Casimir experiments showing saturation effects
Sernelius, Bo E.
2009-10-15
We address several different Casimir experiments where theory and experiment disagree. First out is the classical Casimir force measurement between two metal half spaces; here both in the form of the torsion pendulum experiment by Lamoreaux and in the form of the Casimir pressure measurement between a gold sphere and a gold plate as performed by Decca et al.; theory predicts a large negative thermal correction, absent in the high precision experiments. The third experiment is the measurement of the Casimir force between a metal plate and a laser irradiated semiconductor membrane as performed by Chen et al.; the change in force with laser intensity is larger than predicted by theory. The fourth experiment is the measurement of the Casimir force between an atom and a wall in the form of the measurement by Obrecht et al. of the change in oscillation frequency of a {sup 87}Rb Bose-Einstein condensate trapped to a fused silica wall; the change is smaller than predicted by theory. We show that saturation effects can explain the discrepancies between theory and experiment observed in all these cases.
SAGE II inversion algorithm. [Stratospheric Aerosol and Gas Experiment
NASA Technical Reports Server (NTRS)
Chu, W. P.; Mccormick, M. P.; Lenoble, J.; Brogniez, C.; Pruvost, P.
1989-01-01
The operational Stratospheric Aerosol and Gas Experiment II multichannel data inversion algorithm is described. Aerosol and ozone retrievals obtained with the algorithm are discussed. The algorithm is compared to an independently developed algorithm (Lenoble, 1989), showing that the inverted aerosol and ozone profiles from the two algorithms are similar within their respective uncertainties.
Experiments showing dynamics of materials interfaces
Benjamin, R.F.
1997-02-01
The discipline of materials science and engineering often involves understanding and controlling properties of interfaces. The authors address the challenge of educating students about properties of interfaces, particularly dynamic properties and effects of unstable interfaces. A series of simple, inexpensive, hands-on activities about fluid interfaces provides students with a testbed to develop intuition about interface dynamics. The experiments highlight the essential role of initial interfacial perturbations in determining the dynamic response of the interface. The experiments produce dramatic, unexpected effects when initial perturbations are controlled and inhibited. These activities help students to develop insight about unstable interfaces that can be applied to analogous problems in materials science and engineering. The lessons examine ``Rayleigh-Taylor instability,`` an interfacial instability that occurs when a higher-density fluid is above a lower-density fluid.
Worldwide experience shows horizontal well success
Karlsson, H.; Bitto, R.
1989-03-01
The convergence of technology and experience has made horizontal drilling an important tool in increasing production and solving a variety of completion problems. Since the early 1980s, horizontal drilling has been used to improve production on more than 700 oil and gas wells throughout the world. Approximately 200 horizontal wells were drilled in 1988 alone. Interest in horizontal drilling has been accelerating rapidly as service companies have developed and offered new technology for drilling and producing horizontal wells. Simultaneously, oil companies have developed better methods for evaluating reservoirs for potential horizontal applications, while their production departments have gained experience at completing and producing them. To date, most horizontal wells have been drilled in the United States. A major application is to complete naturally fractured formations, such as the Austin chalk in Texas, the Bakken shale in the Williston basin, the Spraberry in West Texas and the Devonian shale in the Eastern states. In addition, many horizontal wells have been drilled to produce the Niagaran reefs and the irregular Antrim shale reservoirs in Michigan.
Children's Art Show: An Educational Family Experience
ERIC Educational Resources Information Center
Bakerlis, Julienne
2007-01-01
In a time of seemingly rampant budget cuts in the arts in school systems throughout the country, a children's art show reaps many rewards. It can strengthen family-school relationships and community ties and stimulate questions and comments about the benefits of art and its significance in the development of young children. In this photo essay of…
Retrieval Algorithms for the Halogen Occultation Experiment
NASA Technical Reports Server (NTRS)
Thompson, Robert E.; Gordley, Larry L.
2009-01-01
The Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite (UARS) provided high quality measurements of key middle atmosphere constituents, aerosol characteristics, and temperature for 14 years (1991-2005). This report is an outline of the Level 2 retrieval algorithms, and it also describes the great care that was taken in characterizing the instrument prior to launch and throughout its mission life. It represents an historical record of the techniques used to analyze the data and of the steps that must be considered for the development of a similar experiment for future satellite missions.
Algorithmic Animation in Education--Review of Academic Experience
ERIC Educational Resources Information Center
Esponda-Arguero, Margarita
2008-01-01
This article is a review of the pedagogical experience obtained with systems for algorithmic animation. Algorithms consist of a sequence of operations whose effect on data structures can be visualized using a computer. Students learn algorithms by stepping the animation through the different individual operations, possibly reversing their effect.…
Patient Experience Shows Little Relationship with Hospital Quality Management Strategies
Groene, Oliver; Arah, Onyebuchi A.; Klazinga, Niek S.; Wagner, Cordula; Bartels, Paul D.; Kristensen, Solvejg; Saillour, Florence; Thompson, Andrew; Thompson, Caroline A.; Pfaff, Holger; DerSarkissian, Maral; Sunol, Rosa
2015-01-01
Objectives Patient-reported experience measures are increasingly being used to routinely monitor the quality of care. With the increasing attention on such measures, hospital managers seek ways to systematically improve patient experience across hospital departments, in particular where outcomes are used for public reporting or reimbursement. However, it is currently unclear whether hospitals with more mature quality management systems or stronger focus on patient involvement and patient-centered care strategies perform better on patient-reported experience. We assessed the effect of such strategies on a range of patient-reported experience measures. Materials and Methods We employed a cross-sectional, multi-level study design randomly recruiting hospitals from the Czech Republic, France, Germany, Poland, Portugal, Spain, and Turkey between May 2011 and January 2012. Each hospital contributed patient level data for four conditions/pathways: acute myocardial infarction, stroke, hip fracture and deliveries. The outcome variables in this study were a set of patient-reported experience measures including a generic 6-item measure of patient experience (NORPEQ), a 3-item measure of patient-perceived discharge preparation (Health Care Transition Measure) and two single item measures of perceived involvement in care and hospital recommendation. Predictor variables included three hospital management strategies: maturity of the hospital quality management system, patient involvement in quality management functions and patient-centered care strategies. We used directed acyclic graphs to detail and guide the modeling of the complex relationships between predictor variables and outcome variables, and fitted multivariable linear mixed models with random intercept by hospital, and adjusted for fixed effects at the country level, hospital level and patient level. Results Overall, 74 hospitals and 276 hospital departments contributed data on 6,536 patients to this study (acute
The Macnamara Medicine Show: an Experiment in Higher Education.
ERIC Educational Resources Information Center
O'Keefe, Phil; Halverson, Bret
1979-01-01
Describes an experiment using theatrical methods to present the impact of natural disasters upon the poorest classes of the population. Concludes that it is essential to include affective learning opportunities in course design. Journal availability: see SO 507 262. (Author/CK)
Model experiments showing simultaneous development of folds and transcurrent faults
NASA Astrophysics Data System (ADS)
Dubey, Ashok Kumar
1980-05-01
Simultaneous development of noncylindrical folds and transcurrent fractures has been studied using model techniques. A plasticine model was compressed in one direction and an initial formation of folds was followed by the initiation of conjugate sets of transcurrent fractures. It was recorded that with progressive deformation the length of each fracture and the displacement along it increase steadily and the rate of displacement varies at different stages of deformation. Individual fold geometries vary along their hinge lines and these geometrical variations appear to be due to interference of folds with the transcurrent fractures. These interference effects also change the amount of rotation of fractures. Fold structures are different on either side of the fault plane. A natural example from the Bude area, England, shows similar geometrical features. The method of determining fault displacement by comparing the positions of fold hinge lines on either side of a fault is discussed in the light of the above results.
Experiments on Supervised Learning Algorithms for Text Categorization
NASA Technical Reports Server (NTRS)
Namburu, Setu Madhavi; Tu, Haiying; Luo, Jianhui; Pattipati, Krishna R.
2005-01-01
Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.
IDEAL: Images Across Domains, Experiments, Algorithms and Learning
NASA Astrophysics Data System (ADS)
Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao
2016-09-01
Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.
Experience with a Genetic Algorithm Implemented on a Multiprocessor Computer
NASA Technical Reports Server (NTRS)
Plassman, Gerald E.; Sobieszczanski-Sobieski, Jaroslaw
2000-01-01
Numerical experiments were conducted to find out the extent to which a Genetic Algorithm (GA) may benefit from a multiprocessor implementation, considering, on one hand, that analyses of individual designs in a population are independent of each other so that they may be executed concurrently on separate processors, and, on the other hand, that there are some operations in a GA that cannot be so distributed. The algorithm experimented with was based on a gaussian distribution rather than bit exchange in the GA reproductive mechanism, and the test case was a hub frame structure of up to 1080 design variables. The experimentation engaging up to 128 processors confirmed expectations of radical elapsed time reductions comparing to a conventional single processor implementation. It also demonstrated that the time spent in the non-distributable parts of the algorithm and the attendant cross-processor communication may have a very detrimental effect on the efficient utilization of the multiprocessor machine and on the number of processors that can be used effectively in a concurrent manner. Three techniques were devised and tested to mitigate that effect, resulting in efficiency increasing to exceed 99 percent.
Data inversion algorithm development for the hologen occultation experiment
NASA Technical Reports Server (NTRS)
Gordley, Larry L.; Mlynczak, Martin G.
1986-01-01
The successful retrieval of atmospheric parameters from radiometric measurement requires not only the ability to do ideal radiometric calculations, but also a detailed understanding of instrument characteristics. Therefore a considerable amount of time was spent in instrument characterization in the form of test data analysis and mathematical formulation. Analyses of solar-to-reference interference (electrical cross-talk), detector nonuniformity, instrument balance error, electronic filter time-constants and noise character were conducted. A second area of effort was the development of techniques for the ideal radiometric calculations required for the Halogen Occultation Experiment (HALOE) data reduction. The computer code for these calculations must be extremely complex and fast. A scheme for meeting these requirements was defined and the algorithms needed form implementation are currently under development. A third area of work included consulting on the implementation of the Emissivity Growth Approximation (EGA) method of absorption calculation into a HALOE broadband radiometer channel retrieval algorithm.
Experience with CANDID: Comparison algorithm for navigating digital image databases
Kelly, P.; Cannon, M.
1994-10-01
This paper presents results from the authors experience with CANDID (Comparison Algorithm for Navigating Digital Image Databases), which was designed to facilitate image retrieval by content using a query-by-example methodology. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized similarity measure between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to a user-provided example image. Results for three test applications are included.
Experience with CANDID: comparison algorithm for navigating digital image databases
NASA Astrophysics Data System (ADS)
Kelly, Patrick M.; Cannon, T. Michael
1995-01-01
This paper presents results from our experience with CANDID (comparison algorithm for navigating digital image databases), which was designed to facilitate image retrieval by content using a query-by-example methodology. A global signature describing the texture, shape, or color content is first computed for every image stored in a database, and a normalized similarity measure between probability density functions of feature vectors is used to match signatures. This method can be used to retrieve images from a database that are similar to a user-provided example image. Results for three test applications are included.
Experiments with a Parallel Multi-Objective Evolutionary Algorithm for Scheduling
NASA Technical Reports Server (NTRS)
Brown, Matthew; Johnston, Mark D.
2013-01-01
Evolutionary multi-objective algorithms have great potential for scheduling in those situations where tradeoffs among competing objectives represent a key requirement. One challenge, however, is runtime performance, as a consequence of evolving not just a single schedule, but an entire population, while attempting to sample the Pareto frontier as accurately and uniformly as possible. The growing availability of multi-core processors in end user workstations, and even laptops, has raised the question of the extent to which such hardware can be used to speed up evolutionary algorithms. In this paper we report on early experiments in parallelizing a Generalized Differential Evolution (GDE) algorithm for scheduling long-range activities on NASA's Deep Space Network. Initial results show that significant speedups can be achieved, but that performance does not necessarily improve as more cores are utilized. We describe our preliminary results and some initial suggestions from parallelizing the GDE algorithm. Directions for future work are outlined.
Pile-Up Discrimination Algorithms for the HOLMES Experiment
NASA Astrophysics Data System (ADS)
Ferri, E.; Alpert, B.; Bennett, D.; Faverzani, M.; Fowler, J.; Giachero, A.; Hays-Wehle, J.; Maino, M.; Nucciotti, A.; Puiu, A.; Ullom, J.
2016-07-01
The HOLMES experiment is a new large-scale experiment for the electron neutrino mass determination by means of the electron capture decay of ^{163}Ho. In such an experiment, random coincidence events are one of the main sources of background which impair the ability to identify the effect of a non-vanishing neutrino mass. In order to resolve these spurious events, detectors characterized by a fast response are needed as well as pile-up recognition algorithms. For that reason, we have developed a code for testing the discrimination efficiency of various algorithms in recognizing pile up events in dependence of the time separation between two pulses. The tests are performed on simulated realistic TES signals and noise. Indeed, the pulse profile is obtained by solving the two coupled differential equations which describe the response of the TES according to the Irwin-Hilton model. To these pulses, a noise waveform which takes into account all the noise sources regularly present in a real TES is added. The amplitude of the generated pulses is distributed as the ^{163}Ho calorimetric spectrum. Furthermore, the rise time of these pulses has been chosen taking into account the constraints given by both the bandwidth of the microwave multiplexing read out with a flux ramp demodulation and the bandwidth of the ADC boards currently available for ROACH2. Among the different rejection techniques evaluated, the Wiener Filter technique, a digital filter to gain time resolution, has shown an excellent pile-up rejection efficiency. The obtained time resolution closely matches the baseline specifications of the HOLMES experiment. We report here a description of our simulation code and a comparison of the different rejection techniques.
Experiences and evolutions of the ALICE DAQ Detector Algorithms framework
NASA Astrophysics Data System (ADS)
Chapeland, Sylvain; Carena, Franco; Carena, Wisla; Chibante Barroso, Vasco; Costa, Filippo; Denes, Ervin; Divia, Roberto; Fuchs, Ulrich; Grigore, Alexandru; Simonetti, Giuseppe; Soos, Csaba; Telesca, Adriana; Vande Vyvre, Pierre; von Haller, Barthelemy
2012-12-01
ALICE (A Large Ion Collider Experiment) is the heavy-ion detector studying the physics of strongly interacting matter and the quark-gluon plasma at the CERN LHC (Large Hadron Collider). The 18 ALICE sub-detectors are regularly calibrated in order to achieve most accurate physics measurements. Some of these procedures are done online in the DAQ (Data Acquisition System) so that calibration results can be directly used for detector electronics configuration before physics data taking, at run time for online event monitoring, and offline for data analysis. A framework was designed to collect statistics and compute calibration parameters, and has been used in production since 2008. This paper focuses on the recent features developed to benefit from the multi-cores architecture of CPUs, and to optimize the processing power available for the calibration tasks. It involves some C++ base classes to effectively implement detector specific code, with independent processing of events in parallel threads and aggregation of partial results. The Detector Algorithm (DA) framework provides utility interfaces for handling of input and output (configuration, monitored physics data, results, logging), and self-documentation of the produced executable. New algorithms are created quickly by inheritance of base functionality and implementation of few ad-hoc virtual members, while the framework features are kept expandable thanks to the isolation of the detector calibration code. The DA control system also handles unexpected processes behaviour, logs execution status, and collects performance statistics.
Searching the UVSP database and a list of experiments showing mass motions
NASA Technical Reports Server (NTRS)
Thompson, William
1986-01-01
Since the Solar Maximum Mission (SMM) satellite was launched, a large database has been built up of experiments using the Ultraviolet Spectrometer and Polarimeter (UVSP) instrument. Access to this database can be gained through the SMM Vax 750 computer at Goddard Space Flight Center. One useful way to do this is with a program called USEARCH. This program allows one to make a listing of different types of UVSP experiments. It is evident that this program is useful to those who would wish to make use of UVSP data, but who don't know what data is available. Therefore it was decided to include a short description of how to make use of the USEARCH program. Also described, but not included, is a listing of all UVSP experiments showing mass motions in prominences and filaments. This list was made with the aid of the USEARCH program.
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.
Eigensystem realization algorithm modal identification experiences with mini-mast
NASA Technical Reports Server (NTRS)
Pappa, Richard S.; Schenk, Axel; Noll, Christopher
1992-01-01
This paper summarizes work performed under a collaborative research effort between the National Aeronautics and Space Administration (NASA) and the German Aerospace Research Establishment (DLR, Deutsche Forschungsanstalt fur Luft- und Raumfahrt). The objective is to develop and demonstrate system identification technology for future large space structures. Recent experiences using the Eigensystem Realization Algorithm (ERA), for modal identification of Mini-Mast, are reported. Mini-Mast is a 20 m long deployable space truss used for structural dynamics and active vibration-control research at the Langley Research Center. A comprehensive analysis of 306 frequency response functions (3 excitation forces and 102 displacement responses) was performed. Emphasis is placed on two topics of current research: (1) gaining an improved understanding of ERA performance characteristics (theory vs. practice); and (2) developing reliable techniques to improve identification results for complex experimental data. Because of nonlinearities and numerous local modes, modal identification of Mini-Mast proved to be surprisingly difficult. Methods were available, ERA, for obtaining detailed, high-confidence results.
ERIC Educational Resources Information Center
Hundhausen, Christopher D.; Brown, Jonathan L.
2008-01-01
Within the context of an introductory CS1 unit on algorithmic problem-solving, we are exploring the pedagogical value of a novel active learning activity--the "studio experience"--that actively engages learners with algorithm visualization technology. In a studio experience, student pairs are tasked with (a) developing a solution to an algorithm…
A general algorithm for peak-tracking in multi-dimensional NMR experiments.
Ravel, P; Kister, G; Malliavin, T E; Delsuc, M A
2007-04-01
We present an algorithmic method allowing automatic tracking of NMR peaks in a series of spectra. It consists in a two phase analysis. The first phase is a local modeling of the peak displacement between two consecutive experiments using distance matrices. Then, from the coefficients of these matrices, a value graph containing the a priori set of possible paths used by these peaks is generated. On this set, the minimization under constraint of the target function by a heuristic approach provides a solution to the peak-tracking problem. This approach has been named GAPT, standing for General Algorithm for NMR Peak Tracking. It has been validated in numerous simulations resembling those encountered in NMR spectroscopy. We show the robustness and limits of the method for situations with many peak-picking errors, and presenting a high local density of peaks. It is then applied to the case of a temperature study of the NMR spectrum of the Lipid Transfer Protein (LTP).
Experiences with the PGAPack Parallel Genetic Algorithm library
Levine, D.; Hallstrom, P.; Noelle, D.; Walenz, B.
1997-07-01
PGAPack is the first widely distributed parallel genetic algorithm library. Since its release, several thousand copies have been distributed worldwide to interested users. In this paper we discuss the key components of the PGAPack design philosophy and present a number of application examples that use PGAPack.
PSO algorithm enhanced with Lozi Chaotic Map - Tuning experiment
Pluhacek, Michal; Senkerik, Roman; Zelinka, Ivan
2015-03-10
In this paper it is investigated the effect of tuning of control parameters of the Lozi Chaotic Map employed as a chaotic pseudo-random number generator for the particle swarm optimization algorithm. Three different benchmark functions are selected from the IEEE CEC 2013 competition benchmark set. The Lozi map is extensively tuned and the performance of PSO is evaluated.
Video tracking algorithm of long-term experiment using stand-alone recording system.
Chen, Yu-Jen; Li, Yan-Chay; Huang, Ke-Nung; Jen, Sun-Lon; Young, Ming-Shing
2008-08-01
Many medical and behavioral applications require the ability to monitor and quantify the behavior of small animals. In general these animals are confined in small cages. Often these situations involve very large numbers of cages. Modern research facilities commonly monitor simultaneously thousands of animals over long periods of time. However, conventional systems require one personal computer per monitoring platform, which is too complex, expensive, and increases power consumption for large laboratory applications. This paper presents a simplified video tracking algorithm for long-term recording using a stand-alone system. The feature of the presented tracking algorithm revealed that computation speed is very fast data storage requirements are small, and hardware requirements are minimal. The stand-alone system automatically performs tracking and saving acquired data to a secure digital card. The proposed system is designed for video collected at a 640 x 480 pixel with 16 bit color resolution. The tracking result is updated every 30 frames/s. Only the locomotive data are stored. Therefore, the data storage requirements could be minimized. In addition, detection via the designed algorithm uses the Cb and Cr values of a colored marker affixed to the target to define the tracked position and allows multiobject tracking against complex backgrounds. Preliminary experiment showed that such tracking information stored by the portable and stand-alone system could provide comprehensive information on the animal's activity.
Video tracking algorithm of long-term experiment using stand-alone recording system
NASA Astrophysics Data System (ADS)
Chen, Yu-Jen; Li, Yan-Chay; Huang, Ke-Nung; Jen, Sun-Lon; Young, Ming-Shing
2008-08-01
Many medical and behavioral applications require the ability to monitor and quantify the behavior of small animals. In general these animals are confined in small cages. Often these situations involve very large numbers of cages. Modern research facilities commonly monitor simultaneously thousands of animals over long periods of time. However, conventional systems require one personal computer per monitoring platform, which is too complex, expensive, and increases power consumption for large laboratory applications. This paper presents a simplified video tracking algorithm for long-term recording using a stand-alone system. The feature of the presented tracking algorithm revealed that computation speed is very fast data storage requirements are small, and hardware requirements are minimal. The stand-alone system automatically performs tracking and saving acquired data to a secure digital card. The proposed system is designed for video collected at a 640×480 pixel with 16 bit color resolution. The tracking result is updated every 30 frames/s. Only the locomotive data are stored. Therefore, the data storage requirements could be minimized. In addition, detection via the designed algorithm uses the Cb and Cr values of a colored marker affixed to the target to define the tracked position and allows multiobject tracking against complex backgrounds. Preliminary experiment showed that such tracking information stored by the portable and stand-alone system could provide comprehensive information on the animal's activity.
F-18 SRA closeup of nose cap showing Advanced L-Probe Air Data Integration experiment
NASA Technical Reports Server (NTRS)
1997-01-01
This L-shaped probe mounted on the forward fuselage of a modified F-18 Systems Research Aircraft was the focus of an air data collection experiment flown at NASA's Dryden Flight Research Center, Edwards, California. The Advanced L-Probe Air Data Integration (ALADIN) experiment focused on providing pilots with angle-of-attack and angle-of-sideslip information as well as traditional airspeed and altitude data from a single system. For the experiment, the probes--one mounted on either side of the F-18's forward fuselage--were hooked to a series of four transducers, which relayed pressure measurements to an on-board research computer.
Lullaby Light Shows: Everyday Musical Experience among Under-Two-Year-Olds
ERIC Educational Resources Information Center
Young, Susan
2008-01-01
This article reports on information gathered from a set of interviews carried out with 88 mothers of under-two-year-olds. The interviews enquired about the everyday musical experiences of their babies and very young children in the home. From the process of analysis, the responses to the interviews were grouped into three main areas: musical…
Do Talk Shows Cultivate Adolescents' Views of the World? A Prolonged-Exposure Experiment.
ERIC Educational Resources Information Center
Rossler, Patrick; Brosius, Hans-Bernd
2001-01-01
Investigates effects of German daily talk shows (dealing with lesbian or gay male relationships, transsexuality, and body adornment) on adolescents. Shows that cultivation effects occurred at both first- and second-order level, but were restricted to the issues; and no transfer effects pertaining to a general change of attitudes. Concludes…
Real Science: MIT Reality Show Tracks Experiences, Frustrations of Chemistry Lab Students
ERIC Educational Resources Information Center
Cooper, Kenneth J.
2012-01-01
A reality show about a college course--a chemistry class no less? That's what "ChemLab Boot Camp" is. The 14-part series of short videos is being released one episode at a time on the online learning site of the Massachusetts Institute of Technology. The novel show follows a diverse group of 14 freshmen as they struggle to master the laboratory…
Sinaiko, Anna D; Ross-Degnan, Dennis; Soumerai, Stephen B; Lieu, Tracy; Galbraith, Alison
2013-01-01
In 2022 twenty-five million people are expected to purchase health insurance through exchanges to be established under the Affordable Care Act. Understanding how people seek information and make decisions about the insurance plans that are available to them may improve their ability to select a plan and their satisfaction with it. We conducted a survey in 2010 of enrollees in one plan offered through Massachusetts's unsubsidized health insurance exchange to analyze how a sample of consumers selected their plans. More than 40 percent found plan information difficult to understand. Approximately one-third of respondents had help selecting plans-most commonly from friends or family members. However, one-fifth of respondents wished they had had help narrowing plan choices; these enrollees were more likely to report negative experiences related to plan understanding, satisfaction with affordability and coverage, and unexpected costs. Some may have been eligible for subsidized plans. Exchanges may need to provide more resources and decision-support tools to improve consumers' experiences in selecting a health plan. PMID:23297274
Multiagent pursuit-evasion games: Algorithms and experiments
NASA Astrophysics Data System (ADS)
Kim, Hyounjin
Deployment of intelligent agents has been made possible through advances in control software, microprocessors, sensor/actuator technology, communication technology, and artificial intelligence. Intelligent agents now play important roles in many applications where human operation is too dangerous or inefficient. There is little doubt that the world of the future will be filled with intelligent robotic agents employed to autonomously perform tasks, or embedded in systems all around us, extending our capabilities to perceive, reason and act, and replacing human efforts. There are numerous real-world applications in which a single autonomous agent is not suitable and multiple agents are required. However, after years of active research in multi-agent systems, current technology is still far from achieving many of these real-world applications. Here, we consider the problem of deploying a team of unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV) to pursue a second team of UGV evaders while concurrently building a map in an unknown environment. This pursuit-evasion game encompasses many of the challenging issues that arise in operations using intelligent multi-agent systems. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible pursuit policies: greedy and global-max. We also formulate this probabilistic pursuit-evasion game as a partially observable Markov decision process and employ a policy search algorithm to obtain a good pursuit policy from a restricted class of policies. The estimated value of this policy is guaranteed to be uniformly close to the optimal value in the given policy class under mild conditions. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We then describe our implementation on a fleet of UGVs and UAVs, detailing components such
Shia, R L; Ha, Y L; Wen, J S; Yung, Y L
1990-05-20
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. We generalize the original scheme to include higher-order moments. In addition, we show 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.
Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent
WALL, DIANA H; BRADFORD, MARK A; ST JOHN, MARK G; TROFYMOW, JOHN A; BEHAN-PELLETIER, VALERIE; BIGNELL, DAVID E; DANGERFIELD, J MARK; PARTON, WILLIAM J; RUSEK, JOSEF; VOIGT, WINFRIED; WOLTERS, VOLKMAR; GARDEL, HOLLEY ZADEH; AYUKE, FRED O; BASHFORD, RICHARD; BELJAKOVA, OLGA I; BOHLEN, PATRICK J; BRAUMAN, ALAIN; FLEMMING, STEPHEN; HENSCHEL, JOH R; JOHNSON, DAN L; JONES, T HEFIN; KOVAROVA, MARCELA; KRANABETTER, J MARTY; KUTNY, LES; LIN, KUO-CHUAN; MARYATI, MOHAMED; MASSE, DOMINIQUE; POKARZHEVSKII, ANDREI; RAHMAN, HOMATHEVI; SABARÁ, MILLOR G; SALAMON, JOERG-ALFRED; SWIFT, MICHAEL J; VARELA, AMANDA; VASCONCELOS, HERALDO L; WHITE, DON; ZOU, XIAOMING
2008-01-01
Climate and litter quality are primary drivers of terrestrial decomposition and, based on evidence from multisite experiments at regional and global scales, are universally factored into global decomposition models. In contrast, soil animals are considered key regulators of decomposition at local scales but their role at larger scales is unresolved. Soil animals are consequently excluded from global models of organic mineralization processes. Incomplete assessment of the roles of soil animals stems from the difficulties of manipulating invertebrate animals experimentally across large geographic gradients. This is compounded by deficient or inconsistent taxonomy. We report a global decomposition experiment to assess the importance of soil animals in C mineralization, in which a common grass litter substrate was exposed to natural decomposition in either control or reduced animal treatments across 30 sites distributed from 43°S to 68°N on six continents. Animals in the mesofaunal size range were recovered from the litter by Tullgren extraction and identified to common specifications, mostly at the ordinal level. The design of the trials enabled faunal contribution to be evaluated against abiotic parameters between sites. Soil animals increase decomposition rates in temperate and wet tropical climates, but have neutral effects where temperature or moisture constrain biological activity. Our findings highlight that faunal influences on decomposition are dependent on prevailing climatic conditions. We conclude that (1) inclusion of soil animals will improve the predictive capabilities of region- or biome-scale decomposition models, (2) soil animal influences on decomposition are important at the regional scale when attempting to predict global change scenarios, and (3) the statistical relationship between decomposition rates and climate, at the global scale, is robust against changes in soil faunal abundance and diversity.
Online Tracking Algorithms on GPUs for the P̅ANDA Experiment at FAIR
NASA Astrophysics Data System (ADS)
Bianchi, L.; Herten, A.; Ritman, J.; Stockmanns, T.; Adinetz,
2015-12-01
P̅ANDA is a future hadron and nuclear physics experiment at the FAIR facility in construction in Darmstadt, Germany. In contrast to the majority of current experiments, PANDA's strategy for data acquisition is based on event reconstruction from free-streaming data, performed in real time entirely by software algorithms using global detector information. This paper reports the status of the development of algorithms for the reconstruction of charged particle tracks, optimized online data processing applications, using General-Purpose Graphic Processing Units (GPU). Two algorithms for trackfinding, the Triplet Finder and the Circle Hough, are described, and details of their GPU implementations are highlighted. Average track reconstruction times of less than 100 ns are obtained running the Triplet Finder on state-of- the-art GPU cards. In addition, a proof-of-concept system for the dispatch of data to tracking algorithms using Message Queues is presented.
Stochastic optimization of a cold atom experiment using a genetic algorithm
Rohringer, W.; Buecker, R.; Manz, S.; Betz, T.; Koller, Ch.; Goebel, M.; Perrin, A.; Schmiedmayer, J.; Schumm, T.
2008-12-29
We employ an evolutionary algorithm to automatically optimize different stages of a cold atom experiment without human intervention. This approach closes the loop between computer based experimental control systems and automatic real time analysis and can be applied to a wide range of experimental situations. The genetic algorithm quickly and reliably converges to the most performing parameter set independent of the starting population. Especially in many-dimensional or connected parameter spaces, the automatic optimization outperforms a manual search.
A new FOD recognition algorithm based on multi-source information fusion and experiment analysis
NASA Astrophysics Data System (ADS)
Li, Yu; Xiao, Gang
2011-08-01
Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.
Specific yield - laboratory experiments showing the effect of time on column drainage
Prill, Robert C.; Johnson, A.I.; Morris, Donald Arthur
1965-01-01
The increasing use of ground water from many major aquifers in the United States has required a more thorough understanding of gravity drainage, or specific yield. This report describes one phase of specific yield research by the U.S. Geological Survey's Hydrologic Laboratory in cooperation with the California Department of Water Resources. An earlier phase of the research concentrated on the final distribution of moisture retained after drainage of saturated columns of porous media. This report presents the phase that concentrated on the distribution of moisture retained in similar columns after drainage for various periods of time. Five columns, about 4 cm in diameter by 170 cm long, were packed with homogenous sand of very fine, medium, and coarse sizes, and one column was packed with alternating layers of coarse and medium sand. The very fine materials were more uniform in size range than were the medium materials. As the saturated columns drained, tensiometers installed throughout the length recorded changes in moisture tension. The relation of tension to moisture content, determined for each of the materials, was then used to convert the tension readings to moisture content. Data were then available on the distribution of retained moisture for different periods of drainage from 1 to 148 hours. Data also are presented on the final distribution of moisture content by weight and volume and on the degree of saturation. The final zone of capillary saturation was approximately 12 cm for coarse sand, 13 cm for medium sand, and 52 cm for very fine sand. The data showed these zones were 92 to 100 percent saturated. Most of the outflow from the columns occurred in the earlier hours of drainage--90 percent in 1 hour for the coarse materials, 50 percent for the medium, and 60 percent for the very fine. Although the largest percentage of the specific yield was reached during the early hours of .drainage, this study amply demonstrates that a very long time would be
Santamaría, A; Merino, A; Viñas, O; Arrizabalaga, P
2009-02-01
Have invisible barriers for women been broken in 2007, or do we still have to break through medicine's glass ceiling? Data from two of the most prestigious university hospitals in Barcelona with 700-800 beds, Hospital Clínic (HC) and Hospital de la Santa Creu i Sant Pau (HSCSP) address this issue. In the HSCSP, 87% of the department chairs are men and 85% of the department unit chiefs are also men. With respect to women, only 5 (13%) are in the top position (department chair) and 4 (15%) are department unit chiefs. Similar statistics are also found at the HC: 87% of the department chairs and 89% of the department unit chiefs are men. Currently, only 6 women (13%) are in the top position and 6 (11%) are department unit chiefs. Analysis of the 2002 data of internal promotions in HC showed that for the first level (senior specialist) sex distribution was similar. Nevertheless, for the second level (consultant) only 25% were women, and for the top level (senior consultant) only 8% were women. These proportions have not changed in 2007 in spite of a 10% increase in leadership positions during this period. Similar proportions were found in HSCSP where 68% of the top promotions were held by men. The data obtained from these two different medical institutions in Barcelona are probably representative of other hospitals in Spain. It would be ethically desirable to have males and females in leadership positions in the medical profession.
Three Decades of Field Experiments Show Minimal Variability in Maximum Preferential Flow Speed
NASA Astrophysics Data System (ADS)
Nimmo, J. R.
2005-12-01
Evaluation of about 50 published field tests shows that the maximum transport speed in macropores and other preferential channels varies surprisingly little. The tests differ substantially: in type of medium, including fractured rock and various soil textures; in travel distance, ranging from less than 1 to more than 1000 m; in type of tracer; and in vertical or horizontal flow direction. One factor that significantly affects transport speed is the supply of water that generates the flow. Continuous application of water at the land surface, such as ponding or steady irrigation, as opposed to a sporadic supply such as natural rainfall, causes preferential flow that is faster and that varies less among studies. For continuously supplied water, nearly all observations of maximum transport speed fall between 1 and 100 m/d, suggesting that a value in that range could serve as a guideline for expected transport speed under comparable conditions. For sporadically applied water, if transport speeds are adjusted by a factor equal to the fraction of time during which water is applied, the adjusted values also fall in a range of about 1 to 100 m/d. Results suggest that in some common modes of preferential flow, certain mechanisms tend to compensate for factors that would normally cause substantial differences in flow rate. For example, an increase in water content within an unsaturated fracture may not affect the speed of solute transport in thick films if the greater water content is accommodated not by changing film thickness but by covering a larger portion of fracture-wall surface. The generalization that certain transport speeds are predictable to a large extent from water input conditions may improve the reliability and ease of predicting worst-case contaminant travel times and other quantities of hydrologic importance.
Aalaei, Shokoufeh; Shahraki, Hadi; Rowhanimanesh, Alireza; Eslami, Saeid
2016-01-01
Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we employed three different classifiers artificial neural network (ANN) and PS-classifier and genetic algorithm based classifier (GA-classifier) on Wisconsin breast cancer datasets include Wisconsin breast cancer dataset (WBC), Wisconsin diagnosis breast cancer (WDBC), and Wisconsin prognosis breast cancer (WPBC). Results: For WBC dataset, it is observed that feature selection improved the accuracy of all classifiers expect of ANN and the best accuracy with feature selection achieved by PS-classifier. For WDBC and WPBC, results show feature selection improved accuracy of all three classifiers and the best accuracy with feature selection achieved by ANN. Also specificity and sensitivity improved after feature selection. Conclusion: The results show that feature selection can improve accuracy, specificity and sensitivity of classifiers. Result of this study is comparable with the other studies on Wisconsin breast cancer datasets. PMID:27403253
NASA Technical Reports Server (NTRS)
Adams, J. H., Jr.; Andreev, Valeri; Christl, M. J.; Cline, David B.; Crawford, Hank; Judd, E. G.; Pennypacker, Carl; Watts, J. W.
2007-01-01
The JEM-EUSO collaboration intends to study high energy cosmic ray showers using a large downward looking telescope mounted on the Japanese Experiment Module of the International Space Station. The telescope focal plane is instrumented with approx.300k pixels operating as a digital camera, taking snapshots at approx. 1MHz rate. We report an investigation of the trigger and reconstruction efficiency of various algorithms based on time and spatial analysis of the pixel images. Our goal is to develop trigger and reconstruction algorithms that will allow the instrument to detect energies low enough to connect smoothly to ground-based observations.
Vertigo in childhood: proposal for a diagnostic algorithm based upon clinical experience.
Casani, A P; Dallan, I; Navari, E; Sellari Franceschini, S; Cerchiai, N
2015-06-01
The aim of this paper is to analyse, after clinical experience with a series of patients with established diagnoses and review of the literature, all relevant anamnestic features in order to build a simple diagnostic algorithm for vertigo in childhood. This study is a retrospective chart review. A series of 37 children underwent complete clinical and instrumental vestibular examination. Only neurological disorders or genetic diseases represented exclusion criteria. All diagnoses were reviewed after applying the most recent diagnostic guidelines. In our experience, the most common aetiology for dizziness is vestibular migraine (38%), followed by acute labyrinthitis/neuritis (16%) and somatoform vertigo (16%). Benign paroxysmal vertigo was diagnosed in 4 patients (11%) and paroxysmal torticollis was diagnosed in a 1-year-old child. In 8% (3 patients) of cases, the dizziness had a post-traumatic origin: 1 canalolithiasis of the posterior semicircular canal and 2 labyrinthine concussions, respectively. Menière's disease was diagnosed in 2 cases. A bilateral vestibular failure of unknown origin caused chronic dizziness in 1 patient. In conclusion, this algorithm could represent a good tool for guiding clinical suspicion to correct diagnostic assessment in dizzy children where no neurological findings are detectable. The algorithm has just a few simple steps, based mainly on two aspects to be investigated early: temporal features of vertigo and presence of hearing impairment. A different algorithm has been proposed for cases in which a traumatic origin is suspected.
Data Association and Bullet Tracking Algorithms for the Fight Sight Experiment
Breitfeller, E; Roberts, R
2005-10-07
Previous LLNL investigators developed a bullet and projectile tracking system over a decade ago. Renewed interest in the technology has spawned research that culminated in a live-fire experiment, called Fight Sight, in September 2005. The experiment was more complex than previous LLNL bullet tracking experiments in that it included multiple shooters with simultaneous fire, new sensor-shooter geometries, large amounts of optical clutter, and greatly increased sensor-shooter distances. This presentation describes the data association and tracking algorithms for the Fight Sight experiment. Image processing applied to the imagery yields a sequence of bullet features which are input to a data association routine. The data association routine matches features with existing tracks, or initializes new tracks as needed. A Kalman filter is used to smooth and extrapolate existing tracks. The Kalman filter is also used to back-track bullets to their point of origin, thereby revealing the location of the shooter. It also provides an error ellipse for each shooter, quantifying the uncertainty of shooter location. In addition to describing the data association and tracking algorithms, several examples from the Fight Sight experiment are also presented.
Chu, W.P.; Thomason, L.W.; Buglia, J.J.; McCormick, M.P.; McMaster, L.M. ); Chiou, E.W.; Larsen, J.C. ); Rind, D. ); Oltmans, S. )
1993-03-20
This paper provides a detailed description of the current operational inversion algorithm for the retrieval of water vapor vertical profiles from the Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation data at the 0.94-[mu]m wavelength channel. This algorithm is different from the algorithm used for the retrieval of the other species such as aerosol, ozone, and nitrogen dioxide because of the nonlinear relationship between the concentration versus the broad band absorption characteristics of water vapor. Included in the discussion of the retrieval algorithm are problems related to the accuracy of the computational scheme, accuracy of the removal of other interfering species, and the expected uncertainty of the retrieved profile. A comparative analysis on the computational schemes used for the calculation of the water vapor transmission at the 0.94-[mu]m wavelength region is presented. Analyses are also presented on the sensitivity of the retrievals to interferences from the other species which contribute to the total signature as observed at the 0.94-[mu]m wavelength channel on SAGE II instrument. Error analyses of the SAGE II water vapor retrieval is shown, indicating that good quality water vapor data are being produced by the SAGE II measurements. 27 refs., 10 figs., 1 tab.
F-18 SRA closeup of nose cap showing L-Probe experiment and standard air data sensors
NASA Technical Reports Server (NTRS)
1997-01-01
This under-the-nose view of a modified F-18 Systems Research Aircraft at NASA's Dryden Flight Research Center, Edwards, California, shows three critical components of the aircraft's air data systems which are mounted on both sides of the forward fuselage. Furthest forward are two L-probes that were the focus of the recent Advanced L-probe Air Data Integration (ALADIN) experiment. Behind the L-probes are angle-of-attack vanes, while below them are the aircraft's standard pitot-static air data probes. The ALADIN experiment focused on providing pilots with angle-of-attack and angle-of-sideslip air data as well as traditional airspeed and altitude information, all from a single system. Once fully developed, the new L-probes have the potential to give pilots more accurate air data information with less hardware.
Darzi, Soodabeh; Tiong, Sieh Kiong; Tariqul Islam, Mohammad; Rezai Soleymanpour, Hassan; Kibria, Salehin
2016-01-01
An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (α), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents’ positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness. PMID:27399904
Darzi, Soodabeh; Tiong, Sieh Kiong; Tariqul Islam, Mohammad; Rezai Soleymanpour, Hassan; Kibria, Salehin
2016-01-01
An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (α), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents' positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness. PMID:27399904
Blümel, Marcus; Guschlbauer, Christoph; Daun-Gruhn, Silvia; Hooper, Scott L; Büschges, Ansgar
2012-11-01
Models built using mean data can represent only a very small percentage, or none, of the population being modeled, and produce different activity than any member of it. Overcoming this "averaging" pitfall requires measuring, in single individuals in single experiments, all of the system's defining characteristics. We have developed protocols that allow all the parameters in the curves used in typical Hill-type models (passive and active force-length, series elasticity, force-activation, force-velocity) to be determined from experiments on individual stick insect muscles (Blümel et al. 2012a). A requirement for means to not well represent the population is that the population shows large variation in its defining characteristics. We therefore used these protocols to measure extensor muscle defining parameters in multiple animals. Across-animal variability in these parameters can be very large, ranging from 1.3- to 17-fold. This large variation is consistent with earlier data in which extensor muscle responses to identical motor neuron driving showed large animal-to-animal variability (Hooper et al. 2006), and suggests accurate modeling of extensor muscles requires modeling individual-by-individual. These complete characterizations of individual muscles also allowed us to test for parameter correlations. Two parameter pairs significantly co-varied, suggesting that a simpler model could as well reproduce muscle response.
Analysis of soil moisture extraction algorithm using data from aircraft experiments
NASA Technical Reports Server (NTRS)
Burke, H. H. K.; Ho, J. H.
1981-01-01
A soil moisture extraction algorithm is developed using a statistical parameter inversion method. Data sets from two aircraft experiments are utilized for the test. Multifrequency microwave radiometric data surface temperature, and soil moisture information are contained in the data sets. The surface and near surface ( or = 5 cm) soil moisture content can be extracted with accuracy of approximately 5% to 6% for bare fields and fields with grass cover by using L, C, and X band radiometer data. This technique is used for handling large amounts of remote sensing data from space.
SU-E-T-344: Validation and Clinical Experience of Eclipse Electron Monte Carlo Algorithm (EMC)
Pokharel, S; Rana, S
2014-06-01
Purpose: The purpose of this study is to validate Eclipse Electron Monte Carlo (Algorithm for routine clinical uses. Methods: The PTW inhomogeneity phantom (T40037) with different combination of heterogeneous slabs has been CT-scanned with Philips Brilliance 16 slice scanner. The phantom contains blocks of Rando Alderson materials mimicking lung, Polystyrene (Tissue), PTFE (Bone) and PMAA. The phantom has 30×30×2.5 cm base plate with 2cm recesses to insert inhomogeneity. The detector systems used in this study are diode, tlds and Gafchromic EBT2 films. The diode and tlds were included in CT scans. The CT sets are transferred to Eclipse treatment planning system. Several plans have been created with Eclipse Monte Carlo (EMC) algorithm 11.0.21. Measurements have been carried out in Varian TrueBeam machine for energy from 6–22mev. Results: The measured and calculated doses agreed very well for tissue like media. The agreement was reasonably okay for the presence of lung inhomogeneity. The point dose agreement was within 3.5% and Gamma passing rate at 3%/3mm was greater than 93% except for 6Mev(85%). The disagreement can reach as high as 10% in the presence of bone inhomogeneity. This is due to eclipse reporting dose to the medium as opposed to the dose to the water as in conventional calculation engines. Conclusion: Care must be taken when using Varian Eclipse EMC algorithm for dose calculation for routine clinical uses. The algorithm dose not report dose to water in which most of the clinical experiences are based on rather it just reports dose to medium directly. In the presence of inhomogeneity such as bone, the dose discrepancy can be as high as 10% or even more depending on the location of normalization point or volume. As Radiation oncology as an empirical science, care must be taken before using EMC reported monitor units for clinical uses.
Lapham, Laura L; Wilson, Rachel M; Chanton, Jeffrey P
2012-01-15
The stable carbon isotopic ratio of methane (δ(13)C-CH(4)) recovered from marine sediments containing gas hydrate is often used to infer the gas source and associated microbial processes. This is a powerful approach because of distinct isotopic fractionation patterns associated with methane production by biogenic and thermogenic pathways and microbial oxidation. However, isotope fractionations due to physical processes, such as hydrate dissolution, have not been fully evaluated. We have conducted experiments to determine if hydrate dissolution or dissociation (two distinct physical processes) results in isotopic fractionation. In a pressure chamber, hydrate was formed from a methane gas source at 2.5 MPa and 4 °C, well within the hydrate stability field. Following formation, the methane source was removed while maintaining the hydrate at the same pressure and temperature which stimulated hydrate dissolution. Over the duration of two dissolution experiments (each ~20-30 days), water and headspace samples were periodically collected and measured for methane concentrations and δ(13)C-CH(4) while the hydrate dissolved. For both experiments, the methane concentrations in the pressure chamber water and headspace increased over time, indicating that the hydrate was dissolving, but the δ(13)C-CH(4) values showed no significant trend and remained constant, within 0.5‰. This lack of isotope change over time indicates that there is no fractionation during hydrate dissolution. We also investigated previous findings that little isotopic fractionation occurs when the gas hydrate dissociates into gas bubbles and water due to the release of pressure. Over a 2.5 MPa pressure drop, the difference in the δ(13)C-CH(4) was <0.3‰. We have therefore confirmed that there is no isotope fractionation when the gas hydrate dissociates and demonstrated that there is no fractionation when the hydrate dissolves. Therefore, measured δ(13)C-CH(4) values near gas hydrates are not affected
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.
Sorting algorithms for single-particle imaging experiments at X-ray free-electron lasers.
Bobkov, S A; Teslyuk, A B; Kurta, R P; Gorobtsov, O Yu; Yefanov, O M; Ilyin, V A; Senin, R A; Vartanyants, I A
2015-11-01
Modern X-ray free-electron lasers (XFELs) operating at high repetition rates produce a tremendous amount of data. It is a great challenge to classify this information and reduce the initial data set to a manageable size for further analysis. Here an approach for classification of diffraction patterns measured in prototypical diffract-and-destroy single-particle imaging experiments at XFELs is presented. It is proposed that the data are classified on the basis of a set of parameters that take into account the underlying diffraction physics and specific relations between the real-space structure of a particle and its reciprocal-space intensity distribution. The approach is demonstrated by applying principal component analysis and support vector machine algorithms to the simulated and measured X-ray data sets.
Zimmerman, K; Levitis, D; Addicott, E; Pringle, A
2016-02-01
We present a novel algorithm for the design of crossing experiments. The algorithm identifies a set of individuals (a 'crossing-set') from a larger pool of potential crossing-sets by maximizing the diversity of traits of interest, for example, maximizing the range of genetic and geographic distances between individuals included in the crossing-set. To calculate diversity, we use the mean nearest neighbor distance of crosses plotted in trait space. We implement our algorithm on a real dataset of Neurospora crassa strains, using the genetic and geographic distances between potential crosses as a two-dimensional trait space. In simulated mating experiments, crossing-sets selected by our algorithm provide better estimates of underlying parameter values than randomly chosen crossing-sets.
NASA Astrophysics Data System (ADS)
Li, Liang; Chen, Zhiqiang; Zhao, Ziran; Wu, Dufan
2013-01-01
At present, there are mainly three x-ray imaging modalities for dental clinical diagnosis: radiography, panorama and computed tomography (CT). We develop a new x-ray digital intra-oral tomosynthesis (IDT) system for quasi-three-dimensional dental imaging which can be seen as an intermediate modality between traditional radiography and CT. In addition to normal x-ray tube and digital sensor used in intra-oral radiography, IDT has a specially designed mechanical device to complete the tomosynthesis data acquisition. During the scanning, the measurement geometry is such that the sensor is stationary inside the patient's mouth and the x-ray tube moves along an arc trajectory with respect to the intra-oral sensor. Therefore, the projection geometry can be obtained without any other reference objects, which makes it be easily accepted in clinical applications. We also present a compressed sensing-based iterative reconstruction algorithm for this kind of intra-oral tomosynthesis. Finally, simulation and experiment were both carried out to evaluate this intra-oral imaging modality and algorithm. The results show that IDT has its potentiality to become a new tool for dental clinical diagnosis.
Level 3 trigger algorithm and Hardware Platform for the HADES experiment
NASA Astrophysics Data System (ADS)
Kirschner, Daniel Georg; Agakishiev, Geydar; Liu, Ming; Perez, Tiago; Kühn, Wolfgang; Pechenov, Vladimir; Spataro, Stefano
2009-01-01
A next generation real time trigger method to improve the enrichment of lepton events in the High Acceptance DiElectron Spectrometer (HADES) trigger system has been developed. In addition, a flexible Hardware Platform (Gigabit Ethernet-Multi-Node, GE-MN) was developed to implement and test the trigger method. The trigger method correlates the ring information of the HADES Ring Imaging Cherenkov (RICH) detector with the fired wires (drift cells) of the HADES Mini Drift Chamber (MDC) detector. It is demonstrated that this Level 3 trigger method can enhance the number of events which contain leptons by a factor of up to 50 at efficiencies above 80%. The performance of the correlation method in terms of the events analyzed per second has been studied with the GE-MN prototype in a lab test setup by streaming previously recorded experiment data to the module. This paper is a compilation from Kirschner [Level 3 trigger algorithm and Hardware Platform for the HADES experiment, Ph.D. Thesis, II. Physikalisches Institut der Justus-Liebig-Universität Gießen, urn:nbn:de:hebis:26-opus-50784, October 2007 [1
Munkácsy, Gyöngyi; Sztupinszki, Zsófia; Herman, Péter; Bán, Bence; Pénzváltó, Zsófia; Szarvas, Nóra; Győrffy, Balázs
2016-01-01
No independent cross-validation of success rate for studies utilizing small interfering RNA (siRNA) for gene silencing has been completed before. To assess the influence of experimental parameters like cell line, transfection technique, validation method, and type of control, we have to validate these in a large set of studies. We utilized gene chip data published for siRNA experiments to assess success rate and to compare methods used in these experiments. We searched NCBI GEO for samples with whole transcriptome analysis before and after gene silencing and evaluated the efficiency for the target and off-target genes using the array-based expression data. Wilcoxon signed-rank test was used to assess silencing efficacy and Kruskal–Wallis tests and Spearman rank correlation were used to evaluate study parameters. All together 1,643 samples representing 429 experiments published in 207 studies were evaluated. The fold change (FC) of down-regulation of the target gene was above 0.7 in 18.5% and was above 0.5 in 38.7% of experiments. Silencing efficiency was lowest in MCF7 and highest in SW480 cells (FC = 0.59 and FC = 0.30, respectively, P = 9.3E−06). Studies utilizing Western blot for validation performed better than those with quantitative polymerase chain reaction (qPCR) or microarray (FC = 0.43, FC = 0.47, and FC = 0.55, respectively, P = 2.8E−04). There was no correlation between type of control, transfection method, publication year, and silencing efficiency. Although gene silencing is a robust feature successfully cross-validated in the majority of experiments, efficiency remained insufficient in a significant proportion of studies. Selection of cell line model and validation method had the highest influence on silencing proficiency. PMID:27673562
Munkácsy, Gyöngyi; Sztupinszki, Zsófia; Herman, Péter; Bán, Bence; Pénzváltó, Zsófia; Szarvas, Nóra; Győrffy, Balázs
2016-01-01
No independent cross-validation of success rate for studies utilizing small interfering RNA (siRNA) for gene silencing has been completed before. To assess the influence of experimental parameters like cell line, transfection technique, validation method, and type of control, we have to validate these in a large set of studies. We utilized gene chip data published for siRNA experiments to assess success rate and to compare methods used in these experiments. We searched NCBI GEO for samples with whole transcriptome analysis before and after gene silencing and evaluated the efficiency for the target and off-target genes using the array-based expression data. Wilcoxon signed-rank test was used to assess silencing efficacy and Kruskal-Wallis tests and Spearman rank correlation were used to evaluate study parameters. All together 1,643 samples representing 429 experiments published in 207 studies were evaluated. The fold change (FC) of down-regulation of the target gene was above 0.7 in 18.5% and was above 0.5 in 38.7% of experiments. Silencing efficiency was lowest in MCF7 and highest in SW480 cells (FC = 0.59 and FC = 0.30, respectively, P = 9.3E-06). Studies utilizing Western blot for validation performed better than those with quantitative polymerase chain reaction (qPCR) or microarray (FC = 0.43, FC = 0.47, and FC = 0.55, respectively, P = 2.8E-04). There was no correlation between type of control, transfection method, publication year, and silencing efficiency. Although gene silencing is a robust feature successfully cross-validated in the majority of experiments, efficiency remained insufficient in a significant proportion of studies. Selection of cell line model and validation method had the highest influence on silencing proficiency. PMID:27673562
Deriving rules from activity diary data: A learning algorithm and results of computer experiments
NASA Astrophysics Data System (ADS)
Arentze, Theo A.; Hofman, Frank; Timmermans, Harry J. P.
Activity-based models consider travel as a derived demand from the activities households need to conduct in space and time. Over the last 15 years, computational or rule-based models of activity scheduling have gained increasing interest in time-geography and transportation research. This paper argues that a lack of techniques for deriving rules from empirical data hinders the further development of rule-based systems in this area. To overcome this problem, this paper develops and tests an algorithm for inductively deriving rules from activity-diary data. The decision table formalism is used to exhaustively represent the theoretically possible decision rules that individuals may use in sequencing a given set of activities. Actual activity patterns of individuals are supplied to the system as examples. In an incremental learning process, the system progressively improves on the selection of rules used for reproducing the examples. Computer experiments based on simulated data are performed to fine-tune rule selection and rule value update functions. The results suggest that the system is effective and fairly robust for parameter settings. It is concluded, therefore, that the proposed approach opens up possibilities to derive empirically tested rule-based models of activity scheduling. Follow-up research will be concerned with testing the system on empirical data.
Performance of the reconstruction algorithms of the FIRST experiment pixel sensors vertex detector
NASA Astrophysics Data System (ADS)
Rescigno, R.; Finck, Ch.; Juliani, D.; Spiriti, E.; Baudot, J.; Abou-Haidar, Z.; Agodi, C.; Alvarez, M. A. G.; Aumann, T.; Battistoni, G.; Bocci, A.; Böhlen, T. T.; Boudard, A.; Brunetti, A.; Carpinelli, M.; Cirrone, G. A. P.; Cortes-Giraldo, M. A.; Cuttone, G.; De Napoli, M.; Durante, M.; Gallardo, M. I.; Golosio, B.; Iarocci, E.; Iazzi, F.; Ickert, G.; Introzzi, R.; Krimmer, J.; Kurz, N.; Labalme, M.; Leifels, Y.; Le Fevre, A.; Leray, S.; Marchetto, F.; Monaco, V.; Morone, M. C.; Oliva, P.; Paoloni, A.; Patera, V.; Piersanti, L.; Pleskac, R.; Quesada, J. M.; Randazzo, N.; Romano, F.; Rossi, D.; Rousseau, M.; Sacchi, R.; Sala, P.; Sarti, A.; Scheidenberger, C.; Schuy, C.; Sciubba, A.; Sfienti, C.; Simon, H.; Sipala, V.; Tropea, S.; Vanstalle, M.; Younis, H.
2014-12-01
Hadrontherapy treatments use charged particles (e.g. protons and carbon ions) to treat tumors. During a therapeutic treatment with carbon ions, the beam undergoes nuclear fragmentation processes giving rise to significant yields of secondary charged particles. An accurate prediction of these production rates is necessary to estimate precisely the dose deposited into the tumours and the surrounding healthy tissues. Nowadays, a limited set of double differential carbon fragmentation cross-section is available. Experimental data are necessary to benchmark Monte Carlo simulations for their use in hadrontherapy. The purpose of the FIRST experiment is to study nuclear fragmentation processes of ions with kinetic energy in the range from 100 to 1000 MeV/u. Tracks are reconstructed using information from a pixel silicon detector based on the CMOS technology. The performances achieved using this device for hadrontherapy purpose are discussed. For each reconstruction step (clustering, tracking and vertexing), different methods are implemented. The algorithm performances and the accuracy on reconstructed observables are evaluated on the basis of simulated and experimental data.
Tracking at CDF: algorithms and experience from Run I and Run II
Snider, F.D.; /Fermilab
2005-10-01
The authors describe the tracking algorithms used during Run I and Run II by CDF at the Fermilab Tevatron Collider, covering the time from about 1992 through the present, and discuss the performance of the algorithms at high luminosity. By tracing the evolution of the detectors and algorithms, they reveal some of the successful strategies used by CDF to address the problems of tracking at high luminosities.
Thermal weapon sights with integrated fire control computers: algorithms and experiences
NASA Astrophysics Data System (ADS)
Rothe, Hendrik; Graswald, Markus; Breiter, Rainer
2008-04-01
The HuntIR long range thermal weapon sight of AIM is deployed in various out of area missions since 2004 as a part of the German Future Infantryman system (IdZ). In 2007 AIM fielded RangIR as upgrade with integrated laser Range finder (LRF), digital magnetic compass (DMC) and fire control unit (FCU). RangIR fills the capability gaps of day/night fire control for grenade machine guns (GMG) and the enhanced system of the IdZ. Due to proven expertise and proprietary methods in fire control, fast access to military trials for optimisation loops and similar hardware platforms, AIM and the University of the Federal Armed Forces Hamburg (HSU) decided to team for the development of suitable fire control algorithms. The pronounced ballistic trajectory of the 40mm GMG requires most accurate FCU-solutions specifically for air burst ammunition (ABM) and is most sensitive to faint effects like levelling or firing up/downhill. This weapon was therefore selected to validate the quality of the FCU hard- and software under relevant military conditions. For exterior ballistics the modified point mass model according to STANAG 4355 is used. The differential equations of motions are solved numerically, the two point boundary value problem is solved iteratively. Computing time varies according to the precision needed and is typical in the range from 0.1 - 0.5 seconds. RangIR provided outstanding hit accuracy including ABM fuze timing in various trials of the German Army and allied partners in 2007 and is now ready for series production. This paper deals mainly with the fundamentals of the fire control algorithms and shows how to implement them in combination with any DSP-equipped thermal weapon sights (TWS) in a variety of light supporting weapon systems.
NASA Astrophysics Data System (ADS)
Matthews, James; Wright, Matthew; Bacak, Asan; Silva, Hugo; Priestley, Michael; Martin, Damien; Percival, Carl; Shallcross, Dudley
2016-04-01
Cyclic perfluorocarbons (PFCs) have been used to measure the passage of air in urban and rural settings as they are chemically inert, non-toxic and have low background concentrations. The use of pre-concentrators and chemical ionisation gas chromatography enables concentrations of a few parts per quadrillion (ppq) to be measured in bag samples. Three PFC tracers were used in Manchester, UK in the summer of 2015 to map airflow in the city and ingress into buildings: perfluomethylcyclohexane (PMCH), perfluoro-2-4-dimethylcyclohexane (mPDMCH) and perfluoro-2-methyl-3-ethylpentene (PMEP). A known quantity of each PFC was released for 15 minutes from steel canisters using pre-prepared PFC mixtures. Release points were chosen to be upwind of the central sampling location (Simon Building, University of Manchester) and varied in distance up to 2.2 km. Six releases using one or three tracers in different configurations and under different conditions were undertaken in the summer. Three further experiments were conducted in the Autumn, to more closely investigate the rate of ingress and decay of tracer indoors. In each experiment, 10 litre samples were made over 30 minutes into Tedlar bags, starting at the same time the as PFC release. Samples were taken in 11 locations chosen from 15 identified areas including three in public parks, three outside within the University of Manchester area, seven inside and five outside of the Simon building and two outside a building nearby. For building measurements, receptors were placed inside the buildings on different floors; outside measurements were achieved through a sample line out of the window. Three of the sample positions inside the Simon building were paired with samplers outside to allow indoor-outdoor comparisons. PFC concentrations varied depending on location and height. The highest measured concentrations occurred when the tracer was released at sunrise; up to 330 ppq above background (11 ppq) of PMCH was measured at the 6
NASA Astrophysics Data System (ADS)
Domínguez-Rué, Emma; Mrotzek, Maximilian
2014-01-01
Previous research has shown that using tools from systems science for teaching and learning in the Humanities offers innovative insights that can prove helpful for both students and lecturers. Our contention here is that a method used in systems science, namely the influence matrix, can be a suitable tool to facilitate the understanding of elementary notions in Aesthetics by means of systematizing this process. As we will demonstrate in the upcoming sections, the influence matrix can help us to understand the nature and function of the basic elements that take part in the aesthetic experience and their evolving relevance in the history of Aesthetics. The implementation of these elements to an influence matrix will contribute to a more detailed understanding of (i) the nature of each element, (ii) the interrelation between them and (iii) the influence each element has on all the others.
An Object-Oriented Collection of Minimum Degree Algorithms: Design, Implementation, and Experiences
NASA Technical Reports Server (NTRS)
Kumfert, Gary; Pothen, Alex
1999-01-01
The multiple minimum degree (MMD) algorithm and its variants have enjoyed 20+ years of research and progress in generating fill-reducing orderings for sparse, symmetric positive definite matrices. Although conceptually simple, efficient implementations of these algorithms are deceptively complex and highly specialized. In this case study, we present an object-oriented library that implements several recent minimum degree-like algorithms. We discuss how object-oriented design forces us to decompose these algorithms in a different manner than earlier codes and demonstrate how this impacts the flexibility and efficiency of our C++ implementation. We compare the performance of our code against other implementations in C or Fortran.
Malykh, A B; Iakovlev, S V; Valevskiĭ, V V
2014-03-01
Authors showed data about medical backup of military personnel taking part in the parade on Red Square dedicating to anniversary of Victory in the Great Patriotic War. Experience of running such events allowed to work out an algorithm for medical service: preparatory stage, training stage, running of parade, stage of move out to permanent base. During the parade on Red Square for medical care asked 18 people (participants of parade and civilians). Authors came to conclusion that as a result of medical backup of military personnel taking part in the parade no infectious and group diseases were registered.
NASA Astrophysics Data System (ADS)
Cetinić, I.; Perry, M. J.; D'Asaro, E.; Briggs, N.; Poulton, N.; Sieracki, M. E.; Lee, C. M.
2015-04-01
The ratio of two in situ optical measurements - chlorophyll fluorescence (Chl F) and optical particulate backscattering (bbp) - varied with changes in phytoplankton community composition during the North Atlantic Bloom Experiment in the Iceland Basin in 2008. Using ship-based measurements of Chl F, bbp, chlorophyll a (Chl), high-performance liquid chromatography (HPLC) pigments, phytoplankton composition and carbon biomass, we found that oscillations in the ratio varied with changes in plankton community composition; hence we refer to Chl F/bbp as an "optical community index". The index varied by more than a factor of 2, with low values associated with pico- and nanophytoplankton and high values associated with diatom-dominated phytoplankton communities. Observed changes in the optical index were driven by taxa-specific chlorophyll-to-autotrophic carbon ratios and by physiological changes in Chl F associated with the silica limitation. A Lagrangian mixed-layer float and four Seagliders, operating continuously for 2 months, made similar measurements of the optical community index and followed the evolution and later demise of the diatom spring bloom. Temporal changes in optical community index and, by implication, the transition in community composition from diatom to post-diatom bloom communities were not simultaneous over the spatial domain surveyed by the ship, float and gliders. The ratio of simple optical properties measured from autonomous platforms, when carefully validated, provides a unique tool for studying phytoplankton patchiness on extended temporal scales and ecologically relevant spatial scales and should offer new insights into the processes regulating patchiness.
Finnerty, P.; Aguayo, Estanislao; Amman, M.; Avignone, Frank T.; Barabash, Alexander S.; Barton, P. J.; Beene, Jim; Bertrand, F.; Boswell, M.; Brudanin, V.; Busch, Matthew; Chan, Yuen-Dat; Christofferson, Cabot-Ann; Collar, J. I.; Combs, Dustin C.; Cooper, R. J.; Detwiler, Jason A.; Doe, P. J.; Efremenko, Yuri; Egorov, Viatcheslav; Ejiri, H.; Elliott, S. R.; Esterline, James H.; Fast, James E.; Fields, N.; Fraenkle, Florian; Galindo-Uribarri, A.; Gehman, Victor M.; Giovanetti, G. K.; Green, M.; Guiseppe, Vincente; Gusey, K.; Hallin, A. L.; Hazama, R.; Henning, Reyco; Hoppe, Eric W.; Horton, Mark; Howard, Stanley; Howe, M. A.; Johnson, R. A.; Keeter, K.; Kidd, M. F.; Knecht, A.; Kochetov, Oleg; Konovalov, S.; Kouzes, Richard T.; LaFerriere, Brian D.; Leon, Jonathan D.; Leviner, L.; Loach, J. C.; Looker, Q.; Luke, P.; MacMullin, S.; Marino, Michael G.; Martin, R. D.; Merriman, Jason H.; Miller, M. L.; Mizouni, Leila; Nomachi, Masaharu; Orrell, John L.; Overman, Nicole R.; Perumpilly, Gopakumar; Phillips, David; Poon, Alan; Radford, D. C.; Rielage, Keith; Robertson, R. G. H.; Ronquest, M. C.; Schubert, Alexis G.; Shima, T.; Shirchenko, M.; Snavely, Kyle J.; Steele, David; Strain, J.; Timkin, V.; Tornow, Werner; Varner, R. L.; Vetter, Kai; Vorren, Kris R.; Wilkerson, J. F.; Yakushev, E.; Yaver, Harold; Young, A.; Yu, Chang-Hong; Yumatov, Vladimir
2014-03-24
The Majorana Demonstrator will search for the neutrinoless double-beta decay (0*) of the 76Ge isotope with a mixed array of enriched and natural germanium detectors. The observation of this rare decay would indicate the neutrino is its own anti-particle, demonstrate that lepton number is not conserved, and provide information on the absolute mass-scale of the neutrino. The Demonstrator is being assembled at the 4850 foot level of the Sanford Underground Research Facility in Lead, South Dakota. The array will be contained in a lowbackground environment and surrounded by passive and active shielding. The goals for the Demonstrator are: demonstrating a background rate less than 3 counts tonne -1 year-1 in the 4 keV region of interest (ROI) surrounding the 2039 keV 76Ge endpoint energy; establishing the technology required to build a tonne-scale germanium based double-beta decay experiment; testing the recent claim of observation of 0; and performing a direct search for lightWIMPs (3-10 GeV/c2).
NASA Astrophysics Data System (ADS)
Klaessens, John H. G. M.; Hopman, Jeroen C. W.; Liem, K. Djien; de Roode, Rowland; Verdaasdonk, Rudolf M.; Thijssen, Johan M.
2008-02-01
Continuous wave Near Infrared Spectroscopy is a well known non invasive technique for measuring changes in tissue oxygenation. Absorption changes (ΔO2Hb and ΔHHb) are calculated from the light attenuations using the modified Lambert Beer equation. Generally, the concentration changes are calculated relative to the concentration at a starting point in time (delta time method). It is also possible, under certain assumptions, to calculate the concentrations by subtracting the equations at different wavelengths (delta wavelength method). We derived a new algorithm and will show the possibilities and limitations. In the delta wavelength method, the assumption is that the oxygen independent attenuation term will be eliminated from the formula even if its value changes in time, we verified the results with the classical delta time method using extinction coefficients from different literature sources for the wavelengths 767nm, 850nm and 905nm. The different methods of calculating concentration changes were applied to the data collected from animal experiments. The animals (lambs) were in a stable normoxic condition; stepwise they were made hypoxic and thereafter they returned to normoxic condition. The two algorithms were also applied for measuring two dimensional blood oxygen saturation changes in human skin tissue. The different oxygen saturation levels were induced by alterations in the respiration and by temporary arm clamping. The new delta wavelength method yielded in a steady state measurement the same changes in oxy and deoxy hemoglobin as the classical delta time method. The advantage of the new method is the independence of eventual variation of the oxygen independent attenuations in time.
NASA Technical Reports Server (NTRS)
Hancock, G. D.; Waite, W. P.
1984-01-01
Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil.
Parallel algorithms for unconstrained optimizations by multisplitting
He, Qing
1994-12-31
In this paper a new parallel iterative algorithm for unconstrained optimization using the idea of multisplitting is proposed. This algorithm uses the existing sequential algorithms without any parallelization. Some convergence and numerical results for this algorithm are presented. The experiments are performed on an Intel iPSC/860 Hyper Cube with 64 nodes. It is interesting that the sequential implementation on one node shows that if the problem is split properly, the algorithm converges much faster than one without splitting.
Lage-Castellanos, Agustin; Nieto, Juan I; Quiñones, Ileana; Martinez-Montes, Eduardo
2010-01-01
This paper proposes a machine learning based approach to discriminate between EEG single trials of two experimental conditions in a face recognition experiment. The algorithm works using a single-trial EEG database of multiple subjects and thus does not require subject-specific training data. This approach supports the idea that zero-training classification and on-line detection Brain Computer Interface (BCI) systems are areas with a significant amount of potential.
Experiences with serial and parallel algorithms for channel routing using simulated annealing
NASA Technical Reports Server (NTRS)
Brouwer, Randall Jay
1988-01-01
Two algorithms for channel routing using simulated annealing are presented. Simulated annealing is an optimization methodology which allows the solution process to back up out of local minima that may be encountered by inappropriate selections. By properly controlling the annealing process, it is very likely that the optimal solution to an NP-complete problem such as channel routing may be found. The algorithm presented proposes very relaxed restrictions on the types of allowable transformations, including overlapping nets. By freeing that restriction and controlling overlap situations with an appropriate cost function, the algorithm becomes very flexible and can be applied to many extensions of channel routing. The selection of the transformation utilizes a number of heuristics, still retaining the pseudorandom nature of simulated annealing. The algorithm was implemented as a serial program for a workstation, and a parallel program designed for a hypercube computer. The details of the serial implementation are presented, including many of the heuristics used and some of the resulting solutions.
ERIC Educational Resources Information Center
Beddard, Godfrey S.
2011-01-01
Thermodynamic quantities such as the average energy, heat capacity, and entropy are calculated using a Monte Carlo method based on the Metropolis algorithm. This method is illustrated with reference to the harmonic oscillator but is particularly useful when the partition function cannot be evaluated; an example using a one-dimensional spin system…
NASA Technical Reports Server (NTRS)
Emmitt, G. D.; Wood, S. A.; Morris, M.
1990-01-01
Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.
NASA Astrophysics Data System (ADS)
Garmendia, Iñaki; Anglada, Eva
2016-05-01
Genetic algorithms have been used for matching temperature values generated using thermal mathematical models against actual temperatures measured in thermal testing of spacecrafts and space instruments. Up to now, results for small models have been very encouraging. This work will examine the correlation of a small-medium size model, whose thermal test results were available, by means of genetic algorithms. The thermal mathematical model reviewed herein corresponds to Tribolab, a materials experiment deployed on board the International Space Station and subjected to preflight thermal testing. This paper will also discuss in great detail the influence of both the number of reference temperatures available and the number of thermal parameters included in the correlation, taking into account the presence of heat sources and the maximum range of temperature mismatch. Conclusions and recommendations for the thermal test design will be provided, as well as some indications for future improvements.
Pre-Mrna Introns as a Model for Cryptographic Algorithm:. Theory and Experiments
NASA Astrophysics Data System (ADS)
Regoli, Massimo
2010-01-01
The RNA-Crypto System (shortly RCS) is a symmetric key algorithm to cipher data. The idea for this new algorithm starts from the observation of nature. In particular from the observation of RNA behavior and some of its properties. In particular the RNA sequences have some sections called Introns. Introns, derived from the term "intragenic regions", are non-coding sections of precursor mRNA (pre-mRNA) or other RNAs, that are removed (spliced out of the RNA) before the mature RNA is formed. Once the introns have been spliced out of a pre-mRNA, the resulting mRNA sequence is ready to be translated into a protein. The corresponding parts of a gene are known as introns as well. The nature and the role of Introns in the pre-mRNA is not clear and it is under ponderous researches by Biologists but, in our case, we will use the presence of Introns in the RNA-Crypto System output as a strong method to add chaotic non coding information and an unnecessary behaviour in the access to the secret key to code the messages. In the RNA-Crypto System algorithm the introns are sections of the ciphered message with non-coding information as well as in the precursor mRNA.
ERIC Educational Resources Information Center
Gehring, John
2004-01-01
For the past 16 years, the blue-collar city of Huntington, West Virginia, has rolled out the red carpet to welcome young wrestlers and their families as old friends. They have come to town chasing the same dream for a spot in what many of them call "The Show". For three days, under the lights of an arena packed with 5,000 fans, the state's best…
NASA Technical Reports Server (NTRS)
Carter, Richard G.
1989-01-01
For optimization problems associated with engineering design, parameter estimation, image reconstruction, and other optimization/simulation applications, low accuracy function and gradient values are frequently much less expensive to obtain than high accuracy values. Here, researchers investigate the computational performance of trust region methods for nonlinear optimization when high accuracy evaluations are unavailable or prohibitively expensive, and confirm earlier theoretical predictions when the algorithm is convergent even with relative gradient errors of 0.5 or more. The proper choice of the amount of accuracy to use in function and gradient evaluations can result in orders-of-magnitude savings in computational cost.
NASA Astrophysics Data System (ADS)
Myrcha, Julian; Rokita, Przemysław
2015-09-01
Visual data stereoscopic 3D reconstruction is an important challenge in the LHC ALICE detector experiment. Stereoscopic visualization of 3D data is also an important subject of photonics in general. In this paper we have proposed several solutions enabling effective perception based stereoscopic visualization of data provided by detectors in high energy physics experiments.
NASA Astrophysics Data System (ADS)
Peeling, S. M.
1985-12-01
It is demonstrated that the ZIP algorithm is capable of perfect alignment of annotated and unannotated speech files in the majority of cases, even when the files are from different speakers. It can therefore form the basis of an automatic annotation system. It is unlikely that ZIP can completely remove the need for human inspection. However, in cases where misalignment occurs it frequently only affects a small portion of the two files so that a minimal amount of human correction is required. Experiments suggest that a reduced representation of two channels is adequate. For the particular 2 channel representation used, a beamwidth of 200 and deletion penalties of 15 are suitable parameters. By calculating the sum of the differences between the minimum scores in consecutive windows, and averaging this sum over the whole file it is possible to automatically determine the quality of the alignment.
Fernandes, Edite M. G. P.
2015-01-01
This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as ‘erf’, is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. PMID:25875591
NASA Astrophysics Data System (ADS)
schipper, peter; stuyt, lodewijk; straat, van der, andre; schans, van der, martin
2014-05-01
processes in the soil have been modelled with simulation model SWAP. The experiment started in 2010 and is ongoing. Data, collected so far show that the plots with controlled drainage (all compared with plots equipped with conventional drainage) conserve more rain water (higher groundwater tables in early spring), lower discharges under average weather conditions and storm events, reduce N-loads and saline seepage to surface waters, enhance denitrification, show a different 'first flush' effect and show similar crop yields. The results of the experiments will contribute to a better understanding of the impact of controlled drainage on complex hydrological en geochemical processes in agricultural clay soils, the interaction between ground- en surface water and its effects on drain water quantity, quality and crop yield.
Hybrid-PIC Algorithms for Simulation of Merging Plasma Jets in the Plasma Liner Experiment
NASA Astrophysics Data System (ADS)
Thoma, Carsten; Welch, Dale; Clark, Robert; Macfarlane, Joseph; Golovkin, Igor; Witherspoon, F. Douglas
2010-11-01
In the upcoming Plasma Liner Experiment (PLX) at Los Alamos National Laboratory a spherical array of 30-60 jets generated by plasma guns will be merged to form imploding plasma liners. We describe the Hybrid particle-in-cell (PIC) methods implemented in the code LSP for plasma jet simulation and present results of simulations of merging Ar jets. Electron macroparticles are treated as fluid elements which carry an intrinsic temperature while ion macroparticles are treated kinetically. The effective charge state is obtained from EOS tables as a function of the local plasma parameters under the assumption of local thermodynamic equilibrium (LTE). The effect of radiation cooling on the electrons is also included self-consistently into the Hybrid PIC formalism. The LSP results of jet merging simulations will be post-processed using the SPECT3D code to generate simulated radiation flux levels, spectra and images (MacFarlane et al., this meeting).
On the Juno radio science experiment: models, algorithms and sensitivity analysis
NASA Astrophysics Data System (ADS)
Tommei, G.; Dimare, L.; Serra, D.; Milani, A.
2015-01-01
Juno is a NASA mission launched in 2011 with the goal of studying Jupiter. The probe will arrive to the planet in 2016 and will be placed for one year in a polar high-eccentric orbit to study the composition of the planet, the gravity and the magnetic field. The Italian Space Agency (ASI) provided the radio science instrument KaT (Ka-Band Translator) used for the gravity experiment, which has the goal of studying the Jupiter's deep structure by mapping the planet's gravity: such instrument takes advantage of synergies with a similar tool in development for BepiColombo, the ESA cornerstone mission to Mercury. The Celestial Mechanics Group of the University of Pisa, being part of the Juno Italian team, is developing an orbit determination and parameters estimation software for processing the real data independently from NASA software ODP. This paper has a twofold goal: first, to tell about the development of this software highlighting the models used, secondly, to perform a sensitivity analysis on the parameters of interest to the mission.
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
Parallelized dilate algorithm for remote sensing image.
Zhang, Suli; Hu, Haoran; Pan, Xin
2014-01-01
As an important algorithm, dilate algorithm can give us more connective view of a remote sensing image which has broken lines or objects. However, with the technological progress of satellite sensor, the resolution of remote sensing image has been increasing and its data quantities become very large. This would lead to the decrease of algorithm running speed or cannot obtain a result in limited memory or time. To solve this problem, our research proposed a parallelized dilate algorithm for remote sensing Image based on MPI and MP. Experiments show that our method runs faster than traditional single-process algorithm.
Spaceborne SAR Imaging Algorithm for Coherence Optimized.
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446
Spaceborne SAR Imaging Algorithm for Coherence Optimized.
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.
Spaceborne SAR Imaging Algorithm for Coherence Optimized
Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun
2016-01-01
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446
NASA Astrophysics Data System (ADS)
Arpinar, V. E.; Hamamura, M. J.; Degirmenci, E.; Muftuler, L. T.
2012-07-01
Magnetic resonance electrical impedance tomography (MREIT) is a technique that produces images of conductivity in tissues and phantoms. In this technique, electrical currents are applied to an object and the resulting magnetic flux density is measured using magnetic resonance imaging (MRI) and the conductivity distribution is reconstructed using these MRI data. Currently, the technique is used in research environments, primarily studying phantoms and animals. In order to translate MREIT to clinical applications, strict safety standards need to be established, especially for safe current limits. However, there are currently no standards for safe current limits specific to MREIT. Until such standards are established, human MREIT applications need to conform to existing electrical safety standards in medical instrumentation, such as IEC601. This protocol limits patient auxiliary currents to 100 µA for low frequencies. However, published MREIT studies have utilized currents 10-400 times larger than this limit, bringing into question whether the clinical applications of MREIT are attainable under current standards. In this study, we investigated the feasibility of MREIT to accurately reconstruct the relative conductivity of a simple agarose phantom using 200 µA total injected current and tested the performance of two MREIT reconstruction algorithms. These reconstruction algorithms used are the iterative sensitivity matrix method (SMM) by Ider and Birgul (1998 Elektrik 6 215-25) with Tikhonov regularization and the harmonic BZ proposed by Oh et al (2003 Magn. Reason. Med. 50 875-8). The reconstruction techniques were tested at both 200 µA and 5 mA injected currents to investigate their noise sensitivity at low and high current conditions. It should be noted that 200 µA total injected current into a cylindrical phantom generates only 14.7 µA current in imaging slice. Similarly, 5 mA total injected current results in 367 µA in imaging slice. Total acquisition time
Arpinar, V E; Hamamura, M J; Degirmenci, E; Muftuler, L T
2012-01-01
Magnetic resonance electrical impedance tomography (MREIT) is a technique that produces images of conductivity in tissues and phantoms. In this technique electrical currents are applied to an object and the resulting magnetic flux density is measured using magnetic resonance imaging (MRI) and the conductivity distribution is reconstructed using these MRI data. Currently the technique is used in research environments, primarily studying phantoms and animals. In order to translate MREIT to clinical applications, strict safety standards need to be established, especially for safe current limits. However, there are currently no standards for safe current limits specific to MREIT. Until such standards are established, human MREIT applications need to conform to existing electrical safety standards in medical instrumentation, such as the IEC601. This protocol limits patient auxiliary currents to 100μA for low frequencies. However, published MREIT studies have utilized currents 10 to 400 times larger than this limit, bringing into question whether the clinical applications of MREIT are attainable under current standards. In this study, we investigated the feasibility of MREIT to accurately reconstruct the relative conductivity of a simple agarose phantom using 200μA total injected current and we tested the performance of two MREIT reconstruction algorithms. These reconstruction algorithms used are the iterative sensitivity matrix method (SMM) by Ider and Birgul in 1998 with Tikhonov regularization and the Harmonic BZ proposed by Oh et al in 2003. The reconstruction techniques were tested at both 200μA and 5mA injected currents to investigate their noise sensitivity at low and high current conditions. It should be noted that 200μA total injected current into a cylindrical phantom generates only 14.7μA current in imaging slice. Similarly, 5mA total injected current results in 367μA in imaging slice. Total acquisition time for 200μA and 5mA experiments were about one
An Intrusion Detection Algorithm Based On NFPA
NASA Astrophysics Data System (ADS)
Anming, Zhong
A process oriented intrusion detection algorithm based on Probabilistic Automaton with No Final probabilities (NFPA) is introduced, system call sequence of process is used as the source data. By using information in system call sequence of normal process and system call sequence of anomaly process, the anomaly detection and the misuse detection are efficiently combined. Experiments show better performance of our algorithm compared to the classical algorithm in this field.
NASA Astrophysics Data System (ADS)
Gabrovšek, F.; Grašič, B.; Božnar, M. Z.; Mlakar, P.; Udén, M.; Davies, E.
2014-02-01
The paper presents an experiment demonstrating a novel and successful application of delay- and disruption-tolerant networking (DTN) technology for automatic data transfer in a karst cave early warning and measuring system. The experiment took place inside the Postojna Cave in Slovenia, which is open to tourists. Several automatic meteorological measuring stations are set up inside the cave, as an adjunct to the surveillance infrastructure; the regular data transfer provided by the DTN technology allows the surveillance system to take on the role of an early warning system (EWS). One of the stations is set up alongside the railway tracks, which allows the tourist to travel inside the cave by train. The experiment was carried out by placing a DTN "data mule" (a DTN-enabled computer with WiFi connection) on the train and by upgrading the meteorological station with a DTN-enabled WiFi transmission system. When the data mule is in the wireless drive-by mode, it collects measurement data from the station over a period of several seconds as the train without stopping passes the stationary equipment, and delivers data at the final train station by the cave entrance. This paper describes an overview of the experimental equipment and organization allowing the use of a DTN system for data collection and an EWS inside karst caves where there is regular traffic of tourists and researchers.
NASA Astrophysics Data System (ADS)
Gabrovšek, F.; Grašič, B.; Božnar, M. Z.; Mlakar, P.; Udén, M.; Davies, E.
2013-10-01
The paper presents an experiment demonstrating a novel and successful application of Delay- and Disruption-Tolerant Networking (DTN) technology for automatic data transfer in a karst cave Early Warning and Measuring System. The experiment took place inside the Postojna Cave in Slovenia, which is open to tourists. Several automatic meteorological measuring stations are set up inside the cave, as an adjunct to the surveillance infrastructure; the regular data transfer provided by the DTN technology allows the surveillance system to take on the role of an Early Warning System (EWS). One of the stations is set up alongside the railway tracks, which allows the tourist to travel inside the cave by train. The experiment was carried out by placing a DTN "data mule" (a DTN-enabled computer with WiFi connection) on the train and by upgrading the meteorological station with a DTN-enabled WiFi transmission system. When the data mule is in the wireless drive-by mode, it collects measurement data from the station over a period of several seconds as the train passes the stationary equipment, and delivers data at the final train station by the cave entrance. This paper describes an overview of the experimental equipment and organisation allowing the use of a DTN system for data collection and an EWS inside karst caves where there is a regular traffic of tourists and researchers.
NASA Astrophysics Data System (ADS)
Zheng, Genrang; Lin, ZhengChun
The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.
Honored Teacher Shows Commitment.
ERIC Educational Resources Information Center
Ratte, Kathy
1987-01-01
Part of the acceptance speech of the 1985 National Council for the Social Studies Teacher of the Year, this article describes the censorship experience of this honored social studies teacher. The incident involved the showing of a videotape version of the feature film entitled "The Seduction of Joe Tynan." (JDH)
Nagata, Kosei; Yamamoto, Shinichi; Miyoshi, Kota; Sato, Masaki; Arino, Yusuke; Mikami, Yoji
2016-08-01
Eosinophilic granulomatosis with polyangiitis (EGPA, Churg-Strauss syndrome) is a rare systemic vasculitis and is difficult to diagnose. EGPA has a number of symptoms including peripheral dysesthesia caused by mononeuropathy multiplex, which is similar to radiculopathy due to lumbar disc hernia or lumbar spinal stenosis. Therefore, EGPA patients with mononeuropathy multiplex often visit orthopedic clinics, but orthopedic doctors and spine neurosurgeons have limited experience in diagnosing EGPA because of its rarity. We report a consecutive series of patients who were initially diagnosed as having lumbar disc hernia or lumbar spinal stenosis by at least 2 medical institutions from March 2006 to April 2013 but whose final diagnosis was EGPA. All patients had past histories of asthma or eosinophilic pneumonia, and four out of five had peripheral edema. Laboratory data showed abnormally increased eosinophil counts, and nerve conduction studies of all patients revealed axonal damage patterns. All patients recovered from paralysis to a functional level after high-dose steroid treatment. We shortened the duration of diagnosis from 49 days to one day by adopting a diagnostic algorithm after experiencing the first case. PMID:27549670
Miller, L.F.
1980-11-01
A brief description of the Oak Ridge Reactor Pool Side Facility (ORR-PSF) and of the associated control system is given. The ORR-PSF capsule temperatures are controlled by a digital computer which regulates the percent power delivered to electrical heaters. The total electrical power which can be input to a particular heater is determined by the setting of an associated variac. This report concentrates on the description of the ORR-PSF irradiation experiment computer control algorithm. The algorithm is an implementation of a discrete-time, state variable, optimal control approach. The Riccati equation is solved for a discretized system model to determine the control law. Experiments performed to obtain system model parameters are described. Results of performance evaluation experiments are also presented. The control algorithm maintains both capsule temperatures within a 288/sup 0/C +-10/sup 0/C band as required. The pressure vessel capsule temperatures are effectively maintained within a 288/sup 0/C +-5/sup 0/C band.
NASA Technical Reports Server (NTRS)
Arenstorf, Norbert S.; Jordan, Harry F.
1987-01-01
A barrier is a method for synchronizing a large number of concurrent computer processes. After considering some basic synchronization mechanisms, a collection of barrier algorithms with either linear or logarithmic depth are presented. A graphical model is described that profiles the execution of the barriers and other parallel programming constructs. This model shows how the interaction between the barrier algorithms and the work that they synchronize can impact their performance. One result is that logarithmic tree structured barriers show good performance when synchronizing fixed length work, while linear self-scheduled barriers show better performance when synchronizing fixed length work with an imbedded critical section. The linear barriers are better able to exploit the process skew associated with critical sections. Timing experiments, performed on an eighteen processor Flex/32 shared memory multiprocessor, that support these conclusions are detailed.
Rother, W.; Dewald, A.; Fransen, C.; Hackstein, M.; Jolie, J.; Pissulla, Th.; Zel, K.-O.; Iwasaki, H.; Baugher, T.; Brown, B. A.; Gade, A.; Glasmacher, T.; McDaniel, S.; Ratkiewicz, A.; Voss, P.; Walsh, K. A.; Lenzi, S. M.; Ur, C. A.; Starosta, K.; Bazin, D.
2011-10-28
Probing shell structure at a large neutron excess has been of particular interest in recent times. Neutron-rich nuclei between the proton shell closures Z = 20 and Z = 28 offer an exotic testing ground for shell evolution. The development of the N = 40gap between neutron fp and lg{sub 9/2} shells gives rise to highly interesting variations of collectivity for nuclei in this region. While {sup 68}Ni shows doubly magic properties in level energies and transition strengths, this was not observed in neighbouring nuclei. Especially neutron-rich Fe isotopes proved particularly resistant to calculational approaches using the canonical valence space (fpg) resulting in important deviations of the predicted collectivity. Only an inclusion of the d{sub 5/2}-orbital could solve the problem [1]. Hitherto no transition strengths for {sup 66}Fe have been reported. We determined B(E2,2{sup +}{sub 1}{yields}0{sup +}{sub 1}) values from lifetimes measured with the recoil distance Doppler-shift method using the Cologne plunger for radioactive beams at National Superconducting Cyclotron Laboratory at Michigan State University. Excited states were populated by projectile Coulomb excitation for {sup 62,64,66}Fe. The data show a rise in collectivity for Fe isotopes towards N = 40. Results [2] are interpreted by means of a modified version of the Valence Proton Symmetry [3] and compared to shell model calculations using a new effective interaction recently developed for the fpgd valence space [4].
Solving SAT Problem Based on Hybrid Differential Evolution Algorithm
NASA Astrophysics Data System (ADS)
Liu, Kunqi; Zhang, Jingmin; Liu, Gang; Kang, Lishan
Satisfiability (SAT) problem is an NP-complete problem. Based on the analysis about it, SAT problem is translated equally into an optimization problem on the minimum of objective function. A hybrid differential evolution algorithm is proposed to solve the Satisfiability problem. It makes full use of strong local search capacity of hill-climbing algorithm and strong global search capability of differential evolution algorithm, which makes up their disadvantages, improves the efficiency of algorithm and avoids the stagnation phenomenon. The experiment results show that the hybrid algorithm is efficient in solving SAT problem.
A hybrid monkey search algorithm for clustering analysis.
Chen, Xin; Zhou, Yongquan; Luo, Qifang
2014-01-01
Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis.
A swaying object detection algorithm
NASA Astrophysics Data System (ADS)
Wang, Shidong; Rong, Jianzhong; Zhou, Dechuang; Wang, Jian
2013-07-01
Moving object detection is a most important preliminary step in video analysis. Some moving objects such as spitting steam, fire and smoke have unique motion feature whose lower position keep basically unchanged and the upper position move back and forth. Based on this unique motion feature, a swaying object detection algorithm is presented in this paper. Firstly, fuzzy integral was adopted to integrate color features for extracting moving objects from video frames. Secondly, a swaying identification algorithm based on centroid calculation was used to distinguish the swaying object from other moving objects. Experiments show that the proposed method is effective to detect swaying object.
Wrong, Terence; Baumgart, Erica
2013-01-01
The authors of the preceding articles raise legitimate questions about patient and staff rights and the unintended consequences of allowing ABC News to film inside teaching hospitals. We explain why we regard their fears as baseless and not supported by what we heard from individuals portrayed in the filming, our decade-long experience making medical documentaries, and the full un-aired context of the scenes shown in the broadcast. The authors don't and can't know what conversations we had, what documents we reviewed, and what protections we put in place in each televised scene. Finally, we hope to correct several misleading examples cited by the authors as well as their offhand mischaracterization of our program as a "reality" show. PMID:23631336
Wrong, Terence; Baumgart, Erica
2013-01-01
The authors of the preceding articles raise legitimate questions about patient and staff rights and the unintended consequences of allowing ABC News to film inside teaching hospitals. We explain why we regard their fears as baseless and not supported by what we heard from individuals portrayed in the filming, our decade-long experience making medical documentaries, and the full un-aired context of the scenes shown in the broadcast. The authors don't and can't know what conversations we had, what documents we reviewed, and what protections we put in place in each televised scene. Finally, we hope to correct several misleading examples cited by the authors as well as their offhand mischaracterization of our program as a "reality" show.
NASA Astrophysics Data System (ADS)
Que, Dashun; Li, Gang; Yue, Peng
2007-12-01
An adaptive optimization watermarking algorithm based on Genetic Algorithm (GA) and discrete wavelet transform (DWT) is proposed in this paper. The core of this algorithm is the fitness function optimization model for digital watermarking based on GA. The embedding intensity for digital watermarking can be modified adaptively, and the algorithm can effectively ensure the imperceptibility of watermarking while the robustness is ensured. The optimization model research may provide a new idea for anti-coalition attacks of digital watermarking algorithm. The paper has fulfilled many experiments, including the embedding and extracting experiments of watermarking, the influence experiments by the weighting factor, the experiments of embedding same watermarking to the different cover image, the experiments of embedding different watermarking to the same cover image, the comparative analysis experiments between this optimization algorithm and human visual system (HVS) algorithm and etc. The simulation results and the further analysis show the effectiveness and advantage of the new algorithm, which also has versatility and expandability. And meanwhile it has better ability of anti-coalition attacks. Moreover, the robustness and security of watermarking algorithm are improved by scrambling transformation and chaotic encryption while preprocessing the watermarking.
NASA Technical Reports Server (NTRS)
Pflaum, Christoph
1996-01-01
A multilevel algorithm is presented that solves general second order elliptic partial differential equations on adaptive sparse grids. The multilevel algorithm consists of several V-cycles. Suitable discretizations provide that the discrete equation system can be solved in an efficient way. Numerical experiments show a convergence rate of order Omicron(1) for the multilevel algorithm.
Calculation of substructural analysis weights using a genetic algorithm.
Holliday, John D; Sani, Nor; Willett, Peter
2015-02-23
This work describes a genetic algorithm for the calculation of substructural analysis for use in ligand-based virtual screening. The algorithm is simple in concept and effective in operation, with simulated virtual screening experiments using the MDDR and WOMBAT data sets showing it to be superior to substructural analysis weights based on a naive Bayesian classifier.
Advancements to the planogram frequency–distance rebinning algorithm
Champley, Kyle M; Raylman, Raymond R; Kinahan, Paul E
2010-01-01
In this paper we consider the task of image reconstruction in positron emission tomography (PET) with the planogram frequency–distance rebinning (PFDR) algorithm. The PFDR algorithm is a rebinning algorithm for PET systems with panel detectors. The algorithm is derived in the planogram coordinate system which is a native data format for PET systems with panel detectors. A rebinning algorithm averages over the redundant four-dimensional set of PET data to produce a three-dimensional set of data. Images can be reconstructed from this rebinned three-dimensional set of data. This process enables one to reconstruct PET images more quickly than reconstructing directly from the four-dimensional PET data. The PFDR algorithm is an approximate rebinning algorithm. We show that implementing the PFDR algorithm followed by the (ramp) filtered backprojection (FBP) algorithm in linogram coordinates from multiple views reconstructs a filtered version of our image. We develop an explicit formula for this filter which can be used to achieve exact reconstruction by means of a modified FBP algorithm applied to the stack of rebinned linograms and can also be used to quantify the errors introduced by the PFDR algorithm. This filter is similar to the filter in the planogram filtered backprojection algorithm derived by Brasse et al. The planogram filtered backprojection and exact reconstruction with the PFDR algorithm require complete projections which can be completed with a reprojection algorithm. The PFDR algorithm is similar to the rebinning algorithm developed by Kao et al. By expressing the PFDR algorithm in detector coordinates, we provide a comparative analysis between the two algorithms. Numerical experiments using both simulated data and measured data from a positron emission mammography/tomography (PEM/PET) system are performed. Images are reconstructed by PFDR+FBP (PFDR followed by 2D FBP reconstruction), PFDRX (PFDR followed by the modified FBP algorithm for exact
Improved hybrid optimization algorithm for 3D protein structure prediction.
Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang
2014-07-01
A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins. PMID:25069136
NASA Astrophysics Data System (ADS)
Lalande, Jean-Marie; Waxler, Roger; Velea, Doru
2016-04-01
As infrasonic waves propagate at long ranges through atmospheric ducts it has been suggested that observations of such waves can be used as a remote sensing techniques in order to update properties such as temperature and wind speed. In this study we investigate a new inverse approach based on Markov Chain Monte Carlo methods. This approach as the advantage of searching for the full Probability Density Function in the parameter space at a lower computational cost than extensive parameters search performed by the standard Monte Carlo approach. We apply this inverse methods to observations from the Humming Roadrunner experiment (New Mexico) and discuss implications for atmospheric updates, explosion characterization, localization and yield estimation.
Rème, Thierry; Hose, Dirk; De Vos, John; Vassal, Aurélien; Poulain, Pierre-Olivier; Pantesco, Véronique; Goldschmidt, Hartmut; Klein, Bernard
2008-01-01
Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM). Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks
Algorithms for automated DNA assembly
Densmore, Douglas; Hsiau, Timothy H.-C.; Kittleson, Joshua T.; DeLoache, Will; Batten, Christopher; Anderson, J. Christopher
2010-01-01
Generating a defined set of genetic constructs within a large combinatorial space provides a powerful method for engineering novel biological functions. However, the process of assembling more than a few specific DNA sequences can be costly, time consuming and error prone. Even if a correct theoretical construction scheme is developed manually, it is likely to be suboptimal by any number of cost metrics. Modular, robust and formal approaches are needed for exploring these vast design spaces. By automating the design of DNA fabrication schemes using computational algorithms, we can eliminate human error while reducing redundant operations, thus minimizing the time and cost required for conducting biological engineering experiments. Here, we provide algorithms that optimize the simultaneous assembly of a collection of related DNA sequences. We compare our algorithms to an exhaustive search on a small synthetic dataset and our results show that our algorithms can quickly find an optimal solution. Comparison with random search approaches on two real-world datasets show that our algorithms can also quickly find lower-cost solutions for large datasets. PMID:20335162
Algorithm for Public Electric Transport Schedule Control for Intelligent Embedded Devices
NASA Astrophysics Data System (ADS)
Alps, Ivars; Potapov, Andrey; Gorobetz, Mikhail; Levchenkov, Anatoly
2010-01-01
In this paper authors present heuristics algorithm for precise schedule fulfilment in city traffic conditions taking in account traffic lights. The algorithm is proposed for programmable controller. PLC is proposed to be installed in electric vehicle to control its motion speed and signals of traffic lights. Algorithm is tested using real controller connected to virtual devices and real functional models of real tram devices. Results of experiments show high precision of public transport schedule fulfilment using proposed algorithm.
A Multistrategy Optimization Improved Artificial Bee Colony Algorithm
Liu, Wen
2014-01-01
Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed. Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate. Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster. PMID:24982924
NASA Technical Reports Server (NTRS)
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
NASA Technical Reports Server (NTRS)
Entekhabi, Dara; Njoku, Eni E.; O'Neill, Peggy E.; Kellogg, Kent H.; Entin, Jared K.
2010-01-01
Talk outline 1. Derivation of SMAP basic and applied science requirements from the NRC Earth Science Decadal Survey applications 2. Data products and latencies 3. Algorithm highlights 4. SMAP Algorithm Testbed 5. SMAP Working Groups and community engagement
A new SPECT reconstruction algorithm based on the Novikov explicit inversion formula
NASA Astrophysics Data System (ADS)
Kunyansky, Leonid A.
2001-04-01
We present a new reconstruction algorithm for single-photon emission computed tomography. The algorithm is based on the Novikov explicit inversion formula for the attenuated Radon transform with non-uniform attenuation. Our reconstruction technique can be viewed as a generalization of both the filtered backprojection algorithm and the Tretiak-Metz algorithm. We test the performance of the present algorithm in a variety of numerical experiments. Our numerical examples show that the algorithm is capable of accurate image reconstruction even in the case of strongly non-uniform attenuation coefficient, similar to that occurring in a human thorax.
Modeling algorithm execution time on processor arrays
NASA Technical Reports Server (NTRS)
Adams, L. M.; Crockett, T. W.
1984-01-01
An approach to modelling the execution time of algorithms on parallel arrays is presented. This time is expressed as a function of the number of processors and system parameters. The resulting model has been applied to a parallel implementation of the conjugate-gradient algorithm on NASA's FEM. Results of experiments performed to compare the model predictions against actual behavior show that the floating-point arithmetic, communication, and synchronization components of the parallel algorithm execution time were correctly modelled. The results also show that the overhead caused by the interaction of the system software and the actual parallel hardware must be reflected in the model parameters. The model has been used to predict the performance of the conjugate gradient algorithm on a given problem as the number of processors and machine characteristics varied.
NASA Astrophysics Data System (ADS)
García, Alicia; De la Cruz-Reyna, Servando; Marrero, José M.; Ortiz, Ramón
2016-05-01
Under certain conditions, volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behaviour that may allow the occurrence and magnitude of major events to be forecast. Thus governmental decision makers can be supplied with warnings of the increased probability of larger-magnitude earthquakes on the short-term timescale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a mean recurrence time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10-day time windows, of volcano-tectonic earthquakes.
New Effective Multithreaded Matching Algorithms
Manne, Fredrik; Halappanavar, Mahantesh
2014-05-19
Matching is an important combinatorial problem with a number of applications in areas such as community detection, sparse linear algebra, and network alignment. Since computing optimal matchings can be very time consuming, several fast approximation algorithms, both sequential and parallel, have been suggested. Common to the algorithms giving the best solutions is that they tend to be sequential by nature, while algorithms more suitable for parallel computation give solutions of less quality. We present a new simple 1 2 -approximation algorithm for the weighted matching problem. This algorithm is both faster than any other suggested sequential 1 2 -approximation algorithm on almost all inputs and also scales better than previous multithreaded algorithms. We further extend this to a general scalable multithreaded algorithm that computes matchings of weight comparable with the best sequential algorithms. The performance of the suggested algorithms is documented through extensive experiments on different multithreaded architectures.
Fast parallel algorithm for slicing STL based on pipeline
NASA Astrophysics Data System (ADS)
Ma, Xulong; Lin, Feng; Yao, Bo
2016-05-01
In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms.
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
Fast Optimal Load Balancing Algorithms for 1D Partitioning
Pinar, Ali; Aykanat, Cevdet
2002-12-09
One-dimensional decomposition of nonuniform workload arrays for optimal load balancing is investigated. The problem has been studied in the literature as ''chains-on-chains partitioning'' problem. Despite extensive research efforts, heuristics are still used in parallel computing community with the ''hope'' of good decompositions and the ''myth'' of exact algorithms being hard to implement and not runtime efficient. The main objective of this paper is to show that using exact algorithms instead of heuristics yields significant load balance improvements with negligible increase in preprocessing time. We provide detailed pseudocodes of our algorithms so that our results can be easily reproduced. We start with a review of literature on chains-on-chains partitioning problem. We propose improvements on these algorithms as well as efficient implementation tips. We also introduce novel algorithms, which are asymptotically and runtime efficient. We experimented with data sets from two different applications: Sparse matrix computations and Direct volume rendering. Experiments showed that the proposed algorithms are 100 times faster than a single sparse-matrix vector multiplication for 64-way decompositions on average. Experiments also verify that load balance can be significantly improved by using exact algorithms instead of heuristics. These two findings show that exact algorithms with efficient implementations discussed in this paper can effectively replace heuristics.
Fast proximity algorithm for MAP ECT reconstruction
NASA Astrophysics Data System (ADS)
Li, Si; Krol, Andrzej; Shen, Lixin; Xu, Yuesheng
2012-03-01
We arrived at the fixed-point formulation of the total variation maximum a posteriori (MAP) regularized emission computed tomography (ECT) reconstruction problem and we proposed an iterative alternating scheme to numerically calculate the fixed point. We theoretically proved that our algorithm converges to unique solutions. Because the obtained algorithm exhibits slow convergence speed, we further developed the proximity algorithm in the transformed image space, i.e. the preconditioned proximity algorithm. We used the bias-noise curve method to select optimal regularization hyperparameters for both our algorithm and expectation maximization with total variation regularization (EM-TV). We showed in the numerical experiments that our proposed algorithms, with an appropriately selected preconditioner, outperformed conventional EM-TV algorithm in many critical aspects, such as comparatively very low noise and bias for Shepp-Logan phantom. This has major ramification for nuclear medicine because clinical implementation of our preconditioned fixed-point algorithms might result in very significant radiation dose reduction in the medical applications of emission tomography.
Dual-Byte-Marker Algorithm for Detecting JFIF Header
NASA Astrophysics Data System (ADS)
Mohamad, Kamaruddin Malik; Herawan, Tutut; Deris, Mustafa Mat
The use of efficient algorithm to detect JPEG file is vital to reduce time taken for analyzing ever increasing data in hard drive or physical memory. In the previous paper, single-byte-marker algorithm is proposed for header detection. In this paper, another novel header detection algorithm called dual-byte-marker is proposed. Based on the experiments done on images from hard disk, physical memory and data set from DFRWS 2006 Challenge, results showed that dual-byte-marker algorithm gives better performance with better execution time for header detection as compared to single-byte-marker.
NASA Astrophysics Data System (ADS)
Petersen, W. A.; Jensen, M. P.
2011-12-01
The joint NASA GPM - DOE ARM Midlatitude Continental Convective Clouds Experiment (MC3E) was conducted from April 22-June 6, 2011, centered on the DOE-ARM Southern Great Plains Central Facility site in northern Oklahoma. GPM field campaign objectives focused on the collection of airborne and ground-based measurements of warm-season continental precipitation processes to support refinement of GPM retrieval algorithm physics over land, and to improve the fidelity of coupled cloud resolving and land-surface satellite simulator models. DOE ARM objectives were synergistically focused on relating observations of cloud microphysics and the surrounding environment to feedbacks on convective system dynamics, an effort driven by the need to better represent those interactions in numerical modeling frameworks. More specific topics addressed by MC3E include ice processes and ice characteristics as coupled to precipitation at the surface and radiometer signals measured in space, the correlation properties of rainfall and drop size distributions and impacts on dual-frequency radar retrieval algorithms, the transition of cloud water to rain water (e.g., autoconversion processes) and the vertical distribution of cloud water in precipitating clouds, and vertical draft structure statistics in cumulus convection. The MC3E observational strategy relied on NASA ER-2 high-altitude airborne multi-frequency radar (HIWRAP Ka-Ku band) and radiometer (AMPR, CoSMIR; 10-183 GHz) sampling (a GPM "proxy") over an atmospheric column being simultaneously profiled in situ by the University of North Dakota Citation microphysics aircraft, an array of ground-based multi-frequency scanning polarimetric radars (DOE Ka-W, X and C-band; NASA D3R Ka-Ku and NPOL S-bands) and wind-profilers (S/UHF bands), supported by a dense network of over 20 disdrometers and rain gauges, all nested in the coverage of a six-station mesoscale rawinsonde network. As an exploratory effort to examine land-surface emissivity
NASA Technical Reports Server (NTRS)
Petersen, Walter A.; Jensen, Michael P.
2011-01-01
The joint NASA Global Precipitation Measurement (GPM) -- DOE Atmospheric Radiation Measurement (ARM) Midlatitude Continental Convective Clouds Experiment (MC3E) was conducted from April 22-June 6, 2011, centered on the DOE-ARM Southern Great Plains Central Facility site in northern Oklahoma. GPM field campaign objectives focused on the collection of airborne and ground-based measurements of warm-season continental precipitation processes to support refinement of GPM retrieval algorithm physics over land, and to improve the fidelity of coupled cloud resolving and land-surface satellite simulator models. DOE ARM objectives were synergistically focused on relating observations of cloud microphysics and the surrounding environment to feedbacks on convective system dynamics, an effort driven by the need to better represent those interactions in numerical modeling frameworks. More specific topics addressed by MC3E include ice processes and ice characteristics as coupled to precipitation at the surface and radiometer signals measured in space, the correlation properties of rainfall and drop size distributions and impacts on dual-frequency radar retrieval algorithms, the transition of cloud water to rain water (e.g., autoconversion processes) and the vertical distribution of cloud water in precipitating clouds, and vertical draft structure statistics in cumulus convection. The MC3E observational strategy relied on NASA ER-2 high-altitude airborne multi-frequency radar (HIWRAP Ka-Ku band) and radiometer (AMPR, CoSMIR; 10-183 GHz) sampling (a GPM "proxy") over an atmospheric column being simultaneously profiled in situ by the University of North Dakota Citation microphysics aircraft, an array of ground-based multi-frequency scanning polarimetric radars (DOE Ka-W, X and C-band; NASA D3R Ka-Ku and NPOL S-bands) and wind-profilers (S/UHF bands), supported by a dense network of over 20 disdrometers and rain gauges, all nested in the coverage of a six-station mesoscale rawinsonde
Television Quiz Show Simulation
ERIC Educational Resources Information Center
Hill, Jonnie Lynn
2007-01-01
This article explores the simulation of four television quiz shows for students in China studying English as a foreign language (EFL). It discusses the adaptation and implementation of television quiz shows and how the students reacted to them.
ERIC Educational Resources Information Center
Watters, Audrey
2012-01-01
As changing student demographics make it harder for today's learners to earn a four-year degree, educators are experimenting with smaller credentialing steps, such as digital badges. Mark Milliron, chancellor of Western Governors University Texas, advocates the creation of a "family of credentials," ranging from digital badges to certifications,…
Styopin, Nikita E; Vershinin, Anatoly V; Zingerman, Konstantin M; Levin, Vladimir A
2016-09-01
Different variants of the Uzawa algorithm are compared with one another. The comparison is performed for the case in which this algorithm is applied to large-scale systems of linear algebraic equations. These systems arise in the finite-element solution of the problems of elasticity theory for incompressible materials. A modification of the Uzawa algorithm is proposed. Computational experiments show that this modification improves the convergence of the Uzawa algorithm for the problems of solid mechanics. The results of computational experiments show that each variant of the Uzawa algorithm considered has its advantages and disadvantages and may be convenient in one case or another.
Styopin, Nikita E; Vershinin, Anatoly V; Zingerman, Konstantin M; Levin, Vladimir A
2016-09-01
Different variants of the Uzawa algorithm are compared with one another. The comparison is performed for the case in which this algorithm is applied to large-scale systems of linear algebraic equations. These systems arise in the finite-element solution of the problems of elasticity theory for incompressible materials. A modification of the Uzawa algorithm is proposed. Computational experiments show that this modification improves the convergence of the Uzawa algorithm for the problems of solid mechanics. The results of computational experiments show that each variant of the Uzawa algorithm considered has its advantages and disadvantages and may be convenient in one case or another. PMID:27595019
An enhanced dynamic hash TRIE algorithm for lexicon search
NASA Astrophysics Data System (ADS)
Yang, Lai; Xu, Lida; Shi, Zhongzhi
2012-11-01
Information retrieval (IR) is essential to enterprise systems along with growing orders, customers and materials. In this article, an enhanced dynamic hash TRIE (eDH-TRIE) algorithm is proposed that can be used in a lexicon search in Chinese, Japanese and Korean (CJK) segmentation and in URL identification. In particular, the eDH-TRIE algorithm is suitable for Unicode retrieval. The Auto-Array algorithm and Hash-Array algorithm are proposed to handle the auxiliary memory allocation; the former changes its size on demand without redundant restructuring, and the latter replaces linked lists with arrays, saving the overhead of memory. Comparative experiments show that the Auto-Array algorithm and Hash-Array algorithm have better spatial performance; they can be used in a multitude of situations. The eDH-TRIE is evaluated for both speed and storage and compared with the naïve DH-TRIE algorithms. The experiments show that the eDH-TRIE algorithm performs better. These algorithms reduce memory overheads and speed up IR.
Subsurface biological activity zone detection using genetic search algorithms
Mahinthakumar, G.; Gwo, J.P.; Moline, G.R.; Webb, O.F.
1999-12-01
Use of generic search algorithms for detection of subsurface biological activity zones (BAZ) is investigated through a series of hypothetical numerical biostimulation experiments. Continuous injection of dissolved oxygen and methane with periodically varying concentration stimulates the cometabolism of indigenous methanotropic bacteria. The observed breakthroughs of methane are used to deduce possible BAZ in the subsurface. The numerical experiments are implemented in a parallel computing environment to make possible the large number of simultaneous transport simulations required by the algorithm. The results show that genetic algorithms are very efficient in locating multiple activity zones, provided the observed signals adequately sample the BAZ.
ERIC Educational Resources Information Center
Kirkpatrick, Larry D.; Rugheimer, Mac
1979-01-01
Describes the viewing sessions and the holograms of a holographic road show. The traveling exhibits, believed to stimulate interest in physics, include a wide variety of holograms and demonstrate several physical principles. (GA)
Competing Sudakov veto algorithms
NASA Astrophysics Data System (ADS)
Kleiss, Ronald; Verheyen, Rob
2016-07-01
We present a formalism to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The formal analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance in a semi-realistic setting and show that there are significantly faster alternatives to the commonly used algorithms.
Improved artificial bee colony algorithm based gravity matching navigation method.
Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang
2014-07-18
Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.
An adaptive algorithm for low contrast infrared image enhancement
NASA Astrophysics Data System (ADS)
Liu, Sheng-dong; Peng, Cheng-yuan; Wang, Ming-jia; Wu, Zhi-guo; Liu, Jia-qi
2013-08-01
An adaptive infrared image enhancement algorithm for low contrast is proposed in this paper, to deal with the problem that conventional image enhancement algorithm is not able to effective identify the interesting region when dynamic range is large in image. This algorithm begin with the human visual perception characteristics, take account of the global adaptive image enhancement and local feature boost, not only the contrast of image is raised, but also the texture of picture is more distinct. Firstly, the global image dynamic range is adjusted from the overall, the dynamic range of original image and display grayscale form corresponding relationship, the gray scale of bright object is raised and the the gray scale of dark target is reduced at the same time, to improve the overall image contrast. Secondly, the corresponding filtering algorithm is used on the current point and its neighborhood pixels to extract image texture information, to adjust the brightness of the current point in order to enhance the local contrast of the image. The algorithm overcomes the default that the outline is easy to vague in traditional edge detection algorithm, and ensure the distinctness of texture detail in image enhancement. Lastly, we normalize the global luminance adjustment image and the local brightness adjustment image, to ensure a smooth transition of image details. A lot of experiments is made to compare the algorithm proposed in this paper with other convention image enhancement algorithm, and two groups of vague IR image are taken in experiment. Experiments show that: the contrast ratio of the picture is boosted after handled by histogram equalization algorithm, but the detail of the picture is not clear, the detail of the picture can be distinguished after handled by the Retinex algorithm. The image after deal with by self-adaptive enhancement algorithm proposed in this paper becomes clear in details, and the image contrast is markedly improved in compared with Retinex
NASA Technical Reports Server (NTRS)
Halyo, Nesim; Choi, Sang H.
1987-01-01
Two count conversion algorithms and the associated dynamic sensor model for the M/WFOV nonscanner radiometers are defined. The sensor model provides and updates the constants necessary for the conversion algorithms, though the frequency with which these updates were needed was uncertain. This analysis therefore develops mathematical models for the conversion of irradiance at the sensor field of view (FOV) limiter into data counts, derives from this model two algorithms for the conversion of data counts to irradiance at the sensor FOV aperture and develops measurement models which account for a specific target source together with a sensor. The resulting algorithms are of the gain/offset and Kalman filter types. The gain/offset algorithm was chosen since it provided sufficient accuracy using simpler computations.
ERIC Educational Resources Information Center
Mathieu, Aaron
2000-01-01
Uses a talk show activity for a final assessment tool for students to debate about the ozone hole. Students are assessed on five areas: (1) cooperative learning; (2) the written component; (3) content; (4) self-evaluation; and (5) peer evaluation. (SAH)
ERIC Educational Resources Information Center
Eccleston, Jeff
2007-01-01
Big things come in small packages. This saying came to the mind of the author after he created a simple math review activity for his fourth grade students. Though simple, it has proven to be extremely advantageous in reinforcing math concepts. He uses this activity, which he calls "Show What You Know," often. This activity provides the perfect…
ERIC Educational Resources Information Center
Cech, Scott J.
2008-01-01
Having students show their skills in three dimensions, known as performance-based assessment, dates back at least to Socrates. Individual schools such as Barrington High School--located just outside of Providence--have been requiring students to actively demonstrate their knowledge for years. The Rhode Island's high school graduating class became…
ERIC Educational Resources Information Center
Frasier, Debra
2008-01-01
In the author's book titled "The Incredible Water Show," the characters from "Miss Alaineus: A Vocabulary Disaster" used an ocean of information to stage an inventive performance about the water cycle. In this article, the author relates how she turned the story into hands-on science teaching for real-life fifth-grade students. The author also…
ERIC Educational Resources Information Center
Geological Survey (Dept. of Interior), Reston, VA.
This curriculum packet, appropriate for grades 4-8, features a teaching poster which shows different types of maps (different views of Salt Lake City, Utah), as well as three reproducible maps and reproducible activity sheets which complement the maps. The poster provides teacher background, including step-by-step lesson plans for four geography…
Corbee, R J
2014-12-01
Obesity is an important disease with a high prevalence in cats. Because obesity is related to several other diseases, it is important to identify the population at risk. Several risk factors for obesity have been described in the literature. A higher incidence of obesity in certain cat breeds has been suggested. The aim of this study was to determine whether obesity occurs more often in certain breeds. The second aim was to relate the increased prevalence of obesity in certain breeds to the official standards of that breed. To this end, 268 cats of 22 different breeds investigated by determining their body condition score (BCS) on a nine-point scale by inspection and palpation, at two different cat shows. Overall, 45.5% of the show cats had a BCS > 5, and 4.5% of the show cats had a BCS > 7. There were significant differences between breeds, which could be related to the breed standards. Most overweight and obese cats were in the neutered group. It warrants firm discussions with breeders and cat show judges to come to different interpretations of the standards in order to prevent overweight conditions in certain breeds from being the standard of beauty. Neutering predisposes for obesity and requires early nutritional intervention to prevent obese conditions. PMID:24612018
ERIC Educational Resources Information Center
Dicks, Matthew J.
2005-01-01
Because today's students have grown up steeped in video games and the Internet, most of them expect feedback, and usually gratification, very soon after they expend effort on a task. Teachers can get quick feedback to students by showing them videotapes of their learning performances. The author, a 3rd grade teacher describes how the seemingly…
ERIC Educational Resources Information Center
Scolarici, Alicia
2004-01-01
This article describes what once was thought to be impossible--a formal art show extravaganza at an elementary school with 1,000 students, a Department of Defense Dependent School (DODDS) located overseas, on RAF Lakenheath, England. The dream of this this event involved the transformation of the school cafeteria into an elegant art show…
Algorithm for dynamic Speckle pattern processing
NASA Astrophysics Data System (ADS)
Cariñe, J.; Guzmán, R.; Torres-Ruiz, F. A.
2016-07-01
In this paper we present a new algorithm for determining surface activity by processing speckle pattern images recorded with a CCD camera. Surface activity can be produced by motility or small displacements among other causes, and is manifested as a change in the pattern recorded in the camera with reference to a static background pattern. This intensity variation is considered to be a small perturbation compared with the mean intensity. Based on a perturbative method we obtain an equation with which we can infer information about the dynamic behavior of the surface that generates the speckle pattern. We define an activity index based on our algorithm that can be easily compared with the outcomes from other algorithms. It is shown experimentally that this index evolves in time in the same way as the Inertia Moment method, however our algorithm is based on direct processing of speckle patterns without the need for other kinds of post-processes (like THSP and co-occurrence matrix), making it a viable real-time method. We also show how this algorithm compares with several other algorithms when applied to calibration experiments. From these results we conclude that our algorithm offer qualitative and quantitative advantages over current methods.
NASA Astrophysics Data System (ADS)
Matsui, Shouichi; Watanabe, Isamu; Tokoro, Ken-Ichi
A new genetic algorithm is proposed for solving job-shop scheduling problems where the total number of search points is limited. The objective of the problem is to minimize the makespan. The solution is represented by an operation sequence, i.e., a permutation of operations. The proposed algorithm is based on the framework of the parameter-free genetic algorithm. It encodes a permutation using random keys into a chromosome. A schedule is derived from a permutation using a hybrid scheduling (HS), and the parameter of HS is also encoded in a chromosome. Experiments using benchmark problems show that the proposed algorithm outperforms the previously proposed algorithms, genetic algorithm by Shi et al. and the improved local search by Nakano et al., for large-scale problems under the constraint of limited number of search points.
Adaptive path planning: Algorithm and analysis
Chen, Pang C.
1995-03-01
To address the need for a fast path planner, we present a learning algorithm that improves path planning by using past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions difficult tasks. From these solutions, an evolving sparse work of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a framework in which a slow but effective planner may be improved both cost-wise and capability-wise by a faster but less effective planner coupled with experience. We analyze algorithm by formalizing the concept of improvability and deriving conditions under which a planner can be improved within the framework. The analysis is based on two stochastic models, one pessimistic (on task complexity), the other randomized (on experience utility). Using these models, we derive quantitative bounds to predict the learning behavior. We use these estimation tools to characterize the situations in which the algorithm is useful and to provide bounds on the training time. In particular, we show how to predict the maximum achievable speedup. Additionally, our analysis techniques are elementary and should be useful for studying other types of probabilistic learning as well.
Boden, Timothy W
2016-01-01
Many medical practices have cut back on education and staff development expenses, especially those costs associated with conventions and conferences. But there are hard-to-value returns on your investment in these live events--beyond the obvious benefits of acquired knowledge and skills. Major vendors still exhibit their services and wares at many events, and the exhibit hall is a treasure-house of information and resources for the savvy physician or administrator. Make and stick to a purposeful plan to exploit the trade show. You can compare products, gain new insights and ideas, and even negotiate better deals with representatives anxious to realize returns on their exhibition investments. PMID:27249887
Boden, Timothy W
2016-01-01
Many medical practices have cut back on education and staff development expenses, especially those costs associated with conventions and conferences. But there are hard-to-value returns on your investment in these live events--beyond the obvious benefits of acquired knowledge and skills. Major vendors still exhibit their services and wares at many events, and the exhibit hall is a treasure-house of information and resources for the savvy physician or administrator. Make and stick to a purposeful plan to exploit the trade show. You can compare products, gain new insights and ideas, and even negotiate better deals with representatives anxious to realize returns on their exhibition investments.
Corbee, R J
2013-10-01
Obesity is an important disease with a growing incidence. Because obesity is related to several other diseases, and decreases life span, it is important to identify the population at risk. Several risk factors for obesity have been described in the literature. A higher incidence of obesity in certain breeds is often suggested. The aim of this study was to determine whether obesity occurs more often in certain breeds. The second aim was to relate the increased prevalence of obesity in certain breeds to the official standards of that breed. To this end, we investigated 1379 dogs of 128 different breeds by determining their body condition score (BCS). Overall, 18.6% of the show dogs had a BCS >5, and 1.1% of the show dogs had a BCS>7. There were significant differences between breeds, which could be correlated to the breed standards. It warrants firm discussions with breeders and judges in order to come to different interpretations of the standards to prevent overweight conditions from being the standard of beauty. PMID:22882163
Automatic design of decision-tree algorithms with evolutionary algorithms.
Barros, Rodrigo C; Basgalupp, Márcio P; de Carvalho, André C P L F; Freitas, Alex A
2013-01-01
This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. The automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. The proposed hyper-heuristic evolutionary algorithm, HEAD-DT, is extensively tested using 20 public UCI datasets and 10 microarray gene expression datasets. The algorithms automatically designed by HEAD-DT are compared with traditional decision-tree induction algorithms, such as C4.5 and CART. Experimental results show that HEAD-DT is capable of generating algorithms which are significantly more accurate than C4.5 and CART.
NASA Astrophysics Data System (ADS)
Li, Zhaokun; Cao, Jingtai; Liu, Wei; Feng, Jianfeng; Zhao, Xiaohui
2015-03-01
We use conventional adaptive optical system to compensate atmospheric turbulence in free space optical (FSO) communication system under strong scintillation circumstances, undesired wave-front measurements based on Shark-Hartman sensor (SH). Since wavefront sensor-less adaptive optics is a feasible option, we propose several swarm intelligence algorithms to compensate the wavefront aberration from atmospheric interference in FSO and mainly discuss the algorithm principle, basic flows, and simulation result. The numerical simulation experiment and result analysis show that compared with SPGD algorithm, the proposed algorithms can effectively restrain wavefront aberration, and improve convergence rate of the algorithms and the coupling efficiency of receiver in large extent.
Saleh, Marwan D; Eswaran, C
2012-01-01
Retinal blood vessel detection and analysis play vital roles in early diagnosis and prevention of several diseases, such as hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. This paper presents an automated algorithm for retinal blood vessel segmentation. The proposed algorithm takes advantage of powerful image processing techniques such as contrast enhancement, filtration and thresholding for more efficient segmentation. To evaluate the performance of the proposed algorithm, experiments were conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm yields an accuracy rate of 96.5%, which is higher than the results achieved by other known algorithms.
Saleh, Marwan D; Eswaran, C; Mueen, Ahmed
2011-08-01
This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhancement and thresholding offers an automated segmentation procedure for retinal blood vessels. To evaluate the performance of the new algorithm, experiments are conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm performs better than the other known algorithms in terms of accuracy. Furthermore, the proposed algorithm being simple and easy to implement, is best suited for fast processing applications.
Analysis of the numerical effects of parallelism on a parallel genetic algorithm
Hart, W.E.; Belew, R.K.; Kohn, S.; Baden, S.
1995-09-18
This paper examines the effects of relaxed synchronization on both the numerical and parallel efficiency of parallel genetic algorithms (GAs). We describe a coarse-grain geographically structured parallel genetic algorithm. Our experiments show that asynchronous versions of these algorithms have a lower run time than-synchronous GAs. Furthermore, we demonstrate that this improvement in performance is partly due to the fact that the numerical efficiency of the asynchronous genetic algorithm is better than the synchronous genetic algorithm. Our analysis includes a critique of the utility of traditional parallel performance measures for parallel GAs, and we evaluate the claims made by several researchers that parallel GAs can have superlinear speedup.
Walusinski, Olivier
2014-01-01
In the second half of the 19th century, Jean-Martin Charcot (1825-1893) became famous for the quality of his teaching and his innovative neurological discoveries, bringing many French and foreign students to Paris. A hunger for recognition, together with progressive and anticlerical ideals, led Charcot to invite writers, journalists, and politicians to his lessons, during which he presented the results of his work on hysteria. These events became public performances, for which physicians and patients were transformed into actors. Major newspapers ran accounts of these consultations, more like theatrical shows in some respects. The resultant enthusiasm prompted other physicians in Paris and throughout France to try and imitate them. We will compare the form and substance of Charcot's lessons with those given by Jules-Bernard Luys (1828-1897), Victor Dumontpallier (1826-1899), Ambroise-Auguste Liébault (1823-1904), Hippolyte Bernheim (1840-1919), Joseph Grasset (1849-1918), and Albert Pitres (1848-1928). We will also note their impact on contemporary cinema and theatre. PMID:25273491
Speckle imaging algorithms for planetary imaging
Johansson, E.
1994-11-15
I will discuss the speckle imaging algorithms used to process images of the impact sites of the collision of comet Shoemaker-Levy 9 with Jupiter. The algorithms use a phase retrieval process based on the average bispectrum of the speckle image data. High resolution images are produced by estimating the Fourier magnitude and Fourier phase of the image separately, then combining them and inverse transforming to achieve the final result. I will show raw speckle image data and high-resolution image reconstructions from our recent experiment at Lick Observatory.
NASA Astrophysics Data System (ADS)
2007-01-01
its high spatial and spectral resolution, it was possible to zoom into the very heart of this very massive star. In this innermost region, the observations are dominated by the extremely dense stellar wind that totally obscures the underlying central star. The AMBER observations show that this dense stellar wind is not spherically symmetric, but exhibits a clearly elongated structure. Overall, the AMBER observations confirm that the extremely high mass loss of Eta Carinae's massive central star is non-spherical and much stronger along the poles than in the equatorial plane. This is in agreement with theoretical models that predict such an enhanced polar mass-loss in the case of rapidly rotating stars. ESO PR Photo 06c/07 ESO PR Photo 06c/07 RS Ophiuchi in Outburst Several papers from this special feature focus on the later stages in a star's life. One looks at the binary system Gamma 2 Velorum, which contains the closest example of a star known as a Wolf-Rayet. A single AMBER observation allowed the astronomers to separate the spectra of the two components, offering new insights in the modeling of Wolf-Rayet stars, but made it also possible to measure the separation between the two stars. This led to a new determination of the distance of the system, showing that previous estimates were incorrect. The observations also revealed information on the region where the winds from the two stars collide. The famous binary system RS Ophiuchi, an example of a recurrent nova, was observed just 5 days after it was discovered to be in outburst on 12 February 2006, an event that has been expected for 21 years. AMBER was able to detect the extension of the expanding nova emission. These observations show a complex geometry and kinematics, far from the simple interpretation of a spherical fireball in extension. AMBER has detected a high velocity jet probably perpendicular to the orbital plane of the binary system, and allowed a precise and careful study of the wind and the shockwave
Stretched View Showing 'Victoria'
NASA Technical Reports Server (NTRS)
2006-01-01
[figure removed for brevity, see original site] Stretched View Showing 'Victoria'
This pair of images from the panoramic camera on NASA's Mars Exploration Rover Opportunity served as initial confirmation that the two-year-old rover is within sight of 'Victoria Crater,' which it has been approaching for more than a year. Engineers on the rover team were unsure whether Opportunity would make it as far as Victoria, but scientists hoped for the chance to study such a large crater with their roving geologist. Victoria Crater is 800 meters (nearly half a mile) in diameter, about six times wider than 'Endurance Crater,' where Opportunity spent several months in 2004 examining rock layers affected by ancient water.
When scientists using orbital data calculated that they should be able to detect Victoria's rim in rover images, they scrutinized frames taken in the direction of the crater by the panoramic camera. To positively characterize the subtle horizon profile of the crater and some of the features leading up to it, researchers created a vertically-stretched image (top) from a mosaic of regular frames from the panoramic camera (bottom), taken on Opportunity's 804th Martian day (April 29, 2006).
The stretched image makes mild nearby dunes look like more threatening peaks, but that is only a result of the exaggerated vertical dimension. This vertical stretch technique was first applied to Viking Lander 2 panoramas by Philip Stooke, of the University of Western Ontario, Canada, to help locate the lander with respect to orbiter images. Vertically stretching the image allows features to be more readily identified by the Mars Exploration Rover science team.
The bright white dot near the horizon to the right of center (barely visible without labeling or zoom-in) is thought to be a light-toned outcrop on the far wall of the crater, suggesting that the rover can see over the low rim of Victoria. In figure 1, the northeast and southeast rims are labeled
Multipartite entanglement in quantum algorithms
Bruss, D.; Macchiavello, C.
2011-05-15
We investigate the entanglement features of the quantum states employed in quantum algorithms. In particular, we analyze the multipartite entanglement properties in the Deutsch-Jozsa, Grover, and Simon algorithms. Our results show that for these algorithms most instances involve multipartite entanglement.
Rudnik-Schöneborn, S; Tölle, D; Senderek, J; Eggermann, K; Elbracht, M; Kornak, U; von der Hagen, M; Kirschner, J; Leube, B; Müller-Felber, W; Schara, U; von Au, K; Wieczorek, D; Bußmann, C; Zerres, K
2016-01-01
We present clinical features and genetic results of 1206 index patients and 124 affected relatives who were referred for genetic testing of Charcot-Marie-Tooth (CMT) neuropathy at the laboratory in Aachen between 2001 and 2012. Genetic detection rates were 56% in demyelinating CMT (71% of autosomal dominant (AD) CMT1/CMTX), and 17% in axonal CMT (24% of AD CMT2/CMTX). Three genetic defects (PMP22 duplication/deletion, GJB1/Cx32 or MPZ/P0 mutation) were responsible for 89.3% of demyelinating CMT index patients in whom a genetic diagnosis was achieved, and the diagnostic yield of the three main genetic defects in axonal CMT (GJB1/Cx32, MFN2, MPZ/P0 mutations) was 84.2%. De novo mutations were detected in 1.3% of PMP22 duplication, 25% of MPZ/P0, and none in GJB1/Cx32. Motor nerve conduction velocity was uniformly <38 m/s in median or ulnar nerves in PMP22 duplication, >40 m/s in MFN2, and more variable in GJB1/Cx32, MPZ/P0 mutations. Patients with CMT2A showed a broad clinical severity regardless of the type or position of the MFN2 mutation. Out of 75 patients, 8 patients (11%) with PMP22 deletions were categorized as CMT1 or CMT2. Diagnostic algorithms are still useful for cost-efficient mutation detection and for the interpretation of large-scale genetic data made available by next generation sequencing strategies.
NASA Astrophysics Data System (ADS)
Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.
2013-01-01
A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.
Restart-Based Genetic Algorithm for the Quadratic Assignment Problem
NASA Astrophysics Data System (ADS)
Misevicius, Alfonsas
The power of genetic algorithms (GAs) has been demonstrated for various domains of the computer science, including combinatorial optimization. In this paper, we propose a new conceptual modification of the genetic algorithm entitled a "restart-based genetic algorithm" (RGA). An effective implementation of RGA for a well-known combinatorial optimization problem, the quadratic assignment problem (QAP), is discussed. The results obtained from the computational experiments on the QAP instances from the publicly available library QAPLIB show excellent performance of RGA. This is especially true for the real-life like QAPs.
An algorithm for prescribed mean curvature using isogeometric methods
NASA Astrophysics Data System (ADS)
Chicco-Ruiz, Aníbal; Morin, Pedro; Pauletti, M. Sebastian
2016-07-01
We present a Newton type algorithm to find parametric surfaces of prescribed mean curvature with a fixed given boundary. In particular, it applies to the problem of minimal surfaces. The algorithm relies on some global regularity of the spaces where it is posed, which is naturally fitted for discretization with isogeometric type of spaces. We introduce a discretization of the continuous algorithm and present a simple implementation using the recently released isogeometric software library igatools. Finally, we show several numerical experiments which highlight the convergence properties of the scheme.
An ant colony algorithm on continuous searching space
NASA Astrophysics Data System (ADS)
Xie, Jing; Cai, Chao
2015-12-01
Ant colony algorithm is heuristic, bionic and parallel. Because of it is property of positive feedback, parallelism and simplicity to cooperate with other method, it is widely adopted in planning on discrete space. But it is still not good at planning on continuous space. After a basic introduction to the basic ant colony algorithm, we will propose an ant colony algorithm on continuous space. Our method makes use of the following three tricks. We search for the next nodes of the route according to fixed-step to guarantee the continuity of solution. When storing pheromone, it discretizes field of pheromone, clusters states and sums up the values of pheromone of these states. When updating pheromone, it makes good resolutions measured in relative score functions leave more pheromone, so that ant colony algorithm can find a sub-optimal solution in shorter time. The simulated experiment shows that our ant colony algorithm can find sub-optimal solution in relatively shorter time.
Adaptive image contrast enhancement algorithm for point-based rendering
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Liu, Xiaoping P.
2015-03-01
Surgical simulation is a major application in computer graphics and virtual reality, and most of the existing work indicates that interactive real-time cutting simulation of soft tissue is a fundamental but challenging research problem in virtual surgery simulation systems. More specifically, it is difficult to achieve a fast enough graphic update rate (at least 30 Hz) on commodity PC hardware by utilizing traditional triangle-based rendering algorithms. In recent years, point-based rendering (PBR) has been shown to offer the potential to outperform the traditional triangle-based rendering in speed when it is applied to highly complex soft tissue cutting models. Nevertheless, the PBR algorithms are still limited in visual quality due to inherent contrast distortion. We propose an adaptive image contrast enhancement algorithm as a postprocessing module for PBR, providing high visual rendering quality as well as acceptable rendering efficiency. Our approach is based on a perceptible image quality technique with automatic parameter selection, resulting in a visual quality comparable to existing conventional PBR algorithms. Experimental results show that our adaptive image contrast enhancement algorithm produces encouraging results both visually and numerically compared to representative algorithms, and experiments conducted on the latest hardware demonstrate that the proposed PBR framework with the postprocessing module is superior to the conventional PBR algorithm and that the proposed contrast enhancement algorithm can be utilized in (or compatible with) various variants of the conventional PBR algorithm.
Blind Alley Aware ACO Routing Algorithm
NASA Astrophysics Data System (ADS)
Yoshikawa, Masaya; Otani, Kazuo
2010-10-01
The routing problem is applied to various engineering fields. Many researchers study this problem. In this paper, we propose a new routing algorithm which is based on Ant Colony Optimization. The proposed algorithm introduces the tabu search mechanism to escape the blind alley. Thus, the proposed algorithm enables to find the shortest route, even if the map data contains the blind alley. Experiments using map data prove the effectiveness in comparison with Dijkstra algorithm which is the most popular conventional routing algorithm.
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.
Acoustic simulation in architecture with parallel algorithm
NASA Astrophysics Data System (ADS)
Li, Xiaohong; Zhang, Xinrong; Li, Dan
2004-03-01
In allusion to complexity of architecture environment and Real-time simulation of architecture acoustics, a parallel radiosity algorithm was developed. The distribution of sound energy in scene is solved with this method. And then the impulse response between sources and receivers at frequency segment, which are calculated with multi-process, are combined into whole frequency response. The numerical experiment shows that parallel arithmetic can improve the acoustic simulating efficiency of complex scene.
A highly accurate heuristic algorithm for the haplotype assembly problem
2013-01-01
Background Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation in human DNA. The sequence of SNPs in each of the two copies of a given chromosome in a diploid organism is referred to as a haplotype. Haplotype information has many applications such as gene disease diagnoses, drug design, etc. The haplotype assembly problem is defined as follows: Given a set of fragments sequenced from the two copies of a chromosome of a single individual, and their locations in the chromosome, which can be pre-determined by aligning the fragments to a reference DNA sequence, the goal here is to reconstruct two haplotypes (h1, h2) from the input fragments. Existing algorithms do not work well when the error rate of fragments is high. Here we design an algorithm that can give accurate solutions, even if the error rate of fragments is high. Results We first give a dynamic programming algorithm that can give exact solutions to the haplotype assembly problem. The time complexity of the algorithm is O(n × 2t × t), where n is the number of SNPs, and t is the maximum coverage of a SNP site. The algorithm is slow when t is large. To solve the problem when t is large, we further propose a heuristic algorithm on the basis of the dynamic programming algorithm. Experiments show that our heuristic algorithm can give very accurate solutions. Conclusions We have tested our algorithm on a set of benchmark datasets. Experiments show that our algorithm can give very accurate solutions. It outperforms most of the existing programs when the error rate of the input fragments is high. PMID:23445458
Flocking algorithm for autonomous flying robots.
Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, Tamás; Somorjai, Gergő; Nepusz, Tamás; Vicsek, Tamás
2014-06-01
Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks. PMID:24852272
Flocking algorithm for autonomous flying robots.
Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, Tamás; Somorjai, Gergő; Nepusz, Tamás; Vicsek, Tamás
2014-06-01
Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks.
A Novel Complex Networks Clustering Algorithm Based on the Core Influence of Nodes
Dai, Bin; Xie, Zhongyu
2014-01-01
In complex networks, cluster structure, identified by the heterogeneity of nodes, has become a common and important topological property. Network clustering methods are thus significant for the study of complex networks. Currently, many typical clustering algorithms have some weakness like inaccuracy and slow convergence. In this paper, we propose a clustering algorithm by calculating the core influence of nodes. The clustering process is a simulation of the process of cluster formation in sociology. The algorithm detects the nodes with core influence through their betweenness centrality, and builds the cluster's core structure by discriminant functions. Next, the algorithm gets the final cluster structure after clustering the rest of the nodes in the network by optimizing method. Experiments on different datasets show that the clustering accuracy of this algorithm is superior to the classical clustering algorithm (Fast-Newman algorithm). It clusters faster and plays a positive role in revealing the real cluster structure of complex networks precisely. PMID:24741359
TSaT-MUSIC: a novel algorithm for rapid and accurate ultrasonic 3D localization
NASA Astrophysics Data System (ADS)
Mizutani, Kyohei; Ito, Toshio; Sugimoto, Masanori; Hashizume, Hiromichi
2011-12-01
We describe a fast and accurate indoor localization technique using the multiple signal classification (MUSIC) algorithm. The MUSIC algorithm is known as a high-resolution method for estimating directions of arrival (DOAs) or propagation delays. A critical problem in using the MUSIC algorithm for localization is its computational complexity. Therefore, we devised a novel algorithm called Time Space additional Temporal-MUSIC, which can rapidly and simultaneously identify DOAs and delays of mul-ticarrier ultrasonic waves from transmitters. Computer simulations have proved that the computation time of the proposed algorithm is almost constant in spite of increasing numbers of incoming waves and is faster than that of existing methods based on the MUSIC algorithm. The robustness of the proposed algorithm is discussed through simulations. Experiments in real environments showed that the standard deviation of position estimations in 3D space is less than 10 mm, which is satisfactory for indoor localization.
One high-accuracy camera calibration algorithm based on computer vision images
NASA Astrophysics Data System (ADS)
Wang, Ying; Huang, Jianming; Wei, Xiangquan
2015-12-01
Camera calibration is the first step of computer vision and one of the most active research fields nowadays. In order to improve the measurement precision, the internal parameters of the camera should be accurately calibrated. So one high-accuracy camera calibration algorithm is proposed based on the images of planar targets or tridimensional targets. By using the algorithm, the internal parameters of the camera are calibrated based on the existing planar target at the vision-based navigation experiment. The experimental results show that the accuracy of the proposed algorithm is obviously improved compared with the conventional linear algorithm, Tsai general algorithm, and Zhang Zhengyou calibration algorithm. The algorithm proposed by the article can satisfy the need of computer vision and provide reference for precise measurement of the relative position and attitude.
Du, Tingsong; Hu, Yang; Ke, Xianting
2015-01-01
An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.
NASA Astrophysics Data System (ADS)
Sellitto, P.; Del Frate, F.
2014-07-01
Atmospheric temperature profiles are inferred from passive satellite instruments, using thermal infrared or microwave observations. Here we investigate on the feasibility of the retrieval of height resolved temperature information in the ultraviolet spectral region. The temperature dependence of the absorption cross sections of ozone in the Huggins band, in particular in the interval 320-325 nm, is exploited. We carried out a sensitivity analysis and demonstrated that a non-negligible information on the temperature profile can be extracted from this small band. Starting from these results, we developed a neural network inversion algorithm, trained and tested with simulated nadir EnviSat-SCIAMACHY ultraviolet observations. The algorithm is able to retrieve the temperature profile with root mean square errors and biases comparable to existing retrieval schemes that use thermal infrared or microwave observations. This demonstrates, for the first time, the feasibility of temperature profiles retrieval from space-borne instruments operating in the ultraviolet.
NASA Astrophysics Data System (ADS)
Kothari, K. M.; Meroney, R. N.; Bouwmeester, R. J. B.
1981-08-01
Highest concentrations of pollutant at ground level are often produced from surface sources with stable or unstable atmospheric conditions and near calm erratic winds. This paper describes a weighted data methodology developed to predict surface concentrations from stationary wind-tunnel measurements and actual meteorological wind fields. Field measurements made downwind of the Rancho Seco Nuclear Power Station in 1975 have been compared against a set of wind-tunnel measurements around a 1:500 scale model of the same facilities. The weighted data algorithm was realistic in both predicting centerline concentration values as well as the horizontal spread of the plume. On the average the wind-tunnel data combined with the weighting algorithm was some 40 times more accurate in predicting field data than the conventional Pasquill-Gifford formulas.
Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi
2014-01-01
Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: "bats approach their prey." Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425
A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.
Ali, Ahmed F; Tawhid, Mohamed A
2016-01-01
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time. PMID:27217988
A hybrid cuckoo search algorithm with Nelder Mead method for solving global optimization problems.
Ali, Ahmed F; Tawhid, Mohamed A
2016-01-01
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization problems. We call the proposed algorithm by hybrid cuckoo search and Nelder-Mead method (HCSNM). HCSNM starts the search by applying the standard cuckoo search for number of iterations then the best obtained solution is passing to the Nelder-Mead algorithm as an intensification process in order to accelerate the search and overcome the slow convergence of the standard cuckoo search algorithm. The proposed algorithm is balancing between the global exploration of the Cuckoo search algorithm and the deep exploitation of the Nelder-Mead method. We test HCSNM algorithm on seven integer programming problems and ten minimax problems and compare against eight algorithms for solving integer programming problems and seven algorithms for solving minimax problems. The experiments results show the efficiency of the proposed algorithm and its ability to solve integer and minimax optimization problems in reasonable time.
Algorithms to detect multiprotein modularity conserved during evolution.
Hodgkinson, Luqman; Karp, Richard M
2012-01-01
Detecting essential multiprotein modules that change infrequently during evolution is a challenging algorithmic task that is important for understanding the structure, function, and evolution of the biological cell. In this paper, we define a measure of modularity for interactomes and present a linear-time algorithm, Produles, for detecting multiprotein modularity conserved during evolution that improves on the running time of previous algorithms for related problems and offers desirable theoretical guarantees. We present a biologically motivated graph theoretic set of evaluation measures complementary to previous evaluation measures, demonstrate that Produles exhibits good performance by all measures, and describe certain recurrent anomalies in the performance of previous algorithms that are not detected by previous measures. Consideration of the newly defined measures and algorithm performance on these measures leads to useful insights on the nature of interactomics data and the goals of previous and current algorithms. Through randomization experiments, we demonstrate that conserved modularity is a defining characteristic of interactomes. Computational experiments on current experimentally derived interactomes for Homo sapiens and Drosophila melanogaster, combining results across algorithms, show that nearly 10 percent of current interactome proteins participate in multiprotein modules with good evidence in the protein interaction data of being conserved between human and Drosophila.
Designing experiments through compressed sensing.
Young, Joseph G.; Ridzal, Denis
2013-06-01
In the following paper, we discuss how to design an ensemble of experiments through the use of compressed sensing. Specifically, we show how to conduct a small number of physical experiments and then use compressed sensing to reconstruct a larger set of data. In order to accomplish this, we organize our results into four sections. We begin by extending the theory of compressed sensing to a finite product of Hilbert spaces. Then, we show how these results apply to experiment design. Next, we develop an efficient reconstruction algorithm that allows us to reconstruct experimental data projected onto a finite element basis. Finally, we verify our approach with two computational experiments.
Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di
2015-01-01
In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy.
Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di
2015-01-01
In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy. PMID:26366164
Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di
2015-01-01
In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy. PMID:26366164
A compilation of jet finding algorithms
Flaugher, B.; Meier, K.
1992-12-31
Technical descriptions of jet finding algorithms currently in use in p{anti p} collider experiments (CDF, UA1, UA2), e{sup +}e{sup {minus}} experiments and Monte-Carlo event generators (LUND programs, ISAJET) have been collected. For the hadron collider experiments, the clustering methods fall into two categories: cone algorithms and nearest-neighbor algorithms. In addition, UA2 has employed a combination of both methods for some analysis. While there are clearly differences between the cone and nearest-neighbor algorithms, the authors have found that there are also differences among the cone algorithms in the details of how the centroid of a cone cluster is located and how the E{sub T} and P{sub T} of the jet are defined. The most commonly used jet algorithm in electron-positron experiments is the JADE-type cluster algorithm. Five various incarnations of this approach have been described.
NASA Technical Reports Server (NTRS)
Barth, Timothy J.; Lomax, Harvard
1987-01-01
The past decade has seen considerable activity in algorithm development for the Navier-Stokes equations. This has resulted in a wide variety of useful new techniques. Some examples for the numerical solution of the Navier-Stokes equations are presented, divided into two parts. One is devoted to the incompressible Navier-Stokes equations, and the other to the compressible form.
Kernel MAD Algorithm for Relative Radiometric Normalization
NASA Astrophysics Data System (ADS)
Bai, Yang; Tang, Ping; Hu, Changmiao
2016-06-01
The multivariate alteration detection (MAD) algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA) which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA). The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1) data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.
Schmogrow, R; Nebendahl, B; Josten, A; Schindler, P C; Koos, C; Freude, W; Leuthold, J
2014-04-21
Efficient algorithms for timing, carrier frequency and phase recovery of Nyquist and OFDM signals are introduced and experimentally verified. The algorithms exploit the statistical properties of the received signals to efficiently derive the optimum sampling time, the carrier frequency offset, and the carrier phase. Among the proposed methods, the mean modulus algorithm (MMA) shows a very robust performance at reduced computational complexity. This is especially important for optical communications where data rates can exceed 100 Gbit/s per wavelength. All proposed algorithms are verified by simulations and by experiments using optical M-ary QAM Nyquist and OFDM signals with data rates up to 84 Gbit/s.
Application of watersheds algorithms to train wheel tread check and measure systems
NASA Astrophysics Data System (ADS)
Shen, Bangxing; Zhang, Haibo; Wang, Wei
2006-11-01
A image system and a new kind of image processing algorithm (watersheds algorithm) are introduced; First, we get the prime wheel tread data by a Charge Coupled Device (CCD), after the pretreatment of the data, we use the watersheds algorithm to get the trail wheel abrasion and peel off strips, than we will get the numerical value of the damage. The result of the experiment shows that the system can obtain the edge of the trail wheel abrasion and peel off strips; the algorithm is fast, stable and anti-jamming; the recognition system can satisfy the manufactory requirements.
Analysis and applications of a general boresight algorithm for the DSS-13 beam waveguide antenna
NASA Technical Reports Server (NTRS)
Alvarez, L. S.
1992-01-01
A general antenna beam boresight algorithm is presented. Equations for axial pointing error, peak received signal level, and antenna half-power beamwidth are given. A pointing error variance equation is derived that illustrates the dependence of the measurement estimation performance on the various algorithm inputs, including RF signal level uncertainty. Plots showing pointing error uncertainty as function of algorithm inputs are presented. Insight gained from the performance analysis is discussed in terms of its application to the areas of antenna controller and receiver interfacing, pointing error compensation, and antenna calibrations. Current and planned applications of the boresight algorithm, including its role in the upcoming Ka-band downlink experiment (KABLE), are highlighted.
A multi-level solution algorithm for steady-state Markov chains
NASA Technical Reports Server (NTRS)
Horton, Graham; Leutenegger, Scott T.
1993-01-01
A new iterative algorithm, the multi-level algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial differential equations. Initial results of numerical experiments are reported, showing significant reductions in computation time, often an order of magnitude or more, relative to the Gauss-Seidel and optimal SOR algorithms for a variety of test problems. The multi-level method is compared and contrasted with the iterative aggregation-disaggregation algorithm of Takahashi.
On algorithmic rate-coded AER generation.
Linares-Barranco, Alejandro; Jimenez-Moreno, Gabriel; Linares-Barranco, Bernabé; Civit-Balcells, Antón
2006-05-01
This paper addresses the problem of converting a conventional video stream based on sequences of frames into the spike event-based representation known as the address-event-representation (AER). In this paper we concentrate on rate-coded AER. The problem is addressed as an algorithmic problem, in which different methods are proposed, implemented and tested through software algorithms. The proposed algorithms are comparatively evaluated according to different criteria. Emphasis is put on the potential of such algorithms for a) doing the frame-based to event-based representation in real time, and b) that the resulting event streams ressemble as much as possible those generated naturally by rate-coded address-event VLSI chips, such as silicon AER retinae. It is found that simple and straightforward algorithms tend to have high potential for real time but produce event distributions that differ considerably from those obtained in AER VLSI chips. On the other hand, sophisticated algorithms that yield better event distributions are not efficient for real time operations. The methods based on linear-feedback-shift-register (LFSR) pseudorandom number generation is a good compromise, which is feasible for real time and yield reasonably well distributed events in time. Our software experiments, on a 1.6-GHz Pentium IV, show that at 50% AER bus load the proposed algorithms require between 0.011 and 1.14 ms per 8 bit-pixel per frame. One of the proposed LFSR methods is implemented in real time hardware using a prototyping board that includes a VirtexE 300 FPGA. The demonstration hardware is capable of transforming frames of 64 x 64 pixels of 8-bit depth at a frame rate of 25 frames per second, producing spike events at a peak rate of 10(7) events per second. PMID:16722179
Evolutionary pattern search algorithms
Hart, W.E.
1995-09-19
This paper defines a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolutionary strategie and real-coded genetic algorithms. EPSAs are self-adapting systems that modify the step size of the mutation operator in response to the success of previous optimization steps. The rule used to adapt the step size can be used to provide a stationary point convergence theory for EPSAs on any continuous function. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods. An experimental analysis of the performance of EPSAs demonstrates that these algorithms can perform a level of global search that is comparable to that of canonical EAs. We also describe a stopping rule for EPSAs, which reliably terminated near stationary points in our experiments. This is the first stopping rule for any class of EAs that can terminate at a given distance from stationary points.
Study of image matching algorithm and sub-pixel fitting algorithm in target tracking
NASA Astrophysics Data System (ADS)
Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu
2015-03-01
Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image
Compound algorithm for restoration of heavy turbulence-degraded image for space target
NASA Astrophysics Data System (ADS)
Wang, Liang-liang; Wang, Ru-jie; Li, Ming; Kang, Zi-qian; Xu, Xiao-qin; Gao, Xin
2012-11-01
Restoration of atmospheric turbulence degraded image is needed to be solved as soon as possible in the field of astronomical space technology. Owing to the fact that the point spread function of turbulence is unknown, changeable with time, hard to be described by mathematics models, withal, kinds of noises would be brought during the imaging processes (such as sensor noise), the image for space target is edge blurred and heavy noised, which making a single restoration algorithm to reach the requirement of restoration difficult. Focusing the fact that the image for space target which was fetched during observation by ground-based optical telescopes is heavy noisy turbulence degraded, this paper discusses the adjustment and reformation of various algorithm structures as well as the selection of various parameters, after the combination of the nonlinear filter algorithm based on noise spatial characteristics, restoration algorithm of heavy turbulence degrade image for space target based on regularization, and the statistics theory based EM restoration algorithm. In order to test the validity of the algorithm, a series of restoration experiments are performed on the heavy noisy turbulence-degraded images for space target. The experiment results show that the new compound algorithm can achieve noise restriction and detail preservation simultaneously, which is effective and practical. Withal, the definition measures and relative definition measures show that the new compound algorithm is better than the traditional algorithms.
An improved HMM/SVM dynamic hand gesture recognition algorithm
NASA Astrophysics Data System (ADS)
Zhang, Yi; Yao, Yuanyuan; Luo, Yuan
2015-10-01
In order to improve the recognition rate and stability of dynamic hand gesture recognition, for the low accuracy rate of the classical HMM algorithm in train the B parameter, this paper proposed an improved HMM/SVM dynamic gesture recognition algorithm. In the calculation of the B parameter of HMM model, this paper introduced the SVM algorithm which has the strong ability of classification. Through the sigmoid function converted the state output of the SVM into the probability and treat this probability as the observation state transition probability of the HMM model. After this, it optimized the B parameter of HMM model and improved the recognition rate of the system. At the same time, it also enhanced the accuracy and the real-time performance of the human-computer interaction. Experiments show that this algorithm has a strong robustness under the complex background environment and the varying illumination environment. The average recognition rate increased from 86.4% to 97.55%.
An improved robust ADMM algorithm for quantum state tomography
NASA Astrophysics Data System (ADS)
Li, Kezhi; Zhang, Hui; Kuang, Sen; Meng, Fangfang; Cong, Shuang
2016-06-01
In this paper, an improved adaptive weights alternating direction method of multipliers algorithm is developed to implement the optimization scheme for recovering the quantum state in nearly pure states. The proposed approach is superior to many existing methods because it exploits the low-rank property of density matrices, and it can deal with unexpected sparse outliers as well. The numerical experiments are provided to verify our statements by comparing the results to three different optimization algorithms, using both adaptive and fixed weights in the algorithm, in the cases of with and without external noise, respectively. The results indicate that the improved algorithm has better performances in both estimation accuracy and robustness to external noise. The further simulation results show that the successful recovery rate increases when more qubits are estimated, which in fact satisfies the compressive sensing theory and makes the proposed approach more promising.
Algorithm aversion: people erroneously avoid algorithms after seeing them err.
Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade
2015-02-01
Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.
Design of experiments in Biomedical Signal Processing Course.
Li, Ling; Li, Bin
2008-01-01
Biomedical Signal Processing is one of the most important major subjects in Biomedical Engineering. The contents of Biomedical Signal Processing include the theories of digital signal processing, the knowledge of different biomedical signals, physiology and the ability of computer programming. Based on our past five years teaching experiences, in order to let students master the signal processing algorithm well, we found that the design of experiments following algorithm was very important. In this paper we presented the ideas and aims in designing the experiments. The results showed that our methods facilitated the study of abstractive signal processing algorithms and made understanding of biomedical signals in a simple way.
Plan Showing Cross Bracing Under Upper Stringers, Typical Section Showing ...
Plan Showing Cross Bracing Under Upper Stringers, Typical Section Showing End Framing, Plan Showing Cross Bracing Under Lower Stringers, End Elevation - Covered Bridge, Spanning Contoocook River, Hopkinton, Merrimack County, NH
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.
Algorithm Visualization in Teaching Practice
ERIC Educational Resources Information Center
Törley, Gábor
2014-01-01
This paper presents the history of algorithm visualization (AV), highlighting teaching-methodology aspects. A combined, two-group pedagogical experiment will be presented as well, which measured the efficiency and the impact on the abstract thinking of AV. According to the results, students, who learned with AV, performed better in the experiment.
Temperature Corrected Bootstrap Algorithm
NASA Technical Reports Server (NTRS)
Comiso, Joey C.; Zwally, H. Jay
1997-01-01
A temperature corrected Bootstrap Algorithm has been developed using Nimbus-7 Scanning Multichannel Microwave Radiometer data in preparation to the upcoming AMSR instrument aboard ADEOS and EOS-PM. The procedure first calculates the effective surface emissivity using emissivities of ice and water at 6 GHz and a mixing formulation that utilizes ice concentrations derived using the current Bootstrap algorithm but using brightness temperatures from 6 GHz and 37 GHz channels. These effective emissivities are then used to calculate surface ice which in turn are used to convert the 18 GHz and 37 GHz brightness temperatures to emissivities. Ice concentrations are then derived using the same technique as with the Bootstrap algorithm but using emissivities instead of brightness temperatures. The results show significant improvement in the area where ice temperature is expected to vary considerably such as near the continental areas in the Antarctic, where the ice temperature is colder than average, and in marginal ice zones.
Power spectral estimation algorithms
NASA Technical Reports Server (NTRS)
Bhatia, Manjit S.
1989-01-01
Algorithms to estimate the power spectrum using Maximum Entropy Methods were developed. These algorithms were coded in FORTRAN 77 and were implemented on the VAX 780. The important considerations in this analysis are: (1) resolution, i.e., how close in frequency two spectral components can be spaced and still be identified; (2) dynamic range, i.e., how small a spectral peak can be, relative to the largest, and still be observed in the spectra; and (3) variance, i.e., how accurate the estimate of the spectra is to the actual spectra. The application of the algorithms based on Maximum Entropy Methods to a variety of data shows that these criteria are met quite well. Additional work in this direction would help confirm the findings. All of the software developed was turned over to the technical monitor. A copy of a typical program is included. Some of the actual data and graphs used on this data are also included.
Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.
Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo
2014-01-01
Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.
A pegging algorithm for separable continuous nonlinear knapsack problems with box constraints
NASA Astrophysics Data System (ADS)
Kim, Gitae; Wu, Chih-Hang
2012-10-01
This article proposes an efficient pegging algorithm for solving separable continuous nonlinear knapsack problems with box constraints. A well-known pegging algorithm for solving this problem is the Bitran-Hax algorithm, a preferred choice for large-scale problems. However, at each iteration, it must calculate an optimal dual variable and update all free primal variables, which is time consuming. The proposed algorithm checks the box constraints implicitly using the bounds on the Lagrange multiplier without explicitly calculating primal variables at each iteration as well as updating the dual solution in a more efficient manner. Results of computational experiments have shown that the proposed algorithm consistently outperforms the Bitran-Hax in all baseline testing and two real-time application models. The proposed algorithm shows significant potential for many other mathematical models in real-world applications with straightforward extensions.
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS.
NASA Astrophysics Data System (ADS)
Nawi, Nazri Mohd.; Khan, Abdullah; Rehman, M. Z.
2015-05-01
A nature inspired behavior metaheuristic techniques which provide derivative-free solutions to solve complex problems. One of the latest additions to the group of nature inspired optimization procedure is Cuckoo Search (CS) algorithm. Artificial Neural Network (ANN) training is an optimization task since it is desired to find optimal weight set of a neural network in training process. Traditional training algorithms have some limitation such as getting trapped in local minima and slow convergence rate. This study proposed a new technique CSLM by combining the best features of two known algorithms back-propagation (BP) and Levenberg Marquardt algorithm (LM) for improving the convergence speed of ANN training and avoiding local minima problem by training this network. Some selected benchmark classification datasets are used for simulation. The experiment result show that the proposed cuckoo search with Levenberg Marquardt algorithm has better performance than other algorithm used in this study.
Dynamically Incremental K-means++ Clustering Algorithm Based on Fuzzy Rough Set Theory
NASA Astrophysics Data System (ADS)
Li, Wei; Wang, Rujing; Jia, Xiufang; Jiang, Qing
Being classic K-means++ clustering algorithm only for static data, dynamically incremental K-means++ clustering algorithm (DK-Means++) is presented based on fuzzy rough set theory in this paper. Firstly, in DK-Means++ clustering algorithm, the formula of similar degree is improved by weights computed by using of the important degree of attributes which are reduced on the basis of rough fuzzy set theory. Secondly, new data only need match granular which was clustered by K-means++ algorithm or seldom new data is clustered by classic K-means++ algorithm in global data. In this way, that all data is re-clustered each time in dynamic data set is avoided, so the efficiency of clustering is improved. Throughout our experiments showing, DK-Means++ algorithm can objectively and efficiently deal with clustering problem of dynamically incremental data.
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS. PMID:26445048
Nicolini, G.; Clivio, A.; Vanetti, E.; Cozzi, L.; Fogliata, A.; Krauss, H.; Fenoglietto, P.
2013-11-15
Purpose: To demonstrate the feasibility of portal dosimetry with an amorphous silicon mega voltage imager for flattening filter free (FFF) photon beams by means of the GLAaS methodology and to validate it for pretreatment quality assurance of volumetric modulated arc therapy (RapidArc).Methods: The GLAaS algorithm, developed for flattened beams, was applied to FFF beams of nominal energy of 6 and 10 MV generated by a Varian TrueBeam (TB). The amorphous silicon electronic portal imager [named mega voltage imager (MVI) on TB] was used to generate integrated images that were converted into matrices of absorbed dose to water. To enable GLAaS use under the increased dose-per-pulse and dose-rate conditions of the FFF beams, new operational source-detector-distance (SDD) was identified to solve detector saturation issues. Empirical corrections were defined to account for the shape of the profiles of the FFF beams to expand the original methodology of beam profile and arm backscattering correction. GLAaS for FFF beams was validated on pretreatment verification of RapidArc plans for three different TB linacs. In addition, the first pretreatment results from clinical experience on 74 arcs were reported in terms of γ analysis.Results: MVI saturates at 100 cm SDD for FFF beams but this can be avoided if images are acquired at 150 cm for all nominal dose rates of FFF beams. Rotational stability of the gantry-imager system was tested and resulted in a minimal apparent imager displacement during rotation of 0.2 ± 0.2 mm at SDD = 150 cm. The accuracy of this approach was tested with three different Varian TrueBeam linacs from different institutes. Data were stratified per energy and machine and showed no dependence with beam quality and MLC model. The results from clinical pretreatment quality assurance, provided a gamma agreement index (GAI) in the field area for six and ten FFF beams of (99.8 ± 0.3)% and (99.5 ± 0.6)% with distance to agreement and dose difference criteria
Optimisation of nonlinear motion cueing algorithm based on genetic algorithm
NASA Astrophysics Data System (ADS)
Asadi, Houshyar; Mohamed, Shady; Rahim Zadeh, Delpak; Nahavandi, Saeid
2015-04-01
Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching
Ozone differential absorption lidar algorithm intercomparison.
Godin, S; Carswell, A I; Donovan, D P; Claude, H; Steinbrecht, W; McDermid, I S; McGee, T J; Gross, M R; Nakane, H; Swart, D P; Bergwerff, H B; Uchino, O; von der Gathen, P; Neuber, R
1999-10-20
An intercomparison of ozone differential absorption lidar algorithms was performed in 1996 within the framework of the Network for the Detection of Stratospheric Changes (NDSC) lidar working group. The objective of this research was mainly to test the differentiating techniques used by the various lidar teams involved in the NDSC for the calculation of the ozone number density from the lidar signals. The exercise consisted of processing synthetic lidar signals computed from simple Rayleigh scattering and three initial ozone profiles. Two of these profiles contained perturbations in the low and the high stratosphere to test the vertical resolution of the various algorithms. For the unperturbed profiles the results of the simulations show the correct behavior of the lidar processing methods in the low and the middle stratosphere with biases of less than 1% with respect to the initial profile to as high as 30 km in most cases. In the upper stratosphere, significant biases reaching 10% at 45 km for most of the algorithms are obtained. This bias is due to the decrease in the signal-to-noise ratio with altitude, which makes it necessary to increase the number of points of the derivative low-pass filter used for data processing. As a consequence the response of the various retrieval algorithms to perturbations in the ozone profile is much better in the lower stratosphere than in the higher range. These results show the necessity of limiting the vertical smoothing in the ozone lidar retrieval algorithm and questions the ability of current lidar systems to detect long-term ozone trends above 40 km. Otherwise the simulations show in general a correct estimation of the ozone profile random error and, as shown by the tests involving the perturbed ozone profiles, some inconsistency in the estimation of the vertical resolution among the lidar teams involved in this experiment.
Fast, Parallel and Secure Cryptography Algorithm Using Lorenz's Attractor
NASA Astrophysics Data System (ADS)
Marco, Anderson Gonçalves; Martinez, Alexandre Souto; Bruno, Odemir Martinez
A novel cryptography method based on the Lorenz's attractor chaotic system is presented. The proposed algorithm is secure and fast, making it practical for general use. We introduce the chaotic operation mode, which provides an interaction among the password, message and a chaotic system. It ensures that the algorithm yields a secure codification, even if the nature of the chaotic system is known. The algorithm has been implemented in two versions: one sequential and slow and the other, parallel and fast. Our algorithm assures the integrity of the ciphertext (we know if it has been altered, which is not assured by traditional algorithms) and consequently its authenticity. Numerical experiments are presented, discussed and show the behavior of the method in terms of security and performance. The fast version of the algorithm has a performance comparable to AES, a popular cryptography program used commercially nowadays, but it is more secure, which makes it immediately suitable for general purpose cryptography applications. An internet page has been set up, which enables the readers to test the algorithm and also to try to break into the cipher.
An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones.
Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han
2015-12-11
Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel "quasi-dynamic" Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the "process-level" fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.
An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones.
Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han
2015-01-01
Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel "quasi-dynamic" Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the "process-level" fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move. PMID:26690447
An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones
Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han
2015-01-01
Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move. PMID:26690447
An improved particle swarm optimization algorithm for reliability problems.
Wu, Peifeng; Gao, Liqun; Zou, Dexuan; Li, Steven
2011-01-01
An improved particle swarm optimization (IPSO) algorithm is proposed to solve reliability problems in this paper. The IPSO designs two position updating strategies: In the early iterations, each particle flies and searches according to its own best experience with a large probability; in the late iterations, each particle flies and searches according to the fling experience of the most successful particle with a large probability. In addition, the IPSO introduces a mutation operator after position updating, which can not only prevent the IPSO from trapping into the local optimum, but also enhances its space developing ability. Experimental results show that the proposed algorithm has stronger convergence and stability than the other four particle swarm optimization algorithms on solving reliability problems, and that the solutions obtained by the IPSO are better than the previously reported best-known solutions in the recent literature.
Algorithm to optimize transient hot-wire thermal property measurement.
Bran-Anleu, Gabriela; Lavine, Adrienne S; Wirz, Richard E; Kavehpour, H Pirouz
2014-04-01
The transient hot-wire method has been widely used to measure the thermal conductivity of fluids. The ideal working equation is based on the solution of the transient heat conduction equation for an infinite linear heat source assuming no natural convection or thermal end effects. In practice, the assumptions inherent in the model are only valid for a portion of the measurement time. In this study, an algorithm was developed to automatically select the proper data range from a transient hot-wire experiment. Numerical simulations of the experiment were used in order to validate the algorithm. The experimental results show that the developed algorithm can be used to improve the accuracy of thermal conductivity measurements.
Evaluation of Algorithms for Compressing Hyperspectral Data
NASA Technical Reports Server (NTRS)
Cook, Sid; Harsanyi, Joseph; Faber, Vance
2003-01-01
With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.
Lessons from Recessions: Connecticut's Experience Shows Need for Strategic Planning.
ERIC Educational Resources Information Center
Anderes, Thomas K.
1993-01-01
Fiscal crisis in New England has been greater than that of early 1980s; colleges and universities should heed lessons. Presents guidelines extracted from study on organizations that effectively managed cutbacks in programs. Effective strategic planning was based on 8 preconditions that define system's capabilities to identify and react to decline…
DNABIT Compress - Genome compression algorithm.
Rajarajeswari, Pothuraju; Apparao, Allam
2011-01-01
Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.
Improved imaging algorithm for bridge crack detection
NASA Astrophysics Data System (ADS)
Lu, Jingxiao; Song, Pingli; Han, Kaihong
2012-04-01
This paper present an improved imaging algorithm for bridge crack detection, through optimizing the eight-direction Sobel edge detection operator, making the positioning of edge points more accurate than without the optimization, and effectively reducing the false edges information, so as to facilitate follow-up treatment. In calculating the crack geometry characteristics, we use the method of extracting skeleton on single crack length. In order to calculate crack area, we construct the template of area by making logical bitwise AND operation of the crack image. After experiment, the results show errors of the crack detection method and actual manual measurement are within an acceptable range, meet the needs of engineering applications. This algorithm is high-speed and effective for automated crack measurement, it can provide more valid data for proper planning and appropriate performance of the maintenance and rehabilitation processes of bridge.
Genetic Algorithms for Multiple-Choice Problems
NASA Astrophysics Data System (ADS)
Aickelin, Uwe
2010-04-01
This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems.It shows that such information can significantly enhance performance, but that the choice of information and the way it is included are important factors for success.Two multiple-choice problems are considered.The first is constructing a feasible nurse roster that considers as many requests as possible.In the second problem, shops are allocated to locations in a mall subject to constraints and maximising the overall income.Genetic algorithms are chosen for their well-known robustness and ability to solve large and complex discrete optimisation problems.However, a survey of the literature reveals room for further research into generic ways to include constraints into a genetic algorithm framework.Hence, the main theme of this work is to balance feasibility and cost of solutions.In particular, co-operative co-evolution with hierarchical sub-populations, problem structure exploiting repair schemes and indirect genetic algorithms with self-adjusting decoder functions are identified as promising approaches.The research starts by applying standard genetic algorithms to the problems and explaining the failure of such approaches due to epistasis.To overcome this, problem-specific information is added in a variety of ways, some of which are designed to increase the number of feasible solutions found whilst others are intended to improve the quality of such solutions.As well as a theoretical discussion as to the underlying reasons for using each operator,extensive computational experiments are carried out on a variety of data.These show that the indirect approach relies less on problem structure and hence is easier to implement and superior in solution quality.
Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.
Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo
2015-08-01
Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.
Preconditioned Alternating Projection Algorithms for Maximum a Posteriori ECT Reconstruction
Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng
2012-01-01
We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constrain involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the preconditioned alternating projection algorithm. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. PMID:23271835
A consistent-mode indicator for the eigensystem realization algorithm
NASA Technical Reports Server (NTRS)
Pappa, Richard S.; Elliott, Kenny B.; Schenk, Axel
1992-01-01
A new method is described for assessing the consistency of model parameters identified with the Eigensystem Realization Algorithm (ERA). Identification results show varying consistency in practice due to many sources, including high modal density, nonlinearity, and inadequate excitation. Consistency is considered to be a reliable indicator of accuracy. The new method is the culmination of many years of experience in developing a practical implementation of the Eigensystem Realization Algorithm. The effectiveness of the method is illustrated using data from NASA Langley's Controls-Structures-Interaction Evolutionary Model.
8. Detail showing concrete abutment, showing substructure of bridge, specifically ...
8. Detail showing concrete abutment, showing substructure of bridge, specifically west side of arch and substructure. - Presumpscot Falls Bridge, Spanning Presumptscot River at Allen Avenue extension, 0.75 mile west of U.S. Interstate 95, Falmouth, Cumberland County, ME
28. MAP SHOWING LOCATION OF ARVFS FACILITY AS BUILT. SHOWS ...
28. MAP SHOWING LOCATION OF ARVFS FACILITY AS BUILT. SHOWS LINCOLN BOULEVARD, BIG LOST RIVER, AND NAVAL REACTORS FACILITY. F.C. TORKELSON DRAWING NUMBER 842-ARVFS-101-2. DATED OCTOBER 12, 1965. INEL INDEX CODE NUMBER: 075 0101 851 151969. - Idaho National Engineering Laboratory, Advanced Reentry Vehicle Fusing System, Scoville, Butte County, ID
Analysis of multigrid algorithms for nonsymmetric and indefinite elliptic problems
Bramble, J.H.; Pasciak, J.E.; Xu, J.
1988-10-01
We prove some new estimates for the convergence of multigrid algorithms applied to nonsymmetric and indefinite elliptic boundary value problems. We provide results for the so-called 'symmetric' multigrid schemes. We show that for the variable V-script-cycle and the W-script-cycle schemes, multigrid algorithms with any amount of smoothing on the finest grid converge at a rate that is independent of the number of levels or unknowns, provided that the initial grid is sufficiently fine. We show that the V-script-cycle algorithm also converges (under appropriate assumptions on the coarsest grid) but at a rate which may deteriorate as the number of levels increases. This deterioration for the V-script-cycle may occur even in the case of full elliptic regularity. Finally, the results of numerical experiments are given which illustrate the convergence behavior suggested by the theory.
Why is Boris algorithm so good?
Qin, Hong; Zhang, Shuangxi; Xiao, Jianyuan; Liu, Jian; Sun, Yajuan; Tang, William M.
2013-08-15
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this paper, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Why is Boris Algorithm So Good?
et al, Hong Qin
2013-03-03
Due to its excellent long term accuracy, the Boris algorithm is the de facto standard for advancing a charged particle. Despite its popularity, up to now there has been no convincing explanation why the Boris algorithm has this advantageous feature. In this letter, we provide an answer to this question. We show that the Boris algorithm conserves phase space volume, even though it is not symplectic. The global bound on energy error typically associated with symplectic algorithms still holds for the Boris algorithm, making it an effective algorithm for the multi-scale dynamics of plasmas.
Higher-order force gradient symplectic algorithms
NASA Astrophysics Data System (ADS)
Chin, Siu A.; Kidwell, Donald W.
2000-12-01
We show that a recently discovered fourth order symplectic algorithm, which requires one evaluation of force gradient in addition to three evaluations of the force, when iterated to higher order, yielded algorithms that are far superior to similarly iterated higher order algorithms based on the standard Forest-Ruth algorithm. We gauge the accuracy of each algorithm by comparing the step-size independent error functions associated with energy conservation and the rotation of the Laplace-Runge-Lenz vector when solving a highly eccentric Kepler problem. For orders 6, 8, 10, and 12, the new algorithms are approximately a factor of 103, 104, 104, and 105 better.
Self-adapting root-MUSIC algorithm and its real-valued formulation for acoustic vector sensor array
NASA Astrophysics Data System (ADS)
Wang, Peng; Zhang, Guo-jun; Xue, Chen-yang; Zhang, Wen-dong; Xiong, Ji-jun
2012-12-01
In this paper, based on the root-MUSIC algorithm for acoustic pressure sensor array, a new self-adapting root-MUSIC algorithm for acoustic vector sensor array is proposed by self-adaptive selecting the lead orientation vector, and its real-valued formulation by Forward-Backward(FB) smoothing and real-valued inverse covariance matrix is also proposed, which can reduce the computational complexity and distinguish the coherent signals. The simulation experiment results show the better performance of two new algorithm with low Signal-to-Noise (SNR) in direction of arrival (DOA) estimation than traditional MUSIC algorithm, and the experiment results using MEMS vector hydrophone array in lake trails show the engineering practicability of two new algorithms.
Schwarz-Based Algorithms for Compressible Flows
NASA Technical Reports Server (NTRS)
Tidriri, M. D.
1996-01-01
We investigate in this paper the application of Schwarz-based algorithms to compressible flows. First we study the combination of these methods with defect-correction procedures. We then study the effect on the Schwarz-based methods of replacing the explicit treatment of the boundary conditions by an implicit one. In the last part of this paper we study the combination of these methods with Newton-Krylov matrix-free methods. Numerical experiments that show the performance of our approaches are then presented.
Comprehensive eye evaluation algorithm
NASA Astrophysics Data System (ADS)
Agurto, C.; Nemeth, S.; Zamora, G.; Vahtel, M.; Soliz, P.; Barriga, S.
2016-03-01
In recent years, several research groups have developed automatic algorithms to detect diabetic retinopathy (DR) in individuals with diabetes (DM), using digital retinal images. Studies have indicated that diabetics have 1.5 times the annual risk of developing primary open angle glaucoma (POAG) as do people without DM. Moreover, DM patients have 1.8 times the risk for age-related macular degeneration (AMD). Although numerous investigators are developing automatic DR detection algorithms, there have been few successful efforts to create an automatic algorithm that can detect other ocular diseases, such as POAG and AMD. Consequently, our aim in the current study was to develop a comprehensive eye evaluation algorithm that not only detects DR in retinal images, but also automatically identifies glaucoma suspects and AMD by integrating other personal medical information with the retinal features. The proposed system is fully automatic and provides the likelihood of each of the three eye disease. The system was evaluated in two datasets of 104 and 88 diabetic cases. For each eye, we used two non-mydriatic digital color fundus photographs (macula and optic disc centered) and, when available, information about age, duration of diabetes, cataracts, hypertension, gender, and laboratory data. Our results show that the combination of multimodal features can increase the AUC by up to 5%, 7%, and 8% in the detection of AMD, DR, and glaucoma respectively. Marked improvement was achieved when laboratory results were combined with retinal image features.
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
... shows the ranges for blood glucose levels after 8 to 12 hours of fasting (not eating). It shows the normal range and the abnormal ranges that are a sign of prediabetes or diabetes. Plasma Glucose Results (mg/dL)* Diagnosis 70 to 99 ...
Linear Bregman algorithm implemented in parallel GPU
NASA Astrophysics Data System (ADS)
Li, Pengyan; Ke, Jue; Sui, Dong; Wei, Ping
2015-08-01
At present, most compressed sensing (CS) algorithms have poor converging speed, thus are difficult to run on PC. To deal with this issue, we use a parallel GPU, to implement a broadly used compressed sensing algorithm, the Linear Bregman algorithm. Linear iterative Bregman algorithm is a reconstruction algorithm proposed by Osher and Cai. Compared with other CS reconstruction algorithms, the linear Bregman algorithm only involves the vector and matrix multiplication and thresholding operation, and is simpler and more efficient for programming. We use C as a development language and adopt CUDA (Compute Unified Device Architecture) as parallel computing architectures. In this paper, we compared the parallel Bregman algorithm with traditional CPU realized Bregaman algorithm. In addition, we also compared the parallel Bregman algorithm with other CS reconstruction algorithms, such as OMP and TwIST algorithms. Compared with these two algorithms, the result of this paper shows that, the parallel Bregman algorithm needs shorter time, and thus is more convenient for real-time object reconstruction, which is important to people's fast growing demand to information technology.
Benchmarking monthly homogenization algorithms
NASA Astrophysics Data System (ADS)
Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.
2011-08-01
. Training was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.
Hwang, J Y; Kang, J M; Jang, Y W; Kim, H
2004-01-01
Novel algorithm and real-time ambulatory monitoring system for fall detection in elderly people is described. Our system is comprised of accelerometer, tilt sensor and gyroscope. For real-time monitoring, we used Bluetooth. Accelerometer measures kinetic force, tilt sensor and gyroscope estimates body posture. Also, we suggested algorithm using signals which obtained from the system attached to the chest for fall detection. To evaluate our system and algorithm, we experimented on three people aged over 26 years. The experiment of four cases such as forward fall, backward fall, side fall and sit-stand was repeated ten times and the experiment in daily life activity was performed one time to each subject. These experiments showed that our system and algorithm could distinguish between falling and daily life activity. Moreover, the accuracy of fall detection is 96.7%. Our system is especially adapted for long-time and real-time ambulatory monitoring of elderly people in emergency situation.
Texture orientation-based algorithm for detecting infrared maritime targets.
Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai
2015-05-20
Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.
Adaptive bad pixel correction algorithm for IRFPA based on PCNN
NASA Astrophysics Data System (ADS)
Leng, Hanbing; Zhou, Zuofeng; Cao, Jianzhong; Yi, Bo; Yan, Aqi; Zhang, Jian
2013-10-01
Bad pixels and response non-uniformity are the primary obstacles when IRFPA is used in different thermal imaging systems. The bad pixels of IRFPA include fixed bad pixels and random bad pixels. The former is caused by material or manufacture defect and their positions are always fixed, the latter is caused by temperature drift and their positions are always changing. Traditional radiometric calibration-based bad pixel detection and compensation algorithm is only valid to the fixed bad pixels. Scene-based bad pixel correction algorithm is the effective way to eliminate these two kinds of bad pixels. Currently, the most used scene-based bad pixel correction algorithm is based on adaptive median filter (AMF). In this algorithm, bad pixels are regarded as image noise and then be replaced by filtered value. However, missed correction and false correction often happens when AMF is used to handle complex infrared scenes. To solve this problem, a new adaptive bad pixel correction algorithm based on pulse coupled neural networks (PCNN) is proposed. Potential bad pixels are detected by PCNN in the first step, then image sequences are used periodically to confirm the real bad pixels and exclude the false one, finally bad pixels are replaced by the filtered result. With the real infrared images obtained from a camera, the experiment results show the effectiveness of the proposed algorithm.
Scalable Virtual Network Mapping Algorithm for Internet-Scale Networks
NASA Astrophysics Data System (ADS)
Yang, Qiang; Wu, Chunming; Zhang, Min
The proper allocation of network resources from a common physical substrate to a set of virtual networks (VNs) is one of the key technical challenges of network virtualization. While a variety of state-of-the-art algorithms have been proposed in an attempt to address this issue from different facets, the challenge still remains in the context of large-scale networks as the existing solutions mainly perform in a centralized manner which requires maintaining the overall and up-to-date information of the underlying substrate network. This implies the restricted scalability and computational efficiency when the network scale becomes large. This paper tackles the virtual network mapping problem and proposes a novel hierarchical algorithm in conjunction with a substrate network decomposition approach. By appropriately transforming the underlying substrate network into a collection of sub-networks, the hierarchical virtual network mapping algorithm can be carried out through a global virtual network mapping algorithm (GVNMA) and a local virtual network mapping algorithm (LVNMA) operated in the network central server and within individual sub-networks respectively with their cooperation and coordination as necessary. The proposed algorithm is assessed against the centralized approaches through a set of numerical simulation experiments for a range of network scenarios. The results show that the proposed hierarchical approach can be about 5-20 times faster for VN mapping tasks than conventional centralized approaches with acceptable communication overhead between GVNCA and LVNCA for all examined networks, whilst performs almost as well as the centralized solutions.
Meyer, Joerg
2007-01-01
measurement of the top quark mass by the D0 experiment at Fermilab in the dilepton final states. The comparison of the measured top quark masses in different final states allows an important consistency check of the Standard Model. Inconsistent results would be a clear hint of a misinterpretation of the analyzed data set. With the exception of the Higgs boson, all particles predicted by the Standard Model have been found. The search for the Higgs boson is one of the main focuses in high energy physics. The theory section will discuss the close relationship between the physics of the Higgs boson and the top quark.
Satellite Movie Shows Erika Dissipate
This animation of visible and infrared imagery from NOAA's GOES-West satellite from Aug. 27 to 29 shows Tropical Storm Erika move through the Eastern Caribbean Sea and dissipate near eastern Cuba. ...
Improvements of HITS Algorithms for Spam Links
NASA Astrophysics Data System (ADS)
Asano, Yasuhito; Tezuka, Yu; Nishizeki, Takao
The HITS algorithm proposed by Kleinberg is one of the representative methods of scoring Web pages by using hyperlinks. In the days when the algorithm was proposed, most of the pages given high score by the algorithm were really related to a given topic, and hence the algorithm could be used to find related pages. However, the algorithm and the variants including Bharat's improved HITS, abbreviated to BHITS, proposed by Bharat and Henzinger cannot be used to find related pages any more on today's Web, due to an increase of spam links. In this paper, we first propose three methods to find “linkfarms,” that is, sets of spam links forming a densely connected subgraph of a Web graph. We then present an algorithm, called a trust-score algorithm, to give high scores to pages which are not spam pages with a high probability. Combining the three methods and the trust-score algorithm with BHITS, we obtain several variants of the HITS algorithm. We ascertain by experiments that one of them, named TaN+BHITS using the trust-score algorithm and the method of finding linkfarms by employing name servers, is most suitable for finding related pages on today's Web. Our algorithms take time and memory no more than those required by the original HITS algorithm, and can be executed on a PC with a small amount of main memory.
A symbol-map wavelet zero-tree image coding algorithm
NASA Astrophysics Data System (ADS)
Wang, Xiaodong; Liu, Wenyao; Peng, Xiang; Liu, Xiaoli
2008-03-01
A improved SPIHT image compression algorithm called symbol-map zero-tree coding algorithm (SMZTC) is proposed in this paper based on wavelet transform. The SPIHT algorithm is a high efficiency wavelet coefficients coding method and have good image compressing effect, but it has more complexity and need too much memory. The algorithm presented in this paper utilizes two small symbol-maps Mark and FC to store the status of coefficients and zero tree sets during coding procedure so as to reduce the memory requirement. By this strategy, the memory cost is reduced distinctly as well as the scanning speed of coefficients is improved. Those comparison experiments for 512 by 512 images are done with some other zerotree coding algorithms, such as SPIHT, NLS method. During the experiments, the biorthogonal 9/7 lifting wavelet transform is used to image transform. The results of coding experiments show that this algorithm speed of codec is improved significantly, and compression-ratio is almost uniformed with SPIHT algorithm.
Multiprojection algorithms with generalized projections
Censor, J.; Elfving, T.
1994-12-31
Generalized distances give raise to generalized projections onto convex sets. An important question is whether or not one can use, within the same projection algorithm, different types of such generalized projections. This question has practical consequences in the areas of signal detection and image recovery, in situations that can be formulated mathematically as convex feasibility problems. We show here that a simultaneous multiprojection algorithmic scheme converges. Different specific multiprojection algorithms can be derived from our scheme by a judicious choice of the Bregman functions which govern the process. As a by-product of the investigation we also obtain block-iterative schemes for certain kinds of linearly constrained optimization problems.
A maximum power point tracking algorithm for buoy-rope-drum wave energy converters
NASA Astrophysics Data System (ADS)
Wang, J. Q.; Zhang, X. C.; Zhou, Y.; Cui, Z. C.; Zhu, L. S.
2016-08-01
The maximum power point tracking control is the key link to improve the energy conversion efficiency of wave energy converters (WEC). This paper presents a novel variable step size Perturb and Observe maximum power point tracking algorithm with a power classification standard for control of a buoy-rope-drum WEC. The algorithm and simulation model of the buoy-rope-drum WEC are presented in details, as well as simulation experiment results. The results show that the algorithm tracks the maximum power point of the WEC fast and accurately.
The RHSA strategy for the allocation of outbound containers based on the hybrid genetic algorithm
NASA Astrophysics Data System (ADS)
Le, Meilong; Yu, Hang
2013-09-01
Secure storage yard is one of the optimal core goals of container transportation; thus, making the necessary storage arrangements has become the most crucial part of the container terminal management systems (CTMS). This paper investigates a random hybrid stacking algorithm (RHSA) for outbound containers that randomly enter the yard. In the first stage of RHSA, the distribution among blocks was analyzed with respect to the utilization ratio. In the second stage, the optimization of bay configuration was carried out by using the hybrid genetic algorithm. Moreover, an experiment was performed to test the RHSA. The results show that the explored algorithm is useful to increase the efficiency.
Adaptive algorithm for active control of high-amplitude acoustic field in resonator
NASA Astrophysics Data System (ADS)
Červenka, M.; Bednařík, M.; Koníček, P.
2008-06-01
This work is concerned with suppression of nonlinear effects in piston-driven acoustic resonators by means of two-frequency driving technique. An iterative adaptive algorithm is proposed to calculate parameters of the driving signal in order that amplitude of the second harmonics of the acoustic pressure is minimized. Functionality of the algorithm is verified firstly by means of numerical model and secondly, it is used in real computer-controlled experiment. The numerical and experimental results show that the proposed algorithm can be successfully used for generation of high-amplitude shock-free acoustic field in resonators.
Block clustering based on difference of convex functions (DC) programming and DC algorithms.
Le, Hoai Minh; Le Thi, Hoai An; Dinh, Tao Pham; Huynh, Van Ngai
2013-10-01
We investigate difference of convex functions (DC) programming and the DC algorithm (DCA) to solve the block clustering problem in the continuous framework, which traditionally requires solving a hard combinatorial optimization problem. DC reformulation techniques and exact penalty in DC programming are developed to build an appropriate equivalent DC program of the block clustering problem. They lead to an elegant and explicit DCA scheme for the resulting DC program. Computational experiments show the robustness and efficiency of the proposed algorithm and its superiority over standard algorithms such as two-mode K-means, two-mode fuzzy clustering, and block classification EM.
NASA Astrophysics Data System (ADS)
Li, Zhaokun; Cao, Jingtai; Zhao, Xiaohui; Liu, Wei
2015-03-01
A conventional adaptive optics (AO) system is widely used to compensate atmospheric turbulence in free space optical (FSO) communication systems, but wavefront measurements based on phase-conjugation principle are not desired under strong scintillation circumstances. In this study we propose a novel swarm intelligence optimization algorithm, which is called modified shuffled frog leaping algorithm (MSFL), to compensate the wavefront aberration. Simulation and experiments results show that MSFL algorithm performs well in the atmospheric compensation and it can increase the coupling efficiency in receiver terminal and significantly improve the performance of the FSO communication systems.
NASA Astrophysics Data System (ADS)
Lopez-Baeza, Ernesto; Wigneron, Jean-Pierre; Schwank, Mike; Miernecki, Maciej; Kerr, Yann; Casal, Tania; Delwart, Steven; Fernandez-Moran, Roberto; Mecklenburg, Susanne; Coll Pajaron, M. Amparo; Salgado Hernanz, Paula
The main activity of the Valencia Anchor Station (VAS) is currently now to support the validation of SMOS (Soil Moisture and Ocean Salinity) Level 2 and 3 land products (soil moisture, SM, and vegetation optical depth, TAU). With this aim, the European Space Agency (ESA) has provided the Climatology from Satellites Group of the University of Valencia with an ELBARA-II microwave radiometer under a loan agreement since September 2009. During this time, brightness temperatures (TB) have continuously been acquired, except during normal maintenance or minor repair interruptions. ELBARA-II is an L-band dual-polarization radiometer with two channels (1400-1418 MHz, 1409-1427 MHz). It is continuously measuring over a vineyard field (El Renegado, Caudete de las Fuentes, Valencia) from a 15 m platform with a constant protocol for calibration and angular scanning measurements with the aim to assisting the validation of SMOS land products and the calibration of the L-MEB (L-Band Emission of the Biosphere) -basis for the SMOS Level 2 Land Processor- over the VAS validation site. One of the advantages of using the VAS site is the possibility of studying two different environmental conditions along the year. While the vine cycle extends mainly between April and October, during the rest of the year the area remains under bare soil conditions, adequate for the calibration of the soil model. The measurement protocol currently running has shown to be robust during the whole operation time and will be extended in time as much as possible to continue providing a long-term data set of ELBARA-II TB measurements and retrieved SM and TAU. This data set is also showing to be useful in support of SMOS scientific activities: the VAS area and, specifically the ELBARA-II site, offer good conditions to control the long-term evolution of SMOS Level 2 and Level 3 land products and interpret eventual anomalies that may obscure sensor hidden biases. In addition, SM and TAU that are currently
National Orange Show Photovoltaic Demonstration
Dan Jimenez Sheri Raborn, CPA; Tom Baker
2008-03-31
National Orange Show Photovoltaic Demonstration created a 400KW Photovoltaic self-generation plant at the National Orange Show Events Center (NOS). The NOS owns a 120-acre state fairground where it operates an events center and produces an annual citrus fair known as the Orange Show. The NOS governing board wanted to employ cost-saving programs for annual energy expenses. It is hoped the Photovoltaic program will result in overall savings for the NOS, help reduce the State's energy demands as relating to electrical power consumption, improve quality of life within the affected grid area as well as increase the energy efficiency of buildings at our venue. In addition, the potential to reduce operational expenses would have a tremendous effect on the ability of the NOS to service its community.
Greedy heuristic algorithm for solving series of eee components classification problems*
NASA Astrophysics Data System (ADS)
Kazakovtsev, A. L.; Antamoshkin, A. N.; Fedosov, V. V.
2016-04-01
Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE device and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem.
A Community Detection Algorithm Based on Topology Potential and Spectral Clustering
Wang, Zhixiao; Chen, Zhaotong; Zhao, Ya; Chen, Shaoda
2014-01-01
Community detection is of great value for complex networks in understanding their inherent law and predicting their behavior. Spectral clustering algorithms have been successfully applied in community detection. This kind of methods has two inadequacies: one is that the input matrixes they used cannot provide sufficient structural information for community detection and the other is that they cannot necessarily derive the proper community number from the ladder distribution of eigenvector elements. In order to solve these problems, this paper puts forward a novel community detection algorithm based on topology potential and spectral clustering. The new algorithm constructs the normalized Laplacian matrix with nodes' topology potential, which contains rich structural information of the network. In addition, the new algorithm can automatically get the optimal community number from the local maximum potential nodes. Experiments results showed that the new algorithm gave excellent performance on artificial networks and real world networks and outperforms other community detection methods. PMID:25147846
An enhancement algorithm for low quality fingerprint image based on edge filter and Gabor filter
NASA Astrophysics Data System (ADS)
Xue, Jun-tao; Liu, Jie; Liu, Zheng-guang
2009-07-01
On account of restriction of man-made and collection environment, the fingerprint image generally has low quality, especially a contaminated background. In this paper, an enhancement algorithm based on edge filter and Gabor filter is proposed to solve this kind of fingerprint image. Firstly, a gray-based algorithm is used to enhance the edge and segment the image. Then, a multilevel block size method is used to extract the orientation field from segmented fingerprint image. Finally, Gabor filter is used to fulfill the enhancement of the fingerprint image. The experiment results show that the proposed enhancement algorithm is effective than the normal Gabor filter algorithm. The fingerprint image enhance by our algorithm has better enhancement effect, so it is helpful for the subsequent research, such as classification, feature exaction and identification.
A regularization-free Young's modulus reconstruction algorithm for ultrasound elasticity imaging.
Pan, Xiaochang; Gao, Jing; Shao, Jinhua; Luo, Jianwen; Bai, Jing
2013-01-01
Ultrasound elasticity imaging aims to reconstruct the distribution of elastic modulus (e.g., Young's modulus) within biological tissues, since the value of elastic modulus is often related to pathological changes. Currently, most elasticity imaging algorithms face a challenge of choosing the value of the regularization constant. We propose a more applicable algorithm without the need of any regularization. This algorithm is not only simple to use, but has a relatively high accuracy. Our method comprises of a nonrigid registration technique and tissue incompressibility assumption to estimate the two-dimensional (2D) displacement field, and finite element method (FEM) to reconstruct the Young's modulus distribution. Simulation and phantom experiments are performed to evaluate the algorithm. Simulation and phantom results showed that the proposed algorithm can reconstruct the Young's modulus with an accuracy of 63∼85%.
Arches showing UV flaring activity
NASA Technical Reports Server (NTRS)
Fontenla, J. M.
1988-01-01
The UVSP data obtained in the previous maximum activity cycle show the frequent appearance of flaring events in the UV. In many cases these flaring events are characterized by at least two footpoints which show compact impulsive non-simultaneous brightenings and a fainter but clearly observed arch developes between the footpoints. These arches and footpoints are observed in line corresponding to different temperatures, as Lyman alpha, N V, and C IV, and when observed above the limb display large Doppler shifts at some stages. The size of the arches can be larger than 20 arcsec.
Multi-pattern string matching algorithms comparison for intrusion detection system
NASA Astrophysics Data System (ADS)
Hasan, Awsan A.; Rashid, Nur'Aini Abdul; Abdulrazzaq, Atheer A.
2014-12-01
Computer networks are developing exponentially and running at high speeds. With the increasing number of Internet users, computers have become the preferred target for complex attacks that require complex analyses to be detected. The Intrusion detection system (IDS) is created and turned into an important part of any modern network to protect the network from attacks. The IDS relies on string matching algorithms to identify network attacks, but these string matching algorithms consume a considerable amount of IDS processing time, thereby slows down the IDS performance. A new algorithm that can overcome the weakness of the IDS needs to be developed. Improving the multi-pattern matching algorithm ensure that an IDS can work properly and the limitations can be overcome. In this paper, we perform a comparison between our three multi-pattern matching algorithms; MP-KR, MPHQS and MPH-BMH with their corresponding original algorithms Kr, QS and BMH respectively. The experiments show that MPH-QS performs best among the proposed algorithms, followed by MPH-BMH, and MP-KR is the slowest. MPH-QS detects a large number of signature patterns in short time compared to other two algorithms. This finding can prove that the multi-pattern matching algorithms are more efficient in high-speed networks.
Frontal optimization algorithms for multiprocessor computers
Sergienko, I.V.; Gulyanitskii, L.F.
1981-11-01
The authors describe one of the approaches to the construction of locally optimal optimization algorithms on multiprocessor computers. Algorithms of this type, called frontal, have been realized previously on single-processor computers, although this configuration does not fully exploit the specific features of their computational scheme. Experience with a number of practical discrete optimization problems confirms that the frontal algorithms are highly successful even with single-processor computers. 9 references.
Aerosol retrieval experiments in the ESA Aerosol_cci project
NASA Astrophysics Data System (ADS)
Holzer-Popp, T.; de Leeuw, G.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.
2013-03-01
Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010-2013) algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components and their mixing ratios. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data qualitatively by visible analysis of monthly mean AOD maps and quantitatively by comparing global daily gridded satellite data against daily
Create a Polarized Light Show.
ERIC Educational Resources Information Center
Conrad, William H.
1992-01-01
Presents a lesson that introduces students to polarized light using a problem-solving approach. After illustrating the concept using a slinky and poster board with a vertical slot, students solve the problem of creating a polarized light show using Polya's problem-solving methods. (MDH)
Pembrolizumab Shows Promise for NSCLC.
2015-06-01
Data from the KEYNOTE-001 trial show that pembrolizumab improves clinical outcomes for patients with advanced non-small cell lung cancer, and is well tolerated. PD-L1 expression in at least 50% of tumor cells correlated with improved efficacy.
NASA Astrophysics Data System (ADS)
Rao, Sailesh K.; Kollath, T.
1986-07-01
In this paper, we show that every systolic array executes a Regular Iterative Algorithm with a strongly separating hyperplane and conversely, that every such algorithm can be implemented on a systolic array. This characterization provides us with an unified framework for describing the contributions of other authors. It also exposes the relevance of many fundamental concepts that were introduced in the sixties by Hennie, Waite and Karp, Miller and Winograd, to the present day concern of systolic array
An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging.
Van Eyndhoven, Geert; Batenburg, K Joost; Kazantsev, Daniil; Van Nieuwenhove, Vincent; Lee, Peter D; Dobson, Katherine J; Sijbers, Jan
2015-11-01
The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed.
Evaluating and comparing algorithms for respiratory motion prediction.
Ernst, F; Dürichen, R; Schlaefer, A; Schweikard, A
2013-06-01
In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm-which is one of the algorithms currently used in the CyberKnife-is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient's respiratory
Evaluating and comparing algorithms for respiratory motion prediction.
Ernst, F; Dürichen, R; Schlaefer, A; Schweikard, A
2013-06-01
In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm-which is one of the algorithms currently used in the CyberKnife-is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient's respiratory
Experimental study on subaperture testing with iterative triangulation algorithm.
Yan, Lisong; Wang, Xiaokun; Zheng, Ligong; Zeng, Xuefeng; Hu, Haixiang; Zhang, Xuejun
2013-09-23
Applying the iterative triangulation stitching algorithm, we provide an experimental demonstration by testing a Φ120 mm flat mirror, a Φ1450 mm off-axis parabolic mirror and a convex hyperboloid mirror. By comparing the stitching results with the self-examine subaperture, it shows that the reconstruction results are in consistent with that of the subaperture testing. As all the experiments are conducted with a 5-dof adjustment platform with big adjustment errors, it proves that using the above mentioned algorithm, the subaperture stitching can be easily performed without a precise positioning system. In addition, with the algorithm, we accomplish the coordinate unification between the testing and processing that makes it possible to guide the processing by the stitching result.
Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs
Chen, Haijian; Han, Dongmei; Dai, Yonghui; Zhao, Lina
2015-01-01
In recent years, Massive Open Online Courses (MOOCs) are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP) algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM) is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of “C programming language” are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate. PMID:26448738
Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs.
Chen, Haijian; Han, Dongmei; Dai, Yonghui; Zhao, Lina
2015-01-01
In recent years, Massive Open Online Courses (MOOCs) are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP) algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM) is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of "C programming language" are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate. PMID:26448738
Measuring Constraint-Set Utility for Partitional Clustering Algorithms
NASA Technical Reports Server (NTRS)
Davidson, Ian; Wagstaff, Kiri L.; Basu, Sugato
2006-01-01
Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves the performance of a variety of algorithms. However, in most of these experiments, results are averaged over different randomly chosen constraint sets from a given set of labels, thereby masking interesting properties of individual sets. We demonstrate that constraint sets vary significantly in how useful they are for constrained clustering; some constraint sets can actually decrease algorithm performance. We create two quantitative measures, informativeness and coherence, that can be used to identify useful constraint sets. We show that these measures can also help explain differences in performance for four particular constrained clustering algorithms.
A practical O(n log2 n) time algorithm for computing the triplet distance on binary trees.
Sand, Andreas; Brodal, Gerth Stølting; Fagerberg, Rolf; Pedersen, Christian N S; Mailund, Thomas
2013-01-01
The triplet distance is a distance measure that compares two rooted trees on the same set of leaves by enumerating all sub-sets of three leaves and counting how often the induced topologies of the tree are equal or different. We present an algorithm that computes the triplet distance between two rooted binary trees in time O (n log2 n). The algorithm is related to an algorithm for computing the quartet distance between two unrooted binary trees in time O (n log n). While the quartet distance algorithm has a very severe overhead in the asymptotic time complexity that makes it impractical compared to O (n2) time algorithms, we show through experiments that the triplet distance algorithm can be implemented to give a competitive wall-time running time.
NASA Technical Reports Server (NTRS)
2004-01-01
The upper left image in this display is from the panoramic camera on the Mars Exploration Rover Spirit, showing the 'Magic Carpet' region near the rover at Gusev Crater, Mars, on Sol 7, the seventh martian day of its journey (Jan. 10, 2004). The lower image, also from the panoramic camera, is a monochrome (single filter) image of a rock in the 'Magic Carpet' area. Note that colored portions of the rock correlate with extracted spectra shown in the plot to the side. Four different types of materials are shown: the rock itself, the soil in front of the rock, some brighter soil on top of the rock, and some dust that has collected in small recesses on the rock face ('spots'). Each color on the spectra matches a line on the graph, showing how the panoramic camera's different colored filters are used to broadly assess the varying mineral compositions of martian rocks and soils.
Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation
Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi
2015-01-01
Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133
Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation.
Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi
2015-01-01
Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133
Dongarra, J.J.; Hewitt, T.
1985-08-01
This note describes some experiments on simple, dense linear algebra algorithms. These experiments show that the CRAY X-MP is capable of small-grain multitasking arising from standard implementations of LU and Cholesky decomposition. The implementation described here provides the ''fastest'' execution rate for LU decomposition, 718 MFLOPS for a matrix of order 1000.
A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389
Liu, Dong-sheng; Fan, Shu-jiang
2014-01-01
In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity.
Quantitative validation of a new coregistration algorithm
Pickar, R.D.; Esser, P.D.; Pozniakoff, T.A.; Van Heertum, R.L.; Stoddart, H.A. Jr.
1995-08-01
A new coregistration software package, Neuro9OO Image Coregistration software, has been developed specifically for nuclear medicine. With this algorithm, the correlation coefficient is maximized between volumes generated from sets of transaxial slices. No localization markers or segmented surfaces are needed. The coregistration program was evaluated for translational and rotational registration accuracy. A Tc-99m HM-PAO split-dose study (0.53 mCi low dose, L, and 1.01 mCi high dose, H) was simulated with a Hoffman Brain Phantom with five fiducial markers. Translation error was determined by a shift in image centroid, and rotation error was determined by a simplified two-axis approach. Changes in registration accuracy were measured with respect to: (1) slice spacing, using the four different combinations LL, LH, HL, HH, (2) translational and rotational misalignment before coregistration, (3) changes in the step size of the iterative parameters. In all the cases the algorithm converged with only small difference in translation offset, 0 and 0. At 6 nun slice spacing, translational efforts ranged from 0.9 to 2.8 mm (system resolution at 100 mm, 6.8 mm). The converged parameters showed little sensitivity to count density. In addition the correlation coefficient increased with decreasing iterative step size, as expected. From these experiments, the authors found that this algorithm based on the maximization of the correlation coefficient between studies was an accurate way to coregister SPECT brain images.
An enhanced algorithm to estimate BDS satellite's differential code biases
NASA Astrophysics Data System (ADS)
Shi, Chuang; Fan, Lei; Li, Min; Liu, Zhizhao; Gu, Shengfeng; Zhong, Shiming; Song, Weiwei
2016-02-01
This paper proposes an enhanced algorithm to estimate the differential code biases (DCB) on three frequencies of the BeiDou Navigation Satellite System (BDS) satellites. By forming ionospheric observables derived from uncombined precise point positioning and geometry-free linear combination of phase-smoothed range, satellite DCBs are determined together with ionospheric delay that is modeled at each individual station. Specifically, the DCB and ionospheric delay are estimated in a weighted least-squares estimator by considering the precision of ionospheric observables, and a misclosure constraint for different types of satellite DCBs is introduced. This algorithm was tested by GNSS data collected in November and December 2013 from 29 stations of Multi-GNSS Experiment (MGEX) and BeiDou Experimental Tracking Stations. Results show that the proposed algorithm is able to precisely estimate BDS satellite DCBs, where the mean value of day-to-day scattering is about 0.19 ns and the RMS of the difference with respect to MGEX DCB products is about 0.24 ns. In order to make comparison, an existing algorithm based on IGG: Institute of Geodesy and Geophysics, China (IGGDCB), is also used to process the same dataset. Results show that, the DCB difference between results from the enhanced algorithm and the DCB products from Center for Orbit Determination in Europe (CODE) and MGEX is reduced in average by 46 % for GPS satellites and 14 % for BDS satellites, when compared with DCB difference between the results of IGGDCB algorithm and the DCB products from CODE and MGEX. In addition, we find the day-to-day scattering of BDS IGSO satellites is obviously lower than that of GEO and MEO satellites, and a significant bias exists in daily DCB values of GEO satellites comparing with MGEX DCB product. This proposed algorithm also provides a new approach to estimate the satellite DCBs of multiple GNSS systems.
Alternative learning algorithms for feedforward neural networks
Vitela, J.E.
1996-03-01
The efficiency of the back propagation algorithm to train feed forward multilayer neural networks has originated the erroneous belief among many neural networks users, that this is the only possible way to obtain the gradient of the error in this type of networks. The purpose of this paper is to show how alternative algorithms can be obtained within the framework of ordered partial derivatives. Two alternative forward-propagating algorithms are derived in this work which are mathematically equivalent to the BP algorithm. This systematic way of obtaining learning algorithms illustrated with this particular type of neural networks can also be used with other types such as recurrent neural networks.
Sinclair, Michael B
2012-01-05
ShowMe3D is a data visualization graphical user interface specifically designed for use with hyperspectral image obtained from the Hyperspectral Confocal Microscope. The program allows the user to select and display any single image from a three dimensional hyperspectral image stack. By moving a slider control, the user can easily move between images of the stack. The user can zoom into any region of the image. The user can select any pixel or region from the displayed image and display the fluorescence spectrum associated with that pixel or region. The user can define up to 3 spectral filters to apply to the hyperspectral image and view the image as it would appear from a filter-based confocal microscope. The user can also obtain statistics such as intensity average and variance from selected regions.
"Show me" bioethics and politics.
Christopher, Myra J
2007-10-01
Missouri, the "Show Me State," has become the epicenter of several important national public policy debates, including abortion rights, the right to choose and refuse medical treatment, and, most recently, early stem cell research. In this environment, the Center for Practical Bioethics (formerly, Midwest Bioethics Center) emerged and grew. The Center's role in these "cultural wars" is not to advocate for a particular position but to provide well researched and objective information, perspective, and advocacy for the ethical justification of policy positions; and to serve as a neutral convener and provider of a public forum for discussion. In this article, the Center's work on early stem cell research is a case study through which to argue that not only the Center, but also the field of bioethics has a critical role in the politics of public health policy.
2012-01-05
ShowMe3D is a data visualization graphical user interface specifically designed for use with hyperspectral image obtained from the Hyperspectral Confocal Microscope. The program allows the user to select and display any single image from a three dimensional hyperspectral image stack. By moving a slider control, the user can easily move between images of the stack. The user can zoom into any region of the image. The user can select any pixel or region from themore » displayed image and display the fluorescence spectrum associated with that pixel or region. The user can define up to 3 spectral filters to apply to the hyperspectral image and view the image as it would appear from a filter-based confocal microscope. The user can also obtain statistics such as intensity average and variance from selected regions.« less
Library of Continuation Algorithms
2005-03-01
LOCA (Library of Continuation Algorithms) is scientific software written in C++ that provides advanced analysis tools for nonlinear systems. In particular, it provides parameter continuation algorithms. bifurcation tracking algorithms, and drivers for linear stability analysis. The algorithms are aimed at large-scale applications that use Newtons method for their nonlinear solve.
NASA Astrophysics Data System (ADS)
Bolognesi, Tommaso
2011-07-01
In the context of quantum gravity theories, several researchers have proposed causal sets as appropriate discrete models of spacetime. We investigate families of causal sets obtained from two simple models of computation - 2D Turing machines and network mobile automata - that operate on 'high-dimensional' supports, namely 2D arrays of cells and planar graphs, respectively. We study a number of quantitative and qualitative emergent properties of these causal sets, including dimension, curvature and localized structures, or 'particles'. We show how the possibility to detect and separate particles from background space depends on the choice between a global or local view at the causal set. Finally, we spot very rare cases of pseudo-randomness, or deterministic chaos; these exhibit a spontaneous phenomenon of 'causal compartmentation' that appears as a prerequisite for the occurrence of anything of physical interest in the evolution of spacetime.
Multikernel least mean square algorithm.
Tobar, Felipe A; Kung, Sun-Yuan; Mandic, Danilo P
2014-02-01
The multikernel least-mean-square algorithm is introduced for adaptive estimation of vector-valued nonlinear and nonstationary signals. This is achieved by mapping the multivariate input data to a Hilbert space of time-varying vector-valued functions, whose inner products (kernels) are combined in an online fashion. The proposed algorithm is equipped with novel adaptive sparsification criteria ensuring a finite dictionary, and is computationally efficient and suitable for nonstationary environments. We also show the ability of the proposed vector-valued reproducing kernel Hilbert space to serve as a feature space for the class of multikernel least-squares algorithms. The benefits of adaptive multikernel (MK) estimation algorithms are illuminated in the nonlinear multivariate adaptive prediction setting. Simulations on nonlinear inertial body sensor signals and nonstationary real-world wind signals of low, medium, and high dynamic regimes support the approach. PMID:24807027
The Origins of Counting Algorithms
Cantlon, Jessica F.; Piantadosi, Steven T.; Ferrigno, Stephen; Hughes, Kelly D.; Barnard, Allison M.
2015-01-01
Humans’ ability to ‘count’ by verbally labeling discrete quantities is unique in animal cognition. The evolutionary origins of counting algorithms are not understood. We report that non-human primates exhibit a cognitive ability that is algorithmically and logically similar to human counting. Monkeys were given the task of choosing between two food caches. Monkeys saw one cache baited with some number of food items, one item at a time. Then, a second cache was baited with food items, one at a time. At the point when the second set approximately outnumbered the first set, monkeys spontaneously moved to choose the second set even before it was completely baited. Using a novel Bayesian analysis, we show that monkeys used an approximate counting algorithm to increment and compare quantities in sequence. This algorithm is structurally similar to formal counting in humans and thus may have been an important evolutionary precursor to human counting. PMID:25953949
Adaptive Routing Algorithm in Wireless Communication Networks Using Evolutionary Algorithm
NASA Astrophysics Data System (ADS)
Yan, Xuesong; Wu, Qinghua; Cai, Zhihua
At present, mobile communications traffic routing designs are complicated because there are more systems inter-connecting to one another. For example, Mobile Communication in the wireless communication networks has two routing design conditions to consider, i.e. the circuit switching and the packet switching. The problem in the Packet Switching routing design is its use of high-speed transmission link and its dynamic routing nature. In this paper, Evolutionary Algorithms is used to determine the best solution and the shortest communication paths. We developed a Genetic Optimization Process that can help network planners solving the best solutions or the best paths of routing table in wireless communication networks are easily and quickly. From the experiment results can be noted that the evolutionary algorithm not only gets good solutions, but also a more predictable running time when compared to sequential genetic algorithm.
Pea Plants Show Risk Sensitivity.
Dener, Efrat; Kacelnik, Alex; Shemesh, Hagai
2016-07-11
Sensitivity to variability in resources has been documented in humans, primates, birds, and social insects, but the fit between empirical results and the predictions of risk sensitivity theory (RST), which aims to explain this sensitivity in adaptive terms, is weak [1]. RST predicts that agents should switch between risk proneness and risk aversion depending on state and circumstances, especially according to the richness of the least variable option [2]. Unrealistic assumptions about agents' information processing mechanisms and poor knowledge of the extent to which variability imposes specific selection in nature are strong candidates to explain the gap between theory and data. RST's rationale also applies to plants, where it has not hitherto been tested. Given the differences between animals' and plants' information processing mechanisms, such tests should help unravel the conflicts between theory and data. Measuring root growth allocation by split-root pea plants, we show that they favor variability when mean nutrient levels are low and the opposite when they are high, supporting the most widespread RST prediction. However, the combination of non-linear effects of nitrogen availability at local and systemic levels may explain some of these effects as a consequence of mechanisms not necessarily evolved to cope with variance [3, 4]. This resembles animal examples in which properties of perception and learning cause risk sensitivity even though they are not risk adaptations [5]. PMID:27374342
WDM Multicast Tree Construction Algorithms and Their Comparative Evaluations
NASA Astrophysics Data System (ADS)
Makabe, Tsutomu; Mikoshi, Taiju; Takenaka, Toyofumi
We propose novel tree construction algorithms for multicast communication in photonic networks. Since multicast communications consume many more link resources than unicast communications, effective algorithms for route selection and wavelength assignment are required. We propose a novel tree construction algorithm, called the Weighted Steiner Tree (WST) algorithm and a variation of the WST algorithm, called the Composite Weighted Steiner Tree (CWST) algorithm. Because these algorithms are based on the Steiner Tree algorithm, link resources among source and destination pairs tend to be commonly used and link utilization ratios are improved. Because of this, these algorithms can accept many more multicast requests than other multicast tree construction algorithms based on the Dijkstra algorithm. However, under certain delay constraints, the blocking characteristics of the proposed Weighted Steiner Tree algorithm deteriorate since some light paths between source and destinations use many hops and cannot satisfy the delay constraint. In order to adapt the approach to the delay-sensitive environments, we have devised the Composite Weighted Steiner Tree algorithm comprising the Weighted Steiner Tree algorithm and the Dijkstra algorithm for use in a delay constrained environment such as an IPTV application. In this paper, we also give the results of simulation experiments which demonstrate the superiority of the proposed Composite Weighted Steiner Tree algorithm compared with the Distributed Minimum Hop Tree (DMHT) algorithm, from the viewpoint of the light-tree request blocking.
TaDb: A time-aware diffusion-based recommender algorithm
NASA Astrophysics Data System (ADS)
Li, Wen-Jun; Xu, Yuan-Yuan; Dong, Qiang; Zhou, Jun-Lin; Fu, Yan
2015-02-01
Traditional recommender algorithms usually employ the early and recent records indiscriminately, which overlooks the change of user interests over time. In this paper, we show that the interests of a user remain stable in a short-term interval and drift during a long-term period. Based on this observation, we propose a time-aware diffusion-based (TaDb) recommender algorithm, which assigns different temporal weights to the leading links existing before the target user's collection and the following links appearing after that in the diffusion process. Experiments on four real datasets, Netflix, MovieLens, FriendFeed and Delicious show that TaDb algorithm significantly improves the prediction accuracy compared with the algorithms not considering temporal effects.
Breadth-First Search-Based Single-Phase Algorithms for Bridge Detection in Wireless Sensor Networks
Akram, Vahid Khalilpour; Dagdeviren, Orhan
2013-01-01
Wireless sensor networks (WSNs) are promising technologies for exploring harsh environments, such as oceans, wild forests, volcanic regions and outer space. Since sensor nodes may have limited transmission range, application packets may be transmitted by multi-hop communication. Thus, connectivity is a very important issue. A bridge is a critical edge whose removal breaks the connectivity of the network. Hence, it is crucial to detect bridges and take preventions. Since sensor nodes are battery-powered, services running on nodes should consume low energy. In this paper, we propose energy-efficient and distributed bridge detection algorithms for WSNs. Our algorithms run single phase and they are integrated with the Breadth-First Search (BFS) algorithm, which is a popular routing algorithm. Our first algorithm is an extended version of Milic's algorithm, which is designed to reduce the message length. Our second algorithm is novel and uses ancestral knowledge to detect bridges. We explain the operation of the algorithms, analyze their proof of correctness, message, time, space and computational complexities. To evaluate practical importance, we provide testbed experiments and extensive simulations. We show that our proposed algorithms provide less resource consumption, and the energy savings of our algorithms are up by 5.5-times. PMID:23845930
Evaluating and comparing algorithms for respiratory motion prediction
NASA Astrophysics Data System (ADS)
Ernst, F.; Dürichen, R.; Schlaefer, A.; Schweikard, A.
2013-06-01
In robotic radiosurgery, it is necessary to compensate for systematic latencies arising from target tracking and mechanical constraints. This compensation is usually achieved by means of an algorithm which computes the future target position. In most scientific works on respiratory motion prediction, only one or two algorithms are evaluated on a limited amount of very short motion traces. The purpose of this work is to gain more insight into the real world capabilities of respiratory motion prediction methods by evaluating many algorithms on an unprecedented amount of data. We have evaluated six algorithms, the normalized least mean squares (nLMS), recursive least squares (RLS), multi-step linear methods (MULIN), wavelet-based multiscale autoregression (wLMS), extended Kalman filtering, and ε-support vector regression (SVRpred) methods, on an extensive database of 304 respiratory motion traces. The traces were collected during treatment with the CyberKnife (Accuray, Inc., Sunnyvale, CA, USA) and feature an average length of 71 min. Evaluation was done using a graphical prediction toolkit, which is available to the general public, as is the data we used. The experiments show that the nLMS algorithm—which is one of the algorithms currently used in the CyberKnife—is outperformed by all other methods. This is especially true in the case of the wLMS, the SVRpred, and the MULIN algorithms, which perform much better. The nLMS algorithm produces a relative root mean square (RMS) error of 75% or less (i.e., a reduction in error of 25% or more when compared to not doing prediction) in only 38% of the test cases, whereas the MULIN and SVRpred methods reach this level in more than 77%, the wLMS algorithm in more than 84% of the test cases. Our work shows that the wLMS algorithm is the most accurate algorithm and does not require parameter tuning, making it an ideal candidate for clinical implementation. Additionally, we have seen that the structure of a patient
Bader, D A; Moret, B M; Yan, M
2001-01-01
Hannenhalli and Pevzner gave the first polynomial-time algorithm for computing the inversion distance between two signed permutations, as part of the larger task of determining the shortest sequence of inversions needed to transform one permutation into the other. Their algorithm (restricted to distance calculation) proceeds in two stages: in the first stage, the overlap graph induced by the permutation is decomposed into connected components; then, in the second stage, certain graph structures (hurdles and others) are identified. Berman and Hannenhalli avoided the explicit computation of the overlap graph and gave an O(nalpha(n)) algorithm, based on a Union-Find structure, to find its connected components, where alpha is the inverse Ackerman function. Since for all practical purposes alpha(n) is a constant no larger than four, this algorithm has been the fastest practical algorithm to date. In this paper, we present a new linear-time algorithm for computing the connected components, which is more efficient than that of Berman and Hannenhalli in both theory and practice. Our algorithm uses only a stack and is very easy to implement. We give the results of computational experiments over a large range of permutation pairs produced through simulated evolution; our experiments show a speed-up by a factor of 2 to 5 in the computation of the connected components and by a factor of 1.3 to 2 in the overall distance computation.
Multi-objective Emergency Facility Location Problem Based on Genetic Algorithm
NASA Astrophysics Data System (ADS)
Zhao, Dan; Zhao, Yunsheng; Li, Zhenhua; Chen, Jin
Recent years, emergent disasters have occurred frequently. This has attracted more attention on emergency management, especially the multi-objective emergency facility location problem (EFLP), a NP problem. However, few algorithms are efficient to solve the probleme and so the application of genetic algorithm (GA) can be a good choice. This paper first introduces the mathematical models for this problem and transforms it from complex constraints into simple constraints by punishment function. The solutions to the experiments are obtained by applying GA. The experiment results show that GA could solve the problems effectively.
Dynamic Programming Algorithm vs. Genetic Algorithm: Which is Faster?
NASA Astrophysics Data System (ADS)
Petković, Dušan
The article compares two different approaches for the optimization problem of large join queries (LJQs). Almost all commercial database systems use a form of the dynamic programming algorithm to solve the ordering of join operations for large join queries, i.e. joins with more than dozen join operations. The property of the dynamic programming algorithm is that the execution time increases significantly in the case, where the number of join operations in a query is large. Genetic algorithms (GAs), as a data mining technique, have been shown as a promising technique in solving the ordering of join operations in LJQs. Using the existing implementation of GA, we compare the dynamic programming algorithm implemented in commercial database systems with the corresponding GA module. Our results show that the use of a genetic algorithm is a better solution for optimization of large join queries, i.e., that such a technique outperforms the implementations of the dynamic programming algorithm in conventional query optimization components for very large join queries.
NASA Technical Reports Server (NTRS)
2005-01-01
False color images of Saturn's moon, Mimas, reveal variation in either the composition or texture across its surface.
During its approach to Mimas on Aug. 2, 2005, the Cassini spacecraft narrow-angle camera obtained multi-spectral views of the moon from a range of 228,000 kilometers (142,500 miles).
The image at the left is a narrow angle clear-filter image, which was separately processed to enhance the contrast in brightness and sharpness of visible features. The image at the right is a color composite of narrow-angle ultraviolet, green, infrared and clear filter images, which have been specially processed to accentuate subtle changes in the spectral properties of Mimas' surface materials. To create this view, three color images (ultraviolet, green and infrared) were combined into a single black and white picture that isolates and maps regional color differences. This 'color map' was then superimposed over the clear-filter image at the left.
The combination of color map and brightness image shows how the color differences across the Mimas surface materials are tied to geological features. Shades of blue and violet in the image at the right are used to identify surface materials that are bluer in color and have a weaker infrared brightness than average Mimas materials, which are represented by green.
Herschel crater, a 140-kilometer-wide (88-mile) impact feature with a prominent central peak, is visible in the upper right of each image. The unusual bluer materials are seen to broadly surround Herschel crater. However, the bluer material is not uniformly distributed in and around the crater. Instead, it appears to be concentrated on the outside of the crater and more to the west than to the north or south. The origin of the color differences is not yet understood. It may represent ejecta material that was excavated from inside Mimas when the Herschel impact occurred. The bluer color of these materials may be caused by subtle differences in
Computational algorithms to predict Gene Ontology annotations
2015-01-01
Background Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful. Methods We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set. Results We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm. Conclusions Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper
A shape constrained MAP-EM algorithm for colorectal segmentation
NASA Astrophysics Data System (ADS)
Wang, Huafeng; Li, Lihong; Song, Bowen; Han, Fangfang; Liang, Zhengrong
2013-02-01
The task of effectively segmenting colon areas in CT images is an important area of interest in medical imaging field. The ability to distinguish the colon wall in an image from the background is a critical step in several approaches for achieving larger goals in automated computer-aided diagnosis (CAD). The related task of polyp detection, the ability to determine which objects or classes of polyps are present in a scene, also relies on colon wall segmentation. When modeling each tissue type as a conditionally independent Gaussian distribution, the tissue mixture fractions in each voxel via the modeled unobservable random processes of the underlying tissue types can be estimated by maximum a posteriori expectation-maximization (MAP-EM) algorithm in an iterative manner. This paper presents, based on the assumption that the partial volume effect (PVE) could be fully described by a tissue mixture model, a theoretical solution to the MAP-EM segmentation algorithm. However, the MAP-EM algorithm may miss some small regions which also belong to the colon wall. Combining with the shape constrained model, we present an improved algorithm which is able to merge similar regions and reserve fine structures. Experiment results show that the new approach can refine the jagged-like boundaries and achieve better results than merely exploited our previously presented MAP-EM algorithm.
A synthesized heuristic task scheduling algorithm.
Dai, Yanyan; Zhang, Xiangli
2014-01-01
Aiming at the static task scheduling problems in heterogeneous environment, a heuristic task scheduling algorithm named HCPPEFT is proposed. In task prioritizing phase, there are three levels of priority in the algorithm to choose task. First, the critical tasks have the highest priority, secondly the tasks with longer path to exit task will be selected, and then algorithm will choose tasks with less predecessors to schedule. In resource selection phase, the algorithm is selected task duplication to reduce the interresource communication cost, besides forecasting the impact of an assignment for all children of the current task permits better decisions to be made in selecting resources. The algorithm proposed is compared with STDH, PEFT, and HEFT algorithms through randomly generated graphs and sets of task graphs. The experimental results show that the new algorithm can achieve better scheduling performance.
Kaptein, B L; Valstar, E R; Stoel, B C; Rozing, P M; Reiber, J H C
2004-01-01
Model-based roentgen stereophotogrammetric analysis (RSA) uses a three-dimensional surface model of an implant in order to estimate accurately the pose of that implant from a stereo pair of roentgen images. The technique is based on minimization of the difference between the actually projected contour of an implant and the virtually projected contour of a model of that same implant. The advantage of model-based RSA over conventional marker-based RSA is that it is not necessary to attach markers to the implant. In this paper, three pose estimation algorithms for model-based RSA are evaluated. The algorithms were assessed on the basis of their sensitivities to noise in the actual contour, to the amount of drop-outs in the actual contour, to the number of points in the actual contour and to shrinkage or expansion of the actual contour. The algorithms that were studied are the iterative inverse perspective matching (IIPM) algorithm, an algorithm based on minimization of the difference (DIF) between the actual contour and the virtual contour, and an algorithm based on minimization of the non-overlapping area (NOA) between the actual and virtual contour. The results of the simulation and phantom experiments show that the NOA algorithm does not fulfil the high accuracy that is necessary for model-based RSA. The IIPM and DIF algorithms are robust to the different distortions, making model-based RSA a possible replacement for marker-based RSA.
Parallel Directionally Split Solver Based on Reformulation of Pipelined Thomas Algorithm
NASA Technical Reports Server (NTRS)
Povitsky, A.
1998-01-01
In this research an efficient parallel algorithm for 3-D directionally split problems is developed. The proposed algorithm is based on a reformulated version of the pipelined Thomas algorithm that starts the backward step computations immediately after the completion of the forward step computations for the first portion of lines This algorithm has data available for other computational tasks while processors are idle from the Thomas algorithm. The proposed 3-D directionally split solver is based on the static scheduling of processors where local and non-local, data-dependent and data-independent computations are scheduled while processors are idle. A theoretical model of parallelization efficiency is used to define optimal parameters of the algorithm, to show an asymptotic parallelization penalty and to obtain an optimal cover of a global domain with subdomains. It is shown by computational experiments and by the theoretical model that the proposed algorithm reduces the parallelization penalty about two times over the basic algorithm for the range of the number of processors (subdomains) considered and the number of grid nodes per subdomain.
NASA Astrophysics Data System (ADS)
Huang, Yin; Chen, Jianhua; Xiong, Shaojun
2009-07-01
Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.
Ear feature region detection based on a combined image segmentation algorithm-KRM
NASA Astrophysics Data System (ADS)
Jiang, Jingying; Zhang, Hao; Zhang, Qi; Lu, Junsheng; Ma, Zhenhe; Xu, Kexin
2014-02-01
Scale Invariant Feature Transform SIFT algorithm is widely used for ear feature matching and recognition. However, the application of the algorithm is usually interfered by the non-target areas within the whole image, and the interference would then affect the matching and recognition of ear features. To solve this problem, a combined image segmentation algorithm i.e. KRM was introduced in this paper, As the human ear recognition pretreatment method. Firstly, the target areas of ears were extracted by the KRM algorithm and then SIFT algorithm could be applied to the detection and matching of features. The present KRM algorithm follows three steps: (1)the image was preliminarily segmented into foreground target area and background area by using K-means clustering algorithm; (2)Region growing method was used to merge the over-segmented areas; (3)Morphology erosion filtering method was applied to obtain the final segmented regions. The experiment results showed that the KRM method could effectively improve the accuracy and robustness of ear feature matching and recognition based on SIFT algorithm.
Saving Resources with Plagues in Genetic Algorithms
de Vega, F F; Cantu-Paz, E; Lopez, J I; Manzano, T
2004-06-15
The population size of genetic algorithms (GAs) affects the quality of the solutions and the time required to find them. While progress has been made in estimating the population sizes required to reach a desired solution quality for certain problems, in practice the sizing of populations is still usually performed by trial and error. These trials might lead to find a population that is large enough to reach a satisfactory solution, but there may still be opportunities to optimize the computational cost by reducing the size of the population. This paper presents a technique called plague that periodically removes a number of individuals from the population as the GA executes. Recently, the usefulness of the plague has been demonstrated for genetic programming. The objective of this paper is to extend the study of plagues to genetic algorithms. We experiment with deceptive trap functions, a tunable difficult problem for GAs, and the experiments show that plagues can save computational time while maintaining solution quality and reliability.
Software for portable laser light show system
NASA Astrophysics Data System (ADS)
Buruchin, Dmitrey J.; Leonov, Alexander F.
1995-04-01
Portable laser light show system LS-3500-10M is connected to the parallel port of IBM PC/AT compatible computer. Computer performs output of digital control data describing images. Specially designed control device is used to convert digital data coming from parallel port to the analog signal driving scanner. Capabilities of even cost nothing 286 computer are quite enough for laser graphics control. Technology of scanning used in laser graphics system LS-3500-10M essentially differs from widely spread systems based on galvanometers with mobile core or with mobile magnet. Such devices are based on the same principle of work as electrically driven servo-mechanism. As scanner we use elastic system with hydraulic dampen oscillations and opened loop. For most of applications of laser graphics such system provides satisfactory precision and speed of scanning. LS-3500-10M software gives user ability to create on PC and play his own laser graphics demonstrations. It is possible to render recognizable text and pictures using different styles, 3D and abstract animation. All types of demonstrations can be mixed in slide-show. Time synchronization is supported. Software has the following features: (1) Different types of text output. Built-in text editor for typing and editing of textural information. Different fonts can be used to display text. User can create his own fonts using specially developed font editor. (2) Editor of 3D animation with library of predefined shapes. (3) Abstract animation provided by software routines. (4) Support of different graphics files formats (PCX or DXF). Original algorithm of raster image tracing was implemented. (5) Built-in slide-show editor.
Motion object tracking algorithm using multi-cameras
NASA Astrophysics Data System (ADS)
Kong, Xiaofang; Chen, Qian; Gu, Guohua
2015-09-01
Motion object tracking is one of the most important research directions in computer vision. Challenges in designing a robust tracking method are usually caused by partial or complete occlusions on targets. However, motion object tracking algorithm based on multiple cameras according to the homography relation in three views can deal with this issue effectively since the information combining from multiple cameras in different views can make the target more complete and accurate. In this paper, a robust visual tracking algorithm based on the homography relations of three cameras in different views is presented to cope with the occlusion. First of all, being the main contribution of this paper, the motion object tracking algorithm based on the low-rank matrix representation under the framework of the particle filter is applied to track the same target in the public region respectively in different views. The target model and the occlusion model are established and an alternating optimization algorithm is utilized to solve the proposed optimization formulation while tracking. Then, we confirm the plane in which the target has the largest occlusion weight to be the principal plane and calculate the homography to find out the mapping relations between different views. Finally, the images of the other two views are projected into the main plane. By making use of the homography relation between different views, the information of the occluded target can be obtained completely. The proposed algorithm has been examined throughout several challenging image sequences, and experiments show that it overcomes the failure of the motion tracking especially under the situation of the occlusion. Besides, the proposed algorithm improves the accuracy of the motion tracking comparing with other state-of-the-art algorithms.
NASA Astrophysics Data System (ADS)
Zhu, Li; He, Yongxiang; Xue, Haidong; Chen, Leichen
Traditional genetic algorithms (GA) displays a disadvantage of early-constringency in dealing with scheduling problem. To improve the crossover operators and mutation operators self-adaptively, this paper proposes a self-adaptive GA at the target of multitask scheduling optimization under limited resources. The experiment results show that the proposed algorithm outperforms the traditional GA in evolutive ability to deal with complex task scheduling optimization.
New algorithms for binary wavefront optimization
NASA Astrophysics Data System (ADS)
Zhang, Xiaolong; Kner, Peter
2015-03-01
Binary amplitude modulation promises to allow rapid focusing through strongly scattering media with a large number of segments due to the faster update rates of digital micromirror devices (DMDs) compared to spatial light modulators (SLMs). While binary amplitude modulation has a lower theoretical enhancement than phase modulation, the faster update rate should more than compensate for the difference - a factor of π2 /2. Here we present two new algorithms, a genetic algorithm and a transmission matrix algorithm, for optimizing the focus with binary amplitude modulation that achieve enhancements close to the theoretical maximum. Genetic algorithms have been shown to work well in noisy environments and we show that the genetic algorithm performs better than a stepwise algorithm. Transmission matrix algorithms allow complete characterization and control of the medium but require phase control either at the input or output. Here we introduce a transmission matrix algorithm that works with only binary amplitude control and intensity measurements. We apply these algorithms to binary amplitude modulation using a Texas Instruments Digital Micromirror Device. Here we report an enhancement of 152 with 1536 segments (9.90%×N) using a genetic algorithm with binary amplitude modulation and an enhancement of 136 with 1536 segments (8.9%×N) using an intensity-only transmission matrix algorithm.
Interpreting the Standard Division Algorithm in a "Candy Factory" Context
ERIC Educational Resources Information Center
Gregg, Jeff; Gregg, Diana Underwood
2007-01-01
This article discusses the difficulties preservice teachers experience when they try to make sense of the standard long-division algorithm, describes a realistic context that we have found productive in helping our students think about why the algorithm works and the role of place value in the algorithm, and suggests the applicability of this…
Educational Outreach: The Space Science Road Show
NASA Astrophysics Data System (ADS)
Cox, N. L. J.
2002-01-01
The poster presented will give an overview of a study towards a "Space Road Show". The topic of this show is space science. The target group is adolescents, aged 12 to 15, at Dutch high schools. The show and its accompanying experiments would be supported with suitable educational material. Science teachers at schools can decide for themselves if they want to use this material in advance, afterwards or not at all. The aims of this outreach effort are: to motivate students for space science and engineering, to help them understand the importance of (space) research, to give them a positive feeling about the possibilities offered by space and in the process give them useful knowledge on space basics. The show revolves around three main themes: applications, science and society. First the students will get some historical background on the importance of space/astronomy to civilization. Secondly they will learn more about novel uses of space. On the one hand they will learn of "Views on Earth" involving technologies like Remote Sensing (or Spying), Communication, Broadcasting, GPS and Telemedicine. On the other hand they will experience "Views on Space" illustrated by past, present and future space research missions, like the space exploration missions (Cassini/Huygens, Mars Express and Rosetta) and the astronomy missions (Soho and XMM). Meanwhile, the students will learn more about the technology of launchers and satellites needed to accomplish these space missions. Throughout the show and especially towards the end attention will be paid to the third theme "Why go to space"? Other reasons for people to get into space will be explored. An important question in this is the commercial (manned) exploration of space. Thus, the questions of benefit of space to society are integrated in the entire show. It raises some fundamental questions about the effects of space travel on our environment, poverty and other moral issues. The show attempts to connect scientific with
Algorithms for computing and integrating physical maps using unique probes.
Jain, M; Myers, E W
1997-01-01
Current physical mapping projects based on STS-probes involve additional clues such as the fact that some probes are anchored to a known map and that others come from the ends of clones. Because of the disparate combinatorial contributions of these varied data items, it is difficult to design a "tailored" algorithm that incorporates them all. Moreover, it is inevitable that new experiments will provide new kinds of data, making obsolete any such algorithm. We show how to convert the physical mapping problem into a 0/1 linear programming (LP) problem. We further show how one can incorporate additional clues as additional constraints in the LP formulation. We give a simple relaxation of the 0/1 LP problem, which solves problems of the same scale as previously reported tailored algorithms, to equal or greater optimization levels. We also present a theorem proving that when the data is 100% accurate, then the relaxed and integer solutions coincide. The LP algorithm suffices to solve problems on the order of 80-100 probes--the typical size of the 2- or 3-connected contigs of Arratia et al. (1991). We give a heuristic algorithm which attempts to order and link the set of LP-solved contigs. Unlike previous work, this algorithm only links and orders contigs when the join is 90% or more likely to be correct. It is our view that there is no value in computing an optimal solution with respect to some criteria over very noisy data as this optimal solution rarely corresponds to the true solution. The paper involves extensive empirical trials over real and simulated data. PMID:9385539
Reasoning about systolic algorithms
Purushothaman, S.
1986-01-01
Systolic algorithms are a class of parallel algorithms, with small grain concurrency, well suited for implementation in VLSI. They are intended to be implemented as high-performance, computation-bound back-end processors and are characterized by a tesselating interconnection of identical processing elements. This dissertation investigates the problem of providing correctness of systolic algorithms. The following are reported in this dissertation: (1) a methodology for verifying correctness of systolic algorithms based on solving the representation of an algorithm as recurrence equations. The methodology is demonstrated by proving the correctness of a systolic architecture for optimal parenthesization. (2) The implementation of mechanical proofs of correctness of two systolic algorithms, a convolution algorithm and an optimal parenthesization algorithm, using the Boyer-Moore theorem prover. (3) An induction principle for proving correctness of systolic arrays which are modular. Two attendant inference rules, weak equivalence and shift transformation, which capture equivalent behavior of systolic arrays, are also presented.
Algorithm-development activities
NASA Technical Reports Server (NTRS)
Carder, Kendall L.
1994-01-01
The task of algorithm-development activities at USF continues. The algorithm for determining chlorophyll alpha concentration, (Chl alpha) and gelbstoff absorption coefficient for SeaWiFS and MODIS-N radiance data is our current priority.
Noise-enhanced clustering and competitive learning algorithms.
Osoba, Osonde; Kosko, Bart
2013-01-01
Noise can provably speed up convergence in many centroid-based clustering algorithms. This includes the popular k-means clustering algorithm. The clustering noise benefit follows from the general noise benefit for the expectation-maximization algorithm because many clustering algorithms are special cases of the expectation-maximization algorithm. Simulations show that noise also speeds up convergence in stochastic unsupervised competitive learning, supervised competitive learning, and differential competitive learning.
INSENS classification algorithm report
Hernandez, J.E.; Frerking, C.J.; Myers, D.W.
1993-07-28
This report describes a new algorithm developed for the Imigration and Naturalization Service (INS) in support of the INSENS project for classifying vehicles and pedestrians using seismic data. This algorithm is less sensitive to nuisance alarms due to environmental events than the previous algorithm. Furthermore, the algorithm is simple enough that it can be implemented in the 8-bit microprocessor used in the INSENS system.
Accurate Finite Difference Algorithms
NASA Technical Reports Server (NTRS)
Goodrich, John W.
1996-01-01
Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.
Hubble Space Telescope characterized by using phase-retrieval algorithms.
Fienup, J R; Marron, J C; Schulz, T J; Seldin, J H
1993-04-01
We describe several results characterizing the Hubble Space Telescope from measured point spread functions by using phase-retrieval algorithms. The Cramer-Rao lower bounds show that point spread functions taken well out of focus result in smaller errors when aberrations are estimated and that, for those images, photon noise is not a limiting factor. Reconstruction experiments with both simulated and real data show that the calculation of wave-front propagation by the retrieval algorithms must be performed with a multiple-plane propagation rather than a simple fast Fourier transform to ensure the high accuracy required. Pupil reconstruction was performed and indicates a misalignment of the optical axis of a camera relay telescope relative to the main telescope. After we accounted for measured spherical aberration in the relay telescope, our estimate of the conic constant of the primary mirror of the HST was - 1.0144.
Cognitive radio resource allocation based on coupled chaotic genetic algorithm
NASA Astrophysics Data System (ADS)
Zu, Yun-Xiao; Zhou, Jie; Zeng, Chang-Chang
2010-11-01
A coupled chaotic genetic algorithm for cognitive radio resource allocation which is based on genetic algorithm and coupled Logistic map is proposed. A fitness function for cognitive radio resource allocation is provided. Simulations are conducted for cognitive radio resource allocation by using the coupled chaotic genetic algorithm, simple genetic algorithm and dynamic allocation algorithm respectively. The simulation results show that, compared with simple genetic and dynamic allocation algorithm, coupled chaotic genetic algorithm reduces the total transmission power and bit error rate in cognitive radio system, and has faster convergence speed.
Interior search algorithm (ISA): a novel approach for global optimization.
Gandomi, Amir H
2014-07-01
This paper presents the interior search algorithm (ISA) as a novel method for solving optimization tasks. The proposed ISA is inspired by interior design and decoration. The algorithm is different from other metaheuristic algorithms and provides new insight for global optimization. The proposed method is verified using some benchmark mathematical and engineering problems commonly used in the area of optimization. ISA results are further compared with well-known optimization algorithms. The results show that the ISA is efficiently capable of solving optimization problems. The proposed algorithm can outperform the other well-known algorithms. Further, the proposed algorithm is very simple and it only has one parameter to tune.
A Short Survey of Document Structure Similarity Algorithms
Buttler, D
2004-02-27
This paper provides a brief survey of document structural similarity algorithms, including the optimal Tree Edit Distance algorithm and various approximation algorithms. The approximation algorithms include the simple weighted tag similarity algorithm, Fourier transforms of the structure, and a new application of the shingle technique to structural similarity. We show three surprising results. First, the Fourier transform technique proves to be the least accurate of any of approximation algorithms, while also being slowest. Second, optimal Tree Edit Distance algorithms may not be the best technique for clustering pages from different sites. Third, the simplest approximation to structure may be the most effective and efficient mechanism for many applications.
Implementing the Deutsch-Jozsa algorithm with macroscopic ensembles
NASA Astrophysics Data System (ADS)
Semenenko, Henry; Byrnes, Tim
2016-05-01
Quantum computing implementations under consideration today typically deal with systems with microscopic degrees of freedom such as photons, ions, cold atoms, and superconducting circuits. The quantum information is stored typically in low-dimensional Hilbert spaces such as qubits, as quantum effects are strongest in such systems. It has, however, been demonstrated that quantum effects can be observed in mesoscopic and macroscopic systems, such as nanomechanical systems and gas ensembles. While few-qubit quantum information demonstrations have been performed with such macroscopic systems, a quantum algorithm showing exponential speedup over classical algorithms is yet to be shown. Here, we show that the Deutsch-Jozsa algorithm can be implemented with macroscopic ensembles. The encoding that we use avoids the detrimental effects of decoherence that normally plagues macroscopic implementations. We discuss two mapping procedures which can be chosen depending upon the constraints of the oracle and the experiment. Both methods have an exponential speedup over the classical case, and only require control of the ensembles at the level of the total spin of the ensembles. It is shown that both approaches reproduce the qubit Deutsch-Jozsa algorithm, and are robust under decoherence.
The convergence analysis of parallel genetic algorithm based on allied strategy
NASA Astrophysics Data System (ADS)
Lin, Feng; Sun, Wei; Chang, K. C.
2010-04-01
Genetic algorithms (GAs) have been applied to many difficult optimization problems such as track assignment and hypothesis managements for multisensor integration and data fusion. However, premature convergence has been a main problem for GAs. In order to prevent premature convergence, we introduce an allied strategy based on biological evolution and present a parallel Genetic Algorithm with the allied strategy (PGAAS). The PGAAS can prevent premature convergence, increase the optimization speed, and has been successfully applied in a few applications. In this paper, we first present a Markov chain model in the PGAAS. Based on this model, we analyze the convergence property of PGAAS. We then present the proof of global convergence for the PGAAS algorithm. The experiments results show that PGAAS is an efficient and effective parallel Genetic algorithm. Finally, we discuss several potential applications of the proposed methodology.
NASA Astrophysics Data System (ADS)
Guo, Li; Li, Pei; Pan, Cong; Liao, Rujia; Cheng, Yuxuan; Hu, Weiwei; Chen, Zhong; Ding, Zhihua; Li, Peng
2016-02-01
The complex-based OCT angiography (Angio-OCT) offers high motion contrast by combining both the intensity and phase information. However, due to involuntary bulk tissue motions, complex-valued OCT raw data are processed sequentially with different algorithms for correcting bulk image shifts (BISs), compensating global phase fluctuations (GPFs) and extracting flow signals. Such a complicated procedure results in massive computational load. To mitigate such a problem, in this work, we present an inter-frame complex-correlation (CC) algorithm. The CC algorithm is suitable for parallel processing of both flow signal extraction and BIS correction, and it does not need GPF compensation. This method provides high processing efficiency and shows superiority in motion contrast. The feasibility and performance of the proposed CC algorithm is demonstrated using both flow phantom and live animal experiments.
NASA Astrophysics Data System (ADS)
Muramatsu, Daigo
Attacks using hill-climbing methods have been reported as a vulnerability of biometric authentication systems. In this paper, we propose a robust online signature verification algorithm against such attacks. Specifically, the attack considered in this paper is a hill-climbing forged data attack. Artificial forgeries are generated offline by using the hill-climbing method, and the forgeries are input to a target system to be attacked. In this paper, we analyze the menace of hill-climbing forged data attacks using six types of hill-climbing forged data and propose a robust algorithm by incorporating the hill-climbing method into an online signature verification algorithm. Experiments to evaluate the proposed system were performed using a public online signature database. The proposed algorithm showed improved performance against this kind of attack.
The analysis of multigrid algorithms for pseudodifferential operators of order minus one
Bramble, J.H.; Leyk, Z.; Pasciak, J.E. ||
1994-10-01
Multigrid algorithms are developed to solve the discrete systems approximating the solutions of operator equations involving pseudodifferential operators of order minus one. Classical multigrid theory deals with the case of differential operators of positive order. The pseudodifferential operator gives rise to a coercive form on H{sup {minus}1/2}({Omega}). Effective multigrid algorithms are developed for this problem. These algorithms are novel in that they use the inner product on H{sup {minus}1}({Omega}) as a base inner product for the multigrid development. The authors show that the resulting rate of iterative convergence can, at worst, depend linearly on the number of levels in these novel multigrid algorithms. In addition, it is shown that the convergence rate is independent of the number of levels (and unknowns) in the case of a pseudodifferential operator defined by a single-layer potential. Finally, the results of numerical experiments illustrating the theory are presented. 19 refs., 1 fig., 2 tabs.
Fast computing global structural balance in signed networks based on memetic algorithm
NASA Astrophysics Data System (ADS)
Sun, Yixiang; Du, Haifeng; Gong, Maoguo; Ma, Lijia; Wang, Shanfeng
2014-12-01
Structural balance is a large area of study in signed networks, and it is intrinsically a global property of the whole network. Computing global structural balance in signed networks, which has attracted some attention in recent years, is to measure how unbalanced a signed network is and it is a nondeterministic polynomial-time hard problem. Many approaches are developed to compute global balance. However, the results obtained by them are partial and unsatisfactory. In this study, the computation of global structural balance is solved as an optimization problem by using the Memetic Algorithm. The optimization algorithm, named Meme-SB, is proposed to optimize an evaluation function, energy function, which is used to compute a distance to exact balance. Our proposed algorithm combines Genetic Algorithm and a greedy strategy as the local search procedure. Experiments on social and biological networks show the excellent effectiveness and efficiency of the proposed method.
Application of ant colony algorithm in plant leaves classification based on infrared spectroscopy
NASA Astrophysics Data System (ADS)
Guo, Tiantai; Hong, Bo; Kong, Ming; Zhao, Jun
2014-04-01
This paper proposes to use ant colony algorithm in the analysis of spectral data of plant leaves to achieve the best classification of different plants within a short time. Intelligent classification is realized according to different components of featured information included in near infrared spectrum data of plants. The near infrared diffusive emission spectrum curves of the leaves of Cinnamomum camphora and Acer saccharum Marsh are acquired, which have 75 leaves respectively, and are divided into two groups. Then, the acquired data are processed using ant colony algorithm and the same kind of leaves can be classified as a class by ant colony clustering algorithm. Finally, the two groups of data are classified into two classes. Experiment results show that the algorithm can distinguish different species up to the percentage of 100%. The classification of plant leaves has important application value in agricultural development, research of species invasion, floriculture etc.
Algorithm of weak edge detection based on the Nilpotent minimum fusion
NASA Astrophysics Data System (ADS)
Sun, Genyun; Zhang, Aizhu; Han, Xujun
2011-11-01
To overcome the shortcoming in traditional edge detection, such as the losing of weak edges and the too rough detected edges, a new edge detection method is proposed in this paper. The new algorithm is based on the Nilpotent minimum fusion. First of all, based on the space fuzzy relation of weak edges, the algorithm makes decision fusion to improve the structure of weak edges by using the Nilpotent minimum operator. Secondly, detect edges based on the fusion results. As a result, the weak edges are detected. Experiments on a variety of weak edge images show that the new algorithm can actually overcome the shortcoming in traditional edge detection, for the results are much better than traditional methods. On one hand, some of the weak edges of complex images, such as medical images, are detected. On the other hand, the edges detected by the new algorithm are thinner.
Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue.
Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan
2015-01-01
Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.
Xu, Zhenzhen; Zou, Yongxing; Kong, Xiangjie
2015-01-01
To our knowledge, this paper investigates the first application of meta-heuristic algorithms to tackle the parallel machines scheduling problem with weighted late work criterion and common due date ([Formula: see text]). Late work criterion is one of the performance measures of scheduling problems which considers the length of late parts of particular jobs when evaluating the quality of scheduling. Since this problem is known to be NP-hard, three meta-heuristic algorithms, namely ant colony system, genetic algorithm, and simulated annealing are designed and implemented, respectively. We also propose a novel algorithm named LDF (largest density first) which is improved from LPT (longest processing time first). The computational experiments compared these meta-heuristic algorithms with LDF, LPT and LS (list scheduling), and the experimental results show that SA performs the best in most cases. However, LDF is better than SA in some conditions, moreover, the running time of LDF is much shorter than SA. PMID:26702371
Alshamlan, Hala; Badr, Ghada; Alohali, Yousef
2015-01-01
An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028
Heuristic-based tabu search algorithm for folding two-dimensional AB off-lattice model proteins.
Liu, Jingfa; Sun, Yuanyuan; Li, Gang; Song, Beibei; Huang, Weibo
2013-12-01
The protein structure prediction problem is a classical NP hard problem in bioinformatics. The lack of an effective global optimization method is the key obstacle in solving this problem. As one of the global optimization algorithms, tabu search (TS) algorithm has been successfully applied in many optimization problems. We define the new neighborhood conformation, tabu object and acceptance criteria of current conformation based on the original TS algorithm and put forward an improved TS algorithm. By integrating the heuristic initialization mechanism, the heuristic conformation updating mechanism, and the gradient method into the improved TS algorithm, a heuristic-based tabu search (HTS) algorithm is presented for predicting the two-dimensional (2D) protein folding structure in AB off-lattice model which consists of hydrophobic (A) and hydrophilic (B) monomers. The tabu search minimization leads to the basins of local minima, near which a local search mechanism is then proposed to further search for lower-energy conformations. To test the performance of the proposed algorithm, experiments are performed on four Fibonacci sequences and two real protein sequences. The experimental results show that the proposed algorithm has found the lowest-energy conformations so far for three shorter Fibonacci sequences and renewed the results for the longest one, as well as two real protein sequences, demonstrating that the HTS algorithm is quite promising in finding the ground states for AB off-lattice model proteins. PMID:24077543
Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan
2016-01-01
Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner-Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266
Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms
NASA Technical Reports Server (NTRS)
Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)
2000-01-01
In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.
Monte Carlo algorithm for free energy calculation.
Bi, Sheng; Tong, Ning-Hua
2015-07-01
We propose a Monte Carlo algorithm for the free energy calculation based on configuration space sampling. An upward or downward temperature scan can be used to produce F(T). We implement this algorithm for the Ising model on a square lattice and triangular lattice. Comparison with the exact free energy shows an excellent agreement. We analyze the properties of this algorithm and compare it with the Wang-Landau algorithm, which samples in energy space. This method is applicable to general classical statistical models. The possibility of extending it to quantum systems is discussed.
Thermostat algorithm for generating target ensembles.
Bravetti, A; Tapias, D
2016-02-01
We present a deterministic algorithm called contact density dynamics that generates any prescribed target distribution in the physical phase space. Akin to the famous model of Nosé and Hoover, our algorithm is based on a non-Hamiltonian system in an extended phase space. However, the equations of motion in our case follow from contact geometry and we show that in general they have a similar form to those of the so-called density dynamics algorithm. As a prototypical example, we apply our algorithm to produce a Gibbs canonical distribution for a one-dimensional harmonic oscillator. PMID:26986320
Thermostat algorithm for generating target ensembles.
Bravetti, A; Tapias, D
2016-02-01
We present a deterministic algorithm called contact density dynamics that generates any prescribed target distribution in the physical phase space. Akin to the famous model of Nosé and Hoover, our algorithm is based on a non-Hamiltonian system in an extended phase space. However, the equations of motion in our case follow from contact geometry and we show that in general they have a similar form to those of the so-called density dynamics algorithm. As a prototypical example, we apply our algorithm to produce a Gibbs canonical distribution for a one-dimensional harmonic oscillator.
Thermostat algorithm for generating target ensembles
NASA Astrophysics Data System (ADS)
Bravetti, A.; Tapias, D.
2016-02-01
We present a deterministic algorithm called contact density dynamics that generates any prescribed target distribution in the physical phase space. Akin to the famous model of Nosé and Hoover, our algorithm is based on a non-Hamiltonian system in an extended phase space. However, the equations of motion in our case follow from contact geometry and we show that in general they have a similar form to those of the so-called density dynamics algorithm. As a prototypical example, we apply our algorithm to produce a Gibbs canonical distribution for a one-dimensional harmonic oscillator.
2010-01-01
Background Exon arrays provide a way to measure the expression of different isoforms of genes in an organism. Most of the procedures to deal with these arrays are focused on gene expression or on exon expression. Although the only biological analytes that can be properly assigned a concentration are transcripts, there are very few algorithms that focus on them. The reason is that previously developed summarization methods do not work well if applied to transcripts. In addition, gene structure prediction, i.e., the correspondence between probes and novel isoforms, is a field which is still unexplored. Results We have modified and adapted a previous algorithm to take advantage of the special characteristics of the Affymetrix exon arrays. The structure and concentration of transcripts -some of them possibly unknown- in microarray experiments were predicted using this algorithm. Simulations showed that the suggested modifications improved both specificity (SP) and sensitivity (ST) of the predictions. The algorithm was also applied to different real datasets showing its effectiveness and the concordance with PCR validated results. Conclusions The proposed algorithm shows a substantial improvement in the performance over the previous version. This improvement is mainly due to the exploitation of the redundancy of the Affymetrix exon arrays. An R-Package of SPACE with the updated algorithms have been developed and is freely available. PMID:21110835
Modified OMP Algorithm for Exponentially Decaying Signals
Kazimierczuk, Krzysztof; Kasprzak, Paweł
2015-01-01
A group of signal reconstruction methods, referred to as compressed sensing (CS), has recently found a variety of applications in numerous branches of science and technology. However, the condition of the applicability of standard CS algorithms (e.g., orthogonal matching pursuit, OMP), i.e., the existence of the strictly sparse representation of a signal, is rarely met. Thus, dedicated algorithms for solving particular problems have to be developed. In this paper, we introduce a modification of OMP motivated by nuclear magnetic resonance (NMR) application of CS. The algorithm is based on the fact that the NMR spectrum consists of Lorentzian peaks and matches a single Lorentzian peak in each of its iterations. Thus, we propose the name Lorentzian peak matching pursuit (LPMP). We also consider certain modification of the algorithm by introducing the allowed positions of the Lorentzian peaks' centers. Our results show that the LPMP algorithm outperforms other CS algorithms when applied to exponentially decaying signals. PMID:25609044
Draijer, Matthijs; Hondebrink, Erwin; van Leeuwen, Ton; Steenbergen, Wiendelt
2009-10-01
Advances in optical array sensor technology allow for the real time acquisition of dynamic laser speckle patterns generated by tissue perfusion, which, in principle,allows for real time laser Doppler perfusion imaging(LDPI). Exploitation of these developments is enhanced with the introduction of faster algorithms to transform photo currents into perfusion estimates using the first moment of the power spectrum. A time domain (TD)algorithm is presented for determining the first-order spectral moment. Experiments are performed to compare this algorithm with the widely used Fast Fourier Transform(FFT). This study shows that the TD-algorithm is twice as fast as the FFT-algorithm without loss of accuracy.Compared to FFT, the TD-algorithm is efficient in terms of processor time, memory usage and data transport. PMID:19820976
SDR Input Power Estimation Algorithms
NASA Technical Reports Server (NTRS)
Nappier, Jennifer M.; Briones, Janette C.
2013-01-01
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
SDR input power estimation algorithms
NASA Astrophysics Data System (ADS)
Briones, J. C.; Nappier, J. M.
The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.
Intelligent perturbation algorithms for space scheduling optimization
NASA Technical Reports Server (NTRS)
Kurtzman, Clifford R.
1991-01-01
Intelligent perturbation algorithms for space scheduling optimization are presented in the form of the viewgraphs. The following subject areas are covered: optimization of planning, scheduling, and manifesting; searching a discrete configuration space; heuristic algorithms used for optimization; use of heuristic methods on a sample scheduling problem; intelligent perturbation algorithms are iterative refinement techniques; properties of a good iterative search operator; dispatching examples of intelligent perturbation algorithm and perturbation operator attributes; scheduling implementations using intelligent perturbation algorithms; major advances in scheduling capabilities; the prototype ISF (industrial Space Facility) experiment scheduler; optimized schedule (max revenue); multi-variable optimization; Space Station design reference mission scheduling; ISF-TDRSS command scheduling demonstration; and example task - communications check.
A new algorithm for coding geological terminology
NASA Astrophysics Data System (ADS)
Apon, W.
The Geological Survey of The Netherlands has developed an algorithm to convert the plain geological language of lithologic well logs into codes suitable for computer processing and link these to existing plotting programs. The algorithm is based on the "direct method" and operates in three steps: (1) searching for defined word combinations and assigning codes; (2) deleting duplicated codes; (3) correcting incorrect code combinations. Two simple auxiliary files are used. A simple PC demonstration program is included to enable readers to experiment with this algorithm. The Department of Quarternary Geology of the Geological Survey of The Netherlands possesses a large database of shallow lithologic well logs in plain language and has been using a program based on this algorithm for about 3 yr. Erroneous codes resulting from using this algorithm are less than 2%.
Basic firefly algorithm for document clustering
NASA Astrophysics Data System (ADS)
Mohammed, Athraa Jasim; Yusof, Yuhanis; Husni, Husniza
2015-12-01
The Document clustering plays significant role in Information Retrieval (IR) where it organizes documents prior to the retrieval process. To date, various clustering algorithms have been proposed and this includes the K-means and Particle Swarm Optimization. Even though these algorithms have been widely applied in many disciplines due to its simplicity, such an approach tends to be trapped in a local minimum during its search for an optimal solution. To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents. The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. Experiments utilizing the proposed algorithm were conducted on the 20Newsgroups benchmark dataset. Results demonstrate that the Basic FA generates a more robust and compact clusters than the ones produced by K-means and Particle Swarm Optimization (PSO).
Lamberti, Alfredo; Vanlanduit, Steve; De Pauw, Ben; Berghmans, Francis
2014-01-01
The working principle of fiber Bragg grating (FBG) sensors is mostly based on the tracking of the Bragg wavelength shift. To accomplish this task, different algorithms have been proposed, from conventional maximum and centroid detection algorithms to more recently-developed correlation-based techniques. Several studies regarding the performance of these algorithms have been conducted, but they did not take into account spectral distortions, which appear in many practical applications. This paper addresses this issue and analyzes the performance of four different wavelength tracking algorithms (maximum detection, centroid detection, cross-correlation and fast phase-correlation) when applied to distorted FBG spectra used for measuring dynamic loads. Both simulations and experiments are used for the analyses. The dynamic behavior of distorted FBG spectra is simulated using the transfer-matrix approach, and the amount of distortion of the spectra is quantified using dedicated distortion indices. The algorithms are compared in terms of achievable precision and accuracy. To corroborate the simulation results, experiments were conducted using three FBG sensors glued on a steel plate and subjected to a combination of transverse force and vibration loads. The analysis of the results showed that the fast phase-correlation algorithm guarantees the best combination of versatility, precision and accuracy. PMID:25521386
Alignment algorithms for planar optical waveguides
NASA Astrophysics Data System (ADS)
Zheng, Yu; Duan, Ji-an
2012-10-01
Planar optical waveguides are the key elements in a modern, high-speed optical network. An important problem facing the optical fiber communication system is optical-axis alignment and coupling between waveguide chips and transmission fibers. The advantages and disadvantages of the various algorithms used for the optical-axis alignment, namely, hill-climbing, pattern search, and genetic algorithm are analyzed. A new optical-axis alignment for planar optical waveguides is presented which is a composite of a genetic algorithm and a pattern search algorithm. Experiments have proved the proposed alignment's feasibility; compared with hill climbing, the search process can reduce the number of movements by 88% and reduce the search time by 83%. Moreover, the search success rate in the experiment can reach 100%.
Discrete artificial bee colony algorithm for lot-streaming flowshop with total flowtime minimization
NASA Astrophysics Data System (ADS)
Sang, Hongyan; Gao, Liang; Pan, Quanke
2012-09-01
Unlike a traditional flowshop problem where a job is assumed to be indivisible, in the lot-streaming flowshop problem, a job is allowed to overlap its operations between successive machines by splitting it into a number of smaller sub-lots and moving the completed portion of the sub-lots to downstream machine. In this way, the production is accelerated. This paper presents a discrete artificial bee colony (DABC) algorithm for a lot-streaming flowshop scheduling problem with total flowtime criterion. Unlike the basic ABC algorithm, the proposed DABC algorithm represents a solution as a discrete job permutation. An efficient initialization scheme based on the extended Nawaz-Enscore-Ham heuristic is utilized to produce an initial population with a certain level of quality and diversity. Employed and onlooker bees generate new solutions in their neighborhood, whereas scout bees generate new solutions by performing insert operator and swap operator to the best solution found so far. Moreover, a simple but effective local search is embedded in the algorithm to enhance local exploitation capability. A comparative experiment is carried out with the existing discrete particle swarm optimization, hybrid genetic algorithm, threshold accepting, simulated annealing and ant colony optimization algorithms based on a total of 160 randomly generated instances. The experimental results show that the proposed DABC algorithm is quite effective for the lot-streaming flowshop with total flowtime criterion in terms of searching quality, robustness and effectiveness. This research provides the references to the optimization research on lot-streaming flowshop.
A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations.
Chen, Tao; Wu, Huanxin; Guo, Limin; Liu, Lutao
2015-01-01
In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV) problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA) is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity. PMID:26610521
A Modified MinMax k-Means Algorithm Based on PSO
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
A Modified MinMax k-Means Algorithm Based on PSO
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.
Du, Tingsong; Hu, Yang; Ke, Xianting
2015-01-01
An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713
A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations
Chen, Tao; Wu, Huanxin; Guo, Limin; Liu, Lutao
2015-01-01
In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV) problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA) is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity. PMID:26610521
Du, Tingsong; Hu, Yang; Ke, Xianting
2015-01-01
An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713
A new algorithm for reliable and general NMR resonance assignment.
Schmidt, Elena; Güntert, Peter
2012-08-01
The new FLYA automated resonance assignment algorithm determines NMR chemical shift assignments on the basis of peak lists from any combination of multidimensional through-bond or through-space NMR experiments for proteins. Backbone and side-chain assignments can be determined. All experimental data are used simultaneously, thereby exploiting optimally the redundancy present in the input peak lists and circumventing potential pitfalls of assignment strategies in which results obtained in a given step remain fixed input data for subsequent steps. Instead of prescribing a specific assignment strategy, the FLYA resonance assignment algorithm requires only experimental peak lists and the primary structure of the protein, from which the peaks expected in a given spectrum can be generated by applying a set of rules, defined in a straightforward way by specifying through-bond or through-space magnetization transfer pathways. The algorithm determines the resonance assignment by finding an optimal mapping between the set of expected peaks that are assigned by definition but have unknown positions and the set of measured peaks in the input peak lists that are initially unassigned but have a known position in the spectrum. Using peak lists obtained by purely automated peak picking from the experimental spectra of three proteins, FLYA assigned correctly 96-99% of the backbone and 90-91% of all resonances that could be assigned manually. Systematic studies quantified the impact of various factors on the assignment accuracy, namely the extent of missing real peaks and the amount of additional artifact peaks in the input peak lists, as well as the accuracy of the peak positions. Comparing the resonance assignments from FLYA with those obtained from two other existing algorithms showed that using identical experimental input data these other algorithms yielded significantly (40-142%) more erroneous assignments than FLYA. The FLYA resonance assignment algorithm thus has the
A constraint consensus memetic algorithm for solving constrained optimization problems
NASA Astrophysics Data System (ADS)
Hamza, Noha M.; Sarker, Ruhul A.; Essam, Daryl L.; Deb, Kalyanmoy; Elsayed, Saber M.
2014-11-01
Constraint handling is an important aspect of evolutionary constrained optimization. Currently, the mechanism used for constraint handling with evolutionary algorithms mainly assists the selection process, but not the actual search process. In this article, first a genetic algorithm is combined with a class of search methods, known as constraint consensus methods, that assist infeasible individuals to move towards the feasible region. This approach is also integrated with a memetic algorithm. The proposed algorithm is tested and analysed by solving two sets of standard benchmark problems, and the results are compared with other state-of-the-art algorithms. The comparisons show that the proposed algorithm outperforms other similar algorithms. The algorithm has also been applied to solve a practical economic load dispatch problem, where it also shows superior performance over other algorithms.
Introduction to systolic algorithms and architectures
Bentley, J.L.; Kung, H.T.
1983-01-01
The authors survey the class of systolic special-purpose computer architectures and algorithms, which are particularly well-suited for implementation in very large scale integrated circuitry (VLSI). They give a brief introduction to systolic arrays for a reader with a broad technical background and some experience in using a computer, but who is not necessarily a computer scientist. In addition they briefly survey the technological advances in VLSI that led to the development of systolic algorithms and architectures. 38 references.
Semioptimal practicable algorithmic cooling
NASA Astrophysics Data System (ADS)
Elias, Yuval; Mor, Tal; Weinstein, Yossi
2011-04-01
Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon’s entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.
UWB Tracking System Design with TDOA Algorithm
NASA Technical Reports Server (NTRS)
Ni, Jianjun; Arndt, Dickey; Ngo, Phong; Phan, Chau; Gross, Julia; Dusl, John; Schwing, Alan
2006-01-01
This presentation discusses an ultra-wideband (UWB) tracking system design effort using a tracking algorithm TDOA (Time Difference of Arrival). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A two-stage weighted least square method is chosen to solve the TDOA non-linear equations. Matlab simulations in both two-dimensional space and three-dimensional space show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. The error analysis reveals various ways to improve the tracking resolution. Lab experiments demonstrate the UWBTDOA tracking capability with fine resolution. This research effort is motivated by a prototype development project Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS).
CUDT: A CUDA Based Decision Tree Algorithm
Sheu, Ruey-Kai; Chiu, Chun-Chieh
2014-01-01
Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture), which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5∼55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set. PMID:25140346
Algorithm design of liquid lens inspection system
NASA Astrophysics Data System (ADS)
Hsieh, Lu-Lin; Wang, Chun-Chieh
2008-08-01
In mobile lens domain, the glass lens is often to be applied in high-resolution requirement situation; but the glass zoom lens needs to be collocated with movable machinery and voice-coil motor, which usually arises some space limits in minimum design. In high level molding component technology development, the appearance of liquid lens has become the focus of mobile phone and digital camera companies. The liquid lens sets with solid optical lens and driving circuit has replaced the original components. As a result, the volume requirement is decreased to merely 50% of the original design. Besides, with the high focus adjusting speed, low energy requirement, high durability, and low-cost manufacturing process, the liquid lens shows advantages in the competitive market. In the past, authors only need to inspect the scrape defect made by external force for the glass lens. As to the liquid lens, authors need to inspect the state of four different structural layers due to the different design and structure. In this paper, authors apply machine vision and digital image processing technology to administer inspections in the particular layer according to the needs of users. According to our experiment results, the algorithm proposed can automatically delete non-focus background, extract the region of interest, find out and analyze the defects efficiently in the particular layer. In the future, authors will combine the algorithm of the system with automatic-focus technology to implement the inside inspection based on the product inspective demands.
QPSO-based adaptive DNA computing algorithm.
Karakose, Mehmet; Cigdem, Ugur
2013-01-01
DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm.
Evaluation of TCP congestion control algorithms.
Long, Robert Michael
2003-12-01
Sandia, Los Alamos, and Lawrence Livermore National Laboratories currently deploy high speed, Wide Area Network links to permit remote access to their Supercomputer systems. The current TCP congestion algorithm does not take full advantage of high delay, large bandwidth environments. This report involves evaluating alternative TCP congestion algorithms and comparing them with the currently used congestion algorithm. The goal was to find if an alternative algorithm could provide higher throughput with minimal impact on existing network traffic. The alternative congestion algorithms used were Scalable TCP and High-Speed TCP. Network lab experiments were run to record the performance of each algorithm under different network configurations. The network configurations used were back-to-back with no delay, back-to-back with a 30ms delay, and two-to-one with a 30ms delay. The performance of each algorithm was then compared to the existing TCP congestion algorithm to determine if an acceptable alternative had been found. Comparisons were made based on throughput, stability, and fairness.
A New Algorithm to Optimize Maximal Information Coefficient
Luo, Feng; Yuan, Zheming
2016-01-01
The maximal information coefficient (MIC) captures dependences between paired variables, including both functional and non-functional relationships. In this paper, we develop a new method, ChiMIC, to calculate the MIC values. The ChiMIC algorithm uses the chi-square test to terminate grid optimization and then removes the restriction of maximal grid size limitation of original ApproxMaxMI algorithm. Computational experiments show that ChiMIC algorithm can maintain same MIC values for noiseless functional relationships, but gives much smaller MIC values for independent variables. For noise functional relationship, the ChiMIC algorithm can reach the optimal partition much faster. Furthermore, the MCN values based on MIC calculated by ChiMIC can capture the complexity of functional relationships in a better way, and the statistical powers of MIC calculated by ChiMIC are higher than those calculated by ApproxMaxMI. Moreover, the computational costs of ChiMIC are much less than those of ApproxMaxMI. We apply the MIC values tofeature selection and obtain better classification accuracy using features selected by the MIC values from ChiMIC. PMID:27333001
Multi-jagged: A scalable parallel spatial partitioning algorithm
Deveci, Mehmet; Rajamanickam, Sivasankaran; Devine, Karen D.; Catalyurek, Umit V.
2015-03-18
Geometric partitioning is fast and effective for load-balancing dynamic applications, particularly those requiring geometric locality of data (particle methods, crash simulations). We present, to our knowledge, the first parallel implementation of a multidimensional-jagged geometric partitioner. In contrast to the traditional recursive coordinate bisection algorithm (RCB), which recursively bisects subdomains perpendicular to their longest dimension until the desired number of parts is obtained, our algorithm does recursive multi-section with a given number of parts in each dimension. By computing multiple cut lines concurrently and intelligently deciding when to migrate data while computing the partition, we minimize data movement compared to efficient implementations of recursive bisection. We demonstrate the algorithm's scalability and quality relative to the RCB implementation in Zoltan on both real and synthetic datasets. Our experiments show that the proposed algorithm performs and scales better than RCB in terms of run-time without degrading the load balance. Lastly, our implementation partitions 24 billion points into 65,536 parts within a few seconds and exhibits near perfect weak scaling up to 6K cores.
Multi-jagged: A scalable parallel spatial partitioning algorithm
Deveci, Mehmet; Rajamanickam, Sivasankaran; Devine, Karen D.; Catalyurek, Umit V.
2015-03-18
Geometric partitioning is fast and effective for load-balancing dynamic applications, particularly those requiring geometric locality of data (particle methods, crash simulations). We present, to our knowledge, the first parallel implementation of a multidimensional-jagged geometric partitioner. In contrast to the traditional recursive coordinate bisection algorithm (RCB), which recursively bisects subdomains perpendicular to their longest dimension until the desired number of parts is obtained, our algorithm does recursive multi-section with a given number of parts in each dimension. By computing multiple cut lines concurrently and intelligently deciding when to migrate data while computing the partition, we minimize data movement compared to efficientmore » implementations of recursive bisection. We demonstrate the algorithm's scalability and quality relative to the RCB implementation in Zoltan on both real and synthetic datasets. Our experiments show that the proposed algorithm performs and scales better than RCB in terms of run-time without degrading the load balance. Lastly, our implementation partitions 24 billion points into 65,536 parts within a few seconds and exhibits near perfect weak scaling up to 6K cores.« less
A New Algorithm to Optimize Maximal Information Coefficient.
Chen, Yuan; Zeng, Ying; Luo, Feng; Yuan, Zheming
2016-01-01
The maximal information coefficient (MIC) captures dependences between paired variables, including both functional and non-functional relationships. In this paper, we develop a new method, ChiMIC, to calculate the MIC values. The ChiMIC algorithm uses the chi-square test to terminate grid optimization and then removes the restriction of maximal grid size limitation of original ApproxMaxMI algorithm. Computational experiments show that ChiMIC algorithm can maintain same MIC values for noiseless functional relationships, but gives much smaller MIC values for independent variables. For noise functional relationship, the ChiMIC algorithm can reach the optimal partition much faster. Furthermore, the MCN values based on MIC calculated by ChiMIC can capture the complexity of functional relationships in a better way, and the statistical powers of MIC calculated by ChiMIC are higher than those calculated by ApproxMaxMI. Moreover, the computational costs of ChiMIC are much less than those of ApproxMaxMI. We apply the MIC values tofeature selection and obtain better classification accuracy using features selected by the MIC values from ChiMIC. PMID:27333001
A quantum algorithm for Viterbi decoding of classical convolutional codes
NASA Astrophysics Data System (ADS)
Grice, Jon R.; Meyer, David A.
2015-07-01
We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper, the proposed algorithm is applied to decoding classical convolutional codes, for instance, large constraint length and short decode frames . Other applications of the classical Viterbi algorithm where is large (e.g., speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butterfly diagram of the fast Fourier transform, with its corresponding fast quantum algorithm. The tensor-product structure of the butterfly diagram corresponds to a quantum superposition that we show can be efficiently prepared. The quantum speedup is possible because the performance of the QVA depends on the fanout (number of possible transitions from any given state in the hidden Markov model) which is in general much less than . The QVA constructs a superposition of states which correspond to all legal paths through the decoding lattice, with phase as a function of the probability of the path being taken given received data. A specialized amplitude amplification procedure is applied one or more times to recover a superposition where the most probable path has a high probability of being measured.
Panniculitides, an algorithmic approach.
Zelger, B
2013-08-01
The issue of inflammatory diseases of subcutis and its mimicries is generally considered a difficult field of dermatopathology. Yet, in my experience, with appropriate biopsies and good clinicopathological correlation, a specific diagnosis of panniculitides can usually be made. Thereby, knowledge about some basic anatomic and pathological issues is essential. Anatomy differentiates within the panniculus between the fatty lobules separated by fibrous septa. Pathologically, inflammation of panniculus is defined and recognized by an inflammatory process which leads to tissue damage and necrosis. Several types of fat necrosis are observed: xanthomatized macrophages in lipophagic necrosis; granular fat necrosis and fat micropseudocysts in liquefactive fat necrosis; mummified adipocytes in "hyalinizing" fat necrosis with/without saponification and/or calcification; and lipomembranous membranes in membranous fat necrosis. In an algorithmic approach the recognition of an inflammatory process recognized by features as elaborated above is best followed in three steps: recognition of pattern, second of subpattern, and finally of presence and composition of inflammatory cells. Pattern differentiates a mostly septal or mostly lobular distribution at scanning magnification. In the subpattern category one looks for the presence or absence of vasculitis, and, if this is the case, the size and the nature of the involved blood vessel: arterioles and small arteries or veins; capillaries or postcapillary venules. The third step will be to identify the nature of the cells present in the inflammatory infiltrate and, finally, to look for additional histopathologic features that allow for a specific final diagnosis in the language of clinical dermatology of disease involving the subcutaneous fat.
Reasoning about systolic algorithms
Purushothaman, S.; Subrahmanyam, P.A.
1988-12-01
The authors present a methodology for verifying correctness of systolic algorithms. The methodology is based on solving a set of Uniform Recurrence Equations obtained from a description of systolic algorithms as a set of recursive equations. They present an approach to mechanically verify correctness of systolic algorithms, using the Boyer-Moore theorem proven. A mechanical correctness proof of an example from the literature is also presented.
A novel dynamical community detection algorithm based on weighting scheme
NASA Astrophysics Data System (ADS)
Li, Ju; Yu, Kai; Hu, Ke
2015-12-01
Network dynamics plays an important role in analyzing the correlation between the function properties and the topological structure. In this paper, we propose a novel dynamical iteration (DI) algorithm, which incorporates the iterative process of membership vector with weighting scheme, i.e. weighting W and tightness T. These new elements can be used to adjust the link strength and the node compactness for improving the speed and accuracy of community structure detection. To estimate the optimal stop time of iteration, we utilize a new stability measure which is defined as the Markov random walk auto-covariance. We do not need to specify the number of communities in advance. It naturally supports the overlapping communities by associating each node with a membership vector describing the node's involvement in each community. Theoretical analysis and experiments show that the algorithm can uncover communities effectively and efficiently.
A hierarchical algorithm for molecular similarity (H-FORMS).
Ramirez-Manzanares, Alonso; Peña, Joaquin; Azpiroz, Jon M; Merino, Gabriel
2015-07-15
A new hierarchical method to determine molecular similarity is introduced. The goal of this method is to detect if a pair of molecules has the same structure by estimating a rigid transformation that aligns the molecules and a correspondence function that matches their atoms. The algorithm firstly detect similarity based on the global spatial structure. If this analysis is not sufficient, the algorithm computes novel local structural rotation-invariant descriptors for the atom neighborhood and uses this information to match atoms. Two strategies (deterministic and stochastic) on the matching based alignment computation are tested. As a result, the atom-matching based on local similarity indexes decreases the number of testing trials and significantly reduces the dimensionality of the Hungarian assignation problem. The experiments on well-known datasets show that our proposal outperforms state-of-the-art methods in terms of the required computational time and accuracy.
Operational algorithm development and refinement approaches
NASA Astrophysics Data System (ADS)
Ardanuy, Philip E.
2003-11-01
Next-generation polar and geostationary systems, such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and the Geostationary Operational Environmental Satellite (GOES)-R, will deploy new generations of electro-optical reflective and emissive capabilities. These will include low-radiometric-noise, improved spatial resolution multi-spectral and hyperspectral imagers and sounders. To achieve specified performances (e.g., measurement accuracy, precision, uncertainty, and stability), and best utilize the advanced space-borne sensing capabilities, a new generation of retrieval algorithms will be implemented. In most cases, these advanced algorithms benefit from ongoing testing and validation using heritage research mission algorithms and data [e.g., the Earth Observing System (EOS)] Moderate-resolution Imaging Spectroradiometer (MODIS) and Shuttle Ozone Limb Scattering Experiment (SOLSE)/Limb Ozone Retreival Experiment (LORE). In these instances, an algorithm's theoretical basis is not static, but rather improves with time. Once frozen, an operational algorithm can "lose ground" relative to research analogs. Cost/benefit analyses provide a basis for change management. The challenge is in reconciling and balancing the stability, and "comfort," that today"s generation of operational platforms provide (well-characterized, known, sensors and algorithms) with the greatly improved quality, opportunities, and risks, that the next generation of operational sensors and algorithms offer. By using the best practices and lessons learned from heritage/groundbreaking activities, it is possible to implement an agile process that enables change, while managing change. This approach combines a "known-risk" frozen baseline with preset completion schedules with insertion opportunities for algorithm advances as ongoing validation activities identify and repair areas of weak performance. This paper describes an objective, adaptive implementation roadmap that
Quantum-inspired immune clonal algorithm for global optimization.
Jiao, Licheng; Li, Yangyang; Gong, Maoguo; Zhang, Xiangrong
2008-10-01
Based on the concepts and principles of quantum computing, a novel immune clonal algorithm, called a quantum-inspired immune clonal algorithm (QICA), is proposed to deal with the problem of global optimization. In QICA, the antibody is proliferated and divided into a set of subpopulation groups. The antibodies in a subpopulation group are represented by multistate gene quantum bits. In the antibody's updating, the general quantum rotation gate strategy and the dynamic adjusting angle mechanism are applied to accelerate convergence. The quantum not gate is used to realize quantum mutation to avoid premature convergences. The proposed quantum recombination realizes the information communication between subpopulation groups to improve the search efficiency. Theoretical analysis proves that QICA converges to the global optimum. In the first part of the experiments, 10 unconstrained and 13 constrained benchmark functions are used to test the performance of QICA. The results show that QICA performs much better than the other improved genetic algorithms in terms of the quality of solution and computational cost. In the second part of the experiments, QICA is applied to a practical problem (i.e., multiuser detection in direct-sequence code-division multiple-access systems) with a satisfying result.
An evaluation of optical flow algorithms for background oriented schlieren imaging
NASA Astrophysics Data System (ADS)
Atcheson, Bradley; Heidrich, Wolfgang; Ihrke, Ivo
2009-03-01
The background oriented schlieren method (BOS) allows for accurate flow measurements with a simple experimental configuration. To estimate per-pixel displacement vectors between two images, BOS systems traditionally borrow window-based algorithms from particle image velocimetry. In this paper, we evaluate the performance of more recent optical flow methods in BOS settings. We also analyze the impact of different background patterns, suggesting the use of a pattern with detail at many scales. Experiments with both synthetic and real datasets show that the performance of BOS systems can be significantly improved through a combination of optical flow algorithms and multiscale background.
A 2D vector map watermarking algorithm resistant to simplication attack
NASA Astrophysics Data System (ADS)
Wang, Chuanjian; Liang, Bin; Zhao, Qingzhan; Qiu, Zuqi; Peng, Yuwei; Yu, Liang
2009-12-01
Vector maps are valuable asset of data producers. How to protect copyright of vector maps effectively using digital watermarking is a hot research issue. In this paper, we propose a new robust and blind watermarking algorithm resilient to simplification attack. We proof that spatial topological relation between map objects bears an important property of approximate simplification invariance. We choose spatial topological relations as watermark feature domain and embed watermarks by slightly modifying spatial topological relation between map objects. Experiment shows that our algorithm has good performance to resist simplification attack and tradeoff of the robustness and data fidelity is acquired.
Pedestrian navigation algorithm based on MIMU with building heading/magnetometer
NASA Astrophysics Data System (ADS)
Meng, Xiang-bin; Pan, Xian-fei; Chen, Chang-hao; Hu, Xiao-ping
2016-01-01
In order to improve the accuracy of the low-cost MIMU Inertial navigation system in the application of pedestrian navigation.And to reduce the effect of the heading error because of the low accuracy of the component of MIMU. A novel algorithm was put forward, which fusing the building heading constraint information and the magnetic heading information to achieve more advantages. We analysed the application condition and the modified effect of building heading and magnetic heading. Then experiments were conducted in indoor environment. The results show that the algorithm proposed has a better effect to restrict the heading drift problem and to achieve a higher navigation precision.
Calibration of a polarization navigation sensor using the NSGA-II algorithm
NASA Astrophysics Data System (ADS)
Ma, Tao; Hu, Xiaoping; Zhang, Lilian; He, Xiaofeng
2016-10-01
A bio-inspired polarization navigation sensor is designed based on the polarization sensitivity mechanisms of insects. A new calibration model by formulating the calibration problem as a multi-objective optimization problem is presented. Unlike existing calibration models, the proposed model makes the calibration problem well-posed. The calibration parameters are optimized through Non-dominated Sorting Genetic Algorithm-II (NSGA-II) approach to minimize both angle of polarization (AOP) residuals and degree of linear polarization (DOLP) dispersions. The results of simulation and experiments show that the proposed algorithm is more stable than the compared methods for the calibration applications of polarization navigation sensors.
Jablonski, Ireneusz; Mroczka, Janusz
2010-01-01
The paper offers an enhancement of the classical interrupter technique algorithm dedicated to respiratory mechanics measurements. Idea consists in exploitation of information contained in postocclusional transient states during indirect measurement of parameter characteristics by model identification. It needs the adequacy of an inverse analogue to general behavior of the real system and a reliable algorithm of parameter estimation. The second one was a subject of reported works, which finally showed the potential of the approach to separation of airway and tissue response in a case of short-term excitation by interrupter valve operation. Investigations were conducted in a regime of forward-inverse computer experiment.
Shock capturing data assimilation algorithm for 1D shallow water equations
NASA Astrophysics Data System (ADS)
Tirupathi, Seshu; Tchrakian, Tigran T.; Zhuk, Sergiy; McKenna, Sean
2016-02-01
We propose a new data assimilation algorithm for shallow water equations in one dimension. The algorithm is based upon Discontinuous Galerkin spatial discretization of shallow water equations (DG-SW model) and the continuous formulation of the minimax filter. The latter allows for construction of a robust estimation of the state of the DG-SW model and computes worst-case bounds for the estimation error, provided the uncertain parameters belong to a given bounding set. Numerical studies show that, given sparse observations from numerical or physical experiments, the proposed algorithm quickly reconstructs the true solution even in the presence of shocks, rarefaction waves and unknown values of model parameters. The minimax filter is compared against the ensemble Kalman filter (EnKF) for a benchmark dam-break problem and the results show that the minimax filter converges faster to the true solution for sparse observations.
Applications and accuracy of the parallel diagonal dominant algorithm
NASA Technical Reports Server (NTRS)
Sun, Xian-He
1993-01-01
The Parallel Diagonal Dominant (PDD) algorithm is a highly efficient, ideally scalable tridiagonal solver. In this paper, a detailed study of the PDD algorithm is given. First the PDD algorithm is introduced. Then the algorithm is extended to solve periodic tridiagonal systems. A variant, the reduced PDD algorithm, is also proposed. Accuracy analysis is provided for a class of tridiagonal systems, the symmetric, and anti-symmetric Toeplitz tridiagonal systems. Implementation results show that the analysis gives a good bound on the relative error, and the algorithm is a good candidate for the emerging massively parallel machines.
New formulations of monotonically convergent quantum control algorithms
NASA Astrophysics Data System (ADS)
Maday, Yvon; Turinici, Gabriel
2003-05-01
Most of the numerical simulation in quantum (bilinear) control have used one of the monotonically convergent algorithms of Krotov (introduced by Tannor et al.) or of Zhu and Rabitz. However, until now no explicit relationship has been revealed between the two algorithms in order to understand their common properties. Within this framework, we propose in this paper a unified formulation that comprises both algorithms and that extends to a new class of monotonically convergent algorithms. Numerical results show that the newly derived algorithms behave as well as (and sometimes better than) the well-known algorithms cited above.
NASA Astrophysics Data System (ADS)
Rastogi, Richa; Srivastava, Abhishek; Khonde, Kiran; Sirasala, Kirannmayi M.; Londhe, Ashutosh; Chavhan, Hitesh
2015-07-01
This paper presents an efficient parallel 3D Kirchhoff depth migration algorithm suitable for current class of multicore architecture. The fundamental Kirchhoff depth migration algorithm exhibits inherent parallelism however, when it comes to 3D data migration, as the data size increases the resource requirement of the algorithm also increases. This challenges its practical implementation even on current generation high performance computing systems. Therefore a smart parallelization approach is essential to handle 3D data for migration. The most compute intensive part of Kirchhoff depth migration algorithm is the calculation of traveltime tables due to its resource requirements such as memory/storage and I/O. In the current research work, we target this area and develop a competent parallel algorithm for post and prestack 3D Kirchhoff depth migration, using hybrid MPI+OpenMP programming techniques. We introduce a concept of flexi-depth iterations while depth migrating data in parallel imaging space, using optimized traveltime table computations. This concept provides flexibility to the algorithm by migrating data in a number of depth iterations, which depends upon the available node memory and the size of data to be migrated during runtime. Furthermore, it minimizes the requirements of storage, I/O and inter-node communication, thus making it advantageous over the conventional parallelization approaches. The developed parallel algorithm is demonstrated and analysed on Yuva II, a PARAM series of supercomputers. Optimization, performance and scalability experiment results along with the migration outcome show the effectiveness of the parallel algorithm.
NASA Astrophysics Data System (ADS)
Yin, Jiale; Liu, Lei; Li, He; Liu, Qiankun
2016-07-01
This paper presents the infrared moving object detection and security detection related algorithms in video surveillance based on the classical W4 and frame difference algorithm. Classical W4 algorithm is one of the powerful background subtraction algorithms applying to infrared images which can accurately, integrally and quickly detect moving object. However, the classical W4 algorithm can only overcome the deficiency in the slight movement of background. The error will become bigger and bigger for long-term surveillance system since the background model is unchanged once established. In this paper, we present the detection algorithm based on the classical W4 and frame difference. It cannot only overcome the shortcoming of falsely detecting because of state mutations from background, but also eliminate holes caused by frame difference. Based on these we further design various security detection related algorithms such as illegal intrusion alarm, illegal persistence alarm and illegal displacement alarm. We compare our method with the classical W4, frame difference, and other state-of-the-art methods. Experiments detailed in this paper show the method proposed in this paper outperforms the classical W4 and frame difference and serves well for the security detection related algorithms.
Basis for spectral curvature algorithms in remote sensing of chlorophyll
NASA Technical Reports Server (NTRS)
Campbell, J. W.; Esaias, W. E.
1983-01-01
A simple, empirically derived algorithm for estimating oceanic chlorophyll concentrations from spectral radiances measured by a low-flying spectroradiometer has proved highly successful in field experiments in 1980-82. The sensor used was the Multichannel Ocean Color Sensor, and the originator of the algorithm was Grew (1981). This paper presents an explanation for the algorithm based on the optical properties of waters containing chlorophyll and other phytoplankton pigments and the radiative transfer equations governing the remotely sensed signal. The effects of varying solar zenith, atmospheric transmittance, and interfering substances in the water on the chlorophyll algorithm are characterized, and applicability of the algorithm is discussed.
ERIC Educational Resources Information Center
Robertson, Alexander M.; Willett, Peter
1996-01-01
Describes a genetic algorithm (GA) that assigns weights to query terms in a ranked-output document retrieval system. Experiments showed the GA often found weights slightly superior to those produced by deterministic weighting (F4). Many times, however, the two methods gave the same results and sometimes the F4 results were superior, indicating…
Algorithm That Synthesizes Other Algorithms for Hashing
NASA Technical Reports Server (NTRS)
James, Mark
2010-01-01
An algorithm that includes a collection of several subalgorithms has been devised as a means of synthesizing still other algorithms (which could include computer code) that utilize hashing to determine whether an element (typically, a number or other datum) is a member of a set (typically, a list of numbers). Each subalgorithm synthesizes an algorithm (e.g., a block of code) that maps a static set of key hashes to a somewhat linear monotonically increasing sequence of integers. The goal in formulating this mapping is to cause the length of the sequence thus generated to be as close as practicable to the original length of the set and thus to minimize gaps between the elements. The advantage of the approach embodied in this algorithm is that it completely avoids the traditional approach of hash-key look-ups that involve either secondary hash generation and look-up or further searching of a hash table for a desired key in the event of collisions. This algorithm guarantees that it will never be necessary to perform a search or to generate a secondary key in order to determine whether an element is a member of a set. This algorithm further guarantees that any algorithm that it synthesizes can be executed in constant time. To enforce these guarantees, the subalgorithms are formulated to employ a set of techniques, each of which works very effectively covering a certain class of hash-key values. These subalgorithms are of two types, summarized as follows: Given a list of numbers, try to find one or more solutions in which, if each number is shifted to the right by a constant number of bits and then masked with a rotating mask that isolates a set of bits, a unique number is thereby generated. In a variant of the foregoing procedure, omit the masking. Try various combinations of shifting, masking, and/or offsets until the solutions are found. From the set of solutions, select the one that provides the greatest compression for the representation and is executable in the
Rate distortion optimization for H.264 interframe coding: a general framework and algorithms.
Yang, En-Hui; Yu, Xiang
2007-07-01
Rate distortion (RD) optimization for H.264 interframe coding with complete baseline decoding compatibility is investigated on a frame basis. Using soft decision quantization (SDQ) rather than the standard hard decision quantization, we first establish a general framework in which motion estimation, quantization, and entropy coding (in H.264) for the current frame can be jointly designed to minimize a true RD cost given previously coded reference frames. We then propose three RD optimization algorithms--a graph-based algorithm for near optimal SDQ in H.264 baseline encoding given motion estimation and quantization step sizes, an algorithm for near optimal residual coding in H.264 baseline encoding given motion estimation, and an iterative overall algorithm to optimize H.264 baseline encoding for each individual frame given previously coded reference frames-with them embedded in the indicated order. The graph-based algorithm for near optimal SDQ is the core; given motion estimation and quantization step sizes, it is guaranteed to perform optimal SDQ if the weak adjacent block dependency utilized in the context adaptive variable length coding of H.264 is ignored for optimization. The proposed algorithms have been implemented based on the reference encoder JM82 of H.264 with complete compatibility to the baseline profile. Experiments show that for a set of typical video testing sequences, the graph-based algorithm for near optimal SDQ, the algorithm for near optimal residual coding, and the overall algorithm achieve on average, 6%, 8%, and 12%, respectively, rate reduction at the same PSNR (ranging from 30 to 38 dB) when compared with the RD optimization method implemented in the H.264 reference software.
Negative Selection Algorithm for Aircraft Fault Detection
NASA Technical Reports Server (NTRS)
Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.
2004-01-01
We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The detection algorithm uses body-axes angular rate sensory data exhibiting the normal flight behavior patterns, to generate probabilistically a set of fault detectors that can detect any abnormalities (including faults and damages) in the behavior pattern of the aircraft flight. We performed experiments with datasets (collected under normal and various simulated failure conditions) using the NASA Ames man-in-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.
GPU-accelerated MRF segmentation algorithm for SAR images
NASA Astrophysics Data System (ADS)
Sui, Haigang; Peng, Feifei; Xu, Chuan; Sun, Kaimin; Gong, Jianya
2012-06-01
Markov Random Field (MRF) approaches have been widely studied for Synthetic Aperture Radar (SAR) image segmentation, but they have a large computational cost and hence are not widely used in practice. Fortunately parallel algorithms have been documented to enjoy significant speedups when ported to run on a graphics processing units (GPUs) instead of a standard CPU. Presented here is an implementation of graphics processing units in General Purpose Computation (GPGPU) for SAR image segmentation based on the MRF method, using the C-oriented Compute Unified Device Architecture (CUDA) developed by NVIDIA. This experiment with GPGPU shows that the speed of segmentation can be increased by a factor of 10 for large images.
Genetic Algorithm for Initial Orbit Determination with Too Short Arc
NASA Astrophysics Data System (ADS)
Li, X. R.; Wang, X.
2016-01-01
The sky surveys of space objects have obtained a huge quantity of too-short-arc (TSA) observation data. However, the classical method of initial orbit determination (IOD) can hardly get reasonable results for the TSAs. The IOD is reduced to a two-stage hierarchical optimization problem containing three variables for each stage. Using the genetic algorithm, a new method of the IOD for TSAs is established, through the selection of optimizing variables as well as the corresponding genetic operator for specific problems. Numerical experiments based on the real measurements show that the method can provide valid initial values for the follow-up work.
The origins of counting algorithms.
Cantlon, Jessica F; Piantadosi, Steven T; Ferrigno, Stephen; Hughes, Kelly D; Barnard, Allison M
2015-06-01
Humans' ability to count by verbally labeling discrete quantities is unique in animal cognition. The evolutionary origins of counting algorithms are not understood. We report that nonhuman primates exhibit a cognitive ability that is algorithmically and logically similar to human counting. Monkeys were given the task of choosing between two food caches. First, they saw one cache baited with some number of food items, one item at a time. Then, a second cache was baited with food items, one at a time. At the point when the second set was approximately equal to the first set, the monkeys spontaneously moved to choose the second set even before that cache was completely baited. Using a novel Bayesian analysis, we show that the monkeys used an approximate counting algorithm for comparing quantities in sequence that is incremental, iterative, and condition controlled. This proto-counting algorithm is structurally similar to formal counting in humans and thus may have been an important evolutionary precursor to human counting. PMID:25953949
A parallel Jacobson-Oksman optimization algorithm. [parallel processing (computers)
NASA Technical Reports Server (NTRS)
Straeter, T. A.; Markos, A. T.
1975-01-01
A gradient-dependent optimization technique which exploits the vector-streaming or parallel-computing capabilities of some modern computers is presented. The algorithm, derived by assuming that the function to be minimized is homogeneous, is a modification of the Jacobson-Oksman serial minimization method. In addition to describing the algorithm, conditions insuring the convergence of the iterates of the algorithm and the results of numerical experiments on a group of sample test functions are presented. The results of these experiments indicate that this algorithm will solve optimization problems in less computing time than conventional serial methods on machines having vector-streaming or parallel-computing capabilities.
Totally parallel multilevel algorithms
NASA Technical Reports Server (NTRS)
Frederickson, Paul O.
1988-01-01
Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.
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.
A Revision of the NASA Team Sea Ice Algorithm
NASA Technical Reports Server (NTRS)
Markus, T.; Cavalieri, Donald J.
1998-01-01
In a recent paper, two operational algorithms to derive ice concentration from satellite multichannel passive microwave sensors have been compared. Although the results of these, known as the NASA Team algorithm and the Bootstrap algorithm, have been validated and are generally in good agreement, there are areas where the ice concentrations differ, by up to 30%. These differences can be explained by shortcomings in one or the other algorithm. Here, we present an algorithm which, in addition to the 19 and 37 GHz channels used by both the Bootstrap and NASA Team algorithms, makes use of the 85 GHz channels as well. Atmospheric effects particularly at 85 GHz are reduced by using a forward atmospheric radiative transfer model. Comparisons with the NASA Team and Bootstrap algorithm show that the individual shortcomings of these algorithms are not apparent in this new approach. The results further show better quantitative agreement with ice concentrations derived from NOAA AVHRR infrared data.
A comprehensive evaluation of alignment algorithms in the context of RNA-seq.
Lindner, Robert; Friedel, Caroline C
2012-01-01
Transcriptome sequencing (RNA-Seq) overcomes limitations of previously used RNA quantification methods and provides one experimental framework for both high-throughput characterization and quantification of transcripts at the nucleotide level. The first step and a major challenge in the analysis of such experiments is the mapping of sequencing reads to a transcriptomic origin including the identification of splicing events. In recent years, a large number of such mapping algorithms have been developed, all of which have in common that they require algorithms for aligning a vast number of reads to genomic or transcriptomic sequences. Although the FM-index based aligner Bowtie has become a de facto standard within mapping pipelines, a much larger number of possible alignment algorithms have been developed also including other variants of FM-index based aligners. Accordingly, developers and users of RNA-seq mapping pipelines have the choice among a large number of available alignment algorithms. To provide guidance in the choice of alignment algorithms for these purposes, we evaluated the performance of 14 widely used alignment programs from three different algorithmic classes: algorithms using either hashing of the reference transcriptome, hashing of reads, or a compressed FM-index representation of the genome. Here, special emphasis was placed on both precision and recall and the performance for different read lengths and numbers of mismatches and indels in a read. Our results clearly showed the significant reduction in memory footprint and runtime provided by FM-index based aligners at a precision and recall comparable to the best hash table based aligners. Furthermore, the recently developed Bowtie 2 alignment algorithm shows a remarkable tolerance to both sequencing errors and indels, thus, essentially making hash-based aligners obsolete.
Interpreting Quantifier Scope Ambiguity: Evidence of Heuristic First, Algorithmic Second Processing
Dwivedi, Veena D.
2013-01-01
The present work suggests that sentence processing requires both heuristic and algorithmic processing streams, where the heuristic processing strategy precedes the algorithmic phase. This conclusion is based on three self-paced reading experiments in which the processing of two-sentence discourses was investigated, where context sentences exhibited quantifier scope ambiguity. Experiment 1 demonstrates that such sentences are processed in a shallow manner. Experiment 2 uses the same stimuli as Experiment 1 but adds questions to ensure deeper processing. Results indicate that reading times are consistent with a lexical-pragmatic interpretation of number associated with context sentences, but responses to questions are consistent with the algorithmic computation of quantifier scope. Experiment 3 shows the same pattern of results as Experiment 2, despite using stimuli with different lexical-pragmatic biases. These effects suggest that language processing can be superficial, and that deeper processing, which is sensitive to structure, only occurs if required. Implications for recent studies of quantifier scope ambiguity are discussed. PMID:24278439
Freer, Phoebe E.; Slanetz, Priscilla J.; Haas, Jennifer S.; Tung, Nadine M.; Hughes, Kevin S.; Armstrong, Katrina; Semine, A. Alan; Troyan, Susan L.; Birdwell, Robyn L.
2015-01-01
Purpose Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. Methods We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review (ICER), the Cochrane review, National Comprehensive Cancer Network (NCCN) guidelines, American Cancer Society (ACS) recommendations, and American College of Radiology (ACR) appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. Results The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (<15% lifetime risk), do not routinely require supplemental screening per the expert consensus. Women of high risk (>20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. Conclusion We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman. PMID:26290416
Recent Advancements in Lightning Jump Algorithm Work
NASA Technical Reports Server (NTRS)
Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.
2010-01-01
In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).
A comprehensive review of swarm optimization algorithms.
Ab Wahab, Mohd Nadhir; Nefti-Meziani, Samia; Atyabi, Adham
2015-01-01
Many swarm optimization algorithms have been introduced since the early 60's, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655
A Comprehensive Review of Swarm Optimization Algorithms
2015-01-01
Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655
Scheduling Earth Observing Satellites with Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna
2003-01-01
We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.
A parallel variable metric optimization algorithm
NASA Technical Reports Server (NTRS)
Straeter, T. A.
1973-01-01
An algorithm, designed to exploit the parallel computing or vector streaming (pipeline) capabilities of computers is presented. When p is the degree of parallelism, then one cycle of the parallel variable metric algorithm is defined as follows: first, the function and its gradient are computed in parallel at p different values of the independent variable; then the metric is modified by p rank-one corrections; and finally, a single univariant minimization is carried out in the Newton-like direction. Several properties of this algorithm are established. The convergence of the iterates to the solution is proved for a quadratic functional on a real separable Hilbert space. For a finite-dimensional space the convergence is in one cycle when p equals the dimension of the space. Results of numerical experiments indicate that the new algorithm will exploit parallel or pipeline computing capabilities to effect faster convergence than serial techniques.
Fourth Order Algorithms for Solving Diverse Many-Body Problems
NASA Astrophysics Data System (ADS)
Chin, Siu A.; Forbert, Harald A.; Chen, Chia-Rong; Kidwell, Donald W.; Ciftja, Orion
2001-03-01
We show that the method of factorizing an evolution operator of the form e^ɛ(A+B) to fourth order with purely positive coefficient yields new classes of symplectic algorithms for solving classical dynamical problems, unitary algorithms for solving the time-dependent Schrödinger equation, norm preserving algorithms for solving the Langevin equation and large time step convergent Diffusion Monte Carlo algorithms. Results for each class of problems will be presented and disucss
Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories
NASA Technical Reports Server (NTRS)
Burchett, Bradley T.
2003-01-01
The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.
An incremental clustering algorithm based on Mahalanobis distance
NASA Astrophysics Data System (ADS)
Aik, Lim Eng; Choon, Tan Wee
2014-12-01
Classical fuzzy c-means clustering algorithm is insufficient to cluster non-spherical or elliptical distributed datasets. The paper replaces classical fuzzy c-means clustering euclidean distance with Mahalanobis distance. It applies Mahalanobis distance to incremental learning for its merits. A Mahalanobis distance based fuzzy incremental clustering learning algorithm is proposed. Experimental results show the algorithm is an effective remedy for the defect in fuzzy c-means algorithm but also increase training accuracy.
Quantum Algorithm for Linear Programming Problems
NASA Astrophysics Data System (ADS)
Joag, Pramod; Mehendale, Dhananjay
The quantum algorithm (PRL 103, 150502, 2009) solves a system of linear equations with exponential speedup over existing classical algorithms. We show that the above algorithm can be readily adopted in the iterative algorithms for solving linear programming (LP) problems. The first iterative algorithm that we suggest for LP problem follows from duality theory. It consists of finding nonnegative solution of the equation forduality condition; forconstraints imposed by the given primal problem and for constraints imposed by its corresponding dual problem. This problem is called the problem of nonnegative least squares, or simply the NNLS problem. We use a well known method for solving the problem of NNLS due to Lawson and Hanson. This algorithm essentially consists of solving in each iterative step a new system of linear equations . The other iterative algorithms that can be used are those based on interior point methods. The same technique can be adopted for solving network flow problems as these problems can be readily formulated as LP problems. The suggested quantum algorithm cansolveLP problems and Network Flow problems of very large size involving millions of variables.
A novel algorithm for Bluetooth ECG.
Pandya, Utpal T; Desai, Uday B
2012-11-01
In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.
Adaptive path planning: Algorithm and analysis
Chen, Pang C.
1993-03-01
Path planning has to be fast to support real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To alleviate this problem, we present a learning algorithm that uses past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful subgoals is learned to support faster planning. The algorithm is suitable for both stationary and incrementally-changing environments. To analyze our algorithm, we use a previously developed stochastic model that quantifies experience utility. Using this model, we characterize the situations in which the adaptive planner is useful, and provide quantitative bounds to predict its behavior. The results are demonstrated with problems in manipulator planning. Our algorithm and analysis are sufficiently general that they may also be applied to task planning or other planning domains in which experience is useful.
Novel similarity-based clustering algorithm for grouping broadcast news
NASA Astrophysics Data System (ADS)
Ibrahimov, Oktay V.; Sethi, Ishwar K.; Dimitrova, Nevenka
2002-03-01
The goal of the current paper is to introduce a novel clustering algorithm that has been designed for grouping transcribed textual documents obtained out of audio, video segments. Since audio transcripts are normally highly erroneous documents, one of the major challenges at the text processing stage is to reduce the negative impacts of errors gained at the speech recognition stage. Other difficulties come from the nature of conversational speech. In the paper we describe the main difficulties of the spoken documents and suggest an approach restricting their negative effects. In our paper we also present a clustering algorithm that groups transcripts on the base of informative closeness of documents. To carry out such partitioning we give an intuitive definition of informative field of a transcript and use it in our algorithm. To assess informative closeness of the transcripts, we apply Chi-square similarity measure, which is also described in the paper. Our experiments with Chi-square similarity measure showed its robustness and high efficacy. In particular, the performance analysis that have been carried out in regard to Chi-square and three other similarity measures such as Cosine, Dice, and Jaccard showed that Chi-square is more robust to specific features of spoken documents.
An Efficient Algorithm for Clustering of Large-Scale Mass Spectrometry Data
Saeed, Fahad; Pisitkun, Trairak; Knepper, Mark A.; Hoffert, Jason D.
2012-01-01
High-throughput spectrometers are capable of producing data sets containing thousands of spectra for a single biological sample. These data sets contain a substantial amount of redundancy from peptides that may get selected multiple times in a LC-MS/MS experiment. In this paper, we present an efficient algorithm, CAMS (Clustering Algorithm for Mass Spectra) for clustering mass spectrometry data which increases both the sensitivity and confidence of spectral assignment. CAMS utilizes a novel metric, called F-set, that allows accurate identification of the spectra that are similar. A graph theoretic framework is defined that allows the use of F-set metric efficiently for accurate cluster identifications. The accuracy of the algorithm is tested on real HCD and CID data sets with varying amounts of peptides. Our experiments show that the proposed algorithm is able to cluster spectra with very high accuracy in a reasonable amount of time for large spectral data sets. Thus, the algorithm is able to decrease the computational time by compressing the data sets while increasing the throughput of the data by interpreting low S/N spectra. PMID:23471471
a Fast and Robust Algorithm for Road Edges Extraction from LIDAR Data
NASA Astrophysics Data System (ADS)
Qiu, Kaijin; Sun, Kai; Ding, Kou; Shu, Zhen
2016-06-01
Fast mapping of roads plays an important role in many geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance. How to extract various road edges fast and robustly is a challenging task. In this paper, we present a fast and robust algorithm for the automatic road edges extraction from terrestrial mobile LiDAR data. The algorithm is based on a key observation: most roads around edges have difference in elevation and road edges with pavement are seen in two different planes. In our algorithm, we firstly extract a rough plane based on RANSAC algorithm, and then multiple refined planes which only contains pavement are extracted from the rough plane. The road edges are extracted based on these refined planes. In practice, there is a serious problem that the rough and refined planes usually extracted badly due to rough roads and different density of point cloud. To eliminate the influence of rough roads, the technology which is similar with the difference of DSM (digital surface model) and DTM (digital terrain model) is used, and we also propose a method which adjust the point clouds to a similar density to eliminate the influence of different density. Experiments show the validities of the proposed method with multiple datasets (e.g. urban road, highway, and some rural road). We use the same parameters through the experiments and our algorithm can achieve real-time processing speeds.
Magnetic localization and orientation of the capsule endoscope based on a random complex algorithm
He, Xiaoqi; Zheng, Zizhao; Hu, Chao
2015-01-01
The development of the capsule endoscope has made possible the examination of the whole gastrointestinal tract without much pain. However, there are still some important problems to be solved, among which, one important problem is the localization of the capsule. Currently, magnetic positioning technology is a suitable method for capsule localization, and this depends on a reliable system and algorithm. In this paper, based on the magnetic dipole model as well as magnetic sensor array, we propose nonlinear optimization algorithms using a random complex algorithm, applied to the optimization calculation for the nonlinear function of the dipole, to determine the three-dimensional position parameters and two-dimensional direction parameters. The stability and the antinoise ability of the algorithm is compared with the Levenberg–Marquart algorithm. The simulation and experiment results show that in terms of the error level of the initial guess of magnet location, the random complex algorithm is more accurate, more stable, and has a higher “denoise” capacity, with a larger range for initial guess values. PMID:25914561
Log-linear model based behavior selection method for artificial fish swarm algorithm.
Huang, Zhehuang; Chen, Yidong
2015-01-01
Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm. PMID:25691895
Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm
Huang, Zhehuang; Chen, Yidong
2015-01-01
Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm. PMID:25691895
NASA Astrophysics Data System (ADS)
Wu, Qiong; Wang, Jihua; Wang, Cheng; Xu, Tongyu
2016-09-01
Genetic algorithm (GA) has a significant effect in the band optimization selection of Partial Least Squares (PLS) correction model. Application of genetic algorithm in selection of characteristic bands can achieve the optimal solution more rapidly, effectively improve measurement accuracy and reduce variables used for modeling. In this study, genetic algorithm as a module conducted band selection for the application of hyperspectral imaging in nondestructive testing of corn seedling leaves, and GA-PLS model was established. In addition, PLS quantitative model of full spectrum and experienced-spectrum region were established in order to suggest the feasibility of genetic algorithm optimizing wave bands, and model robustness was evaluated. There were 12 characteristic bands selected by genetic algorithm. With reflectance values of corn seedling component information at spectral characteristic wavelengths corresponding to 12 characteristic bands as variables, a model about SPAD values of corn leaves acquired was established by PLS, and modeling results showed r = 0.7825. The model results were better than those of PLS model established in full spectrum and experience-based selected bands. The results suggested that genetic algorithm can be used for data optimization and screening before establishing the corn seedling component information model by PLS method and effectively increase measurement accuracy and greatly reduce variables used for modeling.
A multiobjective evolutionary algorithm to find community structures based on affinity propagation
NASA Astrophysics Data System (ADS)
Shang, Ronghua; Luo, Shuang; Zhang, Weitong; Stolkin, Rustam; Jiao, Licheng
2016-07-01
Community detection plays an important role in reflecting and understanding the topological structure of complex networks, and can be used to help mine the potential information in networks. This paper presents a Multiobjective Evolutionary Algorithm based on Affinity Propagation (APMOEA) which improves the accuracy of community detection. Firstly, APMOEA takes the method of affinity propagation (AP) to initially divide the network. To accelerate its convergence, the multiobjective evolutionary algorithm selects nondominated solutions from the preliminary partitioning results as its initial population. Secondly, the multiobjective evolutionary algorithm finds solutions approximating the true Pareto optimal front through constantly selecting nondominated solutions from the population after crossover and mutation in iterations, which overcomes the tendency of data clustering methods to fall into local optima. Finally, APMOEA uses an elitist strategy, called "external archive", to prevent degeneration during the process of searching using the multiobjective evolutionary algorithm. According to this strategy, the preliminary partitioning results obtained by AP will be archived and participate in the final selection of Pareto-optimal solutions. Experiments on benchmark test data, including both computer-generated networks and eight real-world networks, show that the proposed algorithm achieves more accurate results and has faster convergence speed compared with seven other state-of-art algorithms.
Log-linear model based behavior selection method for artificial fish swarm algorithm.
Huang, Zhehuang; Chen, Yidong
2015-01-01
Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.
Algorithm for Autonomous Landing
NASA Technical Reports Server (NTRS)
Kuwata, Yoshiaki
2011-01-01
Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.
GOES-West Shows U.S. West's Record Rainfall
A new time-lapse animation of data from NOAA's GOES-West satellite provides a good picture of why the U.S. West Coast continues to experience record rainfall. The new animation shows the movement o...
Rempp, Florian; Mahler, Guenter; Michel, Mathias
2007-09-15
We introduce a scheme to perform the cooling algorithm, first presented by Boykin et al. in 2002, for an arbitrary number of times on the same set of qbits. We achieve this goal by adding an additional SWAP gate and a bath contact to the algorithm. This way one qbit may repeatedly be cooled without adding additional qbits to the system. By using a product Liouville space to model the bath contact we calculate the density matrix of the system after a given number of applications of the algorithm.
NASA Technical Reports Server (NTRS)
Chan, Hak-Wai; Yan, Tsun-Yee
1989-01-01
Algorithm developed for optimal routing of packets of data along links of multilink, multinode digital communication network. Algorithm iterative and converges to cost-optimal assignment independent of initial assignment. Each node connected to other nodes through links, each containing number of two-way channels. Algorithm assigns channels according to message traffic leaving and arriving at each node. Modified to take account of different priorities among packets belonging to different users by using different delay constraints or imposing additional penalties via cost function.
NASA Astrophysics Data System (ADS)
Ahmed, Yasser A.; Afifi, Hossam; Rubino, Gerardo
1999-05-01
This paper present a new algorithm for stereo matching. The main idea is to decompose the original problem into independent hierarchical and more elementary problems that can be solved faster without any complicated mathematics using BBD. To achieve that, we use a new image feature called 'continuity feature' instead of classical noise. This feature can be extracted from any kind of images by a simple process and without using a searching technique. A new matching technique is proposed to match the continuity feature. The new algorithm resolves the main disadvantages of feature based stereo matching algorithms.
Global structual optimizations of surface systems with a genetic algorithm
Chuang, Feng-Chuan
2005-01-01
Global structural optimizations with a genetic algorithm were performed for atomic cluster and surface systems including aluminum atomic clusters, Si magic clusters on the Si(111) 7 x 7 surface, silicon high-index surfaces, and Ag-induced Si(111) reconstructions. First, the global structural optimizations of neutral aluminum clusters Al_{n} algorithm in combination with tight-binding and first-principles calculations were performed to study the structures of magic clusters on the Si(111) 7 x 7 surface. Extensive calculations show that the magic cluster observed in scanning tunneling microscopy (STM) experiments consist of eight Si atoms. Simulated STM images of the Si magic cluster exhibit a ring-like feature similar to STM experiments. Third, a genetic algorithm coupled with a highly optimized empirical potential were used to determine the lowest energy structure of high-index semiconductor surfaces. The lowest energy structures of Si(105) and Si(114) were determined successfully. The results of Si(105) and Si(114) are reported within the framework of highly optimized empirical potential and first-principles calculations. Finally, a genetic algorithm coupled with Si and Ag tight-binding potentials were used to search for Ag-induced Si(111) reconstructions at various Ag and Si coverages. The optimized structural models of √3 x √3, 3 x 1, and 5 x 2 phases were reported using first-principles calculations. A novel model is found to have lower surface energy than the proposed double-honeycomb chained (DHC) model both for Au/Si(111) 5 x 2 and Ag/Si(111) 5 x 2 systems.
Improving Search Algorithms by Using Intelligent Coordinates
NASA Technical Reports Server (NTRS)
Wolpert, David H.; Tumer, Kagan; Bandari, Esfandiar
2004-01-01
We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.
Design and implementation of parallel multigrid algorithms
NASA Technical Reports Server (NTRS)
Chan, Tony F.; Tuminaro, Ray S.
1988-01-01
Techniques for mapping multigrid algorithms to solve elliptic PDEs on hypercube parallel computers are described and demonstrated. The need for proper data mapping to minimize communication distances is stressed, and an execution-time model is developed to show how algorithm efficiency is affected by changes in the machine and algorithm parameters. Particular attention is then given to the case of coarse computational grids, which can lead to idle processors, load imbalances, and inefficient performance. It is shown that convergence can be improved by using idle processors to solve a new problem concurrently on the fine grid defined by a splitting.
Quantum hyperparallel algorithm for matrix multiplication.
Zhang, Xin-Ding; Zhang, Xiao-Ming; Xue, Zheng-Yuan
2016-01-01
Hyperentangled states, entangled states with more than one degree of freedom, are considered as promising resource in quantum computation. Here we present a hyperparallel quantum algorithm for matrix multiplication with time complexity O(N(2)), which is better than the best known classical algorithm. In our scheme, an N dimensional vector is mapped to the state of a single source, which is separated to N paths. With the assistance of hyperentangled states, the inner product of two vectors can be calculated with a time complexity independent of dimension N. Our algorithm shows that hyperparallel quantum computation may provide a useful tool in quantum machine learning and "big data" analysis. PMID:27125586
Quantum hyperparallel algorithm for matrix multiplication
NASA Astrophysics Data System (ADS)
Zhang, Xin-Ding; Zhang, Xiao-Ming; Xue, Zheng-Yuan
2016-04-01
Hyperentangled states, entangled states with more than one degree of freedom, are considered as promising resource in quantum computation. Here we present a hyperparallel quantum algorithm for matrix multiplication with time complexity O(N2), which is better than the best known classical algorithm. In our scheme, an N dimensional vector is mapped to the state of a single source, which is separated to N paths. With the assistance of hyperentangled states, the inner product of two vectors can be calculated with a time complexity independent of dimension N. Our algorithm shows that hyperparallel quantum computation may provide a useful tool in quantum machine learning and “big data” analysis.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models
Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou
2015-01-01
Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1)βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations. PMID:26502409
Authenticated algorithms for Byzantine agreement
Dolev, D.; Strong, H.R.
1983-11-01
Reaching agreement in a distributed system in the presence of fault processors is a central issue for reliable computer systems. Using an authentication protocol, one can limit the undetected behavior of faulty processors to a simple failure to relay messages to all intended targets. In this paper the authors show that, in spite of such an ability to limit faulty behavior, and no matter what message types or protocols are allowed, reaching (Byzantine) agreement requires at least t+1 phases or rounds of information exchange, where t is an upper bound on the number of faulty processors. They present algorithms for reaching agreement based on authentication that require a total number of messages sent by correctly operating processors that is polynomial in both t and the number of processors, n. The best algorithm uses only t+1 phases and o(nt) messages. 9 references.
A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning
NASA Astrophysics Data System (ADS)
Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei
2013-03-01
In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.
A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning
NASA Astrophysics Data System (ADS)
Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei
2012-04-01
In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.
Guidance algorithms for a free-flying space robot
NASA Technical Reports Server (NTRS)
Brindle, A. F.; Viggh, H. E. M.; Albert, J. H.
1989-01-01
Robotics is a promising technology for assembly, servicing, and maintenance of platforms in space. Several aspects of planning and guidance for telesupervised and fully autonomous robotic servicers are investigated. Guidance algorithms for proximity operation of a free flyer are described. Numeric trajectory optimization is combined with artificial intelligence based obstacle avoidance. An initial algorithm and the results of its simulating platform servicing scenario are discussed. A second algorithm experiment is then proposed.
2013-07-29
The OpenEIS Algorithm package seeks to provide a low-risk path for building owners, service providers and managers to explore analytical methods for improving building control and operational efficiency. Users of this software can analyze building data, and learn how commercial implementations would provide long-term value. The code also serves as a reference implementation for developers who wish to adapt the algorithms for use in commercial tools or service offerings.
The Superior Lambert Algorithm
NASA Astrophysics Data System (ADS)
der, G.
2011-09-01
Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most
[An Algorithm for Correcting Fetal Heart Rate Baseline].
Li, Xiaodong; Lu, Yaosheng
2015-10-01
Fetal heart rate (FHR) baseline estimation is of significance for the computerized analysis of fetal heart rate and the assessment of fetal state. In our work, a fetal heart rate baseline correction algorithm was presented to make the existing baseline more accurate and fit to the tracings. Firstly, the deviation of the existing FHR baseline was found and corrected. And then a new baseline was obtained finally after treatment with some smoothing methods. To assess the performance of FHR baseline correction algorithm, a new FHR baseline estimation algorithm that combined baseline estimation algorithm and the baseline correction algorithm was compared with two existing FHR baseline estimation algorithms. The results showed that the new FHR baseline estimation algorithm did well in both accuracy and efficiency. And the results also proved the effectiveness of the FHR baseline correction algorithm.
Improved Bat Algorithm Applied to Multilevel Image Thresholding
2014-01-01
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733
Implementations of back propagation algorithm in ecosystems applications
NASA Astrophysics Data System (ADS)
Ali, Khalda F.; Sulaiman, Riza; Elamir, Amir Mohamed
2015-05-01
Artificial Neural Networks (ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is in solving problems which are too complex for conventional technologies, that do not have an algorithmic solutions or their algorithmic Solutions is too complex to be found. In general, because of their abstraction from the biological brain, ANNs are developed from concept that evolved in the late twentieth century neuro-physiological experiments on the cells of the human brain to overcome the perceived inadequacies with conventional ecological data analysis methods. ANNs have gained increasing attention in ecosystems applications, because of ANN's capacity to detect patterns in data through non-linear relationships, this characteristic confers them a superior predictive ability. In this research, ANNs is applied in an ecological system analysis. The neural networks use the well known Back Propagation (BP) Algorithm with the Delta Rule for adaptation of the system. The Back Propagation (BP) training Algorithm is an effective analytical method for adaptation of the ecosystems applications, the main reason because of their capacity to detect patterns in data through non-linear relationships. This characteristic confers them a superior predicting ability. The BP algorithm uses supervised learning, which means that we provide the algorithm with examples of the inputs and outputs we want the network to compute, and then the error is calculated. The idea of the back propagation algorithm is to reduce this error, until the ANNs learns the training data. The training begins with random weights, and the goal is to adjust them so that the error will be minimal. This research evaluated the use of artificial neural networks (ANNs) techniques in an ecological system analysis and modeling. The experimental results from this research demonstrate that an artificial neural network system can be trained to act as an expert
An improved localization algorithm based on genetic algorithm in wireless sensor networks.
Peng, Bo; Li, Lei
2015-04-01
Wireless sensor network (WSN) are widely used in many applications. A WSN is a wireless decentralized structure network comprised of nodes, which autonomously set up a network. The node localization that is to be aware of position of the node in the network is an essential part of many sensor network operations and applications. The existing localization algorithms can be classified into two categories: range-based and range-free. The range-based localization algorithm has requirements on hardware, thus is expensive to be implemented in practice. The range-free localization algorithm reduces the hardware cost. Because of the hardware limitations of WSN devices, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. However, these techniques usually have higher localization error compared to the range-based algorithms. DV-Hop is a typical range-free localization algorithm utilizing hop-distance estimation. In this paper, we propose an improved DV-Hop algorithm based on genetic algorithm. Simulation results show that our proposed algorithm improves the localization accuracy compared with previous algorithms.
Combined string searching algorithm based on knuth-morris- pratt and boyer-moore algorithms
NASA Astrophysics Data System (ADS)
Tsarev, R. Yu; Chernigovskiy, A. S.; Tsareva, E. A.; Brezitskaya, V. V.; Nikiforov, A. Yu; Smirnov, N. A.
2016-04-01
The string searching task can be classified as a classic information processing task. Users either encounter the solution of this task while working with text processors or browsers, employing standard built-in tools, or this task is solved unseen by the users, while they are working with various computer programmes. Nowadays there are many algorithms for solving the string searching problem. The main criterion of these algorithms’ effectiveness is searching speed. The larger the shift of the pattern relative to the string in case of pattern and string characters’ mismatch is, the higher is the algorithm running speed. This article offers a combined algorithm, which has been developed on the basis of well-known Knuth-Morris-Pratt and Boyer-Moore string searching algorithms. These algorithms are based on two different basic principles of pattern matching. Knuth-Morris-Pratt algorithm is based upon forward pattern matching and Boyer-Moore is based upon backward pattern matching. Having united these two algorithms, the combined algorithm allows acquiring the larger shift in case of pattern and string characters’ mismatch. The article provides an example, which illustrates the results of Boyer-Moore and Knuth-Morris- Pratt algorithms and combined algorithm’s work and shows advantage of the latter in solving string searching problem.
Khaji, Erfan; Karami, Masoumeh; Garkani-Nejad, Zahra
2016-02-21
Predicting the native structure of proteins based on half-sphere exposure and contact numbers has been studied deeply within recent years. Online predictors of these vectors and secondary structures of amino acids sequences have made it possible to design a function for the folding process. By choosing variant structures and directs for each secondary structure, a random conformation can be generated, and a potential function can then be assigned. Minimizing the potential function utilizing meta-heuristic algorithms is the final step of finding the native structure of a given amino acid sequence. In this work, Imperialist Competitive algorithm was used in order to accelerate the process of minimization. Moreover, we applied an adaptive procedure to apply revolutionary changes. Finally, we considered a more accurate tool for prediction of secondary structure. The results of the computational experiments on standard benchmark show the superiority of the new algorithm over the previous methods with similar potential function. PMID:26718864
Jin, Ying; Song, Yang; Qu, Xiangju; Li, Zhenhua; Ji, Yunjing; He, Anzhi
2016-08-01
Flame tomography of chemiluminescence is a necessary combustion diagnostic technique that provides instantaneous 3D information on flame structure and excited species concentrations. During combustion diagnostics, imaging overexposure always causes missing information, which obviously decreases the accuracy in further reconstructions. In order to compensate imaging overexposure, a hybrid algorithm combining weight correction and Tikhonov's regularization is proposed in this paper. The intensity of the overexposure region can be estimated via the accumulation of weight coefficients. Meanwhile, Tikhonov's regularization is utilized to ameliorate the quality of reconstruction. The numerical simulation quantitatively evaluates the performance of the hybrid algorithm. Additionally, an experiment system consisting of 12 cameras was established to reconstruct the 3D combustion structure of axisymmetric flame with different exposure time settings. This work further investigates dynamic nonaxisymmetric propane diffusion flame. The obtained results show that the hybrid algorithm can effectively reveal the flame structure less influenced by imaging overexposure and achieve better results.
New algorithm for efficient pattern recall using a static threshold with the Steinbuch Lernmatrix
NASA Astrophysics Data System (ADS)
Juan Carbajal Hernández, José; Sánchez Fernández, Luis P.
2011-03-01
An associative memory is a binary relationship between inputs and outputs, which is stored in an M matrix. The fundamental purpose of an associative memory is to recover correct output patterns from input patterns, which can be altered by additive, subtractive or combined noise. The Steinbuch Lernmatrix was the first associative memory developed in 1961, and is used as a pattern recognition classifier. However, a misclassification problem is presented when crossbar saturation occurs. A new algorithm that corrects the misclassification in the Lernmatrix is proposed in this work. The results of crossbar saturation with fundamental patterns demonstrate a better performance of pattern recalling using the new algorithm. Experiments with real data show a more efficient classifier when the algorithm is introduced in the original Lernmatrix. Therefore, the thresholded Lernmatrix memory emerges as a suitable and alternative classifier to be used in the developing pattern processing field.
Effective Echo Detection and Accurate Orbit Estimation Algorithms for Space Debris Radar
NASA Astrophysics Data System (ADS)
Isoda, Kentaro; Sakamoto, Takuya; Sato, Toru
Orbit estimation of space debris, objects of no inherent value orbiting the earth, is a task that is important for avoiding collisions with spacecraft. The Kamisaibara Spaceguard Center radar system was built in 2004 as the first radar facility in Japan devoted to the observation of space debris. In order to detect the smaller debris, coherent integration is effective in improving SNR (Signal-to-Noise Ratio). However, it is difficult to apply coherent integration to real data because the motions of the targets are unknown. An effective algorithm is proposed for echo detection and orbit estimation of the faint echoes from space debris. The characteristics of the evaluation function are utilized by the algorithm. Experiments show the proposed algorithm improves SNR by 8.32dB and enables estimation of orbital parameters accurately to allow for re-tracking with a single radar.
NASA Astrophysics Data System (ADS)
Khambampati, A. K.; Rashid, A.; Kim, B. S.; Liu, Dong; Kim, S.; Kim, K. Y.
2010-04-01
EIT has been used for the dynamic estimation of organ boundaries. One specific application in this context is the estimation of lung boundaries during pulmonary circulation. This would help track the size and shape of lungs of the patients suffering from diseases like pulmonary edema and acute respiratory failure (ARF). The dynamic boundary estimation of the lungs can also be utilized to set and control the air volume and pressure delivered to the patients during artificial ventilation. In this paper, the expectation-maximization (EM) algorithm is used as an inverse algorithm to estimate the non-stationary lung boundary. The uncertainties caused in Kalman-type filters due to inaccurate selection of model parameters are overcome using EM algorithm. Numerical experiments using chest shaped geometry are carried out with proposed method and the performance is compared with extended Kalman filter (EKF). Results show superior performance of EM in estimation of the lung boundary.
The Search for Effective Algorithms for Recovery from Loss of Separation
NASA Technical Reports Server (NTRS)
Butler, Ricky W.; Hagen, George E.; Maddalon, Jeffrey M.; Munoz, Cesar A.; Narawicz, Anthony J.
2012-01-01
Our previous work presented an approach for developing high confidence algorithms for recovering aircraft from loss of separation situations. The correctness theorems for the algorithms relied on several key assumptions, namely that state data for all local aircraft is perfectly known, that resolution maneuvers can be achieved instantaneously, and that all aircraft compute resolutions using exactly the same data. Experiments showed that these assumptions were adequate in cases where the aircraft are far away from losing separation, but are insufficient when the aircraft have already lost separation. This paper describes the results of this experimentation and proposes a new criteria specification for loss of separation recovery that preserves the formal safety properties of the previous criteria while overcoming some key limitations. Candidate algorithms that satisfy the new criteria are presented.
Khaji, Erfan; Karami, Masoumeh; Garkani-Nejad, Zahra
2016-02-21
Predicting the native structure of proteins based on half-sphere exposure and contact numbers has been studied deeply within recent years. Online predictors of these vectors and secondary structures of amino acids sequences have made it possible to design a function for the folding process. By choosing variant structures and directs for each secondary structure, a random conformation can be generated, and a potential function can then be assigned. Minimizing the potential function utilizing meta-heuristic algorithms is the final step of finding the native structure of a given amino acid sequence. In this work, Imperialist Competitive algorithm was used in order to accelerate the process of minimization. Moreover, we applied an adaptive procedure to apply revolutionary changes. Finally, we considered a more accurate tool for prediction of secondary structure. The results of the computational experiments on standard benchmark show the superiority of the new algorithm over the previous methods with similar potential function.
Jin, Ying; Song, Yang; Qu, Xiangju; Li, Zhenhua; Ji, Yunjing; He, Anzhi
2016-08-01
Flame tomography of chemiluminescence is a necessary combustion diagnostic technique that provides instantaneous 3D information on flame structure and excited species concentrations. During combustion diagnostics, imaging overexposure always causes missing information, which obviously decreases the accuracy in further reconstructions. In order to compensate imaging overexposure, a hybrid algorithm combining weight correction and Tikhonov's regularization is proposed in this paper. The intensity of the overexposure region can be estimated via the accumulation of weight coefficients. Meanwhile, Tikhonov's regularization is utilized to ameliorate the quality of reconstruction. The numerical simulation quantitatively evaluates the performance of the hybrid algorithm. Additionally, an experiment system consisting of 12 cameras was established to reconstruct the 3D combustion structure of axisymmetric flame with different exposure time settings. This work further investigates dynamic nonaxisymmetric propane diffusion flame. The obtained results show that the hybrid algorithm can effectively reveal the flame structure less influenced by imaging overexposure and achieve better results. PMID:27505371
Liver Segmentation Based on Snakes Model and Improved GrowCut Algorithm in Abdominal CT Image
He, Baochun; Ma, Zhiyuan; Zong, Mao; Zhou, Xiangrong; Fujita, Hiroshi
2013-01-01
A novel method based on Snakes Model and GrowCut algorithm is proposed to segment liver region in abdominal CT images. First, according to the traditional GrowCut method, a pretreatment process using K-means algorithm is conducted to reduce the running time. Then, the segmentation result of our improved GrowCut approach is used as an initial contour for the future precise segmentation based on Snakes model. At last, several experiments are carried out to demonstrate the performance of our proposed approach and some comparisons are conducted between the traditional GrowCut algorithm. Experimental results show that the improved approach not only has a better robustness and precision but also is more efficient than the traditional GrowCut method. PMID:24066017
A 3-D industrial CT reconstruction algorithm to directly reconstruct the characteristics
NASA Astrophysics Data System (ADS)
Zhao, Ying-Liang; Wang, Li-Ming; Han, Yan
2011-01-01
In traditional 3-D CT reconstruction methods, for the projection procedure is low-pass smoothing, the high-frequency characters are difficult to obtain after the projection data are reconstructed. In addition the design and implementation of three-dimensional filter are relatively harder. A new 3D industrial CT reconstruction algorithm to directly reconstruct the characteristics is put forth. Based on the FDK method and the trait of RADON transform, the feasibility of the novel algorithm is theoretically deduced. Combined with the wavelet, it is deduced to extract the characteristics using the 2-D wavelet transform and to directly reconstruct the characteristics in 3-D CT. The experiments show that the algorithm can preferably stand out the useful information, is of engineering practicability and the design of the filter is relatively simpler.
Scheduling for the National Hockey League Using a Multi-objective Evolutionary Algorithm
NASA Astrophysics Data System (ADS)
Craig, Sam; While, Lyndon; Barone, Luigi
We describe a multi-objective evolutionary algorithm that derives schedules for the National Hockey League according to three objectives: minimising the teams' total travel, promoting equity in rest time between games, and minimising long streaks of home or away games. Experiments show that the system is able to derive schedules that beat the 2008-9 NHL schedule in all objectives simultaneously, and that it returns a set of schedules that offer a range of trade-offs across the objectives.
Quantum Adiabatic Algorithms and Large Spin Tunnelling
NASA Technical Reports Server (NTRS)
Boulatov, A.; Smelyanskiy, V. N.
2003-01-01
We provide a theoretical study of the quantum adiabatic evolution algorithm with different evolution paths proposed in this paper. The algorithm is applied to a random binary optimization problem (a version of the 3-Satisfiability problem) where the n-bit cost function is symmetric with respect to the permutation of individual bits. The evolution paths are produced, using the generic control Hamiltonians H (r) that preserve the bit symmetry of the underlying optimization problem. In the case where the ground state of H(0) coincides with the totally-symmetric state of an n-qubit system the algorithm dynamics is completely described in terms of the motion of a spin-n/2. We show that different control Hamiltonians can be parameterized by a set of independent parameters that are expansion coefficients of H (r) in a certain universal set of operators. Only one of these operators can be responsible for avoiding the tunnelling in the spin-n/2 system during the quantum adiabatic algorithm. We show that it is possible to select a coefficient for this operator that guarantees a polynomial complexity of the algorithm for all problem instances. We show that a successful evolution path of the algorithm always corresponds to the trajectory of a classical spin-n/2 and provide a complete characterization of such paths.
DNA-based watermarks using the DNA-Crypt algorithm
Heider, Dominik; Barnekow, Angelika
2007-01-01
Background The aim of this paper is to demonstrate the application of watermarks based on DNA sequences to identify the unauthorized use of genetically modified organisms (GMOs) protected by patents. Predicted mutations in the genome can be corrected by the DNA-Crypt program leaving the encrypted information intact. Existing DNA cryptographic and steganographic algorithms use synthetic DNA sequences to store binary information however, although these sequences can be used for authentication, they may change the target DNA sequence when introduced into living organisms. Results The DNA-Crypt algorithm and image steganography are based on the same watermark-hiding principle, namely using the least significant base in case of DNA-Crypt and the least significant bit in case of the image steganography. It can be combined with binary encryption algorithms like AES, RSA or Blowfish. DNA-Crypt is able to correct mutations in the target DNA with several mutation correction codes such as the Hamming-code or the WDH-code. Mutations which can occur infrequently may destroy the encrypted information, however an integrated fuzzy controller decides on a set of heuristics based on three input dimensions, and recommends whether or not to use a correction code. These three input dimensions are the length of the sequence, the individual mutation rate and the stability over time, which is represented by the number of generations. In silico experiments using the Ypt7 in Saccharomyces cerevisiae shows that the DNA watermarks produced by DNA-Crypt do not alter the translation of mRNA into protein. Conclusion The program is able to store watermarks in living organisms and can maintain the original information by correcting mutations itself. Pairwise or multiple sequence alignments show that DNA-Crypt produces few mismatches between the sequences similar to all steganographic algorithms. PMID:17535434
Lightning detection and exposure algorithms for smartphones
NASA Astrophysics Data System (ADS)
Wang, Haixin; Shao, Xiaopeng; Wang, Lin; Su, Laili; Huang, Yining
2015-05-01
This study focuses on the key theory of lightning detection, exposure and the experiments. Firstly, the algorithm based on differential operation between two adjacent frames is selected to remove the lightning background information and extract lighting signal, and the threshold detection algorithm is applied to achieve the purpose of precise detection of lightning. Secondly, an algorithm is proposed to obtain scene exposure value, which can automatically detect external illumination status. Subsequently, a look-up table could be built on the basis of the relationships between the exposure value and average image brightness to achieve rapid automatic exposure. Finally, based on a USB 3.0 industrial camera including a CMOS imaging sensor, a set of hardware test platform is established and experiments are carried out on this platform to verify the performances of the proposed algorithms. The algorithms can effectively and fast capture clear lightning pictures such as special nighttime scenes, which will provide beneficial supporting to the smartphone industry, since the current exposure methods in smartphones often lost capture or induce overexposed or underexposed pictures.
[Multispectral image compression algorithms for color reproduction].
Liang, Wei; Zeng, Ping; Luo, Xue-mei; Wang, Yi-feng; Xie, Kun
2015-01-01
In order to improve multispectral images compression efficiency and further facilitate their storage and transmission for the application of color reproduction and so on, in which fields high color accuracy is desired, WF serial methods is proposed, and APWS_RA algorithm is designed. Then the WF_APWS_RA algorithm, which has advantages of low complexity, good illuminant stability and supporting consistent coior reproduction across devices, is presented. The conventional MSE based wavelet embedded coding principle is first studied. And then color perception distortion criterion and visual characteristic matrix W are proposed. Meanwhile, APWS_RA algorithm is formed by optimizing the. rate allocation strategy of APWS. Finally, combined above technologies, a new coding method named WF_APWS_RA is designed. Colorimetric error criterion is used in the algorithm and APWS_RA is applied on visual weighted multispectral image. In WF_APWS_RA, affinity propagation clustering is utilized to exploit spectral correlation of weighted image. Then two-dimensional wavelet transform is used to remove the spatial redundancy. Subsequently, error compensation mechanism and rate pre-allocation are combined to accomplish the embedded wavelet coding. Experimental results show that at the same bit rate, compared with classical coding algorithms, WF serial algorithms have better performance on color retention. APWS_RA preserves least spectral error and WF APWS_RA algorithm has obvious superiority on color accuracy.
LCD motion blur: modeling, analysis, and algorithm.
Chan, Stanley H; Nguyen, Truong Q
2011-08-01
Liquid crystal display (LCD) devices are well known for their slow responses due to the physical limitations of liquid crystals. Therefore, fast moving objects in a scene are often perceived as blurred. This effect is known as the LCD motion blur. In order to reduce LCD motion blur, an accurate LCD model and an efficient deblurring algorithm are needed. However, existing LCD motion blur models are insufficient to reflect the limitation of human-eye-tracking system. Also, the spatiotemporal equivalence in LCD motion blur models has not been proven directly in the discrete 2-D spatial domain, although it is widely used. There are three main contributions of this paper: modeling, analysis, and algorithm. First, a comprehensive LCD motion blur model is presented, in which human-eye-tracking limits are taken into consideration. Second, a complete analysis of spatiotemporal equivalence is provided and verified using real video sequences. Third, an LCD motion blur reduction algorithm is proposed. The proposed algorithm solves an l(1)-norm regularized least-squares minimization problem using a subgradient projection method. Numerical results show that the proposed algorithm gives higher peak SNR, lower temporal error, and lower spatial error than motion-compensated inverse filtering and Lucy-Richardson deconvolution algorithm, which are two state-of-the-art LCD deblurring algorithms. PMID:21292596
Novel and efficient tag SNPs selection algorithms.
Chen, Wen-Pei; Hung, Che-Lun; Tsai, Suh-Jen Jane; Lin, Yaw-Ling
2014-01-01
SNPs are the most abundant forms of genetic variations amongst species; the association studies between complex diseases and SNPs or haplotypes have received great attention. However, these studies are restricted by the cost of genotyping all SNPs; thus, it is necessary to find smaller subsets, or tag SNPs, representing the rest of the SNPs. In fact, the existing tag SNP selection algorithms are notoriously time-consuming. An efficient algorithm for tag SNP selection was presented, which was applied to analyze the HapMap YRI data. The experimental results show that the proposed algorithm can achieve better performance than the existing tag SNP selection algorithms; in most cases, this proposed algorithm is at least ten times faster than the existing methods. In many cases, when the redundant ratio of the block is high, the proposed algorithm can even be thousands times faster than the previously known methods. Tools and web services for haplotype block analysis integrated by hadoop MapReduce framework are also developed using the proposed algorithm as computation kernels. PMID:24212035
Image segmentation using an improved differential algorithm
NASA Astrophysics Data System (ADS)
Gao, Hao; Shi, Yujiao; Wu, Dongmei
2014-10-01
Among all the existing segmentation techniques, the thresholding technique is one of the most popular due to its simplicity, robustness, and accuracy (e.g. the maximum entropy method, Otsu's method, and K-means clustering). However, the computation time of these algorithms grows exponentially with the number of thresholds due to their exhaustive searching strategy. As a population-based optimization algorithm, differential algorithm (DE) uses a population of potential solutions and decision-making processes. It has shown considerable success in solving complex optimization problems within a reasonable time limit. Thus, applying this method into segmentation algorithm should be a good choice during to its fast computational ability. In this paper, we first propose a new differential algorithm with a balance strategy, which seeks a balance between the exploration of new regions and the exploitation of the already sampled regions. Then, we apply the new DE into the traditional Otsu's method to shorten the computation time. Experimental results of the new algorithm on a variety of images show that, compared with the EA-based thresholding methods, the proposed DE algorithm gets more effective and efficient results. It also shortens the computation time of the traditional Otsu method.
Least significant qubit algorithm for quantum images
NASA Astrophysics Data System (ADS)
Sang, Jianzhi; Wang, Shen; Li, Qiong
2016-08-01
To study the feasibility of the classical image least significant bit (LSB) information hiding algorithm on quantum computer, a least significant qubit (LSQb) information hiding algorithm of quantum image is proposed. In this paper, we focus on a novel quantum representation for color digital images (NCQI). Firstly, by designing the three qubits comparator and unitary operators, the reasonability and feasibility of LSQb based on NCQI are presented. Then, the concrete LSQb information hiding algorithm is proposed, which can realize the aim of embedding the secret qubits into the least significant qubits of RGB channels of quantum cover image. Quantum circuit of the LSQb information hiding algorithm is also illustrated. Furthermore, the secrets extracting algorithm and circuit are illustrated through utilizing control-swap gates. The two merits of our algorithm are: (1) it is absolutely blind and (2) when extracting secret binary qubits, it does not need any quantum measurement operation or any other help from classical computer. Finally, simulation and comparative analysis show the performance of our algorithm.
A parallel algorithm for the eigenvalues and eigenvectors for a general complex matrix
NASA Technical Reports Server (NTRS)
Shroff, Gautam
1989-01-01
A new parallel Jacobi-like algorithm is developed for computing the eigenvalues of a general complex matrix. Most parallel methods for this parallel typically display only linear convergence. Sequential norm-reducing algorithms also exit and they display quadratic convergence in most cases. The new algorithm is a parallel form of the norm-reducing algorithm due to Eberlein. It is proven that the asymptotic convergence rate of this algorithm is quadratic. Numerical experiments are presented which demonstrate the quadratic convergence of the algorithm and certain situations where the convergence is slow are also identified. The algorithm promises to be very competitive on a variety of parallel architectures.
Hierarchical artificial bee colony algorithm for RFID network planning optimization.
Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong
2014-01-01
This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200
Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization
Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong
2014-01-01
This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200
Optimal design of link systems using successive zooming genetic algorithm
NASA Astrophysics Data System (ADS)
Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo
2009-07-01
Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.
Hierarchical artificial bee colony algorithm for RFID network planning optimization.
Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong
2014-01-01
This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.
A hybrid artificial bee colony algorithm for numerical function optimization
NASA Astrophysics Data System (ADS)
Alqattan, Zakaria N.; Abdullah, Rosni
2015-02-01
Artificial Bee Colony (ABC) algorithm is one of the swarm intelligence algorithms; it has been introduced by Karaboga in 2005. It is a meta-heuristic optimization search algorithm inspired from the intelligent foraging behavior of the honey bees in nature. Its unique search process made it as one of the most competitive algorithm with some other search algorithms in the area of optimization, such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, the ABC performance of the local search process and the bee movement or the solution improvement equation still has some weaknesses. The ABC is good in avoiding trapping at the local optimum but it spends its time searching around unpromising random selected solutions. Inspired by the PSO, we propose a Hybrid Particle-movement ABC algorithm called HPABC, which adapts the particle movement process to improve the exploration of the original ABC algorithm. Numerical benchmark functions were used in order to experimentally test the HPABC algorithm. The results illustrate that the HPABC algorithm can outperform the ABC algorithm in most of the experiments (75% better in accuracy and over 3 times faster).
Grooming of arbitrary traffic using improved genetic algorithms
NASA Astrophysics Data System (ADS)
Jiao, Yueguang; Xu, Zhengchun; Zhang, Hanyi
2004-04-01
A genetic algorithm is proposed with permutation based chromosome presentation and roulette wheel selection to solve traffic grooming problems in WDM ring network. The parameters of the algorithm are evaluated by calculating of large amount of traffic patterns at different conditions. Four methods were developed to improve the algorithm, which can be used combining with each other. Effects of them on the algorithm are studied via computer simulations. The results show that they can all make the algorithm more powerful to reduce the number of add-drop multiplexers or wavelengths required in a network.
A Unified Differential Evolution Algorithm for Global Optimization
Qiang, Ji; Mitchell, Chad
2014-06-24
Abstract?In this paper, we propose a new unified differential evolution (uDE) algorithm for single objective global optimization. Instead of selecting among multiple mutation strategies as in the conventional differential evolution algorithm, this algorithm employs a single equation as the mutation strategy. It has the virtue of mathematical simplicity and also provides users the flexbility for broader exploration of different mutation strategies. Numerical tests using twelve basic unimodal and multimodal functions show promising performance of the proposed algorithm in comparison to convential differential evolution algorithms.
Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm
Yang, Zhang; Li, Guo; Weifeng, Ding
2016-01-01
The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428
Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm.
Yang, Zhang; Shufan, Ye; Li, Guo; Weifeng, Ding
2016-01-01
The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428
Aerosol retrieval experiments in the ESA Aerosol_cci project
NASA Astrophysics Data System (ADS)
Holzer-Popp, T.; de Leeuw, G.; Griesfeller, J.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.
2013-08-01
Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010-2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer
Parallel algorithms for the spectral transform method
Foster, I.T.; Worley, P.H.
1994-04-01
The spectral transform method is a standard numerical technique for solving partial differential equations on a sphere and is widely used in atmospheric circulation models. Recent research has identified several promising algorithms for implementing this method on massively parallel computers; however, no detailed comparison of the different algorithms has previously been attempted. In this paper, we describe these different parallel algorithms and report on computational experiments that we have conducted to evaluate their efficiency on parallel computers. The experiments used a testbed code that solves the nonlinear shallow water equations or a sphere; considerable care was taken to ensure that the experiments provide a fair comparison of the different algorithms and that the results are relevant to global models. We focus on hypercube- and mesh-connected multicomputers with cut-through routing, such as the Intel iPSC/860, DELTA, and Paragon, and the nCUBE/2, but also indicate how the results extend to other parallel computer architectures. The results of this study are relevant not only to the spectral transform method but also to multidimensional FFTs and other parallel transforms.
Parallel algorithms for the spectral transform method
Foster, I.T.; Worley, P.H.
1997-05-01
The spectral transform method is a standard numerical technique for solving partial differential equations on a sphere and is widely used in atmospheric circulation models. Recent research has identified several promising algorithms for implementing this method on massively parallel computers; however, no detailed comparison of the different algorithms has previously been attempted. In this paper, the authors describe these different parallel algorithms and report on computational experiments that they have conducted to evaluate their efficiency on parallel computers. The experiments used a testbed code that solves the nonlinear shallow water equations on a sphere; considerable care was taken to ensure that the experiments provide a fair comparison of the different algorithms and that the results are relevant to global models. The authors focus on hypercube- and mesh-connected multicomputers with cut-through routing, such as the Intel iPSC/860, DELTA, and Paragon, and the nCUBE/2, but they also indicate how the results extend to other parallel computer architectures. The results of this study are relevant not only to the spectral transform method but also to multidimensional fast Fourier transforms (FFTs) and other parallel transforms.
Advanced optimization of permanent magnet wigglers using a genetic algorithm
Hajima, Ryoichi
1995-12-31
In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms.
Perceptual Tests of an Algorithm for Musical Key-Finding
ERIC Educational Resources Information Center
Schmuckler, Mark A.; Tomovski, Robert
2005-01-01
Perceiving the tonality of a musical passage is a fundamental aspect of the experience of hearing music. Models for determining tonality have thus occupied a central place in music cognition research. Three experiments investigated 1 well-known model of tonal determination: the Krumhansl-Schmuckler key-finding algorithm. In Experiment 1,…
EARLY EXPERIENCE WITH A HYBRID PROCESSOR: K-MEANS CLUSTERING
M. GOKHALE; ET AL
2001-02-01
We discuss hardware/software coprocessing on a hybrid processor for a compute- and data-intensive hyper-spectral imaging algorithm, K-Means Clustering. The experiments are performed on the Altera Excalibur board using the soft IP core 32-bit NIOS RISC processor. In our experiments, we compare performance of the sequential algorithm with two different accelerated versions. We consider granularity and synchronization issues when mapping an algorithm to a hybrid processor. Our results show that on the Excalibur NIOS, a 15% speedup can be achieved over the sequential algorithm on images with 8 spectral bands where the pixels are divided into 8 categories. Speedup is limited by the communication cost of transferring data from external memory through the NIOS processor to the customized circuits. Our results indicate that future hybrid processors must either (1) have a clock rate 10X the speed of the configurable logic circuits or (2) include dual port memories that both the processor and configurable logic can access. If either of these conditions is met, the hybrid processor will show a factor of 10 speedup over the sequential algorithm. Such systems will combine the convenience of conventional processors with the speed of configurable logic.
Five-dimensional Janis-Newman algorithm
NASA Astrophysics Data System (ADS)
Erbin, Harold; Heurtier, Lucien
2015-08-01
The Janis-Newman algorithm has been shown to be successful in finding new stationary solutions of four-dimensional gravity. Attempts for a generalization to higher dimensions have already been found for the restricted cases with only one angular momentum. In this paper we propose an extension of this algorithm to five-dimensions with two angular momenta—using the prescription of Giampieri—through two specific examples, that are the Myers-Perry and BMPV black holes. We also discuss possible enlargements of our prescriptions to other dimensions and maximal number of angular momenta, and show how dimensions higher than six appear to be much more challenging to treat within this framework. Nonetheless this general algorithm provides a unification of the formulation in d=3,4,5 of the Janis-Newman algorithm, from which several examples are exposed, including the BTZ black hole.
Rigorous estimates for the relegation algorithm
NASA Astrophysics Data System (ADS)
Sansottera, Marco; Ceccaroni, Marta
2016-07-01
We revisit the relegation algorithm by Deprit et al. (Celest. Mech. Dyn. Astron. 79:157-182, 2001) in the light of the rigorous Nekhoroshev's like theory. This relatively recent algorithm is nowadays widely used for implementing closed form analytic perturbation theories, as it generalises the classical Birkhoff normalisation algorithm. The algorithm, here briefly explained by means of Lie transformations, has been so far introduced and used in a formal way, i.e. without providing any rigorous convergence or asymptotic estimates. The overall aim of this paper is to find such quantitative estimates and to show how the results about stability over exponentially long times can be recovered in a simple and effective way, at least in the non-resonant case.
Universal lossless compression algorithm for textual images
NASA Astrophysics Data System (ADS)
al Zahir, Saif
2012-03-01
In recent years, an unparalleled volume of textual information has been transported over the Internet via email, chatting, blogging, tweeting, digital libraries, and information retrieval systems. As the volume of text data has now exceeded 40% of the total volume of traffic on the Internet, compressing textual data becomes imperative. Many sophisticated algorithms were introduced and employed for this purpose including Huffman encoding, arithmetic encoding, the Ziv-Lempel family, Dynamic Markov Compression, and Burrow-Wheeler Transform. My research presents novel universal algorithm for compressing textual images. The algorithm comprises two parts: 1. a universal fixed-to-variable codebook; and 2. our row and column elimination coding scheme. Simulation results on a large number of Arabic, Persian, and Hebrew textual images show that this algorithm has a compression ratio of nearly 87%, which exceeds published results including JBIG2.
A New Pivot Algorithm for Star Identification
NASA Astrophysics Data System (ADS)
Nah, Jakyoung; Yi, Yu; Kim, Yong Ha
2014-09-01
In this study, a star identification algorithm which utilizes pivot patterns instead of apparent magnitude information was developed. The new star identification algorithm consists of two steps of recognition process. In the first step, the brightest star in a sensor image is identified using the orientation of brightness between two stars as recognition information. In the second step, cell indexes are used as new recognition information to identify dimmer stars, which are derived from the brightest star already identified. If we use the cell index information, we can search over limited portion of the star catalogue database, which enables the faster identification of dimmer stars. The new pivot algorithm does not require calibrations on the apparent magnitude of a star but it shows robust characteristics on the errors of apparent magnitude compared to conventional pivot algorithms which require the apparent magnitude information.
Optical rate sensor algorithms
NASA Astrophysics Data System (ADS)
Uhde-Lacovara, Jo A.
1989-12-01
Optical sensors, in particular Charge Coupled Device (CCD) arrays, will be used on Space Station to track stars in order to provide inertial attitude reference. Algorithms are presented to derive attitude rate from the optical sensors. The first algorithm is a recursive differentiator. A variance reduction factor (VRF) of 0.0228 was achieved with a rise time of 10 samples. A VRF of 0.2522 gives a rise time of 4 samples. The second algorithm is based on the direct manipulation of the pixel intensity outputs of the sensor. In 1-dimensional simulations, the derived rate was with 0.07 percent of the actual rate in the presence of additive Gaussian noise with a signal to noise ratio of 60 dB.
Optical rate sensor algorithms
NASA Technical Reports Server (NTRS)
Uhde-Lacovara, Jo A.
1989-01-01
Optical sensors, in particular Charge Coupled Device (CCD) arrays, will be used on Space Station to track stars in order to provide inertial attitude reference. Algorithms are presented to derive attitude rate from the optical sensors. The first algorithm is a recursive differentiator. A variance reduction factor (VRF) of 0.0228 was achieved with a rise time of 10 samples. A VRF of 0.2522 gives a rise time of 4 samples. The second algorithm is based on the direct manipulation of the pixel intensity outputs of the sensor. In 1-dimensional simulations, the derived rate was with 0.07 percent of the actual rate in the presence of additive Gaussian noise with a signal to noise ratio of 60 dB.
Dynamic gate algorithm for multimode fiber Bragg grating sensor systems.
Ganziy, D; Jespersen, O; Woyessa, G; Rose, B; Bang, O
2015-06-20
We propose a novel dynamic gate algorithm (DGA) for precise and accurate peak detection. The algorithm uses a threshold-determined detection window and center of gravity algorithm with bias compensation. We analyze the wavelength fit resolution of the DGA for different values of the signal-to-noise ratio and different peak shapes. Our simulations and experiments demonstrate that the DGA method is fast and robust with better stability and accuracy than conventional algorithms. This makes it very attractive for future implementation in sensing systems, especially based on multimode fiber Bragg gratings. PMID:26193010