Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms
Pacheco, Maria P.; Pfau, Thomas; Sauter, Thomas
2016-01-01
Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. PMID:26834640
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.
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
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.
Fast ordering algorithm for exact histogram specification.
Nikolova, Mila; Steidl, Gabriele
2014-12-01
This paper provides a fast algorithm to order in a meaningful, strict way the integer gray values in digital (quantized) images. It can be used in any exact histogram specification-based application. Our algorithm relies on the ordering procedure based on the specialized variational approach. This variational method was shown to be superior to all other state-of-the art ordering algorithms in terms of faithful total strict ordering but not in speed. Indeed, the relevant functionals are in general difficult to minimize because their gradient is nearly flat over vast regions. In this paper, we propose a simple and fast fixed point algorithm to minimize these functionals. The fast convergence of our algorithm results from known analytical properties of the model. Our algorithm is equivalent to an iterative nonlinear filtering. Furthermore, we show that a particular form of the variational model gives rise to much faster convergence than other alternative forms. We demonstrate that only a few iterations of this filter yield almost the same pixel ordering as the minimizer. Thus, we apply only few iteration steps to obtain images, whose pixels can be ordered in a strict and faithful way. Numerical experiments confirm that our algorithm outperforms by far its main competitors. PMID:25347881
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.
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.
Specific optimization of genetic algorithm on special algebras
NASA Astrophysics Data System (ADS)
Habiballa, Hashim; Novak, Vilem; Dyba, Martin; Schenk, Jiri
2016-06-01
Searching for complex finite algebras can be succesfully done by the means of genetic algorithm as we showed in former works. This genetic algorithm needs specific optimization of crossover and mutation. We present details about these optimizations which are already implemented in software application for this task - EQCreator.
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.
Sequence-Specific Copolymer Compatibilizers designed via a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Meenakshisundaram, Venkatesh; Patra, Tarak; Hung, Jui-Hsiang; Simmons, David
For several decades, block copolymers have been employed as surfactants to reduce interfacial energy for applications from emulsification to surface adhesion. While the simplest approach employs symmetric diblocks, studies have examined asymmetric diblocks, multiblock copolymers, gradient copolymers, and copolymer-grafted nanoparticles. However, there exists no established approach to determining the optimal copolymer compatibilizer sequence for a given application. Here we employ molecular dynamics simulations within a genetic algorithm to identify copolymer surfactant sequences yielding maximum reductions the interfacial energy of model immiscible polymers. The optimal copolymer sequence depends significantly on surfactant concentration. Most surprisingly, at high surface concentrations, where the surfactant achieves the greatest interfacial energy reduction, specific non-periodic sequences are found to significantly outperform any regularly blocky sequence. This emergence of polymer sequence-specificity within a non-sequenced environment adds to a recent body of work suggesting that specific sequence may have the potential to play a greater role in polymer properties than previously understood. We acknowledge the W. M. Keck Foundation for financial support of this research.
GPU-specific reformulations of image compression algorithms
NASA Astrophysics Data System (ADS)
Matela, JiÅ™Ã; Holub, Petr; Jirman, Martin; Ã…rom, Martin
2012-10-01
Image compression has a number of applications in various fields, where processing throughput and/or latency is a crucial attribute and the main limitation of state-of-the-art implementations of compression algorithms. At the same time contemporary GPU platforms provide tremendous processing power but they call for specific algorithm design. We discuss key components of successful design of compression algorithms for GPUs and demonstrate this on JPEG and JPEG2000 implementations, each of which contains several types of algorithms requiring different approaches to efficient parallelization for GPUs. Performance evaluation of the optimized JPEG and JPEG2000 chain is used to demonstrate the importance of various aspects of GPU programming, especially with respect to real-time applications.
Model Specification Searches Using Ant Colony Optimization Algorithms
ERIC Educational Resources Information Center
Marcoulides, George A.; Drezner, Zvi
2003-01-01
Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.
High specific heat superconducting composite
Steyert, Jr., William A.
1979-01-01
A composite superconductor formed from a high specific heat ceramic such as gadolinium oxide or gadolinium-aluminum oxide and a conventional metal conductor such as copper or aluminum which are insolubly mixed together to provide adiabatic stability in a superconducting mode of operation. The addition of a few percent of insoluble gadolinium-aluminum oxide powder or gadolinium oxide powder to copper, increases the measured specific heat of the composite by one to two orders of magnitude below the 5.degree. K. level while maintaining the high thermal and electrical conductivity of the conventional metal conductor.
High Rate Pulse Processing Algorithms for Microcalorimeters
NASA Astrophysics Data System (ADS)
Tan, Hui; Breus, Dimitry; Hennig, Wolfgang; Sabourov, Konstantin; Collins, Jeffrey W.; Warburton, William K.; Bertrand Doriese, W.; Ullom, Joel N.; Bacrania, Minesh K.; Hoover, Andrew S.; Rabin, Michael W.
2009-12-01
It has been demonstrated that microcalorimeter spectrometers based on superconducting transition-edge-sensors can readily achieve sub-100 eV energy resolution near 100 keV. However, the active volume of a single microcalorimeter has to be small in order to maintain good energy resolution, and pulse decay times are normally on the order of milliseconds due to slow thermal relaxation. Therefore, spectrometers are typically built with an array of microcalorimeters to increase detection efficiency and count rate. For large arrays, however, as much pulse processing as possible must be performed at the front end of readout electronics to avoid transferring large amounts of waveform data to a host computer for post-processing. In this paper, we present digital filtering algorithms for processing microcalorimeter pulses in real time at high count rates. The goal for these algorithms, which are being implemented in readout electronics that we are also currently developing, is to achieve sufficiently good energy resolution for most applications while being: a) simple enough to be implemented in the readout electronics; and, b) capable of processing overlapping pulses, and thus achieving much higher output count rates than those achieved by existing algorithms. Details of our algorithms are presented, and their performance is compared to that of the "optimal filter" that is currently the predominantly used pulse processing algorithm in the cryogenic-detector community.
High rate pulse processing algorithms for microcalorimeters
Rabin, Michael; Hoover, Andrew S; Bacrania, Mnesh K; Tan, Hui; Breus, Dimitry; Henning, Wolfgang; Sabourov, Konstantin; Collins, Jeff; Warburton, William K; Dorise, Bertrand; Ullom, Joel N
2009-01-01
It has been demonstrated that microcalorimeter spectrometers based on superconducting transition-edge-sensor can readily achieve sub-100 eV energy resolution near 100 keV. However, the active volume of a single microcalorimeter has to be small to maintain good energy resolution, and pulse decay times are normally in the order of milliseconds due to slow thermal relaxation. Consequently, spectrometers are typically built with an array of microcalorimeters to increase detection efficiency and count rate. Large arrays, however, require as much pulse processing as possible to be performed at the front end of the readout electronics to avoid transferring large amounts of waveform data to a host computer for processing. In this paper, they present digital filtering algorithms for processing microcalorimeter pulses in real time at high count rates. The goal for these algorithms, which are being implemented in the readout electronics that they are also currently developing, is to achieve sufficiently good energy resolution for most applications while being (a) simple enough to be implemented in the readout electronics and (b) capable of processing overlapping pulses and thus achieving much higher output count rates than the rates that existing algorithms are currently achieving. Details of these algorithms are presented, and their performance was compared to that of the 'optimal filter' that is the dominant pulse processing algorithm in the cryogenic-detector community.
Orientation estimation algorithm applied to high-spin projectiles
NASA Astrophysics Data System (ADS)
Long, D. F.; Lin, J.; Zhang, X. M.; Li, J.
2014-06-01
High-spin projectiles are low cost military weapons. Accurate orientation information is critical to the performance of the high-spin projectiles control system. However, orientation estimators have not been well translated from flight vehicles since they are too expensive, lack launch robustness, do not fit within the allotted space, or are too application specific. This paper presents an orientation estimation algorithm specific for these projectiles. The orientation estimator uses an integrated filter to combine feedback from a three-axis magnetometer, two single-axis gyros and a GPS receiver. As a new feature of this algorithm, the magnetometer feedback estimates roll angular rate of projectile. The algorithm also incorporates online sensor error parameter estimation performed simultaneously with the projectile attitude estimation. The second part of the paper deals with the verification of the proposed orientation algorithm through numerical simulation and experimental tests. Simulations and experiments demonstrate that the orientation estimator can effectively estimate the attitude of high-spin projectiles. Moreover, online sensor calibration significantly enhances the estimation performance of the algorithm.
THE HIGH ENERGY TRANSIENT EXPLORER TRIGGERING ALGORITHM
E. FENIMORE; M. GALASSI
2001-05-01
The High Energy Transient Explorer uses a triggering algorithm for gamma-ray bursts that can achieve near the statistical limit by fitting to several background regions to remove trends. Dozens of trigger criteria run simultaneously covering time scales from 80 msec to 10.5 sec or longer. Each criteria is controlled by about 25 constants which gives the flexibility to search wide parameter spaces. On orbit, we have been able to operate at 6{sigma}, a factor of two more sensitive than previous experiments.
Brambley, Michael R.; Katipamula, Srinivas
2006-10-06
Pacific Northwest National Laboratory (PNNL) is assisting the U.S. Department of Energy (DOE) Distributed Energy (DE) Program by developing advanced control algorithms that would lead to development of tools to enhance performance and reliability, and reduce emissions of distributed energy technologies, including combined heat and power technologies. This report documents phase 2 of the program, providing a detailed functional specification for algorithms for performance monitoring and commissioning verification, scheduled for development in FY 2006. The report identifies the systems for which algorithms will be developed, the specific functions of each algorithm, metrics which the algorithms will output, and inputs required by each algorithm.
High specific activity silicon-32
Phillips, D.R.; Brzezinski, M.A.
1996-06-11
A process for preparation of silicon-32 is provided and includes contacting an irradiated potassium chloride target, including spallation products from a prior irradiation, with sufficient water, hydrochloric acid or potassium hydroxide to form a solution, filtering the solution, adjusting pH of the solution from about 5.5 to about 7.5, admixing sufficient molybdate-reagent to the solution to adjust the pH of the solution to about 1.5 and to form a silicon-molybdate complex, contacting the solution including the silicon-molybdate complex with a dextran-based material, washing the dextran-based material to remove residual contaminants such as sodium-22, separating the silicon-molybdate complex from the dextran-based material as another solution, adding sufficient hydrochloric acid and hydrogen peroxide to the solution to prevent reformation of the silicon-molybdate complex and to yield an oxidation state of the molybdate adapted for subsequent separation by an anion exchange material, contacting the solution with an anion exchange material whereby the molybdate is retained by the anion exchange material and the silicon remains in solution, and optionally adding sufficient alkali metal hydroxide to adjust the pH of the solution to about 12 to 13. Additionally, a high specific activity silicon-32 product having a high purity is provided.
High specific activity silicon-32
Phillips, Dennis R.; Brzezinski, Mark A.
1996-01-01
A process for preparation of silicon-32 is provided and includes contacting an irradiated potassium chloride target, including spallation products from a prior irradiation, with sufficient water, hydrochloric acid or potassium hydroxide to form a solution, filtering the solution, adjusting pH of the solution to from about 5.5 to about 7.5, admixing sufficient molybdate-reagent to the solution to adjust the pH of the solution to about 1.5 and to form a silicon-molybdate complex, contacting the solution including the silicon-molybdate complex with a dextran-based material, washing the dextran-based material to remove residual contaminants such as sodium-22, separating the silicon-molybdate complex from the dextran-based material as another solution, adding sufficient hydrochloric acid and hydrogen peroxide to the solution to prevent reformation of the silicon-molybdate complex and to yield an oxidization state of the molybdate adapted for subsequent separation by an anion exchange material, contacting the solution with an anion exchange material whereby the molybdate is retained by the anion exchange material and the silicon remains in solution, and optionally adding sufficient alkali metal hydroxide to adjust the pH of the solution to about 12 to 13. Additionally, a high specific activity silicon-32 product having a high purity is provided.
Generic algorithms for high performance scalable geocomputing
NASA Astrophysics Data System (ADS)
de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek
2016-04-01
During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system
Generic algorithms for high performance scalable geocomputing
NASA Astrophysics Data System (ADS)
de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek
2016-04-01
During the last decade, the characteristics of computing hardware have changed a lot. For example, instead of a single general purpose CPU core, personal computers nowadays contain multiple cores per CPU and often general purpose accelerators, like GPUs. Additionally, compute nodes are often grouped together to form clusters or a supercomputer, providing enormous amounts of compute power. For existing earth simulation models to be able to use modern hardware platforms, their compute intensive parts must be rewritten. This can be a major undertaking and may involve many technical challenges. Compute tasks must be distributed over CPU cores, offloaded to hardware accelerators, or distributed to different compute nodes. And ideally, all of this should be done in such a way that the compute task scales well with the hardware resources. This presents two challenges: 1) how to make good use of all the compute resources and 2) how to make these compute resources available for developers of simulation models, who may not (want to) have the required technical background for distributing compute tasks. The first challenge requires the use of specialized technology (e.g.: threads, OpenMP, MPI, OpenCL, CUDA). The second challenge requires the abstraction of the logic handling the distribution of compute tasks from the model-specific logic, hiding the technical details from the model developer. To assist the model developer, we are developing a C++ software library (called Fern) containing algorithms that can use all CPU cores available in a single compute node (distributing tasks over multiple compute nodes will be done at a later stage). The algorithms are grid-based (finite difference) and include local and spatial operations such as convolution filters. The algorithms handle distribution of the compute tasks to CPU cores internally. In the resulting model the low-level details of how this is done is separated from the model-specific logic representing the modeled system
Qualls, Joseph; Russomanno, David J.
2011-01-01
The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demonstrate the efficacy of the ontological problem-solving architecture, a family of persistence surveillance sensor systems and algorithms has been instantiated in a prototype environment to demonstrate the assignment of systems to subtasks of high-level missions. PMID:22164081
Design specification for the whole-body algorithm
NASA Technical Reports Server (NTRS)
Fitzjerrell, D. G.
1974-01-01
The necessary requirements and guidelines for the construction of a computer program of the whole-body algorithm are presented. The minimum subsystem models required to effectively simulate the total body response to stresses of interest are (1) cardiovascular (exercise/LBNP/tilt); (2) respiratory (Grodin's model); (3) thermoregulatory (Stolwijk's model); and (4) long-term circulatory fluid and electrolyte (Guyton's model). The whole-body algorithm must be capable of simulating response to stresses from CO2 inhalation, hypoxia, thermal environmental exercise (sitting and supine), LBNP, and tilt (changing body angles in gravity).
On constructing optimistic simulation algorithms for the discrete event system specification
Nutaro, James J
2008-01-01
This article describes a Time Warp simulation algorithm for discrete event models that are described in terms of the Discrete Event System Specification (DEVS). The article shows how the total state transition and total output function of a DEVS atomic model can be transformed into an event processing procedure for a logical process. A specific Time Warp algorithm is constructed around this logical process, and it is shown that the algorithm correctly simulates a DEVS coupled model that consists entirely of interacting atomic models. The simulation algorithm is presented abstractly; it is intended to provide a basis for implementing efficient and scalable parallel algorithms that correctly simulate DEVS models.
High contrast laminography using iterative algorithms
NASA Astrophysics Data System (ADS)
Kroupa, M.; Jakubek, J.
2011-01-01
3D X-ray imaging of internal structure of large flat objects is often complicated by limited access to all viewing angles or extremely high absorption in certain directions, therefore the standard method of computed tomography (CT) fails. This problem can be solved by the method of laminography. During a laminographic measurement the imaging detector is placed close to the sample while the X-ray source irradiates both sample and detector at different angles. The application of the state-of-the-art pixel detector Medipix in laminography together with adapted tomographic iterative alghorithms for 3D reconstruction of sample structure has been investigated. Iterative algorithms such as EM (Expectation Maximization) and OSEM (Ordered Subset Expectation Maximization) improve the quality of the reconstruction and allow including more complex physical models. In this contribution results and proposed future approaches which could be used for resolution enhancement are presented.
Concurrent constant modulus algorithm and multi-modulus algorithm scheme for high-order QAM signals
NASA Astrophysics Data System (ADS)
Rao, Wei
2011-10-01
In order to overcome the slow convergence rate and large steady-state mean square error of constant modulus algorithm (CMA), a concurrent constant modulus algorithm and multi-modulus algorithm scheme for high-order QAM signals is proposed, which makes full use of the character which is that the high-order QAM signals locate in the different modulus. This algorithm uses the CMA as the basal mode. And in the second mode it uses the multi-modulus algorithm. Furthermore, the two modes operate concurrently. The efficiency of the method is proved by computer simulations in underwater acoustic channels.
GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms
NASA Technical Reports Server (NTRS)
Mach, Douglas M.; Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Petersen, William A.; Boldi, Robert A.; Carey, Lawrence D.; Bateman, Monte G.; Buchler, Dennis E.; McCaul, E. William, Jr.
2008-01-01
The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.
A Proposed India-Specific Algorithm for Management of Type 2 Diabetes.
2016-06-01
Several algorithms and guidelines have been proposed by countries and international professional bodies; however, no recent updated management algorithm is available for Asian Indians. Specifically, algorithms developed and validated in developed nations may not be relevant or applicable to patients in India because of several factors: early age of onset of diabetes, occurrence of diabetes in nonobese and sometimes lean people, differences in the relative contributions of insulin resistance and Î²-cell dysfunction, marked postprandial glycemia, frequent infections including tuberculosis, low access to healthcare and medications in people of low socioeconomic stratum, ethnic dietary practices (e.g., ingestion of high-carbohydrate diets), and inadequate education regarding hypoglycemia. All these factors should be considered to choose appropriate therapeutic option in this population. The proposed algorithm is simple, suggests less expensive drugs, and tries to provide an effective and comprehensive framework for delivery of diabetes therapy in primary care in India. The proposed guidelines agree with international recommendations in favoring individualization of therapeutic targets as well as modalities of treatment in a flexible manner suitable to the Indian population. PMID:26909751
Highly Scalable Matching Pursuit Signal Decomposition Algorithm
NASA Technical Reports Server (NTRS)
Christensen, Daniel; Das, Santanu; Srivastava, Ashok N.
2009-01-01
Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the
C-element: a new clustering algorithm to find high quality functional modules in PPI networks.
Ghasemi, Mahdieh; Rahgozar, Maseud; Bidkhori, Gholamreza; Masoudi-Nejad, Ali
2013-01-01
Graph clustering algorithms are widely used in the analysis of biological networks. Extracting functional modules in protein-protein interaction (PPI) networks is one such use. Most clustering algorithms whose focuses are on finding functional modules try either to find a clique like sub networks or to grow clusters starting from vertices with high degrees as seeds. These algorithms do not make any difference between a biological network and any other networks. In the current research, we present a new procedure to find functional modules in PPI networks. Our main idea is to model a biological concept and to use this concept for finding good functional modules in PPI networks. In order to evaluate the quality of the obtained clusters, we compared the results of our algorithm with those of some other widely used clustering algorithms on three high throughput PPI networks from Sacchromyces Cerevisiae, Homo sapiens and Caenorhabditis elegans as well as on some tissue specific networks. Gene Ontology (GO) analyses were used to compare the results of different algorithms. Each algorithm's result was then compared with GO-term derived functional modules. We also analyzed the effect of using tissue specific networks on the quality of the obtained clusters. The experimental results indicate that the new algorithm outperforms most of the others, and this improvement is more significant when tissue specific networks are used. PMID:24039752
On the importance of FIB-SEM specific segmentation algorithms for porous media
Salzer, Martin; Thiele, Simon; Zengerle, Roland; Schmidt, Volker
2014-09-15
A new algorithmic approach to segmentation of highly porous three dimensional image data gained by focused ion beam tomography is described which extends the key-principle of local threshold backpropagation described in Salzer et al. (2012). The technique of focused ion beam tomography has shown to be capable of imaging the microstructure of functional materials. In order to perform a quantitative analysis on the corresponding microstructure a segmentation task needs to be performed. However, algorithmic segmentation of images obtained with focused ion beam tomography is a challenging problem for highly porous materials if filling the pore phase, e.g. with epoxy resin, is difficult. The gray intensities of individual voxels are not sufficient to determine the phase represented by them and usual thresholding methods are not applicable. We thus propose a new approach to segmentation that pays respect to the specifics of the imaging process of focused ion beam tomography. As an application of our approach, the segmentation of three dimensional images for a cathode material used in polymer electrolyte membrane fuel cells is discussed. We show that our approach preserves significantly more of the original nanostructure than a thresholding approach. - Highlights: â€¢ We describe a new approach to the segmentation of FIB-SEM images of porous media. â€¢ The first and last occurrences of structures are detected by analysing the z-profiles. â€¢ The algorithm is validated by comparing it to a manual segmentation. â€¢ The new approach shows significantly less artifacts than a thresholding approach. â€¢ A structural analysis also shows improved results for the obtained microstructure.
Scalable Nearest Neighbor Algorithms for High Dimensional Data.
Muja, Marius; Lowe, David G
2014-11-01
For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching. PMID:26353063
High-speed scanning: an improved algorithm
NASA Astrophysics Data System (ADS)
Nachimuthu, A.; Hoang, Khoi
1995-10-01
In using machine vision for assessing an object's surface quality, many images are required to be processed in order to separate the good areas from the defective ones. Examples can be found in the leather hide grading process; in the inspection of garments/canvas on the production line; in the nesting of irregular shapes into a given surface... . The most common method of subtracting the total area from the sum of defective areas does not give an acceptable indication of how much of the `good' area can be used, particularly if the findings are to be used for the nesting of irregular shapes. This paper presents an image scanning technique which enables the estimation of useable areas within an inspected surface in terms of the user's definition, not the supplier's claims. That is, how much useable area the user can use, not the total good area as the supplier estimated. An important application of the developed technique is in the leather industry where the tanner (the supplier) and the footwear manufacturer (the user) are constantly locked in argument due to disputed quality standards of finished leather hide, which disrupts production schedules and wasted costs in re-grading, re- sorting... . The developed basic algorithm for area scanning of a digital image will be presented. The implementation of an improved scanning algorithm will be discussed in detail. The improved features include Boolean OR operations and many other innovative functions which aim at optimizing the scanning process in terms of computing time and the accurate estimation of useable areas.
An improved dehazing algorithm of aerial high-definition image
NASA Astrophysics Data System (ADS)
Jiang, Wentao; Ji, Ming; Huang, Xiying; Wang, Chao; Yang, Yizhou; Li, Tao; Wang, Jiaoying; Zhang, Ying
2016-01-01
For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.
Technical Report: Scalable Parallel Algorithms for High Dimensional Numerical Integration
Masalma, Yahya; Jiao, Yu
2010-10-01
We implemented a scalable parallel quasi-Monte Carlo numerical high-dimensional integration for tera-scale data points. The implemented algorithm uses the Sobol s quasi-sequences to generate random samples. Sobol s sequence was used to avoid clustering effects in the generated random samples and to produce low-discrepancy random samples which cover the entire integration domain. The performance of the algorithm was tested. Obtained results prove the scalability and accuracy of the implemented algorithms. The implemented algorithm could be used in different applications where a huge data volume is generated and numerical integration is required. We suggest using the hyprid MPI and OpenMP programming model to improve the performance of the algorithms. If the mixed model is used, attention should be paid to the scalability and accuracy.
A fast directional algorithm for high-frequency electromagnetic scattering
Tsuji, Paul; Ying Lexing
2011-06-20
This paper is concerned with the fast solution of high-frequency electromagnetic scattering problems using the boundary integral formulation. We extend the O(N log N) directional multilevel algorithm previously proposed for the acoustic scattering case to the vector electromagnetic case. We also detail how to incorporate the curl operator of the magnetic field integral equation into the algorithm. When combined with a standard iterative method, this results in an almost linear complexity solver for the combined field integral equations. In addition, the butterfly algorithm is utilized to compute the far field pattern and radar cross section with O(N log N) complexity.
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
A high capacity 3D steganography algorithm.
Chao, Min-Wen; Lin, Chao-hung; Yu, Cheng-Wei; Lee, Tong-Yee
2009-01-01
In this paper, we present a very high-capacity and low-distortion 3D steganography scheme. Our steganography approach is based on a novel multilayered embedding scheme to hide secret messages in the vertices of 3D polygon models. Experimental results show that the cover model distortion is very small as the number of hiding layers ranges from 7 to 13 layers. To the best of our knowledge, this novel approach can provide much higher hiding capacity than other state-of-the-art approaches, while obeying the low distortion and security basic requirements for steganography on 3D models. PMID:19147891
A novel highly parallel algorithm for linearly unmixing hyperspectral images
NASA Astrophysics Data System (ADS)
Guerra, RaÃºl; LÃ³pez, SebastiÃ¡n.; Callico, Gustavo M.; LÃ³pez, Jose F.; Sarmiento, Roberto
2014-10-01
Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operations involved in these time-consuming processes. This work proposes an algorithm to estimate the endmembers of a hyperspectral image under analysis and its abundances at the same time. The main advantage of this algorithm is its high parallelization degree and the mathematical simplicity of the operations implemented. This algorithm estimates the endmembers as virtual pixels. In particular, the proposed algorithm performs the descent gradient method to iteratively refine the endmembers and the abundances, reducing the mean square error, according with the linear unmixing model. Some mathematical restrictions must be added so the method converges in a unique and realistic solution. According with the algorithm nature, these restrictions can be easily implemented. The results obtained with synthetic images demonstrate the well behavior of the algorithm proposed. Moreover, the results obtained with the well-known Cuprite dataset also corroborate the benefits of our proposal.
Melo; Puga; Gentil; Brito; Alves; Ramos
2000-05-01
Molecular dynamics is a well-known technique very much used in the study of biomolecular systems. The trajectory files produced by molecular dynamics simulations are extensive, and the classical lossless algorithms give poor efficiencies in their compression. In this work, a new specific algorithm, named byte structure variable length coding (BS-VLC), is introduced. Trajectory files, obtained by molecular dynamics applied to trypsin and a trypsin:pancreatic trypsin inhibitor complex, were compressed using four classical lossless algorithms (Huffman, adaptive Huffman, LZW, and LZ77) as well as the BS-VLC algorithm. The results obtained show that BS-VLC nearly triplicates the compression efficiency of the best classical lossless algorithm, preserving a near lossless behavior. Compression efficiencies close to 50% can be obtained with a high degree of precision, and the maximum efficiency possible (75%), within this algorithm, can be performed with good precision. PMID:10850759
Production of high specific activity silicon-32
Phillips, D.R.; Brzezinski, M.A.
1998-12-31
This is the final report of a three-year, Laboratory Directed Research and Development Project (LDRD) at Los Alamos National Laboratory (LANL). There were two primary objectives for the work performed under this project. The first was to take advantage of capabilities and facilities at Los Alamos to produce the radionuclide {sup 32}Si in unusually high specific activity. The second was to combine the radioanalytical expertise at Los Alamos with the expertise at the University of California to develop methods for the application of {sup 32}Si in biological oceanographic research related to global climate modeling. The first objective was met by developing targetry for proton spallation production of {sup 32}Si in KCl targets and chemistry for its recovery in very high specific activity. The second objective was met by developing a validated field-useable, radioanalytical technique, based upon gas-flow proportional counting, to measure the dynamics of silicon uptake by naturally occurring diatoms.
Development of High Specific Strength Envelope Materials
NASA Astrophysics Data System (ADS)
Komatsu, Keiji; Sano, Masa-Aki; Kakuta, Yoshiaki
Progress in materials technology has produced a much more durable synthetic fabric envelope for the non-rigid airship. Flexible materials are required to form airship envelopes, ballonets, load curtains, gas bags and covering rigid structures. Polybenzoxazole fiber (Zylon) and polyalirate fiber (Vectran) show high specific tensile strength, so that we developed membrane using these high specific tensile strength fibers as a load carrier. The main material developed is a Zylon or Vectran load carrier sealed internally with a polyurethane bonded inner gas retention film (EVOH). The external surface provides weather protecting with, for instance, a titanium oxide integrated polyurethane or Tedlar film. The mechanical test results show that tensile strength 1,000 N/cm is attained with weight less than 230g/m2. In addition to the mechanical properties, temperature dependence of the joint strength and solar absorptivity and emissivity of the surface are measured.ã€€
Benefits Assessment of Algorithmically Combining Generic High Altitude Airspace Sectors
NASA Technical Reports Server (NTRS)
Bloem, Michael; Gupta, Pramod; Lai, Chok Fung; Kopardekar, Parimal
2009-01-01
In today's air traffic control operations, sectors that have traffic demand below capacity are combined so that fewer controller teams are required to manage air traffic. Controllers in current operations are certified to control a group of six to eight sectors, known as an area of specialization. Sector combinations are restricted to occur within areas of specialization. Since there are few sector combination possibilities in each area of specialization, human supervisors can effectively make sector combination decisions. In the future, automation and procedures will allow any appropriately trained controller to control any of a large set of generic sectors. The primary benefit of this will be increased controller staffing flexibility. Generic sectors will also allow more options for combining sectors, making sector combination decisions difficult for human supervisors. A sector-combining algorithm can assist supervisors as they make generic sector combination decisions. A heuristic algorithm for combining under-utilized air space sectors to conserve air traffic control resources has been described and analyzed. Analysis of the algorithm and comparisons with operational sector combinations indicate that this algorithm could more efficiently utilize air traffic control resources than current sector combinations. This paper investigates the benefits of using the sector-combining algorithm proposed in previous research to combine high altitude generic airspace sectors. Simulations are conducted in which all the high altitude sectors in a center are allowed to combine, as will be possible in generic high altitude airspace. Furthermore, the algorithm is adjusted to use a version of the simplified dynamic density (SDD) workload metric that has been modified to account for workload reductions due to automatic handoffs and Automatic Dependent Surveillance Broadcast (ADS-B). This modified metric is referred to here as future simplified dynamic density (FSDD). Finally
NASA Technical Reports Server (NTRS)
Lawton, Pat
2004-01-01
The objective of this work was to support the design of improved IUE NEWSIPS high dispersion extraction algorithms. The purpose of this work was to evaluate use of the Linearized Image (LIHI) file versus the Re-Sampled Image (SIHI) file, evaluate various extraction, and design algorithms for evaluation of IUE High Dispersion spectra. It was concluded the use of the Re-Sampled Image (SIHI) file was acceptable. Since the Gaussian profile worked well for the core and the Lorentzian profile worked well for the wings, the Voigt profile was chosen for use in the extraction algorithm. It was found that the gamma and sigma parameters varied significantly across the detector, so gamma and sigma masks for the SWP detector were developed. Extraction code was written.
NASA Astrophysics Data System (ADS)
Gilat-Schmidt, Taly; Wang, Adam; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh
2016-03-01
The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multiatlas approach was also investigated. We hypothesize that the auto-segmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.
An Incremental High-Utility Mining Algorithm with Transaction Insertion
Gan, Wensheng; Zhang, Binbin
2015-01-01
Association-rule mining is commonly used to discover useful and meaningful patterns from a very large database. It only considers the occurrence frequencies of items to reveal the relationships among itemsets. Traditional association-rule mining is, however, not suitable in real-world applications since the purchased items from a customer may have various factors, such as profit or quantity. High-utility mining was designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of high-utility mining are designed to handle the static database. Fewer researches handle the dynamic high-utility mining with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up the computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, memory consumption, and number of generated patterns. PMID:25811038
Electromagnetic properties of high specific surface minerals
NASA Astrophysics Data System (ADS)
Klein, Katherine Anne
Interparticle electrical forces play a dominant role in the behaviour of high specific surface minerals, such as clays. This fact encourages the use of small electromagnetic perturbations to assess the microscale properties of these materials. Thus, this research focuses on using electromagnetic waves to understand fundamental particle-particle and particle-fluid interactions, and fabric formation in high specific surface mineral-fluid mixtures (particle size <~1 Î¼m). Topics addressed in this study include: the role of specific surface and double layer phenomena in the engineering behaviour of clay-water-electrolyte mixtures; the interplay between surface conduction, double layer polarization, and interfacial polarization; the relationship between fabric, permittivity, shear wave velocity, and engineering properties in soft slurries; and the effect of ferromagnetic impurities on electromagnetic measurements. The critical role of specific surface on the engineering properties of fine-grained soils is demonstrated through fundamental principles and empirical correlations. Afterwards, the effect of specific surface on the electromagnetic properties of particulate materials is studied using simple microscale analyses of conduction and polarization phenomena in particle-fluid mixtures, and corroborated by experimentation. These results clarify the relative importance of specific surface, water content, electrolyte type, and ionic concentration on the electrical properties of particulate materials. The sensitivity of electromagnetic parameters to particle orientation is addressed in light of the potential assessment of anisotropy in engineering properties. It is shown that effective conductivity measurements provide a robust method to determine electrical anisotropy in particle-fluid mixtures. However, real relative dielectric measurements at frequencies below 1 MHz are unreliable due to electrode effects (especially in highly conductive mixtures). The relationship
Wp specific methylation of highly proliferated LCLs
Park, Jung-Hoon; Jeon, Jae-Pil; Shim, Sung-Mi; Nam, Hye-Young; Kim, Joon-Woo; Han, Bok-Ghee; Lee, Suman . E-mail: suman@cha.ac.kr
2007-06-29
The epigenetic regulation of viral genes may be important for the life cycle of EBV. We determined the methylation status of three viral promoters (Wp, Cp, Qp) from EBV B-lymphoblastoid cell lines (LCLs) by pyrosequencing. Our pyrosequencing data showed that the CpG region of Wp was methylated, but the others were not. Interestingly, Wp methylation was increased with proliferation of LCLs. Wp methylation was as high as 74.9% in late-passage LCLs, but 25.6% in early-passage LCLs. From two Burkitt's lymphoma cell lines, Wp specific hypermethylation was also found (>80%). Interestingly, the expression of EBNA2 gene which located directly next to Wp was associated with its methylation. Our data suggested that Wp specific methylation may be important for the indicator of the proliferation status of LCLs, and the epigenetic viral gene regulation of EBNA2 gene by Wp should be further defined possibly with other biological processes.
Subsemble: an ensemble method for combining subset-specific algorithm fits
Sapp, Stephanie; van der Laan, Mark J.; Canny, John
2013-01-01
Ensemble methods using the same underlying algorithm trained on different subsets of observations have recently received increased attention as practical prediction tools for massive datasets. We propose Subsemble: a general subset ensemble prediction method, which can be used for small, moderate, or large datasets. Subsemble partitions the full dataset into subsets of observations, fits a specified underlying algorithm on each subset, and uses a clever form of V-fold cross-validation to output a prediction function that combines the subset-specific fits. We give an oracle result that provides a theoretical performance guarantee for Subsemble. Through simulations, we demonstrate that Subsemble can be a beneficial tool for small to moderate sized datasets, and often has better prediction performance than the underlying algorithm fit just once on the full dataset. We also describe how to include Subsemble as a candidate in a SuperLearner library, providing a practical way to evaluate the performance of Subsemlbe relative to the underlying algorithm fit just once on the full dataset. PMID:24778462
Stride Search: a general algorithm for storm detection in high-resolution climate data
NASA Astrophysics Data System (ADS)
Bosler, Peter A.; Roesler, Erika L.; Taylor, Mark A.; Mundt, Miranda R.
2016-04-01
This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.
A high performance hardware implementation image encryption with AES algorithm
NASA Astrophysics Data System (ADS)
Farmani, Ali; Jafari, Mohamad; Miremadi, Seyed Sohrab
2011-06-01
This paper describes implementation of a high-speed encryption algorithm with high throughput for encrypting the image. Therefore, we select a highly secured symmetric key encryption algorithm AES(Advanced Encryption Standard), in order to increase the speed and throughput using pipeline technique in four stages, control unit based on logic gates, optimal design of multiplier blocks in mixcolumn phase and simultaneous production keys and rounds. Such procedure makes AES suitable for fast image encryption. Implementation of a 128-bit AES on FPGA of Altra company has been done and the results are as follow: throughput, 6 Gbps in 471MHz. The time of encrypting in tested image with 32*32 size is 1.15ms.
A DRAM compiler algorithm for high performance VLSI embedded memories
NASA Technical Reports Server (NTRS)
Eldin, A. G.
1992-01-01
In many applications, the limited density of the embedded SRAM does not allow integrating the memory on the same chip with other logic and functional blocks. In such cases, the embedded DRAM provides the optimum combination of very high density, low power, and high performance. For ASIC's to take full advantage of this design strategy, an efficient and highly reliable DRAM compiler must be used. The embedded DRAM architecture, cell, and peripheral circuit design considerations and the algorithm of a high performance memory compiler are presented .
Production Of High Specific Activity Copper-67
Jamriska, Sr., David J.; Taylor, Wayne A.; Ott, Martin A.; Fowler, Malcolm; Heaton, Richard C.
2003-10-28
A process for the selective production and isolation of high specific activity Cu.sup.67 from proton-irradiated enriched Zn.sup.70 target comprises target fabrication, target irradiation with low energy (<25 MeV) protons, chemical separation of the Cu.sup.67 product from the target material and radioactive impurities of gallium, cobalt, iron, and stable aluminum via electrochemical methods or ion exchange using both anion and cation organic ion exchangers, chemical recovery of the enriched Zn.sup.70 target material, and fabrication of new targets for re-irradiation is disclosed.
Production Of High Specific Activity Copper-67
Jamriska, Sr., David J.; Taylor, Wayne A.; Ott, Martin A.; Fowler, Malcolm; Heaton, Richard C.
2002-12-03
A process for the selective production and isolation of high specific activity cu.sup.67 from proton-irradiated enriched Zn.sup.70 target comprises target fabrication, target irradiation with low energy (<25 MeV) protons, chemical separation of the Cu.sup.67 product from the target material and radioactive impurities of gallium, cobalt, iron, and stable aluminum via electrochemical methods or ion exchange using both anion and cation organic ion exchangers, chemical recovery of the enriched Zn.sup.70 target material, and fabrication of new targets for re-irradiation is disclosed.
A rib-specific multimodal registration algorithm for fused unfolded rib visualization using PET/CT
NASA Astrophysics Data System (ADS)
Kaftan, Jens N.; Kopaczka, Marcin; Wimmer, Andreas; Platsch, GÃ¼nther; Declerck, JÃ©rÃ´me
2014-03-01
Respiratory motion affects the alignment of PET and CT volumes from PET/CT examinations in a non-rigid manner. This becomes particularly apparent if reviewing fine anatomical structures such as ribs when assessing bone metastases, which frequently occur in many advanced cancers. To make this routine diagnostic task more efficient, a fused unfolded rib visualization for 18F-NaF PET/CT is presented. It allows to review the whole rib cage in a single image. This advanced visualization is enabled by a novel rib-specific registration algorithm that rigidly optimizes the local alignment of each individual rib in both modalities based on a matched filter response function. More specifically, rib centerlines are automatically extracted from CT and subsequently individually aligned to the corresponding bone-specific PET rib uptake pattern. The proposed method has been validated on 20 PET/CT scans acquired at different clinical sites. It has been demonstrated that the presented rib- specific registration method significantly improves the rib alignment without having to run complex deformable registration algorithms. At the same time, it guarantees that rib lesions are not further deformed, which may otherwise affect quantitative measurements such as SUVs. Considering clinically relevant distance thresholds, the centerline portion with good alignment compared to the ground truth improved from 60:6% to 86:7% after registration while approximately 98% can be still considered as acceptably aligned.
High specific energy, high capacity nickel-hydrogen cell design
NASA Technical Reports Server (NTRS)
Wheeler, James R.
1993-01-01
A 3.5 inch rabbit-ear-terminal nickel-hydrogen cell has been designed and tested to deliver high capacity at a C/1.5 discharge rate. Its specific energy yield of 60.6 wh/kg is believed to be the highest yet achieved in a slurry-process nickel-hydrogen cell, and its 10 C capacity of 113.9 AH the highest capacity yet made at a discharge rate this high in the 3.5 inch diameter size. The cell also demonstrated a pulse capability of 180 amps for 20 seconds. Specific cell parameters, performance, and future test plans are described.
Feature extraction and classification algorithms for high dimensional data
NASA Technical Reports Server (NTRS)
Lee, Chulhee; Landgrebe, David
1993-01-01
Feature extraction and classification algorithms for high dimensional data are investigated. Developments with regard to sensors for Earth observation are moving in the direction of providing much higher dimensional multispectral imagery than is now possible. In analyzing such high dimensional data, processing time becomes an important factor. With large increases in dimensionality and the number of classes, processing time will increase significantly. To address this problem, a multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage. Several truncation criteria are developed and the relationship between thresholds and the error caused by the truncation is investigated. Next an approach to feature extraction for classification is proposed based directly on the decision boundaries. It is shown that all the features needed for classification can be extracted from decision boundaries. A characteristic of the proposed method arises by noting that only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is introduced. The proposed feature extraction algorithm has several desirable properties: it predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal means or equal covariances as some previous algorithms do. In addition, the decision boundary feature extraction algorithm can be used both for parametric and non-parametric classifiers. Finally, some problems encountered in analyzing high dimensional data are studied and possible solutions are proposed. First, the increased importance of the second order statistics in analyzing high dimensional data is recognized
Zhang, Yanjun; Krueger, Dana; Durst, Robert; Lee, Rupo; Wang, David; Seeram, Navindra; Heber, David
2009-03-25
The pomegranate fruit ( Punica granatum ) has become an international high-value crop for the production of commercial pomegranate juice (PJ). The perceived consumer value of PJ is due in large part to its potential health benefits based on a significant body of medical research conducted with authentic PJ. To establish criteria for authenticating PJ, a new International Multidimensional Authenticity Specifications (IMAS) algorithm was developed through consideration of existing databases and comprehensive chemical characterization of 45 commercial juice samples from 23 different manufacturers in the United States. In addition to analysis of commercial juice samples obtained in the United States, data from other analyses of pomegranate juice and fruits including samples from Iran, Turkey, Azerbaijan, Syria, India, and China were considered in developing this protocol. There is universal agreement that the presence of a highly constant group of six anthocyanins together with punicalagins characterizes polyphenols in PJ. At a total sugar concentration of 16 degrees Brix, PJ contains characteristic sugars including mannitol at >0.3 g/100 mL. Ratios of glucose to mannitol of 4-15 and of glucose to fructose of 0.8-1.0 are also characteristic of PJ. In addition, no sucrose should be present because of isomerase activity during commercial processing. Stable isotope ratio mass spectrometry as > -25 per thousand assures that there is no added corn or cane sugar added to PJ. Sorbitol was present at <0.025 g/100 mL; maltose and tartaric acid were not detected. The presence of the amino acid proline at >25 mg/L is indicative of added grape products. Malic acid at >0.1 g/100 mL indicates adulteration with apple, pear, grape, cherry, plum, or aronia juice. Other adulteration methods include the addition of highly concentrated aronia, blueberry, or blackberry juices or natural grape pigments to poor-quality juices to imitate the color of pomegranate juice, which results in
High pressure humidification columns: Design equations, algorithm, and computer code
Enick, R.M.; Klara, S.M.; Marano, J.J.
1994-07-01
This report describes the detailed development of a computer model to simulate the humidification of an air stream in contact with a water stream in a countercurrent, packed tower, humidification column. The computer model has been developed as a user model for the Advanced System for Process Engineering (ASPEN) simulator. This was done to utilize the powerful ASPEN flash algorithms as well as to provide ease of use when using ASPEN to model systems containing humidification columns. The model can easily be modified for stand-alone use by incorporating any standard algorithm for performing flash calculations. The model was primarily developed to analyze Humid Air Turbine (HAT) power cycles; however, it can be used for any application that involves a humidifier or saturator. The solution is based on a multiple stage model of a packed column which incorporates mass and energy, balances, mass transfer and heat transfer rate expressions, the Lewis relation and a thermodynamic equilibrium model for the air-water system. The inlet air properties, inlet water properties and a measure of the mass transfer and heat transfer which occur in the column are the only required input parameters to the model. Several example problems are provided to illustrate the algorithm`s ability to generate the temperature of the water, flow rate of the water, temperature of the air, flow rate of the air and humidity of the air as a function of height in the column. The algorithm can be used to model any high-pressure air humidification column operating at pressures up to 50 atm. This discussion includes descriptions of various humidification processes, detailed derivations of the relevant expressions, and methods of incorporating these equations into a computer model for a humidification column.
A moving frame algorithm for high Mach number hydrodynamics
NASA Astrophysics Data System (ADS)
Trac, Hy; Pen, Ue-Li
2004-07-01
We present a new approach to Eulerian computational fluid dynamics that is designed to work at high Mach numbers encountered in astrophysical hydrodynamic simulations. Standard Eulerian schemes that strictly conserve total energy suffer from the high Mach number problem and proposed solutions to additionally solve the entropy or thermal energy still have their limitations. In our approach, the Eulerian conservation equations are solved in an adaptive frame moving with the fluid where Mach numbers are minimized. The moving frame approach uses a velocity decomposition technique to define local kinetic variables while storing the bulk kinetic components in a smoothed background velocity field that is associated with the grid velocity. Gravitationally induced accelerations are added to the grid, thereby minimizing the spurious heating problem encountered in cold gas flows. Separately tracking local and bulk flow components allows thermodynamic variables to be accurately calculated in both subsonic and supersonic regions. A main feature of the algorithm, that is not possible in previous Eulerian implementations, is the ability to resolve shocks and prevent spurious heating where both the pre-shock and post-shock fluid are supersonic. The hybrid algorithm combines the high-resolution shock capturing ability of the second-order accurate Eulerian TVD scheme with a low-diffusion Lagrangian advection scheme. We have implemented a cosmological code where the hydrodynamic evolution of the baryons is captured using the moving frame algorithm while the gravitational evolution of the collisionless dark matter is tracked using a particle-mesh N-body algorithm. Hydrodynamic and cosmological tests are described and results presented. The current code is fast, memory-friendly, and parallelized for shared-memory machines.
NASA Astrophysics Data System (ADS)
Janidarmian, Majid; Fekr, Atena Roshan; Bokharaei, Vahhab Samadi
2011-08-01
Mapping algorithm which means which core should be linked to which router is one of the key issues in the design flow of network-on-chip. To achieve an application-specific NoC design procedure that minimizes the communication cost and improves the fault tolerant property, first a heuristic mapping algorithm that produces a set of different mappings in a reasonable time is presented. This algorithm allows the designers to identify the set of most promising solutions in a large design space, which has low communication costs while yielding optimum communication costs in some cases. Another evaluated parameter, vulnerability index, is then considered as a principle of estimating the fault-tolerance property in all produced mappings. Finally, in order to yield a mapping which considers trade-offs between these two parameters, a linear function is defined and introduced. It is also observed that more flexibility to prioritize solutions within the design space is possible by adjusting a set of if-then rules in fuzzy logic.
Algorithmic tools for mining high-dimensional cytometry data
Chester, Cariad; Maecker, Holden T.
2015-01-01
The advent of mass cytometry has lead to an unprecedented increase in the number of analytes measured in individual cells, thereby increasing the complexity and information content of cytometric data. While this technology is ideally suited to detailed examination of the immune system, the applicability of the different methods for analyzing such complex data are less clear. Conventional data analysis by â€˜manualâ€™ gating of cells in biaxial dotplots is often subjective, time consuming, and neglectful of much of the information contained in a highly dimensional cytometric dataset. Algorithmic data mining has the promise to eliminate these concerns and several such tools have been recently applied to mass cytometry data. Herein, we review computational data mining tools that have been used to analyze mass cytometry data, outline their differences, and comment on their strengths and limitations. This review will help immunologists identify suitable algorithmic tools for their particular projects. PMID:26188071
Production of high specific activity silicon-32
Phillips, Dennis R.; Brzezinski, Mark A.
1994-01-01
A process for preparation of silicon-32 is provide and includes contacting an irradiated potassium chloride target, including spallation products from a prior irradiation, with sufficient water, hydrochloric acid or potassium hydroxide to form a solution, filtering the solution, adjusting pH of the solution to from about 5.5 to about 7.5, admixing sufficient molybdate-reagent to the solution to adjust the pH of the solution to about 1.5 and to form a silicon-molybdate complex, contacting the solution including the silicon-molybdate complex with a dextran-based material, washing the dextran-based material to remove residual contaminants such as sodium-22, separating the silicon-molybdate complex from the dextran-based material as another solution, adding sufficient hydrochloric acid and hydrogen peroxide to the solution to prevent reformation of the silicon-molybdate complex and to yield an oxidization state of the molybdate adapted for subsequent separation by an anion exchange material, contacting the solution with an anion exchange material whereby the molybdate is retained by the anion exchange material and the silicon remains in solution, and optionally adding sufficient alkali metal hydroxide to adjust the pH of the solution to about 12 to 13. Additionally, a high specific activity silicon-32 product having a high purity is provided.
Production of high specific activity silicon-32
Phillips, D.R.; Brzezinski, M.A.
1994-09-13
A process for the preparation of silicon-32 is provided and includes contacting an irradiated potassium chloride target, including spallation products from a prior irradiation, with sufficient water, hydrochloric acid or potassium hydroxide to form a solution, filtering the solution, adjusting pH of the solution to from about 5.5 to about 7.5, admixing sufficient molybdate-reagent to the solution to adjust the pH of the solution to about 1.5 and to form a silicon-molybdate complex, contacting the solution including the silicon-molybdate complex with a dextran-based material, washing the dextran-based material to remove residual contaminants such as sodium-22, separating the silicon-molybdate complex from the dextran-based material as another solution, adding sufficient hydrochloric acid and hydrogen peroxide to the solution to prevent reformation of the silicon-molybdate complex and to yield an oxidization state of the molybdate adapted for subsequent separation by an anion exchange material, contacting the solution with an anion exchange material whereby the molybdate is retained by the anion exchange material and the silicon remains in solution, and optionally adding sufficient alkali metal hydroxide to adjust the pH of the solution to about 12 to 13. Additionally, a high specific activity silicon-32 product having a high purity is provided.
Site-specific range uncertainties caused by dose calculation algorithms for proton therapy.
Schuemann, J; Dowdell, S; Grassberger, C; Min, C H; Paganetti, H
2014-08-01
The purpose of this study was to assess the possibility of introducing site-specific range margins to replace current generic margins in proton therapy. Further, the goal was to study the potential of reducing margins with current analytical dose calculations methods. For this purpose we investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo (MC) simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for seven disease sites (liver, prostate, breast, medulloblastoma-spine, medulloblastoma-whole brain, lung and head and neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and MC algorithms to obtain the average range differences and root mean square deviation for each field for theÂ distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80-R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing MC dose calculations. We recommend range margins of 2.8%Â +Â 1.2Â mm for liver and prostate treatments and 3.1%Â +Â 1.2Â mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head and neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3%Â +Â 1.2Â
Site-specific range uncertainties caused by dose calculation algorithms for proton therapy
NASA Astrophysics Data System (ADS)
Schuemann, J.; Dowdell, S.; Grassberger, C.; Min, C. H.; Paganetti, H.
2014-08-01
The purpose of this study was to assess the possibility of introducing site-specific range margins to replace current generic margins in proton therapy. Further, the goal was to study the potential of reducing margins with current analytical dose calculations methods. For this purpose we investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo (MC) simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for seven disease sites (liver, prostate, breast, medulloblastoma-spine, medulloblastoma-whole brain, lung and head and neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and MC algorithms to obtain the average range differences and root mean square deviation for each field for the distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80-R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing MC dose calculations. We recommend range margins of 2.8% + 1.2 mm for liver and prostate treatments and 3.1% + 1.2 mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head and neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3% + 1.2 mm would be
Jimenez, Edward Steven,
2013-09-01
The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.
Finite element solution for energy conservation using a highly stable explicit integration algorithm
NASA Technical Reports Server (NTRS)
Baker, A. J.; Manhardt, P. D.
1972-01-01
Theoretical derivation of a finite element solution algorithm for the transient energy conservation equation in multidimensional, stationary multi-media continua with irregular solution domain closure is considered. The complete finite element matrix forms for arbitrarily irregular discretizations are established, using natural coordinate function representations. The algorithm is embodied into a user-oriented computer program (COMOC) which obtains transient temperature distributions at the node points of the finite element discretization using a highly stable explicit integration procedure with automatic error control features. The finite element algorithm is shown to posses convergence with discretization for a transient sample problem. The condensed form for the specific heat element matrix is shown to be preferable to the consistent form. Computed results for diverse problems illustrate the versatility of COMOC, and easily prepared output subroutines are shown to allow quick engineering assessment of solution behavior.
Site-specific range uncertainties caused by dose calculation algorithms for proton therapy
Schuemann, J.; Dowdell, S.; Grassberger, C.; Min, C. H.; Paganetti, H.
2014-01-01
The purpose of this study was to investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for 7 disease sites (liver, prostate, breast, medulloblastoma-spine, medulloblastoma-whole brain, lung and head & neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and Monte Carlo algorithms to obtain the average range differences (ARD) and root mean square deviation (RMSD) for each field for the distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation (ADD) of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80-R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing Monte Carlo dose calculations. We recommend range margins of 2.8% + 1.2 mm for liver and prostate treatments and 3.1% + 1.2 mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head & neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3% + 1.2 mm would be needed for breast, lung and head & neck treatments. We conclude that currently used generic range uncertainty margins in proton therapy should be redefined site specific and that complex geometries may require a field specific
NASA Astrophysics Data System (ADS)
Palamara, Simone; Vergara, Christian; Faggiano, Elena; Nobile, Fabio
2015-02-01
The Purkinje network is responsible for the fast and coordinated distribution of the electrical impulse in the ventricle that triggers its contraction. Therefore, it is necessary to model its presence to obtain an accurate patient-specific model of the ventricular electrical activation. In this paper, we present an efficient algorithm for the generation of a patient-specific Purkinje network, driven by measures of the electrical activation acquired on the endocardium. The proposed method provides a correction of an initial network, generated by means of a fractal law, and it is based on the solution of Eikonal problems both in the muscle and in the Purkinje network. We present several numerical results both in an ideal geometry with synthetic data and in a real geometry with patient-specific clinical measures. These results highlight an improvement of the accuracy provided by the patient-specific Purkinje network with respect to the initial one. In particular, a cross-validation test shows an accuracy increase of 19% when only the 3% of the total points are used to generate the network, whereas an increment of 44% is observed when a random noise equal to 20% of the maximum value of the clinical data is added to the measures.
High-Speed General Purpose Genetic Algorithm Processor.
Hoseini Alinodehi, Seyed Pourya; Moshfe, Sajjad; Saber Zaeimian, Masoumeh; Khoei, Abdollah; Hadidi, Khairollah
2016-07-01
In this paper, an ultrafast steady-state genetic algorithm processor (GAP) is presented. Due to the heavy computational load of genetic algorithms (GAs), they usually take a long time to find optimum solutions. Hardware implementation is a significant approach to overcome the problem by speeding up the GAs procedure. Hence, we designed a digital CMOS implementation of GA in [Formula: see text] process. The proposed processor is not bounded to a specific application. Indeed, it is a general-purpose processor, which is capable of performing optimization in any possible application. Utilizing speed-boosting techniques, such as pipeline scheme, parallel coarse-grained processing, parallel fitness computation, parallel selection of parents, dual-population scheme, and support for pipelined fitness computation, the proposed processor significantly reduces the processing time. Furthermore, by relying on a built-in discard operator the proposed hardware may be used in constrained problems that are very common in control applications. In the proposed design, a large search space is achievable through the bit string length extension of individuals in the genetic population by connecting the 32-bit GAPs. In addition, the proposed processor supports parallel processing, in which the GAs procedure can be run on several connected processors simultaneously. PMID:26241984
Robust Optimization Design Algorithm for High-Frequency TWTs
NASA Technical Reports Server (NTRS)
Wilson, Jeffrey D.; Chevalier, Christine T.
2010-01-01
Traveling-wave tubes (TWTs), such as the Ka-band (26-GHz) model recently developed for the Lunar Reconnaissance Orbiter, are essential as communication amplifiers in spacecraft for virtually all near- and deep-space missions. This innovation is a computational design algorithm that, for the first time, optimizes the efficiency and output power of a TWT while taking into account the effects of dimensional tolerance variations. Because they are primary power consumers and power generation is very expensive in space, much effort has been exerted over the last 30 years to increase the power efficiency of TWTs. However, at frequencies higher than about 60 GHz, efficiencies of TWTs are still quite low. A major reason is that at higher frequencies, dimensional tolerance variations from conventional micromachining techniques become relatively large with respect to the circuit dimensions. When this is the case, conventional design- optimization procedures, which ignore dimensional variations, provide inaccurate designs for which the actual amplifier performance substantially under-performs that of the design. Thus, this new, robust TWT optimization design algorithm was created to take account of and ameliorate the deleterious effects of dimensional variations and to increase efficiency, power, and yield of high-frequency TWTs. This design algorithm can help extend the use of TWTs into the terahertz frequency regime of 300-3000 GHz. Currently, these frequencies are under-utilized because of the lack of efficient amplifiers, thus this regime is known as the "terahertz gap." The development of an efficient terahertz TWT amplifier could enable breakthrough applications in space science molecular spectroscopy, remote sensing, nondestructive testing, high-resolution "through-the-wall" imaging, biomedical imaging, and detection of explosives and toxic biochemical agents.
High specific energy, high capacity nickel-hydrogen cell design
NASA Technical Reports Server (NTRS)
Wheeler, James R.
1993-01-01
A 3.5 inch rabbit-ear-terminal nickel-hydrogen cell was designed and tested to deliver high capacity at steady discharge rates up to and including a C rate. Its specific energy yield of 60.6 wh/kg is believed to be the highest yet achieved in a slurry-process nickel-hydrogen cell, and its 10 C capacity of 113.9 AH the highest capacity yet of any type in a 3.5 inch diameter size. The cell also demonstrated a pulse capability of 180 amps for 20 seconds. Specific cell parameters and performance are described. Also covered is an episode of capacity fading due to electrode swelling and its successful recovery by means of additional activation procedures.
Toghi Eshghi, Shadi; Shah, Punit; Yang, Weiming; Li, Xingde; Zhang, Hui
2015-01-01
Glycoprotein changes occur in not only protein abundance but also the occupancy of each glycosylation site by different glycoforms during biological or pathological processes. Recent advances in mass spectrometry instrumentation and techniques have facilitated analysis of intact glycopeptides in complex biological samples by allowing the users to generate spectra of intact glycopeptides with glycans attached to each specific glycosylation site. However, assigning these spectra, leading to identification of the glycopeptides, is challenging. Here, we report an algorithm, named GPQuest, for site-specific identification of intact glycopeptides using higher-energy collisional dissociation (HCD) fragmentation of complex samples. In this algorithm, a spectral library of glycosite-containing peptides in the sample was built by analyzing the isolated glycosite-containing peptides using HCD LC-MS/MS. Spectra of intact glycopeptides were selected by using glycan oxonium ions as signature ions for glycopeptide spectra. These oxonium-ion-containing spectra were then compared with the spectral library generated from glycosite-containing peptides, resulting in assignment of each intact glycopeptide MS/MS spectrum to a specific glycosite-containing peptide. The glycan occupying each glycosite was determined by matching the mass difference between the precursor ion of intact glycopeptide and the glycosite-containing peptide to a glycan database. Using GPQuest, we analyzed LC-MS/MS spectra of protein extracts from prostate tumor LNCaP cells. Without enrichment of glycopeptides from global tryptic peptides and at a false discovery rate of 1%, 1008 glycan-containing MS/MS spectra were assigned to 769 unique intact N-linked glycopeptides, representing 344 N-linked glycosites with 57 different N-glycans. Spectral library matching using GPQuest assigns the HCD LC-MS/MS generated spectra of intact glycopeptides in an automated and high-throughput manner. Additionally, spectral library
Algorithms for High-Speed Noninvasive Eye-Tracking System
NASA Technical Reports Server (NTRS)
Talukder, Ashit; Morookian, John-Michael; Lambert, James
2010-01-01
Two image-data-processing algorithms are essential to the successful operation of a system of electronic hardware and software that noninvasively tracks the direction of a person s gaze in real time. The system was described in High-Speed Noninvasive Eye-Tracking System (NPO-30700) NASA Tech Briefs, Vol. 31, No. 8 (August 2007), page 51. To recapitulate from the cited article: Like prior commercial noninvasive eyetracking systems, this system is based on (1) illumination of an eye by a low-power infrared light-emitting diode (LED); (2) acquisition of video images of the pupil, iris, and cornea in the reflected infrared light; (3) digitization of the images; and (4) processing the digital image data to determine the direction of gaze from the centroids of the pupil and cornea in the images. Most of the prior commercial noninvasive eyetracking systems rely on standard video cameras, which operate at frame rates of about 30 Hz. Such systems are limited to slow, full-frame operation. The video camera in the present system includes a charge-coupled-device (CCD) image detector plus electronic circuitry capable of implementing an advanced control scheme that effects readout from a small region of interest (ROI), or subwindow, of the full image. Inasmuch as the image features of interest (the cornea and pupil) typically occupy a small part of the camera frame, this ROI capability can be exploited to determine the direction of gaze at a high frame rate by reading out from the ROI that contains the cornea and pupil (but not from the rest of the image) repeatedly. One of the present algorithms exploits the ROI capability. The algorithm takes horizontal row slices and takes advantage of the symmetry of the pupil and cornea circles and of the gray-scale contrasts of the pupil and cornea with respect to other parts of the eye. The algorithm determines which horizontal image slices contain the pupil and cornea, and, on each valid slice, the end coordinates of the pupil and cornea
Kapp, Eugene; Schutz, Frederick; Connolly, Lisa M.; Chakel, John A.; Meza, Jose E.; Miller, Christine A.; Fenyo, David; Eng, Jimmy K.; Adkins, Joshua N.; Omenn, Gilbert; Simpson, Richard
2005-08-01
MS/MS and associated database search algorithms are essential proteomic tools for identifying peptides. Due to their widespread use, it is now time to perform a systematic analysis of the various algorithms currently in use. Using blood specimens used in the HUPO Plasma Proteome Project, we have evaluated five search algorithms with respect to their sensitivity and specificity, and have also accurately benchmarked them based on specified false-positive (FP) rates. Spectrum Mill and SEQUEST performed well in terms of sensitivity, but were inferior to MASCOT, X-Tandem, and Sonar in terms of specificity. Overall, MASCOT, a probabilistic search algorithm, correctly identified most peptides based on a specified FP rate. The rescoring algorithm, Peptide Prophet, enhanced the overall performance of the SEQUEST algorithm, as well as provided predictable FP error rates. Ideally, score thresholds should be calculated for each peptide spectrum or minimally, derived from a reversed-sequence search as demonstrated in this study based on a validated data set. The availability of open-source search algorithms, such as X-Tandem, makes it feasible to further improve the validation process (manual or automatic) on the basis of ''consensus scoring'', i.e., the use of multiple (at least two) search algorithms to reduce the number of FPs. complement.
Trajectories for High Specific Impulse High Specific Power Deep Space Exploration
NASA Technical Reports Server (NTRS)
Polsgrove, T.; Adams, R. B.; Brady, Hugh J. (Technical Monitor)
2002-01-01
Preliminary results are presented for two methods to approximate the mission performance of high specific impulse high specific power vehicles. The first method is based on an analytical approximation derived by Williams and Shepherd and can be used to approximate mission performance to outer planets and interstellar space. The second method is based on a parametric analysis of trajectories created using the well known trajectory optimization code, VARITOP. This parametric analysis allows the reader to approximate payload ratios and optimal power requirements for both one-way and round-trip missions. While this second method only addresses missions to and from Jupiter, future work will encompass all of the outer planet destinations and some interstellar precursor missions.
NASA Astrophysics Data System (ADS)
Hagenmuller, Pascal; Matzl, Margret; Chambon, Guillaume; Schneebeli, Martin
2016-05-01
Microtomography can measure the X-ray attenuation coefficient in a 3-D volume of snow with a spatial resolution of a few microns. In order to extract quantitative characteristics of the microstructure, such as the specific surface area (SSA), from these data, the greyscale image first needs to be segmented into a binary image of ice and air. Different numerical algorithms can then be used to compute the surface area of the binary image. In this paper, we report on the effect of commonly used segmentation and surface area computation techniques on the evaluation of density and specific surface area. The evaluation is based on a set of 38 X-ray tomographies of different snow samples without impregnation, scanned with an effective voxel size of 10 and 18 Î¼m. We found that different surface area computation methods can induce relative variations up to 5 % in the density and SSA values. Regarding segmentation, similar results were obtained by sequential and energy-based approaches, provided the associated parameters were correctly chosen. The voxel size also appears to affect the values of density and SSA, but because images with the higher resolution also show the higher noise level, it was not possible to draw a definitive conclusion on this effect of resolution.
Algorithms for a very high speed universal noiseless coding module
NASA Technical Reports Server (NTRS)
Rice, Robert F.; Yeh, Pen-Shu
1991-01-01
The algorithmic definitions and performance characterizations are presented for a high performance adaptive coding module. Operation of at least one of these (single chip) implementations is expected to exceed 500 Mbits/s under laboratory conditions. Operation of a companion decoding module should operate at up to half the coder's rate. The module incorporates a powerful noiseless coder for Standard Form Data Sources (i.e., sources whose symbols can be represented by uncorrelated non-negative integers where the smaller integers are more likely than the larger ones). Performance close to data entropies can be expected over a Dynamic Range of from 1.5 to 12 to 14 bits/sample (depending on the implementation).
Parallel algorithms for high-speed SAR processing
NASA Astrophysics Data System (ADS)
Mallorqui, Jordi J.; Bara, Marc; Broquetas, Antoni; Wis, Mariano; Martinez, Antonio; Nogueira, Leonardo; Moreno, Victoriano
1998-11-01
The mass production of SAR products and its usage on monitoring emergency situations (oil spill detection, floods, etc.) requires high-speed SAR processors. Two different parallel strategies for near real time SAR processing based on a multiblock version of the Chirp Scaling Algorithm (CSA) have been studied. The first one is useful for small companies that would like to reduce computation times with no extra investment. It uses a cluster of heterogeneous UNIX workstations as a parallel computer. The second one is oriented to institutions, which have to process large amounts of data in short times and can afford the cost of large parallel computers. The parallel programming has reduced in both cases the computational times when compared with the sequential versions.
High specific activity platinum-195m
Mirzadeh, Saed; Du, Miting; Beets, Arnold L.; Knapp, Jr., Furn F.
2004-10-12
A new composition of matter includes .sup.195m Pt characterized by a specific activity of at least 30 mCi/mg Pt, generally made by method that includes the steps of: exposing .sup.193 Ir to a flux of neutrons sufficient to convert a portion of the .sup.193 Ir to .sup.195m Pt to form an irradiated material; dissolving the irradiated material to form an intermediate solution comprising Ir and Pt; and separating the Pt from the Ir by cation exchange chromatography to produce .sup.195m Pt.
NASA Astrophysics Data System (ADS)
An, Zhao; Zhounian, Lai; Peng, Wu; Linlin, Cao; Dazhuan, Wu
2016-07-01
This paper describes the shape optimization of a low specific speed centrifugal pump at the design point. The target pump has already been manually modified on the basis of empirical knowledge. A genetic algorithm (NSGA-II) with certain enhancements is adopted to improve its performance further with respect to two goals. In order to limit the number of design variables without losing geometric information, the impeller is parametrized using the BÃ©zier curve and a B-spline. Numerical simulation based on a Reynolds averaged Navier-Stokes (RANS) turbulent model is done in parallel to evaluate the flow field. A back-propagating neural network is constructed as a surrogate for performance prediction to save computing time, while initial samples are selected according to an orthogonal array. Then global Pareto-optimal solutions are obtained and analysed. The results manifest that unexpected flow structures, such as the secondary flow on the meridian plane, have diminished or vanished in the optimized pump.
Algorithms for high-speed universal noiseless coding
NASA Technical Reports Server (NTRS)
Rice, Robert F.; Yeh, Pen-Shu; Miller, Warner
1993-01-01
This paper provides the basic algorithmic definitions and performance characterizations for a high-performance adaptive noiseless (lossless) 'coding module' which is currently under separate developments as single-chip microelectronic circuits at two NASA centers. Laboratory tests of one of these implementations recently demonstrated coding rates of up to 900 Mbits/s. Operation of a companion 'decoding module' can operate at up to half the coder's rate. The functionality provided by these modules should be applicable to most of NASA's science data. The hardware modules incorporate a powerful adaptive noiseless coder for 'standard form' data sources (i.e., sources whose symbols can be represented by uncorrelated nonnegative integers where the smaller integers are more likely than the larger ones). Performance close to data entries can be expected over a 'dynamic range' of from 1.5 to 12-15 bits/sample (depending on the implementation). This is accomplished by adaptively choosing the best of many Huffman equivalent codes to use on each block of 1-16 samples. Because of the extreme simplicity of these codes no table lookups are actually required in an implementation, thus leading to the expected very high data rate capabilities already noted.
High-Dimensional Exploratory Item Factor Analysis by a Metropolis-Hastings Robbins-Monro Algorithm
ERIC Educational Resources Information Center
Cai, Li
2010-01-01
A Metropolis-Hastings Robbins-Monro (MH-RM) algorithm for high-dimensional maximum marginal likelihood exploratory item factor analysis is proposed. The sequence of estimates from the MH-RM algorithm converges with probability one to the maximum likelihood solution. Details on the computer implementation of this algorithm are provided. Theâ€¦
Heuristic-based scheduling algorithm for high level synthesis
NASA Technical Reports Server (NTRS)
Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye
1992-01-01
A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.
Ramyachitra, D.; Sofia, M.; Manikandan, P.
2015-01-01
Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions. PMID:26484222
Ramyachitra, D; Sofia, M; Manikandan, P
2015-09-01
Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions. PMID:26484222
Evaluation of machine learning algorithms for prediction of regions of high RANS uncertainty
Ling, Julia; Templeton, Jeremy Alan
2015-08-04
Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests. The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.
Evaluation of machine learning algorithms for prediction of regions of high RANS uncertainty
Ling, Julia; Templeton, Jeremy Alan
2015-08-04
Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests.moreÂ Â» The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.Â«Â less
NASA Astrophysics Data System (ADS)
Ling, J.; Templeton, J.
2015-08-01
Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests. The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. Feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.
Ling, Julia; Templeton, Jeremy Alan
2015-08-04
Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests.moreÂ Â» The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.Â«Â less
Ling, Julia; Templeton, Jeremy Alan
2015-08-04
Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests. The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.
An Algorithm for the Segmentation of Highly Abnormal Hearts Using a Generic Statistical Shape Model.
Alba, Xenia; Pereanez, Marco; Hoogendoorn, Corne; Swift, Andrew J; Wild, Jim M; Frangi, Alejandro F; Lekadir, Karim
2016-03-01
Statistical shape models (SSMs) have been widely employed in cardiac image segmentation. However, in conditions that induce severe shape abnormality and remodeling, such as in the case of pulmonary hypertension (PH) or hypertrophic cardiomyopathy (HCM), a single SSM is rarely capable of capturing the anatomical variability in the extremes of the distribution. This work presents a new algorithm for the segmentation of severely abnormal hearts. The algorithm is highly flexible, as it does not require a priori knowledge of the involved pathology or any specific parameter tuning to be applied to the cardiac image under analysis. The fundamental idea is to approximate the gross effect of the abnormality with a virtual remodeling transformation between the patient-specific geometry and the average shape of the reference model (e.g., average normal morphology). To define this mapping, a set of landmark points are automatically identified during boundary point search, by estimating the reliability of the candidate points. With the obtained transformation, the feature points extracted from the patient image volume are then projected onto the space of the reference SSM, where the model is used to effectively constrain and guide the segmentation process. The extracted shape in the reference space is finally propagated back to the original image of the abnormal heart to obtain the final segmentation. Detailed validation with patients diagnosed with PH and HCM shows the robustness and flexibility of the technique for the segmentation of highly abnormal hearts of different pathologies. PMID:26552082
Wang, Lei-Guang; Zheng, Chen; Lin, Li-Yu; Chen, Rong-Yuan; Mei, Tian-Can
2011-01-01
Mean Shift algorithm is a robust approach toward feature space analysis and it has been used wildly for natural scene image and medical image segmentation. However, high computational complexity of the algorithm has constrained its application in remote sensing images with massive information. A fast image segmentation algorithm is presented by extending traditional mean shift method to wavelet domain. In order to evaluate the effectiveness of the proposed algorithm, multispectral remote sensing image and synthetic image are utilized. The results show that the proposed algorithm can improve the speed 5-7 times compared to the traditional MS method in the premise of segmentation quality assurance. PMID:21428083
NASA Technical Reports Server (NTRS)
Pagnutti, Mary
2006-01-01
This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.
High School Educational Specifications: Facilities Planning Standards. Edition I.
ERIC Educational Resources Information Center
Jefferson County School District R-1, Denver, CO.
The Jefferson County School District (Colorado) has developed a manual of high school specifications for Design Advisory Groups and consultants to use for planning and designing the district's high school facilities. The specifications are provided to help build facilities that best meet the educational needs of the students to be served.â€¦
NASA Technical Reports Server (NTRS)
Mielke, R.; Stoughton, J.; Som, S.; Obando, R.; Malekpour, M.; Mandala, B.
1990-01-01
A functional description of the ATAMM Multicomputer Operating System is presented. ATAMM (Algorithm to Architecture Mapping Model) is a marked graph model which describes the implementation of large grained, decomposed algorithms on data flow architectures. AMOS, the ATAMM Multicomputer Operating System, is an operating system which implements the ATAMM rules. A first generation version of AMOS which was developed for the Advanced Development Module (ADM) is described. A second generation version of AMOS being developed for the Generic VHSIC Spaceborne Computer (GVSC) is also presented.
High-Performance Algorithm for Solving the Diagnosis Problem
NASA Technical Reports Server (NTRS)
Fijany, Amir; Vatan, Farrokh
2009-01-01
An improved method of model-based diagnosis of a complex engineering system is embodied in an algorithm that involves considerably less computation than do prior such algorithms. This method and algorithm are based largely on developments reported in several NASA Tech Briefs articles: The Complexity of the Diagnosis Problem (NPO-30315), Vol. 26, No. 4 (April 2002), page 20; Fast Algorithms for Model-Based Diagnosis (NPO-30582), Vol. 29, No. 3 (March 2005), page 69; Two Methods of Efficient Solution of the Hitting-Set Problem (NPO-30584), Vol. 29, No. 3 (March 2005), page 73; and Efficient Model-Based Diagnosis Engine (NPO-40544), on the following page. Some background information from the cited articles is prerequisite to a meaningful summary of the innovative aspects of the present method and algorithm. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD. Diagnosis the task of finding faulty components is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. The calculation of a minimal diagnosis is inherently a hard problem, the solution of which requires amounts of computation time and memory that increase exponentially with the number of components of the engineering system. Among the developments to reduce the computational burden, as reported in the cited articles, is the mapping of the diagnosis problem onto the integer-programming (IP) problem. This mapping makes it possible to utilize a variety of algorithms developed previously
SU-E-T-305: Study of the Eclipse Electron Monte Carlo Algorithm for Patient Specific MU Calculations
Wang, X; Qi, S; Agazaryan, N; DeMarco, J
2014-06-01
Purpose: To evaluate the Eclipse electron Monte Carlo (eMC) algorithm based on patient specific monitor unit (MU) calculations, and to propose a new factor which quantitatively predicts the discrepancy of MUs between the eMC algorithm and hand calculations. Methods: Electron treatments were planned for 61 patients on Eclipse (Version 10.0) using the eMC algorithm for Varian TrueBeam linear accelerators. For each patient, the same treatment beam angle was kept for a point dose calculation at dmax performed with the reference condition, which used an open beam with a 15Ã—15 cm2 size cone and 100 SSD. A patient specific correction factor (PCF) was obtained by getting the ratio between this point dose and the calibration dose, which is 1 cGy per MU delivered at dmax. The hand calculation results were corrected by the PCFs and compared with MUs from the treatment plans. Results: The MU from the treatment plans were in average (7.1Â±6.1)% higher than the hand calculations. The average MU difference between the corrected hand calculations and the eMC treatment plans was (0.07Â±3.48)%. A correlation coefficient of 0.8 was found between (1-PCF) and the percentage difference between the treatment plan and hand calculations. Most outliers were treatment plans with small beam opening (< 4 cm) and low energy beams (6 and 9 MeV). Conclusion: For CT-based patient treatment plans, the eMC algorithm tends to generate a larger MU than hand calculations. Caution should be taken for eMC patient plans with small field sizes and low energy beams. We hypothesize that the PCF ratio reflects the influence of patient surface curvature and tissue inhomogeneity to patient specific percent depth dose (PDD) curve and MU calculations in eMC algorithm.
Stride search: A general algorithm for storm detection in high resolution climate data
Bosler, Peter Andrew; Roesler, Erika Louise; Taylor, Mark A.; Mundt, Miranda
2015-09-08
This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared. The commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. Stride Search is designed to work at all latitudes, while grid point searches may fail in polar regions. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. The time required for both algorithms to search the same data set is compared. Furthermore, Stride Search's ability to search extreme latitudes is demonstrated for the case of polar low detection.
Stride search: A general algorithm for storm detection in high resolution climate data
Bosler, Peter Andrew; Roesler, Erika Louise; Taylor, Mark A.; Mundt, Miranda
2015-09-08
This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared. The commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. Stride Search is designed to work at all latitudes, while grid point searches may fail in polar regions. Results from the two algorithms are compared for the application of tropicalmoreÂ Â» cyclone detection, and shown to produce similar results for the same set of storm identification criteria. The time required for both algorithms to search the same data set is compared. Furthermore, Stride Search's ability to search extreme latitudes is demonstrated for the case of polar low detection.Â«Â less
One high-accuracy camera calibration algorithm based on computer vision images
NASA Astrophysics Data System (ADS)
Wang, Ying; Huang, Jianming; Wei, Xiangquan
2015-12-01
Camera calibration is the first step of computer vision and one of the most active research fields nowadays. In order to improve the measurement precision, the internal parameters of the camera should be accurately calibrated. So one high-accuracy camera calibration algorithm is proposed based on the images of planar targets or tridimensional targets. By using the algorithm, the internal parameters of the camera are calibrated based on the existing planar target at the vision-based navigation experiment. The experimental results show that the accuracy of the proposed algorithm is obviously improved compared with the conventional linear algorithm, Tsai general algorithm, and Zhang Zhengyou calibration algorithm. The algorithm proposed by the article can satisfy the need of computer vision and provide reference for precise measurement of the relative position and attitude.
Computationally efficient algorithm for high sampling-frequency operation of active noise control
NASA Astrophysics Data System (ADS)
Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati
2015-05-01
In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.
A new adaptive GMRES algorithm for achieving high accuracy
Sosonkina, M.; Watson, L.T.; Kapania, R.K.; Walker, H.F.
1996-12-31
GMRES(k) is widely used for solving nonsymmetric linear systems. However, it is inadequate either when it converges only for k close to the problem size or when numerical error in the modified Gram-Schmidt process used in the GMRES orthogonalization phase dramatically affects the algorithm performance. An adaptive version of GMRES (k) which tunes the restart value k based on criteria estimating the GMRES convergence rate for the given problem is proposed here. The essence of the adaptive GMRES strategy is to adapt the parameter k to the problem, similar in spirit to how a variable order ODE algorithm tunes the order k. With FORTRAN 90, which provides pointers and dynamic memory management, dealing with the variable storage requirements implied by varying k is not too difficult. The parameter k can be both increased and decreased-an increase-only strategy is described next followed by pseudocode.
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.
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.
Automated coronary artery calcium scoring from non-contrast CT using a patient-specific algorithm
NASA Astrophysics Data System (ADS)
Ding, Xiaowei; Slomka, Piotr J.; Diaz-Zamudio, Mariana; Germano, Guido; Berman, Daniel S.; Terzopoulos, Demetri; Dey, Damini
2015-03-01
Non-contrast cardiac CT is used worldwide to assess coronary artery calcium (CAC), a subclinical marker of coronary atherosclerosis. Manual quantification of regional CAC scores includes identifying candidate regions, followed by thresholding and connected component labeling. We aimed to develop and validate a fully-automated, algorithm for both overall and regional measurement of CAC scores from non-contrast CT using a hybrid multi-atlas registration, active contours and knowledge-based region separation algorithm. A co-registered segmented CT atlas was created from manually segmented non-contrast CT data from 10 patients (5 men, 5 women) and stored offline. For each patient scan, the heart region, left ventricle, right ventricle, ascending aorta and aortic root are located by multi-atlas registration followed by active contours refinement. Regional coronary artery territories (left anterior descending artery, left circumflex artery and right coronary artery) are separated using a knowledge-based region separation algorithm. Calcifications from these coronary artery territories are detected by region growing at each lesion. Global and regional Agatston scores and volume scores were calculated in 50 patients. Agatston scores and volume scores calculated by the algorithm and the expert showed excellent correlation (Agatston score: r = 0.97, p < 0.0001, volume score: r = 0.97, p < 0.0001) with no significant differences by comparison of individual data points (Agatston score: p = 0.30, volume score: p = 0.33). The total time was <60 sec on a standard computer. Our results show that fast accurate and automated quantification of CAC scores from non-contrast CT is feasible.
NASA Technical Reports Server (NTRS)
Williams, Craig Hamilton
1995-01-01
A simple, analytic approximation is derived to calculate trip time and performance for propulsion systems of very high specific impulse (50,000 to 200,000 seconds) and very high specific power (10 to 1000 kW/kg) for human interplanetary space missions. The approach assumed field-free space, constant thrust/constant specific power, and near straight line (radial) trajectories between the planets. Closed form, one dimensional equations of motion for two-burn rendezvous and four-burn round trip missions are derived as a function of specific impulse, specific power, and propellant mass ratio. The equations are coupled to an optimizing parameter that maximizes performance and minimizes trip time. Data generated for hypothetical one-way and round trip human missions to Jupiter were found to be within 1% and 6% accuracy of integrated solutions respectively, verifying that for these systems, credible analysis does not require computationally intensive numerical techniques.
Viewer preferences for classes of noise removal algorithms for high definition content
NASA Astrophysics Data System (ADS)
Deshpande, Sachin
2012-03-01
Perceived video quality studies were performed on a number of key classes of noise removal algorithms to determine viewer preference. The noise removal algorithm classes represent increase in complexity from linear filter to nonlinear filter to adaptive filter to spatio-temporal filter. The subjective results quantify the perceived quality improvements that can be obtained with increasing complexity. The specific algorithm classes tested include: linear spatial one channel filter, nonlinear spatial two-channel filter, adaptive nonlinear spatial filter, multi-frame spatio-temporal adaptive filter. All algorithms were applied on full HD (1080P) content. Our subjective results show that spatio-temporal (multi-frame) noise removal algorithm performs best amongst the various algorithm classes. The spatio-temporal algorithm improvement compared to original video sequences is statistically significant. On the average, noise-removed video sequences are preferred over original (noisy) video sequences. The Adaptive bilateral and non-adaptive bilateral two channel noise removal algorithms perform similarly on the average thus suggesting that a non-adaptive parameter tuned algorithm may be adequate.
A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case
Tsai, Chun-Wei; Tseng, Shih-Pang; Yang, Chu-Sing
2014-01-01
This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA. PMID:24892038
Trajectories for High Specific Impulse High Specific Power Deep Space Exploration
NASA Technical Reports Server (NTRS)
Polsgrove, Tara; Adams, Robert B.; Brady, Hugh J. (Technical Monitor)
2002-01-01
Flight times and deliverable masses for electric and fusion propulsion systems are difficult to approximate. Numerical integration is required for these continuous thrust systems. Many scientists are not equipped with the tools and expertise to conduct interplanetary and interstellar trajectory analysis for their concepts. Several charts plotting the results of well-known trajectory simulation codes were developed and are contained in this paper. These charts illustrate the dependence of time of flight and payload ratio on jet power, initial mass, specific impulse and specific power. These charts are intended to be a tool by which people in the propulsion community can explore the possibilities of their propulsion system concepts. Trajectories were simulated using the tools VARITOP and IPOST. VARITOP is a well known trajectory optimization code that involves numerical integration based on calculus of variations. IPOST has several methods of trajectory simulation; the one used in this paper is Cowell's method for full integration of the equations of motion. An analytical method derived in the companion paper was also evaluated. The accuracy of this method is discussed in the paper.
NASA Astrophysics Data System (ADS)
Jin, Minglei; Jin, Weiqi; Li, Yiyang; Li, Shuo
2015-08-01
In this paper, we propose a novel scene-based non-uniformity correction algorithm for infrared image processing-temporal high-pass non-uniformity correction algorithm based on grayscale mapping (THP and GM). The main sources of non-uniformity are: (1) detector fabrication inaccuracies; (2) non-linearity and variations in the read-out electronics and (3) optical path effects. The non-uniformity will be reduced by non-uniformity correction (NUC) algorithms. The NUC algorithms are often divided into calibration-based non-uniformity correction (CBNUC) algorithms and scene-based non-uniformity correction (SBNUC) algorithms. As non-uniformity drifts temporally, CBNUC algorithms must be repeated by inserting a uniform radiation source which SBNUC algorithms do not need into the view, so the SBNUC algorithm becomes an essential part of infrared imaging system. The SBNUC algorithms' poor robustness often leads two defects: artifacts and over-correction, meanwhile due to complicated calculation process and large storage consumption, hardware implementation of the SBNUC algorithms is difficult, especially in Field Programmable Gate Array (FPGA) platform. The THP and GM algorithm proposed in this paper can eliminate the non-uniformity without causing defects. The hardware implementation of the algorithm only based on FPGA has two advantages: (1) low resources consumption, and (2) small hardware delay: less than 20 lines, it can be transplanted to a variety of infrared detectors equipped with FPGA image processing module, it can reduce the stripe non-uniformity and the ripple non-uniformity.
NASA Astrophysics Data System (ADS)
Yadav, Deepti; Arora, M. K.; Tiwari, K. C.; Ghosh, J. K.
2016-04-01
Hyperspectral imaging is a powerful tool in the field of remote sensing and has been used for many applications like mineral detection, detection of landmines, target detection etc. Major issues in target detection using HSI are spectral variability, noise, small size of the target, huge data dimensions, high computation cost, complex backgrounds etc. Many of the popular detection algorithms do not work for difficult targets like small, camouflaged etc. and may result in high false alarms. Thus, target/background discrimination is a key issue and therefore analyzing target's behaviour in realistic environments is crucial for the accurate interpretation of hyperspectral imagery. Use of standard libraries for studying target's spectral behaviour has limitation that targets are measured in different environmental conditions than application. This study uses the spectral data of the same target which is used during collection of the HSI image. This paper analyze spectrums of targets in a way that each target can be spectrally distinguished from a mixture of spectral data. Artificial neural network (ANN) has been used to identify the spectral range for reducing data and further its efficacy for improving target detection is verified. The results of ANN proposes discriminating band range for targets; these ranges were further used to perform target detection using four popular spectral matching target detection algorithm. Further, the results of algorithms were analyzed using ROC curves to evaluate the effectiveness of the ranges suggested by ANN over full spectrum for detection of desired targets. In addition, comparative assessment of algorithms is also performed using ROC.
Development of a high-specific-speed centrifugal compressor
Rodgers, C.
1997-07-01
This paper describes the development of a subscale single-stage centrifugal compressor with a dimensionless specific speed (Ns) of 1.8, originally designed for full-size application as a high volume flow, low pressure ratio, gas booster compressor. The specific stage is noteworthy in that it provides a benchmark representing the performance potential of very high-specific-speed compressors, of which limited information is found in the open literature. Stage and component test performance characteristics are presented together with traverse results at the impeller exit. Traverse test results were compared with recent CFD computational predictions for an exploratory analytical calibration of a very high-specific-speed impeller geometry. The tested subscale (0.583) compressor essentially satisfied design performance expectations with an overall stage efficiency of 74% including, excessive exit casing losses. It was estimated that stage efficiency could be increased to 81% with exit casing losses halved.
A novel algorithm for simultaneous SNP selection in high-dimensional genome-wide association studies
2012-01-01
Background Identification of causal SNPs in most genome wide association studies relies on approaches that consider each SNP individually. However, there is a strong correlation structure among SNPs that needs to be taken into account. Hence, increasingly modern computationally expensive regression methods are employed for SNP selection that consider all markers simultaneously and thus incorporate dependencies among SNPs. Results We develop a novel multivariate algorithm for large scale SNP selection using CAR score regression, a promising new approach for prioritizing biomarkers. Specifically, we propose a computationally efficient procedure for shrinkage estimation of CAR scores from high-dimensional data. Subsequently, we conduct a comprehensive comparison study including five advanced regression approaches (boosting, lasso, NEG, MCP, and CAR score) and a univariate approach (marginal correlation) to determine the effectiveness in finding true causal SNPs. Conclusions Simultaneous SNP selection is a challenging task. We demonstrate that our CAR score-based algorithm consistently outperforms all competing approaches, both uni- and multivariate, in terms of correctly recovered causal SNPs and SNP ranking. An R package implementing the approach as well as R code to reproduce the complete study presented here is available from http://strimmerlab.org/software/care/. PMID:23113980
A highly efficient multi-core algorithm for clustering extremely large datasets
2010-01-01
Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922
High performance cone-beam spiral backprojection with voxel-specific weighting.
Steckmann, Sven; Knaup, Michael; Kachelriess, Marc
2009-06-21
Cone-beam spiral backprojection is computationally highly demanding. At first sight, the backprojection requirements are similar to those of cone-beam backprojection from circular scans such as it is performed in the widely used Feldkamp algorithm. However, there is an additional complication: the illumination of each voxel, i.e. the range of angles the voxel is seen by the x-ray cone, is a complex function of the voxel position. In general, one needs to multiply a voxel-specific weight w(x, y, z, alpha) prior to adding a projection from angle alpha to a voxel at position x, y, z. Often, the weight function has no analytically closed form and must be numerically determined. Storage of the weights is prohibitive since the amount of memory required equals the number of voxels per spiral rotation times the number of projections a voxel receives contributions and therefore is in the order of up to 10(12) floating point values for typical spiral scans. We propose a new algorithm that combines the spiral symmetry with the ability of today's 64 bit operating systems to store large amounts of precomputed weights, even above the 4 GB limit. Our trick is to backproject into slices that are rotated in the same manner as the spiral trajectory rotates. Using the spiral symmetry in this way allows one to exploit data-level paralellism and thereby to achieve a very high level of vectorization. An additional postprocessing step rotates these slices back to normal images. Our new backprojection algorithm achieves up to 17 giga voxel updates per second on our systems that are equipped with four standard Intel X7460 hexa core CPUs (Intel Xeon 7300 platform, 2.66 GHz, Intel Corporation). This equals the reconstruction of 344 images per second assuming that each slice consists of 512 x 512 pixels and receives contributions from 512 projections. Thereby, it is an order of magnitude faster than a highly optimized code that does not make use of the spiral symmetry. In its present version
High performance cone-beam spiral backprojection with voxel-specific weighting
NASA Astrophysics Data System (ADS)
Steckmann, Sven; Knaup, Michael; KachelrieÃŸ, Marc
2009-06-01
Cone-beam spiral backprojection is computationally highly demanding. At first sight, the backprojection requirements are similar to those of cone-beam backprojection from circular scans such as it is performed in the widely used Feldkamp algorithm. However, there is an additional complication: the illumination of each voxel, i.e. the range of angles the voxel is seen by the x-ray cone, is a complex function of the voxel position. In general, one needs to multiply a voxel-specific weight w(x, y, z, Î±) prior to adding a projection from angle Î± to a voxel at position x, y, z. Often, the weight function has no analytically closed form and must be numerically determined. Storage of the weights is prohibitive since the amount of memory required equals the number of voxels per spiral rotation times the number of projections a voxel receives contributions and therefore is in the order of up to 1012 floating point values for typical spiral scans. We propose a new algorithm that combines the spiral symmetry with the ability of today's 64 bit operating systems to store large amounts of precomputed weights, even above the 4 GB limit. Our trick is to backproject into slices that are rotated in the same manner as the spiral trajectory rotates. Using the spiral symmetry in this way allows one to exploit data-level paralellism and thereby to achieve a very high level of vectorization. An additional postprocessing step rotates these slices back to normal images. Our new backprojection algorithm achieves up to 17 giga voxel updates per second on our systems that are equipped with four standard Intel X7460 hexa core CPUs (Intel Xeon 7300 platform, 2.66 GHz, Intel Corporation). This equals the reconstruction of 344 images per second assuming that each slice consists of 512 Ã— 512 pixels and receives contributions from 512 projections. Thereby, it is an order of magnitude faster than a highly optimized code that does not make use of the spiral symmetry. In its present version, the
Algorithms and architectures for high performance analysis of semantic graphs.
Hendrickson, Bruce Alan
2005-09-01
analysis. Since intelligence datasets can be extremely large, the focus of this work is on the use of parallel computers. We have been working to develop scalable parallel algorithms that will be at the core of a semantic graph analysis infrastructure. Our work has involved two different thrusts, corresponding to two different computer architectures. The first architecture of interest is distributed memory, message passing computers. These machines are ubiquitous and affordable, but they are challenging targets for graph algorithms. Much of our distributed-memory work to date has been collaborative with researchers at Lawrence Livermore National Laboratory and has focused on finding short paths on distributed memory parallel machines. Our implementation on 32K processors of BlueGene/Light finds shortest paths between two specified vertices in just over a second for random graphs with 4 billion vertices.
NASA Astrophysics Data System (ADS)
Boiko, I. M.
2012-01-01
The modified second-order sliding mode algorithm is used for controller tuning. Namely, the modified suboptimal algorithm-based test (modified SOT) and non-parametric tuning rules for proportional-integral-derivative (PID) controllers are presented in this article. In the developed method of test and tuning, the idea of coordinated selection of the test parameters and the controller tuning parameters is introduced. The proposed approach allows for the formulation of simple non-parametric tuning rules for PID controllers that provide desired amplitude or phase margins exactly. In the modified SOT, the frequency of the self-excited oscillations can be generated equal to either the phase crossover frequency or the magnitude crossover frequency of the open-loop system frequency response (including a future PID controller) - depending on the tuning method choice. The first option will provide tuning with specification on gain margin, and the second option will ensure tuning with specification on phase margin. Tuning rules for a PID controller and simulation examples are provided.
Noncovalent functionalization of carbon nanotubes for highly specific electronic biosensors
NASA Astrophysics Data System (ADS)
Chen, Robert J.; Bangsaruntip, Sarunya; Drouvalakis, Katerina A.; Wong Shi Kam, Nadine; Shim, Moonsub; Li, Yiming; Kim, Woong; Utz, Paul J.; Dai, Hongjie
2003-04-01
Novel nanomaterials for bioassay applications represent a rapidly progressing field of nanotechnology and nanobiotechnology. Here, we present an exploration of single-walled carbon nanotubes as a platform for investigating surface-protein and protein-protein binding and developing highly specific electronic biomolecule detectors. Nonspecific binding on nanotubes, a phenomenon found with a wide range of proteins, is overcome by immobilization of polyethylene oxide chains. A general approach is then advanced to enable the selective recognition and binding of target proteins by conjugation of their specific receptors to polyethylene oxide-functionalized nanotubes. This scheme, combined with the sensitivity of nanotube electronic devices, enables highly specific electronic sensors for detecting clinically important biomolecules such as antibodies associated with human autoimmune diseases.
The evolutionary development of high specific impulse electric thruster technology
NASA Technical Reports Server (NTRS)
Sovey, James S.; Hamley, John A.; Patterson, Michael J.; Rawlin, Vincent K.; Myers, Roger M.
1992-01-01
Electric propulsion flight and technology demonstrations conducted primarily by Europe, Japan, China, the U.S., and the USSR are reviewed. Evolutionary mission applications for high specific impulse electric thruster systems are discussed, and the status of arcjet, ion, and magnetoplasmadynamic thrusters and associated power processor technologies are summarized.
The evolutionary development of high specific impulse electric thruster technology
Sovey, J.S.; Hamley, J.A.; Patterson, M.J.; Rawlin, V.K.; Meyers, R.M.
1992-03-01
Electric propulsion flight and technology demonstrations conducted primarily by Europe, Japan, Peoples Republic of China, USA, and USSR are reviewed. Evolutionary mission applications for high specific impulse electric thruster systems are discussed, and the status of arcjet, ion, and magnetoplasmadynamic thruster and associated power processor technologies are summarized.
A Ratio Test of Interrater Agreement with High Specificity
ERIC Educational Resources Information Center
Cousineau, Denis; Laurencelle, Louis
2015-01-01
Existing tests of interrater agreements have high statistical power; however, they lack specificity. If the ratings of the two raters do not show agreement but are not random, the current tests, some of which are based on Cohen's kappa, will often reject the null hypothesis, leading to the wrong conclusion that agreement is present. A new test ofâ€¦
Experiences with the hydraulic design of the high specific speed Francis turbine
NASA Astrophysics Data System (ADS)
Obrovsky, J.; Zouhar, J.
2014-03-01
The high specific speed Francis turbine is still suitable alternative for refurbishment of older hydro power plants with lower heads and worse cavitation conditions. In the paper the design process of such kind of turbine together with the results comparison of homological model tests performed in hydraulic laboratory of ÄŒKD Blansko Engineering is introduced. The turbine runner was designed using the optimization algorithm and considering the high specific speed hydraulic profile. It means that hydraulic profiles of the spiral case, the distributor and the draft tube were used from a Kaplan turbine. The optimization was done as the automatic cycle and was based on a simplex optimization method as well as on a genetic algorithm. The number of blades is shown as the parameter which changes the resulting specific speed of the turbine between ns=425 to 455 together with the cavitation characteristics. Minimizing of cavitation on the blade surface as well as on the inlet edge of the runner blade was taken into account during the design process. The results of CFD analyses as well as the model tests are mentioned in the paper.
Phase-unwrapping algorithm for images with high noise content based on a local histogram
NASA Astrophysics Data System (ADS)
Meneses, Jaime; Gharbi, Tijani; Humbert, Philippe
2005-03-01
We present a robust algorithm of phase unwrapping that was designed for use on phase images with high noise content. We proceed with the algorithm by first identifying regions with continuous phase values placed between fringe boundaries in an image and then phase shifting the regions with respect to one another by multiples of 2pi to unwrap the phase. Image pixels are segmented between interfringe and fringe boundary areas by use of a local histogram of a wrapped phase. The algorithm has been used successfully to unwrap phase images generated in a three-dimensional shape measurement for noninvasive quantification of human skin structure in dermatology, cosmetology, and plastic surgery.
Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin
2015-10-19
The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study. PMID:26480397
Next Generation Seismic Imaging; High Fidelity Algorithms and High-End Computing
NASA Astrophysics Data System (ADS)
Bevc, D.; Ortigosa, F.; Guitton, A.; Kaelin, B.
2007-05-01
uniquely powerful computing power of the MareNostrum supercomputer in Barcelona to realize the promise of RTM, incorporate it into daily processing flows, and to help solve exploration problems in a highly cost-effective way. Uniquely, the Kaleidoscope Project is simultaneously integrating software (algorithms) and hardware (Cell BE), steps that are traditionally taken sequentially. This unique integration of software and hardware will accelerate seismic imaging by several orders of magnitude compared to conventional solutions running on standard Linux Clusters.
A novel algorithm combining oversampling and digital lock-in amplifier of high speed and precision
NASA Astrophysics Data System (ADS)
Li, Gang; Zhou, Mei; He, Feng; Lin, Ling
2011-09-01
Because of a large amount of arithmetic in the standard digital lock-in detection, a high performance processor is needed to implement the algorithm in real time. This paper presents a novel algorithm that integrates oversampling and high-speed lock-in detection. The algorithm sets the sampling frequency as a whole-number multiple of four of the input signal frequency, and then uses the common downsampling technology to lower the sampling frequency to four times of the input signal frequency. It could effectively remove the noise interference and improve the detection accuracy. After that the phase sensitive detector is implemented. It simply does the addition and subtraction on four points in the period of same phase and replaces almost all the multiplication operations to speed up digital lock-in detection calculation substantially. Furthermore, the correction factor is introduced to improve the calculation accuracy of the amplitude, and an error caused by the algorithm in theory can be eliminated completely. The results of the simulation and actual experiments show that the novel algorithm combining digital lock-in detection and oversampling not only has the high precision, but also has the unprecedented speed. In our work, the new algorithm is suitable for the real-time weak signal detection in the general microprocessor not just digital signal processor.
Overton, Terry; Fielding, Cheryl; de Alba, Roman Garcia
2008-07-01
This study compared Autism diagnostic observation schedule (ADOS) algorithm scores of a sample of 26 children who were administered modules 1-3 of the ADOS with the scores obtained applying the revised ADOS algorithm proposed by Gotham et al. (2007). Results of this application were inconsistent, yielding slightly more accurate results for module 1. New algorithm scores on modules 2 and 3 remained consistent with the original algorithm scores. The Mann-Whitney U was applied to compare revised algorithm and clinical levels of social impairment to determine if significant differences were evident. Results of Mann-Whitney U analyses were inconsistent and demonstrated less specificity for children with milder levels of social impairment. The revised algorithm demonstrated accuracy for the more severe autistic group. PMID:18026872
An end-to-end workflow for engineering of biological networks from high-level specifications.
Beal, Jacob; Weiss, Ron; Densmore, Douglas; Adler, Aaron; Appleton, Evan; Babb, Jonathan; Bhatia, Swapnil; Davidsohn, Noah; Haddock, Traci; Loyall, Joseph; Schantz, Richard; Vasilev, Viktor; Yaman, Fusun
2012-08-17
We present a workflow for the design and production of biological networks from high-level program specifications. The workflow is based on a sequence of intermediate models that incrementally translate high-level specifications into DNA samples that implement them. We identify algorithms for translating between adjacent models and implement them as a set of software tools, organized into a four-stage toolchain: Specification, Compilation, Part Assignment, and Assembly. The specification stage begins with a Boolean logic computation specified in the Proto programming language. The compilation stage uses a library of network motifs and cellular platforms, also specified in Proto, to transform the program into an optimized Abstract Genetic Regulatory Network (AGRN) that implements the programmed behavior. The part assignment stage assigns DNA parts to the AGRN, drawing the parts from a database for the target cellular platform, to create a DNA sequence implementing the AGRN. Finally, the assembly stage computes an optimized assembly plan to create the DNA sequence from available part samples, yielding a protocol for producing a sample of engineered plasmids with robotics assistance. Our workflow is the first to automate the production of biological networks from a high-level program specification. Furthermore, the workflow's modular design allows the same program to be realized on different cellular platforms simply by swapping workflow configurations. We validated our workflow by specifying a small-molecule sensor-reporter program and verifying the resulting plasmids in both HEK 293 mammalian cells and in E. coli bacterial cells. PMID:23651286
High-speed computation of the EM algorithm for PET image reconstruction
Rajan, K.; Patnaik, L.M.; Ramakrishna, J. )
1994-10-01
The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution backprojection algorithms. However, two major drawbacks have impeded the routine use of the EM algorithm, namely, the long computational time due to slow convergence and the large memory required for the storage of the image, projection data and the probability matrix. In this study, the authors attempts to solve these two problems by parallelizing the EM algorithm on a multiprocessor system. The authors have implemented an extended hypercube (EH) architecture for the high-speed computation of the EM algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs). The authors discuss and compare the performance of the EM algorithm on a 386/387 machine, CD 4360 mainframe, and on the EH system. The results show that the computational speed performance of an EH using DSP chips as PEs executing the EM image reconstruction algorithm is about 130 times better than that of the CD 4360 mainframe. The EH topology is expandable with more number of PEs.
High speed multiplier using Nikhilam Sutra algorithm of Vedic mathematics
NASA Astrophysics Data System (ADS)
Pradhan, Manoranjan; Panda, Rutuparna
2014-03-01
This article presents the design of a new high-speed multiplier architecture using Nikhilam Sutra of Vedic mathematics. The proposed multiplier architecture finds out the compliment of the large operand from its nearest base to perform the multiplication. The multiplication of two large operands is reduced to the multiplication of their compliments and addition. It is more efficient when the magnitudes of both operands are more than half of their maximum values. The carry save adder in the multiplier architecture increases the speed of addition of partial products. The multiplier circuit is synthesised and simulated using Xilinx ISE 10.1 software and implemented on Spartan 2 FPGA device XC2S30-5pq208. The output parameters such as propagation delay and device utilisation are calculated from synthesis results. The performance evaluation results in terms of speed and device utilisation are compared with earlier multiplier architecture. The proposed design has speed improvements compared to multiplier architecture presented in the literature.
Fast two-dimensional super-resolution image reconstruction algorithm for ultra-high emitter density.
Huang, Jiaqing; Gumpper, Kristyn; Chi, Yuejie; Sun, Mingzhai; Ma, Jianjie
2015-07-01
Single-molecule localization microscopy achieves sub-diffraction-limit resolution by localizing a sparse subset of stochastically activated emitters in each frame. Its temporal resolution is limited by the maximal emitter density that can be handled by the image reconstruction algorithms. Multiple algorithms have been developed to accurately locate the emitters even when they have significant overlaps. Currently, compressive-sensing-based algorithm (CSSTORM) achieves the highest emitter density. However, CSSTORM is extremely computationally expensive, which limits its practical application. Here, we develop a new algorithm (MempSTORM) based on two-dimensional spectrum analysis. With the same localization accuracy and recall rate, MempSTORM is 100 times faster than CSSTORM with â„“(1)-homotopy. In addition, MempSTORM can be implemented on a GPU for parallelism, which can further increase its computational speed and make it possible for online super-resolution reconstruction of high-density emitters. PMID:26125349
Zhang Changjiang; Wang Xiaodong
2008-11-06
An efficient typhoon cloud image restoration algorithm is proposed. Having implemented contourlet transform to a typhoon cloud image, noise is reduced in the high sub-bands. Weight median value filter is used to reduce the noise in the contourlet domain. Inverse contourlet transform is done to obtain the de-noising image. In order to enhance the global contrast of the typhoon cloud image, in-complete Beta transform (IBT) is used to determine non-linear gray transform curve so as to enhance global contrast for the de-noising typhoon cloud image. Genetic algorithm is used to obtain the optimal gray transform curve. Information entropy is used as the fitness function of the genetic algorithm. Experimental results show that the new algorithm is able to well enhance the global for the typhoon cloud image while well reducing the noises in the typhoon cloud image.
Chuan, He; Dishan, Qiu; Jin, Liu
2012-01-01
The cooperative scheduling problem on high-altitude airships for imaging observation tasks is discussed. A constraint programming model is established by analyzing the main constraints, which takes the maximum task benefit and the minimum cruising distance as two optimization objectives. The cooperative scheduling problem of high-altitude airships is converted into a main problem and a subproblem by adopting hierarchy architecture. The solution to the main problem can construct the preliminary matching between tasks and observation resource in order to reduce the search space of the original problem. Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA). Then, a novel swarm intelligence algorithm named propagation algorithm (PA) is combined with the key node search algorithm (KNSA) to optimize the cruising path of each airship and determine the execution time interval of each task. Meanwhile, this paper also provides the realization approach of the above algorithm and especially makes a detailed introduction on the encoding rules, search models, and propagation mechanism of the PA. Finally, the application results and comparison analysis show the proposed models and algorithms are effective and feasible. PMID:23365522
Chuan, He; Dishan, Qiu; Jin, Liu
2012-01-01
The cooperative scheduling problem on high-altitude airships for imaging observation tasks is discussed. A constraint programming model is established by analyzing the main constraints, which takes the maximum task benefit and the minimum cruising distance as two optimization objectives. The cooperative scheduling problem of high-altitude airships is converted into a main problem and a subproblem by adopting hierarchy architecture. The solution to the main problem can construct the preliminary matching between tasks and observation resource in order to reduce the search space of the original problem. Furthermore, the solution to the sub-problem can detect the key nodes that each airship needs to fly through in sequence, so as to get the cruising path. Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA). Then, a novel swarm intelligence algorithm named propagation algorithm (PA) is combined with the key node search algorithm (KNSA) to optimize the cruising path of each airship and determine the execution time interval of each task. Meanwhile, this paper also provides the realization approach of the above algorithm and especially makes a detailed introduction on the encoding rules, search models, and propagation mechanism of the PA. Finally, the application results and comparison analysis show the proposed models and algorithms are effective and feasible. PMID:23365522
The evolutionary development of high specific impulse electric thruster technology
NASA Technical Reports Server (NTRS)
Sovey, James S.; Hamley, John A.; Patterson, Michael J.; Rawlin, Vincent K.; Myers, Roger M.
1992-01-01
Electric propulsion flight and technology demonstrations conducted in the USA, Europe, Japan, China, and USSR are reviewed with reference to the major flight qualified electric propulsion systems. These include resistojets, ion thrusters, ablative pulsed plasma thrusters, stationary plasma thrusters, pulsed magnetoplasmic thrusters, and arcjets. Evolutionary mission applications are presented for high specific impulse electric thruster systems. The current status of arcjet, ion, and magnetoplasmadynamic thrusters and their associated power processor technologies are summarized.
The evolutionary development of high specific impulse electric thruster technology
Sovey, J.S.; Hamley, J.A.; Patterson, M.J.; Rawlin, V.K.; Myers, R.M. Sverdrup Technology, Inc., Brook Park, OH )
1992-03-01
Electric propulsion flight and technology demonstrations conducted in the USA, Europe, Japan, China, and USSR are reviewed with reference to the major flight qualified electric propulsion systems. These include resistojets, ion thrusters, ablative pulsed plasma thrusters, stationary plasma thrusters, pulsed magnetoplasmic thrusters, and arcjets. Evolutionary mission applications are presented for high specific impulse electric thruster systems. The current status of arcjet, ion, and magnetoplasmadynamic thrusters and their associated power processor technologies are summarized. 114 refs.
Method of preparing high specific activity platinum-195m
Mirzadeh, Saed; Du, Miting; Beets, Arnold L.; Knapp, Jr., Furn F.
2004-06-15
A method of preparing high-specific-activity .sup.195m Pt includes the steps of: exposing .sup.193 Ir to a flux of neutrons sufficient to convert a portion of the .sup.193 Ir to .sup.195m Pt to form an irradiated material; dissolving the irradiated material to form an intermediate solution comprising Ir and Pt; and separating the Pt from the Ir by cation exchange chromatography to produce .sup.195m Pt.
Method for preparing high specific activity 177Lu
Mirzadeh, Saed; Du, Miting; Beets, Arnold L.; Knapp, Jr., Furn F.
2004-04-06
A method of separating lutetium from a solution containing Lu and Yb, particularly reactor-produced .sup.177 Lu and .sup.177 Yb, includes the steps of: providing a chromatographic separation apparatus containing LN resin; loading the apparatus with a solution containing Lu and Yb; and eluting the apparatus to chromatographically separate the Lu and the Yb in order to produce high-specific-activity .sup.177 Yb.
Technology Transfer Automated Retrieval System (TEKTRAN)
Ground water levels are declining at unsustainable rates in the Texas High Plains. Accurate evapotranspiration (ET) maps would provide valuable information on regional crop water use and hydrology. This study evaluated three remote sensing based algorithms for estimating ET rates for the Texas High ...
Andrici, Juliana; Farzin, Mahtab; Clarkson, Adele; Sioson, Loretta; Sheen, Amy; Watson, Nicole; Toon, Christopher W; Koleth, Mary; Stevenson, William; Gill, Anthony J
2016-06-01
The identification of somatic calreticulin (CALR) mutations can be used to confirm the diagnosis of a myeloproliferative disorder in Philadelphia chromosome-negative, JAK2 and MPL wild type patients with thrombocytosis. All pathogenic CALR mutations result in an identical C-terminal protein and therefore may be identifiable by immunohistochemistry. We sought to test the sensitivity and specificity of mutation specific immunohistochemistry for pathogenic CALR mutations using a commercially available mouse monoclonal antibody (clone CAL2). Immunohistochemistry for mutant calreticulin was performed on the most recent bone marrow trephine from a cohort of patients enriched for CALR mutations and compared to mutation testing performed by polymerase chain reaction (PCR) amplification followed by fragment length analysis. Twenty-nine patients underwent both immunohistochemistry and molecular testing. Eleven patients had CALR mutation, and immunohistochemistry was positive in nine (82%). One discrepant case appeared to represent genuine false negative immunohistochemistry. The other may be attributable to a 12 year delay between the bone marrow trephine and the specimen which underwent molecular testing, particularly because a liver biopsy performed at the same time as molecular testing demonstrated positive staining in megakaryocytes in extramedullary haematopoiesis. All 18 cases which lacked CALR mutation demonstrated negative staining. In this population enriched for CALR mutations, the specificity was 100%; sensitivity 82-91%, positive predictive value 100% and negative predictive value 90-95%. We conclude that mutation specific immunohistochemistry is highly specific for the presence of CALR mutations. Whilst it may not identify all mutations, it may be very valuable in routine clinical care. PMID:27114372
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
NASA Astrophysics Data System (ADS)
Tkaczyk, Tomasz S.; Rahman, Mohammed; Mack, Vivian; Sokolov, Konstantin; Rogers, Jeremy D.; Richards-Kortum, Rebecca; Descour, Michael R.
2004-08-01
Structured-illumination microscopy delivers confocal-imaging capabilities and may be used for optical sectioning in bio-imaging applications. However, previous structured-illumination implementations are not capable of imaging molecular changes within highly scattering, biological samples in reflectance mode. Here, we present two advances which enable successful structured illumination reflectance microscopy to image molecular changes in epithelial tissue phantoms. First, we present the sine approximation algorithm to improve the ability to reconstruct the in-focus plane when the out-of-focus light is much greater in magnitude. We characterize the dependencies of this algorithm on phase step error, random noise and backscattered out-of-focus contributions. Second, we utilize a molecular-specific reflectance contrast agent based on gold nanoparticles to label disease-related biomarkers and increase the signal and signal-to-noise ratio (SNR) in structured illumination microscopy of biological tissue. Imaging results for multi-layer epithelial cell phantoms with optical properties characteristic of normal and cancerous tissue labeled with nanoparticles targeted against the epidermal growth factor receptor (EGFR) are presented. Structured illumination images reconstructed with the sine approximation algorithm compare favorably to those obtained with a standard confocal microscope; this new technique can be implemented in simple and small imaging platforms for future clinical studies.
Automatic, Real-Time Algorithms for Anomaly Detection in High Resolution Satellite Imagery
NASA Astrophysics Data System (ADS)
Srivastava, A. N.; Nemani, R. R.; Votava, P.
2008-12-01
Earth observing satellites are generating data at an unprecedented rate, surpassing almost all other data intensive applications. However, most of the data that arrives from the satellites is not analyzed directly. Rather, multiple scientific teams analyze only a small fraction of the total data available in the data stream. Although there are many reasons for this situation one paramount concern is developing algorithms and methods that can analyze the vast, high dimensional, streaming satellite images. This paper describes a new set of methods that are among the fastest available algorithms for real-time anomaly detection. These algorithms were built to maximize accuracy and speed for a variety of applications in fields outside of the earth sciences. However, our studies indicate that with appropriate modifications, these algorithms can be extremely valuable for identifying anomalies rapidly using only modest computational power. We review two algorithms which are used as benchmarks in the field: Orca, One-Class Support Vector Machines and discuss the anomalies that are discovered in MODIS data taken over the Central California region. We are especially interested in automatic identification of disturbances within the ecosystems (e,g, wildfires, droughts, floods, insect/pest damage, wind damage, logging). We show the scalability of the algorithms and demonstrate that with appropriately adapted technology, the dream of real-time analysis can be made a reality.
High efficiency cell-specific targeting of cytokine activity
NASA Astrophysics Data System (ADS)
Garcin, GeneviÃ¨ve; Paul, Franciane; Staufenbiel, Markus; Bordat, Yann; van der Heyden, JosÃ©; Wilmes, Stephan; Cartron, Guillaume; Apparailly, Florence; de Koker, Stefaan; Piehler, Jacob; Tavernier, Jan; UzÃ©, Gilles
2014-01-01
Systemic toxicity currently prevents exploiting the huge potential of many cytokines for medical applications. Here we present a novel strategy to engineer immunocytokines with very high targeting efficacies. The method lies in the use of mutants of toxic cytokines that markedly reduce their receptor-binding affinities, and that are thus rendered essentially inactive. Upon fusion to nanobodies specifically binding to marker proteins, activity of these cytokines is selectively restored for cell populations expressing this marker. This â€˜activity-by-targetingâ€™ concept was validated for type I interferons and leptin. In the case of interferon, activity can be directed to target cells in vitro and to selected cell populations in mice, with up to 1,000-fold increased specific activity. This targeting strategy holds promise to revitalize the clinical potential of many cytokines.
Cellulose antibody films for highly specific evanescent wave immunosensors
NASA Astrophysics Data System (ADS)
Hartmann, Andreas; Bock, Daniel; Jaworek, Thomas; Kaul, Sepp; Schulze, Matthais; Tebbe, H.; Wegner, Gerhard; Seeger, Stefan
1996-01-01
For the production of recognition elements for evanescent wave immunosensors optical waveguides have to be coated with ultrathin stable antibody films. In the present work non amphiphilic alkylated cellulose and copolyglutamate films are tested as monolayer matrices for the antibody immobilization using the Langmuir-Blodgett technique. These films are transferred onto optical waveguides and serve as excellent matrices for the immobilization of antibodies in high density and specificity. In addition to the multi-step immobilization of immunoglobulin G(IgG) on photochemically crosslinked and oxidized polymer films, the direct one-step transfer of mixed antibody-polymer films is performed. Both planar waveguides and optical fibers are suitable substrates for the immobilization. The activity and specificity of immobilized antibodies is controlled by the enzyme-linked immunosorbent assay (ELISA) technique. As a result reduced non-specific interactions between antigens and the substrate surface are observed if cinnamoylbutyether-cellulose is used as the film matrix for the antibody immobilization. Using the evanescent wave senor (EWS) technology immunosensor assays are performed in order to determine both the non-specific adsorption of different coated polymethylmethacrylat (PMMA) fibers and the long-term stability of the antibody films. Specificities of one-step transferred IgG-cellulose films are drastically enhanced compared to IgG-copolyglutamate films. Cellulose IgG films are used in enzymatic sandwich assays using mucine as a clinical relevant antigen that is recognized by the antibodies BM2 and BM7. A mucine calibration measurement is recorded. So far the observed detection limit for mucine is about 8 ng/ml.
A High-Order Finite-Volume Algorithm for Fokker-Planck Collisions in Magnetized Plasmas
Xiong, Z; Cohen, R H; Rognlien, T D; Xu, X Q
2007-04-18
A high-order finite volume algorithm is developed for the Fokker-Planck Operator (FPO) describing Coulomb collisions in strongly magnetized plasmas. The algorithm is based on a general fourth-order reconstruction scheme for an unstructured grid in the velocity space spanned by parallel velocity and magnetic moment. The method provides density conservation and high-order-accurate evaluation of the FPO independent of the choice of the velocity coordinates. As an example, a linearized FPO in constant-of-motion coordinates, i.e. the total energy and the magnetic moment, is developed using the present algorithm combined with a cut-cell merging procedure. Numerical tests include the Spitzer thermalization problem and the return to isotropy for distributions initialized with velocity space loss cones. Utilization of the method for a nonlinear FPO is straightforward but requires evaluation of the Rosenbluth potentials.
A fast and high performance multiple data integration algorithm for identifying human disease genes
2015-01-01
Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620
A Monolithic Algorithm for High Reynolds Number Fluid-Structure Interaction Simulations
NASA Astrophysics Data System (ADS)
Lieberknecht, Erika; Sheldon, Jason; Pitt, Jonathan
2013-11-01
Simulations of fluid-structure interaction problems with high Reynolds number flows are typically approached with partitioned algorithms that leverage the robustness of traditional finite volume method based CFD techniques for flows of this nature. However, such partitioned algorithms are subject to many sub-iterations per simulation time-step, which substantially increases the computational cost when a tightly coupled solution is desired. To address this issue, we present a finite element method based monolithic algorithm for fluid-structure interaction problems with high Reynolds number flow. The use of a monolithic algorithm will potentially reduce the computational cost during each time-step, but requires that all of the governing equations be simultaneously cast in a single Arbitrary Lagrangian-Eulerian (ALE) frame of reference and subjected to the same discretization strategy. The formulation for the fluid solution is stabilized by implementing a Streamline Upwind Galerkin (SUPG) method, and a projection method for equal order interpolation of all of the solution unknowns; numerical and programming details are discussed. Preliminary convergence studies and numerical investigations are presented, to demonstrate the algorithm's robustness and performance. The authors acknowledge support for this project from the Applied Research Laboratory Eric Walker Graduate Fellowship Program.
NASA Astrophysics Data System (ADS)
Fan, X.; Wang, X.; Wang, X.; Xu, Y.; Que, J.; He, H.; Wang, X.; Tang, M.
2016-02-01
Background noise is one of the main interference sources of the Raman spectroscopy measurement and imaging technique. In this paper, a sparse representation based algorithm is presented to process the Raman signals under high background noise. In contrast with the existing de-noising methods, the proposed method reconstructs the pure Raman signals by estimating the Raman peak information. The advantage of the proposed algorithm is its high anti-noise capacity and low pure Raman signal reduction contributed by its reconstruction principle. Meanwhile, the Batch-OMP algorithm is applied to accelerate the training of the sparse representation. Therefore, it is very suitable to be adopted in the Raman measurement or imaging instruments to observe fast dynamic processes where the scanning time has to be shortened and the signal-to-noise ratio (SNR) of the raw tested signal is reduced. In the simulation and experiment, the de-noising result obtained by the proposed algorithm was better than the traditional Savitzky-Golay (S-G) filter and the fixed-threshold wavelet de-noising algorithm.
A new algorithm for generating highly accurate benchmark solutions to transport test problems
Azmy, Y.Y.
1997-06-01
We present a new algorithm for solving the neutron transport equation in its discrete-variable form. The new algorithm is based on computing the full matrix relating the scalar flux spatial moments in all cells to the fixed neutron source spatial moments, foregoing the need to compute the angular flux spatial moments, and thereby eliminating the need for sweeping the spatial mesh in each discrete-angular direction. The matrix equation is solved exactly in test cases, producing a solution vector that is free from iteration convergence error, and subject only to truncation and roundoff errors. Our algorithm is designed to provide method developers with a quick and simple solution scheme to test their new methods on difficult test problems without the need to develop sophisticated solution techniques, e.g. acceleration, before establishing the worthiness of their innovation. We demonstrate the utility of the new algorithm by applying it to the Arbitrarily High Order Transport Nodal (AHOT-N) method, and using it to solve two of Burre`s Suite of Test Problems (BSTP). Our results provide highly accurate benchmark solutions, that can be distributed electronically and used to verify the pointwise accuracy of other solution methods and algorithms.
Design optimization of a high specific speed Francis turbine runner
NASA Astrophysics Data System (ADS)
Enomoto, Y.; Kurosawa, S.; Kawajiri, H.
2012-11-01
Francis turbine is used in many hydroelectric power stations. This paper presents the development of hydraulic performance in a high specific speed Francis turbine runner. In order to achieve the improvements of turbine efficiency throughout a wide operating range, a new runner design method which combines the latest Computational Fluid Dynamics (CFD) and a multi objective optimization method with an existing design system was applied in this study. The validity of the new design system was evaluated by model performance tests. As the results, it was confirmed that the optimized runner presented higher efficiency compared with an originally designed runner. Besides optimization of runner, instability vibration which occurred at high part load operating condition was investigated by model test and gas-liquid two-phase flow analysis. As the results, it was confirmed that the instability vibration was caused by oval cross section whirl which was caused by recirculation flow near runner cone wall.
CONTUR: A FORTRAN ALGORITHM FOR TWO-DIMENSIONAL HIGH-QUALITY CONTOURING
The contouring algorithm described allows one to produce high-quality two-dimensional contour diagrams from values of a dependent variable located on a uniform grid system (i.e., spacing of nodal points in x and y directions is constant). Computer subroutines (supplied) were deve...
MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra
2014-01-01
Todayâ€™s highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda, is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform. PMID:24909410
Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School
ERIC Educational Resources Information Center
Avancena, Aimee Theresa; Nishihara, Akinori
2014-01-01
Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in theâ€¦
High-precision position-specific isotopeâ€‰analysis
Corso, Thomasâ€‰N.; Brenna, J.â€‰Thomas
1997-01-01
Intramolecular carbon isotope distributions reflect details of the origin of organic compounds and may record the status of complex systems, such as environmental or physiological states. A strategy is reported here for high-precision determination of 13C/12C ratios at specific positions in organic compounds separated from complex mixtures. Free radical fragmentation of methyl palmitate, a test compound, is induced by an open tube furnace. Two series of peaks corresponding to bond breaking from each end of the molecule are analyzed by isotope ratio mass spectrometry and yield precisions of SD(Î´-13C) < 0.4â€°. Isotope labeling in the carboxyl, terminal, and methyl positions demonstrates the absence of rearrangement during activation and fragmentation. Negligible isotopic fractionation was observed as degree of fragmentation was adjusted by changing pyrolysis temperature. [1-13C]methyl palmitate with overall Î´-13C = 4.06â€°, yielded values of +457â€° for the carboxyl position, in agreement with expectations from the dilution, and an average of âˆ’27.95â€° for the rest of the molecule, corresponding to âˆ’27.46â€° for the olefin series. These data demonstrate the feasibility of automated high-precision position-specific analysis of carbon for molecules contained in complex mixtures. PMID:11038597
Efficiency Analysis of a High-Specific Impulse Hall Thruster
NASA Technical Reports Server (NTRS)
Jacobson, David (Technical Monitor); Hofer, Richard R.; Gallimore, Alec D.
2004-01-01
Performance and plasma measurements of the high-specific impulse NASA-173Mv2 Hall thruster were analyzed using a phenomenological performance model that accounts for a partially-ionized plasma containing multiply-charged ions. Between discharge voltages of 300 to 900 V, the results showed that although the net decrease of efficiency due to multiply-charged ions was only 1.5 to 3.0 percent, the effects of multiply-charged ions on the ion and electron currents could not be neglected. Between 300 to 900 V, the increase of the discharge current was attributed to the increasing fraction of multiply-charged ions, while the maximum deviation of the electron current from its average value was only +5/-14 percent. These findings revealed how efficient operation at high-specific impulse was enabled through the regulation of the electron current with the applied magnetic field. Between 300 to 900 V, the voltage utilization ranged from 89 to 97 percent, the mass utilization from 86 to 90 percent, and the current utilization from 77 to 81 percent. Therefore, the anode efficiency was largely determined by the current utilization. The electron Hall parameter was nearly constant with voltage, decreasing from an average of 210 at 300 V to an average of 160 between 400 to 900 V. These results confirmed our claim that efficient operation can be achieved only over a limited range of Hall parameters.
NASA Technical Reports Server (NTRS)
Vemaganti, Gururaja R.; Wieting, Allan R.
1990-01-01
A higher-order streamline upwinding Petrov-Galerkin finite element method is employed for high speed viscous flow analysis using structured and unstructured meshes. For a Mach 8.03 shock interference problem, successive mesh adaptation was performed using an adaptive remeshing method. Results from the finite element algorithm compare well with both experimental data and results from an upwind cell-centered method. Finite element results for a Mach 14.1 flow over a 24 degree compression corner compare well with experimental data and two other numerical algorithms for both structured and unstructured meshes.
A quasi-Newton acceleration for high-dimensional optimization algorithms
Alexander, David; Lange, Kenneth
2010-01-01
In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of these algorithms to modern high-dimensional problems in data mining, genomics, and imaging. Unfortunately, most existing acceleration techniques are ill-suited to complicated models involving large numbers of parameters. The squared iterative methods (SQUAREM) recently proposed by Varadhan and Roland constitute one notable exception. This paper presents a new quasi-Newton acceleration scheme that requires only modest increments in computation per iteration and overall storage and rivals or surpasses the performance of SQUAREM on several representative test problems. PMID:21359052
NASA Technical Reports Server (NTRS)
Fatemi, Emad; Jerome, Joseph; Osher, Stanley
1989-01-01
A micron n+ - n - n+ silicon diode is simulated via the hydrodynamic model for carrier transport. The numerical algorithms employed are for the non-steady case, and a limiting process is used to reach steady state. The simulation employs shock capturing algorithms, and indeed shocks, or very rapid transition regimes, are observed in the transient case for the coupled system, consisting of the potential equation and the conservation equations describing charge, momentum, and energy transfer for the electron carriers. These algorithms, termed essentially non-oscillatory, were successfully applied in other contexts to model the flow in gas dynamics, magnetohydrodynamics, and other physical situations involving the conservation laws in fluid mechanics. The method here is first order in time, but the use of small time steps allows for good accuracy. Runge-Kutta methods allow one to achieve higher accuracy in time if desired. The spatial accuracy is of high order in regions of smoothness.
Wang, C L
2016-05-01
Three high-resolution positioning methods based on the FluoroBancroft linear-algebraic method [S. B. Andersson, Opt. Express 16, 18714 (2008)] are proposed for wavelength-shifting fiber (WLSF) neutron detectors. Using a Gaussian or exponential-decay light-response function, the non-linear relation of photon-number profiles vs. x-pixels was linearized and neutron positions were determined. After taking the super-Poissonian photon noise into account, the proposed algorithms give an average of 0.03-0.08 pixel position error much smaller than that (0.29 pixel) from a traditional maximum photon algorithm (MPA). The new algorithms result in better detector uniformity, less position misassignment (ghosting), better spatial resolution, and an equivalent or better instrument resolution in powder diffraction than the MPA. These improvements will facilitate broader applications of WLSF detectors at time-of-flight neutron powder diffraction beamlines, including single-crystal diffraction and texture analysis. PMID:27250410
Wang, C. L.
2016-05-17
On the basis of FluoroBancroft linear-algebraic method [S.B. Andersson, Opt. Exp. 16, 18714 (2008)] three highly-resolved positioning methodswere proposed for wavelength-shifting fiber (WLSF) neutron detectors. Using a Gaussian or exponential-decay light-response function (LRF), the non-linear relation of photon-number profiles vs. x-pixels was linearized and neutron positions were determined. The proposed algorithms give an average 0.03-0.08 pixel position error, much smaller than that (0.29 pixel) from a traditional maximum photon algorithm (MPA). The new algorithms result in better detector uniformity, less position misassignment (ghosting), better spatial resolution, and an equivalent or better instrument resolution in powder diffraction than the MPA. Moreover,moreÂ Â» these characters will facilitate broader applications of WLSF detectors at time-of-flight neutron powder diffraction beamlines, including single-crystal diffraction and texture analysis.Â«Â less
High-accuracy spectral reduction algorithm for the Ã©chelle spectrometer.
Yin, Lu; Bayanheshig; Yang, Jin; Lu, Yuxian; Zhang, Rui; Sun, Ci; Cui, Jicheng
2016-05-01
A spectral reduction algorithm for an Ã©chelle spectrometer with spherical mirrors that builds a one-to-one correspondence between the wavelength and pixel position is proposed. The algorithm accuracy is improved by calculating the offset distance of the principal ray from the center of the image plane in the two-dimensional vertical direction and compensating the spectral line bending from the reflecting prism. The simulation and experimental results verify that the maximum deviation of the entire image plane is less than one pixel. This algorithm ensures that the wavelengths calculated from spectrograms have a high spectral resolution, meaning the precision from the spectral analysis reaches engineering standards of practice. PMID:27140373
A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm
Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah
2015-01-01
A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974
An infrared small target detection algorithm based on high-speed local contrast method
NASA Astrophysics Data System (ADS)
Cui, Zheng; Yang, Jingli; Jiang, Shouda; Li, Junbao
2016-05-01
Small-target detection in infrared imagery with a complex background is always an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate, and speed. However, current algorithms usually improve one or two of the detection capabilities while sacrificing the other. In this letter, an Infrared (IR) small target detection algorithm with two layers inspired by Human Visual System (HVS) is proposed to balance those detection capabilities. The first layer uses high speed simplified local contrast method to select significant information. And the second layer uses machine learning classifier to separate targets from background clutters. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously.
Algorithm of lithography advanced process control system for high-mix low-volume products
NASA Astrophysics Data System (ADS)
Kawamura, Eiichi
2007-03-01
We have proposed a new algorithm of Lithography Advanced Process Control System for high-mix low-volume production. This algorithm works well for 1 st lot of a new device input into the production line, or 1st lot of an existing device to be exposed with a newly introduced exposure tool. The algorithm consists of 1) searching the most suitable trend of other similar devices referring to an attribute table and a look-up table for priority of searching order, and 2) correction of differences between the two devices for deciding optimum exposure conditions. The attribute table categorizes same layers across different devices and similar layers within a device. Look-up table describes the order of searching keys. To attain cost-effective process control system, information useful to compensate referred trend is compiled into the database.
Representation of high frequency Space Shuttle data by ARMA algorithms and random response spectra
NASA Technical Reports Server (NTRS)
Spanos, P. D.; Mushung, L. J.
1990-01-01
High frequency Space Shuttle lift-off data are treated by autoregressive (AR) and autoregressive-moving-average (ARMA) digital algorithms. These algorithms provide useful information on the spectral densities of the data. Further, they yield spectral models which lend themselves to incorporation to the concept of the random response spectrum. This concept yields a reasonably smooth power spectrum for the design of structural and mechanical systems when the available data bank is limited. Due to the non-stationarity of the lift-off event, the pertinent data are split into three slices. Each of the slices is associated with a rather distinguishable phase of the lift-off event, where stationarity can be expected. The presented results are rather preliminary in nature; it is aimed to call attention to the availability of the discussed digital algorithms and to the need to augment the Space Shuttle data bank as more flights are completed.
A high fuel consumption efficiency management scheme for PHEVs using an adaptive genetic algorithm.
Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah
2015-01-01
A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974
Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry
Polanski, Andrzej; Marczyk, Michal; Pietrowska, Monika; Widlak, Piotr; Polanska, Joanna
2015-01-01
Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses. In this paper we present an efficient algorithm for Gaussian mixture modeling of proteomic mass spectra of different types (e.g., MALDI-ToF profiling, MALDI-IMS). The main idea is automated partitioning of protein mass spectral signal into fragments. The obtained fragments are separately decomposed into Gaussian mixture models. The parameters of the mixture models of fragments are then aggregated to form the mixture model of the whole spectrum. We compare the elaborated algorithm to existing algorithms for peak detection and we demonstrate improvements of peak detection efficiency obtained by using Gaussian mixture modeling. We also show applications of the elaborated algorithm to real proteomic datasets of low and high resolution. PMID:26230717
A high throughput architecture for a low complexity soft-output demapping algorithm
NASA Astrophysics Data System (ADS)
Ali, I.; WasenmÃ¼ller, U.; Wehn, N.
2015-11-01
Iterative channel decoders such as Turbo-Code and LDPC decoders show exceptional performance and therefore they are a part of many wireless communication receivers nowadays. These decoders require a soft input, i.e., the logarithmic likelihood ratio (LLR) of the received bits with a typical quantization of 4 to 6 bits. For computing the LLR values from a received complex symbol, a soft demapper is employed in the receiver. The implementation cost of traditional soft-output demapping methods is relatively large in high order modulation systems, and therefore low complexity demapping algorithms are indispensable in low power receivers. In the presence of multiple wireless communication standards where each standard defines multiple modulation schemes, there is a need to have an efficient demapper architecture covering all the flexibility requirements of these standards. Another challenge associated with hardware implementation of the demapper is to achieve a very high throughput in double iterative systems, for instance, MIMO and Code-Aided Synchronization. In this paper, we present a comprehensive communication and hardware performance evaluation of low complexity soft-output demapping algorithms to select the best algorithm for implementation. The main goal of this work is to design a high throughput, flexible, and area efficient architecture. We describe architectures to execute the investigated algorithms. We implement these architectures on a FPGA device to evaluate their hardware performance. The work has resulted in a hardware architecture based on the figured out best low complexity algorithm delivering a high throughput of 166 Msymbols/second for Gray mapped 16-QAM modulation on Virtex-5. This efficient architecture occupies only 127 slice registers, 248 slice LUTs and 2 DSP48Es.
A Very-High-Specific-Impulse Relativistic Laser Thruster
Horisawa, Hideyuki; Kimura, Itsuro
2008-04-28
Characteristics of compact laser plasma accelerators utilizing high-power laser and thin-target interaction were reviewed as a potential candidate of future spacecraft thrusters capable of generating relativistic plasma beams for interstellar missions. Based on the special theory of relativity, motion of the relativistic plasma beam exhausted from the thruster was formulated. Relationships of thrust, specific impulse, input power and momentum coupling coefficient for the relativistic plasma thruster were derived. It was shown that under relativistic conditions, the thrust could be extremely large even with a small amount of propellant flow rate. Moreover, it was shown that for a given value of input power thrust tended to approach the value of the photon rocket under the relativistic conditions regardless of the propellant flow rate.
High Specificity in CheR Methyltransferase Function
GarcÃa-Fontana, Cristina; Reyes-Darias, JosÃ© Antonio; MuÃ±oz-MartÃnez, Francisco; Alfonso, Carlos; Morel, Bertrand; Ramos, Juan Luis; Krell, Tino
2013-01-01
Chemosensory pathways are a major signal transduction mechanism in bacteria. CheR methyltransferases catalyze the methylation of the cytosolic signaling domain of chemoreceptors and are among the core proteins of chemosensory cascades. These enzymes have primarily been studied Escherichia coli and Salmonella typhimurium, which possess a single CheR involved in chemotaxis. Many other bacteria possess multiple cheR genes. Because the sequences of chemoreceptor signaling domains are highly conserved, it remains to be established with what degree of specificity CheR paralogues exert their activity. We report here a comparative analysis of the three CheR paralogues of Pseudomonas putida. Isothermal titration calorimetry studies show that these paralogues bind the product of the methylation reaction, S-adenosylhomocysteine, with much higher affinity (KD of 0.14â€“2.2 Î¼m) than the substrate S-adenosylmethionine (KD of 22â€“43 Î¼m), which indicates product feedback inhibition. Product binding was particularly tight for CheR2. Analytical ultracentrifugation experiments demonstrate that CheR2 is monomeric in the absence and presence of S-adenosylmethionine or S-adenosylhomocysteine. Methylation assays show that CheR2, but not the other paralogues, methylates the McpS and McpT chemotaxis receptors. The mutant in CheR2 was deficient in chemotaxis, whereas mutation of CheR1 and CheR3 had either no or little effect on chemotaxis. In contrast, biofilm formation of the CheR1 mutant was largely impaired but not affected in the other mutants. We conclude that CheR2 forms part of a chemotaxis pathway, and CheR1 forms part of a chemosensory route that controls biofilm formation. Data suggest that CheR methyltransferases act with high specificity on their cognate chemoreceptors. PMID:23677992
Tighe, Patrick J.; Harle, Christopher A.; Hurley, Robert W.; Aytug, Haldun; Boezaart, Andre P.; Fillingim, Roger B.
2015-01-01
Background Given their ability to process highly dimensional datasets with hundreds of variables, machine learning algorithms may offer one solution to the vexing challenge of predicting postoperative pain. Methods Here, we report on the application of machine learning algorithms to predict postoperative pain outcomes in a retrospective cohort of 8071 surgical patients using 796 clinical variables. Five algorithms were compared in terms of their ability to forecast moderate to severe postoperative pain: Least Absolute Shrinkage and Selection Operator (LASSO), gradient-boosted decision tree, support vector machine, neural network, and k-nearest neighbor, with logistic regression included for baseline comparison. Results In forecasting moderate to severe postoperative pain for postoperative day (POD) 1, the LASSO algorithm, using all 796 variables, had the highest accuracy with an area under the receiver-operating curve (ROC) of 0.704. Next, the gradient-boosted decision tree had an ROC of 0.665 and the k-nearest neighbor algorithm had an ROC of 0.643. For POD 3, the LASSO algorithm, using all variables, again had the highest accuracy, with an ROC of 0.727. Logistic regression had a lower ROC of 0.5 for predicting pain outcomes on POD 1 and 3. Conclusions Machine learning algorithms, when combined with complex and heterogeneous data from electronic medical record systems, can forecast acute postoperative pain outcomes with accuracies similar to methods that rely only on variables specifically collected for pain outcome prediction. PMID:26031220
Postley, John E; Luo, Yanting; Wong, Nathan D; Gardin, Julius M
2015-11-15
Atherosclerotic cardiovascular disease (ASCVD) events are the leading cause of death in the United States and globally. Traditional global risk algorithms may miss 50% of patients who experience ASCVD events. Noninvasive ultrasound evaluation of the carotid and femoral arteries can identify subjects at high risk for ASCVD events. We examined the ability of different global risk algorithms to identify subjects with femoral and/or carotid plaques found by ultrasound. The study population consisted of 1,464 asymptomatic adults (39.8% women) aged 23 to 87 years without previous evidence of ASCVD who had ultrasound evaluation of the carotid and femoral arteries. Three ASCVD risk algorithms (10-year Framingham Risk Score [FRS], 30-year FRS, and lifetime risk) were compared for the 939 subjects who met the algorithm age criteria. The frequency of femoral plaque as the only plaque was 18.3% in the total group and 14.8% in the risk algorithm groups (n = 939) without a significant difference between genders in frequency of femoral plaque as the only plaque. Those identified as high risk by the lifetime risk algorithm included the most men and women who had plaques either femoral or carotid (59% and 55%) but had lower specificity because the proportion of subjects who actually had plaques in the high-risk group was lower (50% and 35%) than in those at high risk defined by the FRS algorithms. In conclusion, ultrasound evaluation of the carotid and femoral arteries can identify subjects at risk of ASCVD events missed by traditional risk-predicting algorithms. The large proportion of subjects with femoral plaque only supports the use of including both femoral and carotid arteries in ultrasound evaluation. PMID:26434511
High-resolution climate data over conterminous US using random forest algorithm
NASA Astrophysics Data System (ADS)
Hashimoto, H.; Nemani, R. R.; Wang, W.
2014-12-01
We developed a new methodology to create high-resolution precipitation data using the random forest algorithm. We have used two approaches: physical downscaling from GCM data using a regional climate model, and interpolation from ground observation data. Physical downscaling method can be applied only for a small region because it is computationally expensive and complex to deploy. On the other hand, interpolation schemes from ground observations do not consider physical processes. In this study, we utilized the random forest algorithm to integrate atmospheric reanalysis data, satellite data, topography data, and ground observation data. First we considered situations where precipitation is same across the domain, largely dominated by storm like systems. We then picked several points to train random forest algorithm. The random forest algorithm estimates out-of-bag errors spatially, and produces the relative importance of each of the input variable.This methodology has the following advantages. (1) The methodology can ingest any spatial dataset to improve downscaling. Even non-precipitation datasets can be ingested such as satellite cloud cover data, radar reflectivity image, or modeled convective available potential energy. (2) The methodology is purely statistical so that physical assumptions are not required. Meanwhile, most of interpolation schemes assume empirical relationship between precipitation and elevation for orographic precipitation. (3) Low quality value in ingested data does not cause critical bias in the results because of the ensemble feature of random forest. Therefore, users do not need to pay a special attention to quality control of input data compared to other interpolation methodologies. (4) Same methodology can be applied to produce other high-resolution climate datasets, such as wind and cloud cover. Those variables are usually hard to be interpolated by conventional algorithms. In conclusion, the proposed methodology can produce reasonable
Neugebauer, Romain; Schmittdiel, Julie A; Zhu, Zheng; Rassen, Jeremy A; Seeger, John D; Schneeweiss, Sebastian
2015-02-28
The high-dimensional propensity score (hdPS) algorithm was proposed for automation of confounding adjustment in problems involving large healthcare databases. It has been evaluated in comparative effectiveness research (CER) with point treatments to handle baseline confounding through matching or covariance adjustment on the hdPS. In observational studies with time-varying interventions, such hdPS approaches are often inadequate to handle time-dependent confounding and selection bias. Inverse probability weighting (IPW) estimation to fit marginal structural models can adequately handle these biases under the fundamental assumption of no unmeasured confounders. Upholding of this assumption relies on the selection of an adequate set of covariates for bias adjustment. We describe the application and performance of the hdPS algorithm to improve covariate selection in CER with time-varying interventions based on IPW estimation and explore stabilization of the resulting estimates using Super Learning. The evaluation is based on both the analysis of electronic health records data in a real-world CER study of adults with type 2 diabetes and a simulation study. This report (i) establishes the feasibility of IPW estimation with the hdPS algorithm based on large electronic health records databases, (ii) demonstrates little impact on inferences when supplementing the set of expert-selected covariates using the hdPS algorithm in a setting with extensive background knowledge, (iii) supports the application of the hdPS algorithm in discovery settings with little background knowledge or limited data availability, and (iv) motivates the application of Super Learning to stabilize effect estimates based on the hdPS algorithm. PMID:25488047
Nanoporous ultra-high specific surface inorganic fibres
NASA Astrophysics Data System (ADS)
Kanehata, Masaki; Ding, Bin; Shiratori, Seimei
2007-08-01
Nanoporous inorganic (silica) nanofibres with ultra-high specific surface have been fabricated by electrospinning the blend solutions of poly(vinyl alcohol) (PVA) and colloidal silica nanoparticles, followed by selective removal of the PVA component. The configurations of the composite and inorganic nanofibres were investigated by changing the average silica particle diameters and the concentrations of colloidal silica particles in polymer solutions. After the removal of PVA by calcination, the fibre shape of pure silica particle assembly was maintained. The nanoporous silica fibres were assembled as a porous membrane with a high surface roughness. From the results of Brunauer-Emmett-Teller (BET) measurements, the BET surface area of inorganic silica nanofibrous membranes was increased with the decrease of the particle diameters. The membrane composed of silica particles with diameters of 15 nm showed the largest BET surface area of 270.3 m2 g-1 and total pore volume of 0.66 cm3 g-1. The physical absorption of methylene blue dye molecules by nanoporous silica membranes was examined using UV-vis spectrometry. Additionally, the porous silica membranes modified with fluoroalkylsilane showed super-hydrophobicity due to their porous structures.
Plasmoid Thruster for High Specific-Impulse Propulsion
NASA Technical Reports Server (NTRS)
Fimognari, Peter; Eskridge, Richard; Martin, Adam; Lee, Michael
2007-01-01
A report discusses a new multi-turn, multi-lead design for the first generation PT-1 (Plasmoid Thruster) that produces thrust by expelling plasmas with embedded magnetic fields (plasmoids) at high velocities. This thruster is completely electrodeless, capable of using in-situ resources, and offers efficiencies as high as 70 percent at a specific impulse, I(sub sp), of up to 8,000 s. This unit consists of drive and bias coils wound around a ceramic form, and the capacitor bank and switches are an integral part of the assembly. Multiple thrusters may be gauged to inductively recapture unused energy to boost efficiency and to increase the repetition rate, which, in turn increases the average thrust of the system. The thruster assembly can use storable propellants such as H2O, ammonia, and NO, among others. Any available propellant gases can be used to produce an I(sub sp) in the range of 2,000 to 8,000 s with a single-stage thruster. These capabilities will allow the transport of greater payloads to outer planets, especially in the case of an I(sub sp) greater than 6,000 s.
NASA Astrophysics Data System (ADS)
Li, Weixuan; Lin, Guang; Li, Bing
2016-09-01
Many uncertainty quantification (UQ) approaches suffer from the curse of dimensionality, that is, their computational costs become intractable for problems involving a large number of uncertainty parameters. In these situations, the classic Monte Carlo often remains the preferred method of choice because its convergence rate O (n - 1 / 2), where n is the required number of model simulations, does not depend on the dimension of the problem. However, many high-dimensional UQ problems are intrinsically low-dimensional, because the variation of the quantity of interest (QoI) is often caused by only a few latent parameters varying within a low-dimensional subspace, known as the sufficient dimension reduction (SDR) subspace in the statistics literature. Motivated by this observation, we propose two inverse regression-based UQ algorithms (IRUQ) for high-dimensional problems. Both algorithms use inverse regression to convert the original high-dimensional problem to a low-dimensional one, which is then efficiently solved by building a response surface for the reduced model, for example via the polynomial chaos expansion. The first algorithm, which is for the situations where an exact SDR subspace exists, is proved to converge at rate O (n-1), hence much faster than MC. The second algorithm, which doesn't require an exact SDR, employs the reduced model as a control variate to reduce the error of the MC estimate. The accuracy gain could still be significant, depending on how well the reduced model approximates the original high-dimensional one. IRUQ also provides several additional practical advantages: it is non-intrusive; it does not require computing the high-dimensional gradient of the QoI; and it reports an error bar so the user knows how reliable the result is.
Structure of a highly NADP+-specific isocitrate dehydrogenase.
Sidhu, Navdeep S; Delbaere, Louis T J; Sheldrick, George M
2011-10-01
Isocitrate dehydrogenase catalyzes the first oxidative and decarboxylation steps in the citric acid cycle. It also lies at a crucial bifurcation point between CO2-generating steps in the cycle and carbon-conserving steps in the glyoxylate bypass. Hence, the enzyme is a focus of regulation. The bacterial enzyme is typically dependent on the coenzyme nicotinamide adenine dinucleotide phosphate. The monomeric enzyme from Corynebacterium glutamicum is highly specific towards this coenzyme and the substrate isocitrate while retaining a high overall efficiency. Here, a 1.9â€…Ã… resolution crystal structure of the enzyme in complex with its coenzyme and the cofactor Mg2+ is reported. Coenzyme specificity is mediated by interactions with the negatively charged 2'-phosphate group, which is surrounded by the side chains of two arginines, one histidine and, via a water, one lysine residue, forming ion pairs and hydrogen bonds. Comparison with a previous apoenzyme structure indicates that the binding site is essentially preconfigured for coenzyme binding. In a second enzyme molecule in the asymmetric unit negatively charged aspartate and glutamate residues from a symmetry-related enzyme molecule interact with the positively charged arginines, abolishing coenzyme binding. The holoenzyme from C. glutamicum displays a 36Â° interdomain hinge-opening movement relative to the only previous holoenzyme structure of the monomeric enzyme: that from Azotobacter vinelandii. As a result, the active site is not blocked by the bound coenzyme as in the closed conformation of the latter, but is accessible to the substrate isocitrate. However, the substrate-binding site is disrupted in the open conformation. Hinge points could be pinpointed for the two molecules in the same crystal, which show a 13Â° hinge-bending movement relative to each other. One of the two pairs of hinge residues is intimately flanked on both sides by the isocitrate-binding site. This suggests that binding of a relatively
Closed loop, DM diversity-based, wavefront correction algorithm for high contrast imaging systems.
Give'on, Amir; Belikov, Ruslan; Shaklan, Stuart; Kasdin, Jeremy
2007-09-17
High contrast imaging from space relies on coronagraphs to limit diffraction and a wavefront control systems to compensate for imperfections in both the telescope optics and the coronagraph. The extreme contrast required (up to 10(-10) for terrestrial planets) puts severe requirements on the wavefront control system, as the achievable contrast is limited by the quality of the wavefront. This paper presents a general closed loop correction algorithm for high contrast imaging coronagraphs by minimizing the energy in a predefined region in the image where terrestrial planets could be found. The estimation part of the algorithm reconstructs the complex field in the image plane using phase diversity caused by the deformable mirror. This method has been shown to achieve faster and better correction than classical speckle nulling. PMID:19547602
A Jitter-Mitigating High Gain Antenna Pointing Algorithm for the Solar Dynamics Observatory
NASA Technical Reports Server (NTRS)
Bourkland, Kristin L.; Liu, Kuo-Chia; Blaurock, Carl
2007-01-01
This paper details a High Gain Antenna (HGA) pointing algorithm which mitigates jitter during the motion of the antennas on the Solar Dynamics Observatory (SDO) spacecraft. SDO has two HGAs which point towards the Earth and send data to a ground station at a high rate. These antennas are required to track the ground station during the spacecraft Inertial and Science modes, which include periods of inertial Sunpointing as well as calibration slews. The HGAs also experience handoff seasons, where the antennas trade off between pointing at the ground station and pointing away from the Earth. The science instruments on SDO require fine Sun pointing and have a very low jitter tolerance. Analysis showed that the nominal tracking and slewing motions of the antennas cause enough jitter to exceed the HGA portion of the jitter budget. The HGA pointing control algorithm was expanded from its original form as a means to mitigate the jitter.
Supercomputer implementation of finite element algorithms for high speed compressible flows
NASA Technical Reports Server (NTRS)
Thornton, E. A.; Ramakrishnan, R.
1986-01-01
Prediction of compressible flow phenomena using the finite element method is of recent origin and considerable interest. Two shock capturing finite element formulations for high speed compressible flows are described. A Taylor-Galerkin formulation uses a Taylor series expansion in time coupled with a Galerkin weighted residual statement. The Taylor-Galerkin algorithms use explicit artificial dissipation, and the performance of three dissipation models are compared. A Petrov-Galerkin algorithm has as its basis the concepts of streamline upwinding. Vectorization strategies are developed to implement the finite element formulations on the NASA Langley VPS-32. The vectorization scheme results in finite element programs that use vectors of length of the order of the number of nodes or elements. The use of the vectorization procedure speeds up processing rates by over two orders of magnitude. The Taylor-Galerkin and Petrov-Galerkin algorithms are evaluated for 2D inviscid flows on criteria such as solution accuracy, shock resolution, computational speed and storage requirements. The convergence rates for both algorithms are enhanced by local time-stepping schemes. Extension of the vectorization procedure for predicting 2D viscous and 3D inviscid flows are demonstrated. Conclusions are drawn regarding the applicability of the finite element procedures for realistic problems that require hundreds of thousands of nodes.
Algorithm for Automatic Behavior Quantification of Laboratory Mice Using High-Frame-Rate Videos
NASA Astrophysics Data System (ADS)
Nie, Yuman; Takaki, Takeshi; Ishii, Idaku; Matsuda, Hiroshi
In this paper, we propose an algorithm for automatic behavior quantification in laboratory mice to quantify several model behaviors. The algorithm can detect repetitive motions of the fore- or hind-limbs at several or dozens of hertz, which are too rapid for the naked eye, from high-frame-rate video images. Multiple repetitive motions can always be identified from periodic frame-differential image features in four segmented regions â€” the head, left side, right side, and tail. Even when a mouse changes its posture and orientation relative to the camera, these features can still be extracted from the shift- and orientation-invariant shape of the mouse silhouette by using the polar coordinate system and adjusting the angle coordinate according to the head and tail positions. The effectiveness of the algorithm is evaluated by analyzing long-term 240-fps videos of four laboratory mice for six typical model behaviors: moving, rearing, immobility, head grooming, left-side scratching, and right-side scratching. The time durations for the model behaviors determined by the algorithm have detection/correction ratios greater than 80% for all the model behaviors. This shows good quantification results for actual animal testing.
NASA Astrophysics Data System (ADS)
Carlsson Tedgren, Ã…sa; Alm Carlsson, Gudrun
2013-04-01
Model-based dose calculation algorithms (MBDCAs), recently introduced in treatment planning systems (TPS) for brachytherapy, calculate tissue absorbed doses. In the TPS framework, doses have hereto been reported as dose to water and water may still be preferred as a dose specification medium. Dose to tissue medium Dmed then needs to be converted into dose to water in tissue Dw,med. Methods to calculate absorbed dose to differently sized water compartments/cavities inside tissue, infinitesimal (used for definition of absorbed dose), small, large or intermediate, are reviewed. Burlin theory is applied to estimate photon energies at which cavity sizes in the range 1 nm-10 mm can be considered small or large. Photon and electron energy spectra are calculated at 1 cm distance from the central axis in cylindrical phantoms of bone, muscle and adipose tissue for 20, 50, 300 keV photons and photons from 125I, 169Yb and 192Ir sources; ratios of mass-collision-stopping powers and mass energy absorption coefficients are calculated as applicable to convert Dmed into Dw,med for small and large cavities. Results show that 1-10 nm sized cavities are small at all investigated photon energies; 100 Âµm cavities are large only at photon energies <20 keV. A choice of an appropriate conversion coefficient Dw, med/Dmed is discussed in terms of the cavity size in relation to the size of important cellular targets. Free radicals from DNA bound water of nanometre dimensions contribute to DNA damage and cell killing and may be the most important water compartment in cells implying use of ratios of mass-collision-stopping powers for converting Dmed into Dw,med.
Parallel technology for numerical modeling of fluid dynamics problems by high-accuracy algorithms
NASA Astrophysics Data System (ADS)
Gorobets, A. V.
2015-04-01
A parallel computation technology for modeling fluid dynamics problems by finite-volume and finite-difference methods of high accuracy is presented. The development of an algorithm, the design of a software implementation, and the creation of parallel programs for computations on large-scale computing systems are considered. The presented parallel technology is based on a multilevel parallel model combining various types of parallelism: with shared and distributed memory and with multiple and single instruction streams to multiple data flows.
NASA Astrophysics Data System (ADS)
Schwenk, Kurt; Huber, Felix
2015-10-01
Connected Component Labeling (CCL) is a basic algorithm in image processing and an essential step in nearly every application dealing with object detection. It groups together pixels belonging to the same connected component (e.g. object). Special architectures such as ASICs, FPGAs and GPUs were utilised for achieving high data throughput, primarily for video processing. In this article, the FPGA implementation of a CCL method is presented, which was specially designed to process high resolution images with complex structure at high speed, generating a label mask. In general, CCL is a dynamic task and therefore not well suited for parallelisation, which is needed to achieve high processing speed with an FPGA. Facing this issue, most of the FPGA CCL implementations are restricted to low or medium resolution images (â‰¤ 2048 âˆ— 2048 pixels) with lower complexity, where the fastest implementations do not create a label mask. Instead, they extract object features like size and position directly, which can be realized with high performance and perfectly suits the need for many video applications. Since these restrictions are incompatible with the requirements to label high resolution images with highly complex structures and the need for generating a label mask, a new approach was required. The CCL method presented in this work is based on a two-pass CCL algorithm, which was modified with respect to low memory consumption and suitability for an FPGA implementation. Nevertheless, since not all parts of CCL can be parallelised, a stop-and-go high-performance pipeline processing CCL module was designed. The algorithm, the performance and the hardware requirements of a prototype implementation are presented. Furthermore, a clock-accurate runtime analysis is shown, which illustrates the dependency between processing speed and image complexity in detail. Finally, the performance of the FPGA implementation is compared with that of a software implementation on modern embedded
Streptococcal C5a peptidase is a highly specific endopeptidase.
Cleary, P P; Prahbu, U; Dale, J B; Wexler, D E; Handley, J
1992-01-01
Compositional analysis of streptococcal C5a peptidase (SCPA) cleavage products from a synthetic peptide corresponding to the 20 C-terminal residues of C5a demonstrated that the target cleavage site is His-Lys rather than Lys-Asp, as previously suggested. A C5a peptide analog with Lys replaced by Gln was also subject to cleavage by SCPA. This confirmed that His-Lys rather than Lys-Asp is the scissile bond. Cleavage at histidine is unusual but is the same as that suggested for a peptidase produced by group B streptococci. Native C5 protein was also resistant to SCPA, suggesting that the His-Lys bond is inaccessible prior to proteolytic cleavage by C5 convertase. These experiments showed that the streptococcal C5a peptidase is highly specific for C5a and suggest that its function is not merely to process protein for metabolic consumption but to act primarily to eliminate this chemotactic signal from inflammatory foci. Images PMID:1452354
Figuring algorithm for high-gradient mirrors with axis-symmetrical removal function.
Jiao, Changjun; Li, Shengyi; Xie, Xuhui; Chen, Shanyong; Wu, Dongliang; Kang, Nianhui
2010-02-01
Figuring technologies based on intracone and intercone stitching for high-gradient mirrors are discussed. Based on the conventional computer-controlled optics shaping principle, a process model for a single cone with intracone stitching is constructed. With the circular stitching property of the model, a modified Bayesian-based Richardson-Lucy (RL) algorithm is deduced to deconvolute dwell time for single cone. Building on this algorithm, with the introduction of intercone stitching, a process model for a complex cone is built. Then another modified Bayesian-based RL algorithm is deduced to deconvolute the dwell time for a complex cone from the properties of intracone stitching and intercone stitching. With a velocity realization method for dwell time on a spiral path of the cone and the determination criterion of the path parameter, figuring technologies for single and complex cones are presented. Simulation and experiment demonstrate that theories and methods discussed can solve key problems of figuring high-gradient mirrors; the figuring technologies are novel methods for high-gradient mirrors and can be used to figure mirrors finely. PMID:20119004
Vibration extraction based on fast NCC algorithm and high-speed camera.
Lei, Xiujun; Jin, Yi; Guo, Jie; Zhu, Chang'an
2015-09-20
In this study, a high-speed camera system is developed to complete the vibration measurement in real time and to overcome the mass introduced by conventional contact measurements. The proposed system consists of a notebook computer and a high-speed camera which can capture the images as many as 1000 frames per second. In order to process the captured images in the computer, the normalized cross-correlation (NCC) template tracking algorithm with subpixel accuracy is introduced. Additionally, a modified local search algorithm based on the NCC is proposed to reduce the computation time and to increase efficiency significantly. The modified algorithm can rapidly accomplish one displacement extraction 10 times faster than the traditional template matching without installing any target panel onto the structures. Two experiments were carried out under laboratory and outdoor conditions to validate the accuracy and efficiency of the system performance in practice. The results demonstrated the high accuracy and efficiency of the camera system in extracting vibrating signals. PMID:26406525
MTRC compensation in high-resolution ISAR imaging via improved polar format algorithm
NASA Astrophysics Data System (ADS)
Liu, Yang; Li, Hao; Li, Na; Xu, Shiyou; Chen, Zengping
2014-10-01
Migration through resolution cells (MTRC) is generated in high-resolution inverse synthetic aperture radar (ISAR) imaging. A MTRC compensation algorithm for high-resolution ISAR imaging based on improved polar format algorithm (PFA) is proposed in this paper. Firstly, in the situation that a rigid-body target stably flies, the initial value of the rotation angle and center of the target is obtained from the rotation of radar line of sight (RLOS) and high range resolution profile (HRRP). Then, the PFA is iteratively applied to the echo data to search the optimization solution based on minimum entropy criterion. The procedure starts with the estimated initial rotation angle and center, and terminated when the entropy of the compensated ISAR image is minimized. To reduce the computational load, the 2-D iterative search is divided into two 1-D search. One is carried along the rotation angle and the other one is carried along rotation center. Each of the 1-D searches is realized by using of the golden section search method. The accurate rotation angle and center can be obtained when the iterative search terminates. Finally, apply the PFA to compensate the MTRC by the use of the obtained optimized rotation angle and center. After MTRC compensation, the ISAR image can be best focused. Simulated and real data demonstrate the effectiveness and robustness of the proposed algorithm.
High voltage and high specific capacity dual intercalating electrode Li-ion batteries
NASA Technical Reports Server (NTRS)
West, William C. (Inventor); Blanco, Mario (Inventor)
2010-01-01
The present invention provides high capacity and high voltage Li-ion batteries that have a carbonaceous cathode and a nonaqueous electrolyte solution comprising LiF salt and an anion receptor that binds the fluoride ion. The batteries can comprise dual intercalating electrode Li ion batteries. Methods of the present invention use a cathode and electrode pair, wherein each of the electrodes reversibly intercalate ions provided by a LiF salt to make a high voltage and high specific capacity dual intercalating electrode Li-ion battery. The present methods and systems provide high-capacity batteries particularly useful in powering devices where minimizing battery mass is important.
A high order accurate finite element algorithm for high Reynolds number flow prediction
NASA Technical Reports Server (NTRS)
Baker, A. J.
1978-01-01
A Galerkin-weighted residuals formulation is employed to establish an implicit finite element solution algorithm for generally nonlinear initial-boundary value problems. Solution accuracy, and convergence rate with discretization refinement, are quantized in several error norms, by a systematic study of numerical solutions to several nonlinear parabolic and a hyperbolic partial differential equation characteristic of the equations governing fluid flows. Solutions are generated using selective linear, quadratic and cubic basis functions. Richardson extrapolation is employed to generate a higher-order accurate solution to facilitate isolation of truncation error in all norms. Extension of the mathematical theory underlying accuracy and convergence concepts for linear elliptic equations is predicted for equations characteristic of laminar and turbulent fluid flows at nonmodest Reynolds number. The nondiagonal initial-value matrix structure introduced by the finite element theory is determined intrinsic to improved solution accuracy and convergence. A factored Jacobian iteration algorithm is derived and evaluated to yield a consequential reduction in both computer storage and execution CPU requirements while retaining solution accuracy.
Genetic algorithm based system for patient scheduling in highly constrained situations.
Podgorelec, V; Kokol, P
1997-12-01
In medicine and health care there are a lot of situations when patients have to be scheduled on different devices and/or with different physicians or therapists. It may concern preventive examinations, laboratory tests or convalescent therapies, therefore we are always looking for an optimal schedule that would result in finishing all the activities scheduled as soon as possible, with the least patient waiting time and maximum device utilization. Since patient scheduling is a highly complex problem, it is impossible to make a qualitative schedule by hand or even with exact heuristic methods. Therefore we developed a powerful automated scheduling method for highly constrained situations based on genetic algorithms and machine learning. In this paper we present the method, together with the whole process of schedule generation, the important parameters to direct the evolution and how the algorithm is guaranteed to produce only feasible solutions, not breaking any of the required constraints. We applied the described method to a problem of scheduling patients with different therapy needs to a limited number of therapeutic devices, but the algorithm can be easily modified for use in similar situations. The results are quite encouraging and since all the solutions are feasible, the method can be easily incorporated into an interactive user interface, which can be of major importance when scheduling patients, and human resources in general, is considered. PMID:9555628
NASA Astrophysics Data System (ADS)
Zhang, XiaoLi; Liang, DaKai; Zeng, Jie; Asundi, Anand
2012-02-01
Structural Health Monitoring (SHM) based on fiber Bragg grating (FBG) sensor network has attracted considerable attention in recent years. However, FBG sensor network is embedded or glued in the structure simply with series or parallel. In this case, if optic fiber sensors or fiber nodes fail, the fiber sensors cannot be sensed behind the failure point. Therefore, for improving the survivability of the FBG-based sensor system in the SHM, it is necessary to build high reliability FBG sensor network for the SHM engineering application. In this study, a model reconstruction soft computing recognition algorithm based on genetic algorithm-support vector regression (GA-SVR) is proposed to achieve the reliability of the FBG-based sensor system. Furthermore, an 8-point FBG sensor system is experimented in an aircraft wing box. The external loading damage position prediction is an important subject for SHM system; as an example, different failure modes are selected to demonstrate the SHM system's survivability of the FBG-based sensor network. Simultaneously, the results are compared with the non-reconstruct model based on GA-SVR in each failure mode. Results show that the proposed model reconstruction algorithm based on GA-SVR can still keep the predicting precision when partial sensors failure in the SHM system; thus a highly reliable sensor network for the SHM system is facilitated without introducing extra component and noise.
A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train
Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen
2012-01-01
High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582
A high precision position sensor design and its signal processing algorithm for a maglev train.
Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen
2012-01-01
High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582
NASA Astrophysics Data System (ADS)
Hoffmann, Mathias; Schulz-Hanke, Maximilian; Garcia Alba, Joana; Jurisch, Nicole; Hagemann, Ulrike; Sachs, Torsten; Sommer, Michael; Augustin, JÃ¼rgen
2016-04-01
Processes driving methane (CH4) emissions in wetland ecosystems are highly complex. Especially, the separation of CH4 emissions into ebullition and diffusion derived flux components, a perquisite for the mechanistic process understanding and identification of potential environmental driver is rather challenging. We present a simple calculation algorithm, based on an adaptive R-script, which separates open-water, closed chamber CH4 flux measurements into diffusion- and ebullition-derived components. Hence, flux component specific dynamics are revealed and potential environmental driver identified. Flux separation is based on a statistical approach, using ebullition related sudden concentration changes obtained during high resolution CH4 concentration measurements. By applying the lower and upper quartile Â± the interquartile range (IQR) as a variable threshold, diffusion dominated periods of the flux measurement are filtered. Subsequently, flux calculation and separation is performed. The algorithm was verified in a laboratory experiment and tested under field conditions, using flux measurement data (July to September 2013) from a flooded, former fen grassland site. Erratic ebullition events contributed 46% to total CH4 emissions, which is comparable to values reported by literature. Additionally, a shift in the diurnal trend of diffusive fluxes throughout the measurement period, driven by the water temperature gradient, was revealed.
Trajectory Specification for High-Capacity Air Traffic Control
NASA Technical Reports Server (NTRS)
Paielli, Russell A.
2004-01-01
In the current air traffic management system, the fundamental limitation on airspace capacity is the cognitive ability of human air traffic controllers to maintain safe separation with high reliability. The doubling or tripling of airspace capacity that will be needed over the next couple of decades will require that tactical separation be at least partially automated. Standardized conflict-free four-dimensional trajectory assignment will be needed to accomplish that objective. A trajectory specification format based on the Extensible Markup Language is proposed for that purpose. This format can be used to downlink a trajectory request, which can then be checked on the ground for conflicts and approved or modified, if necessary, then uplinked as the assigned trajectory. The horizontal path is specified as a series of geodetic waypoints connected by great circles, and the great-circle segments are connected by turns of specified radius. Vertical profiles for climb and descent are specified as low-order polynomial functions of along-track position, which is itself specified as a function of time. Flight technical error tolerances in the along-track, cross-track, and vertical axes define a bounding space around the reference trajectory, and conformance will guarantee the required separation for a period of time known as the conflict time horizon. An important safety benefit of this regimen is that the traffic will be able to fly free of conflicts for at least several minutes even if all ground systems and the entire communication infrastructure fail. Periodic updates in the along-track axis will adjust for errors in the predicted along-track winds.
A fast high-order finite difference algorithm for pricing American options
NASA Astrophysics Data System (ADS)
Tangman, D. Y.; Gopaul, A.; Bhuruth, M.
2008-12-01
We describe an improvement of Han and Wu's algorithm [H. Han, X.Wu, A fast numerical method for the Black-Scholes equation of American options, SIAM J. Numer. Anal. 41 (6) (2003) 2081-2095] for American options. A high-order optimal compact scheme is used to discretise the transformed Black-Scholes PDE under a singularity separating framework. A more accurate free boundary location based on the smooth pasting condition and the use of a non-uniform grid with a modified tridiagonal solver lead to an efficient implementation of the free boundary value problem. Extensive numerical experiments show that the new finite difference algorithm converges rapidly and numerical solutions with good accuracy are obtained. Comparisons with some recently proposed methods for the American options problem are carried out to show the advantage of our numerical method.
A high-order statistical tensor based algorithm for anomaly detection in hyperspectral imagery.
Geng, Xiurui; Sun, Kang; Ji, Luyan; Zhao, Yongchao
2014-01-01
Recently, high-order statistics have received more and more interest in the field of hyperspectral anomaly detection. However, most of the existing high-order statistics based anomaly detection methods require stepwise iterations since they are the direct applications of blind source separation. Moreover, these methods usually produce multiple detection maps rather than a single anomaly distribution image. In this study, we exploit the concept of coskewness tensor and propose a new anomaly detection method, which is called COSD (coskewness detector). COSD does not need iteration and can produce single detection map. The experiments based on both simulated and real hyperspectral data sets verify the effectiveness of our algorithm. PMID:25366706
NASA Technical Reports Server (NTRS)
Cross, James H., II; Morrison, Kelly I.; May, Charles H., Jr.; Waddel, Kathryn C.
1989-01-01
The first phase of a three-phase effort to develop a new graphically oriented specification language which will facilitate the reverse engineering of Ada source code into graphical representations (GRs) as well as the automatic generation of Ada source code is described. A simplified view of the three phases of Graphical Representations for Algorithms, Structure, and Processes for Ada (GRASP/Ada) with respect to three basic classes of GRs is presented. Phase 1 concentrated on the derivation of an algorithmic diagram, the control structure diagram (CSD) (CRO88a) from Ada source code or Ada PDL. Phase 2 includes the generation of architectural and system level diagrams such as structure charts and data flow diagrams and should result in a requirements specification for a graphically oriented language able to support automatic code generation. Phase 3 will concentrate on the development of a prototype to demonstrate the feasibility of this new specification language.
High-resolution algorithms for the Navier-Stokes equations for generalized discretizations
NASA Astrophysics Data System (ADS)
Mitchell, Curtis Randall
Accurate finite volume solution algorithms for the two dimensional Navier Stokes equations and the three dimensional Euler equations for both structured and unstructured grid topologies are presented. Results for two dimensional quadrilateral and triangular elements and three dimensional tetrahedral elements will be provided. Fundamental to the solution algorithm is a technique for generating multidimensional polynomials which model the spatial variation of the flow variables. Cell averaged data is used to reconstruct pointwise distributions of the dependent variables. The reconstruction errors are evaluated on triangular meshes. The implementation of the algorithm is unique in that three reconstructions are performed for each cell face in the domain. Two of the reconstructions are used to evaluate the inviscid fluxes and correspond to the right and left interface states needed for the solution of a Riemann problem. The third reconstruction is used to evaluate the viscous fluxes. The gradient terms that appear in the viscous fluxes are formed by simply differentiating the polynomial. By selecting the appropriate cell control volumes, centered, upwind and upwind-biased stencils are possible. Numerical calculations in two dimensions include solutions to elliptic boundary value problems, Ringlebs' flow, an inviscid shock reflection, a flat plate boundary layer, and a shock induced separation over a flat plate. Three dimensional results include the ONERA M6 wing. All of the unstructured grids were generated using an advancing front mesh generation procedure. Modifications to the three dimensional grid generator were necessary to discretize the surface grids for bodies with high curvature. In addition, mesh refinement algorithms were implemented to improve the surface grid integrity. Examples include a Glasair fuselage, High Speed Civil Transport, and the ONERA M6 wing. The role of reconstruction as applied to adaptive remeshing is discussed and a new first order error
Hwang, Hee Sang; Park, Chan-Sik; Yoon, Dok Hyun; Suh, Cheolwon; Huh, Jooryung
2014-08-01
Diffuse large B-cell lymphoma (DLBCL) is classified into prognostically distinct germinal center B-cell (GCB) and activated B-cell subtypes by gene expression profiling (GEP). Recent reports suggest the role of GEP subtypes in targeted therapy. Immunohistochemistry (IHC) algorithms have been proposed as surrogates of GEP, but their utility remains controversial. Using microarray, we examined the concordance of 4 GEP-correlated and 2 non-GEP-correlated IHC algorithms in 381 DLBCLs, not otherwise specified. Subtypes and variants of DLBCL were excluded to minimize the possible confounding effect on prognosis and phenotype. Survival was analyzed in 138 cyclophosphamide, adriamycin, vincristine, and prednisone (CHOP)-treated and 147 rituximab plus CHOP (R-CHOP)-treated patients. Of the GEP-correlated algorithms, high concordance was observed among Hans, Choi, and Visco-Young algorithms (total concordance, 87.1%; Îº score: 0.726 to 0.889), whereas Tally algorithm exhibited slightly lower concordance (total concordance 77.4%; Îº score: 0.502 to 0.643). Two non-GEP-correlated algorithms (Muris and Nyman) exhibited poor concordance. Compared with the Western data, incidence of the non-GCB subtype was higher in all algorithms. Univariate analysis showed prognostic significance for Hans, Choi, and Visco-Young algorithms and BCL6, GCET1, LMO2, and BCL2 in CHOP-treated patients. On multivariate analysis, Hans algorithm retained its prognostic significance. By contrast, neither the algorithms nor individual antigens predicted survival in R-CHOP treatment. The high concordance among GEP-correlated algorithms suggests their usefulness as reliable discriminators of molecular subtype in DLBCL, not otherwise specified. Our study also indicates that prognostic significance of IHC algorithms may be limited in R-CHOP-treated Asian patients because of the predominance of the non-GCB type. PMID:24705314
The performance of flux-split algorithms in high-speed viscous flows
NASA Astrophysics Data System (ADS)
Gaitonde, Datta; Shang, J. S.
1992-01-01
The algorithms are investigated in terms of their behavior in 2D perfect gas laminar viscous flows with attention given to the van Leer, Modified Steger-Warming (MSW), and Roe methods. The techniques are studied in the context of examples including a blunt flow at Mach 16, a Mach-14 flow past a 24-deg compression corner, and a Mach-8 type-IV shock-shock interaction. Existing experimental values are compared to the results of the corresponding grid-resolution studies. The algorithms indicate similar surface pressures for the blunt-body and corner flows, but the van Leer approach predicts a very high heat-transfer value. Anomalous carbuncle solutions appear in the blunt-body solutions for the MSW and Roe techniques. Accurate predictions of the separated flow regions are found with the MSW method, the Roe scheme, and the finer grids of the van Leer algorithm, but only the MSW scheme predicts an oscillatory supersonic jet structure in the limit cycle.
Extension of least squares spectral resolution algorithm to high-resolution lipidomics data.
Zeng, Ying-Xu; MjÃ¸s, Svein Are; David, Fabrice P A; Schmid, Adrien W
2016-03-31
Lipidomics, which focuses on the global study of molecular lipids in biological systems, has been driven tremendously by technical advances in mass spectrometry (MS) instrumentation, particularly high-resolution MS. This requires powerful computational tools that handle the high-throughput lipidomics data analysis. To address this issue, a novel computational tool has been developed for the analysis of high-resolution MS data, including the data pretreatment, visualization, automated identification, deconvolution and quantification of lipid species. The algorithm features the customized generation of a lipid compound library and mass spectral library, which covers the major lipid classes such as glycerolipids, glycerophospholipids and sphingolipids. Next, the algorithm performs least squares resolution of spectra and chromatograms based on the theoretical isotope distribution of molecular ions, which enables automated identification and quantification of molecular lipid species. Currently, this methodology supports analysis of both high and low resolution MS as well as liquid chromatography-MS (LC-MS) lipidomics data. The flexibility of the methodology allows it to be expanded to support more lipid classes and more data interpretation functions, making it a promising tool in lipidomic data analysis. PMID:26965325
Spectral deblurring: an algorithm for high-resolution, hybrid spectral CT
NASA Astrophysics Data System (ADS)
Clark, D. P.; Badea, C. T.
2015-03-01
We are developing a hybrid, dual-source micro-CT system based on the combined use of an energy integrating (EID) x-ray detector and a photon counting x-ray detector (PCXD). Due to their superior spectral resolving power, PCXDs have the potential to reduce radiation dose and to enable functional and molecular imaging with CT. In most current PCXDs, however, spatial resolution and field of view are limited by hardware development and charge sharing effects. To address these problems, we propose spectral deblurringâ€”a relatively simple algorithm for increasing the spatial resolution of hybrid, spectral CT data. At the heart of the algorithm is the assumption that the underlying CT data is piecewise constant, enabling robust recovery in the presence of noise and spatial blur by enforcing gradient sparsity. After describing the proposed algorithm, we summarize simulation experiments which assess the trade-offs between spatial resolution, contrast, and material decomposition accuracy given realistic levels of noise. When the spatial resolution between imaging chains has a ratio of 5:1, spectral deblurring results in a 52% increase in the material decomposition accuracy of iodine, gadolinium, barium, and water vs. linear interpolation. For a ratio of 10:1, a realistic representation of our hybrid imaging system, a 52% improvement was also seen. Overall, we conclude that the performance breaks down around high frequency and low contrast structures. Following the simulation experiments, we apply the algorithm to ex vivo data acquired in a mouse injected with an iodinated contrast agent and surrounded by vials of iodine, gadolinium, barium, and water.
Development and Characterization of High-Efficiency, High-Specific Impulse Xenon Hall Thrusters
NASA Technical Reports Server (NTRS)
Hofer, Richard R.; Jacobson, David (Technical Monitor)
2004-01-01
This dissertation presents research aimed at extending the efficient operation of 1600 s specific impulse Hall thruster technology to the 2000 to 3000 s range. Motivated by previous industry efforts and mission studies, the aim of this research was to develop and characterize xenon Hall thrusters capable of both high-specific impulse and high-efficiency operation. During the development phase, the laboratory-model NASA 173M Hall thrusters were designed and their performance and plasma characteristics were evaluated. Experiments with the NASA-173M version 1 (v1) validated the plasma lens magnetic field design. Experiments with the NASA 173M version 2 (v2) showed there was a minimum current density and optimum magnetic field topography at which efficiency monotonically increased with voltage. Comparison of the thrusters showed that efficiency can be optimized for specific impulse by varying the plasma lens. During the characterization phase, additional plasma properties of the NASA 173Mv2 were measured and a performance model was derived. Results from the model and experimental data showed how efficient operation at high-specific impulse was enabled through regulation of the electron current with the magnetic field. The electron Hall parameter was approximately constant with voltage, which confirmed efficient operation can be realized only over a limited range of Hall parameters.
Isotope specific resolution recovery image reconstruction in high resolution PET imaging
Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib
2014-05-15
Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution
NASA Astrophysics Data System (ADS)
Song, Xianhai; Li, Lei; Zhang, Xueqiang; Huang, Jianquan; Shi, Xinchun; Jin, Si; Bai, Yiming
2014-10-01
In recent years, Rayleigh waves are gaining popularity to obtain near-surface shear (S)-wave velocity profiles. However, inversion of Rayleigh wave dispersion curves is challenging for most local-search methods due to its high nonlinearity and to its multimodality. In this study, we proposed and tested a new Rayleigh wave dispersion curve inversion scheme based on differential evolution (DE) algorithm. DE is a novel stochastic search approach that possesses several attractive advantages: (1) Capable of handling non-differentiable, non-linear and multimodal objective functions because of its stochastic search strategy; (2) Parallelizability to cope with computation intensive objective functions without being time consuming by using a vector population where the stochastic perturbation of the population vectors can be done independently; (3) Ease of use, i.e. few control variables to steer the minimization/maximization by DE's self-organizing scheme; and (4) Good convergence properties. The proposed inverse procedure was applied to nonlinear inversion of fundamental-mode Rayleigh wave dispersion curves for near-surface S-wave velocity profiles. To evaluate calculation efficiency and stability of DE, we firstly inverted four noise-free and four noisy synthetic data sets. Secondly, we investigated effects of the number of layers on DE algorithm and made an uncertainty appraisal analysis by DE algorithm. Thirdly, we made a comparative analysis with genetic algorithms (GA) by a synthetic data set to further investigate the performance of the proposed inverse procedure. Finally, we inverted a real-world example from a waste disposal site in NE Italy to examine the applicability of DE on Rayleigh wave dispersion curves. Furthermore, we compared the performance of the proposed approach to that of GA to further evaluate scores of the inverse procedure described here. Results from both synthetic and actual field data demonstrate that differential evolution algorithm applied
NASA Astrophysics Data System (ADS)
Sadeghi, Zahra; Valadan Zoej, Mohammad Javad; Dehghani, Maryam; Chang, Ni-Bin
2012-01-01
Persistent scatterer interferometry (PSI) techniques using amplitude analysis and considering a temporal deformation model for PS pixel selection are unable to identify PS pixels in rural areas lacking human-made structures. In contrast, high rates of land subsidence lead to significant phase-unwrapping errors in a recently developed PSI algorithm (StaMPS) that applies phase stability and amplitude analysis to select the PS pixels in rural areas. The objective of this paper is to present an enhanced algorithm based on PSI to estimate the deformation rate in rural areas undergoing high and nearly constant rates of deformation. The proposed approach integrates the strengths of all of the existing PSI algorithms in PS pixel selection and phase unwrapping. PS pixels are first selected based on the amplitude information and phase-stability estimation as performed in StaMPS. The phase-unwrapping step, including the deformation rate and phase-ambiguity estimation, is then performed using least-squares ambiguity decorrelation adjustment (LAMBDA). The atmospheric phase screen (APS) and nonlinear deformation contribution to the phase are estimated by applying a high-pass temporal filter to the residuals derived from the LAMBDA method. The final deformation rate and the ambiguity parameter are re-estimated after subtracting the APS and the nonlinear deformation from that of the initial phase. The proposed method is applied to 22 ENVISAT ASAR images of southwestern Tehran basin captured between 2003 and 2008. A quantitative comparison with the results obtained with leveling and GPS measurements demonstrates the significant improvement of the PSI technique.
An Efficient Algorithm for Some Highly Nonlinear Fractional PDEs in Mathematical Physics
Ahmad, Jamshad; Mohyud-Din, Syed Tauseef
2014-01-01
In this paper, a fractional complex transform (FCT) is used to convert the given fractional partial differential equations (FPDEs) into corresponding partial differential equations (PDEs) and subsequently Reduced Differential Transform Method (RDTM) is applied on the transformed system of linear and nonlinear time-fractional PDEs. The results so obtained are re-stated by making use of inverse transformation which yields it in terms of original variables. It is observed that the proposed algorithm is highly efficient and appropriate for fractional PDEs and hence can be extended to other complex problems of diversified nonlinear nature. PMID:25525804
Adaptation of the CVT algorithm for catheter optimization in high dose rate brachytherapy
Poulin, Eric; Fekete, Charles-Antoine Collins; Beaulieu, Luc; LÃ©tourneau, MÃ©lanie; Fenster, Aaron; Pouliot, Jean
2013-11-15
Purpose: An innovative, simple, and fast method to optimize the number and position of catheters is presented for prostate and breast high dose rate (HDR) brachytherapy, both for arbitrary templates or template-free implants (such as robotic templates).Methods: Eight clinical cases were chosen randomly from a bank of patients, previously treated in our clinic to test our method. The 2D Centroidal Voronoi Tessellations (CVT) algorithm was adapted to distribute catheters uniformly in space, within the maximum external contour of the planning target volume. The catheters optimization procedure includes the inverse planning simulated annealing algorithm (IPSA). Complete treatment plans can then be generated from the algorithm for different number of catheters. The best plan is chosen from different dosimetry criteria and will automatically provide the number of catheters and their positions. After the CVT algorithm parameters were optimized for speed and dosimetric results, it was validated against prostate clinical cases, using clinically relevant dose parameters. The robustness to implantation error was also evaluated. Finally, the efficiency of the method was tested in breast interstitial HDR brachytherapy cases.Results: The effect of the number and locations of the catheters on prostate cancer patients was studied. Treatment plans with a better or equivalent dose distributions could be obtained with fewer catheters. A better or equal prostate V100 was obtained down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of prostate V100 and D90. Implantation errors up to 3 mm were acceptable since no statistical difference was found when compared to 0 mm error (p > 0.05). No significant difference in dosimetric indices was observed for the different combination of parameters within the CVT algorithm. A linear relation was found between the number of random points and the optimization time of the CVT algorithm. Because the
Age specific fecundity of Lygus hesperus in high, fluctuating temperatures.
Technology Transfer Automated Retrieval System (TEKTRAN)
We have simulated hourly temperatures to examine Lygus response to hot summers in the San Joaquin Valley. Constant temperature of 33C quickly killed Lygus and SJV temperatures routinely surpass this level. Average hourly temperatures were tested for the months May, July, and September. Age specific ...
Specification of High Activity Gamma-Ray Sources.
ERIC Educational Resources Information Center
International Commission on Radiation Units and Measurements, Washington, DC.
The report is concerned with making recommendations for the specifications of gamma ray sources, which relate to the quantity of radioactive material and the radiation emitted. Primary consideration is given to sources in teletherapy and to a lesser extent those used in industrial radiography and in irradiation units used in industry and research.â€¦
Optimization of the K-means algorithm for the solution of high dimensional instances
NASA Astrophysics Data System (ADS)
PÃ©rez, JoaquÃn; Pazos, Rodolfo; Olivares, VÃctor; Hidalgo, Miguel; Ruiz, Jorge; MartÃnez, Alicia; Almanza, Nelva; GonzÃ¡lez, MoisÃ©s
2016-06-01
This paper addresses the problem of clustering instances with a high number of dimensions. In particular, a new heuristic for reducing the complexity of the K-means algorithm is proposed. Traditionally, there are two approaches that deal with the clustering of instances with high dimensionality. The first executes a preprocessing step to remove those attributes of limited importance. The second, called divide and conquer, creates subsets that are clustered separately and later their results are integrated through post-processing. In contrast, this paper proposes a new solution which consists of the reduction of distance calculations from the objects to the centroids at the classification step. This heuristic is derived from the visual observation of the clustering process of K-means, in which it was found that the objects can only migrate to adjacent clusters without crossing distant clusters. Therefore, this heuristic can significantly reduce the number of distance calculations from an object to the centroids of the potential clusters that it may be classified to. To validate the proposed heuristic, it was designed a set of experiments with synthetic and high dimensional instances. One of the most notable results was obtained for an instance of 25,000 objects and 200 dimensions, where its execution time was reduced up to 96.5% and the quality of the solution decreased by only 0.24% when compared to the K-means algorithm.
Finsterle, S.; Kowalsky, M.B.
2010-10-15
We propose a modification to the Levenberg-Marquardt minimization algorithm for a more robust and more efficient calibration of highly parameterized, strongly nonlinear models of multiphase flow through porous media. The new method combines the advantages of truncated singular value decomposition with those of the classical Levenberg-Marquardt algorithm, thus enabling a more robust solution of underdetermined inverse problems with complex relations between the parameters to be estimated and the observable state variables used for calibration. The truncation limit separating the solution space from the calibration null space is re-evaluated during the iterative calibration process. In between these re-evaluations, fewer forward simulations are required, compared to the standard approach, to calculate the approximate sensitivity matrix. Truncated singular values are used to calculate the Levenberg-Marquardt parameter updates, ensuring that safe small steps along the steepest-descent direction are taken for highly correlated parameters of low sensitivity, whereas efficient quasi-Gauss-Newton steps are taken for independent parameters with high impact. The performance of the proposed scheme is demonstrated for a synthetic data set representing infiltration into a partially saturated, heterogeneous soil, where hydrogeological, petrophysical, and geostatistical parameters are estimated based on the joint inversion of hydrological and geophysical data.
Algorithms for Low-Cost High Accuracy Geomagnetic Measurements in LEO
NASA Astrophysics Data System (ADS)
Beach, T. L.; Zesta, E.; Allen, L.; Chepko, A.; Bonalsky, T.; Wendel, D. E.; Clavier, O.
2013-12-01
Geomagnetic field measurements are a fundamental, key parameter measurement for any space weather application, particularly for tracking the electromagnetic energy input in the Ionosphere-Thermosphere system and for high latitude dynamics governed by the large-scale field-aligned currents. The full characterization of the Magnetosphere-Ionosphere-Thermosphere coupled system necessitates measurements with higher spatial/temporal resolution and from multiple locations simultaneously. This becomes extremely challenging in the current state of shrinking budgets. Traditionally, including a science-grade magnetometer in a mission necessitates very costly integration and design (sensor on long boom) and imposes magnetic cleanliness restrictions on all components of the bus and payload. This work presents an innovative algorithm approach that enables high quality magnetic field measurements by one or more high-quality magnetometers mounted on the spacecraft without booms. The algorithm estimates the background field using multiple magnetometers and current telemetry on board a spacecraft. Results of a hardware-in-the-loop simulation showed an order of magnitude reduction in the magnetic effects of spacecraft onboard time-varying currents--from 300 nT to an average residual of 15 nT.
Surface contribution to high-order aberrations using the Aldis therem and Andersen's algorithms
NASA Astrophysics Data System (ADS)
Ortiz-Estardante, A.; Cornejo-Rodriguez, Alejandro
1990-07-01
Formulae and computer programs were developed for surface contributions to high order aberrations coefficients using the Aldis theorem and Andersen algor ithms for a symmetr ical optical system. 2. THEORY Using the algorithms developed by T. B. Andersent which allow to calculate the high order aberrations coefficients of an optical system. We were able to obtain a set of equations for the contributions of each surface of a centered optical system to such aberration coefficiets by using the equations of Andersen and the so called Aldis theorem 3. COMPUTER PROGRAMS AND EXAMPLES. The study for the case of an object at infinite has been completed and more recently the object to finite distance case has been also finished . The equations have been properly programed for the two above mentioned situations . Some typical designs of optical systems will be presented and some advantages and disadvantages of the developed formulae and method will be discussed. 4. CONCLUSIONS The algorithm developed by Anderson has a compact notation and structure which is suitable for computers. Using those results obtained by Anderson together with the Aldis theorem a set of equations were derived and programmed for the surface contributions of a centered optical system to high order aberrations. 5. REFERENCES 1. T . B. Andersen App 1. Opt. 3800 (1980) 2. A. Cox A system of Optical Design Focal Press 1964 18 / SPIE
NASA Astrophysics Data System (ADS)
Buhari, Adamu Muhammad; Ling, Huo-Chong; Baskaran, Vishnu Monn; Wong, KokSheik
2015-01-01
The progression toward spatially scalable video coding (SVC) solutions for ubiquitous endpoint systems introduces challenges to sustain real-time frame rates in downsampling high-resolution videos into multiple layers. In addressing these challenges, we put forward a hardware accelerated downsampling algorithm on a parallel computing platform. First, we investigate the principal architecture of a serial downsampling algorithm in the Joint-Scalable-Video-Model reference software to identify the performance limitations for spatially SVC. Then, a parallel multicore-based downsampling algorithm is studied as a benchmark. Experimental results for this algorithm using an 8-core processor exhibit performance speedup of 5.25Ã— against the serial algorithm in downsampling a quantum extended graphics array at 1536p video resolution into three lower resolution layers (i.e., Full-HD at 1080p, HD at 720p, and Quarter-HD at 540p). However, the achieved speedup here does not translate into the minimum required frame rate of 15 frames per second (fps) for real-time video processing. To improve the speedup, a many-core based downsampling algorithm using the compute unified device architecture parallel computing platform is proposed. The proposed algorithm increases the performance speedup to 26.14Ã— against the serial algorithm. Crucially, the proposed algorithm exceeds the target frame rate of 15 fps, which in turn is advantageous to the overall performance of the video encoding process.
High Spectral Resolution MODIS Algorithms for Ocean Chlorophyll in Case II Waters
NASA Technical Reports Server (NTRS)
Carder, Kendall L.
2004-01-01
The Case 2 chlorophyll a algorithm is based on a semi-analytical, bio-optical model of remote sensing reflectance, R(sub rs)(lambda), where R(sub rs)(lambda) is defined as the water-leaving radiance, L(sub w)(lambda), divided by the downwelling irradiance just above the sea surface, E(sub d)(lambda,0(+)). The R(sub rs)(lambda) model (Section 3) has two free variables, the absorption coefficient due to phytoplankton at 675 nm, a(sub phi)(675), and the absorption coefficient due to colored dissolved organic matter (CDOM) or gelbstoff at 400 nm, a(sub g)(400). The R(rs) model has several parameters that are fixed or can be specified based on the region and season of the MODIS scene. These control the spectral shapes of the optical constituents of the model. R(sub rs)(lambda(sub i)) values from the MODIS data processing system are placed into the model, the model is inverted, and a(sub phi)(675), a(sub g)(400) (MOD24), and chlorophyll a (MOD21, Chlor_a_3) are computed. Algorithm development is initially focused on tropical, subtropical, and summer temperate environments, and the model is parameterized in Section 4 for three different bio-optical domains: (1) high ratios of photoprotective pigments to chlorophyll and low self-shading, which for brevity, we designate as 'unpackaged'; (2) low ratios and high self-shading, which we designate as 'packaged'; and (3) a transitional or global-average type. These domains can be identified from space by comparing sea-surface temperature to nitrogen-depletion temperatures for each domain (Section 5). Algorithm errors of more than 45% are reduced to errors of less than 30% with this approach, with the greatest effect occurring at the eastern and polar boundaries of the basins. Section 6 provides an expansion of bio-optical domains into high-latitude waters. The 'fully packaged' pigment domain is introduced in this section along with a revised strategy for implementing these variable packaging domains. Chlor_a_3 values derived semi
NASA Astrophysics Data System (ADS)
Lee, Seungbeom; Lee, Hanho
This paper presents a novel high-speed low-complexity pipelined degree-computationless modified Euclidean (pDCME) algorithm architecture for high-speed RS decoders. The pDCME algorithm allows elimination of the degree-computation so as to reduce hardware complexity and obtain high-speed processing. A high-speed RS decoder based on the pDCME algorithm has been designed and implemented with 0.13-Î¼m CMOS standard cell technology in a supply voltage of 1.1V. The proposed RS decoder operates at a clock frequency of 660MHz and has a throughput of 5.3Gb/s. The proposed architecture requires approximately 15% fewer gate counts and a simpler control logic than architectures based on the popular modified Euclidean algorithm.
Byer, R.L.
1982-04-01
Progress made over a four year period on a computer controlled laser wavelength meter is summarized. The optical system of the laser wavelength meter consists of a series of Fabry-Perot interferometers and one high resolution confocal interferometer, preceeded by a one-half meter grating spectrometer. The interferometrically generated fringes are imaged on linear diode arrays, read into computer memory and processed by an efficient, noise resistant, algorithm which calculates the wavelength. The algorithm fitting routine generates high accuracy fringe fits at a rate of 5Hz with the present LSI 11/2 processor. A 10 Hz fitting rate is expected with the LSI 11/23 processor. Fringes are fit with an rms error of less than +- 0.01. The wavelength measurement accuracy is thus one hundredth of the free spectral range of the interferometers, which at present are 10 cm/sup -1/, 1 cm/sup -1/, 0.1 cm/sup -1/ and 0.01 cm/sup -1/. Thus wavelengths can be measured to +- .0001 cm/sup -1/ or +- 3 MHz. The wavelength meter interferometers are calibrated by a stabilized HeNe laser source with a long term stability of better than +- 1 MHz. Fringes have been fit for over 10/sup 6/ cycles to demonstrate the stability of the algorithm. When the hardware is transferred from the present bread-borad mounting to final mounting, the wavelength meter will provide an accurate and versatile approach for measuring and displaying cw, pulsed, single mode or multi mode laser spectra.
Coaxial plasma thrusters for high specific impulse propulsion
NASA Technical Reports Server (NTRS)
Schoenberg, Kurt F.; Gerwin, Richard A.; Barnes, Cris W.; Henins, Ivars; Mayo, Robert; Moses, Ronald, Jr.; Scarberry, Richard; Wurden, Glen
1991-01-01
A fundamental basis for coaxial plasma thruster performance is presented and the steady-state, ideal MHD properties of a coaxial thruster using an annular magnetic nozzle are discussed. Formulas for power usage, thrust, mass flow rate, and specific impulse are acquired and employed to assess thruster performance. The performance estimates are compared with the observed properties of an unoptimized coaxial plasma gun. These comparisons support the hypothesis that ideal MHD has an important role in coaxial plasma thruster dynamics.
NASA Astrophysics Data System (ADS)
Ashton, Douglas J.; Liu, Jiwen; Luijten, Erik; Wilding, Nigel B.
2010-11-01
Highly size-asymmetrical fluid mixtures arise in a variety of physical contexts, notably in suspensions of colloidal particles to which much smaller particles have been added in the form of polymers or nanoparticles. Conventional schemes for simulating models of such systems are hamstrung by the difficulty of relaxing the large species in the presence of the small one. Here we describe how the rejection-free geometrical cluster algorithm of Liu and Luijten [J. Liu and E. Luijten, Phys. Rev. Lett. 92, 035504 (2004)] can be embedded within a restricted Gibbs ensemble to facilitate efficient and accurate studies of fluid phase behavior of highly size-asymmetrical mixtures. After providing a detailed description of the algorithm, we summarize the bespoke analysis techniques of [Ashton et al., J. Chem. Phys. 132, 074111 (2010)] that permit accurate estimates of coexisting densities and critical-point parameters. We apply our methods to study the liquid-vapor phase diagram of a particular mixture of Lennard-Jones particles having a 10:1 size ratio. As the reservoir volume fraction of small particles is increased in the range of 0%-5%, the critical temperature decreases by approximately 50%, while the critical density drops by some 30%. These trends imply that in our system, adding small particles decreases the net attraction between large particles, a situation that contrasts with hard-sphere mixtures where an attractive depletion force occurs.
Defining and Evaluating Classification Algorithm for High-Dimensional Data Based on Latent Topics
Luo, Le; Li, Li
2014-01-01
Automatic text categorization is one of the key techniques in information retrieval and the data mining field. The classification is usually time-consuming when the training dataset is large and high-dimensional. Many methods have been proposed to solve this problem, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the Latent Dirichlet Allocation (LDA) algorithm and the Support Vector Machine (SVM). LDA is first used to generate reduced dimensional representation of topics as feature in VSM. It is able to reduce features dramatically but keeps the necessary semantic information. The Support Vector Machine (SVM) is then employed to classify the data based on the generated features. We evaluate the algorithm on 20 Newsgroups and Reuters-21578 datasets, respectively. The experimental results show that the classification based on our proposed LDA+SVM model achieves high performance in terms of precision, recall and F1 measure. Further, it can achieve this within a much shorter time-frame. Our process improves greatly upon the previous work in this field and displays strong potential to achieve a streamlined classification process for a wide range of applications. PMID:24416136
NASA Astrophysics Data System (ADS)
Zhang, J. X.; Yang, J. H.; Reinartz, P.
2016-06-01
Pan-sharpening of very high resolution remotely sensed imagery need enhancing spatial details while preserving spectral characteristics, and adjusting the sharpened results to realize the different emphases between the two abilities. In order to meet the requirements, this paper is aimed at providing an innovative solution. The block-regression-based algorithm (BR), which was previously presented for fusion of SAR and optical imagery, is firstly applied to sharpen the very high resolution satellite imagery, and the important parameter for adjustment of fusion result, i.e., block size, is optimized according to the two experiments for Worldview-2 and QuickBird datasets in which the optimal block size is selected through the quantitative comparison of the fusion results of different block sizes. Compared to five fusion algorithms (i.e., PC, CN, AWT, Ehlers, BDF) in fusion effects by means of quantitative analysis, BR is reliable for different data sources and can maximize enhancement of spatial details at the expense of a minimum spectral distortion.
Effects of high count rate and gain shift on isotope identification algorithms
Robinson, Sean M.; Kiff, Scott D.; Ashbaker, Eric D.; Flumerfelt, Eric L.; Salvitti, Matthew
2009-11-01
Spectroscopic gamma-ray detectors are used for many research, industrial, and homeland- security applications. Thallium-doped sodium iodide, (NaI(Tl)), scintillation crystals coupled to photomultiplier tubes provide medium-resolution spectral data about the surrounding environment. NaI(Tl)-based detectors, paired with spectral identification algorithms, are often effective for identifying gamma-ray sources by isotope. However, intrinsic limitations for NaI(Tl) systems exist, including gain shifts and spectral marring (e.g., loss of resolution and count-rate saturation) at high count rates. These effects are hardware dependent and have strong effects on the radioisotopic identification capability of NaI(Tl)-based systems. In this work, the effects of high count rate on the response of isotope-identification algorithms are explored. It is shown that a small gain shift of a few tens of keV is sufficient to disturb identification. The onset of this and other spectral effects is estimated for NaI(Tl) crystals, and a mechanism for mitigating these effects by estimating and correcting for them is implemented and evaluated.
Effects of High Count Rate and Gain Shift on Isotope Identification Algorithms
Robinson, Sean M.; Kiff, Scott D.; Ashbaker, Eric D.; Bender, Sarah E.; Flumerfelt, Eric L.; Salvitti, Matthew; Borgardt, James D.; Woodring, Mitchell L.
2007-12-31
Spectroscopic gamma-ray detectors are used for many research applications, as well as Homeland Security screening applications. Sodium iodide (NaI) scintillator crystals coupled with photomultiplier tubes (PMTs) provide medium-resolution spectral data about the surrounding environment. NaI based detectors, paired with spectral identification algorithms, are often effective in identifying sources of interest by isotope. However, intrinsic limitations exist for NaI systems because of gain shifts and spectral marring (e.g., loss of resolution and count-rate saturation) at high count rates. These effects are hardware dependent, and have strong effects on the radioisotopic identification capability of these systems. In this work, the effects of high count rate on the capability of isotope identification algorithms are explored. It is shown that a small gain shift of a few tens of keV is sufficient to disturb identification. The onset of this and other spectral effects are estimated for several systems., and a mechanism for mitigating these effects by estimating and correcting for them is implemented and evaluated.
Crystal Symmetry Algorithms in a High-Throughput Framework for Materials
NASA Astrophysics Data System (ADS)
Taylor, Richard
The high-throughput framework AFLOW that has been developed and used successfully over the last decade is improved to include fully-integrated software for crystallographic symmetry characterization. The standards used in the symmetry algorithms conform with the conventions and prescriptions given in the International Tables of Crystallography (ITC). A standard cell choice with standard origin is selected, and the space group, point group, Bravais lattice, crystal system, lattice system, and representative symmetry operations are determined. Following the conventions of the ITC, the Wyckoff sites are also determined and their labels and site symmetry are provided. The symmetry code makes no assumptions on the input cell orientation, origin, or reduction and has been integrated in the AFLOW high-throughput framework for materials discovery by adding to the existing code base and making use of existing classes and functions. The software is written in object-oriented C++ for flexibility and reuse. A performance analysis and examination of the algorithms scaling with cell size and symmetry is also reported.
L2-Boosting algorithm applied to high-dimensional problems in genomic selection.
GonzÃ¡lez-Recio, Oscar; Weigel, Kent A; Gianola, Daniel; Naya, Hugo; Rosa, Guilherme J M
2010-06-01
The L(2)-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm in a genomic selection context to make predictions of yet to be observed outcomes. Two data sets were used: (1) productive lifetime predicted transmitting abilities from 4702 Holstein sires genotyped for 32 611 single nucleotide polymorphisms (SNPs) derived from the Illumina BovineSNP50 BeadChip, and (2) progeny averages of food conversion rate, pre-corrected by environmental and mate effects, in 394 broilers genotyped for 3481 SNPs. Each of these data sets was split into training and testing sets, the latter comprising dairy or broiler sires whose ancestors were in the training set. Two weak learners, ordinary least squares (OLS) and non-parametric (NP) regression were used for the L2-Boosting algorithm, to provide a stringent evaluation of the procedure. This algorithm was compared with BL [Bayesian LASSO (least absolute shrinkage and selection operator)] and BayesA regression. Learning tasks were carried out in the training set, whereas validation of the models was performed in the testing set. Pearson correlations between predicted and observed responses in the dairy cattle (broiler) data set were 0.65 (0.33), 0.53 (0.37), 0.66 (0.26) and 0.63 (0.27) for OLS-Boosting, NP-Boosting, BL and BayesA, respectively. The smallest bias and mean-squared errors (MSEs) were obtained with OLS-Boosting in both the dairy cattle (0.08 and 1.08, respectively) and broiler (-0.011 and 0.006) data sets, respectively. In the dairy cattle data set, the BL was more accurate (bias=0.10 and MSE=1.10) than BayesA (bias=1.26 and MSE=2.81), whereas no differences between these two methods were found in the broiler data set. L2-Boosting with a suitable learner was found to be a competitive
NASA Astrophysics Data System (ADS)
Monteiller, Vadim; Beller, Stephen; Nolet, Guust; Operto, Stephane; Brossier, Romain; MÃ©tivier, Ludovic; Paul, Anne; Virieux, Jean
2014-05-01
The current development of dense seismic arrays and high performance computing make feasible today application of full-waveform inversion (FWI) on teleseismic data for high-resolution lithospheric imaging. In teleseismic configuration, the source is to first-order a plane-wave that impinges the base of the lithospheric target located below the receiver array. In this setting, FWI aims to exploit not only the forward-scattered waves propagating up to the receiver but also second-order arrivals that are back-scattered from the free-surface and the reflectors before their recordings on the surface. FWI requires using full-wave methods modeling such as finite-difference or finite-element methods. In this framework, careful design of FWI algorithms is topical to mitigate as much as possible the computational burden of multi-source full-waveform modeling. In this presentation, we review some key specifications that might be considered for versatile FWI implementation. An abstraction level between the forward and inverse problems that allows for the interfacing of different modeling engines with the inversion. This requires the subsurface meshings that are used to perform seismic modeling and update the subsurface models during inversion to be fully independent through some back-and-forth projection processes. The subsurface parameterization should be carefully chosen during multi-parameter FWI as it controls the trade-off between parameters of different nature. A versatile FWI algorithm should be designed such that different subsurface parameterizations for the model update can be easily implemented. The gradient of the misfit function should be computed as easily as possible with the adjoint-state method in parallel environment. This first requires the gradient to be independent to the discretization method that is used to perform seismic modeling. Second, the incident and adjoint wavefields should be computed with the same numerical scheme, even if the forward problem
Lafreniere, D; Marois, C; Doyon, R; Artigau, E; Nadeau, D
2006-09-19
Direct imaging of exoplanets is limited by bright quasi-static speckles in the point spread function (PSF) of the central star. This limitation can be reduced by subtraction of reference PSF images. We have developed an algorithm to construct an optimal reference PSF image from an arbitrary set of reference images. This image is built as a linear combination of all available images and is optimized independently inside multiple subsections of the image to ensure that the absolute minimum residual noise is achieved within each subsection. The algorithm developed is completely general and can be used with many high contrast imaging observing strategies, such as angular differential imaging (ADI), roll subtraction, spectral differential imaging, reference star observations, etc. The performance of the algorithm is demonstrated for ADI data. It is shown that for this type of data the new algorithm provides a gain in sensitivity by up 22 to a factor 3 at small separation over the algorithm previously used.
A protein multiplex microarray substrate with high sensitivity and specificity
Fici, Dolores A.; McCormick, William; Brown, David W.; Herrmann, John E.; Kumar, Vikram; Awdeh, Zuheir L.
2010-01-01
The problems that have been associated with protein multiplex microarray immunoassay substrates and existing technology platforms include: binding, sensitivity, a low signal to noise ratio, target immobilization and the optimal simultaneous detection of diverse protein targets. Current commercial substrates for planar multiplex microarrays rely on protein attachment chemistries that range from covalent attachment to affinity ligand capture, to simple adsorption. In this pilot study, experimental performance parameters for direct monoclonal mouse IgG detection were compared for available two and three dimensional slide surface coatings with a new colloidal nitrocellulose substrate. New technology multiplex microarrays were also developed and evaluated for the detection of pathogen specific antibodies in human serum and the direct detection of enteric viral antigens. Data supports the nitrocellulose colloid as an effective reagent with the capacity to immobilize sufficient diverse protein target quantities for increased specificory signal without compromising authentic protein structure. The nitrocellulose colloid reagent is compatible with the array spotters and scanners routinely used for microarray preparation and processing. More importantly, as an alternate to fluorescence, colorimetric chemistries may be used for specific and sensitive protein target detection. The advantages of the nitrocellulose colloid platform indicate that this technology may be a valuable tool for the further development and expansion of multiplex microarray immunoassays in both the clinical and research laborat environment. PMID:20974147
Simulation of Trajectories for High Specific Impulse Deep Space Exploration
NASA Technical Reports Server (NTRS)
Polsgrove, Tara; Adams, Robert B.; Brady, Hugh J. (Technical Monitor)
2002-01-01
Difficulties in approximating flight times and deliverable masses for continuous thrust propulsion systems have complicated comparison and evaluation of proposed propulsion concepts. These continuous thrust propulsion systems are of interest to many groups, not the least of which are the electric propulsion and fusion communities. Several charts plotting the results of well-known trajectory simulation codes were developed and are contained in this paper. These charts illustrate the dependence of time of flight and payload ratio on jet power, initial mass, specific impulse and specific power. These charts are intended to be a tool by which people in the propulsion community can explore the possibilities of their propulsion system concepts. Trajectories were simulated using the tools VARITOP and IPOST. VARITOP is a well known trajectory optimization code that involves numerical integration based on calculus of variations. IPOST has several methods of trajectory simulation; the one used in this paper is Cowell's method for full integration of the equations of motion. The analytical method derived in the companion paper was also used to simulate the trajectory. The accuracy of this method is discussed in the paper.
Toward an image compression algorithm for the high-resolution electronic still camera
NASA Technical Reports Server (NTRS)
Nerheim, Rosalee
1989-01-01
Taking pictures with a camera that uses a digital recording medium instead of film has the advantage of recording and transmitting images without the use of a darkroom or a courier. However, high-resolution images contain an enormous amount of information and strain data-storage systems. Image compression will allow multiple images to be stored in the High-Resolution Electronic Still Camera. The camera is under development at Johnson Space Center. Fidelity of the reproduced image and compression speed are of tantamount importance. Lossless compression algorithms are fast and faithfully reproduce the image, but their compression ratios will be unacceptably low due to noise in the front end of the camera. Future efforts will include exploring methods that will reduce the noise in the image and increase the compression ratio.
On high-order denoising models and fast algorithms for vector-valued images.
Brito-Loeza, Carlos; Chen, Ke
2010-06-01
Variational techniques for gray-scale image denoising have been deeply investigated for many years; however, little research has been done for the vector-valued denoising case and the very few existent works are all based on total-variation regularization. It is known that total-variation models for denoising gray-scaled images suffer from staircasing effect and there is no reason to suggest this effect is not transported into the vector-valued models. High-order models, on the contrary, do not present staircasing. In this paper, we introduce three high-order and curvature-based denoising models for vector-valued images. Their properties are analyzed and a fast multigrid algorithm for the numerical solution is provided. AMS subject classifications: 68U10, 65F10, 65K10. PMID:20172828
Application of artificial bee colony (ABC) algorithm in search of optimal release of Aswan High Dam
NASA Astrophysics Data System (ADS)
Hossain, Md S.; El-shafie, A.
2013-04-01
The paper presents a study on developing an optimum reservoir release policy by using ABC algorithm. The decision maker of a reservoir system always needs a guideline to operate the reservoir in an optimal way. Release curves have developed for high, medium and low inflow category that can answer how much water need to be release for a month by observing the reservoir level (storage condition). The Aswan high dam of Egypt has considered as the case study. 18 years of historical inflow data has used for simulation purpose and the general system performance measuring indices has measured. The application procedure and problem formulation of ABC is very simple and can be used in optimizing reservoir system. After using the actual historical inflow, the release policy succeeded in meeting demand for about 98% of total time period.
Architecture for High Speed Learning of Neural Network using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Yoshikawa, Masaya; Terai, Hidekazu
This paper discusses the architecture for high speed learning of Neural Network (NN) using Genetic Algorithm (GA). The proposed architecture prevents local minimum by using the GA characteristic of holding several individual populations for a population-based search and achieves high speed processing adopting dedicated hardware. To keep general purpose equal software processing, the proposed architecture can be flexible genetic operations on GA and is introduced both Sigmoid function and Heaviside function on NN. Furthermore, the proposed architecture is not optimized only the pipeline at evaluation phase on NN, but also optimized hierarchic pipelines on the whole at evolutionary phase. We have done the simulation, verification and logic synthesis using library of 0.35Î¼m CMOS standard cell. Simulation results evaluating the proposed architecture show to achieve 22 times speed on average compared with software processing.
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.; Tikhomirov, Vasily V.
2015-08-01
Principal limitations of the standard THz-TDS method for the detection and identification are demonstrated under real conditions (at long distance of about 3.5 m and at a high relative humidity more than 50%) using neutral substances thick paper bag, paper napkins and chocolate. We show also that the THz-TDS method detects spectral features of dangerous substances even if the THz signals were measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); silicon-based semiconductors were used as the samples. However, the integral correlation criteria, based on SDA method, allows us to detect the absence of dangerous substances in the neutral substances. The discussed algorithm shows high probability of the substance identification and a reliability of realization in practice, especially for security applications and non-destructive testing.
Enhanced ATR algorithm for high resolution multi-band sonar imagery
NASA Astrophysics Data System (ADS)
Aridgides, Tom; FernÃ¡ndez, Manuel
2008-04-01
An improved automatic target recognition (ATR) processing string has been developed. The overall processing string consists of pre-processing, subimage adaptive clutter filtering (SACF), normalization, detection, data regularization, feature extraction, optimal subset feature selection, feature orthogonalization and classification processing blocks. A new improvement was made to the processing string, data regularization, which entails computing the input data mean, clipping the data to a multiple of its mean and scaling it, prior to feature extraction. The classified objects of 3 distinct strings are fused using the classification confidence values and their expansions as features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. The utility of the overall processing strings and their fusion was demonstrated with new high-resolution three-frequency band sonar imagery. The ATR processing strings were individually tuned to the corresponding three-frequency band data, making use of the new processing improvement, data regularization, which resulted in a 3:1 reduction in false alarms. Two significant fusion algorithm improvements were made. First, a nonlinear 2nd order (Volterra) feature LLRT fusion algorithm was developed. Second, a repeated application of a subset Volterra feature selection / feature orthogonalization / LLRT fusion block was utilized. It was shown that cascaded Volterra feature LLRT fusion of the ATR processing strings outperforms baseline summing and single-stage Volterra feature LLRT algorithms, yielding significant improvements over the best single ATR processing string results, and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate.
Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.
2016-08-19
Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themoreÂ Â» problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~101 to ~102 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.Â«Â less
NASA Astrophysics Data System (ADS)
Williams, Arnold C.; Pachowicz, Peter W.
2004-09-01
Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.
NASA Astrophysics Data System (ADS)
Piles, M.; Entekhabi, D.; Camps, A.
2009-09-01
Soil moisture is a critical hydrological variable that links the terrestrial water, energy and carbon cycles. Global and regional observations of soil moisture are needed to estimate the water and energy fluxes at the land surface, to quantify the net carbon flux in boreal landscapes, to enhance weather and climate forecast skill and to develop improved flood prediction and drought monitoring capability. Active and Passive L-band microwave remote sensing provide a unique ability to monitor global soil moisture over land surfaces with an acceptable spatial resolution and temporal frequency [1]. Radars are capable of a very high spatial resolution (~ 3km) but, since radar backscatter is hightly influenced by surface roughness, vegetation canopy structure and water content, they have a low sensitivity to soil moisture, and the algorithms developed for retrieval of soil moisture from radar backscattering are only valid in low-vegetation water content conditions [3]. In contrast, the spatial resolution of radiometers is typically low (~ 40km), they have a high sensitivity to soil moisture, and the retrieval of soil moisture from radiometers is well established [4]. To overcome the individual limitations of active and passive approaches, the Soil Moisture Active and Passive (SMAP) mission of the NASA, scheduled for launch in the 2010-2013 time frame, is combining these two technologies [2]. The SMAP mission payload consists on an approximately 40-km L-band microwave radiometer measuring hh and vv brightness temperatures and a 3-km L-band synthetic aperture radar sensing backscatter cross-sections at hh, vv and hv polarizations. It will provide global scale land surface soil moisture observations with a three day revisit time and its key derived products are: soil moisture at 40-km for hydroclimatology, obtained from the radiometer measurements; soil moisture at 10-km resolution for hydrometeorology obtained by combining the radar and radiometer measurements in a joint
Educational Specifications for the Pojoaque Valley Senior High School.
ERIC Educational Resources Information Center
Tonigan, Richard F.; And Others
The middle school and senior high school of the Pojoaque Valley (New Mexico) School District share many facilities and services. Because of the need for expansion of facilities, some construction projects are budgeted that include remodeling the vocational building, building the music building, and adding built-in equipment to all remodeled andâ€¦
Snyder, Abigail C.; Jiao, Yu
2010-10-01
Neutron experiments at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) frequently generate large amounts of data (on the order of 106-1012 data points). Hence, traditional data analysis tools run on a single CPU take too long to be practical and scientists are unable to efficiently analyze all data generated by experiments. Our goal is to develop a scalable algorithm to efficiently compute high-dimensional integrals of arbitrary functions. This algorithm can then be used to integrate the four-dimensional integrals that arise as part of modeling intensity from the experiments at the SNS. Here, three different one-dimensional numerical integration solvers from the GNU Scientific Library were modified and implemented to solve four-dimensional integrals. The results of these solvers on a final integrand provided by scientists at the SNS can be compared to the results of other methods, such as quasi-Monte Carlo methods, computing the same integral. A parallelized version of the most efficient method can allow scientists the opportunity to more effectively analyze all experimental data.