be expected to contain every endmember. The SPLASSO is a novel approach we introduce here for HSI analysis which takes the framework of the LASSO algorithm a step further and incorporates the rich spatial information which is available in HSI to further improve the estimates of abundance. In our work here we introduce the dye mixture platform as a new benchmark data set for hyperspectral biomedical image processing and show our algorithm's improvement over the standard LASSO. PMID:22741077