Trust-Based Analysis of an Air Force Collision Avoidance System

DTIC Science & Technology

2015-12-01

that test pilots’ trust depended on a number of factors, including the development of a nuisance free algorithm, designing fly-up evasive maneuvers...revealed that test pilots’ trust depended on a number of factors, including the development of a nuisance- free algorithm, designing fly-up evasive ...the terrain collision evasion maneuver. To overcome these limitations, Auto-GCAS was developed with a number of innovative approaches and solutions

A hospital-level cost-effectiveness analysis model for toxigenic Clostridium difficile detection algorithms.

PubMed

Verhoye, E; Vandecandelaere, P; De Beenhouwer, H; Coppens, G; Cartuyvels, R; Van den Abeele, A; Frans, J; Laffut, W

2015-10-01

Despite thorough analyses of the analytical performance of Clostridium difficile tests and test algorithms, the financial impact at hospital level has not been well described. Such a model should take institution-specific variables into account, such as incidence, request behaviour and infection control policies. To calculate the total hospital costs of different test algorithms, accounting for days on which infected patients with toxigenic strains were not isolated and therefore posed an infectious risk for new/secondary nosocomial infections. A mathematical algorithm was developed to gather the above parameters using data from seven Flemish hospital laboratories (Bilulu Microbiology Study Group) (number of tests, local prevalence and hospital hygiene measures). Measures of sensitivity and specificity for the evaluated tests were taken from the literature. List prices and costs of assays were provided by the manufacturer or the institutions. The calculated cost included reagent costs, personnel costs and the financial burden following due and undue isolations and antibiotic therapies. Five different test algorithms were compared. A dynamic calculation model was constructed to evaluate the cost:benefit ratio of each algorithm for a set of institution- and time-dependent inputted variables (prevalence, cost fluctuations and test performances), making it possible to choose the most advantageous algorithm for its setting. A two-step test algorithm with concomitant glutamate dehydrogenase and toxin testing, followed by a rapid molecular assay was found to be the most cost-effective algorithm. This enabled resolution of almost all cases on the day of arrival, minimizing the number of unnecessary or missing isolations. Copyright © 2015 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Implementation on Landsat Data of a Simple Cloud Mask Algorithm Developed for MODIS Land Bands

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Wilson, Michael J.; Varnai, Tamas

2010-01-01

This letter assesses the performance on Landsat-7 images of a modified version of a cloud masking algorithm originally developed for clear-sky compositing of Moderate Resolution Imaging Spectroradiometer (MODIS) images at northern mid-latitudes. While data from recent Landsat missions include measurements at thermal wavelengths, and such measurements are also planned for the next mission, thermal tests are not included in the suggested algorithm in its present form to maintain greater versatility and ease of use. To evaluate the masking algorithm we take advantage of the availability of manual (visual) cloud masks developed at USGS for the collection of Landsat scenes used here. As part of our evaluation we also include the Automated Cloud Cover Assesment (ACCA) algorithm that includes thermal tests and is used operationally by the Landsat-7 mission to provide scene cloud fractions, but no cloud masks. We show that the suggested algorithm can perform about as well as ACCA both in terms of scene cloud fraction and pixel-level cloud identification. Specifically, we find that the algorithm gives an error of 1.3% for the scene cloud fraction of 156 scenes, and a root mean square error of 7.2%, while it agrees with the manual mask for 93% of the pixels, figures very similar to those from ACCA (1.2%, 7.1%, 93.7%).

An Innovative Thinking-Based Intelligent Information Fusion Algorithm

PubMed Central

Hu, Liang; Liu, Gang; Zhou, Jin

2013-01-01

This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information. PMID:23956699

An innovative thinking-based intelligent information fusion algorithm.

PubMed

Lu, Huimin; Hu, Liang; Liu, Gang; Zhou, Jin

2013-01-01

This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information.

Hull Form Design and Optimization Tool Development

DTIC Science & Technology

2012-07-01

global minimum. The algorithm accomplishes this by using a method known as metaheuristics which allows the algorithm to examine a large area by...further development of these tools including the implementation and testing of a new optimization algorithm , the improvement of a rapid hull form...under the 2012 Naval Research Enterprise Intern Program. 15. SUBJECT TERMS hydrodynamic, hull form, generation, optimization, algorithm

Online Calibration of Polytomous Items Under the Generalized Partial Credit Model

PubMed Central

Zheng, Yi

2016-01-01

Online calibration is a technology-enhanced architecture for item calibration in computerized adaptive tests (CATs). Many CATs are administered continuously over a long term and rely on large item banks. To ensure test validity, these item banks need to be frequently replenished with new items, and these new items need to be pretested before being used operationally. Online calibration dynamically embeds pretest items in operational tests and calibrates their parameters as response data are gradually obtained through the continuous test administration. This study extends existing formulas, procedures, and algorithms for dichotomous item response theory models to the generalized partial credit model, a popular model for items scored in more than two categories. A simulation study was conducted to investigate the developed algorithms and procedures under a variety of conditions, including two estimation algorithms, three pretest item selection methods, three seeding locations, two numbers of score categories, and three calibration sample sizes. Results demonstrated acceptable estimation accuracy of the two estimation algorithms in some of the simulated conditions. A variety of findings were also revealed for the interacted effects of included factors, and recommendations were made respectively. PMID:29881063

Memetic algorithms for de novo motif-finding in biomedical sequences.

PubMed

Bi, Chengpeng

2012-09-01

The objectives of this study are to design and implement a new memetic algorithm for de novo motif discovery, which is then applied to detect important signals hidden in various biomedical molecular sequences. In this paper, memetic algorithms are developed and tested in de novo motif-finding problems. Several strategies in the algorithm design are employed that are to not only efficiently explore the multiple sequence local alignment space, but also effectively uncover the molecular signals. As a result, there are a number of key features in the implementation of the memetic motif-finding algorithm (MaMotif), including a chromosome replacement operator, a chromosome alteration-aware local search operator, a truncated local search strategy, and a stochastic operation of local search imposed on individual learning. To test the new algorithm, we compare MaMotif with a few of other similar algorithms using simulated and experimental data including genomic DNA, primary microRNA sequences (let-7 family), and transmembrane protein sequences. The new memetic motif-finding algorithm is successfully implemented in C++, and exhaustively tested with various simulated and real biological sequences. In the simulation, it shows that MaMotif is the most time-efficient algorithm compared with others, that is, it runs 2 times faster than the expectation maximization (EM) method and 16 times faster than the genetic algorithm-based EM hybrid. In both simulated and experimental testing, results show that the new algorithm is compared favorably or superior to other algorithms. Notably, MaMotif is able to successfully discover the transcription factors' binding sites in the chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) data, correctly uncover the RNA splicing signals in gene expression, and precisely find the highly conserved helix motif in the transmembrane protein sequences, as well as rightly detect the palindromic segments in the primary microRNA sequences. The memetic motif-finding algorithm is effectively designed and implemented, and its applications demonstrate it is not only time-efficient, but also exhibits excellent performance while compared with other popular algorithms. Copyright © 2012 Elsevier B.V. All rights reserved.

The evaluation of the OSGLR algorithm for restructurable controls

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Wagner, E.; Hall, S. R.; Motyka, P.

1986-01-01

The detection and isolation of commercial aircraft control surface and actuator failures using the orthogonal series generalized likelihood ratio (OSGLR) test was evaluated. The OSGLR algorithm was chosen as the most promising algorithm based on a preliminary evaluation of three failure detection and isolation (FDI) algorithms (the detection filter, the generalized likelihood ratio test, and the OSGLR test) and a survey of the literature. One difficulty of analytic FDI techniques and the OSGLR algorithm in particular is their sensitivity to modeling errors. Therefore, methods of improving the robustness of the algorithm were examined with the incorporation of age-weighting into the algorithm being the most effective approach, significantly reducing the sensitivity of the algorithm to modeling errors. The steady-state implementation of the algorithm based on a single cruise linear model was evaluated using a nonlinear simulation of a C-130 aircraft. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling the linear models used by the algorithm on dynamic pressure and flap deflection was also considered. Since simply scheduling the linear models over the entire flight envelope is unlikely to be adequate, scheduling of the steady-state implentation of the algorithm was briefly investigated.

Use of Management Pathways or Algorithms in Children With Chronic Cough: Systematic Reviews.

PubMed

Chang, Anne B; Oppenheimer, John J; Weinberger, Miles; Weir, Kelly; Rubin, Bruce K; Irwin, Richard S

2016-01-01

Use of appropriate cough pathways or algorithms may reduce the morbidity of chronic cough, lead to earlier diagnosis of chronic underlying illness, and reduce unnecessary costs and medications. We undertook three systematic reviews to examine three related key questions (KQ): In children aged ?14 years with chronic cough (> 4 weeks' duration), KQ1, do cough management protocols (or algorithms) improve clinical outcomes? KQ2, should the cough management or testing algorithm differ depending on the duration and/or severity? KQ3, should the cough management or testing algorithm differ depending on the associated characteristics of the cough and clinical history? We used the CHEST expert cough panel's protocol. Two authors screened searches and selected and extracted data. Only systematic reviews, randomized controlled trials (RCTs), and cohort studies published in English were included. Data were presented in Preferred Reporting Items for Systematic Reviews and Meta-analyses flowcharts and summary tabulated. Nine studies were included in KQ1 (RCT = 1; cohort studies = 7) and eight in KQ3 (RCT = 2; cohort = 6), but none in KQ2. There is high-quality evidence that in children aged ?14 years with chronic cough (> 4 weeks' duration), the use of cough management protocols (or algorithms) improves clinical outcomes and cough management or the testing algorithm should differ depending on the associated characteristics of the cough and clinical history. It remains uncertain whether the management or testing algorithm should depend on the duration or severity of chronic cough. Pending new data, chronic cough in children should be defined as > 4 weeks' duration and children should be systematically evaluated with treatment targeted to the underlying cause irrespective of the cough severity. Copyright © 2016 American College of Chest Physicians. All rights reserved.

Algorithm and code development for unsteady three-dimensional Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Obayashi, Shigeru

1991-01-01

A streamwise upwind algorithm for solving the unsteady 3-D Navier-Stokes equations was extended to handle the moving grid system. It is noted that the finite volume concept is essential to extend the algorithm. The resulting algorithm is conservative for any motion of the coordinate system. Two extensions to an implicit method were considered and the implicit extension that makes the algorithm computationally efficient is implemented into Ames's aeroelasticity code, ENSAERO. The new flow solver has been validated through the solution of test problems. Test cases include three-dimensional problems with fixed and moving grids. The first test case shown is an unsteady viscous flow over an F-5 wing, while the second test considers the motion of the leading edge vortex as well as the motion of the shock wave for a clipped delta wing. The resulting algorithm has been implemented into ENSAERO. The upwind version leads to higher accuracy in both steady and unsteady computations than the previously used central-difference method does, while the increase in the computational time is small.

Economic evaluation of laboratory testing strategies for hospital-associated Clostridium difficile infection.

PubMed

Schroeder, Lee F; Robilotti, Elizabeth; Peterson, Lance R; Banaei, Niaz; Dowdy, David W

2014-02-01

Clostridium difficile infection (CDI) is the most common cause of infectious diarrhea in health care settings, and for patients presumed to have CDI, their isolation while awaiting laboratory results is costly. Newer rapid tests for CDI may reduce this burden, but the economic consequences of different testing algorithms remain unexplored. We used decision analysis from the hospital perspective to compare multiple CDI testing algorithms for adult inpatients with suspected CDI, assuming patient management according to laboratory results. CDI testing strategies included combinations of on-demand PCR (odPCR), batch PCR, lateral-flow diagnostics, plate-reader enzyme immunoassay, and direct tissue culture cytotoxicity. In the reference scenario, algorithms incorporating rapid testing were cost-effective relative to nonrapid algorithms. For every 10,000 symptomatic adults, relative to a strategy of treating nobody, lateral-flow glutamate dehydrogenase (GDH)/odPCR generated 831 true-positive results and cost $1,600 per additional true-positive case treated. Stand-alone odPCR was more effective and more expensive, identifying 174 additional true-positive cases at $6,900 per additional case treated. All other testing strategies were dominated by (i.e., more costly and less effective than) stand-alone odPCR or odPCR preceded by lateral-flow screening. A cost-benefit analysis (including estimated costs of missed cases) favored stand-alone odPCR in most settings but favored odPCR preceded by lateral-flow testing if a missed CDI case resulted in less than $5,000 of extended hospital stay costs and <2 transmissions, if lateral-flow GDH diagnostic sensitivity was >93%, or if the symptomatic carrier proportion among the toxigenic culture-positive cases was >80%. These results can aid guideline developers and laboratory directors who are considering rapid testing algorithms for diagnosing CDI.

Economic Evaluation of Laboratory Testing Strategies for Hospital-Associated Clostridium difficile Infection

PubMed Central

Robilotti, Elizabeth; Peterson, Lance R.; Banaei, Niaz; Dowdy, David W.

2014-01-01

Clostridium difficile infection (CDI) is the most common cause of infectious diarrhea in health care settings, and for patients presumed to have CDI, their isolation while awaiting laboratory results is costly. Newer rapid tests for CDI may reduce this burden, but the economic consequences of different testing algorithms remain unexplored. We used decision analysis from the hospital perspective to compare multiple CDI testing algorithms for adult inpatients with suspected CDI, assuming patient management according to laboratory results. CDI testing strategies included combinations of on-demand PCR (odPCR), batch PCR, lateral-flow diagnostics, plate-reader enzyme immunoassay, and direct tissue culture cytotoxicity. In the reference scenario, algorithms incorporating rapid testing were cost-effective relative to nonrapid algorithms. For every 10,000 symptomatic adults, relative to a strategy of treating nobody, lateral-flow glutamate dehydrogenase (GDH)/odPCR generated 831 true-positive results and cost $1,600 per additional true-positive case treated. Stand-alone odPCR was more effective and more expensive, identifying 174 additional true-positive cases at $6,900 per additional case treated. All other testing strategies were dominated by (i.e., more costly and less effective than) stand-alone odPCR or odPCR preceded by lateral-flow screening. A cost-benefit analysis (including estimated costs of missed cases) favored stand-alone odPCR in most settings but favored odPCR preceded by lateral-flow testing if a missed CDI case resulted in less than $5,000 of extended hospital stay costs and <2 transmissions, if lateral-flow GDH diagnostic sensitivity was >93%, or if the symptomatic carrier proportion among the toxigenic culture-positive cases was >80%. These results can aid guideline developers and laboratory directors who are considering rapid testing algorithms for diagnosing CDI. PMID:24478478

A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Vuik, C.; Lucas, Peter; vanGijzen, Martin; Bijl, Hester

2010-01-01

A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.

TALARIS project update: Overview of flight testing and development of a prototype planetary surface exploration hopper

NASA Astrophysics Data System (ADS)

Rossi, Christopher; Cunio, Phillip M.; Alibay, Farah; Morrow, Joe; Nothnagel, Sarah L.; Steiner, Ted; Han, Christopher J.; Lanford, Ephraim; Hoffman, Jeffrey A.

2012-12-01

The TALARIS (Terrestrial Artificial Lunar And Reduced GravIty Simulator) project is intended to test GNC (Guidance, Navigation, and Control) algorithms on a prototype planetary surface exploration hopper in a dynamic environment with simulated reduced gravity. The vehicle is being developed by the Charles Stark Draper Laboratory and Massachusetts Institute of Technology in support of efforts in the Google Lunar X-Prize contest. This paper presents progress achieved since September 2010 in vehicle development and flight testing. Upgrades to the vehicle are described, including a redesign of the power train for the gravity-offset propulsion system and a redesign of key elements of the spacecraft emulator propulsion system. The integration of flight algorithms into modular flight software is also discussed. Results are reported for restricted degree of freedom (DOF) tests used to tune GNC algorithms on the path to a full 6-DOF hover-hop flight profile. These tests include 3-DOF tests on flat surfaces restricted to horizontal motion, and 2-DOF vertical tests restricted to vertical motion and 1-DOF attitude control. The results of tests leading up to full flight operations are described, as are lessons learned and future test plans.

The tradition algorithm approach underestimates the prevalence of serodiagnosis of syphilis in HIV-infected individuals.

PubMed

Chen, Bin; Peng, Xiuming; Xie, Tiansheng; Jin, Changzhong; Liu, Fumin; Wu, Nanping

2017-07-01

Currently, there are three algorithms for screening of syphilis: traditional algorithm, reverse algorithm and European Centre for Disease Prevention and Control (ECDC) algorithm. To date, there is not a generally recognized diagnostic algorithm. When syphilis meets HIV, the situation is even more complex. To evaluate their screening performance and impact on the seroprevalence of syphilis in HIV-infected individuals, we conducted a cross-sectional study included 865 serum samples from HIV-infected patients in a tertiary hospital. Every sample (one per patient) was tested with toluidine red unheated serum test (TRUST), T. pallidum particle agglutination assay (TPPA), and Treponema pallidum enzyme immunoassay (TP-EIA) according to the manufacturer's instructions. The results of syphilis serological testing were interpreted following different algorithms respectively. We directly compared the traditional syphilis screening algorithm with the reverse syphilis screening algorithm in this unique population. The reverse algorithm achieved remarkable higher seroprevalence of syphilis than the traditional algorithm (24.9% vs. 14.2%, p < 0.0001). Compared to the reverse algorithm, the traditional algorithm also had a missed serodiagnosis rate of 42.8%. The total percentages of agreement and corresponding kappa values of tradition and ECDC algorithm compared with those of reverse algorithm were as follows: 89.4%,0.668; 99.8%, 0.994. There was a very good strength of agreement between the reverse and the ECDC algorithm. Our results supported the reverse (or ECDC) algorithm in screening of syphilis in HIV-infected populations. In addition, our study demonstrated that screening of HIV-populations using different algorithms may result in a statistically different seroprevalence of syphilis.

Syphilis testing in antenatal care: Policies and practices among laboratories in the Americas.

PubMed

Luu, Minh; Ham, Cal; Kamb, Mary L; Caffe, Sonja; Hoover, Karen W; Perez, Freddy

2015-06-01

To asses laboratory syphilis testing policies and practices among laboratories in the Americas. Laboratory directors or designees from PAHO member countries were invited to participate in a structured, electronically-delivered survey between March and August, 2014. Data on syphilis tests, algorithms, and quality control (QC) practices were analyzed, focusing on laboratories receiving specimens from antenatal clinics (ANCs). Surveys were completed by 69 laboratories representing 30 (86%) countries. Participating laboratories included 36 (52%) national or regional reference labs and 33 (48%) lower-level laboratories. Most (94%) were public sector facilities and 71% reported existence of a national algorithm for syphilis testing in pregnancy, usually involving both treponemal and non-treponemal testing (72%). Less than half (41%) used rapid syphilis tests (RSTs); and only seven laboratories representing five countries reported RSTs were included in the national algorithm for pregnant women. Most (83%) laboratories serving ANCs reported using some type of QC system; 68% of laboratories reported participation in external QC. Only 36% of laboratories reported data to national/local surveillance. Half of all laboratories serving ANC settings reported a stockout of one or more essential supplies during the previous year (median duration, 30days). Updating laboratory algorithms, improving testing standards, integrating data into existing surveillance, and improved procurement and distribution of commodities may be needed to ensure elimination of MTCT of syphilis in the Americas. Copyright © 2015. Published by Elsevier Ireland Ltd.

Investigation into the efficiency of different bionic algorithm combinations for a COBRA meta-heuristic

NASA Astrophysics Data System (ADS)

Akhmedova, Sh; Semenkin, E.

2017-02-01

Previously, a meta-heuristic approach, called Co-Operation of Biology-Related Algorithms or COBRA, for solving real-parameter optimization problems was introduced and described. COBRA’s basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, which were chosen due to the similarity of their schemes. The performance of this meta-heuristic was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms’ cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the five above-listed algorithms and additionally the Fish School Search algorithm were used for the development of five different modifications of COBRA by varying the number of component-algorithms. These modifications were tested on the same set of functions and the best of them was found. Ways of further improving the COBRA algorithm are then discussed.

Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) Project Status as of May 2010

NASA Technical Reports Server (NTRS)

Striepe, Scott A.; Epp, Chirold D.; Robertson, Edward A.

2010-01-01

This paper includes the current status of NASA s Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) Project. The ALHAT team has completed several flight tests and two major design analysis cycles. These tests and analyses examine terrain relative navigation sensors, hazard detection and avoidance sensors and algorithms, and hazard relative navigation algorithms, and the guidance and navigation system using these ALHAT functions. The next flight test is scheduled for July 2010. The paper contains results from completed flight tests and analysis cycles. ALHAT system status, upcoming tests and analyses is also addressed. The current ALHAT plans as of May 2010 are discussed. Application of the ALHAT system to landing on bodies other than the Moon is included

Accounting for False Positive HIV Tests: Is Visceral Leishmaniasis Responsible?

PubMed Central

Shanks, Leslie; Ritmeijer, Koert; Piriou, Erwan; Siddiqui, M. Ruby; Kliescikova, Jarmila; Pearce, Neil; Ariti, Cono; Muluneh, Libsework; Masiga, Johnson; Abebe, Almaz

2015-01-01

Background Co-infection with HIV and visceral leishmaniasis is an important consideration in treatment of either disease in endemic areas. Diagnosis of HIV in resource-limited settings relies on rapid diagnostic tests used together in an algorithm. A limitation of the HIV diagnostic algorithm is that it is vulnerable to falsely positive reactions due to cross reactivity. It has been postulated that visceral leishmaniasis (VL) infection can increase this risk of false positive HIV results. This cross sectional study compared the risk of false positive HIV results in VL patients with non-VL individuals. Methodology/Principal Findings Participants were recruited from 2 sites in Ethiopia. The Ethiopian algorithm of a tiebreaker using 3 rapid diagnostic tests (RDTs) was used to test for HIV. The gold standard test was the Western Blot, with indeterminate results resolved by PCR testing. Every RDT screen positive individual was included for testing with the gold standard along with 10% of all negatives. The final analysis included 89 VL and 405 non-VL patients. HIV prevalence was found to be 12.8% (47/ 367) in the VL group compared to 7.9% (200/2526) in the non-VL group. The RDT algorithm in the VL group yielded 47 positives, 4 false positives, and 38 negatives. The same algorithm for those without VL had 200 positives, 14 false positives, and 191 negatives. Specificity and positive predictive value for the group with VL was less than the non-VL group; however, the difference was not found to be significant (p = 0.52 and p = 0.76, respectively). Conclusion The test algorithm yielded a high number of HIV false positive results. However, we were unable to demonstrate a significant difference between groups with and without VL disease. This suggests that the presence of endemic visceral leishmaniasis alone cannot account for the high number of false positive HIV results in our study. PMID:26161864

Accounting for False Positive HIV Tests: Is Visceral Leishmaniasis Responsible?

PubMed

Shanks, Leslie; Ritmeijer, Koert; Piriou, Erwan; Siddiqui, M Ruby; Kliescikova, Jarmila; Pearce, Neil; Ariti, Cono; Muluneh, Libsework; Masiga, Johnson; Abebe, Almaz

2015-01-01

Co-infection with HIV and visceral leishmaniasis is an important consideration in treatment of either disease in endemic areas. Diagnosis of HIV in resource-limited settings relies on rapid diagnostic tests used together in an algorithm. A limitation of the HIV diagnostic algorithm is that it is vulnerable to falsely positive reactions due to cross reactivity. It has been postulated that visceral leishmaniasis (VL) infection can increase this risk of false positive HIV results. This cross sectional study compared the risk of false positive HIV results in VL patients with non-VL individuals. Participants were recruited from 2 sites in Ethiopia. The Ethiopian algorithm of a tiebreaker using 3 rapid diagnostic tests (RDTs) was used to test for HIV. The gold standard test was the Western Blot, with indeterminate results resolved by PCR testing. Every RDT screen positive individual was included for testing with the gold standard along with 10% of all negatives. The final analysis included 89 VL and 405 non-VL patients. HIV prevalence was found to be 12.8% (47/ 367) in the VL group compared to 7.9% (200/2526) in the non-VL group. The RDT algorithm in the VL group yielded 47 positives, 4 false positives, and 38 negatives. The same algorithm for those without VL had 200 positives, 14 false positives, and 191 negatives. Specificity and positive predictive value for the group with VL was less than the non-VL group; however, the difference was not found to be significant (p = 0.52 and p = 0.76, respectively). The test algorithm yielded a high number of HIV false positive results. However, we were unable to demonstrate a significant difference between groups with and without VL disease. This suggests that the presence of endemic visceral leishmaniasis alone cannot account for the high number of false positive HIV results in our study.

HIV misdiagnosis in sub-Saharan Africa: performance of diagnostic algorithms at six testing sites

PubMed Central

Kosack, Cara S.; Shanks, Leslie; Beelaert, Greet; Benson, Tumwesigye; Savane, Aboubacar; Ng’ang’a, Anne; Andre, Bita; Zahinda, Jean-Paul BN; Fransen, Katrien; Page, Anne-Laure

2017-01-01

Abstract Introduction: We evaluated the diagnostic accuracy of HIV testing algorithms at six programmes in five sub-Saharan African countries. Methods: In this prospective multisite diagnostic evaluation study (Conakry, Guinea; Kitgum, Uganda; Arua, Uganda; Homa Bay, Kenya; Doula, Cameroun and Baraka, Democratic Republic of Congo), samples from clients (greater than equal to five years of age) testing for HIV were collected and compared to a state-of-the-art algorithm from the AIDS reference laboratory at the Institute of Tropical Medicine, Belgium. The reference algorithm consisted of an enzyme-linked immuno-sorbent assay, a line-immunoassay, a single antigen-enzyme immunoassay and a DNA polymerase chain reaction test. Results: Between August 2011 and January 2015, over 14,000 clients were tested for HIV at 6 HIV counselling and testing sites. Of those, 2786 (median age: 30; 38.1% males) were included in the study. Sensitivity of the testing algorithms ranged from 89.5% in Arua to 100% in Douala and Conakry, while specificity ranged from 98.3% in Doula to 100% in Conakry. Overall, 24 (0.9%) clients, and as many as 8 per site (1.7%), were misdiagnosed, with 16 false-positive and 8 false-negative results. Six false-negative specimens were retested with the on-site algorithm on the same sample and were found to be positive. Conversely, 13 false-positive specimens were retested: 8 remained false-positive with the on-site algorithm. Conclusions: The performance of algorithms at several sites failed to meet expectations and thresholds set by the World Health Organization, with unacceptably high rates of false results. Alongside the careful selection of rapid diagnostic tests and the validation of algorithms, strictly observing correct procedures can reduce the risk of false results. In the meantime, to identify false-positive diagnoses at initial testing, patients should be retested upon initiating antiretroviral therapy. PMID:28691437

HIV misdiagnosis in sub-Saharan Africa: performance of diagnostic algorithms at six testing sites.

PubMed

Kosack, Cara S; Shanks, Leslie; Beelaert, Greet; Benson, Tumwesigye; Savane, Aboubacar; Ng'ang'a, Anne; Andre, Bita; Zahinda, Jean-Paul Bn; Fransen, Katrien; Page, Anne-Laure

2017-07-03

We evaluated the diagnostic accuracy of HIV testing algorithms at six programmes in five sub-Saharan African countries. In this prospective multisite diagnostic evaluation study (Conakry, Guinea; Kitgum, Uganda; Arua, Uganda; Homa Bay, Kenya; Doula, Cameroun and Baraka, Democratic Republic of Congo), samples from clients (greater than equal to five years of age) testing for HIV were collected and compared to a state-of-the-art algorithm from the AIDS reference laboratory at the Institute of Tropical Medicine, Belgium. The reference algorithm consisted of an enzyme-linked immuno-sorbent assay, a line-immunoassay, a single antigen-enzyme immunoassay and a DNA polymerase chain reaction test. Between August 2011 and January 2015, over 14,000 clients were tested for HIV at 6 HIV counselling and testing sites. Of those, 2786 (median age: 30; 38.1% males) were included in the study. Sensitivity of the testing algorithms ranged from 89.5% in Arua to 100% in Douala and Conakry, while specificity ranged from 98.3% in Doula to 100% in Conakry. Overall, 24 (0.9%) clients, and as many as 8 per site (1.7%), were misdiagnosed, with 16 false-positive and 8 false-negative results. Six false-negative specimens were retested with the on-site algorithm on the same sample and were found to be positive. Conversely, 13 false-positive specimens were retested: 8 remained false-positive with the on-site algorithm. The performance of algorithms at several sites failed to meet expectations and thresholds set by the World Health Organization, with unacceptably high rates of false results. Alongside the careful selection of rapid diagnostic tests and the validation of algorithms, strictly observing correct procedures can reduce the risk of false results. In the meantime, to identify false-positive diagnoses at initial testing, patients should be retested upon initiating antiretroviral therapy.

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the configurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, are taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

Real time test bed development for power system operation, control and cyber security

NASA Astrophysics Data System (ADS)

Reddi, Ram Mohan

The operation and control of the power system in an efficient way is important in order to keep the system secure, reliable and economical. With advancements in smart grid, several new algorithms have been developed for improved operation and control. These algorithms need to be extensively tested and validated in real time before applying to the real electric power grid. This work focuses on the development of a real time test bed for testing and validating power system control algorithms, hardware devices and cyber security vulnerability. The test bed developed utilizes several hardware components including relays, phasor measurement units, phasor data concentrator, programmable logic controllers and several software tools. Current work also integrates historian for power system monitoring and data archiving. Finally, two different power system test cases are simulated to demonstrate the applications of developed test bed. The developed test bed can also be used for power system education.

Baseline mathematics and geodetics for tracking operations

NASA Technical Reports Server (NTRS)

James, R.

1981-01-01

Various geodetic and mapping algorithms are analyzed as they apply to radar tracking systems and tested in extended BASIC computer language for real time computer applications. Closed-form approaches to the solution of converting Earth centered coordinates to latitude, longitude, and altitude are compared with classical approximations. A simplified approach to atmospheric refractivity called gradient refraction is compared with conventional ray tracing processes. An extremely detailed set of documentation which provides the theory, derivations, and application of algorithms used in the programs is included. Validation methods are also presented for testing the accuracy of the algorithms.

Colony image acquisition and segmentation

NASA Astrophysics Data System (ADS)

Wang, W. X.

2007-12-01

For counting of both colonies and plaques, there is a large number of applications including food, dairy, beverages, hygiene, environmental monitoring, water, toxicology, sterility testing, AMES testing, pharmaceuticals, paints, sterile fluids and fungal contamination. Recently, many researchers and developers have made efforts for this kind of systems. By investigation, some existing systems have some problems. The main problems are image acquisition and image segmentation. In order to acquire colony images with good quality, an illumination box was constructed as: the box includes front lightning and back lightning, which can be selected by users based on properties of colony dishes. With the illumination box, lightning can be uniform; colony dish can be put in the same place every time, which make image processing easy. The developed colony image segmentation algorithm consists of the sub-algorithms: (1) image classification; (2) image processing; and (3) colony delineation. The colony delineation algorithm main contain: the procedures based on grey level similarity, on boundary tracing, on shape information and colony excluding. In addition, a number of algorithms are developed for colony analysis. The system has been tested and satisfactory.

Mean field analysis of algorithms for scale-free networks in molecular biology

PubMed Central

2017-01-01

The sampling of scale-free networks in Molecular Biology is usually achieved by growing networks from a seed using recursive algorithms with elementary moves which include the addition and deletion of nodes and bonds. These algorithms include the Barabási-Albert algorithm. Later algorithms, such as the Duplication-Divergence algorithm, the Solé algorithm and the iSite algorithm, were inspired by biological processes underlying the evolution of protein networks, and the networks they produce differ essentially from networks grown by the Barabási-Albert algorithm. In this paper the mean field analysis of these algorithms is reconsidered, and extended to variant and modified implementations of the algorithms. The degree sequences of scale-free networks decay according to a powerlaw distribution, namely P(k) ∼ k−γ, where γ is a scaling exponent. We derive mean field expressions for γ, and test these by numerical simulations. Generally, good agreement is obtained. We also found that some algorithms do not produce scale-free networks (for example some variant Barabási-Albert and Solé networks). PMID:29272285

Mean field analysis of algorithms for scale-free networks in molecular biology.

PubMed

Konini, S; Janse van Rensburg, E J

2017-01-01

The sampling of scale-free networks in Molecular Biology is usually achieved by growing networks from a seed using recursive algorithms with elementary moves which include the addition and deletion of nodes and bonds. These algorithms include the Barabási-Albert algorithm. Later algorithms, such as the Duplication-Divergence algorithm, the Solé algorithm and the iSite algorithm, were inspired by biological processes underlying the evolution of protein networks, and the networks they produce differ essentially from networks grown by the Barabási-Albert algorithm. In this paper the mean field analysis of these algorithms is reconsidered, and extended to variant and modified implementations of the algorithms. The degree sequences of scale-free networks decay according to a powerlaw distribution, namely P(k) ∼ k-γ, where γ is a scaling exponent. We derive mean field expressions for γ, and test these by numerical simulations. Generally, good agreement is obtained. We also found that some algorithms do not produce scale-free networks (for example some variant Barabási-Albert and Solé networks).

Comparison of Traditional and Reverse Syphilis Screening Algorithms in Medical Health Checkups.

PubMed

Nah, Eun Hee; Cho, Seon; Kim, Suyoung; Cho, Han Ik; Chai, Jong Yil

2017-11-01

The syphilis diagnostic algorithms applied in different countries vary significantly depending on the local syphilis epidemiology and other considerations, including the expected workload, the need for automation in the laboratory and budget factors. This study was performed to investigate the efficacy of traditional and reverse syphilis diagnostic algorithms during general health checkups. In total, 1,000 blood specimens were obtained from 908 men and 92 women during their regular health checkups. Traditional screening and reverse screening were applied to the same specimens using automatic rapid plasma regain (RPR) and Treponema pallidum latex agglutination (TPLA) tests, respectively. Specimens that were reverse algorithm (TPLA) reactive, were subjected to a second treponemal test performed by using the chemiluminescent microparticle immunoassay (CMIA). Of the 1,000 specimens tested, 68 (6.8%) were reactive by reverse screening (TPLA) compared with 11 (1.1%) by traditional screening (RPR). The traditional algorithm failed to detect 48 specimens [TPLA(+)/RPR(-)/CMIA(+)]. The median TPLA cutoff index (COI) was higher in CMIA-reactive cases than in CMIA-nonreactive cases (90.5 vs 12.5 U). The reverse screening algorithm could detect the subjects with possible latent syphilis who were not detected by the traditional algorithm. Those individuals could be provided with opportunities for evaluating syphilis during their health checkups. The COI values of the initial TPLA test may be helpful in excluding false-positive TPLA test results in the reverse algorithm. © The Korean Society for Laboratory Medicine

SPARTAN: A High-Fidelity Simulation for Automated Rendezvous and Docking Applications

NASA Technical Reports Server (NTRS)

Turbe, Michael A.; McDuffie, James H.; DeKock, Brandon K.; Betts, Kevin M.; Carrington, Connie K.

2007-01-01

bd Systems (a subsidiary of SAIC) has developed the Simulation Package for Autonomous Rendezvous Test and ANalysis (SPARTAN), a high-fidelity on-orbit simulation featuring multiple six-degree-of-freedom (6DOF) vehicles. SPARTAN has been developed in a modular fashion in Matlab/Simulink to test next-generation automated rendezvous and docking guidance, navigation,and control algorithms for NASA's new Vision for Space Exploration. SPARTAN includes autonomous state-based mission manager algorithms responsible for sequencing the vehicle through various flight phases based on on-board sensor inputs and closed-loop guidance algorithms, including Lambert transfers, Clohessy-Wiltshire maneuvers, and glideslope approaches The guidance commands are implemented using an integrated translation and attitude control system to provide 6DOF control of each vehicle in the simulation. SPARTAN also includes high-fidelity representations of a variety of absolute and relative navigation sensors that maybe used for NASA missions, including radio frequency, lidar, and video-based rendezvous sensors. Proprietary navigation sensor fusion algorithms have been developed that allow the integration of these sensor measurements through an extended Kalman filter framework to create a single optimal estimate of the relative state of the vehicles. SPARTAN provides capability for Monte Carlo dispersion analysis, allowing for rigorous evaluation of the performance of the complete proposed AR&D system, including software, sensors, and mechanisms. SPARTAN also supports hardware-in-the-loop testing through conversion of the algorithms to C code using Real-Time Workshop in order to be hosted in a mission computer engineering development unit running an embedded real-time operating system. SPARTAN also contains both runtime TCP/IP socket interface and post-processing compatibility with bdStudio, a visualization tool developed by bd Systems, allowing for intuitive evaluation of simulation results. A description of the SPARTAN architecture and capabilities is provided, along with details on the models and algorithms utilized and results from representative missions.

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

NASA Astrophysics Data System (ADS)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms

NASA Astrophysics Data System (ADS)

de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team

2011-12-01

The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for several runs with a prescribed set of aerosol models and an a priori data set derived from the median of AEROCOM model runs. The aerosol models and a priori data can be used in several ways, i.e. fully prescribed or with some freedom to choose a combination of aerosol models, based on the a priori or not. Another test gives insight in the effect of the cloud masks used, i.e. retrievals using the same cloud mask (the AATSR APOLLO cloud mask for collocated instruments) are compared with runs using the standard cloud masks. Tests to determine the influence of surface treatment are planned as well. The results of all these tests are evaluated by an independent team which compares the retrieval results with ground-based remote sensing (in particular AERONET) and in-situ data, and by a scoring method. Results are compared with other satellites such as MODIS and MISR. Blind tests using synthetic data are part of the algorithm characterization. The presentation will summarize results of the ongoing phase 1 inter-comparison and evaluation work within the Aerosol_cci project.

Algorithms for optimization of branching gravity-driven water networks

NASA Astrophysics Data System (ADS)

Dardani, Ian; Jones, Gerard F.

2018-05-01

The design of a water network involves the selection of pipe diameters that satisfy pressure and flow requirements while considering cost. A variety of design approaches can be used to optimize for hydraulic performance or reduce costs. To help designers select an appropriate approach in the context of gravity-driven water networks (GDWNs), this work assesses three cost-minimization algorithms on six moderate-scale GDWN test cases. Two algorithms, a backtracking algorithm and a genetic algorithm, use a set of discrete pipe diameters, while a new calculus-based algorithm produces a continuous-diameter solution which is mapped onto a discrete-diameter set. The backtracking algorithm finds the global optimum for all but the largest of cases tested, for which its long runtime makes it an infeasible option. The calculus-based algorithm's discrete-diameter solution produced slightly higher-cost results but was more scalable to larger network cases. Furthermore, the new calculus-based algorithm's continuous-diameter and mapped solutions provided lower and upper bounds, respectively, on the discrete-diameter global optimum cost, where the mapped solutions were typically within one diameter size of the global optimum. The genetic algorithm produced solutions even closer to the global optimum with consistently short run times, although slightly higher solution costs were seen for the larger network cases tested. The results of this study highlight the advantages and weaknesses of each GDWN design method including closeness to the global optimum, the ability to prune the solution space of infeasible and suboptimal candidates without missing the global optimum, and algorithm run time. We also extend an existing closed-form model of Jones (2011) to include minor losses and a more comprehensive two-part cost model, which realistically applies to pipe sizes that span a broad range typical of GDWNs of interest in this work, and for smooth and commercial steel roughness values.

The performance of the SEPT9 gene methylation assay and a comparison with other CRC screening tests: A meta-analysis.

PubMed

Song, Lele; Jia, Jia; Peng, Xiumei; Xiao, Wenhua; Li, Yuemin

2017-06-08

The SEPT9 gene methylation assay is the first FDA-approved blood assay for colorectal cancer (CRC) screening. Fecal immunochemical test (FIT), FIT-DNA test and CEA assay are also in vitro diagnostic (IVD) tests used in CRC screening. This meta-analysis aims to review the SEPT9 assay performance and compare it with other IVD CRC screening tests. By searching the Ovid MEDLINE, EMBASE, CBMdisc and CJFD database, 25 out of 180 studies were identified to report the SEPT9 assay performance. 2613 CRC cases and 6030 controls were included, and sensitivity and specificity were used to evaluate its performance at various algorithms. 1/3 algorithm exhibited the best sensitivity while 2/3 and 1/1 algorithm exhibited the best balance between sensitivity and specificity. The performance of the blood SEPT9 assay is superior to that of the serum protein markers and the FIT test in symptomatic population, while appeared to be less potent than FIT and FIT-DNA tests in asymptomatic population. In conclusion, 1/3 algorithm is recommended for CRC screening, and 2/3 or 1/1 algorithms are suitable for early detection for diagnostic purpose. The SEPT9 assay exhibited better performance in symptomatic population than in asymptomatic population.

PACE: Power-Aware Computing Engines

DTIC Science & Technology

2005-02-01

more costly than compu- tation on our test platform, and it is memory access that dominates most lossless data compression algorithms . In fact, even...Performance and implementation concerns A compression algorithm may be implemented with many different, yet reasonable, data structures (including...Related work This section discusses data compression for low- bandwidth devices and optimizing algorithms for low energy. Though much work has gone

HIV point of care diagnosis: preventing misdiagnosis experience from a pilot of rapid test algorithm implementation in selected communes in Vietnam.

PubMed

Nguyen, Van Thi Thuy; Best, Susan; Pham, Hong Thang; Troung, Thi Xuan Lien; Hoang, Thi Thanh Ha; Wilson, Kim; Ngo, Thi Hong Hanh; Chien, Xuan; Lai, Kim Anh; Bui, Duc Duong; Kato, Masaya

2017-08-29

In Vietnam, HIV testing services had been available only at provincial and district health facilities, but not at the primary health facilities. Consequently, access to HIV testing services had been limited especially in rural areas. In 2012, Vietnam piloted decentralization and integration of HIV services at commune health stations (CHSs). As a part of this pilot, a three-rapid test algorithm was introduced at CHSs. The objective of this study was to assess the performance of a three-rapid test algorithm and the implementation of quality assurance measures to prevent misdiagnosis, at primary health facilities. The three-rapid test algorithm (Determine HIV-1/2, followed by ACON HIV 1/2 and DoubleCheckGold HIV 1&2 in parallel) was piloted at CHSs from August 2012 to December 2013. Commune health staff were trained to perform HIV testing. Specimens from CHSs were sent to the provincial confirmatory laboratory (PCL) for confirmatory and validation testing. Quality assurance measures were undertaken including training, competency assessment, field technical assistance, supervision and monitoring and external quality assessment (EQA). Data on HIV testing were collected from the testing logbooks at commune and provincial facilities. Descriptive analysis was conducted. Sensitivity and specificity of the rapid testing algorithm were calculated. A total of 1,373 people received HIV testing and counselling (HTC) at CHSs. Eighty people were diagnosed with HIV infection (5.8%). The 755/1244 specimens reported as HIV negative at the CHS were sent to PCL and confirmed as negative, and all 80 specimens reported as HIV positive at CHS were confirmed as positive at the PCL. Forty-nine specimens that were reactive with Determine but negative with ACON and DoubleCheckGold at the CHSs were confirmed negative at the PCL. The results show this rapid test algorithm to be 100% sensitive and 100% specific. Of 21 CHSs that received two rounds of EQA panels, 20 CHSs submitted accurate results. Decentralization of HIV confirmatory testing to CHS is feasible in Vietnam. The results obtained from this pilot provided strong evidence of the feasibility of HIV testing at primary health facilities. Quality assurance measures including training, competency assessment, regular monitoring and supervision and an EQA scheme are essential for prevention of misdiagnosis.

Evaluation of rapid HIV test kits on whole blood and development of rapid testing algorithm for voluntary testing and counseling centers in Ethiopia.

PubMed

Tegbaru, Belete; Messele, Tsehaynesh; Wolday, Dawit; Meles, PhD Hailu; Tesema, Desalegn; Birhanu, Hiwot; Tesfaye, Girma; Bond, Kyle B; Martin, Robert; Rayfield, Mark A; Wuhib, Tadesse; Fekadu, Makonnen

2004-10-01

Five simple and rapid HIV antibody detection assays viz. Determine, Capillus, Oraquick, Unigold and Hemastrip were evaluated to examine their performance and to develop an alternative rapid test based testing algorithm for voluntary counseling and testing (VCT) in Ethiopia. All the kits were tested on whole blood, plasma and serum. The evaluation had three phases: Primary lab review, piloting at point of service and implementation. This report includes the results of the first two phases. A total of 2,693 specimens (both whole blood and plasma) were included in the evaluation. Results were compared to double Enzyme Linked Immuno-Sorbent Assay (ELISA) system. Discordant EIA results were resolved using Western Blot. The assays had very good sensitivities and specificities, 99-100%, at the two different phases of the evaluation. A 98-100% result agreement was obtained from those tested at VCT centers and National Referral Laboratory for AIDS (NRLA), in the quality control phase of the evaluation. A testing strategy yielding 100% [95% CI; 98.9-100.0] sensitivity was achieved by the sequential use of the three rapid test kits. Direct cost comparison showed serial testing algorithm reduces the cost of testing by over 30% compared to parallel testing in the current situation. Determine, Capillus/Oraquick (presence/absence of frefrigeration) and Unigold were recommended as screening, confirmation and tiebreaker tests, respectively.

A digitally implemented preambleless demodulator for maritime and mobile data communications

NASA Astrophysics Data System (ADS)

Chalmers, Harvey; Shenoy, Ajit; Verahrami, Farhad B.

The hardware design and software algorithms for a low-bit-rate, low-cost, all-digital preambleless demodulator are described. The demodulator operates under severe high-noise conditions, fast Doppler frequency shifts, large frequency offsets, and multipath fading. Sophisticated algorithms, including a fast Fourier transform (FFT)-based burst acquisition algorithm, a cycle-slip resistant carrier phase tracker, an innovative Doppler tracker, and a fast acquisition symbol synchronizer, were developed and extensively simulated for reliable burst reception. The compact digital signal processor (DSP)-based demodulator hardware uses a unique personal computer test interface for downloading test data files. The demodulator test results demonstrate a near-ideal performance within 0.2 dB of theory.

Error-proofing test system of industrial components based on image processing

NASA Astrophysics Data System (ADS)

Huang, Ying; Huang, Tao

2018-05-01

Due to the improvement of modern industrial level and accuracy, conventional manual test fails to satisfy the test standards of enterprises, so digital image processing technique should be utilized to gather and analyze the information on the surface of industrial components, so as to achieve the purpose of test. To test the installation parts of automotive engine, this paper employs camera to capture the images of the components. After these images are preprocessed including denoising, the image processing algorithm relying on flood fill algorithm is used to test the installation of the components. The results prove that this system has very high test accuracy.

Aircraft control surface failure detection and isolation using the OSGLR test. [orthogonal series generalized likelihood ratio

NASA Technical Reports Server (NTRS)

Bonnice, W. F.; Motyka, P.; Wagner, E.; Hall, S. R.

1986-01-01

The performance of the orthogonal series generalized likelihood ratio (OSGLR) test in detecting and isolating commercial aircraft control surface and actuator failures is evaluated. A modification to incorporate age-weighting which significantly reduces the sensitivity of the algorithm to modeling errors is presented. The steady-state implementation of the algorithm based on a single linear model valid for a cruise flight condition is tested using a nonlinear aircraft simulation. A number of off-nominal no-failure flight conditions including maneuvers, nonzero flap deflections, different turbulence levels and steady winds were tested. Based on the no-failure decision functions produced by off-nominal flight conditions, the failure detection and isolation performance at the nominal flight condition was determined. The extension of the algorithm to a wider flight envelope by scheduling on dynamic pressure and flap deflection is examined. Based on this testing, the OSGLR algorithm should be capable of detecting control surface failures that would affect the safe operation of a commercial aircraft. Isolation may be difficult if there are several surfaces which produce similar effects on the aircraft. Extending the algorithm over the entire operating envelope of a commercial aircraft appears feasible.

Poster - Thur Eve - 68: Evaluation and analytical comparison of different 2D and 3D treatment planning systems using dosimetry in anthropomorphic phantom.

PubMed

Khosravi, H R; Nodehi, Mr Golrokh; Asnaashari, Kh; Mahdavi, S R; Shirazi, A R; Gholami, S

2012-07-01

The aim of this study was to evaluate and analytically compare different calculation algorithms applied in our country radiotherapy centers base on the methodology developed by IAEA for treatment planning systems (TPS) commissioning (IAEA TEC-DOC 1583). Thorax anthropomorphic phantom (002LFC CIRS inc.), was used to measure 7 tests that simulate the whole chain of external beam TPS. The dose were measured with ion chambers and the deviation between measured and TPS calculated dose was reported. This methodology, which employs the same phantom and the same setup test cases, was tested in 4 different hospitals which were using 5 different algorithms/ inhomogeneity correction methods implemented in different TPS. The algorithms in this study were divided into two groups including correction based and model based algorithms. A total of 84 clinical test case datasets for different energies and calculation algorithms were produced, which amounts of differences in inhomogeneity points with low density (lung) and high density (bone) was decreased meaningfully with advanced algorithms. The number of deviations outside agreement criteria was increased with the beam energy and decreased with advancement of the TPS calculation algorithm. Large deviations were seen in some correction based algorithms, so sophisticated algorithms, would be preferred in clinical practices, especially for calculation in inhomogeneous media. Use of model based algorithms with lateral transport calculation, is recommended. Some systematic errors which were revealed during this study, is showing necessity of performing periodic audits on TPS in radiotherapy centers. © 2012 American Association of Physicists in Medicine.

Integrated communications and optical navigation system

NASA Astrophysics Data System (ADS)

Mueller, J.; Pajer, G.; Paluszek, M.

2013-12-01

The Integrated Communications and Optical Navigation System (ICONS) is a flexible navigation system for spacecraft that does not require global positioning system (GPS) measurements. The navigation solution is computed using an Unscented Kalman Filter (UKF) that can accept any combination of range, range-rate, planet chord width, landmark, and angle measurements using any celestial object. Both absolute and relative orbit determination is supported. The UKF employs a full nonlinear dynamical model of the orbit including gravity models and disturbance models. The ICONS package also includes attitude determination algorithms using the UKF algorithm with the Inertial Measurement Unit (IMU). The IMU is used as the dynamical base for the attitude determination algorithms. This makes the sensor a more capable plug-in replacement for a star tracker, thus reducing the integration and test cost of adding this sensor to a spacecraft. Recent additions include an integrated optical communications system which adds communications, and integrated range and range rate measurement and timing. The paper includes test results from trajectories based on the NASA New Horizons spacecraft.

Operation management of daily economic dispatch using novel hybrid particle swarm optimization and gravitational search algorithm with hybrid mutation strategy

NASA Astrophysics Data System (ADS)

Wang, Yan; Huang, Song; Ji, Zhicheng

2017-07-01

This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.

Comparison of various contact algorithms for poroelastic tissues.

PubMed

Galbusera, Fabio; Bashkuev, Maxim; Wilke, Hans-Joachim; Shirazi-Adl, Aboulfazl; Schmidt, Hendrik

2014-01-01

Capabilities of the commercial finite element package ABAQUS in simulating frictionless contact between two saturated porous structures were evaluated and compared with those of an open source code, FEBio. In ABAQUS, both the default contact implementation and another algorithm based on an iterative approach requiring script programming were considered. Test simulations included a patch test of two cylindrical slabs in a gapless contact and confined compression conditions; a confined compression test of a porous cylindrical slab with a spherical porous indenter; and finally two unconfined compression tests of soft tissues mimicking diarthrodial joints. The patch test showed almost identical results for all algorithms. On the contrary, the confined and unconfined compression tests demonstrated large differences related to distinct physical and boundary conditions considered in each of the three contact algorithms investigated in this study. In general, contact with non-uniform gaps between fluid-filled porous structures could be effectively simulated with either ABAQUS or FEBio. The user should be aware of the parameter definitions, assumptions and limitations in each case, and take into consideration the physics and boundary conditions of the problem of interest when searching for the most appropriate model.

Detection of person borne IEDs using multiple cooperative sensors

NASA Astrophysics Data System (ADS)

MacIntosh, Scott; Deming, Ross; Hansen, Thorkild; Kishan, Neel; Tang, Ling; Shea, Jing; Lang, Stephen

2011-06-01

The use of multiple cooperative sensors for the detection of person borne IEDs is investigated. The purpose of the effort is to evaluate the performance benefits of adding multiple sensor data streams into an aided threat detection algorithm, and a quantitative analysis of which sensor data combinations improve overall detection performance. Testing includes both mannequins and human subjects with simulated suicide bomb devices of various configurations, materials, sizes and metal content. Aided threat recognition algorithms are being developed to test detection performance of individual sensors against combined fused sensors inputs. Sensors investigated include active and passive millimeter wave imaging systems, passive infrared, 3-D profiling sensors and acoustic imaging. The paper describes the experimental set-up and outlines the methodology behind a decision fusion algorithm-based on the concept of a "body model".

Point-Counterpoint: Cervical Cancer Screening Should Be Done by Primary Human Papillomavirus Testing with Genotyping and Reflex Cytology for Women over the Age of 25 Years

PubMed Central

Zhao, Chengquan

2015-01-01

Screening for cervical cancer with cytology testing has been very effective in reducing cervical cancer in the United States. For decades, the approach was an annual Pap test. In 2000, the Hybrid Capture 2 human papillomavirus (HPV) test was approved by the U.S. Food and Drug Administration (FDA) for screening women who have atypical squamous cells of underdetermined significance (ASCUS) detected by Pap test to determine the need for colposcopy. In 2003, the FDA approved expanding the use of the test to include screening performed in conjunction with a Pap test for women over the age of 30 years, referred to as “cotesting.” Cotesting allows women to extend the testing interval to 3 years if both tests have negative results. In April of 2014, the FDA approved the use of an HPV test (the cobas HPV test) for primary cervical cancer screening for women over the age of 25 years, without the need for a concomitant Pap test. The approval recommended either colposcopy or a Pap test for patients with specific high-risk HPV types detected by the HPV test. This was based on the results of the ATHENA trial, which included more than 40,000 women. Reaction to this decision has been mixed. Supporters point to the fact that the primary-screening algorithm found more disease (cervical intraepithelial neoplasia 3 or worse [CIN3+]) and also found it earlier than did cytology or cotesting. Moreover, the positive predictive value and positive-likelihood ratio of the primary-screening algorithm were higher than those of cytology. Opponents of the decision prefer cotesting, as this approach detects more disease than the HPV test alone. In addition, the performance of this new algorithm has not been assessed in routine clinical use. Professional organizations will need to develop guidelines that incorporate this testing algorithm. In this Point-Counterpoint, Dr. Stoler explains why he favors the primary-screening algorithm, while Drs. Austin and Zhao explain why they prefer the cotesting approach to screening for cervical cancer. PMID:25948606

Generation and assessment of turntable SAR data for the support of ATR development

NASA Astrophysics Data System (ADS)

Cohen, Marvin N.; Showman, Gregory A.; Sangston, K. James; Sylvester, Vincent B.; Gostin, Lamar; Scheer, C. Ruby

1998-10-01

Inverse synthetic aperture radar (ISAR) imaging on a turntable-tower test range permits convenient generation of high resolution two-dimensional images of radar targets under controlled conditions for testing SAR image processing and for supporting automatic target recognition (ATR) algorithm development. However, turntable ISAR images are often obtained under near-field geometries and hence may suffer geometric distortions not present in airborne SAR images. In this paper, turntable data collected at Georgia Tech's Electromagnetic Test Facility are used to begin to assess the utility of two- dimensional ISAR imaging algorithms in forming images to support ATR development. The imaging algorithms considered include a simple 2D discrete Fourier transform (DFT), a 2-D DFT with geometric correction based on image domain resampling, and a computationally-intensive geometric matched filter solution. Images formed with the various algorithms are used to develop ATR templates, which are then compared with an eye toward utilization in an ATR algorithm.

A Frequency-Domain Substructure System Identification Algorithm

NASA Technical Reports Server (NTRS)

Blades, Eric L.; Craig, Roy R., Jr.

1996-01-01

A new frequency-domain system identification algorithm is presented for system identification of substructures, such as payloads to be flown aboard the Space Shuttle. In the vibration test, all interface degrees of freedom where the substructure is connected to the carrier structure are either subjected to active excitation or are supported by a test stand with the reaction forces measured. The measured frequency-response data is used to obtain a linear, viscous-damped model with all interface-degree of freedom entries included. This model can then be used to validate analytical substructure models. This procedure makes it possible to obtain not only the fixed-interface modal data associated with a Craig-Bampton substructure model, but also the data associated with constraint modes. With this proposed algorithm, multiple-boundary-condition tests are not required, and test-stand dynamics is accounted for without requiring a separate modal test or finite element modeling of the test stand. Numerical simulations are used in examining the algorithm's ability to estimate valid reduced-order structural models. The algorithm's performance when frequency-response data covering narrow and broad frequency bandwidths is used as input is explored. Its performance when noise is added to the frequency-response data and the use of different least squares solution techniques are also examined. The identified reduced-order models are also compared for accuracy with other test-analysis models and a formulation for a Craig-Bampton test-analysis model is also presented.

N-terminal pro-B-type natriuretic peptide diagnostic algorithm versus American Heart Association algorithm for Kawasaki disease.

PubMed

Dionne, Audrey; Meloche-Dumas, Léamarie; Desjardins, Laurent; Turgeon, Jean; Saint-Cyr, Claire; Autmizguine, Julie; Spigelblatt, Linda; Fournier, Anne; Dahdah, Nagib

2017-03-01

Diagnosis of Kawasaki disease (KD) can be challenging in the absence of a confirmatory test or pathognomonic finding, especially when clinical criteria are incomplete. We recently proposed serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) as an adjunctive diagnostic test. We retrospectively tested a new algorithm to help KD diagnosis based on NT-proBNP, coronary artery dilation (CAD) at onset, and abnormal serum albumin or C-reactive protein (CRP). The goal was to assess the performance of the algorithm and compare its performance with that of the 2004 American Heart Association (AHA)/American Academy of Pediatrics (AAP) algorithm. The algorithm was tested on 124 KD patients with NT-proBNP measured on admission at the present institutions between 2007 and 2013. Age at diagnosis was 3.4 ± 3.0 years, with a median of five diagnostic criteria; and 55 of the 124 patients (44%) had incomplete KD. CA complications occurred in 64 (52%), with aneurysm in 14 (11%). Using this algorithm, 120/124 (97%) were to be treated, based on high NT-proBNP alone for 79 (64%); on onset CAD for 14 (11%); and on high CRP or low albumin for 27 (22%). Using the AHA/AAP algorithm, 22/47 (47%) of the eligible patients with incomplete KD would not have been referred for treatment, compared with 3/55 (5%) with the NT-proBNP algorithm (P < 0.001). This NT-proBNP-based algorithm is efficient to identify and treat patients with KD, including those with incomplete KD. This study paves the way for a prospective validation trial of the algorithm. © 2016 Japan Pediatric Society.

Machine Learning for Biological Trajectory Classification Applications

NASA Technical Reports Server (NTRS)

Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros

2002-01-01

Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

Directed Design of Experiments for Validating Probability of Detection Capability of a Testing System

NASA Technical Reports Server (NTRS)

Generazio, Edward R. (Inventor)

2012-01-01

A method of validating a probability of detection (POD) testing system using directed design of experiments (DOE) includes recording an input data set of observed hit and miss or analog data for sample components as a function of size of a flaw in the components. The method also includes processing the input data set to generate an output data set having an optimal class width, assigning a case number to the output data set, and generating validation instructions based on the assigned case number. An apparatus includes a host machine for receiving the input data set from the testing system and an algorithm for executing DOE to validate the test system. The algorithm applies DOE to the input data set to determine a data set having an optimal class width, assigns a case number to that data set, and generates validation instructions based on the case number.

Testing the accuracy of redshift-space group-finding algorithms

NASA Astrophysics Data System (ADS)

Frederic, James J.

1995-04-01

Using simulated redshift surveys generated from a high-resolution N-body cosmological structure simulation, we study algorithms used to identify groups of galaxies in redshift space. Two algorithms are investigated; both are friends-of-friends schemes with variable linking lengths in the radial and transverse dimenisons. The chief difference between the algorithms is in the redshift linking length. The algorithm proposed by Huchra & Geller (1982) uses a generous linking length designed to find 'fingers of god,' while that of Nolthenius & White (1987) uses a smaller linking length to minimize contamination by projection. We find that neither of the algorithms studied is intrinsically superior to the other; rather, the ideal algorithm as well as the ideal algorithm parameters depends on the purpose for which groups are to be studied. The Huchra & Geller algorithm misses few real groups, at the cost of including some spurious groups and members, while the Nolthenius & White algorithm misses high velocity dispersion groups and members but is less likely to include interlopers in its group assignments. Adjusting the parameters of either algorithm results in a trade-off between group accuracy and completeness. In a companion paper we investigate the accuracy of virial mass estimates and clustering properties of groups identified using these algorithms.

Exploration of the Performance of a Hybrid Closed Loop Insulin Delivery Algorithm That Includes Insulin Delivery Limits Designed to Protect Against Hypoglycemia.

PubMed

de Bock, Martin; Dart, Julie; Roy, Anirban; Davey, Raymond; Soon, Wayne; Berthold, Carolyn; Retterath, Adam; Grosman, Benyamin; Kurtz, Natalie; Davis, Elizabeth; Jones, Timothy

2017-01-01

Hypoglycemia remains a risk for closed loop insulin delivery particularly following exercise or if the glucose sensor is inaccurate. The aim of this study was to test whether an algorithm that includes a limit to insulin delivery is effective at protecting against hypoglycemia under those circumstances. An observational study on 8 participants with type 1 diabetes was conducted, where a hybrid closed loop system (HCL) (Medtronic™ 670G) was challenged with hypoglycemic stimuli: exercise and an overreading glucose sensor. There was no overnight or exercise-induced hypoglycemia during HCL insulin delivery. All daytime hypoglycemia was attributable to postmeal bolused insulin in those participants with a more aggressive carbohydrate factor. HCL systems rely on accurate carbohydrate ratios and carbohydrate counting to avoid hypoglycemia. The algorithm that was tested against moderate exercise and an overreading glucose sensor performed well in terms of hypoglycemia avoidance. Algorithm refinement continues in preparation for long-term outpatient trials.

Prediction of Baseflow Index of Catchments using Machine Learning Algorithms

NASA Astrophysics Data System (ADS)

Yadav, B.; Hatfield, K.

2017-12-01

We present the results of eight machine learning techniques for predicting the baseflow index (BFI) of ungauged basins using a surrogate of catchment scale climate and physiographic data. The tested algorithms include ordinary least squares, ridge regression, least absolute shrinkage and selection operator (lasso), elasticnet, support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Our work seeks to identify the dominant controls of BFI that can be readily obtained from ancillary geospatial databases and remote sensing measurements, such that the developed techniques can be extended to ungauged catchments. More than 800 gauged catchments spanning the continental United States were selected to develop the general methodology. The BFI calculation was based on the baseflow separated from daily streamflow hydrograph using HYSEP filter. The surrogate catchment attributes were compiled from multiple sources including digital elevation model, soil, landuse, climate data, other publicly available ancillary and geospatial data. 80% catchments were used to train the ML algorithms, and the remaining 20% of the catchments were used as an independent test set to measure the generalization performance of fitted models. A k-fold cross-validation using exhaustive grid search was used to fit the hyperparameters of each model. Initial model development was based on 19 independent variables, but after variable selection and feature ranking, we generated revised sparse models of BFI prediction that are based on only six catchment attributes. These key predictive variables selected after the careful evaluation of bias-variance tradeoff include average catchment elevation, slope, fraction of sand, permeability, temperature, and precipitation. The most promising algorithms exceeding an accuracy score (r-square) of 0.7 on test data include support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Considering both the accuracy and the computational complexity of these algorithms, we identify the extremely randomized trees as the best performing algorithm for BFI prediction in ungauged basins.

Implementing a self-structuring data learning algorithm

NASA Astrophysics Data System (ADS)

Graham, James; Carson, Daniel; Ternovskiy, Igor

2016-05-01

In this paper, we elaborate on what we did to implement our self-structuring data learning algorithm. To recap, we are working to develop a data learning algorithm that will eventually be capable of goal driven pattern learning and extrapolation of more complex patterns from less complex ones. At this point we have developed a conceptual framework for the algorithm, but have yet to discuss our actual implementation and the consideration and shortcuts we needed to take to create said implementation. We will elaborate on our initial setup of the algorithm and the scenarios we used to test our early stage algorithm. While we want this to be a general algorithm, it is necessary to start with a simple scenario or two to provide a viable development and testing environment. To that end, our discussion will be geared toward what we include in our initial implementation and why, as well as what concerns we may have. In the future, we expect to be able to apply our algorithm to a more general approach, but to do so within a reasonable time, we needed to pick a place to start.

Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

NASA Astrophysics Data System (ADS)

Oesterle, Jonathan; Lionel, Amodeo

2018-06-01

The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.

Analysis of image thresholding segmentation algorithms based on swarm intelligence

NASA Astrophysics Data System (ADS)

Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo

2013-03-01

Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.

Radar Detection of Marine Mammals

DTIC Science & Technology

2010-09-30

associative tracker using the Munkres algorithm was used. This was then expanded to include a track - before - detect algorithm, the Baysean Field...small, slow moving objects (i.e. whales). In order to address the third concern (M2 mode), we have tested using a track - before - detect tracker termed

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Approximate string matching algorithms for limited-vocabulary OCR output correction

NASA Astrophysics Data System (ADS)

Lasko, Thomas A.; Hauser, Susan E.

2000-12-01

Five methods for matching words mistranslated by optical character recognition to their most likely match in a reference dictionary were tested on data from the archives of the National Library of Medicine. The methods, including an adaptation of the cross correlation algorithm, the generic edit distance algorithm, the edit distance algorithm with a probabilistic substitution matrix, Bayesian analysis, and Bayesian analysis on an actively thinned reference dictionary were implemented and their accuracy rates compared. Of the five, the Bayesian algorithm produced the most correct matches (87%), and had the advantage of producing scores that have a useful and practical interpretation.

Objective speech quality assessment and the RPE-LTP coding algorithm in different noise and language conditions.

PubMed

Hansen, J H; Nandkumar, S

1995-01-01

The formulation of reliable signal processing algorithms for speech coding and synthesis require the selection of a prior criterion of performance. Though coding efficiency (bits/second) or computational requirements can be used, a final performance measure must always include speech quality. In this paper, three objective speech quality measures are considered with respect to quality assessment for American English, noisy American English, and noise-free versions of seven languages. The purpose is to determine whether objective quality measures can be used to quantify changes in quality for a given voice coding method, with a known subjective performance level, as background noise or language conditions are changed. The speech coding algorithm chosen is regular-pulse excitation with long-term prediction (RPE-LTP), which has been chosen as the standard voice compression algorithm for the European Digital Mobile Radio system. Three areas are considered for objective quality assessment which include: (i) vocoder performance for American English in a noise-free environment, (ii) speech quality variation for three additive background noise sources, and (iii) noise-free performance for seven languages which include English, Japanese, Finnish, German, Hindi, Spanish, and French. It is suggested that although existing objective quality measures will never replace subjective testing, they can be a useful means of assessing changes in performance, identifying areas for improvement in algorithm design, and augmenting subjective quality tests for voice coding/compression algorithms in noise-free, noisy, and/or non-English applications.

Improved classification accuracy by feature extraction using genetic algorithms

NASA Astrophysics Data System (ADS)

Patriarche, Julia; Manduca, Armando; Erickson, Bradley J.

2003-05-01

A feature extraction algorithm has been developed for the purposes of improving classification accuracy. The algorithm uses a genetic algorithm / hill-climber hybrid to generate a set of linearly recombined features, which may be of reduced dimensionality compared with the original set. The genetic algorithm performs the global exploration, and a hill climber explores local neighborhoods. Hybridizing the genetic algorithm with a hill climber improves both the rate of convergence, and the final overall cost function value; it also reduces the sensitivity of the genetic algorithm to parameter selection. The genetic algorithm includes the operators: crossover, mutation, and deletion / reactivation - the last of these effects dimensionality reduction. The feature extractor is supervised, and is capable of deriving a separate feature space for each tissue (which are reintegrated during classification). A non-anatomical digital phantom was developed as a gold standard for testing purposes. In tests with the phantom, and with images of multiple sclerosis patients, classification with feature extractor derived features yielded lower error rates than using standard pulse sequences, and with features derived using principal components analysis. Using the multiple sclerosis patient data, the algorithm resulted in a mean 31% reduction in classification error of pure tissues.

Applying FastSLAM to Articulated Rovers

NASA Astrophysics Data System (ADS)

Hewitt, Robert Alexander

This thesis presents the navigation algorithms designed for use on Kapvik, a 30 kg planetary micro-rover built for the Canadian Space Agency; the simulations used to test the algorithm; and novel techniques for terrain classification using Kapvik's LIDAR (Light Detection And Ranging) sensor. Kapvik implements a six-wheeled, skid-steered, rocker-bogie mobility system. This warrants a more complicated kinematic model for navigation than a typical 4-wheel differential drive system. The design of a 3D navigation algorithm is presented that includes nonlinear Kalman filtering and Simultaneous Localization and Mapping (SLAM). A neural network for terrain classification is used to improve navigation performance. Simulation is used to train the neural network and validate the navigation algorithms. Real world tests of the terrain classification algorithm validate the use of simulation for training and the improvement to SLAM through the reduction of extraneous LIDAR measurements in each scan.

Space vehicle Viterbi decoder. [data converters, algorithms

NASA Technical Reports Server (NTRS)

1975-01-01

The design and fabrication of an extremely low-power, constraint-length 7, rate 1/3 Viterbi decoder brassboard capable of operating at information rates of up to 100 kb/s is presented. The brassboard is partitioned to facilitate a later transition to an LSI version requiring even less power. The effect of soft-decision thresholds, path memory lengths, and output selection algorithms on the bit error rate is evaluated. A branch synchronization algorithm is compared with a more conventional approach. The implementation of the decoder and its test set (including all-digital noise source) are described along with the results of various system tests and evaluations. Results and recommendations are presented.

Application of a novel particle tracking algorithm in the flow visualization of an artificial abdominal aortic aneurysm.

PubMed

Zhang, Yang; Wang, Yuan; He, Wenbo; Yang, Bin

2014-01-01

A novel Particle Tracking Velocimetry (PTV) algorithm based on Voronoi Diagram (VD) is proposed and briefed as VD-PTV. The robustness of VD-PTV for pulsatile flow is verified through a test that includes a widely used artificial flow and a classic reference algorithm. The proposed algorithm is then applied to visualize the flow in an artificial abdominal aortic aneurysm included in a pulsatile circulation system that simulates the aortic blood flow in human body. Results show that, large particles tend to gather at the upstream boundary because of the backflow eddies that follow the pulsation. This qualitative description, together with VD-PTV, has laid a foundation for future works that demand high-level quantification.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

Two aspects of work on automatic target detection and tracking for electro-optic (EO) surveillance are described. Firstly, a detection and tracking algorithm test-bed developed by DSTO and running on a PC under Windows NT is being used to assess candidate algorithms for unresolved and minimally resolved target detection. The structure of this test-bed is described and examples are given of its user interfaces and outputs. Secondly, a development by Australian industry under a Defence-funded contract, of a reconfigurable generic track processor (GTP) is outlined. The GTP will include reconfigurable image processing stages and target tracking algorithms. It will be used to demonstrate to the Australian Defence Force automatic detection and tracking capabilities, and to serve as a hardware base for real time algorithm refinement.

[Evaluation of the benefit of different complementary exams in the search for a TB diagnosis algorithm for HIV patients put on ART in Niamey, Niger].

PubMed

Ouedraogo, E; Lurton, G; Mohamadou, S; Dillé, I; Diallo, I; Mamadou, S; Adehossi, E; Hanki, Y; Tchousso, O; Arzika, M; Gazeré, O; Amadou, F; Illo, N; Abdourahmane, Y; Idé, M; Alhousseini, Z; Lamontagne, F; Deze, C; D'Ortenzio, E; Diallo, S

2016-12-01

In Niger, the tuberculosis (TB) screening among people living with human immunodeficiency virus (HIV) (PLHIV) is nonsystematic and the use of additional tests is very often limited. The objective of this research is to evaluate the performance and the cost-effectiveness of various paraclinical testing strategies of TB among adult patients with HIV, using available tests in routine for patients cared in Niamey. This is a multicentric prospective intervention study performed in Niamey between 2010 and 2013. TB screening has been sought in newly diagnosed PLHIV, before ART treatment, performing consistently: a sputum examination by MZN (Ziehl-Nielsen staining) and microscopy fluorescence (MIF), chest radiography (CR), and abdominal ultrasound. The performance of these different tests was calculated using sputum culture as a gold standard. The various examinations were then combined in different algorithms. The cost-effectiveness of different algorithms was assessed by calculating the money needed to prevent a patient, put on ART, dying of TB. Between November 2010 and November 2012, 509 PLHIV were included. TB was diagnosed in 78 patients (15.3%), including 35 pulmonary forms, 24 ganglion, and 19 multifocal. The sensitivity of the evaluated algorithms varied between 0.35 and 0.85. The specificity ranged from 0.85 to 0.97. The most costeffective algorithm was the one involving MIF and CR. We recommend implementing a systematic and free direct examination of sputum by MIF and a CR for the detection of TB among newly diagnosed PLHIV in Niger.

Application of the Trend Filtering Algorithm for Photometric Time Series Data

NASA Astrophysics Data System (ADS)

Gopalan, Giri; Plavchan, Peter; van Eyken, Julian; Ciardi, David; von Braun, Kaspar; Kane, Stephen R.

2016-08-01

Detecting transient light curves (e.g., transiting planets) requires high-precision data, and thus it is important to effectively filter systematic trends affecting ground-based wide-field surveys. We apply an implementation of the Trend Filtering Algorithm (TFA) to the 2MASS calibration catalog and select Palomar Transient Factory (PTF) photometric time series data. TFA is successful at reducing the overall dispersion of light curves, however, it may over-filter intrinsic variables and increase “instantaneous” dispersion when a template set is not judiciously chosen. In an attempt to rectify these issues we modify the original TFA from the literature by including measurement uncertainties in its computation, including ancillary data correlated with noise, and algorithmically selecting a template set using clustering algorithms as suggested by various authors. This approach may be particularly useful for appropriately accounting for variable photometric precision surveys and/or combined data sets. In summary, our contributions are to provide a MATLAB software implementation of TFA and a number of modifications tested on synthetics and real data, summarize the performance of TFA and various modifications on real ground-based data sets (2MASS and PTF), and assess the efficacy of TFA and modifications using synthetic light curve tests consisting of transiting and sinusoidal variables. While the transiting variables test indicates that these modifications confer no advantage to transit detection, the sinusoidal variables test indicates potential improvements in detection accuracy.

Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

PubMed Central

Li, Jun-qing; Pan, Quan-ke; Mao, Kun

2014-01-01

A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414

Testing of next-generation nonlinear calibration based non-uniformity correction techniques using SWIR devices

NASA Astrophysics Data System (ADS)

Lovejoy, McKenna R.; Wickert, Mark A.

2017-05-01

A known problem with infrared imaging devices is their non-uniformity. This non-uniformity is the result of dark current, amplifier mismatch as well as the individual photo response of the detectors. To improve performance, non-uniformity correction (NUC) techniques are applied. Standard calibration techniques use linear, or piecewise linear models to approximate the non-uniform gain and off set characteristics as well as the nonlinear response. Piecewise linear models perform better than the one and two-point models, but in many cases require storing an unmanageable number of correction coefficients. Most nonlinear NUC algorithms use a second order polynomial to improve performance and allow for a minimal number of stored coefficients. However, advances in technology now make higher order polynomial NUC algorithms feasible. This study comprehensively tests higher order polynomial NUC algorithms targeted at short wave infrared (SWIR) imagers. Using data collected from actual SWIR cameras, the nonlinear techniques and corresponding performance metrics are compared with current linear methods including the standard one and two-point algorithms. Machine learning, including principal component analysis, is explored for identifying and replacing bad pixels. The data sets are analyzed and the impact of hardware implementation is discussed. Average floating point results show 30% less non-uniformity, in post-corrected data, when using a third order polynomial correction algorithm rather than a second order algorithm. To maximize overall performance, a trade off analysis on polynomial order and coefficient precision is performed. Comprehensive testing, across multiple data sets, provides next generation model validation and performance benchmarks for higher order polynomial NUC methods.

Combing Visible and Infrared Spectral Tests for Dust Identification

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Levy, Robert; Kleidman, Richard; Remer, Lorraine; Mattoo, Shana

2016-01-01

The MODIS Dark Target aerosol algorithm over Ocean (DT-O) uses spectral reflectance in the visible, near-IR and SWIR wavelengths to determine aerosol optical depth (AOD) and Angstrom Exponent (AE). Even though DT-O does have "dust-like" models to choose from, dust is not identified a priori before inversion. The "dust-like" models are not true "dust models" as they are spherical and do not have enough absorption at short wavelengths, so retrieved AOD and AE for dusty regions tends to be biased. The inference of "dust" is based on postprocessing criteria for AOD and AE by users. Dust aerosol has known spectral signatures in the near-UV (Deep blue), visible, and thermal infrared (TIR) wavelength regions. Multiple dust detection algorithms have been developed over the years with varying detection capabilities. Here, we test a few of these dust detection algorithms, to determine whether they can be useful to help inform the choices made by the DT-O algorithm. We evaluate the following methods: The multichannel imager (MCI) algorithm uses spectral threshold tests in (0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 micrometer) channels and spatial uniformity test [Zhao et al., 2010]. The NOAA dust aerosol index (DAI) uses spectral contrast in the blue channels (412nm and 440nm) [Ciren and Kundragunta, 2014]. The MCI is already included as tests within the "Wisconsin" (MOD35) Cloud mask algorithm.

A two-stage algorithm for Clostridium difficile including PCR: can we replace the toxin EIA?

PubMed

Orendi, J M; Monnery, D J; Manzoor, S; Hawkey, P M

2012-01-01

A two step, three-test algorithm for Clostridium difficile infection (CDI) was reviewed. Stool samples were tested by enzyme immunoassays for C. difficile common antigen glutamate dehydrogenase (G) and toxin A/B (T). Samples with discordant results were tested by polymerase chain reaction detecting the toxin B gene (P). The algorithm quickly identified patients with detectable toxin A/B, whereas a large group of patients excreting toxigenic C. difficile but with toxin A/B production below detection level (G(+)T(-)P(+)) was identified separately. The average white blood cell count in patients with a G(+)T(+) result was higher than in those with a G(+)T(-)P(+) result. Copyright © 2011 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Failure detection and isolation analysis of a redundant strapdown inertial measurement unit

NASA Technical Reports Server (NTRS)

Motyka, P.; Landey, M.; Mckern, R.

1981-01-01

The objective of this study was to define and develop techniques for failure detection and isolation (FDI) algorithms for a dual fail/operational redundant strapdown inertial navigation system are defined and developed. The FDI techniques chosen include provisions for hard and soft failure detection in the context of flight control and navigation. Analyses were done to determine error detection and switching levels for the inertial navigation system, which is intended for a conventional takeoff or landing (CTOL) operating environment. In addition, investigations of false alarms and missed alarms were included for the FDI techniques developed, along with the analyses of filters to be used in conjunction with FDI processing. Two specific FDI algorithms were compared: the generalized likelihood test and the edge vector test. A deterministic digital computer simulation was used to compare and evaluate the algorithms and FDI systems.

Sensitivity and Specificity of Human Immunodeficiency Virus Rapid Serologic Assays and Testing Algorithms in an Antenatal Clinic in Abidjan, Ivory Coast

PubMed Central

Koblavi-Dème, Stéphania; Maurice, Chantal; Yavo, Daniel; Sibailly, Toussaint S.; N′guessan, Kabran; Kamelan-Tano, Yvonne; Wiktor, Stefan Z.; Roels, Thierry H.; Chorba, Terence; Nkengasong, John N.

2001-01-01

To evaluate serologic testing algorithms for human immunodeficiency virus (HIV) based on a combination of rapid assays among persons with HIV-1 (non-B subtypes) infection, HIV-2 infection, and HIV-1–HIV-2 dual infections in Abidjan, Ivory Coast, a total of 1,216 sera with known HIV serologic status were used to evaluate the sensitivity and specificity of four rapid assays: Determine HIV-1/2, Capillus HIV-1/HIV-2, HIV-SPOT, and Genie II HIV-1/HIV-2. Two serum panels obtained from patients recently infected with HIV-1 subtypes B and non-B were also included. Based on sensitivity and specificity, three of the four rapid assays were evaluated prospectively in parallel (serum samples tested by two simultaneous rapid assays) and serial (serum samples tested by two consecutive rapid assays) testing algorithms. All assays were 100% sensitive, and specificities ranged from 99.4 to 100%. In the prospective evaluation, both the parallel and serial algorithms were 100% sensitive and specific. Our results suggest that rapid assays have high sensitivity and specificity and, when used in parallel or serial testing algorithms, yield results similar to those of enzyme-linked immunosorbent assay-based testing strategies. HIV serodiagnosis based on rapid assays may be a valuable alternative in implementing HIV prevention and surveillance programs in areas where sophisticated laboratories are difficult to establish. PMID:11325995

Comparison of turnaround time and total cost of HIV testing before and after implementation of the 2014 CDC/APHL Laboratory Testing Algorithm for diagnosis of HIV infection.

PubMed

Chen, Derrick J; Yao, Joseph D

2017-06-01

Updated recommendations for HIV diagnostic laboratory testing published by the Centers for Disease Control and Prevention and the Association of Public Health Laboratories incorporate 4th generation HIV immunoassays, which are capable of identifying HIV infection prior to seroconversion. The purpose of this study was to compare turnaround time and cost between 3rd and 4th generation HIV immunoassay-based testing algorithms for initially reactive results. The clinical microbiology laboratory database at Mayo Clinic, Rochester, MN was queried for 3rd generation (from November 2012 to May 2014) and 4th generation (from May 2014 to November 2015) HIV immunoassay results. All results from downstream supplemental testing were recorded. Turnaround time (defined as the time of initial sample receipt in the laboratory to the time the final supplemental test in the algorithm was resulted) and cost (based on 2016 Medicare reimbursement rates) were assessed. A total of 76,454 and 78,998 initial tests were performed during the study period using the 3rd generation and 4th generation HIV immunoassays, respectively. There were 516 (0.7%) and 581 (0.7%) total initially reactive results, respectively. Of these, 304 (58.9%) and 457 (78.7%) were positive by supplemental testing. There were 10 (0.01%) cases of acute HIV infection identified with the 4th generation algorithm. The most frequent tests performed to confirm an HIV-positive case using the 3rd generation algorithm, which were reactive initial immunoassay and positive HIV-1 Western blot, took a median time of 1.1 days to complete at a cost of $45.00. In contrast, the most frequent tests performed to confirm an HIV-positive case using the 4th generation algorithm, which included a reactive initial immunoassay and positive HIV-1/-2 antibody differentiation immunoassay for HIV-1, took a median time of 0.4 days and cost $63.25. Overall median turnaround time was 2.2 and 1.5 days, and overall median cost was $63.90 and $72.50 for 3rd and 4th generation algorithms, respectively. Both 3rd and 4th generation HIV immunoassays had similar total numbers of tests performed and positivity rates during the study period. A greater proportion of reactive 4th generation immunoassays were confirmed to be positive, and the 4th generation algorithm identified several cases of acute HIV infection that would have been missed by the 3rd generation algorithm. The 4th generation algorithm had a more rapid turnaround time but higher cost for confirmed positive HIV infections and overall, compared to the 3rd generation algorithm. Copyright © 2017 Elsevier B.V. All rights reserved.

MSS D Multispectral Scanner System

NASA Technical Reports Server (NTRS)

Lauletta, A. M.; Johnson, R. L.; Brinkman, K. L. (Principal Investigator)

1982-01-01

The development and acceptance testing of the 4-band Multispectral Scanners to be flown on LANDSAT D and LANDSAT D Earth resources satellites are summarized. Emphasis is placed on the acceptance test phase of the program. Test history and acceptance test algorithms are discussed. Trend data of all the key performance parameters are included and discussed separately for each of the two multispectral scanner instruments. Anomalies encountered and their resolutions are included.

Inertial Gait Phase Detection for control of a drop foot stimulator Inertial sensing for gait phase detection.

PubMed

Kotiadis, D; Hermens, H J; Veltink, P H

2010-05-01

An Inertial Gait Phase Detection system was developed to replace heel switches and footswitches currently being used for the triggering of drop foot stimulators. A series of four algorithms utilising accelerometers and gyroscopes individually and in combination were tested and initial results are shown. Sensors were positioned on the outside of the upper shank. Tests were performed on data gathered from a subject, sufferer of stroke, implanted with a drop foot stimulator and triggered with the current trigger, the heel switch. Data tested includes a variety of activities representing everyday life. Flat surface walking, rough terrain and carpet walking show 100% detection and the ability of the algorithms to ignore non-gait events such as weight shifts. Timing analysis is performed against the current triggering method, the heel switch. After evaluating the heel switch timing against a reference system, namely the Vicon 370 marker and force plates system. Initial results show a close correlation between the current trigger detection and the inertial sensor based triggering algorithms. Algorithms were tested for stairs up and stairs down. Best results are observed for algorithms using gyroscope data. Algorithms were designed using threshold techniques for lowest possible computational load and with least possible sensor components to minimize power requirements and to allow for potential future implantation of sensor system.

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

NASA Technical Reports Server (NTRS)

Overmeyer, Austin D.

2015-01-01

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection.

PubMed

Guvensan, M Amac; Dusun, Burak; Can, Baris; Turkmen, H Irem

2017-12-30

Transportation planning and solutions have an enormous impact on city life. To minimize the transport duration, urban planners should understand and elaborate the mobility of a city. Thus, researchers look toward monitoring people's daily activities including transportation types and duration by taking advantage of individual's smartphones. This paper introduces a novel segment-based transport mode detection architecture in order to improve the results of traditional classification algorithms in the literature. The proposed post-processing algorithm, namely the Healing algorithm, aims to correct the misclassification results of machine learning-based solutions. Our real-life test results show that the Healing algorithm could achieve up to 40% improvement of the classification results. As a result, the implemented mobile application could predict eight classes including stationary, walking, car, bus, tram, train, metro and ferry with a success rate of 95% thanks to the proposed multi-tier architecture and Healing algorithm.

An Introduction to the Computerized Adaptive Testing

ERIC Educational Resources Information Center

Tian, Jian-quan; Miao, Dan-min; Zhu, Xia; Gong, Jing-jing

2007-01-01

Computerized adaptive testing (CAT) has unsurpassable advantages over traditional testing. It has become the mainstream in large scale examinations in modern society. This paper gives a brief introduction to CAT including differences between traditional testing and CAT, the principles of CAT, psychometric theory and computer algorithms of CAT, the…

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

NASA Technical Reports Server (NTRS)

Trevino, Luis; Johnson, Stephen B.; Patterson, Jonathan; Teare, David

2015-01-01

The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Precise Image-Based Motion Estimation for Autonomous Small Body Exploration

NASA Technical Reports Server (NTRS)

Johnson, Andrew Edie; Matthies, Larry H.

2000-01-01

We have developed and tested a software algorithm that enables onboard autonomous motion estimation near small bodies using descent camera imagery and laser altimetry. Through simulation and testing, we have shown that visual feature tracking can decrease uncertainty in spacecraft motion to a level that makes landing on small, irregularly shaped, bodies feasible. Possible future work will include qualification of the algorithm as a flight experiment for the Deep Space 4/Champollion comet lander mission currently under study at the Jet Propulsion Laboratory.

An Adaptive Inpainting Algorithm Based on DCT Induced Wavelet Regularization

DTIC Science & Technology

2013-01-01

research in image processing. Applications of image inpainting include old films restoration, video inpainting [4], de -interlacing of video sequences...show 5 (a) (b) (c) (d) (e) (f) Fig. 1. Performance of various inpainting algorithms for a cartoon image with text. (a) the original test image; (b...the test image with text; inpainted images by (c) SF (PSNR=37.38 dB); (d) SF-LDCT (PSNR=37.37 dB); (e) MCA (PSNR=37.04 dB); and (f) the proposed

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

Benchmarking for Bayesian Reinforcement Learning

PubMed Central

Ernst, Damien; Couëtoux, Adrien

2016-01-01

In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the collected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand. Many BRL algorithms have already been proposed, but the benchmarks used to compare them are only relevant for specific cases. The paper addresses this problem, and provides a new BRL comparison methodology along with the corresponding open source library. In this methodology, a comparison criterion that measures the performance of algorithms on large sets of Markov Decision Processes (MDPs) drawn from some probability distributions is defined. In order to enable the comparison of non-anytime algorithms, our methodology also includes a detailed analysis of the computation time requirement of each algorithm. Our library is released with all source code and documentation: it includes three test problems, each of which has two different prior distributions, and seven state-of-the-art RL algorithms. Finally, our library is illustrated by comparing all the available algorithms and the results are discussed. PMID:27304891

Benchmarking for Bayesian Reinforcement Learning.

PubMed

Castronovo, Michael; Ernst, Damien; Couëtoux, Adrien; Fonteneau, Raphael

2016-01-01

In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the collected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand. Many BRL algorithms have already been proposed, but the benchmarks used to compare them are only relevant for specific cases. The paper addresses this problem, and provides a new BRL comparison methodology along with the corresponding open source library. In this methodology, a comparison criterion that measures the performance of algorithms on large sets of Markov Decision Processes (MDPs) drawn from some probability distributions is defined. In order to enable the comparison of non-anytime algorithms, our methodology also includes a detailed analysis of the computation time requirement of each algorithm. Our library is released with all source code and documentation: it includes three test problems, each of which has two different prior distributions, and seven state-of-the-art RL algorithms. Finally, our library is illustrated by comparing all the available algorithms and the results are discussed.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System Data Integration Algorithm.

PubMed

Nikolic, Dejan; Stojkovic, Nikola; Lekic, Nikola

2018-04-09

To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data.

Towards a robust framework for catchment classification

NASA Astrophysics Data System (ADS)

Deshmukh, A.; Samal, A.; Singh, R.

2017-12-01

Classification of catchments based on various measures of similarity has emerged as an important technique to understand regional scale hydrologic behavior. Classification of catchment characteristics and/or streamflow response has been used reveal which characteristics are more likely to explain the observed variability of hydrologic response. However, numerous algorithms for supervised or unsupervised classification are available, making it hard to identify the algorithm most suitable for the dataset at hand. Consequently, existing catchment classification studies vary significantly in the classification algorithms employed with no previous attempt at understanding the degree of uncertainty in classification due to this algorithmic choice. This hinders the generalizability of interpretations related to hydrologic behavior. Our goal is to develop a protocol that can be followed while classifying hydrologic datasets. We focus on a classification framework for unsupervised classification and provide a step-by-step classification procedure. The steps include testing the clusterabiltiy of original dataset prior to classification, feature selection, validation of clustered data, and quantification of similarity of two clusterings. We test several commonly available methods within this framework to understand the level of similarity of classification results across algorithms. We apply the proposed framework on recently developed datasets for India to analyze to what extent catchment properties can explain observed catchment response. Our testing dataset includes watershed characteristics for over 200 watersheds which comprise of both natural (physio-climatic) characteristics and socio-economic characteristics. This framework allows us to understand the controls on observed hydrologic variability across India.

A new method of real-time detection of changes in periodic data stream

NASA Astrophysics Data System (ADS)

Lyu, Chen; Lu, Guoliang; Cheng, Bin; Zheng, Xiangwei

2017-07-01

The change point detection in periodic time series is much desirable in many practical usages. We present a novel algorithm for this task, which includes two phases: 1) anomaly measure- on the basis of a typical regression model, we propose a new computation method to measure anomalies in time series which does not require any reference data from other measurement(s); 2) change detection- we introduce a new martingale test for detection which can be operated in an unsupervised and nonparametric way. We have conducted extensive experiments to systematically test our algorithm. The results make us believe that our algorithm can be directly applicable in many real-world change-point-detection applications.

Constrained-transport Magnetohydrodynamics with Adaptive Mesh Refinement in CHARM

NASA Astrophysics Data System (ADS)

Miniati, Francesco; Martin, Daniel F.

2011-07-01

We present the implementation of a three-dimensional, second-order accurate Godunov-type algorithm for magnetohydrodynamics (MHD) in the adaptive-mesh-refinement (AMR) cosmological code CHARM. The algorithm is based on the full 12-solve spatially unsplit corner-transport-upwind (CTU) scheme. The fluid quantities are cell-centered and are updated using the piecewise-parabolic method (PPM), while the magnetic field variables are face-centered and are evolved through application of the Stokes theorem on cell edges via a constrained-transport (CT) method. The so-called multidimensional MHD source terms required in the predictor step for high-order accuracy are applied in a simplified form which reduces their complexity in three dimensions without loss of accuracy or robustness. The algorithm is implemented on an AMR framework which requires specific synchronization steps across refinement levels. These include face-centered restriction and prolongation operations and a reflux-curl operation, which maintains a solenoidal magnetic field across refinement boundaries. The code is tested against a large suite of test problems, including convergence tests in smooth flows, shock-tube tests, classical two- and three-dimensional MHD tests, a three-dimensional shock-cloud interaction problem, and the formation of a cluster of galaxies in a fully cosmological context. The magnetic field divergence is shown to remain negligible throughout.

An ATR architecture for algorithm development and testing

NASA Astrophysics Data System (ADS)

Breivik, Gøril M.; Løkken, Kristin H.; Brattli, Alvin; Palm, Hans C.; Haavardsholm, Trym

2013-05-01

A research platform with four cameras in the infrared and visible spectral domains is under development at the Norwegian Defence Research Establishment (FFI). The platform will be mounted on a high-speed jet aircraft and will primarily be used for image acquisition and for development and test of automatic target recognition (ATR) algorithms. The sensors on board produce large amounts of data, the algorithms can be computationally intensive and the data processing is complex. This puts great demands on the system architecture; it has to run in real-time and at the same time be suitable for algorithm development. In this paper we present an architecture for ATR systems that is designed to be exible, generic and efficient. The architecture is module based so that certain parts, e.g. specific ATR algorithms, can be exchanged without affecting the rest of the system. The modules are generic and can be used in various ATR system configurations. A software framework in C++ that handles large data ows in non-linear pipelines is used for implementation. The framework exploits several levels of parallelism and lets the hardware processing capacity be fully utilised. The ATR system is under development and has reached a first level that can be used for segmentation algorithm development and testing. The implemented system consists of several modules, and although their content is still limited, the segmentation module includes two different segmentation algorithms that can be easily exchanged. We demonstrate the system by applying the two segmentation algorithms to infrared images from sea trial recordings.

Richardson-Lucy/maximum likelihood image restoration algorithm for fluorescence microscopy: further testing.

PubMed

Holmes, T J; Liu, Y H

1989-11-15

A maximum likelihood based iterative algorithm adapted from nuclear medicine imaging for noncoherent optical imaging was presented in a previous publication with some initial computer-simulation testing. This algorithm is identical in form to that previously derived in a different way by W. H. Richardson "Bayesian-Based Iterative Method of Image Restoration," J. Opt. Soc. Am. 62, 55-59 (1972) and L. B. Lucy "An Iterative Technique for the Rectification of Observed Distributions," Astron. J. 79, 745-765 (1974). Foreseen applications include superresolution and 3-D fluorescence microscopy. This paper presents further simulation testing of this algorithm and a preliminary experiment with a defocused camera. The simulations show quantified resolution improvement as a function of iteration number, and they show qualitatively the trend in limitations on restored resolution when noise is present in the data. Also shown are results of a simulation in restoring missing-cone information for 3-D imaging. Conclusions are in support of the feasibility of using these methods with real systems, while computational cost and timing estimates indicate that it should be realistic to implement these methods. Itis suggested in the Appendix that future extensions to the maximum likelihood based derivation of this algorithm will address some of the limitations that are experienced with the nonextended form of the algorithm presented here.

Ion flux through membrane channels--an enhanced algorithm for the Poisson-Nernst-Planck model.

PubMed

Dyrka, Witold; Augousti, Andy T; Kotulska, Malgorzata

2008-09-01

A novel algorithmic scheme for numerical solution of the 3D Poisson-Nernst-Planck model is proposed. The algorithmic improvements are universal and independent of the detailed physical model. They include three major steps: an adjustable gradient-based step value, an adjustable relaxation coefficient, and an optimized segmentation of the modeled space. The enhanced algorithm significantly accelerates the speed of computation and reduces the computational demands. The theoretical model was tested on a regular artificial channel and validated on a real protein channel-alpha-hemolysin, proving its efficiency. (c) 2008 Wiley Periodicals, Inc.

Model of ballistic targets' dynamics used for trajectory tracking algorithms

NASA Astrophysics Data System (ADS)

Okoń-FÄ fara, Marta; Kawalec, Adam; Witczak, Andrzej

2017-04-01

There are known only few ballistic object tracking algorithms. To develop such algorithms and to its further testing, it is necessary to implement possibly simple and reliable objects' dynamics model. The article presents the dynamics' model of a tactical ballistic missile (TBM) including the three stages of flight: the boost stage and two passive stages - the ascending one and the descending one. Additionally, the procedure of transformation from the local coordinate system to the polar-radar oriented and the global is presented. The prepared theoretical data may be used to determine the tracking algorithm parameters and to its further verification.

Performance and policy dimensions in internet routing

NASA Technical Reports Server (NTRS)

Mills, David L.; Boncelet, Charles G.; Elias, John G.; Schragger, Paul A.; Jackson, Alden W.; Thyagarajan, Ajit

1995-01-01

The Internet Routing Project, referred to in this report as the 'Highball Project', has been investigating architectures suitable for networks spanning large geographic areas and capable of very high data rates. The Highball network architecture is based on a high speed crossbar switch and an adaptive, distributed, TDMA scheduling algorithm. The scheduling algorithm controls the instantaneous configuration and swell time of the switch, one of which is attached to each node. In order to send a single burst or a multi-burst packet, a reservation request is sent to all nodes. The scheduling algorithm then configures the switches immediately prior to the arrival of each burst, so it can be relayed immediately without requiring local storage. Reservations and housekeeping information are sent using a special broadcast-spanning-tree schedule. Progress to date in the Highball Project includes the design and testing of a suite of scheduling algorithms, construction of software reservation/scheduling simulators, and construction of a strawman hardware and software implementation. A prototype switch controller and timestamp generator have been completed and are in test. Detailed documentation on the algorithms, protocols and experiments conducted are given in various reports and papers published. Abstracts of this literature are included in the bibliography at the end of this report, which serves as an extended executive summary.

Algorithms for the detection of chewing behavior in dietary monitoring applications

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Helal, Abdelsalam; Mendez-Vasquez, Andres

2009-08-01

The detection of food consumption is key to the implementation of successful behavior modification in support of dietary monitoring and therapy, for example, during the course of controlling obesity, diabetes, or cardiovascular disease. Since the vast majority of humans consume food via mastication (chewing), we have designed an algorithm that automatically detects chewing behaviors in surveillance video of a person eating. Our algorithm first detects the mouth region, then computes the spatiotemporal frequency spectrum of a small perioral region (including the mouth). Spectral data are analyzed to determine the presence of periodic motion that characterizes chewing. A classifier is then applied to discriminate different types of chewing behaviors. Our algorithm was tested on seven volunteers, whose behaviors included chewing with mouth open, chewing with mouth closed, talking, static face presentation (control case), and moving face presentation. Early test results show that the chewing behaviors induce a temporal frequency peak at 0.5Hz to 2.5Hz, which is readily detected using a distance-based classifier. Computational cost is analyzed for implementation on embedded processing nodes, for example, in a healthcare sensor network. Complexity analysis emphasizes the relationship between the work and space estimates of the algorithm, and its estimated error. It is shown that chewing detection is possible within a computationally efficient, accurate, and subject-independent framework.

Harmony search algorithm: application to the redundancy optimization problem

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Thien-My, Dao

2010-09-01

The redundancy optimization problem is a well known NP-hard problem which involves the selection of elements and redundancy levels to maximize system performance, given different system-level constraints. This article presents an efficient algorithm based on the harmony search algorithm (HSA) to solve this optimization problem. The HSA is a new nature-inspired algorithm which mimics the improvization process of music players. Two kinds of problems are considered in testing the proposed algorithm, with the first limited to the binary series-parallel system, where the problem consists of a selection of elements and redundancy levels used to maximize the system reliability given various system-level constraints; the second problem for its part concerns the multi-state series-parallel systems with performance levels ranging from perfect operation to complete failure, and in which identical redundant elements are included in order to achieve a desirable level of availability. Numerical results for test problems from previous research are reported and compared. The results of HSA showed that this algorithm could provide very good solutions when compared to those obtained through other approaches.

Knowledge-based tracking algorithm

NASA Astrophysics Data System (ADS)

Corbeil, Allan F.; Hawkins, Linda J.; Gilgallon, Paul F.

1990-10-01

This paper describes the Knowledge-Based Tracking (KBT) algorithm for which a real-time flight test demonstration was recently conducted at Rome Air Development Center (RADC). In KBT processing, the radar signal in each resolution cell is thresholded at a lower than normal setting to detect low RCS targets. This lower threshold produces a larger than normal false alarm rate. Therefore, additional signal processing including spectral filtering, CFAR and knowledge-based acceptance testing are performed to eliminate some of the false alarms. TSC's knowledge-based Track-Before-Detect (TBD) algorithm is then applied to the data from each azimuth sector to detect target tracks. In this algorithm, tentative track templates are formed for each threshold crossing and knowledge-based association rules are applied to the range, Doppler, and azimuth measurements from successive scans. Lastly, an M-association out of N-scan rule is used to declare a detection. This scan-to-scan integration enhances the probability of target detection while maintaining an acceptably low output false alarm rate. For a real-time demonstration of the KBT algorithm, the L-band radar in the Surveillance Laboratory (SL) at RADC was used to illuminate a small Cessna 310 test aircraft. The received radar signal wa digitized and processed by a ST-100 Array Processor and VAX computer network in the lab. The ST-100 performed all of the radar signal processing functions, including Moving Target Indicator (MTI) pulse cancelling, FFT Doppler filtering, and CFAR detection. The VAX computers performed the remaining range-Doppler clustering, beamsplitting and TBD processing functions. The KBT algorithm provided a 9.5 dB improvement relative to single scan performance with a nominal real time delay of less than one second between illumination and display.

Comparison between variable and fixed dwell-time PN acquisition algorithms. [for synchronization in pseudonoise spread spectrum systems

NASA Technical Reports Server (NTRS)

Braun, W. R.

1981-01-01

Pseudo noise (PN) spread spectrum systems require a very accurate alignment between the PN code epochs at the transmitter and receiver. This synchronism is typically established through a two-step algorithm, including a coarse synchronization procedure and a fine synchronization procedure. A standard approach for the coarse synchronization is a sequential search over all code phases. The measurement of the power in the filtered signal is used to either accept or reject the code phase under test as the phase of the received PN code. This acquisition strategy, called a single dwell-time system, has been analyzed by Holmes and Chen (1977). A synopsis of the field of sequential analysis as it applies to the PN acquisition problem is provided. From this, the implementation of the variable dwell time algorithm as a sequential probability ratio test is developed. The performance of this algorithm is compared to the optimum detection algorithm and to the fixed dwell-time system.

Mixed raster content (MRC) model for compound image compression

NASA Astrophysics Data System (ADS)

de Queiroz, Ricardo L.; Buckley, Robert R.; Xu, Ming

1998-12-01

This paper will describe the Mixed Raster Content (MRC) method for compressing compound images, containing both binary test and continuous-tone images. A single compression algorithm that simultaneously meets the requirements for both text and image compression has been elusive. MRC takes a different approach. Rather than using a single algorithm, MRC uses a multi-layered imaging model for representing the results of multiple compression algorithms, including ones developed specifically for text and for images. As a result, MRC can combine the best of existing or new compression algorithms and offer different quality-compression ratio tradeoffs. The algorithms used by MRC set the lower bound on its compression performance. Compared to existing algorithms, MRC has some image-processing overhead to manage multiple algorithms and the imaging model. This paper will develop the rationale for the MRC approach by describing the multi-layered imaging model in light of a rate-distortion trade-off. Results will be presented comparing images compressed using MRC, JPEG and state-of-the-art wavelet algorithms such as SPIHT. MRC has been approved or proposed as an architectural model for several standards, including ITU Color Fax, IETF Internet Fax, and JPEG 2000.

Motion Cueing Algorithm Development: Piloted Performance Testing of the Cueing Algorithms

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.; Kelly, Lon C.

2005-01-01

The relative effectiveness in simulating aircraft maneuvers with both current and newly developed motion cueing algorithms was assessed with an eleven-subject piloted performance evaluation conducted on the NASA Langley Visual Motion Simulator (VMS). In addition to the current NASA adaptive algorithm, two new cueing algorithms were evaluated: the optimal algorithm and the nonlinear algorithm. The test maneuvers included a straight-in approach with a rotating wind vector, an offset approach with severe turbulence and an on/off lateral gust that occurs as the aircraft approaches the runway threshold, and a takeoff both with and without engine failure after liftoff. The maneuvers were executed with each cueing algorithm with added visual display delay conditions ranging from zero to 200 msec. Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. Piloted performance parameters for the approach maneuvers, the vertical velocity upon touchdown and the runway touchdown position, were also analyzed but did not show any noticeable difference among the cueing algorithms. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach were less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.

Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

PubMed

Liu, Chun; Kroll, Andreas

2016-01-01

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

The Results of a Simulator Study to Determine the Effects on Pilot Performance of Two Different Motion Cueing Algorithms and Various Delays, Compensated and Uncompensated

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.

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

The optimal sequence and selection of screening test items to predict fall risk in older disabled women: the Women's Health and Aging Study.

PubMed

Lamb, Sarah E; McCabe, Chris; Becker, Clemens; Fried, Linda P; Guralnik, Jack M

2008-10-01

Falls are a major cause of disability, dependence, and death in older people. Brief screening algorithms may be helpful in identifying risk and leading to more detailed assessment. Our aim was to determine the most effective sequence of falls screening test items from a wide selection of recommended items including self-report and performance tests, and to compare performance with other published guidelines. Data were from a prospective, age-stratified, cohort study. Participants were 1002 community-dwelling women aged 65 years old or older, experiencing at least some mild disability. Assessments of fall risk factors were conducted in participants' homes. Fall outcomes were collected at 6 monthly intervals. Algorithms were built for prediction of any fall over a 12-month period using tree classification with cross-set validation. Algorithms using performance tests provided the best prediction of fall events, and achieved moderate to strong performance when compared to commonly accepted benchmarks. The items selected by the best performing algorithm were the number of falls in the last year and, in selected subpopulations, frequency of difficulty balancing while walking, a 4 m walking speed test, body mass index, and a test of knee extensor strength. The algorithm performed better than that from the American Geriatric Society/British Geriatric Society/American Academy of Orthopaedic Surgeons and other guidance, although these findings should be treated with caution. Suggestions are made on the type, number, and sequence of tests that could be used to maximize estimation of the probability of falling in older disabled women.

Novel algorithm implementations in DARC: the Durham AO real-time controller

NASA Astrophysics Data System (ADS)

Basden, Alastair; Bitenc, Urban; Jenkins, David

2016-07-01

The Durham AO Real-time Controller has been used on-sky with the CANARY AO demonstrator instrument since 2010, and is also used to provide control for several AO test-benches, including DRAGON. Over this period, many new real-time algorithms have been developed, implemented and demonstrated, leading to performance improvements for CANARY. Additionally, the computational performance of this real-time system has continued to improve. Here, we provide details about recent updates and changes made to DARC, and the relevance of these updates, including new algorithms, to forthcoming AO systems. We present the computational performance of DARC when used on different hardware platforms, including hardware accelerators, and determine the relevance and potential for ELT scale systems. Recent updates to DARC have included algorithms to handle elongated laser guide star images, including correlation wavefront sensing, with options to automatically update references during AO loop operation. Additionally, sub-aperture masking options have been developed to increase signal to noise ratio when operating with non-symmetrical wavefront sensor images. The development of end-user tools has progressed with new options for configuration and control of the system. New wavefront sensor camera models and DM models have been integrated with the system, increasing the number of possible hardware configurations available, and a fully open-source AO system is now a reality, including drivers necessary for commercial cameras and DMs. The computational performance of DARC makes it suitable for ELT scale systems when implemented on suitable hardware. We present tests made on different hardware platforms, along with the strategies taken to optimise DARC for these systems.

Self-tuning regulators for multicyclic control of helicopter vibration

NASA Technical Reports Server (NTRS)

Johnson, W.

1982-01-01

A class of algorithms for the multicyclic control of helicopter vibration and loads is derived and discussed. This class is characterized by a linear, quasi-static, frequency-domain model of the helicopter response to control; identification of the helicopter model by least-squared-error or Kalman filter methods; and a minimum variance or quadratic performance function controller. Previous research on such controllers is reviewed. The derivations and discussions cover the helicopter model; the identification problem, including both off-line and on-line (recursive) algorithms; the control problem, including both open-loop and closed-loop feedback; and the various regulator configurations possible within this class. Conclusions from analysis and numerical simulations of the regulators provide guidance in the design and selection of algorithms for further development, including wind tunnel and flight tests.

Test Generation Algorithm for Fault Detection of Analog Circuits Based on Extreme Learning Machine

PubMed Central

Zhou, Jingyu; Tian, Shulin; Yang, Chenglin; Ren, Xuelong

2014-01-01

This paper proposes a novel test generation algorithm based on extreme learning machine (ELM), and such algorithm is cost-effective and low-risk for analog device under test (DUT). This method uses test patterns derived from the test generation algorithm to stimulate DUT, and then samples output responses of the DUT for fault classification and detection. The novel ELM-based test generation algorithm proposed in this paper contains mainly three aspects of innovation. Firstly, this algorithm saves time efficiently by classifying response space with ELM. Secondly, this algorithm can avoid reduced test precision efficiently in case of reduction of the number of impulse-response samples. Thirdly, a new process of test signal generator and a test structure in test generation algorithm are presented, and both of them are very simple. Finally, the abovementioned improvement and functioning are confirmed in experiments. PMID:25610458

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

PubMed

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P < 0.01). This algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P < 0.05), whereas it shows results not significantly different to 3D-COFFEE (P > 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Testing of the on-board attitude determination and control algorithms for SAMPEX

NASA Technical Reports Server (NTRS)

Mccullough, Jon D.; Flatley, Thomas W.; Henretty, Debra A.; Markley, F. Landis; San, Josephine K.

1993-01-01

Algorithms for on-board attitude determination and control of the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) have been expanded to include a constant gain Kalman filter for the spacecraft angular momentum, pulse width modulation for the reaction wheel command, an algorithm to avoid pointing the Heavy Ion Large Telescope (HILT) instrument boresight along the spacecraft velocity vector, and the addition of digital sun sensor (DSS) failure detection logic. These improved algorithms were tested in a closed-loop environment for three orbit geometries, one with the sun perpendicular to the orbit plane, and two with the sun near the orbit plane - at Autumnal Equinox and at Winter Solstice. The closed-loop simulator was enhanced and used as a truth model for the control systems' performance evaluation and sensor/actuator contingency analysis. The simulations were performed on a VAX 8830 using a prototype version of the on-board software.

Using the ADAP Learning Algorithm to Forecast the Onset of Diabetes Mellitus

PubMed Central

Smith, Jack W.; Everhart, J.E.; Dickson, W.C.; Knowler, W.C.; Johannes, R.S.

1988-01-01

Neural networks or connectionist models for parallel processing are not new. However, a resurgence of interest in the past half decade has occurred. In part, this is related to a better understanding of what are now referred to as hidden nodes. These algorithms are considered to be of marked value in pattern recognition problems. Because of that, we tested the ability of an early neural network model, ADAP, to forecast the onset of diabetes mellitus in a high risk population of Pima Indians. The algorithm's performance was analyzed using standard measures for clinical tests: sensitivity, specificity, and a receiver operating characteristic curve. The crossover point for sensitivity and specificity is 0.76. We are currently further examining these methods by comparing the ADAP results with those obtained from logistic regression and linear perceptron models using precisely the same training and forecasting sets. A description of the algorithm is included.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

Development of a takeoff performance monitoring system. Ph.D. Thesis. Contractor Report, Jan. 1984 - Jun. 1985

NASA Technical Reports Server (NTRS)

Srivatsan, Raghavachari; Downing, David R.

1987-01-01

Discussed are the development and testing of a real-time takeoff performance monitoring algorithm. The algorithm is made up of two segments: a pretakeoff segment and a real-time segment. One-time imputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate scheduled performance data for that takeoff. The real-time segment uses the scheduled performance data generated in the pretakeoff segment, runway length data, and measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. An important feature of this algorithm is the one-time estimation of the runway rolling friction coefficient. The algorithm was tested using a six-degree-of-freedom airplane model in a computer simulation. Results from a series of sensitivity analyses are also included.

Robotic Lunar Lander Development Project Status

NASA Technical Reports Server (NTRS)

Hammond, Monica; Bassler, Julie; Morse, Brian

2010-01-01

This slide presentation reviews the status of the development of a robotic lunar lander. The goal of the project is to perform engineering tests and risk reduction activities to support the development of a small lunar lander for lunar surface science. This includes: (1) risk reduction for the flight of the robotic lander, (i.e., testing and analyzing various phase of the project); (2) the incremental development for the design of the robotic lander, which is to demonstrate autonomous, controlled descent and landing on airless bodies, and design of thruster configuration for 1/6th of the gravity of earth; (3) cold gas test article in flight demonstration testing; (4) warm gas testing of the robotic lander design; (5) develop and test landing algorithms; (6) validate the algorithms through analysis and test; and (7) tests of the flight propulsion system.

Performance of a Limiting-Antigen Avidity Enzyme Immunoassay for Cross-Sectional Estimation of HIV Incidence in the United States

PubMed Central

Konikoff, Jacob; Brookmeyer, Ron; Longosz, Andrew F.; Cousins, Matthew M.; Celum, Connie; Buchbinder, Susan P.; Seage, George R.; Kirk, Gregory D.; Moore, Richard D.; Mehta, Shruti H.; Margolick, Joseph B.; Brown, Joelle; Mayer, Kenneth H.; Koblin, Beryl A.; Justman, Jessica E.; Hodder, Sally L.; Quinn, Thomas C.; Eshleman, Susan H.; Laeyendecker, Oliver

2013-01-01

Background A limiting antigen avidity enzyme immunoassay (HIV-1 LAg-Avidity assay) was recently developed for cross-sectional HIV incidence estimation. We evaluated the performance of the LAg-Avidity assay alone and in multi-assay algorithms (MAAs) that included other biomarkers. Methods and Findings Performance of testing algorithms was evaluated using 2,282 samples from individuals in the United States collected 1 month to >8 years after HIV seroconversion. The capacity of selected testing algorithms to accurately estimate incidence was evaluated in three longitudinal cohorts. When used in a single-assay format, the LAg-Avidity assay classified some individuals infected >5 years as assay positive and failed to provide reliable incidence estimates in cohorts that included individuals with long-term infections. We evaluated >500,000 testing algorithms, that included the LAg-Avidity assay alone and MAAs with other biomarkers (BED capture immunoassay [BED-CEIA], BioRad-Avidity assay, HIV viral load, CD4 cell count), varying the assays and assay cutoffs. We identified an optimized 2-assay MAA that included the LAg-Avidity and BioRad-Avidity assays, and an optimized 4-assay MAA that included those assays, as well as HIV viral load and CD4 cell count. The two optimized MAAs classified all 845 samples from individuals infected >5 years as MAA negative and estimated incidence within a year of sample collection. These two MAAs produced incidence estimates that were consistent with those from longitudinal follow-up of cohorts. A comparison of the laboratory assay costs of the MAAs was also performed, and we found that the costs associated with the optimal two assay MAA were substantially less than with the four assay MAA. Conclusions The LAg-Avidity assay did not perform well in a single-assay format, regardless of the assay cutoff. MAAs that include the LAg-Avidity and BioRad-Avidity assays, with or without viral load and CD4 cell count, provide accurate incidence estimates. PMID:24386116

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem

PubMed Central

Akutsah, Francis; Olusanya, Micheal O.; Adewumi, Aderemi O.

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems. PMID:29554662

Enhanced intelligent water drops algorithm for multi-depot vehicle routing problem.

PubMed

Ezugwu, Absalom E; Akutsah, Francis; Olusanya, Micheal O; Adewumi, Aderemi O

2018-01-01

The intelligent water drop algorithm is a swarm-based metaheuristic algorithm, inspired by the characteristics of water drops in the river and the environmental changes resulting from the action of the flowing river. Since its appearance as an alternative stochastic optimization method, the algorithm has found applications in solving a wide range of combinatorial and functional optimization problems. This paper presents an improved intelligent water drop algorithm for solving multi-depot vehicle routing problems. A simulated annealing algorithm was introduced into the proposed algorithm as a local search metaheuristic to prevent the intelligent water drop algorithm from getting trapped into local minima and also improve its solution quality. In addition, some of the potential problematic issues associated with using simulated annealing that include high computational runtime and exponential calculation of the probability of acceptance criteria, are investigated. The exponential calculation of the probability of acceptance criteria for the simulated annealing based techniques is computationally expensive. Therefore, in order to maximize the performance of the intelligent water drop algorithm using simulated annealing, a better way of calculating the probability of acceptance criteria is considered. The performance of the proposed hybrid algorithm is evaluated by using 33 standard test problems, with the results obtained compared with the solutions offered by four well-known techniques from the subject literature. Experimental results and statistical tests show that the new method possesses outstanding performance in terms of solution quality and runtime consumed. In addition, the proposed algorithm is suitable for solving large-scale problems.

Soil Moisture Active Passive (SMAP) Project Algorithm Theoretical Basis Document SMAP L1B Radiometer Data Product: L1B_TB

NASA Technical Reports Server (NTRS)

Piepmeier, Jeffrey; Mohammed, Priscilla; De Amici, Giovanni; Kim, Edward; Peng, Jinzheng; Ruf, Christopher; Hanna, Maher; Yueh, Simon; Entekhabi, Dara

2016-01-01

The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm.

An implementation of differential evolution algorithm for inversion of geoelectrical data

NASA Astrophysics Data System (ADS)

Balkaya, Çağlayan

2013-11-01

Differential evolution (DE), a population-based evolutionary algorithm (EA) has been implemented to invert self-potential (SP) and vertical electrical sounding (VES) data sets. The algorithm uses three operators including mutation, crossover and selection similar to genetic algorithm (GA). Mutation is the most important operator for the success of DE. Three commonly used mutation strategies including DE/best/1 (strategy 1), DE/rand/1 (strategy 2) and DE/rand-to-best/1 (strategy 3) were applied together with a binomial type crossover. Evolution cycle of DE was realized without boundary constraints. For the test studies performed with SP data, in addition to both noise-free and noisy synthetic data sets two field data sets observed over the sulfide ore body in the Malachite mine (Colorado) and over the ore bodies in the Neem-Ka Thana cooper belt (India) were considered. VES test studies were carried out using synthetically produced resistivity data representing a three-layered earth model and a field data set example from Gökçeada (Turkey), which displays a seawater infiltration problem. Mutation strategies mentioned above were also extensively tested on both synthetic and field data sets in consideration. Of these, strategy 1 was found to be the most effective strategy for the parameter estimation by providing less computational cost together with a good accuracy. The solutions obtained by DE for the synthetic cases of SP were quite consistent with particle swarm optimization (PSO) which is a more widely used population-based optimization algorithm than DE in geophysics. Estimated parameters of SP and VES data were also compared with those obtained from Metropolis-Hastings (M-H) sampling algorithm based on simulated annealing (SA) without cooling to clarify uncertainties in the solutions. Comparison to the M-H algorithm shows that DE performs a fast approximate posterior sampling for the case of low-dimensional inverse geophysical problems.

Comparison of cytology, HPV DNA testing and HPV 16/18 genotyping alone or combined targeting to the more balanced methodology for cervical cancer screening.

PubMed

Chatzistamatiou, Kimon; Moysiadis, Theodoros; Moschaki, Viktoria; Panteleris, Nikolaos; Agorastos, Theodoros

2016-07-01

The objective of the present study was to identify the most effective cervical cancer screening algorithm incorporating different combinations of cytology, HPV testing and genotyping. Women 25-55years old recruited for the "HERMES" (HEllenic Real life Multicentric cErvical Screening) study were screened in terms of cytology and high-risk (hr) HPV testing with HPV 16/18 genotyping. Women positive for cytology or/and hrHPV were referred for colposcopy, biopsy and treatment. Ten screening algorithms based on different combinations of cytology, HPV testing and HPV 16/18 genotyping were investigated in terms of diagnostic accuracy. Three clusters of algorithms were formed according to the balance between effectiveness and harm caused by screening. The cluster showing the best balance included two algorithms based on co-testing and two based on HPV primary screening with HPV 16/18 genotyping. Among these, hrHPV testing with HPV 16/18 genotyping and reflex cytology (atypical squamous cells of undetermined significance - ASCUS threshold) presented the optimal combination of sensitivity (82.9%) and specificity relative to cytology alone (0.99) with 1.26 false positive rate relative to cytology alone. HPV testing with HPV 16/18 genotyping, referring HPV 16/18 positive women directly to colposcopy, and hrHPV (non 16/18) positive women to reflex cytology (ASCUS threshold), as a triage method to colposcopy, reflects the best equilibrium between screening effectiveness and harm. Algorithms, based on cytology as initial screening method, on co-testing or HPV primary without genotyping, and on HPV primary with genotyping but without cytology triage, are not supported according to the present analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Graphical programming interface: A development environment for MRI methods.

PubMed

Zwart, Nicholas R; Pipe, James G

2015-11-01

To introduce a multiplatform, Python language-based, development environment called graphical programming interface for prototyping MRI techniques. The interface allows developers to interact with their scientific algorithm prototypes visually in an event-driven environment making tasks such as parameterization, algorithm testing, data manipulation, and visualization an integrated part of the work-flow. Algorithm developers extend the built-in functionality through simple code interfaces designed to facilitate rapid implementation. This article shows several examples of algorithms developed in graphical programming interface including the non-Cartesian MR reconstruction algorithms for PROPELLER and spiral as well as spin simulation and trajectory visualization of a FLORET example. The graphical programming interface framework is shown to be a versatile prototyping environment for developing numeric algorithms used in the latest MR techniques. © 2014 Wiley Periodicals, Inc.

Applications of multiscale change point detections to monthly stream flow and rainfall in Xijiang River in southern China, part I: correlation and variance

NASA Astrophysics Data System (ADS)

Zhu, Yuxiang; Jiang, Jianmin; Huang, Changxing; Chen, Yongqin David; Zhang, Qiang

2018-04-01

This article, as part I, introduces three algorithms and applies them to both series of the monthly stream flow and rainfall in Xijiang River, southern China. The three algorithms include (1) normalization of probability distribution, (2) scanning U test for change points in correlation between two time series, and (3) scanning F-test for change points in variances. The normalization algorithm adopts the quantile method to normalize data from a non-normal into the normal probability distribution. The scanning U test and F-test have three common features: grafting the classical statistics onto the wavelet algorithm, adding corrections for independence into each statistic criteria at given confidence respectively, and being almost objective and automatic detection on multiscale time scales. In addition, the coherency analyses between two series are also carried out for changes in variance. The application results show that the changes of the monthly discharge are still controlled by natural precipitation variations in Xijiang's fluvial system. Human activities disturbed the ecological balance perhaps in certain content and in shorter spells but did not violate the natural relationships of correlation and variance changes so far.

Exploring Effects of High School Students' Mathematical Processing Skills and Conceptual Understanding of Chemical Concepts on Algorithmic Problem Solving

ERIC Educational Resources Information Center

Gultepe, Nejla; Yalcin Celik, Ayse; Kilic, Ziya

2013-01-01

The purpose of the study was to examine the effects of students' conceptual understanding of chemical concepts and mathematical processing skills on algorithmic problem-solving skills. The sample (N = 554) included grades 9, 10, and 11 students in Turkey. Data were collected using the instrument "MPC Test" and with interviews. The MPC…

Mining Peripheral Arterial Disease Cases from Narrative Clinical Notes Using Natural Language Processing

PubMed Central

Afzal, Naveed; Sohn, Sunghwan; Abram, Sara; Scott, Christopher G.; Chaudhry, Rajeev; Liu, Hongfang; Kullo, Iftikhar J.; Arruda-Olson, Adelaide M.

2016-01-01

Objective Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative notes and compared the performance of the NLP algorithm to billing code algorithms, using ankle-brachial index (ABI) test results as the gold standard. Methods We compared the performance of the NLP algorithm to 1) results of gold standard ABI; 2) previously validated algorithms based on relevant ICD-9 diagnostic codes (simple model) and 3) a combination of ICD-9 codes with procedural codes (full model). A dataset of 1,569 PAD patients and controls was randomly divided into training (n= 935) and testing (n= 634) subsets. Results We iteratively refined the NLP algorithm in the training set including narrative note sections, note types and service types, to maximize its accuracy. In the testing dataset, when compared with both simple and full models, the NLP algorithm had better accuracy (NLP: 91.8%, full model: 81.8%, simple model: 83%, P<.001), PPV (NLP: 92.9%, full model: 74.3%, simple model: 79.9%, P<.001), and specificity (NLP: 92.5%, full model: 64.2%, simple model: 75.9%, P<.001). Conclusions A knowledge-driven NLP algorithm for automatic ascertainment of PAD cases from clinical notes had greater accuracy than billing code algorithms. Our findings highlight the potential of NLP tools for rapid and efficient ascertainment of PAD cases from electronic health records to facilitate clinical investigation and eventually improve care by clinical decision support. PMID:28189359

ICCD: interactive continuous collision detection between deformable models using connectivity-based culling.

PubMed

Tang, Min; Curtis, Sean; Yoon, Sung-Eui; Manocha, Dinesh

2009-01-01

We present an interactive algorithm for continuous collision detection between deformable models. We introduce multiple techniques to improve the culling efficiency and the overall performance of continuous collision detection. First, we present a novel formulation for continuous normal cones and use these normal cones to efficiently cull large regions of the mesh as part of self-collision tests. Second, we introduce the concept of "procedural representative triangles" to remove all redundant elementary tests between nonadjacent triangles. Finally, we exploit the mesh connectivity and introduce the concept of "orphan sets" to eliminate redundant elementary tests between adjacent triangle primitives. In practice, we can reduce the number of elementary tests by two orders of magnitude. These culling techniques have been combined with bounding volume hierarchies and can result in one order of magnitude performance improvement as compared to prior collision detection algorithms for deformable models. We highlight the performance of our algorithm on several benchmarks, including cloth simulations, N-body simulations, and breaking objects.

Simple non-laboratory- and laboratory-based risk assessment algorithms and nomogram for detecting undiagnosed diabetes mellitus.

PubMed

Wong, Carlos K H; Siu, Shing-Chung; Wan, Eric Y F; Jiao, Fang-Fang; Yu, Esther Y T; Fung, Colman S C; Wong, Ka-Wai; Leung, Angela Y M; Lam, Cindy L K

2016-05-01

The aim of the present study was to develop a simple nomogram that can be used to predict the risk of diabetes mellitus (DM) in the asymptomatic non-diabetic subjects based on non-laboratory- and laboratory-based risk algorithms. Anthropometric data, plasma fasting glucose, full lipid profile, exercise habits, and family history of DM were collected from Chinese non-diabetic subjects aged 18-70 years. Logistic regression analysis was performed on a random sample of 2518 subjects to construct non-laboratory- and laboratory-based risk assessment algorithms for detection of undiagnosed DM; both algorithms were validated on data of the remaining sample (n = 839). The Hosmer-Lemeshow test and area under the receiver operating characteristic (ROC) curve (AUC) were used to assess the calibration and discrimination of the DM risk algorithms. Of 3357 subjects recruited, 271 (8.1%) had undiagnosed DM defined by fasting glucose ≥7.0 mmol/L or 2-h post-load plasma glucose ≥11.1 mmol/L after an oral glucose tolerance test. The non-laboratory-based risk algorithm, with scores ranging from 0 to 33, included age, body mass index, family history of DM, regular exercise, and uncontrolled blood pressure; the laboratory-based risk algorithm, with scores ranging from 0 to 37, added triglyceride level to the risk factors. Both algorithms demonstrated acceptable calibration (Hosmer-Lemeshow test: P = 0.229 and P = 0.483) and discrimination (AUC 0.709 and 0.711) for detection of undiagnosed DM. A simple-to-use nomogram for detecting undiagnosed DM has been developed using validated non-laboratory-based and laboratory-based risk algorithms. © 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Gilligan, Eric T.; Wall, John H.; Orr, Jeb S.; Miller, Christopher J.; Hanson, Curtis E.

2014-01-01

The NASA Marshall Space Flight Center (MSFC) Flight Mechanics and Analysis Division developed an Adaptive Augmenting Control (AAC) algorithm for launch vehicles that improves robustness and performance by adapting an otherwise welltuned classical control algorithm to unexpected environments or variations in vehicle dynamics. This AAC algorithm is currently part of the baseline design for the SLS Flight Control System (FCS), but prior to this series of research flights it was the only component of the autopilot design that had not been flight tested. The Space Launch System (SLS) flight software prototype, including the adaptive component, was recently tested on a piloted aircraft at Dryden Flight Research Center (DFRC) which has the capability to achieve a high level of dynamic similarity to a launch vehicle. Scenarios for the flight test campaign were designed specifically to evaluate the AAC algorithm to ensure that it is able to achieve the expected performance improvements with no adverse impacts in nominal or nearnominal scenarios. Having completed the recent series of flight characterization experiments on DFRC's F/A-18, the AAC algorithm's capability, robustness, and reproducibility, have been successfully demonstrated. Thus, the entire SLS control architecture has been successfully flight tested in a relevant environment. This has increased NASA's confidence that the autopilot design is ready to fly on the SLS Block I vehicle and will exceed the performance of previous architectures.

High Frequency Adaptive Instability Suppression Controls in a Liquid-Fueled Combustor

NASA Technical Reports Server (NTRS)

Kopasakis, George

2003-01-01

This effort extends into high frequency (>500 Hz), an earlier developed adaptive control algorithm for the suppression of thermo-acoustic instabilities in a liquidfueled combustor. The earlier work covered the development of a controls algorithm for the suppression of a low frequency (280 Hz) combustion instability based on simulations, with no hardware testing involved. The work described here includes changes to the simulation and controller design necessary to control the high frequency instability, augmentations to the control algorithm to improve its performance, and finally hardware testing and results with an experimental combustor rig developed for the high frequency case. The Adaptive Sliding Phasor Averaged Control (ASPAC) algorithm modulates the fuel flow in the combustor with a control phase that continuously slides back and forth within the phase region that reduces the amplitude of the instability. The results demonstrate the power of the method - that it can identify and suppress the instability even when the instability amplitude is buried in the noise of the combustor pressure. The successful testing of the ASPAC approach helped complete an important NASA milestone to demonstrate advanced technologies for low-emission combustors.

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness.

An Improved SoC Test Scheduling Method Based on Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Jingjing; Shen, Zhihang; Gao, Huaien; Chen, Bianna; Zheng, Weida; Xiong, Xiaoming

2017-02-01

In this paper, we propose an improved SoC test scheduling method based on simulated annealing algorithm (SA). It is our first to disorganize IP core assignment for each TAM to produce a new solution for SA, allocate TAM width for each TAM using greedy algorithm and calculate corresponding testing time. And accepting the core assignment according to the principle of simulated annealing algorithm and finally attain the optimum solution. Simultaneously, we run the test scheduling experiment with the international reference circuits provided by International Test Conference 2002(ITC’02) and the result shows that our algorithm is superior to the conventional integer linear programming algorithm (ILP), simulated annealing algorithm (SA) and genetic algorithm(GA). When TAM width reaches to 48,56 and 64, the testing time based on our algorithm is lesser than the classic methods and the optimization rates are 30.74%, 3.32%, 16.13% respectively. Moreover, the testing time based on our algorithm is very close to that of improved genetic algorithm (IGA), which is state-of-the-art at present.

A ground track control algorithm for the Topographic Mapping Laser Altimeter (TMLA)

NASA Technical Reports Server (NTRS)

Blaes, V.; Mcintosh, R.; Roszman, L.; Cooley, J.

1993-01-01

The results of an analysis of an algorithm that will provide autonomous onboard orbit control using orbits determined with Global Positioning System (GPS) data. The algorithm uses the GPS data to (1) compute the ground track error relative to a fixed longitude grid, and (2) determine the altitude adjustment required to correct the longitude error. A program was written on a personal computer (PC) to test the concept for numerous altitudes and values of solar flux using a simplified orbit model including only the J sub 2 zonal harmonic and simple orbit decay computations. The algorithm was then implemented in a precision orbit propagation program having a full range of perturbations. The analysis showed that, even with all perturbations (including actual time histories of solar flux variation), the algorithm could effectively control the spacecraft ground track and yield more than 99 percent Earth coverage in the time required to complete one coverage cycle on the fixed grid (220 to 230 days depending on altitude and overlap allowance).

Power of automated algorithms for combining time-line follow-back and urine drug screening test results in stimulant-abuse clinical trials.

PubMed

Oden, Neal L; VanVeldhuisen, Paul C; Wakim, Paul G; Trivedi, Madhukar H; Somoza, Eugene; Lewis, Daniel

2011-09-01

In clinical trials of treatment for stimulant abuse, researchers commonly record both Time-Line Follow-Back (TLFB) self-reports and urine drug screen (UDS) results. To compare the power of self-report, qualitative (use vs. no use) UDS assessment, and various algorithms to generate self-report-UDS composite measures to detect treatment differences via t-test in simulated clinical trial data. We performed Monte Carlo simulations patterned in part on real data to model self-report reliability, UDS errors, dropout, informatively missing UDS reports, incomplete adherence to a urine donation schedule, temporal correlation of drug use, number of days in the study period, number of patients per arm, and distribution of drug-use probabilities. Investigated algorithms include maximum likelihood and Bayesian estimates, self-report alone, UDS alone, and several simple modifications of self-report (referred to here as ELCON algorithms) which eliminate perceived contradictions between it and UDS. Among the algorithms investigated, simple ELCON algorithms gave rise to the most powerful t-tests to detect mean group differences in stimulant drug use. Further investigation is needed to determine if simple, naïve procedures such as the ELCON algorithms are optimal for comparing clinical study treatment arms. But researchers who currently require an automated algorithm in scenarios similar to those simulated for combining TLFB and UDS to test group differences in stimulant use should consider one of the ELCON algorithms. This analysis continues a line of inquiry which could determine how best to measure outpatient stimulant use in clinical trials (NIDA. NIDA Monograph-57: Self-Report Methods of Estimating Drug Abuse: Meeting Current Challenges to Validity. NTIS PB 88248083. Bethesda, MD: National Institutes of Health, 1985; NIDA. NIDA Research Monograph 73: Urine Testing for Drugs of Abuse. NTIS PB 89151971. Bethesda, MD: National Institutes of Health, 1987; NIDA. NIDA Research Monograph 167: The Validity of Self-Reported Drug Use: Improving the Accuracy of Survey Estimates. NTIS PB 97175889. GPO 017-024-01607-1. Bethesda, MD: National Institutes of Health, 1997).

Simultaneous Mass Determination for Gravitationally Coupled Asteroids

NASA Astrophysics Data System (ADS)

Baer, James; Chesley, Steven R.

2017-08-01

The conventional least-squares asteroid mass determination algorithm allows us to solve for the mass of a large subject asteroid that is perturbing the trajectory of a smaller test asteroid. However, this algorithm is necessarily a first approximation, ignoring the possibility that the subject asteroid may itself be perturbed by the test asteroid, or that the encounter’s precise geometry may be entangled with encounters involving other asteroids. After reviewing the conventional algorithm, we use it to calculate the masses of 30 main-belt asteroids. Compared to our previous results, we find new mass estimates for eight asteroids (11 Parthenope, 27 Euterpe, 51 Neimausa, 76 Freia, 121 Hermione, 324 Bamberga, 476 Hedwig, and 532 Herculina) and significantly more precise estimates for six others (2 Pallas, 3 Juno, 4 Vesta, 9 Metis, 16 Psyche, and 88 Thisbe). However, we also find that the conventional algorithm yields questionable results in several gravitationally coupled cases. To address such cases, we describe a new algorithm that allows the epoch state vectors of the subject asteroids to be included as solve-for parameters, allowing for the simultaneous solution of the masses and epoch state vectors of multiple subject and test asteroids. We then apply this algorithm to the same 30 main-belt asteroids and conclude that mass determinations resulting from current and future high-precision astrometric sources (such as Gaia) should conduct a thorough search for possible gravitational couplings and account for their effects.

Development of a Smart Release Algorithm for Mid-Air Separation of Parachute Test Articles

NASA Technical Reports Server (NTRS)

Moore, James W.

2011-01-01

The Crew Exploration Vehicle Parachute Assembly System (CPAS) project is currently developing an autonomous method to separate a capsule-shaped parachute test vehicle from an air-drop platform for use in the test program to develop and validate the parachute system for the Orion spacecraft. The CPAS project seeks to perform air-drop tests of an Orion-like boilerplate capsule. Delivery of the boilerplate capsule to the test condition has proven to be a critical and complicated task. In the current concept, the boilerplate vehicle is extracted from an aircraft on top of a Type V pallet and then separated from the pallet in mid-air. The attitude of the vehicles at separation is critical to avoiding re-contact and successfully deploying the boilerplate into a heatshield-down orientation. Neither the pallet nor the boilerplate has an active control system. However, the attitude of the mated vehicle as a function of time is somewhat predictable. CPAS engineers have designed an avionics system to monitor the attitude of the mated vehicle as it is extracted from the aircraft and command a release when the desired conditions are met. The algorithm includes contingency capabilities designed to release the test vehicle before undesirable orientations occur. The algorithm was verified with simulation and ground testing. The pre-flight development and testing is discussed and limitations of ground testing are noted. The CPAS project performed a series of three drop tests as a proof-of-concept of the release technique. These tests helped to refine the attitude instrumentation and software algorithm to be used on future tests. The drop tests are described in detail and the evolution of the release system with each test is described.

Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen S.; Orr, Jeb S.; Wall, John H.; Gilligan, Eric T.

2014-01-01

This paper summarizes the Adaptive Augmenting Control (AAC) flight characterization experiments performed using an F/A-18 (TN 853). AAC was designed and developed specifically for launch vehicles, and is currently part of the baseline autopilot design for NASA's Space Launch System (SLS). The scope covered here includes a brief overview of the algorithm (covered in more detail elsewhere), motivation and benefits of flight testing, top-level SLS flight test objectives, applicability of the F/A-18 as a platform for testing a launch vehicle control design, test cases designed to fully vet the AAC algorithm, flight test results, and conclusions regarding the functionality of AAC. The AAC algorithm developed at Marshall Space Flight Center is a forward loop gain multiplicative adaptive algorithm that modifies the total attitude control system gain in response to sensed model errors or undesirable parasitic mode resonances. The AAC algorithm provides the capability to improve or decrease performance by balancing attitude tracking with the mitigation of parasitic dynamics, such as control-structure interaction or servo-actuator limit cycles. In the case of the latter, if unmodeled or mismodeled parasitic dynamics are present that would otherwise result in a closed-loop instability or near instability, the adaptive controller decreases the total loop gain to reduce the interaction between these dynamics and the controller. This is in contrast to traditional adaptive control logic, which focuses on improving performance by increasing gain. The computationally simple AAC attitude control algorithm has stability properties that are reconcilable in the context of classical frequency-domain criteria (i.e., gain and phase margin). The algorithm assumes that the baseline attitude control design is well-tuned for a nominal trajectory and is designed to adapt only when necessary. Furthermore, the adaptation is attracted to the nominal design and adapts only on an as-needed basis (see Figure 1). The MSFC algorithm design was formulated during the Constellation Program and reached a high maturity level during SLS through simulation-based development and internal and external analytical review. The AAC algorithm design has three summary-level objectives: (1) "Do no harm;" return to baseline control design when not needed, (2) Increase performance; respond to error in ability of vehicle to track command, and (3) Regain stability; respond to undesirable control-structure interaction or other parasitic dynamics. AAC has been successfully implemented as part of the Space Launch System baseline design, including extensive testing in high-fidelity 6-DOF simulations the details of which are described in [1]. The Dryden Flight Research Center's F/A-18 Full-Scale Advanced Systems Testbed (FAST) platform is used to conduct an algorithm flight characterization experiment intended to fully vet the aforementioned design objectives. FAST was specifically designed with this type of test program in mind. The onboard flight control system has full-authority experiment control of ten aerodynamic effectors and two throttles. It has production and research sensor inputs and pilot engage/disengage and real-time configuration of up to eight different experiments on a single flight. It has failure detection and automatic reversion to fail-safe mode. The F/A-18 aircraft has an experiment envelope cleared for full-authority control and maneuvering and exhibits characteristics for robust recovery from unusual attitudes and configurations aided by the presence of a qualified test pilot. The F/A-18 aircraft has relatively high mass and inertia with exceptional performance; the F/A-18 also has a large thrust-to-weight ratio, owing to its military heritage. This enables the simulation of a portion of the ascent trajectory with a high degree of dynamic similarity to a launch vehicle, and the research flight control system can simulate unstable longitudinal dynamics. Parasitic dynamics such as slosh and bending modes, as well as atmospheric disturbances, are being produced by the airframe via modification of bending filters and the use of secondary control surfaces, including leading and trailing edge flaps, symmetric ailerons, and symmetric rudders. The platform also has the ability to inject signals in flight to simulate structural mode resonances or other challenging dynamics. This platform also offers more test maneuvers and longer maneuver times than a single rocket or missile test, which provides ample opportunity to fully and repeatedly exercise all aspects of the algorithm. Prior to testing on an F/A-18, AAC was the only component of the SLS autopilot design that had not been flight tested. The testing described in this paper raises the Technology Readiness Level (TRL) early in the SLS Program and is able to demonstrate its capabilities and robustness in a flight environment.

Optimization and experimental realization of the quantum permutation algorithm

NASA Astrophysics Data System (ADS)

Yalçınkaya, I.; Gedik, Z.

2017-12-01

The quantum permutation algorithm provides computational speed-up over classical algorithms for determining the parity of a given cyclic permutation. For its n -qubit implementations, the number of required quantum gates scales quadratically with n due to the quantum Fourier transforms included. We show here for the n -qubit case that the algorithm can be simplified so that it requires only O (n ) quantum gates, which theoretically reduces the complexity of the implementation. To test our results experimentally, we utilize IBM's 5-qubit quantum processor to realize the algorithm by using the original and simplified recipes for the 2-qubit case. It turns out that the latter results in a significantly higher success probability which allows us to verify the algorithm more precisely than the previous experimental realizations. We also verify the algorithm for the first time for the 3-qubit case with a considerable success probability by taking the advantage of our simplified scheme.

Comparison and testing of extended Kalman filters for attitude estimation of the Earth radiation budget satellite

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.; Rokni, Mohammad

1990-01-01

The testing and comparison of two Extended Kalman Filters (EKFs) developed for the Earth Radiation Budget Satellite (ERBS) is described. One EKF updates the attitude quaternion using a four component additive error quaternion. This technique is compared to that of a second EKF, which uses a multiplicative error quaternion. A brief development of the multiplicative algorithm is included. The mathematical development of the additive EKF was presented in the 1989 Flight Mechanics/Estimation Theory Symposium along with some preliminary testing results using real spacecraft data. A summary of the additive EKF algorithm is included. The convergence properties, singularity problems, and normalization techniques of the two filters are addressed. Both filters are also compared to those from the ERBS operational ground support software, which uses a batch differential correction algorithm to estimate attitude and gyro biases. Sensitivity studies are performed on the estimation of sensor calibration states. The potential application of the EKF for real time and non-real time ground attitude determination and sensor calibration for future missions such as the Gamma Ray Observatory (GRO) and the Small Explorer Mission (SMEX) is also presented.

Advancement and results in hostile fire indication using potassium line missile warning sensors

NASA Astrophysics Data System (ADS)

Montgomery, Joel; Montgomery, Marjorie; Hardie, Russell

2014-06-01

M&M Aviation has been developing and conducting Hostile Fire Indication (HFI) tests using potassium line emission sensors for the Air Force Visible Missile Warning System (VMWS) to advance both algorithm and sensor technologies for UAV and other airborne systems for self protection and intelligence purposes. Work began in 2008 as an outgrowth of detecting and classifying false alarm sources for the VMWS using the same K-line spectral discrimination region but soon became a focus of research due to the high interest in both machine-gun fire and sniper geo-location via airborne systems. Several initial tests were accomplished in 2009 using small and medium caliber weapons including rifles. Based on these results, the Air Force Research Laboratory (AFRL) funded the Falcon Sentinel program in 2010 to provide for additional development of both the sensor concept, algorithm suite changes and verification of basic phenomenology including variance based on ammunition type for given weapons platform. Results from testing over the past 3 years have showed that the system would be able to detect and declare a sniper rifle at upwards of 3km, medium machine gun at 5km, and explosive events like hand-grenades at greater than 5km. This paper will outline the development of the sensor systems, algorithms used for detection and classification, and test results from VMWS prototypes as well as outline algorithms used for the VMWS. The Falcon Sentinel Program will be outlined and results shown. Finally, the paper will show the future work for ATD and transition efforts after the Falcon Sentinel program completed.

SeaWiFS Science Algorithm Flow Chart

NASA Technical Reports Server (NTRS)

Darzi, Michael

1998-01-01

This flow chart describes the baseline science algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Processing System (SDPS). As such, it includes only processing steps used in the generation of the operational products that are archived by NASA's Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC). It is meant to provide the reader with a basic understanding of the scientific algorithm steps applied to SeaWiFS data. It does not include non-science steps, such as format conversions, and places the greatest emphasis on the geophysical calculations of the level-2 processing. Finally, the flow chart reflects the logic sequences and the conditional tests of the software so that it may be used to evaluate the fidelity of the implementation of the scientific algorithm. In many cases however, the chart may deviate from the details of the software implementation so as to simplify the presentation.

Implementation of Rivest Shamir Adleman Algorithm (RSA) and Vigenere Cipher In Web Based Information System

NASA Astrophysics Data System (ADS)

Aryanti, Aryanti; Mekongga, Ikhthison

2018-02-01

Data security and confidentiality is one of the most important aspects of information systems at the moment. One attempt to secure data such as by using cryptography. In this study developed a data security system by implementing the cryptography algorithm Rivest, Shamir Adleman (RSA) and Vigenere Cipher. The research was done by combining Rivest, Shamir Adleman (RSA) and Vigenere Cipher cryptographic algorithms to document file either word, excel, and pdf. This application includes the process of encryption and decryption of data, which is created by using PHP software and my SQL. Data encryption is done on the transmit side through RSA cryptographic calculations using the public key, then proceed with Vigenere Cipher algorithm which also uses public key. As for the stage of the decryption side received by using the Vigenere Cipher algorithm still use public key and then the RSA cryptographic algorithm using a private key. Test results show that the system can encrypt files, decrypt files and transmit files. Tests performed on the process of encryption and decryption of files with different file sizes, file size affects the process of encryption and decryption. The larger the file size the longer the process of encryption and decryption.

Advanced synthetic image generation models and their application to multi/hyperspectral algorithm development

NASA Astrophysics Data System (ADS)

Schott, John R.; Brown, Scott D.; Raqueno, Rolando V.; Gross, Harry N.; Robinson, Gary

1999-01-01

The need for robust image data sets for algorithm development and testing has prompted the consideration of synthetic imagery as a supplement to real imagery. The unique ability of synthetic image generation (SIG) tools to supply per-pixel truth allows algorithm writers to test difficult scenarios that would require expensive collection and instrumentation efforts. In addition, SIG data products can supply the user with `actual' truth measurements of the entire image area that are not subject to measurement error thereby allowing the user to more accurately evaluate the performance of their algorithm. Advanced algorithms place a high demand on synthetic imagery to reproduce both the spectro-radiometric and spatial character observed in real imagery. This paper describes a synthetic image generation model that strives to include the radiometric processes that affect spectral image formation and capture. In particular, it addresses recent advances in SIG modeling that attempt to capture the spatial/spectral correlation inherent in real images. The model is capable of simultaneously generating imagery from a wide range of sensors allowing it to generate daylight, low-light-level and thermal image inputs for broadband, multi- and hyper-spectral exploitation algorithms.

Feasibility of the TBDx automated digital microscopy system for the diagnosis of pulmonary tuberculosis.

PubMed

Nabeta, Pamela; Havumaki, Joshua; Ha, Dang Thi Minh; Caceres, Tatiana; Hang, Pham Thu; Collantes, Jimena; Thi Ngoc Lan, Nguyen; Gotuzzo, Eduardo; Denkinger, Claudia M

2017-01-01

Improved and affordable diagnostic or triage tests are urgently needed at the microscopy centre level. Automated digital microscopy has the potential to overcome issues related to conventional microscopy, including training time requirement and inconsistencies in results interpretation. For this blinded prospective study, sputum samples were collected from adults with presumptive pulmonary tuberculosis in Lima, Peru and Ho Chi Minh City, Vietnam. TBDx performance was evaluated as a stand-alone and as a triage test against conventional microscopy and Xpert, with culture as the reference standard. Xpert was used to confirm positive cases. A total of 613 subjects were enrolled between October 2014 and March 2015, with 539 included in the final analysis. The sensitivity of TBDx was 62·2% (95% CI 56·6-67·4) and specificity was 90·7% (95% CI 85·9-94·2) compared to culture. The algorithm assessing TBDx as a triage test achieved a specificity of 100% while maintaining sensitivity. While the diagnostic performance of TBDx did not reach the levels obtained by experienced microscopists in reference laboratories, it is conceivable that it would exceed the performance of less experienced microscopists. In the absence of highly sensitive and specific molecular tests at the microscopy centre level, TBDx in a triage-testing algorithm would optimize specificity and limit overall cost without compromising the number of patients receiving up-front drug susceptibility testing for rifampicin. However, the algorithm would miss over one third of patients compared to Xpert alone.

A diagnostic algorithm for atypical spitzoid tumors: guidelines for immunohistochemical and molecular assessment.

PubMed

Cho-Vega, Jeong Hee

2016-07-01

Atypical spitzoid tumors are a morphologically diverse group of rare melanocytic lesions most frequently seen in children and young adults. As atypical spitzoid tumors bear striking resemblance to Spitz nevus and spitzoid melanomas clinically and histopathologically, it is crucial to determine its malignant potential and predict its clinical behavior. To date, many researchers have attempted to differentiate atypical spitzoid tumors from unequivocal melanomas based on morphological, immonohistochemical, and molecular diagnostic differences. A diagnostic algorithm is proposed here to assess the malignant potential of atypical spitzoid tumors by using a combination of immunohistochemical and cytogenetic/molecular tests. Together with classical morphological evaluation, this algorithm includes a set of immunohistochemistry assays (p16(Ink4a), a dual-color Ki67/MART-1, and HMB45), fluorescence in situ hybridization (FISH) with five probes (6p25, 8q24, 11q13, CEN9, and 9p21), and an array-based comparative genomic hybridization. This review discusses details of the algorithm, the rationale of each test used in the algorithm, and utility of this algorithm in routine dermatopathology practice. This algorithmic approach will provide a comprehensive diagnostic tool that complements conventional histological criteria and will significantly contribute to improve the diagnosis and prediction of the clinical behavior of atypical spitzoid tumors.

2012 HIV Diagnostics Conference: the molecular diagnostics perspective.

PubMed

Branson, Bernard M; Pandori, Mark

2013-04-01

2012 HIV Diagnostic Conference Atlanta, GA, USA, 12-14 December 2012. This report highlights the presentations and discussions from the 2012 National HIV Diagnostic Conference held in Atlanta (GA, USA), on 12-14 December 2012. Reflecting changes in the evolving field of HIV diagnostics, the conference provided a forum for evaluating developments in molecular diagnostics and their role in HIV diagnosis. In 2010, the HIV Diagnostics Conference concluded with the proposal of a new diagnostic algorithm which included nucleic acid testing to resolve discordant screening and supplemental antibody test results. The 2012 meeting, picking up where the 2010 meeting left off, focused on scientific presentations that assessed this new algorithm and the role played by RNA testing and new developments in molecular diagnostics, including detection of total and integrated HIV-1 DNA, detection and quantification of HIV-2 RNA, and rapid formats for detection of HIV-1 RNA.

Effectiveness and cost-effectiveness of a cardiovascular risk prediction algorithm for people with severe mental illness (PRIMROSE).

PubMed

Zomer, Ella; Osborn, David; Nazareth, Irwin; Blackburn, Ruth; Burton, Alexandra; Hardoon, Sarah; Holt, Richard Ian Gregory; King, Michael; Marston, Louise; Morris, Stephen; Omar, Rumana; Petersen, Irene; Walters, Kate; Hunter, Rachael Maree

2017-09-05

To determine the cost-effectiveness of two bespoke severe mental illness (SMI)-specific risk algorithms compared with standard risk algorithms for primary cardiovascular disease (CVD) prevention in those with SMI. Primary care setting in the UK. The analysis was from the National Health Service perspective. 1000 individuals with SMI from The Health Improvement Network Database, aged 30-74 years and without existing CVD, populated the model. Four cardiovascular risk algorithms were assessed: (1) general population lipid, (2) general population body mass index (BMI), (3) SMI-specific lipid and (4) SMI-specific BMI, compared against no algorithm. At baseline, each cardiovascular risk algorithm was applied and those considered high risk ( > 10%) were assumed to be prescribed statin therapy while others received usual care. Quality-adjusted life years (QALYs) and costs were accrued for each algorithm including no algorithm, and cost-effectiveness was calculated using the net monetary benefit (NMB) approach. Deterministic and probabilistic sensitivity analyses were performed to test assumptions made and uncertainty around parameter estimates. The SMI-specific BMI algorithm had the highest NMB resulting in 15 additional QALYs and a cost saving of approximately £53 000 per 1000 patients with SMI over 10 years, followed by the general population lipid algorithm (13 additional QALYs and a cost saving of £46 000). The general population lipid and SMI-specific BMI algorithms performed equally well. The ease and acceptability of use of an SMI-specific BMI algorithm (blood tests not required) makes it an attractive algorithm to implement in clinical settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Strategies for concurrent processing of complex algorithms in data driven architectures

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Mielke, Roland R.; Som, Sukhamony

1990-01-01

The performance modeling and enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures is examined. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called ATAMM (Algorithm To Architecture Mapping Model). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

Strategies for concurrent processing of complex algorithms in data driven architectures

NASA Technical Reports Server (NTRS)

Som, Sukhamoy; Stoughton, John W.; Mielke, Roland R.

1990-01-01

Performance modeling and performance enhancement for periodic execution of large-grain, decision-free algorithms in data flow architectures are discussed. Applications include real-time implementation of control and signal processing algorithms where performance is required to be highly predictable. The mapping of algorithms onto the specified class of data flow architectures is realized by a marked graph model called algorithm to architecture mapping model (ATAMM). Performance measures and bounds are established. Algorithm transformation techniques are identified for performance enhancement and reduction of resource (computing element) requirements. A systematic design procedure is described for generating operating conditions for predictable performance both with and without resource constraints. An ATAMM simulator is used to test and validate the performance prediction by the design procedure. Experiments on a three resource testbed provide verification of the ATAMM model and the design procedure.

A Cancer Gene Selection Algorithm Based on the K-S Test and CFS.

PubMed

Su, Qiang; Wang, Yina; Jiang, Xiaobing; Chen, Fuxue; Lu, Wen-Cong

2017-01-01

To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S) test and correlation-based feature selection (CFS) principles. The algorithm selects distinguished genes first using the K-S test, and then, it uses CFS to select genes from those selected by the K-S test. We adopted support vector machines (SVM) as the classification tool and used the criteria of accuracy to evaluate the performance of the classifiers on the selected gene subsets. This approach compared the proposed gene subset selection algorithm with the K-S test, CFS, minimum-redundancy maximum-relevancy (mRMR), and ReliefF algorithms. The average experimental results of the aforementioned gene selection algorithms for 5 gene expression datasets demonstrate that, based on accuracy, the performance of the new K-S and CFS-based algorithm is better than those of the K-S test, CFS, mRMR, and ReliefF algorithms. The experimental results show that the K-S test-CFS gene selection algorithm is a very effective and promising approach compared to the K-S test, CFS, mRMR, and ReliefF algorithms.

Diagnosing breast cancer using Raman spectroscopy: prospective analysis

NASA Astrophysics Data System (ADS)

Haka, Abigail S.; Volynskaya, Zoya; Gardecki, Joseph A.; Nazemi, Jon; Shenk, Robert; Wang, Nancy; Dasari, Ramachandra R.; Fitzmaurice, Maryann; Feld, Michael S.

2009-09-01

We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided.

Benchmarking protein classification algorithms via supervised cross-validation.

PubMed

Kertész-Farkas, Attila; Dhir, Somdutta; Sonego, Paolo; Pacurar, Mircea; Netoteia, Sergiu; Nijveen, Harm; Kuzniar, Arnold; Leunissen, Jack A M; Kocsor, András; Pongor, Sándor

2008-04-24

Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold, leave-one-out, etc.) may not give reliable estimates on how an algorithm will generalize to novel, distantly related subtypes of the known protein classes. Supervised cross-validation, i.e., selection of test and train sets according to the known subtypes within a database has been successfully used earlier in conjunction with the SCOP database. Our goal was to extend this principle to other databases and to design standardized benchmark datasets for protein classification. Hierarchical classification trees of protein categories provide a simple and general framework for designing supervised cross-validation strategies for protein classification. Benchmark datasets can be designed at various levels of the concept hierarchy using a simple graph-theoretic distance. A combination of supervised and random sampling was selected to construct reduced size model datasets, suitable for algorithm comparison. Over 3000 new classification tasks were added to our recently established protein classification benchmark collection that currently includes protein sequence (including protein domains and entire proteins), protein structure and reading frame DNA sequence data. We carried out an extensive evaluation based on various machine-learning algorithms such as nearest neighbor, support vector machines, artificial neural networks, random forests and logistic regression, used in conjunction with comparison algorithms, BLAST, Smith-Waterman, Needleman-Wunsch, as well as 3D comparison methods DALI and PRIDE. The resulting datasets provide lower, and in our opinion more realistic estimates of the classifier performance than do random cross-validation schemes. A combination of supervised and random sampling was used to construct model datasets, suitable for algorithm comparison.

Robust camera calibration for sport videos using court models

NASA Astrophysics Data System (ADS)

Farin, Dirk; Krabbe, Susanne; de With, Peter H. N.; Effelsberg, Wolfgang

2003-12-01

We propose an automatic camera calibration algorithm for court sports. The obtained camera calibration parameters are required for applications that need to convert positions in the video frame to real-world coordinates or vice versa. Our algorithm uses a model of the arrangement of court lines for calibration. Since the court model can be specified by the user, the algorithm can be applied to a variety of different sports. The algorithm starts with a model initialization step which locates the court in the image without any user assistance or a-priori knowledge about the most probable position. Image pixels are classified as court line pixels if they pass several tests including color and local texture constraints. A Hough transform is applied to extract line elements, forming a set of court line candidates. The subsequent combinatorial search establishes correspondences between lines in the input image and lines from the court model. For the succeeding input frames, an abbreviated calibration algorithm is used, which predicts the camera parameters for the new image and optimizes the parameters using a gradient-descent algorithm. We have conducted experiments on a variety of sport videos (tennis, volleyball, and goal area sequences of soccer games). Video scenes with considerable difficulties were selected to test the robustness of the algorithm. Results show that the algorithm is very robust to occlusions, partial court views, bad lighting conditions, or shadows.

Operational feasibility of using whole blood in the rapid HIV testing algorithm of a resource-limited settings like Bangladesh.

PubMed

Munshi, Saif U; Oyewale, Tajudeen O; Begum, Shahnaz; Uddin, Ziya; Tabassum, Shahina

2016-03-01

Serum-based rapid HIV testing algorithm in Bangladesh constitutes operational challenge to scaleup HIV testing and counselling (HTC) in the country. This study explored the operational feasibility of using whole blood as alternative to serum for rapid HIV testing in Bangladesh. Whole blood specimens were collected from two study groups. The groups included HIV-positive patients (n = 200) and HIV-negative individuals (n = 200) presenting at the reference laboratory in Dhaka, Bangladesh. The specimens were subjected to rapid HIV tests using the national algorithm with A1 = Alere Determine (United States), A2 = Uni-Gold (Ireland), and A3 = First Response (India). The sensitivity and specificity of the test results, and the operational cost were compared with current serum-based testing. The sensitivities [95% of confidence interval (CI)] for A1, A2, and A3 tests using whole blood were 100% (CI: 99.1-100%), 100% (CI: 99.1-100%), and 97% (CI: 96.4-98.2%), respectively, and specificities of all test kits were 100% (CI: 99.1-100%). Significant (P < 0.05) reduction in the cost of establishing HTC centre and consumables by 94 and 61%, respectively, were observed. The cost of administration and external quality assurance reduced by 39 and 43%, respectively. Overall, there was a 36% cost reduction in total operational cost of rapid HIV testing with blood when compared with serum. Considering the similar sensitivity and specificity of the two specimens, and significant cost reduction, rapid HIV testing with whole blood is feasible. A review of the national HIV rapid testing algorithm with whole blood will contribute toward improving HTC coverage in Bangladesh.

6DOF Testing of the SLS Inertial Navigation Unit

NASA Technical Reports Server (NTRS)

Geohagan, Kevin W.; Bernard, William P.; Oliver, T. Emerson; Strickland, Dennis J.; Leggett, Jared O.

2018-01-01

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Pressure ulcer prevention algorithm content validation: a mixed-methods, quantitative study.

PubMed

van Rijswijk, Lia; Beitz, Janice M

2015-04-01

Translating pressure ulcer prevention (PUP) evidence-based recommendations into practice remains challenging for a variety of reasons, including the perceived quality, validity, and usability of the research or the guideline itself. Following the development and face validation testing of an evidence-based PUP algorithm, additional stakeholder input and testing were needed. Using convenience sampling methods, wound care experts attending a national wound care conference and a regional wound ostomy continence nursing (WOCN) conference and/or graduates of a WOCN program were invited to participate in an Internal Review Board-approved, mixed-methods quantitative survey with qualitative components to examine algorithm content validity. After participants provided written informed consent, demographic variables were collected and participants were asked to comment on and rate the relevance and appropriateness of each of the 26 algorithm decision points/steps using standard content validation study procedures. All responses were anonymous. Descriptive summary statistics, mean relevance/appropriateness scores, and the content validity index (CVI) were calculated. Qualitative comments were transcribed and thematically analyzed. Of the 553 wound care experts invited, 79 (average age 52.9 years, SD 10.1; range 23-73) consented to participate and completed the study (a response rate of 14%). Most (67, 85%) were female, registered (49, 62%) or advanced practice (12, 15%) nurses, and had > 10 years of health care experience (88, 92%). Other health disciplines included medical doctors, physical therapists, nurse practitioners, and certified nurse specialists. Almost all had received formal wound care education (75, 95%). On a Likert-type scale of 1 (not relevant/appropriate) to 4 (very relevant and appropriate), the average score for the entire algorithm/all decision points (N = 1,912) was 3.72 with an overall CVI of 0.94 (out of 1). The only decision point/step recommendation with a CVI of ≤ 0.70 was the recommendation to provide medical-grade sheepskin for patients at high risk for friction/shear. Many positive and substantive suggestions for minor modifications including color, flow, and algorithm orientation were received. The high overall and individual item rating scores and CVI further support the validity and appropriateness of the PUP algorithm with the addition of the minor modifications. The generic recommendations facilitate individualization, and future research should focus on construct validation testing.

The Cyborg Astrobiologist: testing a novelty detection algorithm on two mobile exploration systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah

NASA Astrophysics Data System (ADS)

McGuire, P. C.; Gross, C.; Wendt, L.; Bonnici, A.; Souza-Egipsy, V.; Ormö, J.; Díaz-Martínez, E.; Foing, B. H.; Bose, R.; Walter, S.; Oesker, M.; Ontrup, J.; Haschke, R.; Ritter, H.

2010-01-01

In previous work, a platform was developed for testing computer-vision algorithms for robotic planetary exploration. This platform consisted of a digital video camera connected to a wearable computer for real-time processing of images at geological and astrobiological field sites. The real-time processing included image segmentation and the generation of interest points based upon uncommonness in the segmentation maps. Also in previous work, this platform for testing computer-vision algorithms has been ported to a more ergonomic alternative platform, consisting of a phone camera connected via the Global System for Mobile Communications (GSM) network to a remote-server computer. The wearable-computer platform has been tested at geological and astrobiological field sites in Spain (Rivas Vaciamadrid and Riba de Santiuste), and the phone camera has been tested at a geological field site in Malta. In this work, we (i) apply a Hopfield neural-network algorithm for novelty detection based upon colour, (ii) integrate a field-capable digital microscope on the wearable computer platform, (iii) test this novelty detection with the digital microscope at Rivas Vaciamadrid, (iv) develop a Bluetooth communication mode for the phone-camera platform, in order to allow access to a mobile processing computer at the field sites, and (v) test the novelty detection on the Bluetooth-enabled phone camera connected to a netbook computer at the Mars Desert Research Station in Utah. This systems engineering and field testing have together allowed us to develop a real-time computer-vision system that is capable, for example, of identifying lichens as novel within a series of images acquired in semi-arid desert environments. We acquired sequences of images of geologic outcrops in Utah and Spain consisting of various rock types and colours to test this algorithm. The algorithm robustly recognized previously observed units by their colour, while requiring only a single image or a few images to learn colours as familiar, demonstrating its fast learning capability.

Mining peripheral arterial disease cases from narrative clinical notes using natural language processing.

PubMed

Afzal, Naveed; Sohn, Sunghwan; Abram, Sara; Scott, Christopher G; Chaudhry, Rajeev; Liu, Hongfang; Kullo, Iftikhar J; Arruda-Olson, Adelaide M

2017-06-01

Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative notes and compared the performance of the NLP algorithm with billing code algorithms, using ankle-brachial index test results as the gold standard. We compared the performance of the NLP algorithm to (1) results of gold standard ankle-brachial index; (2) previously validated algorithms based on relevant International Classification of Diseases, Ninth Revision diagnostic codes (simple model); and (3) a combination of International Classification of Diseases, Ninth Revision codes with procedural codes (full model). A dataset of 1569 patients with PAD and controls was randomly divided into training (n = 935) and testing (n = 634) subsets. We iteratively refined the NLP algorithm in the training set including narrative note sections, note types, and service types, to maximize its accuracy. In the testing dataset, when compared with both simple and full models, the NLP algorithm had better accuracy (NLP, 91.8%; full model, 81.8%; simple model, 83%; P < .001), positive predictive value (NLP, 92.9%; full model, 74.3%; simple model, 79.9%; P < .001), and specificity (NLP, 92.5%; full model, 64.2%; simple model, 75.9%; P < .001). A knowledge-driven NLP algorithm for automatic ascertainment of PAD cases from clinical notes had greater accuracy than billing code algorithms. Our findings highlight the potential of NLP tools for rapid and efficient ascertainment of PAD cases from electronic health records to facilitate clinical investigation and eventually improve care by clinical decision support. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Medical chart validation of an algorithm for identifying multiple sclerosis relapse in healthcare claims.

PubMed

Chastek, Benjamin J; Oleen-Burkey, Merrikay; Lopez-Bresnahan, Maria V

2010-01-01

Relapse is a common measure of disease activity in relapsing-remitting multiple sclerosis (MS). The objective of this study was to test the content validity of an operational algorithm for detecting relapse in claims data. A claims-based relapse detection algorithm was tested by comparing its detection rate over a 1-year period with relapses identified based on medical chart review. According to the algorithm, MS patients in a US healthcare claims database who had either (1) a primary claim for MS during hospitalization or (2) a corticosteroid claim following a MS-related outpatient visit were designated as having a relapse. Patient charts were examined for explicit indication of relapse or care suggestive of relapse. Positive and negative predictive values were calculated. Medical charts were reviewed for 300 MS patients, half of whom had a relapse according to the algorithm. The claims-based criteria correctly classified 67.3% of patients with relapses (positive predictive value) and 70.0% of patients without relapses (negative predictive value; kappa 0.373: p < 0.001). Alternative algorithms did not improve on the predictive value of the operational algorithm. Limitations of the algorithm include lack of differentiation between relapsing-remitting MS and other types, and that it does not incorporate measures of function and disability. The claims-based algorithm appeared to successfully detect moderate-to-severe MS relapse. This validated definition can be applied to future claims-based MS studies.

SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters

NASA Technical Reports Server (NTRS)

McKinna, Lachlan I. W.; Werdell, P. Jeremy; Fearns, Peter R. C. S.; Weeks, Scarla J.; Reichstetter, Martina; Franz, Bryan A.; Bailey, Sean W.; Shea, Donald M.; Feldman, Gene C.

2014-01-01

In clear shallow waters, light that is transmitted downward through the water column can reflect off the sea floor and thereby influence the water-leaving radiance signal. This effect can confound contemporary ocean color algorithms designed for deep waters where the seafloor has little or no effect on the water-leaving radiance. Thus, inappropriate use of deep water ocean color algorithms in optically shallow regions can lead to inaccurate retrievals of inherent optical properties (IOPs) and therefore have a detrimental impact on IOP-based estimates of marine parameters, including chlorophyll-a and the diffuse attenuation coefficient. In order to improve IOP retrievals in optically shallow regions, a semi-analytical inversion algorithm, the Shallow Water Inversion Model (SWIM), has been developed. Unlike established ocean color algorithms, SWIM considers both the water column depth and the benthic albedo. A radiative transfer study was conducted that demonstrated how SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Properties algorithm (GIOP) and Quasi-Analytical Algorithm (QAA), performed in optically deep and shallow scenarios. The results showed that SWIM performed well, whilst both GIOP and QAA showed distinct positive bias in IOP retrievals in optically shallow waters. The SWIM algorithm was also applied to a test region: the Great Barrier Reef, Australia. Using a single test scene and time series data collected by NASA's MODIS-Aqua sensor (2002-2013), a comparison of IOPs retrieved by SWIM, GIOP and QAA was conducted.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Detection of illicit substances in fingerprints by infrared spectral imaging.

PubMed

Ng, Ping Hei Ronnie; Walker, Sarah; Tahtouh, Mark; Reedy, Brian

2009-08-01

FTIR and Raman spectral imaging can be used to simultaneously image a latent fingerprint and detect exogenous substances deposited within it. These substances might include drugs of abuse or traces of explosives or gunshot residue. In this work, spectral searching algorithms were tested for their efficacy in finding targeted substances deposited within fingerprints. "Reverse" library searching, where a large number of possibly poor-quality spectra from a spectral image are searched against a small number of high-quality reference spectra, poses problems for common search algorithms as they are usually implemented. Out of a range of algorithms which included conventional Euclidean distance searching, the spectral angle mapper (SAM) and correlation algorithms gave the best results when used with second-derivative image and reference spectra. All methods tested gave poorer performances with first derivative and undifferentiated spectra. In a search against a caffeine reference, the SAM and correlation methods were able to correctly rank a set of 40 confirmed but poor-quality caffeine spectra at the top of a dataset which also contained 4,096 spectra from an image of an uncontaminated latent fingerprint. These methods also successfully and individually detected aspirin, diazepam and caffeine that had been deposited together in another fingerprint, and they did not indicate any of these substances as a match in a search for another substance which was known not to be present. The SAM was used to successfully locate explosive components in fingerprints deposited on silicon windows. The potential of other spectral searching algorithms used in the field of remote sensing is considered, and the applicability of the methods tested in this work to other modes of spectral imaging is discussed.

Implementation and testing of a sensor-netting algorithm for early warning and high confidence C/B threat detection

NASA Astrophysics Data System (ADS)

Gruber, Thomas; Grim, Larry; Fauth, Ryan; Tercha, Brian; Powell, Chris; Steinhardt, Kristin

2011-05-01

Large networks of disparate chemical/biological (C/B) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. Sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A data fusion algorithm design was completed in a Phase I SBIR effort and development continues in the Phase II SBIR effort. The initial implementation and testing of the algorithm has produced some performance results. The algorithm accepts point and/or standoff sensor data, and event detection data (e.g., the location of an explosion) from various ISR sensors (e.g., acoustic, infrared cameras, etc.). These input data are preprocessed to assign estimated uncertainty to each incoming piece of data. The data are then sent to a weighted tomography process to obtain a consensus threat map, including estimated threat concentration level uncertainty. The threat map is then tested for consistency and the overall confidence for the map result is estimated. The map and confidence results are displayed on a COP. The benefits of a modular implementation of the algorithm and comparisons of fused / un-fused data results will be presented. The metrics for judging the sensor-netting algorithm performance are warning time, threat map accuracy (as compared to ground truth), false alarm rate, and false alarm rate v. reported threat confidence level.

Continuous detection and decoding of dexterous finger flexions with implantable myoelectric sensors.

PubMed

Baker, Justin J; Scheme, Erik; Englehart, Kevin; Hutchinson, Douglas T; Greger, Bradley

2010-08-01

A rhesus monkey was trained to perform individuated and combined finger flexions of the thumb, index, and middle finger. Nine implantable myoelectric sensors (IMES) were then surgically implanted into the finger muscles of the monkey's forearm, without any adverse effects over two years postimplantation. Using an inductive link, EMG was wirelessly recorded from the IMES as the monkey performed a finger flexion task. The EMG from the different IMES implants showed very little cross correlation. An offline parallel linear discriminant analysis (LDA) based algorithm was used to decode finger activity based on features extracted from continuously presented frames of recorded EMG. The offline parallel LDA was run on intraday sessions as well as on sessions where the algorithm was trained on one day and tested on following days. The performance of the algorithm was evaluated continuously by comparing classification output by the algorithm to the current state of the finger switches. The algorithm detected and classified seven different finger movements, including individual and combined finger flexions, and a no-movement state (chance performance = 12.5%) . When the algorithm was trained and tested on data collected the same day, the average performance was 43.8+/-3.6% n=10. When the training-testing separation period was five months, the average performance of the algorithm was 46.5+/-3.4% n=8. These results demonstrated that using EMG recorded and wirelessly transmitted by IMES offers a promising approach for providing intuitive, dexterous control of artificial limbs where human patients have sufficient, functional residual muscle following amputation.

AESS: Accelerated Exact Stochastic Simulation

NASA Astrophysics Data System (ADS)

Jenkins, David D.; Peterson, Gregory D.

2011-12-01

The Stochastic Simulation Algorithm (SSA) developed by Gillespie provides a powerful mechanism for exploring the behavior of chemical systems with small species populations or with important noise contributions. Gene circuit simulations for systems biology commonly employ the SSA method, as do ecological applications. This algorithm tends to be computationally expensive, so researchers seek an efficient implementation of SSA. In this program package, the Accelerated Exact Stochastic Simulation Algorithm (AESS) contains optimized implementations of Gillespie's SSA that improve the performance of individual simulation runs or ensembles of simulations used for sweeping parameters or to provide statistically significant results. Program summaryProgram title: AESS Catalogue identifier: AEJW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: University of Tennessee copyright agreement No. of lines in distributed program, including test data, etc.: 10 861 No. of bytes in distributed program, including test data, etc.: 394 631 Distribution format: tar.gz Programming language: C for processors, CUDA for NVIDIA GPUs Computer: Developed and tested on various x86 computers and NVIDIA C1060 Tesla and GTX 480 Fermi GPUs. The system targets x86 workstations, optionally with multicore processors or NVIDIA GPUs as accelerators. Operating system: Tested under Ubuntu Linux OS and CentOS 5.5 Linux OS Classification: 3, 16.12 Nature of problem: Simulation of chemical systems, particularly with low species populations, can be accurately performed using Gillespie's method of stochastic simulation. Numerous variations on the original stochastic simulation algorithm have been developed, including approaches that produce results with statistics that exactly match the chemical master equation (CME) as well as other approaches that approximate the CME. Solution method: The Accelerated Exact Stochastic Simulation (AESS) tool provides implementations of a wide variety of popular variations on the Gillespie method. Users can select the specific algorithm considered most appropriate. Comparisons between the methods and with other available implementations indicate that AESS provides the fastest known implementation of Gillespie's method for a variety of test models. Users may wish to execute ensembles of simulations to sweep parameters or to obtain better statistical results, so AESS supports acceleration of ensembles of simulation using parallel processing with MPI, SSE vector units on x86 processors, and/or using NVIDIA GPUs with CUDA.

Syphilis testing practices in the Americas.

PubMed

Trinh, Thuy T; Kamb, Mary L; Luu, Minh; Ham, D Cal; Perez, Freddy

2017-09-01

To present the findings of the Pan American Health Organization's 2014 survey on syphilis testing policies and practices in the Americas. Representatives of national/regional reference and large, lower-level laboratories from 35 member states were invited to participate. A semi-structured, electronically administered questionnaire collected data on syphilis tests, algorithms, equipment/commodities, challenges faced and basic quality assurance (QA) strategies employed (i.e. daily controls, standard operating procedures, technician training, participating in external QA programmes, on-site evaluations). The 69 participating laboratories from 30 (86%) member states included 41 (59%) national/regional reference and 28 (41%) lower-level laboratories. Common syphilis tests conducted were the rapid plasma reagin (RPR) (62% of surveyed laboratories), venereal disease research laboratory (VDRL) (54%), fluorescent treponemal antibody absorption (FTA-ABS) (41%) and Treponema pallidum haemagglutination assay (TPHA) (32%). Only three facilities reported using direct detection methods, and 28 (41% overall, 32% of lower-level facilities) used rapid tests. Most laboratories (62%) used only traditional testing algorithms (non-treponemal screening and treponemal confirmatory testing); however, 12% used only a reverse sequence algorithm (treponemal test first), and 14% employed both algorithms. Another nine (12%) laboratories conducted only one type of serologic test. Although most reference (97%) and lower-level (89%) laboratories used at least one QA strategy, only 16% reported using all five basic strategies. Commonly reported challenges were stock-outs of essential reagents or commodities (46%), limited staff training (73%) and insufficient equipment (39%). Many reference and clinical laboratories in the Americas face challenges in conducting appropriate syphilis testing and in ensuring quality of testing. © 2017 John Wiley & Sons Ltd The Pan-American Health Organization retains copyright and all other rights in the manuscript of this article as submitted for publication.

Performance Review of Harmony Search, Differential Evolution and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Mohan Pandey, Hari

2017-08-01

Metaheuristic algorithms are effective in the design of an intelligent system. These algorithms are widely applied to solve complex optimization problems, including image processing, big data analytics, language processing, pattern recognition and others. This paper presents a performance comparison of three meta-heuristic algorithms, namely Harmony Search, Differential Evolution, and Particle Swarm Optimization. These algorithms are originated altogether from different fields of meta-heuristics yet share a common objective. The standard benchmark functions are used for the simulation. Statistical tests are conducted to derive a conclusion on the performance. The key motivation to conduct this research is to categorize the computational capabilities, which might be useful to the researchers.

A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data

NASA Technical Reports Server (NTRS)

Schultz, Howard

1990-01-01

The retrieval algorithm for spaceborne scatterometry proposed by Schultz (1985) is extended. A circular median filter (CMF) method is presented, which operates on wind directions independently of wind speed, removing any implicit wind speed dependence. A cell weighting scheme is included in the algorithm, permitting greater weights to be assigned to more reliable data. The mathematical properties of the ambiguous solutions to the wind retrieval problem are reviewed. The CMF algorithm is tested on twelve simulated data sets. The effects of spatially correlated likelihood assignment errors on the performance of the CMF algorithm are examined. Also, consideration is given to a wind field smoothing technique that uses a CMF.

Document localization algorithms based on feature points and straight lines

NASA Astrophysics Data System (ADS)

Skoryukina, Natalya; Shemiakina, Julia; Arlazarov, Vladimir L.; Faradjev, Igor

2018-04-01

The important part of the system of a planar rectangular object analysis is the localization: the estimation of projective transform from template image of an object to its photograph. The system also includes such subsystems as the selection and recognition of text fields, the usage of contexts etc. In this paper three localization algorithms are described. All algorithms use feature points and two of them also analyze near-horizontal and near- vertical lines on the photograph. The algorithms and their combinations are tested on a dataset of real document photographs. Also the method of localization quality estimation is proposed that allows configuring the localization subsystem independently of the other subsystems quality.

Decomposing the electromagnetic response of magnetic dipoles to determine the geometric parameters of a dipole conductor

NASA Astrophysics Data System (ADS)

Desmarais, Jacques K.; Smith, Richard S.

2016-03-01

A novel automatic data interpretation algorithm is presented for modelling airborne electromagnetic (AEM) data acquired over resistive environments, using a single-component (vertical) transmitter, where the position and orientation of a dipole conductor is allowed to vary in three dimensions. The algorithm assumes that the magnetic fields produced from compact vortex currents are expressed as a linear combinations of the fields arising from dipoles in the subsurface oriented parallel to the [1, 0, 0], [0, 1, 0], and [0, 0, 1], unit vectors. In this manner, AEM responses can be represented as 12 terms. The relative size of each term in the decomposition can be used to determine geometrical information about the orientation of the subsurface conductivity structure. The geometrical parameters of the dipole (location, depth, dip, strike) are estimated using a combination of a look-up table and a matrix inverted in a least-squares sense. Tests on 703 synthetic models show that the algorithm is capable of extracting most of the correct geometrical parameters of a dipole conductor when three-component receiver data is included in the interpretation procedure. The algorithm is unstable when the target is perfectly horizontal, as the strike is undefined. Ambiguities may occur in predicting the orientation of the dipole conductor if y-component data is excluded from the analysis. Application of our approach to an anomaly on line 15 of the Reid Mahaffy test site yields geometrical parameters in reasonable agreement with previous authors. However, our algorithm provides additional information on the strike and offset from the traverse line of the conductor. Disparities in the values of predicted dip and depth are within the range of numerical precision. The index of fit was better when strike and offset were included in the interpretation procedure. Tests on the data from line 15701 of the Chibougamau MEGATEM survey shows that the algorithm is applicable to situations where three-component AEM data is available.

Experimental validation of clock synchronization algorithms

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.; Graham, R. Lynn

1992-01-01

The objective of this work is to validate mathematically derived clock synchronization theories and their associated algorithms through experiment. Two theories are considered, the Interactive Convergence Clock Synchronization Algorithm and the Midpoint Algorithm. Special clock circuitry was designed and built so that several operating conditions and failure modes (including malicious failures) could be tested. Both theories are shown to predict conservative upper bounds (i.e., measured values of clock skew were always less than the theory prediction). Insight gained during experimentation led to alternative derivations of the theories. These new theories accurately predict the behavior of the clock system. It is found that a 100 percent penalty is paid to tolerate worst-case failures. It is also shown that under optimal conditions (with minimum error and no failures) the clock skew can be as much as three clock ticks. Clock skew grows to six clock ticks when failures are present. Finally, it is concluded that one cannot rely solely on test procedures or theoretical analysis to predict worst-case conditions.

An efficient robust sound classification algorithm for hearing aids.

PubMed

Nordqvist, Peter; Leijon, Arne

2004-06-01

An efficient robust sound classification algorithm based on hidden Markov models is presented. The system would enable a hearing aid to automatically change its behavior for differing listening environments according to the user's preferences. This work attempts to distinguish between three listening environment categories: speech in traffic noise, speech in babble, and clean speech, regardless of the signal-to-noise ratio. The classifier uses only the modulation characteristics of the signal. The classifier ignores the absolute sound pressure level and the absolute spectrum shape, resulting in an algorithm that is robust against irrelevant acoustic variations. The measured classification hit rate was 96.7%-99.5% when the classifier was tested with sounds representing one of the three environment categories included in the classifier. False-alarm rates were 0.2%-1.7% in these tests. The algorithm is robust and efficient and consumes a small amount of instructions and memory. It is fully possible to implement the classifier in a DSP-based hearing instrument.

Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial points

NASA Astrophysics Data System (ADS)

Regis, Rommel G.

2014-02-01

This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems.

Applied algorithm in the liner inspection of solid rocket motors

NASA Astrophysics Data System (ADS)

Hoffmann, Luiz Felipe Simões; Bizarria, Francisco Carlos Parquet; Bizarria, José Walter Parquet

2018-03-01

In rocket motors, the bonding between the solid propellant and thermal insulation is accomplished by a thin adhesive layer, known as liner. The liner application method involves a complex sequence of tasks, which includes in its final stage, the surface integrity inspection. Nowadays in Brazil, an expert carries out a thorough visual inspection to detect defects on the liner surface that may compromise the propellant interface bonding. Therefore, this paper proposes an algorithm that uses the photometric stereo technique and the K-nearest neighbor (KNN) classifier to assist the expert in the surface inspection. Photometric stereo allows the surface information recovery of the test images, while the KNN method enables image pixels classification into two classes: non-defect and defect. Tests performed on a computer vision based prototype validate the algorithm. The positive results suggest that the algorithm is feasible and when implemented in a real scenario, will be able to help the expert in detecting defective areas on the liner surface.

Collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation

NASA Astrophysics Data System (ADS)

Yang, Shangwen; Guo, Baohua; Xiao, Xuefei; Gao, Haichao

2018-01-01

To allocate the en-routes and slots to the flights with collaborative decision making, a collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation was proposed. Evaluation indexes include flight delay costs, delay time and the number of turning points. Analytic hierarchy process is applied to determining index weights. Remark set for current two flights not yet obtained the en-route and slot in flight schedule is established. Then, fuzzy comprehensive evaluation is performed, and the en-route and slot for the current two flights are determined. Continue selecting the flight not yet obtained an en-route and a slot in flight schedule. Perform fuzzy comprehensive evaluation until all flights have obtained the en-routes and slots. MatlabR2007b was applied to numerical test based on the simulated data of a civil en-route. Test results show that, compared with the traditional strategy of first come first service, the algorithm gains better effect. The effectiveness of the algorithm was verified.

Simultaneous Mass Determination for Gravitationally Coupled Asteroids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baer, James; Chesley, Steven R., E-mail: jimbaer1@earthlink.net

The conventional least-squares asteroid mass determination algorithm allows us to solve for the mass of a large subject asteroid that is perturbing the trajectory of a smaller test asteroid. However, this algorithm is necessarily a first approximation, ignoring the possibility that the subject asteroid may itself be perturbed by the test asteroid, or that the encounter’s precise geometry may be entangled with encounters involving other asteroids. After reviewing the conventional algorithm, we use it to calculate the masses of 30 main-belt asteroids. Compared to our previous results, we find new mass estimates for eight asteroids (11 Parthenope, 27 Euterpe, 51more » Neimausa, 76 Freia, 121 Hermione, 324 Bamberga, 476 Hedwig, and 532 Herculina) and significantly more precise estimates for six others (2 Pallas, 3 Juno, 4 Vesta, 9 Metis, 16 Psyche, and 88 Thisbe). However, we also find that the conventional algorithm yields questionable results in several gravitationally coupled cases. To address such cases, we describe a new algorithm that allows the epoch state vectors of the subject asteroids to be included as solve-for parameters, allowing for the simultaneous solution of the masses and epoch state vectors of multiple subject and test asteroids. We then apply this algorithm to the same 30 main-belt asteroids and conclude that mass determinations resulting from current and future high-precision astrometric sources (such as Gaia ) should conduct a thorough search for possible gravitational couplings and account for their effects.« less

Locomotion with loads: practical techniques for predicting performance outcomes

DTIC Science & Technology

including load), speed, and grade algorithms proposed will allow walking metabolic rates to be predicted to within 6.0 and 12.0 in laboratory and field...speeds to be predicted to within6.0 in both laboratory and field settings. Respective load-carriage algorithms for walking energy expenditure and...running speed will be developed and tested( Technical Objectives 1.0 and 2.0) in the laboratory and the field.

B* Probability Based Search

DTIC Science & Technology

1994-06-27

success . The key ideas behind the algorithm are: 1. Stopping when one alternative is clearly better than all the others, and 2. Focusing the search on...search algorithm has been implemented on the chess machine Hitech . En route we have developed effective techniques for: "* Dealing with independence of...report describes the implementation, and the results of tests including games played against brute- force programs. The data indicate that B* Hitech is a

Development of anomaly detection models for deep subsurface monitoring

NASA Astrophysics Data System (ADS)

Sun, A. Y.

2017-12-01

Deep subsurface repositories are used for waste disposal and carbon sequestration. Monitoring deep subsurface repositories for potential anomalies is challenging, not only because the number of sensor networks and the quality of data are often limited, but also because of the lack of labeled data needed to train and validate machine learning (ML) algorithms. Although physical simulation models may be applied to predict anomalies (or the system's nominal state for that sake), the accuracy of such predictions may be limited by inherent conceptual and parameter uncertainties. The main objective of this study was to demonstrate the potential of data-driven models for leakage detection in carbon sequestration repositories. Monitoring data collected during an artificial CO2 release test at a carbon sequestration repository were used, which include both scalar time series (pressure) and vector time series (distributed temperature sensing). For each type of data, separate online anomaly detection algorithms were developed using the baseline experiment data (no leak) and then tested on the leak experiment data. Performance of a number of different online algorithms was compared. Results show the importance of including contextual information in the dataset to mitigate the impact of reservoir noise and reduce false positive rate. The developed algorithms were integrated into a generic Web-based platform for real-time anomaly detection.

FPGA Online Tracking Algorithm for the PANDA Straw Tube Tracker

NASA Astrophysics Data System (ADS)

Liang, Yutie; Ye, Hua; Galuska, Martin J.; Gessler, Thomas; Kuhn, Wolfgang; Lange, Jens Soren; Wagner, Milan N.; Liu, Zhen'an; Zhao, Jingzhou

2017-06-01

A novel FPGA based online tracking algorithm for helix track reconstruction in a solenoidal field, developed for the PANDA spectrometer, is described. Employing the Straw Tube Tracker detector with 4636 straw tubes, the algorithm includes a complex track finder, and a track fitter. Implemented in VHDL, the algorithm is tested on a Xilinx Virtex-4 FX60 FPGA chip with different types of events, at different event rates. A processing time of 7 $\\mu$s per event for an average of 6 charged tracks is obtained. The momentum resolution is about 3\\% (4\\%) for $p_t$ ($p_z$) at 1 GeV/c. Comparing to the algorithm running on a CPU chip (single core Intel Xeon E5520 at 2.26 GHz), an improvement of 3 orders of magnitude in processing time is obtained. The algorithm can handle severe overlapping of events which are typical for interaction rates above 10 MHz.

Solving large test-day models by iteration on data and preconditioned conjugate gradient.

PubMed

Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A

1999-12-01

A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.

Accelerated probabilistic inference of RNA structure evolution

PubMed Central

Holmes, Ian

2005-01-01

Background Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for evolutionary analysis of RNA, including simultaneous RNA sequence alignment and secondary structure prediction, but the associated algorithms are intensive in both CPU and memory usage. The same problem is faced by other RNA alignment-and-folding algorithms based on Sankoff's 1985 algorithm. It is therefore desirable to constrain such algorithms, by pre-processing the sequences and using this first pass to limit the range of structures and/or alignments that can be considered. Results We demonstrate how flexible classes of constraint can be imposed, greatly reducing the computational costs while maintaining a high quality of structural homology prediction. Any score-attributed context-free grammar (e.g. energy-based scoring schemes, or conditionally normalized Pair SCFGs) is amenable to this treatment. It is now possible to combine independent structural and alignment constraints of unprecedented general flexibility in Pair SCFG alignment algorithms. We outline several applications to the bioinformatics of RNA sequence and structure, including Waterman-Eggert N-best alignments and progressive multiple alignment. We evaluate the performance of the algorithm on test examples from the RFAM database. Conclusion A program, Stemloc, that implements these algorithms for efficient RNA sequence alignment and structure prediction is available under the GNU General Public License. PMID:15790387

DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D.

PubMed

Shuvaev, Sergey A; Lazutkin, Alexander A; Kedrov, Alexander V; Anokhin, Konstantin V; Enikolopov, Grigori N; Koulakov, Alexei A

2017-01-01

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.

StirMark Benchmark: audio watermarking attacks based on lossy compression

NASA Astrophysics Data System (ADS)

Steinebach, Martin; Lang, Andreas; Dittmann, Jana

2002-04-01

StirMark Benchmark is a well-known evaluation tool for watermarking robustness. Additional attacks are added to it continuously. To enable application based evaluation, in our paper we address attacks against audio watermarks based on lossy audio compression algorithms to be included in the test environment. We discuss the effect of different lossy compression algorithms like MPEG-2 audio Layer 3, Ogg or VQF on a selection of audio test data. Our focus is on changes regarding the basic characteristics of the audio data like spectrum or average power and on removal of embedded watermarks. Furthermore we compare results of different watermarking algorithms and show that lossy compression is still a challenge for most of them. There are two strategies for adding evaluation of robustness against lossy compression to StirMark Benchmark: (a) use of existing free compression algorithms (b) implementation of a generic lossy compression simulation. We discuss how such a model can be implemented based on the results of our tests. This method is less complex, as no real psycho acoustic model has to be applied. Our model can be used for audio watermarking evaluation of numerous application fields. As an example, we describe its importance for e-commerce applications with watermarking security.

Testing and Validating Machine Learning Classifiers by Metamorphic Testing☆

PubMed Central

Xie, Xiaoyuan; Ho, Joshua W. K.; Murphy, Christian; Kaiser, Gail; Xu, Baowen; Chen, Tsong Yueh

2011-01-01

Machine Learning algorithms have provided core functionality to many application domains - such as bioinformatics, computational linguistics, etc. However, it is difficult to detect faults in such applications because often there is no “test oracle” to verify the correctness of the computed outputs. To help address the software quality, in this paper we present a technique for testing the implementations of machine learning classification algorithms which support such applications. Our approach is based on the technique “metamorphic testing”, which has been shown to be effective to alleviate the oracle problem. Also presented include a case study on a real-world machine learning application framework, and a discussion of how programmers implementing machine learning algorithms can avoid the common pitfalls discovered in our study. We also conduct mutation analysis and cross-validation, which reveal that our method has high effectiveness in killing mutants, and that observing expected cross-validation result alone is not sufficiently effective to detect faults in a supervised classification program. The effectiveness of metamorphic testing is further confirmed by the detection of real faults in a popular open-source classification program. PMID:21532969

Capacity of non-invasive hepatic fibrosis algorithms to replace transient elastography to exclude cirrhosis in people with hepatitis C virus infection: A multi-centre observational study

PubMed Central

Riordan, Stephen M.; Bopage, Rohan; Lloyd, Andrew R.

2018-01-01

Introduction Achievement of the 2030 World Health Organisation (WHO) global hepatitis C virus (HCV) elimination targets will be underpinned by scale-up of testing and use of direct-acting antiviral treatments. In Australia, despite publically-funded testing and treatment, less than 15% of patients were treated in the first year of treatment access, highlighting the need for greater efficiency of health service delivery. To this end, non-invasive fibrosis algorithms were examined to reduce reliance on transient elastography (TE) which is currently utilised for the assessment of cirrhosis in most Australian clinical settings. Materials and methods This retrospective and prospective study, with derivation and validation cohorts, examined consecutive patients in a tertiary referral centre, a sexual health clinic, and a prison-based hepatitis program. The negative predictive value (NPV) of seven non-invasive algorithms were measured using published and newly derived cut-offs. The number of TEs avoided for each algorithm, or combination of algorithms, was determined. Results The 850 patients included 780 (92%) with HCV mono-infection, and 70 (8%) co-infected with HIV or hepatitis B. The mono-infected cohort included 612 men (79%), with an overall prevalence of cirrhosis of 16% (125/780). An ‘APRI’ algorithm cut-off of 1.0 had a 94% NPV (95%CI: 91–96%). Newly derived cut-offs of ‘APRI’ (0.49), ‘FIB-4’ (0.93) and ‘GUCI’ (0.5) algorithms each had NPVs of 99% (95%CI: 97–100%), allowing avoidance of TE in 40% (315/780), 40% (310/780) and 40% (298/749) respectively. When used in combination, NPV was retained and TE avoidance reached 54% (405/749), regardless of gender or co-infection. Conclusions Non-invasive algorithms can reliably exclude cirrhosis in many patients, allowing improved efficiency of HCV assessment services in Australia and worldwide. PMID:29438397

Capacity of non-invasive hepatic fibrosis algorithms to replace transient elastography to exclude cirrhosis in people with hepatitis C virus infection: A multi-centre observational study.

PubMed

Kelly, Melissa Louise; Riordan, Stephen M; Bopage, Rohan; Lloyd, Andrew R; Post, Jeffrey John

2018-01-01

Achievement of the 2030 World Health Organisation (WHO) global hepatitis C virus (HCV) elimination targets will be underpinned by scale-up of testing and use of direct-acting antiviral treatments. In Australia, despite publically-funded testing and treatment, less than 15% of patients were treated in the first year of treatment access, highlighting the need for greater efficiency of health service delivery. To this end, non-invasive fibrosis algorithms were examined to reduce reliance on transient elastography (TE) which is currently utilised for the assessment of cirrhosis in most Australian clinical settings. This retrospective and prospective study, with derivation and validation cohorts, examined consecutive patients in a tertiary referral centre, a sexual health clinic, and a prison-based hepatitis program. The negative predictive value (NPV) of seven non-invasive algorithms were measured using published and newly derived cut-offs. The number of TEs avoided for each algorithm, or combination of algorithms, was determined. The 850 patients included 780 (92%) with HCV mono-infection, and 70 (8%) co-infected with HIV or hepatitis B. The mono-infected cohort included 612 men (79%), with an overall prevalence of cirrhosis of 16% (125/780). An 'APRI' algorithm cut-off of 1.0 had a 94% NPV (95%CI: 91-96%). Newly derived cut-offs of 'APRI' (0.49), 'FIB-4' (0.93) and 'GUCI' (0.5) algorithms each had NPVs of 99% (95%CI: 97-100%), allowing avoidance of TE in 40% (315/780), 40% (310/780) and 40% (298/749) respectively. When used in combination, NPV was retained and TE avoidance reached 54% (405/749), regardless of gender or co-infection. Non-invasive algorithms can reliably exclude cirrhosis in many patients, allowing improved efficiency of HCV assessment services in Australia and worldwide.

Geometrical features assessment of liver's tumor with application of artificial neural network evolved by imperialist competitive algorithm.

PubMed

Keshavarz, M; Mojra, A

2015-05-01

Geometrical features of a cancerous tumor embedded in biological soft tissue, including tumor size and depth, are a necessity in the follow-up procedure and making suitable therapeutic decisions. In this paper, a new socio-politically motivated global search strategy which is called imperialist competitive algorithm (ICA) is implemented to train a feed forward neural network (FFNN) to estimate the tumor's geometrical characteristics (FFNNICA). First, a viscoelastic model of liver tissue is constructed by using a series of in vitro uniaxial and relaxation test data. Then, 163 samples of the tissue including a tumor with different depths and diameters are generated by making use of PYTHON programming to link the ABAQUS and MATLAB together. Next, the samples are divided into 123 samples as training dataset and 40 samples as testing dataset. Training inputs of the network are mechanical parameters extracted from palpation of the tissue through a developing noninvasive technology called artificial tactile sensing (ATS). Last, to evaluate the FFNNICA performance, outputs of the network including tumor's depth and diameter are compared with desired values for both training and testing datasets. Deviations of the outputs from desired values are calculated by a regression analysis. Statistical analysis is also performed by measuring Root Mean Square Error (RMSE) and Efficiency (E). RMSE in diameter and depth estimations are 0.50 mm and 1.49, respectively, for the testing dataset. Results affirm that the proposed optimization algorithm for training neural network can be useful to characterize soft tissue tumors accurately by employing an artificial palpation approach. Copyright © 2015 John Wiley & Sons, Ltd.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

A Novel Optical/digital Processing System for Pattern Recognition

NASA Technical Reports Server (NTRS)

Boone, Bradley G.; Shukla, Oodaye B.

1993-01-01

This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

A new modified conjugate gradient coefficient for solving system of linear equations

NASA Astrophysics Data System (ADS)

Hajar, N.; ‘Aini, N.; Shapiee, N.; Abidin, Z. Z.; Khadijah, W.; Rivaie, M.; Mamat, M.

2017-09-01

Conjugate gradient (CG) method is an evolution of computational method in solving unconstrained optimization problems. This approach is easy to implement due to its simplicity and has been proven to be effective in solving real-life application. Although this field has received copious amount of attentions in recent years, some of the new approaches of CG algorithm cannot surpass the efficiency of the previous versions. Therefore, in this paper, a new CG coefficient which retains the sufficient descent and global convergence properties of the original CG methods is proposed. This new CG is tested on a set of test functions under exact line search. Its performance is then compared to that of some of the well-known previous CG methods based on number of iterations and CPU time. The results show that the new CG algorithm has the best efficiency amongst all the methods tested. This paper also includes an application of the new CG algorithm for solving large system of linear equations

Warfarin Pharmacogenomics in Diverse Populations.

PubMed

Kaye, Justin B; Schultz, Lauren E; Steiner, Heidi E; Kittles, Rick A; Cavallari, Larisa H; Karnes, Jason H

2017-09-01

Genotype-guided warfarin dosing algorithms are a rational approach to optimize warfarin dosing and potentially reduce adverse drug events. Diverse populations, such as African Americans and Latinos, have greater variability in warfarin dose requirements and are at greater risk for experiencing warfarin-related adverse events compared with individuals of European ancestry. Although these data suggest that patients of diverse populations may benefit from improved warfarin dose estimation, the vast majority of literature on genotype-guided warfarin dosing, including data from prospective randomized trials, is in populations of European ancestry. Despite differing frequencies of variants by race/ethnicity, most evidence in diverse populations evaluates variants that are most common in populations of European ancestry. Algorithms that do not include variants important across race/ethnic groups are unlikely to benefit diverse populations. In some race/ethnic groups, development of race-specific or admixture-based algorithms may facilitate improved genotype-guided warfarin dosing algorithms above and beyond that seen in individuals of European ancestry. These observations should be considered in the interpretation of literature evaluating the clinical utility of genotype-guided warfarin dosing. Careful consideration of race/ethnicity and additional evidence focused on improving warfarin dosing algorithms across race/ethnic groups will be necessary for successful clinical implementation of warfarin pharmacogenomics. The evidence for warfarin pharmacogenomics has a broad significance for pharmacogenomic testing, emphasizing the consideration of race/ethnicity in discovery of gene-drug pairs and development of clinical recommendations for pharmacogenetic testing. © 2017 Pharmacotherapy Publications, Inc.

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

NASA Technical Reports Server (NTRS)

Trevino, Luis; Johnson, Stephen B.; Patterson, Jonathan; Teare, David

2015-01-01

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

The Performance Analysis of a 3d Map Embedded Ins/gps Fusion Algorithm for Seamless Vehicular Navigation in Elevated Highway Environments

NASA Astrophysics Data System (ADS)

Lee, Y. H.; Chiang, K. W.

2012-07-01

In this study, a 3D Map Matching (3D MM) algorithm is embedded to current INS/GPS fusion algorithm for enhancing the sustainability and accuracy of INS/GPS integration systems, especially the height component. In addition, this study propose an effective solutions to the limitation of current commercial vehicular navigation systems where they fail to distinguish whether the vehicle is moving on the elevated highway or the road under it because those systems don't have sufficient height resolution. To validate the performance of proposed 3D MM embedded INS/GPS integration algorithms, in the test area, two scenarios were considered, paths under the freeways and streets between tall buildings, where the GPS signal is obstacle or interfered easily. The test platform was mounted on the top of a land vehicle and also systems in the vehicle. The IMUs applied includes SPAN-LCI (0.1 deg/hr gyro bias) from NovAtel, which was used as the reference system, and two MEMS IMUs with different specifications for verifying the performance of proposed algorithm. The preliminary results indicate the proposed algorithms are able to improve the accuracy of positional components in GPS denied environments significantly with the use of INS/GPS integrated systems in SPP mode.

POSE Algorithms for Automated Docking

NASA Technical Reports Server (NTRS)

Heaton, Andrew F.; Howard, Richard T.

2011-01-01

POSE (relative position and attitude) can be computed in many different ways. Given a sensor that measures bearing to a finite number of spots corresponding to known features (such as a target) of a spacecraft, a number of different algorithms can be used to compute the POSE. NASA has sponsored the development of a flash LIDAR proximity sensor called the Vision Navigation Sensor (VNS) for use by the Orion capsule in future docking missions. This sensor generates data that can be used by a variety of algorithms to compute POSE solutions inside of 15 meters, including at the critical docking range of approximately 1-2 meters. Previously NASA participated in a DARPA program called Orbital Express that achieved the first automated docking for the American space program. During this mission a large set of high quality mated sensor data was obtained at what is essentially the docking distance. This data set is perhaps the most accurate truth data in existence for docking proximity sensors in orbit. In this paper, the flight data from Orbital Express is used to test POSE algorithms at 1.22 meters range. Two different POSE algorithms are tested for two different Fields-of-View (FOVs) and two different pixel noise levels. The results of the analysis are used to predict future performance of the POSE algorithms with VNS data.

Experiments with conjugate gradient algorithms for homotopy curve tracking

NASA Technical Reports Server (NTRS)

Irani, Kashmira M.; Ribbens, Calvin J.; Watson, Layne T.; Kamat, Manohar P.; Walker, Homer F.

1991-01-01

There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here, variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.

A return-to-sport algorithm for acute hamstring injuries.

PubMed

Mendiguchia, Jurdan; Brughelli, Matt

2011-02-01

Acute hamstring injuries are the most prevalent muscle injuries reported in sport. Despite a thorough and concentrated effort to prevent and rehabilitate hamstring injuries, injury occurrence and re-injury rates have not improved over the past 28 years. This failure is most likely due to the following: 1) an over-reliance on treating the symptoms of injury, such as subjective measures of "pain", with drugs and interventions; 2) the risk factors investigated for hamstring injuries have not been related to the actual movements that cause hamstring injuries i.e. not functional; and, 3) a multi-factorial approach to assessment and treatment has not been utilized. The purpose of this clinical commentary is to introduce a model for progression through a return-to-sport rehabilitation following an acute hamstring injury. This model is developed from objective and quantifiable tests (i.e. clinical and functional tests) that are structured into a step-by-step algorithm. In addition, each step in the algorithm includes a treatment protocol. These protocols are meant to help the athlete to improve through each phase safely so that they can achieve the desired goals and progress through the algorithm and back to their chosen sport. We hope that this algorithm can serve as a foundation for future evidence based research and aid in the development of new objective and quantifiable testing methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

A variational technique for smoothing flight-test and accident data

NASA Technical Reports Server (NTRS)

Bach, R. E., Jr.

1980-01-01

The problem of determining aircraft motions along a trajectory is solved using a variational algorithm that generates unmeasured states and forcing functions, and estimates instrument bias and scale-factor errors. The problem is formulated as a nonlinear fixed-interval smoothing problem, and is solved as a sequence of linear two-point boundary value problems, using a sweep method. The algorithm has been implemented for use in flight-test and accident analysis. Aircraft motions are assumed to be governed by a six-degree-of-freedom kinematic model; forcing functions consist of body accelerations and winds, and the measurement model includes aerodynamic and radar data. Examples of the determination of aircraft motions from typical flight-test and accident data are presented.

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.

Field comparison of OraQuick® ADVANCE Rapid HIV-1/2 antibody test and two blood-based rapid HIV antibody tests in Zambia

PubMed Central

2012-01-01

Background Zambia’s national HIV testing algorithm specifies use of two rapid blood based antibody assays, Determine®HIV-1/2 (Inverness Medical) and if positive then Uni-GoldTM Recombigen HIV-1/2 (Trinity Biotech). Little is known about the performance of oral fluid based HIV testing in Zambia. The aims of this study are two-fold: 1) to compare the diagnostic accuracy (sensitivity and specificity) under field conditions of the OraQuick® ADVANCE® Rapid HIV-1/2 (OraSure Technologies, Inc.) to two blood-based rapid antibody tests currently in use in the Zambia National Algorithm, and 2) to perform a cost analysis of large-scale field testing employing the OraQuick®. Methods This was a operational retrospective research of HIV testing and questionnaire data collected in 2010 as part of the ZAMSTAR (Zambia South Africa TB and AIDS reduction) study. Randomly sampled individuals in twelve communities were tested consecutively with OraQuick® test using oral fluid versus two blood-based rapid HIV tests, Determine® and Uni-GoldTM. A cost analysis of four algorithms from health systems perspective were performed: 1) Determine® and if positive, then Uni-GoldTM (Determine®/Uni-GoldTM); based on current algorithm, 2) Determine® and if positive, then OraQuick® (Determine®/OraQuick®), 3) OraQuick® and if positive, then Determine® (OraQuick®/Determine®), 4) OraQuick® and if positive, then Uni-GoldTM (OraQuick®/Uni-GoldTM). This information was then used to construct a model using a hypothetical population of 5,000 persons with varying prevalence of HIV infection from 1–30%. Results 4,458 participants received both a Determine® and OraQuick® test. The sensitivity and specificity of the OraQuick® test were 98.7 (95%CI, 97.5–99.4) and 99.8 (95%CI, 99.6–99.9), respectively when compared to HIV positive serostatus. The average unit costs per algorithm were US$3.76, US$4.03, US$7.35, and US$7.67 for Determine®/Uni-GoldTM, Determine®/OraQuick®, OraQuick®/Determine®, and OraQuick®/Uni-GoldTM, respectively, for an HIV prevalence of 15%. Conclusions An alternative HIV testing algorithm could include OraQuick® test which had a high sensitivity and specificity. The current Determine®/Uni-GoldTM testing algorithm is the least expensive when compared to Determine®/OraQuick®, OraQuick®/Determine®, and OraQuick®/Uni-GoldTM in the Zambian setting. From our field experience, oral fluid based testing offers many advantages over blood-based testing, especially with self testing on the horizon. PMID:22871032

A Seed-Based Plant Propagation Algorithm: The Feeding Station Model

PubMed Central

Salhi, Abdellah

2015-01-01

The seasonal production of fruit and seeds is akin to opening a feeding station, such as a restaurant. Agents coming to feed on the fruit are like customers attending the restaurant; they arrive at a certain rate and get served at a certain rate following some appropriate processes. The same applies to birds and animals visiting and feeding on ripe fruit produced by plants such as the strawberry plant. This phenomenon underpins the seed dispersion of the plants. Modelling it as a queuing process results in a seed-based search/optimisation algorithm. This variant of the Plant Propagation Algorithm is described, analysed, tested on nontrivial problems, and compared with well established algorithms. The results are included. PMID:25821858

Constellation design with geometric and probabilistic shaping

NASA Astrophysics Data System (ADS)

Zhang, Shaoliang; Yaman, Fatih

2018-02-01

A systematic study, including theory, simulation and experiments, is carried out to review the generalized pairwise optimization algorithm for designing optimized constellation. In order to verify its effectiveness, the algorithm is applied in three testing cases: 2-dimensional 8 quadrature amplitude modulation (QAM), 4-dimensional set-partitioning QAM, and probabilistic-shaped (PS) 32QAM. The results suggest that geometric shaping can work together with PS to further bridge the gap toward the Shannon limit.

Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

PubMed Central

Qian, Jiuchao; Pei, Ling; Ma, Jiabin; Ying, Rendong; Liu, Peilin

2015-01-01

The paper presents a hybrid indoor positioning solution based on a pedestrian dead reckoning (PDR) approach using built-in sensors on a smartphone. To address the challenges of flexible and complex contexts of carrying a phone while walking, a robust step detection algorithm based on motion-awareness has been proposed. Given the fact that step length is influenced by different motion states, an adaptive step length estimation algorithm based on motion recognition is developed. Heading estimation is carried out by an attitude acquisition algorithm, which contains a two-phase filter to mitigate the distortion of magnetic anomalies. In order to estimate the heading for an unconstrained smartphone, principal component analysis (PCA) of acceleration is applied to determine the offset between the orientation of smartphone and the actual heading of a pedestrian. Moreover, a particle filter with vector graph assisted particle weighting is introduced to correct the deviation in step length and heading estimation. Extensive field tests, including four contexts of carrying a phone, have been conducted in an office building to verify the performance of the proposed algorithm. Test results show that the proposed algorithm can achieve sub-meter mean error in all contexts. PMID:25738763

Multisensory System for Fruit Harvesting Robots. Experimental Testing in Natural Scenarios and with Different Kinds of Crops

PubMed Central

Fernández, Roemi; Salinas, Carlota; Montes, Héctor; Sarria, Javier

2014-01-01

The motivation of this research was to explore the feasibility of detecting and locating fruits from different kinds of crops in natural scenarios. To this end, a unique, modular and easily adaptable multisensory system and a set of associated pre-processing algorithms are proposed. The offered multisensory rig combines a high resolution colour camera and a multispectral system for the detection of fruits, as well as for the discrimination of the different elements of the plants, and a Time-Of-Flight (TOF) camera that provides fast acquisition of distances enabling the localisation of the targets in the coordinate space. A controlled lighting system completes the set-up, increasing its flexibility for being used in different working conditions. The pre-processing algorithms designed for the proposed multisensory system include a pixel-based classification algorithm that labels areas of interest that belong to fruits and a registration algorithm that combines the results of the aforementioned classification algorithm with the data provided by the TOF camera for the 3D reconstruction of the desired regions. Several experimental tests have been carried out in outdoors conditions in order to validate the capabilities of the proposed system. PMID:25615730

Application of temporal moments and other signal processing algorithms to analysis of ultrasonic signals through melting wax

DOE PAGES

Lau, Sarah J.; Moore, David G.; Stair, Sarah L.; ...

2016-01-01

Ultrasonic analysis is being explored as a way to capture events during melting of highly dispersive wax. Typical events include temperature changes in the material, phase transition of the material, surface flows and reformations, and void filling as the material melts. Melt tests are performed with wax to evaluate the usefulness of different signal processing algorithms in capturing event data. Several algorithm paths are being pursued. The first looks at changes in the velocity of the signal through the material. This is only appropriate when the changes from one ultrasonic signal to the next can be represented by a linearmore » relationship, which is not always the case. The second tracks changes in the frequency content of the signal. The third algorithm tracks changes in the temporal moments of a signal over a full test. This method does not require that the changes in the signal be represented by a linear relationship, but attaching changes in the temporal moments to physical events can be difficult. This study describes the algorithm paths applied to experimental data from ultrasonic signals as wax melts and explores different ways to display the results.« less

Automatic detection of zebra crossings from mobile LiDAR data

NASA Astrophysics Data System (ADS)

Riveiro, B.; González-Jorge, H.; Martínez-Sánchez, J.; Díaz-Vilariño, L.; Arias, P.

2015-07-01

An algorithm for the automatic detection of zebra crossings from mobile LiDAR data is developed and tested to be applied for road management purposes. The algorithm consists of several subsequent processes starting with road segmentation by performing a curvature analysis for each laser cycle. Then, intensity images are created from the point cloud using rasterization techniques, in order to detect zebra crossing using the Standard Hough Transform and logical constrains. To optimize the results, image processing algorithms are applied to the intensity images from the point cloud. These algorithms include binarization to separate the painting area from the rest of the pavement, median filtering to avoid noisy points, and mathematical morphology to fill the gaps between the pixels in the border of white marks. Once the road marking is detected, its position is calculated. This information is valuable for inventorying purposes of road managers that use Geographic Information Systems. The performance of the algorithm has been evaluated over several mobile LiDAR strips accounting for a total of 30 zebra crossings. That test showed a completeness of 83%. Non-detected marks mainly come from painting deterioration of the zebra crossing or by occlusions in the point cloud produced by other vehicles on the road.

Performance Analysis of a Hardware Implemented Complex Signal Kurtosis Radio-Frequency Interference Detector

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark

2016-01-01

Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves.

Gaussian Discriminant Analysis for Optimal Delineation of Mild Cognitive Impairment in Alzheimer's Disease.

PubMed

Fang, Chen; Li, Chunfei; Cabrerizo, Mercedes; Barreto, Armando; Andrian, Jean; Rishe, Naphtali; Loewenstein, David; Duara, Ranjan; Adjouadi, Malek

2018-04-12

Over the past few years, several approaches have been proposed to assist in the early diagnosis of Alzheimer's disease (AD) and its prodromal stage of mild cognitive impairment (MCI). Using multimodal biomarkers for this high-dimensional classification problem, the widely used algorithms include Support Vector Machines (SVM), Sparse Representation-based classification (SRC), Deep Belief Networks (DBN) and Random Forest (RF). These widely used algorithms continue to yield unsatisfactory performance for delineating the MCI participants from the cognitively normal control (CN) group. A novel Gaussian discriminant analysis-based algorithm is thus introduced to achieve a more effective and accurate classification performance than the aforementioned state-of-the-art algorithms. This study makes use of magnetic resonance imaging (MRI) data uniquely as input to two separate high-dimensional decision spaces that reflect the structural measures of the two brain hemispheres. The data used include 190 CN, 305 MCI and 133 AD subjects as part of the AD Big Data DREAM Challenge #1. Using 80% data for a 10-fold cross-validation, the proposed algorithm achieved an average F1 score of 95.89% and an accuracy of 96.54% for discriminating AD from CN; and more importantly, an average F1 score of 92.08% and an accuracy of 90.26% for discriminating MCI from CN. Then, a true test was implemented on the remaining 20% held-out test data. For discriminating MCI from CN, an accuracy of 80.61%, a sensitivity of 81.97% and a specificity of 78.38% were obtained. These results show significant improvement over existing algorithms for discriminating the subtle differences between MCI participants and the CN group.

Metaheuristic optimisation methods for approximate solving of singular boundary value problems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Yadav, Neha; Gao, Kaizhou; Su, Rong

2017-07-01

This paper presents a novel approximation technique based on metaheuristics and weighted residual function (WRF) for tackling singular boundary value problems (BVPs) arising in engineering and science. With the aid of certain fundamental concepts of mathematics, Fourier series expansion, and metaheuristic optimisation algorithms, singular BVPs can be approximated as an optimisation problem with boundary conditions as constraints. The target is to minimise the WRF (i.e. error function) constructed in approximation of BVPs. The scheme involves generational distance metric for quality evaluation of the approximate solutions against exact solutions (i.e. error evaluator metric). Four test problems including two linear and two non-linear singular BVPs are considered in this paper to check the efficiency and accuracy of the proposed algorithm. The optimisation task is performed using three different optimisers including the particle swarm optimisation, the water cycle algorithm, and the harmony search algorithm. Optimisation results obtained show that the suggested technique can be successfully applied for approximate solving of singular BVPs.

Performance Analysis of a Hardware Implemented Complex Signal Kurtosis Radio-Frequency Interference Detector

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark

2016-01-01

Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves. The complex kurtosis algorithm has the potential to reduce data rate due to onboard processing in addition to improving RFI detection performance.

Different CT perfusion algorithms in the detection of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage.

PubMed

Cremers, Charlotte H P; Dankbaar, Jan Willem; Vergouwen, Mervyn D I; Vos, Pieter C; Bennink, Edwin; Rinkel, Gabriel J E; Velthuis, Birgitta K; van der Schaaf, Irene C

2015-05-01

Tracer delay-sensitive perfusion algorithms in CT perfusion (CTP) result in an overestimation of the extent of ischemia in thromboembolic stroke. In diagnosing delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH), delayed arrival of contrast due to vasospasm may also overestimate the extent of ischemia. We investigated the diagnostic accuracy of tracer delay-sensitive and tracer delay-insensitive algorithms for detecting DCI. From a prospectively collected series of aSAH patients admitted between 2007-2011, we included patients with any clinical deterioration other than rebleeding within 21 days after SAH who underwent NCCT/CTP/CTA imaging. Causes of clinical deterioration were categorized into DCI and no DCI. CTP maps were calculated with tracer delay-sensitive and tracer delay-insensitive algorithms and were visually assessed for the presence of perfusion deficits by two independent observers with different levels of experience. The diagnostic value of both algorithms was calculated for both observers. Seventy-one patients were included. For the experienced observer, the positive predictive values (PPVs) were 0.67 for the delay-sensitive and 0.66 for the delay-insensitive algorithm, and the negative predictive values (NPVs) were 0.73 and 0.74. For the less experienced observer, PPVs were 0.60 for both algorithms, and NPVs were 0.66 for the delay-sensitive and 0.63 for the delay-insensitive algorithm. Test characteristics are comparable for tracer delay-sensitive and tracer delay-insensitive algorithms for the visual assessment of CTP in diagnosing DCI. This indicates that both algorithms can be used for this purpose.

Use of the preconditioned conjugate gradient algorithm as a generic solver for mixed-model equations in animal breeding applications.

PubMed

Tsuruta, S; Misztal, I; Strandén, I

2001-05-01

Utility of the preconditioned conjugate gradient algorithm with a diagonal preconditioner for solving mixed-model equations in animal breeding applications was evaluated with 16 test problems. The problems included single- and multiple-trait analyses, with data on beef, dairy, and swine ranging from small examples to national data sets. Multiple-trait models considered low and high genetic correlations. Convergence was based on relative differences between left- and right-hand sides. The ordering of equations was fixed effects followed by random effects, with no special ordering within random effects. The preconditioned conjugate gradient program implemented with double precision converged for all models. However, when implemented in single precision, the preconditioned conjugate gradient algorithm did not converge for seven large models. The preconditioned conjugate gradient and successive overrelaxation algorithms were subsequently compared for 13 of the test problems. The preconditioned conjugate gradient algorithm was easy to implement with the iteration on data for general models. However, successive overrelaxation requires specific programming for each set of models. On average, the preconditioned conjugate gradient algorithm converged in three times fewer rounds of iteration than successive overrelaxation. With straightforward implementations, programs using the preconditioned conjugate gradient algorithm may be two or more times faster than those using successive overrelaxation. However, programs using the preconditioned conjugate gradient algorithm would use more memory than would comparable implementations using successive overrelaxation. Extensive optimization of either algorithm can influence rankings. The preconditioned conjugate gradient implemented with iteration on data, a diagonal preconditioner, and in double precision may be the algorithm of choice for solving mixed-model equations when sufficient memory is available and ease of implementation is essential.

Inter-method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-retest Data

PubMed Central

Buckler, Andrew J.; Danagoulian, Jovanna; Johnson, Kjell; Peskin, Adele; Gavrielides, Marios A.; Petrick, Nicholas; Obuchowski, Nancy A.; Beaumont, Hubert; Hadjiiski, Lubomir; Jarecha, Rudresh; Kuhnigk, Jan-Martin; Mantri, Ninad; McNitt-Gray, Michael; Moltz, Jan Hendrik; Nyiri, Gergely; Peterson, Sam; Tervé, Pierre; Tietjen, Christian; von Lavante, Etienne; Ma, Xiaonan; Pierre, Samantha St.; Athelogou, Maria

2015-01-01

Rationale and objectives Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semi-automated lung tumor volume measurement algorithms from clinical thoracic CT datasets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) CT Volumetry Profile. Materials and Methods Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. Results Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility determined in three partitions and found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters above 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not just in overall volume but in detail. Conclusions Nine of the twelve participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the current study was not designed to explicitly evaluate algorithm Profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes above 10 mm. No partition of the algorithms were able to meet the QIBA requirements for interchangeability down to 10 mm, though the partition comprised of the best performing algorithms did meet this requirement above a tumor size of approximately 40 mm. PMID:26376841

A Modified MinMax k-Means Algorithm Based on PSO.

PubMed

Wang, Xiaoyan; Bai, Yanping

The MinMax k -means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical framework is given. Such framework extends the MinMax k -means to automatically adapt the exponent parameter to the data set. It has been believed that if the maximum exponent parameter has been set, then the programme can reach the lowest intraclustering errors. However, our experiments show that this is not always correct. In this paper, we modified the MinMax k -means algorithm by PSO to determine the proper values of parameters which can subject the algorithm to attain the lowest clustering errors. The proposed clustering method is tested on some favorite data sets in several different initial situations and is compared to the k -means algorithm and the original MinMax k -means algorithm. The experimental results indicate that our proposed algorithm can reach the lowest clustering errors automatically.

TPS In-Flight Health Monitoring Project Progress Report

NASA Technical Reports Server (NTRS)

Kostyk, Chris; Richards, Lance; Hudston, Larry; Prosser, William

2007-01-01

Progress in the development of new thermal protection systems (TPS) is reported. New approaches use embedded lightweight, sensitive, fiber optic strain and temperature sensors within the TPS. Goals of the program are to develop and demonstrate a prototype TPS health monitoring system, develop a thermal-based damage detection algorithm, characterize limits of sensor/system performance, and develop ea methodology transferable to new designs of TPS health monitoring systems. Tasks completed during the project helped establish confidence in understanding of both test setup and the model and validated system/sensor performance in a simple TPS structure. Other progress included complete initial system testing, commencement of the algorithm development effort, generation of a damaged thermal response characteristics database, initial development of a test plan for integration testing of proven FBG sensors in simple TPS structure, and development of partnerships to apply the technology.

Evaluation of odometry algorithm performances using a railway vehicle dynamic model

NASA Astrophysics Data System (ADS)

Allotta, B.; Pugi, L.; Ridolfi, A.; Malvezzi, M.; Vettori, G.; Rindi, A.

2012-05-01

In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink™, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances.

Comparative evaluation of the Bio-Rad Geenius HIV-1/2 Confirmatory Assay and the Bio-Rad Multispot HIV-1/2 Rapid Test as an alternative differentiation assay for CLSI M53 algorithm-I.

PubMed

Malloch, L; Kadivar, K; Putz, J; Levett, P N; Tang, J; Hatchette, T F; Kadkhoda, K; Ng, D; Ho, J; Kim, J

2013-12-01

The CLSI-M53-A, Criteria for Laboratory Testing and Diagnosis of Human Immunodeficiency Virus (HIV) Infection; Approved Guideline includes an algorithm in which samples that are reactive on a 4th generation EIA screen proceed to a supplemental assay that is able to confirm and differentiate between antibodies to HIV-1 and HIV-2. The recently CE-marked Bio-Rad Geenius HIV-1/2 Confirmatory Assay was evaluated as an alternative to the FDA-approved Bio-Rad Multispot HIV-1/HIV-2 Rapid Test which has been previously validated for use in this new algorithm. This study used reference samples submitted to the Canadian - NLHRS and samples from commercial sources. Data was tabulated in 2×2 tables for statistical analysis; sensitivity, specificity, predictive values, kappa and likelihood ratios. The overall performance of the Geenius and Multispot was very high; sensitivity (100%, 100%), specificity (96.3%, 99.1%), positive (45.3, 181) and negative (0, 0) likelihood ratios respectively, high kappa (0.96) and low bias index (0.0068). The ability to differentiate HIV-1 (99.2%, 100%) and HIV-2 (98.1%, 98.1%) Ab was also very high. The Bio-Rad Geenius HIV-1/2 Confirmatory Assay is a suitable alternative to the validated Multispot for use in the second stage of CLSI M53 algorithm-I. The Geenius has additional features including traceability and sample and cassette barcoding that improve the quality management/assurance of HIV testing. It is anticipated that the CLSI M53 guideline and assays such as the Geenius will reduce the number of indeterminate test results previously associated with the HIV-1 WB and improve the ability to differentiate HIV-2 infections. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

NASA Technical Reports Server (NTRS)

Trevino, Luis; Patterson, Jonathan; Teare, David; Johnson, Stephen

2015-01-01

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes.

Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms.

PubMed

Arts, E E A; Popa, C D; Den Broeder, A A; Donders, R; Sandoo, A; Toms, T; Rollefstad, S; Ikdahl, E; Semb, A G; Kitas, G D; Van Riel, P L C M; Fransen, J

2016-04-01

Predictive performance of cardiovascular disease (CVD) risk calculators appears suboptimal in rheumatoid arthritis (RA). A disease-specific CVD risk algorithm may improve CVD risk prediction in RA. The objectives of this study are to adapt the Systematic COronary Risk Evaluation (SCORE) algorithm with determinants of CVD risk in RA and to assess the accuracy of CVD risk prediction calculated with the adapted SCORE algorithm. Data from the Nijmegen early RA inception cohort were used. The primary outcome was first CVD events. The SCORE algorithm was recalibrated by reweighing included traditional CVD risk factors and adapted by adding other potential predictors of CVD. Predictive performance of the recalibrated and adapted SCORE algorithms was assessed and the adapted SCORE was externally validated. Of the 1016 included patients with RA, 103 patients experienced a CVD event. Discriminatory ability was comparable across the original, recalibrated and adapted SCORE algorithms. The Hosmer-Lemeshow test results indicated that all three algorithms provided poor model fit (p<0.05) for the Nijmegen and external validation cohort. The adapted SCORE algorithm mainly improves CVD risk estimation in non-event cases and does not show a clear advantage in reclassifying patients with RA who develop CVD (event cases) into more appropriate risk groups. This study demonstrates for the first time that adaptations of the SCORE algorithm do not provide sufficient improvement in risk prediction of future CVD in RA to serve as an appropriate alternative to the original SCORE. Risk assessment using the original SCORE algorithm may underestimate CVD risk in patients with RA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A survey of upwind methods for flows with equilibrium and non-equilibrium chemistry and thermodynamics

NASA Technical Reports Server (NTRS)

Grossman, B.; Garrett, J.; Cinnella, P.

1989-01-01

Several versions of flux-vector split and flux-difference split algorithms were compared with regard to general applicability and complexity. Test computations were performed using curve-fit equilibrium air chemistry for an M = 5 high-temperature inviscid flow over a wedge, and an M = 24.5 inviscid flow over a blunt cylinder for test computations; for these cases, little difference in accuracy was found among the versions of the same flux-split algorithm. For flows with nonequilibrium chemistry, the effects of the thermodynamic model on the development of flux-vector split and flux-difference split algorithms were investigated using an equilibrium model, a general nonequilibrium model, and a simplified model based on vibrational relaxation. Several numerical examples are presented, including nonequilibrium air chemistry in a high-temperature shock tube and nonequilibrium hydrogen-air chemistry in a supersonic diffuser.

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

NASA Astrophysics Data System (ADS)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.

Adaptive DFT-based Interferometer Fringe Tracking

NASA Technical Reports Server (NTRS)

Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

2004-01-01

An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA) observatory at Mt. Hopkins, Arizona. The system can minimize the optical path differences (OPDs) for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse.

Adaptive DIT-Based Fringe Tracking and Prediction at IOTA

NASA Technical Reports Server (NTRS)

Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

2004-01-01

An automatic fringe tracking system has been developed and implemented at the Infrared Optical Telescope Array (IOTA). In testing during May 2002, the system successfully minimized the optical path differences (OPDs) for all three baselines at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHZ PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. Preliminary analysis on an extension of this algorithm indicates a potential for predictive tracking, although at present, real-time implementation of this extension would require significantly more computational capacity.

Testing an earthquake prediction algorithm

USGS Publications Warehouse

Kossobokov, V.G.; Healy, J.H.; Dewey, J.W.

1997-01-01

A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known as M8. The M8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1995-01-01

An investigation of the influence of stratospheric aerosol on the performance of the atmospheric correction algorithm was carried out. The results indicate how the performance of the algorithm is degraded if the stratospheric aerosol is ignored. Use of the MODIS 1380 nm band to effect a correction for stratospheric aerosols was also studied. The development of a multi-layer Monte Carlo radiative transfer code that includes polarization by molecular and aerosol scattering and wind-induced sea surface roughness has been completed. Comparison tests with an existing two-layer successive order of scattering code suggests that both codes are capable of producing top-of-atmosphere radiances with errors usually less than 0.1 percent. An initial set of simulations to study the effects of ignoring the polarization of the the ocean-atmosphere light field, in both the development of the atmospheric correction algorithm and the generation of the lookup tables used for operation of the algorithm, have been completed. An algorithm was developed that can be used to invert the radiance exiting the top and bottom of the atmosphere to yield the columnar optical properties of the atmospheric aerosol under clear sky conditions over the ocean, for aerosol optical thicknesses as large as 2. The algorithm is capable of retrievals with such large optical thicknesses because all significant orders of multiple scattering are included.

CREKID: A computer code for transient, gas-phase combustion of kinetics

NASA Technical Reports Server (NTRS)

Pratt, D. T.; Radhakrishnan, K.

1984-01-01

A new algorithm was developed for fast, automatic integration of chemical kinetic rate equations describing homogeneous, gas-phase combustion at constant pressure. Particular attention is paid to the distinguishing physical and computational characteristics of the induction, heat-release and equilibration regimes. The two-part predictor-corrector algorithm, based on an exponentially-fitted trapezoidal rule, includes filtering of ill-posed initial conditions, automatic selection of Newton-Jacobi or Newton iteration for convergence to achieve maximum computational efficiency while observing a prescribed error tolerance. The new algorithm was found to compare favorably with LSODE on two representative test problems drawn from combustion kinetics.

Algorithm for loading shot noise microbunching in multi-dimensional, free-electron laser simulation codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fawley, William M.

We discuss the underlying reasoning behind and the details of the numerical algorithm used in the GINGER free-electron laser(FEL) simulation code to load the initial shot noise microbunching on the electron beam. In particular, we point out that there are some additional subtleties which must be followed for multi-dimensional codes which are not necessary for one-dimensional formulations. Moreover, requiring that the higher harmonics of the microbunching also be properly initialized with the correct statistics leads to additional complexities. We present some numerical results including the predicted incoherent, spontaneous emission as tests of the shot noise algorithm's correctness.

New human-centered linear and nonlinear motion cueing algorithms for control of simulator motion systems

NASA Astrophysics Data System (ADS)

Telban, Robert J.

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach are less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.

Progress on the development of automated data analysis algorithms and software for ultrasonic inspection of composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Coughlin, Chris; Forsyth, David S.; Welter, John T.

2014-02-01

Progress is presented on the development and implementation of automated data analysis (ADA) software to address the burden in interpreting ultrasonic inspection data for large composite structures. The automated data analysis algorithm is presented in detail, which follows standard procedures for analyzing signals for time-of-flight indications and backwall amplitude dropout. ADA processing results are presented for test specimens that include inserted materials and discontinuities produced under poor manufacturing conditions.

Adaption of unstructured meshes using node movement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carpenter, J.G.; McRae, V.D.S.

1996-12-31

The adaption algorithm of Benson and McRae is modified for application to unstructured grids. The weight function generation was modified for application to unstructured grids and movement was limited to prevent cross over. A NACA 0012 airfoil is used as a test case to evaluate the modified algorithm when applied to unstructured grids and compared to results obtained by Warren. An adaptive mesh solution for the Sudhoo and Hall four element airfoil is included as a demonstration case.

Developing a New Wireless Sensor Network Platform and Its Application in Precision Agriculture

PubMed Central

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of “smart dust” offer great advantages due to their small size, low power consumption, easy integration and support for “green” applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network. PMID:22346622

Developing a new wireless sensor network platform and its application in precision agriculture.

PubMed

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of "smart dust" offer great advantages due to their small size, low power consumption, easy integration and support for "green" applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network.

Comparison of edge analysis techniques for the determination of the MTF of digital radiographic systems.

PubMed

Samei, Ehsan; Buhr, Egbert; Granfors, Paul; Vandenbroucke, Dirk; Wang, Xiaohui

2005-08-07

The modulation transfer function (MTF) is well established as a metric to characterize the resolution performance of a digital radiographic system. Implemented by various laboratories, the edge technique is currently the most widespread approach to measure the MTF. However, there can be differences in the results attributed to differences in the analysis technique employed. The objective of this study was to determine whether comparable results can be obtained from different algorithms processing identical images representative of those of current digital radiographic systems. Five laboratories participated in a round-robin evaluation of six different algorithms including one prescribed in the International Electrotechnical Commission (IEC) 62220-1 standard. The algorithms were applied to two synthetic and 12 real edge images from different digital radiographic systems including CR, and direct- and indirect-conversion detector systems. The results were analysed in terms of variability as well as accuracy of the resulting presampled MTFs. The results indicated that differences between the individual MTFs and the mean MTF were largely below 0.02. In the case of the two simulated edge images, all algorithms yielded similar results within 0.01 of the expected true MTF. The findings indicated that all algorithms tested in this round-robin evaluation, including the IEC-prescribed algorithm, were suitable for accurate MTF determination from edge images, provided the images are not excessively noisy. The agreement of the MTF results was judged sufficient for the measurement of the MTF necessary for the determination of the DQE.

Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1993-01-01

The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.

Scalable and portable visualization of large atomistic datasets

NASA Astrophysics Data System (ADS)

Sharma, Ashish; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2004-10-01

A scalable and portable code named Atomsviewer has been developed to interactively visualize a large atomistic dataset consisting of up to a billion atoms. The code uses a hierarchical view frustum-culling algorithm based on the octree data structure to efficiently remove atoms outside of the user's field-of-view. Probabilistic and depth-based occlusion-culling algorithms then select atoms, which have a high probability of being visible. Finally a multiresolution algorithm is used to render the selected subset of visible atoms at varying levels of detail. Atomsviewer is written in C++ and OpenGL, and it has been tested on a number of architectures including Windows, Macintosh, and SGI. Atomsviewer has been used to visualize tens of millions of atoms on a standard desktop computer and, in its parallel version, up to a billion atoms. Program summaryTitle of program: Atomsviewer Catalogue identifier: ADUM Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUM Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: 2.4 GHz Pentium 4/Xeon processor, professional graphics card; Apple G4 (867 MHz)/G5, professional graphics card Operating systems under which the program has been tested: Windows 2000/XP, Mac OS 10.2/10.3, SGI IRIX 6.5 Programming languages used: C++, C and OpenGL Memory required to execute with typical data: 1 gigabyte of RAM High speed storage required: 60 gigabytes No. of lines in the distributed program including test data, etc.: 550 241 No. of bytes in the distributed program including test data, etc.: 6 258 245 Number of bits in a word: Arbitrary Number of processors used: 1 Has the code been vectorized or parallelized: No Distribution format: tar gzip file Nature of physical problem: Scientific visualization of atomic systems Method of solution: Rendering of atoms using computer graphic techniques, culling algorithms for data minimization, and levels-of-detail for minimal rendering Restrictions on the complexity of the problem: None Typical running time: The program is interactive in its execution Unusual features of the program: None References: The conceptual foundation and subsequent implementation of the algorithms are found in [A. Sharma, A. Nakano, R.K. Kalia, P. Vashishta, S. Kodiyalam, P. Miller, W. Zhao, X.L. Liu, T.J. Campbell, A. Haas, Presence—Teleoperators and Virtual Environments 12 (1) (2003)].

A generalised significance test for individual communities in networks.

PubMed

Kojaku, Sadamori; Masuda, Naoki

2018-05-09

Many empirical networks have community structure, in which nodes are densely interconnected within each community (i.e., a group of nodes) and sparsely across different communities. Like other local and meso-scale structure of networks, communities are generally heterogeneous in various aspects such as the size, density of edges, connectivity to other communities and significance. In the present study, we propose a method to statistically test the significance of individual communities in a given network. Compared to the previous methods, the present algorithm is unique in that it accepts different community-detection algorithms and the corresponding quality function for single communities. The present method requires that a quality of each community can be quantified and that community detection is performed as optimisation of such a quality function summed over the communities. Various community detection algorithms including modularity maximisation and graph partitioning meet this criterion. Our method estimates a distribution of the quality function for randomised networks to calculate a likelihood of each community in the given network. We illustrate our algorithm by synthetic and empirical networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lau, Sarah J.; Moore, David G.; Stair, Sarah L.

Ultrasonic analysis is being explored as a way to capture events during melting of highly dispersive wax. Typical events include temperature changes in the material, phase transition of the material, surface flows and reformations, and void filling as the material melts. Melt tests are performed with wax to evaluate the usefulness of different signal processing algorithms in capturing event data. Several algorithm paths are being pursued. The first looks at changes in the velocity of the signal through the material. This is only appropriate when the changes from one ultrasonic signal to the next can be represented by a linearmore » relationship, which is not always the case. The second tracks changes in the frequency content of the signal. The third algorithm tracks changes in the temporal moments of a signal over a full test. This method does not require that the changes in the signal be represented by a linear relationship, but attaching changes in the temporal moments to physical events can be difficult. This study describes the algorithm paths applied to experimental data from ultrasonic signals as wax melts and explores different ways to display the results.« less

Novel trace chemical detection algorithms: a comparative study

NASA Astrophysics Data System (ADS)

Raz, Gil; Murphy, Cara; Georgan, Chelsea; Greenwood, Ross; Prasanth, R. K.; Myers, Travis; Goyal, Anish; Kelley, David; Wood, Derek; Kotidis, Petros

2017-05-01

Algorithms for standoff detection and estimation of trace chemicals in hyperspectral images in the IR band are a key component for a variety of applications relevant to law-enforcement and the intelligence communities. Performance of these methods is impacted by the spectral signature variability due to presence of contaminants, surface roughness, nonlinear dependence on abundances as well as operational limitations on the compute platforms. In this work we provide a comparative performance and complexity analysis of several classes of algorithms as a function of noise levels, error distribution, scene complexity, and spatial degrees of freedom. The algorithm classes we analyze and test include adaptive cosine estimator (ACE and modifications to it), compressive/sparse methods, Bayesian estimation, and machine learning. We explicitly call out the conditions under which each algorithm class is optimal or near optimal as well as their built-in limitations and failure modes.

Water flow algorithm decision support tool for travelling salesman problem

NASA Astrophysics Data System (ADS)

Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd

2016-08-01

This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.

SU-F-T-20: Novel Catheter Lumen Recognition Algorithm for Rapid Digitization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dise, J; McDonald, D; Ashenafi, M

Purpose: Manual catheter recognition remains a time-consuming aspect of high-dose-rate brachytherapy (HDR) treatment planning. In this work, a novel catheter lumen recognition algorithm was created for accurate and rapid digitization. Methods: MatLab v8.5 was used to create the catheter recognition algorithm. Initially, the algorithm searches the patient CT dataset using an intensity based k-means filter designed to locate catheters. Once the catheters have been located, seed points are manually selected to initialize digitization of each catheter. From each seed point, the algorithm searches locally in order to automatically digitize the remaining catheter. This digitization is accomplished by finding pixels withmore » similar image curvature and divergence parameters compared to the seed pixel. Newly digitized pixels are treated as new seed positions, and hessian image analysis is used to direct the algorithm toward neighboring catheter pixels, and to make the algorithm insensitive to adjacent catheters that are unresolvable on CT, air pockets, and high Z artifacts. The algorithm was tested using 11 HDR treatment plans, including the Syed template, tandem and ovoid applicator, and multi-catheter lung brachytherapy. Digitization error was calculated by comparing manually determined catheter positions to those determined by the algorithm. Results: he digitization error was 0.23 mm ± 0.14 mm axially and 0.62 mm ± 0.13 mm longitudinally at the tip. The time of digitization, following initial seed placement was less than 1 second per catheter. The maximum total time required to digitize all tested applicators was 4 minutes (Syed template with 15 needles). Conclusion: This algorithm successfully digitizes HDR catheters for a variety of applicators with or without CT markers. The minimal axial error demonstrates the accuracy of the algorithm, and its insensitivity to image artifacts and challenging catheter positioning. Future work to automatically place initial seed positions would improve the algorithm speed.« less

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

On the robustness of EC-PC spike detection method for online neural recording.

PubMed

Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

2014-09-30

Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

Robust Segmentation of Overlapping Cells in Histopathology Specimens Using Parallel Seed Detection and Repulsive Level Set

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Automated image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of breast cancer. Automated segmentation of the cells comprising imaged tissue microarrays (TMA) is a prerequisite for any subsequent quantitative analysis. Unfortunately, crowding and overlapping of cells present significant challenges for most traditional segmentation algorithms. In this paper, we propose a novel algorithm which can reliably separate touching cells in hematoxylin stained breast TMA specimens which have been acquired using a standard RGB camera. The algorithm is composed of two steps. It begins with a fast, reliable object center localization approach which utilizes single-path voting followed by mean-shift clustering. Next, the contour of each cell is obtained using a level set algorithm based on an interactive model. We compared the experimental results with those reported in the most current literature. Finally, performance was evaluated by comparing the pixel-wise accuracy provided by human experts with that produced by the new automated segmentation algorithm. The method was systematically tested on 234 image patches exhibiting dense overlap and containing more than 2200 cells. It was also tested on whole slide images including blood smears and tissue microarrays containing thousands of cells. Since the voting step of the seed detection algorithm is well suited for parallelization, a parallel version of the algorithm was implemented using graphic processing units (GPU) which resulted in significant speed-up over the C/C++ implementation. PMID:22167559

An Environmental for Hardware-in-the-Loop Formation Navigation and Control

NASA Technical Reports Server (NTRS)

Burns, Rich; Naasz, Bo; Gaylor, Dave; Higinbotham, John

2004-01-01

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Test Bed (FFTB) at NASA Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the inclusion of GPS receiver hardware in the simulation loop. Support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented.

Threshold matrix for digital halftoning by genetic algorithm optimization

NASA Astrophysics Data System (ADS)

Alander, Jarmo T.; Mantere, Timo J.; Pyylampi, Tero

1998-10-01

Digital halftoning is used both in low and high resolution high quality printing technologies. Our method is designed to be mainly used for low resolution ink jet marking machines to produce both gray tone and color images. The main problem with digital halftoning is pink noise caused by the human eye's visual transfer function. To compensate for this the random dot patterns used are optimized to contain more blue than pink noise. Several such dot pattern generator threshold matrices have been created automatically by using genetic algorithm optimization, a non-deterministic global optimization method imitating natural evolution and genetics. A hybrid of genetic algorithm with a search method based on local backtracking was developed together with several fitness functions evaluating dot patterns for rectangular grids. By modifying the fitness function, a family of dot generators results, each with its particular statistical features. Several versions of genetic algorithms, backtracking and fitness functions were tested to find a reasonable combination. The generated threshold matrices have been tested by simulating a set of test images using the Khoros image processing system. Even though the work was focused on developing low resolution marking technology, the resulting family of dot generators can be applied also in other halftoning application areas including high resolution printing technology.

Diagnosing acute HIV infection: The performance of quantitative HIV-1 RNA testing (viral load) in the 2014 laboratory testing algorithm.

PubMed

Wu, Hsiu; Cohen, Stephanie E; Westheimer, Emily; Gay, Cynthia L; Hall, Laura; Rose, Charles; Hightow-Weidman, Lisa B; Gose, Severin; Fu, Jie; Peters, Philip J

2017-08-01

New recommendations for laboratory diagnosis of HIV infection in the United States were published in 2014. The updated testing algorithm includes a qualitative HIV-1 RNA assay to resolve discordant immunoassay results and to identify acute HIV-1 infection (AHI). The qualitative HIV-1 RNA assay is not widely available; therefore, we evaluated the performance of a more widely available quantitative HIV-1 RNA assay, viral load, for diagnosing AHI. We determined that quantitative viral loads consistently distinguished AHI from a false-positive immunoassay result. Among 100 study participants with AHI and a viral load result, the estimated geometric mean viral load was 1,377,793copies/mL. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and Testing of Data Mining Algorithms for Earth Observation

NASA Technical Reports Server (NTRS)

Glymour, Clark

2005-01-01

The new algorithms developed under this project included a principled procedure for classification of objects, events or circumstances according to a target variable when a very large number of potential predictor variables is available but the number of cases that can be used for training a classifier is relatively small. These "high dimensional" problems require finding a minimal set of variables -called the Markov Blanket-- sufficient for predicting the value of the target variable. An algorithm, the Markov Blanket Fan Search, was developed, implemented and tested on both simulated and real data in conjunction with a graphical model classifier, which was also implemented. Another algorithm developed and implemented in TETRAD IV for time series elaborated on work by C. Granger and N. Swanson, which in turn exploited some of our earlier work. The algorithms in question learn a linear time series model from data. Given such a time series, the simultaneous residual covariances, after factoring out time dependencies, may provide information about causal processes that occur more rapidly than the time series representation allow, so called simultaneous or contemporaneous causal processes. Working with A. Monetta, a graduate student from Italy, we produced the correct statistics for estimating the contemporaneous causal structure from time series data using the TETRAD IV suite of algorithms. Two economists, David Bessler and Kevin Hoover, have independently published applications using TETRAD style algorithms to the same purpose. These implementations and algorithmic developments were separately used in two kinds of studies of climate data: Short time series of geographically proximate climate variables predicting agricultural effects in California, and longer duration climate measurements of temperature teleconnections.

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

PubMed Central

2014-01-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, H. M. Abdul; Zhu, Feng; Ukkusuri, Satish V.

Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better atmore » higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO 2, NO x, VOC, PM 10) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.« less

Radionuclide identification algorithm for organic scintillator-based radiation portal monitor

NASA Astrophysics Data System (ADS)

Paff, Marc Gerrit; Di Fulvio, Angela; Clarke, Shaun D.; Pozzi, Sara A.

2017-03-01

We have developed an algorithm for on-the-fly radionuclide identification for radiation portal monitors using organic scintillation detectors. The algorithm was demonstrated on experimental data acquired with our pedestrian portal monitor on moving special nuclear material and industrial sources at a purpose-built radiation portal monitor testing facility. The experimental data also included common medical isotopes. The algorithm takes the power spectral density of the cumulative distribution function of the measured pulse height distributions and matches these to reference spectra using a spectral angle mapper. F-score analysis showed that the new algorithm exhibited significant performance improvements over previously implemented radionuclide identification algorithms for organic scintillators. Reliable on-the-fly radionuclide identification would help portal monitor operators more effectively screen out the hundreds of thousands of nuisance alarms they encounter annually due to recent nuclear-medicine patients and cargo containing naturally occurring radioactive material. Portal monitor operators could instead focus on the rare but potentially high impact incidents of nuclear and radiological material smuggling detection for which portal monitors are intended.

Parameter optimization of differential evolution algorithm for automatic playlist generation problem

NASA Astrophysics Data System (ADS)

Alamag, Kaye Melina Natividad B.; Addawe, Joel M.

2017-11-01

With the digitalization of music, the number of collection of music increased largely and there is a need to create lists of music that filter the collection according to user preferences, thus giving rise to the Automatic Playlist Generation Problem (APGP). Previous attempts to solve this problem include the use of search and optimization algorithms. If a music database is very large, the algorithm to be used must be able to search the lists thoroughly taking into account the quality of the playlist given a set of user constraints. In this paper we perform an evolutionary meta-heuristic optimization algorithm, Differential Evolution (DE) using different combination of parameter values and select the best performing set when used to solve four standard test functions. Performance of the proposed algorithm is then compared with normal Genetic Algorithm (GA) and a hybrid GA with Tabu Search. Numerical simulations are carried out to show better results from Differential Evolution approach with the optimized parameter values.

Some aspects of algorithm performance and modeling in transient analysis of structures

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

1981-01-01

The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit algorithms with variable time steps, known as the GEAR package, is described. Four test problems, used for evaluating and comparing various algorithms, were selected and finite-element models of the configurations are described. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system, and a model of the wing of the space shuttle orbiter. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures).

Special-effect edit detection using VideoTrails: a comparison with existing techniques

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

1998-12-01

Video segmentation plays an integral role in many multimedia applications, such as digital libraries, content management systems, and various other video browsing, indexing, and retrieval systems. Many algorithms for segmentation of video have appeared within the past few years. Most of these algorithms perform well on cuts, but yield poor performance on gradual transitions or special effects edits. A complete video segmentation system must also achieve good performance on special effect edit detection. In this paper, we discuss the performance of our Video Trails-based algorithms, with other existing special effect edit-detection algorithms within the literature. Results from experiments testing for the ability to detect edits from TV programs, ranging from commercials to news magazine programs, including diverse special effect edits, which we have introduced.

Conservative algorithms for non-Maxwellian plasma kinetics

DOE PAGES

Le, Hai P.; Cambier, Jean -Luc

2017-12-08

Here, we present a numerical model and a set of conservative algorithms for Non-Maxwellian plasma kinetics with inelastic collisions. These algorithms self-consistently solve for the time evolution of an isotropic electron energy distribution function interacting with an atomic state distribution function of an arbitrary number of levels through collisional excitation, deexcitation, as well as ionization and recombination. Electron-electron collisions, responsible for thermalization of the electron distribution, are also included in the model. The proposed algorithms guarantee mass/charge and energy conservation in a single step, and is applied to the case of non-uniform gridding of the energy axis in the phasemore » space of the electron distribution function. Numerical test cases are shown to demonstrate the accuracy of the method and its conservation properties.« less

An electron tomography algorithm for reconstructing 3D morphology using surface tangents of projected scattering interfaces

NASA Astrophysics Data System (ADS)

Petersen, T. C.; Ringer, S. P.

2010-03-01

Upon discerning the mere shape of an imaged object, as portrayed by projected perimeters, the full three-dimensional scattering density may not be of particular interest. In this situation considerable simplifications to the reconstruction problem are possible, allowing calculations based upon geometric principles. Here we describe and provide an algorithm which reconstructs the three-dimensional morphology of specimens from tilt series of images for application to electron tomography. Our algorithm uses a differential approach to infer the intersection of projected tangent lines with surfaces which define boundaries between regions of different scattering densities within and around the perimeters of specimens. Details of the algorithm implementation are given and explained using reconstruction calculations from simulations, which are built into the code. An experimental application of the algorithm to a nano-sized Aluminium tip is also presented to demonstrate practical analysis for a real specimen. Program summaryProgram title: STOMO version 1.0 Catalogue identifier: AEFS_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2988 No. of bytes in distributed program, including test data, etc.: 191 605 Distribution format: tar.gz Programming language: C/C++ Computer: PC Operating system: Windows XP RAM: Depends upon the size of experimental data as input, ranging from 200 Mb to 1.5 Gb Supplementary material: Sample output files, for the test run provided, are available. Classification: 7.4, 14 External routines: Dev-C++ ( http://www.bloodshed.net/devcpp.html) Nature of problem: Electron tomography of specimens for which conventional back projection may fail and/or data for which there is a limited angular range. The algorithm does not solve the tomographic back-projection problem but rather reconstructs the local 3D morphology of surfaces defined by varied scattering densities. Solution method: Reconstruction using differential geometry applied to image analysis computations. Restrictions: The code has only been tested with square images and has been developed for only single-axis tilting. Running time: For high quality reconstruction, 5-15 min

An extension of the QZ algorithm for solving the generalized matrix eigenvalue problem

NASA Technical Reports Server (NTRS)

Ward, R. C.

1973-01-01

This algorithm is an extension of Moler and Stewart's QZ algorithm with some added features for saving time and operations. Also, some additional properties of the QR algorithm which were not practical to implement in the QZ algorithm can be generalized with the combination shift QZ algorithm. Numerous test cases are presented to give practical application tests for algorithm. Based on results, this algorithm should be preferred over existing algorithms which attempt to solve the class of generalized eigenproblems where both matrices are singular or nearly singular.

In Pursuit of LSST Science Requirements: A Comparison of Photometry Algorithms

NASA Astrophysics Data System (ADS)

Becker, Andrew C.; Silvestri, Nicole M.; Owen, Russell E.; Ivezić, Željko; Lupton, Robert H.

2007-12-01

We have developed an end-to-end photometric data-processing pipeline to compare current photometric algorithms commonly used on ground-based imaging data. This test bed is exceedingly adaptable and enables us to perform many research and development tasks, including image subtraction and co-addition, object detection and measurements, the production of photometric catalogs, and the creation and stocking of database tables with time-series information. This testing has been undertaken to evaluate existing photometry algorithms for consideration by a next-generation image-processing pipeline for the Large Synoptic Survey Telescope (LSST). We outline the results of our tests for four packages: the Sloan Digital Sky Survey's Photo package, DAOPHOT and ALLFRAME, DOPHOT, and two versions of Source Extractor (SExtractor). The ability of these algorithms to perform point-source photometry, astrometry, shape measurements, and star-galaxy separation and to measure objects at low signal-to-noise ratio is quantified. We also perform a detailed crowded-field comparison of DAOPHOT and ALLFRAME, and profile the speed and memory requirements in detail for SExtractor. We find that both DAOPHOT and Photo are able to perform aperture photometry to high enough precision to meet LSST's science requirements, and less adequately at PSF-fitting photometry. Photo performs the best at simultaneous point- and extended-source shape and brightness measurements. SExtractor is the fastest algorithm, and recent upgrades in the software yield high-quality centroid and shape measurements with little bias toward faint magnitudes. ALLFRAME yields the best photometric results in crowded fields.

Influence of aging on thermal and vibratory thresholds of quantitative sensory testing.

PubMed

Lin, Yea-Huey; Hsieh, Song-Chou; Chao, Chi-Chao; Chang, Yang-Chyuan; Hsieh, Sung-Tsang

2005-09-01

Quantitative sensory testing has become a common approach to evaluate thermal and vibratory thresholds in various types of neuropathies. To understand the effect of aging on sensory perception, we measured warm, cold, and vibratory thresholds by performing quantitative sensory testing on a population of 484 normal subjects (175 males and 309 females), aged 48.61 +/- 14.10 (range 20-86) years. Sensory thresholds of the hand and foot were measured with two algorithms: the method of limits (Limits) and the method of level (Level). Thresholds measured by Limits are reaction-time-dependent, while those measured by Level are independent of reaction time. In addition, we explored (1) the correlations of thresholds between these two algorithms, (2) the effect of age on differences in thresholds between algorithms, and (3) differences in sensory thresholds between the two test sites. Age was consistently and significantly correlated with sensory thresholds of all tested modalities measured by both algorithms on multivariate regression analysis compared with other factors, including gender, body height, body weight, and body mass index. When thresholds were plotted against age, slopes differed between sensory thresholds of the hand and those of the foot: for the foot, slopes were steeper compared with those for the hand for each sensory modality. Sensory thresholds of both test sites measured by Level were highly correlated with those measured by Limits, and thresholds measured by Limits were higher than those measured by Level. Differences in sensory thresholds between the two algorithms were also correlated with age: thresholds of the foot were higher than those of the hand for each sensory modality. This difference in thresholds (measured with both Level and Limits) between the hand and foot was also correlated with age. These findings suggest that age is the most significant factor in determining sensory thresholds compared with the other factors of gender and anthropometric parameters, and this provides a foundation for investigating the neurobiologic significance of aging on the processing of sensory stimuli.

Fuzzy Set Methods for Object Recognition in Space Applications

NASA Technical Reports Server (NTRS)

Keller, James M. (Editor)

1992-01-01

Progress on the following four tasks is described: (1) fuzzy set based decision methodologies; (2) membership calculation; (3) clustering methods (including derivation of pose estimation parameters), and (4) acquisition of images and testing of 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.

The recursive maximum likelihood proportion estimator: User's guide and test results

NASA Technical Reports Server (NTRS)

Vanrooy, D. L.

1976-01-01

Implementation of the recursive maximum likelihood proportion estimator is described. A user's guide to programs as they currently exist on the IBM 360/67 at LARS, Purdue is included, and test results on LANDSAT data are described. On Hill County data, the algorithm yields results comparable to the standard maximum likelihood proportion estimator.

Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm

NASA Astrophysics Data System (ADS)

Kania, Adhe; Sidarto, Kuntjoro Adji

2016-02-01

Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.

Investigation into the influence of build parameters on failure of 3D printed parts

NASA Astrophysics Data System (ADS)

Fornasini, Giacomo

Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.

Warfarin therapy: in need of improvement after all these years

PubMed Central

Kimmel, Stephen E

2010-01-01

Background Warfarin therapy has been used clinically for over 60 years, yet continues to be problematic because of its narrow therapeutic index and large inter-individual variability in patient response. As a result, warfarin is a leading cause of serious medication-related adverse events, and its efficacy is also suboptimal. Objective To review factors that are responsible for variable response to warfarin, including clinical, environmental, and genetic factors, and to explore some possible approaches to improving warfarin therapy. Results Recent efforts have focused on developing dosing algorithms that included genetic information to try to improve warfarin dosing. These dosing algorithms hold promise, but have not been fully validated or tested in rigorous clinical trials. Perhaps equally importantly, adherence to warfarin is a major problem that should be addressed with innovative and cost-effective interventions. Conclusion Additional research is needed to further test whether interventions can be used to improve warfarin dosing and outcomes. PMID:18345947

A systematic review of validated methods for identifying hypersensitivity reactions other than anaphylaxis (fever, rash, and lymphadenopathy), using administrative and claims data.

PubMed

Schneider, Gary; Kachroo, Sumesh; Jones, Natalie; Crean, Sheila; Rotella, Philip; Avetisyan, Ruzan; Reynolds, Matthew W

2012-01-01

The Food and Drug Administration's Mini-Sentinel pilot program aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest from administrative and claims data. This article summarizes the process and findings of the algorithm review of hypersensitivity reactions. PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the hypersensitivity reactions of health outcomes of interest. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify hypersensitivity reactions and including validation estimates of the coding algorithms. We identified five studies that provided validated hypersensitivity-reaction algorithms. Algorithm positive predictive values (PPVs) for various definitions of hypersensitivity reactions ranged from 3% to 95%. PPVs were high (i.e. 90%-95%) when both exposures and diagnoses were very specific. PPV generally decreased when the definition of hypersensitivity was expanded, except in one study that used data mining methodology for algorithm development. The ability of coding algorithms to identify hypersensitivity reactions varied, with decreasing performance occurring with expanded outcome definitions. This examination of hypersensitivity-reaction coding algorithms provides an example of surveillance bias resulting from outcome definitions that include mild cases. Data mining may provide tools for algorithm development for hypersensitivity and other health outcomes. Research needs to be conducted on designing validation studies to test hypersensitivity-reaction algorithms and estimating their predictive power, sensitivity, and specificity. Copyright © 2012 John Wiley & Sons, Ltd.

Audit of Use and Overuse of Serum Protein Immunofixation Electrophoresis and Serum Free Light Chain Assay in Tertiary Health Care: A Case for Algorithmic Testing to Optimize Laboratory Utilization.

PubMed

Heaton, Christopher; Vyas, Shikhar G; Singh, Gurmukh

2016-04-01

Overuse of laboratory tests is a persistent issue. We examined the use and overuse of serum immunofixation electrophoresis and serum free light chain assays to develop an algorithm for optimizing utilization. A retrospective review of all tests, for investigation of monoclonal gammopathies, for all patients who had any of these tests done from April 24, 2014, through July 25, 2014, was carried out. The test orders were categorized as warranted or not warranted according to criteria presented in the article. A total of 237 patients were tested, and their historical records included 1,503 episodes of testing for one or more of serum protein electrophoresis, serum immunofixation electrophoresis, and serum free light chain assays. Only 46% of the serum immunofixation and 42% serum free light chain assays were warranted. Proper utilization, at our institution alone, would have obviated $64,182.95/year in health care costs, reduced laboratory cost of reagent alone by $26,436.04/year, and put $21,904.92/year of part B reimbursement at risk. Fewer than half of the serum immunofixation and serum free light chain assays added value. The proposed algorithm for testing should improve utilization. Risk to part B billing may be a disincentive to reducing test utilization. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Parameter Subset Selection Algorithm for Mixed-Effects Models

DOE PAGES

Schmidt, Kathleen L.; Smith, Ralph C.

2016-01-01

Mixed-effects models are commonly used to statistically model phenomena that include attributes associated with a population or general underlying mechanism as well as effects specific to individuals or components of the general mechanism. This can include individual effects associated with data from multiple experiments. However, the parameterizations used to incorporate the population and individual effects are often unidentifiable in the sense that parameters are not uniquely specified by the data. As a result, the current literature focuses on model selection, by which insensitive parameters are fixed or removed from the model. Model selection methods that employ information criteria are applicablemore » to both linear and nonlinear mixed-effects models, but such techniques are limited in that they are computationally prohibitive for large problems due to the number of possible models that must be tested. To limit the scope of possible models for model selection via information criteria, we introduce a parameter subset selection (PSS) algorithm for mixed-effects models, which orders the parameters by their significance. In conclusion, we provide examples to verify the effectiveness of the PSS algorithm and to test the performance of mixed-effects model selection that makes use of parameter subset selection.« less

XTALOPT: An open-source evolutionary algorithm for crystal structure prediction

NASA Astrophysics Data System (ADS)

Lonie, David C.; Zurek, Eva

2011-02-01

The implementation and testing of XTALOPT, an evolutionary algorithm for crystal structure prediction, is outlined. We present our new periodic displacement (ripple) operator which is ideally suited to extended systems. It is demonstrated that hybrid operators, which combine two pure operators, reduce the number of duplicate structures in the search. This allows for better exploration of the potential energy surface of the system in question, while simultaneously zooming in on the most promising regions. A continuous workflow, which makes better use of computational resources as compared to traditional generation based algorithms, is employed. Various parameters in XTALOPT are optimized using a novel benchmarking scheme. XTALOPT is available under the GNU Public License, has been interfaced with various codes commonly used to study extended systems, and has an easy to use, intuitive graphical interface. Program summaryProgram title:XTALOPT Catalogue identifier: AEGX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL v2.1 or later [1] No. of lines in distributed program, including test data, etc.: 36 849 No. of bytes in distributed program, including test data, etc.: 1 149 399 Distribution format: tar.gz Programming language: C++ Computer: PCs, workstations, or clusters Operating system: Linux Classification: 7.7 External routines: QT [2], OpenBabel [3], AVOGADRO [4], SPGLIB [8] and one of: VASP [5], PWSCF [6], GULP [7]. Nature of problem: Predicting the crystal structure of a system from its stoichiometry alone remains a grand challenge in computational materials science, chemistry, and physics. Solution method: Evolutionary algorithms are stochastic search techniques which use concepts from biological evolution in order to locate the global minimum on their potential energy surface. Our evolutionary algorithm, XTALOPT, is freely available to the scientific community for use and collaboration under the GNU Public License. Running time: User dependent. The program runs until stopped by the user.

Reduction of metal artifacts from hip prostheses on CT images of the pelvis: value of iterative reconstructions.

PubMed

Morsbach, Fabian; Bickelhaupt, Sebastian; Wanner, Guido A; Krauss, Andreas; Schmidt, Bernhard; Alkadhi, Hatem

2013-07-01

To assess the value of iterative frequency split-normalized (IFS) metal artifact reduction (MAR) for computed tomography (CT) of hip prostheses. This study had institutional review board and local ethics committee approval. First, a hip phantom with steel and titanium prostheses that had inlays of water, fat, and contrast media in the pelvis was used to optimize the IFS algorithm. Second, 41 consecutive patients with hip prostheses who were undergoing CT were included. Data sets were reconstructed with filtered back projection, the IFS algorithm, and a linear interpolation MAR algorithm. Two blinded, independent readers evaluated axial, coronal, and sagittal CT reformations for overall image quality, image quality of pelvic organs, and assessment of pelvic abnormalities. CT attenuation and image noise were measured. Statistical analysis included the Friedman test, Wilcoxon signed-rank test, and Levene test. Ex vivo experiments demonstrated an optimized IFS algorithm by using a threshold of 2200 HU with four iterations for both steel and titanium prostheses. Measurements of CT attenuation of the inlays were significantly (P < .001) more accurate for IFS when compared with filtered back projection. In patients, best overall and pelvic organ image quality was found in all reformations with IFS (P < .001). Pelvic abnormalities in 11 of 41 patients (27%) were diagnosed with significantly (P = .002) higher confidence on the basis of IFS images. CT attenuation of bladder (P < .001) and muscle (P = .043) was significantly less variable with IFS compared with filtered back projection and linear interpolation MAR. In comparison with that of FBP and linear interpolation MAR, noise with IFS was similar close to and far from the prosthesis (P = .295). The IFS algorithm for CT image reconstruction significantly reduces metal artifacts from hip prostheses, improves the reliability of CT number measurements, and improves the confidence for depicting pelvic abnormalities.

SMOS L1PP Performance Analysis from Commissioning Phase - Improved Algorithms and Major Results

NASA Astrophysics Data System (ADS)

Castro, Rita; Oliva, Roger; Gutiérrez, Antonio; Barbosa, José; Catarino, Nuno; Martin-Neira, Manuel; Zundo, Michele; Cabot, François

2010-05-01

Following the Soil Moisture and Ocean Salinity (SMOS) launch in November 2009, a Commissioning Phase has taken place for six months, having Deimos closely cooperated with the European Space Agency's (ESA) Level 1 team. During these six months several studies have been conducted on calibration optimization, image reconstruction improvement, geolocation assessment and the impact on scientific results, in particular to insure optimal input to Level 2 Soil Moisture and Ocean Salinity retrieval. In parallel with the scientific studies, some new algorithms/mitigation techniques had to be developed, tested and implemented during the Commissioning Phase. Prior to launch, the Level 1 Prototype Processor (L1PP) included already several experimental algorithms different from the ones existent in the operational chain. These algorithms were tested during Commissioning and some were included in the final processing baseline as a result of the planned studies. Some unforeseen algorithms had to be defined, implemented and tested during the Commissioning Phase itself and these will also be described below. In L1a, for example, the calibration of the Power Measuring Systems (PMS) can be done using a cold target as reference, i.e., the Sky at ~3 K. This has been extensively analyzed and the results will be presented here. At least two linearity corrections to the PMS response function have been tested and compared. The deflection method was selected for inclusion on the operational chain and the results leading to this decision will be also presented. In Level 1B, all the foreign sources algorithms have been tested and validated using real data. The System Response Function (G-matrix) computed for different events has been analyzed and criteria for validation of its pseudo inverse, the J+ matrix, have been defined during the Commissioning Phase. The impact of errors in the J+ matrix has been studied and well characterized. The effects of the Flat Target Response (FTR) have also been addressed and the criteria for an acceptable Flat Target Transformation auxiliary data file have been assessed and implemented during the Commissioning Phase. In L1c, the performance of L1PP's geolocation routines has been analyzed by comparing the estimated and real positions of known land features. An important activity during the Commissioning Phase was the study and impact of Radio Frequency Interference (RFI) sources in the final reconstructed image. The quantity of expected RFIs has been under-estimated and, therefore, error mitigation techniques had to be developed to overcome these unwanted sources of errors. In this presentation the latest news and results for this issue will be presented.

Optimization and large scale computation of an entropy-based moment closure

NASA Astrophysics Data System (ADS)

Kristopher Garrett, C.; Hauck, Cory; Hill, Judith

2015-12-01

We present computational advances and results in the implementation of an entropy-based moment closure, MN, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as PN, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. These results show, in particular, load balancing issues in scaling the MN algorithm that do not appear for the PN algorithm. We also observe that in weak scaling tests, the ratio in time to solution of MN to PN decreases.

Optimization and large scale computation of an entropy-based moment closure

DOE PAGES

Hauck, Cory D.; Hill, Judith C.; Garrett, C. Kristopher

2015-09-10

We present computational advances and results in the implementation of an entropy-based moment closure, M N, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as P N, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which aremore » used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. Lastly, these results show, in particular, load balancing issues in scaling the M N algorithm that do not appear for the P N algorithm. We also observe that in weak scaling tests, the ratio in time to solution of M N to P N decreases.« less

Renewable energy in electric utility capacity planning: a decomposition approach with application to a Mexican utility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staschus, K.

1985-01-01

In this dissertation, efficient algorithms for electric-utility capacity expansion planning with renewable energy are developed. The algorithms include a deterministic phase that quickly finds a near-optimal expansion plan using derating and a linearized approximation to the time-dependent availability of nondispatchable energy sources. A probabilistic second phase needs comparatively few computer-time consuming probabilistic simulation iterations to modify this solution towards the optimal expansion plan. For the deterministic first phase, two algorithms, based on a Lagrangian Dual decomposition and a Generalized Benders Decomposition, are developed. The probabilistic second phase uses a Generalized Benders Decomposition approach. Extensive computational tests of the algorithms aremore » reported. Among the deterministic algorithms, the one based on Lagrangian Duality proves fastest. The two-phase approach is shown to save up to 80% in computing time as compared to a purely probabilistic algorithm. The algorithms are applied to determine the optimal expansion plan for the Tijuana-Mexicali subsystem of the Mexican electric utility system. A strong recommendation to push conservation programs in the desert city of Mexicali results from this implementation.« less

The Cross-Correlation and Reshuffling Tests in Discerning Induced Seismicity

NASA Astrophysics Data System (ADS)

Schultz, Ryan; Telesca, Luciano

2018-05-01

In recent years, cases of newly emergent induced clusters have increased seismic hazard and risk in locations with social, environmental, and economic consequence. Thus, the need for a quantitative and robust means to discern induced seismicity has become a critical concern. This paper reviews a Matlab-based algorithm designed to quantify the statistical confidence between two time-series datasets. Similar to prior approaches, our method utilizes the cross-correlation to delineate the strength and lag of correlated signals. In addition, use of surrogate reshuffling tests allows for the dynamic testing against statistical confidence intervals of anticipated spurious correlations. We demonstrate the robust nature of our algorithm in a suite of synthetic tests to determine the limits of accurate signal detection in the presence of noise and sub-sampling. Overall, this routine has considerable merit in terms of delineating the strength of correlated signals, one of which includes the discernment of induced seismicity from natural.

Production of τ τ jj final states at the LHC and the TauSpinner algorithm: the spin-2 case

NASA Astrophysics Data System (ADS)

Bahmani, M.; Kalinowski, J.; Kotlarski, W.; Richter-Wąs, E.; Wąs, Z.

2018-01-01

The TauSpinner algorithm is a tool that allows one to modify the physics model of the Monte Carlo generated samples due to the changed assumptions of event production dynamics, but without the need of re-generating events. With the help of weights τ -lepton production or decay processes can be modified accordingly to a new physics model. In a recent paper a new version TauSpinner ver.2.0.0 has been presented which includes a provision for introducing non-standard states and couplings and study their effects in the vector-boson-fusion processes by exploiting the spin correlations of τ -lepton pair decay products in processes where final states include also two hard jets. In the present paper we document how this can be achieved taking as an example the non-standard spin-2 state that couples to Standard Model particles and tree-level matrix elements with complete helicity information included for the parton-parton scattering amplitudes into a τ -lepton pair and two outgoing partons. This implementation is prepared as the external (user-provided) routine for the TauSpinner algorithm. It exploits amplitudes generated by MadGraph5 and adapted to the TauSpinner algorithm format. Consistency tests of the implemented matrix elements, re-weighting algorithm and numerical results for observables sensitive to τ polarisation are presented.

A systematic review of validated methods for identifying pulmonary fibrosis and interstitial lung disease using administrative and claims data.

PubMed

Jones, Natalie; Schneider, Gary; Kachroo, Sumesh; Rotella, Philip; Avetisyan, Ruzan; Reynolds, Matthew W

2012-01-01

The Food and Drug Administration's Mini-Sentinel pilot program initially aimed to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest (HOIs) from administrative and claims data. This paper summarizes the process and findings of the algorithm review of pulmonary fibrosis and interstitial lung disease. PubMed and Iowa Drug Information Service Web searches were conducted to identify citations applicable to the pulmonary fibrosis/interstitial lung disease HOI. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify pulmonary fibrosis and interstitial lung disease, including validation estimates of the coding algorithms. Our search revealed a deficiency of literature focusing on pulmonary fibrosis and interstitial lung disease algorithms and validation estimates. Only five studies provided codes; none provided validation estimates. Because interstitial lung disease includes a broad spectrum of diseases, including pulmonary fibrosis, the scope of these studies varied, as did the corresponding diagnostic codes used. Research needs to be conducted on designing validation studies to test pulmonary fibrosis and interstitial lung disease algorithms and estimating their predictive power, sensitivity, and specificity. Copyright © 2012 John Wiley & Sons, Ltd.

Simulation of a navigator algorithm for a low-cost GPS receiver

NASA Technical Reports Server (NTRS)

Hodge, W. F.

1980-01-01

The analytical structure of an existing navigator algorithm for a low cost global positioning system receiver is described in detail to facilitate its implementation on in-house digital computers and real-time simulators. The material presented includes a simulation of GPS pseudorange measurements, based on a two-body representation of the NAVSTAR spacecraft orbits, and a four component model of the receiver bias errors. A simpler test for loss of pseudorange measurements due to spacecraft shielding is also noted.

A sequential coalescent algorithm for chromosomal inversions

PubMed Central

Peischl, S; Koch, E; Guerrero, R F; Kirkpatrick, M

2013-01-01

Chromosomal inversions are common in natural populations and are believed to be involved in many important evolutionary phenomena, including speciation, the evolution of sex chromosomes and local adaptation. While recent advances in sequencing and genotyping methods are leading to rapidly increasing amounts of genome-wide sequence data that reveal interesting patterns of genetic variation within inverted regions, efficient simulation methods to study these patterns are largely missing. In this work, we extend the sequential Markovian coalescent, an approximation to the coalescent with recombination, to include the effects of polymorphic inversions on patterns of recombination. Results show that our algorithm is fast, memory-efficient and accurate, making it feasible to simulate large inversions in large populations for the first time. The SMC algorithm enables studies of patterns of genetic variation (for example, linkage disequilibria) and tests of hypotheses (using simulation-based approaches) that were previously intractable. PMID:23632894

An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

NASA Technical Reports Server (NTRS)

Sliwa, S. M.

1984-01-01

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Ares I-X Best Estimated Trajectory Analysis and Results

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Beck, Roger E.; Starr, Brett R.; Derry, Stephen D.; Brandon, Jay; Olds, Aaron D.

2011-01-01

The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air-data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.

Ares I-X Best Estimated Trajectory and Comparison with Pre-Flight Predictions

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Beck, Roger E.; Derry, Stephen D.; Brandon, Jay M.; Starr, Brett R.; Tartabini, Paul V.; Olds, Aaron D.

2011-01-01

The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air- data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.

On the precision of automated activation time estimation

NASA Technical Reports Server (NTRS)

Kaplan, D. T.; Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

1988-01-01

We examined how the assignment of local activation times in epicardial and endocardial electrograms is affected by sampling rate, ambient signal-to-noise ratio, and sinx/x waveform interpolation. Algorithms used for the estimation of fiducial point locations included dV/dtmax, and a matched filter detection algorithm. Test signals included epicardial and endocardial electrograms overlying both normal and infarcted regions of dog myocardium. Signal-to-noise levels were adjusted by combining known data sets with white noise "colored" to match the spectral characteristics of experimentally recorded noise. For typical signal-to-noise ratios and sampling rates, the template-matching algorithm provided the greatest precision in reproducibly estimating fiducial point location, and sinx/x interpolation allowed for an additional significant improvement. With few restrictions, combining these two techniques may allow for use of digitization rates below the Nyquist rate without significant loss of precision.

Development of an above-knee prosthesis equipped with a microcomputer-controlled knee joint: first test results.

PubMed

Aeyels, B; Peeraer, L; Vander Sloten, J; Van der Perre, G

1992-05-01

The shortcomings of conventional above-knee prostheses are due to their lack of adaptive control. Implementation of a microcomputer controlling the knee joint in a passive way has been suggested to enhance the patient's gait comfort, safety and cosmesis. This approach was used in the design of a new prosthetic system for the above-knee amputee, and tested on one patient. The knee joint of a conventional, modular prosthesis was replaced by a knee joint mechanism, equipped with a controllable brake on the knee joint axis. Sensors and a microcomputer were added, keeping the system self-contained. The modularity of the design permits the use of an alternative, external, PC-based control unit, emulating the self-contained one, and offering extended data monitoring and storage facilities. For both units an operating environment was written, including sensor/actuator interfacing and the implementation of a real-time interrupt, executing the control algorithm. A double finite state approach was used in the design of the control algorithm. On a higher level, the mode identification algorithm reveals the patient's intent. Within a specific mode (lower level), the relevant mode control algorithm looks for the current phase within the gait cycle. Within a particular phase, a specific simple control action with the brake replaces normal knee muscle activity. Tests were carried out with one prosthetic patient using a basic control algorithm for level walking, allowing controlled knee flexion during stance phase. The technical feasibility of such a concept is illustrated by the test results, even though only flexion during early stance phase was controlled during the trials.(ABSTRACT TRUNCATED AT 250 WORDS)

A hybrid-domain approach for modeling climate data time series

NASA Astrophysics Data System (ADS)

Wen, Qiuzi H.; Wang, Xiaolan L.; Wong, Augustine

2011-09-01

In order to model climate data time series that often contain periodic variations, trends, and sudden changes in mean (mean shifts, mostly artificial), this study proposes a hybrid-domain (HD) algorithm, which incorporates a time domain test and a newly developed frequency domain test through an iterative procedure that is analogue to the well known backfitting algorithm. A two-phase competition procedure is developed to address the confounding issue between modeling periodic variations and mean shifts. A variety of distinctive features of climate data time series, including trends, periodic variations, mean shifts, and a dependent noise structure, can be modeled in tandem using the HD algorithm. This is particularly important for homogenization of climate data from a low density observing network in which reference series are not available to help preserve climatic trends and long-term periodic variations, preventing them from being mistaken as artificial shifts. The HD algorithm is also powerful in estimating trend and periodicity in a homogeneous data time series (i.e., in the absence of any mean shift). The performance of the HD algorithm (in terms of false alarm rate and hit rate in detecting shifts/cycles, and estimation accuracy) is assessed via a simulation study. Its power is further illustrated through its application to a few climate data time series.

Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

NASA Astrophysics Data System (ADS)

Riboldi, M.; Baroni, G.; Spadea, M. F.; Tagaste, B.; Garibaldi, C.; Cambria, R.; Orecchia, R.; Pedotti, A.

2007-09-01

In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process.

NLP based congestive heart failure case finding: A prospective analysis on statewide electronic medical records.

PubMed

Wang, Yue; Luo, Jin; Hao, Shiying; Xu, Haihua; Shin, Andrew Young; Jin, Bo; Liu, Rui; Deng, Xiaohong; Wang, Lijuan; Zheng, Le; Zhao, Yifan; Zhu, Chunqing; Hu, Zhongkai; Fu, Changlin; Hao, Yanpeng; Zhao, Yingzhen; Jiang, Yunliang; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Todd, Rogow; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng B

2015-12-01

In order to proactively manage congestive heart failure (CHF) patients, an effective CHF case finding algorithm is required to process both structured and unstructured electronic medical records (EMR) to allow complementary and cost-efficient identification of CHF patients. We set to identify CHF cases from both EMR codified and natural language processing (NLP) found cases. Using narrative clinical notes from all Maine Health Information Exchange (HIE) patients, the NLP case finding algorithm was retrospectively (July 1, 2012-June 30, 2013) developed with a random subset of HIE associated facilities, and blind-tested with the remaining facilities. The NLP based method was integrated into a live HIE population exploration system and validated prospectively (July 1, 2013-June 30, 2014). Total of 18,295 codified CHF patients were included in Maine HIE. Among the 253,803 subjects without CHF codings, our case finding algorithm prospectively identified 2411 uncodified CHF cases. The positive predictive value (PPV) is 0.914, and 70.1% of these 2411 cases were found to be with CHF histories in the clinical notes. A CHF case finding algorithm was developed, tested and prospectively validated. The successful integration of the CHF case findings algorithm into the Maine HIE live system is expected to improve the Maine CHF care. Copyright © 2015. Published by Elsevier Ireland Ltd.

The mGA1.0: A common LISP implementation of a messy genetic algorithm

NASA Technical Reports Server (NTRS)

Goldberg, David E.; Kerzic, Travis

1990-01-01

Genetic algorithms (GAs) are finding increased application in difficult search, optimization, and machine learning problems in science and engineering. Increasing demands are being placed on algorithm performance, and the remaining challenges of genetic algorithm theory and practice are becoming increasingly unavoidable. Perhaps the most difficult of these challenges is the so-called linkage problem. Messy GAs were created to overcome the linkage problem of simple genetic algorithms by combining variable-length strings, gene expression, messy operators, and a nonhomogeneous phasing of evolutionary processing. Results on a number of difficult deceptive test functions are encouraging with the mGA always finding global optima in a polynomial number of function evaluations. Theoretical and empirical studies are continuing, and a first version of a messy GA is ready for testing by others. A Common LISP implementation called mGA1.0 is documented and related to the basic principles and operators developed by Goldberg et. al. (1989, 1990). Although the code was prepared with care, it is not a general-purpose code, only a research version. Important data structures and global variations are described. Thereafter brief function descriptions are given, and sample input data are presented together with sample program output. A source listing with comments is also included.

Costs per Diagnosis of Acute HIV Infection in Community-based Screening Strategies: A Comparative Analysis of Four Screening Algorithms

PubMed Central

Hoenigl, Martin; Graff-Zivin, Joshua; Little, Susan J.

2016-01-01

Background. In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking. Methods. To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%. Results. Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%. Conclusions. Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%. PMID:26508512

Guidance simulation and test support for differential GPS flight experiment

NASA Technical Reports Server (NTRS)

Geier, G. J.; Loomis, P. V. W.; Cabak, A.

1987-01-01

Three separate tasks which supported the test preparation, test operations, and post test analysis of the NASA Ames flight test evaluation of the differential Global Positioning System (GPS) are presented. Task 1 consisted of a navigation filter design, coding, and testing to optimally make use of GPS in a differential mode. The filter can be configured to accept inputs from external censors such as an accelerometer and a barometric or radar altimeter. The filter runs in real time onboard a NASA helicopter. It processes raw pseudo and delta range measurements from a single channel sequential GPS receiver. The Kalman filter software interfaces are described in detail, followed by a description of the filter algorithm, including the basic propagation and measurement update equations. The performance during flight tests is reviewed and discussed. Task 2 describes a refinement performed on the lateral and vertical steering algorithms developed on a previous contract. The refinements include modification of the internal logic to allow more diverse inflight initialization procedures, further data smoothing and compensation for system induced time delays. Task 3 describes the TAU Corp participation in the analysis of the real time Kalman navigation filter. The performance was compared to that of the Z-set filter in flight and to the laser tracker position data during post test analysis. This analysis allowed a more optimum selection of the parameters of the filter.

Clinical evaluation of the vector algorithm for neonatal hearing screening using automated auditory brainstem response.

PubMed

Keohane, Bernie M; Mason, Steve M; Baguley, David M

2004-02-01

A novel auditory brainstem response (ABR) detection and scoring algorithm, entitled the Vector algorithm is described. An independent clinical evaluation of the algorithm using 464 tests (120 non-stimulated and 344 stimulated tests) on 60 infants, with a mean age of approximately 6.5 weeks, estimated test sensitivity greater than 0.99 and test specificity at 0.87 for one test. Specificity was estimated to be greater than 0.95 for a two stage screen. Test times were of the order of 1.5 minutes per ear for detection of an ABR and 4.5 minutes per ear in the absence of a clear response. The Vector algorithm is commercially available for both automated screening and threshold estimation in hearing screening devices.

Injecting Errors for Testing Built-In Test Software

NASA Technical Reports Server (NTRS)

Gender, Thomas K.; Chow, James

2010-01-01

Two algorithms have been conceived to enable automated, thorough testing of Built-in test (BIT) software. The first algorithm applies to BIT routines that define pass/fail criteria based on values of data read from such hardware devices as memories, input ports, or registers. This algorithm simulates effects of errors in a device under test by (1) intercepting data from the device and (2) performing AND operations between the data and the data mask specific to the device. This operation yields values not expected by the BIT routine. This algorithm entails very small, permanent instrumentation of the software under test (SUT) for performing the AND operations. The second algorithm applies to BIT programs that provide services to users application programs via commands or callable interfaces and requires a capability for test-driver software to read and write the memory used in execution of the SUT. This algorithm identifies all SUT code execution addresses where errors are to be injected, then temporarily replaces the code at those addresses with small test code sequences to inject latent severe errors, then determines whether, as desired, the SUT detects the errors and recovers

An algorithm for calculating exam quality as a basis for performance-based allocation of funds at medical schools.

PubMed

Kirschstein, Timo; Wolters, Alexander; Lenz, Jan-Hendrik; Fröhlich, Susanne; Hakenberg, Oliver; Kundt, Günther; Darmüntzel, Martin; Hecker, Michael; Altiner, Attila; Müller-Hilke, Brigitte

2016-01-01

The amendment of the Medical Licensing Act (ÄAppO) in Germany in 2002 led to the introduction of graded assessments in the clinical part of medical studies. This, in turn, lent new weight to the importance of written tests, even though the minimum requirements for exam quality are sometimes difficult to reach. Introducing exam quality as a criterion for the award of performance-based allocation of funds is expected to steer the attention of faculty members towards more quality and perpetuate higher standards. However, at present there is a lack of suitable algorithms for calculating exam quality. In the spring of 2014, the students' dean commissioned the "core group" for curricular improvement at the University Medical Center in Rostock to revise the criteria for the allocation of performance-based funds for teaching. In a first approach, we developed an algorithm that was based on the results of the most common type of exam in medical education, multiple choice tests. It included item difficulty and discrimination, reliability as well as the distribution of grades achieved. This algorithm quantitatively describes exam quality of multiple choice exams. However, it can also be applied to exams involving short assay questions and the OSCE. It thus allows for the quantitation of exam quality in the various subjects and - in analogy to impact factors and third party grants - a ranking among faculty. Our algorithm can be applied to all test formats in which item difficulty, the discriminatory power of the individual items, reliability of the exam and the distribution of grades are measured. Even though the content validity of an exam is not considered here, we believe that our algorithm is suitable as a general basis for performance-based allocation of funds.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Characterizing volcanic activity: Application of freely-available webcams

NASA Astrophysics Data System (ADS)

Dehn, J.; Harrild, M.; Webley, P. W.

2017-12-01

In recent years, freely-available web-based cameras, or webcams, have become more readily available allowing an increased level of monitoring at active volcanoes across the globe. While these cameras have been extensively used as qualitative tools, they provide a unique dataset to perform quantitative analyzes of the changing behavior of the particular volcano within the cameras field of view. We focus on the multitude of these freely-available webcams and present a new algorithm to detect changes in volcanic activity using nighttime webcam data. Our approach uses a quick, efficient, and fully automated algorithm to identify changes in webcam data in near real-time, including techniques such as edge detection, Gaussian mixture models, and temporal/spatial statistical tests, which are applied to each target image. Often the image metadata (exposure, gain settings, aperture, focal length, etc.) are unknown, meaning we developed our algorithm to identify the quantity of volcanically incandescent pixels as well as the number of specific algorithm tests needed to detect thermal activity, instead of directly correlating brightness in the webcam to eruption temperatures. We compared our algorithm results to a manual analysis of webcam data for several volcanoes and determined a false detection rate of less than 3% for the automated approach. In our presentation, we describe the different tests integrated into our algorithm, lessons learned, and how we applied our method to several volcanoes across the North Pacific during its development and implementation. We will finish with a discussion on the global applicability of our approach and how to build a 24/7, 365 day a year tool that can be used as an additional data source for real-time analysis of volcanic activity.

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

NASA Technical Reports Server (NTRS)

Carder, Kendall L.; Hawes, Steve K.; Lee, Zhongping

1997-01-01

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm.

A stepwise algorithm using an at-a-glance first-line test for the non-invasive diagnosis of advanced liver fibrosis and cirrhosis.

PubMed

Boursier, Jérôme; de Ledinghen, Victor; Leroy, Vincent; Anty, Rodolphe; Francque, Sven; Salmon, Dominique; Lannes, Adrien; Bertrais, Sandrine; Oberti, Frederic; Fouchard-Hubert, Isabelle; Calès, Paul

2017-06-01

Chronic liver diseases (CLD) are common, and are therefore mainly managed by non-hepatologists. These physicians lack access to the best non-invasive tests of liver fibrosis, and consequently cannot accurately determine the disease severity. Referral to a hepatologist is then needed. We aimed to implement an algorithm, comprising a new first-line test usable by all physicians, for the detection of advanced liver fibrosis in all CLD patients. Diagnostic study: 3754 CLD patients with liver biopsy were 2:1 randomized into derivation and validation sets. Prognostic study: longitudinal follow-up of 1275 CLD patients with baseline fibrosis tests. Diagnostic study: the easy liver fibrosis test (eLIFT), an "at-a-glance" sum of points attributed to age, gender, gamma-glutamyl transferase, aspartate aminotransferase (AST), platelets and prothrombin time, was developed for the diagnosis of advanced fibrosis. In the validation set, eLIFT and fibrosis-4 (FIB4) had the same sensitivity (78.0% vs. 76.6%, p=0.470) but eLIFT gave fewer false positive results, especially in patients ≥60years old (53.8% vs. 82.0%, p<0.001), and was thus more suitable as screening test. FibroMeter with vibration controlled transient elastography (VCTE) was the most accurate among the eight fibrosis tests evaluated. The sensitivity of the eLIFT-FM VCTE algorithm (first-line eLIFT, second-line FibroMeter VCTE ) was 76.1% for advanced fibrosis and 92.1% for cirrhosis. Prognostic study: patients diagnosed as having "no/mild fibrosis" by the algorithm had excellent liver-related prognosis with thus no need for referral to a hepatologist. The eLIFT-FM VCTE algorithm extends the detection of advanced liver fibrosis to all CLD patients and reduces unnecessary referrals of patients without significant CLD to hepatologists. Blood fibrosis tests and transient elastography accurately diagnose advanced liver fibrosis in the large population of patients having chronic liver disease, but these non-invasive tests are only currently available in specialized centers. We have developed an algorithm including the easy liver fibrosis test (eLIFT), a new simple and widely available blood test. It is used as a first-line procedure that selects at-risk patients who need further evaluation with the FibroMeter VCTE , an accurate fibrosis test combining blood markers and transient elastography result. This new algorithm, called the eLIFT-FM VCTE , accurately identifies the patients with advanced chronic liver disease who need referral to a specialist, and those with no or mild liver lesions who can remain under the care of their usual physician. No registration (analysis of pooled data from previously published diagnostic studies). Copyright © 2017 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Comparison and optimization of in silico algorithms for predicting the pathogenicity of sodium channel variants in epilepsy.

PubMed

Holland, Katherine D; Bouley, Thomas M; Horn, Paul S

2017-07-01

Variants in neuronal voltage-gated sodium channel α-subunits genes SCN1A, SCN2A, and SCN8A are common in early onset epileptic encephalopathies and other autosomal dominant childhood epilepsy syndromes. However, in clinical practice, missense variants are often classified as variants of uncertain significance when missense variants are identified but heritability cannot be determined. Genetic testing reports often include results of computational tests to estimate pathogenicity and the frequency of that variant in population-based databases. The objective of this work was to enhance clinicians' understanding of results by (1) determining how effectively computational algorithms predict epileptogenicity of sodium channel (SCN) missense variants; (2) optimizing their predictive capabilities; and (3) determining if epilepsy-associated SCN variants are present in population-based databases. This will help clinicians better understand the results of indeterminate SCN test results in people with epilepsy. Pathogenic, likely pathogenic, and benign variants in SCNs were identified using databases of sodium channel variants. Benign variants were also identified from population-based databases. Eight algorithms commonly used to predict pathogenicity were compared. In addition, logistic regression was used to determine if a combination of algorithms could better predict pathogenicity. Based on American College of Medical Genetic Criteria, 440 variants were classified as pathogenic or likely pathogenic and 84 were classified as benign or likely benign. Twenty-eight variants previously associated with epilepsy were present in population-based gene databases. The output provided by most computational algorithms had a high sensitivity but low specificity with an accuracy of 0.52-0.77. Accuracy could be improved by adjusting the threshold for pathogenicity. Using this adjustment, the Mendelian Clinically Applicable Pathogenicity (M-CAP) algorithm had an accuracy of 0.90 and a combination of algorithms increased the accuracy to 0.92. Potentially pathogenic variants are present in population-based sources. Most computational algorithms overestimate pathogenicity; however, a weighted combination of several algorithms increased classification accuracy to >0.90. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

A Modified MinMax k-Means Algorithm Based on PSO

PubMed Central

2016-01-01

The MinMax k-means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical framework is given. Such framework extends the MinMax k-means to automatically adapt the exponent parameter to the data set. It has been believed that if the maximum exponent parameter has been set, then the programme can reach the lowest intraclustering errors. However, our experiments show that this is not always correct. In this paper, we modified the MinMax k-means algorithm by PSO to determine the proper values of parameters which can subject the algorithm to attain the lowest clustering errors. The proposed clustering method is tested on some favorite data sets in several different initial situations and is compared to the k-means algorithm and the original MinMax k-means algorithm. The experimental results indicate that our proposed algorithm can reach the lowest clustering errors automatically. PMID:27656201

Improved detection and false alarm rejection for chemical vapors using passive hyperspectral imaging

NASA Astrophysics Data System (ADS)

Marinelli, William J.; Miyashiro, Rex; Gittins, Christopher M.; Konno, Daisei; Chang, Shing; Farr, Matt; Perkins, Brad

2013-05-01

Two AIRIS sensors were tested at Dugway Proving Grounds against chemical agent vapor simulants. The primary objectives of the test were to: 1) assess performance of algorithm improvements designed to reduce false alarm rates with a special emphasis on solar effects, and 3) evaluate performance in target detection at 5 km. The tests included 66 total releases comprising alternating 120 kg glacial acetic acid (GAA) and 60 kg triethyl phosphate (TEP) events. The AIRIS sensors had common algorithms, detection thresholds, and sensor parameters. The sensors used the target set defined for the Joint Service Lightweight Chemical Agent Detector (JSLSCAD) with TEP substituted for GA and GAA substituted for VX. They were exercised at two sites located at either 3 km or 5 km from the release point. Data from the tests will be presented showing that: 1) excellent detection capability was obtained at both ranges with significantly shorter alarm times at 5 km, 2) inter-sensor comparison revealed very comparable performance, 3) false alarm rates < 1 incident per 10 hours running time over 143 hours of sensor operations were achieved, 4) algorithm improvements eliminated both solar and cloud false alarms. The algorithms enabling the improved false alarm rejection will be discussed. The sensor technology has recently been extended to address the problem of detection of liquid and solid chemical agents and toxic industrial chemical on surfaces. The phenomenology and applicability of passive infrared hyperspectral imaging to this problem will be discussed and demonstrated.

Software for Simulating a Complex Robot

NASA Technical Reports Server (NTRS)

Goza, S. Michael

2003-01-01

RoboSim (Robot Simulation) is a computer program that simulates the poses and motions of the Robonaut a developmental anthropomorphic robot that has a complex system of joints with 43 degrees of freedom and multiple modes of operation and control. RoboSim performs a full kinematic simulation of all degrees of freedom. It also includes interface components that duplicate the functionality of the real Robonaut interface with control software and human operators. Basically, users see no difference between the real Robonaut and the simulation. Consequently, new control algorithms can be tested by computational simulation, without risk to the Robonaut hardware, and without using excessive Robonaut-hardware experimental time, which is always at a premium. Previously developed software incorporated into RoboSim includes Enigma (for graphical displays), OSCAR (for kinematical computations), and NDDS (for communication between the Robonaut and external software). In addition, RoboSim incorporates unique inverse-kinematical algorithms for chains of joints that have fewer than six degrees of freedom (e.g., finger joints). In comparison with the algorithms of OSCAR, these algorithms are more readily adaptable and provide better results when using equivalent sets of data.

On recent advances and future research directions for computational fluid dynamics

NASA Technical Reports Server (NTRS)

Baker, A. J.; Soliman, M. O.; Manhardt, P. D.

1986-01-01

This paper highlights some recent accomplishments regarding CFD numerical algorithm constructions for generation of discrete approximate solutions to classes of Reynolds-averaged Navier-Stokes equations. Following an overview of turbulent closure modeling, and development of appropriate conservation law systems, a Taylor weak-statement semi-discrete approximate solution algorithm is developed. Various forms for completion to the final linear algebra statement are cited, as are a range of candidate numerical linear algebra solution procedures. This development sequence emphasizes the key building blocks of a CFD RNS algorithm, including solution trial and test spaces, integration procedure and added numerical stability mechanisms. A range of numerical results are discussed focusing on key topics guiding future research directions.

Algorithm of OMA for large-scale orthology inference

PubMed Central

Roth, Alexander CJ; Gonnet, Gaston H; Dessimoz, Christophe

2008-01-01

Background OMA is a project that aims to identify orthologs within publicly available, complete genomes. With 657 genomes analyzed to date, OMA is one of the largest projects of its kind. Results The algorithm of OMA improves upon standard bidirectional best-hit approach in several respects: it uses evolutionary distances instead of scores, considers distance inference uncertainty, includes many-to-many orthologous relations, and accounts for differential gene losses. Herein, we describe in detail the algorithm for inference of orthology and provide the rationale for parameter selection through multiple tests. Conclusion OMA contains several novel improvement ideas for orthology inference and provides a unique dataset of large-scale orthology assignments. PMID:19055798

Multigrid solutions to quasi-elliptic schemes

NASA Technical Reports Server (NTRS)

Brandt, A.; Taasan, S.

1985-01-01

Quasi-elliptic schemes arise from central differencing or finite element discretization of elliptic systems with odd order derivatives on non-staggered grids. They are somewhat unstable and less accurate then corresponding staggered-grid schemes. When usual multigrid solvers are applied to them, the asymptotic algebraic convergence is necessarily slow. Nevertheless, it is shown by mode analyses and numerical experiments that the usual FMG algorithm is very efficient in solving quasi-elliptic equations to the level of truncation errors. Also, a new type of multigrid algorithm is presented, mode analyzed and tested, for which even the asymptotic algebraic convergence is fast. The essence of that algorithm is applicable to other kinds of problems, including highly indefinite ones.

Multigrid solutions to quasi-elliptic schemes

NASA Technical Reports Server (NTRS)

Brandt, A.; Taasan, S.

1985-01-01

Quasi-elliptic schemes arise from central differencing or finite element discretization of elliptic systems with odd order derivatives on non-staggered grids. They are somewhat unstable and less accurate than corresponding staggered-grid schemes. When usual multigrid solvers are applied to them, the asymptotic algebraic convergence is necessarily slow. Nevertheless, it is shown by mode analyses and numerical experiments that the usual FMG algorithm is very efficient in solving quasi-elliptic equations to the level of truncation errors. Also, a new type of multigrid algorithm is presented, mode analyzed and tested, for which even the asymptotic algebraic convergence is fast. The essence of that algorithm is applicable to other kinds of problems, including highly indefinite ones.

CrossSim

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plimpton, Steven J.; Agarwal, Sapan; Schiek, Richard

2016-09-02

CrossSim is a simulator for modeling neural-inspired machine learning algorithms on analog hardware, such as resistive memory crossbars. It includes noise models for reading and updating the resistances, which can be based on idealized equations or experimental data. It can also introduce noise and finite precision effects when converting values from digital to analog and vice versa. All of these effects can be turned on or off as an algorithm processes a data set and attempts to learn its salient attributes so that it can be categorized in the machine learning training/classification context. CrossSim thus allows the robustness, accuracy, andmore » energy usage of a machine learning algorithm to be tested on simulated hardware.« less

Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

2014-05-01

The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

Integrating Natural Language Processing and Machine Learning Algorithms to Categorize Oncologic Response in Radiology Reports.

PubMed

Chen, Po-Hao; Zafar, Hanna; Galperin-Aizenberg, Maya; Cook, Tessa

2018-04-01

A significant volume of medical data remains unstructured. Natural language processing (NLP) and machine learning (ML) techniques have shown to successfully extract insights from radiology reports. However, the codependent effects of NLP and ML in this context have not been well-studied. Between April 1, 2015 and November 1, 2016, 9418 cross-sectional abdomen/pelvis CT and MR examinations containing our internal structured reporting element for cancer were separated into four categories: Progression, Stable Disease, Improvement, or No Cancer. We combined each of three NLP techniques with five ML algorithms to predict the assigned label using the unstructured report text and compared the performance of each combination. The three NLP algorithms included term frequency-inverse document frequency (TF-IDF), term frequency weighting (TF), and 16-bit feature hashing. The ML algorithms included logistic regression (LR), random decision forest (RDF), one-vs-all support vector machine (SVM), one-vs-all Bayes point machine (BPM), and fully connected neural network (NN). The best-performing NLP model consisted of tokenized unigrams and bigrams with TF-IDF. Increasing N-gram length yielded little to no added benefit for most ML algorithms. With all parameters optimized, SVM had the best performance on the test dataset, with 90.6 average accuracy and F score of 0.813. The interplay between ML and NLP algorithms and their effect on interpretation accuracy is complex. The best accuracy is achieved when both algorithms are optimized concurrently.

Symmetric encryption algorithms using chaotic and non-chaotic generators: A review

PubMed Central

Radwan, Ahmed G.; AbdElHaleem, Sherif H.; Abd-El-Hafiz, Salwa K.

2015-01-01

This paper summarizes the symmetric image encryption results of 27 different algorithms, which include substitution-only, permutation-only or both phases. The cores of these algorithms are based on several discrete chaotic maps (Arnold’s cat map and a combination of three generalized maps), one continuous chaotic system (Lorenz) and two non-chaotic generators (fractals and chess-based algorithms). Each algorithm has been analyzed by the correlation coefficients between pixels (horizontal, vertical and diagonal), differential attack measures, Mean Square Error (MSE), entropy, sensitivity analyses and the 15 standard tests of the National Institute of Standards and Technology (NIST) SP-800-22 statistical suite. The analyzed algorithms include a set of new image encryption algorithms based on non-chaotic generators, either using substitution only (using fractals) and permutation only (chess-based) or both. Moreover, two different permutation scenarios are presented where the permutation-phase has or does not have a relationship with the input image through an ON/OFF switch. Different encryption-key lengths and complexities are provided from short to long key to persist brute-force attacks. In addition, sensitivities of those different techniques to a one bit change in the input parameters of the substitution key as well as the permutation key are assessed. Finally, a comparative discussion of this work versus many recent research with respect to the used generators, type of encryption, and analyses is presented to highlight the strengths and added contribution of this paper. PMID:26966561

Automated detection of hospital outbreaks: A systematic review of methods.

PubMed

Leclère, Brice; Buckeridge, David L; Boëlle, Pierre-Yves; Astagneau, Pascal; Lepelletier, Didier

2017-01-01

Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results. We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies. Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%. Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results.

Multiplex PCR Tests for Detection of Pathogens Associated with Gastroenteritis

PubMed Central

Zhang, Hongwei; Morrison, Scott; Tang, Yi-Wei

2016-01-01

Synopsis A wide range of enteric pathogens can cause infectious gastroenteritis. Conventional diagnostic algorithms including culture, biochemical identification, immunoassay and microscopic examination are time consuming and often lack sensitivity and specificity. Advances in molecular technology have as allowed its use as clinical diagnostic tools. Multiplex PCR based testing has made its way to gastroenterology diagnostic arena in recent years. In this article we present a review of recent laboratory developed multiplex PCR tests and current commercial multiplex gastrointestinal pathogen tests. We will focus on two FDA cleared commercial syndromic multiplex tests: Luminex xTAG GPP and Biofire FimArray GI test. These multiplex tests can detect and identify multiple enteric pathogens in one test and provide results within hours. Multiplex PCR tests have shown superior sensitivity to conventional methods for detection of most pathogens. The high negative predictive value of these multiplex tests has led to the suggestion that they be used as screening tools especially in outbreaks. Although the clinical utility and benefit of multiplex PCR test are to be further investigated, implementing these multiplex PCR tests in gastroenterology diagnostic algorithm has the potential to improve diagnosis of infectious gastroenteritis. PMID:26004652

An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms.

PubMed

Andreotti, Fernando; Behar, Joachim; Zaunseder, Sebastian; Oster, Julien; Clifford, Gari D

2016-05-01

Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphological features from the NI-FECG. However, due to the shortage of available public databases, the large variety of performance measures employed and the lack of open-source reference algorithms, most contributions cannot be meaningfully assessed. This article attempts to address these issues by presenting a standardised methodology for stress testing NI-FECG algorithms, including absolute data, as well as extraction and evaluation routines. To that end, a large database of realistic artificial signals was created, totaling 145.8 h of multichannel data and over one million FQRS complexes. An important characteristic of this dataset is the inclusion of several non-stationary events (e.g. foetal movements, uterine contractions and heart rate fluctuations) that are critical for evaluating extraction routines. To demonstrate our testing methodology, three classes of NI-FECG extraction algorithms were evaluated: blind source separation (BSS), template subtraction (TS) and adaptive methods (AM). Experiments were conducted to benchmark the performance of eight NI-FECG extraction algorithms on the artificial database focusing on: FQRS detection and morphological analysis (foetal QT and T/QRS ratio). The overall median FQRS detection accuracies (i.e. considering all non-stationary events) for the best performing methods in each group were 99.9% for BSS, 97.9% for AM and 96.0% for TS. Both FQRS detections and morphological parameters were shown to heavily depend on the extraction techniques and signal-to-noise ratio. Particularly, it is shown that their evaluation in the source domain, obtained after using a BSS technique, should be avoided. Data, extraction algorithms and evaluation routines were released as part of the fecgsyn toolbox on Physionet under an GNU GPL open-source license. This contribution provides a standard framework for benchmarking and regulatory testing of NI-FECG extraction algorithms.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

PubMed

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

Target Classification of Canonical Scatterers Using Classical Estimation and Dictionary Based Techniques

DTIC Science & Technology

2012-03-22

shapes tested , when the objective parameter set was confined to a dictionary’s de - fined parameter space. These physical characteristics included...8 2.3 Hypothesis Testing and Detection Theory . . . . . . . . . . . . . . . 8 2.4 3-D SAR Scattering Models...basis pursuit de -noising (BPDN) algorithm is chosen to perform extraction due to inherent efficiency and error tolerance. Multiple shape dictionaries

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

NASA Technical Reports Server (NTRS)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.

2005-01-01

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Study

PubMed Central

Zhong, Victor W.; Pfaff, Emily R.; Beavers, Daniel P.; Thomas, Joan; Jaacks, Lindsay M.; Bowlby, Deborah A.; Carey, Timothy S.; Lawrence, Jean M.; Dabelea, Dana; Hamman, Richard F.; Pihoker, Catherine; Saydah, Sharon H.; Mayer-Davis, Elizabeth J.

2014-01-01

Background The performance of automated algorithms for childhood diabetes case ascertainment and type classification may differ by demographic characteristics. Objective This study evaluated the potential of administrative and electronic health record (EHR) data from a large academic care delivery system to conduct diabetes case ascertainment in youth according to type, age and race/ethnicity. Subjects 57,767 children aged <20 years as of December 31, 2011 seen at University of North Carolina Health Care System in 2011 were included. Methods Using an initial algorithm including billing data, patient problem lists, laboratory test results and diabetes related medications between July 1, 2008 and December 31, 2011, presumptive cases were identified and validated by chart review. More refined algorithms were evaluated by type (type 1 versus type 2), age (<10 versus ≥10 years) and race/ethnicity (non-Hispanic white versus “other”). Sensitivity, specificity and positive predictive value were calculated and compared. Results The best algorithm for ascertainment of diabetes cases overall was billing data. The best type 1 algorithm was the ratio of the number of type 1 billing codes to the sum of type 1 and type 2 billing codes ≥0.5. A useful algorithm to ascertain type 2 youth with “other” race/ethnicity was identified. Considerable age and racial/ethnic differences were present in type-non-specific and type 2 algorithms. Conclusions Administrative and EHR data may be used to identify cases of childhood diabetes (any type), and to identify type 1 cases. The performance of type 2 case ascertainment algorithms differed substantially by race/ethnicity. PMID:24913103

A systematic review of validated methods for identifying anaphylaxis, including anaphylactic shock and angioneurotic edema, using administrative and claims data.

PubMed

Schneider, Gary; Kachroo, Sumesh; Jones, Natalie; Crean, Sheila; Rotella, Philip; Avetisyan, Ruzan; Reynolds, Matthew W

2012-01-01

The Food and Drug Administration's Mini-Sentinel pilot program initially aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest from administrative and claims data. This article summarizes the process and findings of the algorithm review of anaphylaxis. PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxis health outcome of interest. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify anaphylaxis and including validation estimates of the coding algorithms. Our search revealed limited literature focusing on anaphylaxis that provided administrative and claims data-based algorithms and validation estimates. Only four studies identified via literature searches provided validated algorithms; however, two additional studies were identified by Mini-Sentinel collaborators and were incorporated. The International Classification of Diseases, Ninth Revision, codes varied, as did the positive predictive value, depending on the cohort characteristics and the specific codes used to identify anaphylaxis. Research needs to be conducted on designing validation studies to test anaphylaxis algorithms and estimating their predictive power, sensitivity, and specificity. Copyright © 2012 John Wiley & Sons, Ltd.

Optical Coherence Tomography (OCT) Device Independent Intraretinal Layer Segmentation

PubMed Central

Ehnes, Alexander; Wenner, Yaroslava; Friedburg, Christoph; Preising, Markus N.; Bowl, Wadim; Sekundo, Walter; zu Bexten, Erdmuthe Meyer; Stieger, Knut; Lorenz, Birgit

2014-01-01

Purpose To develop and test an algorithm to segment intraretinal layers irrespectively of the actual Optical Coherence Tomography (OCT) device used. Methods The developed algorithm is based on the graph theory optimization. The algorithm's performance was evaluated against that of three expert graders for unsigned boundary position difference and thickness measurement of a retinal layer group in 50 and 41 B-scans, respectively. Reproducibility of the algorithm was tested in 30 C-scans of 10 healthy subjects each with the Spectralis and the Stratus OCT. Comparability between different devices was evaluated in 84 C-scans (volume or radial scans) obtained from 21 healthy subjects, two scans per subject with the Spectralis OCT, and one scan per subject each with the Stratus OCT and the RTVue-100 OCT. Each C-scan was segmented and the mean thickness for each retinal layer in sections of the early treatment of diabetic retinopathy study (ETDRS) grid was measured. Results The algorithm was able to segment up to 11 intraretinal layers. Measurements with the algorithm were within the 95% confidence interval of a single grader and the difference was smaller than the interindividual difference between the expert graders themselves. The cross-device examination of ETDRS-grid related layer thicknesses highly agreed between the three OCT devices. The algorithm correctly segmented a C-scan of a patient with X-linked retinitis pigmentosa. Conclusions The segmentation software provides device-independent, reliable, and reproducible analysis of intraretinal layers, similar to what is obtained from expert graders. Translational Relevance Potential application of the software includes routine clinical practice and multicenter clinical trials. PMID:24820053

Costs per Diagnosis of Acute HIV Infection in Community-based Screening Strategies: A Comparative Analysis of Four Screening Algorithms.

PubMed

Hoenigl, Martin; Graff-Zivin, Joshua; Little, Susan J

2016-02-15

In nonhealthcare settings, widespread screening for acute human immunodeficiency virus (HIV) infection (AHI) is limited by cost and decision algorithms to better prioritize use of resources. Comparative cost analyses for available strategies are lacking. To determine cost-effectiveness of community-based testing strategies, we evaluated annual costs of 3 algorithms that detect AHI based on HIV nucleic acid amplification testing (EarlyTest algorithm) or on HIV p24 antigen (Ag) detection via Architect (Architect algorithm) or Determine (Determine algorithm) as well as 1 algorithm that relies on HIV antibody testing alone (Antibody algorithm). The cost model used data on men who have sex with men (MSM) undergoing community-based AHI screening in San Diego, California. Incremental cost-effectiveness ratios (ICERs) per diagnosis of AHI were calculated for programs with HIV prevalence rates between 0.1% and 2.9%. Among MSM in San Diego, EarlyTest was cost-savings (ie, ICERs per AHI diagnosis less than $13.000) when compared with the 3 other algorithms. Cost analyses relative to regional HIV prevalence showed that EarlyTest was cost-effective (ie, ICERs less than $69.547) for similar populations of MSM with an HIV prevalence rate >0.4%; Architect was the second best alternative for HIV prevalence rates >0.6%. Identification of AHI by the dual EarlyTest screening algorithm is likely to be cost-effective not only among at-risk MSM in San Diego but also among similar populations of MSM with HIV prevalence rates >0.4%. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Determination of HIV Status in African Adults With Discordant HIV Rapid Tests.

PubMed

Fogel, Jessica M; Piwowar-Manning, Estelle; Donohue, Kelsey; Cummings, Vanessa; Marzinke, Mark A; Clarke, William; Breaud, Autumn; Fiamma, Agnès; Donnell, Deborah; Kulich, Michal; Mbwambo, Jessie K K; Richter, Linda; Gray, Glenda; Sweat, Michael; Coates, Thomas J; Eshleman, Susan H

2015-08-01

In resource-limited settings, HIV infection is often diagnosed using 2 rapid tests. If the results are discordant, a third tie-breaker test is often used to determine HIV status. This study characterized samples with discordant rapid tests and compared different testing strategies for determining HIV status in these cases. Samples were previously collected from 173 African adults in a population-based survey who had discordant rapid test results. Samples were classified as HIV positive or HIV negative using a rigorous testing algorithm that included two fourth-generation tests, a discriminatory test, and 2 HIV RNA tests. Tie-breaker tests were evaluated, including rapid tests (1 performed in-country), a third-generation enzyme immunoassay, and two fourth-generation tests. Selected samples were further characterized using additional assays. Twenty-nine samples (16.8%) were classified as HIV positive and 24 of those samples (82.8%) had undetectable HIV RNA. Antiretroviral drugs were detected in 1 sample. Sensitivity was 8.3%-43% for the rapid tests; 24.1% for the third-generation enzyme immunoassay; 95.8% and 96.6% for the fourth-generation tests. Specificity was lower for the fourth-generation tests than the other tests. Accuracy ranged from 79.5% to 91.3%. In this population-based survey, most HIV-infected adults with discordant rapid tests were virally suppressed without antiretroviral drugs. Use of individual assays as tie-breaker tests was not a reliable method for determining HIV status in these individuals. More extensive testing algorithms that use a fourth-generation screening test with a discriminatory test and HIV RNA test are preferable for determining HIV status in these cases.

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

Large-scale human immunodeficiency virus rapid test evaluation in a low-prevalence ugandan blood bank population.

PubMed

Eller, Leigh A; Eller, Michael A; Ouma, Benson J; Kataaha, Peter; Bagaya, Bernard S; Olemukan, Robert L; Erima, Simon; Kawala, Lilian; de Souza, Mark S; Kibuuka, Hannah; Wabwire-Mangen, Fred; Peel, Sheila A; O'Connell, Robert J; Robb, Merlin L; Michael, Nelson L

2007-10-01

The use of rapid tests for human immunodeficiency virus (HIV) has become standard in HIV testing algorithms employed in resource-limited settings. We report an extensive HIV rapid test validation study conducted among Ugandan blood bank donors at low risk for HIV infection. The operational characteristics of four readily available commercial HIV rapid test kits were first determined with 940 donor samples and were used to select a serial testing algorithm. Uni-Gold Recombigen HIV was used as the screening test, followed by HIV-1/2 STAT-PAK for reactive samples. OraQuick HIV-1 testing was performed if the first two test results were discordant. This algorithm was then tested with 5,252 blood donor samples, and the results were compared to those of enzyme immunoassays (EIAs) and Western blotting. The unadjusted algorithm sensitivity and specificity were 98.6 and 99.9%, respectively. The adjusted sensitivity and specificity were 100 and 99.96%, respectively. This HIV testing algorithm is a suitable alternative to EIAs and Western blotting for Ugandan blood donors.

Kinetic: A system code for analyzing nuclear thermal propulsion rocket engine transients

NASA Astrophysics Data System (ADS)

Schmidt, Eldon; Lazareth, Otto; Ludewig, Hans

The topics are presented in viewgraph form and include the following: outline of kinetic code; a kinetic information flow diagram; kinetic neutronic equations; turbopump/nozzle algorithm; kinetic heat transfer equations per node; and test problem diagram.

Viking lander camera radiometry calibration report, volume 2

NASA Technical Reports Server (NTRS)

Wolf, M. R.; Atwood, D. L.; Morrill, M. E.

1977-01-01

The requirements the performance validation, and interfaces for the RADCAM program, to convert Viking lander camera image data to radiometric units were established. A proposed algorithm is described, and an appendix summarizing the planned reduction of camera test data was included.

SU-E-T-446: Group-Sparsity Based Angle Generation Method for Beam Angle Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, H

2015-06-15

Purpose: This work is to develop the effective algorithm for beam angle optimization (BAO), with the emphasis on enabling further improvement from existing treatment-dependent templates based on clinical knowledge and experience. Methods: The proposed BAO algorithm utilizes a priori beam angle templates as the initial guess, and iteratively generates angular updates for this initial set, namely angle generation method, with improved dose conformality that is quantitatively measured by the objective function. That is, during each iteration, we select “the test angle” in the initial set, and use group-sparsity based fluence map optimization to identify “the candidate angle” for updating “themore » test angle”, for which all the angles in the initial set except “the test angle”, namely “the fixed set”, are set free, i.e., with no group-sparsity penalty, and the rest of angles including “the test angle” during this iteration are in “the working set”. And then “the candidate angle” is selected with the smallest objective function value from the angles in “the working set” with locally maximal group sparsity, and replaces “the test angle” if “the fixed set” with “the candidate angle” has a smaller objective function value by solving the standard fluence map optimization (with no group-sparsity regularization). Similarly other angles in the initial set are in turn selected as “the test angle” for angular updates and this chain of updates is iterated until no further new angular update is identified for a full loop. Results: The tests using the MGH public prostate dataset demonstrated the effectiveness of the proposed BAO algorithm. For example, the optimized angular set from the proposed BAO algorithm was better the MGH template. Conclusion: A new BAO algorithm is proposed based on the angle generation method via group sparsity, with improved dose conformality from the given template. Hao Gao was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Preliminary Evaluation of a New Semi-Closed-Loop Insulin Therapy System Over the Prandial Period in Adult Patients With Type 1 Diabetes

PubMed Central

Quemerais, Marie Aude; Doron, Maeva; Dutrech, Florent; Melki, Vincent; Franc, Sylvia; Antonakios, Michel; Charpentier, Guillaume; Hanaire, Helene; Charpentier, Guillaume

2014-01-01

There is room for improvement in the algorithms used in closed-loop insulin therapy during the prandial period. This pilot study evaluated the efficacy and safety of the Diabeloop algorithm (model predictive control type) during the postprandial period. This 2-center clinical trial compared interstitial glucose levels over two 5-hour periods (with/without the algorithm) following a calibrated lunch. On the control day, the amount of insulin delivered by the pump was determined according to the patient’s usual parameters. On the test day, 50% or 75% of the theoretical bolus required was delivered, while the algorithm, informed of carbohydrate intake, proposed changes to insulin delivery every 15 minutes using modeling to forecast glucose levels. The primary endpoint was percentage of time spent at near normoglycemia (70-180 mg/dl). Twelve patients with type 1 diabetes (9 men, age 35.6 ± 12.7 years, HbA1c 7.3 ± 0.8%) were included. The percentage of time spent in the target range was 84.5 ± 20.8 (test day) versus 69.2 ± 33.9% (control day, P = .11). The percentage of time spent in hypoglycemia < 70 mg/dl was 0.2 ± 0.8 (test) versus 4.4 ± 8.2% (control, P = .18). Interstitial glucose at the end of the test (5 hours) was 127.5 ± 40.1 (test) versus 146 ± 53.5 mg/dl (control, P = .25). The insulin doses did not differ, and no differences were observed between the 50% and 75% boluses. In a semi-closed-loop configuration with manual priming boluses (25% or 50% reduction), the Diabeloop v1 algorithm was as successful as the manual method in determining the prandial bolus, without any exposure to excessive hypoglycemic risk. PMID:25097057

Effectiveness of physical therapy for patients with neck pain: an individualized approach using a clinical decision-making algorithm.

PubMed

Wang, Wendy T J; Olson, Sharon L; Campbell, Anne H; Hanten, William P; Gleeson, Peggy B

2003-03-01

The purpose of this study was to determine the effectiveness of an individualized physical therapy intervention in treating neck pain based on a clinical reasoning algorithm. Treatment effectiveness was examined by assessing changes in impairment, physical performance, and disability in response to intervention. One treatment group of 30 patients with neck pain completed physical therapy treatment. The control group of convenience was formed by a cohort group of 27 subjects who also had neck pain but did not receive treatment for various reasons. There were no significant differences between groups in demographic data and the initial test scores of the outcome measures. A quasi-experimental, nonequivalent, pretest-posttest control group design was used. A physical therapist rendered an eclectic intervention to the treatment group based on a clinical decision-making algorithm. Treatment outcome measures included the following five dependent variables: cervical range of motion, numeric pain rating, timed weighted overhead endurance, the supine capital flexion endurance test, and the Patient Specific Functional Scale. Both the treatment and control groups completed the initial and follow-up examinations, with an average duration of 4 wk between tests. Five mixed analyses of variance with follow-up tests showed a significant difference for all outcome measures in the treatment group compared with the control group. After an average 4 wk of physical therapy intervention, patients in the treatment group demonstrated statistically significant increases of cervical range of motion, decrease of pain, increases of physical performance measures, and decreases in the level of disability. The control group showed no differences in all five outcome variables between the initial and follow-up test scores. This study delineated algorithm-based clinical reasoning strategies for evaluating and treating patients with cervical pain. The algorithm can help clinicians classify patients with cervical pain into clinical patterns and provides pattern-specific guidelines for physical therapy interventions. An organized and specific physical therapy program was effective in improving the status of patients with neck pain.

Modeling and analysis of pinhole occulter experiment: Initial study phase

NASA Technical Reports Server (NTRS)

Vandervoort, R. J.

1985-01-01

The feasibility of using a generic simulation, TREETOPS, to simulate the Pinhole/Occulter Facility (P/OF) to be tested on the space shuttle was demonstrated. The baseline control system was used to determine the pointing performance of the P/OF. The task included modeling the structure as a three body problem (shuttle-instrument pointing system- P/OP) including the flexibility of the 32 meter P/OF boom. Modeling of sensors, actuators, and control algorithms was also required. Detailed mathematical models for the structure, sensors, and actuators are presented, as well as the control algorithm and corresponding design procedure. Closed loop performance using this controller and computer listings for the simulator are also given.

On-Board Cryospheric Change Detection By The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Doggett, T.; Greeley, R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Baker, V.; Dohm, J.; Ip, F.

2004-12-01

The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible/near-IR spectrometer. ASE science activities include autonomous monitoring of cryopsheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. This would have application to the study of cryospheres on Earth, Mars and the icy moons of the outer solar system. A cryosphere classification algorithm, in combination with a previously developed cloud algorithm [1] has been tested on-board ten times from March through August 2004. The cloud algorithm correctly screened out three scenes with total cloud cover, while the cryosphere algorithm detected alpine snow cover in the Rocky Mountains, lake thaw near Madison, Wisconsin, and the presence and subsequent break-up of sea ice in the Barrow Strait of the Canadian Arctic. Hyperion has 220 bands ranging from 400 to 2400 nm, with a spatial resolution of 30 m/pixel and a spectral resolution of 10 nm. Limited on-board memory and processing speed imposed the constraint that only partially processed Level 0.5 data with dark image subtraction and gain factors applied, but not full radiometric calibration. In addition, a maximum of 12 bands could be used for any stacked sequence of algorithms run for a scene on-board. The cryosphere algorithm was developed to classify snow, water, ice and land, using six Hyperion bands at 427, 559, 661, 864, 1245 and 1649 nm. Of these, only 427 nm does overlap with the cloud algorithm. The cloud algorithm was developed with Level 1 data, which introduces complications because of the incomplete calibration of SWIR in Level 0.5 data, including a high level of noise in the 1377 nm band used by the cloud algorithm. Development of a more robust cryosphere classifier, including cloud classification specifically adapted to Level 0.5, is in progress for deployment on EO-1 as part of continued ASE operations. [1] Griffin, M.K. et al., Cloud Cover Detection Algorithm For EO-1 Hyperion Imagery, SPIE 17, 2003.

Identification of genes related to proliferative diabetic retinopathy through RWR algorithm based on protein-protein interaction network.

PubMed

Zhang, Jian; Suo, Yan; Liu, Min; Xu, Xun

2018-06-01

Proliferative diabetic retinopathy (PDR) is one of the most common complications of diabetes and can lead to blindness. Proteomic studies have provided insight into the pathogenesis of PDR and a series of PDR-related genes has been identified but are far from fully characterized because the experimental methods are expensive and time consuming. In our previous study, we successfully identified 35 candidate PDR-related genes through the shortest-path algorithm. In the current study, we developed a computational method using the random walk with restart (RWR) algorithm and the protein-protein interaction (PPI) network to identify potential PDR-related genes. After some possible genes were obtained by the RWR algorithm, a three-stage filtration strategy, which includes the permutation test, interaction test and enrichment test, was applied to exclude potential false positives caused by the structure of PPI network, the poor interaction strength, and the limited similarity on gene ontology (GO) terms and biological pathways. As a result, 36 candidate genes were discovered by the method which was different from the 35 genes reported in our previous study. A literature review showed that 21 of these 36 genes are supported by previous experiments. These findings suggest the robustness and complementary effects of both our efforts using different computational methods, thus providing an alternative method to study PDR pathogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

LP and NLP decomposition without a master problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fuller, D.; Lan, B.

We describe a new algorithm for decomposition of linear programs and a class of convex nonlinear programs, together with theoretical properties and some test results. Its most striking feature is the absence of a master problem; the subproblems pass primal and dual proposals directly to one another. The algorithm is defined for multi-stage LPs or NLPs, in which the constraints link the current stage`s variables to earlier stages` variables. This problem class is general enough to include many problem structures that do not immediately suggest stages, such as block diagonal problems. The basic algorithmis derived for two-stage problems and extendedmore » to more than two stages through nested decomposition. The main theoretical result assures convergence, to within any preset tolerance of the optimal value, in a finite number of iterations. This asymptotic convergence result contrasts with the results of limited tests on LPs, in which the optimal solution is apparently found exactly, i.e., to machine accuracy, in a small number of iterations. The tests further suggest that for LPs, the new algorithm is faster than the simplex method applied to the whole problem, as long as the stages are linked loosely; that the speedup over the simpex method improves as the number of stages increases; and that the algorithm is more reliable than nested Dantzig-Wolfe or Benders` methods in its improvement over the simplex method.« less

Development and Evaluation of a Performance Modeling Flight Test Approach Based on Quasi Steady-State Maneuvers

NASA Technical Reports Server (NTRS)

Yechout, T. R.; Braman, K. B.

1984-01-01

The development, implementation and flight test evaluation of a performance modeling technique which required a limited amount of quasisteady state flight test data to predict the overall one g performance characteristics of an aircraft. The concept definition phase of the program include development of: (1) the relationship for defining aerodynamic characteristics from quasi steady state maneuvers; (2) a simplified in flight thrust and airflow prediction technique; (3) a flight test maneuvering sequence which efficiently provided definition of baseline aerodynamic and engine characteristics including power effects on lift and drag; and (4) the algorithms necessary for cruise and flight trajectory predictions. Implementation of the concept include design of the overall flight test data flow, definition of instrumentation system and ground test requirements, development and verification of all applicable software and consolidation of the overall requirements in a flight test plan.

Developing a Screening Algorithm for Type II Diabetes Mellitus in the Resource-Limited Setting of Rural Tanzania.

PubMed

West, Caroline; Ploth, David; Fonner, Virginia; Mbwambo, Jessie; Fredrick, Francis; Sweat, Michael

2016-04-01

Noncommunicable diseases are on pace to outnumber infectious disease as the leading cause of death in sub-Saharan Africa, yet many questions remain unanswered with concern toward effective methods of screening for type II diabetes mellitus (DM) in this resource-limited setting. We aim to design a screening algorithm for type II DM that optimizes sensitivity and specificity of identifying individuals with undiagnosed DM, as well as affordability to health systems and individuals. Baseline demographic and clinical data, including hemoglobin A1c (HbA1c), were collected from 713 participants using probability sampling of the general population. We used these data, along with model parameters obtained from the literature, to mathematically model 8 purposed DM screening algorithms, while optimizing the sensitivity and specificity using Monte Carlo and Latin Hypercube simulation. An algorithm that combines risk assessment and measurement of fasting blood glucose was found to be superior for the most resource-limited settings (sensitivity 68%, sensitivity 99% and cost per patient having DM identified as $2.94). Incorporating HbA1c testing improves the sensitivity to 75.62%, but raises the cost per DM case identified to $6.04. The preferred algorithms are heavily biased to diagnose those with more severe cases of DM. Using basic risk assessment tools and fasting blood sugar testing in lieu of HbA1c testing in resource-limited settings could allow for significantly more feasible DM screening programs with reasonable sensitivity and specificity. Copyright © 2016 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

QDENSITY—A Mathematica Quantum Computer simulation

NASA Astrophysics Data System (ADS)

Juliá-Díaz, Bruno; Burdis, Joseph M.; Tabakin, Frank

2006-06-01

This Mathematica 5.2 package is a simulation of a Quantum Computer. The program provides a modular, instructive approach for generating the basic elements that make up a quantum circuit. The main emphasis is on using the density matrix, although an approach using state vectors is also implemented in the package. The package commands are defined in Qdensity.m which contains the tools needed in quantum circuits, e.g., multiqubit kets, projectors, gates, etc. Selected examples of the basic commands are presented here and a tutorial notebook, Tutorial.nb is provided with the package (available on our website) that serves as a full guide to the package. Finally, application is made to a variety of relevant cases, including Teleportation, Quantum Fourier transform, Grover's search and Shor's algorithm, in separate notebooks: QFT.nb, Teleportation.nb, Grover.nb and Shor.nb where each algorithm is explained in detail. Finally, two examples of the construction and manipulation of cluster states, which are part of "one way computing" ideas, are included as an additional tool in the notebook Cluster.nb. A Mathematica palette containing most commands in QDENSITY is also included: QDENSpalette.nb. Program summaryTitle of program: QDENSITY Catalogue identifier: ADXH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXH_v1_0 Program available from: CPC Program Library, Queen's University of Belfast, N. Ireland Operating systems: Any which supports Mathematica; tested under Microsoft Windows XP, Macintosh OS X, and Linux FC4 Programming language used: Mathematica 5.2 No. of bytes in distributed program, including test data, etc.: 180 581 No. of lines in distributed program, including test data, etc.: 19 382 Distribution format: tar.gz Method of solution: A Mathematica package is provided which contains commands to create and analyze quantum circuits. Several Mathematica notebooks containing relevant examples: Teleportation, Shor's Algorithm and Grover's search are explained in detail. A tutorial, Tutorial.nb is also enclosed. QDENSITY is available at http://www.pitt.edu/~tabakin/QDENSITY.

Prognostics Approach for Power MOSFET Under Thermal-Stress

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon Celaya; Saxena, Abhinav; Kulkarni, Chetan S.; Saha, Sankalita; Goebel, Kai

2012-01-01

The prognostic technique for a power MOSFET presented in this paper is based on accelerated aging of MOSFET IRF520Npbf in a TO-220 package. The methodology utilizes thermal and power cycling to accelerate the life of the devices. The major failure mechanism for the stress conditions is dieattachment degradation, typical for discrete devices with leadfree solder die attachment. It has been determined that dieattach degradation results in an increase in ON-state resistance due to its dependence on junction temperature. Increasing resistance, thus, can be used as a precursor of failure for the die-attach failure mechanism under thermal stress. A feature based on normalized ON-resistance is computed from in-situ measurements of the electro-thermal response. An Extended Kalman filter is used as a model-based prognostics techniques based on the Bayesian tracking framework. The proposed prognostics technique reports on preliminary work that serves as a case study on the prediction of remaining life of power MOSFETs and builds upon the work presented in [1]. The algorithm considered in this study had been used as prognostics algorithm in different applications and is regarded as suitable candidate for component level prognostics. This work attempts to further the validation of such algorithm by presenting it with real degradation data including measurements from real sensors, which include all the complications (noise, bias, etc.) that are regularly not captured on simulated degradation data. The algorithm is developed and tested on the accelerated aging test timescale. In real world operation, the timescale of the degradation process and therefore the RUL predictions will be considerable larger. It is hypothesized that even though the timescale will be larger, it remains constant through the degradation process and the algorithm and model would still apply under the slower degradation process. By using accelerated aging data with actual device measurements and real sensors (no simulated behavior), we are attempting to assess how such algorithm behaves under realistic conditions.

Performance of an open-source heart sound segmentation algorithm on eight independent databases.

PubMed

Liu, Chengyu; Springer, David; Clifford, Gari D

2017-08-01

Heart sound segmentation is a prerequisite step for the automatic analysis of heart sound signals, facilitating the subsequent identification and classification of pathological events. Recently, hidden Markov model-based algorithms have received increased interest due to their robustness in processing noisy recordings. In this study we aim to evaluate the performance of the recently published logistic regression based hidden semi-Markov model (HSMM) heart sound segmentation method, by using a wider variety of independently acquired data of varying quality. Firstly, we constructed a systematic evaluation scheme based on a new collection of heart sound databases, which we assembled for the PhysioNet/CinC Challenge 2016. This collection includes a total of more than 120 000 s of heart sounds recorded from 1297 subjects (including both healthy subjects and cardiovascular patients) and comprises eight independent heart sound databases sourced from multiple independent research groups around the world. Then, the HSMM-based segmentation method was evaluated using the assembled eight databases. The common evaluation metrics of sensitivity, specificity, accuracy, as well as the [Formula: see text] measure were used. In addition, the effect of varying the tolerance window for determining a correct segmentation was evaluated. The results confirm the high accuracy of the HSMM-based algorithm on a separate test dataset comprised of 102 306 heart sounds. An average [Formula: see text] score of 98.5% for segmenting S1 and systole intervals and 97.2% for segmenting S2 and diastole intervals were observed. The [Formula: see text] score was shown to increases with an increases in the tolerance window size, as expected. The high segmentation accuracy of the HSMM-based algorithm on a large database confirmed the algorithm's effectiveness. The described evaluation framework, combined with the largest collection of open access heart sound data, provides essential resources for evaluators who need to test their algorithms with realistic data and share reproducible results.

Automated discovery of local search heuristics for satisfiability testing.

PubMed

Fukunaga, Alex S

2008-01-01

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.

Derivation and experimental verification of clock synchronization theory

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.

1994-01-01

The objective of this work is to validate mathematically derived clock synchronization theories and their associated algorithms through experiment. Two theories are considered, the Interactive Convergence Clock Synchronization Algorithm and the Mid-Point Algorithm. Special clock circuitry was designed and built so that several operating conditions and failure modes (including malicious failures) could be tested. Both theories are shown to predict conservative upper bounds (i.e., measured values of clock skew were always less than the theory prediction). Insight gained during experimentation led to alternative derivations of the theories. These new theories accurately predict the clock system's behavior. It is found that a 100% penalty is paid to tolerate worst case failures. It is also shown that under optimal conditions (with minimum error and no failures) the clock skew can be as much as 3 clock ticks. Clock skew grows to 6 clock ticks when failures are present. Finally, it is concluded that one cannot rely solely on test procedures or theoretical analysis to predict worst case conditions. conditions.

Matching algorithm of missile tail flame based on back-propagation neural network

NASA Astrophysics Data System (ADS)

Huang, Da; Huang, Shucai; Tang, Yidong; Zhao, Wei; Cao, Wenhuan

2018-02-01

This work presents a spectral matching algorithm of missile plume detection that based on neural network. The radiation value of the characteristic spectrum of the missile tail flame is taken as the input of the network. The network's structure including the number of nodes and layers is determined according to the number of characteristic spectral bands and missile types. We can get the network weight matrixes and threshold vectors through training the network using training samples, and we can determine the performance of the network through testing the network using the test samples. A small amount of data cause the network has the advantages of simple structure and practicality. Network structure composed of weight matrix and threshold vector can complete task of spectrum matching without large database support. Network can achieve real-time requirements with a small quantity of data. Experiment results show that the algorithm has the ability to match the precise spectrum and strong robustness.

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

NASA Technical Reports Server (NTRS)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wollaber, Allan Benton; Park, HyeongKae; Lowrie, Robert Byron

Recent efforts at Los Alamos National Laboratory to develop a moment-based, scale-bridging [or high-order (HO)–low-order (LO)] algorithm for solving large varieties of the transport (kinetic) systems have shown promising results. A part of our ongoing effort is incorporating this methodology into the framework of the Eulerian Applications Project to achieve algorithmic acceleration of radiationhydrodynamics simulations in production software. By starting from the thermal radiative transfer equations with a simple material-motion correction, we derive a discretely consistent energy balance equation (LO equation). We demonstrate that the corresponding LO system for the Monte Carlo HO solver is closely related to the originalmore » LO system without material-motion corrections. We test the implementation on a radiative shock problem and show consistency between the energy densities and temperatures in the HO and LO solutions as well as agreement with the semianalytic solution. We also test the approach on a more challenging two-dimensional problem and demonstrate accuracy enhancements and algorithmic speedups. This paper extends a recent conference paper by including multigroup effects.« less

RANdom SAmple Consensus (RANSAC) algorithm for material-informatics: application to photovoltaic solar cells.

PubMed

Kaspi, Omer; Yosipof, Abraham; Senderowitz, Hanoch

2017-06-06

An important aspect of chemoinformatics and material-informatics is the usage of machine learning algorithms to build Quantitative Structure Activity Relationship (QSAR) models. The RANdom SAmple Consensus (RANSAC) algorithm is a predictive modeling tool widely used in the image processing field for cleaning datasets from noise. RANSAC could be used as a "one stop shop" algorithm for developing and validating QSAR models, performing outlier removal, descriptors selection, model development and predictions for test set samples using applicability domain. For "future" predictions (i.e., for samples not included in the original test set) RANSAC provides a statistical estimate for the probability of obtaining reliable predictions, i.e., predictions within a pre-defined number of standard deviations from the true values. In this work we describe the first application of RNASAC in material informatics, focusing on the analysis of solar cells. We demonstrate that for three datasets representing different metal oxide (MO) based solar cell libraries RANSAC-derived models select descriptors previously shown to correlate with key photovoltaic properties and lead to good predictive statistics for these properties. These models were subsequently used to predict the properties of virtual solar cells libraries highlighting interesting dependencies of PV properties on MO compositions.

Efficient algorithm for locating and sizing series compensation devices in large power transmission grids: II. Solutions and applications

DOE PAGES

Frolov, Vladimir; Backhaus, Scott; Chertkov, Misha

2014-10-01

In a companion manuscript, we developed a novel optimization method for placement, sizing, and operation of Flexible Alternating Current Transmission System (FACTS) devices to relieve transmission network congestion. Specifically, we addressed FACTS that provide Series Compensation (SC) via modification of line inductance. In this manuscript, this heuristic algorithm and its solutions are explored on a number of test cases: a 30-bus test network and a realistically-sized model of the Polish grid (~ 2700 nodes and ~ 3300 lines). The results on the 30-bus network are used to study the general properties of the solutions including non-locality and sparsity. The Polishmore » grid is used as a demonstration of the computational efficiency of the heuristics that leverages sequential linearization of power flow constraints and cutting plane methods that take advantage of the sparse nature of the SC placement solutions. Using these approaches, the algorithm is able to solve an instance of Polish grid in tens of seconds. We explore the utility of the algorithm by analyzing transmission networks congested by (a) uniform load growth, (b) multiple overloaded configurations, and (c) sequential generator retirements.« less

Robust hashing for 3D models

NASA Astrophysics Data System (ADS)

Berchtold, Waldemar; Schäfer, Marcel; Rettig, Michael; Steinebach, Martin

2014-02-01

3D models and applications are of utmost interest in both science and industry. With the increment of their usage, their number and thereby the challenge to correctly identify them increases. Content identification is commonly done by cryptographic hashes. However, they fail as a solution in application scenarios such as computer aided design (CAD), scientific visualization or video games, because even the smallest alteration of the 3D model, e.g. conversion or compression operations, massively changes the cryptographic hash as well. Therefore, this work presents a robust hashing algorithm for 3D mesh data. The algorithm applies several different bit extraction methods. They are built to resist desired alterations of the model as well as malicious attacks intending to prevent correct allocation. The different bit extraction methods are tested against each other and, as far as possible, the hashing algorithm is compared to the state of the art. The parameters tested are robustness, security and runtime performance as well as False Acceptance Rate (FAR) and False Rejection Rate (FRR), also the probability calculation of hash collision is included. The introduced hashing algorithm is kept adaptive e.g. in hash length, to serve as a proper tool for all applications in practice.

Accelerated Training for Large Feedforward Neural Networks

NASA Technical Reports Server (NTRS)

Stepniewski, Slawomir W.; Jorgensen, Charles C.

1998-01-01

In this paper we introduce a new training algorithm, the scaled variable metric (SVM) method. Our approach attempts to increase the convergence rate of the modified variable metric method. It is also combined with the RBackprop algorithm, which computes the product of the matrix of second derivatives (Hessian) with an arbitrary vector. The RBackprop method allows us to avoid computationally expensive, direct line searches. In addition, it can be utilized in the new, 'predictive' updating technique of the inverse Hessian approximation. We have used directional slope testing to adjust the step size and found that this strategy works exceptionally well in conjunction with the Rbackprop algorithm. Some supplementary, but nevertheless important enhancements to the basic training scheme such as improved setting of a scaling factor for the variable metric update and computationally more efficient procedure for updating the inverse Hessian approximation are presented as well. We summarize by comparing the SVM method with four first- and second- order optimization algorithms including a very effective implementation of the Levenberg-Marquardt method. Our tests indicate promising computational speed gains of the new training technique, particularly for large feedforward networks, i.e., for problems where the training process may be the most laborious.

Inductive learning of thyroid functional states using the ID3 algorithm. The effect of poor examples on the learning result.

PubMed

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.

Efficient Algorithm for Locating and Sizing Series Compensation Devices in Large Transmission Grids: Solutions and Applications (PART II)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frolov, Vladimir; Backhaus, Scott N.; Chertkov, Michael

2014-01-14

In a companion manuscript, we developed a novel optimization method for placement, sizing, and operation of Flexible Alternating Current Transmission System (FACTS) devices to relieve transmission network congestion. Specifically, we addressed FACTS that provide Series Compensation (SC) via modification of line inductance. In this manuscript, this heuristic algorithm and its solutions are explored on a number of test cases: a 30-bus test network and a realistically-sized model of the Polish grid (~2700 nodes and ~3300 lines). The results on the 30-bus network are used to study the general properties of the solutions including non-locality and sparsity. The Polish grid ismore » used as a demonstration of the computational efficiency of the heuristics that leverages sequential linearization of power flow constraints and cutting plane methods that take advantage of the sparse nature of the SC placement solutions. Using these approaches, the algorithm is able to solve an instance of Polish grid in tens of seconds. We explore the utility of the algorithm by analyzing transmission networks congested by (a) uniform load growth, (b) multiple overloaded configurations, and (c) sequential generator retirements« less

The FBI compression standard for digitized fingerprint images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brislawn, C.M.; Bradley, J.N.; Onyshczak, R.J.

1996-10-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the currentmore » status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.« less

FBI compression standard for digitized fingerprint images

NASA Astrophysics Data System (ADS)

Brislawn, Christopher M.; Bradley, Jonathan N.; Onyshczak, Remigius J.; Hopper, Thomas

1996-11-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the current status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.

Estimating Western U.S. Reservoir Sedimentation

NASA Astrophysics Data System (ADS)

Bensching, L.; Livneh, B.; Greimann, B. P.

2017-12-01

Reservoir sedimentation is a long-term problem for water management across the Western U.S. Observations of sedimentation are limited to reservoir surveys that are costly and infrequent, with many reservoirs having only two or fewer surveys. This work aims to apply a recently developed ensemble of sediment algorithms to estimate reservoir sedimentation over several western U.S. reservoirs. The sediment algorithms include empirical, conceptual, stochastic, and processes based approaches and are coupled with a hydrologic modeling framework. Preliminary results showed that the more complex and processed based algorithms performed better in predicting high sediment flux values and in a basin transferability experiment. However, more testing and validation is required to confirm sediment model skill. This work is carried out in partnership with the Bureau of Reclamation with the goal of evaluating the viability of reservoir sediment yield prediction across the western U.S. using a multi-algorithm approach. Simulations of streamflow and sediment fluxes are validated against observed discharges, as well as a Reservoir Sedimentation Information database that is being developed by the US Army Corps of Engineers. Specific goals of this research include (i) quantifying whether inter-algorithm differences consistently capture observational variability; (ii) identifying whether certain categories of models consistently produce the best results, (iii) assessing the expected sedimentation life-span of several western U.S. reservoirs through long-term simulations.

Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design

NASA Astrophysics Data System (ADS)

Schaffer, J. David

2015-06-01

Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.

SSULI/SSUSI UV Tomographic Images of Large-Scale Plasma Structuring

NASA Astrophysics Data System (ADS)

Hei, M. A.; Budzien, S. A.; Dymond, K.; Paxton, L. J.; Schaefer, R. K.; Groves, K. M.

2015-12-01

We present a new technique that creates tomographic reconstructions of atmospheric ultraviolet emission based on data from the Special Sensor Ultraviolet Limb Imager (SSULI) and the Special Sensor Ultraviolet Spectrographic Imager (SSUSI), both flown on the Defense Meteorological Satellite Program (DMSP) Block 5D3 series satellites. Until now, the data from these two instruments have been used independently of each other. The new algorithm combines SSULI/SSUSI measurements of 135.6 nm emission using the tomographic technique; the resultant data product - whole-orbit reconstructions of atmospheric volume emission within the satellite orbital plane - is substantially improved over the original data sets. Tests using simulated atmospheric emission verify that the algorithm performs well in a variety of situations, including daytime, nighttime, and even in the challenging terminator regions. A comparison with ALTAIR radar data validates that the volume emission reconstructions can be inverted to yield maps of electron density. The algorithm incorporates several innovative new features, including the use of both SSULI and SSUSI data to create tomographic reconstructions, the use of an inversion algorithm (Richardson-Lucy; RL) that explicitly accounts for the Poisson statistics inherent in optical measurements, and a pseudo-diffusion based regularization scheme implemented between iterations of the RL code. The algorithm also explicitly accounts for extinction due to absorption by molecular oxygen.

Validation of the Child Premorbid Intelligence Estimate method to predict premorbid Wechsler Intelligence Scale for Children-Fourth Edition Full Scale IQ among children with brain injury.

PubMed

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H; Suarez, Mariann; Brickell, Tracey A

2008-12-01

Determination of neuropsychological impairment involves contrasting obtained performances with a comparison standard, which is often an estimate of premorbid IQ. M. R. Schoenberg, R. T. Lange, T. A. Brickell, and D. H. Saklofske (2007) proposed the Child Premorbid Intelligence Estimate (CPIE) to predict premorbid Full Scale IQ (FSIQ) using the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV; Wechsler, 2003). The CPIE includes 12 algorithms to predict FSIQ, 1 using demographic variables and 11 algorithms combining WISC-IV subtest raw scores with demographic variables. The CPIE was applied to a sample of children with acquired traumatic brain injury (TBI sample; n = 40) and a healthy demographically matched sample (n = 40). Paired-samples t tests found estimated premorbid FSIQ differed from obtained FSIQ when applied to the TBI sample (ps .02). The demographic only algorithm performed well at a group level, but estimates were restricted in range. Algorithms combining single subtest scores with demographics performed adequately. Results support the clinical application of the CPIE algorithms. However, limitations to estimating individual premorbid ability, including statistical and developmental factors, must be considered. (c) 2008 APA, all rights reserved.

Development and Implementation of a Hardware In-the-Loop Test Bed for Unmanned Aerial Vehicle Control Algorithms

NASA Technical Reports Server (NTRS)

Nyangweso, Emmanuel; Bole, Brian

2014-01-01

Successful prediction and management of battery life using prognostic algorithms through ground and flight tests is important for performance evaluation of electrical systems. This paper details the design of test beds suitable for replicating loading profiles that would be encountered in deployed electrical systems. The test bed data will be used to develop and validate prognostic algorithms for predicting battery discharge time and battery failure time. Online battery prognostic algorithms will enable health management strategies. The platform used for algorithm demonstration is the EDGE 540T electric unmanned aerial vehicle (UAV). The fully designed test beds developed and detailed in this paper can be used to conduct battery life tests by controlling current and recording voltage and temperature to develop a model that makes a prediction of end-of-charge and end-of-life of the system based on rapid state of health (SOH) assessment.

Simulated Stochastic Approximation Annealing for Global Optimization with a Square-Root Cooling Schedule

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liang, Faming; Cheng, Yichen; Lin, Guang

2014-06-13

Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to have such a long CPU time. This paper proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation Markov chain Monte Carlo, it is shown that themore » new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, e.g., a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors.« less

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks.

PubMed

Savalia, Shalin; Emamian, Vahid

2018-05-04

The electrocardiogram (ECG) plays an imperative role in the medical field, as it records heart signal over time and is used to discover numerous cardiovascular diseases. If a documented ECG signal has a certain irregularity in its predefined features, this is called arrhythmia, the types of which include tachycardia, bradycardia, supraventricular arrhythmias, and ventricular, etc. This has encouraged us to do research that consists of distinguishing between several arrhythmias by using deep neural network algorithms such as multi-layer perceptron (MLP) and convolution neural network (CNN). The TensorFlow library that was established by Google for deep learning and machine learning is used in python to acquire the algorithms proposed here. The ECG databases accessible at PhysioBank.com and kaggle.com were used for training, testing, and validation of the MLP and CNN algorithms. The proposed algorithm consists of four hidden layers with weights, biases in MLP, and four-layer convolution neural networks which map ECG samples to the different classes of arrhythmia. The accuracy of the algorithm surpasses the performance of the current algorithms that have been developed by other cardiologists in both sensitivity and precision.

An improved immune algorithm for optimizing the pulse width modulation control sequence of inverters

NASA Astrophysics Data System (ADS)

Sheng, L.; Qian, S. Q.; Ye, Y. Q.; Wu, Y. H.

2017-09-01

In this article, an improved immune algorithm (IIA), based on the fundamental principles of the biological immune system, is proposed for optimizing the pulse width modulation (PWM) control sequence of a single-phase full-bridge inverter. The IIA takes advantage of the receptor editing and adaptive mutation mechanisms of the immune system to develop two operations that enhance the population diversity and convergence of the proposed algorithm. To verify the effectiveness and examine the performance of the IIA, 17 cases are considered, including fixed and disturbed resistances. Simulation results show that the IIA is able to obtain an effective PWM control sequence. Furthermore, when compared with existing immune algorithms (IAs), genetic algorithms (GAs), a non-traditional GA, simplified simulated annealing, and a generalized Hopfield neural network method, the IIA can achieve small total harmonic distortion (THD) and large magnitude. Meanwhile, a non-parametric test indicates that the IIA is significantly better than most comparison algorithms. Supplemental data for this article can be accessed at http://dx.doi.org/10.1080/0305215X.2016.1250894.

Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

PubMed

Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

2015-02-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Detecting an atomic clock frequency anomaly using an adaptive Kalman filter algorithm

NASA Astrophysics Data System (ADS)

Song, Huijie; Dong, Shaowu; Wu, Wenjun; Jiang, Meng; Wang, Weixiong

2018-06-01

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. The Kalman filter algorithm, as a linear optimal algorithm, has been widely used in real-time detection for abnormal frequency. In order to obtain an optimal state estimation, the observation model and dynamic model of the Kalman filter algorithm should satisfy Gaussian white noise conditions. The detection performance is degraded if anomalies affect the observation model or dynamic model. The idea of the adaptive Kalman filter algorithm, applied to clock frequency anomaly detection, uses the residuals given by the prediction for building ‘an adaptive factor’ the prediction state covariance matrix is real-time corrected by the adaptive factor. The results show that the model error is reduced and the detection performance is improved. The effectiveness of the algorithm is verified by the frequency jump simulation, the frequency drift jump simulation and the measured data of the atomic clock by using the chi-square test.

On the performance of explicit and implicit algorithms for transient thermal analysis

NASA Astrophysics Data System (ADS)

Adelman, H. M.; Haftka, R. T.

1980-09-01

The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, have been selected and finite element models of the configurations are discribed. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system and a model of the space shuttle orbiter wing. Calculations were carried out using the SPAR finite element program, the MITAS lumped parameter program and a special purpose finite element program incorporating the GEAR algorithms. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff. Careful attention to modeling detail such as avoiding thin or short high-conducting elements can sometimes reduce the stiffness to the extent that explicit methods become advantageous.

Fast Katz and Commuters: Efficient Estimation of Social Relatedness in Large Networks

NASA Astrophysics Data System (ADS)

Esfandiar, Pooya; Bonchi, Francesco; Gleich, David F.; Greif, Chen; Lakshmanan, Laks V. S.; On, Byung-Won

Motivated by social network data mining problems such as link prediction and collaborative filtering, significant research effort has been devoted to computing topological measures including the Katz score and the commute time. Existing approaches typically approximate all pairwise relationships simultaneously. In this paper, we are interested in computing: the score for a single pair of nodes, and the top-k nodes with the best scores from a given source node. For the pairwise problem, we apply an iterative algorithm that computes upper and lower bounds for the measures we seek. This algorithm exploits a relationship between the Lanczos process and a quadrature rule. For the top-k problem, we propose an algorithm that only accesses a small portion of the graph and is related to techniques used in personalized PageRank computing. To test the scalability and accuracy of our algorithms we experiment with three real-world networks and find that these algorithms run in milliseconds to seconds without any preprocessing.

Progress on automated data analysis algorithms for ultrasonic inspection of composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Forsyth, David S.; Welter, John T.

2015-03-01

Progress is presented on the development and demonstration of automated data analysis (ADA) software to address the burden in interpreting ultrasonic inspection data for large composite structures. The automated data analysis algorithm is presented in detail, which follows standard procedures for analyzing signals for time-of-flight indications and backwall amplitude dropout. New algorithms have been implemented to reliably identify indications in time-of-flight images near the front and back walls of composite panels. Adaptive call criteria have also been applied to address sensitivity to variation in backwall signal level, panel thickness variation, and internal signal noise. ADA processing results are presented for a variety of test specimens that include inserted materials and discontinuities produced under poor manufacturing conditions. Software tools have been developed to support both ADA algorithm design and certification, producing a statistical evaluation of indication results and false calls using a matching process with predefined truth tables. Parametric studies were performed to evaluate detection and false call results with respect to varying algorithm settings.

Definition of an Enhanced Map-Matching Algorithm for Urban Environments with Poor GNSS Signal Quality.

PubMed

Jiménez, Felipe; Monzón, Sergio; Naranjo, Jose Eugenio

2016-02-04

Vehicle positioning is a key factor for numerous information and assistance applications that are included in vehicles and for which satellite positioning is mainly used. However, this positioning process can result in errors and lead to measurement uncertainties. These errors come mainly from two sources: errors and simplifications of digital maps and errors in locating the vehicle. From that inaccurate data, the task of assigning the vehicle's location to a link on the digital map at every instant is carried out by map-matching algorithms. These algorithms have been developed to fulfil that need and attempt to amend these errors to offer the user a suitable positioning. In this research; an algorithm is developed that attempts to solve the errors in positioning when the Global Navigation Satellite System (GNSS) signal reception is frequently lost. The algorithm has been tested with satisfactory results in a complex urban environment of narrow streets and tall buildings where errors and signal reception losses of the GPS receiver are frequent.

Fast katz and commuters : efficient estimation of social relatedness in large networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

On, Byung-Won; Lakshmanan, Laks V. S.; Greif, Chen

Motivated by social network data mining problems such as link prediction and collaborative filtering, significant research effort has been devoted to computing topological measures including the Katz score and the commute time. Existing approaches typically approximate all pairwise relationships simultaneously. In this paper, we are interested in computing: the score for a single pair of nodes, and the top-k nodes with the best scores from a given source node. For the pairwise problem, we apply an iterative algorithm that computes upper and lower bounds for the measures we seek. This algorithm exploits a relationship between the Lanczos process and amore » quadrature rule. For the top-k problem, we propose an algorithm that only accesses a small portion of the graph and is related to techniques used in personalized PageRank computing. To test the scalability and accuracy of our algorithms we experiment with three real-world networks and find that these algorithms run in milliseconds to seconds without any preprocessing.« less

Definition of an Enhanced Map-Matching Algorithm for Urban Environments with Poor GNSS Signal Quality

PubMed Central

Jiménez, Felipe; Monzón, Sergio; Naranjo, Jose Eugenio

2016-01-01

Vehicle positioning is a key factor for numerous information and assistance applications that are included in vehicles and for which satellite positioning is mainly used. However, this positioning process can result in errors and lead to measurement uncertainties. These errors come mainly from two sources: errors and simplifications of digital maps and errors in locating the vehicle. From that inaccurate data, the task of assigning the vehicle’s location to a link on the digital map at every instant is carried out by map-matching algorithms. These algorithms have been developed to fulfil that need and attempt to amend these errors to offer the user a suitable positioning. In this research; an algorithm is developed that attempts to solve the errors in positioning when the Global Navigation Satellite System (GNSS) signal reception is frequently lost. The algorithm has been tested with satisfactory results in a complex urban environment of narrow streets and tall buildings where errors and signal reception losses of the GPS receiver are frequent. PMID:26861320

Comparison of Snow Mass Estimates from a Prototype Passive Microwave Snow Algorithm, a Revised Algorithm and a Snow Depth Climatology

NASA Technical Reports Server (NTRS)

Foster, J. L.; Chang, A. T. C.; Hall, D. K.

1997-01-01

While it is recognized that no single snow algorithm is capable of producing accurate global estimates of snow depth, for research purposes it is useful to test an algorithm's performance in different climatic areas in order to see how it responds to a variety of snow conditions. This study is one of the first to develop separate passive microwave snow algorithms for North America and Eurasia by including parameters that consider the effects of variations in forest cover and crystal size on microwave brightness temperature. A new algorithm (GSFC 1996) is compared to a prototype algorithm (Chang et al., 1987) and to a snow depth climatology (SDC), which for this study is considered to be a standard reference or baseline. It is shown that the GSFC 1996 algorithm compares much more favorably to the SDC than does the Chang et al. (1987) algorithm. For example, in North America in February there is a 15% difference between the GSFC 198-96 Algorithm and the SDC, but with the Chang et al. (1987) algorithm the difference is greater than 50%. In Eurasia, also in February, there is only a 1.3% difference between the GSFC 1996 algorithm and the SDC, whereas with the Chang et al. (1987) algorithm the difference is about 20%. As expected, differences tend to be less when the snow cover extent is greater, particularly for Eurasia. The GSFC 1996 algorithm performs better in North America in each month than dose the Chang et al. (1987) algorithm. This is also the case in Eurasia, except in April and May when the Chang et al.(1987) algorithms is in closer accord to the SDC than is GSFC 1996 algorithm.

Validation of clinical testing for warfarin sensitivity: comparison of CYP2C9-VKORC1 genotyping assays and warfarin-dosing algorithms.

PubMed

Langley, Michael R; Booker, Jessica K; Evans, James P; McLeod, Howard L; Weck, Karen E

2009-05-01

Responses to warfarin (Coumadin) anticoagulation therapy are affected by genetic variability in both the CYP2C9 and VKORC1 genes. Validation of pharmacogenetic testing for warfarin responses includes demonstration of analytical validity of testing platforms and of the clinical validity of testing. We compared four platforms for determining the relevant single nucleotide polymorphisms (SNPs) in both CYP2C9 and VKORC1 that are associated with warfarin sensitivity (Third Wave Invader Plus, ParagonDx/Cepheid Smart Cycler, Idaho Technology LightCycler, and AutoGenomics Infiniti). Each method was examined for accuracy, cost, and turnaround time. All genotyping methods demonstrated greater than 95% accuracy for identifying the relevant SNPs (CYP2C9 *2 and *3; VKORC1 -1639 or 1173). The ParagonDx and Idaho Technology assays had the shortest turnaround and hands-on times. The Third Wave assay was readily scalable to higher test volumes but had the longest hands-on time. The AutoGenomics assay interrogated the largest number of SNPs but had the longest turnaround time. Four published warfarin-dosing algorithms (Washington University, UCSF, Louisville, and Newcastle) were compared for accuracy for predicting warfarin dose in a retrospective analysis of a local patient population on long-term, stable warfarin therapy. The predicted doses from both the Washington University and UCSF algorithms demonstrated the best correlation with actual warfarin doses.

Self-Reported HIV-Positive Status But Subsequent HIV-Negative Test Result Using Rapid Diagnostic Testing Algorithms Among Seven Sub-Saharan African Military Populations

DTIC Science & Technology

2017-07-07

RESEARCH ARTICLE Self-reported HIV-positive status but subsequent HIV-negative test result using rapid diagnostic testing algorithms among seven sub...America * judith.harbertson.ctr@mail.mil Abstract HIV rapid diagnostic tests (RDTs) combined in an algorithm are the current standard for HIV diagnosis...in many sub-Saharan African countries, and extensive laboratory testing has con- firmed HIV RDTs have excellent sensitivity and specificity. However

Development of Online Cognitive and Algorithm Tests as Assessment Tools in Introductory Computer Science Courses

ERIC Educational Resources Information Center

Avancena, Aimee Theresa; Nishihara, Akinori; Vergara, John Paul

2012-01-01

This paper presents the online cognitive and algorithm tests, which were developed in order to determine if certain cognitive factors and fundamental algorithms correlate with the performance of students in their introductory computer science course. The tests were implemented among Management Information Systems majors from the Philippines and…

Testing Algorithmic Skills in Traditional and Non-Traditional Programming Environments

ERIC Educational Resources Information Center

Csernoch, Mária; Biró, Piroska; Máth, János; Abari, Kálmán

2015-01-01

The Testing Algorithmic and Application Skills (TAaAS) project was launched in the 2011/2012 academic year to test first year students of Informatics, focusing on their algorithmic skills in traditional and non-traditional programming environments, and on the transference of their knowledge of Informatics from secondary to tertiary education. The…

A fast and robust bulk-loading algorithm for indexing very large digital elevation datasets II. Experimental results

NASA Astrophysics Data System (ADS)

Rodríguez, Félix R.; Barrena, Manuel

2011-07-01

The spatial indexing of eventually all the available topographic information of Earth is a highly valuable tool for different geoscientific application domains. The Shuttle Radar Topography Mission (SRTM) collected and made available to the public one of the world's largest digital elevation models (DEMs). With the aim of providing on easier and faster access to these data by improving their further analysis and processing, we have indexed the SRTM DEM by means of a spatial index based on the kd-tree data structure, called the Q-tree. This paper is the second in a two-part series that includes a thorough performance analysis to validate the bulk-load algorithm efficiency of the Q-tree. We investigate performance measuring elapsed time in different contexts, analyzing disk space usage, testing response time with typical queries, and validating the final index structure balance. In addition, the paper includes performance comparisons with Oracle 11g that helps to understand the real cost of our proposal. Our tests prove that the proposed algorithm outperforms Oracle 11g using around a 9% of the elapsed time, taking six times less storage with more than 96% of page utilization, and getting faster response times to spatial queries issued on 4.5 million points. In addition to this, the behavior of the spatial index has been successfully tested on both an open GIS (VT Builder) and a visualizer tool derived from the previous one.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keyes, D.; McInnes, L. C.; Woodward, C.

This report is an outcome of the workshop Multiphysics Simulations: Challenges and Opportunities, sponsored by the Institute of Computing in Science (ICiS). Additional information about the workshop, including relevant reading and presentations on multiphysics issues in applications, algorithms, and software, is available via https://sites.google.com/site/icismultiphysics2011/. We consider multiphysics applications from algorithmic and architectural perspectives, where 'algorithmic' includes both mathematical analysis and computational complexity and 'architectural' includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not alwaysmore » practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities. We also initiate a modest suite of test problems encompassing features present in many applications.« less

Dimension from covariance matrices.

PubMed

Carroll, T L; Byers, J M

2017-02-01

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

GPU Acceleration of DSP for Communication Receivers.

PubMed

Gunther, Jake; Gunther, Hyrum; Moon, Todd

2017-09-01

Graphics processing unit (GPU) implementations of signal processing algorithms can outperform CPU-based implementations. This paper describes the GPU implementation of several algorithms encountered in a wide range of high-data rate communication receivers including filters, multirate filters, numerically controlled oscillators, and multi-stage digital down converters. These structures are tested by processing the 20 MHz wide FM radio band (88-108 MHz). Two receiver structures are explored: a single channel receiver and a filter bank channelizer. Both run in real time on NVIDIA GeForce GTX 1080 graphics card.

Evaluation of bioMérieux's Dissociated Vidas Lyme IgM II and IgG II as a First-Tier Diagnostic Assay for Lyme Disease

PubMed Central

Delorey, Mark J.; Replogle, Adam; Sexton, Christopher; Schriefer, Martin E.

2017-01-01

ABSTRACT The recommended laboratory diagnostic approach for Lyme disease is a standard two-tiered testing (STTT) algorithm where the first tier is typically an enzyme immunoassay (EIA) that if positive or equivocal is reflexed to Western immunoblotting as the second tier. bioMérieux manufactures one of the most commonly used first-tier EIAs in the United States, the combined IgM/IgG Vidas test (LYT). Recently, bioMérieux launched its dissociated first-tier tests, the Vidas Lyme IgM II (LYM) and IgG II (LYG) EIAs, which use purified recombinant test antigens and a different algorithm than STTT. The dissociated LYM/LYG EIAs were evaluated against the combined LYT EIA using samples from 471 well-characterized Lyme patients and controls. Statistical analyses were conducted to assess the performance of these EIAs as first-tier tests and when used in two-tiered algorithms, including a modified two-tiered testing (MTTT) approach where the second-tier test was a C6 EIA. Similar sensitivities and specificities were obtained for the two testing strategies (LYT versus LYM/LYG) when used as first-tier tests (sensitivity, 83 to 85%; specificity, 85 to 88%) with an observed agreement of 80%. Sensitivities of 68 to 69% and 76 to 77% and specificities of 97% and 98 to 99% resulted when the two EIA strategies were followed by Western immunoblotting and when used in an MTTT, respectively. The MTTT approach resulted in significantly higher sensitivities than did STTT. Overall, the LYM/LYG EIAs performed equivalently to the LYT EIA in test-to-test comparisons or as first-tier assays in STTT or MTTT with few exceptions. PMID:28330884

Central safety factor and β N control on NSTX-U via beam power and plasma boundary shape modification, using TRANSP for closed loop simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyer, M. D.; Andre, R.; Gates, D. A.

The high-performance operational goals of NSTX-U will require development of advanced feedback control algorithms, including control of ßN and the safety factor profile. In this work, a novel approach to simultaneously controlling ßN and the value of the safety factor on the magnetic axis, q0, through manipulation of the plasma boundary shape and total beam power, is proposed. Simulations of the proposed scheme show promising results and motivate future experimental implementation and eventual integration into a more complex current profile control scheme planned to include actuation of individual beam powers, density, and loop voltage. As part of this work, amore » flexible framework for closed loop simulations within the high-fidelity code TRANSP was developed. The framework, used here to identify control-design-oriented models and to tune and test the proposed controller, exploits many of the predictive capabilities of TRANSP and provides a means for performing control calculations based on user-supplied data (controller matrices, target waveforms, etc.). The flexible framework should enable high-fidelity testing of a variety of control algorithms, thereby reducing the amount of expensive experimental time needed to implement new control algorithms on NSTX-U and other devices.« less

Central safety factor and βN control on NSTX-U via beam power and plasma boundary shape modification, using TRANSP for closed loop simulations

NASA Astrophysics Data System (ADS)

Boyer, M. D.; Andre, R.; Gates, D. A.; Gerhardt, S.; Goumiri, I. R.; Menard, J.

2015-05-01

The high-performance operational goals of NSTX-U will require development of advanced feedback control algorithms, including control of βN and the safety factor profile. In this work, a novel approach to simultaneously controlling βN and the value of the safety factor on the magnetic axis, q0, through manipulation of the plasma boundary shape and total beam power, is proposed. Simulations of the proposed scheme show promising results and motivate future experimental implementation and eventual integration into a more complex current profile control scheme planned to include actuation of individual beam powers, density, and loop voltage. As part of this work, a flexible framework for closed loop simulations within the high-fidelity code TRANSP was developed. The framework, used here to identify control-design-oriented models and to tune and test the proposed controller, exploits many of the predictive capabilities of TRANSP and provides a means for performing control calculations based on user-supplied data (controller matrices, target waveforms, etc). The flexible framework should enable high-fidelity testing of a variety of control algorithms, thereby reducing the amount of expensive experimental time needed to implement new control algorithms on NSTX-U and other devices.

Computerized classification of proximal occlusion in the left anterior descending coronary artery.

PubMed

Gregg, Richard E; Nikus, Kjell C; Zhou, Sophia H; Startt Selvester, Ronald H; Barbara, Victoria

2010-01-01

Proximal occlusion within the left anterior descending (LAD) coronary artery in patients with acute myocardial infarction leads to higher mortality than does nonproximal occlusion. We evaluated an automated program to detect proximal LAD occlusion. All patients with suspected acute coronary syndrome (n = 7,710) presenting consecutively to the emergency department of a local hospital with a coronary angiogram–confirmed flow-limiting lesion and notation of occlusion site were included in the study (n = 711). Electrocardiograms (ECGs) that met ST-segment elevation myocardial infarction (STEMI) criteria were included in the training set (n = 183). Paired angiographic location of proximal LAD and ECGs with ST elevation in the anterolateral region were used for the computer program development (n = 36). The test set was based on ECG criteria for anterolateral STEMI only without angiographic reports (n = 162). Tested against 2 expert cardiologists' agreed reading of proximal LAD occlusion, the algorithm has a sensitivity of 95% and a specificity of 82%. The algorithm is designed to have high sensitivity rather than high specificity for the purpose of not missing any proximal LAD in the STEMI population. Our preliminary evaluation suggests that the algorithm can detect proximal LAD occlusion as an additional interpretation to STEMI detection with similar accuracy as cardiologist readers.

Multiagency Urban Search Experiment Detector and Algorithm Test Bed

NASA Astrophysics Data System (ADS)

Nicholson, Andrew D.; Garishvili, Irakli; Peplow, Douglas E.; Archer, Daniel E.; Ray, William R.; Swinney, Mathew W.; Willis, Michael J.; Davidson, Gregory G.; Cleveland, Steven L.; Patton, Bruce W.; Hornback, Donald E.; Peltz, James J.; McLean, M. S. Lance; Plionis, Alexander A.; Quiter, Brian J.; Bandstra, Mark S.

2017-07-01

In order to provide benchmark data sets for radiation detector and algorithm development, a particle transport test bed has been created using experimental data as model input and validation. A detailed radiation measurement campaign at the Combined Arms Collective Training Facility in Fort Indiantown Gap, PA (FTIG), USA, provides sample background radiation levels for a variety of materials present at the site (including cinder block, gravel, asphalt, and soil) using long dwell high-purity germanium (HPGe) measurements. In addition, detailed light detection and ranging data and ground-truth measurements inform model geometry. This paper describes the collected data and the application of these data to create background and injected source synthetic data for an arbitrary gamma-ray detection system using particle transport model detector response calculations and statistical sampling. In the methodology presented here, HPGe measurements inform model source terms while detector response calculations are validated via long dwell measurements using 2"×4"×16" NaI(Tl) detectors at a variety of measurement points. A collection of responses, along with sampling methods and interpolation, can be used to create data sets to gauge radiation detector and algorithm (including detection, identification, and localization) performance under a variety of scenarios. Data collected at the FTIG site are available for query, filtering, visualization, and download at muse.lbl.gov.

RNA design rules from a massive open laboratory

PubMed Central

Lee, Jeehyung; Kladwang, Wipapat; Lee, Minjae; Cantu, Daniel; Azizyan, Martin; Kim, Hanjoo; Limpaecher, Alex; Gaikwad, Snehal; Yoon, Sungroh; Treuille, Adrien; Das, Rhiju

2014-01-01

Self-assembling RNA molecules present compelling substrates for the rational interrogation and control of living systems. However, imperfect in silico models—even at the secondary structure level—hinder the design of new RNAs that function properly when synthesized. Here, we present a unique and potentially general approach to such empirical problems: the Massive Open Laboratory. The EteRNA project connects 37,000 enthusiasts to RNA design puzzles through an online interface. Uniquely, EteRNA participants not only manipulate simulated molecules but also control a remote experimental pipeline for high-throughput RNA synthesis and structure mapping. We show herein that the EteRNA community leveraged dozens of cycles of continuous wet laboratory feedback to learn strategies for solving in vitro RNA design problems on which automated methods fail. The top strategies—including several previously unrecognized negative design rules—were distilled by machine learning into an algorithm, EteRNABot. Over a rigorous 1-y testing phase, both the EteRNA community and EteRNABot significantly outperformed prior algorithms in a dozen RNA secondary structure design tests, including the creation of dendrimer-like structures and scaffolds for small molecule sensors. These results show that an online community can carry out large-scale experiments, hypothesis generation, and algorithm design to create practical advances in empirical science. PMID:24469816

A Preliminary Analysis of Keystroke Log Data from a Timed Writing Task. Research Report. ETS RR-12-23

ERIC Educational Resources Information Center

Almond, Russell; Deane, Paul; Quinlan, Thomas; Wagner, Michael; Sydorenko, Tetyana

2012-01-01

The Fall 2007 and Spring 2008 pilot tests for the "CBAL"™ Writing assessment included experimental keystroke logging capabilities. This report documents the approaches used to capture the keystroke logs and the algorithms used to process the outputs. It also includes some preliminary findings based on the pilot data. In particular, it…

Two-IMU FDI performance of the sequential probability ratio test during shuttle entry

NASA Technical Reports Server (NTRS)

Rich, T. M.

1976-01-01

Performance data for the sequential probability ratio test (SPRT) during shuttle entry are presented. Current modeling constants and failure thresholds are included for the full mission 3B from entry through landing trajectory. Minimum 100 percent detection/isolation failure levels and a discussion of the effects of failure direction are presented. Finally, a limited comparison of failures introduced at trajectory initiation shows that the SPRT algorithm performs slightly worse than the data tracking test.

Recent advances on terrain database correlation testing

NASA Astrophysics Data System (ADS)

Sakude, Milton T.; Schiavone, Guy A.; Morelos-Borja, Hector; Martin, Glenn; Cortes, Art

1998-08-01

Terrain database correlation is a major requirement for interoperability in distributed simulation. There are numerous situations in which terrain database correlation problems can occur that, in turn, lead to lack of interoperability in distributed training simulations. Examples are the use of different run-time terrain databases derived from inconsistent on source data, the use of different resolutions, and the use of different data models between databases for both terrain and culture data. IST has been developing a suite of software tools, named ZCAP, to address terrain database interoperability issues. In this paper we discuss recent enhancements made to this suite, including improved algorithms for sampling and calculating line-of-sight, an improved method for measuring terrain roughness, and the application of a sparse matrix method to the terrain remediation solution developed at the Visual Systems Lab of the Institute for Simulation and Training. We review the application of some of these new algorithms to the terrain correlation measurement processes. The application of these new algorithms improves our support for very large terrain databases, and provides the capability for performing test replications to estimate the sampling error of the tests. With this set of tools, a user can quantitatively assess the degree of correlation between large terrain databases.

A hybrid algorithm for clustering of time series data based on affinity search technique.

PubMed

Aghabozorgi, Saeed; Ying Wah, Teh; Herawan, Tutut; Jalab, Hamid A; Shaygan, Mohammad Amin; Jalali, Alireza

2014-01-01

Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impracticality results in poor clustering accuracy in several systems. In this paper, a new hybrid clustering algorithm is proposed based on the similarity in shape of time series data. Time series data are first grouped as subclusters based on similarity in time. The subclusters are then merged using the k-Medoids algorithm based on similarity in shape. This model has two contributions: (1) it is more accurate than other conventional and hybrid approaches and (2) it determines the similarity in shape among time series data with a low complexity. To evaluate the accuracy of the proposed model, the model is tested extensively using syntactic and real-world time series datasets.

Computational Workbench for Multibody Dynamics

NASA Technical Reports Server (NTRS)

Edmonds, Karina

2007-01-01

PyCraft is a computer program that provides an interactive, workbenchlike computing environment for developing and testing algorithms for multibody dynamics. Examples of multibody dynamic systems amenable to analysis with the help of PyCraft include land vehicles, spacecraft, robots, and molecular models. PyCraft is based on the Spatial-Operator- Algebra (SOA) formulation for multibody dynamics. The SOA operators enable construction of simple and compact representations of complex multibody dynamical equations. Within the Py-Craft computational workbench, users can, essentially, use the high-level SOA operator notation to represent the variety of dynamical quantities and algorithms and to perform computations interactively. PyCraft provides a Python-language interface to underlying C++ code. Working with SOA concepts, a user can create and manipulate Python-level operator classes in order to implement and evaluate new dynamical quantities and algorithms. During use of PyCraft, virtually all SOA-based algorithms are available for computational experiments.

A Hybrid Algorithm for Clustering of Time Series Data Based on Affinity Search Technique

PubMed Central

Aghabozorgi, Saeed; Ying Wah, Teh; Herawan, Tutut; Jalab, Hamid A.; Shaygan, Mohammad Amin; Jalali, Alireza

2014-01-01

Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impracticality results in poor clustering accuracy in several systems. In this paper, a new hybrid clustering algorithm is proposed based on the similarity in shape of time series data. Time series data are first grouped as subclusters based on similarity in time. The subclusters are then merged using the k-Medoids algorithm based on similarity in shape. This model has two contributions: (1) it is more accurate than other conventional and hybrid approaches and (2) it determines the similarity in shape among time series data with a low complexity. To evaluate the accuracy of the proposed model, the model is tested extensively using syntactic and real-world time series datasets. PMID:24982966

A novel orthoimage mosaic method using the weighted A* algorithm for UAV imagery

NASA Astrophysics Data System (ADS)

Zheng, Maoteng; Zhou, Shunping; Xiong, Xiaodong; Zhu, Junfeng

2017-12-01

A weighted A* algorithm is proposed to select optimal seam-lines in orthoimage mosaic for UAV (Unmanned Aircraft Vehicle) imagery. The whole workflow includes four steps: the initial seam-line network is firstly generated by standard Voronoi Diagram algorithm; an edge diagram is then detected based on DSM (Digital Surface Model) data; the vertices (conjunction nodes) of initial network are relocated since some of them are on the high objects (buildings, trees and other artificial structures); and, the initial seam-lines are finally refined using the weighted A* algorithm based on the edge diagram and the relocated vertices. The method was tested with two real UAV datasets. Preliminary results show that the proposed method produces acceptable mosaic images in both the urban and mountainous areas, and is better than the result of the state-of-the-art methods on the datasets.

Concurrent approach for evolving compact decision rule sets

NASA Astrophysics Data System (ADS)

Marmelstein, Robert E.; Hammack, Lonnie P.; Lamont, Gary B.

1999-02-01

The induction of decision rules from data is important to many disciplines, including artificial intelligence and pattern recognition. To improve the state of the art in this area, we introduced the genetic rule and classifier construction environment (GRaCCE). It was previously shown that GRaCCE consistently evolved decision rule sets from data, which were significantly more compact than those produced by other methods (such as decision tree algorithms). The primary disadvantage of GRaCCe, however, is its relatively poor run-time execution performance. In this paper, a concurrent version of the GRaCCE architecture is introduced, which improves the efficiency of the original algorithm. A prototype of the algorithm is tested on an in- house parallel processor configuration and the results are discussed.

Validating Retinal Fundus Image Analysis Algorithms: Issues and a Proposal

PubMed Central

Trucco, Emanuele; Ruggeri, Alfredo; Karnowski, Thomas; Giancardo, Luca; Chaum, Edward; Hubschman, Jean Pierre; al-Diri, Bashir; Cheung, Carol Y.; Wong, Damon; Abràmoff, Michael; Lim, Gilbert; Kumar, Dinesh; Burlina, Philippe; Bressler, Neil M.; Jelinek, Herbert F.; Meriaudeau, Fabrice; Quellec, Gwénolé; MacGillivray, Tom; Dhillon, Bal

2013-01-01

This paper concerns the validation of automatic retinal image analysis (ARIA) algorithms. For reasons of space and consistency, we concentrate on the validation of algorithms processing color fundus camera images, currently the largest section of the ARIA literature. We sketch the context (imaging instruments and target tasks) of ARIA validation, summarizing the main image analysis and validation techniques. We then present a list of recommendations focusing on the creation of large repositories of test data created by international consortia, easily accessible via moderated Web sites, including multicenter annotations by multiple experts, specific to clinical tasks, and capable of running submitted software automatically on the data stored, with clear and widely agreed-on performance criteria, to provide a fair comparison. PMID:23794433

Novel probabilistic neuroclassifier

NASA Astrophysics Data System (ADS)

Hong, Jiang; Serpen, Gursel

2003-09-01

A novel probabilistic potential function neural network classifier algorithm to deal with classes which are multi-modally distributed and formed from sets of disjoint pattern clusters is proposed in this paper. The proposed classifier has a number of desirable properties which distinguish it from other neural network classifiers. A complete description of the algorithm in terms of its architecture and the pseudocode is presented. Simulation analysis of the newly proposed neuro-classifier algorithm on a set of benchmark problems is presented. Benchmark problems tested include IRIS, Sonar, Vowel Recognition, Two-Spiral, Wisconsin Breast Cancer, Cleveland Heart Disease and Thyroid Gland Disease. Simulation results indicate that the proposed neuro-classifier performs consistently better for a subset of problems for which other neural classifiers perform relatively poorly.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le, Hai P.; Cambier, Jean -Luc

Here, we present a numerical model and a set of conservative algorithms for Non-Maxwellian plasma kinetics with inelastic collisions. These algorithms self-consistently solve for the time evolution of an isotropic electron energy distribution function interacting with an atomic state distribution function of an arbitrary number of levels through collisional excitation, deexcitation, as well as ionization and recombination. Electron-electron collisions, responsible for thermalization of the electron distribution, are also included in the model. The proposed algorithms guarantee mass/charge and energy conservation in a single step, and is applied to the case of non-uniform gridding of the energy axis in the phasemore » space of the electron distribution function. Numerical test cases are shown to demonstrate the accuracy of the method and its conservation properties.« less

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

NASA Technical Reports Server (NTRS)

Baluja, Shumeet

1995-01-01

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

Learning Extended Finite State Machines

NASA Technical Reports Server (NTRS)

Cassel, Sofia; Howar, Falk; Jonsson, Bengt; Steffen, Bernhard

2014-01-01

We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.

Design of automata theory of cubical complexes with applications to diagnosis and algorithmic description

NASA Technical Reports Server (NTRS)

Roth, J. P.

1972-01-01

The following problems are considered: (1) methods for development of logic design together with algorithms, so that it is possible to compute a test for any failure in the logic design, if such a test exists, and developing algorithms and heuristics for the purpose of minimizing the computation for tests; and (2) a method of design of logic for ultra LSI (large scale integration). It was discovered that the so-called quantum calculus can be extended to render it possible: (1) to describe the functional behavior of a mechanism component by component, and (2) to compute tests for failures, in the mechanism, using the diagnosis algorithm. The development of an algorithm for the multioutput two-level minimization problem is presented and the program MIN 360 was written for this algorithm. The program has options of mode (exact minimum or various approximations), cost function, cost bound, etc., providing flexibility.

Use of data mining to predict significant factors and benefits of bilateral cochlear implantation.

PubMed

Ramos-Miguel, Angel; Perez-Zaballos, Teresa; Perez, Daniel; Falconb, Juan Carlos; Ramosb, Angel

2015-11-01

Data mining (DM) is a technique used to discover pattern and knowledge from a big amount of data. It uses artificial intelligence, automatic learning, statistics, databases, etc. In this study, DM was successfully used as a predictive tool to assess disyllabic speech test performance in bilateral implanted patients with a success rate above 90%. 60 bilateral sequentially implanted adult patients were included in the study. The DM algorithms developed found correlations between unilateral medical records and Audiological test results and bilateral performance by establishing relevant variables based on two DM techniques: the classifier and the estimation. The nearest neighbor algorithm was implemented in the first case, and the linear regression in the second. The results showed that patients with unilateral disyllabic test results below 70% benefited the most from a bilateral implantation. Finally, it was observed that its benefits decrease as the inter-implant time increases.

A Boundary Condition Relaxation Algorithm for Strongly Coupled, Ablating Flows Including Shape Change

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Johnston, Christopher O.

2011-01-01

Implementations of a model for equilibrium, steady-state ablation boundary conditions are tested for the purpose of providing strong coupling with a hypersonic flow solver. The objective is to remove correction factors or film cooling approximations that are usually applied in coupled implementations of the flow solver and the ablation response. Three test cases are considered - the IRV-2, the Galileo probe, and a notional slender, blunted cone launched at 10 km/s from the Earth's surface. A successive substitution is employed and the order of succession is varied as a function of surface temperature to obtain converged solutions. The implementation is tested on a specified trajectory for the IRV-2 to compute shape change under the approximation of steady-state ablation. Issues associated with stability of the shape change algorithm caused by explicit time step limits are also discussed.

Clinical Characteristics and Associated Systemic Diseases in Patients With Esophageal "Absent Contractility"-A Clinical Algorithm.

PubMed

Laique, Sobia; Singh, Tavankit; Dornblaser, David; Gadre, Abhishek; Rangan, Vikram; Fass, Ronnie; Kirby, Donald; Chatterjee, Soumya; Gabbard, Scott

2018-01-19

This study was carried out to assess the clinical characteristics and associated systemic diseases seen in patients diagnosed with absent contractility as per the Chicago Classification version 3.0, allowing us to propose a diagnostic algorithm for their etiologic testing. The Chicago Classification version 3.0 has redefined major and minor esophageal motility disorders using high-resolution esophageal manometry. There is a dearth of publications based on research on absent contractility, which historically has been associated with myopathic processes such as systemic sclerosis (SSc). We conducted a retrospective, multicenter study. Data of patients diagnosed with absent contractility were pooled from Cleveland Clinic, Cleveland, OH (January 2006 to July 2016) and Metrohealth Medical Center, Cleveland, OH (July 2014 to July 2016) and included: age, gender, associated medical conditions, surgical history, medications, and specific antibody testing. A total of 207 patients, including 57 male individuals and 150 female individuals, with mean age of 56.1 and 60.0 years, respectively, were included. Disease distribution was as follows: SSc (diffuse or limited cutaneous) 132, overlap syndromes 7, systemic lupus erythematosus17, Sjögren syndrome 4, polymyositis 3, and dermatomyositis 3. Various other etiologies including gastroesophageal reflux disease, postradiation esophagitis, neuromuscular disorders, and surgical complications were seen in the remaining cohort. Most practitioners use the term "absent contractility" interchangeably with "scleroderma esophagus"; however, only 63% of patients with absent contractility had SSc. Overall, 20% had another systemic autoimmune rheumatologic disease and 16% had a nonrheumatologic etiology for absent contractility. Therefore, alternate diagnosis must be sought in these patients. We propose an algorithm for their etiologic evaluation.

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

NASA Technical Reports Server (NTRS)

Olson, William S.; Grecu, Mircea; Yang, Song; Tao, Wei-Kuo

2004-01-01

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression of random errors requires averaging to at least half-degree resolution. Analysis of mesoscale and larger space-time scale phenomena based upon passive and passive/active microwave heating estimates from TRMM, SSMI, and AMSR data will be presented at the conference.

Automated detection of hospital outbreaks: A systematic review of methods

PubMed Central

Buckeridge, David L.; Lepelletier, Didier

2017-01-01

Objectives Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results. Methods We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies. Results Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%. Conclusion Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results. PMID:28441422

Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails

PubMed Central

2012-01-01

Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742

Generalization of the Lord-Wingersky Algorithm to Computing the Distribution of Summed Test Scores Based on Real-Number Item Scores

ERIC Educational Resources Information Center

Kim, Seonghoon

2013-01-01

With known item response theory (IRT) item parameters, Lord and Wingersky provided a recursive algorithm for computing the conditional frequency distribution of number-correct test scores, given proficiency. This article presents a generalized algorithm for computing the conditional distribution of summed test scores involving real-number item…

Cryptography: Cracking Codes.

ERIC Educational Resources Information Center

Myerscough, Don; And Others

1996-01-01

Describes an activity whose objectives are to encode and decode messages using linear functions and their inverses; to use modular arithmetic, including use of the reciprocal for simple equation solving; to analyze patterns and make and test conjectures; to communicate procedures and algorithms; and to use problem-solving strategies. (ASK)

Constructing Aligned Assessments Using Automated Test Construction

ERIC Educational Resources Information Center

Porter, Andrew; Polikoff, Morgan S.; Barghaus, Katherine M.; Yang, Rui

2013-01-01

We describe an innovative automated test construction algorithm for building aligned achievement tests. By incorporating the algorithm into the test construction process, along with other test construction procedures for building reliable and unbiased assessments, the result is much more valid tests than result from current test construction…

On the suitability of different representations of solid catalysts for combinatorial library design by genetic algorithms.

PubMed

Gobin, Oliver C; Schüth, Ferdi

2008-01-01

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Substructure System Identification for Finite Element Model Updating

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.; Blades, Eric L.

1997-01-01

This report summarizes research conducted under a NASA grant on the topic 'Substructure System Identification for Finite Element Model Updating.' The research concerns ongoing development of the Substructure System Identification Algorithm (SSID Algorithm), a system identification algorithm that can be used to obtain mathematical models of substructures, like Space Shuttle payloads. In the present study, particular attention was given to the following topics: making the algorithm robust to noisy test data, extending the algorithm to accept experimental FRF data that covers a broad frequency bandwidth, and developing a test analytical model (TAM) for use in relating test data to reduced-order finite element models.

Clinical algorithms for the diagnosis and prognosis of interstitial lung disease in systemic sclerosis.

PubMed

Hax, Vanessa; Bredemeier, Markus; Didonet Moro, Ana Laura; Pavan, Thaís Rohde; Vieira, Marcelo Vasconcellos; Pitrez, Eduardo Hennemann; da Silva Chakr, Rafael Mendonça; Xavier, Ricardo Machado

2017-10-01

Interstitial lung disease (ILD) is currently the primary cause of death in systemic sclerosis (SSc). Thoracic high-resolution computed tomography (HRCT) is considered the gold standard for diagnosis. Recent studies have proposed several clinical algorithms to predict the diagnosis and prognosis of SSc-ILD. To test the clinical algorithms to predict the presence and prognosis of SSc-ILD and to evaluate the association of extent of ILD with mortality in a cohort of SSc patients. Retrospective cohort study, including 177 SSc patients assessed by clinical evaluation, laboratory tests, pulmonary function tests, and HRCT. Three clinical algorithms, combining lung auscultation, chest radiography, and percentage predicted forced vital capacity (FVC), were applied for the diagnosis of different extents of ILD on HRCT. Univariate and multivariate Cox proportional models were used to analyze the association of algorithms and the extent of ILD on HRCT with the risk of death using hazard ratios (HR). The prevalence of ILD on HRCT was 57.1% and 79 patients died (44.6%) in a median follow-up of 11.1 years. For identification of ILD with extent ≥10% and ≥20% on HRCT, all algorithms presented a high sensitivity (>89%) and a very low negative likelihood ratio (<0.16). For prognosis, survival was decreased for all algorithms, especially the algorithm C (HR = 3.47, 95% CI: 1.62-7.42), which identified the presence of ILD based on crackles on lung auscultation, findings on chest X-ray, or FVC <80%. Extensive disease as proposed by Goh et al. (extent of ILD > 20% on HRCT or, in indeterminate cases, FVC < 70%) had a significantly higher risk of death (HR = 3.42, 95% CI: 2.12-5.52). Survival was not different between patients with extent of 10% or 20% of ILD on HRCT, and analysis of 10-year mortality suggested that a threshold of 10% may also have a good predictive value for mortality. However, there is no clear cutoff above which mortality is sharply increased. Clinical algorithms had a good diagnostic performance for extents of SSc-ILD on HRCT with clinical and prognostic relevance (≥10% and ≥20%), and were also strongly related to mortality. Non-HRCT-based algorithms could be useful when HRCT is not available. This is the first study to replicate the prognostic algorithm proposed by Goh et al. in a developing country. Copyright © 2017 Elsevier Inc. All rights reserved.

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

Predicting Vasovagal Syncope from Heart Rate and Blood Pressure: A Prospective Study in 140 Subjects.

PubMed

Virag, Nathalie; Erickson, Mark; Taraborrelli, Patricia; Vetter, Rolf; Lim, Phang Boon; Sutton, Richard

2018-04-28

We developed a vasovagal syncope (VVS) prediction algorithm for use during head-up tilt with simultaneous analysis of heart rate (HR) and systolic blood pressure (SBP). We previously tested this algorithm retrospectively in 1155 subjects, showing sensitivity 95%, specificity 93% and median prediction time of 59s. This study was prospective, single center, on 140 subjects to evaluate this VVS prediction algorithm and assess if retrospective results were reproduced and clinically relevant. Primary endpoint was VVS prediction: sensitivity and specificity >80%. In subjects, referred for 60° head-up tilt (Italian protocol), non-invasive HR and SBP were supplied to the VVS prediction algorithm: simultaneous analysis of RR intervals, SBP trends and their variability represented by low-frequency power generated cumulative risk which was compared with a predetermined VVS risk threshold. When cumulative risk exceeded threshold, an alert was generated. Prediction time was duration between first alert and syncope. Of 140 subjects enrolled, data was usable for 134. Of 83 tilt+ve (61.9%), 81 VVS events were correctly predicted and of 51 tilt-ve subjects (38.1%), 45 were correctly identified as negative by the algorithm. Resulting algorithm performance was sensitivity 97.6%, specificity 88.2%, meeting primary endpoint. Mean VVS prediction time was 2min 26s±3min16s with median 1min 25s. Using only HR and HR variability (without SBP) the mean prediction time reduced to 1min34s±1min45s with median 1min13s. The VVS prediction algorithm, is clinically-relevant tool and could offer applications including providing a patient alarm, shortening tilt-test time, or triggering pacing intervention in implantable devices. Copyright © 2018. Published by Elsevier Inc.

Verification of ICESat-2/ATLAS Science Receiver Algorithm Onboard Databases

NASA Astrophysics Data System (ADS)

Carabajal, C. C.; Saba, J. L.; Leigh, H. W.; Magruder, L. A.; Urban, T. J.; Mcgarry, J.; Schutz, B. E.

2013-12-01

NASA's ICESat-2 mission will fly the Advanced Topographic Laser Altimetry System (ATLAS) instrument on a 3-year mission scheduled to launch in 2016. ATLAS is a single-photon detection system transmitting at 532nm with a laser repetition rate of 10 kHz, and a 6 spot pattern on the Earth's surface. A set of onboard Receiver Algorithms will perform signal processing to reduce the data rate and data volume to acceptable levels. These Algorithms distinguish surface echoes from the background noise, limit the daily data volume, and allow the instrument to telemeter only a small vertical region about the signal. For this purpose, three onboard databases are used: a Surface Reference Map (SRM), a Digital Elevation Model (DEM), and a Digital Relief Maps (DRMs). The DEM provides minimum and maximum heights that limit the signal search region of the onboard algorithms, including a margin for errors in the source databases, and onboard geolocation. Since the surface echoes will be correlated while noise will be randomly distributed, the signal location is found by histogramming the received event times and identifying the histogram bins with statistically significant counts. Once the signal location has been established, the onboard Digital Relief Maps (DRMs) will be used to determine the vertical width of the telemetry band about the signal. University of Texas-Center for Space Research (UT-CSR) is developing the ICESat-2 onboard databases, which are currently being tested using preliminary versions and equivalent representations of elevation ranges and relief more recently developed at Goddard Space Flight Center (GSFC). Global and regional elevation models have been assessed in terms of their accuracy using ICESat geodetic control, and have been used to develop equivalent representations of the onboard databases for testing against the UT-CSR databases, with special emphasis on the ice sheet regions. A series of verification checks have been implemented, including comparisons against ICESat altimetry for selected regions with tall vegetation and high relief. The extensive verification effort by the Receiver Algorithm team at GSFC is aimed at assuring that the onboard databases are sufficiently accurate. We will present the results of those assessments and verification tests, along with measures taken to implement modifications to the databases to optimize their use by the receiver algorithms. Companion presentations by McGarry et al. and Leigh et al. describe the details on the ATLAS Onboard Receiver Algorithms and databases development, respectively.

An efficient mosaic algorithm considering seasonal variation: application to KOMPSAT-2 satellite images.

PubMed

Choi, Jaewon; Jung, Hyung-Sup; Yun, Sang-Ho

2015-03-09

As the aerospace industry grows, images obtained from Earth observation satellites have been successfully used in various fields. Specifically, the demand for a high-resolution (HR) optical images is gradually increasing, and hence the generation of a high-quality mosaic image is being magnified as an interesting issue. In this paper, we have proposed an efficient mosaic algorithm for HR optical images that are significantly different due to seasonal change. The algorithm includes main steps such as: (1) seamline extraction from gradient magnitude and seam images; (2) histogram matching; and (3) image feathering. Eleven Kompsat-2 images characterized by seasonal variations are used for the performance validation of the proposed method. The results of the performance test show that the proposed method effectively mosaics Kompsat-2 adjacent images including severe seasonal changes. Moreover, the results reveal that the proposed method is applicable to HR optic images such as GeoEye, IKONOS, QuickBird, RapidEye, SPOT, WorldView, etc.

Performance and Accuracy of LAPACK's Symmetric TridiagonalEigensolvers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demmel, Jim W.; Marques, Osni A.; Parlett, Beresford N.

2007-04-19

We compare four algorithms from the latest LAPACK 3.1 release for computing eigenpairs of a symmetric tridiagonal matrix. These include QR iteration, bisection and inverse iteration (BI), the Divide-and-Conquer method (DC), and the method of Multiple Relatively Robust Representations (MR). Our evaluation considers speed and accuracy when computing all eigenpairs, and additionally subset computations. Using a variety of carefully selected test problems, our study includes a variety of today's computer architectures. Our conclusions can be summarized as follows. (1) DC and MR are generally much faster than QR and BI on large matrices. (2) MR almost always does the fewestmore » floating point operations, but at a lower MFlop rate than all the other algorithms. (3) The exact performance of MR and DC strongly depends on the matrix at hand. (4) DC and QR are the most accurate algorithms with observed accuracy O({radical}ne). The accuracy of BI and MR is generally O(ne). (5) MR is preferable to BI for subset computations.« less

Automated quantification of surface water inundation in wetlands using optical satellite imagery

USGS Publications Warehouse

DeVries, Ben; Huang, Chengquan; Lang, Megan W.; Jones, John W.; Huang, Wenli; Creed, Irena F.; Carroll, Mark L.

2017-01-01

We present a fully automated and scalable algorithm for quantifying surface water inundation in wetlands. Requiring no external training data, our algorithm estimates sub-pixel water fraction (SWF) over large areas and long time periods using Landsat data. We tested our SWF algorithm over three wetland sites across North America, including the Prairie Pothole Region, the Delmarva Peninsula and the Everglades, representing a gradient of inundation and vegetation conditions. We estimated SWF at 30-m resolution with accuracies ranging from a normalized root-mean-square-error of 0.11 to 0.19 when compared with various high-resolution ground and airborne datasets. SWF estimates were more sensitive to subtle inundated features compared to previously published surface water datasets, accurately depicting water bodies, large heterogeneously inundated surfaces, narrow water courses and canopy-covered water features. Despite this enhanced sensitivity, several sources of errors affected SWF estimates, including emergent or floating vegetation and forest canopies, shadows from topographic features, urban structures and unmasked clouds. The automated algorithm described in this article allows for the production of high temporal resolution wetland inundation data products to support a broad range of applications.

A new artefacts resistant method for automatic lineament extraction using Multi-Hillshade Hierarchic Clustering (MHHC)

NASA Astrophysics Data System (ADS)

Šilhavý, Jakub; Minár, Jozef; Mentlík, Pavel; Sládek, Ján

2016-07-01

This paper presents a new method of automatic lineament extraction which includes the removal of the 'artefacts effect' which is associated with the process of raster based analysis. The core of the proposed Multi-Hillshade Hierarchic Clustering (MHHC) method incorporates a set of variously illuminated and rotated hillshades in combination with hierarchic clustering of derived 'protolineaments'. The algorithm also includes classification into positive and negative lineaments. MHHC was tested in two different territories in Bohemian Forest and Central Western Carpathians. The original vector-based algorithm was developed for comparison of the individual lineaments proximity. Its use confirms the compatibility of manual and automatic extraction and their similar relationships to structural data in the study areas.

Two-dimensional atmospheric transport and chemistry model - Numerical experiments with a new advection algorithm

NASA Technical Reports Server (NTRS)

Shia, Run-Lie; Ha, Yuk Lung; Wen, Jun-Shan; Yung, Yuk L.

1990-01-01

Extensive testing of the advective scheme proposed by Prather (1986) has been carried out in support of the California Institute of Technology-Jet Propulsion Laboratory two-dimensional model of the middle atmosphere. The original scheme is generalized to include higher-order moments. In addition, it is shown how well the scheme works in the presence of chemistry as well as eddy diffusion. Six types of numerical experiments including simple clock motion and pure advection in two dimensions have been investigated in detail. By comparison with analytic solutions, it is shown that the new algorithm can faithfully preserve concentration profiles, has essentially no numerical diffusion, and is superior to a typical fourth-order finite difference scheme.

An Efficient Functional Test Generation Method For Processors Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Hudec, Ján; Gramatová, Elena

2015-07-01

The paper presents a new functional test generation method for processors testing based on genetic algorithms and evolutionary strategies. The tests are generated over an instruction set architecture and a processor description. Such functional tests belong to the software-oriented testing. Quality of the tests is evaluated by code coverage of the processor description using simulation. The presented test generation method uses VHDL models of processors and the professional simulator ModelSim. The rules, parameters and fitness functions were defined for various genetic algorithms used in automatic test generation. Functionality and effectiveness were evaluated using the RISC type processor DP32.

Hybrid flower pollination algorithm strategies for t-way test suite generation.

PubMed

Nasser, Abdullah B; Zamli, Kamal Z; Alsewari, AbdulRahman A; Ahmed, Bestoun S

2018-01-01

The application of meta-heuristic algorithms for t-way testing has recently become prevalent. Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). Mixed results have been reported in the literature to highlight the fact that no single strategy appears to be superior compared with other configurations. The hybridization of two or more algorithms can enhance the overall search capabilities, that is, by compensating the limitation of one algorithm with the strength of others. Thus, hybrid variants of the flower pollination algorithm (FPA) are proposed in the current work. Four hybrid variants of FPA are considered by combining FPA with other algorithmic components. The experimental results demonstrate that FPA hybrids overcome the problems of slow convergence in the original FPA and offers statistically superior performance compared with existing t-way strategies in terms of test suite size.

Hybrid flower pollination algorithm strategies for t-way test suite generation

PubMed Central

Zamli, Kamal Z.; Alsewari, AbdulRahman A.

2018-01-01

The application of meta-heuristic algorithms for t-way testing has recently become prevalent. Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). Mixed results have been reported in the literature to highlight the fact that no single strategy appears to be superior compared with other configurations. The hybridization of two or more algorithms can enhance the overall search capabilities, that is, by compensating the limitation of one algorithm with the strength of others. Thus, hybrid variants of the flower pollination algorithm (FPA) are proposed in the current work. Four hybrid variants of FPA are considered by combining FPA with other algorithmic components. The experimental results demonstrate that FPA hybrids overcome the problems of slow convergence in the original FPA and offers statistically superior performance compared with existing t-way strategies in terms of test suite size. PMID:29718918

VDLLA: A virtual daddy-long legs optimization

NASA Astrophysics Data System (ADS)

Yaakub, Abdul Razak; Ghathwan, Khalil I.

2016-08-01

Swarm intelligence is a strong optimization algorithm based on a biological behavior of insects or animals. The success of any optimization algorithm is depending on the balance between exploration and exploitation. In this paper, we present a new swarm intelligence algorithm, which is based on daddy long legs spider (VDLLA) as a new optimization algorithm with virtual behavior. In VDLLA, each agent (spider) has nine positions which represent the legs of spider and each position represent one solution. The proposed VDLLA is tested on four standard functions using average fitness, Medium fitness and standard deviation. The results of proposed VDLLA have been compared against Particle Swarm Optimization (PSO), Differential Evolution (DE) and Bat Inspired Algorithm (BA). Additionally, the T-Test has been conducted to show the significant deference between our proposed and other algorithms. VDLLA showed very promising results on benchmark test functions for unconstrained optimization problems and also significantly improved the original swarm algorithms.

Identification of chronic rhinosinusitis phenotypes using cluster analysis.

PubMed

Soler, Zachary M; Hyer, J Madison; Ramakrishnan, Viswanathan; Smith, Timothy L; Mace, Jess; Rudmik, Luke; Schlosser, Rodney J

2015-05-01

Current clinical classifications of chronic rhinosinusitis (CRS) have been largely defined based upon preconceived notions of factors thought to be important, such as polyp or eosinophil status. Unfortunately, these classification systems have little correlation with symptom severity or treatment outcomes. Unsupervised clustering can be used to identify phenotypic subgroups of CRS patients, describe clinical differences in these clusters and define simple algorithms for classification. A multi-institutional, prospective study of 382 patients with CRS who had failed initial medical therapy completed the Sino-Nasal Outcome Test (SNOT-22), Rhinosinusitis Disability Index (RSDI), Medical Outcomes Study Short Form-12 (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire (PHQ-2). Objective measures of CRS severity included Brief Smell Identification Test (B-SIT), CT, and endoscopy scoring. All variables were reduced and unsupervised hierarchical clustering was performed. After clusters were defined, variations in medication usage were analyzed. Discriminant analysis was performed to develop a simplified, clinically useful algorithm for clustering. Clustering was largely determined by age, severity of patient reported outcome measures, depression, and fibromyalgia. CT and endoscopy varied somewhat among clusters. Traditional clinical measures, including polyp/atopic status, prior surgery, B-SIT and asthma, did not vary among clusters. A simplified algorithm based upon productivity loss, SNOT-22 score, and age predicted clustering with 89% accuracy. Medication usage among clusters did vary significantly. A simplified algorithm based upon hierarchical clustering is able to classify CRS patients and predict medication usage. Further studies are warranted to determine if such clustering predicts treatment outcomes. © 2015 ARS-AAOA, LLC.

Computerised lung sound analysis to improve the specificity of paediatric pneumonia diagnosis in resource-poor settings: protocol and methods for an observational study

PubMed Central

Gilman, Robert H; Tielsch, James M; Steinhoff, Mark; Figueroa, Dante; Rodriguez, Shalim; Caffo, Brian; Tracey, Brian; Elhilali, Mounya; West, James; Checkley, William

2012-01-01

Introduction WHO case management algorithm for paediatric pneumonia relies solely on symptoms of shortness of breath or cough and tachypnoea for treatment and has poor diagnostic specificity, tends to increase antibiotic resistance. Alternatives, including oxygen saturation measurement, chest ultrasound and chest auscultation, exist but with potential disadvantages. Electronic auscultation has potential for improved detection of paediatric pneumonia but has yet to be standardised. The authors aim to investigate the use of electronic auscultation to improve the specificity of the current WHO algorithm in developing countries. Methods This study is designed to test the hypothesis that pulmonary pathology can be differentiated from normal using computerised lung sound analysis (CLSA). The authors will record lung sounds from 600 children aged ≤5 years, 100 each with consolidative pneumonia, diffuse interstitial pneumonia, asthma, bronchiolitis, upper respiratory infections and normal lungs at a children's hospital in Lima, Peru. The authors will compare CLSA with the WHO algorithm and other detection approaches, including physical exam findings, chest ultrasound and microbiologic testing to construct an improved algorithm for pneumonia diagnosis. Discussion This study will develop standardised methods for electronic auscultation and chest ultrasound and compare their utility for detection of pneumonia to standard approaches. Utilising signal processing techniques, the authors aim to characterise lung sounds and through machine learning, develop a classification system to distinguish pathologic sounds. Data will allow a better understanding of the benefits and limitations of novel diagnostic techniques in paediatric pneumonia. PMID:22307098

Cost effectiveness analysis of the New Jersey rapid testing algorithm for HIV testing in publicly funded testing sites.

PubMed

Stevinson, Kendall; Martin, Eugene G; Marcella, Stephen; Paul, Sindy M

2011-12-01

Before 2009, New Jersey (NJ) publicly funded counseling and testing sites (CTS) tested for HIV using a single rapid test followed, when positive, by a Western Blot (WB) for confirmation. With this strategy, 74.8% of confirmed positive clients returned to receive test results. To improve the client notification rate at these centers, the New Jersey (NJ) Division of HIV, STD and TB Services (DHSTS) implemented a rapid testing algorithm (RTA) which utilizes a second, different, rapid test to verify a preliminary positive. To compare the cost-effectiveness of the two testing algorithms. This was a retrospective cost-effectiveness analysis. New Jersey HIV Rapid Testing Support Program (NJHIV) records, DHSTS grant documents, counseling time estimates from an online survey of site supervisors. Costs included test kits and personnel costs from month of RTA implementation through 11/30 in 2008 and 2009. The incremental cost of the RTA was calculated per additional percent of positive clients who were notified and per day earlier notification. In 2008, 215 of 247 clients with a positive rapid HIV test were confirmed positive by WB. 90.9% of clients were notified a mean of 11.4 days after their initial test. 12 refused confirmatory WB. In 2009, 152 of 170 clients with one positive rapid test had a confirmatory second positive rapid test and were notified on the same day. The incremental cost of the RTA was $20.31 per additional positive person notified and $24.31 per day earlier notification or $3.23 per additional positive person and $3.87 per day earlier notification if the WB were eliminated. The RTA is a cost-effective strategy achieving 100% notification of newly HIV positive clients a mean of 11.4 days earlier compared to standard testing. Copyright © 2011 Elsevier B.V. All rights reserved.

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

NASA Technical Reports Server (NTRS)

Trevino, Luis; Berg, Peter; England, Dwight; Johnson, Stephen B.

2016-01-01

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Evaluation of the Jonker-Volgenant-Castanon (JVC) assignment algorithm for track association

NASA Astrophysics Data System (ADS)

Malkoff, Donald B.

1997-07-01

The Jonker-Volgenant-Castanon (JVC) assignment algorithm was used by Lockheed Martin Advanced Technology Laboratories (ATL) for track association in the Rotorcraft Pilot's Associate (RPA) program. RPA is Army Aviation's largest science and technology program, involving an integrated hardware/software system approach for a next generation helicopter containing advanced sensor equipments and applying artificial intelligence `associate' technologies. ATL is responsible for the multisensor, multitarget, onboard/offboard track fusion. McDonnell Douglas Helicopter Systems is the prime contractor and Lockheed Martin Federal Systems is responsible for developing much of the cognitive decision aiding and controls-and-displays subsystems. RPA is scheduled for flight testing beginning in 1997. RPA is unique in requiring real-time tracking and fusion for large numbers of highly-maneuverable ground (and air) targets in a target-dense environment. It uses diverse sensors and is concerned with a large area of interest. Target class and identification data is tightly integrated with spatial and kinematic data throughout the processing. Because of platform constraints, processing hardware for track fusion was quite limited. No previous experience using JVC in this type environment had been reported. ATL performed extensive testing of the JVC, concentrating on error rates and run- times under a variety of conditions. These included wide ranging numbers and types of targets, sensor uncertainties, target attributes, differing degrees of target maneuverability, and diverse combinations of sensors. Testing utilized Monte Carlo approaches, as well as many kinds of challenging scenarios. Comparisons were made with a nearest-neighbor algorithm and a new, proprietary algorithm (the `Competition' algorithm). The JVC proved to be an excellent choice for the RPA environment, providing a good balance between speed of operation and accuracy of results.

Evaluation of Machine Learning Algorithms for Classification of Primary Biological Aerosol using a new UV-LIF spectrometer

NASA Astrophysics Data System (ADS)

Ruske, S. T.; Topping, D. O.; Foot, V. E.; Kaye, P. H.; Stanley, W. R.; Morse, A. P.; Crawford, I.; Gallagher, M. W.

2016-12-01

Characterisation of bio-aerosols has important implications within Environment and Public Health sectors. Recent developments in Ultra-Violet Light Induced Fluorescence (UV-LIF) detectors such as the Wideband Integrated bio-aerosol Spectrometer (WIBS) and the newly introduced Multiparameter bio-aerosol Spectrometer (MBS) has allowed for the real time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal Spores and pollen. This new generation of instruments has enabled ever-larger data sets to be compiled with the aim of studying more complex environments, yet the algorithms used for specie classification remain largely invalidated. It is therefore imperative that we validate the performance of different algorithms that can be used for the task of classification, which is the focus of this study. For unsupervised learning we test Hierarchical Agglomerative Clustering with various different linkages. For supervised learning, ten methods were tested; including decision trees, ensemble methods: Random Forests, Gradient Boosting and AdaBoost; two implementations for support vector machines: libsvm and liblinear; Gaussian methods: Gaussian naïve Bayesian, quadratic and linear discriminant analysis and finally the k-nearest neighbours algorithm. The methods were applied to two different data sets measured using a new Multiparameter bio-aerosol Spectrometer. We find that clustering, in general, performs slightly worse than the supervised learning methods correctly classifying, at best, only 72.7 and 91.1 percent for the two data sets. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 88.1 and 97.8 percent of the testing data respectively across the two data sets. We discuss the wider relevance of these results with regards to challenging existing classification in real-world environments.

Finalize field testing of cold climate heat pump (CCHP) based on tandem vapor injection compressors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Bo; Baxter, Van D.; Abdelaziz, Omar

2017-03-01

This report describes the system diagram and control algorithm of a prototype air-source cold climate heat pump (CCHP) using tandem vapor injection (VI) compressors. The prototype was installed in Fairbanks, Alaska and underwent field testing starting in 09/2016. The field testing results of the past six months, including compressor run time fractions, measured COPs and heating capacities, etc., are presented as a function of the ambient temperature. Two lessons learned are also reported.

Investigating prior probabilities in a multiple hypothesis test for use in space domain awareness

NASA Astrophysics Data System (ADS)

Hardy, Tyler J.; Cain, Stephen C.

2016-05-01

The goal of this research effort is to improve Space Domain Awareness (SDA) capabilities of current telescope systems through improved detection algorithms. Ground-based optical SDA telescopes are often spatially under-sampled, or aliased. This fact negatively impacts the detection performance of traditionally proposed binary and correlation-based detection algorithms. A Multiple Hypothesis Test (MHT) algorithm has been previously developed to mitigate the effects of spatial aliasing. This is done by testing potential Resident Space Objects (RSOs) against several sub-pixel shifted Point Spread Functions (PSFs). A MHT has been shown to increase detection performance for the same false alarm rate. In this paper, the assumption of a priori probability used in a MHT algorithm is investigated. First, an analysis of the pixel decision space is completed to determine alternate hypothesis prior probabilities. These probabilities are then implemented into a MHT algorithm, and the algorithm is then tested against previous MHT algorithms using simulated RSO data. Results are reported with Receiver Operating Characteristic (ROC) curves and probability of detection, Pd, analysis.

Unified Framework for Development, Deployment and Robust Testing of Neuroimaging Algorithms

PubMed Central

Joshi, Alark; Scheinost, Dustin; Okuda, Hirohito; Belhachemi, Dominique; Murphy, Isabella; Staib, Lawrence H.; Papademetris, Xenophon

2011-01-01

Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software—BioImage Suite (bioimagesuite.org). PMID:21249532

Determination of feature generation methods for PTZ camera object tracking

NASA Astrophysics Data System (ADS)

Doyle, Daniel D.; Black, Jonathan T.

2012-06-01

Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

Multi-temporal AirSWOT elevations on the Willamette river: error characterization and algorithm testing

NASA Astrophysics Data System (ADS)

Tuozzolo, S.; Frasson, R. P. M.; Durand, M. T.

2017-12-01

We analyze a multi-temporal dataset of in-situ and airborne water surface measurements from the March 2015 AirSWOT field campaign on the Willamette River in Western Oregon, which included six days of AirSWOT flights over a 75km stretch of the river. We examine systematic errors associated with dark water and layover effects in the AirSWOT dataset, and test the efficacies of different filtering and spatial averaging techniques at reconstructing the water surface profile. Finally, we generate a spatially-averaged time-series of water surface elevation and water surface slope. These AirSWOT-derived reach-averaged values are ingested in a prospective SWOT discharge algorithm to assess its performance on SWOT-like data collected from a borderline SWOT-measurable river (mean width = 90m).

Combining Risk Analysis and Slicing for Test Reduction in Open Architecture

DTIC Science & Technology

2014-04-30

collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...full-system testing, whose purpose is to check that all the parts work harmoniously together. This part of the effort cannot be reduced unless it is...that eliminates program statements irrelevant to a given slicing criterion. Slicing algorithms detect and follow dependencies of the kinds described

An implicit higher-order spatially accurate scheme for solving time dependent flows on unstructured meshes

NASA Astrophysics Data System (ADS)

Tomaro, Robert F.

1998-07-01

The present research is aimed at developing a higher-order, spatially accurate scheme for both steady and unsteady flow simulations using unstructured meshes. The resulting scheme must work on a variety of general problems to ensure the creation of a flexible, reliable and accurate aerodynamic analysis tool. To calculate the flow around complex configurations, unstructured grids and the associated flow solvers have been developed. Efficient simulations require the minimum use of computer memory and computational times. Unstructured flow solvers typically require more computer memory than a structured flow solver due to the indirect addressing of the cells. The approach taken in the present research was to modify an existing three-dimensional unstructured flow solver to first decrease the computational time required for a solution and then to increase the spatial accuracy. The terms required to simulate flow involving non-stationary grids were also implemented. First, an implicit solution algorithm was implemented to replace the existing explicit procedure. Several test cases, including internal and external, inviscid and viscous, two-dimensional, three-dimensional and axi-symmetric problems, were simulated for comparison between the explicit and implicit solution procedures. The increased efficiency and robustness of modified code due to the implicit algorithm was demonstrated. Two unsteady test cases, a plunging airfoil and a wing undergoing bending and torsion, were simulated using the implicit algorithm modified to include the terms required for a moving and/or deforming grid. Secondly, a higher than second-order spatially accurate scheme was developed and implemented into the baseline code. Third- and fourth-order spatially accurate schemes were implemented and tested. The original dissipation was modified to include higher-order terms and modified near shock waves to limit pre- and post-shock oscillations. The unsteady cases were repeated using the higher-order spatially accurate code. The new solutions were compared with those obtained using the second-order spatially accurate scheme. Finally, the increased efficiency of using an implicit solution algorithm in a production Computational Fluid Dynamics flow solver was demonstrated for steady and unsteady flows. A third- and fourth-order spatially accurate scheme has been implemented creating a basis for a state-of-the-art aerodynamic analysis tool.

Automated Speech Rate Measurement in Dysarthria.

PubMed

Martens, Heidi; Dekens, Tomas; Van Nuffelen, Gwen; Latacz, Lukas; Verhelst, Werner; De Bodt, Marc

2015-06-01

In this study, a new algorithm for automated determination of speech rate (SR) in dysarthric speech is evaluated. We investigated how reliably the algorithm calculates the SR of dysarthric speech samples when compared with calculation performed by speech-language pathologists. The new algorithm was trained and tested using Dutch speech samples of 36 speakers with no history of speech impairment and 40 speakers with mild to moderate dysarthria. We tested the algorithm under various conditions: according to speech task type (sentence reading, passage reading, and storytelling) and algorithm optimization method (speaker group optimization and individual speaker optimization). Correlations between automated and human SR determination were calculated for each condition. High correlations between automated and human SR determination were found in the various testing conditions. The new algorithm measures SR in a sufficiently reliable manner. It is currently being integrated in a clinical software tool for assessing and managing prosody in dysarthric speech. Further research is needed to fine-tune the algorithm to severely dysarthric speech, to make the algorithm less sensitive to background noise, and to evaluate how the algorithm deals with syllabic consonants.

Air Traffic Control Experimentation and Evaluation with the NASA ATS-6 Satellite : Volume 4. Data Reduction and Analysis Software.

DOT National Transportation Integrated Search

1976-09-01

Software used for the reduction and analysis of the multipath prober, modem evaluation (voice, digital data, and ranging), and antenna evaluation data acquired during the ATS-6 field test program is described. Multipath algorithms include reformattin...

Prevalence of Traditional and Reverse-Algorithm Syphilis Screening in Laboratory Practice: A Survey of Participants in the College of American Pathologists Syphilis Serology Proficiency Testing Program.

PubMed

Rhoads, Daniel D; Genzen, Jonathan R; Bashleben, Christine P; Faix, James D; Ansari, M Qasim

2017-01-01

-Syphilis serology screening in laboratory practice is evolving. Traditionally, the syphilis screening algorithm begins with a nontreponemal immunoassay, which is manually performed by a laboratory technologist. In contrast, the reverse algorithm begins with a treponemal immunoassay, which can be automated. The Centers for Disease Control and Prevention has recognized both approaches, but little is known about the current state of laboratory practice, which could impact test utilization and interpretation. -To assess the current state of laboratory practice for syphilis serologic screening. -In August 2015, a voluntary questionnaire was sent to the 2360 laboratories that subscribe to the College of American Pathologists syphilis serology proficiency survey. -Of the laboratories surveyed, 98% (2316 of 2360) returned the questionnaire, and about 83% (1911 of 2316) responded to at least some questions. Twenty-eight percent (378 of 1364) reported revision of their syphilis screening algorithm within the past 2 years, and 9% (170 of 1905) of laboratories anticipated changing their screening algorithm in the coming year. Sixty-three percent (1205 of 1911) reported using the traditional algorithm, 16% (304 of 1911) reported using the reverse algorithm, and 2.5% (47 of 1911) reported using both algorithms, whereas 9% (169 of 1911) reported not performing a reflex confirmation test. Of those performing the reverse algorithm, 74% (282 of 380) implemented a new testing platform when introducing the new algorithm. -The majority of laboratories still perform the traditional algorithm, but a significant minority have implemented the reverse-screening algorithm. Although the nontreponemal immunologic response typically wanes after cure and becomes undetectable, treponemal immunoassays typically remain positive for life, and it is important for laboratorians and clinicians to consider these assay differences when implementing, using, and interpreting serologic syphilis screening algorithms.

Development and testing of incident detection algorithms. Vol. 2, research methodology and detailed results.

DOT National Transportation Integrated Search

1976-04-01

The development and testing of incident detection algorithms was based on Los Angeles and Minneapolis freeway surveillance data. Algorithms considered were based on times series and pattern recognition techniques. Attention was given to the effects o...

Incremental cost-effectiveness of algorithm-driven genetic testing versus no testing for Maturity Onset Diabetes of the Young (MODY) in Singapore.

PubMed

Nguyen, Hai Van; Finkelstein, Eric Andrew; Mital, Shweta; Gardner, Daphne Su-Lyn

2017-11-01

Offering genetic testing for Maturity Onset Diabetes of the Young (MODY) to all young patients with type 2 diabetes has been shown to be not cost-effective. This study tests whether a novel algorithm-driven genetic testing strategy for MODY is incrementally cost-effective relative to the setting of no testing. A decision tree was constructed to estimate the costs and effectiveness of the algorithm-driven MODY testing strategy and a strategy of no genetic testing over a 30-year time horizon from a payer's perspective. The algorithm uses glutamic acid decarboxylase (GAD) antibody testing (negative antibodies), age of onset of diabetes (<45 years) and body mass index (<25 kg/m 2 if diagnosed >30 years) to stratify the population of patients with diabetes into three subgroups, and testing for MODY only among the subgroup most likely to have the mutation. Singapore-specific costs and prevalence of MODY obtained from local studies and utility values sourced from the literature are used to populate the model. The algorithm-driven MODY testing strategy has an incremental cost-effectiveness ratio of US$93 663 per quality-adjusted life year relative to the no testing strategy. If the price of genetic testing falls from US$1050 to US$530 (a 50% decrease), it will become cost-effective. Our proposed algorithm-driven testing strategy for MODY is not yet cost-effective based on established benchmarks. However, as genetic testing prices continue to fall, this strategy is likely to become cost-effective in the near future. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.

PubMed

Han, Chengzong; Gregg, Richard E; Feild, Dirk Q; Babaeizadeh, Saeed

2014-01-01

ECG cable interchange can generate erroneous diagnoses. For algorithms detecting ECG cable interchange, high specificity is required to maintain a low total false positive rate because the prevalence of interchange is low. In this study, we propose and evaluate an improved algorithm for automatic detection and classification of ECG cable interchange. The algorithm was developed by using both ECG morphology information and redundancy information. ECG morphology features included QRS-T and P-wave amplitude, frontal axis and clockwise vector loop rotation. The redundancy features were derived based on the EASI™ lead system transformation. The classification was implemented using linear support vector machine. The development database came from multiple sources including both normal subjects and cardiac patients. An independent database was used to test the algorithm performance. Common cable interchanges were simulated by swapping either limb cables or precordial cables. For the whole validation database, the overall sensitivity and specificity for detecting precordial cable interchange were 56.5% and 99.9%, and the sensitivity and specificity for detecting limb cable interchange (excluding left arm-left leg interchange) were 93.8% and 99.9%. Defining precordial cable interchange or limb cable interchange as a single positive event, the total false positive rate was 0.7%. When the algorithm was designed for higher sensitivity, the sensitivity for detecting precordial cable interchange increased to 74.6% and the total false positive rate increased to 2.7%, while the sensitivity for detecting limb cable interchange was maintained at 93.8%. The low total false positive rate was maintained at 0.6% for the more abnormal subset of the validation database including only hypertrophy and infarction patients. The proposed algorithm can detect and classify ECG cable interchanges with high specificity and low total false positive rate, at the cost of decreased sensitivity for certain precordial cable interchanges. The algorithm could also be configured for higher sensitivity for different applications where a lower specificity can be tolerated. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of an indoor location based service test bed and geographic information system with a wireless sensor network.

PubMed

Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming

2010-01-01

In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system.

Development of an Indoor Location Based Service Test Bed and Geographic Information System with a Wireless Sensor Network

PubMed Central

Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming

2010-01-01

In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system. PMID:22319282

A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias.

PubMed

Koa-Wing, Michael; Nakagawa, Hiroshi; Luther, Vishal; Jamil-Copley, Shahnaz; Linton, Nick; Sandler, Belinda; Qureshi, Norman; Peters, Nicholas S; Davies, D Wyn; Francis, Darrel P; Jackman, Warren; Kanagaratnam, Prapa

2015-11-15

Ripple Mapping (RM) is designed to overcome the limitations of existing isochronal 3D mapping systems by representing the intracardiac electrogram as a dynamic bar on a surface bipolar voltage map that changes in height according to the electrogram voltage-time relationship, relative to a fiduciary point. We tested the hypothesis that standard approaches to atrial tachycardia CARTO™ activation maps were inadequate for RM creation and interpretation. From the results, we aimed to develop an algorithm to optimize RMs for future prospective testing on a clinical RM platform. CARTO-XP™ activation maps from atrial tachycardia ablations were reviewed by two blinded assessors on an off-line RM workstation. Ripple Maps were graded according to a diagnostic confidence scale (Grade I - high confidence with clear pattern of activation through to Grade IV - non-diagnostic). The RM-based diagnoses were corroborated against the clinical diagnoses. 43 RMs from 14 patients were classified as Grade I (5 [11.5%]); Grade II (17 [39.5%]); Grade III (9 [21%]) and Grade IV (12 [28%]). Causes of low gradings/errors included the following: insufficient chamber point density; window-of-interest<100% of cycle length (CL); <95% tachycardia CL mapped; variability of CL and/or unstable fiducial reference marker; and suboptimal bar height and scar settings. A data collection and map interpretation algorithm has been developed to optimize Ripple Maps in atrial tachycardias. This algorithm requires prospective testing on a real-time clinical platform. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Finding all solutions of nonlinear equations using the dual simplex method

NASA Astrophysics Data System (ADS)

Yamamura, Kiyotaka; Fujioka, Tsuyoshi

2003-03-01

Recently, an efficient algorithm has been proposed for finding all solutions of systems of nonlinear equations using linear programming. This algorithm is based on a simple test (termed the LP test) for nonexistence of a solution to a system of nonlinear equations using the dual simplex method. In this letter, an improved version of the LP test algorithm is proposed. By numerical examples, it is shown that the proposed algorithm could find all solutions of a system of 300 nonlinear equations in practical computation time.

Scenario Decomposition for 0-1 Stochastic Programs: Improvements and Asynchronous Implementation

DOE PAGES

Ryan, Kevin; Rajan, Deepak; Ahmed, Shabbir

2016-05-01

We recently proposed scenario decomposition algorithm for stochastic 0-1 programs finds an optimal solution by evaluating and removing individual solutions that are discovered by solving scenario subproblems. In our work, we develop an asynchronous, distributed implementation of the algorithm which has computational advantages over existing synchronous implementations of the algorithm. Improvements to both the synchronous and asynchronous algorithm are proposed. We also test the results on well known stochastic 0-1 programs from the SIPLIB test library and is able to solve one previously unsolved instance from the test set.

An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization.

PubMed

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms.

Closed Loop Guidance Trade Study for Space Launch System Block-1B Vehicle

NASA Technical Reports Server (NTRS)

Von der Porten, Paul; Ahmad, Naeem; Hawkins, Matt

2018-01-01

NASA is currently building the Space Launch System (SLS) Block-1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. The design of the next evolution of SLS, Block-1B, is well underway. The Block-1B vehicle is more capable overall than Block-1; however, the relatively low thrust-to-weight ratio of the Exploration Upper Stage (EUS) presents a challenge to the Powered Explicit Guidance (PEG) algorithm used by Block-1. To handle the long burn durations (on the order of 1000 seconds) of EUS missions, two algorithms were examined. An alternative algorithm, OPGUID, was introduced, while modifications were made to PEG. A trade study was conducted to select the guidance algorithm for future SLS vehicles. The chosen algorithm needs to support a wide variety of mission operations: ascent burns to LEO, apogee raise burns, trans-lunar injection burns, hyperbolic Earth departure burns, and contingency disposal burns using the Reaction Control System (RCS). Additionally, the algorithm must be able to respond to a single engine failure scenario. Each algorithm was scored based on pre-selected criteria, including insertion accuracy, algorithmic complexity and robustness, extensibility for potential future missions, and flight heritage. Monte Carlo analysis was used to select the final algorithm. This paper covers the design criteria, approach, and results of this trade study, showing impacts and considerations when adapting launch vehicle guidance algorithms to a broader breadth of in-space operations.

Towards a web-based decision support tool for selecting appropriate statistical test in medical and biological sciences.

PubMed

Suner, Aslı; Karakülah, Gökhan; Dicle, Oğuz

2014-01-01

Statistical hypothesis testing is an essential component of biological and medical studies for making inferences and estimations from the collected data in the study; however, the misuse of statistical tests is widely common. In order to prevent possible errors in convenient statistical test selection, it is currently possible to consult available test selection algorithms developed for various purposes. However, the lack of an algorithm presenting the most common statistical tests used in biomedical research in a single flowchart causes several problems such as shifting users among the algorithms, poor decision support in test selection and lack of satisfaction of potential users. Herein, we demonstrated a unified flowchart; covers mostly used statistical tests in biomedical domain, to provide decision aid to non-statistician users while choosing the appropriate statistical test for testing their hypothesis. We also discuss some of the findings while we are integrating the flowcharts into each other to develop a single but more comprehensive decision algorithm.

Ground Vibration Test of the Aerostructure Test Wing 2

NASA Technical Reports Server (NTRS)

Herrera, Claudia; Moholt, Matthew

2009-01-01

The Aerostructures Test Wing (ATW) was developed to test unique concepts for flutter prediction and control synthesis. A follow-on to the successful ATW, denoted ATW2, was fabricated as a test bed to validate a variety of instrumentation in flight and to collect data for development of advanced signal processing algorithms for flutter prediction and aviation safety. As a means to estimate flutter speed, a ground vibration test (GVT) was performed. The results of a GVT are typically utilized to update structural dynamics finite element (FE) models used for flutter analysis. In this study, two GVT methodologies were explored to determine which nodes provide the best sensor locations: (i) effective independence and (ii) kinetic energy sorting algorithms. For measurement, ten and twenty sensors were used for three and 10 target test modes. A total of six accelerometer configurations measured frequencies and mode shapes. This included locations used in the original ATW GVT. Moreover, an optical measurement system was used to acquire data without mass effects added by conventional sensors. A considerable frequency shift was observed in comparing the data from the accelerometers to the optical data. The optical data provided robust data for use of the ATW2 finite element model update.

SU-F-BRB-05: Collision Avoidance Mapping Using Consumer 3D Camera

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cardan, R; Popple, R

2015-06-15

Purpose: To develop a fast and economical method of scanning a patient’s full body contour for use in collision avoidance mapping without the use of ionizing radiation. Methods: Two consumer level 3D cameras used in electronic gaming were placed in a CT simulator room to scan a phantom patient set up in a high collision probability position. A registration pattern and computer vision algorithms were used to transform the scan into the appropriate coordinate systems. The cameras were then used to scan the surface of a gantry in the treatment vault. Each scan was converted into a polygon mesh formore » collision testing in a general purpose polygon interference algorithm. All clinically relevant transforms were applied to the gantry and patient support to create a map of all possible collisions. The map was then tested for accuracy by physically testing the collisions with the phantom in the vault. Results: The scanning fidelity of both the gantry and patient was sufficient to produce a collision prediction accuracy of 97.1% with 64620 geometry states tested in 11.5 s. The total scanning time including computation, transformation, and generation was 22.3 seconds. Conclusion: Our results demonstrate an economical system to generate collision avoidance maps. Future work includes testing the speed of the framework in real-time collision avoidance scenarios. Research partially supported by a grant from Varian Medical Systems.« less

Identifying injection drug use and estimating population size of people who inject drugs using healthcare administrative datasets.

PubMed

Janjua, Naveed Zafar; Islam, Nazrul; Kuo, Margot; Yu, Amanda; Wong, Stanley; Butt, Zahid A; Gilbert, Mark; Buxton, Jane; Chapinal, Nuria; Samji, Hasina; Chong, Mei; Alvarez, Maria; Wong, Jason; Tyndall, Mark W; Krajden, Mel

2018-05-01

Large linked healthcare administrative datasets could be used to monitor programs providing prevention and treatment services to people who inject drugs (PWID). However, diagnostic codes in administrative datasets do not differentiate non-injection from injection drug use (IDU). We validated algorithms based on diagnostic codes and prescription records representing IDU in administrative datasets against interview-based IDU data. The British Columbia Hepatitis Testers Cohort (BC-HTC) includes ∼1.7 million individuals tested for HCV/HIV or reported HBV/HCV/HIV/tuberculosis cases in BC from 1990 to 2015, linked to administrative datasets including physician visit, hospitalization and prescription drug records. IDU, assessed through interviews as part of enhanced surveillance at the time of HIV or HCV/HBV diagnosis from a subset of cases included in the BC-HTC (n = 6559), was used as the gold standard. ICD-9/ICD-10 codes for IDU and injecting-related infections (IRI) were grouped with records of opioid substitution therapy (OST) into multiple IDU algorithms in administrative datasets. We assessed the performance of IDU algorithms through calculation of sensitivity, specificity, positive predictive, and negative predictive values. Sensitivity was highest (90-94%), and specificity was lowest (42-73%) for algorithms based either on IDU or IRI and drug misuse codes. Algorithms requiring both drug misuse and IRI had lower sensitivity (57-60%) and higher specificity (90-92%). An optimal sensitivity and specificity combination was found with two medical visits or a single hospitalization for injectable drugs with (83%/82%) and without OST (78%/83%), respectively. Based on algorithms that included two medical visits, a single hospitalization or OST records, there were 41,358 (1.2% of 11-65 years individuals in BC) recent PWID in BC based on health encounters during 3- year period (2013-2015). Algorithms for identifying PWID using diagnostic codes in linked administrative data could be used for tracking the progress of programing aimed at PWID. With population-based datasets, this tool can be used to inform much needed estimates of PWID population size. Copyright © 2018 Elsevier B.V. All rights reserved.

TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

NASA Technical Reports Server (NTRS)

Bergh, Christopher P.; Krzeczowski, Kenneth J.; Davis, Thomas J.; Denery, Dallas G. (Technical Monitor)

1995-01-01

A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

Deriving health utilities from the MacNew Heart Disease Quality of Life Questionnaire.

PubMed

Chen, Gang; McKie, John; Khan, Munir A; Richardson, Jeff R

2015-10-01

Quality of life is included in the economic evaluation of health services by measuring the preference for health states, i.e. health state utilities. However, most intervention studies include a disease-specific, not a utility, instrument. Consequently, there has been increasing use of statistical mapping algorithms which permit utilities to be estimated from a disease-specific instrument. The present paper provides such algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and six multi-attribute utility (MAU) instruments, the Euroqol (EQ-5D), the Short Form 6D (SF-6D), the Health Utilities Index (HUI) 3, the Quality of Wellbeing (QWB), the 15D (15 Dimension) and the Assessment of Quality of Life (AQoL-8D). Heart disease patients and members of the healthy public were recruited from six countries. Non-parametric rank tests were used to compare subgroup utilities and MacNew scores. Mapping algorithms were estimated using three separate statistical techniques. Mapping algorithms achieved a high degree of precision. Based on the mean absolute error and the intra class correlation the preferred mapping is MacNew into SF-6D or 15D. Using the R squared statistic the preferred mapping is MacNew into AQoL-8D. The algorithms reported in this paper enable MacNew data to be mapped into utilities predicted from any of six instruments. This permits studies which have included the MacNew to be used in cost utility analyses which, in turn, allows the comparison of services with interventions across the health system. © The European Society of Cardiology 2014.

Preliminary test results of a flight management algorithm for fuel conservative descents in a time based metered traffic environment. [flight tests of an algorithm to minimize fuel consumption of aircraft based on flight time

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.

Tracking and recognition face in videos with incremental local sparse representation model

NASA Astrophysics Data System (ADS)

Wang, Chao; Wang, Yunhong; Zhang, Zhaoxiang

2013-10-01

This paper addresses the problem of tracking and recognizing faces via incremental local sparse representation. First a robust face tracking algorithm is proposed via employing local sparse appearance and covariance pooling method. In the following face recognition stage, with the employment of a novel template update strategy, which combines incremental subspace learning, our recognition algorithm adapts the template to appearance changes and reduces the influence of occlusion and illumination variation. This leads to a robust video-based face tracking and recognition with desirable performance. In the experiments, we test the quality of face recognition in real-world noisy videos on YouTube database, which includes 47 celebrities. Our proposed method produces a high face recognition rate at 95% of all videos. The proposed face tracking and recognition algorithms are also tested on a set of noisy videos under heavy occlusion and illumination variation. The tracking results on challenging benchmark videos demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods. In the case of the challenging dataset in which faces undergo occlusion and illumination variation, and tracking and recognition experiments under significant pose variation on the University of California, San Diego (Honda/UCSD) database, our proposed method also consistently demonstrates a high recognition rate.

Adaptation of a cubic smoothing spline algortihm for multi-channel data stitching at the National Ignition Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, C; Adcock, A; Azevedo, S

2010-12-28

Some diagnostics at the National Ignition Facility (NIF), including the Gamma Reaction History (GRH) diagnostic, require multiple channels of data to achieve the required dynamic range. These channels need to be stitched together into a single time series, and they may have non-uniform and redundant time samples. We chose to apply the popular cubic smoothing spline technique to our stitching problem because we needed a general non-parametric method. We adapted one of the algorithms in the literature, by Hutchinson and deHoog, to our needs. The modified algorithm and the resulting code perform a cubic smoothing spline fit to multiple datamore » channels with redundant time samples and missing data points. The data channels can have different, time-varying, zero-mean white noise characteristics. The method we employ automatically determines an optimal smoothing level by minimizing the Generalized Cross Validation (GCV) score. In order to automatically validate the smoothing level selection, the Weighted Sum-Squared Residual (WSSR) and zero-mean tests are performed on the residuals. Further, confidence intervals, both analytical and Monte Carlo, are also calculated. In this paper, we describe the derivation of our cubic smoothing spline algorithm. We outline the algorithm and test it with simulated and experimental data.« less

A comparison between metaheuristics as strategies for minimizing cyclic instability in Ambient Intelligence.

PubMed

Romero, Leoncio A; Zamudio, Victor; Baltazar, Rosario; Mezura, Efren; Sotelo, Marco; Callaghan, Vic

2012-01-01

In this paper we present a comparison between six novel approaches to the fundamental problem of cyclic instability in Ambient Intelligence. These approaches are based on different optimization algorithms, Particle Swarm Optimization (PSO), Bee Swarm Optimization (BSO), micro Particle Swarm Optimization (μ-PSO), Artificial Immune System (AIS), Genetic Algorithm (GA) and Mutual Information Maximization for Input Clustering (MIMIC). In order to be able to use these algorithms, we introduced the concept of Average Cumulative Oscillation (ACO), which enabled us to measure the average behavior of the system. This approach has the advantage that it does not need to analyze the topological properties of the system, in particular the loops, which can be computationally expensive. In order to test these algorithms we used the well-known discrete system called the Game of Life for 9, 25, 49 and 289 agents. It was found that PSO and μ-PSO have the best performance in terms of the number of agents locked. These results were confirmed using the Wilcoxon Signed Rank Test. This novel and successful approach is very promising and can be used to remove instabilities in real scenarios with a large number of agents (including nomadic agents) and complex interactions and dependencies among them.

A Comparison between Metaheuristics as Strategies for Minimizing Cyclic Instability in Ambient Intelligence

PubMed Central

Romero, Leoncio A.; Zamudio, Victor; Baltazar, Rosario; Mezura, Efren; Sotelo, Marco; Callaghan, Vic

2012-01-01

In this paper we present a comparison between six novel approaches to the fundamental problem of cyclic instability in Ambient Intelligence. These approaches are based on different optimization algorithms, Particle Swarm Optimization (PSO), Bee Swarm Optimization (BSO), micro Particle Swarm Optimization (μ-PSO), Artificial Immune System (AIS), Genetic Algorithm (GA) and Mutual Information Maximization for Input Clustering (MIMIC). In order to be able to use these algorithms, we introduced the concept of Average Cumulative Oscillation (ACO), which enabled us to measure the average behavior of the system. This approach has the advantage that it does not need to analyze the topological properties of the system, in particular the loops, which can be computationally expensive. In order to test these algorithms we used the well-known discrete system called the Game of Life for 9, 25, 49 and 289 agents. It was found that PSO and μ-PSO have the best performance in terms of the number of agents locked. These results were confirmed using the Wilcoxon Signed Rank Test. This novel and successful approach is very promising and can be used to remove instabilities in real scenarios with a large number of agents (including nomadic agents) and complex interactions and dependencies among them. PMID:23112643

Fast kinematic ray tracing of first- and later-arriving global seismic phases

NASA Astrophysics Data System (ADS)

Bijwaard, Harmen; Spakman, Wim

1999-11-01

We have developed a ray tracing algorithm that traces first- and later-arriving global seismic phases precisely (traveltime errors of the order of 0.1 s), and with great computational efficiency (15 rays s- 1). To achieve this, we have extended and adapted two existing ray tracing techniques: a graph method and a perturbation method. The two resulting algorithms are able to trace (critically) refracted, (multiply) reflected, some diffracted (Pdiff), and (multiply) converted seismic phases in a 3-D spherical geometry, thus including the largest part of seismic phases that are commonly observed on seismograms. We have tested and compared the two methods in 2-D and 3-D Cartesian and spherical models, for which both algorithms have yielded precise paths and traveltimes. These tests indicate that only the perturbation method is computationally efficient enough to perform 3-D ray tracing on global data sets of several million phases. To demonstrate its potential for non-linear tomography, we have applied the ray perturbation algorithm to a data set of 7.6 million P and pP phases used by Bijwaard et al. (1998) for linearized tomography. This showed that the expected heterogeneity within the Earth's mantle leads to significant non-linear effects on traveltimes for 10 per cent of the applied phases.

An innovative localisation algorithm for railway vehicles

NASA Astrophysics Data System (ADS)

Allotta, B.; D'Adamio, P.; Malvezzi, M.; Pugi, L.; Ridolfi, A.; Rindi, A.; Vettori, G.

2014-11-01

In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the Italian Sistema Controllo Marcia Treno (SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and an Inertial Measurements Unit (IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements. 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.

ibex: An open infrastructure software platform to facilitate collaborative work in radiomics

PubMed Central

Zhang, Lifei; Fried, David V.; Fave, Xenia J.; Hunter, Luke A.; Court, Laurence E.

2015-01-01

Purpose: Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (ibex), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. Methods: The ibex software package was developed using the matlab and c/c++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, ibex is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, ibex provides an integrated development environment on top of matlab and c/c++, so users are not limited to its built-in functions. In the ibex developer studio, users can plug in, debug, and test new algorithms, extending ibex’s functionality. ibex also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the ibex workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. Results: Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the ibex software to be intuitive, powerful, and easy to use. ibex can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone ibex and ibex’s source code can be downloaded. Conclusions: The authors successfully implemented ibex, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation. PMID:25735289

IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics.

PubMed

Zhang, Lifei; Fried, David V; Fave, Xenia J; Hunter, Luke A; Yang, Jinzhong; Court, Laurence E

2015-03-01

Radiomics, which is the high-throughput extraction and analysis of quantitative image features, has been shown to have considerable potential to quantify the tumor phenotype. However, at present, a lack of software infrastructure has impeded the development of radiomics and its applications. Therefore, the authors developed the imaging biomarker explorer (IBEX), an open infrastructure software platform that flexibly supports common radiomics workflow tasks such as multimodality image data import and review, development of feature extraction algorithms, model validation, and consistent data sharing among multiple institutions. The IBEX software package was developed using the MATLAB and c/c++ programming languages. The software architecture deploys the modern model-view-controller, unit testing, and function handle programming concepts to isolate each quantitative imaging analysis task, to validate if their relevant data and algorithms are fit for use, and to plug in new modules. On one hand, IBEX is self-contained and ready to use: it has implemented common data importers, common image filters, and common feature extraction algorithms. On the other hand, IBEX provides an integrated development environment on top of MATLAB and c/c++, so users are not limited to its built-in functions. In the IBEX developer studio, users can plug in, debug, and test new algorithms, extending IBEX's functionality. IBEX also supports quality assurance for data and feature algorithms: image data, regions of interest, and feature algorithm-related data can be reviewed, validated, and/or modified. More importantly, two key elements in collaborative workflows, the consistency of data sharing and the reproducibility of calculation result, are embedded in the IBEX workflow: image data, feature algorithms, and model validation including newly developed ones from different users can be easily and consistently shared so that results can be more easily reproduced between institutions. Researchers with a variety of technical skill levels, including radiation oncologists, physicists, and computer scientists, have found the IBEX software to be intuitive, powerful, and easy to use. IBEX can be run at any computer with the windows operating system and 1GB RAM. The authors fully validated the implementation of all importers, preprocessing algorithms, and feature extraction algorithms. Windows version 1.0 beta of stand-alone IBEX and IBEX's source code can be downloaded. The authors successfully implemented IBEX, an open infrastructure software platform that streamlines common radiomics workflow tasks. Its transparency, flexibility, and portability can greatly accelerate the pace of radiomics research and pave the way toward successful clinical translation.

Heuristic and algorithmic processing in English, mathematics, and science education.

PubMed

Sharps, Matthew J; Hess, Adam B; Price-Sharps, Jana L; Teh, Jane

2008-01-01

Many college students experience difficulties in basic academic skills. Recent research suggests that much of this difficulty may lie in heuristic competency--the ability to use and successfully manage general cognitive strategies. In the present study, the authors evaluated this possibility. They compared participants' performance on a practice California Basic Educational Skills Test and on a series of questions in the natural sciences with heuristic and algorithmic performance on a series of mathematics and reading comprehension exercises. Heuristic competency in mathematics was associated with better scores in science and mathematics. Verbal and algorithmic skills were associated with better reading comprehension. These results indicate the importance of including heuristic training in educational contexts and highlight the importance of a relatively domain-specific approach to questions of cognition in higher education.

An algorithm for solving the system-level problem in multilevel optimization

NASA Technical Reports Server (NTRS)

Balling, R. J.; Sobieszczanski-Sobieski, J.

1994-01-01

A multilevel optimization approach which is applicable to nonhierarchic coupled systems is presented. The approach includes a general treatment of design (or behavior) constraints and coupling constraints at the discipline level through the use of norms. Three different types of norms are examined: the max norm, the Kreisselmeier-Steinhauser (KS) norm, and the 1(sub p) norm. The max norm is recommended. The approach is demonstrated on a class of hub frame structures which simulate multidisciplinary systems. The max norm is shown to produce system-level constraint functions which are non-smooth. A cutting-plane algorithm is presented which adequately deals with the resulting corners in the constraint functions. The algorithm is tested on hub frames with increasing number of members (which simulate disciplines), and the results are summarized.

Development of an algorithm for improving quality and information processing capacity of MathSpeak synthetic speech renderings.

PubMed

Isaacson, M D; Srinivasan, S; Lloyd, L L

2010-01-01

MathSpeak is a set of rules for non speaking of mathematical expressions. These rules have been incorporated into a computerised module that translates printed mathematics into the non-ambiguous MathSpeak form for synthetic speech rendering. Differences between individual utterances produced with the translator module are difficult to discern because of insufficient pausing between utterances; hence, the purpose of this study was to develop an algorithm for improving the synthetic speech rendering of MathSpeak. To improve synthetic speech renderings, an algorithm for inserting pauses was developed based upon recordings of middle and high school math teachers speaking mathematic expressions. Efficacy testing of this algorithm was conducted with college students without disabilities and high school/college students with visual impairments. Parameters measured included reception accuracy, short-term memory retention, MathSpeak processing capacity and various rankings concerning the quality of synthetic speech renderings. All parameters measured showed statistically significant improvements when the algorithm was used. The algorithm improves the quality and information processing capacity of synthetic speech renderings of MathSpeak. This increases the capacity of individuals with print disabilities to perform mathematical activities and to successfully fulfill science, technology, engineering and mathematics academic and career objectives.

Unsupervised Learning of Overlapping Image Components Using Divisive Input Modulation

PubMed Central

Spratling, M. W.; De Meyer, K.; Kompass, R.

2009-01-01

This paper demonstrates that nonnegative matrix factorisation is mathematically related to a class of neural networks that employ negative feedback as a mechanism of competition. This observation inspires a novel learning algorithm which we call Divisive Input Modulation (DIM). The proposed algorithm provides a mathematically simple and computationally efficient method for the unsupervised learning of image components, even in conditions where these elementary features overlap considerably. To test the proposed algorithm, a novel artificial task is introduced which is similar to the frequently-used bars problem but employs squares rather than bars to increase the degree of overlap between components. Using this task, we investigate how the proposed method performs on the parsing of artificial images composed of overlapping features, given the correct representation of the individual components; and secondly, we investigate how well it can learn the elementary components from artificial training images. We compare the performance of the proposed algorithm with its predecessors including variations on these algorithms that have produced state-of-the-art performance on the bars problem. The proposed algorithm is more successful than its predecessors in dealing with overlap and occlusion in the artificial task that has been used to assess performance. PMID:19424442

Distributed Function Mining for Gene Expression Programming Based on Fast Reduction.

PubMed

Deng, Song; Yue, Dong; Yang, Le-chan; Fu, Xiong; Feng, Ya-zhou

2016-01-01

For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model. Thorough comparative experiments for DFMGEP-FR, centralized GEP and the parallel gene expression programming algorithm based on simulated annealing (parallel GEPSA) are included in this paper. For the waveform, mushroom, connect-4 and musk datasets, the comparative results show that the average time-consumption of DFMGEP-FR drops by 89.09%%, 88.85%, 85.79% and 93.06%, respectively, in contrast to centralized GEP and by 12.5%, 8.42%, 9.62% and 13.75%, respectively, compared with parallel GEPSA. Six well-studied UCI test data sets demonstrate the efficiency and capability of our proposed DFMGEP-FR algorithm for distributed function mining.

Studies of the DIII-D disruption database using Machine Learning algorithms

NASA Astrophysics Data System (ADS)

Rea, Cristina; Granetz, Robert; Meneghini, Orso

2017-10-01

A Random Forests Machine Learning algorithm, trained on a large database of both disruptive and non-disruptive DIII-D discharges, predicts disruptive behavior in DIII-D with about 90% of accuracy. Several algorithms have been tested and Random Forests was found superior in performances for this particular task. Over 40 plasma parameters are included in the database, with data for each of the parameters taken from 500k time slices. We focused on a subset of non-dimensional plasma parameters, deemed to be good predictors based on physics considerations. Both binary (disruptive/non-disruptive) and multi-label (label based on the elapsed time before disruption) classification problems are investigated. The Random Forests algorithm provides insight on the available dataset by ranking the relative importance of the input features. It is found that q95 and Greenwald density fraction (n/nG) are the most relevant parameters for discriminating between DIII-D disruptive and non-disruptive discharges. A comparison with the Gradient Boosted Trees algorithm is shown and the first results coming from the application of regression algorithms are presented. Work supported by the US Department of Energy under DE-FC02-04ER54698, DE-SC0014264 and DE-FG02-95ER54309.

A Comparison of Two Skip Entry Guidance Algorithms

NASA Technical Reports Server (NTRS)

Rea, Jeremy R.; Putnam, Zachary R.

2007-01-01

The Orion capsule vehicle will have a Lift-to-Drag ratio (L/D) of 0.3-0.35. For an Apollo-like direct entry into the Earth's atmosphere from a lunar return trajectory, this L/D will give the vehicle a maximum range of about 2500 nm and a maximum crossrange of 216 nm. In order to y longer ranges, the vehicle lift must be used to loft the trajectory such that the aerodynamic forces are decreased. A Skip-Trajectory results if the vehicle leaves the sensible atmosphere and a second entry occurs downrange of the atmospheric exit point. The Orion capsule is required to have landing site access (either on land or in water) inside the Continental United States (CONUS) for lunar returns anytime during the lunar month. This requirement means the vehicle must be capable of flying ranges of at least 5500 nm. For the L/D of the vehicle, this is only possible with the use of a guided Skip-Trajectory. A skip entry guidance algorithm is necessary to achieve this requirement. Two skip entry guidance algorithms have been developed: the Numerical Skip Entry Guidance (NSEG) algorithm was developed at NASA/JSC and PredGuid was developed at Draper Laboratory. A comparison of these two algorithms will be presented in this paper. Each algorithm has been implemented in a high-fidelity, 6 degree-of-freedom simulation called the Advanced NASA Technology Architecture for Exploration Studies (ANTARES). NASA and Draper engineers have completed several monte carlo analyses in order to compare the performance of each algorithm in various stress states. Each algorithm has been tested for entry-to-target ranges to include direct entries and skip entries of varying length. Dispersions have been included on the initial entry interface state, vehicle mass properties, vehicle aerodynamics, atmosphere, and Reaction Control System (RCS). Performance criteria include miss distance to the target, RCS fuel usage, maximum g-loads and heat rates for the first and second entry, total heat load, and control system saturation. The comparison of the performance criteria has led to a down select and guidance merger that will take the best ideas from each algorithm to create one skip entry guidance algorithm for the Orion vehicle.

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

PubMed

Brown, James M; Campbell, J Peter; Beers, Andrew; Chang, Ken; Ostmo, Susan; Chan, R V Paul; Dy, Jennifer; Erdogmus, Deniz; Ioannidis, Stratis; Kalpathy-Cramer, Jayashree; Chiang, Michael F

2018-05-02

Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The decision to treat is primarily based on the presence of plus disease, defined as dilation and tortuosity of retinal vessels. However, clinical diagnosis of plus disease is highly subjective and variable. To implement and validate an algorithm based on deep learning to automatically diagnose plus disease from retinal photographs. A deep convolutional neural network was trained using a data set of 5511 retinal photographs. Each image was previously assigned a reference standard diagnosis (RSD) based on consensus of image grading by 3 experts and clinical diagnosis by 1 expert (ie, normal, pre-plus disease, or plus disease). The algorithm was evaluated by 5-fold cross-validation and tested on an independent set of 100 images. Images were collected from 8 academic institutions participating in the Imaging and Informatics in ROP (i-ROP) cohort study. The deep learning algorithm was tested against 8 ROP experts, each of whom had more than 10 years of clinical experience and more than 5 peer-reviewed publications about ROP. Data were collected from July 2011 to December 2016. Data were analyzed from December 2016 to September 2017. A deep learning algorithm trained on retinal photographs. Receiver operating characteristic analysis was performed to evaluate performance of the algorithm against the RSD. Quadratic-weighted κ coefficients were calculated for ternary classification (ie, normal, pre-plus disease, and plus disease) to measure agreement with the RSD and 8 independent experts. Of the 5511 included retinal photographs, 4535 (82.3%) were graded as normal, 805 (14.6%) as pre-plus disease, and 172 (3.1%) as plus disease, based on the RSD. Mean (SD) area under the receiver operating characteristic curve statistics were 0.94 (0.01) for the diagnosis of normal (vs pre-plus disease or plus disease) and 0.98 (0.01) for the diagnosis of plus disease (vs normal or pre-plus disease). For diagnosis of plus disease in an independent test set of 100 retinal images, the algorithm achieved a sensitivity of 93% with 94% specificity. For detection of pre-plus disease or worse, the sensitivity and specificity were 100% and 94%, respectively. On the same test set, the algorithm achieved a quadratic-weighted κ coefficient of 0.92 compared with the RSD, outperforming 6 of 8 ROP experts. This fully automated algorithm diagnosed plus disease in ROP with comparable or better accuracy than human experts. This has potential applications in disease detection, monitoring, and prognosis in infants at risk of ROP.

LISA on Table: an optical simulator for LISA

NASA Astrophysics Data System (ADS)

Halloin, H.; Jeannin, O.; Argence, B.; Bourrier, V.; de Vismes, E.; Prat, P.

2017-11-01

LISA, the first space project for detecting gravitational waves, relies on two main technical challenges: the free falling masses and an outstanding precision on phase shift measurements (a few pm on 5 Mkm in the LISA band). The technology of the free falling masses, i.e. their isolation to forces other than gravity and the capability for the spacecraft to precisely follow the test masses, will soon be tested with the technological LISA Pathfinder mission. The performance of the phase measurement will be achieved by at least two stabilization stages: a pre-stabilisation of the laser frequency at a level of 10-13 (relative frequency stability) will be further improved by using numerical algorithms, such as Time Delay Interferometry, which have been theoretically and numerically demonstrated to reach the required performance level (10-21). Nevertheless, these algorithms, though already tested with numerical model of LISA, require experimental validation, including `realistic' hardware elements. Such an experiment would allow to evaluate the expected noise level and the possible interactions between subsystems. To this end, the APC is currently developing an optical benchtop experiment, called LISA On Table (LOT), which is representative of the three LISA spacecraft. A first module of the LOT experiment has been mounted and is being characterized. After completion this facility may be used by the LISA community to test hardware (photodiodes, phasemeters) or software (reconstruction algorithms) components.

The pathway to earthquake early warning in the US

NASA Astrophysics Data System (ADS)

Allen, R. M.; Given, D. D.; Heaton, T. H.; Vidale, J. E.; West Coast Earthquake Early Warning Development Team

2013-05-01

The development of earthquake early warning capabilities in the United States is now accelerating and expanding as the technical capability to provide warning is demonstrated and additional funding resources are making it possible to expand the current testing region to the entire west coast (California, Oregon and Washington). Over the course of the next two years we plan to build a prototype system that will provide a blueprint for a full public system in the US. California currently has a demonstrations warning system, ShakeAlert, that provides alerts to a group of test users from the public and private sector. These include biotech companies, technology companies, the entertainment industry, the transportation sector, and the emergency planning and response community. Most groups are currently in an evaluation mode, receiving the alerts and developing protocols for future response. The Bay Area Rapid Transit (BART) system is the one group who has now implemented an automated response to the warning system. BART now stops trains when an earthquake of sufficient size is detected. Research and development also continues to develop improved early warning algorithms to better predict the distribution of shaking in large earthquakes when the finiteness of the source becomes important. The algorithms under development include the use of both seismic and GPS instrumentation and integration with existing point source algorithms. At the same time, initial testing and development of algorithms in and for the Pacific Northwest is underway. In this presentation we will review the current status of the systems, highlight the new research developments, and lay out a pathway to a full public system for the US west coast. The research and development described is ongoing at Caltech, UC Berkeley, University of Washington, ETH Zurich, Southern California Earthquake Center, and the US Geological Survey, and is funded by the Gordon and Betty Moore Foundation and the US Geological Survey.

Artificial intelligence techniques applied to the development of a decision–support system for diagnosing celiac disease

PubMed Central

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2013-01-01

Background Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. Objective To develop a clinical decision–support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. Methods A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. Results The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision–support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k = 0.68 (p < 0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician’s diagnostic impression and the gold standard k = 0. 64 (p < 0.0001). There was moderate agreement between the physician’s diagnostic impression and CDSS k = 0.46 (p = 0.0008). Conclusions The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent accuracy in differentiating possible positive from negative CD diagnoses. This study may contribute towards developing of a computer-assisted environment to support CD diagnosis. PMID:21917512

Prioritizing earthquake and tsunami alerting efforts

NASA Astrophysics Data System (ADS)

Allen, R. M.; Allen, S.; Aranha, M. A.; Chung, A. I.; Hellweg, M.; Henson, I. H.; Melgar, D.; Neuhauser, D. S.; Nof, R. N.; Strauss, J. A.

2015-12-01

The timeline of hazards associated with earthquakes ranges from seconds for the strong shaking at the epicenter, to minutes for strong shaking at more distant locations in big quakes, to tens of minutes for a local tsunami. Earthquake and tsunami warning systems must therefore include very fast initial alerts, while also taking advantage of available time in bigger and tsunami-generating quakes. At the UC Berkeley Seismological Laboratory we are developing a suite of algorithms to provide the fullest possible information about earthquake shaking and tsunami inundation from seconds to minutes after a quake. The E-larmS algorithm uses the P-wave to rapidly detect an earthquake and issue a warning. It is currently issuing alerts to test users in as little as 3 sec after the origin time. Development of a new waveform detector may lead to even faster alerts. G-larmS uses permanent deformation estimates from GNSS stations to estimate the geometry and extent of rupture underway providing more accurate ground shaking estimates in big (M>~7) earthquakes. It performed well in the M6.0 2014 Napa earthquake. T-larmS is a new algorithm designed to extend alert capabilities to tsunami inundation. Rapid estimates of source characteristics for subduction zones event can not only be used to warn of the shaking hazard, but also the local tsunami inundation hazard. These algorithms are being developed, implemented and tested with a focus on the western US, but are also now being tested in other parts of the world including Israel, Turkey, Korea and Chile. Beta users in the Bay Area are receiving the alerts and beginning to implement automated actions. They also provide feedback on users needs, which has led to the development of the MyEEW smartphone app. This app allows beta users to receive the alerts on their cell phones. All these efforts feed into our ongoing assessment of directions and priorities for future development and implementation efforts.

Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

PubMed

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2011-11-01

Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. To develop a clinical decision-support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision-support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k=0.68 (p<0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician's diagnostic impression and the gold standard k=0. 64 (p<0.0001). There was moderate agreement between the physician's diagnostic impression and CDSS k=0.46 (p=0.0008). The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent accuracy in differentiating possible positive from negative CD diagnoses. This study may contribute towards developing of a computer-assisted environment to support CD diagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A NUMERICAL ALGORITHM FOR MODELING MULTIGROUP NEUTRINO-RADIATION HYDRODYNAMICS IN TWO SPATIAL DIMENSIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swesty, F. Douglas; Myra, Eric S.

It is now generally agreed that multidimensional, multigroup, neutrino-radiation hydrodynamics (RHD) is an indispensable element of any realistic model of stellar-core collapse, core-collapse supernovae, and proto-neutron star instabilities. We have developed a new, two-dimensional, multigroup algorithm that can model neutrino-RHD flows in core-collapse supernovae. Our algorithm uses an approach similar to the ZEUS family of algorithms, originally developed by Stone and Norman. However, this completely new implementation extends that previous work in three significant ways: first, we incorporate multispecies, multigroup RHD in a flux-limited-diffusion approximation. Our approach is capable of modeling pair-coupled neutrino-RHD, and includes effects of Pauli blocking inmore » the collision integrals. Blocking gives rise to nonlinearities in the discretized radiation-transport equations, which we evolve implicitly in time. We employ parallelized Newton-Krylov methods to obtain a solution of these nonlinear, implicit equations. Our second major extension to the ZEUS algorithm is the inclusion of an electron conservation equation that describes the evolution of electron-number density in the hydrodynamic flow. This permits calculating deleptonization of a stellar core. Our third extension modifies the hydrodynamics algorithm to accommodate realistic, complex equations of state, including those having nonconvex behavior. In this paper, we present a description of our complete algorithm, giving sufficient details to allow others to implement, reproduce, and extend our work. Finite-differencing details are presented in appendices. We also discuss implementation of this algorithm on state-of-the-art, parallel-computing architectures. Finally, we present results of verification tests that demonstrate the numerical accuracy of this algorithm on diverse hydrodynamic, gravitational, radiation-transport, and RHD sample problems. We believe our methods to be of general use in a variety of model settings where radiation transport or RHD is important. Extension of this work to three spatial dimensions is straightforward.« less

Efficient Modeling of Gravity Fields Caused by Sources with Arbitrary Geometry and Arbitrary Density Distribution

NASA Astrophysics Data System (ADS)

Wu, Leyuan

2018-01-01

We present a brief review of gravity forward algorithms in Cartesian coordinate system, including both space-domain and Fourier-domain approaches, after which we introduce a truly general and efficient algorithm, namely the convolution-type Gauss fast Fourier transform (Conv-Gauss-FFT) algorithm, for 2D and 3D modeling of gravity potential and its derivatives due to sources with arbitrary geometry and arbitrary density distribution which are defined either by discrete or by continuous functions. The Conv-Gauss-FFT algorithm is based on the combined use of a hybrid rectangle-Gaussian grid and the fast Fourier transform (FFT) algorithm. Since the gravity forward problem in Cartesian coordinate system can be expressed as continuous convolution-type integrals, we first approximate the continuous convolution by a weighted sum of a series of shifted discrete convolutions, and then each shifted discrete convolution, which is essentially a Toeplitz system, is calculated efficiently and accurately by combining circulant embedding with the FFT algorithm. Synthetic and real model tests show that the Conv-Gauss-FFT algorithm can obtain high-precision forward results very efficiently for almost any practical model, and it works especially well for complex 3D models when gravity fields on large 3D regular grids are needed.

An overview of the essential differences and similarities of system identification techniques

NASA Technical Reports Server (NTRS)

Mehra, Raman K.

1991-01-01

Information is given in the form of outlines, graphs, tables and charts. Topics include system identification, Bayesian statistical decision theory, Maximum Likelihood Estimation, identification methods, structural mode identification using a stochastic realization algorithm, and identification results regarding membrane simulations and X-29 flutter flight test data.

A test to evaluate the earthquake prediction algorithm, M8

USGS Publications Warehouse

Healy, John H.; Kossobokov, Vladimir G.; Dewey, James W.

1992-01-01

A test of the algorithm M8 is described. The test is constructed to meet four rules, which we propose to be applicable to the test of any method for earthquake prediction:  1. An earthquake prediction technique should be presented as a well documented, logical algorithm that can be used by  investigators without restrictions. 2. The algorithm should be coded in a common programming language and implementable on widely available computer systems. 3. A test of the earthquake prediction technique should involve future predictions with a black box version of the algorithm in which potentially adjustable parameters are fixed in advance. The source of the input data must be defined and ambiguities in these data must be resolved automatically by the algorithm. 4. At least one reasonable null hypothesis should be stated in advance of testing the earthquake prediction method, and it should be stated how this null hypothesis will be used to estimate the statistical significance of the earthquake predictions. The M8 algorithm has successfully predicted several destructive earthquakes, in the sense that the earthquakes occurred inside regions with linear dimensions from 384 to 854 km that the algorithm had identified as being in times of increased probability for strong earthquakes. In addition, M8 has successfully "post predicted" high percentages of strong earthquakes in regions to which it has been applied in retroactive studies. The statistical significance of previous predictions has not been established, however, and post-prediction studies in general are notoriously subject to success-enhancement through hindsight. Nor has it been determined how much more precise an M8 prediction might be than forecasts and probability-of-occurrence estimates made by other techniques. We view our test of M8 both as a means to better determine the effectiveness of M8 and as an experimental structure within which to make observations that might lead to improvements in the algorithm or conceivably lead to a radically different approach to earthquake prediction.

Advanced methods in NDE using machine learning approaches

NASA Astrophysics Data System (ADS)

Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank

2018-04-01

Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability prediction based on big data becomes possible, even if components are used in different versions or configurations. This is the promise behind German Industry 4.0.

The JPSS Ground Project Algorithm Verification, Test and Evaluation System

NASA Astrophysics Data System (ADS)

Vicente, G. A.; Jain, P.; Chander, G.; Nguyen, V. T.; Dixon, V.

2016-12-01

The Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) is an operational system that provides services to the Suomi National Polar-orbiting Partnership (S-NPP) Mission. It is also a unique environment for Calibration/Validation (Cal/Val) and Data Quality Assessment (DQA) of the Join Polar Satellite System (JPSS) mission data products. GRAVITE provides a fast and direct access to the data and products created by the Interface Data Processing Segment (IDPS), the NASA/NOAA operational system that converts Raw Data Records (RDR's) generated by sensors on the S-NPP into calibrated geo-located Sensor Data Records (SDR's) and generates Mission Unique Products (MUPS). It also facilitates algorithm investigation, integration, checkouts and tuning, instrument and product calibration and data quality support, monitoring and data/products distribution. GRAVITE is the portal for the latest S-NPP and JPSS baselined Processing Coefficient Tables (PCT's) and Look-Up-Tables (LUT's) and hosts a number DQA offline tools that takes advantage of the proximity to the near-real time data flows. It also contains a set of automated and ad-hoc Cal/Val tools used for algorithm analysis and updates, including an instance of the IDPS called GRAVITE Algorithm Development Area (G-ADA), that has the latest installation of the IDPS algorithms running in an identical software and hardware platforms. Two other important GRAVITE component are the Investigator-led Processing System (IPS) and the Investigator Computing Facility (ICF). The IPS is a dedicated environment where authorized users run automated scripts called Product Generation Executables (PGE's) to support Cal/Val and data quality assurance offline. This data-rich and data-driven service holds its own distribution system and allows operators to retrieve science data products. The ICF is a workspace where users can share computing applications and resources and have full access to libraries and science and sensor quality analysis tools. In this presentation we will describe the GRAVITE systems and subsystems, architecture, technical specifications, capabilities and resources, distributed data and products and the latest advances to support the JPSS science algorithm implementation, validation and testing.