Algorithm for Detecting Significant Locations from Raw GPS Data
NASA Astrophysics Data System (ADS)
Kami, Nobuharu; Enomoto, Nobuyuki; Baba, Teruyuki; Yoshikawa, Takashi
We present a fast algorithm for probabilistically extracting significant locations from raw GPS data based on data point density. Extracting significant locations from raw GPS data is the first essential step of algorithms designed for location-aware applications. Assuming that a location is significant if users spend a certain time around that area, most current algorithms compare spatial/temporal variables, such as stay duration and a roaming diameter, with given fixed thresholds to extract significant locations. However, the appropriate threshold values are not clearly known in priori and algorithms with fixed thresholds are inherently error-prone, especially under high noise levels. Moreover, for N data points, they are generally O(N 2) algorithms since distance computation is required. We developed a fast algorithm for selective data point sampling around significant locations based on density information by constructing random histograms using locality sensitive hashing. Evaluations show competitive performance in detecting significant locations even under high noise levels.
Algorithms and Requirements for Measuring Network Bandwidth
Jin, Guojun
2002-12-08
This report unveils new algorithms for actively measuring (not estimating) available bandwidths with very low intrusion, computing cross traffic, thus estimating the physical bandwidth, provides mathematical proof that the algorithms are accurate, and addresses conditions, requirements, and limitations for new and existing algorithms for measuring network bandwidths. The paper also discusses a number of important terminologies and issues for network bandwidth measurement, and introduces a fundamental parameter -Maximum Burst Size that is critical for implementing algorithms based on multiple packets.
Discovering simple DNA sequences by the algorithmic significance method.
Milosavljević, A; Jurka, J
1993-08-01
A new method, 'algorithmic significance', is proposed as a tool for discovery of patterns in DNA sequences. The main idea is that patterns can be discovered by finding ways to encode the observed data concisely. In this sense, the method can be viewed as a formal version of the Occam's Razor principle. In this paper the method is applied to discover significantly simple DNA sequences. We define DNA sequences to be simple if they contain repeated occurrences of certain 'words' and thus can be encoded in a small number of bits. Such definition includes minisatellites and microsatellites. A standard dynamic programming algorithm for data compression is applied to compute the minimal encoding lengths of sequences in linear time. An electronic mail server for identification of simple sequences based on the proposed method has been installed at the Internet address pythia/anl.gov. PMID:8402207
Algorithms for Detecting Significantly Mutated Pathways in Cancer
NASA Astrophysics Data System (ADS)
Vandin, Fabio; Upfal, Eli; Raphael, Benjamin J.
Recent genome sequencing studies have shown that the somatic mutations that drive cancer development are distributed across a large number of genes. This mutational heterogeneity complicates efforts to distinguish functional mutations from sporadic, passenger mutations. Since cancer mutations are hypothesized to target a relatively small number of cellular signaling and regulatory pathways, a common approach is to assess whether known pathways are enriched for mutated genes. However, restricting attention to known pathways will not reveal novel cancer genes or pathways. An alterative strategy is to examine mutated genes in the context of genome-scale interaction networks that include both well characterized pathways and additional gene interactions measured through various approaches. We introduce a computational framework for de novo identification of subnetworks in a large gene interaction network that are mutated in a significant number of patients. This framework includes two major features. First, we introduce a diffusion process on the interaction network to define a local neighborhood of "influence" for each mutated gene in the network. Second, we derive a two-stage multiple hypothesis test to bound the false discovery rate (FDR) associated with the identified subnetworks. We test these algorithms on a large human protein-protein interaction network using mutation data from two recent studies: glioblastoma samples from The Cancer Genome Atlas and lung adenocarcinoma samples from the Tumor Sequencing Project. We successfully recover pathways that are known to be important in these cancers, such as the p53 pathway. We also identify additional pathways, such as the Notch signaling pathway, that have been implicated in other cancers but not previously reported as mutated in these samples. Our approach is the first, to our knowledge, to demonstrate a computationally efficient strategy for de novo identification of statistically significant mutated subnetworks. We
Requirements for significant problem reporting and trend analysis
NASA Technical Reports Server (NTRS)
1988-01-01
This handbook supplements policies, requirements, and procedures of NMI 8070.3 to ensure that NASA management at each organizational level is: fully aware of trends affecting both the level of safety and the potential for mission success established for both NASA manned space programs and its supporting institutions; fully and independently informed of problems that represent significant risk to the safety of all personnel (including the general populace) and to the success of a mission or operation through a program mechanism herein defined as Significant Problem Reporting; and in full agreement with the level of elimination of these problems through the closed-loop accounting of corrective actions. The requirements of this handbook are supportive of the agency's safety, reliability, maintainability, and quality assurance (SRM&QA) program objectives and are applicable to all organizational elements of NASA connected with or supporting developmental or operational manned space program/projects (including associated payloads) and the related institutional facilities.
Reducing the Time Requirement of k-Means Algorithm
Osamor, Victor Chukwudi; Adebiyi, Ezekiel Femi; Oyelade, Jelilli Olarenwaju; Doumbia, Seydou
2012-01-01
Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in d-dimensional space Rd and an integer k. The problem is to determine a set of k points in Rd, called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARIHA). We found that when k is close to d, the quality is good (ARIHA>0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARIHA>0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data. PMID:23239974
Reducing the time requirement of k-means algorithm.
Osamor, Victor Chukwudi; Adebiyi, Ezekiel Femi; Oyelade, Jelilli Olarenwaju; Doumbia, Seydou
2012-01-01
Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in d-dimensional space R(d) and an integer k. The problem is to determine a set of k points in R(d), called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARI(HA)). We found that when k is close to d, the quality is good (ARI(HA)>0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARI(HA)>0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data. PMID:23239974
The significance of requirements engineering for the medical domain.
Kossmann, Mario
2014-07-01
This paper aims to raise awareness of the importance of Requirements Engineering (RE) for the successful and efficient development of high-quality systems and products for the medical domain. It does so by providing an introduction to RE from the viewpoints of project and programme management and systems engineering in general and by illustrating the usefulness of a sound RE approach to the development of a local healthcare system in a deprived region in central Africa. The paper concludes that RE is just as crucial for the development of systems and products in the medical domain, as it is for the development of systems in the aerospace industry or software systems in the consumer electronics industry; while the degree of detail and formality of how RE is used has to be tailored to fit the context in question. PMID:24953681
A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features
Amudha, P.; Karthik, S.; Sivakumari, S.
2015-01-01
Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625
A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features.
Amudha, P; Karthik, S; Sivakumari, S
2015-01-01
Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625
Significant Advances in the AIRS Science Team Version-6 Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Blaisdell, John; Iredell, Lena; Molnar, Gyula
2012-01-01
AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,
NASA Technical Reports Server (NTRS)
Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.
1986-01-01
The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.
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.
Algorithmic requirements for swarm intelligence in differently coupled collective systems.
Stradner, Jürgen; Thenius, Ronald; Zahadat, Payam; Hamann, Heiko; Crailsheim, Karl; Schmickl, Thomas
2013-05-01
Swarm systems are based on intermediate connectivity between individuals and dynamic neighborhoods. In natural swarms self-organizing principles bring their agents to that favorable level of connectivity. They serve as interesting sources of inspiration for control algorithms in swarm robotics on the one hand, and in modular robotics on the other hand. In this paper we demonstrate and compare a set of bio-inspired algorithms that are used to control the collective behavior of swarms and modular systems: BEECLUST, AHHS (hormone controllers), FGRN (fractal genetic regulatory networks), and VE (virtual embryogenesis). We demonstrate how such bio-inspired control paradigms bring their host systems to a level of intermediate connectivity, what delivers sufficient robustness to these systems for collective decentralized control. In parallel, these algorithms allow sufficient volatility of shared information within these systems to help preventing local optima and deadlock situations, this way keeping those systems flexible and adaptive in dynamic non-deterministic environments. PMID:23805030
Algorithmic requirements for swarm intelligence in differently coupled collective systems
Stradner, Jürgen; Thenius, Ronald; Zahadat, Payam; Hamann, Heiko; Crailsheim, Karl; Schmickl, Thomas
2013-01-01
Swarm systems are based on intermediate connectivity between individuals and dynamic neighborhoods. In natural swarms self-organizing principles bring their agents to that favorable level of connectivity. They serve as interesting sources of inspiration for control algorithms in swarm robotics on the one hand, and in modular robotics on the other hand. In this paper we demonstrate and compare a set of bio-inspired algorithms that are used to control the collective behavior of swarms and modular systems: BEECLUST, AHHS (hormone controllers), FGRN (fractal genetic regulatory networks), and VE (virtual embryogenesis). We demonstrate how such bio-inspired control paradigms bring their host systems to a level of intermediate connectivity, what delivers sufficient robustness to these systems for collective decentralized control. In parallel, these algorithms allow sufficient volatility of shared information within these systems to help preventing local optima and deadlock situations, this way keeping those systems flexible and adaptive in dynamic non-deterministic environments. PMID:23805030
El Hag, Imad A.; Elsiddig, Kamal E.; Elsafi, Mohamed E.M.O; Elfaki, Mona E.E.; Musa, Ahmed M.; Musa, Brima Y.; Elhassan, Ahmed M.
2013-01-01
Abstract Background Tuberculosis is a major health problem in developing countries. The distinction between tuberculous lymphadenitis, non-specific lymphadenitis and malignant lymph node enlargement has to be made at primary health care levels using easy, simple and cheap methods. Objective To develop a reliable clinical algorithm for primary care settings to triage cases of non-specific, tuberculous and malignant lymphadenopathies. Methods Calculation of the odd ratios (OR) of the chosen predictor variables was carried out using logistic regression. The numerical score values of the predictor variables were weighed against their respective OR. The performance of the score was evaluated by the ROC (Receiver Operator Characteristic) curve. Results Four predictor variables; Mantoux reading, erythrocytes sedimentation rate (ESR), nocturnal fever and discharging sinuses correlated significantly with TB diagnosis and were included in the reduced model to establish score A. For score B, the reduced model included Mantoux reading, ESR, lymph-node size and lymph-node number as predictor variables for malignant lymph nodes. Score A ranged 0 to 12 and a cut-off point of 6 gave a best sensitivity and specificity of 91% and 90% respectively, whilst score B ranged -3 to 8 and a cut-off point of 3 gave a best sensitivity and specificity of 83% and 76% respectively. The calculated area under the ROC curve was 0.964 (95% CI, 0.949 – 0.980) and -0.856 (95% CI, 0.787 - 0.925) for scores A and B respectively, indicating good performance. Conclusion The developed algorithm can efficiently triage cases with tuberculous and malignant lymphadenopathies for treatment or referral to specialised centres for further work-up.
NASA Astrophysics Data System (ADS)
Alexandre, E.; Cuadra, L.; Nieto-Borge, J. C.; Candil-García, G.; del Pino, M.; Salcedo-Sanz, S.
2015-08-01
Wave parameters computed from time series measured by buoys (significant wave height Hs, mean wave period, etc.) play a key role in coastal engineering and in the design and operation of wave energy converters. Storms or navigation accidents can make measuring buoys break down, leading to missing data gaps. In this paper we tackle the problem of locally reconstructing Hs at out-of-operation buoys by using wave parameters from nearby buoys, based on the spatial correlation among values at neighboring buoy locations. The novelty of our approach for its potential application to problems in coastal engineering is twofold. On one hand, we propose a genetic algorithm hybridized with an extreme learning machine that selects, among the available wave parameters from the nearby buoys, a subset FnSP with nSP parameters that minimizes the Hs reconstruction error. On the other hand, we evaluate to what extent the selected parameters in subset FnSP are good enough in assisting other machine learning (ML) regressors (extreme learning machines, support vector machines and gaussian process regression) to reconstruct Hs. The results show that all the ML method explored achieve a good Hs reconstruction in the two different locations studied (Caribbean Sea and West Atlantic).
Anderson, Brandon M.; Collins, David
2005-10-15
We compare the failure probabilities of ensemble implementations of quantum algorithms which use pseudopure initial states, quantified by their polarization, to those of competing classical probabilistic algorithms. Specifically we consider a class algorithms which require only one bit to output the solution to problems. For large ensemble sizes, we present a general scheme to determine a critical polarization beneath which the quantum algorithm fails with greater probability than its classical competitor. We apply this to the Deutsch-Jozsa algorithm and show that the critical polarization is 86.6%.
A Genetic Algorithm for Learning Significant Phrase Patterns in Radiology Reports
Patton, Robert M; Potok, Thomas E; Beckerman, Barbara G; Treadwell, Jim N
2009-01-01
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. Recently, the focus has been on classifying abnormal or suspicious reports, but even this process needs further layers of clustering and gradation, so that individual lesions can be more effectively classified. Using a genetic algorithm, the approach described here successfully learns phrase patterns for two distinct classes of radiology reports (normal and abnormal). These patterns can then be used as a basis for automatically analyzing, categorizing, clustering, or retrieving relevant radiology reports for the user.
40 CFR 141.708 - Requirements when making a significant change in disinfection practice.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Requirements when making a significant change in disinfection practice. 141.708 Section 141.708 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Enhanced Treatment for Cryptosporidium...
Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.
1999-01-01
Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier
Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu
2016-01-01
Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed. PMID:27446945
Ishibuchi, Hisao; Sudo, Takahiko; Nojima, Yusuke
2016-01-01
In interactive evolutionary computation (IEC), each solution is evaluated by a human user. Usually the total number of examined solutions is very small. In some applications such as hearing aid design and music composition, only a single solution can be evaluated at a time by a human user. Moreover, accurate and precise numerical evaluation is difficult. Based on these considerations, we formulated an IEC model with the minimum requirement for fitness evaluation ability of human users under the following assumptions: They can evaluate only a single solution at a time, they can memorize only a single previous solution they have just evaluated, their evaluation result on the current solution is whether it is better than the previous one or not, and the best solution among the evaluated ones should be identified after a pre-specified number of evaluations. In this paper, we first explain our IEC model in detail. Next we propose a ([Formula: see text])ES-style algorithm for our IEC model. Then we propose an offline meta-level approach to automated algorithm design for our IEC model. The main feature of our approach is the use of a different mechanism (e.g., mutation, crossover, random initialization) to generate each solution to be evaluated. Through computational experiments on test problems, our approach is compared with the ([Formula: see text])ES-style algorithm where a solution generation mechanism is pre-specified and fixed throughout the execution of the algorithm. PMID:27026888
Effort required to finish shotgun-generated genome sequences differs significantly among vertebrates
2010-01-01
Background The approaches for shotgun-based sequencing of vertebrate genomes are now well-established, and have resulted in the generation of numerous draft whole-genome sequence assemblies. In contrast, the process of refining those assemblies to improve contiguity and increase accuracy (known as 'sequence finishing') remains tedious, labor-intensive, and expensive. As a result, the vast majority of vertebrate genome sequences generated to date remain at a draft stage. Results To date, our genome sequencing efforts have focused on comparative studies of targeted genomic regions, requiring sequence finishing of large blocks of orthologous sequence (average size 0.5-2 Mb) from various subsets of 75 vertebrates. This experience has provided a unique opportunity to compare the relative effort required to finish shotgun-generated genome sequence assemblies from different species, which we report here. Importantly, we found that the sequence assemblies generated for the same orthologous regions from various vertebrates show substantial variation with respect to misassemblies and, in particular, the frequency and characteristics of sequence gaps. As a consequence, the work required to finish different species' sequences varied greatly. Application of the same standardized methods for finishing provided a novel opportunity to "assay" characteristics of genome sequences among many vertebrate species. It is important to note that many of the problems we have encountered during sequence finishing reflect unique architectural features of a particular vertebrate's genome, which in some cases may have important functional and/or evolutionary implications. Finally, based on our analyses, we have been able to improve our procedures to overcome some of these problems and to increase the overall efficiency of the sequence-finishing process, although significant challenges still remain. Conclusion Our findings have important implications for the eventual finishing of the draft whole
Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 2 2010-01-01 2010-01-01 false Requirement to publish finding of no significant impact... Requirement to publish finding of no significant impact; limitation on Commission action. (a) Whenever the... published in the Federal Register as provided in § 51.119. (b) Except as provided in § 51.13, the...
Angus, Simon D.; Piotrowska, Monika Joanna
2014-01-01
Multi-dose radiotherapy protocols (fraction dose and timing) currently used in the clinic are the product of human selection based on habit, received wisdom, physician experience and intra-day patient timetabling. However, due to combinatorial considerations, the potential treatment protocol space for a given total dose or treatment length is enormous, even for relatively coarse search; well beyond the capacity of traditional in-vitro methods. In constrast, high fidelity numerical simulation of tumor development is well suited to the challenge. Building on our previous single-dose numerical simulation model of EMT6/Ro spheroids, a multi-dose irradiation response module is added and calibrated to the effective dose arising from 18 independent multi-dose treatment programs available in the experimental literature. With the developed model a constrained, non-linear, search for better performing cadidate protocols is conducted within the vicinity of two benchmarks by genetic algorithm (GA) techniques. After evaluating less than 0.01% of the potential benchmark protocol space, candidate protocols were identified by the GA which conferred an average of 9.4% (max benefit 16.5%) and 7.1% (13.3%) improvement (reduction) on tumour cell count compared to the two benchmarks, respectively. Noticing that a convergent phenomenon of the top performing protocols was their temporal synchronicity, a further series of numerical experiments was conducted with periodic time-gap protocols (10 h to 23 h), leading to the discovery that the performance of the GA search candidates could be replicated by 17–18 h periodic candidates. Further dynamic irradiation-response cell-phase analysis revealed that such periodicity cohered with latent EMT6/Ro cell-phase temporal patterning. Taken together, this study provides powerful evidence towards the hypothesis that even simple inter-fraction timing variations for a given fractional dose program may present a facile, and highly cost
40 CFR 141.708 - Requirements when making a significant change in disinfection practice.
Code of Federal Regulations, 2010 CFR
2010-07-01
... PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Enhanced... source water monitoring under § 141.701(a), a system that plans to make a significant change to...
Code of Federal Regulations, 2011 CFR
2011-04-01
... 26 Internal Revenue 17 2011-04-01 2011-04-01 false Notice requirements for certain pension plan... (CONTINUED) PENSION EXCISE TAXES § 54.4980F-1 Notice requirements for certain pension plan amendments... a plan amendment of an applicable pension plan that significantly reduces the rate of future...
Architectural and Algorithmic Requirements for a Next-Generation System Analysis Code
V.A. Mousseau
2010-05-01
This document presents high-level architectural and system requirements for a next-generation system analysis code (NGSAC) to support reactor safety decision-making by plant operators and others, especially in the context of light water reactor plant life extension. The capabilities of NGSAC will be different from those of current-generation codes, not only because computers have evolved significantly in the generations since the current paradigm was first implemented, but because the decision-making processes that need the support of next-generation codes are very different from the decision-making processes that drove the licensing and design of the current fleet of commercial nuclear power reactors. The implications of these newer decision-making processes for NGSAC requirements are discussed, and resulting top-level goals for the NGSAC are formulated. From these goals, the general architectural and system requirements for the NGSAC are derived.
Enhancements of evolutionary algorithm for the complex requirements of a nurse scheduling problem
NASA Astrophysics Data System (ADS)
Tein, Lim Huai; Ramli, Razamin
2014-12-01
Over the years, nurse scheduling is a noticeable problem that is affected by the global nurse turnover crisis. The more nurses are unsatisfied with their working environment the more severe the condition or implication they tend to leave. Therefore, the current undesirable work schedule is partly due to that working condition. Basically, there is a lack of complimentary requirement between the head nurse's liability and the nurses' need. In particular, subject to highly nurse preferences issue, the sophisticated challenge of doing nurse scheduling is failure to stimulate tolerance behavior between both parties during shifts assignment in real working scenarios. Inevitably, the flexibility in shifts assignment is hard to achieve for the sake of satisfying nurse diverse requests with upholding imperative nurse ward coverage. Hence, Evolutionary Algorithm (EA) is proposed to cater for this complexity in a nurse scheduling problem (NSP). The restriction of EA is discussed and thus, enhancement on the EA operators is suggested so that the EA would have the characteristic of a flexible search. This paper consists of three types of constraints which are the hard, semi-hard and soft constraints that can be handled by the EA with enhanced parent selection and specialized mutation operators. These operators and EA as a whole contribute to the efficiency of constraint handling, fitness computation as well as flexibility in the search, which correspond to the employment of exploration and exploitation principles.
Johnson, V.M.; Rogers, L.L.
1994-09-01
A goal common to both the environmental and petroleum industries is the reduction of costs and/or enhancement of profits by the optimal placement of extraction/production and injection wells. Formal optimization techniques facilitate this goal by searching among the potentially infinite number of possible well patterns for ones that best meet engineering and economic objectives. However, if a flow and transport model or reservoir simulator is being used to evaluate the effectiveness of each network of wells, the computational resources required to apply most optimization techniques to real field problems become prohibitively expensive. This paper describes a new approach to field-scale, nonlinear optimization of well patterns that is intended to make such searches tractable on conventional computer equipment. Artificial neural networks (ANNs) are trained to predict selected information that would normally be calculated by the simulator. The ANNs are then embedded in a variant of the genetic algorithm (GA), which drives the search for increasingly effective well patterns and uses the ANNs, rather than the original simulator, to evaluate the effectiveness of each pattern. Once the search is complete, the ANNs are reused in sensitivity studies to give additional information on the performance of individual or clusters of wells.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 26 Internal Revenue 17 2013-04-01 2013-04-01 false Notice requirements for certain pension plan amendments significantly reducing the rate of future benefit accrual. 54.4980F-1 Section 54.4980F-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES (CONTINUED) PENSION EXCISE TAXES §...
NASA Astrophysics Data System (ADS)
Zhao, Wei; Niu, Tianye; Xing, Lei; Xie, Yaoqin; Xiong, Guanglei; Elmore, Kimberly; Zhu, Jun; Wang, Luyao; Min, James K.
2016-02-01
Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from 11× 11 to 19× 19 , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.
An algorithm for reducing storage requirements in computer calculation of chemical equilibria.
Tripathi, V S
1983-01-01
An algorithm for storage of stoichiometric coefficients of the possible complexes and solids in a multi-component system of metals and ligands is described, along with FORTRAN code for its implementation. The proposed algorithm results in considerable saving in storage over the conventional use of a two-dimensional array. The saving in storage is especially useful for microcomputers, and for very large problems such as those encountered in geochemical calculations. PMID:18963319
The maximum depth of colonization (Zc) is a useful measure of seagrass growth that describes response to light attenuation in the water column. However, lack of standardization among methods for estimating Zc has limited the description of habitat requirements at spatial scales m...
Semioptimal practicable algorithmic cooling
Elias, Yuval; Mor, Tal; Weinstein, Yossi
2011-04-15
Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon's entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.
NASA Technical Reports Server (NTRS)
Heyward, Ann O.; Reilly, Charles H.; Walton, Eric K.; Mata, Fernando; Olen, Carl
1990-01-01
Creation of an Allotment Plan for the Fixed Satellite Service at the 1988 Space World Administrative Radio Conference (WARC) represented a complex satellite plan synthesis problem, involving a large number of planned and existing systems. Solutions to this problem at WARC-88 required the use of both automated and manual procedures to develop an acceptable set of system positions. Development of an Allotment Plan may also be attempted through solution of an optimization problem, known as the Satellite Location Problem (SLP). Three automated heuristic procedures, developed specifically to solve SLP, are presented. The heuristics are then applied to two specific WARC-88 scenarios. Solutions resulting from the fully automated heuristics are then compared with solutions obtained at WARC-88 through a combination of both automated and manual planning efforts.
Code of Federal Regulations, 2010 CFR
2010-04-01
... information is required to be provided in a section 204(h) notice? Q-12. What special rules apply if... information is required to be provided in a section 204(h) notice? A-11. (a) Explanation of notice requirements—(1) In general. Section 204(h) notice must include sufficient information to allow...
Code of Federal Regulations, 2011 CFR
2011-07-01
... facilities at 40 CFR part 112, appendix C, Attachment C-III may be substituted for the distances listed in... the first valve inside the secondary containment required by 40 CFR part 112. (iv) The appendix must... in bulk. A material safety data sheet meeting the requirements of 29 CFR 1910.1200, 33 CFR...
Code of Federal Regulations, 2014 CFR
2014-07-01
... facilities at 40 CFR part 112, appendix C, Attachment C-III may be substituted for the distances listed in... the first valve inside the secondary containment required by 40 CFR part 112. (iv) The appendix must... in bulk. A material safety data sheet meeting the requirements of 29 CFR 1910.1200, 33 CFR...
Code of Federal Regulations, 2013 CFR
2013-07-01
... facilities at 40 CFR part 112, appendix C, Attachment C-III may be substituted for the distances listed in... the first valve inside the secondary containment required by 40 CFR part 112. (iv) The appendix must... in bulk. A material safety data sheet meeting the requirements of 29 CFR 1910.1200, 33 CFR...
Code of Federal Regulations, 2010 CFR
2010-07-01
... facilities at 40 CFR part 112, appendix C, Attachment C-III may be substituted for the distances listed in... the first valve inside the secondary containment required by 40 CFR part 112. (iv) The appendix must... in bulk. A material safety data sheet meeting the requirements of 29 CFR 1910.1200, 33 CFR...
Code of Federal Regulations, 2012 CFR
2012-07-01
... facilities at 40 CFR part 112, appendix C, Attachment C-III may be substituted for the distances listed in... the first valve inside the secondary containment required by 40 CFR part 112. (iv) The appendix must... in bulk. A material safety data sheet meeting the requirements of 29 CFR 1910.1200, 33 CFR...
NASA Astrophysics Data System (ADS)
Cook, K. A.; Albano, F.; Nevius, P. E.; Sastry, A. M.
We have expanded and implemented an algorithm for selecting power supplies into a turnkey MATLAB code, "POWER" (power optimization for wireless energy requirements). Our algorithm uses three approaches to system design, specifying either: (1) a single, aggregate power profile; (2) a power system designed to satisfy several power ranges (micro-, milli- and Watt); or (3) a power system designed to be housed within specified spaces within the system. POWER was verified by conducting two case studies on hearing prosthetics: the TICA (LZ 3001) (Baumann group at the Tübingen University) and Amadeus cochlear implant (CI) (WIMS-ERC at the University of Michigan) based on a volume constraint of 2 cm 3. The most suitable solution identified by POWER for the TICA device came from Approach 1, wherein one secondary cell provided 26,000 cycles of 16 h operation. POWER identified Approach 2 as the solution for the WIMS-ERC Amadeus CI, which consisted of 1 cell for the microWatt power range and 1 cell for the milliWatt range (4.43 cm 3, ∼55% higher than the target volume), and provided 3280 cycles of 16 h operation (including re-charge of the batteries). Future work will be focused on continuously improving our present tool.
Code of Federal Regulations, 2014 CFR
2014-04-01
... amendments significantly reducing the rate of future benefit accrual. 54.4980F-1 Section 54.4980F-1 Internal... significantly reducing the rate of future benefit accrual. The following questions and answers concern the... a plan amendment of an applicable pension plan that significantly reduces the rate of future...
Hummel, H E; Eisinger, M T; Hein, D F; Breuer, M; Schmid, S; Leithold, G
2012-01-01
Pheromone effects discovered some 130 years, but scientifically defined just half a century ago, are a great bonus for basic and applied biology. Specifically, pest management efforts have been advanced in many insect orders, either for purposes or monitoring, mass trapping, or for mating disruption. Finding and applying a new search algorithm, nearly 20,000 entries in the pheromone literature have been counted, a number much higher than originally anticipated. This compilation contains identified and thus synthesizable structures for all major orders of insects. Among them are hundreds of agriculturally significant insect pests whose aggregated damages and costly control measures range in the multibillions of dollars annually. Unfortunately, and despite a lot of effort within the international entomological scene, the number of efficient and cheap engineering solutions for dispensing pheromones under variable field conditions is uncomfortably lagging behind. Some innovative approaches are cited from the relevant literature in an attempt to rectify this situation. Recently, specifically designed electrospun organic nanofibers offer a lot of promise. With their use, the mating communication of vineyard insects like Lobesia botrana (Lep.: Tortricidae) can be disrupted for periods of seven weeks. PMID:23885431
Code of Federal Regulations, 2012 CFR
2012-04-01
... accrual or that eliminates or significantly reduces an early retirement benefit or retirement-type subsidy... or reduces an early retirement benefit or retirement-type subsidy for purposes of determining whether... retirement-type subsidy is significant for purposes of section 4980F and section 204(h)? Q-9. When...
NASA Technical Reports Server (NTRS)
Hinchey, Michael G. (Inventor); Margaria, Tiziana (Inventor); Rash, James L. (Inventor); Rouff, Christopher A. (Inventor); Steffen, Bernard (Inventor)
2010-01-01
Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.
Stevens, Bonnie J; Nathan, Paul C; Seto, Emily; Cafazzo, Joseph A; Stinson, Jennifer N
2014-01-01
Background Pain that occurs both within and outside of the hospital setting is a common and distressing problem for adolescents with cancer. The use of smartphone technology may facilitate rapid, in-the-moment pain support for this population. To ensure the best possible pain management advice is given, evidence-based and expert-vetted care algorithms and system design features, which are designed using user-centered methods, are required. Objective To develop the decision algorithm and system requirements that will inform the pain management advice provided by a real-time smartphone-based pain management app for adolescents with cancer. Methods A systematic approach to algorithm development and system design was utilized. Initially, a comprehensive literature review was undertaken to understand the current body of knowledge pertaining to pediatric cancer pain management. A user-centered approach to development was used as the results of the review were disseminated to 15 international experts (clinicians, scientists, and a consumer) in pediatric pain, pediatric oncology and mHealth design, who participated in a 2-day consensus conference. This conference used nominal group technique to develop consensus on important pain inputs, pain management advice, and system design requirements. Using data generated at the conference, a prototype algorithm was developed. Iterative qualitative testing was conducted with adolescents with cancer, as well as pediatric oncology and pain health care providers to vet and refine the developed algorithm and system requirements for the real-time smartphone app. Results The systematic literature review established the current state of research related to nonpharmacological pediatric cancer pain management. The 2-day consensus conference established which clinically important pain inputs by adolescents would require action (pain management advice) from the app, the appropriate advice the app should provide to adolescents in pain, and the
Code of Federal Regulations, 2014 CFR
2014-07-01
... EPA. (a) A sanitary survey is an onsite review of the water source (identifying sources of... deficiency includes a defect in design, operation, or maintenance, or a failure or malfunction of the sources... performed by EPA, systems must respond in writing to significant deficiencies identified in sanitary...
Code of Federal Regulations, 2012 CFR
2012-07-01
... EPA. (a) A sanitary survey is an onsite review of the water source (identifying sources of... deficiency includes a defect in design, operation, or maintenance, or a failure or malfunction of the sources... performed by EPA, systems must respond in writing to significant deficiencies identified in sanitary...
Code of Federal Regulations, 2013 CFR
2013-07-01
... EPA. (a) A sanitary survey is an onsite review of the water source (identifying sources of... deficiency includes a defect in design, operation, or maintenance, or a failure or malfunction of the sources... performed by EPA, systems must respond in writing to significant deficiencies identified in sanitary...
NASA Technical Reports Server (NTRS)
1975-01-01
Energy consumption in the United States has risen in response to both increasing population and to increasing levels of affluence. Depletion of domestic energy reserves requires consumption modulation, production of fossil fuels, more efficient conversion techniques, and large scale transitions to non-fossile fuel energy sources. Widening disparity between the wealthy and poor nations of the world contributes to trends that increase the likelihood of group action by the lesser developed countries to achieve political and economic goals. The formation of anticartel cartels is envisioned.
Neptune, R R; Zajac, F E; Kautz, S A
2004-06-01
Inverted pendulum models of walking predict that little muscle work is required for the exchange of body potential and kinetic energy in single-limb support. External power during walking (product of the measured ground reaction force and body center-of-mass (COM) velocity) is often analyzed to deduce net work output or mechanical energetic cost by muscles. Based on external power analyses and inverted pendulum theory, it has been suggested that a primary mechanical energetic cost may be associated with the mechanical work required to redirect the COM motion at the step-to-step transition. However, these models do not capture the multi-muscle, multi-segmental properties of walking, co-excitation of muscles to coordinate segmental energetic flow, and simultaneous production of positive and negative muscle work. In this study, a muscle-actuated forward dynamic simulation of walking was used to assess whether: (1). potential and kinetic energy of the body are exchanged with little muscle work; (2). external mechanical power can estimate the mechanical energetic cost for muscles; and (3.) the net work output and the mechanical energetic cost for muscles occurs mostly in double support. We found that the net work output by muscles cannot be estimated from external power and was the highest when the COM moved upward in early single-limb support even though kinetic and potential energy were exchanged, and muscle mechanical (and most likely metabolic) energetic cost is dominated not only by the need to redirect the COM in double support but also by the need to raise the COM in single support. PMID:15111069
NASA Technical Reports Server (NTRS)
Rogers, David
1991-01-01
G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
NASA Astrophysics Data System (ADS)
Wood, Christopher J.; Spekkens, Robert W.
2015-03-01
An active area of research in the fields of machine learning and statistics is the development of causal discovery algorithms, the purpose of which is to infer the causal relations that hold among a set of variables from the correlations that these exhibit . We apply some of these algorithms to the correlations that arise for entangled quantum systems. We show that they cannot distinguish correlations that satisfy Bell inequalities from correlations that violate Bell inequalities, and consequently that they cannot do justice to the challenges of explaining certain quantum correlations causally. Nonetheless, by adapting the conceptual tools of causal inference, we can show that any attempt to provide a causal explanation of nonsignalling correlations that violate a Bell inequality must contradict a core principle of these algorithms, namely, that an observed statistical independence between variables should not be explained by fine-tuning of the causal parameters. In particular, we demonstrate the need for such fine-tuning for most of the causal mechanisms that have been proposed to underlie Bell correlations, including superluminal causal influences, superdeterminism (that is, a denial of freedom of choice of settings), and retrocausal influences which do not introduce causal cycles.
Klein, Kimberly
2010-01-01
The American Recovery and Reinvestment Act of 2009 (ARRA) has set forth legislation for the healthcare community to achieve adoption of electronic health records (EHR), as well as form data standards, health information exchanges (HIE) and compliance with more stringent security and privacy controls under the HITECH Act. While the Office of the National Coordinator for Health Information Technology (ONCHIT) works on the definition of both "meaningful use" and "certification" of information technology systems, providers in particular must move forward with their IT initiatives to achieve the basic requirements for Medicare and Medicaid incentives starting in 2011, and avoid penalties that will reduce reimbursement beginning in 2015. In addition, providers, payors, government and non-government stakeholders will all have to balance the implementation of EHRs, working with HIEs, at the same time that they must upgrade their systems to be in compliance with ICD-10 and HIPAA 5010 code sets. Compliance deadlines for EHRs and HIEs begin in 2011, while ICD-10 diagnosis and procedure code sets compliance is required by October 2013 and HIPAA 5010 transaction sets, with one exception, is required by January 1, 2012. In order to accomplish these strategic and mandatory initiatives successfully and simultaneously, healthcare organizations will require significant and thoughtful planning, prioritization and execution. PMID:20077923
NASA Technical Reports Server (NTRS)
Lu, Yun-Chi; Chang, Hyo Duck; Krupp, Brian; Kumar, Ravindar; Swaroop, Anand
1992-01-01
Volume 3 assists Earth Observing System (EOS) investigators in locating required non-EOS data products by identifying their non-EOS input requirements and providing the information on data sets available at various Distributed Active Archive Centers (DAAC's), including those from Pathfinder Activities and Earth Probes. Volume 3 is intended to complement, not to duplicate, the the EOSDIS Science Data Plan (SDP) by providing detailed data set information which was not presented in the SDP. Section 9 of this volume discusses the algorithm summary tables containing information on retrieval algorithms, expected outputs and required input data. Section 10 describes the non-EOS input requirements of instrument teams and IDS investigators. Also described are the current and future data holdings of the original seven DAACS and data products planned from the future missions and projects including Earth Probes and Pathfinder Activities. Section 11 describes source of information used in compiling data set information presented in this volume. A list of data set attributes used to describe various data sets is presented in section 12 along with their descriptions. Finally, Section 13 presents the SPSO's future plan to improve this report .
NASA Astrophysics Data System (ADS)
Abrams, Daniel S.
This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases (commonly found in ab initio physics and chemistry problems) for which all known classical algorithms require exponential time. Fast algorithms for simulating many body Fermi systems are also provided in both first and second quantized descriptions. An efficient quantum algorithm for anti-symmetrization is given as well as a detailed discussion of a simulation of the Hubbard model. In addition, quantum algorithms that calculate numerical integrals and various characteristics of stochastic processes are described. Two techniques are given, both of which obtain an exponential speed increase in comparison to the fastest known classical deterministic algorithms and a quadratic speed increase in comparison to classical Monte Carlo (probabilistic) methods. I derive a simpler and slightly faster version of Grover's mean algorithm, show how to apply quantum counting to the problem, develop some variations of these algorithms, and show how both (apparently distinct) approaches can be understood from the same unified framework. Finally, the relationship between physics and computation is explored in some more depth, and it is shown that computational complexity theory depends very sensitively on physical laws. In particular, it is shown that nonlinear quantum mechanics allows for the polynomial time solution of NP-complete and #P oracle problems. Using the Weinberg model as a simple example, the explicit construction of the necessary gates is derived from the underlying physics. Nonlinear quantum algorithms are also presented using Polchinski type nonlinearities which do not allow for superluminal communication. (Copies available exclusively from MIT Libraries, Rm. 14- 0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
NASA Astrophysics Data System (ADS)
Coudarcher, Rémi; Duculty, Florent; Serot, Jocelyn; Jurie, Frédéric; Derutin, Jean-Pierre; Dhome, Michel
2005-12-01
SKiPPER is a SKeleton-based Parallel Programming EnviRonment being developed since 1996 and running at LASMEA Laboratory, the Blaise-Pascal University, France. The main goal of the project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This paper deals with the special features embedded in the latest version of the project: algorithmic skeleton nesting capabilities and a fully dynamic operating model. Throughout the case study of a complete and realistic image processing application, in which we have pointed out the requirement for skeleton nesting, we are presenting the operating model of this feature. The work described here is one of the few reported experiments showing the application of skeleton nesting facilities for the parallelisation of a realistic application, especially in the area of image processing. The image processing application we have chosen is a 3D face-tracking algorithm from appearance.
Fast decoding algorithms for coded aperture systems
NASA Astrophysics Data System (ADS)
Byard, Kevin
2014-08-01
Fast decoding algorithms are described for a number of established coded aperture systems. The fast decoding algorithms for all these systems offer significant reductions in the number of calculations required when reconstructing images formed by a coded aperture system and hence require less computation time to produce the images. The algorithms may therefore be of use in applications that require fast image reconstruction, such as near real-time nuclear medicine and location of hazardous radioactive spillage. Experimental tests confirm the efficacy of the fast decoding techniques.
NASA Astrophysics Data System (ADS)
D'Antona, G.; Cirant, S.; Farina, D.; Gandini, F.; Lazzaro, E.; Treuterer, W.; Manini, A.
2008-03-01
The diagnostics requirements for the control of NTM instabilities is outlined stressing the importance of correctly managing the estimate uncertainty by the control system. A methodology for the Bayesian assimilation of model predictions and observations is outlined together with an example of application.
D' Antona, G.; Cirant, S.; Farina, D.; Gandini, F.; Lazzaro, E.; Treuterer, W.; Manini, A.
2008-03-12
The diagnostics requirements for the control of NTM instabilities is outlined stressing the importance of correctly managing the estimate uncertainty by the control system. A methodology for the Bayesian assimilation of model predictions and observations is outlined together with an example of application.
Garcia-Rivera, Jose A; Bobardt, Michael; Chatterji, Udayan; Hopkins, Sam; Gregory, Matthew A; Wilkinson, Barrie; Lin, Kai; Gallay, Philippe A
2012-10-01
Alisporivir is the most advanced host-targeting antiviral cyclophilin (Cyp) inhibitor in phase III studies and has demonstrated a great deal of promise in decreasing hepatitis C virus (HCV) viremia in infected patients. In an attempt to further elucidate the mechanism of action of alisporivir, HCV replicons resistant to the drug were selected. Interestingly, mutations constantly arose in domain II of NS5A. To demonstrate that these mutations are responsible for drug resistance, they were reintroduced into the parental HCV genome, and the resulting mutant viruses were tested for replication in the presence of alisporivir or in the absence of the alisporivir target, CypA. We also examined the effect of the mutations on NS5A binding to itself (oligomerization), CypA, RNA, and NS5B. Importantly, the mutations did not affect any of these interactions. Moreover, the mutations did not preserve NS5A-CypA interactions from alisporivir rupture. NS5A mutations alone render HCV only slightly resistant to alisporivir. In sharp contrast, when multiple NS5A mutations are combined, significant resistance was observed. The introduction of multiple mutations in NS5A significantly restored viral replication in CypA knockdown cells. Interestingly, the combination of NS5A mutations renders HCV resistant to all classes of Cyp inhibitors. This study suggests that a combination of multiple mutations in domain II of NS5A rather than a single mutation is required to render HCV significantly and universally resistant to Cyp inhibitors. This in accordance with in vivo data that suggest that alisporivir is associated with a low potential for development of viral resistance. PMID:22802259
A new frame-based registration algorithm.
Yan, C H; Whalen, R T; Beaupre, G S; Sumanaweera, T S; Yen, S Y; Napel, S
1998-01-01
This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required. PMID:9472834
A new frame-based registration algorithm
NASA Technical Reports Server (NTRS)
Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Sumanaweera, T. S.; Yen, S. Y.; Napel, S.
1998-01-01
This paper presents a new algorithm for frame registration. Our algorithm requires only that the frame be comprised of straight rods, as opposed to the N structures or an accurate frame model required by existing algorithms. The algorithm utilizes the full 3D information in the frame as well as a least squares weighting scheme to achieve highly accurate registration. We use simulated CT data to assess the accuracy of our algorithm. We compare the performance of the proposed algorithm to two commonly used algorithms. Simulation results show that the proposed algorithm is comparable to the best existing techniques with knowledge of the exact mathematical frame model. For CT data corrupted with an unknown in-plane rotation or translation, the proposed technique is also comparable to the best existing techniques. However, in situations where there is a discrepancy of more than 2 mm (0.7% of the frame dimension) between the frame and the mathematical model, the proposed technique is significantly better (p < or = 0.05) than the existing techniques. The proposed algorithm can be applied to any existing frame without modification. It provides better registration accuracy and is robust against model mis-match. It allows greater flexibility on the frame structure. Lastly, it reduces the frame construction cost as adherence to a concise model is not required.
Algorithms for improved performance in cryptographic protocols.
Schroeppel, Richard Crabtree; Beaver, Cheryl Lynn
2003-11-01
Public key cryptographic algorithms provide data authentication and non-repudiation for electronic transmissions. The mathematical nature of the algorithms, however, means they require a significant amount of computation, and encrypted messages and digital signatures possess high bandwidth. Accordingly, there are many environments (e.g. wireless, ad-hoc, remote sensing networks) where public-key requirements are prohibitive and cannot be used. The use of elliptic curves in public-key computations has provided a means by which computations and bandwidth can be somewhat reduced. We report here on the research conducted in an LDRD aimed to find even more efficient algorithms and to make public-key cryptography available to a wider range of computing environments. We improved upon several algorithms, including one for which a patent has been applied. Further we discovered some new problems and relations on which future cryptographic algorithms may be based.
NASA Astrophysics Data System (ADS)
Huang, Xiaobiao; Safranek, James
2014-09-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.
Improved Bat Algorithm Applied to Multilevel Image Thresholding
2014-01-01
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
Improved bat algorithm applied to multilevel image thresholding.
Alihodzic, Adis; Tuba, Milan
2014-01-01
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
Ali, Imad; Ahmad, Salahuddin
2013-10-01
To compare the doses calculated using the BrainLAB pencil beam (PB) and Monte Carlo (MC) algorithms for tumors located in various sites including the lung and evaluate quality assurance procedures required for the verification of the accuracy of dose calculation. The dose-calculation accuracy of PB and MC was also assessed quantitatively with measurement using ionization chamber and Gafchromic films placed in solid water and heterogeneous phantoms. The dose was calculated using PB convolution and MC algorithms in the iPlan treatment planning system from BrainLAB. The dose calculation was performed on the patient's computed tomography images with lesions in various treatment sites including 5 lungs, 5 prostates, 4 brains, 2 head and necks, and 2 paraspinal tissues. A combination of conventional, conformal, and intensity-modulated radiation therapy plans was used in dose calculation. The leaf sequence from intensity-modulated radiation therapy plans or beam shapes from conformal plans and monitor units and other planning parameters calculated by the PB were identical for calculating dose with MC. Heterogeneity correction was considered in both PB and MC dose calculations. Dose-volume parameters such as V95 (volume covered by 95% of prescription dose), dose distributions, and gamma analysis were used to evaluate the calculated dose by PB and MC. The measured doses by ionization chamber and EBT GAFCHROMIC film in solid water and heterogeneous phantoms were used to quantitatively asses the accuracy of dose calculated by PB and MC. The dose-volume histograms and dose distributions calculated by PB and MC in the brain, prostate, paraspinal, and head and neck were in good agreement with one another (within 5%) and provided acceptable planning target volume coverage. However, dose distributions of the patients with lung cancer had large discrepancies. For a plan optimized with PB, the dose coverage was shown as clinically acceptable, whereas in reality, the MC showed a
Barzilai-Borwein method in graph drawing algorithm based on Kamada-Kawai algorithm
NASA Astrophysics Data System (ADS)
Hasal, Martin; Pospisil, Lukas; Nowakova, Jana
2016-06-01
Extension of Kamada-Kawai algorithm, which was designed for calculating layouts of simple undirected graphs, is presented in this paper. Graphs drawn by Kamada-Kawai algorithm exhibit symmetries, tend to produce aesthetically pleasing and crossing-free layouts for planar graphs. Minimization of Kamada-Kawai algorithm is based on Newton-Raphson method, which needs Hessian matrix of second derivatives of minimized node. Disadvantage of Kamada-Kawai embedder algorithm is computational requirements. This is caused by searching of minimal potential energy of the whole system, which is minimized node by node. The node with highest energy is minimized against all nodes till the local equilibrium state is reached. In this paper with Barzilai-Borwein (BB) minimization algorithm, which needs only gradient for minimum searching, instead of Newton-Raphson method, is worked. It significantly improves the computational time and requirements.
Acceleration of iterative image restoration algorithms.
Biggs, D S; Andrews, M
1997-03-10
A new technique for the acceleration of iterative image restoration algorithms is proposed. The method is based on the principles of vector extrapolation and does not require the minimization of a cost function. The algorithm is derived and its performance illustrated with Richardson-Lucy (R-L) and maximum entropy (ME) deconvolution algorithms and the Gerchberg-Saxton magnitude and phase retrieval algorithms. Considerable reduction in restoration times is achieved with little image distortion or computational overhead per iteration. The speedup achieved is shown to increase with the number of iterations performed and is easily adapted to suit different algorithms. An example R-L restoration achieves an average speedup of 40 times after 250 iterations and an ME method 20 times after only 50 iterations. An expression for estimating the acceleration factor is derived and confirmed experimentally. Comparisons with other acceleration techniques in the literature reveal significant improvements in speed and stability. PMID:18250863
Mapping algorithms on regular parallel architectures
Lee, P.
1989-01-01
It is significant that many of time-intensive scientific algorithms are formulated as nested loops, which are inherently regularly structured. In this dissertation the relations between the mathematical structure of nested loop algorithms and the architectural capabilities required for their parallel execution are studied. The architectural model considered in depth is that of an arbitrary dimensional systolic array. The mathematical structure of the algorithm is characterized by classifying its data-dependence vectors according to the new ZERO-ONE-INFINITE property introduced. Using this classification, the first complete set of necessary and sufficient conditions for correct transformation of a nested loop algorithm onto a given systolic array of an arbitrary dimension by means of linear mappings is derived. Practical methods to derive optimal or suboptimal systolic array implementations are also provided. The techniques developed are used constructively to develop families of implementations satisfying various optimization criteria and to design programmable arrays efficiently executing classes of algorithms. In addition, a Computer-Aided Design system running on SUN workstations has been implemented to help in the design. The methodology, which deals with general algorithms, is illustrated by synthesizing linear and planar systolic array algorithms for matrix multiplication, a reindexed Warshall-Floyd transitive closure algorithm, and the longest common subsequence algorithm.
Overview of an Algorithm Plugin Package (APP)
NASA Astrophysics Data System (ADS)
Linda, M.; Tilmes, C.; Fleig, A. J.
2004-12-01
Science software that runs operationally is fundamentally different than software that runs on a scientist's desktop. There are complexities in hosting software for automated production that are necessary and significant. Identifying common aspects of these complexities can simplify algorithm integration. We use NASA's MODIS and OMI data production systems as examples. An Algorithm Plugin Package (APP) is science software that is combined with algorithm-unique elements that permit the algorithm to interface with, and function within, the framework of a data processing system. The framework runs algorithms operationally against large quantities of data. The extra algorithm-unique items are constrained by the design of the data processing system. APPs often include infrastructure that is vastly similar. When the common elements in APPs are identified and abstracted, the cost of APP development, testing, and maintenance will be reduced. This paper is an overview of the extra algorithm-unique pieces that are shared between MODAPS and OMIDAPS APPs. Our exploration of APP structure will help builders of other production systems identify their common elements and reduce algorithm integration costs. Our goal is to complete the development of a library of functions and a menu of implementation choices that reflect common needs of APPs. The library and menu will reduce the time and energy required for science developers to integrate algorithms into production systems.
ERIC Educational Resources Information Center
Andrews, Ian A.
1999-01-01
Provides a crossword puzzle with an answer key corresponding to the book entitled "Significant Treasures/Tresors Parlants" that is filled with color and black-and-white prints of paintings and artifacts from 131 museums and art galleries as a sampling of the 2,200 such Canadian institutions. (CMK)
NASA Technical Reports Server (NTRS)
Herman, G. C.
1986-01-01
A lateral guidance algorithm which controls the location of the line of intersection between the actual and desired orbital planes (the hinge line) is developed for the aerobraking phase of a lift-modulated orbital transfer vehicle. The on-board targeting algorithm associated with this lateral guidance algorithm is simple and concise which is very desirable since computation time and space are limited on an on-board flight computer. A variational equation which describes the movement of the hinge line is derived. Simple relationships between the plane error, the desired hinge line position, the position out-of-plane error, and the velocity out-of-plane error are found. A computer simulation is developed to test the lateral guidance algorithm for a variety of operating conditions. The algorithm does reduce the total burn magnitude needed to achieve the desired orbit by allowing the plane correction and perigee-raising burn to be combined in a single maneuver. The algorithm performs well under vacuum perigee dispersions, pot-hole density disturbance, and thick atmospheres. The results for many different operating conditions are presented.
Romesser, Paul B.; Cahlon, Oren; Scher, Eli; Zhou, Ying; Berry, Sean L.; Rybkin, Alisa; Sine, Kevin M.; Tang, Shikui; Sherman, Eric J.; Wong, Richard; Lee, Nancy Y.
2016-01-01
Background As proton beam radiation therapy (PBRT) may allow greater normal tissue sparing when compared with intensity-modulated radiation therapy (IMRT), we compared the dosimetry and treatment-related toxicities between patients treated to the ipsilateral head and neck with either PBRT or IMRT. Methods Between 01/2011 and 03/2014, 41 consecutive patients underwent ipsilateral irradiation for major salivary gland cancer or cutaneous squamous cell carcinoma. The availability of PBRT, during this period, resulted in an immediate shift in practice from IMRT to PBRT, without any change in target delineation. Acute toxicities were assessed using the National Cancer Institute Common Terminology Criteria for Adverse Events version 4.0. Results Twenty-three (56.1%) patients were treated with IMRT and 18 (43.9%) with PBRT. The groups were balanced in terms of baseline, treatment, and target volume characteristics. IMRT plans had a greater median maximum brainstem (29.7 Gy vs. 0.62 Gy (RBE), P < 0.001), maximum spinal cord (36.3 Gy vs. 1.88 Gy (RBE), P < 0.001), mean oral cavity (20.6 Gy vs. 0.94 Gy (RBE), P < 0.001), mean contralateral parotid (1.4 Gy vs. 0.0 Gy (RBE), P < 0.001), and mean contralateral submandibular (4.1 Gy vs. 0.0 Gy (RBE), P < 0.001) dose when compared to PBRT plans. PBRT had significantly lower rates of grade 2 or greater acute dysgeusia (5.6% vs. 65.2%, P < 0.001), mucositis (16.7% vs. 52.2%, P = 0.019), and nausea (11.1% vs. 56.5%, P = 0.003). Conclusions The unique properties of PBRT allow greater normal tissue sparing without sacrificing target coverage when irradiating the ipsilateral head and neck. This dosimetric advantage seemingly translates into lower rates of acute treatment-related toxicity. PMID:26867969
Advanced Imaging Algorithms for Radiation Imaging Systems
Marleau, Peter
2015-10-01
The intent of the proposed work, in collaboration with University of Michigan, is to develop the algorithms that will bring the analysis from qualitative images to quantitative attributes of objects containing SNM. The first step to achieving this is to develop an indepth understanding of the intrinsic errors associated with the deconvolution and MLEM algorithms. A significant new effort will be undertaken to relate the image data to a posited three-dimensional model of geometric primitives that can be adjusted to get the best fit. In this way, parameters of the model such as sizes, shapes, and masses can be extracted for both radioactive and non-radioactive materials. This model-based algorithm will need the integrated response of a hypothesized configuration of material to be calculated many times. As such, both the MLEM and the model-based algorithm require significant increases in calculation speed in order to converge to solutions in practical amounts of time.
Improved local linearization algorithm for solving the quaternion equations
NASA Technical Reports Server (NTRS)
Yen, K.; Cook, G.
1980-01-01
The objective of this paper is to develop a new and more accurate local linearization algorithm for numerically solving sets of linear time-varying differential equations. Of special interest is the application of this algorithm to the quaternion rate equations. The results are compared, both analytically and experimentally, with previous results using local linearization methods. The new algorithm requires approximately one-third more calculations per step than the previously developed local linearization algorithm; however, this disadvantage could be reduced by using parallel implementation. For some cases the new algorithm yields significant improvement in accuracy, even with an enlarged sampling interval. The reverse is true in other cases. The errors depend on the values of angular velocity, angular acceleration, and integration step size. One important result is that for the worst case the new algorithm can guarantee eigenvalues nearer the region of stability than can the previously developed algorithm.
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.
Reference Materials: Significance, General Requirements, and Demand.
Kiełbasa, Anna; Gadzała-Kopciuch, Renata; Buszewski, Bogusław
2016-05-01
Reference materials play an important part in the quality control of measurements. Rapid development of such new scientific disciplines as proteomics, metabolomics, and genomics also necessitates development of new reference materials. This is a great challenge due to the complexity of the production of new reference materials and difficulties associated with achieving their homogeneity and stability. CRMs of tissue are of particular importance. They can be counted among the matrices that are most complex and time consuming in preparation. Tissue is the place of transformation and accumulation of many substances (e.g., metabolites, which are intermediate or end products resulting from metabolic processes). Trace amounts of many substances in tissues must be determined with adequate precision and accuracy. To meet the needs stemming from research and from problems and challenges faced by chemists, analysts, and toxicologists, the number of certified reference materials should be continuously increased. PMID:26042643
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.
Competing Sudakov veto algorithms
NASA Astrophysics Data System (ADS)
Kleiss, Ronald; Verheyen, Rob
2016-07-01
We present a formalism to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The formal analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance in a semi-realistic setting and show that there are significantly faster alternatives to the commonly used algorithms.
A fast and efficient algorithm for Slater determinant updates in quantum Monte Carlo simulations
Nukala, Phani K. V. V.; Kent, P. R. C.
2009-05-28
We present an efficient low-rank updating algorithm for updating the trial wave functions used in quantum Monte Carlo (QMC) simulations. The algorithm is based on low-rank updating of the Slater determinants. In particular, the computational complexity of the algorithm is O(kN) during the kth step compared to traditional algorithms that require O(N{sup 2}) computations, where N is the system size. For single determinant trial wave functions the new algorithm is faster than the traditional O(N{sup 2}) Sherman-Morrison algorithm for up to O(N) updates. For multideterminant configuration-interaction-type trial wave functions of M+1 determinants, the new algorithm is significantly more efficient, saving both O(MN{sup 2}) work and O(MN{sup 2}) storage. The algorithm enables more accurate and significantly more efficient QMC calculations using configuration-interaction-type wave functions.
A fast and efficient algorithm for Slater determinant updates in quantum Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Nukala, Phani K. V. V.; Kent, P. R. C.
2009-05-01
We present an efficient low-rank updating algorithm for updating the trial wave functions used in quantum Monte Carlo (QMC) simulations. The algorithm is based on low-rank updating of the Slater determinants. In particular, the computational complexity of the algorithm is O(kN) during the kth step compared to traditional algorithms that require O(N2) computations, where N is the system size. For single determinant trial wave functions the new algorithm is faster than the traditional O(N2) Sherman-Morrison algorithm for up to O(N ) updates. For multideterminant configuration-interaction-type trial wave functions of M +1 determinants, the new algorithm is significantly more efficient, saving both O(MN2) work and O(MN2) storage. The algorithm enables more accurate and significantly more efficient QMC calculations using configuration-interaction-type wave functions.
A fast and efficient algorithm for Slater determinant updates in quantum Monte Carlo simulations.
Nukala, Phani K V V; Kent, P R C
2009-05-28
We present an efficient low-rank updating algorithm for updating the trial wave functions used in quantum Monte Carlo (QMC) simulations. The algorithm is based on low-rank updating of the Slater determinants. In particular, the computational complexity of the algorithm is O(kN) during the kth step compared to traditional algorithms that require O(N(2)) computations, where N is the system size. For single determinant trial wave functions the new algorithm is faster than the traditional O(N(2)) Sherman-Morrison algorithm for up to O(N) updates. For multideterminant configuration-interaction-type trial wave functions of M+1 determinants, the new algorithm is significantly more efficient, saving both O(MN(2)) work and O(MN(2)) storage. The algorithm enables more accurate and significantly more efficient QMC calculations using configuration-interaction-type wave functions. PMID:19485435
A Fast and efficient Algorithm for Slater Determinant Updates in Quantum Monte Carlo Simulations
Nukala, Phani K; Kent, Paul R
2009-01-01
We present an efficient low-rank updating algorithm for updating the trial wavefunctions used in Quantum Monte Carlo (QMC) simulations. The algorithm is based on low-rank updating of the Slater determinants. In particular, the computational complexity of the algorithm is $\\mathcal{O}(k N)$ during the $k$-th step compared with traditional algorithms that require $\\mathcal{O}(N^2)$ computations, where $N$ is the system size. For single determinant trial wavefunctions the new algorithm is faster than the traditional $\\mathcal{O}(N^2)$ Sherman-Morrison algorithm for up to $\\mathcal{O}(N)$ updates. For multideterminant configuration-interaction type trial wavefunctions of $M+1$ determinants, the new algorithm is significantly more efficient, saving both $\\mathcal{O}(MN^2)$ work and $\\mathcal{O}(MN^2)$ storage. The algorithm enables more accurate and significantly more efficient QMC calculations using configuration interaction type wavefunctions.
Investigation of registration algorithms for the automatic tile processing system
NASA Technical Reports Server (NTRS)
Tamir, Dan E.
1995-01-01
The Robotic Tile Inspection System (RTPS), under development in NASA-KSC, is expected to automate the processes of post-flight re-water-proofing and the process of inspection of the Shuttle heat absorbing tiles. An important task of the robot vision sub-system is to register the 'real-world' coordinates with the coordinates of the robot model of the Shuttle tiles. The model coordinates relate to a tile data-base and pre-flight tile-images. In the registration process, current (post-flight) images are aligned with pre-flight images to detect the rotation and translation displacement required for the coordinate systems rectification. The research activities performed this summer included study and evaluation of the registration algorithm that is currently implemented by the RTPS, as well as, investigation of the utility of other registration algorithms. It has been found that the current algorithm is not robust enough. This algorithm has a success rate of less than 80% and is, therefore, not suitable for complying with the requirements of the RTPS. Modifications to the current algorithm has been developed and tested. These modifications can improve the performance of the registration algorithm in a significant way. However, this improvement is not sufficient to satisfy system requirements. A new algorithm for registration has been developed and tested. This algorithm presented very high degree of robustness with success rate of 96%.
Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics
NASA Technical Reports Server (NTRS)
Fijany, Amir; Scheid, Robert E.
1989-01-01
The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.
Programming parallel vision algorithms
Shapiro, L.G.
1988-01-01
Computer vision requires the processing of large volumes of data and requires parallel architectures and algorithms to be useful in real-time, industrial applications. The INSIGHT dataflow language was designed to allow encoding of vision algorithms at all levels of the computer vision paradigm. INSIGHT programs, which are relational in nature, can be translated into a graph structure that represents an architecture for solving a particular vision problem or a configuration of a reconfigurable computational network. The authors consider here INSIGHT programs that produce a parallel net architecture for solving low-, mid-, and high-level vision tasks.
Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems
Van Benthem, Mark H.; Keenan, Michael R.
2008-11-11
A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.
Lakhani, Paras; Langlotz, Curtis P
2010-12-01
The purpose of this investigation is to develop an automated method to accurately detect radiology reports that indicate non-routine communication of critical or significant results. Such a classification system would be valuable for performance monitoring and accreditation. Using a database of 2.3 million free-text radiology reports, a rule-based query algorithm was developed after analyzing hundreds of radiology reports that indicated communication of critical or significant results to a healthcare provider. This algorithm consisted of words and phrases used by radiologists to indicate such communications combined with specific handcrafted rules. This algorithm was iteratively refined and retested on hundreds of reports until the precision and recall did not significantly change between iterations. The algorithm was then validated on the entire database of 2.3 million reports, excluding those reports used during the testing and refinement process. Human review was used as the reference standard. The accuracy of this algorithm was determined using precision, recall, and F measure. Confidence intervals were calculated using the adjusted Wald method. The developed algorithm for detecting critical result communication has a precision of 97.0% (95% CI, 93.5-98.8%), recall 98.2% (95% CI, 93.4-100%), and F measure of 97.6% (ß=1). Our query algorithm is accurate for identifying radiology reports that contain non-routine communication of critical or significant results. This algorithm can be applied to a radiology reports database for quality control purposes and help satisfy accreditation requirements. PMID:19826871
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.
Sobel, E.; Lange, K.; O`Connell, J.R.
1996-12-31
Haplotyping is the logical process of inferring gene flow in a pedigree based on phenotyping results at a small number of genetic loci. This paper formalizes the haplotyping problem and suggests four algorithms for haplotype reconstruction. These algorithms range from exhaustive enumeration of all haplotype vectors to combinatorial optimization by simulated annealing. Application of the algorithms to published genetic analyses shows that manual haplotyping is often erroneous. Haplotyping is employed in screening pedigrees for phenotyping errors and in positional cloning of disease genes from conserved haplotypes in population isolates. 26 refs., 6 figs., 3 tabs.
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.
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.
Improved multiprocessor garbage collection algorithms
Newman, I.A.; Stallard, R.P.; Woodward, M.C.
1983-01-01
Outlines the results of an investigation of existing multiprocessor garbage collection algorithms and introduces two new algorithms which significantly improve some aspects of the performance of their predecessors. The two algorithms arise from different starting assumptions. One considers the case where the algorithm will terminate successfully whatever list structure is being processed and assumes that the extra data space should be minimised. The other seeks a very fast garbage collection time for list structures that do not contain loops. Results of both theoretical and experimental investigations are given to demonstrate the efficacy of the algorithms. 7 references.
The Superior Lambert Algorithm
NASA Astrophysics Data System (ADS)
der, G.
2011-09-01
Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most
Efficient Algorithm for Rectangular Spiral Search
NASA Technical Reports Server (NTRS)
Brugarolas, Paul; Breckenridge, William
2008-01-01
An algorithm generates grid coordinates for a computationally efficient spiral search pattern covering an uncertain rectangular area spanned by a coordinate grid. The algorithm does not require that the grid be fixed; the algorithm can search indefinitely, expanding the grid and spiral, as needed, until the target of the search is found. The algorithm also does not require memory of coordinates of previous points on the spiral to generate the current point on the spiral.
Old And New Algorithms For Toeplitz Systems
NASA Astrophysics Data System (ADS)
Brent, Richard P.
1988-02-01
Toeplitz linear systems and Toeplitz least squares problems commonly arise in digital signal processing. In this paper we survey some old, "well known" algorithms and some recent algorithms for solving these problems. We concentrate our attention on algorithms which can be implemented efficiently on a variety of parallel machines (including pipelined vector processors and systolic arrays). We distinguish between algorithms which require inner products, and algorithms which avoid inner products, and thus are better suited to parallel implementation on some parallel architectures. Finally, we mention some "asymptotically fast" 0(n(log n)2) algorithms and compare them with 0(n2) algorithms.
NASA Technical Reports Server (NTRS)
Barth, Timothy J.; Lomax, Harvard
1987-01-01
The past decade has seen considerable activity in algorithm development for the Navier-Stokes equations. This has resulted in a wide variety of useful new techniques. Some examples for the numerical solution of the Navier-Stokes equations are presented, divided into two parts. One is devoted to the incompressible Navier-Stokes equations, and the other to the compressible form.
Noise filtering algorithm for the MFTF-B computer based control system
Minor, E.G.
1983-11-30
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions.
Structure-based algorithms for microvessel classification
Smith, Amy F.; Secomb, Timothy W.; Pries, Axel R.; Smith, Nicolas P.; Shipley, Rebecca J.
2014-01-01
Objective Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries and venules. PMID:25403335
[Orthogonal Vector Projection Algorithm for Spectral Unmixing].
Song, Mei-ping; Xu, Xing-wei; Chang, Chein-I; An, Ju-bai; Yao, Li
2015-12-01
Spectrum unmixing is an important part of hyperspectral technologies, which is essential for material quantity analysis in hyperspectral imagery. Most linear unmixing algorithms require computations of matrix multiplication and matrix inversion or matrix determination. These are difficult for programming, especially hard for realization on hardware. At the same time, the computation costs of the algorithms increase significantly as the number of endmembers grows. Here, based on the traditional algorithm Orthogonal Subspace Projection, a new method called. Orthogonal Vector Projection is prompted using orthogonal principle. It simplifies this process by avoiding matrix multiplication and inversion. It firstly computes the final orthogonal vector via Gram-Schmidt process for each endmember spectrum. And then, these orthogonal vectors are used as projection vector for the pixel signature. The unconstrained abundance can be obtained directly by projecting the signature to the projection vectors, and computing the ratio of projected vector length and orthogonal vector length. Compared to the Orthogonal Subspace Projection and Least Squares Error algorithms, this method does not need matrix inversion, which is much computation costing and hard to implement on hardware. It just completes the orthogonalization process by repeated vector operations, easy for application on both parallel computation and hardware. The reasonability of the algorithm is proved by its relationship with Orthogonal Sub-space Projection and Least Squares Error algorithms. And its computational complexity is also compared with the other two algorithms', which is the lowest one. At last, the experimental results on synthetic image and real image are also provided, giving another evidence for effectiveness of the method. PMID:26964231
A fast algorithm for sparse matrix computations related to inversion
NASA Astrophysics Data System (ADS)
Li, S.; Wu, W.; Darve, E.
2013-06-01
We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green's functions Gr and G< for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round-off errors
NASA Astrophysics Data System (ADS)
Houchin, J. S.
2014-09-01
A common problem for the off-line validation of the calibration algorithms and algorithm coefficients is being able to run science data through the exact same software used for on-line calibration of that data. The Joint Polar Satellite System (JPSS) program solved part of this problem by making the Algorithm Development Library (ADL) available, which allows the operational algorithm code to be compiled and run on a desktop Linux workstation using flat file input and output. However, this solved only part of the problem, as the toolkit and methods to initiate the processing of data through the algorithms were geared specifically toward the algorithm developer, not the calibration analyst. In algorithm development mode, a limited number of sets of test data are staged for the algorithm once, and then run through the algorithm over and over as the software is developed and debugged. In calibration analyst mode, we are continually running new data sets through the algorithm, which requires significant effort to stage each of those data sets for the algorithm without additional tools. AeroADL solves this second problem by providing a set of scripts that wrap the ADL tools, providing both efficient means to stage and process an input data set, to override static calibration coefficient look-up-tables (LUT) with experimental versions of those tables, and to manage a library containing multiple versions of each of the static LUT files in such a way that the correct set of LUTs required for each algorithm are automatically provided to the algorithm without analyst effort. Using AeroADL, The Aerospace Corporation's analyst team has demonstrated the ability to quickly and efficiently perform analysis tasks for both the VIIRS and OMPS sensors with minimal training on the software tools.
The phase correlation algorithm for stabilization of capillary blood flow video frames
NASA Astrophysics Data System (ADS)
Karimov, Konstantin A.; Volkov, Mikhail V.
2015-05-01
The capillary blood flow parameters recovery is one of the videocapillaroscopy objectives. Capillaries position can vary at recorded video sequences due to the registration features of capillary blood flow. Stabilization algorithm of capillary blood flow video frames based on the advanced phase correlation is proposed and investigated. This algorithm is compared to the advanced version of known algorithms of video frames stabilization based on full-frame superposition and key points detection. Programs based on discussed algorithms are compared by processing of the experimentally recorded video sequences of human capillaries and by processing of computer-simulated video frames sequences with the specified offset. The full-frame superposition algorithm provides high quality of stabilization, however, the program based on this algorithm requires significant computational resources. Software implementation of the key points detection algorithm is characterized by good performance, but provides low quality of stabilization for capillary blood flow video sequences. Algorithm based on phase correlation method provides high quality of stabilization and program realization of this algorithm requires minimal computational resources. It is shown that the phase correlation algorithm is the most useful for stabilization of video sequences for capillaries blood flow. Obtained results can be used in software for biomedical diagnostics.
Temperature Corrected Bootstrap Algorithm
NASA Technical Reports Server (NTRS)
Comiso, Joey C.; Zwally, H. Jay
1997-01-01
A temperature corrected Bootstrap Algorithm has been developed using Nimbus-7 Scanning Multichannel Microwave Radiometer data in preparation to the upcoming AMSR instrument aboard ADEOS and EOS-PM. The procedure first calculates the effective surface emissivity using emissivities of ice and water at 6 GHz and a mixing formulation that utilizes ice concentrations derived using the current Bootstrap algorithm but using brightness temperatures from 6 GHz and 37 GHz channels. These effective emissivities are then used to calculate surface ice which in turn are used to convert the 18 GHz and 37 GHz brightness temperatures to emissivities. Ice concentrations are then derived using the same technique as with the Bootstrap algorithm but using emissivities instead of brightness temperatures. The results show significant improvement in the area where ice temperature is expected to vary considerably such as near the continental areas in the Antarctic, where the ice temperature is colder than average, and in marginal ice zones.
Using genetic algorithms to select and create features for pattern classification. Technical report
Chang, E.I.; Lippmann, R.P.
1991-03-11
Genetic algorithms were used to select and create features and to select reference exemplar patterns for machine vision and speech pattern classification tasks. On a 15-feature machine-vision inspection task, it was found that genetic algorithms performed no better than conventional approaches to feature selection but required much more computation. For a speech recognition task, genetic algorithms required no more computation time than traditional approaches but reduced the number of features required by a factor of five (from 153 to 33 features). On a difficult artificial machine-vision task, genetic algorithms were able to create new features (polynomial functions of the original features) that reduced classification error rates from 10 to almost 0 percent. Neural net and nearest-neighbor classifiers were unable to provide such low error rates using only the original features. Genetic algorithms were also used to reduce the number of reference exemplar patterns and to select the value of k for a k-nearest-neighbor classifier. On a .338 training pattern vowel recognition problem with 10 classes, genetic algorithms simultaneously reduced the number of stored exemplars from 338 to 63 and selected k without significantly decreasing classification accuracy. In all applications, genetic algorithms were easy to apply and found good solutions in many fewer trials than would be required by an exhaustive search. Run times were long but not unreasonable. These results suggest that genetic algorithms may soon be practical for pattern classification problems as faster serial and parallel computers are developed.
[Algorithm for treating preoperative anemia].
Bisbe Vives, E; Basora Macaya, M
2015-06-01
Hemoglobin optimization and treatment of preoperative anemia in surgery with a moderate to high risk of surgical bleeding reduces the rate of transfusions and improves hemoglobin levels at discharge and can also improve postoperative outcomes. To this end, we need to schedule preoperative visits sufficiently in advance to treat the anemia. The treatment algorithm we propose comes with a simple checklist to determine whether we should refer the patient to a specialist or if we can treat the patient during the same visit. With the blood count test and additional tests for iron metabolism, inflammation parameter and glomerular filtration rate, we can decide whether to start the treatment with intravenous iron alone or erythropoietin with or without iron. With significant anemia, a visit after 15 days might be necessary to observe the response and supplement the treatment if required. The hemoglobin objective will depend on the type of surgery and the patient's characteristics. PMID:26320341
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
A new root-based direction-finding algorithm
NASA Astrophysics Data System (ADS)
Wasylkiwskyj, Wasyl; Kopriva, Ivica; DoroslovačKi, Miloš; Zaghloul, Amir I.
2007-04-01
Polynomial rooting direction-finding (DF) algorithms are a computationally efficient alternative to search-based DF algorithms and are particularly suitable for uniform linear arrays of physically identical elements provided that mutual interaction among the array elements can be either neglected or compensated for. A popular algorithm in such situations is Root Multiple Signal Classification (Root MUSIC (RM)), wherein the estimation of the directions of arrivals (DOA) requires the computation of the roots of a (2N - 2) -order polynomial, where N represents number of array elements. The DOA are estimated from the L pairs of roots closest to the unit circle, where L represents number of sources. In this paper we derive a modified root polynomial (MRP) algorithm requiring the calculation of only L roots in order to estimate the L DOA. We evaluate the performance of the MRP algorithm numerically and show that it is as accurate as the RM algorithm but with a significantly simpler algebraic structure. In order to demonstrate that the theoretically predicted performance can be achieved in an experimental setting, a decoupled array is emulated in hardware using phase shifters. The results are in excellent agreement with theory.
An innovative localisation algorithm for railway vehicles
NASA Astrophysics Data System (ADS)
Allotta, B.; D'Adamio, P.; Malvezzi, M.; Pugi, L.; Ridolfi, A.; Rindi, A.; Vettori, G.
2014-11-01
In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the Italian Sistema Controllo Marcia Treno (SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and an Inertial Measurements Unit (IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements
An Accelerated Recursive Doubling Algorithm for Block Tridiagonal Systems
Seal, Sudip K
2014-01-01
Block tridiagonal systems of linear equations arise in a wide variety of scientific and engineering applications. Recursive doubling algorithm is a well-known prefix computation-based numerical algorithm that requires O(M^3(N/P + log P)) work to compute the solution of a block tridiagonal system with N block rows and block size M on P processors. In real-world applications, solutions of tridiagonal systems are most often sought with multiple, often hundreds and thousands, of different right hand sides but with the same tridiagonal matrix. Here, we show that a recursive doubling algorithm is sub-optimal when computing solutions of block tridiagonal systems with multiple right hand sides and present a novel algorithm, called the accelerated recursive doubling algorithm, that delivers O(R) improvement when solving block tridiagonal systems with R distinct right hand sides. Since R is typically about 100 1000, this improvement translates to very significant speedups in practice. Detailed complexity analyses of the new algorithm with empirical confirmation of runtime improvements are presented. To the best of our knowledge, this algorithm has not been reported before in the literature.
Learning evasive maneuvers using evolutionary algorithms and neural networks
NASA Astrophysics Data System (ADS)
Kang, Moung Hung
In this research, evolutionary algorithms and recurrent neural networks are combined to evolve control knowledge to help pilots avoid being struck by a missile, based on a two-dimensional air combat simulation model. The recurrent neural network is used for representing the pilot's control knowledge and evolutionary algorithms (i.e., Genetic Algorithms, Evolution Strategies, and Evolutionary Programming) are used for optimizing the weights and/or topology of the recurrent neural network. The simulation model of the two-dimensional evasive maneuver problem evolved is used for evaluating the performance of the recurrent neural network. Five typical air combat conditions were selected to evaluate the performance of the recurrent neural networks evolved by the evolutionary algorithms. Analysis of Variance (ANOVA) tests and response graphs were used to analyze the results. Overall, there was little difference in the performance of the three evolutionary algorithms used to evolve the control knowledge. However, the number of generations of each algorithm required to obtain the best performance was significantly different. ES converges the fastest, followed by EP and then by GA. The recurrent neural networks evolved by the evolutionary algorithms provided better performance than the traditional recommendations for evasive maneuvers, maximum gravitational turn, for each air combat condition. Furthermore, the recommended actions of the recurrent neural networks are reasonable and can be used for pilot training.
Testing of infrared image enhancing algorithm in different spectral bands
NASA Astrophysics Data System (ADS)
Dulski, R.; Sosnowski, T.; Kastek, M.; Trzaskawka, P.
2012-06-01
The paper presents results of testing the infrared image quality enhancing algorithm based on histogram processing. Testing were performed on real images registered in NIR, MWIR, and LWIR spectral bands. Infrared images are a very specific type of information. The perception and interpretation of such image depends not only on radiative properties of observed objects and surrounding scenery. Probably still most important are skills and experience of an observer itself. In practice, the optimal settings of the camera as well as automatic temperature range or contrast control do not guarantee the displayed images are optimal from observer's point of view. The solution to this are algorithms of image quality enhancing based on digital image processing methods. Such algorithms can be implemented inside the camera or applied later, after image registration. They must improve the visibility of low-contrast objects. They should also provide effective dynamic contrast control not only across entire image but also selectively to specific areas in order to maintain optimal visualization of observed scenery. In the paper one histogram equalization algorithm was tested. Adaptive nature of the algorithm should assure significant improvement of the image quality and the same effectiveness of object detection. Another requirement and difficulty is that it should also be effective for any given thermal image and it should not cause a visible image degradation in unpredictable situations. The application of tested algorithm is a promising alternative to a very effective but complex algorithms due to its low complexity and real time operation.
Convergence behavior of a new DSMC algorithm.
Gallis, Michail A.; Rader, Daniel John; Torczynski, John Robert; Bird, Graeme A.
2008-10-01
The convergence rate of a new direct simulation Monte Carlo (DSMC) method, termed 'sophisticated DSMC', is investigated for one-dimensional Fourier flow. An argon-like hard-sphere gas at 273.15K and 266.644Pa is confined between two parallel, fully accommodating walls 1mm apart that have unequal temperatures. The simulations are performed using a one-dimensional implementation of the sophisticated DSMC algorithm. In harmony with previous work, the primary convergence metric studied is the ratio of the DSMC-calculated thermal conductivity to its corresponding infinite-approximation Chapman-Enskog theoretical value. As discretization errors are reduced, the sophisticated DSMC algorithm is shown to approach the theoretical values to high precision. The convergence behavior of sophisticated DSMC is compared to that of original DSMC. The convergence of the new algorithm in a three-dimensional implementation is also characterized. Implementations using transient adaptive sub-cells and virtual sub-cells are compared. The new algorithm is shown to significantly reduce the computational resources required for a DSMC simulation to achieve a particular level of accuracy, thus improving the efficiency of the method by a factor of 2.
Statistically significant relational data mining :
Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann; Pinar, Ali; Robinson, David Gerald; Berger-Wolf, Tanya; Bhowmick, Sanjukta; Casleton, Emily; Kaiser, Mark; Nordman, Daniel J.; Wilson, Alyson G.
2014-02-01
This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publications that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.
A Fast Implementation of the ISOCLUS Algorithm
NASA Technical Reports Server (NTRS)
Memarsadeghi, Nargess; Mount, David M.; Netanyahu, Nathan S.; LeMoigne, Jacqueline
2003-01-01
Unsupervised clustering is a fundamental building block in numerous image processing applications. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute the coordinates of a set of cluster centers in d-space, such that those centers minimize the mean squared distance from each data point to its nearest center. This clustering algorithm is similar to another well-known clustering method, called k-means. One significant feature of ISOCLUS over k-means is that the actual number of clusters reported might be fewer or more than the number supplied as part of the input. The algorithm uses different heuristics to determine whether to merge lor split clusters. As ISOCLUS can run very slowly, particularly on large data sets, there has been a growing .interest in the remote sensing community in computing it efficiently. We have developed a faster implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm of Kanungo, et al. They showed that, by using a kd-tree data structure for storing the data, it is possible to reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm, and we show that it is possible to achieve essentially the same results as ISOCLUS on large data sets, but with significantly lower running times. This adaptation involves computing a number of cluster statistics that are needed for ISOCLUS but not for k-means. Both the k-means and ISOCLUS algorithms are based on iterative schemes, in which nearest neighbors are calculated until some convergence criterion is satisfied. Each iteration requires that the nearest center for each data point be computed. Naively, this requires O
Using Strassen's algorithm to accelerate the solution of linear systems
NASA Technical Reports Server (NTRS)
Bailey, David H.; Lee, King; Simon, Horst D.
1990-01-01
Strassen's algorithm for fast matrix-matrix multiplication has been implemented for matrices of arbitrary shapes on the CRAY-2 and CRAY Y-MP supercomputers. Several techniques have been used to reduce the scratch space requirement for this algorithm while simultaneously preserving a high level of performance. When the resulting Strassen-based matrix multiply routine is combined with some routines from the new LAPACK library, LU decomposition can be performed with rates significantly higher than those achieved by conventional means. We succeeded in factoring a 2048 x 2048 matrix on the CRAY Y-MP at a rate equivalent to 325 MFLOPS.
Tomasz Plawski, J. Hovater
2010-09-01
A digital low level radio frequency (RF) system typically incorporates either a heterodyne or direct sampling technique, followed by fast ADCs, then an FPGA, and finally a transmitting DAC. This universal platform opens up the possibilities for a variety of control algorithm implementations. The foremost concern for an RF control system is cavity field stability, and to meet the required quality of regulation, the chosen control system needs to have sufficient feedback gain. In this paper we will investigate the effectiveness of the regulation for three basic control system algorithms: I&Q (In-phase and Quadrature), Amplitude & Phase and digital SEL (Self Exciting Loop) along with the example of the Jefferson Lab 12 GeV cavity field control system.
CORDIC algorithms in four dimensions
NASA Astrophysics Data System (ADS)
Delosme, Jean-Marc; Hsiao, Shen-Fu
1990-11-01
CORDIC algorithms offer an attractive alternative to multiply-and-add based algorithms for the implementation of two-dimensional rotations preserving either norm: (x2 + 2) or (x2 _ y2)/2 Indeed these norms whose computation is a significant part of the evaluation of the two-dimensional rotations are computed much more easily by the CORDIC algorithms. However the part played by norm computations in the evaluation of rotations becomes quickly small as the dimension of the space increases. Thus in spaces of dimension 5 or more there is no practical alternative to multiply-and-add based algorithms. In the intermediate region dimensions 3 and 4 extensions of the CORDIC algorithms are an interesting option. The four-dimensional extensions are particularly elegant and are the main object of this paper.
Algorithms versus architectures for computational chemistry
NASA Technical Reports Server (NTRS)
Partridge, H.; Bauschlicher, C. W., Jr.
1986-01-01
The algorithms employed are computationally intensive and, as a result, increased performance (both algorithmic and architectural) is required to improve accuracy and to treat larger molecular systems. Several benchmark quantum chemistry codes are examined on a variety of architectures. While these codes are only a small portion of a typical quantum chemistry library, they illustrate many of the computationally intensive kernels and data manipulation requirements of some applications. Furthermore, understanding the performance of the existing algorithm on present and proposed supercomputers serves as a guide for future programs and algorithm development. The algorithms investigated are: (1) a sparse symmetric matrix vector product; (2) a four index integral transformation; and (3) the calculation of diatomic two electron Slater integrals. The vectorization strategies are examined for these algorithms for both the Cyber 205 and Cray XMP. In addition, multiprocessor implementations of the algorithms are looked at on the Cray XMP and on the MIT static data flow machine proposed by DENNIS.
Significant Radionuclides Determination
Jo A. Ziegler
2001-07-31
The purpose of this calculation is to identify radionuclides that are significant to offsite doses from potential preclosure events for spent nuclear fuel (SNF) and high-level radioactive waste expected to be received at the potential Monitored Geologic Repository (MGR). In this calculation, high-level radioactive waste is included in references to DOE SNF. A previous document, ''DOE SNF DBE Offsite Dose Calculations'' (CRWMS M&O 1999b), calculated the source terms and offsite doses for Department of Energy (DOE) and Naval SNF for use in design basis event analyses. This calculation reproduces only DOE SNF work (i.e., no naval SNF work is included in this calculation) created in ''DOE SNF DBE Offsite Dose Calculations'' and expands the calculation to include DOE SNF expected to produce a high dose consequence (even though the quantity of the SNF is expected to be small) and SNF owned by commercial nuclear power producers. The calculation does not address any specific off-normal/DBE event scenarios for receiving, handling, or packaging of SNF. The results of this calculation are developed for comparative analysis to establish the important radionuclides and do not represent the final source terms to be used for license application. This calculation will be used as input to preclosure safety analyses and is performed in accordance with procedure AP-3.12Q, ''Calculations'', and is subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (DOE 2000) as determined by the activity evaluation contained in ''Technical Work Plan for: Preclosure Safety Analysis, TWP-MGR-SE-000010'' (CRWMS M&O 2000b) in accordance with procedure AP-2.21Q, ''Quality Determinations and Planning for Scientific, Engineering, and Regulatory Compliance Activities''.
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
Efficient demultiplexing algorithm for noncontiguous carriers
NASA Technical Reports Server (NTRS)
Thanawala, A. A.; Kwatra, S. C.; Jamali, M. M.; Budinger, J.
1992-01-01
A channel separation algorithm for the frequency division multiple access/time division multiplexing (FDMA/TDM) scheme is presented. It is shown that implementation using this algorithm can be more effective than the fast Fourier transform (FFT) algorithm when only a small number of carriers need to be selected from many, such as satellite Earth terminals. The algorithm is based on polyphase filtering followed by application of a generalized Walsh-Hadamard transform (GWHT). Comparison of the transform technique used in this algorithm with discrete Fourier transform (DFT) and FFT is given. Estimates of the computational rates and power requirements to implement this system are also given.
A generalized memory test algorithm
NASA Technical Reports Server (NTRS)
Milner, E. J.
1982-01-01
A general algorithm for testing digital computer memory is presented. The test checks that (1) every bit can be cleared and set in each memory work, and (2) bits are not erroneously cleared and/or set elsewhere in memory at the same time. The algorithm can be applied to any size memory block and any size memory word. It is concise and efficient, requiring the very few cycles through memory. For example, a test of 16-bit-word-size memory requries only 384 cycles through memory. Approximately 15 seconds were required to test a 32K block of such memory, using a microcomputer having a cycle time of 133 nanoseconds.
Vehicle counting and classification algorithms for unattended ground sensors
NASA Astrophysics Data System (ADS)
Hohil, Myron E.; Heberley, Jeffrey R.; Chang, Jay; Rotolo, Anthony
2003-09-01
Unattended ground sensor technology used for battlefield awareness and other wide area surveillance applications requires state-of-the-art algorithms to address the unprecedented challenges faced in detecting, classifying and tracking military combat vehicles. The performance of traditional acoustic sensor systems often degrades unacceptably against the dynamic and highly mobile multiple target environments in which today's forces must operate. In the present work, a target counting algorithm has been developed to solve problems attributed to unstable tracking performance by resolving track loss deficiencies inherent to closely spaced target environments. The algorithm provides a way to discriminate between vehicles as they pass through an acoustic "trip-line" formed by a sensor in a predetermined field of view (FOV). The proposed approach is realized through an adaptive beamforming algorithm that achieves enhanced directivity in a principal look direction by significantly reducing the effects of interferers outside the precise bearing of the steering direction. The classification algorithm described herein facilitates a minimal representation for features extracted from harmonically related structures characteristic to acoustic emissions from ground vehicles found in battlefield environments. The reduced feature space representation exploits an ordering for the principal narrowband components found in a vehicle's engine noise and has proven effective in solving fundamental problems associated with discriminating between vehicles in variable SNR environments. The performance of the algorithms is demonstrated using signature data collected during various acoustic sensor field test experiments.
CORDIC Algorithms: Theory And Extensions
NASA Astrophysics Data System (ADS)
Delosme, Jean-Marc
1989-11-01
Optimum algorithms for signal processing are notoriously costly to implement since they usually require intensive linear algebra operations to be performed at very high rates. In these cases a cost-effective solution is to design a pipelined or parallel architecture with special-purpose VLSI processors. One may often lower the hardware cost of such a dedicated architecture by using processors that implement CORDIC-like arithmetic algorithms. Indeed, with CORDIC algorithms, the evaluation and the application of an operation, such as determining a rotation that brings a vector onto another one and rotating other vectors by that amount, require the same time on identical processors and can be fully overlapped in most cases, thus leading to highly efficient implementations. We have shown earlier that a necessary condition for a CORDIC-type algorithm to exist is that the function to be implemented can be represented in terms of a matrix exponential. This paper refines this condition to the ability to represent , the desired function in terms of a rational representation of a matrix exponential. This insight gives us a powerful tool for the design of new CORDIC algorithms. This is demonstrated by rederiving classical CORDIC algorithms and introducing several new ones, for Jacobi rotations, three and higher dimensional rotations, etc.
Genetic algorithms as discovery programs
Hilliard, M.R.; Liepins, G.
1986-01-01
Genetic algorithms are mathematical counterparts to natural selection and gene recombination. As such, they have provided one of the few significant breakthroughs in machine learning. Used with appropriate reward functions and apportionment of credit, they have been successfully applied to gas pipeline operation, x-ray registration and mathematical optimization problems. This paper discusses the basics of genetic algorithms, describes a few successes, and reports on current progress at Oak Ridge National Laboratory in applications to set covering and simulated robots.
Scheduling Jobs with Genetic Algorithms
NASA Astrophysics Data System (ADS)
Ferrolho, António; Crisóstomo, Manuel
Most scheduling problems are NP-hard, the time required to solve the problem optimally increases exponentially with the size of the problem. Scheduling problems have important applications, and a number of heuristic algorithms have been proposed to determine relatively good solutions in polynomial time. Recently, genetic algorithms (GA) are successfully used to solve scheduling problems, as shown by the growing numbers of papers. GA are known as one of the most efficient algorithms for solving scheduling problems. But, when a GA is applied to scheduling problems various crossovers and mutations operators can be applicable. This paper presents and examines a new concept of genetic operators for scheduling problems. A software tool called hybrid and flexible genetic algorithm (HybFlexGA) was developed to examine the performance of various crossover and mutation operators by computing simulations of job scheduling problems.
Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system
Fijany, A.; Milman, M.; Redding, D.
1994-12-31
In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.
ALGORITHM FOR SORTING GROUPED DATA
NASA Technical Reports Server (NTRS)
Evans, J. D.
1994-01-01
It is often desirable to sort data sets in ascending or descending order. This becomes more difficult for grouped data, i.e., multiple sets of data, where each set of data involves several measurements or related elements. The sort becomes increasingly cumbersome when more than a few elements exist for each data set. In order to achieve an efficient sorting process, an algorithm has been devised in which the maximum most significant element is found, and then compared to each element in succession. The program was written to handle the daily temperature readings of the Voyager spacecraft, particularly those related to the special tracking requirements of Voyager 2. By reducing each data set to a single representative number, the sorting process becomes very easy. The first step in the process is to reduce the data set of width 'n' to a data set of width '1'. This is done by representing each data set by a polynomial of length 'n' based on the differences of the maximum and minimum elements. These single numbers are then sorted and converted back to obtain the original data sets. Required input data are the name of the data file to read and sort, and the starting and ending record numbers. The package includes a sample data file, containing 500 sets of data with 5 elements in each set. This program will perform a sort of the 500 data sets in 3 - 5 seconds on an IBM PC-AT with a hard disk; on a similarly equipped IBM PC-XT the time is under 10 seconds. This program is written in BASIC (specifically the Microsoft QuickBasic compiler) for interactive execution and has been implemented on the IBM PC computer series operating under PC-DOS with a central memory requirement of approximately 40K of 8 bit bytes. A hard disk is desirable for speed considerations, but is not required. This program was developed in 1986.
Stability of Bareiss algorithm
NASA Astrophysics Data System (ADS)
Bojanczyk, Adam W.; Brent, Richard P.; de Hoog, F. R.
1991-12-01
In this paper, we present a numerical stability analysis of Bareiss algorithm for solving a symmetric positive definite Toeplitz system of linear equations. We also compare Bareiss algorithm with Levinson algorithm and conclude that the former has superior numerical properties.
Eddy-current NDE inverse problem with sparse grid algorithm
NASA Astrophysics Data System (ADS)
Zhou, Liming; Sabbagh, Harold A.; Sabbagh, Elias H.; Murphy, R. Kim; Bernacchi, William; Aldrin, John C.; Forsyth, David; Lindgren, Eric
2016-02-01
In model-based inverse problems, the unknown parameters (such as length, width, depth) need to be estimated. When the unknown parameters are few, the conventional mathematical methods are suitable. But the increasing number of unknown parameters will make the computation become heavy. To reduce the burden of computation, the sparse grid algorithm was used in our work. As a result, we obtain a powerful interpolation method that requires significantly fewer support nodes than conventional interpolation on a full grid.
Riemannian mean and space-time adaptive processing using projection and inversion algorithms
NASA Astrophysics Data System (ADS)
Balaji, Bhashyam; Barbaresco, Frédéric
2013-05-01
The estimation of the covariance matrix from real data is required in the application of space-time adaptive processing (STAP) to an airborne ground moving target indication (GMTI) radar. A natural approach to estimation of the covariance matrix that is based on the information geometry has been proposed. In this paper, the output of the Riemannian mean is used in inversion and projection algorithms. It is found that the projection class of algorithms can yield very significant gains, even when the gains due to inversion-based algorithms are marginal over standard algorithms. The performance of the projection class of algorithms does not appear to be overly sensitive to the projected subspace dimension.
A Dual-Microphone Speech Enhancement Algorithm Based on the Coherence Function
2011-01-01
A novel dual-microphone speech enhancement technique is proposed in the present paper. The technique utilizes the coherence between the target and noise signals as a criterion for noise reduction and can be generally applied to arrays with closely-spaced microphones, where noise captured by the sensors is highly correlated. The proposed algorithm is simple to implement and requires no estimation of noise statistics. In addition, it offers the capability of coping with multiple interfering sources that might be located at different azimuths. The proposed algorithm was evaluated with normal hearing listeners using intelligibility listening tests and compared against a well-established beamforming algorithm. Results indicated large gains in speech intelligibility relative to the baseline (front microphone) algorithm in both single and multiple-noise source scenarios. The proposed algorithm was found to yield substantially higher intelligibility than that obtained by the beamforming algorithm, particularly when multiple noise sources or competing talker(s) were present. Objective quality evaluation of the proposed algorithm also indicated significant quality improvement over that obtained by the beamforming algorithm. The intelligibility and quality benefits observed with the proposed coherence-based algorithm make it a viable candidate for hearing aid and cochlear implant devices. PMID:22207823
Heinstein, M.W.
1997-10-01
A contact enforcement algorithm has been developed for matrix-free quasistatic finite element techniques. Matrix-free (iterative) solution algorithms such as nonlinear Conjugate Gradients (CG) and Dynamic Relaxation (DR) are distinctive in that the number of iterations required for convergence is typically of the same order as the number of degrees of freedom of the model. From iteration to iteration the contact normal and tangential forces vary significantly making contact constraint satisfaction tenuous. Furthermore, global determination and enforcement of the contact constraints every iteration could be questioned on the grounds of efficiency. This work addresses this situation by introducing an intermediate iteration for treating the active gap constraint and at the same time exactly (kinematically) enforcing the linearized gap rate constraint for both frictionless and frictional response.
Singular Parameter Prediction Algorithm for Bistable Neural Systems.
Durand, Dominique M; Jahangiri, Anila
2010-04-01
An algorithm is presented to predict the intensity and timing of a singular single stimulus required to switch the state of a bistable system from repetitive activity to a stable point. The algorithm is first tested on a modified Hodgkin-Huxley model to predict the parameters of a stimulus capable of annihilating the spontaneously occurring repetitive action potentials. Elevation of the potassium equilibrium potential causes oscillations in the V, m, h and n parameters and generates periodic activity. Equations describing the time-varying behavior of these parameters can be used to predict the pulse width, coupling interval and intensity of a single anodic pulse applied between two consecutive action potentials to suppress the activity. The algorithm was then applied to predict the singular parameters of quasi-periodic epileptiform activity generated in the hippocampus slice preparation exposed to high-potassium concentrations. The results indicate that a stimulus with the estimated parameters was able to either completely annihilate the action potentials in the HH model or predict the region of unpredictable latencies. Therefore this algorithm is capable a predicting singular parameters accurately when the model is known. In the case of an experimental system where the equations of the system are not known, the algorithm predicted parameters in the range of those observed experimentally. Therefore, the algorithm could reduce significantly the amount of time required to find the singular parameters of experimental bistable systems normally obtained by a systematic exploration of the parameter space. In particular, this algorithm could be useful to predict the singular parameters of quasi periodic epileptiform activity leading to the suppression of this activity if the system is bistable. PMID:21866209
Improvements of HITS Algorithms for Spam Links
NASA Astrophysics Data System (ADS)
Asano, Yasuhito; Tezuka, Yu; Nishizeki, Takao
The HITS algorithm proposed by Kleinberg is one of the representative methods of scoring Web pages by using hyperlinks. In the days when the algorithm was proposed, most of the pages given high score by the algorithm were really related to a given topic, and hence the algorithm could be used to find related pages. However, the algorithm and the variants including Bharat's improved HITS, abbreviated to BHITS, proposed by Bharat and Henzinger cannot be used to find related pages any more on today's Web, due to an increase of spam links. In this paper, we first propose three methods to find “linkfarms,” that is, sets of spam links forming a densely connected subgraph of a Web graph. We then present an algorithm, called a trust-score algorithm, to give high scores to pages which are not spam pages with a high probability. Combining the three methods and the trust-score algorithm with BHITS, we obtain several variants of the HITS algorithm. We ascertain by experiments that one of them, named TaN+BHITS using the trust-score algorithm and the method of finding linkfarms by employing name servers, is most suitable for finding related pages on today's Web. Our algorithms take time and memory no more than those required by the original HITS algorithm, and can be executed on a PC with a small amount of main memory.
Large scale tracking algorithms.
Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett; Karelitz, David B.; Pitts, Todd Alan; Zollweg, Joshua David; Anderson, Dylan Z.; Nandy, Prabal; Whitlow, Gary L.; Bender, Daniel A.; Byrne, Raymond Harry
2015-01-01
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
Developing dataflow algorithms
Hiromoto, R.E. ); Bohm, A.P.W. . Dept. of Computer Science)
1991-01-01
Our goal is to study the performance of a collection of numerical algorithms written in Id which is available to users of Motorola's dataflow machine Monsoon. We will study the dataflow performance of these implementations first under the parallel profiling simulator Id World, and second in comparison with actual dataflow execution on the Motorola Monsoon. This approach will allow us to follow the computational and structural details of the parallel algorithms as implemented on dataflow systems. When running our programs on the Id World simulator we will examine the behaviour of algorithms at dataflow graph level, where each instruction takes one timestep and data becomes available at the next. This implies that important machine level phenomena such as the effect that global communication time may have on the computation are not addressed. These phenomena will be addressed when we run our programs on the Monsoon hardware. Potential ramifications for compilation techniques, functional programming style, and program efficiency are significant to this study. In a later stage of our research we will compare the efficiency of Id programs to programs written in other languages. This comparison will be of a rather qualitative nature as there are too many degrees of freedom in a language implementation for a quantitative comparison to be of interest. We begin our study by examining one routine that exhibit different computational characteristics. This routine and its corresponding characteristics is Fast Fourier Transforms; computational parallelism and data dependences between the butterfly shuffles.
A fast DFT algorithm using complex integer transforms
NASA Technical Reports Server (NTRS)
Reed, I. S.; Truong, T. K.
1978-01-01
Winograd's algorithm for computing the discrete Fourier transform is extended considerably for certain large transform lengths. This is accomplished by performing the cyclic convolution, required by Winograd's method, by a fast transform over certain complex integer fields. This algorithm requires fewer multiplications than either the standard fast Fourier transform or Winograd's more conventional algorithms.
An improved Camshift algorithm for target recognition
NASA Astrophysics Data System (ADS)
Fu, Min; Cai, Chao; Mao, Yusu
2015-12-01
Camshift algorithm and three frame difference algorithm are the popular target recognition and tracking methods. Camshift algorithm requires a manual initialization of the search window, which needs the subjective error and coherence, and only in the initialization calculating a color histogram, so the color probability model cannot be updated continuously. On the other hand, three frame difference method does not require manual initialization search window, it can make full use of the motion information of the target only to determine the range of motion. But it is unable to determine the contours of the object, and can not make use of the color information of the target object. Therefore, the improved Camshift algorithm is proposed to overcome the disadvantages of the original algorithm, the three frame difference operation is combined with the object's motion information and color information to identify the target object. The improved Camshift algorithm is realized and shows better performance in the recognition and tracking of the target.
LC-Grid: a linear global contact search algorithm for finite element analysis
NASA Astrophysics Data System (ADS)
Chen, Hu; Lei, Zhou; Zang, Mengyan
2014-11-01
The contact searching is computationally intensive and its memory requirement is highly demanding; therefore, it is significant to develop an efficient contact search algorithm with less memory required. In this paper, we propose an efficient global contact search algorithm with linear complexity in terms of computational cost and memory requirement for the finite element analysis of contact problems. This algorithm is named LC-Grid (Lei devised the algorithm and Chen implemented it). The contact space is decomposed; thereafter, all contact nodes and segments are firstly mapped onto layers, then onto rows and lastly onto cells. In each mapping level, the linked-list technique is used for the efficient storing and retrieval of contact nodes and segments. The contact detection is performed in each non-empty cell along non-empty rows in each non-empty layer, and moves to the next non-empty layer once a layer is completed. The use of migration strategy makes the algorithm insensitive to mesh size. The properties of this algorithm are investigated and numerically verified to be linearly proportional to the number of contact segments. Besides, the ideal ranges of two significant scale factors of cell size and buffer zone which strongly affect computational efficiency are determined via an illustrative example.
SLAP lesions: a treatment algorithm.
Brockmeyer, Matthias; Tompkins, Marc; Kohn, Dieter M; Lorbach, Olaf
2016-02-01
Tears of the superior labrum involving the biceps anchor are a common entity, especially in athletes, and may highly impair shoulder function. If conservative treatment fails, successful arthroscopic repair of symptomatic SLAP lesions has been described in the literature particularly for young athletes. However, the results in throwing athletes are less successful with a significant amount of patients who will not regain their pre-injury level of performance. The clinical results of SLAP repairs in middle-aged and older patients are mixed, with worse results and higher revision rates as compared to younger patients. In this population, tenotomy or tenodesis of the biceps tendon is a viable alternative to SLAP repairs in order to improve clinical outcomes. The present article introduces a treatment algorithm for SLAP lesions based upon the recent literature as well as the authors' clinical experience. The type of lesion, age of patient, concomitant lesions, and functional requirements, as well as sport activity level of the patient, need to be considered. Moreover, normal variations and degenerative changes in the SLAP complex have to be distinguished from "true" SLAP lesions in order to improve results and avoid overtreatment. The suggestion for a treatment algorithm includes: type I: conservative treatment or arthroscopic debridement, type II: SLAP repair or biceps tenotomy/tenodesis, type III: resection of the instable bucket-handle tear, type IV: SLAP repair (biceps tenotomy/tenodesis if >50 % of biceps tendon is affected), type V: Bankart repair and SLAP repair, type VI: resection of the flap and SLAP repair, and type VII: refixation of the anterosuperior labrum and SLAP repair. PMID:26818554
The Structure and Evolution of LOCBURST: The BATSE Burst Location Algorithm
NASA Technical Reports Server (NTRS)
Pendleton, Geoffrey N.; Briggs, Michael S.; Kippen, R. Marc; Paciesas, William S.; Stollberg, Mark; Woods, Pete; Meegan, Charles A.; Fishman, Gerald J.; McCollough, Mike L.; Connaughton, Valerie
1999-01-01
The gamma-ray burst (GRB) location algorithm used to produce the BATSE GRB locations is described. The general flow of control of the current location algorithm is presented, and the significant properties of the various physical inputs required are identified. The development of the burst location algorithm during the releases of the BATSE IB, 2B, and 3B GRB catalogs is presented so that the reasons for the differences in the positions and error estimates between the catalogs can be understood. In particular, differences between the 2B and 3B locations are discussed for events that have moved significantly and the reasons for the changes explained. The locations of bursts located independently by the interplanetary network (IPN) are used to illustrate the effect on burst location accuracy of various components of the algorithm. IPN data and locations from other gamma-ray instruments are used to calculate estimates of the systematic errors on BATSE burst locations.
Library of Continuation Algorithms
Energy Science and Technology Software Center (ESTSC)
2005-03-01
LOCA (Library of Continuation Algorithms) is scientific software written in C++ that provides advanced analysis tools for nonlinear systems. In particular, it provides parameter continuation algorithms. bifurcation tracking algorithms, and drivers for linear stability analysis. The algorithms are aimed at large-scale applications that use Newtons method for their nonlinear solve.
Geist, G.A.; Howell, G.W.; Watkins, D.S.
1997-11-01
The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrowband, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the BR algorithm and gives numerical evidence that it works well in conjunction with the Lanczos process. On the biggest problems run so far, the BR algorithm beats the QR algorithm by a factor of 30--60 in computing time and a factor of over 100 in matrix storage space.
A quantum Algorithm for the Moebius Function
NASA Astrophysics Data System (ADS)
Love, Peter
We give an efficient quantum algorithm for the Moebius function from the natural numbers to -1,0,1. The cost of the algorithm is asymptotically quadratic in log n and does not require the computation of the prime factorization of n as an intermediate step.
A fast algorithm for sparse matrix computations related to inversion
Li, S.; Wu, W.; Darve, E.
2013-06-01
We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green’s functions G{sup r} and G{sup <} for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round
Highlights of TOMS Version 9 Total Ozone Algorithm
NASA Technical Reports Server (NTRS)
Bhartia, Pawan; Haffner, David
2012-01-01
The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side
Ocean observations with EOS/MODIS: Algorithm Development and Post Launch Studies
NASA Technical Reports Server (NTRS)
Gordon, Howard R.
1998-01-01
Significant accomplishments made during the present reporting period: (1) We expanded our "spectral-matching" algorithm (SMA), for identifying the presence of absorbing aerosols and simultaneously performing atmospheric correction and derivation of the ocean's bio-optical parameters, to the point where it could be added as a subroutine to the MODIS water-leaving radiance algorithm; (2) A modification to the SMA that does not require detailed aerosol models has been developed. This is important as the requirement for realistic aerosol models has been a weakness of the SMA; and (3) We successfully acquired micro pulse lidar data in a Saharan dust outbreak during ACE-2 in the Canary Islands.
Parallel Algorithms for Graph Optimization using Tree Decompositions
Weerapurage, Dinesh P; Sullivan, Blair D; Groer, Christopher S
2013-01-01
Although many NP-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of required dynamic programming tables and excessive running times of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree-decomposition based approach to solve maximum weighted independent set. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.
Comparison of Fully Numerical Predictor-Corrector and Apollo Skip Entry Guidance Algorithms
NASA Astrophysics Data System (ADS)
Brunner, Christopher W.; Lu, Ping
2012-09-01
The dramatic increase in computational power since the Apollo program has enabled the development of numerical predictor-corrector (NPC) entry guidance algorithms that allow on-board accurate determination of a vehicle's trajectory. These algorithms are sufficiently mature to be flown. They are highly adaptive, especially in the face of extreme dispersion and off-nominal situations compared with reference-trajectory following algorithms. The performance and reliability of entry guidance are critical to mission success. This paper compares the performance of a recently developed fully numerical predictor-corrector entry guidance (FNPEG) algorithm with that of the Apollo skip entry guidance. Through extensive dispersion testing, it is clearly demonstrated that the Apollo skip entry guidance algorithm would be inadequate in meeting the landing precision requirement for missions with medium (4000-7000 km) and long (>7000 km) downrange capability requirements under moderate dispersions chiefly due to poor modeling of atmospheric drag. In the presence of large dispersions, a significant number of failures occur even for short-range missions due to the deviation from planned reference trajectories. The FNPEG algorithm, on the other hand, is able to ensure high landing precision in all cases tested. All factors considered, a strong case is made for adopting fully numerical algorithms for future skip entry missions.
Investigations into a new algorithm for calculating H infinity optimal controllers
NASA Technical Reports Server (NTRS)
Irwin, R. Dennis
1989-01-01
A new algorithm for calculating H (sup infinity) optimal controllers is investigated. The algorithm is significantly simpler than existing approaches and yields much simpler controllers. The design equations are first presented. Special system transformations required to apply the algorithm are then presented. The use of the algorithm with sampled-data systems is outlined in detail. Several constraints on the characteristics of the problem formulation are required for the application of the design equations. The consequences of these constraints are investigated by applying the algorithm to a simplified design for a subsystem of a large space structure ground test facility. The investigation of these constraints is continued by application of the design equations and constraints to an extremely simple tracking problem. The result of these investigations is the development of a frequency dependent weighting strategy that allows realistic control problems to be cast in a form compatible with the new algorithm. Further work is indicated in the area of developing strategies for choosing frequency-dependent weights to achieve specific design goals. The use of the freedom in problem formulation to achieve robustness/performance tradeoffs should also be investigated. It is not clear that the algorithm always leads to simpler controllers. The more restrictive formulation may dictate that frequency-dependent weighting adds to the controller order disproportionately. This effect must also be investigated.
A TLD dose algorithm using artificial neural networks
Moscovitch, M.; Rotunda, J.E.; Tawil, R.A.; Rathbone, B.A.
1995-12-31
An artificial neural network was designed and used to develop a dose algorithm for a multi-element thermoluminescence dosimeter (TLD). The neural network architecture is based on the concept of functional links network (FLN). Neural network is an information processing method inspired by the biological nervous system. A dose algorithm based on neural networks is fundamentally different as compared to conventional algorithms, as it has the capability to learn from its own experience. The neural network algorithm is shown the expected dose values (output) associated with given responses of a multi-element dosimeter (input) many times. The algorithm, being trained that way, eventually is capable to produce its own unique solution to similar (but not exactly the same) dose calculation problems. For personal dosimetry, the output consists of the desired dose components: deep dose, shallow dose and eye dose. The input consists of the TL data obtained from the readout of a multi-element dosimeter. The neural network approach was applied to the Harshaw Type 8825 TLD, and was shown to significantly improve the performance of this dosimeter, well within the U.S. accreditation requirements for personnel dosimeters.
A simple suboptimal least-squares algorithm for attitude determination with multiple sensors
NASA Technical Reports Server (NTRS)
Brozenec, Thomas F.; Bender, Douglas J.
1994-01-01
faster than all but a similarly specialized version of the QUEST algorithm. We also introduce a novel measurement averaging technique which reduces the n-measurement case to the two measurement case for our particular application, a star tracker and earth sensor mounted on an earth-pointed geosynchronous communications satellite. Using this technique, many n-measurement problems reduce to less than or equal to 3 measurements; this reduces the amount of required calculation without significant degradation in accuracy. Finally, we present the results of some tests which compare the least-squares algorithm with the QUEST and FOAM algorithms in the two-measurement case. For our example case, all three algorithms performed with similar accuracy.
Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees
Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng
2015-01-01
In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597
An efficient parallel termination detection algorithm
Baker, A. H.; Crivelli, S.; Jessup, E. R.
2004-05-27
Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Of these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.
Fighting Censorship with Algorithms
NASA Astrophysics Data System (ADS)
Mahdian, Mohammad
In countries such as China or Iran where Internet censorship is prevalent, users usually rely on proxies or anonymizers to freely access the web. The obvious difficulty with this approach is that once the address of a proxy or an anonymizer is announced for use to the public, the authorities can easily filter all traffic to that address. This poses a challenge as to how proxy addresses can be announced to users without leaking too much information to the censorship authorities. In this paper, we formulate this question as an interesting algorithmic problem. We study this problem in a static and a dynamic model, and give almost tight bounds on the number of proxy servers required to give access to n people k of whom are adversaries. We will also discuss how trust networks can be used in this context.
An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks
Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen
2016-01-01
The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper. PMID:27044001
An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.
Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen
2016-01-01
The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper. PMID:27044001
WDM Multicast Tree Construction Algorithms and Their Comparative Evaluations
NASA Astrophysics Data System (ADS)
Makabe, Tsutomu; Mikoshi, Taiju; Takenaka, Toyofumi
We propose novel tree construction algorithms for multicast communication in photonic networks. Since multicast communications consume many more link resources than unicast communications, effective algorithms for route selection and wavelength assignment are required. We propose a novel tree construction algorithm, called the Weighted Steiner Tree (WST) algorithm and a variation of the WST algorithm, called the Composite Weighted Steiner Tree (CWST) algorithm. Because these algorithms are based on the Steiner Tree algorithm, link resources among source and destination pairs tend to be commonly used and link utilization ratios are improved. Because of this, these algorithms can accept many more multicast requests than other multicast tree construction algorithms based on the Dijkstra algorithm. However, under certain delay constraints, the blocking characteristics of the proposed Weighted Steiner Tree algorithm deteriorate since some light paths between source and destinations use many hops and cannot satisfy the delay constraint. In order to adapt the approach to the delay-sensitive environments, we have devised the Composite Weighted Steiner Tree algorithm comprising the Weighted Steiner Tree algorithm and the Dijkstra algorithm for use in a delay constrained environment such as an IPTV application. In this paper, we also give the results of simulation experiments which demonstrate the superiority of the proposed Composite Weighted Steiner Tree algorithm compared with the Distributed Minimum Hop Tree (DMHT) algorithm, from the viewpoint of the light-tree request blocking.
Threshold extended ID3 algorithm
NASA Astrophysics Data System (ADS)
Kumar, A. B. Rajesh; Ramesh, C. Phani; Madhusudhan, E.; Padmavathamma, M.
2012-04-01
Information exchange over insecure networks needs to provide authentication and confidentiality to the database in significant problem in datamining. In this paper we propose a novel authenticated multiparty ID3 Algorithm used to construct multiparty secret sharing decision tree for implementation in medical transactions.
ENAS-RIF algorithm for image restoration
NASA Astrophysics Data System (ADS)
Yang, Yang; Yang, Zhen-wen; Shen, Tian-shuang; Chen, Bo
2012-11-01
mage of objects is inevitably encountered by space-based working in the atmospheric turbulence environment, such as those used in astronomy, remote sensing and so on. The observed images are seriously blurred. The restoration is required for reconstruction turbulence degraded images. In order to enhance the performance of image restoration, a novel enhanced nonnegativity and support constants recursive inverse filtering(ENAS-RIF) algorithm was presented, which was based on the reliable support region and enhanced cost function. Firstly, the Curvelet denoising algorithm was used to weaken image noise. Secondly, the reliable object support region estimation was used to accelerate the algorithm convergence. Then, the average gray was set as the gray of image background pixel. Finally, an object construction limit and the logarithm function were add to enhance algorithm stability. The experimental results prove that the convergence speed of the novel ENAS-RIF algorithm is faster than that of NAS-RIF algorithm and it is better in image restoration.
Orbital objects detection algorithm using faint streaks
NASA Astrophysics Data System (ADS)
Tagawa, Makoto; Yanagisawa, Toshifumi; Kurosaki, Hirohisa; Oda, Hiroshi; Hanada, Toshiya
2016-02-01
This study proposes an algorithm to detect orbital objects that are small or moving at high apparent velocities from optical images by utilizing their faint streaks. In the conventional object-detection algorithm, a high signal-to-noise-ratio (e.g., 3 or more) is required, whereas in our proposed algorithm, the signals are summed along the streak direction to improve object-detection sensitivity. Lower signal-to-noise ratio objects were detected by applying the algorithm to a time series of images. The algorithm comprises the following steps: (1) image skewing, (2) image compression along the vertical axis, (3) detection and determination of streak position, (4) searching for object candidates using the time-series streak-position data, and (5) selecting the candidate with the best linearity and reliability. Our algorithm's ability to detect streaks with signals weaker than the background noise was confirmed using images from the Australia Remote Observatory.
HEATR project: ATR algorithm parallelization
NASA Astrophysics Data System (ADS)
Deardorf, Catherine E.
1998-09-01
High Performance Computing (HPC) Embedded Application for Target Recognition (HEATR) is a project funded by the High Performance Computing Modernization Office through the Common HPC Software Support Initiative (CHSSI). The goal of CHSSI is to produce portable, parallel, multi-purpose, freely distributable, support software to exploit emerging parallel computing technologies and enable application of scalable HPC's for various critical DoD applications. Specifically, the CHSSI goal for HEATR is to provide portable, parallel versions of several existing ATR detection and classification algorithms to the ATR-user community to achieve near real-time capability. The HEATR project will create parallel versions of existing automatic target recognition (ATR) detection and classification algorithms and generate reusable code that will support porting and software development process for ATR HPC software. The HEATR Team has selected detection/classification algorithms from both the model- based and training-based (template-based) arena in order to consider the parallelization requirements for detection/classification algorithms across ATR technology. This would allow the Team to assess the impact that parallelization would have on detection/classification performance across ATR technology. A field demo is included in this project. Finally, any parallel tools produced to support the project will be refined and returned to the ATR user community along with the parallel ATR algorithms. This paper will review: (1) HPCMP structure as it relates to HEATR, (2) Overall structure of the HEATR project, (3) Preliminary results for the first algorithm Alpha Test, (4) CHSSI requirements for HEATR, and (5) Project management issues and lessons learned.
NASA Technical Reports Server (NTRS)
Robinson, Michael; Steiner, Matthias; Wolff, David B.; Ferrier, Brad S.; Kessinger, Cathy; Einaudi, Franco (Technical Monitor)
2000-01-01
The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. A fundamental and extremely important step in creating high-quality GV products is radar data quality control. Quality control (QC) processing of TRMM GV radar data is based on some automated procedures, but the current QC algorithm is not fully operational and requires significant human interaction to assure satisfactory results. Moreover, the TRMM GV QC algorithm, even with continuous manual tuning, still can not completely remove all types of spurious echoes. In an attempt to improve the current operational radar data QC procedures of the TRMM GV effort, an intercomparison of several QC algorithms has been conducted. This presentation will demonstrate how various radar data QC algorithms affect accumulated radar rainfall products. In all, six different QC algorithms will be applied to two months of WSR-88D radar data from Melbourne, Florida. Daily, five-day, and monthly accumulated radar rainfall maps will be produced for each quality-controlled data set. The QC algorithms will be evaluated and compared based on their ability to remove spurious echoes without removing significant precipitation. Strengths and weaknesses of each algorithm will be assessed based on, their abilit to mitigate both erroneous additions and reductions in rainfall accumulation from spurious echo contamination and true precipitation removal, respectively. Contamination from individual spurious echo categories will be quantified to further diagnose the abilities of each radar QC algorithm. Finally, a cost-benefit analysis will be conducted to determine if a more automated QC algorithm is a viable alternative to the current, labor-intensive QC algorithm employed by TRMM GV.
GPU Accelerated Event Detection Algorithm
Energy Science and Technology Software Center (ESTSC)
2011-05-25
Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but alsomore » model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.« less
Conflict-Aware Scheduling Algorithm
NASA Technical Reports Server (NTRS)
Wang, Yeou-Fang; Borden, Chester
2006-01-01
conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.
Benchmarking image fusion algorithm performance
NASA Astrophysics Data System (ADS)
Howell, Christopher L.
2012-06-01
Registering two images produced by two separate imaging sensors having different detector sizes and fields of view requires one of the images to undergo transformation operations that may cause its overall quality to degrade with regards to visual task performance. This possible change in image quality could add to an already existing difference in measured task performance. Ideally, a fusion algorithm would take as input unaltered outputs from each respective sensor used in the process. Therefore, quantifying how well an image fusion algorithm performs should be base lined to whether the fusion algorithm retained the performance benefit achievable by each independent spectral band being fused. This study investigates an identification perception experiment using a simple and intuitive process for discriminating between image fusion algorithm performances. The results from a classification experiment using information theory based image metrics is presented and compared to perception test results. The results show an effective performance benchmark for image fusion algorithms can be established using human perception test data. Additionally, image metrics have been identified that either agree with or surpass the performance benchmark established.
Algorithms for automated DNA assembly
Densmore, Douglas; Hsiau, Timothy H.-C.; Kittleson, Joshua T.; DeLoache, Will; Batten, Christopher; Anderson, J. Christopher
2010-01-01
Generating a defined set of genetic constructs within a large combinatorial space provides a powerful method for engineering novel biological functions. However, the process of assembling more than a few specific DNA sequences can be costly, time consuming and error prone. Even if a correct theoretical construction scheme is developed manually, it is likely to be suboptimal by any number of cost metrics. Modular, robust and formal approaches are needed for exploring these vast design spaces. By automating the design of DNA fabrication schemes using computational algorithms, we can eliminate human error while reducing redundant operations, thus minimizing the time and cost required for conducting biological engineering experiments. Here, we provide algorithms that optimize the simultaneous assembly of a collection of related DNA sequences. We compare our algorithms to an exhaustive search on a small synthetic dataset and our results show that our algorithms can quickly find an optimal solution. Comparison with random search approaches on two real-world datasets show that our algorithms can also quickly find lower-cost solutions for large datasets. PMID:20335162
Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms
NASA Technical Reports Server (NTRS)
Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)
2000-01-01
In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.
Significant lexical relationships
Pedersen, T.; Kayaalp, M.; Bruce, R.
1996-12-31
Statistical NLP inevitably deals with a large number of rare events. As a consequence, NLP data often violates the assumptions implicit in traditional statistical procedures such as significance testing. We describe a significance test, an exact conditional test, that is appropriate for NLP data and can be performed using freely available software. We apply this test to the study of lexical relationships and demonstrate that the results obtained using this test are both theoretically more reliable and different from the results obtained using previously applied tests.
The Structure of Evolution LOCBURST: The BATSE Burst Location Algorithm
NASA Technical Reports Server (NTRS)
Pendleton, Geoffrey N.; Briggs, Michael S.; Kippen, R. March; Paciesas, William S.; Stollberg, Mark; Woods, Pete; Meegan, C. A.; Fishman, G. J.; McCollough, M. L.; Connaughton, V.
1998-01-01
The gamma-ray bursts (GRB) location algorithm used to produce the BATSE GRB locations is described. The general flow of control of the current location algorithm is presented and the significant properties of the various physical inputs required are identified. The development of the burst location algorithm during the releases of the BATSE 1B, 2B, and 3B gamma-ray burst catalogs is presented so that the reasons for the differences in the positions and error estimates between the catalogs can be understood. In particular, differences between the 2B and 3B locations are discussed for events that have moved significantly and the reasons for the changes explained. The locations of bursts located independently by the interplanetary network are used to illustrate the effect on burst location accuracy of various components of the algorithm. IPN data as well as locations from other gamma-ray instruments are used to calculate estimates of the systematic errors on BATSE burst locations.
An automatic and fast centerline extraction algorithm for virtual colonoscopy.
Jiang, Guangxiang; Gu, Lixu
2005-01-01
This paper introduces a new refined centerline extraction algorithm, which is based on and significantly improved from distance mapping algorithms. The new approach include three major parts: employing a colon segmentation method; designing and realizing a fast Euclidean Transform algorithm and inducting boundary voxels cutting (BVC) approach. The main contribution is the BVC processing, which greatly speeds up the Dijkstra algorithm and improves the whole performance of the new algorithm. Experimental results demonstrate that the new centerline algorithm was more efficient and accurate comparing with existing algorithms. PMID:17281406
Statistical Significance Testing.
ERIC Educational Resources Information Center
McLean, James E., Ed.; Kaufman, Alan S., Ed.
1998-01-01
The controversy about the use or misuse of statistical significance testing has become the major methodological issue in educational research. This special issue contains three articles that explore the controversy, three commentaries on these articles, an overall response, and three rejoinders by the first three authors. They are: (1)…
Lack of Statistical Significance
ERIC Educational Resources Information Center
Kehle, Thomas J.; Bray, Melissa A.; Chafouleas, Sandra M.; Kawano, Takuji
2007-01-01
Criticism has been leveled against the use of statistical significance testing (SST) in many disciplines. However, the field of school psychology has been largely devoid of critiques of SST. Inspection of the primary journals in school psychology indicated numerous examples of SST with nonrandom samples and/or samples of convenience. In this…
Reasoning about systolic algorithms
Purushothaman, S.
1986-01-01
Systolic algorithms are a class of parallel algorithms, with small grain concurrency, well suited for implementation in VLSI. They are intended to be implemented as high-performance, computation-bound back-end processors and are characterized by a tesselating interconnection of identical processing elements. This dissertation investigates the problem of providing correctness of systolic algorithms. The following are reported in this dissertation: (1) a methodology for verifying correctness of systolic algorithms based on solving the representation of an algorithm as recurrence equations. The methodology is demonstrated by proving the correctness of a systolic architecture for optimal parenthesization. (2) The implementation of mechanical proofs of correctness of two systolic algorithms, a convolution algorithm and an optimal parenthesization algorithm, using the Boyer-Moore theorem prover. (3) An induction principle for proving correctness of systolic arrays which are modular. Two attendant inference rules, weak equivalence and shift transformation, which capture equivalent behavior of systolic arrays, are also presented.
Algorithm-development activities
NASA Technical Reports Server (NTRS)
Carder, Kendall L.
1994-01-01
The task of algorithm-development activities at USF continues. The algorithm for determining chlorophyll alpha concentration, (Chl alpha) and gelbstoff absorption coefficient for SeaWiFS and MODIS-N radiance data is our current priority.
Accurate Finite Difference Algorithms
NASA Technical Reports Server (NTRS)
Goodrich, John W.
1996-01-01
Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.
Automatic control algorithm effects on energy production
NASA Technical Reports Server (NTRS)
Mcnerney, G. M.
1981-01-01
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
NASA Astrophysics Data System (ADS)
Dunbar, P. K.; Furtney, M.; McLean, S. J.; Sweeney, A. D.
2014-12-01
Tsunamis have inflicted death and destruction on the coastlines of the world throughout history. The occurrence of tsunamis and the resulting effects have been collected and studied as far back as the second millennium B.C. The knowledge gained from cataloging and examining these events has led to significant changes in our understanding of tsunamis, tsunami sources, and methods to mitigate the effects of tsunamis. The most significant, not surprisingly, are often the most devastating, such as the 2011 Tohoku, Japan earthquake and tsunami. The goal of this poster is to give a brief overview of the occurrence of tsunamis and then focus specifically on several significant tsunamis. There are various criteria to determine the most significant tsunamis: the number of deaths, amount of damage, maximum runup height, had a major impact on tsunami science or policy, etc. As a result, descriptions will include some of the most costly (2011 Tohoku, Japan), the most deadly (2004 Sumatra, 1883 Krakatau), and the highest runup ever observed (1958 Lituya Bay, Alaska). The discovery of the Cascadia subduction zone as the source of the 1700 Japanese "Orphan" tsunami and a future tsunami threat to the U.S. northwest coast, contributed to the decision to form the U.S. National Tsunami Hazard Mitigation Program. The great Lisbon earthquake of 1755 marked the beginning of the modern era of seismology. Knowledge gained from the 1964 Alaska earthquake and tsunami helped confirm the theory of plate tectonics. The 1946 Alaska, 1952 Kuril Islands, 1960 Chile, 1964 Alaska, and the 2004 Banda Aceh, tsunamis all resulted in warning centers or systems being established.The data descriptions on this poster were extracted from NOAA's National Geophysical Data Center (NGDC) global historical tsunami database. Additional information about these tsunamis, as well as water level data can be found by accessing the NGDC website www.ngdc.noaa.gov/hazard/
Wavelet based edge detection algorithm for web surface inspection of coated board web
NASA Astrophysics Data System (ADS)
Barjaktarovic, M.; Petricevic, S.
2010-07-01
This paper presents significant improvement of the already installed vision system. System was designed for real time coated board inspection. The improvement is achieved with development of a new algorithm for edge detection. The algorithm is based on the redundant (undecimated) wavelet transform. Compared to the existing algorithm better delineation of edges is achieved. This yields to better defect detection probability and more accurate geometrical classification, which will provide additional reduction of waste. Also, algorithm will provide detailed classification and more reliably tracking of defects. This improvement requires minimal changes in processing hardware, only a replacement of the graphic card would be needed, adding only negligibly to the system cost. Other changes are accomplished entirely in the image processing software.
A fast algorithm for parallel computation of multibody dynamics on MIMD parallel architectures
NASA Technical Reports Server (NTRS)
Fijany, Amir; Kwan, Gregory; Bagherzadeh, Nader
1993-01-01
In this paper the implementation of a parallel O(LogN) algorithm for computation of rigid multibody dynamics on a Hypercube MIMD parallel architecture is presented. To our knowledge, this is the first algorithm that achieves the time lower bound of O(LogN) by using an optimal number of O(N) processors. However, in addition to its theoretical significance, the algorithm is also highly efficient for practical implementation on commercially available MIMD parallel architectures due to its highly coarse grain size and simple communication and synchronization requirements. We present a multilevel parallel computation strategy for implementation of the algorithm on a Hypercube. This strategy allows the exploitation of parallelism at several computational levels as well as maximum overlapping of computation and communication to increase the performance of parallel computation.
Experiments with a Parallel Multi-Objective Evolutionary Algorithm for Scheduling
NASA Technical Reports Server (NTRS)
Brown, Matthew; Johnston, Mark D.
2013-01-01
Evolutionary multi-objective algorithms have great potential for scheduling in those situations where tradeoffs among competing objectives represent a key requirement. One challenge, however, is runtime performance, as a consequence of evolving not just a single schedule, but an entire population, while attempting to sample the Pareto frontier as accurately and uniformly as possible. The growing availability of multi-core processors in end user workstations, and even laptops, has raised the question of the extent to which such hardware can be used to speed up evolutionary algorithms. In this paper we report on early experiments in parallelizing a Generalized Differential Evolution (GDE) algorithm for scheduling long-range activities on NASA's Deep Space Network. Initial results show that significant speedups can be achieved, but that performance does not necessarily improve as more cores are utilized. We describe our preliminary results and some initial suggestions from parallelizing the GDE algorithm. Directions for future work are outlined.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
Poynee, L A
2003-05-06
Shack-Hartmann based Adaptive Optics system with a point-source reference normally use a wave-front sensing algorithm that estimates the centroid (center of mass) of the point-source image 'spot' to determine the wave-front slope. The centroiding algorithm suffers for several weaknesses. For a small number of pixels, the algorithm gain is dependent on spot size. The use of many pixels on the detector leads to significant propagation of read noise. Finally, background light or spot halo aberrations can skew results. In this paper an alternative algorithm that suffers from none of these problems is proposed: correlation of the spot with a ideal reference spot. The correlation method is derived and a theoretical analysis evaluates its performance in comparison with centroiding. Both simulation and data from real AO systems are used to illustrate the results. The correlation algorithm is more robust than centroiding, but requires more computation.
An algorithm for the automatic synchronization of Omega receivers
NASA Technical Reports Server (NTRS)
Stonestreet, W. M.; Marzetta, T. L.
1977-01-01
The Omega navigation system and the requirement for receiver synchronization are discussed. A description of the synchronization algorithm is provided. The numerical simulation and its associated assumptions were examined and results of the simulation are presented. The suggested form of the synchronization algorithm and the suggested receiver design values were surveyed. A Fortran of the synchronization algorithm used in the simulation was also included.
Significant biases affecting abundance determinations
NASA Astrophysics Data System (ADS)
Wesson, Roger
2015-08-01
I have developed two highly efficient codes to automate analyses of emission line nebulae. The tools place particular emphasis on the propagation of uncertainties. The first tool, ALFA, uses a genetic algorithm to rapidly optimise the parameters of gaussian fits to line profiles. It can fit emission line spectra of arbitrary resolution, wavelength range and depth, with no user input at all. It is well suited to highly multiplexed spectroscopy such as that now being carried out with instruments such as MUSE at the VLT. The second tool, NEAT, carries out a full analysis of emission line fluxes, robustly propagating uncertainties using a Monte Carlo technique.Using these tools, I have found that considerable biases can be introduced into abundance determinations if the uncertainty distribution of emission lines is not well characterised. For weak lines, normally distributed uncertainties are generally assumed, though it is incorrect to do so, and significant biases can result. I discuss observational evidence of these biases. The two new codes contain routines to correctly characterise the probability distributions, giving more reliable results in analyses of emission line nebulae.
NASA Astrophysics Data System (ADS)
Litva, John; Zeytinoglu, Mehmet
1990-07-01
A study of the effects of mutual coupling on the performance on direction finding algorithms is presented. The MUltiple SIgnal Classification (MUSIC) and maximum likelihood (ML) algorithms resolved non-coherent and coherent incident wave fields with relative ease when ideal array response models were used. When array output vectors were simulated using free space and lossy ground models which include mutual coupling effects, the performance of the unmodified direction finding algorithms declined sharply. In particular, estimates from unmodified algorithms exhibited a constant, deterministic bias term. Algorithms modified for this bias term displayed a significant residual bias in attempts to resolve incident wave field with closely spaced source signals. Array steering vectors are the main components through which the array models are coupled. Free space and lossy ground response modes that take mutual coupling effects into consideration were modified by assembling array steering vectors directly from simulated raw data. These modified algorithms exhibited exemplary performance in resolving fields from closely spaced source signals when the array output vectors were derived from the same free space or lossy ground models. The MUSIC algorithm permitted array steering vectors modified with free space response data to be used with the array output derived for the lossy ground response mode. However, it was applicable only to non-coherent source signals. The ML algorithm performed equally well with non-correlated and coherent source signals but it had to be perfectly matched with the actual array response. Computation requirements were very demanding for the ML algorithm.
An algorithm for neurite outgrowth reconstruction
NASA Technical Reports Server (NTRS)
Weaver, Christina M.; Pinezich, John D.; Lindquist, W. Brent; Vazquez, Marcelo E.
2003-01-01
We present a numerical method which provides the ability to analyze digitized microscope images of retinal explants and quantify neurite outgrowth. Few parameters are required as input and limited user interaction is necessary to process an entire experiment of images. This eliminates fatigue related errors and user-related bias common to manual analysis. The method does not rely on stained images and handles images of variable quality. The algorithm is used to determine time and dose dependent, in vitro, neurotoxic effects of 1 GeV per nucleon iron particles in retinal explants. No neurotoxic effects are detected until 72 h after exposure; at 72 h, significant reductions of neurite outgrowth occurred at doses higher than 10 cGy.
Linear vs. function-based dose algorithm designs.
Stanford, N
2011-03-01
The performance requirements prescribed in IEC 62387-1, 2007 recommend linear, additive algorithms for external dosimetry [IEC. Radiation protection instrumentation--passive integrating dosimetry systems for environmental and personal monitoring--Part 1: General characteristics and performance requirements. IEC 62387-1 (2007)]. Neither of the two current standards for performance of external dosimetry in the USA address the additivity of dose results [American National Standards Institute, Inc. American National Standard for dosimetry personnel dosimetry performance criteria for testing. ANSI/HPS N13.11 (2009); Department of Energy. Department of Energy Standard for the performance testing of personnel dosimetry systems. DOE/EH-0027 (1986)]. While there are significant merits to adopting a purely linear solution to estimating doses from multi-element external dosemeters, differences in the standards result in technical as well as perception challenges in designing a single algorithm approach that will satisfy both IEC and USA external dosimetry performance requirements. The dosimetry performance testing standards in the USA do not incorporate type testing, but rely on biennial performance tests to demonstrate proficiency in a wide range of pure and mixed fields. The test results are used exclusively to judge the system proficiency, with no specific requirements on the algorithm design. Technical challenges include mixed beta/photon fields with a beta dose as low as 0.30 mSv mixed with 0.05 mSv of low-energy photons. Perception-based challenges, resulting from over 20 y of experience with this type of performance testing in the USA, include the common belief that the overall quality of the dosemeter performance can be judged from performance to pure fields. This paper presents synthetic testing results from currently accredited function-based algorithms and new developed purely linear algorithms. A comparison of the performance data highlights the benefits of each
Distilling the Verification Process for Prognostics Algorithms
NASA Technical Reports Server (NTRS)
Roychoudhury, Indranil; Saxena, Abhinav; Celaya, Jose R.; Goebel, Kai
2013-01-01
The goal of prognostics and health management (PHM) systems is to ensure system safety, and reduce downtime and maintenance costs. It is important that a PHM system is verified and validated before it can be successfully deployed. Prognostics algorithms are integral parts of PHM systems. This paper investigates a systematic process of verification of such prognostics algorithms. To this end, first, this paper distinguishes between technology maturation and product development. Then, the paper describes the verification process for a prognostics algorithm as it moves up to higher maturity levels. This process is shown to be an iterative process where verification activities are interleaved with validation activities at each maturation level. In this work, we adopt the concept of technology readiness levels (TRLs) to represent the different maturity levels of a prognostics algorithm. It is shown that at each TRL, the verification of a prognostics algorithm depends on verifying the different components of the algorithm according to the requirements laid out by the PHM system that adopts this prognostics algorithm. Finally, using simplified examples, the systematic process for verifying a prognostics algorithm is demonstrated as the prognostics algorithm moves up TRLs.
Statistical or biological significance?
Saxon, Emma
2015-01-01
Oat plants grown at an agricultural research facility produce higher yields in Field 1 than in Field 2, under well fertilised conditions and with similar weather exposure; all oat plants in both fields are healthy and show no sign of disease. In this study, the authors hypothesised that the soil microbial community might be different in each field, and these differences might explain the difference in oat plant growth. They carried out a metagenomic analysis of the 16 s ribosomal 'signature' sequences from bacteria in 50 randomly located soil samples in each field to determine the composition of the bacterial community. The study identified >1000 species, most of which were present in both fields. The authors identified two plant growth-promoting species that were significantly reduced in soil from Field 2 (Student's t-test P < 0.05), and concluded that these species might have contributed to reduced yield. PMID:26541972
Anthropological significance of phenylketonuria.
Saugstad, L F
1975-01-01
The highest incidence rates of phenylketonuria (PKU) have been observed in Ireland and Scotlant. Parents heterozygous for PKU in Norway differ significantly from the general population in the Rhesus, Kell and PGM systems. The parents investigated showed an excess of Rh negative, Kell plus and PGM type 1 individuals, which makes them similar to the present populations in Ireland and Scotlant. It is postulated that the heterozygotes for PKU in Norway are descended from a completely assimilated sub-population of Celtic origin, who came or were brought here, 1ooo years ago. Bronze objects of Western European (Scottish, Irish) origin, found in Viking graves widely distributed in Norway, have been taken as evidence of Vikings returning with loot (including a number of Celts) from Western Viking settlements. The continuity of residence since the Viking age in most habitable parts of Norway, and what seems to be a nearly complete regional relationship between the sites where Viking graves contain western imported objects and the birthplaces of grandparents of PKUs identified in Norway, lend further support to the hypothesis that the heterozygotes for PKU in Norway are descended from a completely assimilated subpopulation. The remarkable resemblance between Iceland and Ireland, in respect of several genetic markers (including the Rhesus, PGM and Kell systems), is considered to be an expression of a similar proportion of people of Celtic origin in each of the two countries. Their identical, high incidence rates of PKU are regarded as further evidence of this. The significant decline in the incidence of PKU when one passes from Ireland, Scotland and Iceland, to Denmark and on to Norway and Sweden, is therefore explained as being related to a reduction in the proportion of inhabitants of Celtic extraction in the respective populations. PMID:803884
Testing block subdivision algorithms on block designs
NASA Astrophysics Data System (ADS)
Wiseman, Natalie; Patterson, Zachary
2016-01-01
Integrated land use-transportation models predict future transportation demand taking into account how households and firms arrange themselves partly as a function of the transportation system. Recent integrated models require parcels as inputs and produce household and employment predictions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within blocks. Evaluating block subdivision algorithms is done by way of generating parcels and comparing them to those in a parcel database. Three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from Montreal, Canada. While the authors who developed each of the algorithms have evaluated them, they have used their own metrics and block types to evaluate their own algorithms. This makes it difficult to compare their strengths and weaknesses. The contribution of this paper is in resolving this difficulty with the aim of finding a better algorithm suited to subdividing each block type. The proposed hypothesis is that given the different approaches that block subdivision algorithms take, it's likely that different algorithms are better adapted to subdividing different block types. To test this, a standardized block type classification is used that consists of mutually exclusive and comprehensive categories. A statistical method is used for finding a better algorithm and the probability it will perform well for a given block type. Results suggest the oriented bounding box algorithm performs better for warped non-uniform sites, as well as gridiron and fragmented uniform sites. It also produces more similar parcel areas and widths. The Generalized Parcel Divider 1 algorithm performs better for gridiron non-uniform sites. The Straight Skeleton algorithm performs better for loop and lollipop networks as well as fragmented non-uniform and warped uniform sites. It also produces more similar parcel shapes and patterns.
Scheduling with genetic algorithms
NASA Technical Reports Server (NTRS)
Fennel, Theron R.; Underbrink, A. J., Jr.; Williams, George P. W., Jr.
1994-01-01
In many domains, scheduling a sequence of jobs is an important function contributing to the overall efficiency of the operation. At Boeing, we develop schedules for many different domains, including assembly of military and commercial aircraft, weapons systems, and space vehicles. Boeing is under contract to develop scheduling systems for the Space Station Payload Planning System (PPS) and Payload Operations and Integration Center (POIC). These applications require that we respect certain sequencing restrictions among the jobs to be scheduled while at the same time assigning resources to the jobs. We call this general problem scheduling and resource allocation. Genetic algorithms (GA's) offer a search method that uses a population of solutions and benefits from intrinsic parallelism to search the problem space rapidly, producing near-optimal solutions. Good intermediate solutions are probabalistically recombined to produce better offspring (based upon some application specific measure of solution fitness, e.g., minimum flowtime, or schedule completeness). Also, at any point in the search, any intermediate solution can be accepted as a final solution; allowing the search to proceed longer usually produces a better solution while terminating the search at virtually any time may yield an acceptable solution. Many processes are constrained by restrictions of sequence among the individual jobs. For a specific job, other jobs must be completed beforehand. While there are obviously many other constraints on processes, it is these on which we focussed for this research: how to allocate crews to jobs while satisfying job precedence requirements and personnel, and tooling and fixture (or, more generally, resource) requirements.
On the convergence of the phase gradient autofocus algorithm for synthetic aperture radar imaging
Hicks, M.J.
1996-01-01
Synthetic Aperture Radar (SAR) imaging is a class of coherent range and Doppler signal processing techniques applied to remote sensing. The aperture is synthesized by recording and processing coherent signals at known positions along the flight path. Demands for greater image resolution put an extreme burden on requirements for inertial measurement units that are used to maintain accurate pulse-to-pulse position information. The recently developed Phase Gradient Autofocus algorithm relieves this burden by taking a data-driven digital signal processing approach to estimating the range-invariant phase aberrations due to either uncompensated motions of the SAR platform or to atmospheric turbulence. Although the performance of this four-step algorithm has been demonstrated, its convergence has not been modeled mathematically. A new sensitivity study of algorithm performance is a necessary step towards this model. Insights that are significant to the application of this algorithm to both SAR and to other coherent imaging applications are developed. New details on algorithm implementation identify an easily avoided biased phase estimate. A new algorithm for defining support of the point spread function is proposed, which promises to reduce the number of iterations required even for rural scenes with low signal-to-clutter ratios.
Tectonic significance of serpentinites
NASA Astrophysics Data System (ADS)
Guillot, Stéphane; Schwartz, Stéphane; Reynard, Bruno; Agard, Philippe; Prigent, Cécile
2015-04-01
At plate boundaries, where deformation is localized along centimetre- to kilometre-scale shear zones, the influence of serpentinite on tectonic processes is linked to its unique rheological properties. In this paper we review the physical properties of serpentinites and their role in tectonic processes. At the ocean-continent transition, serpentinization weakens the upper mantle layer, promoting strain localization and allowing the normal faults in the distal margin to root at low angle. Similarly, at slow to ultra-slow spreading ridges, serpentinite is potentially very abundant at the seafloor and locally associated with domal structures. Extensional deformation is localized in a ~ 100 m thick shear zone at the footwall of detachment zones dominated by serpentine derived minerals. Within subduction zone, the depth of decoupling between the mantle wedge and the subducting slab corresponds to the stability depth of serpentine weak mineral. Dehydration of serpentine has also been hypothesized to play an important role in the origin of double seismic zones, however the exact mechanism through which dehydration promotes seismicity remains a matter of debate. During exhumation of high-pressure or ultrahigh-pressure rocks, the opposite trajectories of exhumation and subduction require a decoupling zone within the subducting slab. A serpentinized layer has the potential to become a decoupling zone between the oceanic crust and underlying lithosphere. The buoyancy of serpentinite also likely contributes to eclogite exhumation. Finally, along major strike-slip faults, serpentinites have been associated with fault creep, as well as low fault strength. The presence of serpentinite blocks along creeping segments of active faults worldwide is therefore likely to originate from fluids deriving from the progressive dehydration of the mantle wedge that move such bodies upward.
An efficient QoS-aware routing algorithm for LEO polar constellations
NASA Astrophysics Data System (ADS)
Tian, Xin; Pham, Khanh; Blasch, Erik; Tian, Zhi; Shen, Dan; Chen, Genshe
2013-05-01
In this work, a Quality of Service (QoS)-aware routing (QAR) algorithm is developed for Low-Earth Orbit (LEO) polar constellations. LEO polar orbits are the only type of satellite constellations where inter-plane inter-satellite links (ISLs) are implemented in real world. The QAR algorithm exploits features of the topology of the LEO satellite constellation, which makes it more efficient than general shortest path routing algorithms such as Dijkstra's or extended Bellman-Ford algorithms. Traffic density, priority, and error QoS requirements on communication delays can be easily incorporated into the QAR algorithm through satellite distances. The QAR algorithm also supports efficient load balancing in the satellite network by utilizing the multiple paths from the source satellite to the destination satellite, and effectively lowers the rate of network congestion. The QAR algorithm supports a novel robust routing scheme in LEO polar constellation, which is able to significantly reduce the impact of inter-satellite link (ISL) congestions on QoS in terms of communication delay and jitter.
Algorithmic Summaries of Perioperative Blood Pressure Fluctuations.
Toddenroth, Dennis; Ganslandt, Thomas; Drescher, Caroline; Weith, Thomas; Prokosch, Hans-Ulrich; Schuettler, Juergen; Muenster, Tino
2016-01-01
Automated perioperative measurements such as cardiovascular monitoring data are commonly compared to established upper and lower thresholds, but could also allow for more complex interpretations. Analyzing such time series in extensive electronic medical records for research purposes may itself require customized automation, so we developed a set of algorithms for quantifying different aspects of temporal fluctuations. We implemented conventional measures of dispersion, summaries of absolute gradients between successive values, and Poincaré plots. We aggregated the severity and duration of hypotensive episodes by calculating the average area under different mean arterial pressure (MAP) thresholds. We applied these methods to 30,452 de-identified MAP series, and analyzed the similarity between alternative indices via hierarchical clustering. To explore the potential utility of these propositional metrics, we computed their statistical association with presumed complications due to cardiovascular instability. We observed that hierarchical clustering reliably segregated features that had been designed to quantify dissimilar aspects. Summaries of temporary hypotension turned out to be significantly increased among patient subgroups with subsequent signs of a complicated recovery. These associations were even stronger for measures that were specifically geared to capturing short-term MAP variability. These observations suggest the potential capability of our proposed algorithms for quantifying heterogeneous aspects of short-term MAP fluctuations. Future research might also target a wider selection of outcomes and other attributes that may be subject to intraoperative variability. PMID:27577440
A novel hardware-friendly algorithm for hyperspectral linear unmixing
NASA Astrophysics Data System (ADS)
Guerra, Raúl; Santos, Lucana; López, Sebastián.; Sarmiento, Roberto
2015-10-01
Linear unmixing of hyperspectral images has rapidly become one of the most widely utilized tools for analyzing the content of hyperspectral images captured by state-of-the-art remote hyperspectral sensors. The aforementioned unmixing process consists of the following three sequential steps: dimensionality estimation, endmember extraction and abundances computation. Within this procedure, the first two steps are by far the most demanding from a computational point of view, since they involve a large amount of matrix operations. Moreover, the complex nature of these operations seriously difficult the hardware implementation of these two unmixing steps, leading to non-optimized implementations which are not able to satisfy the strict delay requirements imposed by those applications under real-time or near real-time requirements. This paper uncovers a new algorithm which is capable of estimating the number of endmembers and extracting them from a given hyperspectral image with at least the same accuracy than state-of-the-art approaches while demanding a much lower computational effort, with independence of the characteristics of the image under analysis. In particular, the proposed algorithm is based on the concept of orthogonal projections and allows performing the estimation of the number of end- members and their extraction simultaneously, using simple operations, which can be also easily parallelized. In this sense, it is worth to mention that our algorithm does not perform complex matrix operations, such as the inverse of a matrix or the extraction of eigenvalues and eigenvectors, which makes easier its ulterior hardware. The experimental results obtained with synthetic and real hyperspectral images demonstrate that the accuracy obtained with the proposed algorithm when estimating the number of endmembers and extracting them is similar or better than the one provided by well-known state-of-the-art algorithms, while the complexity of the overall process is
Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Lee, Seungwon; vonAllmen, Paul; Fink, Wolfgang; Petropoulos, Anastassios; Terrile, Richard
2005-01-01
Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.
The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce
NASA Astrophysics Data System (ADS)
Chen, Xi; Zhou, Liqing
2015-12-01
With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.
Algorithms for Automatic Alignment of Arrays
NASA Technical Reports Server (NTRS)
Chatterjee, Siddhartha; Gilbert, John R.; Oliker, Leonid; Schreiber, Robert; Sheffler, Thomas J.
1996-01-01
Aggregate data objects (such as arrays) are distributed across the processor memories when compiling a data-parallel language for a distributed-memory machine. The mapping determines the amount of communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: an alignment that maps all the objects to an abstract template, followed by a distribution that maps the template to the processors. This paper describes algorithms for solving the various facets of the alignment problem: axis and stride alignment, static and mobile offset alignment, and replication labeling. We show that optimal axis and stride alignment is NP-complete for general program graphs, and give a heuristic method that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. We also show how local graph contractions can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. We show how to model the static offset alignment problem using linear programming, and we show that loop-dependent mobile offset alignment is sometimes necessary for optimum performance. We describe an algorithm with for determining mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself or can be used to improve performance. We describe an algorithm based on network flow that replicates objects so as to minimize the total amount of broadcast communication in replication.
Self-adaptive parameters in genetic algorithms
NASA Astrophysics Data System (ADS)
Pellerin, Eric; Pigeon, Luc; Delisle, Sylvain
2004-04-01
Genetic algorithms are powerful search algorithms that can be applied to a wide range of problems. Generally, parameter setting is accomplished prior to running a Genetic Algorithm (GA) and this setting remains unchanged during execution. The problem of interest to us here is the self-adaptive parameters adjustment of a GA. In this research, we propose an approach in which the control of a genetic algorithm"s parameters can be encoded within the chromosome of each individual. The parameters" values are entirely dependent on the evolution mechanism and on the problem context. Our preliminary results show that a GA is able to learn and evaluate the quality of self-set parameters according to their degree of contribution to the resolution of the problem. These results are indicative of a promising approach to the development of GAs with self-adaptive parameter settings that do not require the user to pre-adjust parameters at the outset.
A Parallel Rendering Algorithm for MIMD Architectures
NASA Technical Reports Server (NTRS)
Crockett, Thomas W.; Orloff, Tobias
1991-01-01
Applications such as animation and scientific visualization demand high performance rendering of complex three dimensional scenes. To deliver the necessary rendering rates, highly parallel hardware architectures are required. The challenge is then to design algorithms and software which effectively use the hardware parallelism. A rendering algorithm targeted to distributed memory MIMD architectures is described. For maximum performance, the algorithm exploits both object-level and pixel-level parallelism. The behavior of the algorithm is examined both analytically and experimentally. Its performance for large numbers of processors is found to be limited primarily by communication overheads. An experimental implementation for the Intel iPSC/860 shows increasing performance from 1 to 128 processors across a wide range of scene complexities. It is shown that minimal modifications to the algorithm will adapt it for use on shared memory architectures as well.
Smooth transitions between bump rendering algorithms
Becker, B.G. Max, N.L. |
1993-01-04
A method is described for switching smoothly between rendering algorithms as required by the amount of visible surface detail. The result will be more realism with less computation for displaying objects whose surface detail can be described by one or more bump maps. The three rendering algorithms considered are bidirectional reflection distribution function (BRDF), bump-mapping, and displacement-mapping. The bump-mapping has been modified to make it consistent with the other two. For a given viewpoint, one of these algorithms will show a better trade-off between quality, computation time, and aliasing than the other two. Thus, it needs to be determined for any given viewpoint which regions of the object(s) will be rendered with each algorithm The decision as to which algorithm is appropriate is a function of distance, viewing angle, and the frequency of bumps in the bump map.
Univariate time series forecasting algorithm validation
NASA Astrophysics Data System (ADS)
Ismail, Suzilah; Zakaria, Rohaiza; Muda, Tuan Zalizam Tuan
2014-12-01
Forecasting is a complex process which requires expert tacit knowledge in producing accurate forecast values. This complexity contributes to the gaps between end users and expert. Automating this process by using algorithm can act as a bridge between them. Algorithm is a well-defined rule for solving a problem. In this study a univariate time series forecasting algorithm was developed in JAVA and validated using SPSS and Excel. Two set of simulated data (yearly and non-yearly); several univariate forecasting techniques (i.e. Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) and recent forecasting process (such as data partition, several error measures, recursive evaluation and etc.) were employed. Successfully, the results of the algorithm tally with the results of SPSS and Excel. This algorithm will not just benefit forecaster but also end users that lacking in depth knowledge of forecasting process.
Coagulation algorithms with size binning
NASA Technical Reports Server (NTRS)
Statton, David M.; Gans, Jason; Williams, Eric
1994-01-01
The Smoluchowski equation describes the time evolution of an aerosol particle size distribution due to aggregation or coagulation. Any algorithm for computerized solution of this equation requires a scheme for describing the continuum of aerosol particle sizes as a discrete set. One standard form of the Smoluchowski equation accomplishes this by restricting the particle sizes to integer multiples of a basic unit particle size (the monomer size). This can be inefficient when particle concentrations over a large range of particle sizes must be calculated. Two algorithms employing a geometric size binning convention are examined: the first assumes that the aerosol particle concentration as a function of size can be considered constant within each size bin; the second approximates the concentration as a linear function of particle size within each size bin. The output of each algorithm is compared to an analytical solution in a special case of the Smoluchowski equation for which an exact solution is known . The range of parameters more appropriate for each algorithm is examined.
Fungi producing significant mycotoxins.
2012-01-01
Mycotoxins are secondary metabolites of microfungi that are known to cause sickness or death in humans or animals. Although many such toxic metabolites are known, it is generally agreed that only a few are significant in causing disease: aflatoxins, fumonisins, ochratoxin A, deoxynivalenol, zearalenone, and ergot alkaloids. These toxins are produced by just a few species from the common genera Aspergillus, Penicillium, Fusarium, and Claviceps. All Aspergillus and Penicillium species either are commensals, growing in crops without obvious signs of pathogenicity, or invade crops after harvest and produce toxins during drying and storage. In contrast, the important Fusarium and Claviceps species infect crops before harvest. The most important Aspergillus species, occurring in warmer climates, are A. flavus and A. parasiticus, which produce aflatoxins in maize, groundnuts, tree nuts, and, less frequently, other commodities. The main ochratoxin A producers, A. ochraceus and A. carbonarius, commonly occur in grapes, dried vine fruits, wine, and coffee. Penicillium verrucosum also produces ochratoxin A but occurs only in cool temperate climates, where it infects small grains. F. verticillioides is ubiquitous in maize, with an endophytic nature, and produces fumonisins, which are generally more prevalent when crops are under drought stress or suffer excessive insect damage. It has recently been shown that Aspergillus niger also produces fumonisins, and several commodities may be affected. F. graminearum, which is the major producer of deoxynivalenol and zearalenone, is pathogenic on maize, wheat, and barley and produces these toxins whenever it infects these grains before harvest. Also included is a short section on Claviceps purpurea, which produces sclerotia among the seeds in grasses, including wheat, barley, and triticale. The main thrust of the chapter contains information on the identification of these fungi and their morphological characteristics, as well as factors
Optimal classification of standoff bioaerosol measurements using evolutionary algorithms
NASA Astrophysics Data System (ADS)
Nyhavn, Ragnhild; Moen, Hans J. F.; Farsund, Øystein; Rustad, Gunnar
2011-05-01
Early warning systems based on standoff detection of biological aerosols require real-time signal processing of a large quantity of high-dimensional data, challenging the systems efficiency in terms of both computational complexity and classification accuracy. Hence, optimal feature selection is essential in forming a stable and efficient classification system. This involves finding optimal signal processing parameters, characteristic spectral frequencies and other data transformations in large magnitude variable space, stating the need for an efficient and smart search algorithm. Evolutionary algorithms are population-based optimization methods inspired by Darwinian evolutionary theory. These methods focus on application of selection, mutation and recombination on a population of competing solutions and optimize this set by evolving the population of solutions for each generation. We have employed genetic algorithms in the search for optimal feature selection and signal processing parameters for classification of biological agents. The experimental data were achieved with a spectrally resolved lidar based on ultraviolet laser induced fluorescence, and included several releases of 5 common simulants. The genetic algorithm outperform benchmark methods involving analytic, sequential and random methods like support vector machines, Fisher's linear discriminant and principal component analysis, with significantly improved classification accuracy compared to the best classical method.
A convergent hybrid decomposition algorithm model for SVM training.
Lucidi, Stefano; Palagi, Laura; Risi, Arnaldo; Sciandrone, Marco
2009-06-01
Training of support vector machines (SVMs) requires to solve a linearly constrained convex quadratic problem. In real applications, the number of training data may be very huge and the Hessian matrix cannot be stored. In order to take into account this issue, a common strategy consists in using decomposition algorithms which at each iteration operate only on a small subset of variables, usually referred to as the working set. Training time can be significantly reduced by using a caching technique that allocates some memory space to store the columns of the Hessian matrix corresponding to the variables recently updated. The convergence properties of a decomposition method can be guaranteed by means of a suitable selection of the working set and this can limit the possibility of exploiting the information stored in the cache. We propose a general hybrid algorithm model which combines the capability of producing a globally convergent sequence of points with a flexible use of the information in the cache. As an example of a specific realization of the general hybrid model, we describe an algorithm based on a particular strategy for exploiting the information deriving from a caching technique. We report the results of computational experiments performed by simple implementations of this algorithm. The numerical results point out the potentiality of the approach. PMID:19435679
Algorithm of contrast enhancement for visual document images with underexposure
NASA Astrophysics Data System (ADS)
Tian, Da-zeng; Hao, Yong; Ha, Ming-hu; Tian, Xue-dong; Ha, Yan
2008-03-01
The visual document image is the electronic image about newspapers, books or magazines taken by the digital camera, the digital vidicon etc. Whose getting is more convenient than got from the scanner. Along with the development of OCR technology, visual document images could be recognized by OCR. Affected by some factors, digital image will be degraded during its acquisition, processing, transmission. One of the main problems affecting image quality, leading to unpleasant pictures, comes from improper exposure to light. So preprocessing is becoming much more significant before recognition in order to get an appropriate image satisfied recognition requirements. For the low contrast images with underexposure, according to the visual document image's characteristic, a new algorithm, based on image background separation, for image object enhance is proposed, The proposed method calculate the threshold of separation firstly, And different processing be taken on foreground and background: Various gray values in image background will be merged into unitary gray value, whereas the contrast of foreground will be enhanced. The proposed algorithm implemented in Visual C++ 6.0, and compared the result of proposed algorithm with the results of Otsu's method and histogram equalization. The experimental results show clearly that this algorithm could enhance the details of image object adequately, increase the recognition rate, and avoid the block effect at the same time.
A MULTIRATE STOeRMER ALGORITHM FOR CLOSE ENCOUNTERS
Grazier, K. R.; Newman, W. I.; Sharp, P. W. E-mail: win@ucla.edu
2013-04-15
We present, analyze, and test a multirate Stoermer-based algorithm for integrating close encounters when performing N-body simulations of the Sun, planets, and a large number of test particles. The algorithm is intended primarily for accurate simulations of the outer solar system. The algorithm uses stepsizes H and h{sub i} , i = 1, ..., N{sub p} , where h{sub i} << H and N{sub p} is the number of planets. The stepsize H is used for the integration of the orbital motion of the Sun and planets at all times. H is also used as the stepsize for the integration of the orbital motion of test particles when they are not undergoing a close encounter. The stepsize h{sub i} is used to integrate the orbital motion of test particles during a close encounter with the ith planet. The position of the Sun and planets during a close encounter is calculated using Hermite interpolation. We tested the algorithm on two contrasting problems, and compared its performance with the existing method which uses the same stepsize for all bodies (this stepsize must be significantly smaller than H to ensure the close encounters are integrated accurately). Our tests show that the integration error for the new and existing methods are comparable when the stepsizes are chosen to minimize the error, and that for this choice of stepsizes the new method requires considerably less CPU time than the existing method.
Diagnostic Accuracy Comparison of Artificial Immune Algorithms for Primary Headaches
Çelik, Ufuk; Yurtay, Nilüfer; Koç, Emine Rabia; Tepe, Nermin; Güllüoğlu, Halil; Ertaş, Mustafa
2015-01-01
The present study evaluated the diagnostic accuracy of immune system algorithms with the aim of classifying the primary types of headache that are not related to any organic etiology. They are divided into four types: migraine, tension, cluster, and other primary headaches. After we took this main objective into consideration, three different neurologists were required to fill in the medical records of 850 patients into our web-based expert system hosted on our project web site. In the evaluation process, Artificial Immune Systems (AIS) were used as the classification algorithms. The AIS are classification algorithms that are inspired by the biological immune system mechanism that involves significant and distinct capabilities. These algorithms simulate the specialties of the immune system such as discrimination, learning, and the memorizing process in order to be used for classification, optimization, or pattern recognition. According to the results, the accuracy level of the classifier used in this study reached a success continuum ranging from 95% to 99%, except for the inconvenient one that yielded 71% accuracy. PMID:26075014
Iterative phase retrieval algorithms. I: optimization.
Guo, Changliang; Liu, Shi; Sheridan, John T
2015-05-20
Two modified Gerchberg-Saxton (GS) iterative phase retrieval algorithms are proposed. The first we refer to as the spatial phase perturbation GS algorithm (SPP GSA). The second is a combined GS hybrid input-output algorithm (GS/HIOA). In this paper (Part I), it is demonstrated that the SPP GS and GS/HIO algorithms are both much better at avoiding stagnation during phase retrieval, allowing them to successfully locate superior solutions compared with either the GS or the HIO algorithms. The performances of the SPP GS and GS/HIO algorithms are also compared. Then, the error reduction (ER) algorithm is combined with the HIO algorithm (ER/HIOA) to retrieve the input object image and the phase, given only some knowledge of its extent and the amplitude in the Fourier domain. In Part II, the algorithms developed here are applied to carry out known plaintext and ciphertext attacks on amplitude encoding and phase encoding double random phase encryption systems. Significantly, ER/HIOA is then used to carry out a ciphertext-only attack on AE DRPE systems. PMID:26192504
Implementing Shor's algorithm on Josephson charge qubits
Vartiainen, Juha J.; Salomaa, Martti M.; Niskanen, Antti O.; Nakahara, Mikio
2004-07-01
We investigate the physical implementation of Shor's factorization algorithm on a Josephson charge qubit register. While we pursue a universal method to factor a composite integer of any size, the scheme is demonstrated for the number 21. We consider both the physical and algorithmic requirements for an optimal implementation when only a small number of qubits are available. These aspects of quantum computation are usually the topics of separate research communities; we present a unifying discussion of both of these fundamental features bridging Shor's algorithm to its physical realization using Josephson junction qubits. In order to meet the stringent requirements set by a short decoherence time, we accelerate the algorithm by decomposing the quantum circuit into tailored two- and three-qubit gates and we find their physical realizations through numerical optimization.
Synthesis of logic circuits with evolutionary algorithms
JONES,JAKE S.; DAVIDSON,GEORGE S.
2000-01-26
In the last decade there has been interest and research in the area of designing circuits with genetic algorithms, evolutionary algorithms, and genetic programming. However, the ability to design circuits of the size and complexity required by modern engineering design problems, simply by specifying required outputs for given inputs has as yet eluded researchers. This paper describes current research in the area of designing logic circuits using an evolutionary algorithm. The goal of the research is to improve the effectiveness of this method and make it a practical aid for design engineers. A novel method of implementing the algorithm is introduced, and results are presented for various multiprocessing systems. In addition to evolving standard arithmetic circuits, work in the area of evolving circuits that perform digital signal processing tasks is described.
A hierarchical algorithm for molecular similarity (H-FORMS).
Ramirez-Manzanares, Alonso; Peña, Joaquin; Azpiroz, Jon M; Merino, Gabriel
2015-07-15
A new hierarchical method to determine molecular similarity is introduced. The goal of this method is to detect if a pair of molecules has the same structure by estimating a rigid transformation that aligns the molecules and a correspondence function that matches their atoms. The algorithm firstly detect similarity based on the global spatial structure. If this analysis is not sufficient, the algorithm computes novel local structural rotation-invariant descriptors for the atom neighborhood and uses this information to match atoms. Two strategies (deterministic and stochastic) on the matching based alignment computation are tested. As a result, the atom-matching based on local similarity indexes decreases the number of testing trials and significantly reduces the dimensionality of the Hungarian assignation problem. The experiments on well-known datasets show that our proposal outperforms state-of-the-art methods in terms of the required computational time and accuracy. PMID:26037060
Parallel Algorithms for Graph Optimization using Tree Decompositions
Sullivan, Blair D; Weerapurage, Dinesh P; Groer, Christopher S
2012-06-01
Although many $\\cal{NP}$-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of the necessary dynamic programming tables and excessive runtimes of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree decomposition-based approach to solve the maximum weighted independent set problem. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.
Signal processing algorithms for staring single pixel hyperspectral sensors
NASA Astrophysics Data System (ADS)
Manolakis, Dimitris; Rossacci, Michael; O'Donnell, Erin; D'Amico, Francis M.
2006-08-01
Remote sensing of chemical warfare agents (CWA) with stand-off hyperspectral sensors has a wide range of civilian and military applications. These sensors exploit the spectral changes in the ambient photon flux produced thermal emission or absorption after passage through a region containing the CWA cloud. In this work we focus on (a) staring single-pixel sensors that sample their field of view at regular intervals of time to produce a time series of spectra and (b) scanning single or multiple pixel sensors that sample their FOV as they scan. The main objective of signal processing algorithms is to determine if and when a CWA enters the FOV of the sensor. We shall first develop and evaluate algorithms for staring sensors following two different approaches. First, we will assume that no threat information is available and we design an adaptive anomaly detection algorithm to detect a statistically-significant change in the observed spectrum. The algorithm processes the observed spectra sequentially-in-time, estimates adaptively the background, and checks whether the next spectrum differs significantly from the background based on the Mahalanobis distance or the distance from the background subspace. In the second approach, we will assume that we know the spectral signature of the CWA and develop sequential-in-time adaptive matched filter detectors. In both cases, we assume that the sensor starts its operation before the release of the CWA; otherwise, staring at a nearby CWA-free area is required for background estimation. Experimental evaluation and comparison of the proposed algorithms is accomplished using data from a long-wave infrared (LWIR) Fourier transform spectrometer.
An Efficient Next Hop Selection Algorithm for Multi-Hop Body Area Networks
Ayatollahitafti, Vahid; Ngadi, Md Asri; Mohamad Sharif, Johan bin; Abdullahi, Mohammed
2016-01-01
Body Area Networks (BANs) consist of various sensors which gather patient’s vital signs and deliver them to doctors. One of the most significant challenges faced, is the design of an energy-efficient next hop selection algorithm to satisfy Quality of Service (QoS) requirements for different healthcare applications. In this paper, a novel efficient next hop selection algorithm is proposed in multi-hop BANs. This algorithm uses the minimum hop count and a link cost function jointly in each node to choose the best next hop node. The link cost function includes the residual energy, free buffer size, and the link reliability of the neighboring nodes, which is used to balance the energy consumption and to satisfy QoS requirements in terms of end to end delay and reliability. Extensive simulation experiments were performed to evaluate the efficiency of the proposed algorithm using the NS-2 simulator. Simulation results show that our proposed algorithm provides significant improvement in terms of energy consumption, number of packets forwarded, end to end delay and packet delivery ratio compared to the existing routing protocol. PMID:26771586
Castanon, D.A.
1989-10-01
The objective of weapon-target assignment (WTA) in a ballistic missile defense (BMD) system is to determine how defensive weapons should be assigned to boosters and reentry vehicles in order to maximize the survival of assets belonging to the U.S. and allied countries. The implied optimization problem requires consideration of a large number of potential weapon target assignments in order to select the most effective combination of assignments. The resulting WTA optimization problems are among the most complex encountered in mathematical programming. Indeed, simple versions of the WTA problem have been shown to be NP-complete, implying that the computations required achieve optimal solutions grow exponentially with the numbers of weapons and targets considered in the solution. The computational complexity of the WTA problem has motivated the development of heuristic algorithms that are not altogether satisfactory for use in Strategic Defense Systems (SDS). Some special cases of the WTA problem are not NP-complete and can be solved using standard optimization algorithms such as linear programming and maximum-marginal-return algorithms; these algorithms enjoy low computational requirements and therefore have been adopted as heuristics for solving more general WTA problems. However, experimental studies have demonstrated that these heuristic algorithms lead to significantly suboptimal solutions for certain scenarios.
NASA Astrophysics Data System (ADS)
Freiman, M.; Lamash, Y.; Gilboa, G.; Nickisch, H.; Prevrhal, S.; Schmitt, H.; Vembar, M.; Goshen, L.
2016-03-01
The determination of hemodynamic significance of coronary artery lesions from cardiac computed tomography angiography (CCTA) based on blood flow simulations has the potential to improve CCTA's specificity, thus resulting in improved clinical decision making. Accurate coronary lumen segmentation required for flow simulation is challenging due to several factors. Specifically, the partial-volume effect (PVE) in small-diameter lumina may result in overestimation of the lumen diameter that can lead to an erroneous hemodynamic significance assessment. In this work, we present a coronary artery segmentation algorithm tailored specifically for flow simulations by accounting for the PVE. Our algorithm detects lumen regions that may be subject to the PVE by analyzing the intensity values along the coronary centerline and integrates this information into a machine-learning based graph min-cut segmentation framework to obtain accurate coronary lumen segmentations. We demonstrate the improvement in hemodynamic significance assessment achieved by accounting for the PVE in the automatic segmentation of 91 coronary artery lesions from 85 patients. We compare hemodynamic significance assessments by means of fractional flow reserve (FFR) resulting from simulations on 3D models generated by our segmentation algorithm with and without accounting for the PVE. By accounting for the PVE we improved the area under the ROC curve for detecting hemodynamically significant CAD by 29% (N=91, 0.85 vs. 0.66, p<0.05, Delong's test) with invasive FFR threshold of 0.8 as the reference standard. Our algorithm has the potential to facilitate non-invasive hemodynamic significance assessment of coronary lesions.
Reasoning about systolic algorithms
Purushothaman, S.; Subrahmanyam, P.A.
1988-12-01
The authors present a methodology for verifying correctness of systolic algorithms. The methodology is based on solving a set of Uniform Recurrence Equations obtained from a description of systolic algorithms as a set of recursive equations. They present an approach to mechanically verify correctness of systolic algorithms, using the Boyer-Moore theorem proven. A mechanical correctness proof of an example from the literature is also presented.
48 CFR 2110.7003 - Significant events.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 48 Federal Acquisition Regulations System 6 2014-10-01 2014-10-01 false Significant events. 2110..., AND OTHER PURCHASE DESCRIPTIONS Contract Specifications 2110.7003 Significant events. The contractor is required to inform the contracting officer of all significant events....
48 CFR 2110.7003 - Significant events.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Significant events. 2110..., AND OTHER PURCHASE DESCRIPTIONS Contract Specifications 2110.7003 Significant events. The contractor is required to inform the contracting officer of all significant events....
48 CFR 2110.7003 - Significant events.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 6 2011-10-01 2011-10-01 false Significant events. 2110..., AND OTHER PURCHASE DESCRIPTIONS Contract Specifications 2110.7003 Significant events. The contractor is required to inform the contracting officer of all significant events....
48 CFR 2110.7003 - Significant events.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 6 2013-10-01 2013-10-01 false Significant events. 2110..., AND OTHER PURCHASE DESCRIPTIONS Contract Specifications 2110.7003 Significant events. The contractor is required to inform the contracting officer of all significant events....
48 CFR 2110.7003 - Significant events.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 6 2012-10-01 2012-10-01 false Significant events. 2110..., AND OTHER PURCHASE DESCRIPTIONS Contract Specifications 2110.7003 Significant events. The contractor is required to inform the contracting officer of all significant events....
Complexity of the Quantum Adiabatic Algorithm
NASA Technical Reports Server (NTRS)
Hen, Itay
2013-01-01
The Quantum Adiabatic Algorithm (QAA) has been proposed as a mechanism for efficiently solving optimization problems on a quantum computer. Since adiabatic computation is analog in nature and does not require the design and use of quantum gates, it can be thought of as a simpler and perhaps more profound method for performing quantum computations that might also be easier to implement experimentally. While these features have generated substantial research in QAA, to date there is still a lack of solid evidence that the algorithm can outperform classical optimization algorithms.
Facial Composite System Using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Zahradníková, Barbora; Duchovičová, Soňa; Schreiber, Peter
2014-12-01
The article deals with genetic algorithms and their application in face identification. The purpose of the research is to develop a free and open-source facial composite system using evolutionary algorithms, primarily processes of selection and breeding. The initial testing proved higher quality of the final composites and massive reduction in the composites processing time. System requirements were specified and future research orientation was proposed in order to improve the results.
Exploring a new best information algorithm for Iliad.
Guo, D.; Lincoln, M. J.; Haug, P. J.; Turner, C. W.; Warner, H. R.
1991-01-01
Iliad is a diagnostic expert system for internal medicine. One important feature that Iliad offers is the ability to analyze a particular patient case and to determine the most cost-effective method for pursuing the work-up. Iliad's current "best information" algorithm has not been previously validated and compared to other potential algorithms. Therefore, this paper presents a comparison of four new algorithms to the current algorithm. The basis for this comparison was eighteen "vignette" cases derived from real patient cases from the University of Utah Medical Center. The results indicated that the current algorithm can be significantly improved. More promising algorithms are suggested for future investigation. PMID:1807677
Algorithm for Autonomous Landing
NASA Technical Reports Server (NTRS)
Kuwata, Yoshiaki
2011-01-01
Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.
Berry, K.; Dayton, S.
1996-10-28
Citibank was using a data collection system to create a one-time-only mailing history on prospective credit card customers that was becoming dated in its time to market requirements and as such was in need of performance improvements. To compound problems with their existing system, the assurance of the quality of the data matching process was manpower intensive and needed to be automated. Analysis, design, and prototyping capabilities involving information technology were areas of expertise provided by DOE-LMES Data Systems Research and Development (DSRD) program. The goal of this project was for Data Systems Research and Development (DSRD) to analyze the current Citibank credit card offering system and suggest and prototype technology improvements that would result in faster processing with quality as good as the current system. Technologies investigated include: a high-speed network of reduced instruction set computing (RISC) processors for loosely coupled parallel processing, tightly coupled, high performance parallel processing, higher order computer languages such as `C`, fuzzy matching algorithms applied to very large data files, relational database management system, and advanced programming techniques.
A GROUP FINDING ALGORITHM FOR MULTIDIMENSIONAL DATA SETS
Sharma, Sanjib; Johnston, Kathryn V. E-mail: kvj@astro.columbia.ed
2009-09-20
We describe a density-based hierarchical group finding algorithm capable of identifying structures and substructures of any shape and density in multidimensional data sets where each dimension can be a numeric attribute with arbitrary measurement scale. This has applications in a wide variety of fields from finding structures in galaxy redshift surveys, to identifying halos and subhalos in N-body simulations and group finding in Local Group chemodynamical data sets. In general, clustering schemes require an a priori definition of a metric (a non-negative function that gives the distance between two points in a space) and the quality of clustering depends upon this choice. The general practice is to use a constant global metric which is optimal only if the clusters in the data are self-similar. For complex data configurations even the most finely tuned constant global metric turns out to be suboptimal. Moreover, the correct choice of metric also becomes increasingly important as the number of dimensions increase. To address these problems, we present an entropy-based binary space partitioning algorithm which uses a locally adaptive metric for each data point. The metric is employed to calculate the density at each point and a list of its nearest neighbors, and this information is then used to form a hierarchy of groups. Finally, the ratio of maximum to minimum density of points in a group is used to estimate the significance of the groups. Setting a threshold on this significance can effectively screen out groups arising due to Poisson noise and helps organize the groups into meaningful clusters. For a data set of N points, the algorithm requires only O(N) space and O(N(log N){sup 3}) time which makes it ideally suitable for analyzing large data sets. As an example, we apply the algorithm to identify structures in a simulated stellar halo using the full six-dimensional phase space coordinates.
A Dynamic Framed Slotted ALOHA Algorithm Using Collision Factor for RFID Identification
NASA Astrophysics Data System (ADS)
Choi, Seung Sik; Kim, Sangkyung
In RFID systems, collision resolution is a significant issue in fast tag identification. This letter presents a dynamic frame-slotted ALOHA algorithm that uses a collision factor (DFSA-CF). This method enables fast tag identification by estimating the next frame size with the collision factor in the current frame. Simulation results show that the proposed method reduces slot times Required for RFID identification. When the number of tags is larger than the frame size, the efficiency of the proposed method is greater than those of conventional algorithms.
A fast meteor detection algorithm
NASA Astrophysics Data System (ADS)
Gural, P.
2016-01-01
A low latency meteor detection algorithm for use with fast steering mirrors had been previously developed to track and telescopically follow meteors in real-time (Gural, 2007). It has been rewritten as a generic clustering and tracking software module for meteor detection that meets both the demanding throughput requirements of a Raspberry Pi while also maintaining a high probability of detection. The software interface is generalized to work with various forms of front-end video pre-processing approaches and provides a rich product set of parameterized line detection metrics. Discussion will include the Maximum Temporal Pixel (MTP) compression technique as a fast thresholding option for feeding the detection module, the detection algorithm trade for maximum processing throughput, details on the clustering and tracking methodology, processing products, performance metrics, and a general interface description.
NASA Technical Reports Server (NTRS)
Loewenstein, M.; Greenblatt. B. J.; Jost, H.; Podolske, J. R.; Elkins, Jim; Hurst, Dale; Romanashkin, Pavel; Atlas, Elliott; Schauffler, Sue; Donnelly, Steve; Condon, Estelle (Technical Monitor)
2000-01-01
De-nitrification and excess re-nitrification was widely observed by ER-2 instruments in the Arctic vortex during SOLVE in winter/spring 2000. Analyses of these events requires a knowledge of the initial or pre-vortex state of the sampled air masses. The canonical relationship of NOy to the long-lived tracer N2O observed in the unperturbed stratosphere is generally used for this purpose. In this paper we will attempt to establish the current unperturbed NOy:N2O relationship (NOy* algorithm) using the ensemble of extra-vortex data from in situ instruments flying on the ER-2 and DC-8, and from the Mark IV remote measurements on the OMS balloon. Initial analysis indicates a change in the SOLVE NOy* from the values predicted by the 1994 Northern Hemisphere NOy* algorithm which was derived from the observations in the ASHOE/MAESA campaign.
Adaptive color image watermarking algorithm
NASA Astrophysics Data System (ADS)
Feng, Gui; Lin, Qiwei
2008-03-01
As a major method for intellectual property right protecting, digital watermarking techniques have been widely studied and used. But due to the problems of data amount and color shifted, watermarking techniques on color image was not so widespread studied, although the color image is the principal part for multi-medium usages. Considering the characteristic of Human Visual System (HVS), an adaptive color image watermarking algorithm is proposed in this paper. In this algorithm, HSI color model was adopted both for host and watermark image, the DCT coefficient of intensity component (I) of the host color image was used for watermark date embedding, and while embedding watermark the amount of embedding bit was adaptively changed with the complex degree of the host image. As to the watermark image, preprocessing is applied first, in which the watermark image is decomposed by two layer wavelet transformations. At the same time, for enhancing anti-attack ability and security of the watermarking algorithm, the watermark image was scrambled. According to its significance, some watermark bits were selected and some watermark bits were deleted as to form the actual embedding data. The experimental results show that the proposed watermarking algorithm is robust to several common attacks, and has good perceptual quality at the same time.
Sharma, Ashok; Podolsky, Robert; Zhao, Jieping; McIndoe, Richard A.
2009-01-01
Motivation: As the number of publically available microarray experiments increases, the ability to analyze extremely large datasets across multiple experiments becomes critical. There is a requirement to develop algorithms which are fast and can cluster extremely large datasets without affecting the cluster quality. Clustering is an unsupervised exploratory technique applied to microarray data to find similar data structures or expression patterns. Because of the high input/output costs involved and large distance matrices calculated, most of the algomerative clustering algorithms fail on large datasets (30 000 + genes/200 + arrays). In this article, we propose a new two-stage algorithm which partitions the high-dimensional space associated with microarray data using hyperplanes. The first stage is based on the Balanced Iterative Reducing and Clustering using Hierarchies algorithm with the second stage being a conventional k-means clustering technique. This algorithm has been implemented in a software tool (HPCluster) designed to cluster gene expression data. We compared the clustering results using the two-stage hyperplane algorithm with the conventional k-means algorithm from other available programs. Because, the first stage traverses the data in a single scan, the performance and speed increases substantially. The data reduction accomplished in the first stage of the algorithm reduces the memory requirements allowing us to cluster 44 460 genes without failure and significantly decreases the time to complete when compared with popular k-means programs. The software was written in C# (.NET 1.1). Availability: The program is freely available and can be downloaded from http://www.amdcc.org/bioinformatics/bioinformatics.aspx. Contact: rmcindoe@mail.mcg.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19261720
Algorithm That Synthesizes Other Algorithms for Hashing
NASA Technical Reports Server (NTRS)
James, Mark
2010-01-01
An algorithm that includes a collection of several subalgorithms has been devised as a means of synthesizing still other algorithms (which could include computer code) that utilize hashing to determine whether an element (typically, a number or other datum) is a member of a set (typically, a list of numbers). Each subalgorithm synthesizes an algorithm (e.g., a block of code) that maps a static set of key hashes to a somewhat linear monotonically increasing sequence of integers. The goal in formulating this mapping is to cause the length of the sequence thus generated to be as close as practicable to the original length of the set and thus to minimize gaps between the elements. The advantage of the approach embodied in this algorithm is that it completely avoids the traditional approach of hash-key look-ups that involve either secondary hash generation and look-up or further searching of a hash table for a desired key in the event of collisions. This algorithm guarantees that it will never be necessary to perform a search or to generate a secondary key in order to determine whether an element is a member of a set. This algorithm further guarantees that any algorithm that it synthesizes can be executed in constant time. To enforce these guarantees, the subalgorithms are formulated to employ a set of techniques, each of which works very effectively covering a certain class of hash-key values. These subalgorithms are of two types, summarized as follows: Given a list of numbers, try to find one or more solutions in which, if each number is shifted to the right by a constant number of bits and then masked with a rotating mask that isolates a set of bits, a unique number is thereby generated. In a variant of the foregoing procedure, omit the masking. Try various combinations of shifting, masking, and/or offsets until the solutions are found. From the set of solutions, select the one that provides the greatest compression for the representation and is executable in the
Basic firefly algorithm for document clustering
NASA Astrophysics Data System (ADS)
Mohammed, Athraa Jasim; Yusof, Yuhanis; Husni, Husniza
2015-12-01
The Document clustering plays significant role in Information Retrieval (IR) where it organizes documents prior to the retrieval process. To date, various clustering algorithms have been proposed and this includes the K-means and Particle Swarm Optimization. Even though these algorithms have been widely applied in many disciplines due to its simplicity, such an approach tends to be trapped in a local minimum during its search for an optimal solution. To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents. The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. Experiments utilizing the proposed algorithm were conducted on the 20Newsgroups benchmark dataset. Results demonstrate that the Basic FA generates a more robust and compact clusters than the ones produced by K-means and Particle Swarm Optimization (PSO).
Passive microwave algorithm development and evaluation
NASA Technical Reports Server (NTRS)
Petty, Grant W.
1995-01-01
The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.