Wake Vortex Algorithm Scoring Results
NASA Technical Reports Server (NTRS)
Robins, R. E.; Delisi, D. P.; Hinton, David (Technical Monitor)
2002-01-01
This report compares the performance of two models of trailing vortex evolution for which interaction with the ground is not a significant factor. One model uses eddy dissipation rate (EDR) and the other uses the kinetic energy of turbulence fluctuations (TKE) to represent the effect of turbulence. In other respects, the models are nearly identical. The models are evaluated by comparing their predictions of circulation decay, vertical descent, and lateral transport to observations for over four hundred cases from Memphis and Dallas/Fort Worth International Airports. These observations were obtained during deployments in support of NASA's Aircraft Vortex Spacing System (AVOSS). The results of the comparisons show that the EDR model usually performs slightly better than the TKE model.
New Results in Astrodynamics Using Genetic Algorithms
NASA Technical Reports Server (NTRS)
Coverstone-Carroll, V.; Hartmann, J. W.; Williams, S. N.; Mason, W. J.
1998-01-01
Generic algorithms have gained popularity as an effective procedure for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a brief survey of the use of genetic algorithms to solve astrodynamics problems is presented and is followed by new results obtained from applying a Pareto genetic algorithm to the optimization of low-thrust interplanetary spacecraft missions.
13. DETAIL VIEW OF BUTTRESS 4 SHOWING THE RESULTS OF ...
13. DETAIL VIEW OF BUTTRESS 4 SHOWING THE RESULTS OF POOR CONSTRUCTION WORK. THOUGH NOT A SERIOUS STRUCTURAL DEFICIENCY, THE 'HONEYCOMB' TEXTURE OF THE CONCRETE SURFACE WAS THE RESULT OF INADEQUATE TAMPING AT THE TIME OF THE INITIAL 'POUR'. - Hume Lake Dam, Sequioa National Forest, Hume, Fresno County, CA
Simulation results for the Viterbi decoding algorithm
NASA Technical Reports Server (NTRS)
Batson, B. H.; Moorehead, R. W.; Taqvi, S. Z. H.
1972-01-01
Concepts involved in determining the performance of coded digital communications systems are introduced. The basic concepts of convolutional encoding and decoding are summarized, and hardware implementations of sequential and maximum likelihood decoders are described briefly. Results of parametric studies of the Viterbi decoding algorithm are summarized. Bit error probability is chosen as the measure of performance and is calculated, by using digital computer simulations, for various encoder and decoder parameters. Results are presented for code rates of one-half and one-third, for constraint lengths of 4 to 8, for both hard-decision and soft-decision bit detectors, and for several important systematic and nonsystematic codes. The effect of decoder block length on bit error rate also is considered, so that a more complete estimate of the relationship between performance and decoder complexity can be made.
Convergence Results on Iteration Algorithms to Linear Systems
Wang, Zhuande; Yang, Chuansheng; Yuan, Yubo
2014-01-01
In order to solve the large scale linear systems, backward and Jacobi iteration algorithms are employed. The convergence is the most important issue. In this paper, a unified backward iterative matrix is proposed. It shows that some well-known iterative algorithms can be deduced with it. The most important result is that the convergence results have been proved. Firstly, the spectral radius of the Jacobi iterative matrix is positive and the one of backward iterative matrix is strongly positive (lager than a positive constant). Secondly, the mentioned two iterations have the same convergence results (convergence or divergence simultaneously). Finally, some numerical experiments show that the proposed algorithms are correct and have the merit of backward methods. PMID:24991640
Breast vibro-acoustography: initial results show promise
2012-01-01
Introduction Vibro-acoustography (VA) is a recently developed imaging modality that is sensitive to the dynamic characteristics of tissue. It detects low-frequency harmonic vibrations in tissue that are induced by the radiation force of ultrasound. Here, we have investigated applications of VA for in vivo breast imaging. Methods A recently developed combined mammography-VA system for in vivo breast imaging was tested on female volunteers, aged 25 years or older, with suspected breast lesions on their clinical examination. After mammography, a set of VA scans was acquired by the experimental device. In a masked assessment, VA images were evaluated independently by 3 reviewers who identified mass lesions and calcifications. The diagnostic accuracy of this imaging method was determined by comparing the reviewers' responses with clinical data. Results We collected images from 57 participants: 7 were used for training and 48 for evaluation of diagnostic accuracy (images from 2 participants were excluded because of unexpected imaging artifacts). In total, 16 malignant and 32 benign lesions were examined. Specificity for diagnostic accuracy was 94% or higher for all 3 reviewers, but sensitivity varied (69% to 100%). All reviewers were able to detect 97% of masses, but sensitivity for detection of calcification was lower (≤ 72% for all reviewers). Conclusions VA can be used to detect various breast abnormalities, including calcifications and benign and malignant masses, with relatively high specificity. VA technology may lead to a new clinical tool for breast imaging applications. PMID:23021305
The Aquarius Salinity Retrieval Algorithm: Early Results
NASA Technical Reports Server (NTRS)
Meissner, Thomas; Wentz, Frank J.; Lagerloef, Gary; LeVine, David
2012-01-01
The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to O2, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind. This is based on the radar backscatter measurements by the scatterometer. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation
Experimental Results in the Comparison of Search Algorithms Used with Room Temperature Detectors
Guss, P., Yuan, D., Cutler, M., Beller, D.
2010-11-01
Analysis of time sequence data was run for several higher resolution scintillation detectors using a variety of search algorithms, and results were obtained in predicting the relative performance for these detectors, which included a slightly superior performance by CeBr{sub 3}. Analysis of several search algorithms shows that inclusion of the RSPRT methodology can improve sensitivity.
Evaluation of registration, compression and classification algorithms. Volume 1: Results
NASA Technical Reports Server (NTRS)
Jayroe, R.; Atkinson, R.; Callas, L.; Hodges, J.; Gaggini, B.; Peterson, J.
1979-01-01
The registration, compression, and classification algorithms were selected on the basis that such a group would include most of the different and commonly used approaches. The results of the investigation indicate clearcut, cost effective choices for registering, compressing, and classifying multispectral imagery.
A simple algorithm for analyzing uncertainty of accident reconstruction results.
Zou, Tiefang; Hu, Lin; Li, Pingfan; Wu, Hequan
2015-12-01
In order to analyzing the uncertainty in accident reconstruction, based on the theory of extreme value and the convex model theory, the uncertainty analysis problem is turn to an extreme value problem. In order to calculate the range of the dependent variable, the extreme value in the definition domain and on the boundary of the definition domain are calculated independently, and then the upper and lower bound of the dependent variable can be given by these obtained extreme values. Based on such idea and through analyzing five numerical cases, a simple algorithm for calculating the range of an accident reconstruction result was given; appropriate results can be obtained through the proposed algorithm in these cases. Finally, a real world vehicle-motorcycle accident was given, the range of the reconstructed velocity of the vehicle was calculated by employing the Pc-Crash, the response surface methodology and the new proposed algorithm, the range was [66.1-67.3] km/h. This research will provide another choice for uncertainty analysis in accident reconstruction. PMID:26386339
The Effect of Pansharpening Algorithms on the Resulting Orthoimagery
NASA Astrophysics Data System (ADS)
Agrafiotis, P.; Georgopoulos, A.; Karantzalos, K.
2016-06-01
This paper evaluates the geometric effects of pansharpening algorithms on automatically generated DSMs and thus on the resulting orthoimagery through a quantitative assessment of the accuracy on the end products. The main motivation was based on the fact that for automatically generated Digital Surface Models, an image correlation step is employed for extracting correspondences between the overlapping images. Thus their accuracy and reliability is strictly related to image quality, while pansharpening may result into lower image quality which may affect the DSM generation and the resulting orthoimage accuracy. To this direction, an iterative methodology was applied in order to combine the process described by Agrafiotis and Georgopoulos (2015) with different pansharpening algorithms and check the accuracy of orthoimagery resulting from pansharpened data. Results are thoroughly examined and statistically analysed. The overall evaluation indicated that the pansharpening process didn't affect the geometric accuracy of the resulting DSM with a 10m interval, as well as the resulting orthoimagery. Although some residuals in the orthoimages were observed, their magnitude cannot adversely affect the accuracy of the final orthoimagery.
Shuttle Entry Air Data System (SEADS) - Optimization of preflight algorithms based on flight results
NASA Technical Reports Server (NTRS)
Wolf, H.; Henry, M. W.; Siemers, Paul M., III
1988-01-01
The SEADS pressure model algorithm results were tested against other sources of air data, in particular, the Shuttle Best Estimated Trajectory (BET). The algorithm basis was also tested through a comparison of flight-measured pressure distribution vs the wind tunnel database. It is concluded that the successful flight of SEADS and the subsequent analysis of the data shows good agreement between BET and SEADS air data.
Adaptively resizing populations: Algorithm, analysis, and first results
NASA Technical Reports Server (NTRS)
Smith, Robert E.; Smuda, Ellen
1993-01-01
Deciding on an appropriate population size for a given Genetic Algorithm (GA) application can often be critical to the algorithm's success. Too small, and the GA can fall victim to sampling error, affecting the efficacy of its search. Too large, and the GA wastes computational resources. Although advice exists for sizing GA populations, much of this advice involves theoretical aspects that are not accessible to the novice user. An algorithm for adaptively resizing GA populations is suggested. This algorithm is based on recent theoretical developments that relate population size to schema fitness variance. The suggested algorithm is developed theoretically, and simulated with expected value equations. The algorithm is then tested on a problem where population sizing can mislead the GA. The work presented suggests that the population sizing algorithm may be a viable way to eliminate the population sizing decision from the application of GA's.
Upper cervical injuries: Clinical results using a new treatment algorithm
Joaquim, Andrei F.; Ghizoni, Enrico; Tedeschi, Helder; Yacoub, Alexandre R. D.; Brodke, Darrel S.; Vaccaro, Alexander R.; Patel, Alpesh A.
2015-01-01
Introduction: Upper cervical injuries (UCI) have a wide range of radiological and clinical presentation due to the unique complex bony, ligamentous and vascular anatomy. We recently proposed a rational approach in an attempt to unify prior classification system and guide treatment. In this paper, we evaluate the clinical results of our algorithm for UCI treatment. Materials and Methods: A prospective cohort series of patients with UCI was performed. The primary outcome was the AIS. Surgical treatment was proposed based on our protocol: Ligamentous injuries (abnormal misalignment, facet perched or locked, increase atlanto-dens interval) were treated surgically. Bone fractures without ligamentous injuries were treated with a rigid cervical orthosis, with exception of fractures in the dens base with risk factors for non-union. Results: Twenty-three patients treated initially conservatively had some follow-up (mean of 171 days, range from 60 to 436 days). All of them were neurologically intact. None of the patients developed a new neurological deficit. Fifteen patients were initially surgically treated (mean of 140 days of follow-up, ranging from 60 to 270 days). In the surgical group, preoperatively, 11 (73.3%) patients were AIS E, 2 (13.3%) AIS C and 2 (13.3%) AIS D. At the final follow-up, the American Spine Injury Association (ASIA) score was: 13 (86.6%) AIS E and 2 (13.3%) AIS D. None of the patients had neurological worsening during the follow-up. Conclusions: This prospective cohort suggested that our UCI treatment algorithm can be safely used. Further prospective studies with longer follow-up are necessary to further establish its clinical validity and safety. PMID:25788816
Kry, Stephen F.; Alvarez, Paola; Molineu, Andrea; Amador, Carrie; Galvin, James; Followill, David S.
2012-01-01
Purpose To determine the impact of treatment planning algorithm on the accuracy of heterogeneous dose calculations in the Radiological Physics Center (RPC) thorax phantom. Methods and Materials We retrospectively analyzed the results of 304 irradiations of the RPC thorax phantom at 221 different institutions as part of credentialing for RTOG clinical trials; the irradiations were all done using 6-MV beams. Treatment plans included those for intensity-modulated radiation therapy (IMRT) as well as 3D conformal therapy (3D CRT). Heterogeneous plans were developed using Monte Carlo (MC), convolution/superposition (CS) and the anisotropic analytic algorithm (AAA), as well as pencil beam (PB) algorithms. For each plan and delivery, the absolute dose measured in the center of a lung target was compared to the calculated dose, as was the planar dose in 3 orthogonal planes. The difference between measured and calculated dose was examined as a function of planning algorithm as well as use of IMRT. Results PB algorithms overestimated the dose delivered to the center of the target by 4.9% on average. Surprisingly, CS algorithms and AAA also showed a systematic overestimation of the dose to the center of the target, by 3.7% on average. In contrast, the MC algorithm dose calculations agreed with measurement within 0.6% on average. There was no difference observed between IMRT and 3D CRT calculation accuracy. Conclusion Unexpectedly, advanced treatment planning systems (those using CS and AAA algorithms) overestimated the dose that was delivered to the lung target. This issue requires attention in terms of heterogeneity calculations and potentially in terms of clinical practice. PMID:23237006
2014-01-01
Background Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. Results We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. Conclusions In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to
Comparison of some results of program SHOW with other solar hot water computer programs
NASA Astrophysics Data System (ADS)
Young, M. F.; Baughn, J. W.
The SHOW (solar hot water) computer program is capable of simulating both one and two tank designs of thermosiphon and pumped solar domestic hot water systems. SHOW differs in a number of ways from other programs, the most notable of which is the emphasis on a thermal/hydraulic model of the stratified storage tank. The predicted performance for a typical two tank pumped system, computed by Program SHOW are compared, with results computed using F-CHART and TRNSYS. The results show fair to good agreement between the various computer programs when comparing the annual percent solar contributions. SHOW is also used to compute the expected performance of a two tank thermosiphon system and to compare its performance to the two tank pumped system.
Gun shows and gun violence: fatally flawed study yields misleading results.
Wintemute, Garen J; Hemenway, David; Webster, Daniel; Pierce, Glenn; Braga, Anthony A
2010-10-01
A widely publicized but unpublished study of the relationship between gun shows and gun violence is being cited in debates about the regulation of gun shows and gun commerce. We believe the study is fatally flawed. A working paper entitled "The Effect of Gun Shows on Gun-Related Deaths: Evidence from California and Texas" outlined this study, which found no association between gun shows and gun-related deaths. We believe the study reflects a limited understanding of gun shows and gun markets and is not statistically powered to detect even an implausibly large effect of gun shows on gun violence. In addition, the research contains serious ascertainment and classification errors, produces results that are sensitive to minor specification changes in key variables and in some cases have no face validity, and is contradicted by 1 of its own authors' prior research. The study should not be used as evidence in formulating gun policy. PMID:20724672
Gun Shows and Gun Violence: Fatally Flawed Study Yields Misleading Results
Hemenway, David; Webster, Daniel; Pierce, Glenn; Braga, Anthony A.
2010-01-01
A widely publicized but unpublished study of the relationship between gun shows and gun violence is being cited in debates about the regulation of gun shows and gun commerce. We believe the study is fatally flawed. A working paper entitled “The Effect of Gun Shows on Gun-Related Deaths: Evidence from California and Texas” outlined this study, which found no association between gun shows and gun-related deaths. We believe the study reflects a limited understanding of gun shows and gun markets and is not statistically powered to detect even an implausibly large effect of gun shows on gun violence. In addition, the research contains serious ascertainment and classification errors, produces results that are sensitive to minor specification changes in key variables and in some cases have no face validity, and is contradicted by 1 of its own authors’ prior research. The study should not be used as evidence in formulating gun policy. PMID:20724672
Benetazzo, Flavia; Freddi, Alessandro; Monteriù, Andrea; Longhi, Sauro
2014-09-01
Both the theoretical background and the experimental results of an algorithm developed to perform human respiratory rate measurements without any physical contact are presented. Based on depth image sensing techniques, the respiratory rate is derived by measuring morphological changes of the chest wall. The algorithm identifies the human chest, computes its distance from the camera and compares this value with the instantaneous distance, discerning if it is due to the respiratory act or due to a limited movement of the person being monitored. To experimentally validate the proposed algorithm, the respiratory rate measurements coming from a spirometer were taken as a benchmark and compared with those estimated by the algorithm. Five tests were performed, with five different persons sat in front of the camera. The first test aimed to choose the suitable sampling frequency. The second test was conducted to compare the performances of the proposed system with respect to the gold standard in ideal conditions of light, orientation and clothing. The third, fourth and fifth tests evaluated the algorithm performances under different operating conditions. The experimental results showed that the system can correctly measure the respiratory rate, and it is a viable alternative to monitor the respiratory activity of a person without using invasive sensors. PMID:26609383
Akbari, Hamed; Bilello, Michel; Da, Xiao; Davatzikos, Christos
2015-01-01
Evaluating various algorithms for the inter-subject registration of brain magnetic resonance images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated image registration algorithms in specific tasks or using specific databases (e.g., only for skull-stripped images, only for single-site images, etc.). Consequently, the choice of registration algorithms seems task- and usage/parameter-dependent. Nevertheless, recent large-scale, often multi-institutional imaging-related studies create the need and raise the question whether some registration algorithms can 1) generally apply to various tasks/databases posing various challenges; 2) perform consistently well, and while doing so, 3) require minimal or ideally no parameter tuning. In seeking answers to this question, we evaluated 12 general-purpose registration algorithms, for their generality, accuracy and robustness. We fixed their parameters at values suggested by algorithm developers as reported in the literature. We tested them in 7 databases/tasks, which present one or more of 4 commonly-encountered challenges: 1) inter-subject anatomical variability in skull-stripped images; 2) intensity homogeneity, noise and large structural differences in raw images; 3) imaging protocol and field-of-view (FOV) differences in multi-site data; and 4) missing correspondences in pathology-bearing images. Totally 7,562 registrations were performed. Registration accuracies were measured by (multi-)expert-annotated landmarks or regions of interest (ROIs). To ensure reproducibility, we used public software tools, public databases (whenever possible), and we fully disclose the parameter settings. We show evaluation results, and discuss the performances in light of algorithms’ similarity metrics, transformation models and optimization strategies. We also discuss future directions for the algorithm development and evaluations. PMID:24951685
Gállego, Isaac; Oncins, Gerard; Sisquella, Xavier; Fernàndez-Busquets, Xavier; Daban, Joan-Ramon
2010-01-01
In a previous study, we found that metaphase chromosomes are formed by thin plates, and here we have applied atomic force microscopy (AFM) and friction force measurements at the nanoscale (nanotribology) to analyze the properties of these planar structures in aqueous media at room temperature. Our results show that high concentrations of NaCl and EDTA and extensive digestion with protease and nuclease enzymes cause plate denaturation. Nanotribology studies show that native plates under structuring conditions (5 mM Mg2+) have a relatively high friction coefficient (μ ≈ 0.3), which is markedly reduced when high concentrations of NaCl or EDTA are added (μ ≈ 0.1). This lubricant effect can be interpreted considering the electrostatic repulsion between DNA phosphate groups and the AFM tip. Protease digestion increases the friction coefficient (μ ≈ 0.5), but the highest friction is observed when DNA is cleaved by micrococcal nuclease (μ ≈ 0.9), indicating that DNA is the main structural element of plates. Whereas nuclease-digested plates are irreversibly damaged after the friction measurement, native plates can absorb kinetic energy from the AFM tip without suffering any damage. These results suggest that plates are formed by a flexible and mechanically resistant two-dimensional network which allows the safe storage of DNA during mitosis. PMID:21156137
Meta-analysis of aspirin use and risk of lung cancer shows notable results.
Hochmuth, Friederike; Jochem, Maximilian; Schlattmann, Peter
2016-07-01
Aspirin is a promising agent for chemoprevention of lung cancer. We assessed the association of aspirin use and the development of lung cancer, with a focus on heterogeneity between studies. Databases were searched for relevant studies until September 2014. Studies evaluating the relationship of aspirin use and incidence of lung cancer were considered. Relative risks (RR) were extracted and a pooled estimate was calculated. Heterogeneity was assessed by the I measure, random-effects models, and finite-mixture models. Sources of heterogeneity were investigated using a meta-regression. A decreased risk of lung cancer was found including 20 studies [RR=0.87, 95% confidence interval (CI): 0.79-0.95] on the basis of a random-effects model. Strong heterogeneity was observed (τ=0.0258, I=74.4%). As a result, two subpopulations of studies were identified on the basis of a mixture model. The first subpopulation (42%) has an average RR of 0.64. The remaining subpopulation (58%) shows an RR of 1.04. Different results were found for case-control (RR=0.74, 95% CI: 0.60-0.90) and cohort studies (RR=0.99, 95% CI: 0.93-1.06) in a stratified analysis. In a subgroup analysis, use of aspirin was associated with a decreased risk of non-small-cell lung cancer in case-control studies (RR=0.74; 95% CI: 0.58-0.94). At first glance, our meta-analysis shows an average protective effect. A second glance indicates that there is strong heterogeneity. This leads to a subpopulation with considerable benefit and another subpopulation with no benefit. For further investigations, it is important to identify populations that benefit from aspirin use. PMID:26067033
Knowledge-Aided Multichannel Adaptive SAR/GMTI Processing: Algorithm and Experimental Results
NASA Astrophysics Data System (ADS)
Wu, Di; Zhu, Daiyin; Zhu, Zhaoda
2010-12-01
The multichannel synthetic aperture radar ground moving target indication (SAR/GMTI) technique is a simplified implementation of space-time adaptive processing (STAP), which has been proved to be feasible in the past decades. However, its detection performance will be degraded in heterogeneous environments due to the rapidly varying clutter characteristics. Knowledge-aided (KA) STAP provides an effective way to deal with the nonstationary problem in real-world clutter environment. Based on the KA STAP methods, this paper proposes a KA algorithm for adaptive SAR/GMTI processing in heterogeneous environments. It reduces sample support by its fast convergence properties and shows robust to non-stationary clutter distribution relative to the traditional adaptive SAR/GMTI scheme. Experimental clutter suppression results are employed to verify the virtue of this algorithm.
NASA Technical Reports Server (NTRS)
Carrier, Alain C.; Aubrun, Jean-Noel
1993-01-01
New frequency response measurement procedures, on-line modal tuning techniques, and off-line modal identification algorithms are developed and applied to the modal identification of the Advanced Structures/Controls Integrated Experiment (ASCIE), a generic segmented optics telescope test-bed representative of future complex space structures. The frequency response measurement procedure uses all the actuators simultaneously to excite the structure and all the sensors to measure the structural response so that all the transfer functions are measured simultaneously. Structural responses to sinusoidal excitations are measured and analyzed to calculate spectral responses. The spectral responses in turn are analyzed as the spectral data become available and, which is new, the results are used to maintain high quality measurements. Data acquisition, processing, and checking procedures are fully automated. As the acquisition of the frequency response progresses, an on-line algorithm keeps track of the actuator force distribution that maximizes the structural response to automatically tune to a structural mode when approaching a resonant frequency. This tuning is insensitive to delays, ill-conditioning, and nonproportional damping. Experimental results show that is useful for modal surveys even in high modal density regions. For thorough modeling, a constructive procedure is proposed to identify the dynamics of a complex system from its frequency response with the minimization of a least-squares cost function as a desirable objective. This procedure relies on off-line modal separation algorithms to extract modal information and on least-squares parameter subset optimization to combine the modal results and globally fit the modal parameters to the measured data. The modal separation algorithms resolved modal density of 5 modes/Hz in the ASCIE experiment. They promise to be useful in many challenging applications.
Long-Term Trial Results Show No Mortality Benefit from Annual Prostate Cancer Screening
Thirteen year follow-up data from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial show higher incidence but similar mortality among men screened annually with the prostate-specific antigen (PSA) test and digital rectal examination
Algorithms for personalized therapy of type 2 diabetes: results of a web-based international survey
Gallo, Marco; Mannucci, Edoardo; De Cosmo, Salvatore; Gentile, Sandro; Candido, Riccardo; De Micheli, Alberto; Di Benedetto, Antonino; Esposito, Katherine; Genovese, Stefano; Medea, Gerardo; Ceriello, Antonio
2015-01-01
Objective In recent years increasing interest in the issue of treatment personalization for type 2 diabetes (T2DM) has emerged. This international web-based survey aimed to evaluate opinions of physicians about tailored therapeutic algorithms developed by the Italian Association of Diabetologists (AMD) and available online, and to get suggestions for future developments. Another aim of this initiative was to assess whether the online advertising and the survey would have increased the global visibility of the AMD algorithms. Research design and methods The web-based survey, which comprised five questions, has been available from the homepage of the web-version of the journal Diabetes Care throughout the month of December 2013, and on the AMD website between December 2013 and September 2014. Participation was totally free and responders were anonymous. Results Overall, 452 physicians (M=58.4%) participated in the survey. Diabetologists accounted for 76.8% of responders. The results of the survey show wide agreement (>90%) by participants on the utility of the algorithms proposed, even if they do not cover all possible needs of patients with T2DM for a personalized therapeutic approach. In the online survey period and in the months after its conclusion, a relevant and durable increase in the number of unique users who visited the websites was registered, compared to the period preceding the survey. Conclusions Patients with T2DM are heterogeneous, and there is interest toward accessible and easy to use personalized therapeutic algorithms. Responders opinions probably reflect the peculiar organization of diabetes care in each country. PMID:26301097
Comparison of some results of program SHOW with other solar hot water computer programs
NASA Astrophysics Data System (ADS)
Young, M. F.; Baughn, J. W.
Subroutines and the driver program for the simulation code SHOW (solar hot water) for solar thermosyphon systems are discussed, and simulations are compared with predictions by the F-CHART and TRNSYS codes. SHOW has the driver program MAIN, which defines the system control logic for choosing the appropriate system subroutine for analysis. Ten subroutines are described, which account for the solar system physical parameters, the weather data, the manufacturer-supplied system specifications, mass flow rates, pumped systems, total transformed radiation, load use profiles, stratification in storage, an electric water heater, and economic analyses. The three programs are employed to analyze a thermosiphon installation in Sacramento with two storage tanks. TRNSYS and SHOW were in agreement and lower than F-CHARt for annual predictions, although significantly more computer time was necessary to make TRNSYS converge.
Results From Mars Show Electrostatic Charging of the Mars Pathfinder Sojourner Rover
NASA Technical Reports Server (NTRS)
Kolecki, Joseph C.; Siebert, Mark W.
1998-01-01
Indirect evidence (dust accumulation) has been obtained indicating that the Mars Pathfinder rover, Sojourner, experienced electrostatic charging on Mars. Lander camera images of the Sojourner rover provide distinctive evidence of dust accumulation on rover wheels during traverses, turns, and crabbing maneuvers. The sol 22 (22nd Martian "day" after Pathfinder landed) end-of-day image clearly shows fine red dust concentrated around the wheel edges with additional accumulation in the wheel hubs. A sol 41 image of the rover near the rock "Wedge" (see the next image) shows a more uniform coating of dust on the wheel drive surfaces with accumulation in the hubs similar to that in the previous image. In the sol 41 image, note particularly the loss of black-white contrast on the Wheel Abrasion Experiment strips (center wheel). This loss of contrast was also seen when dust accumulated on test wheels in the laboratory. We believe that this accumulation occurred because the Martian surface dust consists of clay-sized particles, similar to those detected by Viking, which have become electrically charged. By adhering to the wheels, the charged dust carries a net nonzero charge to the rover, raising its electrical potential relative to its surroundings. Similar charging behavior was routinely observed in an experimental facility at the NASA Lewis Research Center, where a Sojourner wheel was driven in a simulated Martian surface environment. There, as the wheel moved and accumulated dust (see the following image), electrical potentials in excess of 100 V (relative to the chamber ground) were detected by a capacitively coupled electrostatic probe located 4 mm from the wheel surface. The measured wheel capacitance was approximately 80 picofarads (pF), and the calculated charge, 8 x 10(exp -9) coulombs (C). Voltage differences of 100 V and greater are believed sufficient to produce Paschen electrical discharge in the Martian atmosphere. With an accumulated net charge of 8 x 10(exp
Evaluation of observation-driven evaporation algorithms: results of the WACMOS-ET project
NASA Astrophysics Data System (ADS)
Miralles, Diego G.; Jimenez, Carlos; Ershadi, Ali; McCabe, Matthew F.; Michel, Dominik; Hirschi, Martin; Seneviratne, Sonia I.; Jung, Martin; Wood, Eric F.; (Bob) Su, Z.; Timmermans, Joris; Chen, Xuelong; Fisher, Joshua B.; Mu, Quiaozen; Fernandez, Diego
2015-04-01
Terrestrial evaporation (ET) links the continental water, energy and carbon cycles. Understanding the magnitude and variability of ET at the global scale is an essential step towards reducing uncertainties in our projections of climatic conditions and water availability for the future. However, the requirement of global observational data of ET can neither be satisfied with our sparse global in-situ networks, nor with the existing satellite sensors (which cannot measure evaporation directly from space). This situation has led to the recent rise of several algorithms dedicated to deriving ET fields from satellite data indirectly, based on the combination of ET-drivers that can be observed from space (e.g. radiation, temperature, phenological variability, water content, etc.). These algorithms can either be based on physics (e.g. Priestley and Taylor or Penman-Monteith approaches) or be purely statistical (e.g., machine learning). However, and despite the efforts from different initiatives like GEWEX LandFlux (Jimenez et al., 2011; Mueller et al., 2013), the uncertainties inherent in the resulting global ET datasets remain largely unexplored, partly due to a lack of inter-product consistency in forcing data. In response to this need, the ESA WACMOS-ET project started in 2012 with the main objectives of (a) developing a Reference Input Data Set to derive and validate ET estimates, and (b) performing a cross-comparison, error characterization and validation exercise of a group of selected ET algorithms driven by this Reference Input Data Set and by in-situ forcing data. The algorithms tested are SEBS (Su et al., 2002), the Penman- Monteith approach from MODIS (Mu et al., 2011), the Priestley and Taylor JPL model (Fisher et al., 2008), the MPI-MTE model (Jung et al., 2010) and GLEAM (Miralles et al., 2011). In this presentation we will show the first results from the ESA WACMOS-ET project. The performance of the different algorithms at multiple spatial and temporal
Jimura, Koji; Hirose, Satoshi; Wada, Hiroyuki; Yoshizawa, Yasunori; Imai, Yoshio; Akahane, Masaaki; Machida, Toru; Shirouzu, Ichiro; Koike, Yasuharu; Konishi, Seiki
2016-09-01
The current data article provides behavioral and neuroimaging data for the research article "Relatedness-dependent rapid development of brain activity in anterior temporal cortex during pair-association retrieval" (Jimura et al., 2016) [1]. Behavioral performance is provided in a table. Fig. 2 of the article is based on this table. Brain regions showing time effect are provided in a table. A statistical activation map for the time effect is shown in Fig. 3C of the article. PMID:27508239
NASA Astrophysics Data System (ADS)
Carr, Ian; Schwartz, Robert; Shadden, Shawn
2012-11-01
Cardiac emboli can have devastating consequences if they enter the cerebral circulation, and are the most common cause of embolic stroke. Little is known about relationships of embolic origin/density/size to cerebral events; as these relationships are difficult to observe. To better understand stoke risk from cardiac and aortic emboli, we developed a computational model to track emboli from the heart to the brain. Patient-specific models of the human aorta and arteries to the brain were derived from CT angiography from 10 MHIF patients. Blood flow was modeled by the Navier-Stokes equations using pulsatile inflow at the aortic valve, and physiologic Windkessel models at the outlets. Particulate was injected at the aortic valve and tracked using modified Maxey-Riley equations with a wall collision model. Results demonstrate aortic emboli that entered the cerebral circulation through the carotid or vertebral arteries were localized to specific locations of the proximal aorta. The percentage of released particles embolic to the brain markedly increased with particle size from 0 to ~1-1.5 mm in all patients. Larger particulate became less likely to traverse the cerebral vessels. These findings are consistent with sparse literature based on transesophageal echo measurements. This work was supported in part by the National Science Foundation, award number 1157041.
Algorithm for calculating turbine cooling flow and the resulting decrease in turbine efficiency
NASA Technical Reports Server (NTRS)
Gauntner, J. W.
1980-01-01
An algorithm is presented for calculating both the quantity of compressor bleed flow required to cool the turbine and the decrease in turbine efficiency caused by the injection of cooling air into the gas stream. The algorithm, which is intended for an axial flow, air routine in a properly written thermodynamic cycle code. Ten different cooling configurations are available for each row of cooled airfoils in the turbine. Results from the algorithm are substantiated by comparison with flows predicted by major engine manufacturers for given bulk metal temperatures and given cooling configurations. A list of definitions for the terms in the subroutine is presented.
Kalpathy-Cramer, Jayashree; Zhao, Binsheng; Goldgof, Dmitry; Gu, Yuhua; Wang, Xingwei; Yang, Hao; Tan, Yongqiang; Gillies, Robert; Napel, Sandy
2016-08-01
Tumor volume estimation, as well as accurate and reproducible borders segmentation in medical images, are important in the diagnosis, staging, and assessment of response to cancer therapy. The goal of this study was to demonstrate the feasibility of a multi-institutional effort to assess the repeatability and reproducibility of nodule borders and volume estimate bias of computerized segmentation algorithms in CT images of lung cancer, and to provide results from such a study. The dataset used for this evaluation consisted of 52 tumors in 41 CT volumes (40 patient datasets and 1 dataset containing scans of 12 phantom nodules of known volume) from five collections available in The Cancer Imaging Archive. Three academic institutions developing lung nodule segmentation algorithms submitted results for three repeat runs for each of the nodules. We compared the performance of lung nodule segmentation algorithms by assessing several measurements of spatial overlap and volume measurement. Nodule sizes varied from 29 μl to 66 ml and demonstrated a diversity of shapes. Agreement in spatial overlap of segmentations was significantly higher for multiple runs of the same algorithm than between segmentations generated by different algorithms (p < 0.05) and was significantly higher on the phantom dataset compared to the other datasets (p < 0.05). Algorithms differed significantly in the bias of the measured volumes of the phantom nodules (p < 0.05) underscoring the need for assessing performance on clinical data in addition to phantoms. Algorithms that most accurately estimated nodule volumes were not the most repeatable, emphasizing the need to evaluate both their accuracy and precision. There were considerable differences between algorithms, especially in a subset of heterogeneous nodules, underscoring the recommendation that the same software be used at all time points in longitudinal studies. PMID:26847203
A super-resolution algorithm for enhancement of flash lidar data: flight test results
NASA Astrophysics Data System (ADS)
Bulyshev, Alexander; Amzajerdian, Farzin; Roback, Eric; Reisse, Robert
2013-03-01
This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.
A Super-Resolution Algorithm for Enhancement of FLASH LIDAR Data: Flight Test Results
NASA Technical Reports Server (NTRS)
Bulyshev, Alexander; Amzajerdian, Farzin; Roback, Eric; Reisse Robert
2014-01-01
This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.
NASA Technical Reports Server (NTRS)
Morrell, F. R.; Motyka, P. R.; Bailey, M. L.
1990-01-01
Flight test results for two sensor fault-tolerant algorithms developed for a redundant strapdown inertial measurement unit are presented. The inertial measurement unit (IMU) consists of four two-degrees-of-freedom gyros and accelerometers mounted on the faces of a semi-octahedron. Fault tolerance is provided by edge vector test and generalized likelihood test algorithms, each of which can provide dual fail-operational capability for the IMU. To detect the wide range of failure magnitudes in inertial sensors, which provide flight crucial information for flight control and navigation, failure detection and isolation are developed in terms of a multi level structure. Threshold compensation techniques, developed to enhance the sensitivity of the failure detection process to navigation level failures, are presented. Four flight tests were conducted in a commercial transport-type environment to compare and determine the performance of the failure detection and isolation methods. Dual flight processors enabled concurrent tests for the algorithms. Failure signals such as hard-over, null, or bias shift, were added to the sensor outputs as simple or multiple failures during the flights. Both algorithms provided timely detection and isolation of flight control level failures. The generalized likelihood test algorithm provided more timely detection of low-level sensor failures, but it produced one false isolation. Both algorithms demonstrated the capability to provide dual fail-operational performance for the skewed array of inertial sensors.
Results from CrIS/ATMS Obtained Using an "AIRS Version-6 Like Retrieval Algorithm
NASA Astrophysics Data System (ADS)
Susskind, J.
2015-12-01
A main objective of AIRS/AMSU on EOS is to provide accurate sounding products that are used to generate climate data sets. Suomi NPP carries CrIS/ATMS that were designed as follow-ons to AIRS/AMSU. Our objective is to generate a long term climate data set of products derived from CrIS/ATMS to serve as a continuation of the AIRS/AMSU products. The Goddard DISC has generated AIRS/AMSU retrieval products, extending from September 2002 through real time, using the AIRS Science Team Version-6 retrieval algorithm. Level-3 gridded monthly mean values of these products, generated using AIRS Version-6, form a state of the art multi-year set of Climate Data Records (CDRs), which is expected to continue through 2022 and possibly beyond, as the AIRS instrument is extremely stable. The goal of this research is to develop and implement a CrIS/ATMS retrieval system to generate CDRs that are compatible with, and are of comparable quality to, those generated operationally using AIRS/AMSU data. The AIRS Science Team has made considerable improvements in AIRS Science Team retrieval methodology and is working on the development of an improved AIRS Science Team Version-7 retrieval methodology to be used to reprocess all AIRS data in the relatively near future. Research is underway by Dr. Susskind and co-workers at the NASA GSFC Sounder Research Team (SRT) towards the finalization of the AIRS Version-7 retrieval algorithm, the current version of which is called SRT AIRS Version-6.22. Dr. Susskind and co-workers have developed analogous retrieval methodology for analysis of CrIS/ATMS data, called SRT CrIS Version-6.22. Results will be presented that show that AIRS and CrIS products derived using a common further improved retrieval algorithm agree closely with each other and are both superior to AIRS Version 6. The goal of the AIRS Science Team is to continue to improve both AIRS and CrIS retrieval products and then use the improved retrieval methodology for the processing of past and
Algorithms for detecting antibodies to HIV-1: results from a rural Ugandan cohort.
Nunn, A J; Biryahwaho, B; Downing, R G; van der Groen, G; Ojwiya, A; Mulder, D W
1993-08-01
Although the Western blot test is widely used to confirm HIV-1 serostatus, concerns over its additional cost have prompted review of the need for supplementary testing and the evaluation of alternative test algorithms. Serostatus tends to be confirmed with this additional test especially when tested individuals will be informed of their serostatus or when results will be used for research purposes. The confirmation procedure has been adopted as a means of securing suitably high levels of specificity and sensitivity. With the goal of exploring potential alternatives to Western blot confirmation, the authors describe the use of parallel testing with a competitive and an indirect enzyme immunoassay with and without supplementary Western blots. Sera were obtained from 7895 people in the rural population survey and tested with an algorithm based on the Recombigen HIV-1 EIA and Wellcozyme HIV-1 Recombinant; alternative algorithms were assessed on negative or confirmed positive sera. None of the 227 sera classified as negative by the 2 assays were positive by Western blot. Of the 192 identified ass positive by both assays, 4 were found to be seronegative with Western blot. The possibility of technical error does, however, exist for 3 of these latter cases. One of the alternative algorithms assessed classified all borderline or discordant assay results as negative with 100% specificity and 98.4% sensitivity. This particular algorithm costs only one-third the price of the conventional algorithm. These results therefore suggest that high specificity and sensitivity may be obtained without using Western blot and at a considerable reduction in cost. PMID:8397940
Image Artifacts Resulting from Gamma-Ray Tracking Algorithms Used with Compton Imagers
Seifert, Carolyn E.; He, Zhong
2005-10-01
For Compton imaging it is necessary to determine the sequence of gamma-ray interactions in a single detector or array of detectors. This can be done by time-of-flight measurements if the interactions are sufficiently far apart. However, in small detectors the time between interactions can be too small to measure, and other means of gamma-ray sequencing must be used. In this work, several popular sequencing algorithms are reviewed for sequences with two observed events and three or more observed events in the detector. These algorithms can result in poor imaging resolution and introduce artifacts in the backprojection images. The effects of gamma-ray tracking algorithms on Compton imaging are explored in the context of the 4π Compton imager built by the University of Michigan.
The design and results of an algorithm for intelligent ground vehicles
NASA Astrophysics Data System (ADS)
Duncan, Matthew; Milam, Justin; Tote, Caleb; Riggins, Robert N.
2010-01-01
This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 Intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.
Latifi, Kujtim; Oliver, Jasmine; Baker, Ryan; Dilling, Thomas J.; Stevens, Craig W.; Kim, Jongphil; Yue, Binglin; DeMarco, MaryLou; Zhang, Geoffrey G.; Moros, Eduardo G.; Feygelman, Vladimir
2014-04-01
Purpose: Pencil beam (PB) and collapsed cone convolution (CCC) dose calculation algorithms differ significantly when used in the thorax. However, such differences have seldom been previously directly correlated with outcomes of lung stereotactic ablative body radiation (SABR). Methods and Materials: Data for 201 non-small cell lung cancer patients treated with SABR were analyzed retrospectively. All patients were treated with 50 Gy in 5 fractions of 10 Gy each. The radiation prescription mandated that 95% of the planning target volume (PTV) receive the prescribed dose. One hundred sixteen patients were planned with BrainLab treatment planning software (TPS) with the PB algorithm and treated on a Novalis unit. The other 85 were planned on the Pinnacle TPS with the CCC algorithm and treated on a Varian linac. Treatment planning objectives were numerically identical for both groups. The median follow-up times were 24 and 17 months for the PB and CCC groups, respectively. The primary endpoint was local/marginal control of the irradiated lesion. Gray's competing risk method was used to determine the statistical differences in local/marginal control rates between the PB and CCC groups. Results: Twenty-five patients planned with PB and 4 patients planned with the CCC algorithms to the same nominal doses experienced local recurrence. There was a statistically significant difference in recurrence rates between the PB and CCC groups (hazard ratio 3.4 [95% confidence interval: 1.18-9.83], Gray's test P=.019). The differences (Δ) between the 2 algorithms for target coverage were as follows: ΔD99{sub GITV} = 7.4 Gy, ΔD99{sub PTV} = 10.4 Gy, ΔV90{sub GITV} = 13.7%, ΔV90{sub PTV} = 37.6%, ΔD95{sub PTV} = 9.8 Gy, and ΔD{sub ISO} = 3.4 Gy. GITV = gross internal tumor volume. Conclusions: Local control in patients receiving who were planned to the same nominal dose with PB and CCC algorithms were statistically significantly different. Possible alternative
Results from the New IGS Time Scale Algorithm (version 2.0)
NASA Astrophysics Data System (ADS)
Senior, K.; Ray, J.
2009-12-01
Since 2004 the IGS Rapid and Final clock products have been aligned to a highly stable time scale derived from a weighted ensemble of clocks in the IGS network. The time scale is driven mostly by Hydrogen Maser ground clocks though the GPS satellite clocks also carry non-negligible weight, resulting in a time scale having a one-day frequency stability of about 1E-15. However, because of the relatively simple weighting scheme used in the time scale algorithm and because the scale is aligned to UTC by steering it to GPS Time the resulting stability beyond several days suffers. The authors present results of a new 2.0 version of the IGS time scale highlighting the improvements to the algorithm, new modeling considerations, as well as improved time scale stability.
Swiler, Laura Painton; Eldred, Michael Scott
2009-09-01
This report documents the results of an FY09 ASC V&V Methods level 2 milestone demonstrating new algorithmic capabilities for mixed aleatory-epistemic uncertainty quantification. Through the combination of stochastic expansions for computing aleatory statistics and interval optimization for computing epistemic bounds, mixed uncertainty analysis studies are shown to be more accurate and efficient than previously achievable. Part I of the report describes the algorithms and presents benchmark performance results. Part II applies these new algorithms to UQ analysis of radiation effects in electronic devices and circuits for the QASPR program.
A treatment algorithm for patients with large skull bone defects and first results.
Lethaus, Bernd; Ter Laak, Marielle Poort; Laeven, Paul; Beerens, Maikel; Koper, David; Poukens, Jules; Kessler, Peter
2011-09-01
Large skull bone defects resulting from craniotomies due to cerebral insults, trauma or tumours create functional and aesthetic disturbances to the patient. The reconstruction of large osseous defects is still challenging. A treatment algorithm is presented based on the close interaction of radiologists, computer engineers and cranio-maxillofacial surgeons. From 2004 until today twelve consecutive patients have been operated on successfully according to this treatment plan. Titanium and polyetheretherketone (PEEK) were used to manufacture the implants. The treatment algorithm is proved to be reliable. No corrections had to be performed either to the skull bone or to the implant. Short operations and hospitalization periods are essential prerequisites for treatment success and justify the high expenses. PMID:21055960
Performance analysis results of a battery fuel gauge algorithm at multiple temperatures
NASA Astrophysics Data System (ADS)
Balasingam, B.; Avvari, G. V.; Pattipati, K. R.; Bar-Shalom, Y.
2015-01-01
Evaluating a battery fuel gauge (BFG) algorithm is a challenging problem due to the fact that there are no reliable mathematical models to represent the complex features of a Li-ion battery, such as hysteresis and relaxation effects, temperature effects on parameters, aging, power fade (PF), and capacity fade (CF) with respect to the chemical composition of the battery. The existing literature is largely focused on developing different BFG strategies and BFG validation has received little attention. In this paper, using hardware in the loop (HIL) data collected form three Li-ion batteries at nine different temperatures ranging from -20 °C to 40 °C, we demonstrate detailed validation results of a battery fuel gauge (BFG) algorithm. The BFG validation is based on three different BFG validation metrics; we provide implementation details of these three BFG evaluation metrics by proposing three different BFG validation load profiles that satisfy varying levels of user requirements.
Photometric redshifts with the quasi Newton algorithm (MLPQNA) Results in the PHAT1 contest
NASA Astrophysics Data System (ADS)
Cavuoti, S.; Brescia, M.; Longo, G.; Mercurio, A.
2012-10-01
Context. Since the advent of modern multiband digital sky surveys, photometric redshifts (photo-z's) have become relevant if not crucial to many fields of observational cosmology, such as the characterization of cosmic structures and the weak and strong lensing. Aims: We describe an application to an astrophysical context, namely the evaluation of photometric redshifts, of MLPQNA, which is a machine-learning method based on the quasi Newton algorithm. Methods: Theoretical methods for photo-z evaluation are based on the interpolation of a priori knowledge (spectroscopic redshifts or SED templates), and they represent an ideal comparison ground for neural network-based methods. The MultiLayer Perceptron with quasi Newton learning rule (MLPQNA) described here is an effective computing implementation of neural networks exploited for the first time to solve regression problems in the astrophysical context. It is offered to the community through the DAMEWARE (DAta Mining & Exploration Web Application REsource) infrastructure. Results: The PHAT contest (Hildebrandt et al. 2010, A&A, 523, A31) provides a standard dataset to test old and new methods for photometric redshift evaluation and with a set of statistical indicators that allow a straightforward comparison among different methods. The MLPQNA model has been applied on the whole PHAT1 dataset of 1984 objects after an optimization of the model performed with the 515 available spectroscopic redshifts as training set. When applied to the PHAT1 dataset, MLPQNA obtains the best bias accuracy (0.0006) and very competitive accuracies in terms of scatter (0.056) and outlier percentage (16.3%), scoring as the second most effective empirical method among those that have so far participated in the contest. MLPQNA shows better generalization capabilities than most other empirical methods especially in the presence of underpopulated regions of the knowledge base.
Orion Guidance and Control Ascent Abort Algorithm Design and Performance Results
NASA Technical Reports Server (NTRS)
Proud, Ryan W.; Bendle, John R.; Tedesco, Mark B.; Hart, Jeremy J.
2009-01-01
During the ascent flight phase of NASA s Constellation Program, the Ares launch vehicle propels the Orion crew vehicle to an agreed to insertion target. If a failure occurs at any point in time during ascent then a system must be in place to abort the mission and return the crew to a safe landing with a high probability of success. To achieve continuous abort coverage one of two sets of effectors is used. Either the Launch Abort System (LAS), consisting of the Attitude Control Motor (ACM) and the Abort Motor (AM), or the Service Module (SM), consisting of SM Orion Main Engine (OME), Auxiliary (Aux) Jets, and Reaction Control System (RCS) jets, is used. The LAS effectors are used for aborts from liftoff through the first 30 seconds of second stage flight. The SM effectors are used from that point through Main Engine Cutoff (MECO). There are two distinct sets of Guidance and Control (G&C) algorithms that are designed to maximize the performance of these abort effectors. This paper will outline the necessary inputs to the G&C subsystem, the preliminary design of the G&C algorithms, the ability of the algorithms to predict what abort modes are achievable, and the resulting success of the abort system. Abort success will be measured against the Preliminary Design Review (PDR) abort performance metrics and overall performance will be reported. Finally, potential improvements to the G&C design will be discussed.
Fast and robust segmentation of solar EUV images: algorithm and results for solar cycle 23
NASA Astrophysics Data System (ADS)
Barra, V.; Delouille, V.; Kretzschmar, M.; Hochedez, J.-F.
2009-10-01
Context: The study of the variability of the solar corona and the monitoring of coronal holes, quiet sun and active regions are of great importance in astrophysics as well as for space weather and space climate applications. Aims: In a previous work, we presented the spatial possibilistic clustering algorithm (SPoCA). This is a multi-channel unsupervised spatially-constrained fuzzy clustering method that automatically segments solar extreme ultraviolet (EUV) images into regions of interest. The results we reported on SoHO-EIT images taken from February 1997 to May 2005 were consistent with previous knowledge in terms of both areas and intensity estimations. However, they presented some artifacts due to the method itself. Methods: Herein, we propose a new algorithm, based on SPoCA, that removes these artifacts. We focus on two points: the definition of an optimal clustering with respect to the regions of interest, and the accurate definition of the cluster edges. We moreover propose methodological extensions to this method, and we illustrate these extensions with the automatic tracking of active regions. Results: The much improved algorithm can decompose the whole set of EIT solar images over the 23rd solar cycle into regions that can clearly be identified as quiet sun, coronal hole and active region. The variations of the parameters resulting from the segmentation, i.e. the area, mean intensity, and relative contribution to the solar irradiance, are consistent with previous results and thus validate the decomposition. Furthermore, we find indications for a small variation of the mean intensity of each region in correlation with the solar cycle. Conclusions: The method is generic enough to allow the introduction of other channels or data. New applications are now expected, e.g. related to SDO-AIA data.
Results from CrIS/ATMS Obtained Using an AIRS "Version-6 like" Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2015-01-01
We tested and evaluated Version-6.22 AIRS and Version-6.22 CrIS products on a single day, December 4, 2013, and compared results to those derived using AIRS Version-6. AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6All AIRS and CrIS products agree reasonably well with each other. CrIS Version-6.22 T(p) and q(p) results are slightly poorer than AIRS over land, especially under very cloudy conditions. Both AIRS and CrIS Version-6.22 run now at JPL. Our short term plans are to analyze many common months at JPL in the near future using Version-6.22 or a further improved algorithm to assess the compatibility of AIRS and CrIS monthly mean products and their interannual differences. Updates to the calibration of both CrIS and ATMS are still being finalized. JPL plans, in collaboration with the Goddard DISC, to reprocess all AIRS data using a still to be finalized Version-7 retrieval algorithm, and to reprocess all recalibrated CrISATMS data using Version-7 as well.
Results from CrIS/ATMS Obtained Using an AIRS "Version-6 Like" Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2015-01-01
We have tested and evaluated Version-6.22 AIRS and Version-6.22 CrIS products on a single day, December 4, 2013, and compared results to those derived using AIRS Version-6. AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6All AIRS and CrIS products agree reasonably well with each other CrIS Version-6.22 T(p) and q(p) results are slightly poorer than AIRS under very cloudy conditions. Both AIRS and CrIS Version-6.22 run now at JPL. Our short term plans are to analyze many common months at JPL in the near future using Version-6.22 or a further improved algorithm to assess the compatibility of AIRS and CrIS monthly mean products and their interannual differencesUpdates to the calibration of both CrIS and ATMS are still being finalized. JPL plans, in collaboration with the Goddard DISC, to reprocess all AIRS data using a still to be finalized Version-7 retrieval algorithm, and to reprocess all recalibrated CrISATMS data using Version-7 as well.
A Formal Algorithm for Verifying the Validity of Clustering Results Based on Model Checking
Huang, Shaobin; Cheng, Yuan; Lang, Dapeng; Chi, Ronghua; Liu, Guofeng
2014-01-01
The limitations in general methods to evaluate clustering will remain difficult to overcome if verifying the clustering validity continues to be based on clustering results and evaluation index values. This study focuses on a clustering process to analyze crisp clustering validity. First, we define the properties that must be satisfied by valid clustering processes and model clustering processes based on program graphs and transition systems. We then recast the analysis of clustering validity as the problem of verifying whether the model of clustering processes satisfies the specified properties with model checking. That is, we try to build a bridge between clustering and model checking. Experiments on several datasets indicate the effectiveness and suitability of our algorithms. Compared with traditional evaluation indices, our formal method can not only indicate whether the clustering results are valid but, in the case the results are invalid, can also detect the objects that have led to the invalidity. PMID:24608823
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.
Kang, Sang Yull; Park, Ho Sung
2016-01-01
Purpose Depth of wall invasion is an important prognostic factor in patients with gastric cancer, whereas the prognostic significance of intraoperative macroscopic serosal invasion (mSE) findings remain unclear when they show a discrepancy in pathologic findings. This study, therefore, assessed the prognostic significance of mSE. Methods Data from cohort of 2,835 patients with resectable gastric cancer who underwent surgery between 1990 and 2010 were retrospectively reviewed. Results The overall accuracy of mSE and pathologic results was 83.4%. The accuracy of mSE was 75.5% in pT2. On the other hand, the accuracy of pT3 dropped to 24.5%. According to mSE findings (+/–), the 5-year disease-specific survival (DSS) rate differed significantly in patients with pT2 (+; 74.2% vs. –; 92.0%), pT3 (+; 76.7% vs. –; 91.8%) and pT4a (+; 51.3% vs. –; 72.8%) (P < 0.001 each), but not in patients with T1 tumor. Multivariate analysis showed that mSE findings (hazard ratio [HR], 2.275; 95% confidence interval [CI], 1.148–4.509), tumor depth (HR, 6.894; 95% CI, 2.325–20.437), nodal status (HR, 5.206; 95% CI, 2.298–11.791), distant metastasis (HR, 2.881; 95% CI, 1.388–6.209), radical resection (HR, 2.002; 95% CI, 1.017–3.940), and lymphatic invasion (HR, 2.713; 95% CI, 1.424–5.167) were independent predictors of 5-year DSS rate. Conclusion We observed considerable discrepancies between macroscopic and pathologic diagnosis of serosal invasion. However, macroscopic diagnosis of serosal invasion was independently prognostic of 5-year DSS. It suggests that because the pathologic results could not be perfect and the local inflammatory change with mSE(+) could affect survival, a combination of mSE(+/–) and pathologic depth may be predictive of prognosis in patients with gastric cancer. PMID:27186569
NASA Astrophysics Data System (ADS)
Burns, D. A.; Schelker, J.; Murray, K. R.; Brigham, M. E.; Aiken, G.
2009-12-01
in ponded areas, and (3) the effects of the widely varying seasonal temperature and snow cover on the rates of microbial processes such as the decomposition of soil organic matter and methylation of Hg. These results emphasize that not all watersheds show simple linear relations between DOC and Hg species on an annual basis, and provide a caution that measurements such as the optical properties of waters are not always a strong surrogate for Hg.
Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberger, Mark; Shidner, Jeremy; Munk, Michelle
2013-01-01
The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012.
Viola, Francesco; Coe, Ryan L.; Owen, Kevin; Guenther, Drake A.; Walker, William F.
2008-01-01
Image registration and motion estimation play central roles in many fields, including RADAR, SONAR, light microscopy, and medical imaging. Because of its central significance, estimator accuracy, precision, and computational cost are of critical importance. We have previously presented a highly accurate, spline-based time delay estimator that directly determines sub-sample time delay estimates from sampled data. The algorithm uses cubic splines to produce a continuous representation of a reference signal and then computes an analytical matching function between this reference and a delayed signal. The location of the minima of this function yields estimates of the time delay. In this paper we describe the MUlti-dimensional Spline-based Estimator (MUSE) that allows accurate and precise estimation of multidimensional displacements/strain components from multidimensional data sets. We describe the mathematical formulation for two- and three-dimensional motion/strain estimation and present simulation results to assess the intrinsic bias and standard deviation of this algorithm and compare it to currently available multi-dimensional estimators. In 1000 noise-free simulations of ultrasound data we found that 2D MUSE exhibits maximum bias of 2.6 × 10−4 samples in range and 2.2 × 10−3 samples in azimuth (corresponding to 4.8 and 297 nm, respectively). The maximum simulated standard deviation of estimates in both dimensions was comparable at roughly 2.8 × 10−3 samples (corresponding to 54 nm axially and 378 nm laterally). These results are between two and three orders of magnitude better than currently used 2D tracking methods. Simulation of performance in 3D yielded similar results to those observed in 2D. We also present experimental results obtained using 2D MUSE on data acquired by an Ultrasonix Sonix RP imaging system with an L14-5/38 linear array transducer operating at 6.6 MHz. While our validation of the algorithm was performed using ultrasound data, MUSE
Mead, David; Drinkwater, Colleen; Brumm, Phillip J.
2013-01-01
Background Alkaliphilic Bacillus species are intrinsically interesting due to the bioenergetic problems posed by growth at high pH and high salt. Three alkaline cellulases have been cloned, sequenced and expressed from Bacillus cellulosilyticus N-4 (Bcell) making it an excellent target for genomic sequencing and mining of biomass-degrading enzymes. Methodology/Principal Findings The genome of Bcell is a single chromosome of 4.7 Mb with no plasmids present and three large phage insertions. The most unusual feature of the genome is the presence of 23 LPXTA membrane anchor proteins; 17 of these are annotated as involved in polysaccharide degradation. These two values are significantly higher than seen in any other Bacillus species. This high number of membrane anchor proteins is seen only in pathogenic Gram-positive organisms such as Listeria monocytogenes or Staphylococcus aureus. Bcell also possesses four sortase D subfamily 4 enzymes that incorporate LPXTA-bearing proteins into the cell wall; three of these are closely related to each other and unique to Bcell. Cell fractionation and enzymatic assay of Bcell cultures show that the majority of polysaccharide degradation is associated with the cell wall LPXTA-enzymes, an unusual feature in Gram-positive aerobes. Genomic analysis and growth studies both strongly argue against Bcell being a truly cellulolytic organism, in spite of its name. Preliminary results suggest that fungal mycelia may be the natural substrate for this organism. Conclusions/Significance Bacillus cellulosilyticus N-4, in spite of its name, does not possess any of the genes necessary for crystalline cellulose degradation, demonstrating the risk of classifying microorganisms without the benefit of genomic analysis. Bcell is the first Gram-positive aerobic organism shown to use predominantly cell-bound, non-cellulosomal enzymes for polysaccharide degradation. The LPXTA-sortase system utilized by Bcell may have applications both in anchoring
Development of region processing algorithm for HSTAMIDS: status and field test results
NASA Astrophysics Data System (ADS)
Ngan, Peter; Burke, Sean; Cresci, Roger; Wilson, Joseph N.; Gader, Paul; Ho, K. C.; Bartosz, Elizabeth; Duvoisin, Herbert
2007-04-01
The Region Processing Algorithm (RPA) has been developed by the Office of the Army Humanitarian Demining Research and Development (HD R&D) Program as part of improvements for the AN/PSS-14. The effort was a collaboration between the HD R&D Program, L-3 Communication CyTerra Corporation, University of Florida, Duke University and University of Missouri. RPA has been integrated into and implemented in a real-time AN/PSS-14. The subject unit was used to collect data and tested for its performance at three Army test sites within the United States of America. This paper describes the status of the technology and its recent test results.
One-year results of an algorithmic approach to managing failed back surgery syndrome
Avellanal, Martín; Diaz-Reganon, Gonzalo; Orts, Alejandro; Soto, Silvia
2014-01-01
BACKGROUND: Failed back surgery syndrome (FBSS) is a major clinical problem. Different etiologies with different incidence rates have been proposed. There are currently no standards regarding the management of these patients. Epiduroscopy is an endoscopic technique that may play a role in the management of FBSS. OBJECTIVE: To evaluate an algorithm for management of severe FBSS including epiduroscopy as a diagnostic and therapeutic tool. METHODS: A total of 133 patients with severe symptoms of FBSS (visual analogue scale score ≥7) and no response to pharmacological treatment and physical therapy were included. A six-step management algorithm was applied. Data, including patient demographics, pain and surgical procedure, were analyzed. In all cases, one or more objective causes of pain were established. Treatment success was defined as ≥50% long-term pain relief maintained during the first year of follow-up. Final allocation of patients was registered: good outcome with conservative treatment, surgical reintervention and palliative treatment with implantable devices. RESULTS: Of 122 patients enrolled, 59.84% underwent instrumented surgery and 40.16% a noninstrumented procedure. Most (64.75%) experienced significant pain relief with conventional pain clinic treatments; 15.57% required surgical treatment. Palliative spinal cord stimulation and spinal analgesia were applied in 9.84% and 2.46% of the cases, respectively. The most common diagnosis was epidural fibrosis, followed by disc herniation, global or lateral stenosis, and foraminal stenosis. CONCLUSIONS: A new six-step ladder approach to severe FBSS management that includes epiduroscopy was analyzed. Etiologies are accurately described and a useful role of epiduroscopy was confirmed. PMID:25222573
NASA Technical Reports Server (NTRS)
Merrill, Walter C.; Delaat, John C.; Kroszkewicz, Steven M.; Abdelwahab, Mahmood
1987-01-01
The objective of the advanced detection, isolation, and accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, algorithms were developed which detect, isolate, and accommodate sensor failures using analytical redundancy. Preliminary results of a full scale engine demonstration of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 turbofan engine control system are determined and compared to those obtained during a previous evaluation of this algorithm using a real-time hybrid computer simulation of the engine.
NASA Astrophysics Data System (ADS)
Merrill, Walter C.; Delaat, John C.; Kroszkewicz, Steven M.; Abdelwahab, Mahmood
The objective of the advanced detection, isolation, and accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, algorithms were developed which detect, isolate, and accommodate sensor failures using analytical redundancy. Preliminary results of a full scale engine demonstration of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 turbofan engine control system are determined and compared to those obtained during a previous evaluation of this algorithm using a real-time hybrid computer simulation of the engine.
NASA Technical Reports Server (NTRS)
Merrill, Walter C.; Delaat, John C.; Kroszkewicz, Steven M.; Abdelwahab, Mahmood
1987-01-01
The objective of the advanced detection, isolation, and accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, algorithms were developed which detect, isolate, and accommodate sensor failures using analytical redundancy. Preliminary results of a full scale engine demonstration of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 turbofan engine control system are determined and compared to those obtained during a previous evaluation of this algorithm using a real-time hybrid computer simulation of the engine.
Wei, Wen-Cheng; Wu, Ching-Yang; Wu, Ching-Feng; Fu, Jui-Ying; Su, Ta-Wei; Yu, Sheng-Yueh; Kao, Tsung-Chi; Ko, Po-Jen
2015-01-01
Abstract Vascular cutdown and echo guide puncture methods have its own limitations under certain conditions. There was no available algorithm for choosing entry vessel. A standard algorithm was introduced to help choose the entry vessel location according to our clinical experience and review of the literature. The goal of this study is to analyze the treatment results of the standard algorithm used to choose the entry vessel for intravenous port implantation. During the period between March 2012 and March 2013, 507 patients who received intravenous port implantation due to advanced chemotherapy were included into this study. Choice of entry vessel was according to standard algorithm. All clinical characteristic factors were collected and complication rate and incidence were further analyzed. Compared with our clinical experience in 2006, procedure-related complication rate declined from 1.09% to 0.4%, whereas the late complication rate decreased from 19.97% to 3.55%. No more pneumothorax, hematoma, catheter kinking, fractures, and pocket erosion were identified after using the standard algorithm. In alive oncology patients, 98% implanted port could serve a functional vascular access to fit therapeutic needs. This standard algorithm for choosing the best entry vessel is a simple guideline that is easy to follow. The algorithm has excellent efficiency and can minimize complication rates and incidence. PMID:26287429
Manning, Andrew H.; Verplanck, Philip L.; Mast, M. Alisa; Wanty, Richard B.
2008-01-01
PREFACE This Open-File Report consists of a presentation given in Crested Butte, Colorado on December 13, 2007 to the Standard Mine Advisory Group. The presentation was paired with another presentation given by the Colorado Division of Reclamation, Mining, and Safety on the physical features and geology of the Standard Mine. The presentation in this Open-File Report summarizes the results and conclusions of a hydrogeochemical investigation of the Standard Mine performed by the U.S. Geological Survey (Manning and others, in press). The purpose of the investigation was to aid the U.S. Environmental Protection Agency in evaluating remediation options for the Standard Mine site. Additional details and supporting data related to the information in this presentation can be found in Manning and others (in press).
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.
Brito Lopes, Fernando; da Silva, Marcelo Corrêa; Magnabosco, Cláudio Ulhôa; Goncalves Narciso, Marcelo; Sainz, Roberto Daniel
2016-01-01
This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection. PMID:26789008
Brito Lopes, Fernando; da Silva, Marcelo Corrêa; Magnabosco, Cláudio Ulhôa; Goncalves Narciso, Marcelo; Sainz, Roberto Daniel
2016-01-01
This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection. PMID:26789008
NASA Technical Reports Server (NTRS)
Morrell, F. R.; Bailey, M. L.; Motyka, P. R.
1988-01-01
Flight test results of a vector-based fault-tolerant algorithm for a redundant strapdown inertial measurement unit are presented. Because the inertial sensors provide flight-critical information for flight control and navigation, failure detection and isolation is developed in terms of a multi-level structure. Threshold compensation techniques for gyros and accelerometers, developed to enhance the sensitivity of the failure detection process to low-level failures, are presented. Four flight tests, conducted in a commercial transport type environment, were used to determine the ability of the failure detection and isolation algorithm to detect failure signals, such a hard-over, null, or bias shifts. The algorithm provided timely detection and correct isolation of flight control- and low-level failures. The flight tests of the vector-based algorithm demonstrated its capability to provide false alarm free dual fail-operational performance for the skewed array of inertial sensors.
New Cirrus Retrieval Algorithms and Results from eMAS during SEAC4RS
NASA Astrophysics Data System (ADS)
Holz, R.; Platnick, S. E.; Meyer, K.; Wang, C.; Wind, G.; Arnold, T.; King, M. D.; Yorks, J. E.; McGill, M. J.
2014-12-01
The enhanced MODIS Airborne Simulator (eMAS) scanning imager was flown on the ER-2 during the SEAC4RS field campaign. The imager provides measurements in 38 spectral channels from the visible into the 13μm CO2 absorption bands at approximately 25 m nadir spatial resolution at cirrus altitudes, and with a swath width of about 18 km, provided substantial context and synergy for other ER-2 cirrus observations. The eMAS is an update to the original MAS scanner, having new midwave and IR spectrometers coupled with the previous VNIR/SWIR spectrometers. In addition to the standard MODIS-like cloud retrieval algorithm (MOD06/MYD06 for MODIS Terra/Aqua, respectively) that provides cirrus optical thickness (COT) and effective particle radius (CER) from several channel combinations, three new algorithms were developed to take advantage of unique aspects of eMAS and/or other ER-2 observations. The first uses a combination of two solar reflectance channels within the 1.88 μm water vapor absorption band, each with significantly different single scattering albedo, allowing for simultaneous COT and CER retrievals. The advantage of this algorithm is that the strong water vapor absorption can significantly reduce the sensitivity to lower level clouds and ocean/land surface properties thus better isolating cirrus properties. A second algorithm uses a suite of infrared channels in an optimal estimation algorithm to simultaneously retrieve COT, CER, and cloud-top pressure/temperature. Finally, a window IR algorithm is used to retrieve COT in synergy with the ER-2 Cloud Physics Lidar (CPL) cloud top/base boundary measurements. Using a variety of quantifiable error sources, uncertainties for all eMAS retrievals will be shown along with comparisons with CPL COT retrievals.
Danilovic, D; Ohm, O J; Stroebel, J; Breivik, K; Hoff, P I; Markowitz, T
1998-05-01
We have developed an algorithmic method for automatic determination of stimulation thresholds in both cardiac chambers in patients with intact atrioventricular (AV) conduction. The algorithm utilizes ventricular sensing, may be used with any type of pacing leads, and may be downloaded via telemetry links into already implanted dual-chamber Thera pacemakers. Thresholds are determined with 0.5 V amplitude and 0.06 ms pulse-width resolution in unipolar, bipolar, or both lead configurations, with a programmable sampling interval from 2 minutes to 48 hours. Measured values are stored in the pacemaker memory for later retrieval and do not influence permanent output settings. The algorithm was intended to gather information on continuous behavior of stimulation thresholds, which is important in the formation of strategies for programming pacemaker outputs. Clinical performance of the algorithm was evaluated in eight patients who received bipolar tined steroid-eluting leads and were observed for a mean of 5.1 months. Patient safety was not compromised by the algorithm, except for the possibility of pacing during the physiologic refractory period. Methods for discrimination of incorrect data points were developed and incorrect values were discarded. Fine resolution threshold measurements collected during this study indicated that: (1) there were great differences in magnitude of threshold peaking in different patients; (2) the initial intensive threshold peaking was usually followed by another less intensive but longer-lasting wave of threshold peaking; (3) the pattern of tissue reaction in the atrium appeared different from that in the ventricle; and (4) threshold peaking in the bipolar lead configuration was greater than in the unipolar configuration. The algorithm proved to be useful in studying ambulatory thresholds. PMID:9604237
NASA Astrophysics Data System (ADS)
Reynolds, William R.; Talcott, Denise; Hilgers, John W.
2002-07-01
A new iterative algorithm (EMLS) via the expectation maximization method is derived for extrapolating a non- negative object function from noisy, diffraction blurred image data. The algorithm has the following desirable attributes; fast convergence is attained for high frequency object components, is less sensitive to constraint parameters, and will accommodate randomly missing data. Speed and convergence results are presented. Field test imagery was obtained with a passive millimeter wave imaging sensor having a 30.5 cm aperture. The algorithm was implemented and tested in near real time using field test imagery. Theoretical results and experimental results using the field test imagery will be compared using an effective aperture measure of resolution increase. The effective aperture measure, based on examination of the edge-spread function, will be detailed.
NASA Technical Reports Server (NTRS)
Knox, C. E.; Vicroy, D. D.; Simmon, D. A.
1985-01-01
A simple, airborne, flight-management descent algorithm was developed and programmed into a small programmable calculator. The algorithm may be operated in either a time mode or speed mode. The time mode was designed to aid the pilot in planning and executing a fuel-conservative descent to arrive at a metering fix at a time designated by the air traffic control system. The speed model was designed for planning fuel-conservative descents when time is not a consideration. The descent path for both modes was calculated for a constant with considerations given for the descent Mach/airspeed schedule, gross weight, wind, wind gradient, and nonstandard temperature effects. Flight tests, using the algorithm on the programmable calculator, showed that the open-loop guidance could be useful to airline flight crews for planning and executing fuel-conservative descents.
Knox, C.E.; Vicroy, D.D.; Simmon, D.A.
1985-05-01
A simple, airborne, flight-management descent algorithm was developed and programmed into a small programmable calculator. The algorithm may be operated in either a time mode or speed mode. The time mode was designed to aid the pilot in planning and executing a fuel-conservative descent to arrive at a metering fix at a time designated by the air traffic control system. The speed model was designed for planning fuel-conservative descents when time is not a consideration. The descent path for both modes was calculated for a constant with considerations given for the descent Mach/airspeed schedule, gross weight, wind, wind gradient, and nonstandard temperature effects. Flight tests, using the algorithm on the programmable calculator, showed that the open-loop guidance could be useful to airline flight crews for planning and executing fuel-conservative descents.
Results with an Algorithmic Approach to Hybrid Repair of the Aortic Arch
Andersen, Nicholas D.; Williams, Judson B.; Hanna, Jennifer M.; Shah, Asad A.; McCann, Richard L.; Hughes, G. Chad
2013-01-01
Objective Hybrid repair of the transverse aortic arch may allow for aortic arch repair with reduced morbidity in patients who are suboptimal candidates for conventional open surgery. Here, we present our results with an algorithmic approach to hybrid arch repair, based upon the extent of aortic disease and patient comorbidities. Methods Between August 2005 and January 2012, 87 patients underwent hybrid arch repair by three principal procedures: zone 1 endograft coverage with extra-anatomic left carotid revascularization (zone 1, n=19), zone 0 endograft coverage with aortic arch debranching (zone 0, n=48), or total arch replacement with staged stented elephant trunk completion (stented elephant trunk, n=20). Results The mean patient age was 64 years and the mean expected in-hospital mortality rate was 16.3% as calculated by the EuroSCORE II. 22% (n=19) of operations were non-elective. Sternotomy, cardiopulmonary bypass, and deep hypothermic circulatory arrest were required in 78% (n=68), 45% (n=39), and 31% (n=27) of patients, respectively, to allow for total arch replacement, arch debranching, or other concomitant cardiac procedures, including ascending ± hemi-arch replacement in 17% (n=8) of patients undergoing zone 0 repair. All stented elephant trunk procedures (n=20) and 19% (n=9) of zone 0 procedures were staged, with 41% (n=12) of patients undergoing staged repair during a single hospitalization. The 30-day/in-hospital rates of stroke and permanent paraplegia/paraparesis were 4.6% (n=4) and 1.2% (n=1), respectively. Three of 27 (11.1%) patients with native ascending aorta zone 0 proximal landing zone experienced retrograde type A dissection following endograft placement. The overall in-hospital mortality rate was 5.7% (n=5), however, 30-day/in-hospital mortality increased to 14.9% (n=13) due to eight 30-day out-of-hospital deaths. Native ascending aorta zone 0 endograft placement was found to be the only univariate predictor of 30-day/in-hospital mortality
Remote sensing of gases by hyperspectral imaging: algorithms and results of field measurements
NASA Astrophysics Data System (ADS)
Sabbah, Samer; Rusch, Peter; Eichmann, Jens; Gerhard, Jörn-Hinnrich; Harig, Roland
2012-09-01
Remote gas detection and visualization provides vital information in scenarios involving chemical accidents, terrorist attacks or gas leaks. Previous work showed how imaging infrared spectroscopy can be used to assess the location, the dimensions, and the dispersion of a potentially hazardous cloud. In this work the latest developments of an infrared hyperspectral imager based on a Michelson interferometer in combination with a focal plane array detector are presented. The performance of the system is evaluated by laboratory measurements. The system was deployed in field measurements to identify industrial gas emissions. Excellent results were obtained by successfully identifying released gases from relatively long distances.
NASA Technical Reports Server (NTRS)
Moes, Timothy R.; Whitmore, Stephen A.
1991-01-01
A technique was developed to improve the fidelity of airdata measurements during dynamic maneuvering. This technique is particularly useful for airdata measured during flight at high angular rates and high angles of attack. To support this research, flight tests using the F-18 high alpha research vehicle (HARV) were conducted at NASA Ames Research Center, Dryden Flight Research Facility. A Kalman filter was used to combine information from research airdata, linear accelerometers, angular rate gyros, and attitude gyros to determine better estimates of airdata quantities such as angle of attack, angle of sideslip, airspeed, and altitude. The state and observation equations used by the Kalman filter are briefly developed and it is shown how the state and measurement covariance matrices were determined from flight data. Flight data are used to show the results of the technique and these results are compared to an independent measurement source. This technique is applicable to both postflight and real-time processing of data.
NASA Technical Reports Server (NTRS)
Guo, Liwen; Cardullo, Frank M.; Kelly, Lon C.
2007-01-01
This report summarizes the results of delay measurement and piloted performance tests that were conducted to assess the effectiveness of the adaptive compensator and the state space compensator for alleviating the phase distortion of transport delay in the visual system in the VMS at the NASA Langley Research Center. Piloted simulation tests were conducted to assess the effectiveness of two novel compensators in comparison to the McFarland predictor and the baseline system with no compensation. Thirteen pilots with heterogeneous flight experience executed straight-in and offset approaches, at various delay configurations, on a flight simulator where different predictors were applied to compensate for transport delay. The glideslope and touchdown errors, power spectral density of the pilot control inputs, NASA Task Load Index, and Cooper-Harper rating of the handling qualities were employed for the analyses. The overall analyses show that the adaptive predictor results in slightly poorer compensation for short added delay (up to 48 ms) and better compensation for long added delay (up to 192 ms) than the McFarland compensator. The analyses also show that the state space predictor is fairly superior for short delay and significantly superior for long delay than the McFarland compensator.
Results from CrIS/ATMS Obtained Using an "AIRS Version-6 Like" Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2015-01-01
A main objective of AIRS/AMSU on EOS is to provide accurate sounding products that are used to generate climate data sets. Suomi NPP carries CrIS/ATMS that were designed as follow-ons to AIRS/AMSU. Our objective is to generate a long term climate data set of products derived from CrIS/ATMS to serve as a continuation of the AIRS/AMSU products. We have modified an improved version of the operational AIRS Version-6 retrieval algorithm for use with CrIS/ATMS. CrIS/ATMS products are of very good quality, and are comparable to, and consistent with, those of AIRS.
An Artificial Immune Univariate Marginal Distribution Algorithm
NASA Astrophysics Data System (ADS)
Zhang, Qingbin; Kang, Shuo; Gao, Junxiang; Wu, Song; Tian, Yanping
Hybridization is an extremely effective way of improving the performance of the Univariate Marginal Distribution Algorithm (UMDA). Owing to its diversity and memory mechanisms, artificial immune algorithm has been widely used to construct hybrid algorithms with other optimization algorithms. This paper proposes a hybrid algorithm which combines the UMDA with the principle of general artificial immune algorithm. Experimental results on deceptive function of order 3 show that the proposed hybrid algorithm can get more building blocks (BBs) than the UMDA.
First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm
NASA Technical Reports Server (NTRS)
Joiner, Joanna; Vasilkov, Alexander P.
2006-01-01
We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds.
Newton, Katherine M; Peissig, Peggy L; Kho, Abel Ngo; Bielinski, Suzette J; Berg, Richard L; Choudhary, Vidhu; Basford, Melissa; Chute, Christopher G; Kullo, Iftikhar J; Li, Rongling; Pacheco, Jennifer A; Rasmussen, Luke V; Spangler, Leslie; Denny, Joshua C
2013-01-01
Background Genetic studies require precise phenotype definitions, but electronic medical record (EMR) phenotype data are recorded inconsistently and in a variety of formats. Objective To present lessons learned about validation of EMR-based phenotypes from the Electronic Medical Records and Genomics (eMERGE) studies. Materials and methods The eMERGE network created and validated 13 EMR-derived phenotype algorithms. Network sites are Group Health, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University. Results By validating EMR-derived phenotypes we learned that: (1) multisite validation improves phenotype algorithm accuracy; (2) targets for validation should be carefully considered and defined; (3) specifying time frames for review of variables eases validation time and improves accuracy; (4) using repeated measures requires defining the relevant time period and specifying the most meaningful value to be studied; (5) patient movement in and out of the health plan (transience) can result in incomplete or fragmented data; (6) the review scope should be defined carefully; (7) particular care is required in combining EMR and research data; (8) medication data can be assessed using claims, medications dispensed, or medications prescribed; (9) algorithm development and validation work best as an iterative process; and (10) validation by content experts or structured chart review can provide accurate results. Conclusions Despite the diverse structure of the five EMRs of the eMERGE sites, we developed, validated, and successfully deployed 13 electronic phenotype algorithms. Validation is a worthwhile process that not only measures phenotype performance but also strengthens phenotype algorithm definitions and enhances their inter-institutional sharing. PMID:23531748
Results from CrIS/ATMS Obtained Using an "AIRS Version-6 Like" Retrieval Algorithm
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena; Blaisdell, John
2015-01-01
AIRS and CrIS Version-6.22 O3(p) and q(p) products are both superior to those of AIRS Version-6.Monthly mean August 2014 Version-6.22 AIRS and CrIS products agree reasonably well with OMPS, CERES, and witheach other. JPL plans to process AIRS and CrIS for many months and compare interannual differences. Updates to thecalibration of both CrIS and ATMS are still being finalized. We are also working with JPL to develop a joint AIRS/CrISlevel-1 to level-3 processing system using a still to be finalized Version-7 retrieval algorithm. The NASA Goddard DISCwill eventually use this system to reprocess all AIRS and recalibrated CrIS/ATMS. .
Six clustering algorithms applied to the WAIS-R: the problem of dissimilar cluster results.
Fraboni, M; Cooper, D
1989-11-01
Clusterings of the Wechsler Adult Intelligence Scale-Revised subtests were obtained from the application of six hierarchical clustering methods (N = 113). These sets of clusters were compared for similarities using the Rand index. The calculated indices suggested similarities of cluster group membership between the Complete Linkage and Centroid methods; Complete Linkage and Ward's methods; Centroid and Ward's methods; and Single Linkage and Average Linkage Between Groups methods. Cautious use of single clustering methods is implied, though the authors suggest some advantages of knowing specific similarities and differences. If between-method comparisons consistently reveal similar cluster membership, a choice could be made from those algorithms that tend to produce similar partitions, thereby enhancing cluster interpretation. PMID:2613904
NASA Astrophysics Data System (ADS)
Montbriand, L. E.
1991-07-01
A peak identification technique which uses the fast Fourier transform (FFT) algorithm is presented for unambiguously identifying up to three sources in signals received by the sampled aperture receiving array (SARA) of the Communications Research Center. The technique involves removing phase rotations resulting from the FFT and the data configuration and interpreting this result as the direction cosine distribution of the received signal. The locations and amplitudes of all peaks for one array arm are matched with those in a master list for a single source in order to identify actual sources. The identification of actual sources was found to be subject to the limitations of the FFT in that there was an inherent bias for the secondary and tertiary sources to appear at the side-lobe positions of the strongest source. There appears to be a limit in the ratio of the magnitude of a weaker source to that of the strongest source, below which it becomes too difficult to reliably identify true sources. For the SARA array this ratio is near-10 dB. Some of the data were also analyzed using the more complex MUSIC algorithm which yields a narrower directional peak for the sources than the FFT. For the SARA array, using ungroomed data, the largest side and grating lobes that the MUSIC algorithm produces are some 10 dB below the largest side and grating lobes that are produced using the FFT algorithm. Consequently the source-separation problem is less than that encountered using the FFT algorithm, but is not eliminated.
Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA
Turner, David D.
2005-04-01
A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 μm, whereas liquid water is more absorbing than ice from 16 to 25 μm. MIXCRA retrievals are only valid for optically thin (τvisible < 6) single-layer clouds when the precipitable water vapor is less than 1 cm. MIXCRA was applied to the Atmospheric Emitted Radiance Interferometer (AERI) data that were collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment from November 1997 to May 1998, where 63% of all of the cloudy scenes above the SHEBA site met this specification. The retrieval determined that approximately 48% of these clouds were mixed phase and that a significant number of clouds (during all 7 months) contained liquid water, even for cloud temperatures as low as 240 K. The retrieved distributions of effective radii for water and ice particles in single-phase clouds are shown to be different than the effective radii in mixed-phase clouds.
NASA Technical Reports Server (NTRS)
Swartz, W. H.; Bucesla, E. J.; Lamsal, L. N.; Celarier, E. A.; Krotkov, N. A.; Bhartia, P, K,; Strahan, S. E.; Gleason, J. F.; Herman, J.; Pickering, K.
2012-01-01
Nitrogen oxides (NOx =NO+NO2) are important atmospheric trace constituents that impact tropospheric air pollution chemistry and air quality. We have developed a new NASA algorithm for the retrieval of stratospheric and tropospheric NO2 vertical column densities using measurements from the nadir-viewing Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. The new products rely on an improved approach to stratospheric NO2 column estimation and stratosphere-troposphere separation and a new monthly NO2 climatology based on the NASA Global Modeling Initiative chemistry-transport model. The retrieval does not rely on daily model profiles, minimizing the influence of a priori information. We evaluate the retrieved tropospheric NO2 columns using surface in situ (e.g., AQS/EPA), ground-based (e.g., DOAS), and airborne measurements (e.g., DISCOVER-AQ). The new, improved OMI tropospheric NO2 product is available at high spatial resolution for the years 200S-present. We believe that this product is valuable for the evaluation of chemistry-transport models, examining the spatial and temporal patterns of NOx emissions, constraining top-down NOx inventories, and for the estimation of NOx lifetimes.
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.
Pancheliuga, V A; Pancheliuga, M S
2013-01-01
In the present work a methodological background for the histogram method of time series analysis is developed. Connection between shapes of smoothed histograms constructed on the basis of short segments of time series of fluctuations and the fractal dimension of the segments is studied. It is shown that the fractal dimension possesses all main properties of the histogram method. Based on it a further development of fractal dimension determination algorithm is proposed. This algorithm allows more precision determination of the fractal dimension by using the "all possible combination" method. The application of the method to noise-like time series analysis leads to results, which could be obtained earlier only by means of the histogram method based on human expert comparisons of histograms shapes. PMID:23755565
Forsström, J
1992-01-01
The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data. PMID:1551737
NASA Astrophysics Data System (ADS)
Venema, Victor; Mestre, Olivier
2010-05-01
As part of the COST Action HOME (Advances in homogenisation methods of climate series: an integrated approach) a dataset was generated that serves as a benchmark for homogenisation algorithms. Members of the Action and third parties have been invited to homogenise this dataset. The results of this exercise are analysed by the HOME Working Groups (WG) on detection (WG2) and correction (WG3) algorithms to obtain recommendations for a standard homogenisation procedure for climate data. This talk will shortly describe this benchmark dataset and present first results comparing the quality of the about 25 contributions. Based upon a survey among homogenisation experts we chose to work with monthly values for temperature and precipitation. Temperature and precipitation were selected because most participants consider these elements the most relevant for their studies. Furthermore, they represent two important types of statistics (additive and multiplicative). The benchmark has three different types of datasets: real data, surrogate data and synthetic data. The real datasets allow comparing the different homogenisation methods with the most realistic type of data and inhomogeneities. Thus this part of the benchmark is important for a faithful comparison of algorithms with each other. However, as in this case the truth is not known, it is not possible to quantify the improvements due to homogenisation. Therefore, the benchmark also has two datasets with artificial data to which we inserted known inhomogeneities: surrogate and synthetic data. The aim of surrogate data is to reproduce the structure of measured data accurately enough that it can be used as substitute for measurements. The surrogate climate networks have the spatial and temporal auto- and cross-correlation functions of real homogenised networks as well as the exact (non-Gaussian) distribution for each station. The idealised synthetic data is based on the surrogate networks. The change is that the difference
ERIC Educational Resources Information Center
Gehring, John
2004-01-01
For the past 16 years, the blue-collar city of Huntington, West Virginia, has rolled out the red carpet to welcome young wrestlers and their families as old friends. They have come to town chasing the same dream for a spot in what many of them call "The Show". For three days, under the lights of an arena packed with 5,000 fans, the state's best…
New products of GOSAT/TANSO-FTS TIR CO2 and CH4 profiles: Algorithm and initial validation results
NASA Astrophysics Data System (ADS)
Saitoh, N.; Imasu, R.; Sugita, T.; Hayashida, S.; Shiomi, K.; Kawakami, S.; Machida, T.; Sawa, Y.; Matsueda, H.; Terao, Y.
2013-12-01
The Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on board the Greenhouse Gases Observing Satellite (GO-SAT) simultaneously observes column abundances and profiles of CO2 and CH4 in the same field of view, from the shortwave infrared (SWIR) and thermal infrared (TIR) bands, respectively. The latest version of the GOSAT Level 1B (L1B) radiance spectra, the version 160.160, is improved compared to the previous versions, but still has a bias judging from comparisons with spectral data of other coincident instruments. The bias is largest at around 14-15 micron band that includes carbon dioxide strong absorption lines [Kataoka et al., 2013]; it probably causes a high bias in mid-tropospheric carbon dioxide concentration of the current released V00.01 TIR products. Besides, relatively low sig-nal-to-noise ratio (SNR) less than 100 at around 7-8 micron band makes CH4 retrieval unstable. We have improved an algorithm for retrieving CO2 and CH4 profiles in order to overcome the spectral bias and low SNR problems. In our new algorithm, we treated surface temperature and surface emissivity as correction parameters for radi-ance-independent and radiance-dependent spectral biases, respectively, and retrieved them simultaneously with gas retrieval. We used 7-8 micron band (1140-1370 wave-number) for methane retrieval and 10 and 14-15 micron bands (930-990, 1040-1090, 690-750, and 790-795 wavenumber) for carbon dioxide retrieval. Temperature, water vapor, ozone, and nitrous oxide were retrieved simultaneously other than CO2 and CH4. CO2 profiles retrieved using our new algorithm have no clear bias in mid-troposphere compared to the previous V00.01 CO2 product. New retrieved CH4 profiles show better agreement with aircraft CH4 profiles than the a priori profiles.
Simulation Results of the Huygens Probe Entry and Descent Trajectory Reconstruction Algorithm
NASA Technical Reports Server (NTRS)
Kazeminejad, B.; Atkinson, D. H.; Perez-Ayucar, M.
2005-01-01
Cassini/Huygens is a joint NASA/ESA mission to explore the Saturnian system. The ESA Huygens probe is scheduled to be released from the Cassini spacecraft on December 25, 2004, enter the atmosphere of Titan in January, 2005, and descend to Titan s surface using a sequence of different parachutes. To correctly interpret and correlate results from the probe science experiments and to provide a reference set of data for "ground-truthing" Orbiter remote sensing measurements, it is essential that the probe entry and descent trajectory reconstruction be performed as early as possible in the postflight data analysis phase. The Huygens Descent Trajectory Working Group (DTWG), a subgroup of the Huygens Science Working Team (HSWT), is responsible for developing a methodology and performing the entry and descent trajectory reconstruction. This paper provides an outline of the trajectory reconstruction methodology, preliminary probe trajectory retrieval test results using a simulated synthetic Huygens dataset developed by the Huygens Project Scientist Team at ESA/ESTEC, and a discussion of strategies for recovery from possible instrument failure.
Deriving Arctic Cloud Microphysics at Barrow, Alaska. Algorithms, Results, and Radiative Closure
Shupe, Matthew D.; Turner, David D.; Zwink, Alexander; Thieman, Mandana M.; Mlawer, Eli J.; Shippert, Timothy
2015-07-01
Cloud phase and microphysical properties control the radiative effects of clouds in the climate system and are therefore crucial to characterize in a variety of conditions and locations. An Arctic-specific, ground-based, multi-sensor cloud retrieval system is described here and applied to two years of observations from Barrow, Alaska. Over these two years, clouds occurred 75% of the time, with cloud ice and liquid each occurring nearly 60% of the time. Liquid water occurred at least 25% of the time even in the winter, and existed up to heights of 8 km. The vertically integrated mass of liquid was typically larger than that of ice. While it is generally difficult to evaluate the overall uncertainty of a comprehensive cloud retrieval system of this type, radiative flux closure analyses were performed where flux calculations using the derived microphysical properties were compared to measurements at the surface and top-of-atmosphere. Radiative closure biases were generally smaller for cloudy scenes relative to clear skies, while the variability of flux closure results was only moderately larger than under clear skies. The best closure at the surface was obtained for liquid-containing clouds. Radiative closure results were compared to those based on a similar, yet simpler, cloud retrieval system. These comparisons demonstrated the importance of accurate cloud phase classification, and specifically the identification of liquid water, for determining radiative fluxes. Enhanced retrievals of liquid water path for thin clouds were also shown to improve radiative flux calculations.
Multipartite entanglement in quantum algorithms
Bruss, D.; Macchiavello, C.
2011-05-15
We investigate the entanglement features of the quantum states employed in quantum algorithms. In particular, we analyze the multipartite entanglement properties in the Deutsch-Jozsa, Grover, and Simon algorithms. Our results show that for these algorithms most instances involve multipartite entanglement.
Minimal Sign Representation of Boolean Functions: Algorithms and Exact Results for Low Dimensions.
Sezener, Can Eren; Oztop, Erhan
2015-08-01
Boolean functions (BFs) are central in many fields of engineering and mathematics, such as cryptography, circuit design, and combinatorics. Moreover, they provide a simple framework for studying neural computation mechanisms of the brain. Many representation schemes for BFs exist to satisfy the needs of the domain they are used in. In neural computation, it is of interest to know how many input lines a neuron would need to represent a given BF. A common BF representation to study this is the so-called polynomial sign representation where [Formula: see text] and 1 are associated with true and false, respectively. The polynomial is treated as a real-valued function and evaluated at its parameters, and the sign of the polynomial is then taken as the function value. The number of input lines for the modeled neuron is exactly the number of terms in the polynomial. This letter investigates the minimum number of terms, that is, the minimum threshold density, that is sufficient to represent a given BF and more generally aims to find the maximum over this quantity for all BFs in a given dimension. With this work, for the first time exact results for four- and five-variable BFs are obtained, and strong bounds for six-variable BFs are derived. In addition, some connections between the sign representation framework and bent functions are derived, which are generally studied for their desirable cryptographic properties. PMID:26079754
The equation of state for stellar envelopes. II - Algorithm and selected results
NASA Technical Reports Server (NTRS)
Mihalas, Dimitri; Dappen, Werner; Hummer, D. G.
1988-01-01
A free-energy-minimization method for computing the dissociation and ionization equilibrium of a multicomponent gas is discussed. The adopted free energy includes terms representing the translational free energy of atoms, ions, and molecules; the internal free energy of particles with excited states; the free energy of a partially degenerate electron gas; and the configurational free energy from shielded Coulomb interactions among charged particles. Internal partition functions are truncated using an occupation probability formalism that accounts for perturbations of bound states by both neutral and charged perturbers. The entire theory is analytical and differentiable to all orders, so it is possible to write explicit analytical formulas for all derivatives required in a Newton-Raphson iteration; these are presented to facilitate future work. Some representative results for both Saha and free-energy-minimization equilibria are presented for a hydrogen-helium plasma with N(He)/N(H) = 0.10. These illustrate nicely the phenomena of pressure dissociation and ionization, and also demonstrate vividly the importance of choosing a reliable cutoff procedure for internal partition functions.
NASA Astrophysics Data System (ADS)
Plach, Andreas; Proschek, Veronika; Kirchengast, Gottfried
2014-05-01
Medium-Range Weather Forecasts (ECMWF). GHG profiles were taken from the Fast Atmospheric Signature Code (FASCODE) model. Three geographic regions were investigated, representing three different atmospheric conditions: Tropics (TRO) - a warm and moist atmosphere, Standard (STD) - an intermediate atmosphere at mid-latitudes, and Sub-Arctic Winter (SAW) - a cold and dry atmosphere. We will discuss the results in windy air, which show an encouraging performance both for the wind retrieval throughout the stratosphere (essentially unbiased l.o.s. winds with rms errors within 2 m/s over about 15 to 35 km) and for the GHG estimation.
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.
NASA Technical Reports Server (NTRS)
Knox, C. E.; Cannon, D. G.
1979-01-01
A flight management algorithm designed to improve the accuracy of delivering the airplane fuel efficiently to a metering fix at a time designated by air traffic control is discussed. The algorithm provides a 3-D path with time control (4-D) for a test B 737 airplane to make an idle thrust, clean configured descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path is calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithms and the results of the flight tests are discussed.
Dittrich, Ernő; Klincsik, Mihály
2015-11-01
A mathematical process, developed in Maple environment, has been successful in decreasing the error of measurement results and in the precise calculation of the moments of corrected tracer functions. It was proved that with this process, the measured tracer results of horizontal subsurface flow constructed wetlands filled with coarse gravel (HSFCW-C) can be fitted more accurately than with the conventionally used distribution functions (Gaussian, Lognormal, Fick (Inverse Gaussian) and Gamma). This statement is true only for the planted HSFCW-Cs. The analysis of unplanted HSFCW-Cs needs more research. The result of the analysis shows that the conventional solutions (completely stirred series tank reactor (CSTR) model and convection-dispersion transport (CDT) model) cannot describe these types of transport processes with sufficient accuracy. These outcomes can help in developing better process descriptions of very difficult transport processes in HSFCW-Cs. Furthermore, a new mathematical process can be developed for the calculation of real hydraulic residence time (HRT) and dispersion coefficient values. The presented method can be generalized to other kinds of hydraulic environments. PMID:26126688
NASA Astrophysics Data System (ADS)
Xiao, Zuo; Hao, Yongqiang; Zhang, Donghe; Xiao, Sai-Guan; Huang, Weiquan
Ionospheric disturbances such as SID and acoustic gravity waves in different scales are well known and commonly discussed topics. Some simple ground equipment was designed and used for monitoring continuously the effects of these disturbances, especially, SWF, SFD. Besides SIDs, They also reflect clearly the acoustic gravity waves in different scale and Spread-F and these data are important supplementary to the traditional ionosonde records. It is of signifi-cance in understanding physical essentials of the ionospheric disturbances and applications in SID warning. In this paper, the designing of the instruments is given and results are discussed in detail. Some case studies were introduced as example which showed very clearly not only immediate effects of solar flare, but also the phenomena of ionospheric responses to large scale gravity waves from lower atmosphere such as typhoon, great earthquake and volcano erup-tion. Particularlyresults showed that acoustic gravity waves play significant role in seeding ionospheric Spread-F. These examples give evidence that lower atmospheric activities strongly influence the ionosphere.
NASA Astrophysics Data System (ADS)
Ulmer, W.; Pyyry, J.; Kaissl, W.
2005-04-01
Based on previous publications on a triple Gaussian analytical pencil beam model and on Monte Carlo calculations using Monte Carlo codes GEANT-Fluka, versions 95, 98, 2002, and BEAMnrc/EGSnrc, a three-dimensional (3D) superposition/convolution algorithm for photon beams (6 MV, 18 MV) is presented. Tissue heterogeneity is taken into account by electron density information of CT images. A clinical beam consists of a superposition of divergent pencil beams. A slab-geometry was used as a phantom model to test computed results by measurements. An essential result is the existence of further dose build-up and build-down effects in the domain of density discontinuities. These effects have increasing magnitude for field sizes <=5.5 cm2 and densities <=0.25 g cm-3, in particular with regard to field sizes considered in stereotaxy. They could be confirmed by measurements (mean standard deviation 2%). A practical impact is the dose distribution at transitions from bone to soft tissue, lung or cavities. This work has partially been presented at WC 2003, Sydney.
Parallel algorithms for unconstrained optimizations by multisplitting
He, Qing
1994-12-31
In this paper a new parallel iterative algorithm for unconstrained optimization using the idea of multisplitting is proposed. This algorithm uses the existing sequential algorithms without any parallelization. Some convergence and numerical results for this algorithm are presented. The experiments are performed on an Intel iPSC/860 Hyper Cube with 64 nodes. It is interesting that the sequential implementation on one node shows that if the problem is split properly, the algorithm converges much faster than one without splitting.
Strandgren, Charlotte; Nasser, Hasina Abdul; McKenna, Tomás; Koskela, Antti; Tuukkanen, Juha; Ohlsson, Claes; Rozell, Björn; Eriksson, Maria
2015-08-01
Hutchinson-Gilford progeria syndrome (HGPS) is a rare premature aging disorder that is most commonly caused by a de novo point mutation in exon 11 of the LMNA gene, c.1824C>T, which results in an increased production of a truncated form of lamin A known as progerin. In this study, we used a mouse model to study the possibility of recovering from HGPS bone disease upon silencing of the HGPS mutation, and the potential benefits from treatment with resveratrol. We show that complete silencing of the transgenic expression of progerin normalized bone morphology and mineralization already after 7 weeks. The improvements included lower frequencies of rib fractures and callus formation, an increased number of osteocytes in remodeled bone, and normalized dentinogenesis. The beneficial effects from resveratrol treatment were less significant and to a large extent similar to mice treated with sucrose alone. However, the reversal of the dental phenotype of overgrown and laterally displaced lower incisors in HGPS mice could be attributed to resveratrol. Our results indicate that the HGPS bone defects were reversible upon suppressed transgenic expression and suggest that treatments targeting aberrant progerin splicing give hope to patients who are affected by HGPS. PMID:25877214
NASA Technical Reports Server (NTRS)
Susskind, Joel; Kouvaris, Louis; Iredell, Lena
2016-01-01
The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.
Saino, Greta; Bonavina, Luigi; Lipham, John C.; Dunn, Daniel
2015-01-01
Abstract Background: As previously reported, the magnetic sphincter augmentation device (MSAD) preserves gastric anatomy and results in less severe side effects than traditional antireflux surgery. The final 5-year results of a pilot study are reported here. Patients and Methods: A prospective, multicenter study evaluated safety and efficacy of the MSAD for 5 years. Prior to MSAD placement, patients had abnormal esophageal acid and symptoms poorly controlled by proton pump inhibitors (PPIs). Patients served as their own control, which allowed comparison between baseline and postoperative measurements to determine individual treatment effect. At 5 years, gastroesophageal reflux disease (GERD)-Health Related Quality of Life (HRQL) questionnaire score, esophageal pH, PPI use, and complications were evaluated. Results: Between February 2007 and October 2008, 44 patients (26 males) had an MSAD implanted by laparoscopy, and 33 patients were followed up at 5 years. Mean total percentage of time with pH <4 was 11.9% at baseline and 4.6% at 5 years (P < .001), with 85% of patients achieving pH normalization or at least a 50% reduction. Mean total GERD-HRQL score improved significantly from 25.7 to 2.9 (P < .001) when comparing baseline and 5 years, and 93.9% of patients had at least a 50% reduction in total score compared with baseline. Complete discontinuation of PPIs was achieved by 87.8% of patients. No complications occurred in the long term, including no device erosions or migrations at any point. Conclusions: Based on long-term reduction in esophageal acid, symptom improvement, and no late complications, this study shows the relative safety and efficacy of magnetic sphincter augmentation for GERD. PMID:26437027
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)
Kuehn, M.; Tillner, E.; Kempka, T.; Nakaten, B.
2012-12-01
The geological storage of CO2 in deep saline formations may cause salinization of shallower freshwater resources by upward flow of displaced brine from the storage formation into potable groundwater. In this regard, permeable faults or fractures can serve as potential leakage pathways for upward brine migration. The present study uses a regional-scale 3D model based on real structural data of a prospective CO2 storage site in Northeastern Germany to determine the impact of compartmentalization and fault permeability on upward brine migration as a result of pressure elevation by CO2 injection. To evaluate the degree of salinization in the shallower aquifers, different fault leakage scenarios were carried out using a newly developed workflow in which the model grid from the software package Petrel applied for pre-processing is transferred to the reservoir simulator TOUGH2-MP/ECO2N. A discrete fault description is achieved by using virtual elements. A static 3D geological model of the CO2 storage site with an a real size of 40 km x 40 km and a thickness of 766 m was implemented. Subsequently, large-scale numerical multi-phase multi-component (CO2, NaCl, H2O) flow simulations were carried out on a high performance computing system. The prospective storage site, located in the Northeast German Basin is part of an anticline structure characterized by a saline multi-layer aquifer system. The NE and SW boundaries of the study area are confined by the Fuerstenwalde Gubener and the Lausitzer Abbruch fault zones represented by four discrete faults in the model. Two formations of the Middle Bunter were chosen to assess brine migration through faults triggered by an annual injection rate of 1.7 Mt CO2 into the lowermost formation over a time span of 20 years. In addition to varying fault permeabilities, different boundary conditions were applied to evaluate the effects of reservoir compartmentalization. Simulation results show that the highest pressurization within the storage
NASA Technical Reports Server (NTRS)
Burt, Adam O.; Tinker, Michael L.
2014-01-01
In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.
Murakami, Yoshimasa; Tsuboi, Naoya; Inden, Yasuya; Yoshida, Yukihiko; Murohara, Toyoaki; Ihara, Zenichi; Takami, Mitsuaki
2010-01-01
Aims Managed ventricular pacing (MVP) and Search AV+ are representative dual-chamber pacing algorithms for minimizing ventricular pacing (VP). This randomized, crossover study aimed to examine the difference in ability to reduce percentage of VP (%VP) between these two algorithms. Methods and results Symptomatic bradyarrhythmia patients implanted with a pacemaker equipped with both algorithms (Adapta DR, Medtronic) were enrolled. The %VPs of the patients during two periods were compared: 1 month operation of either one of the two algorithms for each period. All patients were categorized into subgroups according to the atrioventricular block (AVB) status at baseline: no AVB (nAVB), first-degree AVB (1AVB), second-degree AVB (2AVB), episodic third-degree AVB (e3AVB), and persistent third-degree AVB (p3AVB). Data were available from 127 patients for the analysis. For all patient subgroups, except for p3AVB category, the median %VPs were lower during the MVP operation than those during the Search AV+ (nAVB: 0.2 vs. 0.8%, P < 0.0001; 1AVB: 2.3 vs. 27.4%, P = 0.001; 2AVB: 16.4% vs. 91.9%, P = 0.0052; e3AVB: 37.7% vs. 92.7%, P = 0.0003). Conclusion Managed ventricular pacing algorithm, when compared with Search AV+, offers further %VP reduction in patients implanted with a dual-chamber pacemaker, except for patients diagnosed with persistent loss of atrioventricular conduction. PMID:19762332
ERIC Educational Resources Information Center
Bertera, Elizabeth M.
2014-01-01
This study combined the African American tradition of oral storytelling with the Hispanic medium of "Fotonovelas." A staggered pretest posttest control group design was used to evaluate four Storytelling Slide Shows on health that featured community members. A total of 212 participants were recruited for the intervention and 217 for the…
NASA Astrophysics Data System (ADS)
Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.
2013-01-01
A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.
Hsu, Hsiao-Ping; Binder, Kurt; Klushin, Leonid I; Skvortsov, Alexander M
2008-10-01
A polymer chain containing N monomers confined in a finite cylindrical tube of diameter D grafted at a distance L from the open end of the tube may undergo a rather abrupt transition, where part of the chain escapes from the tube to form a "crownlike" coil outside of the tube. When this problem is studied by Monte Carlo simulation of self-avoiding walks on the simple cubic lattice applying a cylindrical confinement and using the standard pruned-enriched Rosenbluth method (PERM), one obtains spurious results, however, with increasing chain length the transition gets weaker and weaker, due to insufficient sampling of the "escaped" states, as a detailed analysis shows. In order to solve this problem, a new variant of a biased sequential sampling algorithm with resampling is proposed, force-biased PERM: the difficulty of sampling both phases in the region of the first order transition with the correct weights is treated by applying a force at the free end pulling it out of the tube. Different strengths of this force need to be used and reweighting techniques are applied. Using rather long chains (up to N=18000 ) and wide tubes (up to D=29 lattice spacings), the free energy of the chain, its end-to-end distance, the number of "imprisoned" monomers can be estimated, as well as the order parameter and its distribution. It is suggested that this algorithm should be useful for other problems involving state changes of polymers, where the different states belong to rather disjunct "valleys" in the phase space of the system. PMID:18999448
NASA Astrophysics Data System (ADS)
Herring, Jeannette L.; Maurer, Calvin R., Jr.; Muratore, Diane M.; Galloway, Robert L., Jr.; Dawant, Benoit M.
1999-05-01
This paper presents a comparison of iso-intensity-based surface extraction algorithms applied to computed tomography (CT) images of the spine. The extracted vertebral surfaces are used in surface-based registration of CT images to physical space, where our ultimate goal is the development of a technique that can be used for image-guided spinal surgery. The surface extraction process has a direct effect on image-guided surgery in two ways: the extracted surface must provide an accurate representation of the actual surface so that a good registration can be achieved, and the number of polygons in the mesh representation of the extracted surface must be small enough to allow the registration to be performed quickly. To examine the effect of the surface extraction process on registration error and run time, we have performed a large number of experiments on two plastic spine phantoms. Using a marker-based system to assess accuracy, we have found that submillimetric registration accuracy can be achieved using a point-to- surface registration algorithm with simplified and unsimplified members of the general class of iso-intensity- based surface extraction algorithms. This research has practical implications, since it shows that several versions of the widely available class of intensity-based surface extraction algorithms can be used to provide sufficient accuracy for vertebral registration. Since intensity-based algorithms are completely deterministic and fully automatic, this finding simplifies the pre-processing required for image-guided back surgery.
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)
Benea, M. L.; Benea, O. D.
2016-02-01
The method used for purchasing the corrosion behaviour the WC coatings deposited by plasma spraying, on a martensitic stainless steel substrate consists in measuring the electrochemical potential of the coating, respectively that of the substrate, immersed in a NaCl solution as corrosive agent. The mathematical processing of the obtained experimental results in Matlab allowed us to make some correlations between the electrochemical potential of the coating and the solution temperature is very well described by some curves having equations obtained by interpolation order 4.
NASA Technical Reports Server (NTRS)
Knox, C. E.; Cannon, D. G.
1980-01-01
A simple flight management descent algorithm designed to improve the accuracy of delivering an airplane in a fuel-conservative manner to a metering fix at a time designated by air traffic control was developed and flight tested. This algorithm provides a three dimensional path with terminal area time constraints (four dimensional) for an airplane to make an idle thrust, clean configured (landing gear up, flaps zero, and speed brakes retracted) descent to arrive at the metering fix at a predetermined time, altitude, and airspeed. The descent path was calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard pressure and temperature effects. The flight management descent algorithm is described. The results of the flight tests flown with the Terminal Configured Vehicle airplane are presented.
NASA Technical Reports Server (NTRS)
Knox, C. E.
1983-01-01
A simplified flight-management descent algorithm, programmed on a small programmable calculator, was developed and flight tested. It was designed to aid the pilot in planning and executing a fuel-conservative descent to arrive at a metering fix at a time designated by the air traffic control system. The algorithm may also be used for planning fuel-conservative descents when time is not a consideration. The descent path was calculated for a constant Mach/airspeed schedule from linear approximations of airplane performance with considerations given for gross weight, wind, and nonstandard temperature effects. The flight-management descent algorithm is described. The results of flight tests flown with a T-39A (Sabreliner) airplane are presented.
NASA Technical Reports Server (NTRS)
Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas
2012-01-01
Operational Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for MODIS Terra and Aqua, respectively) are currently being reprocessed along with other MODIS Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar reflectance techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud reflectance and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from MODIS Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the MODIS L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.
NASA Astrophysics Data System (ADS)
Buchwitz, Michael; Burrows, John P.
2004-02-01
SCIAMACHY is a UV/visible/near-infrared grating spectrometer on board the European environmental satellite ENVISAT that observes the atmosphere in nadir, limb, and solar and lunar occultation viewing geometries with moderate spectral resolution (0.2-1.5 nm). At the University of Bremen a modified DOAS algorithm (WFM-DOAS) is being developed primarily for the retrieval of CH4, CO, CO2, H2O, N2O, and O2 total columns from SCIAMACHY near-infrared and visible nadir spectra. A first version of this algorithm has been implemented based on a fast look-up table approach. The algorithm and the look-up table is described along with an initial error analysis. Weighting functions and averaging kernels indicate that the SCIAMACHY near-infrared nadir measurements are highly sensitive to trace gas concentration changes even in the lowest kilometer of the atmosphere. The results presented have been obtained by applying WFM-DOAS to small spectral fitting windows focusing on CH4, CO2, CO, and O2 column retrieval and CH4 and CO2 to O2 column ratios (denoted XCH4 and XCO2, respectively). These type of data products are planned to be used within the EU research project EVERGREEN to constrain surface sources and sinks of CH4 and CO2 using inverse modeling techniques. This study discussed the first set of WFM-DOAS products generated for and to be further improved within EVERGREEN. Although no detailed validation has been performed yet we found that the retrieved columns have the right order of magnitude and show (at least qualitatively) the expected correlation of the well mixed gases CO2 and CH4 with O2 and surface topography. The standard deviation of the dry air column averaged mixing ration XCO2 within 10° latitude bands is +/-10 ppmv or 2.7% (XCH4: +/-50 ppbv or +/-2.8%) for measurements over land (over ocean the scatter is a factor of 2-4 larger). These values have been determined from ~25% of the ground pixels of one orbit which fulfill the following requirements: (nearly) cloud
NASA Astrophysics Data System (ADS)
Won, Jihye; Park, Kwan-Dong
2015-04-01
Real-time PPP-RTK positioning algorithms were developed for the purpose of getting precise coordinates of moving platforms. In this implementation, corrections for the satellite orbit and satellite clock were taken from the IGS-RTS products while the ionospheric delay was removed through ionosphere-free combination and the tropospheric delay was either taken care of using the Global Pressure and Temperature (GPT) model or estimated as a stochastic parameter. To improve the convergence speed, all the available GPS and GLONASS measurements were used and Extended Kalman Filter parameters were optimized. To validate our algorithms, we collected the GPS and GLONASS data from a geodetic-quality receiver installed on a roof of a moving vehicle in an open-sky environment and used IGS final products of satellite orbits and clock offsets. The horizontal positioning error got less than 10 cm within 5 minutes, and the error stayed below 10 cm even after the vehicle start moving. When the IGS-RTS product and the GPT model were used instead of the IGS precise product, the positioning accuracy of the moving vehicle was maintained at better than 20 cm once convergence was achieved at around 6 minutes.
"First Things First" Shows Promising Results
ERIC Educational Resources Information Center
Hendrie, Caroline
2005-01-01
In this article, the author discusses a school improvement model, First Things First, developed by James P. Connell, a former tenured professor of psychology at the University of Rochester in New York. The model has three pillars for the high school level: (1) small, themed learning communities that each keep a group of students together…
NASA Technical Reports Server (NTRS)
Guo, Li-Wen; Cardullo, Frank M.; Telban, Robert J.; Houck, Jacob A.; Kelly, Lon C.
2003-01-01
A study was conducted employing the Visual Motion Simulator (VMS) at the NASA Langley Research Center, Hampton, Virginia. This study compared two motion cueing algorithms, the NASA adaptive algorithm and a new optimal control based algorithm. Also, the study included the effects of transport delays and the compensation thereof. The delay compensation algorithm employed is one developed by Richard McFarland at NASA Ames Research Center. This paper reports on the analyses of the results of analyzing the experimental data collected from preliminary simulation tests. This series of tests was conducted to evaluate the protocols and the methodology of data analysis in preparation for more comprehensive tests which will be conducted during the spring of 2003. Therefore only three pilots were used. Nevertheless some useful results were obtained. The experimental conditions involved three maneuvers; a straight-in approach with a rotating wind vector, an offset approach with turbulence and gust, and a takeoff with and without an engine failure shortly after liftoff. For each of the maneuvers the two motion conditions were combined with four delay conditions (0, 50, 100 & 200ms), with and without compensation.
Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425
NASA Astrophysics Data System (ADS)
Hibert, Clément; Provost, Floriane; Malet, Jean-Philippe; Stumpf, André; Maggi, Alessia; Ferrazzini, Valérie
2016-04-01
In the past decades the increasing quality of seismic sensors and capability to transfer remotely large quantity of data led to a fast densification of local, regional and global seismic networks for near real-time monitoring. This technological advance permits the use of seismology to document geological and natural/anthropogenic processes (volcanoes, ice-calving, landslides, snow and rock avalanches, geothermal fields), but also led to an ever-growing quantity of seismic data. This wealth of seismic data makes the construction of complete seismicity catalogs, that include earthquakes but also other sources of seismic waves, more challenging and very time-consuming as this critical pre-processing stage is classically done by human operators. To overcome this issue, the development of automatic methods for the processing of continuous seismic data appears to be a necessity. The classification algorithm should satisfy the need of a method that is robust, precise and versatile enough to be deployed to monitor the seismicity in very different contexts. We propose a multi-class detection method based on the random forests algorithm to automatically classify the source of seismic signals. Random forests is a supervised machine learning technique that is based on the computation of a large number of decision trees. The multiple decision trees are constructed from training sets including each of the target classes. In the case of seismic signals, these attributes may encompass spectral features but also waveform characteristics, multi-stations observations and other relevant information. The Random Forests classifier is used because it provides state-of-the-art performance when compared with other machine learning techniques (e.g. SVM, Neural Networks) and requires no fine tuning. Furthermore it is relatively fast, robust, easy to parallelize, and inherently suitable for multi-class problems. In this work, we present the first results of the classification method applied
NASA Technical Reports Server (NTRS)
Whitmore, Stephen A.; Moes, Timothy R.; Larson, Terry J.
1990-01-01
A nonintrusive high angle-of-attack flush airdata sensing (HI-FADS) system was installed and flight-tested on the F-18 high alpha research vehicle. This paper discusses the airdata algorithm development and composite results expressed as airdata parameter estimates and describes the HI-FADS system hardware, calibration techniques, and algorithm development. An independent empirical verification was performed over a large portion of the subsonic flight envelope. Test points were obtained for Mach numbers from 0.15 to 0.94 and angles of attack from -8.0 to 55.0 deg. Angles of sideslip ranged from -15.0 to 15.0 deg, and test altitudes ranged from 18,000 to 40,000 ft. The HI-FADS system gave excellent results over the entire subsonic Mach number range up to 55 deg angle of attack. The internal pneumatic frequency response of the system is accurate to beyond 10 Hz.
Linear Bregman algorithm implemented in parallel GPU
NASA Astrophysics Data System (ADS)
Li, Pengyan; Ke, Jue; Sui, Dong; Wei, Ping
2015-08-01
At present, most compressed sensing (CS) algorithms have poor converging speed, thus are difficult to run on PC. To deal with this issue, we use a parallel GPU, to implement a broadly used compressed sensing algorithm, the Linear Bregman algorithm. Linear iterative Bregman algorithm is a reconstruction algorithm proposed by Osher and Cai. Compared with other CS reconstruction algorithms, the linear Bregman algorithm only involves the vector and matrix multiplication and thresholding operation, and is simpler and more efficient for programming. We use C as a development language and adopt CUDA (Compute Unified Device Architecture) as parallel computing architectures. In this paper, we compared the parallel Bregman algorithm with traditional CPU realized Bregaman algorithm. In addition, we also compared the parallel Bregman algorithm with other CS reconstruction algorithms, such as OMP and TwIST algorithms. Compared with these two algorithms, the result of this paper shows that, the parallel Bregman algorithm needs shorter time, and thus is more convenient for real-time object reconstruction, which is important to people's fast growing demand to information technology.
Yadav, Rakesh; Jaswal, Aparna; Chennapragada, Sridevi; Kamath, Prakash; Hiremath, Shirish M.S.; Kahali, Dhiman; Anand, Sumit; Sood, Naresh K.; Mishra, Anil; Makkar, Jitendra S.; Kaul, Upendra
2015-01-01
Background Several past clinical studies have demonstrated that frequent and unnecessary right ventricular pacing in patients with sick sinus syndrome and compromised atrio-ventricular conduction (AVC) produces long-term adverse effects. The safety and efficacy of two pacemaker algorithms, Ventricular Intrinsic Preference™ (VIP) and Ventricular AutoCapture (VAC), were evaluated in a multi-center study in pacemaker patients. Methods We evaluated 80 patients across 10 centers in India. Patients were enrolled within 15 days of dual chamber pacemaker (DDDR) implantation, and within 45 days thereafter were classified to either a compromised AVC (cAVC) arm or an intact AVC (iAVC) arm based on intrinsic paced/sensed (AV/PV) delays. In each arm, patients were then randomized (1:1) into the following groups: VIP OFF and VAC OFF (Control group; CG), or VIP ON and VAC ON (Treatment Group; TG). Subsequently, the AV/PV delays in the CG groups were mandatorily programmed at 180/150 ms, and to up to 350 ms in the TG groups. The percentage of right ventricular pacing (%RVp) evaluated at 12-month post-implantation follow-ups were compared between the two groups in each arm. Additionally, in-clinic time required for collecting device data was compared between patients programmed with the automated AutoCapture algorithm activated (VAC ON) vs. the manually programmed method (VAC OFF). Results Patients randomized to the TG with the VIP algorithm activated exhibited a significantly lower %RVp at 12 months than those in the CG in both the cAVC arm (39±41% vs. 97±3%; p=0.0004) and the iAVC arm (15±25% vs. 68±39%; p=0.0067). In-clinic time required to collect device data was less in patients with the VAC algorithm activated. No device-related adverse events were reported during the year-long study period. Conclusions In our study cohort, the use of the VIP algorithm significantly reduced the %RVp, while the VAC algorithm reduced in-clinic time needed to collect device data. PMID
Spaceborne SAR Imaging Algorithm for Coherence Optimized
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446
ERIC Educational Resources Information Center
Zemsky, Robert; Shaman, Susan; Shapiro, Daniel B.
2001-01-01
Describes the Collegiate Results Instrument (CRI), which measures a range of collegiate outcomes for alumni 6 years after graduation. The CRI was designed to target alumni from institutions across market segments and assess their values, abilities, work skills, occupations, and pursuit of lifelong learning. (EV)
NASA Astrophysics Data System (ADS)
LeBlanc, J. P. F.; Antipov, Andrey E.; Becca, Federico; Bulik, Ireneusz W.; Chan, Garnet Kin-Lic; Chung, Chia-Min; Deng, Youjin; Ferrero, Michel; Henderson, Thomas M.; Jiménez-Hoyos, Carlos A.; Kozik, E.; Liu, Xuan-Wen; Millis, Andrew J.; Prokof'ev, N. V.; Qin, Mingpu; Scuseria, Gustavo E.; Shi, Hao; Svistunov, B. V.; Tocchio, Luca F.; Tupitsyn, I. S.; White, Steven R.; Zhang, Shiwei; Zheng, Bo-Xiao; Zhu, Zhenyue; Gull, Emanuel; Simons Collaboration on the Many-Electron Problem
2015-10-01
Numerical results for ground-state and excited-state properties (energies, double occupancies, and Matsubara-axis self-energies) of the single-orbital Hubbard model on a two-dimensional square lattice are presented, in order to provide an assessment of our ability to compute accurate results in the thermodynamic limit. Many methods are employed, including auxiliary-field quantum Monte Carlo, bare and bold-line diagrammatic Monte Carlo, method of dual fermions, density matrix embedding theory, density matrix renormalization group, dynamical cluster approximation, diffusion Monte Carlo within a fixed-node approximation, unrestricted coupled cluster theory, and multireference projected Hartree-Fock methods. Comparison of results obtained by different methods allows for the identification of uncertainties and systematic errors. The importance of extrapolation to converged thermodynamic-limit values is emphasized. Cases where agreement between different methods is obtained establish benchmark results that may be useful in the validation of new approaches and the improvement of existing methods.
A Short Survey of Document Structure Similarity Algorithms
Buttler, D
2004-02-27
This paper provides a brief survey of document structural similarity algorithms, including the optimal Tree Edit Distance algorithm and various approximation algorithms. The approximation algorithms include the simple weighted tag similarity algorithm, Fourier transforms of the structure, and a new application of the shingle technique to structural similarity. We show three surprising results. First, the Fourier transform technique proves to be the least accurate of any of approximation algorithms, while also being slowest. Second, optimal Tree Edit Distance algorithms may not be the best technique for clustering pages from different sites. Third, the simplest approximation to structure may be the most effective and efficient mechanism for many applications.
Parallelized Dilate Algorithm for Remote Sensing Image
Zhang, Suli; Hu, Haoran; Pan, Xin
2014-01-01
As an important algorithm, dilate algorithm can give us more connective view of a remote sensing image which has broken lines or objects. However, with the technological progress of satellite sensor, the resolution of remote sensing image has been increasing and its data quantities become very large. This would lead to the decrease of algorithm running speed or cannot obtain a result in limited memory or time. To solve this problem, our research proposed a parallelized dilate algorithm for remote sensing Image based on MPI and MP. Experiments show that our method runs faster than traditional single-process algorithm. PMID:24955392
LeBlanc, J. P. F.; Antipov, Andrey E.; Becca, Federico; Bulik, Ireneusz W.; Chan, Garnet Kin-Lic; Chung, Chia -Min; Deng, Youjin; Ferrero, Michel; Henderson, Thomas M.; Jiménez-Hoyos, Carlos A.; et al
2015-12-14
Numerical results for ground-state and excited-state properties (energies, double occupancies, and Matsubara-axis self-energies) of the single-orbital Hubbard model on a two-dimensional square lattice are presented, in order to provide an assessment of our ability to compute accurate results in the thermodynamic limit. Many methods are employed, including auxiliary-field quantum Monte Carlo, bare and bold-line diagrammatic Monte Carlo, method of dual fermions, density matrix embedding theory, density matrix renormalization group, dynamical cluster approximation, diffusion Monte Carlo within a fixed-node approximation, unrestricted coupled cluster theory, and multireference projected Hartree-Fock methods. Comparison of results obtained by different methods allows for the identification ofmore » uncertainties and systematic errors. The importance of extrapolation to converged thermodynamic-limit values is emphasized. Furthermore, cases where agreement between different methods is obtained establish benchmark results that may be useful in the validation of new approaches and the improvement of existing methods.« less
LeBlanc, J. P. F.; Antipov, Andrey E.; Becca, Federico; Bulik, Ireneusz W.; Chan, Garnet Kin-Lic; Chung, Chia -Min; Deng, Youjin; Ferrero, Michel; Henderson, Thomas M.; Jiménez-Hoyos, Carlos A.; Kozik, E.; Liu, Xuan -Wen; Millis, Andrew J.; Prokof’ev, N. V.; Qin, Mingpu; Scuseria, Gustavo E.; Shi, Hao; Svistunov, B. V.; Tocchio, Luca F.; Tupitsyn, I. S.; White, Steven R.; Zhang, Shiwei; Zheng, Bo -Xiao; Zhu, Zhenyue; Gull, Emanuel
2015-12-14
Numerical results for ground-state and excited-state properties (energies, double occupancies, and Matsubara-axis self-energies) of the single-orbital Hubbard model on a two-dimensional square lattice are presented, in order to provide an assessment of our ability to compute accurate results in the thermodynamic limit. Many methods are employed, including auxiliary-field quantum Monte Carlo, bare and bold-line diagrammatic Monte Carlo, method of dual fermions, density matrix embedding theory, density matrix renormalization group, dynamical cluster approximation, diffusion Monte Carlo within a fixed-node approximation, unrestricted coupled cluster theory, and multireference projected Hartree-Fock methods. Comparison of results obtained by different methods allows for the identification of uncertainties and systematic errors. The importance of extrapolation to converged thermodynamic-limit values is emphasized. Furthermore, cases where agreement between different methods is obtained establish benchmark results that may be useful in the validation of new approaches and the improvement of existing methods.
Research on Routing Selection Algorithm Based on Genetic Algorithm
NASA Astrophysics Data System (ADS)
Gao, Guohong; Zhang, Baojian; Li, Xueyong; Lv, Jinna
The hereditary algorithm is a kind of random searching and method of optimizing based on living beings natural selection and hereditary mechanism. In recent years, because of the potentiality in solving complicate problems and the successful application in the fields of industrial project, hereditary algorithm has been widely concerned by the domestic and international scholar. Routing Selection communication has been defined a standard communication model of IP version 6.This paper proposes a service model of Routing Selection communication, and designs and implements a new Routing Selection algorithm based on genetic algorithm.The experimental simulation results show that this algorithm can get more resolution at less time and more balanced network load, which enhances search ratio and the availability of network resource, and improves the quality of service.
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.
NASA Technical Reports Server (NTRS)
Entekhabi, Dara; Njoku, Eni E.; O'Neill, Peggy E.; Kellogg, Kent H.; Entin, Jared K.
2010-01-01
Talk outline 1. Derivation of SMAP basic and applied science requirements from the NRC Earth Science Decadal Survey applications 2. Data products and latencies 3. Algorithm highlights 4. SMAP Algorithm Testbed 5. SMAP Working Groups and community engagement
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.
NASA Astrophysics Data System (ADS)
Jiang, Tianzi; Cui, Qinghua; Shi, Guihua; Ma, Songde
2003-08-01
In this paper, a novel hybrid algorithm combining genetic algorithms and tabu search is presented. In the proposed hybrid algorithm, the idea of tabu search is applied to the crossover operator. We demonstrate that the hybrid algorithm can be applied successfully to the protein folding problem based on a hydrophobic-hydrophilic lattice model. The results show that in all cases the hybrid algorithm works better than a genetic algorithm alone. A comparison with other methods is also made.
Parameter incremental learning algorithm for neural networks.
Wan, Sheng; Banta, Larry E
2006-11-01
In this paper, a novel stochastic (or online) training algorithm for neural networks, named parameter incremental learning (PIL) algorithm, is proposed and developed. The main idea of the PIL strategy is that the learning algorithm should not only adapt to the newly presented input-output training pattern by adjusting parameters, but also preserve the prior results. A general PIL algorithm for feedforward neural networks is accordingly presented as the first-order approximate solution to an optimization problem, where the performance index is the combination of proper measures of preservation and adaptation. The PIL algorithms for the multilayer perceptron (MLP) are subsequently derived. Numerical studies show that for all the three benchmark problems used in this paper the PIL algorithm for MLP is measurably superior to the standard online backpropagation (BP) algorithm and the stochastic diagonal Levenberg-Marquardt (SDLM) algorithm in terms of the convergence speed and accuracy. Other appealing features of the PIL algorithm are that it is computationally as simple as the BP algorithm, and as easy to use as the BP algorithm. It, therefore, can be applied, with better performance, to any situations where the standard online BP algorithm is applicable. PMID:17131658
A Synthesized Heuristic Task Scheduling Algorithm
Dai, Yanyan; Zhang, Xiangli
2014-01-01
Aiming at the static task scheduling problems in heterogeneous environment, a heuristic task scheduling algorithm named HCPPEFT is proposed. In task prioritizing phase, there are three levels of priority in the algorithm to choose task. First, the critical tasks have the highest priority, secondly the tasks with longer path to exit task will be selected, and then algorithm will choose tasks with less predecessors to schedule. In resource selection phase, the algorithm is selected task duplication to reduce the interresource communication cost, besides forecasting the impact of an assignment for all children of the current task permits better decisions to be made in selecting resources. The algorithm proposed is compared with STDH, PEFT, and HEFT algorithms through randomly generated graphs and sets of task graphs. The experimental results show that the new algorithm can achieve better scheduling performance. PMID:25254244
Sequential and Parallel Algorithms for Spherical Interpolation
NASA Astrophysics Data System (ADS)
De Rossi, Alessandra
2007-09-01
Given a large set of scattered points on a sphere and their associated real values, we analyze sequential and parallel algorithms for the construction of a function defined on the sphere satisfying the interpolation conditions. The algorithms we implemented are based on a local interpolation method using spherical radial basis functions and the Inverse Distance Weighted method. Several numerical results show accuracy and efficiency of the algorithms.
NASA Technical Reports Server (NTRS)
Arenstorf, Norbert S.; Jordan, Harry F.
1987-01-01
A barrier is a method for synchronizing a large number of concurrent computer processes. After considering some basic synchronization mechanisms, a collection of barrier algorithms with either linear or logarithmic depth are presented. A graphical model is described that profiles the execution of the barriers and other parallel programming constructs. This model shows how the interaction between the barrier algorithms and the work that they synchronize can impact their performance. One result is that logarithmic tree structured barriers show good performance when synchronizing fixed length work, while linear self-scheduled barriers show better performance when synchronizing fixed length work with an imbedded critical section. The linear barriers are better able to exploit the process skew associated with critical sections. Timing experiments, performed on an eighteen processor Flex/32 shared memory multiprocessor, that support these conclusions are detailed.
NASA Technical Reports Server (NTRS)
Arenstorf, Norbert S.; Jordan, Harry F.
1989-01-01
A barrier is a method for synchronizing a large number of concurrent computer processes. After considering some basic synchronization mechanisms, a collection of barrier algorithms with either linear or logarithmic depth are presented. A graphical model is described that profiles the execution of the barriers and other parallel programming constructs. This model shows how the interaction between the barrier algorithms and the work that they synchronize can impact their performance. One result is that logarithmic tree structured barriers show good performance when synchronizing fixed length work, while linear self-scheduled barriers show better performance when synchronizing fixed length work with an imbedded critical section. The linear barriers are better able to exploit the process skew associated with critical sections. Timing experiments, performed on an eighteen processor Flex/32 shared memory multiprocessor that support these conclusions, are detailed.
NASA Astrophysics Data System (ADS)
Zheng, Genrang; Lin, ZhengChun
The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.
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.
Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm.
Yang, Zhang; Shufan, Ye; Li, Guo; Weifeng, Ding
2016-01-01
The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428
Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm
Yang, Zhang; Li, Guo; Weifeng, Ding
2016-01-01
The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428
A Revision of the NASA Team Sea Ice Algorithm
NASA Technical Reports Server (NTRS)
Markus, T.; Cavalieri, Donald J.
1998-01-01
In a recent paper, two operational algorithms to derive ice concentration from satellite multichannel passive microwave sensors have been compared. Although the results of these, known as the NASA Team algorithm and the Bootstrap algorithm, have been validated and are generally in good agreement, there are areas where the ice concentrations differ, by up to 30%. These differences can be explained by shortcomings in one or the other algorithm. Here, we present an algorithm which, in addition to the 19 and 37 GHz channels used by both the Bootstrap and NASA Team algorithms, makes use of the 85 GHz channels as well. Atmospheric effects particularly at 85 GHz are reduced by using a forward atmospheric radiative transfer model. Comparisons with the NASA Team and Bootstrap algorithm show that the individual shortcomings of these algorithms are not apparent in this new approach. The results further show better quantitative agreement with ice concentrations derived from NOAA AVHRR infrared data.
Applications and accuracy of the parallel diagonal dominant algorithm
NASA Technical Reports Server (NTRS)
Sun, Xian-He
1993-01-01
The Parallel Diagonal Dominant (PDD) algorithm is a highly efficient, ideally scalable tridiagonal solver. In this paper, a detailed study of the PDD algorithm is given. First the PDD algorithm is introduced. Then the algorithm is extended to solve periodic tridiagonal systems. A variant, the reduced PDD algorithm, is also proposed. Accuracy analysis is provided for a class of tridiagonal systems, the symmetric, and anti-symmetric Toeplitz tridiagonal systems. Implementation results show that the analysis gives a good bound on the relative error, and the algorithm is a good candidate for the emerging massively parallel machines.
Ordered subsets algorithms for transmission tomography.
Erdogan, H; Fessler, J A
1999-11-01
The ordered subsets EM (OSEM) algorithm has enjoyed considerable interest for emission image reconstruction due to its acceleration of the original EM algorithm and ease of programming. The transmission EM reconstruction algorithm converges very slowly and is not used in practice. In this paper, we introduce a simultaneous update algorithm called separable paraboloidal surrogates (SPS) that converges much faster than the transmission EM algorithm. Furthermore, unlike the 'convex algorithm' for transmission tomography, the proposed algorithm is monotonic even with nonzero background counts. We demonstrate that the ordered subsets principle can also be applied to the new SPS algorithm for transmission tomography to accelerate 'convergence', albeit with similar sacrifice of global convergence properties as for OSEM. We implemented and evaluated this ordered subsets transmission (OSTR) algorithm. The results indicate that the OSTR algorithm speeds up the increase in the objective function by roughly the number of subsets in the early iterates when compared to the ordinary SPS algorithm. We compute mean square errors and segmentation errors for different methods and show that OSTR is superior to OSEM applied to the logarithm of the transmission data. However, penalized-likelihood reconstructions yield the best quality images among all other methods tested. PMID:10588288
A Food Chain Algorithm for Capacitated Vehicle Routing Problem with Recycling in Reverse Logistics
NASA Astrophysics Data System (ADS)
Song, Qiang; Gao, Xuexia; Santos, Emmanuel T.
2015-12-01
This paper introduces the capacitated vehicle routing problem with recycling in reverse logistics, and designs a food chain algorithm for it. Some illustrative examples are selected to conduct simulation and comparison. Numerical results show that the performance of the food chain algorithm is better than the genetic algorithm, particle swarm optimization as well as quantum evolutionary algorithm.
Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories
NASA Technical Reports Server (NTRS)
Burchett, Bradley T.
2003-01-01
The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.
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.
Practical algorithmic probability: an image inpainting example
NASA Astrophysics Data System (ADS)
Potapov, Alexey; Scherbakov, Oleg; Zhdanov, Innokentii
2013-12-01
Possibility of practical application of algorithmic probability is analyzed on an example of image inpainting problem that precisely corresponds to the prediction problem. Such consideration is fruitful both for the theory of universal prediction and practical image inpaiting methods. Efficient application of algorithmic probability implies that its computation is essentially optimized for some specific data representation. In this paper, we considered one image representation, namely spectral representation, for which an image inpainting algorithm is proposed based on the spectrum entropy criterion. This algorithm showed promising results in spite of very simple representation. The same approach can be used for introducing ALP-based criterion for more powerful image representations.
Modified OMP Algorithm for Exponentially Decaying Signals
Kazimierczuk, Krzysztof; Kasprzak, Paweł
2015-01-01
A group of signal reconstruction methods, referred to as compressed sensing (CS), has recently found a variety of applications in numerous branches of science and technology. However, the condition of the applicability of standard CS algorithms (e.g., orthogonal matching pursuit, OMP), i.e., the existence of the strictly sparse representation of a signal, is rarely met. Thus, dedicated algorithms for solving particular problems have to be developed. In this paper, we introduce a modification of OMP motivated by nuclear magnetic resonance (NMR) application of CS. The algorithm is based on the fact that the NMR spectrum consists of Lorentzian peaks and matches a single Lorentzian peak in each of its iterations. Thus, we propose the name Lorentzian peak matching pursuit (LPMP). We also consider certain modification of the algorithm by introducing the allowed positions of the Lorentzian peaks' centers. Our results show that the LPMP algorithm outperforms other CS algorithms when applied to exponentially decaying signals. PMID:25609044
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
NASA Technical Reports Server (NTRS)
Knox, C. E.
1984-01-01
A simple airborne flight management descent algorithm designed to define a flight profile subject to the constraints of using idle thrust, a clean airplane configuration (landing gear up, flaps zero, and speed brakes retracted), and fixed-time end conditions was developed and flight tested in the NASA TSRV B-737 research airplane. The research test flights, conducted in the Denver ARTCC automated time-based metering LFM/PD ATC environment, demonstrated that time guidance and control in the cockpit was acceptable to the pilots and ATC controllers and resulted in arrival of the airplane over the metering fix with standard deviations in airspeed error of 6.5 knots, in altitude error of 23.7 m (77.8 ft), and in arrival time accuracy of 12 sec. These accuracies indicated a good representation of airplane performance and wind modeling. Fuel savings will be obtained on a fleet-wide basis through a reduction of the time error dispersions at the metering fix and on a single-airplane basis by presenting the pilot with guidance for a fuel-efficient descent.
Walusinski, Olivier
2014-01-01
In the second half of the 19th century, Jean-Martin Charcot (1825-1893) became famous for the quality of his teaching and his innovative neurological discoveries, bringing many French and foreign students to Paris. A hunger for recognition, together with progressive and anticlerical ideals, led Charcot to invite writers, journalists, and politicians to his lessons, during which he presented the results of his work on hysteria. These events became public performances, for which physicians and patients were transformed into actors. Major newspapers ran accounts of these consultations, more like theatrical shows in some respects. The resultant enthusiasm prompted other physicians in Paris and throughout France to try and imitate them. We will compare the form and substance of Charcot's lessons with those given by Jules-Bernard Luys (1828-1897), Victor Dumontpallier (1826-1899), Ambroise-Auguste Liébault (1823-1904), Hippolyte Bernheim (1840-1919), Joseph Grasset (1849-1918), and Albert Pitres (1848-1928). We will also note their impact on contemporary cinema and theatre. PMID:25273491
Schmidtlein, CR; Beattie, B; Humm, J; Li, S; Wu, Z; Xu, Y; Zhang, J; Shen, L; Vogelsang, L; Feiglin, D; Krol, A
2014-06-15
Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1st order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved
Television Quiz Show Simulation
ERIC Educational Resources Information Center
Hill, Jonnie Lynn
2007-01-01
This article explores the simulation of four television quiz shows for students in China studying English as a foreign language (EFL). It discusses the adaptation and implementation of television quiz shows and how the students reacted to them.
NASA Astrophysics Data System (ADS)
2007-01-01
The ESO Very Large Telescope Interferometer, which allows astronomers to scrutinise objects with a precision equivalent to that of a 130-m telescope, is proving itself an unequalled success every day. One of the latest instruments installed, AMBER, has led to a flurry of scientific results, an anthology of which is being published this week as special features in the research journal Astronomy & Astrophysics. ESO PR Photo 06a/07 ESO PR Photo 06a/07 The AMBER Instrument "With its unique capabilities, the VLT Interferometer (VLTI) has created itself a niche in which it provide answers to many astronomical questions, from the shape of stars, to discs around stars, to the surroundings of the supermassive black holes in active galaxies," says Jorge Melnick (ESO), the VLT Project Scientist. The VLTI has led to 55 scientific papers already and is in fact producing more than half of the interferometric results worldwide. "With the capability of AMBER to combine up to three of the 8.2-m VLT Unit Telescopes, we can really achieve what nobody else can do," added Fabien Malbet, from the LAOG (France) and the AMBER Project Scientist. Eleven articles will appear this week in Astronomy & Astrophysics' special AMBER section. Three of them describe the unique instrument, while the other eight reveal completely new results about the early and late stages in the life of stars. ESO PR Photo 06b/07 ESO PR Photo 06b/07 The Inner Winds of Eta Carinae The first results presented in this issue cover various fields of stellar and circumstellar physics. Two papers deal with very young solar-like stars, offering new information about the geometry of the surrounding discs and associated outflowing winds. Other articles are devoted to the study of hot active stars of particular interest: Alpha Arae, Kappa Canis Majoris, and CPD -57o2874. They provide new, precise information about their rotating gas envelopes. An important new result concerns the enigmatic object Eta Carinae. Using AMBER with
NASA Astrophysics Data System (ADS)
Auletta, Gianluca; Ditommaso, Rocco; Iacovino, Chiara; Carlo Ponzo, Felice; Pina Limongelli, Maria
2016-04-01
Continuous monitoring based on vibrational identification methods is increasingly employed with the aim of evaluate the state of the health of existing structures and infrastructures and to evaluate the performance of safety interventions over time. In case of earthquakes, data acquired by means of continuous monitoring systems can be used to localize and quantify a possible damage occurred on a monitored structure using appropriate algorithms based on the variations of structural parameters. Most of the damage identification methods are based on the variation of few modal and/or non-modal parameters: the former, are strictly related to the structural eigenfrequencies, equivalent viscous damping factors and mode shapes; the latter, are based on the variation of parameters related to the geometric characteristics of the monitored structure whose variations could be correlated related to damage. In this work results retrieved from the application of a curvature evolution based method and an interpolation error based method are compared. The first method is based on the evaluation of the curvature variation (related to the fundamental mode of vibration) over time and compares the variations before, during and after the earthquake. The Interpolation Method is based on the detection of localized reductions of smoothness in the Operational Deformed Shapes (ODSs) of the structure. A damage feature is defined in terms of the error related to the use of a spline function in interpolating the ODSs of the structure: statistically significant variations of the interpolation error between two successive inspections of the structure indicate the onset of damage. Both methods have been applied using both numerical data retrieved from nonlinear FE models and experimental tests on scaled structures carried out on the shaking table of the University of Basilicata. Acknowledgements This study was partially funded by the Italian Civil Protection Department within the project DPC
Advanced optimization of permanent magnet wigglers using a genetic algorithm
Hajima, Ryoichi
1995-12-31
In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms.
ERIC Educational Resources Information Center
Anderton, Alice
The Intertribal Wordpath Society is a nonprofit educational corporation formed to promote the teaching, status, awareness, and use of Oklahoma Indian languages. The Society produces "Wordpath," a weekly 30-minute public access television show about Oklahoma Indian languages and the people who are teaching and preserving them. The show aims to…
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.
Regier, Michael D; Moodie, Erica E M
2016-05-01
We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience. PMID:27227718
A comparison of heuristic search algorithms for molecular docking.
Westhead, D R; Clark, D E; Murray, C W
1997-05-01
This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone. PMID:9263849
Dynamic Bubble-Check Algorithm for Check Node Processing in Q-Ary LDPC Decoders
NASA Astrophysics Data System (ADS)
Lin, Wei; Bai, Baoming; Ma, Xiao; Sun, Rong
A simplified algorithm for check node processing of extended min-sum (EMS) q-ary LDPC decoders is presented in this letter. Compared with the bubble check algorithm, the so-called dynamic bubble-check (DBC) algorithm aims to further reduce the computational complexity for the elementary check node (ECN) processing. By introducing two flag vectors in ECN processing, The DBC algorithm can use the minimum number of comparisons at each step. Simulation results show that, DBC algorithm uses significantly fewer comparison operations than the bubble check algorithm, and presents no performance loss compared with standard EMS algorithm on AWGN channels.
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.
Solving SAT Problem Based on Hybrid Differential Evolution Algorithm
NASA Astrophysics Data System (ADS)
Liu, Kunqi; Zhang, Jingmin; Liu, Gang; Kang, Lishan
Satisfiability (SAT) problem is an NP-complete problem. Based on the analysis about it, SAT problem is translated equally into an optimization problem on the minimum of objective function. A hybrid differential evolution algorithm is proposed to solve the Satisfiability problem. It makes full use of strong local search capacity of hill-climbing algorithm and strong global search capability of differential evolution algorithm, which makes up their disadvantages, improves the efficiency of algorithm and avoids the stagnation phenomenon. The experiment results show that the hybrid algorithm is efficient in solving SAT problem.
ERIC Educational Resources Information Center
Kirkpatrick, Larry D.; Rugheimer, Mac
1979-01-01
Describes the viewing sessions and the holograms of a holographic road show. The traveling exhibits, believed to stimulate interest in physics, include a wide variety of holograms and demonstrate several physical principles. (GA)
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.
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 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
Vadvala, Harshna; Kim, Phillip; Mayrhofer, Thomas; Pianykh, Oleg; Kalra, Mannudeep; Hoffmann, Udo
2014-01-01
Purpose To evaluate the effect of automatic tube potential selection and automatic exposure control combined with female breast displacement during coronary computed tomography angiography (CCTA) on radiation exposure in women versus men of the same body size. Materials and methods Consecutive clinical exams between January 2012 and July 2013 at an academic medical center were retrospectively analyzed. All examinations were performed using ECG-gating, automated tube potential, and tube current selection algorithm (APS-AEC) with breast displacement in females. Cohorts were stratified by sex and standard World Health Organization body mass index (BMI) ranges. CT dose index volume (CTDIvol), dose length product (DLP) median effective dose (ED), and size specific dose estimate (SSDE) were recorded. Univariable and multivariable regression analyses were performed to evaluate the effect of gender on radiation exposure per BMI. Results A total of 726 exams were included, 343 (47%) were females; mean BMI was similar by gender (28.6±6.9 kg/m2 females vs. 29.2±6.3 kg/m2 males; P=0.168). Median ED was 2.3 mSv (1.4-5.2) for females and 3.6 (2.5-5.9) for males (P<0.001). Females were exposed to less radiation by a difference in median ED of –1.3 mSv, CTDIvol –4.1 mGy, and SSDE –6.8 mGy (all P<0.001). After adjusting for BMI, patient characteristics, and gating mode, females exposure was lower by a median ED of –0.7 mSv, CTDIvol –2.3 mGy, and SSDE –3.15 mGy, respectively (all P<0.01). Conclusions: We observed a difference in radiation exposure to patients undergoing CCTA with the combined use of AEC-APS and breast displacement in female patients as compared to their BMI-matched male counterparts, with female patients receiving one third less exposure. PMID:25610804
ERIC Educational Resources Information Center
Eccleston, Jeff
2007-01-01
Big things come in small packages. This saying came to the mind of the author after he created a simple math review activity for his fourth grade students. Though simple, it has proven to be extremely advantageous in reinforcing math concepts. He uses this activity, which he calls "Show What You Know," often. This activity provides the perfect…
ERIC Educational Resources Information Center
Mathieu, Aaron
2000-01-01
Uses a talk show activity for a final assessment tool for students to debate about the ozone hole. Students are assessed on five areas: (1) cooperative learning; (2) the written component; (3) content; (4) self-evaluation; and (5) peer evaluation. (SAH)
Honored Teacher Shows Commitment.
ERIC Educational Resources Information Center
Ratte, Kathy
1987-01-01
Part of the acceptance speech of the 1985 National Council for the Social Studies Teacher of the Year, this article describes the censorship experience of this honored social studies teacher. The incident involved the showing of a videotape version of the feature film entitled "The Seduction of Joe Tynan." (JDH)
ERIC Educational Resources Information Center
Moore, Mitzi Ruth
1992-01-01
Proposes having students perform skits in which they play the roles of the science concepts they are trying to understand. Provides the dialog for a skit in which hot and cold gas molecules are interviewed on a talk show to study how these properties affect wind, rain, and other weather phenomena. (MDH)
ERIC Educational Resources Information Center
Frasier, Debra
2008-01-01
In the author's book titled "The Incredible Water Show," the characters from "Miss Alaineus: A Vocabulary Disaster" used an ocean of information to stage an inventive performance about the water cycle. In this article, the author relates how she turned the story into hands-on science teaching for real-life fifth-grade students. The author also…
ERIC Educational Resources Information Center
Cech, Scott J.
2008-01-01
Having students show their skills in three dimensions, known as performance-based assessment, dates back at least to Socrates. Individual schools such as Barrington High School--located just outside of Providence--have been requiring students to actively demonstrate their knowledge for years. The Rhode Island's high school graduating class became…
Casu, Sebastian; Häske, David
2016-06-01
Delayed antibiotic treatment for patients in severe sepsis and septic shock decreases the probability of survival. In this survey, medical directors of different emergency medical services (EMS) in Germany were asked if they are prepared for pre-hospital sepsis therapy with antibiotics or special algorithms to evaluate the individual preparations of the different rescue areas for the treatment of patients with this infectious disease. The objective of the survey was to obtain a general picture of the current status of the EMS with respect to rapid antibiotic treatment for sepsis. A total of 166 medical directors were invited to complete a short survey on behalf of the different rescue service districts in Germany via an electronic cover letter. Of the rescue districts, 25.6 % (n = 20) stated that they keep antibiotics on EMS vehicles. In addition, 2.6 % carry blood cultures on the vehicles. The most common antibiotic is ceftriaxone (third generation cephalosporin). In total, 8 (10.3 %) rescue districts use an algorithm for patients with sepsis, severe sepsis or septic shock. Although the German EMS is an emergency physician-based rescue system, special opportunities in the form of antibiotics on emergency physician vehicles are missing. Simultaneously, only 10.3 % of the rescue districts use a special algorithm for sepsis therapy. Sepsis, severe sepsis and septic shock do not appear to be prioritized as highly as these deadly diseases should be in the pre-hospital setting. PMID:26719078
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.
Sampling Within k-Means Algorithm to Cluster Large Datasets
Bejarano, Jeremy; Bose, Koushiki; Brannan, Tyler; Thomas, Anita; Adragni, Kofi; Neerchal, Nagaraj; Ostrouchov, George
2011-08-01
Due to current data collection technology, our ability to gather data has surpassed our ability to analyze it. In particular, k-means, one of the simplest and fastest clustering algorithms, is ill-equipped to handle extremely large datasets on even the most powerful machines. Our new algorithm uses a sample from a dataset to decrease runtime by reducing the amount of data analyzed. We perform a simulation study to compare our sampling based k-means to the standard k-means algorithm by analyzing both the speed and accuracy of the two methods. Results show that our algorithm is significantly more efficient than the existing algorithm with comparable accuracy. Further work on this project might include a more comprehensive study both on more varied test datasets as well as on real weather datasets. This is especially important considering that this preliminary study was performed on rather tame datasets. Also, these datasets should analyze the performance of the algorithm on varied values of k. Lastly, this paper showed that the algorithm was accurate for relatively low sample sizes. We would like to analyze this further to see how accurate the algorithm is for even lower sample sizes. We could find the lowest sample sizes, by manipulating width and confidence level, for which the algorithm would be acceptably accurate. In order for our algorithm to be a success, it needs to meet two benchmarks: match the accuracy of the standard k-means algorithm and significantly reduce runtime. Both goals are accomplished for all six datasets analyzed. However, on datasets of three and four dimension, as the data becomes more difficult to cluster, both algorithms fail to obtain the correct classifications on some trials. Nevertheless, our algorithm consistently matches the performance of the standard algorithm while becoming remarkably more efficient with time. Therefore, we conclude that analysts can use our algorithm, expecting accurate results in considerably less time.
Boden, Timothy W
2016-01-01
Many medical practices have cut back on education and staff development expenses, especially those costs associated with conventions and conferences. But there are hard-to-value returns on your investment in these live events--beyond the obvious benefits of acquired knowledge and skills. Major vendors still exhibit their services and wares at many events, and the exhibit hall is a treasure-house of information and resources for the savvy physician or administrator. Make and stick to a purposeful plan to exploit the trade show. You can compare products, gain new insights and ideas, and even negotiate better deals with representatives anxious to realize returns on their exhibition investments. PMID:27249887
An Iterative Soft-Decision Decoding Algorithm
NASA Technical Reports Server (NTRS)
Lin, Shu; Koumoto, Takuya; Takata, Toyoo; Kasami, Tadao
1996-01-01
This paper presents a new minimum-weight trellis-based soft-decision iterative decoding algorithm for binary linear block codes. Simulation results for the RM(64,22), EBCH(64,24), RM(64,42) and EBCH(64,45) codes show that the proposed decoding algorithm achieves practically (or near) optimal error performance with significant reduction in decoding computational complexity. The average number of search iterations is also small even for low signal-to-noise ratio.
Wrong, Terence; Baumgart, Erica
2013-01-01
The authors of the preceding articles raise legitimate questions about patient and staff rights and the unintended consequences of allowing ABC News to film inside teaching hospitals. We explain why we regard their fears as baseless and not supported by what we heard from individuals portrayed in the filming, our decade-long experience making medical documentaries, and the full un-aired context of the scenes shown in the broadcast. The authors don't and can't know what conversations we had, what documents we reviewed, and what protections we put in place in each televised scene. Finally, we hope to correct several misleading examples cited by the authors as well as their offhand mischaracterization of our program as a "reality" show. PMID:23631336
NASA Astrophysics Data System (ADS)
Zhang, Yanjun; Yu, Chunjuan; Fu, Xinghu; Liu, Wenzhe; Bi, Weihong
2015-12-01
In the distributed optical fiber sensing system based on Brillouin scattering, strain and temperature are the main measuring parameters which can be obtained by analyzing the Brillouin center frequency shift. The novel algorithm which combines the cuckoo search algorithm (CS) with the improved differential evolution (IDE) algorithm is proposed for the Brillouin scattering parameter estimation. The CS-IDE algorithm is compared with CS algorithm and analyzed in different situation. The results show that both the CS and CS-IDE algorithm have very good convergence. The analysis reveals that the CS-IDE algorithm can extract the scattering spectrum features with different linear weight ratio, linewidth combination and SNR. Moreover, the BOTDR temperature measuring system based on electron optical frequency shift is set up to verify the effectiveness of the CS-IDE algorithm. Experimental results show that there is a good linear relationship between the Brillouin center frequency shift and temperature changes.
NASA Astrophysics Data System (ADS)
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Tschudin-Sutter, S; Frei, R; Dangel, M; Jakob, M; Balmelli, C; Schaefer, D J; Weisser, M; Elzi, L; Battegay, M; Widmer, A F
2016-05-01
Success rates for treatment regimens involving retention of an infected implant are conflicting and failure rates of up to 80% have been reported. We aimed to validate a proposed treatment algorithm, based on strict selection criteria, by assessing long-term outcome of treatment for orthopaedic device-related infection (ODRI) with retention. From January 1999 to December 2009, all patients diagnosed with ODRI at the University Hospital Basel, Switzerland were eligible for treatment with open surgical debridement, implant-retention and antibiotics, if duration of clinical symptoms was ≤3 weeks, the implant was stable, the soft-tissue had no abscess or sinus tract, and the causative pathogen was susceptible to antimicrobial agents with activity against surface-adhering microorganisms. Antimicrobial treatment was administered according to a predefined algorithm. The primary outcome was treatment failure after 2-year follow up. A total of 455 patients were diagnosed with an ODRI, of whom 233 (51.2%) patients were eligible for treatment involving implant-retention. Causative pathogens were mainly Staphylococcus aureus (41.6%) and coagulase-negative staphylococci (33.9%). Among patients with ODRIs related to prostheses, failure was documented in 10.8% (12/111) and in patients with ODRIs related to osteosyntheses, failure occurred in 9.8% (12/122) after 2 years of follow up. In all, 90% of ODRIs were successfully cured with surgical debridement and implant-retention in addition to long-term antimicrobial therapy according to a predefined treatment algorithm: if patients fulfilled strict selection criteria and there was susceptibility to rifampin for Gram-positive pathogens and ciprofloxacin for Gram-negative pathogens. PMID:26806134
An improved watershed image segmentation algorithm combining with a new entropy evaluation criterion
NASA Astrophysics Data System (ADS)
Deng, Tingquan; Li, Yanchao
2013-03-01
An improved watershed image segmentation algorithm is proposed to solve the problem of over-segmentation by classical watershed algorithm. The new algorithm combines region growing with classical watershed algorithm. The key to region growing lies in choosing a growing threshold to reach a desired result of image segmentation. An entropy evaluation criterion is constructed to determine the optimal threshold. Considering the entropy evaluation criterion as an objective function, the particle swarm optimization algorithm is employed to search global optimization of the objective function. Experimental results show that this new algorithm can solve the problem of over-segmentation effectively.
SDR input power estimation algorithms
NASA Astrophysics Data System (ADS)
Briones, J. C.; Nappier, J. M.
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
SDR Input Power Estimation Algorithms
NASA Technical Reports Server (NTRS)
Nappier, Jennifer M.; Briones, Janette C.
2013-01-01
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
A cross-layer optimization algorithm for wireless sensor network
NASA Astrophysics Data System (ADS)
Wang, Yan; Liu, Le Qing
2010-07-01
Energy is critical for typical wireless sensor networks (WSN) and how to energy consumption and maximize network lifetime are big challenges for Wireless sensor networks; cross layer algorithm is main method to solve this problem. In this paper, firstly, we analyze current layer-based optimal methods in wireless sensor network and summarize the physical, link and routing optimization techniques. Secondly we compare some strategies in cross-layer optimization algorithms. According to the analysis and summary of the current lifetime algorithms in wireless sensor network A cross layer optimization algorithm is proposed,. Then this optimization algorithm proposed in the paper is adopted to improve the traditional Leach routing protocol. Simulation results show that this algorithm is an excellent cross layer algorithm for reducing energy consumption.
An adaptive algorithm for motion compensated color image coding
NASA Technical Reports Server (NTRS)
Kwatra, Subhash C.; Whyte, Wayne A.; Lin, Chow-Ming
1987-01-01
This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.
A multistrategy optimization improved artificial bee colony algorithm.
Liu, Wen
2014-01-01
Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed. Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate. Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster. PMID:24982924
Efficient algorithm to compute mutually connected components in interdependent networks.
Hwang, S; Choi, S; Lee, Deokjae; Kahng, B
2015-02-01
Mutually connected components (MCCs) play an important role as a measure of resilience in the study of interdependent networks. Despite their importance, an efficient algorithm to obtain the statistics of all MCCs during the removal of links has thus far been absent. Here, using a well-known fully dynamic graph algorithm, we propose an efficient algorithm to accomplish this task. We show that the time complexity of this algorithm is approximately O(N(1.2)) for random graphs, which is more efficient than O(N(2)) of the brute-force algorithm. We confirm the correctness of our algorithm by comparing the behavior of the order parameter as links are removed with existing results for three types of double-layer multiplex networks. We anticipate that this algorithm will be used for simulations of large-size systems that have been previously inaccessible. PMID:25768559
Research on Laser Marking Speed Optimization by Using Genetic Algorithm
Wang, Dongyun; Yu, Qiwei; Zhang, Yu
2015-01-01
Laser Marking Machine is the most common coding equipment on product packaging lines. However, the speed of laser marking has become a bottleneck of production. In order to remove this bottleneck, a new method based on a genetic algorithm is designed. On the basis of this algorithm, a controller was designed and simulations and experiments were performed. The results show that using this algorithm could effectively improve laser marking efficiency by 25%. PMID:25955831
Recent Advancements in Lightning Jump Algorithm Work
NASA Technical Reports Server (NTRS)
Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.
2010-01-01
In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).
A scalable parallel algorithm for multiple objective linear programs
NASA Technical Reports Server (NTRS)
Wiecek, Malgorzata M.; Zhang, Hong
1994-01-01
This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.
Combined string searching algorithm based on knuth-morris- pratt and boyer-moore algorithms
NASA Astrophysics Data System (ADS)
Tsarev, R. Yu; Chernigovskiy, A. S.; Tsareva, E. A.; Brezitskaya, V. V.; Nikiforov, A. Yu; Smirnov, N. A.
2016-04-01
The string searching task can be classified as a classic information processing task. Users either encounter the solution of this task while working with text processors or browsers, employing standard built-in tools, or this task is solved unseen by the users, while they are working with various computer programmes. Nowadays there are many algorithms for solving the string searching problem. The main criterion of these algorithms’ effectiveness is searching speed. The larger the shift of the pattern relative to the string in case of pattern and string characters’ mismatch is, the higher is the algorithm running speed. This article offers a combined algorithm, which has been developed on the basis of well-known Knuth-Morris-Pratt and Boyer-Moore string searching algorithms. These algorithms are based on two different basic principles of pattern matching. Knuth-Morris-Pratt algorithm is based upon forward pattern matching and Boyer-Moore is based upon backward pattern matching. Having united these two algorithms, the combined algorithm allows acquiring the larger shift in case of pattern and string characters’ mismatch. The article provides an example, which illustrates the results of Boyer-Moore and Knuth-Morris- Pratt algorithms and combined algorithm’s work and shows advantage of the latter in solving string searching problem.
Performance of a parallel algorithm for standard cell placement on the Intel Hypercube
NASA Technical Reports Server (NTRS)
Jones, Mark; Banerjee, Prithviraj
1987-01-01
A parallel simulated annealing algorithm for standard cell placement on the Intel Hypercube is presented. A novel tree broadcasting strategy is used extensively for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than uniprocessor simulated annealing algorithms.
Performance-based seismic design of steel frames utilizing colliding bodies algorithm.
Veladi, H
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm. PMID:25202717
Performance-Based Seismic Design of Steel Frames Utilizing Colliding Bodies Algorithm
Veladi, H.
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm. PMID:25202717
... shows the ranges for blood glucose levels after 8 to 12 hours of fasting (not eating). It shows the normal range and the abnormal ranges that are a sign of prediabetes or diabetes. Plasma Glucose Results (mg/dL)* Diagnosis 70 to 99 ...
Kim, Andrea A.; Parekh, Bharat S.; Umuro, Mamo; Galgalo, Tura; Bunnell, Rebecca; Makokha, Ernest; Dobbs, Trudy; Murithi, Patrick; Muraguri, Nicholas; De Cock, Kevin M.; Mermin, Jonathan
2016-01-01
Introduction A recent infection testing algorithm (RITA) that can distinguish recent from long-standing HIV infection can be applied to nationally representative population-based surveys to characterize and identify risk factors for recent infection in a country. Materials and Methods We applied a RITA using the Limiting Antigen Avidity Enzyme Immunoassay (LAg) on stored HIV-positive samples from the 2007 Kenya AIDS Indicator Survey. The case definition for recent infection included testing recent on LAg and having no evidence of antiretroviral therapy use. Multivariate analysis was conducted to determine factors associated with recent and long-standing infection compared to HIV-uninfected persons. All estimates were weighted to adjust for sampling probability and nonresponse. Results Of 1,025 HIV-antibody-positive specimens, 64 (6.2%) met the case definition for recent infection and 961 (93.8%) met the case definition for long-standing infection. Compared to HIV-uninfected individuals, factors associated with higher adjusted odds of recent infection were living in Nairobi (adjusted odds ratio [AOR] 11.37; confidence interval [CI] 2.64–48.87) and Nyanza (AOR 4.55; CI 1.39–14.89) provinces compared to Western province; being widowed (AOR 8.04; CI 1.42–45.50) or currently married (AOR 6.42; CI 1.55–26.58) compared to being never married; having had ≥ 2 sexual partners in the last year (AOR 2.86; CI 1.51–5.41); not using a condom at last sex in the past year (AOR 1.61; CI 1.34–1.93); reporting a sexually transmitted infection (STI) diagnosis or symptoms of STI in the past year (AOR 1.97; CI 1.05–8.37); and being aged <30 years with: 1) HSV-2 infection (AOR 8.84; CI 2.62–29.85), 2) male genital ulcer disease (AOR 8.70; CI 2.36–32.08), or 3) lack of male circumcision (AOR 17.83; CI 2.19–144.90). Compared to HIV-uninfected persons, factors associated with higher adjusted odds of long-standing infection included living in Coast (AOR 1.55; CI 1.04–2
Baxter, Suzanne D; Guinn, Caroline H; Smith, Albert F; Hitchcock, David B; Royer, Julie A; Puryear, Megan P; Collins, Kathleen L; Smith, Alyssa L
2016-04-14
Validation-study data were analysed to investigate retention interval (RI) and prompt effects on the accuracy of fourth-grade children's reports of school-breakfast and school-lunch (in 24-h recalls), and the accuracy of school-breakfast reports by breakfast location (classroom; cafeteria). Randomly selected fourth-grade children at ten schools in four districts were observed eating school-provided breakfast and lunch, and were interviewed under one of eight conditions created by crossing two RIs ('short'--prior-24-hour recall obtained in the afternoon and 'long'--previous-day recall obtained in the morning) with four prompts ('forward'--distant to recent, 'meal name'--breakfast, etc., 'open'--no instructions, and 'reverse'--recent to distant). Each condition had sixty children (half were girls). Of 480 children, 355 and 409 reported meals satisfying criteria for reports of school-breakfast and school-lunch, respectively. For breakfast and lunch separately, a conventional measure--report rate--and reporting-error-sensitive measures--correspondence rate and inflation ratio--were calculated for energy per meal-reporting child. Correspondence rate and inflation ratio--but not report rate--showed better accuracy for school-breakfast and school-lunch reports with the short RI than with the long RI; this pattern was not found for some prompts for each sex. Correspondence rate and inflation ratio showed better school-breakfast report accuracy for the classroom than for cafeteria location for each prompt, but report rate showed the opposite. For each RI, correspondence rate and inflation ratio showed better accuracy for lunch than for breakfast, but report rate showed the opposite. When choosing RI and prompts for recalls, researchers and practitioners should select a short RI to maximise accuracy. Recommendations for prompt selections are less clear. As report rates distort validation-study accuracy conclusions, reporting-error-sensitive measures are recommended. PMID
Universal lossless compression algorithm for textual images
NASA Astrophysics Data System (ADS)
al Zahir, Saif
2012-03-01
In recent years, an unparalleled volume of textual information has been transported over the Internet via email, chatting, blogging, tweeting, digital libraries, and information retrieval systems. As the volume of text data has now exceeded 40% of the total volume of traffic on the Internet, compressing textual data becomes imperative. Many sophisticated algorithms were introduced and employed for this purpose including Huffman encoding, arithmetic encoding, the Ziv-Lempel family, Dynamic Markov Compression, and Burrow-Wheeler Transform. My research presents novel universal algorithm for compressing textual images. The algorithm comprises two parts: 1. a universal fixed-to-variable codebook; and 2. our row and column elimination coding scheme. Simulation results on a large number of Arabic, Persian, and Hebrew textual images show that this algorithm has a compression ratio of nearly 87%, which exceeds published results including JBIG2.
Genetic Algorithms and Local Search
NASA Technical Reports Server (NTRS)
Whitley, Darrell
1996-01-01
The first part of this presentation is a tutorial level introduction to the principles of genetic search and models of simple genetic algorithms. The second half covers the combination of genetic algorithms with local search methods to produce hybrid genetic algorithms. Hybrid algorithms can be modeled within the existing theoretical framework developed for simple genetic algorithms. An application of a hybrid to geometric model matching is given. The hybrid algorithm yields results that improve on the current state-of-the-art for this problem.
The Algorithm Selection Problem
NASA Technical Reports Server (NTRS)
Minton, Steve; Allen, John; Deiss, Ron (Technical Monitor)
1994-01-01
Work on NP-hard problems has shown that many instances of these theoretically computationally difficult problems are quite easy. The field has also shown that choosing the right algorithm for the problem can have a profound effect on the time needed to find a solution. However, to date there has been little work showing how to select the right algorithm for solving any particular problem. The paper refers to this as the algorithm selection problem. It describes some of the aspects that make this problem difficult, as well as proposes a technique for addressing it.
Image segmentation using an improved differential algorithm
NASA Astrophysics Data System (ADS)
Gao, Hao; Shi, Yujiao; Wu, Dongmei
2014-10-01
Among all the existing segmentation techniques, the thresholding technique is one of the most popular due to its simplicity, robustness, and accuracy (e.g. the maximum entropy method, Otsu's method, and K-means clustering). However, the computation time of these algorithms grows exponentially with the number of thresholds due to their exhaustive searching strategy. As a population-based optimization algorithm, differential algorithm (DE) uses a population of potential solutions and decision-making processes. It has shown considerable success in solving complex optimization problems within a reasonable time limit. Thus, applying this method into segmentation algorithm should be a good choice during to its fast computational ability. In this paper, we first propose a new differential algorithm with a balance strategy, which seeks a balance between the exploration of new regions and the exploitation of the already sampled regions. Then, we apply the new DE into the traditional Otsu's method to shorten the computation time. Experimental results of the new algorithm on a variety of images show that, compared with the EA-based thresholding methods, the proposed DE algorithm gets more effective and efficient results. It also shortens the computation time of the traditional Otsu method.
Minimalist ensemble algorithms for genome-wide protein localization prediction
2012-01-01
Background Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. Results This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. Conclusions We
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.
NASA Astrophysics Data System (ADS)
Salami, M. J. E.; Tijani, I. B.; Abdullateef, A. I.; Aibinu, M. A.
2013-12-01
A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. The DE at the upper level is formulated as combinatorial optimization to search for the network architecture while the associated network weights that minimize the prediction error is provided by the GA at the lower level. The performance of the algorithm is evaluated on identification of a laboratory rotary motion system. The system identification results show the effectiveness of the proposed algorithm for nonparametric model development.
Improved artificial bee colony algorithm based gravity matching navigation method.
Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang
2014-01-01
Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019
Fast parallel algorithm for slicing STL based on pipeline
NASA Astrophysics Data System (ADS)
Ma, Xulong; Lin, Feng; Yao, Bo
2016-04-01
In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.
Fast parallel algorithm for slicing STL based on pipeline
NASA Astrophysics Data System (ADS)
Ma, Xulong; Lin, Feng; Yao, Bo
2016-05-01
In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.
ERIC Educational Resources Information Center
Wallace, Dale
2000-01-01
Given the amount of time, energy, and money devoted to provincial achievement exams in Canada, it is disturbing that Alberta students and teachers feel so pressured and that the exams do not accurately reflect what students know. Research shows that intelligence has an (untested) emotional component. (MLH)
Performance of a parallel algorithm for standard cell placement on the Intel Hypercube
NASA Technical Reports Server (NTRS)
Jones, Mark; Banerjee, Prithviraj
1987-01-01
A parallel simulated annealing algorithm for standard cell placement that is targeted to run on the Intel Hypercube is presented. A tree broadcasting strategy that is used extensively in our algorithm for updating cell locations in the parallel environment is presented. Studies on the performance of our algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms.
Algorithm for Public Electric Transport Schedule Control for Intelligent Embedded Devices
NASA Astrophysics Data System (ADS)
Alps, Ivars; Potapov, Andrey; Gorobetz, Mikhail; Levchenkov, Anatoly
2010-01-01
In this paper authors present heuristics algorithm for precise schedule fulfilment in city traffic conditions taking in account traffic lights. The algorithm is proposed for programmable controller. PLC is proposed to be installed in electric vehicle to control its motion speed and signals of traffic lights. Algorithm is tested using real controller connected to virtual devices and real functional models of real tram devices. Results of experiments show high precision of public transport schedule fulfilment using proposed algorithm.
Mutation-Based Artificial Fish Swarm Algorithm for Bound Constrained Global Optimization
NASA Astrophysics Data System (ADS)
Rocha, Ana Maria A. C.; Fernandes, Edite M. G. P.
2011-09-01
The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutation operators to prevent the algorithm to falling into local solutions, diversifying the search, and to accelerate convergence to the global optima. Three mutation strategies are introduced into the AFS algorithm to define the trial points that emerge from random, leaping and searching behaviors. Computational results show that the new algorithm outperforms other well-known global stochastic solution methods.
Polynomial Algorithms for Item Matching.
ERIC Educational Resources Information Center
Armstrong, Ronald D.; Jones, Douglas H.
1992-01-01
Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)
2014-01-01
Background The most important factor discriminating juvenile (JIS) from adolescent idiopathic scoliosis (AIS) is the risk of deformity progression. Brace treatment can change natural history, even when risk of progression is high. The aim of this study was to compare the end of growth results of JIS subjects, treated after 10 years of age, with final results of AIS. Methods Design: prospective observational controlled cohort study nested in a prospective database. Setting: outpatient tertiary referral clinic specialized in conservative treatment of spinal deformities. Inclusion criteria: idiopathic scoliosis; European Risser 0–2; 25 degrees to 45 degrees Cobb; start treatment age: 10 years or more, never treated before. Exclusion criteria: secondary scoliosis, neurological etiology, prior treatment for scoliosis (brace or surgery). Groups: 27 patients met the inclusion criteria for the AJIS, (Juvenile Idiopathic Scoliosis treated in adolescence), demonstrated by an x-ray before 10 year of age, and treatment start after 10 years of age. AIS group included 45 adolescents with a diagnostic x-ray made after the threshold of age 10 years. Results at the end of growth were analysed; the threshold of 5 Cobb degree to define worsened, improved and stabilized curves was considered. Statistics: Mean and SD were used for descriptive statistics of clinical and radiographic changes. Relative Risk of failure (RR), Chi-square and T-test of all data was calculated to find differences among the two groups. 95% Confidence Interval (CI) , and of radiographic changes have been calculated. Results We did not find any Cobb angle significant differences among groups at baseline and at the end of treatment. The only difference was in the number of patients progressed above 45 degrees, found in the JIS group. The RR of progression of AJIS was, 1.35 (IC95% 0.57-3.17) versus AIS, and it wasn't statistically significant in the AJIS group, in respect to AIS group (p = 0.5338). Conclusion
A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems
NASA Astrophysics Data System (ADS)
Thammano, Arit; Teekeng, Wannaporn
2015-05-01
The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.
Dual-Byte-Marker Algorithm for Detecting JFIF Header
NASA Astrophysics Data System (ADS)
Mohamad, Kamaruddin Malik; Herawan, Tutut; Deris, Mustafa Mat
The use of efficient algorithm to detect JPEG file is vital to reduce time taken for analyzing ever increasing data in hard drive or physical memory. In the previous paper, single-byte-marker algorithm is proposed for header detection. In this paper, another novel header detection algorithm called dual-byte-marker is proposed. Based on the experiments done on images from hard disk, physical memory and data set from DFRWS 2006 Challenge, results showed that dual-byte-marker algorithm gives better performance with better execution time for header detection as compared to single-byte-marker.
Graph Matching Algorithms for Business Process Model Similarity Search
NASA Astrophysics Data System (ADS)
Dijkman, Remco; Dumas, Marlon; García-Bañuelos, Luciano
We investigate the problem of ranking all process models in a repository according to their similarity with respect to a given process model. We focus specifically on the application of graph matching algorithms to this similarity search problem. Since the corresponding graph matching problem is NP-complete, we seek to find a compromise between computational complexity and quality of the computed ranking. Using a repository of 100 process models, we evaluate four graph matching algorithms, ranging from a greedy one to a relatively exhaustive one. The results show that the mean average precision obtained by a fast greedy algorithm is close to that obtained with the most exhaustive algorithm.
Nios II hardware acceleration of the epsilon quadratic sieve algorithm
NASA Astrophysics Data System (ADS)
Meyer-Bäse, Uwe; Botella, Guillermo; Castillo, Encarnacion; García, Antonio
2010-04-01
The quadratic sieve (QS) algorithm is one of the most powerful algorithms to factor large composite primes used to break RSA cryptographic systems. The hardware structure of the QS algorithm seems to be a good fit for FPGA acceleration. Our new ɛ-QS algorithm further simplifies the hardware architecture making it an even better candidate for C2H acceleration. This paper shows our design results in FPGA resource and performance when implementing very long arithmetic on the Nios microprocessor platform with C2H acceleration for different libraries (GMP, LIP, FLINT, NRMP) and QS architecture choices for factoring 32-2048 bit RSA numbers.
Identification of Traceability Barcode Based on Phase Correlation Algorithm
NASA Astrophysics Data System (ADS)
Lang, Liying; Zhang, Xiaofang
In the paper phase correlation algorithm based on Fourier transform is applied to the traceability barcode identification, which is a widely used method of image registration. And there is the rotation-invariant phase correlation algorithm which combines polar coordinate transform with phase correlation, that they can recognize the barcode with partly destroyed and rotated. The paper provides the analysis and simulation for the algorithm using Matlab, the results show that the algorithm has the advantages of good real-time and high performance. And it improves the matching precision and reduces the calculation by optimizing the rotation-invariant phase correlation.
Solving Integer Programming Problems by Using Artificial Bee Colony Algorithm
NASA Astrophysics Data System (ADS)
Akay, Bahriye; Karaboga, Dervis
This paper presents a study that applies the Artificial Bee Colony algorithm to integer programming problems and compares its performance with those of Particle Swarm Optimization algorithm variants and Branch and Bound technique presented to the literature. In order to cope with integer programming problems, in neighbour solution production unit, solutions are truncated to the nearest integer values. The experimental results show that Artificial Bee Colony algorithm can handle integer programming problems efficiently and Artificial Bee Colony algorithm can be considered to be very robust by the statistics calculated such as mean, median, standard deviation.
An affine projection algorithm using grouping selection of input vectors
NASA Astrophysics Data System (ADS)
Shin, JaeWook; Kong, NamWoong; Park, PooGyeon
2011-10-01
This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.
Algorithm for dynamic Speckle pattern processing
NASA Astrophysics Data System (ADS)
Cariñe, J.; Guzmán, R.; Torres-Ruiz, F. A.
2016-07-01
In this paper we present a new algorithm for determining surface activity by processing speckle pattern images recorded with a CCD camera. Surface activity can be produced by motility or small displacements among other causes, and is manifested as a change in the pattern recorded in the camera with reference to a static background pattern. This intensity variation is considered to be a small perturbation compared with the mean intensity. Based on a perturbative method we obtain an equation with which we can infer information about the dynamic behavior of the surface that generates the speckle pattern. We define an activity index based on our algorithm that can be easily compared with the outcomes from other algorithms. It is shown experimentally that this index evolves in time in the same way as the Inertia Moment method, however our algorithm is based on direct processing of speckle patterns without the need for other kinds of post-processes (like THSP and co-occurrence matrix), making it a viable real-time method. We also show how this algorithm compares with several other algorithms when applied to calibration experiments. From these results we conclude that our algorithm offer qualitative and quantitative advantages over current methods.
Novel and efficient tag SNPs selection algorithms.
Chen, Wen-Pei; Hung, Che-Lun; Tsai, Suh-Jen Jane; Lin, Yaw-Ling
2014-01-01
SNPs are the most abundant forms of genetic variations amongst species; the association studies between complex diseases and SNPs or haplotypes have received great attention. However, these studies are restricted by the cost of genotyping all SNPs; thus, it is necessary to find smaller subsets, or tag SNPs, representing the rest of the SNPs. In fact, the existing tag SNP selection algorithms are notoriously time-consuming. An efficient algorithm for tag SNP selection was presented, which was applied to analyze the HapMap YRI data. The experimental results show that the proposed algorithm can achieve better performance than the existing tag SNP selection algorithms; in most cases, this proposed algorithm is at least ten times faster than the existing methods. In many cases, when the redundant ratio of the block is high, the proposed algorithm can even be thousands times faster than the previously known methods. Tools and web services for haplotype block analysis integrated by hadoop MapReduce framework are also developed using the proposed algorithm as computation kernels. PMID:24212035
Fast ordering algorithm for exact histogram specification.
Nikolova, Mila; Steidl, Gabriele
2014-12-01
This paper provides a fast algorithm to order in a meaningful, strict way the integer gray values in digital (quantized) images. It can be used in any exact histogram specification-based application. Our algorithm relies on the ordering procedure based on the specialized variational approach. This variational method was shown to be superior to all other state-of-the art ordering algorithms in terms of faithful total strict ordering but not in speed. Indeed, the relevant functionals are in general difficult to minimize because their gradient is nearly flat over vast regions. In this paper, we propose a simple and fast fixed point algorithm to minimize these functionals. The fast convergence of our algorithm results from known analytical properties of the model. Our algorithm is equivalent to an iterative nonlinear filtering. Furthermore, we show that a particular form of the variational model gives rise to much faster convergence than other alternative forms. We demonstrate that only a few iterations of this filter yield almost the same pixel ordering as the minimizer. Thus, we apply only few iteration steps to obtain images, whose pixels can be ordered in a strict and faithful way. Numerical experiments confirm that our algorithm outperforms by far its main competitors. PMID:25347881
LCD motion blur: modeling, analysis, and algorithm.
Chan, Stanley H; Nguyen, Truong Q
2011-08-01
Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD model and an efficient deblurring algorithm are needed. However, existing LCD motion blur models are insufficient to reflect the limitation of human-eye-tracking system. Also, the spatiotemporal equivalence in LCD motion blur models has not been proven directly in the discrete 2-D spatial domain, although it is widely used. There are three main contributions of this paper: modeling, analysis, and algorithm. First, a comprehensive LCD motion blur model is presented, in which human-eye-tracking limits are taken into consideration. Second, a complete analysis of spatiotemporal equivalence is provided and verified using real video sequences. Third, an LCD motion blur reduction algorithm is proposed. The proposed algorithm solves an l(1)-norm regularized least-squares minimization problem using a subgradient projection method. Numerical results show that the proposed algorithm gives higher peak SNR, lower temporal error, and lower spatial error than motion-compensated inverse filtering and Lucy-Richardson deconvolution algorithm, which are two state-of-the-art LCD deblurring algorithms. PMID:21292596
An Improved Back Propagation Neural Network Algorithm on Classification Problems
NASA Astrophysics Data System (ADS)
Nawi, Nazri Mohd; Ransing, R. S.; Salleh, Mohd Najib Mohd; Ghazali, Rozaida; Hamid, Norhamreeza Abdul
The back propagation algorithm is one the most popular algorithms to train feed forward neural networks. However, the convergence of this algorithm is slow, it is mainly because of gradient descent algorithm. Previous research demonstrated that in 'feed forward' algorithm, the slope of the activation function is directly influenced by a parameter referred to as 'gain'. This research proposed an algorithm for improving the performance of the back propagation algorithm by introducing the adaptive gain of the activation function. The gain values change adaptively for each node. The influence of the adaptive gain on the learning ability of a neural network is analysed. Multi layer feed forward neural networks have been assessed. Physical interpretation of the relationship between the gain value and the learning rate and weight values is given. The efficiency of the proposed algorithm is compared with conventional Gradient Descent Method and verified by means of simulation on four classification problems. In learning the patterns, the simulations result demonstrate that the proposed method converged faster on Wisconsin breast cancer with an improvement ratio of nearly 2.8, 1.76 on diabetes problem, 65% better on thyroid data sets and 97% faster on IRIS classification problem. The results clearly show that the proposed algorithm significantly improves the learning speed of the conventional back-propagation algorithm.
A signal invariant wavelet function selection algorithm.
Garg, Girisha
2016-04-01
This paper addresses the problem of mother wavelet selection for wavelet signal processing in feature extraction and pattern recognition. The problem is formulated as an optimization criterion, where a wavelet library is defined using a set of parameters to find the best mother wavelet function. For estimating the fitness function, adopted to evaluate the performance of the wavelet function, analysis of variance is used. Genetic algorithm is exploited to optimize the determination of the best mother wavelet function. For experimental evaluation, solutions for best mother wavelet selection are evaluated on various biomedical signal classification problems, where the solutions of the proposed algorithm are assessed and compared with manual hit-and-trial methods. The results show that the solutions of automated mother wavelet selection algorithm are consistent with the manual selection of wavelet functions. The algorithm is found to be invariant to the type of signals used for classification. PMID:26253283
Rigorous estimates for the relegation algorithm
NASA Astrophysics Data System (ADS)
Sansottera, Marco; Ceccaroni, Marta
2016-07-01
We revisit the relegation algorithm by Deprit et al. (Celest. Mech. Dyn. Astron. 79:157-182, 2001) in the light of the rigorous Nekhoroshev's like theory. This relatively recent algorithm is nowadays widely used for implementing closed form analytic perturbation theories, as it generalises the classical Birkhoff normalisation algorithm. The algorithm, here briefly explained by means of Lie transformations, has been so far introduced and used in a formal way, i.e. without providing any rigorous convergence or asymptotic estimates. The overall aim of this paper is to find such quantitative estimates and to show how the results about stability over exponentially long times can be recovered in a simple and effective way, at least in the non-resonant case.
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.
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.
A novel fitness evaluation method for evolutionary algorithms
NASA Astrophysics Data System (ADS)
Wang, Ji-feng; Tang, Ke-zong
2013-03-01
Fitness evaluation is a crucial task in evolutionary algorithms because it can affect the convergence speed and also the quality of the final solution. But these algorithms may require huge computation power for solving nonlinear programming problems. This paper proposes a novel fitness evaluation approach which employs similarity-base learning embedded in a classical differential evolution (SDE) to evaluate all new individuals. Each individual consists of three elements: parameter vector (v), a fitness value (f), and a reliability value(r). The f is calculated using NFEA, and only when the r is below a threshold is the f calculated using true fitness function. Moreover, applying error compensation system to the proposed algorithm further enhances the performance of the algorithm to make r much closer to true fitness value for each new child. Simulation results over a comprehensive set of benchmark functions show that the convergence rate of the proposed algorithm is much faster than much that of the compared algorithms.
A Danger-Theory-Based Immune Network Optimization Algorithm
Li, Tao; Xiao, Xin; Shi, Yuanquan
2013-01-01
Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853
Advances on image interpolation based on ant colony algorithm.
Rukundo, Olivier; Cao, Hanqiang
2016-01-01
This paper presents an advance on image interpolation based on ant colony algorithm (AACA) for high resolution image scaling. The difference between the proposed algorithm and the previously proposed optimization of bilinear interpolation based on ant colony algorithm (OBACA) is that AACA uses global weighting, whereas OBACA uses local weighting scheme. The strength of the proposed global weighting of AACA algorithm depends on employing solely the pheromone matrix information present on any group of four adjacent pixels to decide which case deserves a maximum global weight value or not. Experimental results are further provided to show the higher performance of the proposed AACA algorithm with reference to the algorithms mentioned in this paper. PMID:27047729
An efficient algorithm for function optimization: modified stem cells algorithm
NASA Astrophysics Data System (ADS)
Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad
2013-03-01
In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).
Efficient Record Linkage Algorithms Using Complete Linkage Clustering
Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar
2016-01-01
Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times. PMID:27124604
Adaptive image contrast enhancement algorithm for point-based rendering
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Liu, Xiaoping P.
2015-03-01
Surgical simulation is a major application in computer graphics and virtual reality, and most of the existing work indicates that interactive real-time cutting simulation of soft tissue is a fundamental but challenging research problem in virtual surgery simulation systems. More specifically, it is difficult to achieve a fast enough graphic update rate (at least 30 Hz) on commodity PC hardware by utilizing traditional triangle-based rendering algorithms. In recent years, point-based rendering (PBR) has been shown to offer the potential to outperform the traditional triangle-based rendering in speed when it is applied to highly complex soft tissue cutting models. Nevertheless, the PBR algorithms are still limited in visual quality due to inherent contrast distortion. We propose an adaptive image contrast enhancement algorithm as a postprocessing module for PBR, providing high visual rendering quality as well as acceptable rendering efficiency. Our approach is based on a perceptible image quality technique with automatic parameter selection, resulting in a visual quality comparable to existing conventional PBR algorithms. Experimental results show that our adaptive image contrast enhancement algorithm produces encouraging results both visually and numerically compared to representative algorithms, and experiments conducted on the latest hardware demonstrate that the proposed PBR framework with the postprocessing module is superior to the conventional PBR algorithm and that the proposed contrast enhancement algorithm can be utilized in (or compatible with) various variants of the conventional PBR algorithm.
New Drug Shows Mixed Results Against Early Alzheimer's
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Rashwan, Shaheera; Sarhan, Amany; Faheem, Muhamed Talaat; Youssef, Bayumy A
2015-01-01
Detection and quantification of protein spots is an important issue in the analysis of two-dimensional electrophoresis images. However, there is a main challenge in the segmentation of 2DGE images which is to separate overlapping protein spots correctly and to find the weak protein spots. In this paper, we describe a new robust technique to segment and model the different spots present in the gels. The watershed segmentation algorithm is modified to handle the problem of over-segmentation by initially partitioning the image to mosaic regions using the composition of fuzzy relations. The experimental results showed the effectiveness of the proposed algorithm to overcome the over segmentation problem associated with the available algorithm. We also use a wavelet denoising function to enhance the quality of the segmented image. The results of using a denoising function before the proposed fuzzy watershed segmentation algorithm is promising as they are better than those without denoising. PMID:26510287
NASA Astrophysics Data System (ADS)
Li, Zhaokun; Cao, Jingtai; Liu, Wei; Feng, Jianfeng; Zhao, Xiaohui
2015-03-01
We use conventional adaptive optical system to compensate atmospheric turbulence in free space optical (FSO) communication system under strong scintillation circumstances, undesired wave-front measurements based on Shark-Hartman sensor (SH). Since wavefront sensor-less adaptive optics is a feasible option, we propose several swarm intelligence algorithms to compensate the wavefront aberration from atmospheric interference in FSO and mainly discuss the algorithm principle, basic flows, and simulation result. The numerical simulation experiment and result analysis show that compared with SPGD algorithm, the proposed algorithms can effectively restrain wavefront aberration, and improve convergence rate of the algorithms and the coupling efficiency of receiver in large extent.
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.
Preconditioned quantum linear system algorithm.
Clader, B D; Jacobs, B C; Sprouse, C R
2013-06-21
We describe a quantum algorithm that generalizes the quantum linear system algorithm [Harrow et al., Phys. Rev. Lett. 103, 150502 (2009)] to arbitrary problem specifications. We develop a state preparation routine that can initialize generic states, show how simple ancilla measurements can be used to calculate many quantities of interest, and integrate a quantum-compatible preconditioner that greatly expands the number of problems that can achieve exponential speedup over classical linear systems solvers. To demonstrate the algorithm's applicability, we show how it can be used to compute the electromagnetic scattering cross section of an arbitrary target exponentially faster than the best classical algorithm. PMID:23829722
National Orange Show Photovoltaic Demonstration
Dan Jimenez Sheri Raborn, CPA; Tom Baker
2008-03-31
National Orange Show Photovoltaic Demonstration created a 400KW Photovoltaic self-generation plant at the National Orange Show Events Center (NOS). The NOS owns a 120-acre state fairground where it operates an events center and produces an annual citrus fair known as the Orange Show. The NOS governing board wanted to employ cost-saving programs for annual energy expenses. It is hoped the Photovoltaic program will result in overall savings for the NOS, help reduce the State's energy demands as relating to electrical power consumption, improve quality of life within the affected grid area as well as increase the energy efficiency of buildings at our venue. In addition, the potential to reduce operational expenses would have a tremendous effect on the ability of the NOS to service its community.
Constrained Multiobjective Biogeography Optimization Algorithm
Mo, Hongwei; Xu, Zhidan; Xu, Lifang; Wu, Zhou; Ma, Haiping
2014-01-01
Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate diverse feasible individuals in order to promote the diversity of individuals on Pareto front. Infeasible individuals nearby feasible region are evolved to feasibility by recombining with their nearest nondominated feasible individuals. The convergence of CMBOA is proved by using probability theory. The performance of CMBOA is evaluated on a set of 6 benchmark problems and experimental results show that the CMBOA performs better than or similar to the classical NSGA-II and IS-MOEA. PMID:25006591
Constrained multiobjective biogeography optimization algorithm.
Mo, Hongwei; Xu, Zhidan; Xu, Lifang; Wu, Zhou; Ma, Haiping
2014-01-01
Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate diverse feasible individuals in order to promote the diversity of individuals on Pareto front. Infeasible individuals nearby feasible region are evolved to feasibility by recombining with their nearest nondominated feasible individuals. The convergence of CMBOA is proved by using probability theory. The performance of CMBOA is evaluated on a set of 6 benchmark problems and experimental results show that the CMBOA performs better than or similar to the classical NSGA-II and IS-MOEA. PMID:25006591
Optimisation algorithms for microarray biclustering.
Perrin, Dimitri; Duhamel, Christophe
2013-01-01
In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic Algorithms. We also introduce a new heuristic "Propagate", which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme, optimal or near-optimal solutions can be identified. PMID:24109756
An improved harmony search algorithm with dynamically varying bandwidth
NASA Astrophysics Data System (ADS)
Kalivarapu, J.; Jain, S.; Bag, S.
2016-07-01
The present work demonstrates a new variant of the harmony search (HS) algorithm where bandwidth (BW) is one of the deciding factors for the time complexity and the performance of the algorithm. The BW needs to have both explorative and exploitative characteristics. The ideology is to use a large BW to search in the full domain and to adjust the BW dynamically closer to the optimal solution. After trying a series of approaches, a methodology inspired by the functioning of a low-pass filter showed satisfactory results. This approach was implemented in the self-adaptive improved harmony search (SIHS) algorithm and tested on several benchmark functions. Compared to the existing HS algorithm and its variants, SIHS showed better performance on most of the test functions. Thereafter, the algorithm was applied to geometric parameter optimization of a friction stir welding tool.
Algorithm for shortest path search in Geographic Information Systems by using reduced graphs.
Rodríguez-Puente, Rafael; Lazo-Cortés, Manuel S
2013-01-01
The use of Geographic Information Systems has increased considerably since the eighties and nineties. As one of their most demanding applications we can mention shortest paths search. Several studies about shortest path search show the feasibility of using graphs for this purpose. Dijkstra's algorithm is one of the classic shortest path search algorithms. This algorithm is not well suited for shortest path search in large graphs. This is the reason why various modifications to Dijkstra's algorithm have been proposed by several authors using heuristics to reduce the run time of shortest path search. One of the most used heuristic algorithms is the A* algorithm, the main goal is to reduce the run time by reducing the search space. This article proposes a modification of Dijkstra's shortest path search algorithm in reduced graphs. It shows that the cost of the path found in this work, is equal to the cost of the path found using Dijkstra's algorithm in the original graph. The results of finding the shortest path, applying the proposed algorithm, Dijkstra's algorithm and A* algorithm, are compared. This comparison shows that, by applying the approach proposed, it is possible to obtain the optimal path in a similar or even in less time than when using heuristic algorithms. PMID:24010024
New convergence estimates for multigrid algorithms
Bramble, J.H.; Pasciak, J.E.
1987-10-01
In this paper, new convergence estimates are proved for both symmetric and nonsymmetric multigrid algorithms applied to symmetric positive definite problems. Our theory relates the convergence of multigrid algorithms to a ''regularity and approximation'' parameter ..cap alpha.. epsilon (0, 1) and the number of relaxations m. We show that for the symmetric and nonsymmetric ..nu.. cycles, the multigrid iteration converges for any positive m at a rate which deteriorates no worse than 1-cj/sup -(1-//sup ..cap alpha..//sup )///sup ..cap alpha../, where j is the number of grid levels. We then define a generalized ..nu.. cycle algorithm which involves exponentially increasing (for example, doubling) the number of smoothings on successively coarser grids. We show that the resulting symmetric and nonsymmetric multigrid iterations converge for any ..cap alpha.. with rates that are independent of the mesh size. The theory is presented in an abstract setting which can be applied to finite element multigrid and finite difference multigrid methods.
Evaluating Algorithm Performance Metrics Tailored for Prognostics
NASA Technical Reports Server (NTRS)
Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar; Saha, Sankalita; Goebel, Kai
2009-01-01
Prognostics has taken a center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of the system so that remedial measures may be taken in advance to avoid catastrophic events or unwanted downtimes. Validation of such predictions is an important but difficult proposition and a lack of appropriate evaluation methods renders prognostics meaningless. Evaluation methods currently used in the research community are not standardized and in many cases do not sufficiently assess key performance aspects expected out of a prognostics algorithm. In this paper we introduce several new evaluation metrics tailored for prognostics and show that they can effectively evaluate various algorithms as compared to other conventional metrics. Specifically four algorithms namely; Relevance Vector Machine (RVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Polynomial Regression (PR) are compared. These algorithms vary in complexity and their ability to manage uncertainty around predicted estimates. Results show that the new metrics rank these algorithms in different manner and depending on the requirements and constraints suitable metrics may be chosen. Beyond these results, these metrics offer ideas about how metrics suitable to prognostics may be designed so that the evaluation procedure can be standardized. 1
Fast Optimal Load Balancing Algorithms for 1D Partitioning
Pinar, Ali; Aykanat, Cevdet
2002-12-09
One-dimensional decomposition of nonuniform workload arrays for optimal load balancing is investigated. The problem has been studied in the literature as ''chains-on-chains partitioning'' problem. Despite extensive research efforts, heuristics are still used in parallel computing community with the ''hope'' of good decompositions and the ''myth'' of exact algorithms being hard to implement and not runtime efficient. The main objective of this paper is to show that using exact algorithms instead of heuristics yields significant load balance improvements with negligible increase in preprocessing time. We provide detailed pseudocodes of our algorithms so that our results can be easily reproduced. We start with a review of literature on chains-on-chains partitioning problem. We propose improvements on these algorithms as well as efficient implementation tips. We also introduce novel algorithms, which are asymptotically and runtime efficient. We experimented with data sets from two different applications: Sparse matrix computations and Direct volume rendering. Experiments showed that the proposed algorithms are 100 times faster than a single sparse-matrix vector multiplication for 64-way decompositions on average. Experiments also verify that load balance can be significantly improved by using exact algorithms instead of heuristics. These two findings show that exact algorithms with efficient implementations discussed in this paper can effectively replace heuristics.
Feature Selection via Modified Gravitational Optimization Algorithm
NASA Astrophysics Data System (ADS)
Nabizadeh, Nooshin; John, Nigel
2015-03-01
Feature selection is the process of selecting a subset of relevant and most informative features, which efficiently represents the input data. We proposed a feature selection algorithm based on n-dimensional gravitational optimization algorithm (NGOA), which is based on the principle of gravitational fields. The objective function of optimization algorithm is a non-linear function of variables, which are called masses and defined based on extracted features. The forces between the masses as well as their new locations are calculated using the value of the objective function and the values of masses. We extracted variety of features applying different wavelet transforms and statistical methods on FLAIR and T1-weighted MR brain images. There are two classes of normal and abnormal tissues. Extracted features are divided into groups of five features. The best feature is selected in each group using N-dimensional gravitational optimization algorithm and support vector machine classifier. Then the selected features from each group make several groups of five features again and so on till desired number of features is selected. The advantage of NGOA algorithm is that the possibility of being drawn into a local optimal solution is very low. The experimental results show that our method outperforms some standard feature selection algorithms on both real-data and simulated brain tumor data.
A semantic characterization of an algorithm for estimating others` beliefs from observation
Isozaki, Hideki; Katsuno, Hirofumi
1996-12-31
Human beings often estimate others beliefs and intentions when they interact with others. Estimation of others beliefs will be useful also in controlling the behavior and utterances of artificial agents, especially when lines of communication are unstable or slow. But, devising such estimation algorithms and background theories for the algorithms is difficult, because of many factors affecting one`s belief. We have proposed an algorithm that estimates others beliefs from observation in the changing world. Experimental results show that this algorithm returns natural answers to various queries. However, the algorithm is only heuristic, and how the algorithm deals with beliefs and their changes is not entirely clear. We propose certain semantics based on a nonstandard structure for modal logic. By using these semantics, we shed light on a logical meaning of the belief estimation that the algorithm deals with. We also discuss how the semantics and the algorithm can be generalized.
Simple, fast codebook training algorithm by entropy sequence for vector quantization
NASA Astrophysics Data System (ADS)
Pang, Chao-yang; Yao, Shaowen; Qi, Zhang; Sun, Shi-xin; Liu, Jingde
2001-09-01
The traditional training algorithm for vector quantization such as the LBG algorithm uses the convergence of distortion sequence as the condition of the end of algorithm. We presented a novel training algorithm for vector quantization in this paper. The convergence of the entropy sequence of each region sequence is employed as the condition of the end of the algorithm. Compared with the famous LBG algorithm, it is simple, fast and easy to be comprehended and controlled. We test the performance of the algorithm by typical test image Lena and Barb. The result shows that the PSNR difference between the algorithm and LBG is less than 0.1dB, but the running time of it is at most one second of LBG.
Study of image matching algorithm and sub-pixel fitting algorithm in target tracking
NASA Astrophysics Data System (ADS)
Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu
2015-03-01
Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image
NASA Astrophysics Data System (ADS)
Galica, G. E.; Dichter, B. K.; Tsui, S.; Golightly, M. J.; Lopate, C.; Connell, J. J.
2016-05-01
The space weather instruments (Space Environment In-Situ Suite - SEISS) on the soon to be launched, NOAA GOES-R series spacecraft offer significant space weather measurement performance advances over the previous GOES N-P series instruments. The specifications require that the instruments ensure proper operation under the most stressful high flux conditions corresponding to the largest solar particle event expected during the program, while maintaining high sensitivity at low flux levels. Since the performance of remote sensing instruments is sensitive to local space weather conditions, the SEISS data will be of be of use to a broad community of users. The SEISS suite comprises five individual sensors and a data processing unit: Magnetospheric Particle Sensor-Low (0.03-30 keV electrons and ions), Magnetospheric Particle Sensor-High (0.05-4 MeV electrons, 0.08-12 MeV protons), two Solar And Galactic Proton Sensors (1 to >500 MeV protons), and the Energetic Heavy ion Sensor (10-200 MeV for H, H to Fe with single element resolution). We present comparisons between the enhanced GOES-R instruments and the current GOES space weather measurement capabilities. We provide an overview of the sensor configurations and performance. Results of extensive sensor modeling with GEANT, FLUKA and SIMION are compared with calibration data measured over nearly the entire energy range of the instruments. Combination of the calibration results and model are used to calculate the geometric factors of the various energy channels. The calibrated geometric factors and typical and extreme space weather environments are used to calculate the expected on-orbit performance.
A Hybrid Evolutionary Algorithm for Wheat Blending Problem
Bonyadi, Mohammad Reza; Michalewicz, Zbigniew; Barone, Luigi
2014-01-01
This paper presents a hybrid evolutionary algorithm to deal with the wheat blending problem. The unique constraints of this problem make many existing algorithms fail: either they do not generate acceptable results or they are not able to complete optimization within the required time. The proposed algorithm starts with a filtering process that follows predefined rules to reduce the search space. Then the linear-relaxed version of the problem is solved using a standard linear programming algorithm. The result is used in conjunction with a solution generated by a heuristic method to generate an initial solution. After that, a hybrid of an evolutionary algorithm, a heuristic method, and a linear programming solver is used to improve the quality of the solution. A local search based posttuning method is also incorporated into the algorithm. The proposed algorithm has been tested on artificial test cases and also real data from past years. Results show that the algorithm is able to find quality results in all cases and outperforms the existing method in terms of both quality and speed. PMID:24707222
Self-contained algorithms to detect communities in networks
NASA Astrophysics Data System (ADS)
Castellano, C.; Cecconi, F.; Loreto, V.; Parisi, D.; Radicchi, F.
2004-03-01
The investigation of community structures in networks is an important issue in many domains and disciplines. In this paper we present a new class of local and fast algorithms which incorporate a quantitative definition of community. In this way the algorithms for the identification of the community structure become fully self-contained and one does not need additional non-topological information in order to evaluate the accuracy of the results. The new algorithms are tested on artificial and real-world graphs. In particular we show how the new algorithms apply to a network of scientific collaborations both in the unweighted and in the weighted version. Moreover we discuss the applicability of these algorithms to other non-social networks and we present preliminary results about the detection of community structures in networks of interacting proteins.
NASA Astrophysics Data System (ADS)
Angermann, Lisa; Lewandowski, Jörg; Fleckenstein, Jan H.; Nützmann, Gunnar
2012-12-01
The hyporheic zone is strongly influenced by the adjacent surface water and groundwater systems. It is subject to hydraulic head and pressure fluctuations at different space and time scales, causing dynamic and heterogeneous flow patterns. These patterns are crucial for many biogeochemical processes in the shallow sediment and need to be considered in investigations of this hydraulically dynamic and biogeochemical active interface. For this purpose a device employing heat as an artificial tracer and a data analysis routine were developed. The method aims at measuring hyporheic flow direction and velocity in three dimensions at a scale of a few centimeters. A short heat pulse is injected into the sediment by a point source and its propagation is detected by up to 24 temperature sensors arranged cylindrically around the heater. The resulting breakthrough curves are analyzed using an analytical solution of the heat transport equation. The device was tested in two laboratory flow-through tanks with defined flow velocities and directions. Using different flow situations and sensor arrays the sensitivity of the method was evaluated. After operational reliability was demonstrated in the laboratory, its applicability in the field was tested in the hyporheic zone of a low gradient stream with sandy streambed in NE-Germany. Median and maximum flow velocity in the hyporheic zone at the site were determined as 0.9 × 10-4 and 2.1 × 10-4 m s-1 respectively. Horizontal flow components were found to be spatially very heterogeneous, while vertical flow component appear to be predominantly driven by the streambed morphology.
Nonlinear physical segmentation algorithm for determining the layer boundary from lidar signal.
Mao, Feiyue; Li, Jun; Li, Chen; Gong, Wei; Min, Qilong; Wang, Wei
2015-11-30
Layer boundary (base and top) detection is a basic problem in lidar data processing, the results of which are used as inputs of optical properties retrieval. However, traditional algorithms not only require manual intervention but also rely heavily on the signal-to-noise ratio. Therefore, we propose a robust and automatic algorithm for layer detection based on a novel algorithm for lidar signal segmentation and representation. Our algorithm is based on the lidar equation and avoids most of the limitations of the traditional algorithms. Testing of the simulated and real signals shows that the algorithm is able to position the base and top accurately even with a low signal to noise ratio. Furthermore, the results of the classification are accurate and satisfactory. The experimental results confirm that our algorithm can be used for automatic detection, retrieval, and analysis of lidar data sets. PMID:26698806
NASA Astrophysics Data System (ADS)
Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang; Zilan, Pan; Dawei, Zhang; Xiuhua, Ma
2016-04-01
In order to improve the reconstruction accuracy and reduce the workload, the algorithm of compressive sensing based on the iterative threshold is combined with the method of adaptive selection of the training sample, and a new algorithm of adaptive compressive sensing is put forward. The three kinds of training sample are used to reconstruct the spectral reflectance of the testing sample based on the compressive sensing algorithm and adaptive compressive sensing algorithm, and the color difference and error are compared. The experiment results show that spectral reconstruction precision based on the adaptive compressive sensing algorithm is better than that based on the algorithm of compressive sensing.
Fractal Landscape Algorithms for Environmental Simulations
NASA Astrophysics Data System (ADS)
Mao, H.; Moran, S.
2014-12-01
Natural science and geographical research are now able to take advantage of environmental simulations that more accurately test experimental hypotheses, resulting in deeper understanding. Experiments affected by the natural environment can benefit from 3D landscape simulations capable of simulating a variety of terrains and environmental phenomena. Such simulations can employ random terrain generation algorithms that dynamically simulate environments to test specific models against a variety of factors. Through the use of noise functions such as Perlin noise, Simplex noise, and diamond square algorithms, computers can generate simulations that model a variety of landscapes and ecosystems. This study shows how these algorithms work together to create realistic landscapes. By seeding values into the diamond square algorithm, one can control the shape of landscape. Perlin noise and Simplex noise are also used to simulate moisture and temperature. The smooth gradient created by coherent noise allows more realistic landscapes to be simulated. Terrain generation algorithms can be used in environmental studies and physics simulations. Potential studies that would benefit from simulations include the geophysical impact of flash floods or drought on a particular region and regional impacts on low lying area due to global warming and rising sea levels. Furthermore, terrain generation algorithms also serve as aesthetic tools to display landscapes (Google Earth), and simulate planetary landscapes. Hence, it can be used as a tool to assist science education. Algorithms used to generate these natural phenomena provide scientists a different approach in analyzing our world. The random algorithms used in terrain generation not only contribute to the generating the terrains themselves, but are also capable of simulating weather patterns.
Parallelization of the Pipelined Thomas Algorithm
NASA Technical Reports Server (NTRS)
Povitsky, A.
1998-01-01
In this study the following questions are addressed. Is it possible to improve the parallelization efficiency of the Thomas algorithm? How should the Thomas algorithm be formulated in order to get solved lines that are used as data for other computational tasks while processors are idle? To answer these questions, two-step pipelined algorithms (PAs) are introduced formally. It is shown that the idle processor time is invariant with respect to the order of backward and forward steps in PAs starting from one outermost processor. The advantage of PAs starting from two outermost processors is small. Versions of the pipelined Thomas algorithms considered here fall into the category of PAs. These results show that the parallelization efficiency of the Thomas algorithm cannot be improved directly. However, the processor idle time can be used if some data has been computed by the time processors become idle. To achieve this goal the Immediate Backward pipelined Thomas Algorithm (IB-PTA) is developed in this article. The backward step is computed immediately after the forward step has been completed for the first portion of lines. This enables the completion of the Thomas algorithm for some of these lines before processors become idle. An algorithm for generating a static processor schedule recursively is developed. This schedule is used to switch between forward and backward computations and to control communications between processors. The advantage of the IB-PTA over the basic PTA is the presence of solved lines, which are available for other computations, by the time processors become idle.
Faster Parameterized Algorithms for Minor Containment
NASA Astrophysics Data System (ADS)
Adler, Isolde; Dorn, Frederic; Fomin, Fedor V.; Sau, Ignasi; Thilikos, Dimitrios M.
The theory of Graph Minors by Robertson and Seymour is one of the deepest and significant theories in modern Combinatorics. This theory has also a strong impact on the recent development of Algorithms, and several areas, like Parameterized Complexity, have roots in Graph Minors. Until very recently it was a common belief that Graph Minors Theory is mainly of theoretical importance. However, it appears that many deep results from Robertson and Seymour's theory can be also used in the design of practical algorithms. Minor containment testing is one of algorithmically most important and technical parts of the theory, and minor containment in graphs of bounded branchwidth is a basic ingredient of this algorithm. In order to implement minor containment testing on graphs of bounded branchwidth, Hicks [NETWORKS 04] described an algorithm, that in time O(3^{k^2}\\cdot (h+k-1)!\\cdot m) decides if a graph G with m edges and branchwidth k, contains a fixed graph H on h vertices as a minor. That algorithm follows the ideas introduced by Robertson and Seymour in [J'CTSB 95]. In this work we improve the dependence on k of Hicks' result by showing that checking if H is a minor of G can be done in time O(2^{(2k +1 )\\cdot log k} \\cdot h^{2k} \\cdot 2^{2h^2} \\cdot m). Our approach is based on a combinatorial object called rooted packing, which captures the properties of the potential models of subgraphs of H that we seek in our dynamic programming algorithm. This formulation with rooted packings allows us to speed up the algorithm when G is embedded in a fixed surface, obtaining the first single-exponential algorithm for minor containment testing. Namely, it runs in time 2^{O(k)} \\cdot h^{2k} \\cdot 2^{O(h)} \\cdot n, with n = |V(G)|. Finally, we show that slight modifications of our algorithm permit to solve some related problems within the same time bounds, like induced minor or contraction minor containment.
A clustering routing algorithm based on improved ant colony clustering for wireless sensor networks
NASA Astrophysics Data System (ADS)
Xiao, Xiaoli; Li, Yang
Because of real wireless sensor network node distribution uniformity, this paper presents a clustering strategy based on the ant colony clustering algorithm (ACC-C). To reduce the energy consumption of the head near the base station and the whole network, The algorithm uses ant colony clustering on non-uniform clustering. The improve route optimal degree is presented to evaluate the performance of the chosen route. Simulation results show that, compared with other algorithms, like the LEACH algorithm and the improve particle cluster kind of clustering algorithm (PSC - C), the proposed approach is able to keep away from the node with less residual energy, which can improve the life of networks.
An Adaptive RFID Anti-Collision Algorithm Based on Dynamic Framed ALOHA
NASA Astrophysics Data System (ADS)
Lee, Chang Woo; Cho, Hyeonwoo; Kim, Sang Woo
The collision of ID signals from a large number of colocated passive RFID tags is a serious problem; to realize a practical RFID systems we need an effective anti-collision algorithm. This letter presents an adaptive algorithm to minimize the total time slots and the number of rounds required for identifying the tags within the RFID reader's interrogation zone. The proposed algorithm is based on the framed ALOHA protocol, and the frame size is adaptively updated each round. Simulation results show that our proposed algorithm is more efficient than the conventional algorithms based on the framed ALOHA.
Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling
Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang
2014-01-01
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220
Wang, Lei-Guang; Zheng, Chen; Lin, Li-Yu; Chen, Rong-Yuan; Mei, Tian-Can
2011-01-01
Mean Shift algorithm is a robust approach toward feature space analysis and it has been used wildly for natural scene image and medical image segmentation. However, high computational complexity of the algorithm has constrained its application in remote sensing images with massive information. A fast image segmentation algorithm is presented by extending traditional mean shift method to wavelet domain. In order to evaluate the effectiveness of the proposed algorithm, multispectral remote sensing image and synthetic image are utilized. The results show that the proposed algorithm can improve the speed 5-7 times compared to the traditional MS method in the premise of segmentation quality assurance. PMID:21428083
Power spectral estimation algorithms
NASA Technical Reports Server (NTRS)
Bhatia, Manjit S.
1989-01-01
Algorithms to estimate the power spectrum using Maximum Entropy Methods were developed. These algorithms were coded in FORTRAN 77 and were implemented on the VAX 780. The important considerations in this analysis are: (1) resolution, i.e., how close in frequency two spectral components can be spaced and still be identified; (2) dynamic range, i.e., how small a spectral peak can be, relative to the largest, and still be observed in the spectra; and (3) variance, i.e., how accurate the estimate of the spectra is to the actual spectra. The application of the algorithms based on Maximum Entropy Methods to a variety of data shows that these criteria are met quite well. Additional work in this direction would help confirm the findings. All of the software developed was turned over to the technical monitor. A copy of a typical program is included. Some of the actual data and graphs used on this data are also included.
Chandrasekhar, Jaya; Baber, Usman; Mehran, Roxana; Aquino, Melissa; Sartori, Samantha; Yu, Jennifer; Kini, Annapoorna; Sharma, Samin; Skurk, Carsten; Shlofmitz, Richard A; Witzenbichler, Bernhard; Dangas, George
2016-08-01
Assessment of platelet reactivity alone for thienopyridine selection with percutaneous coronary intervention (PCI) has not been associated with improved outcomes. In TRIAGE, a prospective multicenter observational pilot study we sought to evaluate the benefit of an integrated algorithm combining clinical risk and platelet function testing to select type of thienopyridine in patients undergoing PCI. Patients on chronic clopidogrel therapy underwent platelet function testing prior to PCI using the VerifyNow assay to determine high on treatment platelet reactivity (HTPR, ≥230 P2Y12 reactivity units or PRU). Based on both PRU and clinical (ischemic and bleeding) risks, patients were switched to prasugrel or continued on clopidogrel per the study algorithm. The primary endpoints were (i) 1-year major adverse cardiovascular events (MACE) composite of death, non-fatal myocardial infarction, or definite or probable stent thrombosis; and (ii) major bleeding, Bleeding Academic Research Consortium type 2, 3 or 5. Out of 318 clopidogrel treated patients with a mean age of 65.9 ± 9.8 years, HTPR was noted in 33.3 %. Ninety (28.0 %) patients overall were switched to prasugrel and 228 (72.0 %) continued clopidogrel. The prasugrel group had fewer smokers and more patients with heart failure. At 1-year MACE occurred in 4.4 % of majority HTPR patients on prasugrel versus 3.5 % of primarily non-HTPR patients on clopidogrel (p = 0.7). Major bleeding (5.6 vs 7.9 %, p = 0.47) was numerically higher with clopidogrel compared with prasugrel. Use of the study clinical risk algorithm for choice and intensity of thienopyridine prescription following PCI resulted in similar ischemic outcomes in HTPR patients receiving prasugrel and primarily non-HTPR patients on clopidogrel without an untoward increase in bleeding with prasugrel. However, the study was prematurely terminated and these findings are therefore hypothesis generating. PMID:27100112
Statistical pattern recognition algorithms for autofluorescence imaging
NASA Astrophysics Data System (ADS)
Kulas, Zbigniew; Bereś-Pawlik, Elżbieta; Wierzbicki, Jarosław
2009-02-01
In cancer diagnostics the most important problems are the early identification and estimation of the tumor growth and spread in order to determine the area to be operated. The aim of the work was to design of statistical algorithms helping doctors to objectively estimate pathologically changed areas and to assess the disease advancement. In the research, algorithms for classifying endoscopic autofluorescence images of larynx and intestine were used. The results show that the statistical pattern recognition offers new possibilities for endoscopic diagnostics and can be of a tremendous help in assessing the area of the pathological changes.
Speckle imaging algorithms for planetary imaging
Johansson, E.
1994-11-15
I will discuss the speckle imaging algorithms used to process images of the impact sites of the collision of comet Shoemaker-Levy 9 with Jupiter. The algorithms use a phase retrieval process based on the average bispectrum of the speckle image data. High resolution images are produced by estimating the Fourier magnitude and Fourier phase of the image separately, then combining them and inverse transforming to achieve the final result. I will show raw speckle image data and high-resolution image reconstructions from our recent experiment at Lick Observatory.
Case study of isosurface extraction algorithm performance
Sutton, P M; Hansen, C D; Shen, H; Schikore, D
1999-12-14
Isosurface extraction is an important and useful visualization method. Over the past ten years, the field has seen numerous isosurface techniques published leaving the user in a quandary about which one should be used. Some papers have published complexity analysis of the techniques yet empirical evidence comparing different methods is lacking. This case study presents a comparative study of several representative isosurface extraction algorithms. It reports and analyzes empirical measurements of execution times and memory behavior for each algorithm. The results show that asymptotically optimal techniques may not be the best choice when implemented on modern computer architectures.
Satellite mission scheduling algorithm based on GA
NASA Astrophysics Data System (ADS)
Sun, Baolin; Mao, Lifei; Wang, Wenxiang; Xie, Xing; Qin, Qianqing
2007-11-01
The Satellite Mission Scheduling problem (SMS) involves scheduling tasks to be performed by a satellite, where new task requests can arrive at any time, non-deterministically, and must be scheduled in real-time. This paper describes a new Satellite Mission Scheduling problem based on Genetic Algorithm (SMSGA). In this paper, it investigates algorithmic approaches for determining an optimal or near-optimal sequence of tasks, allocated to a satellite payload over time, with dynamic tasking considerations. The simulation results show that the proposed approach is effective and efficient in applications to the real problems.
Evaluation of feedback-reduction algorithms for hearing aids.
Greenberg, J E; Zurek, P M; Brantley, M
2000-11-01
Three adaptive feedback-reduction algorithms were implemented in a laboratory-based digital hearing aid system and evaluated with dynamic feedback paths and hearing-impaired subjects. The evaluation included measurements of maximum stable gain and subjective quality ratings. The continuously adapting CNN algorithm (Closed-loop processing with No probe Noise) provided the best performance: 8.5 dB of added stable gain (ASG) relative to a reference algorithm averaged over all subjects, ears, and vent conditions. Two intermittently adapting algorithms, ONO (Open-loop with Noise when Oscillation detected) and ONQ (Open-loop with Noise when Quiet detected), provided an average of 5 dB of ASG. Subjects with more severe hearing losses received greater benefits: 13 dB average ASG for the CNN algorithm and 7-8 dB average ASG for the ONO and ONQ algorithms. These values are conservative estimates of ASG because the fitting procedure produced a frequency-gain characteristic that already included precautions against feedback. Speech quality ratings showed no substantial algorithm effect on pleasantness or intelligibility, although subjects informally expressed strong objections to the probe noise used by the ONO and ONQ algorithms. This objection was not reflected in the speech quality ratings because of limitations of the experimental procedure. The results clearly indicate that the CNN algorithm is the most promising choice for adaptive feedback reduction in hearing aids. PMID:11108377
Extended Relief-F Algorithm for Nominal Attribute Estimation in Small-Document Classification
NASA Astrophysics Data System (ADS)
Park, Heum; Kwon, Hyuk-Chul
This paper presents an extended Relief-F algorithm for nominal attribute estimation, for application to small-document classification. Relief algorithms are general and successful instance-based feature-filtering algorithms for data classification and regression. Many improved Relief algorithms have been introduced as solutions to problems of redundancy and irrelevant noisy features and to the limitations of the algorithms for multiclass datasets. However, these algorithms have only rarely been applied to text classification, because the numerous features in multiclass datasets lead to great time complexity. Therefore, in considering their application to text feature filtering and classification, we presented an extended Relief-F algorithm for numerical attribute estimation (E-Relief-F) in 2007. However, we found limitations and some problems with it. Therefore, in this paper, we introduce additional problems with Relief algorithms for text feature filtering, including the negative influence of computation similarities and weights caused by a small number of features in an instance, the absence of nearest hits and misses for some instances, and great time complexity. We then suggest a new extended Relief-F algorithm for nominal attribute estimation (E-Relief-Fd) to solve these problems, and we apply it to small text-document classification. We used the algorithm in experiments to estimate feature quality for various datasets, its application to classification, and its performance in comparison with existing Relief algorithms. The experimental results show that the new E-Relief-Fd algorithm offers better performance than previous Relief algorithms, including E-Relief-F.
Honey Bees Inspired Optimization Method: The Bees Algorithm.
Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo
2013-01-01
Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem. PMID:26462528
Wavelet Algorithms for Illumination Computations
NASA Astrophysics Data System (ADS)
Schroder, Peter
One of the core problems of computer graphics is the computation of the equilibrium distribution of light in a scene. This distribution is given as the solution to a Fredholm integral equation of the second kind involving an integral over all surfaces in the scene. In the general case such solutions can only be numerically approximated, and are generally costly to compute, due to the geometric complexity of typical computer graphics scenes. For this computation both Monte Carlo and finite element techniques (or hybrid approaches) are typically used. A simplified version of the illumination problem is known as radiosity, which assumes that all surfaces are diffuse reflectors. For this case hierarchical techniques, first introduced by Hanrahan et al. (32), have recently gained prominence. The hierarchical approaches lead to an asymptotic improvement when only finite precision is required. The resulting algorithms have cost proportional to O(k^2 + n) versus the usual O(n^2) (k is the number of input surfaces, n the number of finite elements into which the input surfaces are meshed). Similarly a hierarchical technique has been introduced for the more general radiance problem (which allows glossy reflectors) by Aupperle et al. (6). In this dissertation we show the equivalence of these hierarchical techniques to the use of a Haar wavelet basis in a general Galerkin framework. By so doing, we come to a deeper understanding of the properties of the numerical approximations used and are able to extend the hierarchical techniques to higher orders. In particular, we show the correspondence of the geometric arguments underlying hierarchical methods to the theory of Calderon-Zygmund operators and their sparse realization in wavelet bases. The resulting wavelet algorithms for radiosity and radiance are analyzed and numerical results achieved with our implementation are reported. We find that the resulting algorithms achieve smaller and smoother errors at equivalent work.
Flocking algorithm for autonomous flying robots.
Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, Tamás; Somorjai, Gergő; Nepusz, Tamás; Vicsek, Tamás
2014-06-01
Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks. PMID:24852272
NASA Astrophysics Data System (ADS)
Que, Dashun; Li, Gang; Yue, Peng
2007-12-01
An adaptive optimization watermarking algorithm based on Genetic Algorithm (GA) and discrete wavelet transform (DWT) is proposed in this paper. The core of this algorithm is the fitness function optimization model for digital watermarking based on GA. The embedding intensity for digital watermarking can be modified adaptively, and the algorithm can effectively ensure the imperceptibility of watermarking while the robustness is ensured. The optimization model research may provide a new idea for anti-coalition attacks of digital watermarking algorithm. The paper has fulfilled many experiments, including the embedding and extracting experiments of watermarking, the influence experiments by the weighting factor, the experiments of embedding same watermarking to the different cover image, the experiments of embedding different watermarking to the same cover image, the comparative analysis experiments between this optimization algorithm and human visual system (HVS) algorithm and etc. The simulation results and the further analysis show the effectiveness and advantage of the new algorithm, which also has versatility and expandability. And meanwhile it has better ability of anti-coalition attacks. Moreover, the robustness and security of watermarking algorithm are improved by scrambling transformation and chaotic encryption while preprocessing the watermarking.
Restarted local search algorithms for continuous black box optimization.
Pošík, Petr; Huyer, Waltraud
2012-01-01
Several local search algorithms for real-valued domains (axis parallel line search, Nelder-Mead simplex search, Rosenbrock's algorithm, quasi-Newton method, NEWUOA, and VXQR) are described and thoroughly compared in this article, embedding them in a multi-start method. Their comparison aims (1) to help the researchers from the evolutionary community to choose the right opponent for their algorithm (to choose an opponent that would constitute a hard-to-beat baseline algorithm), (2) to describe individual features of these algorithms and show how they influence the algorithm on different problems, and (3) to provide inspiration for the hybridization of evolutionary algorithms with these local optimizers. The recently proposed Comparing Continuous Optimizers (COCO) methodology was adopted as the basis for the comparison. The results show that in low dimensional spaces, the old method of Nelder and Mead is still the most successful among those compared, while in spaces of higher dimensions, it is better to choose an algorithm based on quadratic modeling, such as NEWUOA or a quasi-Newton method. PMID:22779407
Constant Modulus Algorithm with Reduced Complexity Employing DFT Domain Fast Filtering
NASA Astrophysics Data System (ADS)
Yang, Yoon Gi; Lee, Chang Su; Yang, Soo Mi
In this paper, a novel CMA (constant modulus algorithm) algorithm employing fast convolution in the DFT (discrete Fourier transform) domain is proposed. We propose a non-linear adaptation algorithm that minimizes CMA cost function in the DFT domain. The proposed algorithm is completely new one as compared to the recently introduced similar DFT domain CMA algorithm in that, the original CMA cost function has not been changed to develop DFT domain algorithm, resulting improved convergence properties. Using the proposed approach, we can reduce the number of multiplications to O(N log 2 N), whereas the conventional CMA has the computation order of O(N2). Simulation results show that the proposed algorithm provides a comparable performance to the conventional CMA.
On Learning Algorithms for Nash Equilibria
NASA Astrophysics Data System (ADS)
Daskalakis, Constantinos; Frongillo, Rafael; Papadimitriou, Christos H.; Pierrakos, George; Valiant, Gregory
Can learning algorithms find a Nash equilibrium? This is a natural question for several reasons. Learning algorithms resemble the behavior of players in many naturally arising games, and thus results on the convergence or non-convergence properties of such dynamics may inform our understanding of the applicability of Nash equilibria as a plausible solution concept in some settings. A second reason for asking this question is in the hope of being able to prove an impossibility result, not dependent on complexity assumptions, for computing Nash equilibria via a restricted class of reasonable algorithms. In this work, we begin to answer this question by considering the dynamics of the standard multiplicative weights update learning algorithms (which are known to converge to a Nash equilibrium for zero-sum games). We revisit a 3×3 game defined by Shapley [10] in the 1950s in order to establish that fictitious play does not converge in general games. For this simple game, we show via a potential function argument that in a variety of settings the multiplicative updates algorithm impressively fails to find the unique Nash equilibrium, in that the cumulative distributions of players produced by learning dynamics actually drift away from the equilibrium.
Decryption of pure-position permutation algorithms.
Zhao, Xiao-Yu; Chen, Gang; Zhang, Dan; Wang, Xiao-Hong; Dong, Guang-Chang
2004-07-01
Pure position permutation image encryption algorithms, commonly used as image encryption investigated in this work are unfortunately frail under known-text attack. In view of the weakness of pure position permutation algorithm, we put forward an effective decryption algorithm for all pure-position permutation algorithms. First, a summary of the pure position permutation image encryption algorithms is given by introducing the concept of ergodic matrices. Then, by using probability theory and algebraic principles, the decryption probability of pure-position permutation algorithms is verified theoretically; and then, by defining the operation system of fuzzy ergodic matrices, we improve a specific decryption algorithm. Finally, some simulation results are shown. PMID:15495308
Simple-random-sampling-based multiclass text classification algorithm.
Liu, Wuying; Wang, Lin; Yi, Mianzhu
2014-01-01
Multiclass text classification (MTC) is a challenging issue and the corresponding MTC algorithms can be used in many applications. The space-time overhead of the algorithms must be concerned about the era of big data. Through the investigation of the token frequency distribution in a Chinese web document collection, this paper reexamines the power law and proposes a simple-random-sampling-based MTC (SRSMTC) algorithm. Supported by a token level memory to store labeled documents, the SRSMTC algorithm uses a text retrieval approach to solve text classification problems. The experimental results on the TanCorp data set show that SRSMTC algorithm can achieve the state-of-the-art performance at greatly reduced space-time requirements. PMID:24778587
A Novel Particle Swarm Optimization Algorithm for Global Optimization
Wang, Chun-Feng; Liu, Kui
2016-01-01
Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms. PMID:26955387
A Novel Particle Swarm Optimization Algorithm for Global Optimization.
Wang, Chun-Feng; Liu, Kui
2016-01-01
Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms. PMID:26955387
Time optimal route planning algorithm of LBS online navigation
NASA Astrophysics Data System (ADS)
Li, Yong; Bao, Shitai; Su, Kui; Fang, Qiushui; Yang, Jingfeng
2011-02-01
This paper proposes a time optimal route planning optimization algorithm in the mode of LBS online navigation based on the improved Dijkstra algorithms. Combined with the returning real-time location information by on-line users' handheld terminals, the algorithm can satisfy requirement of the optimal time in the mode of LBS online navigation. A navigation system is developed and applied in actual navigation operations. Operating results show that the algorithm could form a reasonable coordination on the basis of shortest route and fastest velocity in the requirement of optimal time. The algorithm could also store the calculated real-time route information in the cache to improve the efficiency of route planning and to reduce the planning time-consuming.
A simulation algorithm for ultrasound liver backscattered signals.
Zatari, D; Botros, N; Dunn, F
1995-11-01
In this study, we present a simulation algorithm for the backscattered ultrasound signal from liver tissue. The algorithm simulates backscattered signals from normal liver and three different liver abnormalities. The performance of the algorithm has been tested by statistically comparing the simulated signals with corresponding signals obtained from a previous in vivo study. To verify that the simulated signals can be classified correctly we have applied a classification technique based on an artificial neural network. The acoustic features extracted from the spectrum over a 2.5 MHz bandwidth are the attenuation coefficient and the change of speed of sound with frequency (dispersion). Our results show that the algorithm performs satisfactorily. Further testing of the algorithm is conducted by the use of a data acquisition and analysis system designed by the authors, where several simulated signals are stored in memory chips and classified according to their abnormalities. PMID:8560631
Simple-Random-Sampling-Based Multiclass Text Classification Algorithm
Liu, Wuying; Wang, Lin; Yi, Mianzhu
2014-01-01
Multiclass text classification (MTC) is a challenging issue and the corresponding MTC algorithms can be used in many applications. The space-time overhead of the algorithms must be concerned about the era of big data. Through the investigation of the token frequency distribution in a Chinese web document collection, this paper reexamines the power law and proposes a simple-random-sampling-based MTC (SRSMTC) algorithm. Supported by a token level memory to store labeled documents, the SRSMTC algorithm uses a text retrieval approach to solve text classification problems. The experimental results on the TanCorp data set show that SRSMTC algorithm can achieve the state-of-the-art performance at greatly reduced space-time requirements. PMID:24778587
An algorithm to retrieve precipitation with synthetic aperture radar
NASA Astrophysics Data System (ADS)
Xie, Ya'nan; Liu, Zhikun; An, Dawei
2016-06-01
This paper presents a new type of rainfall retrieval algorithm, called the model-oriented statistical and Volterra integration. It is a combination of the model-oriented statistical (MOS) and Volterra integral equation (VIE) approaches. The steps involved in this new algorithm can be briefly illustrated as follows. Firstly, information such as the start point and width of the rain is obtained through pre-analysis of the data received by synthetic aperture radar (SAR). Secondly, the VIE retrieval algorithm is employed over a short distance to obtain information on the shape of the rain. Finally, the rain rate can be calculated by using the MOS retrieval algorithm. Simulation results show that the proposed algorithm is effective and simple, and can lead to time savings of nearly 50% compared with MOS. An example of application of SAR data is also discussed, involving the retrieval of precipitation information over the South China Sea.
The Chopthin Algorithm for Resampling
NASA Astrophysics Data System (ADS)
Gandy, Axel; Lau, F. Din-Houn
2016-08-01
Resampling is a standard step in particle filters and more generally sequential Monte Carlo methods. We present an algorithm, called chopthin, for resampling weighted particles. In contrast to standard resampling methods the algorithm does not produce a set of equally weighted particles; instead it merely enforces an upper bound on the ratio between the weights. Simulation studies show that the chopthin algorithm consistently outperforms standard resampling methods. The algorithms chops up particles with large weight and thins out particles with low weight, hence its name. It implicitly guarantees a lower bound on the effective sample size. The algorithm can be implemented efficiently, making it practically useful. We show that the expected computational effort is linear in the number of particles. Implementations for C++, R (on CRAN), Python and Matlab are available.
VIEW SHOWING WEST ELEVATION, EAST SIDE OF MEYER AVENUE. SHOWS ...
VIEW SHOWING WEST ELEVATION, EAST SIDE OF MEYER AVENUE. SHOWS 499-501, MUNOZ HOUSE (AZ-73-37) ON FAR RIGHT - Antonio Bustamente House, 485-489 South Meyer Avenue & 186 West Kennedy Street, Tucson, Pima County, AZ
General cardinality genetic algorithms
Koehler; Bhattacharyya; Vose
1997-01-01
A complete generalization of the Vose genetic algorithm model from the binary to higher cardinality case is provided. Boolean AND and EXCLUSIVE-OR operators are replaced by multiplication and addition over rings of integers. Walsh matrices are generalized with finite Fourier transforms for higher cardinality usage. Comparison of results to the binary case are provided. PMID:10021767
A novel bee swarm optimization algorithm for numerical function optimization
NASA Astrophysics Data System (ADS)
Akbari, Reza; Mohammadi, Alireza; Ziarati, Koorush
2010-10-01
The optimization algorithms which are inspired from intelligent behavior of honey bees are among the most recently introduced population based techniques. In this paper, a novel algorithm called bee swarm optimization, or BSO, and its two extensions for improving its performance are presented. The BSO is a population based optimization technique which is inspired from foraging behavior of honey bees. The proposed approach provides different patterns which are used by the bees to adjust their flying trajectories. As the first extension, the BSO algorithm introduces different approaches such as repulsion factor and penalizing fitness (RP) to mitigate the stagnation problem. Second, to maintain efficiently the balance between exploration and exploitation, time-varying weights (TVW) are introduced into the BSO algorithm. The proposed algorithm (BSO) and its two extensions (BSO-RP and BSO-RPTVW) are compared with existing algorithms which are based on intelligent behavior of honey bees, on a set of well known numerical test functions. The experimental results show that the BSO algorithms are effective and robust; produce excellent results, and outperform other algorithms investigated in this consideration.
Improved Ant Colony Clustering Algorithm and Its Performance Study.
Gao, Wei
2016-01-01
Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533
Improved Ant Colony Clustering Algorithm and Its Performance Study
Gao, Wei
2016-01-01
Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533
15. Detail showing lower chord pinconnected to vertical member, showing ...
15. Detail showing lower chord pin-connected to vertical member, showing floor beam riveted to extension of vertical member below pin-connection, and showing brackets supporting cantilevered sidewalk. View to southwest. - Selby Avenue Bridge, Spanning Short Line Railways track at Selby Avenue between Hamline & Snelling Avenues, Saint Paul, Ramsey County, MN
Parameter identification using a creeping-random-search algorithm
NASA Technical Reports Server (NTRS)
Parrish, R. V.
1971-01-01
A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.
Semi-flocking algorithm for motion control of mobile sensors in large-scale surveillance systems.
Semnani, Samaneh Hosseini; Basir, Otman A
2015-01-01
The ability of sensors to self-organize is an important asset in surveillance sensor networks. Self-organize implies self-control at the sensor level and coordination at the network level. Biologically inspired approaches have recently gained significant attention as a tool to address the issue of sensor control and coordination in sensor networks. These approaches are exemplified by the two well-known algorithms, namely, the Flocking algorithm and the Anti-Flocking algorithm. Generally speaking, although these two biologically inspired algorithms have demonstrated promising performance, they expose deficiencies when it comes to their ability to maintain simultaneous robust dynamic area coverage and target coverage. These two coverage performance objectives are inherently conflicting. This paper presents Semi-Flocking, a biologically inspired algorithm that benefits from key characteristics of both the Flocking and Anti-Flocking algorithms. The Semi-Flocking algorithm approaches the problem by assigning a small flock of sensors to each target, while at the same time leaving some sensors free to explore the environment. This allows the algorithm to strike balance between robust area coverage and target coverage. Such balance is facilitated via flock-sensor coordination. The performance of the proposed Semi-Flocking algorithm is examined and compared with other two flocking-based algorithms once using randomly moving targets and once using a standard walking pedestrian dataset. The results of both experiments show that the Semi-Flocking algorithm outperforms both the Flocking algorithm and the Anti-Flocking algorithm with respect to the area of coverage and the target coverage objectives. Furthermore, the results show that the proposed algorithm demonstrates shorter target detection time and fewer undetected targets than the other two flocking-based algorithms. PMID:25014985
Styopin, Nikita E; Vershinin, Anatoly V; Zingerman, Konstantin M; Levin, Vladimir A
2016-09-01
Different variants of the Uzawa algorithm are compared with one another. The comparison is performed for the case in which this algorithm is applied to large-scale systems of linear algebraic equations. These systems arise in the finite-element solution of the problems of elasticity theory for incompressible materials. A modification of the Uzawa algorithm is proposed. Computational experiments show that this modification improves the convergence of the Uzawa algorithm for the problems of solid mechanics. The results of computational experiments show that each variant of the Uzawa algorithm considered has its advantages and disadvantages and may be convenient in one case or another. PMID:27595019
Messy genetic algorithms: Recent developments
Kargupta, H.
1996-09-01
Messy genetic algorithms define a rare class of algorithms that realize the need for detecting appropriate relations among members of the search domain in optimization. This paper reviews earlier works in messy genetic algorithms and describes some recent developments. It also describes the gene expression messy GA (GEMGA)--an {Omicron}({Lambda}{sup {kappa}}({ell}{sup 2} + {kappa})) sample complexity algorithm for the class of order-{kappa} delineable problems (problems that can be solved by considering no higher than order-{kappa} relations) of size {ell} and alphabet size {Lambda}. Experimental results are presented to demonstrate the scalability of the GEMGA.
Ebtehaj, Isa; Bonakdari, Hossein
2014-01-01
The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations. PMID:25429460
Castañeda-Villa, N; James, C J
2008-01-01
Many authors have used the Auditory Evoked Potential (AEP) recordings to evaluate the performance of their ICA algorithms and have demonstrated that this procedure can remove the typical EEG artifact in these recordings (i.e. blinking, muscle noise, line noise, etc.). However, there is little work in the literature about the optimal parameters, for each of those algorithms, for the estimation of the AEP components to reliably recover both the auditory response and the specific artifacts generated for the normal function of a Cochlear Implant (CI), used for the rehabilitation of deaf people. In this work we determine the optimal parameters of three ICA algorithms, each based on different independence criteria, and assess the resulting estimations of both the auditory response and CI artifact. We show that the algorithm utilizing temporal structure, such as TDSEP-ICA, is better in estimating the components of the auditory response, in recordings contaminated by CI artifacts, than higher order statistics based algorithms. PMID:19163893
YAMPA: Yet Another Matching Pursuit Algorithm for compressive sensing
NASA Astrophysics Data System (ADS)
Lodhi, Muhammad A.; Voronin, Sergey; Bajwa, Waheed U.
2016-05-01
State-of-the-art sparse recovery methods often rely on the restricted isometry property for their theoretical guarantees. However, they cannot explicitly incorporate metrics such as restricted isometry constants within their recovery procedures due to the computational intractability of calculating such metrics. This paper formulates an iterative algorithm, termed yet another matching pursuit algorithm (YAMPA), for recovery of sparse signals from compressive measurements. YAMPA differs from other pursuit algorithms in that: (i) it adapts to the measurement matrix using a threshold that is explicitly dependent on two computable coherence metrics of the matrix, and (ii) it does not require knowledge of the signal sparsity. Performance comparisons of YAMPA against other matching pursuit and approximate message passing algorithms are made for several types of measurement matrices. These results show that while state-of-the-art approximate message passing algorithms outperform other algorithms (including YAMPA) in the case of well-conditioned random matrices, they completely break down in the case of ill-conditioned measurement matrices. On the other hand, YAMPA and comparable pursuit algorithms not only result in reasonable performance for well-conditioned matrices, but their performance also degrades gracefully for ill-conditioned matrices. The paper also shows that YAMPA uniformly outperforms other pursuit algorithms for the case of thresholding parameters chosen in a clairvoyant fashion. Further, when combined with a simple and fast technique for selecting thresholding parameters in the case of ill-conditioned matrices, YAMPA outperforms other pursuit algorithms in the regime of low undersampling, although some of these algorithms can outperform YAMPA in the regime of high undersampling in this setting.
A limited-memory algorithm for bound-constrained optimization
Byrd, R.H.; Peihuang, L.; Nocedal, J. |
1996-03-01
An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited-memory BFGS matrix to approximate the Hessian of the objective function. We show how to take advantage of the form of the limited-memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.
GASAT: a genetic local search algorithm for the satisfiability problem.
Lardeux, Frédéric; Saubion, Frédéric; Hao, Jin-Kao
2006-01-01
This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results. PMID:16831107
Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems
NASA Astrophysics Data System (ADS)
Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao
Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.
Economic load dispatch using improved gravitational search algorithm
NASA Astrophysics Data System (ADS)
Huang, Yu; Wang, Jia-rong; Guo, Feng
2016-03-01
This paper presents an improved gravitational search algorithm(IGSA) to solve the economic load dispatch(ELD) problem. In order to avoid the local optimum phenomenon, mutation processing is applied to the GSA. The IGSA is applied to solve the economic load dispatch problems with the valve point effects, which has 13 generators and a load demand of 2520 MW. Calculation results show that the algorithm in this paper can deal with the ELD problems with high stability.
Effect of object identification algorithms on feature based verification scores
NASA Astrophysics Data System (ADS)
Weniger, Michael; Friederichs, Petra
2015-04-01
Many modern spatial verification techniques rely on feature identification algorithms. We study the importance of the choice of algorithm and its parameters for the resulting scores. SAL is used as an example to show that these choices have a statistically significant impact on the distributions of object dependent scores. Non-continuous operators used for feature identification are identified as the underlying reason for the observed stability issues, with implications for many feature based verification techniques.
SAGE II inversion algorithm. [Stratospheric Aerosol and Gas Experiment
NASA Technical Reports Server (NTRS)
Chu, W. P.; Mccormick, M. P.; Lenoble, J.; Brogniez, C.; Pruvost, P.
1989-01-01
The operational Stratospheric Aerosol and Gas Experiment II multichannel data inversion algorithm is described. Aerosol and ozone retrievals obtained with the algorithm are discussed. The algorithm is compared to an independently developed algorithm (Lenoble, 1989), showing that the inverted aerosol and ozone profiles from the two algorithms are similar within their respective uncertainties.
Fast image matching algorithm based on projection characteristics
NASA Astrophysics Data System (ADS)
Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun
2011-06-01
Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.
An algorithm for the empirical optimization of antenna arrays
NASA Technical Reports Server (NTRS)
Blank, S.
1983-01-01
A numerical technique is presented to optimize the performance of arbitrary antenna arrays under realistic conditions. An experimental-computational algorithm is formulated in which n-dimensional minimization methods are applied to measured data obtained from the antenna array. A numerical update formula is used to induce partial derivative information without requiring special perturbations of the array parameters. The algorithm provides a new design for the antenna array, and the method proceeds in an iterative fashion. Test case results are presented showing the effectiveness of the algorithm.
Genetic algorithms, path relinking, and the flowshop sequencing problem.
Reeves, C R; Yamada, T
1998-01-01
In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly. PMID:10021740
A scalable parallel graph coloring algorithm for distributed memory computers.
Bozdag, Doruk; Manne, Fredrik; Gebremedhin, Assefaw H.; Catalyurek, Umit; Boman, Erik Gunnar
2005-02-01
In large-scale parallel applications a graph coloring is often carried out to schedule computational tasks. In this paper, we describe a new distributed memory algorithm for doing the coloring itself in parallel. The algorithm operates in an iterative fashion; in each round vertices are speculatively colored based on limited information, and then a set of incorrectly colored vertices, to be recolored in the next round, is identified. Parallel speedup is achieved in part by reducing the frequency of communication among processors. Experimental results on a PC cluster using up to 16 processors show that the algorithm is scalable.
A Novel Image Encryption Algorithm Based on DNA Subsequence Operation
Zhang, Qiang; Xue, Xianglian; Wei, Xiaopeng
2012-01-01
We present a novel image encryption algorithm based on DNA subsequence operation. Different from the traditional DNA encryption methods, our algorithm does not use complex biological operation but just uses the idea of DNA subsequence operations (such as elongation operation, truncation operation, deletion operation, etc.) combining with the logistic chaotic map to scramble the location and the value of pixel points from the image. The experimental results and security analysis show that the proposed algorithm is easy to be implemented, can get good encryption effect, has a wide secret key's space, strong sensitivity to secret key, and has the abilities of resisting exhaustive attack and statistic attack. PMID:23093912
A novel image encryption algorithm based on DNA subsequence operation.
Zhang, Qiang; Xue, Xianglian; Wei, Xiaopeng
2012-01-01
We present a novel image encryption algorithm based on DNA subsequence operation. Different from the traditional DNA encryption methods, our algorithm does not use complex biological operation but just uses the idea of DNA subsequence operations (such as elongation operation, truncation operation, deletion operation, etc.) combining with the logistic chaotic map to scramble the location and the value of pixel points from the image. The experimental results and security analysis show that the proposed algorithm is easy to be implemented, can get good encryption effect, has a wide secret key's space, strong sensitivity to secret key, and has the abilities of resisting exhaustive attack and statistic attack. PMID:23093912
Implementation of the IDEA algorithm for image encryption
NASA Astrophysics Data System (ADS)
Dang, Philip P.; Chau, Paul M.
2000-11-01
In this paper, we present an implementation of the IDEA algorithm for image encryption. The image encryption is incorporated into the compression algorithm for transmission over a data network. In the proposed method, Embedded Wavelet Zero-tree Coding is used for image compression. Experimental results show that our proposed scheme enhances data security and reduces the network bandwidth required for video transmissions. A software implementation and system architecture for hardware implementation of the IDEA image encryption algorithm based on Field Programmable Gate Array (FPGA) technology are presented in this paper.
An efficient cuckoo search algorithm for numerical function optimization
NASA Astrophysics Data System (ADS)
Ong, Pauline; Zainuddin, Zarita
2013-04-01
Cuckoo search algorithm which reproduces the breeding strategy of the best known brood parasitic bird, the cuckoos has demonstrated its superiority in obtaining the global solution for numerical optimization problems. However, the involvement of fixed step approach in its exploration and exploitation behavior might slow down the search process considerably. In this regards, an improved cuckoo search algorithm with adaptive step size adjustment is introduced and its feasibility on a variety of benchmarks is validated. The obtained results show that the proposed scheme outperforms the standard cuckoo search algorithm in terms of convergence characteristic while preserving the fascinating features of the original method.
On algorithmic rate-coded AER generation.
Linares-Barranco, Alejandro; Jimenez-Moreno, Gabriel; Linares-Barranco, Bernabé; Civit-Balcells, Antón
2006-05-01
This paper addresses the problem of converting a conventional video stream based on sequences of frames into the spike event-based representation known as the address-event-representation (AER). In this paper we concentrate on rate-coded AER. The problem is addressed as an algorithmic problem, in which different methods are proposed, implemented and tested through software algorithms. The proposed algorithms are comparatively evaluated according to different criteria. Emphasis is put on the potential of such algorithms for a) doing the frame-based to event-based representation in real time, and b) that the resulting event streams ressemble as much as possible those generated naturally by rate-coded address-event VLSI chips, such as silicon AER retinae. It is found that simple and straightforward algorithms tend to have high potential for real time but produce event distributions that differ considerably from those obtained in AER VLSI chips. On the other hand, sophisticated algorithms that yield better event distributions are not efficient for real time operations. The methods based on linear-feedback-shift-register (LFSR) pseudorandom number generation is a good compromise, which is feasible for real time and yield reasonably well distributed events in time. Our software experiments, on a 1.6-GHz Pentium IV, show that at 50% AER bus load the proposed algorithms require between 0.011 and 1.14 ms per 8 bit-pixel per frame. One of the proposed LFSR methods is implemented in real time hardware using a prototyping board that includes a VirtexE 300 FPGA. The demonstration hardware is capable of transforming frames of 64 x 64 pixels of 8-bit depth at a frame rate of 25 frames per second, producing spike events at a peak rate of 10(7) events per second. PMID:16722179
A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.
Ali, Ahmed F; Tawhid, Mohamed A
2016-01-01
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time. PMID:27217988
Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model.
Zhou, Changjun; Hou, Caixia; Zhang, Qiang; Wei, Xiaopeng
2013-09-01
The problem of protein structure prediction in the hydrophobic-polar (HP) lattice model is the prediction of protein tertiary structure. This problem is usually referred to as the protein folding problem. This paper presents a method for the application of an enhanced hybrid search algorithm to the problem of protein folding prediction, using the three dimensional (3D) HP lattice model. The enhanced hybrid search algorithm is a combination of the particle swarm optimizer (PSO) and tabu search (TS) algorithms. Since the PSO algorithm entraps local minimum in later evolution extremely easily, we combined PSO with the TS algorithm, which has properties of global optimization. Since the technologies of crossover and mutation are applied many times to PSO and TS algorithms, so enhanced hybrid search algorithm is called the MCMPSO-TS (multiple crossover and mutation PSO-TS) algorithm. Experimental results show that the MCMPSO-TS algorithm can find the best solutions so far for the listed benchmarks, which will help comparison with any future paper approach. Moreover, real protein sequences and Fibonacci sequences are verified in the 3D HP lattice model for the first time. Compared with the previous evolutionary algorithms, the new hybrid search algorithm is novel, and can be used effectively to predict 3D protein folding structure. With continuous development and changes in amino acids sequences, the new algorithm will also make a contribution to the study of new protein sequences. PMID:23824509
Comparison and analysis of nonlinear algorithms for compressed sensing in MRI.
Yu, Yeyang; Hong, Mingjian; Liu, Feng; Wang, Hua; Crozier, Stuart
2010-01-01
Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A systematic and comparative study of those commonly used algorithms is therefore essential for the implementation of CS in MRI. In this work, three typical algorithms, namely, the Gradient Projection For Sparse Reconstruction (GPSR) algorithm, Interior-point algorithm (l(1)_ls), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm are compared and investigated in three different imaging scenarios, brain, angiogram and phantom imaging. The algorithms' performances are characterized in terms of image quality and reconstruction speed. The theoretical results show that the performance of the CS algorithms is case sensitive; overall, the StOMP algorithm offers the best solution in imaging quality, while the GPSR algorithm is the most efficient one among the three methods. In the next step, the algorithm performances and characteristics will be experimentally explored. It is hoped that this research will further support the applications of CS in MRI. PMID:21097312
28. MAP SHOWING LOCATION OF ARVFS FACILITY AS BUILT. SHOWS ...
28. MAP SHOWING LOCATION OF ARVFS FACILITY AS BUILT. SHOWS LINCOLN BOULEVARD, BIG LOST RIVER, AND NAVAL REACTORS FACILITY. F.C. TORKELSON DRAWING NUMBER 842-ARVFS-101-2. DATED OCTOBER 12, 1965. INEL INDEX CODE NUMBER: 075 0101 851 151969. - Idaho National Engineering Laboratory, Advanced Reentry Vehicle Fusing System, Scoville, Butte County, ID
8. Detail showing concrete abutment, showing substructure of bridge, specifically ...
8. Detail showing concrete abutment, showing substructure of bridge, specifically west side of arch and substructure. - Presumpscot Falls Bridge, Spanning Presumptscot River at Allen Avenue extension, 0.75 mile west of U.S. Interstate 95, Falmouth, Cumberland County, ME
Kernel MAD Algorithm for Relative Radiometric Normalization
NASA Astrophysics Data System (ADS)
Bai, Yang; Tang, Ping; Hu, Changmiao
2016-06-01
The multivariate alteration detection (MAD) algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA) which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA). The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1) data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.
Efficient algorithms for survivable virtual network embedding
NASA Astrophysics Data System (ADS)
Sun, Gang; Yu, Hongfang; Li, Lemin; Anand, Vishal; di, Hao; Gao, Xiujiao
2010-12-01
Network Virtualization Technology is serving as an effective method for providing a flexible and highly adaptable shared substrate network to satisfy the diversity of demands. But the problem of efficiently embedding Virtual Network (VN) onto substrate network is intractable since it is NP-hard. How to guarantee survivability of the embedding efficiently is another great challenge. In this paper, we investigate the Survivable Virtual Network Embedding (SVNE) problem and propose two efficient algorithms for solving this problem efficiently. Firstly, we formulate the model with minimum-cost objective of survivable network virtualization problem by Mixed Integer Linear Programming (MILP). We then devise two efficient relaxation-based algorithms for solving survivable virtual network embedding problem: (1) Lagrangian Relaxation based algorithm, called LR-SVNE in this paper; (2) Decomposition based algorithm called DSVNE in this paper. The results of simulation experiments show that these two algorithms both have good performance on time efficiency but LR-SVNE can guarantee the solution converge to optimal one under small scale substrate network.
An Algorithm for Autonomous Formation Obstacle Avoidance
NASA Astrophysics Data System (ADS)
Cruz, Yunior I.
The level of human interaction with Unmanned Aerial Systems varies greatly from remotely piloted aircraft to fully autonomous systems. In the latter end of the spectrum, the challenge lies in designing effective algorithms to dictate the behavior of the autonomous agents. A swarm of autonomous Unmanned Aerial Vehicles requires collision avoidance and formation flight algorithms to negotiate environmental challenges it may encounter during the execution of its mission, which may include obstacles and chokepoints. In this work, a simple algorithm is developed to allow a formation of autonomous vehicles to perform point to point navigation while avoiding obstacles and navigating through chokepoints. Emphasis is placed on maintaining formation structures. Rather than breaking formation and individually navigating around the obstacle or through the chokepoint, vehicles are required to assemble into appropriately sized/shaped sub-formations, bifurcate around the obstacle or negotiate the chokepoint, and reassemble into the original formation at the far side of the obstruction. The algorithm receives vehicle and environmental properties as inputs and outputs trajectories for each vehicle from start to the desired ending location. Simulation results show that the algorithm safely routes all vehicles past the obstruction while adhering to the aforementioned requirements. The formation adapts and successfully negotiates the obstacles and chokepoints in its path while maintaining proper vehicle separation.
Connected-Health Algorithm: Development and Evaluation.
Vlahu-Gjorgievska, Elena; Koceski, Saso; Kulev, Igor; Trajkovik, Vladimir
2016-04-01
Nowadays, there is a growing interest towards the adoption of novel ICT technologies in the field of medical monitoring and personal health care systems. This paper proposes design of a connected health algorithm inspired from social computing paradigm. The purpose of the algorithm is to give a recommendation for performing a specific activity that will improve user's health, based on his health condition and set of knowledge derived from the history of the user and users with similar attitudes to him. The algorithm could help users to have bigger confidence in choosing their physical activities that will improve their health. The proposed algorithm has been experimentally validated using real data collected from a community of 1000 active users. The results showed that the recommended physical activity, contributed towards weight loss of at least 0.5 kg, is found in the first half of the ordered list of recommendations, generated by the algorithm, with the probability > 0.6 with 1 % level of significance. PMID:26922593
General lossless planar coupler design algorithms.
Vance, Rod
2015-08-01
This paper reviews and extends two classes of algorithms for the design of planar couplers with any unitary transfer matrix as design goals. Such couplers find use in optical sensing for fading free interferometry, coherent optical network demodulation, and also for quantum state preparation in quantum optical experiments and technology. The two classes are (1) "atomic coupler algorithms" decomposing a unitary transfer matrix into a planar network of 2×2 couplers, and (2) "Lie theoretic algorithms" concatenating unit cell devices with variable phase delay sets that form canonical coordinates for neighborhoods in the Lie group U(N), so that the concatenations realize any transfer matrix in U(N). As well as review, this paper gives (1) a Lie theoretic proof existence proof showing that both classes of algorithms work and (2) direct proofs of the efficacy of the "atomic coupler" algorithms. The Lie theoretic proof strengthens former results. 5×5 couplers designed by both methods are compared by Monte Carlo analysis, which would seem to imply atomic rather than Lie theoretic methods yield designs more resilient to manufacturing imperfections. PMID:26367295
Why is Boris Algorithm So Good?
et al, Hong Qin
2013-03-03
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this letter, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Why is Boris algorithm so good?
Qin, Hong; Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08543 ; Zhang, Shuangxi; Xiao, Jianyuan; Liu, Jian; Sun, Yajuan; Tang, William M.
2013-08-15
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this paper, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Pea Plants Show Risk Sensitivity.
Dener, Efrat; Kacelnik, Alex; Shemesh, Hagai
2016-07-11
Sensitivity to variability in resources has been documented in humans, primates, birds, and social insects, but the fit between empirical results and the predictions of risk sensitivity theory (RST), which aims to explain this sensitivity in adaptive terms, is weak [1]. RST predicts that agents should switch between risk proneness and risk aversion depending on state and circumstances, especially according to the richness of the least variable option [2]. Unrealistic assumptions about agents' information processing mechanisms and poor knowledge of the extent to which variability imposes specific selection in nature are strong candidates to explain the gap between theory and data. RST's rationale also applies to plants, where it has not hitherto been tested. Given the differences between animals' and plants' information processing mechanisms, such tests should help unravel the conflicts between theory and data. Measuring root growth allocation by split-root pea plants, we show that they favor variability when mean nutrient levels are low and the opposite when they are high, supporting the most widespread RST prediction. However, the combination of non-linear effects of nitrogen availability at local and systemic levels may explain some of these effects as a consequence of mechanisms not necessarily evolved to cope with variance [3, 4]. This resembles animal examples in which properties of perception and learning cause risk sensitivity even though they are not risk adaptations [5]. PMID:27374342
NASA Astrophysics Data System (ADS)
Igeta, Hideki; Hasegawa, Mikio
Chaotic dynamics have been effectively applied to improve various heuristic algorithms for combinatorial optimization problems in many studies. Currently, the most used chaotic optimization scheme is to drive heuristic solution search algorithms applicable to large-scale problems by chaotic neurodynamics including the tabu effect of the tabu search. Alternatively, meta-heuristic algorithms are used for combinatorial optimization by combining a neighboring solution search algorithm, such as tabu, gradient, or other search method, with a global search algorithm, such as genetic algorithms (GA), ant colony optimization (ACO), or others. In these hybrid approaches, the ACO has effectively optimized the solution of many benchmark problems in the quadratic assignment problem library. In this paper, we propose a novel hybrid method that combines the effective chaotic search algorithm that has better performance than the tabu search and global search algorithms such as ACO and GA. Our results show that the proposed chaotic hybrid algorithm has better performance than the conventional chaotic search and conventional hybrid algorithms. In addition, we show that chaotic search algorithm combined with ACO has better performance than when combined with GA.
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.
An improved robust ADMM algorithm for quantum state tomography
NASA Astrophysics Data System (ADS)
Li, Kezhi; Zhang, Hui; Kuang, Sen; Meng, Fangfang; Cong, Shuang
2016-06-01
In this paper, an improved adaptive weights alternating direction method of multipliers algorithm is developed to implement the optimization scheme for recovering the quantum state in nearly pure states. The proposed approach is superior to many existing methods because it exploits the low-rank property of density matrices, and it can deal with unexpected sparse outliers as well. The numerical experiments are provided to verify our statements by comparing the results to three different optimization algorithms, using both adaptive and fixed weights in the algorithm, in the cases of with and without external noise, respectively. The results indicate that the improved algorithm has better performances in both estimation accuracy and robustness to external noise. The further simulation results show that the successful recovery rate increases when more qubits are estimated, which in fact satisfies the compressive sensing theory and makes the proposed approach more promising.
A Parallel Prefix Algorithm for Almost Toeplitz Tridiagonal Systems
NASA Technical Reports Server (NTRS)
Sun, Xian-He; Joslin, Ronald D.
1995-01-01
A compact scheme is a discretization scheme that is advantageous in obtaining highly accurate solutions. However, the resulting systems from compact schemes are tridiagonal systems that are difficult to solve efficiently on parallel computers. Considering the almost symmetric Toeplitz structure, a parallel algorithm, simple parallel prefix (SPP), is proposed. The SPP algorithm requires less memory than the conventional LU decomposition and is efficient on parallel machines. It consists of a prefix communication pattern and AXPY operations. Both the computation and the communication can be truncated without degrading the accuracy when the system is diagonally dominant. A formal accuracy study has been conducted to provide a simple truncation formula. Experimental results have been measured on a MasPar MP-1 SIMD machine and on a Cray 2 vector machine. Experimental results show that the simple parallel prefix algorithm is a good algorithm for symmetric, almost symmetric Toeplitz tridiagonal systems and for the compact scheme on high-performance computers.
WS-BP: An efficient wolf search based back-propagation algorithm
NASA Astrophysics Data System (ADS)
Nawi, Nazri Mohd; Rehman, M. Z.; Khan, Abdullah
2015-05-01
Wolf Search (WS) is a heuristic based optimization algorithm. Inspired by the preying and survival capabilities of the wolves, this algorithm is highly capable to search large spaces in the candidate solutions. This paper investigates the use of WS algorithm in combination with back-propagation neural network (BPNN) algorithm to overcome the local minima problem and to improve convergence in gradient descent. The performance of the proposed Wolf Search based Back-Propagation (WS-BP) algorithm is compared with Artificial Bee Colony Back-Propagation (ABC-BP), Bat Based Back-Propagation (Bat-BP), and conventional BPNN algorithms. Specifically, OR and XOR datasets are used for training the network. The simulation results show that the WS-BP algorithm effectively avoids the local minima and converge to global minima.
Li, Shanshan; Chen, Shaojie; Yue, Chen; Caffo, Brian
2016-01-01
Independent Component analysis (ICA) is a widely used technique for separating signals that have been mixed together. In this manuscript, we propose a novel ICA algorithm using density estimation and maximum likelihood, where the densities of the signals are estimated via p-spline based histogram smoothing and the mixing matrix is simultaneously estimated using an optimization algorithm. The algorithm is exceedingly simple, easy to implement and blind to the underlying distributions of the source signals. To relax the identically distributed assumption in the density function, a modified algorithm is proposed to allow for different density functions on different regions. The performance of the proposed algorithm is evaluated in different simulation settings. For illustration, the algorithm is applied to a research investigation with a large collection of resting state fMRI datasets. The results show that the algorithm successfully recovers the established brain networks. PMID:26858592
AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL
Zhang, Tao; Chen, Liping; Li, Yao
2015-01-01
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV. PMID:26729120
One high-accuracy camera calibration algorithm based on computer vision images
NASA Astrophysics Data System (ADS)
Wang, Ying; Huang, Jianming; Wei, Xiangquan
2015-12-01
Camera calibration is the first step of computer vision and one of the most active research fields nowadays. In order to improve the measurement precision, the internal parameters of the camera should be accurately calibrated. So one high-accuracy camera calibration algorithm is proposed based on the images of planar targets or tridimensional targets. By using the algorithm, the internal parameters of the camera are calibrated based on the existing planar target at the vision-based navigation experiment. The experimental results show that the accuracy of the proposed algorithm is obviously improved compared with the conventional linear algorithm, Tsai general algorithm, and Zhang Zhengyou calibration algorithm. The algorithm proposed by the article can satisfy the need of computer vision and provide reference for precise measurement of the relative position and attitude.
Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch
Karthikeyan, M.; Sree Ranga Raja, T.
2015-01-01
Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods. PMID:26491710
AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL.
Zhang, Tao; Chen, Liping; Li, Yao
2015-01-01
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV. PMID:26729120
A new improved artificial bee colony algorithm for ship hull form optimization
NASA Astrophysics Data System (ADS)
Huang, Fuxin; Wang, Lijue; Yang, Chi
2016-04-01
The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.
Three hypothesis algorithm with occlusion reasoning for multiple people tracking
NASA Astrophysics Data System (ADS)
Reta, Carolina; Altamirano, Leopoldo; Gonzalez, Jesus A.; Medina-Carnicer, Rafael
2015-01-01
This work proposes a detection-based tracking algorithm able to locate and keep the identity of multiple people, who may be occluded, in uncontrolled stationary environments. Our algorithm builds a tracking graph that models spatio-temporal relationships among attributes of interacting people to predict and resolve partial and total occlusions. When a total occlusion occurs, the algorithm generates various hypotheses about the location of the occluded person considering three cases: (a) the person keeps the same direction and speed, (b) the person follows the direction and speed of the occluder, and (c) the person remains motionless during occlusion. By analyzing the graph, our algorithm can detect trajectories produced by false alarms and estimate the location of missing or occluded people. Our algorithm performs acceptably under complex conditions, such as partial visibility of individuals getting inside or outside the scene, continuous interactions and occlusions among people, wrong or missing information on the detection of persons, as well as variation of the person's appearance due to illumination changes and background-clutter distracters. Our algorithm was evaluated on test sequences in the field of intelligent surveillance achieving an overall precision of 93%. Results show that our tracking algorithm outperforms even trajectory-based state-of-the-art algorithms.
Generalized Pattern Search Algorithm for Peptide Structure Prediction
Nicosia, Giuseppe; Stracquadanio, Giovanni
2008-01-01
Finding the near-native structure of a protein is one of the most important open problems in structural biology and biological physics. The problem becomes dramatically more difficult when a given protein has no regular secondary structure or it does not show a fold similar to structures already known. This situation occurs frequently when we need to predict the tertiary structure of small molecules, called peptides. In this research work, we propose a new ab initio algorithm, the generalized pattern search algorithm, based on the well-known class of Search-and-Poll algorithms. We performed an extensive set of simulations over a well-known set of 44 peptides to investigate the robustness and reliability of the proposed algorithm, and we compared the peptide conformation with a state-of-the-art algorithm for peptide structure prediction known as PEPstr. In particular, we tested the algorithm on the instances proposed by the originators of PEPstr, to validate the proposed algorithm; the experimental results confirm that the generalized pattern search algorithm outperforms PEPstr by 21.17% in terms of average root mean-square deviation, RMSD Cα. PMID:18487293
An enhanced fast scanning algorithm for image segmentation
NASA Astrophysics Data System (ADS)
Ismael, Ahmed Naser; Yusof, Yuhanis binti
2015-12-01
Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.
Adaptive algorithm for cloud cover estimation from all-sky images over the sea
NASA Astrophysics Data System (ADS)
Krinitskiy, M. A.; Sinitsyn, A. V.
2016-05-01
A new algorithm for cloud cover estimation has been formulated and developed based on the synthetic control index, called the grayness rate index, and an additional algorithm step of adaptive filtering of the Mie scattering contribution. A setup for automated cloud cover estimation has been designed, assembled, and tested under field conditions. The results shows a significant advantage of the new algorithm over currently commonly used procedures.
A fast algorithm for attribute reduction based on Trie tree and rough set theory
NASA Astrophysics Data System (ADS)
Hu, Feng; Wang, Xiao-yan; Luo, Chuan-jiang
2013-03-01
Attribute reduction is an important issue in rough set theory. Many efficient algorithms have been proposed, however, few of them can process huge data sets quickly. In this paper, combining the Trie tree, the algorithms for computing positive region of decision table are proposed. After that, a new algorithm for attribute reduction based on Trie tree is developed, which can be used to process the attribute reduction of large data sets quickly. Experiment results show its high efficiency.
NASA Astrophysics Data System (ADS)
Kanagaraj, G.; Ponnambalam, S. G.; Jawahar, N.; Mukund Nilakantan, J.
2014-10-01
This article presents an effective hybrid cuckoo search and genetic algorithm (HCSGA) for solving engineering design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. The proposed algorithm, HCSGA, is first applied to 13 standard benchmark constrained optimization functions and subsequently used to solve three well-known design problems reported in the literature. The numerical results obtained by HCSGA show competitive performance with respect to recent algorithms for constrained design optimization problems.
NASA Astrophysics Data System (ADS)
Zeng, Yaoping; Yang, Yixin; Lu, Guangyue
2013-07-01
This paper focuses on the direction of arrival (DOA) under the circumstance of mixed circular and noncircular sources with Minimum-Redundancy Linear Array(MRLA).By exploiting receiving signal data and its conjugate,the proposed algorithm can augment the maximum number of detectable sources.Using the weighted MUSIC algorithm during the whole space, the proposed scheme can obtain perfect quality for MRLA without knowing the number of sources. Simulation results clearly show that the effectiveness of our proposed algorithm.
Affine Projection Algorithm with Improved Data-Selective Method Using the Condition Number
NASA Astrophysics Data System (ADS)
Ban, Sung Jun; Lee, Chang Woo; Kim, Sang Woo
Recently, a data-selective method has been proposed to achieve low misalignment in affine projection algorithm (APA) by keeping the condition number of an input data matrix small. We present an improved method, and a complexity reduction algorithm for the APA with the data-selective method. Experimental results show that the proposed algorithm has lower misalignment and a lower condition number for an input data matrix than both the conventional APA and the APA with the previous data-selective method.
Consensus algorithms in decentralized networks
NASA Astrophysics Data System (ADS)
Coduti, Leonardo Phillip
We consider a decentralized network with the following goal: the state at each node of the network iteratively converges to the same value. Ensuring that this goal is achieved requires certain properties of the topology of the network and the function describing the evolution of the network. We will present these properties for deterministic systems, extending current results in the literature. As an additional contribution, we will show how the convergence results for stochastic systems are direct consequences of the corresponding deterministic systems, drastically simplifying many other current results. In general, these consensus systems can be both time invariant and time varying, and we will extend all our deterministic and stochastic results to include time varying systems as well. We will then consider a more complex consensus problem, the resource allocation problem. In this situation each node of the network has both a state and a capacity. The capacity is a monotone increasing function of the state, and the goal is for the nodes to exchange capacity in a decentralized manner in order to drive all of the states to the same value. Conditions ensuring consensus in the deterministic setting will be presented, and we will show how convergence in this system also comes from the fundamental deterministic result for consensus algorithms. The main results will again be extended to stochastic and time varying systems. The linear consensus system requires the construction of a matrix of weighting parameters with specific properties. We present an iterative algorithm for determining the weighting parameters in a decentralized fashion; the weighting parameters are specified by the nodes and each node only specifies the weighting parameters as sociated with that node. The results assume that the communication graph of the network is directed, and we consider both synchronous communication, and stochastic asynchronous networks.
Broadband beamforming compensation algorithm in CI front-end acquisition
2013-01-01
Background To increase the signal to noise ratio (SNR) and to suppress directional noise in front-end signal acquisition, microphone array technologies are being applied in the cochlear implant (CI). Due to size constraints, the dual microphone-based system is most suitable for actual application. However, direct application of the array technology will result in the low frequency roll-off problem, which can noticeably distort the desired signal. Methods In this paper, we theoretically analyze the roll-off characteristic on the basis of CI parameters and present a new low-complexity compensation algorithm. We obtain the linearized frequency response of the two-microphone array from modeling and analysis for further algorithm realization. Realization and results Linear method was used to approximate the theoretical response with adjustable delay and weight parameters. A CI dual-channel hardware platform is constructed for experimental research. Experimental results show that our algorithm performs well in compensation and realization. Discussions We discuss the effect from environment noise. Actual daily noise with more low-frequency energy will weaken the algorithm performance. A balance between low-frequency distortion and corresponding low-frequency noise need to be considered. Conclusions Our novel compensation algorithm uses linear function to obtain the desired system response, which is a low computational-complexity method for CI real-time processing. Algorithm performance is tested in CI CIS modulation and the influence of experimental distance and environmental noise were further analyzed to evaluate algorithm constraint. PMID:23442782
NASA Astrophysics Data System (ADS)
Sun, Cong; Yang, Yunchuan; Yuan, Yaxiang
2012-12-01
In this article, we investigate the interference alignment (IA) solution for a K-user MIMO interference channel. Proper users' precoders and decoders are designed through a desired signal power maximization model with IA conditions as constraints, which forms a complex matrix optimization problem. We propose two low complexity algorithms, both of which apply the Courant penalty function technique to combine the leakage interference and the desired signal power together as the new objective function. The first proposed algorithm is the modified alternating minimization algorithm (MAMA), where each subproblem has closed-form solution with an eigenvalue decomposition. To further reduce algorithm complexity, we propose a hybrid algorithm which consists of two parts. As the first part, the algorithm iterates with Householder transformation to preserve the orthogonality of precoders and decoders. In each iteration, the matrix optimization problem is considered in a sequence of 2D subspaces, which leads to one dimensional optimization subproblems. From any initial point, this algorithm obtains precoders and decoders with low leakage interference in short time. In the second part, to exploit the advantage of MAMA, it continues to iterate to perfectly align the interference from the output point of the first part. Analysis shows that in one iteration generally both proposed two algorithms have lower computational complexity than the existed maximum signal power (MSP) algorithm, and the hybrid algorithm enjoys lower complexity than MAMA. Simulations reveal that both proposed algorithms achieve similar performances as the MSP algorithm with less executing time, and show better performances than the existed alternating minimization algorithm in terms of sum rate. Besides, from the view of convergence rate, simulation results show that the MAMA enjoys fastest speed with respect to a certain sum rate value, while hybrid algorithm converges fastest to eliminate interference.
Optimisation of nonlinear motion cueing algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Asadi, Houshyar; Mohamed, Shady; Rahim Zadeh, Delpak; Nahavandi, Saeid
2015-04-01
Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching
Planning a Successful Tech Show
ERIC Educational Resources Information Center
Nikirk, Martin
2011-01-01
Tech shows are a great way to introduce prospective students, parents, and local business and industry to a technology and engineering or career and technical education program. In addition to showcasing instructional programs, a tech show allows students to demonstrate their professionalism and skills, practice public presentations, and interact…
Hey Teacher, Your Personality's Showing!
ERIC Educational Resources Information Center
Paulsen, James R.
1977-01-01
A study of 30 fourth, fifth, and sixth grade teachers and 300 of their students showed that a teacher's age, sex, and years of experience did not relate to students' mathematics achievement, but that more effective teachers showed greater "freedom from defensive behavior" than did less effective teachers. (DT)
Ozone Differential Absorption Lidar Algorithm Intercomparison
NASA Astrophysics Data System (ADS)
Godin, Sophie; Carswell, Allen I.; Donovan, David P.; Claude, Hans; Steinbrecht, Wolfgang; McDermid, I. Stuart; McGee, Thomas J.; Gross, Michael R.; Nakane, Hideaki; Swart, Daan P. J.; Bergwerff, Hans B.; Uchino, Osamu; von der Gathen, Peter; Neuber, Roland
1999-10-01
An intercomparison of ozone differential absorption lidar algorithms was performed in 1996 within the framework of the Network for the Detection of Stratospheric Changes (NDSC) lidar working group. The objective of this research was mainly to test the differentiating techniques used by the various lidar teams involved in the NDSC for the calculation of the ozone number density from the lidar signals. The exercise consisted of processing synthetic lidar signals computed from simple Rayleigh scattering and three initial ozone profiles. Two of these profiles contained perturbations in the low and the high stratosphere to test the vertical resolution of the various algorithms. For the unperturbed profiles the results of the simulations show the correct behavior of the lidar processing methods in the low and the middle stratosphere with biases of less than 1% with respect to the initial profile to as high as 30 km in most cases. In the upper stratosphere, significant biases reaching 10% at 45 km for most of the algorithms are obtained. This bias is due to the decrease in the signal-to-noise ratio with altitude, which makes it necessary to increase the number of points of the derivative low-pass filter used for data processing. As a consequence the response of the various retrieval algorithms to perturbations in the ozone profile is much better in the lower stratosphere than in the higher range. These results show the necessity of limiting the vertical smoothing in the ozone lidar retrieval algorithm and questions the ability of current lidar systems to detect long-term ozone trends above 40 km. Otherwise the simulations show in general a correct estimation of the ozone profile random error and, as shown by the tests involving the perturbed ozone profiles, some inconsistency in the estimation of the vertical resolution among the lidar teams involved in this experiment.
Developments in Human Centered Cueing Algorithms for Control of Flight Simulator Motion Systems
NASA Technical Reports Server (NTRS)
Houck, Jacob A.; Telban, Robert J.; Cardullo, Frank M.
1997-01-01
The authors conducted further research with cueing algorithms for control of flight simulator motion systems. A variation of the so-called optimal algorithm was formulated using simulated aircraft angular velocity input as a basis. Models of the human vestibular sensation system, i.e. the semicircular canals and otoliths, are incorporated within the algorithm. Comparisons of angular velocity cueing responses showed a significant improvement over a formulation using angular acceleration input. Results also compared favorably with the coordinated adaptive washout algorithm, yielding similar results for angular velocity cues while eliminating false cues and reducing the tilt rate for longitudinal cues. These results were confirmed in piloted tests on the current motion system at NASA-Langley, the Visual Motion Simulator (VMS). Proposed future developments by the authors in cueing algorithms are revealed. The new motion system, the Cockpit Motion Facility (CMF), where the final evaluation of the cueing algorithms will be conducted, is also described.
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
Efficient implementation of the adaptive scale pixel decomposition algorithm
NASA Astrophysics Data System (ADS)
Zhang, L.; Bhatnagar, S.; Rau, U.; Zhang, M.
2016-08-01
Context. Most popular algorithms in use to remove the effects of a telescope's point spread function (PSF) in radio astronomy are variants of the CLEAN algorithm. Most of these algorithms model the sky brightness using the delta-function basis, which results in undesired artefacts when used to image extended emission. The adaptive scale pixel decomposition (Asp-Clean) algorithm models the sky brightness on a scale-sensitive basis and thus gives a significantly better imaging performance when imaging fields that contain both resolved and unresolved emission. Aims: However, the runtime cost of Asp-Clean is higher than that of scale-insensitive algorithms. In this paper, we identify the most expensive step in the original Asp-Clean algorithm and present an efficient implementation of it, which significantly reduces the computational cost while keeping the imaging performance comparable to the original algorithm. The PSF sidelobe levels of modern wide-band telescopes are significantly reduced, allowing us to make approximations to reduce the computational cost, which in turn allows for the deconvolution of larger images on reasonable timescales. Methods: As in the original algorithm, scales in the image are estimated through function fitting. Here we introduce an analytical method to model extended emission, and a modified method for estimating the initial values used for the fitting procedure, which ultimately leads to a lower computational cost. Results: The new implementation was tested with simulated EVLA data and the imaging performance compared well with the original Asp-Clean algorithm. Tests show that the current algorithm can recover features at different scales with lower computational cost.
A Rapid Convergent Low Complexity Interference Alignment Algorithm for Wireless Sensor Networks
Jiang, Lihui; Wu, Zhilu; Ren, Guanghui; Wang, Gangyi; Zhao, Nan
2015-01-01
Interference alignment (IA) is a novel technique that can effectively eliminate the interference and approach the sum capacity of wireless sensor networks (WSNs) when the signal-to-noise ratio (SNR) is high, by casting the desired signal and interference into different signal subspaces. The traditional alternating minimization interference leakage (AMIL) algorithm for IA shows good performance in high SNR regimes, however, the complexity of the AMIL algorithm increases dramatically as the number of users and antennas increases, posing limits to its applications in the practical systems. In this paper, a novel IA algorithm, called directional quartic optimal (DQO) algorithm, is proposed to minimize the interference leakage with rapid convergence and low complexity. The properties of the AMIL algorithm are investigated, and it is discovered that the difference between the two consecutive iteration results of the AMIL algorithm will approximately point to the convergence solution when the precoding and decoding matrices obtained from the intermediate iterations are sufficiently close to their convergence values. Based on this important property, the proposed DQO algorithm employs the line search procedure so that it can converge to the destination directly. In addition, the optimal step size can be determined analytically by optimizing a quartic function. Numerical results show that the proposed DQO algorithm can suppress the interference leakage more rapidly than the traditional AMIL algorithm, and can achieve the same level of sum rate as that of AMIL algorithm with far less iterations and execution time. PMID:26230697
On the Time Complexity of Dijkstra's Three-State Mutual Exclusion Algorithm
NASA Astrophysics Data System (ADS)
Kimoto, Masahiro; Tsuchiya, Tatsuhiro; Kikuno, Tohru
In this letter we give a lower bound on the worst-case time complexity of Dijkstra's three-state mutual exclusion algorithm by specifying a concrete behavior of the algorithm. We also show that our result is more accurate than the known best bound.
Satellite Movie Shows Erika Dissipate
This animation of visible and infrared imagery from NOAA's GOES-West satellite from Aug. 27 to 29 shows Tropical Storm Erika move through the Eastern Caribbean Sea and dissipate near eastern Cuba. ...
Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di
2015-01-01
In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy. PMID:26366164
Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di
2015-01-01
In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy. PMID:26366164
Algorithmic advances in stochastic programming
Morton, D.P.
1993-07-01
Practical planning problems with deterministic forecasts of inherently uncertain parameters often yield unsatisfactory solutions. Stochastic programming formulations allow uncertain parameters to be modeled as random variables with known distributions, but the size of the resulting mathematical programs can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We consider two classes of decomposition-based stochastic programming algorithms. The first type of algorithm addresses problems with a ``manageable`` number of scenarios. The second class incorporates Monte Carlo sampling within a decomposition algorithm. We develop and empirically study an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs within a prespecified tolerance. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of ``real-world`` multistage stochastic hydroelectric scheduling problems. Recently, there has been an increased focus on decomposition-based algorithms that use sampling within the optimization framework. These approaches hold much promise for solving stochastic programs with many scenarios. A critical component of such algorithms is a stopping criterion to ensure the quality of the solution. With this as motivation, we develop a stopping rule theory for algorithms in which bounds on the optimal objective function value are estimated by sampling. Rules are provided for selecting sample sizes and terminating the algorithm under which asymptotic validity of confidence interval statements for the quality of the proposed solution can be verified. Issues associated with the application of this theory to two sampling-based algorithms are considered, and preliminary empirical coverage results are presented.
Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm
NASA Technical Reports Server (NTRS)
Kummerow, Christian; Berg, Wesley; Thomas-Stahle, Jody; Masunaga, Hirohiko
2006-01-01
While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world's oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%-3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy
Application of a new finite difference algorithm for computational aeroacoustics
NASA Technical Reports Server (NTRS)
Goodrich, John W.
1995-01-01
Acoustic problems have become extremely important in recent years because of research efforts such as the High Speed Civil Transport program. Computational aeroacoustics (CAA) requires a faithful representation of wave propagation over long distances, and needs algorithms that are accurate and boundary conditions that are unobtrusive. This paper applies a new finite difference method and boundary algorithm to the Linearized Euler Equations (LEE). The results demonstrate the ability of a new fourth order propagation algorithm to accurately simulate the genuinely multidimensional wave dynamics of acoustic propagation in two space dimensions with the LEE. The results also show the ability of a new outflow boundary condition and fourth order algorithm to pass the evolving solution from the computational domain with no perceptible degradation of the solution remaining within the domain.
Raytracing Based upon the Sympletic Algorithm
NASA Astrophysics Data System (ADS)
Wang, Y.; Li, C.
2014-12-01
The raytracing is the basic problem in seismic imaging, and the reliability of the imaging depends on the accuracies both spatial trajectory and traveltime of the ray, and is using in seismology broadly. The seismic ray travels through the inhomogeneous media fallows the the eikonal equation, and the eikonal equation is an one order differential equation of traveltime, and satisfies the Hamilton System. In Cartesian coordinate system, we use a separable Hamilton System function. In this paper, the Sympletic algorithm method with bi-cubic convolution algorithm was used to solve the Hamilton System to deal with the raytracing problem. Compared with the Fsat Marching Method (FMM), The result shows that the Sympletic algorithm method (SAM) can keep the stability of the solution for the eikonal equation. Due to the use of the Sympletic algorithm, the method can produce a reliable seismic wavefront with an accurate ray trajectory (Fig.1). Meanwhile, the numerical modeling shows that the use of SAM can not only keep the stability of the Hamilton System with a fast computation but also improve the accuracy of the seismic ray tracing (Fig.2).
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.
PPP Sliding Window Algorithm and Its Application in Deformation Monitoring.
Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming
2016-01-01
Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts. PMID:27241172
PPP Sliding Window Algorithm and Its Application in Deformation Monitoring
NASA Astrophysics Data System (ADS)
Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming
2016-05-01
Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts.
PPP Sliding Window Algorithm and Its Application in Deformation Monitoring
Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming
2016-01-01
Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts. PMID:27241172
Quantum defragmentation algorithm
Burgarth, Daniel; Giovannetti, Vittorio
2010-08-15
In this addendum to our paper [D. Burgarth and V. Giovannetti, Phys. Rev. Lett. 99, 100501 (2007)] we prove that during the transformation that allows one to enforce control by relaxation on a quantum system, the ancillary memory can be kept at a finite size, independently from the fidelity one wants to achieve. The result is obtained by introducing the quantum analog of defragmentation algorithms which are employed for efficiently reorganizing classical information in conventional hard disks.
NASA Astrophysics Data System (ADS)
Nardi, Jerry
The Satellite Aided Search and Rescue (Sarsat) is designed to detect and locate distress beacons using satellite receivers. Algorithms used for calculating the positions of 406 MHz beacons and 121.5/243 MHz beacons are presented. The techniques for matching, resolving and averaging calculated locations from multiple satellite passes are also described along with results pertaining to single pass and multiple pass location estimate accuracy.
Dynamic topology multi force particle swarm optimization algorithm and its application
NASA Astrophysics Data System (ADS)
Chen, Dongning; Zhang, Ruixing; Yao, Chengyu; Zhao, Zheyu
2016-01-01
Particle swarm optimization (PSO) algorithm is an effective bio-inspired algorithm but it has shortage of premature convergence. Researchers have made some improvements especially in force rules and population topologies. However, the current algorithms only consider a single kind of force rules and lack consideration of comprehensive improvement in both multi force rules and population topologies. In this paper, a dynamic topology multi force particle swarm optimization (DTMFPSO) algorithm is proposed in order to get better search performance. First of all, the principle of the presented multi force particle swarm optimization (MFPSO) algorithm is that different force rules are used in different search stages, which can balance the ability of global and local search. Secondly, a fitness-driven edge-changing (FE) topology based on the probability selection mechanism of roulette method is designed to cut and add edges between the particles, and the DTMFPSO algorithm is proposed by combining the FE topology with the MFPSO algorithm through concurrent evolution of both algorithm and structure in order to further improve the search accuracy. Thirdly, Benchmark functions are employed to evaluate the performance of the DTMFPSO algorithm, and test results show that the proposed algorithm is better than the well-known PSO algorithms, such as µPSO, MPSO, and EPSO algorithms. Finally, the proposed algorithm is applied to optimize the process parameters for ultrasonic vibration cutting on SiC wafer, and the surface quality of the SiC wafer is improved by 12.8% compared with the PSO algorithm in Ref. [25]. This research proposes a DTMFPSO algorithm with multi force rules and dynamic population topologies evolved simultaneously, and it has better search performance.
Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A
2015-06-01
Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. PMID:25880524
Mean-shift tracking algorithm based on adaptive fusion of multi-feature
NASA Astrophysics Data System (ADS)
Yang, Kai; Xiao, Yanghui; Wang, Ende; Feng, Junhui
2015-10-01
The classic mean-shift tracking algorithm has achieved success in the field of computer vision because of its speediness and efficiency. However, classic mean-shift tracking algorithm would fail to track in some complicated conditions such as some parts of the target are occluded, little color difference between the target and background exists, or sudden change of illumination and so on. In order to solve the problems, an improved algorithm is proposed based on the mean-shift tracking algorithm and adaptive fusion of features. Color, edges and corners of the target are used to describe the target in the feature space, and a method for measuring the discrimination of various features is presented to make feature selection adaptive. Then the improved mean-shift tracking algorithm is introduced based on the fusion of various features. For the purpose of solving the problem that mean-shift tracking algorithm with the single color feature is vulnerable to sudden change of illumination, we eliminate the effects by the fusion of affine illumination model and color feature space which ensures the correctness and stability of target tracking in that condition. Using a group of videos to test the proposed algorithm, the results show that the tracking correctness and stability of this algorithm are better than the mean-shift tracking algorithm with single feature space. Furthermore the proposed algorithm is more robust than the classic algorithm in the conditions of occlusion, target similar with background or illumination change.
2010-12-31
Conventional methods used for modeling a transmission network have resulted in a high degree of error and instability. This methodology condenses the network for analysis purposes without a loss of precision.
Optimization of composite structures by estimation of distribution algorithms
NASA Astrophysics Data System (ADS)
Grosset, Laurent
The design of high performance composite laminates, such as those used in aerospace structures, leads to complex combinatorial optimization problems that cannot be addressed by conventional methods. These problems are typically solved by stochastic algorithms, such as evolutionary algorithms. This dissertation proposes a new evolutionary algorithm for composite laminate optimization, named Double-Distribution Optimization Algorithm (DDOA). DDOA belongs to the family of estimation of distributions algorithms (EDA) that build a statistical model of promising regions of the design space based on sets of good points, and use it to guide the search. A generic framework for introducing statistical variable dependencies by making use of the physics of the problem is proposed. The algorithm uses two distributions simultaneously: the marginal distributions of the design variables, complemented by the distribution of auxiliary variables. The combination of the two generates complex distributions at a low computational cost. The dissertation demonstrates the efficiency of DDOA for several laminate optimization problems where the design variables are the fiber angles and the auxiliary variables are the lamination parameters. The results show that its reliability in finding the optima is greater than that of a simple EDA and of a standard genetic algorithm, and that its advantage increases with the problem dimension. A continuous version of the algorithm is presented and applied to a constrained quadratic problem. Finally, a modification of the algorithm incorporating probabilistic and directional search mechanisms is proposed. The algorithm exhibits a faster convergence to the optimum and opens the way for a unified framework for stochastic and directional optimization.
Creating Slide Show Book Reports.
ERIC Educational Resources Information Center
Taylor, Harriet G.; Stuhlmann, Janice M.
1995-01-01
Describes the use of "Kid Pix 2" software by fourth grade students to develop slide-show book reports. Highlights include collaboration with education majors from Louisiana State University, changes in attitudes of the education major students and elementary students, and problems with navigation and disk space. (LRW)
Producing Talent and Variety Shows.
ERIC Educational Resources Information Center
Szabo, Chuck
1995-01-01
Identifies key aspects of producing talent shows and outlines helpful hints for avoiding pitfalls and ensuring a smooth production. Presents suggestions concerning publicity, scheduling, and support personnel. Describes types of acts along with special needs and problems specific to each act. Includes a list of resources. (MJP)
NASA Astrophysics Data System (ADS)
Marwati, Rini; Yulianti, Kartika; Pangestu, Herny Wulandari
2016-02-01
A fuzzy evolutionary algorithm is an integration of an evolutionary algorithm and a fuzzy system. In this paper, we present an application of a genetic algorithm to a fuzzy evolutionary algorithm to detect and to solve chromosomes conflict. A chromosome conflict is identified by existence of any two genes in a chromosome that has the same values as two genes in another chromosome. Based on this approach, we construct an algorithm to solve a lecture scheduling problem. Time codes, lecture codes, lecturer codes, and room codes are defined as genes. They are collected to become chromosomes. As a result, the conflicted schedule turns into chromosomes conflict. Built in the Delphi program, results show that the conflicted lecture schedule problem is solvable by this algorithm.
A new algorithm of inter-frame filtering in IR image based on threshold value
NASA Astrophysics Data System (ADS)
Liu, Wei; Leng, Hanbing; Chen, Weining; Yang, Hongtao; Xie, Qingsheng; Yi, Bo; Zhang, Haifeng
2013-09-01
This paper proposed a new algorithm of inter-frame filtering in IR image based on threshold value for the purpose of solving image blur and smear brought by traditional inter-frame filtering algorithm. At first, it finds out causes of image blur and smear by analyzing general inter-frame filtering algorithm and dynamic inter-frame filtering algorithm, hence to bring up a new kind of time-domain filter. In order to obtain coefficients of the filter, it firstly gets difference image of present image and previous image, and then, it gets noisy threshold value by analyzing difference image with probability analysis method. The relationship between difference image and threshold value helps obtaining the coefficients of filter. At last, inter-frame filtering method is adopted to process pixels interrupted by noise. The experimental result shows that this algorithm has successfully repressed IR image blur and smear, and NETD tested by traditional inter filtering algorithm and the new algorithm are respectively 78mK and 70mK, which shows it has a better noise reduction performance than traditional ones. The algorithm is not only applied to still image, but also to sports image. As a new algorithm with great practical value, it is easy to achieve on FPGA, of excellent real-time performance and it effectively extends application scope of time domain filtering algorithm.
NASA Technical Reports Server (NTRS)
2004-01-01
The upper left image in this display is from the panoramic camera on the Mars Exploration Rover Spirit, showing the 'Magic Carpet' region near the rover at Gusev Crater, Mars, on Sol 7, the seventh martian day of its journey (Jan. 10, 2004). The lower image, also from the panoramic camera, is a monochrome (single filter) image of a rock in the 'Magic Carpet' area. Note that colored portions of the rock correlate with extracted spectra shown in the plot to the side. Four different types of materials are shown: the rock itself, the soil in front of the rock, some brighter soil on top of the rock, and some dust that has collected in small recesses on the rock face ('spots'). Each color on the spectra matches a line on the graph, showing how the panoramic camera's different colored filters are used to broadly assess the varying mineral compositions of martian rocks and soils.
Utilizing knowledge-base semantics in graph-based algorithms
Darwiche, A.
1996-12-31
Graph-based algorithms convert a knowledge base with a graph structure into one with a tree structure (a join-tree) and then apply tree-inference on the result. Nodes in the join-tree are cliques of variables and tree-inference is exponential in w*, the size of the maximal clique in the join-tree. A central property of join-trees that validates tree-inference is the running-intersection property: the intersection of any two cliques must belong to every clique on the path between them. We present two key results in connection to graph-based algorithms. First, we show that the running-intersection property, although sufficient, is not necessary for validating tree-inference. We present a weaker property for this purpose, called running-interaction, that depends on non-structural (semantical) properties of a knowledge base. We also present a linear algorithm that may reduce w* of a join-tree, possibly destroying its running-intersection property, while maintaining its running-interaction property and, hence, its validity for tree-inference. Second, we develop a simple algorithm for generating trees satisfying the running-interaction property. The algorithm bypasses triangulation (the standard technique for constructing join-trees) and does not construct a join-tree first. We show that the proposed algorithm may in some cases generate trees that are more efficient than those generated by modifying a join-tree.
Algorithms for builder guidelines
Balcomb, J.D.; Lekov, A.B.
1989-06-01
The Builder Guidelines are designed to make simple, appropriate guidelines available to builders for their specific localities. Builders may select from passive solar and conservation strategies with different performance potentials. They can then compare the calculated results for their particular house design with a typical house in the same location. Algorithms used to develop the Builder Guidelines are described. The main algorithms used are the monthly solar ratio (SLR) method for winter heating, the diurnal heat capacity (DHC) method for temperature swing, and a new simplified calculation method (McCool) for summer cooling. This paper applies the algorithms to estimate the performance potential of passive solar strategies, and the annual heating and cooling loads of various combinations of conservation and passive solar strategies. The basis of the McCool method is described. All three methods are implemented in a microcomputer program used to generate the guideline numbers. Guidelines for Denver, Colorado, are used to illustrate the results. The structure of the guidelines and worksheet booklets are also presented. 5 refs., 3 tabs.
Symbalisty, E.M.D.; Zinn, J.; Whitaker, R.W.
1995-09-01
This paper describes the history, physics, and algorithms of the computer code RADFLO and its extension HYCHEM. RADFLO is a one-dimensional, radiation-transport hydrodynamics code that is used to compute early-time fireball behavior for low-altitude nuclear bursts. The primary use of the code is the prediction of optical signals produced by nuclear explosions. It has also been used to predict thermal and hydrodynamic effects that are used for vulnerability and lethality applications. Another closely related code, HYCHEM, is an extension of RADFLO which includes the effects of nonequilibrium chemistry. Some examples of numerical results will be shown, along with scaling expressions derived from those results. We describe new computations of the structures and luminosities of steady-state shock waves and radiative thermal waves, which have been extended to cover a range of ambient air densities for high-altitude applications. We also describe recent modifications of the codes to use a one-dimensional analog of the CAVEAT fluid-dynamics algorithm in place of the former standard Richtmyer-von Neumann algorithm.
Large scale tracking algorithms.
Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett; Karelitz, David B.; Pitts, Todd Alan; Zollweg, Joshua David; Anderson, Dylan Z.; Nandy, Prabal; Whitlow, Gary L.; Bender, Daniel A.; Byrne, Raymond Harry
2015-01-01
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
Evaluating super resolution algorithms
NASA Astrophysics Data System (ADS)
Kim, Youn Jin; Park, Jong Hyun; Shin, Gun Shik; Lee, Hyun-Seung; Kim, Dong-Hyun; Park, Se Hyeok; Kim, Jaehyun
2011-01-01
This study intends to establish a sound testing and evaluation methodology based upon the human visual characteristics for appreciating the image restoration accuracy; in addition to comparing the subjective results with predictions by some objective evaluation methods. In total, six different super resolution (SR) algorithms - such as iterative back-projection (IBP), robust SR, maximum a posteriori (MAP), projections onto convex sets (POCS), a non-uniform interpolation, and frequency domain approach - were selected. The performance comparison between the SR algorithms in terms of their restoration accuracy was carried out through both subjectively and objectively. The former methodology relies upon the paired comparison method that involves the simultaneous scaling of two stimuli with respect to image restoration accuracy. For the latter, both conventional image quality metrics and color difference methods are implemented. Consequently, POCS and a non-uniform interpolation outperformed the others for an ideal situation, while restoration based methods appear more accurate to the HR image in a real world case where any prior information about the blur kernel is remained unknown. However, the noise-added-image could not be restored successfully by any of those methods. The latest International Commission on Illumination (CIE) standard color difference equation CIEDE2000 was found to predict the subjective results accurately and outperformed conventional methods for evaluating the restoration accuracy of those SR algorithms.
NASA Astrophysics Data System (ADS)
Smail, Linda
2016-06-01
The basic task of any probabilistic inference system in Bayesian networks is computing the posterior probability distribution for a subset or subsets of random variables, given values or evidence for some other variables from the same Bayesian network. Many methods and algorithms have been developed to exact and approximate inference in Bayesian networks. This work compares two exact inference methods in Bayesian networks-Lauritzen-Spiegelhalter and the successive restrictions algorithm-from the perspective of computational efficiency. The two methods were applied for comparison to a Chest Clinic Bayesian Network. Results indicate that the successive restrictions algorithm shows more computational efficiency than the Lauritzen-Spiegelhalter algorithm.
NASA Technical Reports Server (NTRS)
Krosel, S. M.; Milner, E. J.
1982-01-01
The application of Predictor corrector integration algorithms developed for the digital parallel processing environment are investigated. The algorithms are implemented and evaluated through the use of a software simulator which provides an approximate representation of the parallel processing hardware. Test cases which focus on the use of the algorithms are presented and a specific application using a linear model of a turbofan engine is considered. Results are presented showing the effects of integration step size and the number of processors on simulation accuracy. Real time performance, interprocessor communication, and algorithm startup are also discussed.
An Adaptive Digital Image Watermarking Algorithm Based on Morphological Haar Wavelet Transform
NASA Astrophysics Data System (ADS)
Huang, Xiaosheng; Zhao, Sujuan
At present, much more of the wavelet-based digital watermarking algorithms are based on linear wavelet transform and fewer on non-linear wavelet transform. In this paper, we propose an adaptive digital image watermarking algorithm based on non-linear wavelet transform--Morphological Haar Wavelet Transform. In the algorithm, the original image and the watermark image are decomposed with multi-scale morphological wavelet transform respectively. Then the watermark information is adaptively embedded into the original image in different resolutions, combining the features of Human Visual System (HVS). The experimental results show that our method is more robust and effective than the ordinary wavelet transform algorithms.
A multi-level solution algorithm for steady-state Markov chains
NASA Technical Reports Server (NTRS)
Horton, Graham; Leutenegger, Scott T.
1993-01-01
A new iterative algorithm, the multi-level algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial differential equations. Initial results of numerical experiments are reported, showing significant reductions in computation time, often an order of magnitude or more, relative to the Gauss-Seidel and optimal SOR algorithms for a variety of test problems. The multi-level method is compared and contrasted with the iterative aggregation-disaggregation algorithm of Takahashi.
Image haze removal algorithm for transmission lines based on weighted Gaussian PDF
NASA Astrophysics Data System (ADS)
Wang, Wanguo; Zhang, Jingjing; Li, Li; Wang, Zhenli; Li, Jianxiang; Zhao, Jinlong
2015-03-01
Histogram specification is a useful algorithm of image enhancement field. This paper proposes an image haze removal algorithm of histogram specification based on the weighted Gaussian probability density function (Gaussian PDF). Firstly, we consider the characteristics of image histogram that captured when sunny, fogging and haze weather. Then, we solve the weak intensity of image specification through changing the variance and weighted Gaussian PDF. The performance of the algorithm could removal the effective of fog and experimental results show the superiority of the proposed algorithm compared with histogram specification. It also has much advantage in respect of low computational complexity, high efficiency, no manual intervention.
A new image encryption algorithm based on logistic chaotic map with varying parameter.
Liu, Lingfeng; Miao, Suoxia
2016-01-01
In this paper, we proposed a new image encryption algorithm based on parameter-varied logistic chaotic map and dynamical algorithm. The parameter-varied logistic map can cure the weaknesses of logistic map and resist the phase space reconstruction attack. We use the parameter-varied logistic map to shuffle the plain image, and then use a dynamical algorithm to encrypt the image. We carry out several experiments, including Histogram analysis, information entropy analysis, sensitivity analysis, key space analysis, correlation analysis and computational complexity to evaluate its performances. The experiment results show that this algorithm is with high security and can be competitive for image encryption. PMID:27066326
A robust jet reconstruction algorithm for high-energy lepton colliders
NASA Astrophysics Data System (ADS)
Boronat, M.; Fuster, J.; García, I.; Ros, E.; Vos, M.
2015-11-01
We propose a new sequential jet reconstruction algorithm for future lepton colliders at the energy frontier. The Valencia algorithm combines the natural distance criterion for lepton colliders with the greater robustness against backgrounds of algorithms adapted to hadron colliders. Results on a detailed Monte Carlo simulation of t t bar and ZZ production at future linear e+e- colliders (ILC and CLIC) with a realistic level of background overlaid, show that it achieves better performance in the presence of background than the classical algorithms used at previous e+e- colliders.
Zhang, Hao; Zhao, Yan; Cao, Liangcai; Jin, Guofan
2015-02-23
We propose an algorithm based on fully computed holographic stereogram for calculating full-parallax computer-generated holograms (CGHs) with accurate depth cues. The proposed method integrates point source algorithm and holographic stereogram based algorithm to reconstruct the three-dimensional (3D) scenes. Precise accommodation cue and occlusion effect can be created, and computer graphics rendering techniques can be employed in the CGH generation to enhance the image fidelity. Optical experiments have been performed using a spatial light modulator (SLM) and a fabricated high-resolution hologram, the results show that our proposed algorithm can perform quality reconstructions of 3D scenes with arbitrary depth information. PMID:25836429
NASA Astrophysics Data System (ADS)
Bolognesi, Tommaso
2011-07-01
In the context of quantum gravity theories, several researchers have proposed causal sets as appropriate discrete models of spacetime. We investigate families of causal sets obtained from two simple models of computation - 2D Turing machines and network mobile automata - that operate on 'high-dimensional' supports, namely 2D arrays of cells and planar graphs, respectively. We study a number of quantitative and qualitative emergent properties of these causal sets, including dimension, curvature and localized structures, or 'particles'. We show how the possibility to detect and separate particles from background space depends on the choice between a global or local view at the causal set. Finally, we spot very rare cases of pseudo-randomness, or deterministic chaos; these exhibit a spontaneous phenomenon of 'causal compartmentation' that appears as a prerequisite for the occurrence of anything of physical interest in the evolution of spacetime.
NASA Astrophysics Data System (ADS)
Gravirov, V. V.; Kislov, K. V.
2009-12-01
The chief hazard posed by earthquakes consists in their suddenness. The number of earthquakes annually recorded is in excess of 100,000; of these, over 1000 are strong ones. Great human losses usually occur because no devices exist for advance warning of earthquakes. It is therefore high time that mobile information automatic systems should be developed for analysis of seismic information at high levels of manmade noise. The systems should be operated in real time with the minimum possible computational delays and be able to make fast decisions. The chief statement of the project is that sufficiently complete information about an earthquake can be obtained in real time by examining its first onset as recorded by a single seismic sensor or a local seismic array. The essential difference from the existing systems consists in the following: analysis of local seismic data at high levels of manmade noise (that is, when the noise level may be above the seismic signal level), as well as self-contained operation. The algorithms developed during the execution of the project will be capable to be used with success for individual personal protection kits and for warning the population in earthquake-prone areas over the world. The system being developed for this project uses P and S waves as well. The difference in the velocities of these seismic waves permits a technique to be developed for identifying a damaging earthquake. Real time analysis of first onsets yields the time that remains before surface waves arrive and the damage potential of these waves. Estimates show that, when the difference between the earthquake epicenter and the monitored site is of order 200 km, the time difference between the arrivals of P waves and surface waves will be about 30 seconds, which is quite sufficient to evacuate people from potentially hazardous space, insertion of moderators at nuclear power stations, pipeline interlocking, transportation stoppage, warnings issued to rescue services
ENVITEC shows off air technologies
McIlvaine, R.W.
1995-08-01
The ENVITEC International Trade Fair for Environmental Protection and Waste Management Technologies, held in June in Duesseldorf, Germany, is the largest air pollution exhibition in the world and may be the largest environmental technology show overall. Visitors saw thousands of environmental solutions from 1,318 companies representing 29 countries and occupying roughly 43,000 square meters of exhibit space. Many innovations were displayed under the category, ``thermal treatment of air pollutants.`` New technologies include the following: regenerative thermal oxidizers; wet systems for removing pollutants; biological scrubbers;electrostatic precipitators; selective adsorption systems; activated-coke adsorbers; optimization of scrubber systems; and air pollution monitors.
RES: Regularized Stochastic BFGS Algorithm
NASA Astrophysics Data System (ADS)
Mokhtari, Aryan; Ribeiro, Alejandro
2014-12-01
RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.
Ligand Identification Scoring Algorithm (LISA)
Zheng, Zheng; Merz, Kenneth M.
2011-01-01
A central problem in de novo drug design is determining the binding affinity of a ligand with a receptor. A new scoring algorithm is presented that estimates the binding affinity of a protein-ligand complex given a three-dimensional structure. The method, LISA (Ligand Identification Scoring Algorithm), uses an empirical scoring function to describe the binding free energy. Interaction terms have been designed to account for van der Waals (VDW) contacts, hydrogen bonding, desolvation effects and metal chelation to model the dissociation equilibrium constants using a linear model. Atom types have been introduced to differentiate the parameters for VDW, H-bonding interactions and metal chelation between different atom pairs. A training set of 492 protein-ligand complexes was selected for the fitting process. Different test sets have been examined to evaluate its ability to predict experimentally measured binding affinities. By comparing with other well known scoring functions, the results show that LISA has advantages over many existing scoring functions in simulating protein-ligand binding affinity, especially metalloprotein-ligand binding affinity. Artificial Neural Network (ANN) was also used in order to demonstrate that the energy terms in LISA are well designed and do not require extra cross terms. PMID:21561101
A baseline algorithm for face detection and tracking in video
NASA Astrophysics Data System (ADS)
Manohar, Vasant; Soundararajan, Padmanabhan; Korzhova, Valentina; Boonstra, Matthew; Goldgof, Dmitry; Kasturi, Rangachar
2007-10-01
Establishing benchmark datasets, performance metrics and baseline algorithms have considerable research significance in gauging the progress in any application domain. These primarily allow both users and developers to compare the performance of various algorithms on a common platform. In our earlier works, we focused on developing performance metrics and establishing a substantial dataset with ground truth for object detection and tracking tasks (text and face) in two video domains -- broadcast news and meetings. In this paper, we present the results of a face detection and tracking algorithm on broadcast news videos with the objective of establishing a baseline performance for this task-domain pair. The detection algorithm uses a statistical approach that was originally developed by Viola and Jones and later extended by Lienhart. The algorithm uses a feature set that is Haar-like and a cascade of boosted decision tree classifiers as a statistical model. In this work, we used the Intel Open Source Computer Vision Library (OpenCV) implementation of the Haar face detection algorithm. The optimal values for the tunable parameters of this implementation were found through an experimental design strategy commonly used in statistical analyses of industrial processes. Tracking was accomplished as continuous detection with the detected objects in two frames mapped using a greedy algorithm based on the distances between the centroids of bounding boxes. Results on the evaluation set containing 50 sequences (~ 2.5 mins.) using the developed performance metrics show good performance of the algorithm reflecting the state-of-the-art which makes it an appropriate choice as the baseline algorithm for the problem.
A landmark matching algorithm using the improved generalised Hough transform
NASA Astrophysics Data System (ADS)
Chen, Binbin; Deng, Xingpu
2015-10-01
The paper addresses the issue on landmark matching of images from Geosynchronous Earth Orbit (GEO) satellites. In general, satellite imagery is matched against the base image, which is predefined. When the satellite imagery rotation occurs, the accuracy of many landmark matching algorithms deteriorates. To overcome this problem, generalised Hough transform (GHT) is employed for landmark matching. At first an improved GHT algorithm is proposed to enhance rotational invariance. Secondly a global coastline is processed to generate the test image as the satellite image and the base image. Then the test image is matched against the base image using the proposed algorithm. The matching results show that the proposed algorithm is rotation invariant and works well in landmark matching.
Rayleigh wave nonlinear inversion based on the Firefly algorithm
NASA Astrophysics Data System (ADS)
Zhou, Teng-Fei; Peng, Geng-Xin; Hu, Tian-Yue; Duan, Wen-Sheng; Yao, Feng-Chang; Liu, Yi-Mou
2014-06-01
Rayleigh waves have high amplitude, low frequency, and low velocity, which are treated as strong noise to be attenuated in reflected seismic surveys. This study addresses how to identify useful shear wave velocity profile and stratigraphic information from Rayleigh waves. We choose the Firefly algorithm for inversion of surface waves. The Firefly algorithm, a new type of particle swarm optimization, has the advantages of being robust, highly effective, and allows global searching. This algorithm is feasible and has advantages for use in Rayleigh wave inversion with both synthetic models and field data. The results show that the Firefly algorithm, which is a robust and practical method, can achieve nonlinear inversion of surface waves with high resolution.
Genetic-algorithm-based tri-state neural networks
NASA Astrophysics Data System (ADS)
Uang, Chii-Maw; Chen, Wen-Gong; Horng, Ji-Bin
2002-09-01
A new method, using genetic algorithms, for constructing a tri-state neural network is presented. The global searching features of the genetic algorithms are adopted to help us easily find the interconnection weight matrix of a bipolar neural network. The construction method is based on the biological nervous systems, which evolve the parameters encoded in genes. Taking the advantages of conventional (binary) genetic algorithms, a two-level chromosome structure is proposed for training the tri-state neural network. A Matlab program is developed for simulating the network performances. The results show that the proposed genetic algorithms method not only has the features of accurate of constructing the interconnection weight matrix, but also has better network performance.
Filter model based dwell time algorithm for ion beam figuring
NASA Astrophysics Data System (ADS)
Li, Yun; Xing, Tingwen; Jia, Xin; Wei, Haoming
2010-10-01
The process of Ion Beam Figuring (IBF) can be described by a two-dimensional convolution equation which including dwell time. Solving the dwell time is a key problem in IBF. Theoretically, the dwell time can be solved from a two-dimensional deconvolution. However, it is often ill-posed]; the suitable solution of that is hard to get. In this article, a dwell time algorithm is proposed, depending on the characters of IBF. Usually, the Beam Removal Function (BRF) in IBF is Gaussian, which can be regarded as a headstand Gaussian filter. In its stop-band, the filter has various filtering abilities for various frequencies. The dwell time algorithm proposed in this article is just based on this concept. The Curved Surface Smooth Extension (CSSE) method and Fast Fourier Transform (FFT) algorithm are also used. The simulation results show that this algorithm is high precision, effective, and suitable for actual application.
Adaptive Flocking of Robot Swarms: Algorithms and Properties
NASA Astrophysics Data System (ADS)
Lee, Geunho; Chong, Nak Young
This paper presents a distributed approach for adaptive flocking of swarms of mobile robots that enables to navigate autonomously in complex environments populated with obstacles. Based on the observation of the swimming behavior of a school of fish, we propose an integrated algorithm that allows a swarm of robots to navigate in a coordinated manner, split into multiple swarms, or merge with other swarms according to the environment conditions. We prove the convergence of the proposed algorithm using Lyapunov stability theory. We also verify the effectiveness of the algorithm through extensive simulations, where a swarm of robots repeats the process of splitting and merging while passing around multiple stationary and moving obstacles. The simulation results show that the proposed algorithm is scalable, and robust to variations in the sensing capability of individual robots.
Magnetotelluric inversion via reverse time migration algorithm of seismic data
Ha, Taeyoung . E-mail: tyha@math.snu.ac.kr; Shin, Changsoo . E-mail: css@model.snu.ac.kr
2007-07-01
We propose a new algorithm for two-dimensional magnetotelluric (MT) inversion. Our algorithm is an MT inversion based on the steepest descent method, borrowed from the backpropagation technique of seismic inversion or reverse time migration, introduced in the middle 1980s by Lailly and Tarantola. The steepest descent direction can be calculated efficiently by using the symmetry of numerical Green's function derived from a mixed finite element method proposed by Nedelec for Maxwell's equation, without calculating the Jacobian matrix explicitly. We construct three different objective functions by taking the logarithm of the complex apparent resistivity as introduced in the recent waveform inversion algorithm by Shin and Min. These objective functions can be naturally separated into amplitude inversion, phase inversion and simultaneous inversion. We demonstrate our algorithm by showing three inversion results for synthetic data.
Parallel algorithms for computation of the manipulator inertia matrix
NASA Technical Reports Server (NTRS)
Amin-Javaheri, Masoud; Orin, David E.
1989-01-01
The development of an O(log2N) parallel algorithm for the manipulator inertia matrix is presented. It is based on the most efficient serial algorithm which uses the composite rigid body method. Recursive doubling is used to reformulate the linear recurrence equations which are required to compute the diagonal elements of the matrix. It results in O(log2N) levels of computation. Computation of the off-diagonal elements involves N linear recurrences of varying-size and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log2N) algorithm is presented in both equation and graphic forms which clearly show the parallelism inherent in the algorithm.
Alternating minimization algorithm for speckle reduction with a shifting technique.
Woo, Hyenkyun; Yun, Sangwoon
2012-04-01
Speckles (multiplicative noise) in synthetic aperture radar (SAR) make it difficult to interpret the observed image. Due to the edge-preserving feature of total variation (TV), variational models with TV regularization have attracted much interest in reducing speckles. Algorithms based on the augmented Lagrangian function have been proposed to efficiently solve speckle-reduction variational models with TV regularization. However, these algorithms require inner iterations or inverses involving the Laplacian operator at each iteration. In this paper, we adapt Tseng's alternating minimization algorithm with a shifting technique to efficiently remove the speckle without any inner iterations or inverses involving the Laplacian operator. The proposed method is very simple and highly parallelizable; therefore, it is very efficient to despeckle huge-size SAR images. Numerical results show that our proposed method outperforms the state-of-the-art algorithms for speckle-reduction variational models with a TV regularizer in terms of central-processing-unit time. PMID:22106149
The ordered clustered travelling salesman problem: a hybrid genetic algorithm.
Ahmed, Zakir Hussain
2014-01-01
The ordered clustered travelling salesman problem is a variation of the usual travelling salesman problem in which a set of vertices (except the starting vertex) of the network is divided into some prespecified clusters. The objective is to find the least cost Hamiltonian tour in which vertices of any cluster are visited contiguously and the clusters are visited in the prespecified order. The problem is NP-hard, and it arises in practical transportation and sequencing problems. This paper develops a hybrid genetic algorithm using sequential constructive crossover, 2-opt search, and a local search for obtaining heuristic solution to the problem. The efficiency of the algorithm has been examined against two existing algorithms for some asymmetric and symmetric TSPLIB instances of various sizes. The computational results show that the proposed algorithm is very effective in terms of solution quality and computational time. Finally, we present solution to some more symmetric TSPLIB instances. PMID:24701148
Vertical compression algorithms for sequentially processed statistical files
Batory, D.S.
1984-01-01
Horizontal data compression eliminates redundancies or regularities that occur within individual records. Suppression of trailing blanks and leading zeros are examples. Vertical compression eliminates regularities that occur across consecutively stored records. Prefix and suffix compression are examples. Two new vertical compression algorithms, VRE and HVRE, are presented in this paper. They are based on a combination of character matrix transposition (where rows are initially identified with records) and horizontal compression algorithms (run-length encoding and Huffman encoding). Experimental and theoretical results are presented that show the performance of VRE and HVRE is superior to that of some reputable commercial algorithms. Specifically, these are the compression algorithms of the ADABAS, IDMS and SHRINK/2 data management systems. VRE and HVRE are best suited for compressing statistical files which are sequentially processed and batch updated. They may also be used for file archival and for compressing randomly processed files as well.
A Cultural Algorithm for the Urban Public Transportation
NASA Astrophysics Data System (ADS)
Reyes, Laura Cruz; Zezzatti, Carlos Alberto Ochoa Ortíz; Santillán, Claudia Gómez; Hernández, Paula Hernández; Fuerte, Mercedes Villa
In the last years the population of Leon City, located in the state of Guanajuato in Mexico, has been considerably increasing, causing the inhabitants to waste most of their time with public transportation. As a consequence of the demographic growth and traffic bottleneck, users deal with the daily problem of optimizing their travel so that to get to their destination on time. To give a solution to this problem of obtaining an optimized route between two points in a public transportation, a method based on the cultural algorithms technique is proposed. Cultural algorithms are used in the generated knowledge in a set of time periods for a same population, using a belief space. These types of algorithms are a recent creation. The proposed method seeks a path that minimizes the time of traveling and the number of transfers. The results of the experiment show that the technique of the cultural algorithms is applicable to these kinds of multi-objective problems.
Library of Continuation Algorithms
2005-03-01
LOCA (Library of Continuation Algorithms) is scientific software written in C++ that provides advanced analysis tools for nonlinear systems. In particular, it provides parameter continuation algorithms. bifurcation tracking algorithms, and drivers for linear stability analysis. The algorithms are aimed at large-scale applications that use Newtons method for their nonlinear solve.
Predicting mining activity with parallel genetic algorithms
Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.
2005-01-01
We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.
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
. The estimation strategy has good performance also under degraded adhesion conditions and could be put on board of high-speed railway vehicles; it represents an accurate and reliable solution. The IMU board is tested via a dedicated Hardware in the Loop (HIL) test rig: it includes an industrial robot able to replicate the motion of the railway vehicle. Through the generated experimental outputs the performances of the innovative localisation algorithm have been evaluated: the HIL test rig permitted to test the proposed algorithm, avoiding expensive (in terms of time and cost) on-track tests, obtaining encouraging results. In fact, the preliminary results show a significant improvement of the position and speed estimation performances compared to those obtained with SCMT algorithms, currently in use on the Italian railway network.
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.
2012-01-05
ShowMe3D is a data visualization graphical user interface specifically designed for use with hyperspectral image obtained from the Hyperspectral Confocal Microscope. The program allows the user to select and display any single image from a three dimensional hyperspectral image stack. By moving a slider control, the user can easily move between images of the stack. The user can zoom into any region of the image. The user can select any pixel or region from themore » displayed image and display the fluorescence spectrum associated with that pixel or region. The user can define up to 3 spectral filters to apply to the hyperspectral image and view the image as it would appear from a filter-based confocal microscope. The user can also obtain statistics such as intensity average and variance from selected regions.« less
Sinclair, Michael B
2012-01-05
ShowMe3D is a data visualization graphical user interface specifically designed for use with hyperspectral image obtained from the Hyperspectral Confocal Microscope. The program allows the user to select and display any single image from a three dimensional hyperspectral image stack. By moving a slider control, the user can easily move between images of the stack. The user can zoom into any region of the image. The user can select any pixel or region from the displayed image and display the fluorescence spectrum associated with that pixel or region. The user can define up to 3 spectral filters to apply to the hyperspectral image and view the image as it would appear from a filter-based confocal microscope. The user can also obtain statistics such as intensity average and variance from selected regions.
Benchmark graphs for testing community detection algorithms
NASA Astrophysics Data System (ADS)
Lancichinetti, Andrea; Fortunato, Santo; Radicchi, Filippo
2008-10-01
Community structure is one of the most important features of real networks and reveals the internal organization of the nodes. Many algorithms have been proposed but the crucial issue of testing, i.e., the question of how good an algorithm is, with respect to others, is still open. Standard tests include the analysis of simple artificial graphs with a built-in community structure, that the algorithm has to recover. However, the special graphs adopted in actual tests have a structure that does not reflect the real properties of nodes and communities found in real networks. Here we introduce a class of benchmark graphs, that account for the heterogeneity in the distributions of node degrees and of community sizes. We use this benchmark to test two popular methods of community detection, modularity optimization, and Potts model clustering. The results show that the benchmark poses a much more severe test to algorithms than standard benchmarks, revealing limits that may not be apparent at a first analysis.
A graph spectrum based geometric biclustering algorithm.
Wang, Doris Z; Yan, Hong
2013-01-21
Biclustering is capable of performing simultaneous clustering on two dimensions of a data matrix and has many applications in pattern classification. For example, in microarray experiments, a subset of genes is co-expressed in a subset of conditions, and biclustering algorithms can be used to detect the coherent patterns in the data for further analysis of function. In this paper, we present a graph spectrum based geometric biclustering (GSGBC) algorithm. In the geometrical view, biclusters can be seen as different linear geometrical patterns in high dimensional spaces. Based on this, the modified Hough transform is used to find the Hough vector (HV) corresponding to sub-bicluster patterns in 2D spaces. A graph can be built regarding each HV as a node. The graph spectrum is utilized to identify the eigengroups in which the sub-biclusters are grouped naturally to produce larger biclusters. Through a comparative study, we find that the GSGBC achieves as good a result as GBC and outperforms other kinds of biclustering algorithms. Also, compared with the original geometrical biclustering algorithm, it reduces the computing time complexity significantly. We also show that biologically meaningful biclusters can be identified by our method from real microarray gene expression data. PMID:23079285
Evaluation of Algorithms for Compressing Hyperspectral Data
NASA Technical Reports Server (NTRS)
Cook, Sid; Harsanyi, Joseph; Faber, Vance
2003-01-01
With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.
Algorithms and Application of Sparse Matrix Assembly and Equation Solvers for Aeroacoustics
NASA Technical Reports Server (NTRS)
Watson, W. R.; Nguyen, D. T.; Reddy, C. J.; Vatsa, V. N.; Tang, W. H.
2001-01-01
An algorithm for symmetric sparse equation solutions on an unstructured grid is described. Efficient, sequential sparse algorithms for degree-of-freedom reordering, supernodes, symbolic/numerical factorization, and forward backward solution phases are reviewed. Three sparse algorithms for the generation and assembly of symmetric systems of matrix equations are presented. The accuracy and numerical performance of the sequential version of the sparse algorithms are evaluated over the frequency range of interest in a three-dimensional aeroacoustics application. Results show that the solver solutions are accurate using a discretization of 12 points per wavelength. Results also show that the first assembly algorithm is impractical for high-frequency noise calculations. The second and third assembly algorithms have nearly equal performance at low values of source frequencies, but at higher values of source frequencies the third algorithm saves CPU time and RAM. The CPU time and the RAM required by the second and third assembly algorithms are two orders of magnitude smaller than that required by the sparse equation solver. A sequential version of these sparse algorithms can, therefore, be conveniently incorporated into a substructuring for domain decomposition formulation to achieve parallel computation, where different substructures are handles by different parallel processors.
Algorithmic complexity of a protein
NASA Astrophysics Data System (ADS)
Dewey, T. Gregory
1996-07-01
The information contained in a protein's amino acid sequence dictates its three-dimensional structure. To quantitate the transfer of information that occurs in the protein folding process, the Kolmogorov information entropy or algorithmic complexity of the protein structure is investigated. The algorithmic complexity of an object provides a means of quantitating its information content. Recent results have indicated that the algorithmic complexity of microstates of certain statistical mechanical systems can be estimated from the thermodynamic entropy. In the present work, it is shown that the algorithmic complexity of a protein is given by its configurational entropy. Using this result, a quantitative estimate of the information content of a protein's structure is made and is compared to the information content of the sequence. Additionally, the mutual information between sequence and structure is determined. It is seen that virtually all the information contained in the protein structure is shared with the sequence.
Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources
Bradley, Allison; Yao, Jun; Dewald, Jules; Richter, Claus-Peter
2016-01-01
Background Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized. Methods EEG data were generated by simulating multiple cortical sources (2–4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated. Results While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms. PMID:26809000
Casimir experiments showing saturation effects
Sernelius, Bo E.
2009-10-15
We address several different Casimir experiments where theory and experiment disagree. First out is the classical Casimir force measurement between two metal half spaces; here both in the form of the torsion pendulum experiment by Lamoreaux and in the form of the Casimir pressure measurement between a gold sphere and a gold plate as performed by Decca et al.; theory predicts a large negative thermal correction, absent in the high precision experiments. The third experiment is the measurement of the Casimir force between a metal plate and a laser irradiated semiconductor membrane as performed by Chen et al.; the change in force with laser intensity is larger than predicted by theory. The fourth experiment is the measurement of the Casimir force between an atom and a wall in the form of the measurement by Obrecht et al. of the change in oscillation frequency of a {sup 87}Rb Bose-Einstein condensate trapped to a fused silica wall; the change is smaller than predicted by theory. We show that saturation effects can explain the discrepancies between theory and experiment observed in all these cases.
Kim, Ye-seul; Park, Hye-suk; Lee, Haeng-Hwa; Choi, Young-Wook; Choi, Jae-Gu; Kim, Hak Hee; Kim, Hee-Joung
2016-02-01
Digital breast tomosynthesis (DBT) is a recently developed system for three-dimensional imaging that offers the potential to reduce the false positives of mammography by preventing tissue overlap. Many qualitative evaluations of digital breast tomosynthesis were previously performed by using a phantom with an unrealistic model and with heterogeneous background and noise, which is not representative of real breasts. The purpose of the present work was to compare reconstruction algorithms for DBT by using various breast phantoms; validation was also performed by using patient images. DBT was performed by using a prototype unit that was optimized for very low exposures and rapid readout. Three algorithms were compared: a back-projection (BP) algorithm, a filtered BP (FBP) algorithm, and an iterative expectation maximization (EM) algorithm. To compare the algorithms, three types of breast phantoms (homogeneous background phantom, heterogeneous background phantom, and anthropomorphic breast phantom) were evaluated, and clinical images were also reconstructed by using the different reconstruction algorithms. The in-plane image quality was evaluated based on the line profile and the contrast-to-noise ratio (CNR), and out-of-plane artifacts were evaluated by means of the artifact spread function (ASF). Parenchymal texture features of contrast and homogeneity were computed based on reconstructed images of an anthropomorphic breast phantom. The clinical images were studied to validate the effect of reconstruction algorithms. The results showed that the CNRs of masses reconstructed by using the EM algorithm were slightly higher than those obtained by using the BP algorithm, whereas the FBP algorithm yielded much lower CNR due to its high fluctuations of background noise. The FBP algorithm provides the best conspicuity for larger calcifications by enhancing their contrast and sharpness more than the other algorithms; however, in the case of small-size and low
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
Word frequency statistics by tree-structure algorithm research
NASA Astrophysics Data System (ADS)
Li, Huanqin; Yan, Shi-Tao
2013-03-01
English articles for obtaining statistics is very convenient, Because there are space between words , While due to the characteristics of Chinese word-formation, Chinese articles statistical is very difficult. In the study on the basis of previous methods put forward a new kind of more keywords matching method-- Word frequency statistics by Treestructure algorithm. In implementing this algorithm based on its performance is analyzed. The result shows that this method can realize a scan statistics shows all words of information. Consumed time is greatly reduced.
Markov chain algorithms: a template for building future robust low-power systems
Deka, Biplab; Birklykke, Alex A.; Duwe, Henry; Mansinghka, Vikash K.; Kumar, Rakesh
2014-01-01
Although computational systems are looking towards post CMOS devices in the pursuit of lower power, the expected inherent unreliability of such devices makes it difficult to design robust systems without additional power overheads for guaranteeing robustness. As such, algorithmic structures with inherent ability to tolerate computational errors are of significant interest. We propose to cast applications as stochastic algorithms based on Markov chains (MCs) as such algorithms are both sufficiently general and tolerant to transition errors. We show with four example applications—Boolean satisfiability, sorting, low-density parity-check decoding and clustering—how applications can be cast as MC algorithms. Using algorithmic fault injection techniques, we demonstrate the robustness of these implementations to transition errors with high error rates. Based on these results, we make a case for using MCs as an algorithmic template for future robust low-power systems. PMID:24842030
A novel blinding digital watermark algorithm based on lab color space
NASA Astrophysics Data System (ADS)
Dong, Bing-feng; Qiu, Yun-jie; Lu, Hong-tao
2010-02-01
It is necessary for blinding digital image watermark algorithm to extract watermark information without any extra information except the watermarked image itself. But most of the current blinding watermark algorithms have the same disadvantage: besides the watermarked image, they also need the size and other information about the original image when extracting the watermark. This paper presents an innovative blinding color image watermark algorithm based on Lab color space, which does not have the disadvantages mentioned above. This algorithm first marks the watermark region size and position through embedding some regular blocks called anchor points in image spatial domain, and then embeds the watermark into the image. In doing so, the watermark information can be easily extracted after doing cropping and scale change to the image. Experimental results show that the algorithm is particularly robust against the color adjusting and geometry transformation. This algorithm has already been used in a copyright protecting project and works very well.
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Adaptive optics image deconvolution based on a modified Richardson-Lucy algorithm
NASA Astrophysics Data System (ADS)
Chen, Bo; Geng, Ze-xun; Yan, Xiao-dong; Yang, Yang; Sui, Xue-lian; Zhao, Zhen-lei
2007-12-01
Adaptive optical (AO) system provides a real-time compensation for atmospheric turbulence. However, the correction is often only partial, and a deconvolution is required for reaching the diffraction limit. The Richardson-Lucy (R-L) Algorithm is the technique most widely used for AO image deconvolution, but Standard R-L Algorithm (SRLA) is often puzzled by speckling phenomenon, wraparound artifact and noise problem. A Modified R-L Algorithm (MRLA) for AO image deconvolution is presented. This novel algorithm applies Magain's correct sampling approach and incorporating noise statistics to Standard R-L Algorithm. The alternant iterative method is applied to estimate PSF and object in the novel algorithm. Comparing experiments for indoor data and AO image are done with SRLA and the MRLA in this paper. Experimental results show that this novel MRLA outperforms the SRLA.
An improved filter-u least mean square vibration control algorithm for aircraft framework.
Huang, Quanzhen; Luo, Jun; Gao, Zhiyuan; Zhu, Xiaojin; Li, Hengyu
2014-09-01
Active vibration control of aerospace vehicle structures is very a hot spot and in which filter-u least mean square (FULMS) algorithm is one of the key methods. But for practical reasons and technical limitations, vibration reference signal extraction is always a difficult problem for FULMS algorithm. To solve the vibration reference signal extraction problem, an improved FULMS vibration control algorithm is proposed in this paper. Reference signal is constructed based on the controller structure and the data in the algorithm process, using a vibration response residual signal extracted directly from the vibration structure. To test the proposed algorithm, an aircraft frame model is built and an experimental platform is constructed. The simulation and experimental results show that the proposed algorithm is more practical with a good vibration suppression performance. PMID:25273765
A simple, pipelined algorithm for large, irregular all-gather problems.
Traff, J. L.; Ripke, A.; Siebert, C.; Balaji, P.; Thakur, R.; Gropp, W.; Mathematics and Computer Science; NEC Lab.; Univ. of Illinois
2008-01-01
We present and evaluate a new, simple, pipelined algorithm for large, irregular all-gather problems, useful for the implementation of the MPI-Allgatherv collective operation of MPI. The algorithm can be viewed as an adaptation of a linear ring algorithm for regular all-gather problems for single-ported, clustered multiprocessors to the irregular problem. Compared to the standard ring algorithm, whose performance is dominated by the largest data size broadcast by a process (times the number of processes), the performance of the new algorithm depends only on the total amount of data over all processes. The new algorithm has been implemented within different MPI libraries. Benchmark results on NEC SX-8, Linux clusters with InfiniBand and Gigabit Ethernet, Blue Gene/P, and SiCortex systems show huge performance gains in accordance with the expected behavior.
[An improved fast algorithm for ray casting volume rendering of medical images].
Tao, Ling; Wang, Huina; Tian, Zhiliang
2006-10-01
Ray casting algorithm can obtain better quality images in volume rendering, however, it presents some problems such as powerful computing capacity and slow rendering velocity. Therefore, a new fast algorithm of ray casting volume rendering is proposed in this paper. This algorithm reduces matrix computation by the matrix transformation characteristics of re-sampling points in two coordinate system, so re-sampled computational process is accelerated. By extending the Bresenham algorithm to three dimension and utilizing boundary box technique, this algorithm avoids the sampling in empty voxel and greatly improves the efficiency of ray casting. The experiment results show that the improved acceleration algorithm can produce the required quality images, at the same time reduces the total operations remarkably, and speeds up the volume rendering. PMID:17121341
NASA Astrophysics Data System (ADS)
Nawi, Nazri Mohd.; Khan, Abdullah; Rehman, M. Z.
2015-05-01
A nature inspired behavior metaheuristic techniques which provide derivative-free solutions to solve complex problems. One of the latest additions to the group of nature inspired optimization procedure is Cuckoo Search (CS) algorithm. Artificial Neural Network (ANN) training is an optimization task since it is desired to find optimal weight set of a neural network in training process. Traditional training algorithms have some limitation such as getting trapped in local minima and slow convergence rate. This study proposed a new technique CSLM by combining the best features of two known algorithms back-propagation (BP) and Levenberg Marquardt algorithm (LM) for improving the convergence speed of ANN training and avoiding local minima problem by training this network. Some selected benchmark classification datasets are used for simulation. The experiment result show that the proposed cuckoo search with Levenberg Marquardt algorithm has better performance than other algorithm used in this study.
Analysis of multigrid algorithms for nonsymmetric and indefinite elliptic problems
Bramble, J.H.; Pasciak, J.E.; Xu, J.
1988-10-01
We prove some new estimates for the convergence of multigrid algorithms applied to nonsymmetric and indefinite elliptic boundary value problems. We provide results for the so-called 'symmetric' multigrid schemes. We show that for the variable V-script-cycle and the W-script-cycle schemes, multigrid algorithms with any amount of smoothing on the finest grid converge at a rate that is independent of the number of levels or unknowns, provided that the initial grid is sufficiently fine. We show that the V-script-cycle algorithm also converges (under appropriate assumptions on the coarsest grid) but at a rate which may deteriorate as the number of levels increases. This deterioration for the V-script-cycle may occur even in the case of full elliptic regularity. Finally, the results of numerical experiments are given which illustrate the convergence behavior suggested by the theory.
Multiple sequence alignment algorithm based on a dispersion graph and ant colony algorithm.
Chen, Weiyang; Liao, Bo; Zhu, Wen; Xiang, Xuyu
2009-10-01
In this article, we describe a representation for the processes of multiple sequences alignment (MSA) and used it to solve the problem of MSA. By this representation, we took every possible aligning result into account by defining the representation of gap insertion, the value of heuristic information in every optional path and scoring rule. On the basis of the proposed multidimensional graph, we used the ant colony algorithm to find the better path that denotes a better aligning result. In our article, we proposed the instance of three-dimensional graph and four-dimensional graph and advanced a special ichnographic representation to analyze MSA. It is yet only an experimental software, and we gave an example for finding the best aligning result by three-dimensional graph and ant colony algorithm. Experimental results show that our method can improve the solution quality on MSA benchmarks. PMID:19130503
Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci
NASA Astrophysics Data System (ADS)
Kosmale, Miriam; Popp, Thomas
2016-04-01
Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.
Faster algorithms for RNA-folding using the Four-Russians method
2014-01-01
Background The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n3) time using Nussinov’s dynamic programming algorithm. The Four-Russians method is a technique that reduces the running time for certain dynamic programming algorithms by a multiplicative factor after a preprocessing step where solutions to all smaller subproblems of a fixed size are exhaustively enumerated and solved. Frid and Gusfield designed an O(n3logn) algorithm for RNA folding using the Four-Russians technique. In their algorithm the preprocessing is interleaved with the algorithm computation. Theoretical results We simplify the algorithm and the analysis by doing the preprocessing once prior to the algorithm computation. We call this the two-vector method. We also show variants where instead of exhaustive preprocessing, we only solve the subproblems encountered in the main algorithm once and memoize the results. We give a simple proof of correctness and explore the practical advantages over the earlier method. The Nussinov algorithm admits an O(n2) time parallel algorithm. We show a parallel algorithm using the two-vector idea that improves the time bound to O(n2logn). Practical results We have implemented the parallel algorithm on graphics processing units using the CUDA platform. We discuss the organization of the data structures to exploit coalesced memory access for fast running times. The ideas to organize the data structures also help in improving the running time of the serial algorithms. For sequences of length up to 6000 bases the parallel algorithm takes only about 2.5 seconds and the two-vector serial method takes about 57 seconds on a desktop and 15 seconds on a server. Among the serial algorithms, the two-vector and memoized versions are faster than the Frid-Gusfield algorithm by a factor of 3, and are faster than Nussinov by up to a factor of 20. The source-code for the
A comparative analysis of biclustering algorithms for gene expression data.
Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V
2013-05-01
The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837
An enhanced algorithm to estimate BDS satellite's differential code biases
NASA Astrophysics Data System (ADS)
Shi, Chuang; Fan, Lei; Li, Min; Liu, Zhizhao; Gu, Shengfeng; Zhong, Shiming; Song, Weiwei
2016-02-01
This paper proposes an enhanced algorithm to estimate the differential code biases (DCB) on three frequencies of the BeiDou Navigation Satellite System (BDS) satellites. By forming ionospheric observables derived from uncombined precise point positioning and geometry-free linear combination of phase-smoothed range, satellite DCBs are determined together with ionospheric delay that is modeled at each individual station. Specifically, the DCB and ionospheric delay are estimated in a weighted least-squares estimator by considering the precision of ionospheric observables, and a misclosure constraint for different types of satellite DCBs is introduced. This algorithm was tested by GNSS data collected in November and December 2013 from 29 stations of Multi-GNSS Experiment (MGEX) and BeiDou Experimental Tracking Stations. Results show that the proposed algorithm is able to precisely estimate BDS satellite DCBs, where the mean value of day-to-day scattering is about 0.19 ns and the RMS of the difference with respect to MGEX DCB products is about 0.24 ns. In order to make comparison, an existing algorithm based on IGG: Institute of Geodesy and Geophysics, China (IGGDCB), is also used to process the same dataset. Results show that, the DCB difference between results from the enhanced algorithm and the DCB products from Center for Orbit Determination in Europe (CODE) and MGEX is reduced in average by 46 % for GPS satellites and 14 % for BDS satellites, when compared with DCB difference between the results of IGGDCB algorithm and the DCB products from CODE and MGEX. In addition, we find the day-to-day scattering of BDS IGSO satellites is obviously lower than that of GEO and MEO satellites, and a significant bias exists in daily DCB values of GEO satellites comparing with MGEX DCB product. This proposed algorithm also provides a new approach to estimate the satellite DCBs of multiple GNSS systems.
NASA Technical Reports Server (NTRS)
2005-01-01
False color images of Saturn's moon, Mimas, reveal variation in either the composition or texture across its surface.
During its approach to Mimas on Aug. 2, 2005, the Cassini spacecraft narrow-angle camera obtained multi-spectral views of the moon from a range of 228,000 kilometers (142,500 miles).
The image at the left is a narrow angle clear-filter image, which was separately processed to enhance the contrast in brightness and sharpness of visible features. The image at the right is a color composite of narrow-angle ultraviolet, green, infrared and clear filter images, which have been specially processed to accentuate subtle changes in the spectral properties of Mimas' surface materials. To create this view, three color images (ultraviolet, green and infrared) were combined into a single black and white picture that isolates and maps regional color differences. This 'color map' was then superimposed over the clear-filter image at the left.
The combination of color map and brightness image shows how the color differences across the Mimas surface materials are tied to geological features. Shades of blue and violet in the image at the right are used to identify surface materials that are bluer in color and have a weaker infrared brightness than average Mimas materials, which are represented by green.
Herschel crater, a 140-kilometer-wide (88-mile) impact feature with a prominent central peak, is visible in the upper right of each image. The unusual bluer materials are seen to broadly surround Herschel crater. However, the bluer material is not uniformly distributed in and around the crater. Instead, it appears to be concentrated on the outside of the crater and more to the west than to the north or south. The origin of the color differences is not yet understood. It may represent ejecta material that was excavated from inside Mimas when the Herschel impact occurred. The bluer color of these materials may be caused by subtle differences in
Analysis of exclusive kT jet algorithms in electron-positron annihilation
NASA Astrophysics Data System (ADS)
Chay, Junegone; Kim, Chul; Kim, Inchol
2015-10-01
We study the factorization of the dijet cross section in e+e- annihilation using the generalized exclusive jet algorithm which includes the cone-type, the JADE, the kT, the anti-kT and the Cambridge/Aachen jet algorithms as special cases. In order to probe the characteristics of the jet algorithms in a unified way, we consider the generalized kT jet algorithm with an arbitrary weight of the energies, in which various types of the kT-type algorithms are included for specific values of the parameter. We show that the jet algorithm respects the factorization property for the parameter α <2 . The factorized jet function and the soft function are well defined and infrared safe for all the jet algorithms except the kT algorithm. The kT algorithm (α =2 ) breaks the factorization since the jet and the soft functions are infrared divergent and are not defined for α =2 , though the dijet cross section is infrared finite. In the jet algorithms which enable factorization, we give a phenomenological analysis using the resummed and the fixed-order results.
NASA Astrophysics Data System (ADS)
Qi, Wei; Zhang, Chi; Fu, Guangtao; Zhou, Huicheng
2016-02-01
It is widely recognized that optimization algorithm parameters have significant impacts on algorithm performance, but quantifying the influence is very complex and difficult due to high computational demands and dynamic nature of search parameters. The overall aim of this paper is to develop a global sensitivity analysis based framework to dynamically quantify the individual and interactive influence of algorithm parameters on algorithm performance. A variance decomposition sensitivity analysis method, Analysis of Variance (ANOVA), is used for sensitivity quantification, because it is capable of handling small samples and more computationally efficient compared with other approaches. The Shuffled Complex Evolution method developed at the University of Arizona algorithm (SCE-UA) is selected as an optimization algorithm for investigation, and two criteria, i.e., convergence speed and success rate, are used to measure the performance of SCE-UA. Results show the proposed framework can effectively reveal the dynamic sensitivity of algorithm parameters in the search processes, including individual influences of parameters and their interactive impacts. Interactions between algorithm parameters have significant impacts on SCE-UA performance, which has not been reported in previous research. The proposed framework provides a means to understand the dynamics of algorithm parameter influence, and highlights the significance of considering interactive parameter influence to improve algorithm performance in the search processes.
Test Results for Entry Guidance Methods for Reusable Launch Vehicles
NASA Technical Reports Server (NTRS)
Hanson, John M.; Jones, Robert E.
2003-01-01
There are a number of approaches to advanced guidance and control (AG&C) that have the potential for achieving the goals of significantly increasing reusable launch vehicle (RLV) safety and reliability, and reducing the cost. This paper examines some approaches to entry guidance. An effort called Integration and Testing of Advanced Guidance and Control Technologies (ITAGCT) has recently completed a rigorous testing phase where these algorithms faced high-fidelity vehicle models and were required to perform a variety of representative tests. The algorithm developers spent substantial effort improving the algorithm performance in the testing. This paper lists the test cases used to demonstrate that the desired results are achieved, shows an automated test scoring method that greatly reduces the evaluation effort required, and displays results of the tests. Results show a significant improvement over previous guidance approaches. The two best-scoring algorithm approaches show roughly equivalent results and are ready to be applied to future reusable vehicle concepts.
Test Results for Entry Guidance Methods for Space Vehicles
NASA Technical Reports Server (NTRS)
Hanson, John M.; Jones, Robert E.
2004-01-01
There are a number of approaches to advanced guidance and control that have the potential for achieving the goals of significantly increasing reusable launch vehicle (or any space vehicle that enters an atmosphere) safety and reliability, and reducing the cost. This paper examines some approaches to entry guidance. An effort called Integration and Testing of Advanced Guidance and Control Technologies has recently completed a rigorous testing phase where these algorithms faced high-fidelity vehicle models and were required to perform a variety of representative tests. The algorithm developers spent substantial effort improving the algorithm performance in the testing. This paper lists the test cases used to demonstrate that the desired results are achieved, shows an automated test scoring method that greatly reduces the evaluation effort required, and displays results of the tests. Results show a significant improvement over previous guidance approaches. The two best-scoring algorithm approaches show roughly equivalent results and are ready to be applied to future vehicle concepts.
Luo, Liyan; Xu, Luping; Zhang, Hua
2015-01-01
In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233
An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors
Luo, Liyan; Xu, Luping; Zhang, Hua
2015-01-01
In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233
NASA Astrophysics Data System (ADS)
Yuan, Jian-guo; Tong, Qing-zhen; Huang, Sheng; Wang, Yong
2013-11-01
An effective hierarchical reliable belief propagation (HRBP) decoding algorithm is proposed according to the structural characteristics of systematically constructed Gallager low-density parity-check (SCG-LDPC) codes. The novel decoding algorithm combines the layered iteration with the reliability judgment, and can greatly reduce the number of the variable nodes involved in the subsequent iteration process and accelerate the convergence rate. The result of simulation for SCG-LDPC(3969,3720) code shows that the novel HRBP decoding algorithm can greatly reduce the computing amount at the condition of ensuring the performance compared with the traditional belief propagation (BP) algorithm. The bit error rate (BER) of the HRBP algorithm is considerable at the threshold value of 15, but in the subsequent iteration process, the number of the variable nodes for the HRBP algorithm can be reduced by about 70% at the high signal-to-noise ratio (SNR) compared with the BP algorithm. When the threshold value is further increased, the HRBP algorithm will gradually degenerate into the layered-BP algorithm, but at the BER of 10-7 and the maximal iteration number of 30, the net coding gain (NCG) of the HRBP algorithm is 0.2 dB more than that of the BP algorithm, and the average iteration times can be reduced by about 40% at the high SNR. Therefore, the novel HRBP decoding algorithm is more suitable for optical communication systems.
NASA Technical Reports Server (NTRS)
Davis, Curt H.
1993-01-01
The NASA and ESA retracking algorithms are compared with an algorithm based upon a combined surface and volume (S/V) scattering model. First, the S/V, NASA, and ESA algorithms were used to retrack over 400,000 altimeter return waveforms from the Greenland and Antarctic ice sheets. The surface elevations from the S/V algorithm were compared with the elevations produced by the NASA and ESA algorithms to determine the relative accuracy of these algorithms when subsurface volume-scattering occurs. The results show that the NASA algorithm produced surface elevations within 35 to 50 cm of the S/V algorithm, while the performance of the ESA algorithm was slightly worse. Next, by analyzing several thousand satellite crossover points from the Antarctic data set, we determined the retracking algorithm that produced the most repeatable surface elevations. The elevations derived from the S/V algorithm had the smallest RMS error for the region of the East Antarctic plateau examined here. The ESA algorithm produced erroneous estimates of elevation change when seasonal variations were present; it measured 0.7 to 1.6-m change in elevation over a 6-month period on the East Antarctic plateau where accumulation rates are only 10 cm/year.
Yan, Aimin; Wu, Xizeng; Liu, Hong
2010-01-01
The phase retrieval is an important task in x-ray phase contrast imaging. The robustness of phase retrieval is especially important for potential medical imaging applications such as phase contrast mammography. Recently the authors developed an iterative phase retrieval algorithm, the attenuation-partition based algorithm, for the phase retrieval in inline phase-contrast imaging [1]. Applied to experimental images, the algorithm was proven to be fast and robust. However, a quantitative analysis of the performance of this new algorithm is desirable. In this work, we systematically compared the performance of this algorithm with other two widely used phase retrieval algorithms, namely the Gerchberg-Saxton (GS) algorithm and the Transport of Intensity Equation (TIE) algorithm. The systematical comparison is conducted by analyzing phase retrieval performances with a digital breast specimen model. We show that the proposed algorithm converges faster than the GS algorithm in the Fresnel diffraction regime, and is more robust against image noise than the TIE algorithm. These results suggest the significance of the proposed algorithm for future medical applications with the x-ray phase contrast imaging technique. PMID:20720992
CSA: An efficient algorithm to improve circular DNA multiple alignment
Fernandes, Francisco; Pereira, Luísa; Freitas, Ana T
2009-01-01
Background The comparison of homologous sequences from different species is an essential approach to reconstruct the evolutionary history of species and of the genes they harbour in their genomes. Several complete mitochondrial and nuclear genomes are now available, increasing the importance of using multiple sequence alignment algorithms in comparative genomics. MtDNA has long been used in phylogenetic analysis and errors in the alignments can lead to errors in the interpretation of evolutionary information. Although a large number of multiple sequence alignment algorithms have been proposed to date, they all deal with linear DNA and cannot handle directly circular DNA. Researchers interested in aligning circular DNA sequences must first rotate them to the "right" place using an essentially manual process, before they can use multiple sequence alignment tools. Results In this paper we propose an efficient algorithm that identifies the most interesting region to cut circular genomes in order to improve phylogenetic analysis when using standard multiple sequence alignment algorithms. This algorithm identifies the largest chain of non-repeated longest subsequences common to a set of circular mitochondrial DNA sequences. All the sequences are then rotated and made linear for multiple alignment purposes. To evaluate the effectiveness of this new tool, three different sets of mitochondrial DNA sequences were considered. Other tests considering randomly rotated sequences were also performed. The software package Arlequin was used to evaluate the standard genetic measures of the alignments obtained with and without the use of the CSA algorithm with two well known multiple alignment algorithms, the CLUSTALW and the MAVID tools, and also the visualization tool SinicView. Conclusion The results show that a circularization and rotation pre-processing step significantly improves the efficiency of public available multiple sequence alignment algorithms when used in the
Linsen, Sarah; Torbeyns, Joke; Verschaffel, Lieven; Reynvoet, Bert; De Smedt, Bert
2016-03-01
There are two well-known computation methods for solving multi-digit subtraction items, namely mental and algorithmic computation. It has been contended that mental and algorithmic computation differentially rely on numerical magnitude processing, an assumption that has already been examined in children, but not yet in adults. Therefore, in this study, we examined how numerical magnitude processing was associated with mental and algorithmic computation, and whether this association with numerical magnitude processing was different for mental versus algorithmic computation. We also investigated whether the association between numerical magnitude processing and mental and algorithmic computation differed for measures of symbolic versus nonsymbolic numerical magnitude processing. Results showed that symbolic, and not nonsymbolic, numerical magnitude processing was associated with mental computation, but not with algorithmic computation. Additional analyses showed, however, that the size of this association with symbolic numerical magnitude processing was not significantly different for mental and algorithmic computation. We also tried to further clarify the association between numerical magnitude processing and complex calculation by also including relevant arithmetical subskills, i.e. arithmetic facts, needed for complex calculation that are also known to be dependent on numerical magnitude processing. Results showed that the associations between symbolic numerical magnitude processing and mental and algorithmic computation were fully explained by individual differences in elementary arithmetic fact knowledge. PMID:26914586
ICESat-2 / ATLAS Flight Science Receiver Algorithms
NASA Astrophysics Data System (ADS)
Mcgarry, J.; Carabajal, C. C.; Degnan, J. J.; Mallama, A.; Palm, S. P.; Ricklefs, R.; Saba, J. L.
2013-12-01
. This Simulator makes it possible to check all logic paths that could be encountered by the Algorithms on orbit. In addition the NASA airborne instrument MABEL is collecting data with characteristics similar to what ATLAS will see. MABEL data is being used to test the ATLAS Receiver Algorithms. Further verification will be performed during Integration and Testing of the ATLAS instrument and during Environmental Testing on the full ATLAS instrument. Results from testing to date show the Receiver Algorithms have the ability to handle a wide range of signal and noise levels with a very good sensitivity at relatively low signal to noise ratios. In addition, preliminary tests have demonstrated, using the ICESat-2 Science Team's selected land ice and sea ice test cases, the capability of the Algorithms to successfully find and telemeter the surface echoes. In this presentation we will describe the ATLAS Flight Science Receiver Algorithms and the Software Simulator, and will present results of the testing to date. The onboard databases (DEM, DRM and the Surface Reference Mask) are being developed at the University of Texas at Austin as part of the ATLAS Flight Science Receiver Algorithms. Verification of the onboard databases is being performed by ATLAS Receiver Algorithms team members Claudia Carabajal and Jack Saba.
Predicting the performance of a spatial gamut mapping algorithm
NASA Astrophysics Data System (ADS)
Bakke, Arne M.; Farup, Ivar; Hardeberg, Jon Y.
2009-01-01
Gamut mapping algorithms are currently being developed to take advantage of the spatial information in an image to improve the utilization of the destination gamut. These algorithms try to preserve the spatial information between neighboring pixels in the image, such as edges and gradients, without sacrificing global contrast. Experiments have shown that such algorithms can result in significantly improved reproduction of some images compared with non-spatial methods. However, due to the spatial processing of images, they introduce unwanted artifacts when used on certain types of images. In this paper we perform basic image analysis to predict whether a spatial algorithm is likely to perform better or worse than a good, non-spatial algorithm. Our approach starts by detecting the relative amount of areas in the image that are made up of uniformly colored pixels, as well as the amount of areas that contain details in out-of-gamut areas. A weighted difference is computed from these numbers, and we show that the result has a high correlation with the observed performance of the spatial algorithm in a previously conducted psychophysical experiment.
Artificial immune algorithm for multi-depot vehicle scheduling problems
NASA Astrophysics Data System (ADS)
Wu, Zhongyi; Wang, Donggen; Xia, Linyuan; Chen, Xiaoling
2008-10-01
In the fast-developing logistics and supply chain management fields, one of the key problems in the decision support system is that how to arrange, for a lot of customers and suppliers, the supplier-to-customer assignment and produce a detailed supply schedule under a set of constraints. Solutions to the multi-depot vehicle scheduling problems (MDVRP) help in solving this problem in case of transportation applications. The objective of the MDVSP is to minimize the total distance covered by all vehicles, which can be considered as delivery costs or time consumption. The MDVSP is one of nondeterministic polynomial-time hard (NP-hard) problem which cannot be solved to optimality within polynomial bounded computational time. Many different approaches have been developed to tackle MDVSP, such as exact algorithm (EA), one-stage approach (OSA), two-phase heuristic method (TPHM), tabu search algorithm (TSA), genetic algorithm (GA) and hierarchical multiplex structure (HIMS). Most of the methods mentioned above are time consuming and have high risk to result in local optimum. In this paper, a new search algorithm is proposed to solve MDVSP based on Artificial Immune Systems (AIS), which are inspirited by vertebrate immune systems. The proposed AIS algorithm is tested with 30 customers and 6 vehicles located in 3 depots. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving MDVSP problems.
Incremental k-core decomposition: Algorithms and evaluation
Sariyuce, Ahmet Erdem; Gedik, Bugra; Jacques-SIlva, Gabriela; Wu, Kun -Lung; Catalyurek, Umit V.
2016-02-01
A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that ismore » guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. Furthermore, for a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms.« less
Performance of recovery time improvement algorithms for software RAIDs
Riegel, J.; Menon, Jai
1996-12-31
A software RAID is a RAID implemented purely in software running on a host computer. One problem with software RAIDs is that they do not have access to special hardware such as NVRAM. Thus, software RAIDs may need to check every parity group of an array for consistency following a host crash or power failure. This process of checking parity groups is called recovery, and results in long delays when the software RAID is restarted. In this paper, we review two algorithms to reduce this recovery time for software RAIDs: the PGS Bitmap algorithm we proposed in and the List Algorithm proposed in. We compare the performance of these two algorithms using trace-driven simulations. Our results show that the PGS Bitmap Algorithm can reduce recovery time by a factor of 12 with a response time penalty of less than 1%, or by a factor of 50 with a response time penalty of less than 2%, and a memory requirement of around 9 Kbytes. The List Algorithm can reduce recovery time by a factor of 50 but cannot achieve a response time penalty of less than 16%.
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
NASA Technical Reports Server (NTRS)
Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)
2000-01-01
We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.
Alpuche Aviles, Jorge E; Pistorius, Stephen; Gordon, Richard; Elbakri, Idris A
2011-01-01
This work presents a first generation incoherent scatter CT (ISCT) hybrid (analytic-iterative) reconstruction algorithm for accurate ρ{e}imaging of objects with clinically relevant sizes. The algorithm reconstructs quantitative images of ρ{e} within a few iterations, avoiding the challenges of optimization based reconstruction algorithms while addressing the limitations of current analytical algorithms. A 4π detector is conceptualized in order to address the issue of directional dependency and is then replaced with a ring of detectors which detect a constant fraction of the scattered photons. The ISCT algorithm corrects for the attenuation of photons using a limited number of iterations and filtered back projection (FBP) for image reconstruction. This results in a hybrid reconstruction algorithm that was tested with sinograms generated by Monte Carlo (MC) and analytical (AN) simulations. Results show that the ISCT algorithm is weakly dependent on the ρ{e} initial estimate. Simulation results show that the proposed algorithm reconstruct ρ{e} images with a mean error of -1% ± 3% for the AN model and from -6% to -8% for the MC model. Finally, the algorithm is capable of reconstructing qualitatively good images even in the presence of multiple scatter. The proposed algorithm would be suitable for in-vivo medical imaging as long as practical limitations can be addressed. PMID:21422588
Evaluation of Demons- and FEM-Based Registration Algorithms for Lung Cancer.
Yang, Juan; Li, Dengwang; Yin, Yong; Zhao, Fen; Wang, Hongjun
2016-04-01
We evaluated and compared the accuracy of 2 deformable image registration algorithms in 4-dimensional computed tomography images for patients with lung cancer. Ten patients with non-small cell lung cancer or small cell lung cancer were enrolled in this institutional review board-approved study. The displacement vector fields relative to a specific reference image were calculated by using the diffeomorphic demons (DD) algorithm and the finite element method (FEM)-based algorithm. The registration accuracy was evaluated by using normalized mutual information (NMI), the sum of squared intensity difference (SSD), modified Hausdorff distance (dH_M), and ratio of gross tumor volume (rGTV) difference between reference image and deformed phase image. We also compared the registration speed of the 2 algorithms. Of all patients, the FEM-based algorithm showed stronger ability in aligning 2 images than the DD algorithm. The means (±standard deviation) of NMI were 0.86 (±0.05) and 0.90 (±0.05) using the DD algorithm and the FEM-based algorithm, respectively. The means of SSD were 0.006 (±0.003) and 0.003 (±0.002) using the DD algorithm and the FEM-based algorithm, respectively. The means of dH_M were 0.04 (±0.02) and 0.03 (±0.03) using the DD algorithm and the FEM-based algorithm, respectively. The means of rGTV were 3.9% (±1.01%) and 2.9% (±1.1%) using the DD algorithm and the FEM-based algorithm, respectively. However, the FEM-based algorithm costs a longer time than the DD algorithm, with the average running time of 31.4 minutes compared to 21.9 minutes for all patients. The preliminary results showed that the FEM-based algorithm was more accurate than the DD algorithm while compromised with the registration speed. PMID:25817713
Multithreaded Algorithms for Graph Coloring
Catalyurek, Umit V.; Feo, John T.; Gebremedhin, Assefaw H.; Halappanavar, Mahantesh; Pothen, Alex
2012-10-21
Graph algorithms are challenging to parallelize when high performance and scalability are primary goals. Low concurrency, poor data locality, irregular access pattern, and high data access to computation ratio are among the chief reasons for the challenge. The performance implication of these features is exasperated on distributed memory machines. More success is being achieved on shared-memory, multi-core architectures supporting multithreading. We consider a prototypical graph problem, coloring, and show how a greedy algorithm for solving it can be e*ectively parallelized on multithreaded architectures. We present in particular two di*erent parallel algorithms. The first relies on speculation and iteration, and is suitable for any shared-memory, multithreaded system. The second uses data ow principles and is targeted at the massively multithreaded Cray XMT system. We benchmark the algorithms on three di*erent platforms and demonstrate scalable runtime performance. In terms of quality of solution, both algorithms use nearly the same number of colors as the serial algorithm.
Computer program for fast Karhunen Loeve transform algorithm
NASA Technical Reports Server (NTRS)
Jain, A. K.
1976-01-01
The fast KL transform algorithm was applied for data compression of a set of four ERTS multispectral images and its performance was compared with other techniques previously studied on the same image data. The performance criteria used here are mean square error and signal to noise ratio. The results obtained show a superior performance of the fast KL transform coding algorithm on the data set used with respect to the above stated perfomance criteria. A summary of the results is given in Chapter I and details of comparisons and discussion on conclusions are given in Chapter IV.
Acoustic design of rotor blades using a genetic algorithm
NASA Technical Reports Server (NTRS)
Wells, V. L.; Han, A. Y.; Crossley, W. A.
1995-01-01
A genetic algorithm coupled with a simplified acoustic analysis was used to generate low-noise rotor blade designs. The model includes thickness, steady loading and blade-vortex interaction noise estimates. The paper presents solutions for several variations in the fitness function, including thickness noise only, loading noise only, and combinations of the noise types. Preliminary results indicate that the analysis provides reasonable assessments of the noise produced, and that genetic algorithm successfully searches for 'good' designs. The results show that, for a given required thrust coefficient, proper blade design can noticeably reduce the noise produced at some expense to the power requirements.
NASA Astrophysics Data System (ADS)
Liu, Shizhong; Zhang, Zongyun
2013-07-01
Based on the Maximum Degree Construction algorithm, a new select algorithm is proposed in this paper. In the algorithm, each node and its neighbors issue the certificates each other to generate the local In-degree and Out-degree certificate repository. Similar to the ant colony algorithm, it finds the certificate chain between the source node and destination node by selecting the node of the maximum certificated times from the beginning. The algorithm reduces the complexity of the selection, provides a guarantee to find the certificate chain, and saves the spending of space as well. Next, this paper gives the simulation of the algorithm and the simulated results show that this is an optimized select algorithm for local certificate repository.
NASA Astrophysics Data System (ADS)
Witharana, Chandi; LaRue, Michelle A.; Lynch, Heather J.
2016-03-01
Remote sensing is a rapidly developing tool for mapping the abundance and distribution of Antarctic wildlife. While both panchromatic and multispectral imagery have been used in this context, image fusion techniques have received little attention. We tasked seven widely-used fusion algorithms: Ehlers fusion, hyperspherical color space fusion, high-pass fusion, principal component analysis (PCA) fusion, University of New Brunswick fusion, and wavelet-PCA fusion to resolution enhance a series of single-date QuickBird-2 and Worldview-2 image scenes comprising penguin guano, seals, and vegetation. Fused images were assessed for spectral and spatial fidelity using a variety of quantitative quality indicators and visual inspection methods. Our visual evaluation elected the high-pass fusion algorithm and the University of New Brunswick fusion algorithm as best for manual wildlife detection while the quantitative assessment suggested the Gram-Schmidt fusion algorithm and the University of New Brunswick fusion algorithm as best for automated classification. The hyperspherical color space fusion algorithm exhibited mediocre results in terms of spectral and spatial fidelities. The PCA fusion algorithm showed spatial superiority at the expense of spectral inconsistencies. The Ehlers fusion algorithm and the wavelet-PCA algorithm showed the weakest performances. As remote sensing becomes a more routine method of surveying Antarctic wildlife, these benchmarks will provide guidance for image fusion and pave the way for more standardized products for specific types of wildlife surveys.
Compound algorithm for restoration of heavy turbulence-degraded image for space target
NASA Astrophysics Data System (ADS)
Wang, Liang-liang; Wang, Ru-jie; Li, Ming; Kang, Zi-qian; Xu, Xiao-qin; Gao, Xin
2012-11-01
Restoration of atmospheric turbulence degraded image is needed to be solved as soon as possible in the field of astronomical space technology. Owing to the fact that the point spread function of turbulence is unknown, changeable with time, hard to be described by mathematics models, withal, kinds of noises would be brought during the imaging processes (such as sensor noise), the image for space target is edge blurred and heavy noised, which making a single restoration algorithm to reach the requirement of restoration difficult. Focusing the fact that the image for space target which was fetched during observation by ground-based optical telescopes is heavy noisy turbulence degraded, this paper discusses the adjustment and reformation of various algorithm structures as well as the selection of various parameters, after the combination of the nonlinear filter algorithm based on noise spatial characteristics, restoration algorithm of heavy turbulence degrade image for space target based on regularization, and the statistics theory based EM restoration algorithm. In order to test the validity of the algorithm, a series of restoration experiments are performed on the heavy noisy turbulence-degraded images for space target. The experiment results show that the new compound algorithm can achieve noise restriction and detail preservation simultaneously, which is effective and practical. Withal, the definition measures and relative definition measures show that the new compound algorithm is better than the traditional algorithms.
Greedy heuristic algorithm for solving series of eee components classification problems*
NASA Astrophysics Data System (ADS)
Kazakovtsev, A. L.; Antamoshkin, A. N.; Fedosov, V. V.
2016-04-01
Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE device and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem.
Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.
Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A
2012-02-01
Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method. PMID:20703716
NASA Technical Reports Server (NTRS)
Vardi, A.
1984-01-01
The representation min t s.t. F(I)(x). - t less than or equal to 0 for all i is examined. An active set strategy is designed of functions: active, semi-active, and non-active. This technique will help in preventing zigzagging which often occurs when an active set strategy is used. Some of the inequality constraints are handled with slack variables. Also a trust region strategy is used in which at each iteration there is a sphere around the current point in which the local approximation of the function is trusted. The algorithm is implemented into a successful computer program. Numerical results are provided.
Evolutionary algorithms and multi-agent systems
NASA Astrophysics Data System (ADS)
Oh, Jae C.
2006-05-01
This paper discusses how evolutionary algorithms are related to multi-agent systems and the possibility of military applications using the two disciplines. In particular, we present a game theoretic model for multi-agent resource distribution and allocation where agents in the environment must help each other to survive. Each agent maintains a set of variables representing actual friendship and perceived friendship. The model directly addresses problems in reputation management schemes in multi-agent systems and Peer-to-Peer distributed systems. We present algorithms based on evolutionary game process for maintaining the friendship values as well as a utility equation used in each agent's decision making. For an application problem, we adapted our formal model to the military coalition support problem in peace-keeping missions. Simulation results show that efficient resource allocation and sharing with minimum communication cost is achieved without centralized control.
Backtracking algorithm for lepton reconstruction with HADES
NASA Astrophysics Data System (ADS)
Sellheim, P.;
2015-04-01
The High Acceptance Di-Electron Spectrometer (HADES) at the GSI Helmholtzzentrum für Schwerionenforschung investigates dilepton and strangeness production in elementary and heavy-ion collisions. In April - May 2012 HADES recorded 7 billion Au+Au events at a beam energy of 1.23 GeV/u with the highest multiplicities measured so far. The track reconstruction and particle identification in the high track density environment are challenging. The most important detector component for lepton identification is the Ring Imaging Cherenkov detector. Its main purpose is the separation of electrons and positrons from large background of charged hadrons produced in heavy-ion collisions. In order to improve lepton identification this backtracking algorithm was developed. In this contribution we will show the results of the algorithm compared to the currently applied method for e+/-identification. Efficiency and purity of a reconstructed e+/- sample will be discussed as well.
Improved imaging algorithm for bridge crack detection
NASA Astrophysics Data System (ADS)
Lu, Jingxiao; Song, Pingli; Han, Kaihong
2012-04-01
This paper present an improved imaging algorithm for bridge crack detection, through optimizing the eight-direction Sobel edge detection operator, making the positioning of edge points more accurate than without the optimization, and effectively reducing the false edges information, so as to facilitate follow-up treatment. In calculating the crack geometry characteristics, we use the method of extracting skeleton on single crack length. In order to calculate crack area, we construct the template of area by making logical bitwise AND operation of the crack image. After experiment, the results show errors of the crack detection method and actual manual measurement are within an acceptable range, meet the needs of engineering applications. This algorithm is high-speed and effective for automated crack measurement, it can provide more valid data for proper planning and appropriate performance of the maintenance and rehabilitation processes of bridge.
Experimental study on subaperture testing with iterative triangulation algorithm.
Yan, Lisong; Wang, Xiaokun; Zheng, Ligong; Zeng, Xuefeng; Hu, Haixiang; Zhang, Xuejun
2013-09-23
Applying the iterative triangulation stitching algorithm, we provide an experimental demonstration by testing a Φ120 mm flat mirror, a Φ1450 mm off-axis parabolic mirror and a convex hyperboloid mirror. By comparing the stitching results with the self-examine subaperture, it shows that the reconstruction results are in consistent with that of the subaperture testing. As all the experiments are conducted with a 5-dof adjustment platform with big adjustment errors, it proves that using the above mentioned algorithm, the subaperture stitching can be easily performed without a precise positioning system. In addition, with the algorithm, we accomplish the coordinate unification between the testing and processing that makes it possible to guide the processing by the stitching result. PMID:24104151
Chang, C.Y.
1986-01-01
New results on efficient forms of decoding convolutional codes based on Viterbi and stack algorithms using systolic array architecture are presented. Some theoretical aspects of systolic arrays are also investigated. First, systolic array implementation of Viterbi algorithm is considered, and various properties of convolutional codes are derived. A technique called strongly connected trellis decoding is introduced to increase the efficient utilization of all the systolic array processors. The issues dealing with the composite branch metric generation, survivor updating, overall system architecture, throughput rate, and computations overhead ratio are also investigated. Second, the existing stack algorithm is modified and restated in a more concise version so that it can be efficiently implemented by a special type of systolic array called systolic priority queue. Three general schemes of systolic priority queue based on random access memory, shift register, and ripple register are proposed. Finally, a systematic approach is presented to design systolic arrays for certain general classes of recursively formulated algorithms.
Simulation System of Car Crash Test in C-NCAP Analysis Based on an Improved Apriori Algorithm*
NASA Astrophysics Data System (ADS)
Xiang, LI
In order to analysis car crash test in C-NCAP, an improved algorithm is given based on Apriori algorithm in this paper. The new algorithm is implemented with vertical data layout, breadth first searching, and intersecting. It takes advantage of the efficiency of vertical data layout and intersecting, and prunes candidate frequent item sets like Apriori. Finally, the new algorithm is applied in simulation of car crash test analysis system. The result shows that the relations will affect the C-NCAP test results, and it can provide a reference for the automotive design.
Computational algorithms to predict Gene Ontology annotations
2015-01-01
Background Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful. Methods We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set. Results We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm. Conclusions Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper
EDGA: A Population Evolution Direction-Guided Genetic Algorithm for Protein-Ligand Docking.
Guan, Boxin; Zhang, Changsheng; Ning, Jiaxu
2016-07-01
Protein-ligand docking can be formulated as a search algorithm associated with an accurate scoring function. However, most current search algorithms cannot show good performance in docking problems, especially for highly flexible docking. To overcome this drawback, this article presents a novel and robust optimization algorithm (EDGA) based on the Lamarckian genetic algorithm (LGA) for solving flexible protein-ligand docking problems. This method applies a population evolution direction-guided model of genetics, in which search direction evolves to the optimum solution. The method is more efficient to find the lowest energy of protein-ligand docking. We consider four search methods-a tradition genetic algorithm, LGA, SODOCK, and EDGA-and compare their performance in docking of six protein-ligand docking problems. The results show that EDGA is the most stable, reliable, and successful. PMID:26895461