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Sample records for muon identification algorithm

  1. Muon Reconstruction and Identification in CMS

    SciTech Connect

    Everett, A.

    2010-02-10

    We present the design strategies and status of the CMS muon reconstruction and identification identification software. Muon reconstruction and identification is accomplished through a variety of complementary algorithms. The CMS muon reconstruction software is based on a Kalman filter technique and reconstructs muons in the standalone muon system, using information from all three types of muon detectors, and links the resulting muon tracks with tracks reconstructed in the silicon tracker. In addition, a muon identification algorithm has been developed which tries to identify muons with high efficiency while maintaining a low probability of misidentification. The muon identification algorithm is complementary by design to the muon reconstruction algorithm that starts track reconstruction in the muon detectors. The identification algorithm accepts reconstructed tracks from the inner tracker and attempts to quantify the muon compatibility for each track using associated calorimeter and muon detector hit information. The performance status is based on detailed detector simulations as well as initial studies using cosmic muon data.

  2. Identification of Low PT Muon with the Atlas Tile Calorimeter

    NASA Astrophysics Data System (ADS)

    Usai, G.

    2005-02-01

    A method for the identification of muons with the ATLAS Tile Calorimeter is presented and its efficiency and mis-tagging fraction are discussed. It is demonstrated that the Tile Calorimeter can identify muons with good efficiency down to 2 GeV/c transverse momentum, where the stand-alone Muon Spectrometer has zero efficiency. This kinematic region is important for study of B meson physics and in the particular for the CP violating decay channels. The effectiveness of this method is tested, in particular, in the case of bbar {b} events at low LHC luminosity (1033cm-1s-2) with full simulation of experimental conditions. The muon identification with the Tile Calorimeter is fast and can be used for muon selection at the trigger level. A method of exploiting the information available in other ATLAS sub-detectors in order to reduce spurious muon-tag and measure the candidate muon momentum is discussed.

  3. Improved autonomous star identification algorithm

    NASA Astrophysics Data System (ADS)

    Luo, Li-Yan; Xu, Lu-Ping; Zhang, Hua; Sun, Jing-Rong

    2015-06-01

    The log-polar transform (LPT) is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm. Project supported by the National Natural Science Foundation of China (Grant Nos. 61172138 and 61401340), the Open Research Fund of the Academy of Satellite Application, China (Grant No. 2014_CXJJ-DH_12), the Fundamental Research Funds for the Central Universities, China (Grant Nos. JB141303 and 201413B), the Natural Science Basic Research Plan in Shaanxi Province, China (Grant No. 2013JQ8040), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130203120004), and the Xi’an Science and Technology Plan, China (Grant. No CXY1350(4)).

  4. Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography

    NASA Astrophysics Data System (ADS)

    Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.

    2014-11-01

    Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.

  5. Ligand Identification Scoring Algorithm (LISA)

    PubMed Central

    Zheng, Zheng; Merz, Kenneth M.

    2011-01-01

    A central problem in de novo drug design is determining the binding affinity of a ligand with a receptor. A new scoring algorithm is presented that estimates the binding affinity of a protein-ligand complex given a three-dimensional structure. The method, LISA (Ligand Identification Scoring Algorithm), uses an empirical scoring function to describe the binding free energy. Interaction terms have been designed to account for van der Waals (VDW) contacts, hydrogen bonding, desolvation effects and metal chelation to model the dissociation equilibrium constants using a linear model. Atom types have been introduced to differentiate the parameters for VDW, H-bonding interactions and metal chelation between different atom pairs. A training set of 492 protein-ligand complexes was selected for the fitting process. Different test sets have been examined to evaluate its ability to predict experimentally measured binding affinities. By comparing with other well known scoring functions, the results show that LISA has advantages over many existing scoring functions in simulating protein-ligand binding affinity, especially metalloprotein-ligand binding affinity. Artificial Neural Network (ANN) was also used in order to demonstrate that the energy terms in LISA are well designed and do not require extra cross terms. PMID:21561101

  6. Identification of the primary mass of inclined cosmic ray showers from depth of maximum and number of muon parameters

    NASA Astrophysics Data System (ADS)

    Riggi, S.; Parra, A.; Rodriguez, G.; Valiño, I.; Vázquez, R.; Zas, E.

    2013-04-01

    In the present work we carry out a study of the high energy cosmic rays mass identification capabilities of a hybrid detector employing both fluorescence telescopes and particle detectors at ground using simulated data. It involves the analysis of extensive showers with zenith angles above 60° making use of the joint distribution of the depth of maximum and muon size at ground level as mass discriminating parameters. The correlation and sensitivity to the primary mass are investigated. Two different techniques - clustering algorithms and neural networks - are adopted to classify the mass identity on an event-by-event basis. Typical results for the achieved performance of identification are reported and discussed. The analysis can be extended in a very straightforward way to vertical showers or can be complemented with additional discriminating observables coming from different types of detectors.

  7. Trigger algorithms and electronics for the ATLAS muon new small wheel upgrade

    NASA Astrophysics Data System (ADS)

    Guan, L.

    2016-01-01

    The New Small Wheel Upgrade for the ATLAS experiment will replace the innermost station of the Muon Spectrometer in the forward region in order to maintain its current performance during high luminosity data-taking after the LHC Phase-I upgrade. The New Small Wheel, comprising Micromegas and small Thin Gap Chambers, will reduce the rate of fake triggers coming from backgrounds in the forward region and significantly improve the Level-1 muon trigger selectivity by providing precise on-line segment measurements with ~ 1 mrad angular resolution. Such demanding precision, together with the short time (~ 1 μs) to prepare trigger data and perform on-line reconstruction, implies very stringent requirements on the design of trigger system and trigger electronics. This paper presents an overview of the design of the New Small Wheel trigger system, trigger algorithms and processor hardware.

  8. An onboard star identification algorithm

    NASA Astrophysics Data System (ADS)

    Ha, Kong; Femiano, Michael

    The paper presents the autonomous Initial Stellar Acquisition (ISA) algorithm developed for the X-Ray Timing Explorer for prividing the attitude quaternion within the desired accuracy, based on the one-axis attitude knowledge (through the use of the Digital Sun Sensor, CCD Star Trackers, and the onboard star catalog, OSC). Mathematical analysis leads to an accurate measure of the performance of the algorithm as a function of various parameters, such as the probability of a tracked star being in the OSC, the sensor noise level, and the number of stars matched. It is shown that the simplicity, tractability, and robustness of the ISA algorithm, compared to a general three-axis attiude determination algorithm, make it a viable on-board solution.

  9. An onboard star identification algorithm

    NASA Technical Reports Server (NTRS)

    Ha, Kong; Femiano, Michael

    1993-01-01

    The paper presents the autonomous Initial Stellar Acquisition (ISA) algorithm developed for the X-Ray Timing Explorer for prividing the attitude quaternion within the desired accuracy, based on the one-axis attitude knowledge (through the use of the Digital Sun Sensor, CCD Star Trackers, and the onboard star catalog, OSC). Mathematical analysis leads to an accurate measure of the performance of the algorithm as a function of various parameters, such as the probability of a tracked star being in the OSC, the sensor noise level, and the number of stars matched. It is shown that the simplicity, tractability, and robustness of the ISA algorithm, compared to a general three-axis attiude determination algorithm, make it a viable on-board solution.

  10. Dynamic hierarchical algorithm for accelerated microfossil identification

    NASA Astrophysics Data System (ADS)

    Wong, Cindy M.; Joseph, Dileepan

    2015-02-01

    Marine microfossils provide a useful record of the Earth's resources and prehistory via biostratigraphy. To study Hydrocarbon reservoirs and prehistoric climate, geoscientists visually identify the species of microfossils found in core samples. Because microfossil identification is labour intensive, automation has been investigated since the 1980s. With the initial rule-based systems, users still had to examine each specimen under a microscope. While artificial neural network systems showed more promise for reducing expert labour, they also did not displace manual identification for a variety of reasons, which we aim to overcome. In our human-based computation approach, the most difficult step, namely taxon identification is outsourced via a frontend website to human volunteers. A backend algorithm, called dynamic hierarchical identification, uses unsupervised, supervised, and dynamic learning to accelerate microfossil identification. Unsupervised learning clusters specimens so that volunteers need not identify every specimen during supervised learning. Dynamic learning means interim computation outputs prioritize subsequent human inputs. Using a dataset of microfossils identified by an expert, we evaluated correct and incorrect genus and species rates versus simulated time, where each specimen identification defines a moment. The proposed algorithm accelerated microfossil identification effectively, especially compared to benchmark results obtained using a k-nearest neighbour method.

  11. Combat Air Identification Fusion Algorithm (CAIFA)

    NASA Astrophysics Data System (ADS)

    Butler, C. A.; Baker, Joni E.; Crowe, John A.; Kierstead, David P.; Mauro, Carl A.

    2003-04-01

    The Combat Air Identification Fusion Algorithm (CAIFA), developed by Daniel H. Wagner, Associates, is a prototype, inferential reasoning algorithm for air combat identification. Bayesian reasoning and updating techniques are used in CAIFA to fuse multi-source identification evidence to provide identity estimates-allegiance, nationality, platform type, and intent-of detected airborne objects in the air battle space, enabling positive and rapid Combat Identification (CID) decisions. CAIFA was developed for the Composite Combat Identification (CCID) project under the Office of Naval Research (ONR) Missile Defense (MD) Future Naval Capability (FNC) program. CAIFA processes identification (ID) attribute evidence generated by surveillance sensors and other information sources over time by updating the identity estimate for each target using Bayesian inference. CAIFA exploits the conditional interdependencies of attribute variables by constructing a context-dependent Bayesian Network (BN). This formulation offers a well-established, consistent approach for evidential reasoning, renders manageable the potentially large CID state space, and provides a flexible and extensible representation to accommodate requirements for model reconfiguration/restructuring. CAIFA enables reasoning across and at different levels of the Air Space Taxonomy.

  12. Muon ID - taking care of lower momenta muons

    SciTech Connect

    Milstene, C.; Fisk, G.; Para, A.; /Fermilab

    2005-12-01

    In the Muon package under study, the tracks are extrapolated using an algorithm which accounts for the magnetic field and the ionization (dE/dx). We improved the calculation of the field dependent term to increase the muon detection efficiency at lower momenta using a Runge-Kutta method. The muon identification and hadron separation in b-bbar jets is reported with the improved software. In the same framework, the utilization of the Kalman filter is introduced. The principle of the Kalman filter is described in some detail with the propagation matrix, with the Runge-Kutta term included, and the effect on low momenta for low momenta single muons particles is described.

  13. Algorithm and implementation of muon trigger and data transmission system for barrel-endcap overlap region of the CMS detector

    NASA Astrophysics Data System (ADS)

    Zabolotny, W. M.; Byszuk, A.

    2016-03-01

    The CMS experiment Level-1 trigger system is undergoing an upgrade. In the barrel-endcap transition region, it is necessary to merge data from 3 types of muon detectors—RPC, DT and CSC. The Overlap Muon Track Finder (OMTF) uses the novel approach to concentrate and process those data in a uniform manner to identify muons and their transversal momentum. The paper presents the algorithm and FPGA firmware implementation of the OMTF and its data transmission system in CMS. It is foreseen that the OMTF will be subject to significant changes resulting from optimization which will be done with the aid of physics simulations. Therefore, a special, high-level, parameterized HDL implementation is necessary.

  14. Optimization of a chemical identification algorithm

    NASA Astrophysics Data System (ADS)

    Chyba, Thomas H.; Fisk, Brian; Gunning, Christin; Farley, Kevin; Polizzi, Amber; Baughman, David; Simpson, Steven; Slamani, Mohamed-Adel; Almassy, Robert; Da Re, Ryan; Li, Eunice; MacDonald, Steve; Slamani, Ahmed; Mitchell, Scott A.; Pendell-Jones, Jay; Reed, Timothy L.; Emge, Darren

    2010-04-01

    A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

  15. The Muon Detector of Cms

    NASA Astrophysics Data System (ADS)

    Jiang, Chunhua

    2005-04-01

    Muons are an unmistakable signature of most of the LHC physics is designed to explore. The ability to trigger on and reconstruct muons at highest luminorsities is central to the concept of CMS. CMS is characterized by simplicity of design, with one magnet whose solenoideal field facilitates precision racking in the central barrel region and triggering on muons through their bending in the tharnverse and side views. The CMS muon system has three purpose: muon identification, muon trigger and nuon momentum measurement.

  16. ISINA: INTEGRAL Source Identification Network Algorithm

    NASA Astrophysics Data System (ADS)

    Scaringi, S.; Bird, A. J.; Clark, D. J.; Dean, A. J.; Hill, A. B.; McBride, V. A.; Shaw, S. E.

    2008-11-01

    We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. First, we introduce the data set and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky. Three independent random forests are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples. Based on observations with INTEGRAL, an ESA project with instruments and science data centre funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain), Czech Republic and Poland, and the participation of Russia and the USA. E-mail: simo@astro.soton.ac.uk

  17. Applications of an MPI Enhanced Simulated Annealing Algorithm on nuSTORM and 6D Muon Cooling

    SciTech Connect

    Liu, A.

    2015-06-01

    The nuSTORM decay ring is a compact racetrack storage ring with a circumference ~480 m using large aperture ($\\phi$ = 60 cm) magnets. The design goal of the ring is to achieve a momentum acceptance of 3.8 $\\pm$10% GeV/c and a phase space acceptance of 2000 $\\mu$m·rad. The design has many challenges because the acceptance will be affected by many nonlinearity terms with large particle emittance and/or large momentum offset. In this paper, we present the application of a meta-heuristic optimization algorithm to the sextupole correction in the ring. The algorithm is capable of finding a balanced compromise among corrections of the nonlinearity terms, and finding the largest acceptance. This technique can be applied to the design of similar storage rings that store beams with wide transverse phase space and momentum spectra. We also present the recent study on the application of this algorithm to a part of the 6D muon cooling channel. The technique and the cooling concept will be applied to design a cooling channel for the extracted muon beam at nuSTORM in the future study.

  18. Performance characterization of a combined material identification and screening algorithm

    NASA Astrophysics Data System (ADS)

    Green, Robert L.; Hargreaves, Michael D.; Gardner, Craig M.

    2013-05-01

    Portable analytical devices based on a gamut of technologies (Infrared, Raman, X-Ray Fluorescence, Mass Spectrometry, etc.) are now widely available. These tools have seen increasing adoption for field-based assessment by diverse users including military, emergency response, and law enforcement. Frequently, end-users of portable devices are non-scientists who rely on embedded software and the associated algorithms to convert collected data into actionable information. Two classes of problems commonly encountered in field applications are identification and screening. Identification algorithms are designed to scour a library of known materials and determine whether the unknown measurement is consistent with a stored response (or combination of stored responses). Such algorithms can be used to identify a material from many thousands of possible candidates. Screening algorithms evaluate whether at least a subset of features in an unknown measurement correspond to one or more specific substances of interest and are typically configured to detect from a small list potential target analytes. Thus, screening algorithms are much less broadly applicable than identification algorithms; however, they typically provide higher detection rates which makes them attractive for specific applications such as chemical warfare agent or narcotics detection. This paper will present an overview and performance characterization of a combined identification/screening algorithm that has recently been developed. It will be shown that the combined algorithm provides enhanced detection capability more typical of screening algorithms while maintaining a broad identification capability. Additionally, we will highlight how this approach can enable users to incorporate situational awareness during a response.

  19. Effect of object identification algorithms on feature based verification scores

    NASA Astrophysics Data System (ADS)

    Weniger, Michael; Friederichs, Petra

    2015-04-01

    Many modern spatial verification techniques rely on feature identification algorithms. We study the importance of the choice of algorithm and its parameters for the resulting scores. SAL is used as an example to show that these choices have a statistically significant impact on the distributions of object dependent scores. Non-continuous operators used for feature identification are identified as the underlying reason for the observed stability issues, with implications for many feature based verification techniques.

  20. Validation of a Bayesian-based isotope identification algorithm

    NASA Astrophysics Data System (ADS)

    Sullivan, C. J.; Stinnett, J.

    2015-06-01

    Handheld radio-isotope identifiers (RIIDs) are widely used in Homeland Security and other nuclear safety applications. However, most commercially available devices have serious problems in their ability to correctly identify isotopes. It has been reported that this flaw is largely due to the overly simplistic identification algorithms on-board the RIIDs. This paper reports on the experimental validation of a new isotope identification algorithm using a Bayesian statistics approach to identify the source while allowing for calibration drift and unknown shielding. We present here results on further testing of this algorithm and a study on the observed variation in the gamma peak energies and areas from a wavelet-based peak identification algorithm.

  1. Identification of Traceability Barcode Based on Phase Correlation Algorithm

    NASA Astrophysics Data System (ADS)

    Lang, Liying; Zhang, Xiaofang

    In the paper phase correlation algorithm based on Fourier transform is applied to the traceability barcode identification, which is a widely used method of image registration. And there is the rotation-invariant phase correlation algorithm which combines polar coordinate transform with phase correlation, that they can recognize the barcode with partly destroyed and rotated. The paper provides the analysis and simulation for the algorithm using Matlab, the results show that the algorithm has the advantages of good real-time and high performance. And it improves the matching precision and reduces the calculation by optimizing the rotation-invariant phase correlation.

  2. Muon ID at the ILC

    SciTech Connect

    Milstene, C.; Fisk, G.; Para, A.; /Fermilab

    2006-09-01

    This paper describes a new way to reconstruct and identify muons with high efficiency and high pion rejection. Since muons at the ILC are often produced with or in jets, for many of the physics channels of interest [1], an efficient algorithm to deal with the identification and separation of particles within jets is important. The algorithm at the core of the method accounts for the effects of the magnetic field and for the loss of energy by charged particles due to ionization in the detector. We have chosen to develop the analysis within the setup of one of the Linear Collider Concept Detectors adopted by the US. Within b-pair production jets, particles cover a wide range in momenta; however {approx}80% of the particles have a momentum below 30 GeV[2]. Our study, focused on bbar-b jets, is preceded by a careful analysis of single energy particles between 2 and 50 GeV. As medium energy particles are a substantial component of the jets, many of the particles lose part of their energy in the calorimeters and the solenoid coil before reaching the muon detector where they may have energy below 2 GeV. To deal with this problem we have implemented a Runge-Kutta correction of the calculated trajectory to better handle these lower energy particles. The multiple scattering and other stochastic processes, more important at lower energy, is addressed by a Kalman-filter integrated into the reconstruction algorithm. The algorithm provides a unique and powerful separation of muons from pions. The 5 Tesla magnetic field from a solenoid surrounds the hadron calorimeter and allows the reconstruction and precision.

  3. Parameter identification using a creeping-random-search algorithm

    NASA Technical Reports Server (NTRS)

    Parrish, R. V.

    1971-01-01

    A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.

  4. Polygon star identification based on ant colony algorithm

    NASA Astrophysics Data System (ADS)

    Ma, Baolin; Wu, Jie; Zhang, Hongbo

    2014-11-01

    In order to enhance the rate of star identification under different view fields and reduce memory storage, this paper presents a polygon star identification based on ACO algorithm .First, fast cluster analysis. Second, calculate argument for each guide star, using the advantages of ACO in fast path optimization to complete building feature polygon. Third, comparing optimization results and optimization data of guide database to realize match and identifying. Through the simulation shows that the above method can simplify searching process and structure of storage. It can promise the completeness of characteristic patterns of star image. The robustness and reliability are better than traditional triangle identification.

  5. Algorithmic Identification for Wings in Butterfly Diagrams.

    NASA Astrophysics Data System (ADS)

    Illarionov, E. A.; Sokolov, D. D.

    2012-12-01

    We investigate to what extent the wings of solar butterfly diagrams can be separated without an explicit usage of Hale's polarity law as well as the location of the solar equator. Two algorithms of cluster analysis, namely DBSCAN and C-means, have demonstrated their ability to separate the wings of contemporary butterfly diagrams based on the sunspot group density in the diagram only. Here we generalize the method for continuous tracers, give results concerning the migration velocities and presented clusters for 12 - 20 cycles.

  6. A software tool for graphically assembling damage identification algorithms

    NASA Astrophysics Data System (ADS)

    Allen, David W.; Clough, Joshua A.; Sohn, Hoon; Farrar, Charles R.

    2003-08-01

    At Los Alamos National Laboratory (LANL), various algorithms for structural health monitoring problems have been explored in the last 5 to 6 years. The original DIAMOND (Damage Identification And MOdal aNalysis of Data) software was developed as a package of modal analysis tools with some frequency domain damage identification algorithms included. Since the conception of DIAMOND, the Structural Health Monitoring (SHM) paradigm at LANL has been cast in the framework of statistical pattern recognition, promoting data driven damage detection approaches. To reflect this shift and to allow user-friendly analyses of data, a new piece of software, DIAMOND II is under development. The Graphical User Interface (GUI) of the DIAMOND II software is based on the idea of GLASS (Graphical Linking and Assembly of Syntax Structure) technology, which is currently being implemented at LANL. GLASS is a Java based GUI that allows drag and drop construction of algorithms from various categories of existing functions. In the platform of the underlying GLASS technology, DIAMOND II is simply a module specifically targeting damage identification applications. Users can assemble various routines, building their own algorithms or benchmark testing different damage identification approaches without writing a single line of code.

  7. A Simplified Pattern Match Algorithm for Star Identification

    NASA Technical Reports Server (NTRS)

    Lee, Michael H.

    1996-01-01

    A true pattern matching star algorithm similar in concept to the Van Bezooijen algorithm is implemented using an iterative approach. This approach allows for a more compact and simple implementation which can be easily adapted to be either an all-sky, no a priori algorithm or a follow on to a direct match algorithm to distinguish between ambiguous matches. Some simple analysis is shown to indicate the likelihood of mis-identifications. The performance of the algorithm for the all-sky, no a priori situation is detailed assuming he SKYMAP star catalog describes the true sky. The impact of errors and omissions in the SKYMAP catalog on performance are investigated. In addition, differing levels of noise in the star observations are assumed and results shown. The implications for possible implementation on-board spacecraft are discussed.

  8. Cover song identification by sequence alignment algorithms

    NASA Astrophysics Data System (ADS)

    Wang, Chih-Li; Zhong, Qian; Wang, Szu-Ying; Roychowdhury, Vwani

    2011-10-01

    Content-based music analysis has drawn much attention due to the rapidly growing digital music market. This paper describes a method that can be used to effectively identify cover songs. A cover song is a song that preserves only the crucial melody of its reference song but different in some other acoustic properties. Hence, the beat/chroma-synchronous chromagram, which is insensitive to the variation of the timber or rhythm of songs but sensitive to the melody, is chosen. The key transposition is achieved by cyclically shifting the chromatic domain of the chromagram. By using the Hidden Markov Model (HMM) to obtain the time sequences of songs, the system is made even more robust. Similar structure or length between the cover songs and its reference are not necessary by the Smith-Waterman Alignment Algorithm.

  9. Closed Loop System Identification with Genetic Algorithms

    NASA Technical Reports Server (NTRS)

    Whorton, Mark S.

    2004-01-01

    High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

  10. Fast parallel tracking algorithm for the muon detector of the CBM experiment at fair

    NASA Astrophysics Data System (ADS)

    Lebedev, A.; Höhne, C.; Kisel, I.; Ososkov, G.

    2010-07-01

    Particle trajectory recognition is an important and challenging task in the Compressed Baryonic Matter (CBM) experiment at the future FAIR accelerator at Darmstadt. The tracking algorithms have to process terabytes of input data produced in particle collisions. Therefore, the speed of the tracking software is extremely important for data analysis. In this contribution, a fast parallel track reconstruction algorithm which uses available features of modern processors is presented. These features comprise a SIMD instruction set (SSE) and multithreading. The first allows one to pack several data items into one register and to operate on all of them in parallel thus achieving more operations per cycle. The second feature enables the routines to exploit all available CPU cores and hardware threads. This parallel version of the tracking algorithm has been compared to the initial serial scalar version which uses a similar approach for tracking. A speed-up factor of 487 was achieved (from 730 to 1.5 ms/event) for a computer with 2 × Intel Core i7 processors at 2.66 GHz.

  11. A new algorithmic approach for fingers detection and identification

    NASA Astrophysics Data System (ADS)

    Mubashar Khan, Arslan; Umar, Waqas; Choudhary, Taimoor; Hussain, Fawad; Haroon Yousaf, Muhammad

    2013-03-01

    Gesture recognition is concerned with the goal of interpreting human gestures through mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Hand gesture detection in a real time environment, where the time and memory are important issues, is a critical operation. Hand gesture recognition largely depends on the accurate detection of the fingers. This paper presents a new algorithmic approach to detect and identify fingers of human hand. The proposed algorithm does not depend upon the prior knowledge of the scene. It detects the active fingers and Metacarpophalangeal (MCP) of the inactive fingers from an already detected hand. Dynamic thresholding technique and connected component labeling scheme are employed for background elimination and hand detection respectively. Algorithm proposed a new approach for finger identification in real time environment keeping the memory and time constraint as low as possible.

  12. A Novel Binarization Algorithm for Ballistics Firearm Identification

    NASA Astrophysics Data System (ADS)

    Li, Dongguang

    The identification of ballistics specimens from imaging systems is of paramount importance in criminal investigation. Binarization plays a key role in preprocess of recognizing cartridges in the ballistic imaging systems. Unfortunately, it is very difficult to get the satisfactory binary image using existing binary algorithms. In this paper, we utilize the global and local thresholds to enhance the image binarization. Importantly, we present a novel criterion for effectively detecting edges in the images. Comprehensive experiments have been conducted over sample ballistic images. The empirical results demonstrate the proposed method can provide a better solution than existing binary algorithms.

  13. Muon background studies for shallow depth Double - Chooz near detector

    SciTech Connect

    Gómez, H.

    2015-08-17

    Muon events are one of the main concerns regarding background in neutrino experiments. The placement of experimental set-ups in deep underground facilities reduce considerably their impact on the research of the expected signals. But in the cases where the detector is installed on surface or at shallow depth, muon flux remains high, being necessary their precise identification for further rejection. Total flux, mean energy or angular distributions are some of the parameters that can help to characterize the muons. Empirically, the muon rate can be measured in an experiment by a number of methods. Nevertheless, the capability to determine the muons angular distribution strongly depends on the detector features, while the measurement of the muon energy is quite difficult. Also considering that on-site measurements can not be extrapolated to other sites due to the difference on the overburden and its profile, it is necessary to find an adequate solution to perform the muon characterization. The method described in this work to obtain the main features of the muons reaching the experimental set-up, is based on the muon transport simulation by the MUSIC software, combined with a dedicated sampling algorithm for shallow depth installations based on a modified Gaisser parametrization. This method provides all the required information about the muons for any shallow depth installation if the corresponding overburden profile is implemented. In this work, the method has been applied for the recently commissioned Double - Chooz near detector, which will allow the cross-check between the simulation and the experimental data, as it has been done for the far detector.

  14. Muon background studies for shallow depth Double - Chooz near detector

    NASA Astrophysics Data System (ADS)

    Gómez, H.

    2015-08-01

    Muon events are one of the main concerns regarding background in neutrino experiments. The placement of experimental set-ups in deep underground facilities reduce considerably their impact on the research of the expected signals. But in the cases where the detector is installed on surface or at shallow depth, muon flux remains high, being necessary their precise identification for further rejection. Total flux, mean energy or angular distributions are some of the parameters that can help to characterize the muons. Empirically, the muon rate can be measured in an experiment by a number of methods. Nevertheless, the capability to determine the muons angular distribution strongly depends on the detector features, while the measurement of the muon energy is quite difficult. Also considering that on-site measurements can not be extrapolated to other sites due to the difference on the overburden and its profile, it is necessary to find an adequate solution to perform the muon characterization. The method described in this work to obtain the main features of the muons reaching the experimental set-up, is based on the muon transport simulation by the MUSIC software, combined with a dedicated sampling algorithm for shallow depth installations based on a modified Gaisser parametrization. This method provides all the required information about the muons for any shallow depth installation if the corresponding overburden profile is implemented. In this work, the method has been applied for the recently commissioned Double - Chooz near detector, which will allow the cross-check between the simulation and the experimental data, as it has been done for the far detector.

  15. Fast Probabilistic Particle Identification algorithm using silicon strip detectors

    NASA Astrophysics Data System (ADS)

    Di Fino, L.; Zaconte, V.; Ciccotelli, A.; Larosa, M.; Narici, L.

    2012-08-01

    Active detectors used as radiation monitors in space are not usually able to perform Particle Identification (PID). Common techniques need energy loss spectra with high statistics to estimate ion abundances. The ALTEA-space detector system is a set of silicon strip particle telescopes monitoring the radiation environment on board the International Space Station since July 2006 with real-time telemetry capabilities. Its large geometrical factor due to the concurrent use of six detectors permits the acquisition of good energy loss spectra even in a short period of observation. In this paper we present a novel Fast Probabilistic Particle Identification (FPPI) algorithm developed for the ALTEA data analysis in order to perform nuclear identification with low statistics and, with some limitations, also in real time.

  16. A Frequency-Domain Substructure System Identification Algorithm

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  17. Comparing Different Fault Identification Algorithms in Distributed Power System

    NASA Astrophysics Data System (ADS)

    Alkaabi, Salim

    A power system is a huge complex system that delivers the electrical power from the generation units to the consumers. As the demand for electrical power increases, distributed power generation was introduced to the power system. Faults may occur in the power system at any time in different locations. These faults cause a huge damage to the system as they might lead to full failure of the power system. Using distributed generation in the power system made it even harder to identify the location of the faults in the system. The main objective of this work is to test the different fault location identification algorithms while tested on a power system with the different amount of power injected using distributed generators. As faults may lead the system to full failure, this is an important area for research. In this thesis different fault location identification algorithms have been tested and compared while the different amount of power is injected from distributed generators. The algorithms were tested on IEEE 34 node test feeder using MATLAB and the results were compared to find when these algorithms might fail and the reliability of these methods.

  18. Metrics for the comparative evaluation of chemical plume identification algorithms

    NASA Astrophysics Data System (ADS)

    Truslow, E.; Golowich, S.; Manolakis, D.; Ingle, V. K.

    2015-05-01

    The detection of chemical agents with hyperspectral longwave infrared sensors is a difficult problem with many civilian and military applications. System performance can be evaluated by comparing the detected gases in each pixel with the ground truth for each pixel using a confusion matrix. In the presence of chemical mixtures the confusion matrix becomes extremely large and difficult to interpret due to its size. We propose summarizing the confusion matrix using simple scalar metrics tailored for specific applications. Ideally, an identifier should determine exactly which chemicals are in each pixel, but in many applications it is acceptable for the output to contain additional chemicals or lack some constituent chemicals. A performance metric for identification problems should give partially correct results a lower weight than completely correct results. The metric we propose using, the Dice metric, weighs each output by its similarity with the truth for each pixel, thereby giving less importance to partially correct outputs, while still giving full scores only to exactly correct results. Using the Dice metric we evaluated the performance of two identification algorithms: an adaptive cosine estimator (ACE) detector bank approach, and Bayesian model averaging (BMA). Both algorithms were tested individually on real background data with synthetically embedded plumes; performance was evaluated using standard detection performance metrics, and then using the proposed identification metric. We show that ACE performed well as a detector but poorly as an identifier; however, BMA performed poorly as a detector but well as an identifier. Cascading the two algorithms should lead to a system with a substantially lower false alarm rate than using BMA alone, and much better identification performance than the ACE detector bank alone.

  19. 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.

  20. Electron-Muon Identification by Atmospheric Shower and Electron Beam in a New EAS Detector Concept

    NASA Astrophysics Data System (ADS)

    Iori, M.; Denizli, H.; Yilmaz, A.; Ferrarotto, F.; Russ, J.

    2015-03-01

    We present results demonstrating the time resolution and μ/e separation capabilities of a new concept for an EAS detector capable of measuring cosmic rays arriving with large zenith angles. This kind of detector has been designed to be part of a large area (several square kilometer) surface array designed to measure ultra high energy (10-200 PeV) τ neutrinos using the Earth-skimming technique. A criterion to identify electron-gammas is also shown and the particle identification capability is tested by measurements in coincidence with the KASKADE-GRANDE experiment in Karlsruhe, Germany.

  1. PIDA:A new algorithm for pattern identification.

    PubMed

    Putonti, C; Pettitt, Bm; Reid, Jg; Fofanov, Y

    2007-01-01

    Algorithms for motif identification in sequence space have predominately been focused on recognizing patterns of a fixed length containing regions of perfect conservation with possible regions of unconstrained sequence. Such motifs can be found in everything from proteins with distinct active sites to non-coding RNAs with specific structural elements that are necessary to maintain functionality. In the event that an insertion/deletion has occurred within an unconstrained portion of the pattern, it is possible that the pattern retains its functionality. In such a case the length of the pattern is now variable and may be overlooked when utilizing existing motif detection methods. The Pattern Island Detection Algorithm (PIDA) presented here has been developed to recognize patterns that have occurrences of varying length within sequences of any size alphabet. PIDA works by identifying all regions of perfect conservation (for lengths longer than a user-specified threshold), and then builds those conservation "islands" into fixed-length patterns. Next the algorithm modifies these fixed-length patterns by identifying additional (and different) islands that can be incorporated into each pattern through insertions/deletions within the "water" separating the islands. To provide some benchmarks for this analysis, PIDA was used to search for patterns within randomly generated sequences as well as sequences known to contain conserved patterns. For each of the patterns found, the statistical significance is calculated based upon the pattern's likelihood to appear by chance, thus providing a means to determine those patterns which are likely to have a functional role. The PIDA approach to motif finding is designed to perform best when searching for patterns of variable length although it is also able to identify patterns of a fixed length. PIDA has been created to be as generally applicable as possible since there are a variety of sequence problems of this type. The algorithm was

  2. PIDA:A new algorithm for pattern identification

    PubMed Central

    Putonti, C; Pettitt, BM; Reid, JG; Fofanov, Y

    2009-01-01

    Algorithms for motif identification in sequence space have predominately been focused on recognizing patterns of a fixed length containing regions of perfect conservation with possible regions of unconstrained sequence. Such motifs can be found in everything from proteins with distinct active sites to non-coding RNAs with specific structural elements that are necessary to maintain functionality. In the event that an insertion/deletion has occurred within an unconstrained portion of the pattern, it is possible that the pattern retains its functionality. In such a case the length of the pattern is now variable and may be overlooked when utilizing existing motif detection methods. The Pattern Island Detection Algorithm (PIDA) presented here has been developed to recognize patterns that have occurrences of varying length within sequences of any size alphabet. PIDA works by identifying all regions of perfect conservation (for lengths longer than a user-specified threshold), and then builds those conservation “islands” into fixed-length patterns. Next the algorithm modifies these fixed-length patterns by identifying additional (and different) islands that can be incorporated into each pattern through insertions/deletions within the “water” separating the islands. To provide some benchmarks for this analysis, PIDA was used to search for patterns within randomly generated sequences as well as sequences known to contain conserved patterns. For each of the patterns found, the statistical significance is calculated based upon the pattern’s likelihood to appear by chance, thus providing a means to determine those patterns which are likely to have a functional role. The PIDA approach to motif finding is designed to perform best when searching for patterns of variable length although it is also able to identify patterns of a fixed length. PIDA has been created to be as generally applicable as possible since there are a variety of sequence problems of this type. The

  3. Muon colliders

    SciTech Connect

    Palmer, R.B. |; Sessler, A.; Skrinsky, A.

    1996-01-01

    Muon Colliders have unique technical and physics advantages and disadvantages when compared with both hadron and electron machines. They should thus be regarded as complementary. Parameters are given of 4 TeV and 0.5 TeV high luminosity {micro}{sup +}{micro}{sup {minus}}colliders, and of a 0.5 TeV lower luminosity demonstration machine. We discuss the various systems in such muon colliders, starting from the proton accelerator needed to generate the muons and proceeding through muon cooling, acceleration and storage in a collider ring. Problems of detector background are also discussed.

  4. Electron-Muon Ranger: Performance in the MICE muon beam

    DOE PAGESBeta

    Adams, D.

    2015-12-16

    The Muon Ionization Cooling Experiment (MICE) will perform a detailed study of ionization cooling to evaluate the feasibility of the technique. To carry out this program, MICE requires an efficient particle-identification (PID) system to identify muons. The Electron-Muon Ranger (EMR) is a fully-active tracking-calorimeter that forms part of the PID system and tags muons that traverse the cooling channel without decaying. The detector is capable of identifying electrons with an efficiency of 98.6%, providing a purity for the MICE beam that exceeds 99.8%. Lastly, the EMR also proved to be a powerful tool for the reconstruction of muon momenta inmore » the range 100–280 MeV/c.« less

  5. Electron-Muon Ranger: Performance in the MICE muon beam

    SciTech Connect

    Adams, D.

    2015-12-16

    The Muon Ionization Cooling Experiment (MICE) will perform a detailed study of ionization cooling to evaluate the feasibility of the technique. To carry out this program, MICE requires an efficient particle-identification (PID) system to identify muons. The Electron-Muon Ranger (EMR) is a fully-active tracking-calorimeter that forms part of the PID system and tags muons that traverse the cooling channel without decaying. The detector is capable of identifying electrons with an efficiency of 98.6%, providing a purity for the MICE beam that exceeds 99.8%. Lastly, the EMR also proved to be a powerful tool for the reconstruction of muon momenta in the range 100–280 MeV/c.

  6. Electron-muon ranger: performance in the MICE muon beam

    NASA Astrophysics Data System (ADS)

    Adams, D.; Alekou, A.; Apollonio, M.; Asfandiyarov, R.; Barber, G.; Barclay, P.; de Bari, A.; Bayes, R.; Bayliss, V.; Bene, P.; Bertoni, R.; Blackmore, V. J.; Blondel, A.; Blot, S.; Bogomilov, M.; Bonesini, M.; Booth, C. N.; Bowring, D.; Boyd, S.; Bradshaw, T. W.; Bravar, U.; Bross, A. D.; Cadoux, F.; Capponi, M.; Carlisle, T.; Cecchet, G.; Charnley, C.; Chignoli, F.; Cline, D.; Cobb, J. H.; Colling, G.; Collomb, N.; Coney, L.; Cooke, P.; Courthold, M.; Cremaldi, L. M.; Debieux, S.; DeMello, A.; Dick, A.; Dobbs, A.; Dornan, P.; Drielsma, F.; Filthaut, F.; Fitzpatrick, T.; Franchini, P.; Francis, V.; Fry, L.; Gallagher, A.; Gamet, R.; Gardener, R.; Gourlay, S.; Grant, A.; Graulich, J. S.; Greis, J.; Griffiths, S.; Hanlet, P.; Hansen, O. M.; Hanson, G. G.; Hart, T. L.; Hartnett, T.; Hayler, T.; Heidt, C.; Hills, M.; Hodgson, P.; Hunt, C.; Husi, C.; Iaciofano, A.; Ishimoto, S.; Kafka, G.; Kaplan, D. M.; Karadzhov, Y.; Kim, Y. K.; Kuno, Y.; Kyberd, P.; Lagrange, J.-B.; Langlands, J.; Lau, W.; Leonova, M.; Li, D.; Lintern, A.; Littlefield, M.; Long, K.; Luo, T.; Macwaters, C.; Martlew, B.; Martyniak, J.; Masciocchi, F.; Mazza, R.; Middleton, S.; Moretti, A.; Moss, A.; Muir, A.; Mullacrane, I.; Nebrensky, J. J.; Neuffer, D.; Nichols, A.; Nicholson, R.; Nicola, L.; Noah Messomo, E.; Nugent, J. C.; Oates, A.; Onel, Y.; Orestano, D.; Overton, E.; Owens, P.; Palladino, V.; Pasternak, J.; Pastore, F.; Pidcott, C.; Popovic, M.; Preece, R.; Prestemon, S.; Rajaram, D.; Ramberger, S.; Rayner, M. A.; Ricciardi, S.; Roberts, T. J.; Robinson, M.; Rogers, C.; Ronald, K.; Rothenfusser, K.; Rubinov, P.; Rucinski, P.; Sakamato, H.; Sanders, D. A.; Sandström, R.; Santos, E.; Savidge, T.; Smith, P. J.; Snopok, P.; Soler, F. J. P.; Speirs, D.; Stanley, T.; Stokes, G.; Summers, D. J.; Tarrant, J.; Taylor, I.; Tortora, L.; Torun, Y.; Tsenov, R.; Tunnell, C. D.; Uchida, M. A.; Vankova-Kirilova, G.; Virostek, S.; Vretenar, M.; Warburton, P.; Watson, S.; White, C.; Whyte, C. G.; Wilson, A.; Wisting, H.; Yang, X.; Young, A.; Zisman, M.

    2015-12-01

    The Muon Ionization Cooling Experiment (MICE) will perform a detailed study of ionization cooling to evaluate the feasibility of the technique. To carry out this program, MICE requires an efficient particle-identification (PID) system to identify muons. The Electron-Muon Ranger (EMR) is a fully-active tracking-calorimeter that forms part of the PID system and tags muons that traverse the cooling channel without decaying. The detector is capable of identifying electrons with an efficiency of 98.6%, providing a purity for the MICE beam that exceeds 99.8%. The EMR also proved to be a powerful tool for the reconstruction of muon momenta in the range 100-280 MeV/c.

  7. An accurate and efficient algorithm for Peptide and ptm identification by tandem mass spectrometry.

    PubMed

    Ning, Kang; Ng, Hoong Kee; Leong, Hon Wai

    2007-01-01

    Peptide identification by tandem mass spectrometry (MS/MS) is one of the most important problems in proteomics. Recent advances in high throughput MS/MS experiments result in huge amount of spectra. Unfortunately, identification of these spectra is relatively slow, and the accuracies of current algorithms are not high with the presence of noises and post-translational modifications (PTMs). In this paper, we strive to achieve high accuracy and efficiency for peptide identification problem, with special concern on identification of peptides with PTMs. This paper expands our previous work on PepSOM with the introduction of two accurate modified scoring functions: Slambda for peptide identification and Slambda* for identification of peptides with PTMs. Experiments showed that our algorithm is both fast and accurate for peptide identification. Experiments on spectra with simulated and real PTMs confirmed that our algorithm is accurate for identifying PTMs. PMID:18546510

  8. The MeSsI (Merging Systems Identification) Algorithm & Catalogue

    NASA Astrophysics Data System (ADS)

    de los Rios, Martín; Domínguez, R. Mariano J.; Paz, Dante; Merchán., Manuel

    2016-01-01

    Merging galaxy systems provide observational evidence of the existence of dark matter and constraints on its properties. Therefore, statisticaly uniform samples of merging systems would be a powerful tool for several studies. In this work we present a new methodology for the identification of merging systems and the results of its application to galaxy redshift surveys. We use as a starting point a mock catalogue of galaxy systems, identified using FoF algorithms, which experienced a major merger as indicated by its merger tree. Applying machine learning techniques in this training sample, and using several features computed from the observable properties of galaxy members, it is possible to select galaxy groups with a high probability of having experienced a major merger. Next we apply a mixture of Gaussian technique on galaxy members in order to reconstruct the properties of the haloes involved in such merger. This methodology provides a highly reliable sample of merging systems with low contamination and precisely recovered properties. We apply our techniques to samples of galaxy systems obtained from SDSS-DR7, WINGS and HeCS. Our results recover previously known merging systems and provide several new candidates. We present their measured properties and discuss future analysis on current and forthcoming samples.

  9. Research on Palmprint Identification Method Based on Quantum Algorithms

    PubMed Central

    Zhang, Zhanzhan

    2014-01-01

    Quantum image recognition is a technology by using quantum algorithm to process the image information. It can obtain better effect than classical algorithm. In this paper, four different quantum algorithms are used in the three stages of palmprint recognition. First, quantum adaptive median filtering algorithm is presented in palmprint filtering processing. Quantum filtering algorithm can get a better filtering result than classical algorithm through the comparison. Next, quantum Fourier transform (QFT) is used to extract pattern features by only one operation due to quantum parallelism. The proposed algorithm exhibits an exponential speed-up compared with discrete Fourier transform in the feature extraction. Finally, quantum set operations and Grover algorithm are used in palmprint matching. According to the experimental results, quantum algorithm only needs to apply square of N operations to find out the target palmprint, but the traditional method needs N times of calculation. At the same time, the matching accuracy of quantum algorithm is almost 100%. PMID:25105165

  10. Muon Collider

    SciTech Connect

    Palmer, R.

    2009-10-19

    Parameters are given of muon colliders with center of mass energies of 1.5 and 3 TeV. Pion production is from protons on a mercury target. Capture, decay, and phase rotation yields bunch trains of both muon signs. Six dimensional cooling reduces the emittances until the trains are merged into single bunches, one of each sign. Further cooling in 6 dimensions is then applied, followed by final transverse cooling in 50 T solenoids. After acceleration the muons enter the collider ring. Ongoing R&D is discussed.

  11. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    PubMed

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-01-01

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

  12. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

    PubMed Central

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-01-01

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

  13. Bouc-Wen hysteresis model identification using Modified Firefly Algorithm

    NASA Astrophysics Data System (ADS)

    Zaman, Mohammad Asif; Sikder, Urmita

    2015-12-01

    The parameters of Bouc-Wen hysteresis model are identified using a Modified Firefly Algorithm. The proposed algorithm uses dynamic process control parameters to improve its performance. The algorithm is used to find the model parameter values that results in the least amount of error between a set of given data points and points obtained from the Bouc-Wen model. The performance of the algorithm is compared with the performance of conventional Firefly Algorithm, Genetic Algorithm and Differential Evolution algorithm in terms of convergence rate and accuracy. Compared to the other three optimization algorithms, the proposed algorithm is found to have good convergence rate with high degree of accuracy in identifying Bouc-Wen model parameters. Finally, the proposed method is used to find the Bouc-Wen model parameters from experimental data. The obtained model is found to be in good agreement with measured data.

  14. Muon muon collider: Feasibility study

    SciTech Connect

    1996-06-18

    A feasibility study is presented of a 2 + 2 TeV muon collider with a luminosity of L = 10{sup 35} cm{sup {minus}2} s{sup {minus}1}. The resulting design is not optimized for performance, and certainly not for cost; however, it does suffice--the authors believe--to allow them to make a credible case, that a muon collider is a serious possibility for particle physics and, therefore, worthy of R and D support so that the reality of, and interest in, a muon collider can be better assayed. The goal of this support would be to completely assess the physics potential and to evaluate the cost and development of the necessary technology. The muon collider complex consists of components which first produce copious pions, then capture the pions and the resulting muons from their decay; this is followed by an ionization cooling channel to reduce the longitudinal and transverse emittance of the muon beam. The next stage is to accelerate the muons and, finally, inject them into a collider ring which has a small beta function at the colliding point. This is the first attempt at a point design and it will require further study and optimization. Experimental work will be needed to verify the validity of diverse crucial elements in the design.

  15. Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

    NASA Astrophysics Data System (ADS)

    Singh, R.; Verma, H. K.

    2013-12-01

    This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

  16. One-time collision arbitration algorithm in radio-frequency identification based on the Manchester code

    NASA Astrophysics Data System (ADS)

    Liu, Chen-Chung; Chan, Yin-Tsung

    2011-02-01

    In radio-requency identification (RFID) systems, when multiple tags transmit data to a reader simultaneously, these data may collide and create unsuccessful identifications; hence, anticollision algorithms are needed to reduce collisions (collision cycles) to improve the tag identification speed. We propose a one-time collision arbitration algorithm to reduce both the number of collisions and the time consumption for tags' identification in RFID. The proposed algorithm uses Manchester coding to detect the locations of collided bits, uses the divide-and-conquer strategy to find the structure of colliding bits to generate 96-bit query strings as the 96-bit candidate query strings (96BCQSs), and uses query-tree anticollision schemes with 96BCQSs to identify tags. The performance analysis and experimental results show that the proposed algorithm has three advantages: (i) reducing the number of collisions to only one, so that the time complexity of tag identification is the simplest O(1), (ii) storing identified identification numbers (IDs) and the 96BCQSs in a register to save the used memory, and (iii) resulting in the number of bits transmitted by both the reader and tags being evidently less than the other algorithms in one-tag identification or in all tags identification.

  17. Development of an automatic identification algorithm for antibiogram analysis.

    PubMed

    Costa, Luan F R; da Silva, Eduardo S; Noronha, Victor T; Vaz-Moreira, Ivone; Nunes, Olga C; Andrade, Marcelino M de

    2015-12-01

    Routinely, diagnostic and microbiology laboratories perform antibiogram analysis which can present some difficulties leading to misreadings and intra and inter-reader deviations. An Automatic Identification Algorithm (AIA) has been proposed as a solution to overcome some issues associated with the disc diffusion method, which is the main goal of this work. AIA allows automatic scanning of inhibition zones obtained by antibiograms. More than 60 environmental isolates were tested using susceptibility tests which were performed for 12 different antibiotics for a total of 756 readings. Plate images were acquired and classified as standard or oddity. The inhibition zones were measured using the AIA and results were compared with reference method (human reading), using weighted kappa index and statistical analysis to evaluate, respectively, inter-reader agreement and correlation between AIA-based and human-based reading. Agreements were observed in 88% cases and 89% of the tests showed no difference or a <4mm difference between AIA and human analysis, exhibiting a correlation index of 0.85 for all images, 0.90 for standards and 0.80 for oddities with no significant difference between automatic and manual method. AIA resolved some reading problems such as overlapping inhibition zones, imperfect microorganism seeding, non-homogeneity of the circumference, partial action of the antimicrobial, and formation of a second halo of inhibition. Furthermore, AIA proved to overcome some of the limitations observed in other automatic methods. Therefore, AIA may be a practical tool for automated reading of antibiograms in diagnostic and microbiology laboratories. PMID:26513468

  18. Biofilms and Wounds: An Identification Algorithm and Potential Treatment Options

    PubMed Central

    Percival, Steven L.; Vuotto, Claudia; Donelli, Gianfranco; Lipsky, Benjamin A.

    2015-01-01

    Significance: The presence of a “pathogenic” or “highly virulent” biofilm is a fundamental risk factor that prevents a chronic wound from healing and increases the risk of the wound becoming clinically infected. There is presently no unequivocal gold standard method available for clinicians to confirm the presence of biofilms in a wound. Thus, to help support clinician practice, we devised an algorithm intended to demonstrate evidence of the presence of a biofilm in a wound to assist with wound management. Recent Advances: A variety of histological and microscopic methods applied to tissue biopsies are currently the most informative techniques available for demonstrating the presence of generic (not classified as pathogenic or commensal) biofilms and the effect they are having in promoting inflammation and downregulating cellular functions. Critical Issues: Even as we rely on microscopic techniques to visualize biofilms, they are entities which are patchy and dispersed rather than confluent, particularly on biotic surfaces. Consequently, detection of biofilms by microscopic techniques alone can lead to frequent false-negative results. Furthermore, visual identification using the naked eye of a pathogenic biofilm on a macroscopic level on the wound will not be possible, unlike with biofilms on abiotic surfaces. Future Direction: Lacking specific biomarkers to demonstrate microscopic, nonconfluent, virulent biofilms in wounds, the present focus on biofilm research should be placed on changing clinical practice. This is best done by utilizing an anti-biofilm toolbox approach, rather than speculating on unscientific approaches to identifying biofilms, with or without staining, in wounds with the naked eye. The approach to controlling biofilm should include initial wound cleansing, periodic debridement, followed by the application of appropriate antimicrobial wound dressings. This approach appears to be effective in removing pathogenic biofilms. PMID:26155381

  19. Pion contamination in the MICE muon beam

    NASA Astrophysics Data System (ADS)

    Adams, D.; Alekou, A.; Apollonio, M.; Asfandiyarov, R.; Barber, G.; Barclay, P.; de Bari, A.; Bayes, R.; Bayliss, V.; Bertoni, R.; Blackmore, V. J.; Blondel, A.; Blot, S.; Bogomilov, M.; Bonesini, M.; Booth, C. N.; Bowring, D.; Boyd, S.; Brashaw, T. W.; Bravar, U.; Bross, A. D.; Capponi, M.; Carlisle, T.; Cecchet, G.; Charnley, C.; Chignoli, F.; Cline, D.; Cobb, J. H.; Colling, G.; Collomb, N.; Coney, L.; Cooke, P.; Courthold, M.; Cremaldi, L. M.; DeMello, A.; Dick, A.; Dobbs, A.; Dornan, P.; Drews, M.; Drielsma, F.; Filthaut, F.; Fitzpatrick, T.; Franchini, P.; Francis, V.; Fry, L.; Gallagher, A.; Gamet, R.; Gardener, R.; Gourlay, S.; Grant, A.; Greis, J. R.; Griffiths, S.; Hanlet, P.; Hansen, O. M.; Hanson, G. G.; Hart, T. L.; Hartnett, T.; Hayler, T.; Heidt, C.; Hills, M.; Hodgson, P.; Hunt, C.; Iaciofano, A.; Ishimoto, S.; Kafka, G.; Kaplan, D. M.; Karadzhov, Y.; Kim, Y. K.; Kuno, Y.; Kyberd, P.; Lagrange, J.-B.; Langlands, J.; Lau, W.; Leonova, M.; Li, D.; Lintern, A.; Littlefield, M.; Long, K.; Luo, T.; Macwaters, C.; Martlew, B.; Martyniak, J.; Mazza, R.; Middleton, S.; Moretti, A.; Moss, A.; Muir, A.; Mullacrane, I.; Nebrensky, J. J.; Neuffer, D.; Nichols, A.; Nicholson, R.; Nugent, J. C.; Oates, A.; Onel, Y.; Orestano, D.; Overton, E.; Owens, P.; Palladino, V.; Pasternak, J.; Pastore, F.; Pidcott, C.; Popovic, M.; Preece, R.; Prestemon, S.; Rajaram, D.; Ramberger, S.; Rayner, M. A.; Ricciardi, S.; Roberts, T. J.; Robinson, M.; Rogers, C.; Ronald, K.; Rubinov, P.; Rucinski, P.; Sakamato, H.; Sanders, D. A.; Santos, E.; Savidge, T.; Smith, P. J.; Snopok, P.; Soler, F. J. P.; Speirs, D.; Stanley, T.; Stokes, G.; Summers, D. J.; Tarrant, J.; Taylor, I.; Tortora, L.; Torun, Y.; Tsenov, R.; Tunnell, C. D.; Uchida, M. A.; Vankova-Kirilova, G.; Virostek, S.; Vretenar, M.; Warburton, P.; Watson, S.; White, C.; Whyte, C. G.; Wilson, A.; Winter, M.; Yang, X.; Young, A.; Zisman, M.

    2016-03-01

    The international Muon Ionization Cooling Experiment (MICE) will perform a systematic investigation of ionization cooling with muon beams of momentum between 140 and 240 MeV/c at the Rutherford Appleton Laboratory ISIS facility. The measurement of ionization cooling in MICE relies on the selection of a pure sample of muons that traverse the experiment. To make this selection, the MICE Muon Beam is designed to deliver a beam of muons with less than ~1% contamination. To make the final muon selection, MICE employs a particle-identification (PID) system upstream and downstream of the cooling cell. The PID system includes time-of-flight hodoscopes, threshold-Cherenkov counters and calorimetry. The upper limit for the pion contamination measured in this paper is fπ < 1.4% at 90% C.L., including systematic uncertainties. Therefore, the MICE Muon Beam is able to meet the stringent pion-contamination requirements of the study of ionization cooling.

  20. Comparison of Five System Identification Algorithms for Rotorcraft Higher Harmonic Control

    NASA Technical Reports Server (NTRS)

    Jacklin, Stephen A.

    1998-01-01

    This report presents an analysis and performance comparison of five system identification algorithms. The methods are presented in the context of identifying a frequency-domain transfer matrix for the higher harmonic control (HHC) of helicopter vibration. The five system identification algorithms include three previously proposed methods: (1) the weighted-least- squares-error approach (in moving-block format), (2) the Kalman filter method, and (3) the least-mean-squares (LMS) filter method. In addition there are two new ones: (4) a generalized Kalman filter method and (5) a generalized LMS filter method. The generalized Kalman filter method and the generalized LMS filter method were derived as extensions of the classic methods to permit identification by using more than one measurement per identification cycle. Simulation results are presented for conditions ranging from the ideal case of a stationary transfer matrix and no measurement noise to the more complex cases involving both measurement noise and transfer-matrix variation. Both open-loop identification and closed- loop identification were simulated. Closed-loop mode identification was more challenging than open-loop identification because of the decreasing signal-to-noise ratio as the vibration became reduced. The closed-loop simulation considered both local-model identification, with measured vibration feedback and global-model identification with feedback of the identified uncontrolled vibration. The algorithms were evaluated in terms of their accuracy, stability, convergence properties, computation speeds, and relative ease of implementation.

  1. Muon Muon Collider: Feasibility Study

    SciTech Connect

    Gallardo, J.C.; Palmer, R.B.; Tollestrup, A.V.; Sessler, A.M.; Skrinsky, A.N.; Ankenbrandt, C.; Geer, S.; Griffin, J.; Johnstone, C.; Lebrun, P.; McInturff, A.; Mills, Frederick E.; Mokhov, N.; Moretti, A.; Neuffer, D.; Ng, K.Y.; Noble, R.; Novitski, I.; Popovic, M.; Qian, C.; Van Ginneken, A. /Fermilab /Brookhaven /Wisconsin U., Madison /Tel Aviv U. /Indiana U. /UCLA /LBL, Berkeley /SLAC /Argonne /Sobolev IM, Novosibirsk /UC, Davis /Munich, Tech. U. /Virginia U. /KEK, Tsukuba /DESY /Novosibirsk, IYF /Jefferson Lab /Mississippi U. /SUNY, Stony Brook /MIT /Columbia U. /Fairfield U. /UC, Berkeley

    2012-04-05

    A feasibility study is presented of a 2 + 2 TeV muon collider with a luminosity of L = 10{sup 35} cm{sup -2}s{sup -1}. The resulting design is not optimized for performance, and certainly not for cost; however, it does suffice - we believe - to allow us to make a credible case, that a muon collider is a serious possibility for particle physics and, therefore, worthy of R and D support so that the reality of, and interest in, a muon collider can be better assayed. The goal of this support would be to completely assess the physics potential and to evaluate the cost and development of the necessary technology. The muon collider complex consists of components which first produce copious pions, then capture the pions and the resulting muons from their decay; this is followed by an ionization cooling channel to reduce the longitudinal and transverse emittance of the muon beam. The next stage is to accelerate the muons and, finally, inject them into a collider ring wich has a small beta function at the colliding point. This is the first attempt at a point design and it will require further study and optimization. Experimental work will be needed to verify the validity of diverse crucial elements in the design. Muons because of their large mass compared to an electron, do not produce significant synchrotron radiation. As a result there is negligible beamstrahlung and high energy collisions are not limited by this phenomena. In addition, muons can be accelerated in circular devices which will be considerably smaller than two full-energy linacs as required in an e{sup +} - e{sup -} collider. A hadron collider would require a CM energy 5 to 10 times higher than 4 TeV to have an equivalent energy reach. Since the accelerator size is limited by the strength of bending magnets, the hadron collider for the same physics reach would have to be much larger than the muon collider. In addition, muon collisions should be cleaner than hadron collisions. There are many detailed particle

  2. Nonlinear system identification using a neo fuzzy neuron algorithm: electrical drive application.

    PubMed

    Landim, R P; de Menezes, B R; Silva, S R; Caminhas, W M

    1999-06-01

    This work presents a Neo-Fuzzy-Neuron algorithm for the identification of nonlinear dynamic systems at the point of view of a rotor flux observer. The algorithm training is on-line, has low computational cost, does not require previous training and its convergence in one step is proved. The gradient descent method is used for its weights adjustment. Simulation and experimental results demonstrate the effectiveness of the algorithm for flux observer of induction motor drive system. PMID:10560760

  3. A Dynamic Framed Slotted ALOHA Algorithm Using Collision Factor for RFID Identification

    NASA Astrophysics Data System (ADS)

    Choi, Seung Sik; Kim, Sangkyung

    In RFID systems, collision resolution is a significant issue in fast tag identification. This letter presents a dynamic frame-slotted ALOHA algorithm that uses a collision factor (DFSA-CF). This method enables fast tag identification by estimating the next frame size with the collision factor in the current frame. Simulation results show that the proposed method reduces slot times Required for RFID identification. When the number of tags is larger than the frame size, the efficiency of the proposed method is greater than those of conventional algorithms.

  4. Wavelet Algorithm for Feature Identification and Image Analysis

    Energy Science and Technology Software Center (ESTSC)

    2005-10-01

    WVL are a set of python scripts based on the algorithm described in "A novel 3D wavelet-based filter for visualizing features in noisy biological data, " W. C. Moss et al., J. Microsc. 219, 43-49 (2005)

  5. Augmenting real data with synthetic data: an application in assessing radio-isotope identification algorithms

    SciTech Connect

    Burr, Tom L; Hamada, Michael; Graves, Todd; Myers, Steve

    2008-01-01

    The performance of Radio-Isotope Identification (RIID) algorithms using gamma spectroscopy is increasingly important. For example, sensors at locations that screen for illicit nuclear material rely on isotope identification to resolve innocent nuisance alarms arising from naturally occurring radioactive material. Recent data collections for RIID testing consist of repeat measurements for each of several scenarios to test RIID algorithms. Efficient allocation of measurement resources requires an appropriate number of repeats for each scenario. To help allocate measurement resources in such data collections for RIID algorithm testing, we consider using only a few real repeats per scenario. In order to reduce uncertainty in the estimated RIID algorithm performance for each scenario, the potential merit of augmenting these real repeats with realistic synthetic repeats is also considered. Our results suggest that for the scenarios and algorithms considered, approximately 10 real repeats augmented with simulated repeats will result in an estimate having comparable uncertainty to the estimate based on using 60 real repeats.

  6. Common Pharmacophore Identification Using Frequent Clique Detection Algorithm

    PubMed Central

    Podolyan, Yevgeniy; Karypis, George

    2008-01-01

    The knowledge of a pharmacophore, or the 3D arrangement of features in the biologically active molecule that is responsible for its pharmacological activity, can help in the search and design of a new or better drug acting upon the same or related target. In this paper we describe two new algorithms based on the frequent clique detection in the molecular graphs. The first algorithm mines all frequent cliques that are present in at least one of the conformers of each (or a portion of all) molecules. The second algorithm exploits the similarities among the different conformers of the same molecule and achieves an order of magnitude performance speedup compared to the first algorithm. Both algorithms are guaranteed to find all common pharmacophores in the dataset, which is confirmed by the validation on the set of molecules for which pharmacophores have been determined experimentally. In addition, these algorithms are able to scale to datasets with arbitrarily large number of conformers per molecule and identify multiple ligand binding modes or multiple binding sites of the target. PMID:19072298

  7. Polarized muon beams for muon collider

    NASA Astrophysics Data System (ADS)

    Skrinsky, A. N.

    1996-11-01

    An option for the production of intense and highly polarized muon beams, suitable for a high-luminosity muon collider, is described briefly. It is based on a multi-channel pion-collection system, narrow-band pion-to-muon decay channels, proper muon spin gymnastics, and ionization cooling to combine all of the muon beams into a single bunch of ultimately low emittance.

  8. Investigation of scene identification algorithms for radiation budget measurements

    NASA Technical Reports Server (NTRS)

    Diekmann, F. J.

    1986-01-01

    The computation of Earth radiation budget from satellite measurements requires the identification of the scene in order to select spectral factors and bidirectional models. A scene identification procedure is developed for AVHRR SW and LW data by using two radiative transfer models. These AVHRR GAC pixels are then attached to corresponding ERBE pixels and the results are sorted into scene identification probability matrices. These scene intercomparisons show that there generally is a higher tendency for underestimation of cloudiness over ocean at high cloud amounts, e.g., mostly cloudy instead of overcast, partly cloudy instead of mostly cloudy, for the ERBE relative to the AVHRR results. Reasons for this are explained. Preliminary estimates of the errors of exitances due to scene misidentification demonstrates the high dependency on the probability matrices. While the longwave error can generally be neglected the shortwave deviations have reached maximum values of more than 12% of the respective exitances.

  9. Information extraction from muon radiography data

    SciTech Connect

    Borozdin, K. N.; Asaki, T. J.; Chartrand, R.; Hengartner, N. W.; Hogan, G. E.; Morris, C. L.; Priedhorsky, W. C.; Schirato, R.C.; Schultz, L. J.; Sottile, M. J.; Vixie, K. R.; Wohlberg, B. E.; Blanpied, G.

    2004-01-01

    Scattering muon radiography was proposed recently as a technique of detection and 3-d imaging for dense high-Z objects. High-energy cosmic ray muons are deflected in matter in the process of multiple Coulomb scattering. By measuring the deflection angles we are able to reconstruct the configuration of high-Z material in the object. We discuss the methods for information extraction from muon radiography data. Tomographic methods widely used in medical images have been applied to a specific muon radiography information source. Alternative simple technique based on the counting of high-scattered muons in the voxels seems to be efficient in many simulated scenes. SVM-based classifiers and clustering algorithms may allow detection of compact high-Z object without full image reconstruction. The efficiency of muon radiography can be increased using additional informational sources, such as momentum estimation, stopping power measurement, and detection of muonic atom emission.

  10. An almost-parameter-free harmony search algorithm for groundwater pollution source identification

    NASA Astrophysics Data System (ADS)

    Jiang, S.; Zhang, Y.; Zhao, L.; Zheng, M.

    2012-12-01

    The spatiotemporal characterization of unknown groundwater pollution sources is frequently encountered in environment problems. This study adopts the use of optimization approach that combines a numerical groundwater flow and transport model with heuristic harmony search algorithm to identify the unknown pollution sources. In the proposed methodology, an almost-parameter-free harmony search algorithm is developed to overcome the inherent shortcoming (tedious and skillful parameter-setting process for the algorithm parameters) in harmony search algorithm. Another advantage in the new proposed harmony search algorithm is that it uses individual parameter values for each decision variable, while the classical harmony search algorithm uses lump parameter values for all decision variables. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem, and the identified results indicate that the proposed almost-parameter-free harmony search algorithm based optimization model can give satisfactory estimations, even though the irregular geometry, erroneous monitoring data, and prior information shortage on potential locations are considered.Identification results of pollution sources; L: error level of observation dataRE: relative errorSD: standard deviationE: objective functionNEE: Source identification error Actual values of pollution sources;

  11. Performance study of LMS based adaptive algorithms for unknown system identification

    SciTech Connect

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-10

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  12. An algorithm for image clusters detection and identification based on color for an autonomous mobile robot

    SciTech Connect

    Uy, D.L.

    1996-02-01

    An algorithm for detection and identification of image clusters or {open_quotes}blobs{close_quotes} based on color information for an autonomous mobile robot is developed. The input image data are first processed using a crisp color fuszzyfier, a binary smoothing filter, and a median filter. The processed image data is then inputed to the image clusters detection and identification program. The program employed the concept of {open_quotes}elastic rectangle{close_quotes}that stretches in such a way that the whole blob is finally enclosed in a rectangle. A C-program is develop to test the algorithm. The algorithm is tested only on image data of 8x8 sizes with different number of blobs in them. The algorithm works very in detecting and identifying image clusters.

  13. Performance study of LMS based adaptive algorithms for unknown system identification

    NASA Astrophysics Data System (ADS)

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-01

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  14. Model Structures and Algorithms for Identification of Aerodynamic Models for Flight Dynamics Applications

    NASA Technical Reports Server (NTRS)

    Prasanth, Ravi K.; Klein, Vladislav; Murphy, Patrick C.; Mehra, Raman K.

    2005-01-01

    This paper describes model structures and parameter estimation algorithms suitable for the identification of unsteady aerodynamic models from input-output data. The model structures presented are state space models and include linear time-invariant (LTI) models and linear parameter-varying (LPV) models. They cover a wide range of local and parameter dependent identification problems arising in unsteady aerodynamics and nonlinear flight dynamics. We present a residue algorithm for estimating model parameters from data. The algorithm can incorporate apriori information and is described in detail. The algorithms are evaluated on the F-16XL wind-tunnel test data from NAS Langley Research Center. Results of numerical evaluation are presented. The paper concludes with a discussion major issues and directions for future work.

  15. Stroke parameters identification algorithm in handwriting movements analysis by synthesis.

    PubMed

    Liu, Min; Guo, Xuemei; Wang, Guoli

    2015-01-01

    This paper presents a new approach to identify the stroke parameters in handwriting movement data understanding. A two-step analysis by synthesis paradigm is employed to facilitate the coarse-to-fine parameter identification for all strokes. One is the stroke data extraction, the other is the coarse-to-fine stroke parameter identification. The new consideration of using this two-step paradigm is that the nonnegative primitive factorization technique is incorporated to decouple the overlapped strokes from the measurement data. In comparison to the existing paradigms of using the heuristic stroke data decoupling techniques, our paradigm presented here contributes to alleviating the difficulty of local optimum traps with the well-shaped initializations in the global optimization for jointly identifying stroke parameters. Moreover, our paradigm excludes the iteration between two steps, which contributes to the enhancement of computational efficiency. Experimental results are reported to validate the proposed approach. PMID:24771598

  16. Identification of unbalance forces by metaheuristic search algorithms

    NASA Astrophysics Data System (ADS)

    Fiori de Castro, Helio; Lucchesi Cavalca, Katia; Ward Franco de Camargo, Lucas; Bachschmid, Nicoló

    2010-08-01

    This paper discusses the identification of parameters in rotary systems, namely, the unbalance magnitude, phase and position in the rotor system. These parameters can be identified using the measured orbits in the hydrodynamic bearings. The oil film forces are evaluated in the different positions of the orbit of the journal and are applied to the model of the shaft. The model, integrated in time domain, allows with an assumed unbalance, to simulate the orbits. The objective function is basically the difference between measured and simulated orbits, and its minimum corresponds to the identified unbalance amount, phase and position along the shaft. With respect to traditional model based identification procedures, this approach using oil film forces instead of oil film linearized stiffness and damping coefficients, and unfiltered orbits instead of 1X vibration components is suitable to deal with non-linear behaviour of the system.

  17. Star-field identification algorithm. [for implementation on CCD-based imaging camera

    NASA Technical Reports Server (NTRS)

    Scholl, M. S.

    1993-01-01

    A description of a new star-field identification algorithm that is suitable for implementation on CCD-based imaging cameras is presented. The minimum identifiable star pattern element consists of an oriented star triplet defined by three stars, their celestial coordinates, and their visual magnitudes. The algorithm incorporates tolerance to faulty input data, errors in the reference catalog, and instrument-induced systematic errors.

  18. Damage identification of a TLP floating wind turbine by meta-heuristic algorithms

    NASA Astrophysics Data System (ADS)

    Ettefagh, M. M.

    2015-12-01

    Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring (SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP (Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms (GA), Artificial Immune System (AIS), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine (TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.

  19. Modular detector for deep underwater registration of muons and muon groups

    NASA Technical Reports Server (NTRS)

    Demianov, A. I.; Sarycheva, L. I.; Sinyov, N. B.; Varadanyan, I. N.; Yershov, A. A.

    1985-01-01

    Registration and identification of muons and muon groups penetrating into the ocean depth, can be performed using a modular multilayer detector with high resolution bidimensional readout - deep underwater calorimeter (project NADIR). Laboratory testing of a prototype sensor cell with liquid scintillator in light-tight casing, testifies to the practicability of the full-scale experiment within reasonable expences.

  20. Constraint identification and algorithm stabilization for degenerate nonlinear programs.

    SciTech Connect

    Wright, S. J.; Mathematics and Computer Science

    2003-01-01

    In the vicinity of a solution of a nonlinear programming problem at which both strict complementarity and linear independence of the active constraints may fail to hold, we describe a technique for distinguishing weakly active from strongly active constraints. We show that this information can be used to modify the sequential quadratic programming algorithm so that it exhibits superlinear convergence to the solution under assumptions weaker than those made in previous analyses.

  1. Gene Identification Algorithms Using Exploratory Statistical Analysis of Periodicity

    NASA Astrophysics Data System (ADS)

    Mukherjee, Shashi Bajaj; Sen, Pradip Kumar

    2010-10-01

    Studying periodic pattern is expected as a standard line of attack for recognizing DNA sequence in identification of gene and similar problems. But peculiarly very little significant work is done in this direction. This paper studies statistical properties of DNA sequences of complete genome using a new technique. A DNA sequence is converted to a numeric sequence using various types of mappings and standard Fourier technique is applied to study the periodicity. Distinct statistical behaviour of periodicity parameters is found in coding and non-coding sequences, which can be used to distinguish between these parts. Here DNA sequences of Drosophila melanogaster were analyzed with significant accuracy.

  2. Automated mineral identification algorithm using optical properties of crystals

    NASA Astrophysics Data System (ADS)

    Aligholi, Saeed; Khajavi, Reza; Razmara, Morteza

    2015-12-01

    A method has been developed to automatically characterize the type of mineral phases by means of digital image analysis using optical properties of crystals. The method relies on microscope automation, digital image acquisition, image processing and analysis. Two hundred series of digital images were taken from 45 standard thin sections using a digital camera mounted on a conventional microscope and then transmitted to a computer. CIELab color space is selected for the processing, in order to effectively employ its well-defined color difference metric for introducing appropriate color-based feature. Seven basic optical properties of minerals (A. color; B. pleochroism; C. interference color; D. birefringence; E. opacity; F. isotropy; G. extinction angle) are redefined. The Local Binary Pattern (LBP) operator and modeling texture is integrated in the Mineral Identification (MI) scheme to identify homogeneous regions in microscopic images of minerals. The accuracy of mineral identification using the method was %99, %98, %96 and %95 for biotite, hornblende, quartz and calcite minerals, respectively. The method is applicable to other minerals and phases for which individual optical properties of crystals do not provide enough discrimination between the relevant phases. On the basis of this research, it can be concluded that if the CIELab color space and the local binary pattern (LBP) are applied, it is possible to recognize the mineral samples with the accuracy of more than 98%.

  3. Particle identification algorithms for the HARP forward spectrometer

    NASA Astrophysics Data System (ADS)

    Catanesi, M. G.; Radicioni, E.; Edgecock, R.; Ellis, M.; Robbins, S.; Soler, F. J. P.; Gößling, C.; Bunyatov, S.; Chelkov, G.; Chukanov, A.; Dedovitch, D.; Gostkin, M.; Guskov, A.; Khartchenko, D.; Klimov, O.; Krasnoperov, A.; Kroumchtein, Z.; Kustov, D.; Nefedov, Y.; Popov, B.; Serdiouk, V.; Tereshchenko, V.; Zhemchugov, A.; Di Capua, E.; Vidal-Sitjes, G.; Artamonov, A.; Arce, P.; Giani, S.; Gilardoni, S.; Gorbunov, P.; Grant, A.; Grossheim, A.; Gruber, P.; Ivanchenko, V.; Kayis-Topaksu, A.; Panman, J.; Papadopoulos, I.; Pasternak, J.; Tcherniaev, E.; Tsukerman, I.; Veenhof, R.; Wiebusch, C.; Zucchelli, P.; Blondel, A.; Borghi, S.; Campanelli, M.; Cervera-Villanueva, A.; Morone, M. C.; Prior, G.; Schroeter, R.; Kato, I.; Nakaya, T.; Nishikawa, K.; Ueda, S.; Gastaldi, U.; Mills, G. B.; Graulich, J. S.; Grégoire, G.; Bonesini, M.; De Min, A.; Ferri, F.; Paganoni, M.; Paleari, F.; Kirsanov, M.; Bagulya, A.; Grichine, V.; Polukhina, N.; Palladino, V.; Coney, L.; Schmitz, D.; Barr, G.; De Santo, A.; Pattison, C.; Zuber, K.; Bobisut, F.; Gibin, D.; Guglielmi, A.; Laveder, M.; Menegolli, A.; Mezzetto, M.; Dumarchez, J.; Vannucci, F.; Ammosov, V.; Koreshev, V.; Semak, A.; Zaets, V.; Dore, U.; Orestano, D.; Pastore, F.; Tonazzo, A.; Tortora, L.; Booth, C.; Buttar, C.; Hodgson, P.; Howlett, L.; Bogomilov, M.; Chizhov, M.; Kolev, D.; Tsenov, R.; Piperov, S.; Temnikov, P.; Apollonio, M.; Chimenti, P.; Giannini, G.; Santin, G.; Hayato, Y.; Ichikawa, A.; Kobayashi, T.; Burguet-Castell, J.; Gómez-Cadenas, J. J.; Novella, P.; Sorel, M.; Tornero, A.

    2007-03-01

    The particle identification (PID) methods used for the calculation of secondary pion yields with the HARP forward spectrometer are presented. Information from time of flight and Cherenkov detectors is combined using likelihood techniques. The efficiencies and purities associated with the different PID selection criteria are obtained from the data. For the proton-aluminium interactions at 12.9 GeV/ c incident momentum, the PID efficiencies for positive pions are 86% in the momentum range below 2 GeV/ c, 92% between 2 and 3 GeV/ c and 98% in the momentum range above 3 GeV/ c. The purity of the selection is better than 92% for all momenta. Special emphasis has been put on understanding the main error sources. The final PID uncertainty on the pion yield is 3.3%.

  4. Neural network based algorithm for automatic identification of cough sounds.

    PubMed

    Swarnkar, V; Abeyratne, U R; Amrulloh, Yusuf; Hukins, Craig; Triasih, Rina; Setyati, Amalia

    2013-01-01

    Cough is the most common symptom of the several respiratory diseases containing diagnostic information. It is the best suitable candidate to develop a simplified screening technique for the management of respiratory diseases in timely manner, both in developing and developed countries, particularly in remote areas where medical facilities are limited. However, major issue hindering the development is the non-availability of reliable technique to automatically identify cough events. Medical practitioners still rely on manual counting, which is laborious and time consuming. In this paper we propose a novel method, based on the neural network to automatically identify cough segments, discarding other sounds such a speech, ambient noise etc. We achieved the accuracy of 98% in classifying 13395 segments into two classes, 'cough' and 'other sounds', with the sensitivity of 93.44% and specificity of 94.52%. Our preliminary results indicate that method can develop into a real-time cough identification technique in continuous cough monitoring systems. PMID:24110049

  5. A modified Fuzzy C-Means (FCM) Clustering algorithm and its application on carbonate fluid identification

    NASA Astrophysics Data System (ADS)

    Liu, Lifeng; Sun, Sam Zandong; Yu, Hongyu; Yue, Xingtong; Zhang, Dong

    2016-06-01

    Considering the fact that the fluid distribution in carbonate reservoir is very complicated and the existing fluid prediction methods are not able to produce ideal predicted results, this paper proposes a new fluid identification method in carbonate reservoir based on the modified Fuzzy C-Means (FCM) Clustering algorithm. Both initialization and globally optimum cluster center are produced by Chaotic Quantum Particle Swarm Optimization (CQPSO) algorithm, which can effectively avoid the disadvantage of sensitivity to initial values and easily falling into local convergence in the traditional FCM Clustering algorithm. Then, the modified algorithm is applied to fluid identification in the carbonate X area in Tarim Basin of China, and a mapping relation between fluid properties and pre-stack elastic parameters will be built in multi-dimensional space. It has been proven that this modified algorithm has a good ability of fuzzy cluster and its total coincidence rate of fluid prediction reaches 97.10%. Besides, the membership of different fluids can be accumulated to obtain respective probability, which can evaluate the uncertainty in fluid identification result.

  6. A novel algorithm for real-time adaptive signal detection and identification

    SciTech Connect

    Sleefe, G.E.; Ladd, M.D.; Gallegos, D.E.; Sicking, C.W.; Erteza, I.A.

    1998-04-01

    This paper describes a novel digital signal processing algorithm for adaptively detecting and identifying signals buried in noise. The algorithm continually computes and updates the long-term statistics and spectral characteristics of the background noise. Using this noise model, a set of adaptive thresholds and matched digital filters are implemented to enhance and detect signals that are buried in the noise. The algorithm furthermore automatically suppresses coherent noise sources and adapts to time-varying signal conditions. Signal detection is performed in both the time-domain and the frequency-domain, thereby permitting the detection of both broad-band transients and narrow-band signals. The detection algorithm also provides for the computation of important signal features such as amplitude, timing, and phase information. Signal identification is achieved through a combination of frequency-domain template matching and spectral peak picking. The algorithm described herein is well suited for real-time implementation on digital signal processing hardware. This paper presents the theory of the adaptive algorithm, provides an algorithmic block diagram, and demonstrate its implementation and performance with real-world data. The computational efficiency of the algorithm is demonstrated through benchmarks on specific DSP hardware. The applications for this algorithm, which range from vibration analysis to real-time image processing, are also discussed.

  7. Cloud identification using genetic algorithms and massively parallel computation

    NASA Technical Reports Server (NTRS)

    Buckles, Bill P.; Petry, Frederick E.

    1996-01-01

    As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user

  8. The MICE Muon Beam Line

    SciTech Connect

    Apollonio, Marco

    2011-10-06

    In the Muon Ionization Cooling Experiment (MICE) at RAL, muons are produced and transported in a dedicated beam line connecting the production point (target) to the cooling channel. We discuss the main features of the beamline, meant to provide muons with momenta between 140 MeV/c and 240 MeV/c and emittances up to 10 mm rad, which is accomplished by means of a diffuser. Matching procedures to the MICE cooling channel are also described. In summer 2010 we performed an intense data taking campaign to finalize the calibration of the MICE Particle Identification (PID) detectors and the understanding of the beam line, which completes the STEPI phase of MICE. We highlight the main results from these data.

  9. Convergence analysis of the alternating RGLS algorithm for the identification of the reduced complexity Volterra model.

    PubMed

    Laamiri, Imen; Khouaja, Anis; Messaoud, Hassani

    2015-03-01

    In this paper we provide a convergence analysis of the alternating RGLS (Recursive Generalized Least Square) algorithm used for the identification of the reduced complexity Volterra model describing stochastic non-linear systems. The reduced Volterra model used is the 3rd order SVD-PARAFC-Volterra model provided using the Singular Value Decomposition (SVD) and the Parallel Factor (PARAFAC) tensor decomposition of the quadratic and the cubic kernels respectively of the classical Volterra model. The Alternating RGLS (ARGLS) algorithm consists on the execution of the classical RGLS algorithm in alternating way. The ARGLS convergence was proved using the Ordinary Differential Equation (ODE) method. It is noted that the algorithm convergence canno׳t be ensured when the disturbance acting on the system to be identified has specific features. The ARGLS algorithm is tested in simulations on a numerical example by satisfying the determined convergence conditions. To raise the elegies of the proposed algorithm, we proceed to its comparison with the classical Alternating Recursive Least Squares (ARLS) presented in the literature. The comparison has been built on a non-linear satellite channel and a benchmark system CSTR (Continuous Stirred Tank Reactor). Moreover the efficiency of the proposed identification approach is proved on an experimental Communicating Two Tank system (CTTS). PMID:25442399

  10. Muons in gamma showers

    NASA Technical Reports Server (NTRS)

    Stanev, T.; Vankov, C. P.; Halzen, F.

    1985-01-01

    Muon production in gamma-induced air showers, accounting for all major processes. For muon energies in the GeV region the photoproduction is by far the most important process, while the contribution of micron + micron pair creation is not negligible for TeV muons. The total rate of muons in gamma showers is, however, very low.

  11. Evaluation of the ERBE scene identification algo-rithm

    NASA Technical Reports Server (NTRS)

    Vemury, S. K.

    1987-01-01

    The sensitivity of the radiation budget parameters and the scene selection process to different factors is evaluated. The use of ERB-7 CLE models provides instantaneous albedo and longwave flux values which are in essential agreement in the 70 deg cutoff case with those from the SAB method. The increase in albedo with increasing satellite zenith angle cutoff is not apparent at the target area level for different surface types. GOES models seem to show an increase in instantaneous albedo at the global level with satellite zenith angle of the same nature as the ERB-7 models investigated in a previous report and are, therefore, probably not an improvement. The use of recently derived NCLE models did not make a noticeable change in the budget parameters; but the cloud classification did show hemispherical differences and caused a day-night readjustment of cloudiness amounts. Preliminary results for an additional month (December 1979) indicate good agreement between the SAB and MLE methods. Additional work is required to establish the agreement for all seasons. Comparison of derived cloud amounts with other data sets such as THIR/TOMS indicates good zonal agreement. Sampling adequacy investigations at different temporal averaging intervals with the SAB method, indicate large uncertainties in small time average cases. For a 6-day averaging period, sampling is very poor with only 23% of the globe contributing toward the global mean albedo. Effect of modifications to the MLE procedure seem to have little effect on the derived budget quantities in an averaged sense. Significant differences in the flux values due to differences in scene selection are apparent in individual target areas studies. A modification of the MLE procedure to mimic the perpendicular bisector algorithm indicated no effect on the gross radiation budget quantities.

  12. An identification algorithm of model kinetic parameters of the interfacial layer growth in fiber composites

    NASA Astrophysics Data System (ADS)

    Zubov, V.; Lurie, S.; Solyaev, Y.

    2016-04-01

    This paper considers the identification algorithm of parameters included in a parabolic law that is often used to predict the time dependence of the thickness of the interfacial layers in the structure of composite materials based on a metal matrix. The incubation period of the process and the speed of reaction and pressure are taken into account. The proposed algorithm of identification is based on the introduction of a minimized objective function of a special kind. The problem of identification of unknown parameters in the parabolic law is formulated in a variational form. The authors of the paper have determined the desired parameters, under which the objective function has a minimum value. It is shown that on the basis of four known experimental values of the interfacial layer thickness, corresponding to different values of temperature, pressure and the time of the interfacial layer growth, it is possible to identified four model parameters. They are the activation energy, a pre-exponential parameter, the delay time of the start of the interfacial layer formation, and the parameter determining the pressure effect on the rate of interfacial layer growth. The stability of the proposed identification algorithm is also studied.

  13. A Brightness-Referenced Star Identification Algorithm for APS Star Trackers

    PubMed Central

    Zhang, Peng; Zhao, Qile; Liu, Jingnan; Liu, Ning

    2014-01-01

    Star trackers are currently the most accurate spacecraft attitude sensors. As a result, they are widely used in remote sensing satellites. Since traditional charge-coupled device (CCD)-based star trackers have a limited sensitivity range and dynamic range, the matching process for a star tracker is typically not very sensitive to star brightness. For active pixel sensor (APS) star trackers, the intensity of an imaged star is valuable information that can be used in star identification process. In this paper an improved brightness referenced star identification algorithm is presented. This algorithm utilizes the k-vector search theory and adds imaged stars' intensities to narrow the search scope and therefore increase the efficiency of the matching process. Based on different imaging conditions (slew, bright bodies, etc.) the developed matching algorithm operates in one of two identification modes: a three-star mode, and a four-star mode. If the reference bright stars (the stars brighter than three magnitude) show up, the algorithm runs the three-star mode and efficiency is further improved. The proposed method was compared with other two distinctive methods the pyramid and geometric voting methods. All three methods were tested with simulation data and actual in orbit data from the APS star tracker of ZY-3. Using a catalog composed of 1500 stars, the results show that without false stars the efficiency of this new method is 4∼5 times that of the pyramid method and 35∼37 times that of the geometric method. PMID:25299950

  14. Time-varying modal parameters identification of a spacecraft with rotating flexible appendage by recursive algorithm

    NASA Astrophysics Data System (ADS)

    Ni, Zhiyu; Mu, Ruinan; Xun, Guangbin; Wu, Zhigang

    2016-01-01

    The rotation of spacecraft flexible appendage may cause changes in modal parameters. For this time-varying system, the computation cost of the frequently-used singular value decomposition (SVD) identification method is high. Some control problems, such as the self-adaptive control, need the latest modal parameters to update the controller parameters in time. In this paper, the projection approximation subspace tracking (PAST) recursive algorithm is applied as an alternative method to identify the time-varying modal parameters. This method avoids the SVD by signal subspace projection and improves the computational efficiency. To verify the ability of this recursive algorithm in spacecraft modal parameters identification, a spacecraft model with rapid rotational appendage, Soil Moisture Active/Passive (SMAP) satellite, is established, and the time-varying modal parameters of the satellite are identified recursively by designing the input and output signals. The results illustrate that this recursive algorithm can obtain the modal parameters in the high signal noise ratio (SNR) and it has better computational efficiency than the SVD method. Moreover, to improve the identification precision of this recursive algorithm in the low SNR, the wavelet de-noising technology is used to decrease the effect of noises.

  15. A brightness-referenced star identification algorithm for APS star trackers.

    PubMed

    Zhang, Peng; Zhao, Qile; Liu, Jingnan; Liu, Ning

    2014-01-01

    Star trackers are currently the most accurate spacecraft attitude sensors. As a result, they are widely used in remote sensing satellites. Since traditional charge-coupled device (CCD)-based star trackers have a limited sensitivity range and dynamic range, the matching process for a star tracker is typically not very sensitive to star brightness. For active pixel sensor (APS) star trackers, the intensity of an imaged star is valuable information that can be used in star identification process. In this paper an improved brightness referenced star identification algorithm is presented. This algorithm utilizes the k-vector search theory and adds imaged stars' intensities to narrow the search scope and therefore increase the efficiency of the matching process. Based on different imaging conditions (slew, bright bodies, etc.) the developed matching algorithm operates in one of two identification modes: a three-star mode, and a four-star mode. If the reference bright stars (the stars brighter than three magnitude) show up, the algorithm runs the three-star mode and efficiency is further improved. The proposed method was compared with other two distinctive methods the pyramid and geometric voting methods. All three methods were tested with simulation data and actual in orbit data from the APS star tracker of ZY-3. Using a catalog composed of 1500 stars, the results show that without false stars the efficiency of this new method is 4~5 times that of the pyramid method and 35~37 times that of the geometric method. PMID:25299950

  16. Parameters Identification of Fluxgate Magnetic Core Adopting the Biogeography-Based Optimization Algorithm

    PubMed Central

    Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin

    2016-01-01

    The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974

  17. Parameters Identification of Fluxgate Magnetic Core Adopting the Biogeography-Based Optimization Algorithm.

    PubMed

    Jiang, Wenjuan; Shi, Yunbo; Zhao, Wenjie; Wang, Xiangxin

    2016-01-01

    The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect the hysteresis properties of the magnetic material precisely, which makes it widely used in hysteresis modelling and simulation of ferromagnetic materials. However, in practice, it is difficult to determine the parameters accurately owing to the sensitivity of the parameters. In this paper, the Biogeography-Based Optimization (BBO) algorithm is applied to identify the Jiles-Atherton model parameters. To enhance the performances of the BBO algorithm such as global search capability, search accuracy and convergence rate, an improved Biogeography-Based Optimization (IBBO) algorithm is put forward by using Arnold map and mutation strategy of Differential Evolution (DE) algorithm. Simulation results show that IBBO algorithm is superior to Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Differential Evolution algorithm and BBO algorithm in identification accuracy and convergence rate. The IBBO algorithm is applied to identify Jiles-Atherton model parameters of selected permalloy. The simulation hysteresis loop is in high agreement with experimental data. Using permalloy as core of fluxgate probe, the simulation output is consistent with experimental output. The IBBO algorithm can identify the parameters of Jiles-Atherton model accurately, which provides a basis for the precise analysis and design of instruments and equipment with magnetic core. PMID:27347974

  18. A NEW ALGORITHM FOR RADIOISOTOPE IDENTIFICATION OF SHIELDED AND MASKED SNM/RDD MATERIALS

    SciTech Connect

    Jeffcoat, R.

    2012-06-05

    Detection and identification of shielded and masked nuclear materials is crucial to national security, but vast borders and high volumes of traffic impose stringent requirements for practical detection systems. Such tools must be be mobile, and hence low power, provide a low false alarm rate, and be sufficiently robust to be operable by non-technical personnel. Currently fielded systems have not achieved all of these requirements simultaneously. Transport modeling such as that done in GADRAS is able to predict observed spectra to a high degree of fidelity; our research is focusing on a radionuclide identification algorithm that inverts this modeling within the constraints imposed by a handheld device. Key components of this work include incorporation of uncertainty as a function of both the background radiation estimate and the hypothesized sources, dimensionality reduction, and nonnegative matrix factorization. We have partially evaluated performance of our algorithm on a third-party data collection made with two different sodium iodide detection devices. Initial results indicate, with caveats, that our algorithm performs as good as or better than the on-board identification algorithms. The system developed was based on a probabilistic approach with an improved approach to variance modeling relative to past work. This system was chosen based on technical innovation and system performance over algorithms developed at two competing research institutions. One key outcome of this probabilistic approach was the development of an intuitive measure of confidence which was indeed useful enough that a classification algorithm was developed based around alarming on high confidence targets. This paper will present and discuss results of this novel approach to accurately identifying shielded or masked radioisotopes with radiation detection systems.

  19. Utilization of advanced clutter suppression algorithms for improved standoff detection and identification of radionuclide threats

    NASA Astrophysics Data System (ADS)

    Cosofret, Bogdan R.; Shokhirev, Kirill; Mulhall, Phil; Payne, David; Harris, Bernard

    2014-05-01

    Technology development efforts seek to increase the capability of detection systems in low Signal-to-Noise regimes encountered in both portal and urban detection applications. We have recently demonstrated significant performance enhancement in existing Advanced Spectroscopic Portals (ASP), Standoff Radiation Detection Systems (SORDS) and handheld isotope identifiers through the use of new advanced detection and identification algorithms. The Poisson Clutter Split (PCS) algorithm is a novel approach for radiological background estimation that improves the detection and discrimination capability of medium resolution detectors. The algorithm processes energy spectra and performs clutter suppression, yielding de-noised gamma-ray spectra that enable significant enhancements in detection and identification of low activity threats with spectral target recognition algorithms. The performance is achievable at the short integration times (0.5 - 1 second) necessary for operation in a high throughput and dynamic environment. PCS has been integrated with ASP, SORDS and RIID units and evaluated in field trials. We present a quantitative analysis of algorithm performance against data collected by a range of systems in several cluttered environments (urban and containerized) with embedded check sources. We show that the algorithm achieves a high probability of detection/identification with low false alarm rates under low SNR regimes. For example, utilizing only 4 out of 12 NaI detectors currently available within an ASP unit, PCS processing demonstrated Pd,ID > 90% at a CFAR (Constant False Alarm Rate) of 1 in 1000 occupancies against weak activity (7 - 8μCi) and shielded sources traveling through the portal at 30 mph. This vehicle speed is a factor of 6 higher than was previously possible and results in significant increase in system throughput and overall performance.

  20. Crater Identification Algorithm for the Lost in Low Lunar Orbit Scenario

    NASA Technical Reports Server (NTRS)

    Hanak, Chad; Crain, TImothy

    2010-01-01

    Recent emphasis by NASA on returning astronauts to the Moon has placed attention on the subject of lunar surface feature tracking. Although many algorithms have been proposed for lunar surface feature tracking navigation, much less attention has been paid to the issue of navigational state initialization from lunar craters in a lost in low lunar orbit (LLO) scenario. That is, a scenario in which lunar surface feature tracking must begin, but current navigation state knowledge is either unavailable or too poor to initiate a tracking algorithm. The situation is analogous to the lost in space scenario for star trackers. A new crater identification algorithm is developed herein that allows for navigation state initialization from as few as one image of the lunar surface with no a priori state knowledge. The algorithm takes as inputs the locations and diameters of craters that have been detected in an image, and uses the information to match the craters to entries in the USGS lunar crater catalog via non-dimensional crater triangle parameters. Due to the large number of uncataloged craters that exist on the lunar surface, a probability-based check was developed to reject false identifications. The algorithm was tested on craters detected in four revolutions of Apollo 16 LLO images, and shown to perform well.

  1. Identification of continuous-time dynamical systems: Neural network based algorithms and parallel implementation

    SciTech Connect

    Farber, R.M.; Lapedes, A.S.; Rico-Martinez, R.; Kevrekidis, I.G.

    1993-06-01

    Time-delay mappings constructed using neural networks have proven successful performing nonlinear system identification; however, because of their discrete nature, their use in bifurcation analysis of continuous-tune systems is limited. This shortcoming can be avoided by embedding the neural networks in a training algorithm that mimics a numerical integrator. Both explicit and implicit integrators can be used. The former case is based on repeated evaluations of the network in a feedforward implementation; the latter relies on a recurrent network implementation. Here the algorithms and their implementation on parallel machines (SIMD and MIMD architectures) are discussed.

  2. Identification of continuous-time dynamical systems: Neural network based algorithms and parallel implementation

    SciTech Connect

    Farber, R.M.; Lapedes, A.S. ); Rico-Martinez, R.; Kevrekidis, I.G. . Dept. of Chemical Engineering)

    1993-01-01

    Time-delay mappings constructed using neural networks have proven successful performing nonlinear system identification; however, because of their discrete nature, their use in bifurcation analysis of continuous-tune systems is limited. This shortcoming can be avoided by embedding the neural networks in a training algorithm that mimics a numerical integrator. Both explicit and implicit integrators can be used. The former case is based on repeated evaluations of the network in a feedforward implementation; the latter relies on a recurrent network implementation. Here the algorithms and their implementation on parallel machines (SIMD and MIMD architectures) are discussed.

  3. Bearing fault component identification using information gain and machine learning algorithms

    NASA Astrophysics Data System (ADS)

    Vinay, Vakharia; Kumar, Gupta Vijay; Kumar, Kankar Pavan

    2015-04-01

    In the present study an attempt has been made to identify various bearing faults using machine learning algorithm. Vibration signals obtained from faults in inner race, outer race, rolling element and combined faults are considered. Raw vibration signal cannot be used directly since vibration signals are masked by noise. To overcome this difficulty combined time frequency domain method such as wavelet transform is used. Further wavelet selection criteria based on minimum permutation entropy is employed to select most appropriate base wavelet. Statistical features from selected wavelet coefficients are calculated to form feature vector. To reduce size of feature vector information gain attribute selection method is employed. Modified feature set is fed in to machine learning algorithm such as random forest and self-organizing map for getting maximize fault identification efficiency. Results obtained revealed that attribute selection method shows improvement in fault identification accuracy of bearing components.

  4. Application of decision tree algorithm for identification of rock forming minerals using energy dispersive spectrometry

    NASA Astrophysics Data System (ADS)

    Akkaş, Efe; Çubukçu, H. Evren; Artuner, Harun

    2014-05-01

    C5.0 Decision Tree algorithm. The predictions of the decision tree classifier, namely the matching of the test data with the appropriate mineral group, yield an overall accuracy of >90%. Besides, the algorithm successfully discriminated some mineral (groups) despite their similar elemental composition such as orthopyroxene ((Mg,Fe)2[SiO6]) and olivine ((Mg,Fe)2[SiO4]). Furthermore, the effects of various operating conditions have been insignificant for the classifier. These results demonstrate that decision tree algorithm stands as an accurate, rapid and automated method for mineral classification/identification. Hence, decision tree algorithm would be a promising component of an expert system focused on real-time, automated mineral identification using energy dispersive spectrometers without being affected from the operating conditions. Keywords: mineral identification, energy dispersive spectrometry, decision tree algorithm.

  5. Online identification algorithms for integrated dielectric electroactive polymer sensors and self-sensing concepts

    NASA Astrophysics Data System (ADS)

    Hoffstadt, Thorben; Griese, Martin; Maas, Jürgen

    2014-10-01

    Transducers based on dielectric electroactive polymers (DEAP) use electrostatic pressure to convert electric energy into strain energy or vice versa. Besides this, they are also designed for sensor applications in monitoring the actual stretch state on the basis of the deformation dependent capacitive-resistive behavior of the DEAP. In order to enable an efficient and proper closed loop control operation of these transducers, e.g. in positioning or energy harvesting applications, on the one hand, sensors based on DEAP material can be integrated into the transducers and evaluated externally, and on the other hand, the transducer itself can be used as a sensor, also in terms of self-sensing. For this purpose the characteristic electrical behavior of the transducer has to be evaluated in order to determine the mechanical state. Also, adequate online identification algorithms with sufficient accuracy and dynamics are required, independent from the sensor concept utilized, in order to determine the electrical DEAP parameters in real time. Therefore, in this contribution, algorithms are developed in the frequency domain for identifications of the capacitance as well as the electrode and polymer resistance of a DEAP, which are validated by measurements. These algorithms are designed for self-sensing applications, especially if the power electronics utilized is operated at a constant switching frequency, and parasitic harmonic oscillations are induced besides the desired DC value. These oscillations can be used for the online identification, so an additional superimposed excitation is no longer necessary. For this purpose a dual active bridge (DAB) is introduced to drive the DEAP transducer. The capabilities of the real-time identification algorithm in combination with the DAB are presented in detail and discussed, finally.

  6. Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Shou-ping; Xin, Xiao-kang

    2016-01-01

    Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

  7. Structural system identification using degree of freedom-based reduction and hierarchical clustering algorithm

    NASA Astrophysics Data System (ADS)

    Chang, Seongmin; Baek, Sungmin; Kim, Ki-Ook; Cho, Maenghyo

    2015-06-01

    A system identification method has been proposed to validate finite element models of complex structures using measured modal data. Finite element method is used for the system identification as well as the structural analysis. In perturbation methods, the perturbed system is expressed as a combination of the baseline structure and the related perturbations. The changes in dynamic responses are applied to determine the structural modifications so that the equilibrium may be satisfied in the perturbed system. In practical applications, the dynamic measurements are carried out on a limited number of accessible nodes and associated degrees of freedom. The equilibrium equation is, in principle, expressed in terms of the measured (master, primary) and unmeasured (slave, secondary) degrees of freedom. Only the specified degrees of freedom are included in the equation formulation for identification and the unspecified degrees of freedom are eliminated through the iterative improved reduction scheme. A large number of system parameters are included as the unknown variables in the system identification of large-scaled structures. The identification problem with large number of system parameters requires a large amount of computation time and resources. In the present study, a hierarchical clustering algorithm is applied to reduce the number of system parameters effectively. Numerical examples demonstrate that the proposed method greatly improves the accuracy and efficiency in the inverse problem of identification.

  8. Optimal sensor placement for time-domain identification using a wavelet-based genetic algorithm

    NASA Astrophysics Data System (ADS)

    Mahdavi, Seyed Hossein; Razak, Hashim Abdul

    2016-06-01

    This paper presents a wavelet-based genetic algorithm strategy for optimal sensor placement (OSP) effective for time-domain structural identification. Initially, the GA-based fitness evaluation is significantly improved by using adaptive wavelet functions. Later, a multi-species decimal GA coding system is modified to be suitable for an efficient search around the local optima. In this regard, a local operation of mutation is introduced in addition with regeneration and reintroduction operators. It is concluded that different characteristics of applied force influence the features of structural responses, and therefore the accuracy of time-domain structural identification is directly affected. Thus, the reliable OSP strategy prior to the time-domain identification will be achieved by those methods dealing with minimizing the distance of simulated responses for the entire system and condensed system considering the force effects. The numerical and experimental verification on the effectiveness of the proposed strategy demonstrates the considerably high computational performance of the proposed OSP strategy, in terms of computational cost and the accuracy of identification. It is deduced that the robustness of the proposed OSP algorithm lies in the precise and fast fitness evaluation at larger sampling rates which result in the optimum evaluation of the GA-based exploration and exploitation phases towards the global optimum solution.

  9. An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications

    PubMed Central

    Tong, Mingsi; Song, John; Chu, Wei

    2015-01-01

    The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation. PMID:26958441

  10. An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications.

    PubMed

    Tong, Mingsi; Song, John; Chu, Wei

    2015-01-01

    The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation. PMID:26958441

  11. Final Progress Report: Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes Feasibility Study

    SciTech Connect

    Rawool-Sullivan, Mohini; Bounds, John Alan; Brumby, Steven P.; Prasad, Lakshman; Sullivan, John P.

    2012-04-30

    This is the final report of the project titled, 'Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes,' PMIS project number LA10-HUMANID-PD03. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). It summarizes work performed over the FY10 time period. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). Human analysts begin analyzing a spectrum based on features in the spectrum - lines and shapes that are present in a given spectrum. The proposed work was to carry out a feasibility study that will pick out all gamma ray peaks and other features such as Compton edges, bremsstrahlung, presence/absence of shielding and presence of neutrons and escape peaks. Ultimately success of this feasibility study will allow us to collectively explain identified features and form a realistic scenario that produced a given spectrum in the future. We wanted to develop and demonstrate machine learning algorithms that will qualitatively enhance the automated identification capabilities of portable radiological sensors that are currently being used in the field.

  12. Effects of high count rate and gain shift on isotope identification algorithms

    SciTech Connect

    Robinson, Sean M.; Kiff, Scott D.; Ashbaker, Eric D.; Flumerfelt, Eric L.; Salvitti, Matthew

    2009-11-01

    Spectroscopic gamma-ray detectors are used for many research, industrial, and homeland- security applications. Thallium-doped sodium iodide, (NaI(Tl)), scintillation crystals coupled to photomultiplier tubes provide medium-resolution spectral data about the surrounding environment. NaI(Tl)-based detectors, paired with spectral identification algorithms, are often effective for identifying gamma-ray sources by isotope. However, intrinsic limitations for NaI(Tl) systems exist, including gain shifts and spectral marring (e.g., loss of resolution and count-rate saturation) at high count rates. These effects are hardware dependent and have strong effects on the radioisotopic identification capability of NaI(Tl)-based systems. In this work, the effects of high count rate on the response of isotope-identification algorithms are explored. It is shown that a small gain shift of a few tens of keV is sufficient to disturb identification. The onset of this and other spectral effects is estimated for NaI(Tl) crystals, and a mechanism for mitigating these effects by estimating and correcting for them is implemented and evaluated.

  13. Effects of High Count Rate and Gain Shift on Isotope Identification Algorithms

    SciTech Connect

    Robinson, Sean M.; Kiff, Scott D.; Ashbaker, Eric D.; Bender, Sarah E.; Flumerfelt, Eric L.; Salvitti, Matthew; Borgardt, James D.; Woodring, Mitchell L.

    2007-12-31

    Spectroscopic gamma-ray detectors are used for many research applications, as well as Homeland Security screening applications. Sodium iodide (NaI) scintillator crystals coupled with photomultiplier tubes (PMTs) provide medium-resolution spectral data about the surrounding environment. NaI based detectors, paired with spectral identification algorithms, are often effective in identifying sources of interest by isotope. However, intrinsic limitations exist for NaI systems because of gain shifts and spectral marring (e.g., loss of resolution and count-rate saturation) at high count rates. These effects are hardware dependent, and have strong effects on the radioisotopic identification capability of these systems. In this work, the effects of high count rate on the capability of isotope identification algorithms are explored. It is shown that a small gain shift of a few tens of keV is sufficient to disturb identification. The onset of this and other spectral effects are estimated for several systems., and a mechanism for mitigating these effects by estimating and correcting for them is implemented and evaluated.

  14. An efficient identification approach for stable and unstable nonlinear systems using Colliding Bodies Optimization algorithm.

    PubMed

    Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P

    2015-11-01

    This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. PMID:26362314

  15. MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra

    PubMed Central

    2014-01-01

    Today’s highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda, is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform. PMID:24909410

  16. Parameters Identification for Photovoltaic Module Based on an Improved Artificial Fish Swarm Algorithm

    PubMed Central

    Wang, Hong-Hua

    2014-01-01

    A precise mathematical model plays a pivotal role in the simulation, evaluation, and optimization of photovoltaic (PV) power systems. Different from the traditional linear model, the model of PV module has the features of nonlinearity and multiparameters. Since conventional methods are incapable of identifying the parameters of PV module, an excellent optimization algorithm is required. Artificial fish swarm algorithm (AFSA), originally inspired by the simulation of collective behavior of real fish swarms, is proposed to fast and accurately extract the parameters of PV module. In addition to the regular operation, a mutation operator (MO) is designed to enhance the searching performance of the algorithm. The feasibility of the proposed method is demonstrated by various parameters of PV module under different environmental conditions, and the testing results are compared with other studied methods in terms of final solutions and computational time. The simulation results show that the proposed method is capable of obtaining higher parameters identification precision. PMID:25243233

  17. Implementation of an algorithm for cylindrical object identification using range data

    NASA Technical Reports Server (NTRS)

    Bozeman, Sylvia T.; Martin, Benjamin J.

    1989-01-01

    One of the problems in 3-D object identification and localization is addressed. In robotic and navigation applications the vision system must be able to distinguish cylindrical or spherical objects as well as those of other geometric shapes. An algorithm was developed to identify cylindrical objects in an image when range data is used. The algorithm incorporates the Hough transform for line detection using edge points which emerge from a Sobel mask. Slices of the data are examined to locate arcs of circles using the normal equations of an over-determined linear system. Current efforts are devoted to testing the computer implementation of the algorithm. Refinements are expected to continue in order to accommodate cylinders in various positions. A technique is sought which is robust in the presence of noise and partial occlusions.

  18. Point group identification algorithm in dynamic response analysis of nonlinear stochastic systems

    NASA Astrophysics Data System (ADS)

    Li, Tao; Chen, Jian-bing; Li, Jie

    2016-03-01

    The point group identification (PGI) algorithm is proposed to determine the representative point sets in response analysis of nonlinear stochastic dynamic systems. The PGI algorithm is employed to identify point groups and their feature points in an initial point set by combining subspace clustering analysis and the graph theory. Further, the representative point set of the random-variate space is determined according to the minimum generalized F-discrepancy. The dynamic responses obtained by incorporating the algorithm PGI into the probability density evolution method (PDEM) are compared with those by the Monte Carlo simulation method. The investigations indicate that the proposed method can reduce the number of the representative points, lower the generalized F-discrepancy of the representative point set, and also ensure the accuracy of stochastic structural dynamic analysis.

  19. Algorithm for the identification of malfunctioning sensors in the control systems of segmented mirror telescopes.

    PubMed

    Chanan, Gary; Nelson, Jerry

    2009-11-10

    The active control systems of segmented mirror telescopes are vulnerable to a malfunction of a few (or even one) of their segment edge sensors, the effects of which can propagate through the entire system and seriously compromise the overall telescope image quality. Since there are thousands of such sensors in the extremely large telescopes now under development, it is essential to develop fast and efficient algorithms that can identify bad sensors so that they can be removed from the control loop. Such algorithms are nontrivial; for example, a simple residual-to-the-fit test will often fail to identify a bad sensor. We propose an algorithm that can reliably identify a single bad sensor and we extend it to the more difficult case of multiple bad sensors. Somewhat surprisingly, the identification of a fixed number of bad sensors does not necessarily become more difficult as the telescope becomes larger and the number of sensors in the control system increases. PMID:19904329

  20. The Muon Detector at the HERA-B experiment

    NASA Astrophysics Data System (ADS)

    Eiges, V.; Fominykh, B.; Khasanov, F.; Kvaratscheliia, T.; Laptin, L.; Tchoudakov, V.; Tichomirov, I.; Titov, M.; Zaitsev, Yu.; Buchler, M.; Harr, R. F.; Karchin, P. E.; Nam, S.; Shiu, J. G.; Gilitsky, Yu.; Takach, S. F.

    2001-04-01

    The HERA-B experiment is designed to study beauty particle production and decay using the HERA 920 GeV proton beam interactions with an internal target. The Muon detector provides identification for muons having momenta greater than 5 GeV/c and triggering on the muon pair from J/ ψ decay. Three different chamber types are employed for operation in a high-rate environment. The overall design, performance and current status are discussed.

  1. A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms

    PubMed Central

    2014-01-01

    Background Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. Results We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. Conclusions In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to

  2. Application of Decision Tree Algorithm for classification and identification of natural minerals using SEM-EDS

    NASA Astrophysics Data System (ADS)

    Akkaş, Efe; Akin, Lutfiye; Evren Çubukçu, H.; Artuner, Harun

    2015-07-01

    A mineral is a natural, homogeneous solid with a definite chemical composition and a highly ordered atomic arrangement. Recently, fast and accurate mineral identification/classification became a necessity. Energy Dispersive X-ray Spectrometers integrated with Scanning Electron Microscopes (SEM) are used to obtain rapid and reliable elemental analysis or chemical characterization of a solid. However, mineral identification is challenging since there is wide range of spectral dataset for natural minerals. The more mineralogical data acquired, time required for classification procedures increases. Moreover, applied instrumental conditions on a SEM-EDS differ for various applications, affecting the produced X-ray patterns even for the same mineral. This study aims to test whether C5.0 Decision Tree is a rapid and reliable method algorithm for classification and identification of various natural magmatic minerals. Ten distinct mineral groups (olivine, orthopyroxene, clinopyroxene, apatite, amphibole, plagioclase, K-feldspar, zircon, magnetite, biotite) from different igneous rocks have been analyzed on SEM-EDS. 4601 elemental X-ray intensity data have been collected under various instrumental conditions. 2400 elemental data have been used to train and the remaining 2201 data have been tested to identify the minerals. The vast majority of the test data have been classified accurately. Additionally, high accuracy has been reached on the minerals with similar chemical composition, such as olivine ((Mg,Fe)2[SiO4]) and orthopyroxene ((Mg,Fe)2[SiO6]). Furthermore, two members from amphibole group (magnesiohastingsite, tschermakite) and two from clinopyroxene group (diopside, hedenbergite) have been accurately identified by the Decision Tree Algorithm. These results demonstrate that C5.0 Decision Tree Algorithm is an efficient method for mineral group classification and the identification of mineral members.

  3. Jet production in muon scattering at Fermilab E665

    SciTech Connect

    Salgado, C.W.; E665 Collaboration

    1993-11-01

    Measurements of multi-jet production rates from Muon-Nucleon and Muon-Nuclei scattering at Fermilab-E665 are presented. Jet rates are defined by the JADE clustering algorithm. Rates in Muon-Nucleon deep-inelastic scattering are compared to Monte Carlo model predictions. Preliminary results from jet production on heavy targets, in the shadowing region, show a higher suppression of two-forward jets as compared to one-forward jet production.

  4. Pion contamination in the MICE muon beam

    DOE PAGESBeta

    Adams, D.; Alekou, A.; Apollonio, M.; Asfandiyarov, R.; Barber, G.; Barclay, P.; de Bari, A.; Bayes, R.; Bayliss, V.; Bertoni, R.; et al

    2016-03-01

    Here, the international Muon Ionization Cooling Experiment (MICE) will perform a systematic investigation of ionization cooling with muon beams of momentum between 140 and 240\\,MeV/c at the Rutherford Appleton Laboratory ISIS facility. The measurement of ionization cooling in MICE relies on the selection of a pure sample of muons that traverse the experiment. To make this selection, the MICE Muon Beam is designed to deliver a beam of muons with less thanmore » $$\\sim$$1% contamination. To make the final muon selection, MICE employs a particle-identification (PID) system upstream and downstream of the cooling cell. The PID system includes time-of-flight hodoscopes, threshold-Cherenkov counters and calorimetry. The upper limit for the pion contamination measured in this paper is $$f_\\pi < 1.4\\%$$ at 90% C.L., including systematic uncertainties. Therefore, the MICE Muon Beam is able to meet the stringent pion-contamination requirements of the study of ionization cooling.« less

  5. Muon Bunch Coalescing

    SciTech Connect

    Johnson, Rolland P; Ankenbrandt, Charles; Bhat, Chandra; Popovic, Milorad; Bogacz, Alex; Derbenev, Yaroslav

    2007-06-25

    The idea of coalescing multiple muon bunches at high energy to enhance the luminosity of a muon collider provides many advantages. It circumvents space-charge, beam loading, and wakefield problems of intense low energy bunches while restoring the synergy between muon colliders and neutrino factories based on muon storage rings. A sampling of initial conceptual design work for a coalescing ring is presented here.

  6. The CMS muon detector

    NASA Astrophysics Data System (ADS)

    Giacomelli, P.

    2002-02-01

    The muon detection system of the Compact Muon Solenoid experiment is described. It consists of three different detector technologies: drift tubes in the barrel region, cathode strip chambers in the endcap region and resistive plate chambers in both barrel and endcap regions. The CMS muon detection system ensures excellent muon detection and efficient triggering in the pseudorapidity range 0< η<2.4. The most recent developments and some results from the R&D program will also be discussed.

  7. Improvements to the Percolator algorithm for peptide identification from shotgun proteomics data sets

    PubMed Central

    Spivak, Marina; Weston, Jason; Bottou, Léon; Käll, Lukas; Noble, William Stafford

    2009-01-01

    Shotgun proteomics coupled with database search software allows the identification of a large number of peptides in a single experiment. However, some existing search algorithms, such as SEQUEST, use score functions that are designed primarily to identify the best peptide for a given spectrum. Consequently, when comparing identifications across spectra, the SEQUEST score function Xcorr fails to discriminate accurately between correct and incorrect peptide identifications. Several machine learning methods have been proposed to address the resulting classification task of distinguishing between correct and incorrect peptide-spectrum matches (PSMs). A recent example is Percolator, which uses semi-supervised learning and a decoy database search strategy to learn to distinguish between correct and incorrect PSMs identified by a database search algorithm. The current work describes three improvements to Percolator. (1) Percolator’s heuristic optimization is replaced with a clear objective function, with intuitive reasons behind its choice. (2) Tractable nonlinear models are used instead of linear models, leading to improved accuracy over the original Percolator. (3) A method, Q-ranker, for directly optimizing the number of identified spectra at a specified q value is proposed, which achieves further gains. PMID:19385687

  8. Early identification of potentially salvageable tissue with MRI-based predictive algorithms after experimental ischemic stroke

    PubMed Central

    Bouts, Mark J R J; Tiebosch, Ivo A C W; van der Toorn, Annette; Viergever, Max A; Wu, Ona; Dijkhuizen, Rick M

    2013-01-01

    Individualized stroke treatment decisions can be improved by accurate identification of the extent of salvageable tissue. Magnetic resonance imaging (MRI)-based approaches, including measurement of a ‘perfusion-diffusion mismatch' and calculation of infarction probability, allow assessment of tissue-at-risk; however, the ability to explicitly depict potentially salvageable tissue remains uncertain. In this study, five predictive algorithms (generalized linear model (GLM), generalized additive model, support vector machine, adaptive boosting, and random forest) were tested in their potency to depict acute cerebral ischemic tissue that can recover after reperfusion. Acute T2-, diffusion-, and perfusion-weighted MRI, and follow-up T2 maps were collected from rats subjected to right-sided middle cerebral artery occlusion without subsequent reperfusion, for training of algorithms (Group I), and with spontaneous (Group II) or thrombolysis-induced reperfusion (Group III), to determine infarction probability-based viability thresholds and prediction accuracies. The infarction probability difference between irreversible—i.e., infarcted after reperfusion—and salvageable tissue injury—i.e., noninfarcted after reperfusion—was largest for GLM (20±7%) with highest accuracy of risk-based identification of acutely ischemic tissue that could recover on subsequent reperfusion (Dice's similarity index=0.79±0.14). Our study shows that assessment of the heterogeneity of infarction probability with MRI-based algorithms enables estimation of the extent of potentially salvageable tissue after acute ischemic stroke. PMID:23571283

  9. An affine point-set and line invariant algorithm for photo-identification of gray whales

    NASA Astrophysics Data System (ADS)

    Chandan, Chandan; Kehtarnavaz, Nasser; Hillman, Gilbert; Wursig, Bernd

    2004-05-01

    This paper presents an affine point-set and line invariant algorithm within a statistical framework, and its application to photo-identification of gray whales (Eschrichtius robustus). White patches (blotches) appearing on a gray whale's left and right flukes (the flattened broad paddle-like tail) constitute unique identifying features and have been used here for individual identification. The fluke area is extracted from a fluke image via the live-wire edge detection algorithm, followed by optimal thresholding of the fluke area to obtain the blotches. Affine point-set and line invariants of the blotch points are extracted based on three reference points, namely the left and right tips and the middle notch-like point on the fluke. A set of statistics is derived from the invariant values and used as the feature vector representing a database image. The database images are then ranked depending on the degree of similarity between a query and database feature vectors. The results show that the use of this algorithm leads to a reduction in the amount of manual search that is normally done by marine biologists.

  10. Identification and detection of gaseous effluents from hyperspectral imagery using invariant algorithms

    NASA Astrophysics Data System (ADS)

    O'Donnell, Erin M.; Messinger, David W.; Salvaggio, Carl; Schott, John R.

    2004-08-01

    The ability to detect and identify effluent gases is, and will continue to be, of great importance. This would not only aid in the regulation of pollutants but also in treaty enforcement and monitoring the production of weapons. Considering these applications, finding a way to remotely investigate a gaseous emission is highly desirable. This research utilizes hyperspectral imagery in the infrared region of the electromagnetic spectrum to evaluate an invariant method of detecting and identifying gases within a scene. The image is evaluated on a pixel-by-pixel basis and is studied at the subpixel level. A library of target gas spectra is generated using a simple slab radiance model. This results in a more robust description of gas spectra which are representative of real-world observations. This library is the subspace utilized by the detection and identification algorithms. The subspace will be evaluated for the set of basis vectors that best span the subspace. The Lee algorithm will be used to determine the set of basis vectors, which implements the Maximum Distance Method (MaxD). A Generalized Likelihood Ratio Test (GLRT) determines whether or not the pixel contains the target. The target can be either a single species or a combination of gases. Synthetically generated scenes will be used for this research. This work evaluates whether the Lee invariant algorithm will be effective in the gas detection and identification problem.

  11. Estimating index of refraction for material identification in comparison to existing temperature emissivity separation algorithms

    NASA Astrophysics Data System (ADS)

    Martin, Jacob A.; Gross, Kevin C.

    2016-05-01

    As off-nadir viewing platforms become increasingly prevalent in remote sensing, material identification techniques must be robust to changing viewing geometries. Current identification strategies generally rely on estimating reflectivity or emissivity, both of which vary with viewing angle. Presented here is a technique, leveraging polarimetric and hyperspectral imaging (P-HSI), to estimate index of refraction which is invariant to viewing geometry. Results from a quartz window show that index of refraction can be retrieved to within 0.08 rms error from 875-1250 cm-1 for an amorphous material. Results from a silicon carbide (SiC) wafer, which has much sharper features than quartz glass, show the index of refraction can be retrieved to within 0.07 rms error. The results from each of these datasets show an improvement when compared with a maximum smoothness TES algorithm.

  12. High effective algorithm of the detection and identification of substance using the noisy reflected THz pulse

    NASA Astrophysics Data System (ADS)

    Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.; Tikhomirov, Vasily V.

    2015-08-01

    Principal limitations of the standard THz-TDS method for the detection and identification are demonstrated under real conditions (at long distance of about 3.5 m and at a high relative humidity more than 50%) using neutral substances thick paper bag, paper napkins and chocolate. We show also that the THz-TDS method detects spectral features of dangerous substances even if the THz signals were measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); silicon-based semiconductors were used as the samples. However, the integral correlation criteria, based on SDA method, allows us to detect the absence of dangerous substances in the neutral substances. The discussed algorithm shows high probability of the substance identification and a reliability of realization in practice, especially for security applications and non-destructive testing.

  13. An eigensystem realization algorithm using data correlations (ERA/DC) for modal parameter identification

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Cooper, J. E.; Wright, J. R.

    1987-01-01

    A modification to the Eigensystem Realization Algorithm (ERA) for modal parameter identification is presented in this paper. The ERA minimum order realization approach using singular value decomposition is combined with the philosophy of the Correlation Fit method in state space form such that response data correlations rather than actual response values are used for modal parameter identification. This new method, the ERA using data correlations (ERA/DC), reduces bias errors due to noise corruption significantly without the need for model overspecification. This method is tested using simulated five-degree-of-freedom system responses corrupted by measurement noise. It is found for this case that, when model overspecification is permitted and a minimum order solution obtained via singular value truncation, the results from the two methods are of similar quality.

  14. Muon beamline at ISIS

    NASA Astrophysics Data System (ADS)

    Eaton, G. H.; Clarke-Gayther, M. A.; Scott, C. A.; Cox, S. F. J.; Kilcoyne, S. H.

    1994-07-01

    The original pulsed surface muon facility was established at the Rutherford Appleton Laboratory's ISIS in 1987. The facility was then upgraded in 1993 from a single beam line and spectrometer to a triple beam facility with three spectrometers working independently. The layout of ISIS is shown. A plan of the ISIS experimental hall is shown, indicating the respective locations of the neutron beams, the KARMEN neutrino facility and the muon beam line complex. Other topics shown in the report include the following: (1) Muon production; (2) Transport of muons to the experimental areas; (3) Positron elimination from the ISIS muon beam; (4) Creation of three independent beam lines.

  15. Jet production in muon-proton and muon-nuclei scattering at Fermilab-E665

    SciTech Connect

    Salgado, C.W.; E665 Collaboration

    1993-08-01

    Measurements of multi-jet production rates from Muon-Proton Muon- Nuclei scattering at Fermilab-E665 are presented. Jet rates are defined by the JADE clustering algorithm. Rates in Muon-Proton deep-inelastic scattering are compared to perturbative Quantum Chromodynamics (PQCD) and Monte Carlo model predictions. We observe hadronic (2+1)-jet rates which are a factor of two higher than PQCD predictions at the partonic level. Preliminary results from jet production on heavy targets, in the shadowing region, show a suppression of the jet rates as compared to deuterium. The two- forward jet sample present higher suppression as compared to the one-forward jet sample.

  16. Identification of alternative splice variants in Aspergillus flavus through comparison of multiple tandem MS search algorithms

    PubMed Central

    2011-01-01

    Background Database searching is the most frequently used approach for automated peptide assignment and protein inference of tandem mass spectra. The results, however, depend on the sequences in target databases and on search algorithms. Recently by using an alternative splicing database, we identified more proteins than with the annotated proteins in Aspergillus flavus. In this study, we aimed at finding a greater number of eligible splice variants based on newly available transcript sequences and the latest genome annotation. The improved database was then used to compare four search algorithms: Mascot, OMSSA, X! Tandem, and InsPecT. Results The updated alternative splicing database predicted 15833 putative protein variants, 61% more than the previous results. There was transcript evidence for 50% of the updated genes compared to the previous 35% coverage. Database searches were conducted using the same set of spectral data, search parameters, and protein database but with different algorithms. The false discovery rates of the peptide-spectrum matches were estimated < 2%. The numbers of the total identified proteins varied from 765 to 867 between algorithms. Whereas 42% (1651/3891) of peptide assignments were unanimous, the comparison showed that 51% (568/1114) of the RefSeq proteins and 15% (11/72) of the putative splice variants were inferred by all algorithms. 12 plausible isoforms were discovered by focusing on the consensus peptides which were detected by at least three different algorithms. The analysis found different conserved domains in two putative isoforms of UDP-galactose 4-epimerase. Conclusions We were able to detect dozens of new peptides using the improved alternative splicing database with the recently updated annotation of the A. flavus genome. Unlike the identifications of the peptides and the RefSeq proteins, large variations existed between the putative splice variants identified by different algorithms. 12 candidates of putative isoforms

  17. MIDAS: a database-searching algorithm for metabolite identification in metabolomics.

    PubMed

    Wang, Yingfeng; Kora, Guruprasad; Bowen, Benjamin P; Pan, Chongle

    2014-10-01

    A database searching approach can be used for metabolite identification in metabolomics by matching measured tandem mass spectra (MS/MS) against the predicted fragments of metabolites in a database. Here, we present the open-source MIDAS algorithm (Metabolite Identification via Database Searching). To evaluate a metabolite-spectrum match (MSM), MIDAS first enumerates possible fragments from a metabolite by systematic bond dissociation, then calculates the plausibility of the fragments based on their fragmentation pathways, and finally scores the MSM to assess how well the experimental MS/MS spectrum from collision-induced dissociation (CID) is explained by the metabolite's predicted CID MS/MS spectrum. MIDAS was designed to search high-resolution tandem mass spectra acquired on time-of-flight or Orbitrap mass spectrometer against a metabolite database in an automated and high-throughput manner. The accuracy of metabolite identification by MIDAS was benchmarked using four sets of standard tandem mass spectra from MassBank. On average, for 77% of original spectra and 84% of composite spectra, MIDAS correctly ranked the true compounds as the first MSMs out of all MetaCyc metabolites as decoys. MIDAS correctly identified 46% more original spectra and 59% more composite spectra at the first MSMs than an existing database-searching algorithm, MetFrag. MIDAS was showcased by searching a published real-world measurement of a metabolome from Synechococcus sp. PCC 7002 against the MetaCyc metabolite database. MIDAS identified many metabolites missed in the previous study. MIDAS identifications should be considered only as candidate metabolites, which need to be confirmed using standard compounds. To facilitate manual validation, MIDAS provides annotated spectra for MSMs and labels observed mass spectral peaks with predicted fragments. The database searching and manual validation can be performed online at http://midas.omicsbio.org. PMID:25157598

  18. Algorithmic identification of limnological features in vertical profiles from the Great Lakes

    NASA Astrophysics Data System (ADS)

    Wietsma, T.; Collingsworth, P.; Minsker, B. S.

    2013-12-01

    High volume collection of environmental data in digital format presents a range of challenges for the researcher, from quality control and data management to efficient interpretation of the signal and the development of requisite information technology skills. These challenges have been termed the "data deluge". To aid in efficient data interpretation, we describe several algorithmic approaches for feature identification in signal streams, including gradient estimation, spectral analysis, and the hidden Markov model. These approaches are calibrated and evaluated over vertical temperature profiles from the Great Lakes obtained through the U.S. Environmental Protection Agency. To demonstrate the value of this data science approach, we describe how the algorithms can be integrated with the historical sampling record to yield an expert system that assists field technicians with adaptive sampling.

  19. Identification of IPMC nonlinear model via single and multi-objective optimization algorithms.

    PubMed

    Caponetto, Riccardo; Graziani, Salvatore; Pappalardo, Fulvio; Sapuppo, Francesca

    2014-03-01

    Ionic Polymer-Metal Composites (IPMCs) are electro-active polymers transforming mechanical forces into electric signals and vice versa. This paper proposes an improved electro-mechanical grey-box model for IPMC membrane working as actuator. In particular the IPMC nonlinearity has been characterized through experimentation and included within the electric model. Moreover identification of the model parameters has been performed via optimization algorithms using both single- and multi-objective formulation. Minimization was attained via the Nelder-Mead simplex and the Genetic Algorithms considering as cost functions the error between the experimental and modeled absorbed current and the error between experimental and modeled displacement. The obtained results for the different formulations have been then compared. PMID:24342273

  20. A Clinical Algorithm for Early Identification and Intervention of Cervical Muscular Torticollis.

    PubMed

    Nichter, Stephanie

    2016-06-01

    Congenital muscular torticollis (CMT) is a common newborn pediatric muscular deformity of the neck. The purpose of this article is to suggest a clinical algorithm for pediatric clinicians to promote prompt identification and intervention for infants with CMT. Early intervention for a child with CMT at less than 1 month of age yields a 98% success rate by 2.5 months of age, with the infant achieving near normal range of motion. Intervention initiated at 6 months of age or later can require 9 to 10 months of therapy with less success in achieving full range of motion of the cervical musculature. The clinical algorithm proposed here incorporates the American Physical Therapy Association guideline for CMT to optimize outcomes for the child and reduce health care expenditures. Current evidence and guidelines demonstrate that primary care providers are the primary diagnostic clinicians, while physical therapists are the preferred provider for the treatment of CMT. PMID:26307184

  1. Muon Catalyzed Fusion

    NASA Technical Reports Server (NTRS)

    Armour, Edward A.G.

    2007-01-01

    Muon catalyzed fusion is a process in which a negatively charged muon combines with two nuclei of isotopes of hydrogen, e.g, a proton and a deuteron or a deuteron and a triton, to form a muonic molecular ion in which the binding is so tight that nuclear fusion occurs. The muon is normally released after fusion has taken place and so can catalyze further fusions. As the muon has a mean lifetime of 2.2 microseconds, this is the maximum period over which a muon can participate in this process. This article gives an outline of the history of muon catalyzed fusion from 1947, when it was first realised that such a process might occur, to the present day. It includes a description of the contribution that Drachrnan has made to the theory of muon catalyzed fusion and the influence this has had on the author's research.

  2. Probabilistic streamflow forecasting for hydroelectricity production: A comparison of two non-parametric system identification algorithms

    NASA Astrophysics Data System (ADS)

    Pande, Saket; Sharma, Ashish

    2014-05-01

    This study is motivated by the need to robustly specify, identify, and forecast runoff generation processes for hydroelectricity production. It atleast requires the identification of significant predictors of runoff generation and the influence of each such significant predictor on runoff response. To this end, we compare two non-parametric algorithms of predictor subset selection. One is based on information theory that assesses predictor significance (and hence selection) based on Partial Information (PI) rationale of Sharma and Mehrotra (2014). The other algorithm is based on a frequentist approach that uses bounds on probability of error concept of Pande (2005), assesses all possible predictor subsets on-the-go and converges to a predictor subset in an computationally efficient manner. Both the algorithms approximate the underlying system by locally constant functions and select predictor subsets corresponding to these functions. The performance of the two algorithms is compared on a set of synthetic case studies as well as a real world case study of inflow forecasting. References: Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 49, doi:10.1002/2013WR013845. Pande, S. (2005), Generalized local learning in water resource management, PhD dissertation, Utah State University, UT-USA, 148p.

  3. [Study on an Algorithm for Near Infrared Singular Sample Identification Based on Strong Influence Degree].

    PubMed

    Wu, Zhao-na; Ding, Xiang-qian; Gong, Hui-li; Dong, Mel; Wang, Mei-xun

    2015-07-01

    Correcting sample selection and elimination of singular sample is very important for the quantitative and qualitative modeling of near infrared spectroscopy. However, methods for identification of singular sample available are generally based on data center estimates which require an experience decision threshold, this largely limit its recognition accuracy and practicability. Aiming at the low accuracy of the existing methods of singular sample recognition problem, this paper improves the existing metric-Leverage value and presents a new algorithm for near infrared singular sample identification based on strong influence degree. This metric reduces the dependence on the data center to a certain extent, so that the normal samples become more aggregation, and the distance between the singular samples and the normal samples is opened; at the same time, in order to avoid artificial setting threshold unreasonably according to experience, this paper introduces the concept of the jump degree in the field of statistics, and proposes an automatic threshold setting method to distinguish singular samples. In order to verify the validity of our algorithm, abnormal samples of 200 representative samples were eliminated in the calibration set with using Mahalanobis distance, Leverage-Spectral residual method and the algorithm presented in this paper respectively; then through partial least squares (PLS), the rest of the calibration samples were made quantitative modelings (took Nicotine as index), and the results of quantitative modelings were made a comparative analysis; besides, 60 representative testing samples were made a prediction through the modelings; at last, all the algorithms above were made a comparison with took Root Mean Square Error of Cross Validation (RMSECV), Correlation Coefficient (r) and Root Mean Square Error of Prediction (RMSEP) as evaluation Index. The experimental results demonstrate that the algorithm for near infrared singular sample identification

  4. Evaluation of sensor placement algorithms for on-orbit identification of space platforms

    NASA Technical Reports Server (NTRS)

    Glassburn, Robin S.; Smith, Suzanne Weaver

    1994-01-01

    Anticipating the construction of the international space station, on-orbit modal identification of space platforms through optimally placed accelerometers is an area of recent activity. Unwanted vibrations in the platform could affect the results of experiments which are planned. Therefore, it is important that sensors (accelerometers) be strategically placed to identify the amount and extent of these unwanted vibrations, and to validate the mathematical models used to predict the loads and dynamic response. Due to cost, installation, and data management issues, only a limited number of sensors will be available for placement. This work evaluates and compares four representative sensor placement algorithms for modal identification. Most of the sensor placement work to date has employed only numerical simulations for comparison. This work uses experimental data from a fully-instrumented truss structure which was one of a series of structures designed for research in dynamic scale model ground testing of large space structures at NASA Langley Research Center. Results from this comparison show that for this cantilevered structure, the algorithm based on Guyan reduction is rated slightly better than that based on Effective Independence.

  5. Correcting encoder interpolation error on the Green Bank Telescope using an iterative model based identification algorithm

    NASA Astrophysics Data System (ADS)

    Franke, Timothy; Weadon, Tim; Ford, John; Garcia-Sanz, Mario

    2015-10-01

    Various forms of measurement errors limit telescope tracking performance in practice. A new method for identifying the correcting coefficients for encoder interpolation error is developed. The algorithm corrects the encoder measurement by identifying a harmonic model of the system and using that model to compute the necessary correction parameters. The approach improves upon others by explicitly modeling the unknown dynamics of the structure and controller and by not requiring a separate system identification to be performed. Experience gained from pin-pointing the source of encoder error on the Green Bank Radio Telescope (GBT) is presented. Several tell-tale indicators of encoder error are discussed. Experimental data from the telescope, tested with two different encoders, are presented. Demonstration of the identification methodology on the GBT as well as details of its implementation are discussed. A root mean square tracking error reduction from 0.68 arc seconds to 0.21 arc sec was achieved by changing encoders and was further reduced to 0.10 arc sec with the calibration algorithm. In particular, the ubiquity of this error source is shown and how, by careful correction, it is possible to go beyond the advertised accuracy of an encoder.

  6. Semi-automatic stereotactic coordinate identification algorithm for routine localization of Deep Brain Stimulation electrodes.

    PubMed

    Hebb, Adam O; Miller, Kai J

    2010-03-15

    Deep Brain Stimulation (DBS) is a routine therapy for movement disorders, and has several emerging indications. We present a novel protocol to define the stereotactic coordinates of metallic DBS implants that may be routinely employed for validating therapeutic anatomical targets. Patients were referred for troubleshooting or new DBS implantation. A volumetric MRI of the brain obtained prior to or during this protocol was formatted to the Anterior Commissure-Posterior Commissure (AC-PC) coordinate system. Patients underwent a CT scan of the brain in an extended Hounsfield unit (EHU) mode. A semi-automatic detection algorithm based on a Normalized Mutual Information (NMI) co-registration method was implemented to measure the AC-PC coordinates of each DBS contact. This algorithm was validated using manual DBS contact identification. Fifty MRI-CT image pairs were available in 39 patients with a total of 336 DBS electrodes. The median and mean Euclidean distance errors for automatic identification of electrode locations were 0.20mm and 0.22 mm, respectively. This method is an accurate method of localization of active DBS contacts within the sub-cortical region. As the investigational indications of DBS expand, this method may be used for verification of final implant coordinates, critical for understanding clinical benefit and comparing efficacy between subjects. PMID:20036691

  7. Identification of moisture content in tobacco plant leaves using outlier sample eliminating algorithms and hyperspectral data.

    PubMed

    Sun, Jun; Zhou, Xin; Wu, Xiaohong; Zhang, Xiaodong; Li, Qinglin

    2016-02-26

    Fast identification of moisture content in tobacco plant leaves plays a key role in the tobacco cultivation industry and benefits the management of tobacco plant in the farm. In order to identify moisture content of tobacco plant leaves in a fast and nondestructive way, a method involving Mahalanobis distance coupled with Monte Carlo cross validation(MD-MCCV) was proposed to eliminate outlier sample in this study. The hyperspectral data of 200 tobacco plant leaf samples of 20 moisture gradients were obtained using FieldSpc(®) 3 spectrometer. Savitzky-Golay smoothing(SG), roughness penalty smoothing(RPS), kernel smoothing(KS) and median smoothing(MS) were used to preprocess the raw spectra. In addition, Mahalanobis distance(MD), Monte Carlo cross validation(MCCV) and Mahalanobis distance coupled to Monte Carlo cross validation(MD-MCCV) were applied to select the outlier sample of the raw spectrum and four smoothing preprocessing spectra. Successive projections algorithm (SPA) was used to extract the most influential wavelengths. Multiple Linear Regression (MLR) was applied to build the prediction models based on preprocessed spectra feature in characteristic wavelengths. The results showed that the preferably four prediction model were MD-MCCV-SG (Rp(2) = 0.8401 and RMSEP = 0.1355), MD-MCCV-RPS (Rp(2) = 0.8030 and RMSEP = 0.1274), MD-MCCV-KS (Rp(2) = 0.8117 and RMSEP = 0.1433), MD-MCCV-MS (Rp(2) = 0.9132 and RMSEP = 0.1162). MD-MCCV algorithm performed best among MD algorithm, MCCV algorithm and the method without sample pretreatment algorithm in the eliminating outlier sample from 20 different moisture gradients of tobacco plant leaves and MD-MCCV can be used to eliminate outlier sample in the spectral preprocessing. PMID:26809097

  8. Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

    NASA Technical Reports Server (NTRS)

    Molusis, J. A.

    1982-01-01

    An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

  9. Rigid body mode identification of the PAH-2 helicopter using the eigensystem realization algorithm

    NASA Technical Reports Server (NTRS)

    Schenk, Axel; Pappa, Richard S.

    1992-01-01

    The rigid body modes of the PAH-2 'Tiger' helicopter were identified using the Eigensystem Realization Algorithm (ERA). This work complements ground vibration tests performed using DLR's traditional phase resonance technique and the ISSPA (Identification of Structural System Parameters) method. Rigid body modal parameters are important for ground resonance prediction. Time-domain data for ERA were obtained by inverse Fourier transformation of frequency response functions measured with stepped-sine excitation. Mode purity (based on the Phase Resonance Criterion) was generally equal to or greater than corresponding results obtained in the ground vibration tests. All identified natural frequencies and mode shapes correlate well with corresponding ground vibration test results. The modal identification approach discussed in this report has become increasingly attractive in recent years due to the steadily declining cost and increased performance of scientific computers. As illustrated in this application, modern time-domain methods can be successfully applied to data acquired using DLR's existing test equipment. Some suggestions are made for future applications of time domain modal identification in this manner.

  10. A novel algorithm for validating peptide identification from a shotgun proteomics search engine.

    PubMed

    Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J

    2013-03-01

    Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines. PMID:23402659

  11. Multiple muons in MACRO

    NASA Technical Reports Server (NTRS)

    Heinz, R.

    1985-01-01

    An analysis of the multiple muon events in the Monopole Astrophysics and Cosmic Ray Observatory detector was conducted to determine the cosmic ray composition. Particular emphasis is placed on the interesting primary cosmic ray energy region above 2000 TeV/nucleus. An extensive study of muon production in cosmic ray showers has been done. Results were used to parameterize the characteristics of muon penetration into the Earth to the location of a detector.

  12. SNSMIL, a real-time single molecule identification and localization algorithm for super-resolution fluorescence microscopy

    PubMed Central

    Tang, Yunqing; Dai, Luru; Zhang, Xiaoming; Li, Junbai; Hendriks, Johnny; Fan, Xiaoming; Gruteser, Nadine; Meisenberg, Annika; Baumann, Arnd; Katranidis, Alexandros; Gensch, Thomas

    2015-01-01

    Single molecule localization based super-resolution fluorescence microscopy offers significantly higher spatial resolution than predicted by Abbe’s resolution limit for far field optical microscopy. Such super-resolution images are reconstructed from wide-field or total internal reflection single molecule fluorescence recordings. Discrimination between emission of single fluorescent molecules and background noise fluctuations remains a great challenge in current data analysis. Here we present a real-time, and robust single molecule identification and localization algorithm, SNSMIL (Shot Noise based Single Molecule Identification and Localization). This algorithm is based on the intrinsic nature of noise, i.e., its Poisson or shot noise characteristics and a new identification criterion, QSNSMIL, is defined. SNSMIL improves the identification accuracy of single fluorescent molecules in experimental or simulated datasets with high and inhomogeneous background. The implementation of SNSMIL relies on a graphics processing unit (GPU), making real-time analysis feasible as shown for real experimental and simulated datasets. PMID:26098742

  13. A radiative transfer algorithm for identification and retrieval of rain from Megha-Tropiques MADRAS

    NASA Astrophysics Data System (ADS)

    Varma, Atul K.; Piyush, D. N.; Gohil, B. S.; Basu, Sujit; Pal, P. K.

    2015-03-01

    The present study explains a radiative transfer based method for rain retrieval over the global land and oceans. The study explores the possibility of applying an existing algorithm for SSM/I to Megha-Tropiques (MT) MADRAS radiometer which is carried out by developing a radiative transfer based transfer function between scattering index (SI) from SSM/I and MADRAS measurements. Prior to quantitative estimation of rain from MADRAS, rain affected observations are identified. The scheme for rain identification over oceans presented herein from MADRAS, is used for rain flagging in the operational algorithms for the retrieval of other geophysical parameters, like cloud liquid water, total precipitable water and wind speed. SSM/I equivalent SI from MADRAS measurements is used for rain rate retrieval and testing is done with the actual measurements of brightness temperatures from SSM/I. The rain rates retrieved from MADRAS are compared with the other complimentary satellites. A comparison of daily average rain from MADRAS with that from the TRMM 3B42 is found to have a correlation of 0.67 and rms difference of 0.40 mm h-1 and nearly 0 mm h-1 bias. Similar monthly scale comparisons over the oceans provide correlation of 0.83 and 0.79 with bias of -0.03 and 0 mm h-1 with respect to TRMM-3B42 and SSM/I, respectively. Usability of the rain retrieval algorithm for intense rain associated with a deep depression is also demonstrated by comparing the spatial distribution of intense rain with other satellite measurements. Finally, the probability distribution of daily rain from MADRAS with TRMM-3B42 is presented. The approach presented herein can be generalized over other rain retrieval schemes and to any other pair of satellite missions even when they were operational during different periods of time. The study is particularly useful for Global Precipitation Mission (GPM) constellations for using a common precipitation retrieval algorithm.

  14. Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping

    NASA Astrophysics Data System (ADS)

    Pioldi, Fabio; Ferrari, Rosalba; Rizzi, Egidio

    2016-02-01

    The present paper deals with the seismic modal dynamic identification of frame structures by a refined Frequency Domain Decomposition (rFDD) algorithm, autonomously formulated and implemented within MATLAB. First, the output-only identification technique is outlined analytically and then employed to characterize all modal properties. Synthetic response signals generated prior to the dynamic identification are adopted as input channels, in view of assessing a necessary condition for the procedure's efficiency. Initially, the algorithm is verified on canonical input from random excitation. Then, modal identification has been attempted successfully at given seismic input, taken as base excitation, including both strong motion data and single and multiple input ground motions. Rather than different attempts investigating the role of seismic response signals in the Time Domain, this paper considers the identification analysis in the Frequency Domain. Results turn-out very much consistent with the target values, with quite limited errors in the modal estimates, including for the damping ratios, ranging from values in the order of 1% to 10%. Either seismic excitation and high values of damping, resulting critical also in case of well-spaced modes, shall not fulfill traditional FFD assumptions: this shows the consistency of the developed algorithm. Through original strategies and arrangements, the paper shows that a comprehensive rFDD modal dynamic identification of frames at seismic input is feasible, also at concomitant high damping.

  15. Solving inverse problems of groundwater-pollution-source identification using a differential evolution algorithm

    NASA Astrophysics Data System (ADS)

    Gurarslan, Gurhan; Karahan, Halil

    2015-09-01

    In this study, an accurate model was developed for solving problems of groundwater-pollution-source identification. In the developed model, the numerical simulations of flow and pollutant transport in groundwater were carried out using MODFLOW and MT3DMS software. The optimization processes were carried out using a differential evolution algorithm. The performance of the developed model was tested on two hypothetical aquifer models using real and noisy observation data. In the first model, the release histories of the pollution sources were determined assuming that the numbers, locations and active stress periods of the sources are known. In the second model, the release histories of the pollution sources were determined assuming that there is no information on the sources. The results obtained by the developed model were found to be better than those reported in literature.

  16. A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.

    PubMed

    Aghaeepour, Nima; Chattopadhyay, Pratip; Chikina, Maria; Dhaene, Tom; Van Gassen, Sofie; Kursa, Miron; Lambrecht, Bart N; Malek, Mehrnoush; McLachlan, G J; Qian, Yu; Qiu, Peng; Saeys, Yvan; Stanton, Rick; Tong, Dong; Vens, Celine; Walkowiak, Sławomir; Wang, Kui; Finak, Greg; Gottardo, Raphael; Mosmann, Tim; Nolan, Garry P; Scheuermann, Richard H; Brinkman, Ryan R

    2016-01-01

    The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of computational methods for identifying cell populations in multidimensional flow cytometry data. Here we report the results of FlowCAP-IV where algorithms from seven different research groups predicted the time to progression to AIDS among a cohort of 384 HIV+ subjects, using antigen-stimulated peripheral blood mononuclear cell (PBMC) samples analyzed with a 14-color staining panel. Two approaches (FlowReMi.1 and flowDensity-flowType-RchyOptimyx) provided statistically significant predictive value in the blinded test set. Manual validation of submitted results indicated that unbiased analysis of single cell phenotypes could reveal unexpected cell types that correlated with outcomes of interest in high dimensional flow cytometry datasets. PMID:26447924

  17. Variance and bias confidence criteria for ERA modal parameter identification. [Eigensystem Realization Algorithm

    NASA Technical Reports Server (NTRS)

    Longman, Richard W.; Bergmann, Martin; Juang, Jer-Nan

    1988-01-01

    For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.

  18. Universal algorithm for identification of fractional Brownian motion. A case of telomere subdiffusion.

    PubMed

    Burnecki, Krzysztof; Kepten, Eldad; Janczura, Joanna; Bronshtein, Irena; Garini, Yuval; Weron, Aleksander

    2012-11-01

    We present a systematic statistical analysis of the recently measured individual trajectories of fluorescently labeled telomeres in the nucleus of living human cells. The experiments were performed in the U2OS cancer cell line. We propose an algorithm for identification of the telomere motion. By expanding the previously published data set, we are able to explore the dynamics in six time orders, a task not possible earlier. As a result, we establish a rigorous mathematical characterization of the stochastic process and identify the basic mathematical mechanisms behind the telomere motion. We find that the increments of the motion are stationary, Gaussian, ergodic, and even more chaotic--mixing. Moreover, the obtained memory parameter estimates, as well as the ensemble average mean square displacement reveal subdiffusive behavior at all time spans. All these findings statistically prove a fractional Brownian motion for the telomere trajectories, which is confirmed by a generalized p-variation test. Taking into account the biophysical nature of telomeres as monomers in the chromatin chain, we suggest polymer dynamics as a sufficient framework for their motion with no influence of other models. In addition, these results shed light on other studies of telomere motion and the alternative telomere lengthening mechanism. We hope that identification of these mechanisms will allow the development of a proper physical and biological model for telomere subdynamics. This array of tests can be easily implemented to other data sets to enable quick and accurate analysis of their statistical characteristics. PMID:23199912

  19. A constraint-based search algorithm for parameter identification of environmental models

    NASA Astrophysics Data System (ADS)

    Gharari, S.; Shafiei, M.; Hrachowitz, M.; Kumar, R.; Fenicia, F.; Gupta, H. V.; Savenije, H. H. G.

    2014-12-01

    Many environmental systems models, such as conceptual rainfall-runoff models, rely on model calibration for parameter identification. For this, an observed output time series (such as runoff) is needed, but frequently not available (e.g., when making predictions in ungauged basins). In this study, we provide an alternative approach for parameter identification using constraints based on two types of restrictions derived from prior (or expert) knowledge. The first, called parameter constraints, restricts the solution space based on realistic relationships that must hold between the different model parameters while the second, called process constraints requires that additional realism relationships between the fluxes and state variables must be satisfied. Specifically, we propose a search algorithm for finding parameter sets that simultaneously satisfy such constraints, based on stepwise sampling of the parameter space. Such parameter sets have the desirable property of being consistent with the modeler's intuition of how the catchment functions, and can (if necessary) serve as prior information for further investigations by reducing the prior uncertainties associated with both calibration and prediction.

  20. Muon and neutrino fluxes

    NASA Technical Reports Server (NTRS)

    Edwards, P. G.; Protheroe, R. J.

    1985-01-01

    The result of a new calculation of the atmospheric muon and neutrino fluxes and the energy spectrum of muon-neutrinos produced in individual extensive air showers (EAS) initiated by proton and gamma-ray primaries is reported. Also explained is the possibility of detecting atmospheric nu sub mu's due to gamma-rays from these sources.

  1. Telecommunication using muon beams

    DOEpatents

    Arnold, Richard C.

    1976-01-01

    Telecommunication is effected by generating a beam of mu mesons or muons, varying a property of the beam at a modulating rate to generate a modulated beam of muons, and detecting the information in the modulated beam at a remote location.

  2. [Research on the Source Identification of Mine Water Inrush Based on LIF Technology and SIMCA Algorithm].

    PubMed

    Yan, Peng-cheng; Zhou, Meng-ran; Liu, Qi-meng; Zhang, Kai-yuan; He, Chen-yang

    2016-01-01

    Rapid source identification of mine water inrush is of great significance for early warning and prevention in mine water hazard. According to the problem that traditional chemical methods to identify source takes a long time, put forward a method for rapid source identification of mine water inrush with laser induced fluorescence (LIF) technology and soft independent modeling of class analogy (SIMCA) algorithm. Laser induced fluorescence technology has the characteristics of fast analysis, high sensitivity and so on. With the laser assisted, fluorescence spectrums can be collected real-time by the fluorescence spectrometer. According to the fluorescence spectrums, the type of water samples can be identified. If the database is completed, it takes a few seconds for coal mine water source identification, so it is of great significance for early warning and post-disaster relief in coal mine water disaster. The experiment uses 405 nm laser emission laser into the 5 kinds of water inrush samples and get 100 groups of fluorescence spectrum, and then put all fluorescence spectrums into preprocessing. Use 15 group spectrums of each water inrush samples, a total of 75 group spectrums, as the prediction set, the rest of 25 groups spectrums as the test set. Using principal component analysis (PCA) to modeling the 5 kinds of water samples respectively, and then classify the water samples with SIMCA on the basis of the PCA model. It was found that the fluorescence spectrum are obvious different of different water inrush samples. The fluorescence spectrums after preprocessing of Gaussian-Filter, under the condition of the principal component number is 2 and the significant level α = 5%, the accuracy of prediction set and testing set are all 100% with the SIMCA to classify the water inrush samples. PMID:27228775

  3. Lagrangian coherent structure identification using a Voronoi tessellation-based networking algorithm

    NASA Astrophysics Data System (ADS)

    Rosi, Giuseppe A.; Walker, Andrew M.; Rival, David E.

    2015-10-01

    The quantification of Lagrangian coherent structures (LCS) has been investigated using an algorithm based on the tesselation of unstructured data points. The applicability of the algorithm in resolving an LCS was tested using a synthetically generated unsteady double-gyre flow and experimentally in a nominally two-dimensional free shear flow. The effects of two parameters on LCS identification were studied: the threshold track length used to quantify the LCS and resulting effective seeding density upon applying the threshold. At lower threshold track lengths, increases in the threshold track length resulted in finite-time Lyapunov exponent (FTLE) field convergence towards the expected LCS ridge of the double-gyre flow field at several effective seeding densities. However, at higher track lengths, further increases to the threshold track length failed to improve convergence at low effective seeding densities. The FTLE of the experimental data set was well-resolved using moderate threshold track lengths that achieved field convergence but maintained a sufficiently high seeding density. In contrast, the use of lower or higher track lengths produced an FTLE field characterized by an incoherent LCS ridge. From the analytical and experimental results, recommendations are made for future experiments for identifying LCS directly from unstructured data.

  4. Development of a Near-Real Time Hail Damage Swath Identification Algorithm for Vegetation

    NASA Technical Reports Server (NTRS)

    Bell, Jordan R.; Molthan, Andrew L.; Schultz, Lori A.; McGrath, Kevin M.; Burks, Jason E.

    2015-01-01

    The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as

  5. Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

    PubMed

    Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

    2013-01-01

    Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ . PMID:23163785

  6. Data Driven Identification and Selection Algorithms for At-Risk Students Likely to Benefit from High School Academic Support Services

    ERIC Educational Resources Information Center

    Lacefield, Warren E.; Applegate, E. Brooks; Zeller, Pamela J.; Van Kannel-Ray, Nancy; Carpenter, Shelly

    2011-01-01

    This study describes a well-defined data-driven diagnostic identification and selection procedure for choosing students at-risk of academic failure for appropriate academic support services. This algorithmic procedure has been validated both by historical quantitative studies of student precedents and outcomes as well as by current qualitative…

  7. Design and performance simulation of a segmented-absorber based muon detection system for high energy heavy ion collision experiments

    NASA Astrophysics Data System (ADS)

    Ahmad, S.; Bhaduri, P. P.; Jahan, H.; Senger, A.; Adak, R.; Samanta, S.; Prakash, A.; Dey, K.; Lebedev, A.; Kryshen, E.; Chattopadhyay, S.; Senger, P.; Bhattacharjee, B.; Ghosh, S. K.; Raha, S.; Irfan, M.; Ahmad, N.; Farooq, M.; Singh, B.

    2015-03-01

    A muon detection system (MUCH) based on a novel concept using a segmented and instrumented absorber has been designed for high-energy heavy-ion collision experiments. The system consists of 6 hadron absorber blocks and 6 tracking detector triplets. Behind each absorber block a detector triplet is located which measures the tracks of charged particles traversing the absorber. The performance of such a system has been simulated for the CBM experiment at FAIR (Germany) that is scheduled to start taking data in heavy ion collisions in the beam energy range of 6-45 A GeV from 2019. The muon detection system is mounted downstream to a Silicon Tracking System (STS) that is located in a large aperture dipole magnet which provides momentum information of the charged particle tracks. The reconstructed tracks from the STS are to be matched to the hits measured by the muon detector triplets behind the absorber segments. This method allows the identification of muon tracks over a broad range of momenta including tracks of soft muons which do not pass through all the absorber layers. Pairs of oppositely charged muons identified by MUCH could therefore be combined to measure the invariant masses in a wide range starting from low mass vector mesons (LMVM) up to charmonia. The properties of the absorber (material, thickness, position) and of the tracking chambers (granularity, geometry) have been varied in simulations of heavy-ion collision events generated with the UrQMD generator and propagated through the setup using the GEANT3, the particle transport code. The tracks are reconstructed by a Cellular Automaton algorithm followed by a Kalman Filter. The simulations demonstrate that low mass vector mesons and charmonia can be clearly identified in central Au+Au collisions at beam energies provided by the international Facility for Antiproton and Ion Research (FAIR).

  8. Noise reduction in muon tomography for detecting high density objects

    NASA Astrophysics Data System (ADS)

    Benettoni, M.; Bettella, G.; Bonomi, G.; Calvagno, G.; Calvini, P.; Checchia, P.; Cortelazzo, G.; Cossutta, L.; Donzella, A.; Furlan, M.; Gonella, F.; Pegoraro, M.; Rigoni Garola, A.; Ronchese, P.; Squarcia, S.; Subieta, M.; Vanini, S.; Viesti, G.; Zanuttigh, P.; Zenoni, A.; Zumerle, G.

    2013-12-01

    The muon tomography technique, based on multiple Coulomb scattering of cosmic ray muons, has been proposed as a tool to detect the presence of high density objects inside closed volumes. In this paper a new and innovative method is presented to handle the density fluctuations (noise) of reconstructed images, a well known problem of this technique. The effectiveness of our method is evaluated using experimental data obtained with a muon tomography prototype located at the Legnaro National Laboratories (LNL) of the Istituto Nazionale di Fisica Nucleare (INFN). The results reported in this paper, obtained with real cosmic ray data, show that with appropriate image filtering and muon momentum classification, the muon tomography technique can detect high density materials, such as lead, albeit surrounded by light or medium density material, in short times. A comparison with algorithms published in literature is also presented.

  9. Underwater measurements of muon intensity

    NASA Technical Reports Server (NTRS)

    Fedorov, V. M.; Pustovetov, V. P.; Trubkin, Y. A.; Kirilenkov, A. V.

    1985-01-01

    Experimental measurements of cosmic ray muon intensity deep underwater aimed at determining a muon absorption curve are of considerable interest, as they allow to reproduce independently the muon energy spectrum at sea level. The comparison of the muon absorption curve in sea water with that in rock makes it possible to determine muon energy losses caused by nuclear interactions. The data available on muon absorption in water and that in rock are not equivalent. Underground measurements are numerous and have been carried out down to the depth of approx. 15km w.e., whereas underwater muon intensity have been measured twice and only down to approx. 3km deep.

  10. Muon Collider Progress: Accelerators

    SciTech Connect

    Zisman, Michael S.

    2011-09-10

    A muon collider would be a powerful tool for exploring the energy-frontier with leptons, and would complement the studies now under way at the LHC. Such a device would offer several important benefits. Muons, like electrons, are point particles so the full center-of-mass energy is available for particle production. Moreover, on account of their higher mass, muons give rise to very little synchrotron radiation and produce very little beamstrahlung. The first feature permits the use of a circular collider that can make efficient use of the expensive rf system and whose footprint is compatible with an existing laboratory site. The second feature leads to a relatively narrow energy spread at the collision point. Designing an accelerator complex for a muon collider is a challenging task. Firstly, the muons are produced as a tertiary beam, so a high-power proton beam and a target that can withstand it are needed to provide the required luminosity of ~1 × 10{sup 34} cm{sup –2}s{sup –1}. Secondly, the beam is initially produced with a large 6D phase space, which necessitates a scheme for reducing the muon beam emittance (“cooling”). Finally, the muon has a short lifetime so all beam manipulations must be done very rapidly. The Muon Accelerator Program, led by Fermilab and including a number of U.S. national laboratories and universities, has undertaken design and R&D activities aimed toward the eventual construction of a muon collider. Design features of such a facility and the supporting R&D program are described.

  11. The Muon Collider

    SciTech Connect

    Zisman, Michael S.

    2011-01-05

    We describe the scientific motivation for a new type of accelerator, the muon collider. This accelerator would permit an energy-frontier scientific program and yet would fit on the site of an existing laboratory. Such a device is quite challenging, and requires a substantial R&D program. After describing the ingredients of the facility, the ongoing R&D activities of the Muon Accelerator Program are discussed. A possible U.S. scenario that could lead to a muon collider at Fermilab is briefly mentioned.

  12. Muons and neutrinos

    NASA Technical Reports Server (NTRS)

    Stanev, T.

    1986-01-01

    The first generation of large and precise detectors, some initially dedicated to search for nucleon decay has accumulated significant statistics on neutrinos and high-energy muons. A second generation of even better and bigger detectors are already in operation or in advanced construction stage. The present set of experimental data on muon groups and neutrinos is qualitatively better than several years ago and the expectations for the following years are high. Composition studies with underground muon groups, neutrino detection, and expected extraterrestrial neutrino fluxes are discussed.

  13. Neutrino physics at muon colliders

    SciTech Connect

    King, B.J.

    1998-03-01

    An overview is given of the neutrino physics potential of future muon storage rings that use muon collider technology to produce, accelerate and store large currents of muons. After a general characterization of the neutrino beam and its interactions, some crude quantitative estimates are given for the physics performance of a muon ring neutrino experiment (MURINE) consisting of a high rate, high performance neutrino detector at a 250 GeV muon collider storage ring.

  14. The development of a near-real time hail damage swath identification algorithm for vegetation

    NASA Astrophysics Data System (ADS)

    Bell, Jordan R.

    The central United States is primarily covered in agricultural lands with a growing season that peaks during the same time as the region's climatological maximum for severe weather. These severe thunderstorms can bring large hail that can cause extensive areas of crop damage, which can be difficult to survey from the ground. Satellite remote sensing can help with the identification of these damaged areas. This study examined three techniques for identifying damage using satellite imagery that could be used in the development of a near-real time algorithm formulated for the detection of damage to agriculture caused by hail. The three techniques: a short term Normalized Difference Vegetation Index (NDVI) change product, a modified Vegetation Health Index (mVHI) that incorporates both NDVI and land surface temperature (LST), and a feature detection technique based on NDVI and LST anomalies were tested on a single training case and five case studies. Skill scores were computed for each of the techniques during the training case and each case study. Among the best-performing case studies, the probability of detection (POD) for the techniques ranged from 0.527 - 0.742. Greater skill was noted for environments that occurred later in the growing season over areas where the land cover was consistently one or two types of uniform vegetation. The techniques struggled in environments where the land cover was not able to provide uniform vegetation, resulting in POD of 0.067 - 0.223. The feature detection technique was selected to be used for the near-real-time algorithm, based on the consistent performance throughout the entire growing season.

  15. Prototype performance of novel muon telescope detector at STAR

    SciTech Connect

    Ruan,L.; Ames, V.

    2008-02-04

    Research on a large-area, cost-effective Muon Telescope Detector has been carried out for RHIC and for next generation detectors at future QCD Lab. We utilize state-of-the-art multi-gap resistive plate chambers with large modules and long readout strips in detector design [l]. The results from cosmic ray and beam test will be presented to address intrinsic timing and spatial resolution for a Long-MRF'C. The prototype performance of a novel muon telescope detector at STAR will be reported, including muon identification capability, timing and spatial resolution.

  16. Prototype Performance of Novel Muon Telescope Detector at STAR.

    SciTech Connect

    Ruan,L.

    2008-04-05

    Research on a large-area, cost-effective Muon Telescope Detector (MTD) has been carried out for RHIC and for next generation detectors at future QCD Lab. We utilize state-of-the-art multi-gap resistive plate chambers with large modules and long readout strips in detector design. The results from cosmic ray and beam test will be presented to address intrinsic timing and spatial resolution for a Long-MRPC. The prototype performance of a novel muon telescope detector at STAR will be reported, including muon identification capability, timing and spatial resolution.

  17. Muons in chemistry

    NASA Astrophysics Data System (ADS)

    Clayden, N. J.

    2013-12-01

    Positive muons have long been used as extrinsic probes in chemistry, offering unique properties for the investigation of local magnetism, dynamics, transport and radical kinetics. Exciting new developments in muon beam lines offer the opportunity of extending these studies selectively to surfaces permitting, for example, the detection of increased mobility of polymer chains at the surface of a polymer film. So called pump and probe methods, involving external perturbations by laser irradiation to manipulate vibrational and electronic states, can be followed by muon pulses allowing the probing of the properties of these states. Muoniated radical probes are finding greater use in soft matter. Selectivity is achieved in these complex systems through an appropriate target molecule giving the chance to measure partitioning and interfacial transfer in surfactant systems. Improvements in sample environments allow the observation of muons in increasingly extreme combinations of temperature and pressure, such as supercritical water, allowing the characterization of the chemistry in these systems.

  18. Implementation of a conjugate gradient algorithm for thermal diffusivity identification in a moving boundaries system

    NASA Astrophysics Data System (ADS)

    Perez, L.; Autrique, L.; Gillet, M.

    2008-11-01

    The aim of this paper is to investigate the thermal diffusivity identification of a multilayered material dedicated to fire protection. In a military framework, fire protection needs to meet specific requirements, and operational protective systems must be constantly improved in order to keep up with the development of new weapons. In the specific domain of passive fire protections, intumescent coatings can be an effective solution on the battlefield. Intumescent materials have the ability to swell up when they are heated, building a thick multi-layered coating which provides efficient thermal insulation to the underlying material. Due to the heat aggressions (fire or explosion) leading to the intumescent phenomena, high temperatures are considered and prevent from linearization of the mathematical model describing the system state evolution. Previous sensitivity analysis has shown that the thermal diffusivity of the multilayered intumescent coating is a key parameter in order to validate the predictive numerical tool and therefore for thermal protection optimisation. A conjugate gradient method is implemented in order to minimise the quadratic cost function related to the error between predicted temperature and measured temperature. This regularisation algorithm is well adapted for a large number of unknown parameters.

  19. LateBiclustering: Efficient Heuristic Algorithm for Time-Lagged Bicluster Identification.

    PubMed

    Gonçalves, Joana P; Madeira, Sara C

    2014-01-01

    Identifying patterns in temporal data is key to uncover meaningful relationships in diverse domains, from stock trading to social interactions. Also of great interest are clinical and biological applications, namely monitoring patient response to treatment or characterizing activity at the molecular level. In biology, researchers seek to gain insight into gene functions and dynamics of biological processes, as well as potential perturbations of these leading to disease, through the study of patterns emerging from gene expression time series. Clustering can group genes exhibiting similar expression profiles, but focuses on global patterns denoting rather broad, unspecific responses. Biclustering reveals local patterns, which more naturally capture the intricate collaboration between biological players, particularly under a temporal setting. Despite the general biclustering formulation being NP-hard, considering specific properties of time series has led to efficient solutions for the discovery of temporally aligned patterns. Notably, the identification of biclusters with time-lagged patterns, suggestive of transcriptional cascades, remains a challenge due to the combinatorial explosion of delayed occurrences. Herein, we propose LateBiclustering, a sensible heuristic algorithm enabling a polynomial rather than exponential time solution for the problem. We show that it identifies meaningful time-lagged biclusters relevant to the response of Saccharomyces cerevisiae to heat stress. PMID:26356854

  20. System Identification Algorithm Analysis of Acupuncture Effect on Mean Blood Flux of Contralateral Hegu Acupoint

    PubMed Central

    Wang, Guangjun; Han, Jianguo; Litscher, Gerhard; Zhang, Weibo

    2012-01-01

    Background. Acupoints (belonging to 12 meridians) which have the same names are symmetrically distributed on the body. It has been proved that acupoints have certain biological specificities different from the normal parts of the body. However, there is little evidence that acupoints which have the same name and are located bilaterally and symmetrically have lateralized specificity. Thus, researching the lateralized specificity and the relationship between left-side and right-side acupuncture is of special importance. Methodology and Principal Findings. The mean blood flux (MBF) in both Hegu acupoints was measured by Moor full-field laser perfusion imager. With the method of system identification algorithm, the output distribution in different groups was acquired, based on different acupoint stimulation and standard signal input. It is demonstrated that after stimulation of the right Hegu acupoint by needle, the output value of MBF in contralateral Hegu acupoint was strongly amplified, while after acupuncturing the left Hegu acupoint, the output value of MBF in either side Hegu acupoint was amplified moderately. Conclusions and Significance. This paper indicates that the Hegu acupoint has lateralized specificity. After stimulating the ipsilateral Hegu acupoint, symmetry breaking will be produced in contrast to contralateral Hegu acupoint stimulation. PMID:22693535

  1. SuperB Muon Detector Prototype

    SciTech Connect

    Not Available

    2010-11-01

    The test objective is to optimize the muon identification in an experiment at a Super B Factory. To accomplish this, experimenters will study the muon identification capability of a detector with different iron configurations at different beam energies. The detector is a full scale prototype, composed of a stack of iron tiles. The segmentation of the iron allows the study of different configurations. Between the tiles, one or two extruded scintillator slabs can be inserted to test two different readout options; a Binary Readout and a Time Readout. In the Binary Readout option the two coordinates are given by the two orthogonal scintillator bars, and the spatial resolution is driven by the bar width. In the Time Readout option one coordinate is determined by the scintillator position and the other by the arrival time of the signal read with a TDC.

  2. Fast cooling, muon acceleration and the prospect of muon colliders

    NASA Astrophysics Data System (ADS)

    Palmer, Mark

    Facilities based on stored muons offer unique potential for future high-energy physics capabilities. Three key characteristics of the muon make this possible: * The muon is a lepton; * The muon is roughly 200 times as massive as the electron; * The muon decays to an electron and two neutrinos. As the next heavier members of the lepton family with respect to the electron and positron, μ+ and μ-. beams can be collided to provide a precision lepton probe of the electroweak couplings. This makes a muon collider a suitable option for a lepton collider companion to a hadron collider discovery machine...

  3. Reconstruction and identification of $\\tau$ lepton decays to hadrons and $\

    SciTech Connect

    Khachatryan, Vardan

    2015-10-27

    This paper describes the algorithms used by the CMS experiment to reconstruct and identify τ→ hadrons + vt decays during Run 1 of the LHC. The performance of the algorithms is studied in proton-proton collisions recorded at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb-1. The algorithms achieve an identification efficiency of 50–60%, with misidentification rates for quark and gluon jets, electrons, and muons between per mille and per cent levels.

  4. Reconstruction and identification of $$\\tau$$ lepton decays to hadrons and $$\

    DOE PAGESBeta

    Khachatryan, Vardan

    2016-01-29

    This paper describes the algorithms used by the CMS experiment to reconstruct and identify τ→ hadrons + vt decays during Run 1 of the LHC. The performance of the algorithms is studied in proton-proton collisions recorded at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb-1. The algorithms achieve an identification efficiency of 50–60%, with misidentification rates for quark and gluon jets, electrons, and muons between per mille and per cent levels.

  5. Design of a muon tomography system with a plastic scintillator and wavelength-shifting fiber arrays

    NASA Astrophysics Data System (ADS)

    Jo, Woo Jin; Kim, Hyun-Il; An, Su Jung; Lee, Chae Young; Baek, Cheol-Ha; Chung, Yong Hyun

    2013-12-01

    Recently, monitoring nuclear materials to avoid nuclear terrorism has become an important area of national security. It can be difficult to detect gamma rays from nuclear material because they are easily shielded by shielding material. Muon tomography using multiple -Coulomb scattering derived from muons can be utilized to detect special nuclear materials (SNMs) such as uranium-235 and plutonium-239. We designed a muon tomography system composed of four detector modules. The incident and scattered muon tracks can be calculated by two top and two bottom detectors, respectively. 3D tomographic images are obtained by extracting the crossing points of muon tracks with a point-of-closest-approach algorithm. The purpose of this study was to optimize the muon tomography system using Monte Carlo simulation code. The effects of the geometric parameters of the muon tomography system on material Z-discrimination capability were simulated and evaluated.

  6. Improving protein identification from peptide mass fingerprinting through a parameterized multi-level scoring algorithm and an optimized peak detection.

    PubMed

    Gras, R; Müller, M; Gasteiger, E; Gay, S; Binz, P A; Bienvenut, W; Hoogland, C; Sanchez, J C; Bairoch, A; Hochstrasser, D F; Appel, R D

    1999-12-01

    We have developed a new algorithm to identify proteins by means of peptide mass fingerprinting. Starting from the matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) spectra and environmental data such as species, isoelectric point and molecular weight, as well as chemical modifications or number of missed cleavages of a protein, the program performs a fully automated identification of the protein. The first step is a peak detection algorithm, which allows precise and fast determination of peptide masses, even if the peaks are of low intensity or they overlap. In the second step the masses and environmental data are used by the identification algorithm to search in protein sequence databases (SWISS-PROT and/or TrEMBL) for protein entries that match the input data. Consequently, a list of candidate proteins is selected from the database, and a score calculation provides a ranking according to the quality of the match. To define the most discriminating scoring calculation we analyzed the respective role of each parameter in two directions. The first one is based on filtering and exploratory effects, while the second direction focuses on the levels where the parameters intervene in the identification process. Thus, according to our analysis, all input parameters contribute to the score, however with different weights. Since it is difficult to estimate the weights in advance, they have been computed with a generic algorithm, using a training set of 91 protein spectra with their environmental data. We tested the resulting scoring calculation on a test set of ten proteins and compared the identification results with those of other peptide mass fingerprinting programs. PMID:10612280

  7. Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification

    NASA Astrophysics Data System (ADS)

    Huang, Jian; Liu, Gui-xiong

    2016-04-01

    The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm (k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler's numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z '. The training set T z increased to T z+1 by T z if T z was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.

  8. Design and characterization of a small muon tomography system

    NASA Astrophysics Data System (ADS)

    Jo, Woo Jin; An, Su Jung; Kim, Hyun-Il; Lee, Chae Young; Chung, Heejun; Chung, Yong Hyun

    2015-02-01

    Muon tomography is a useful method for monitoring special nuclear materials (SNMs) because it can provide effective information on the presence of high-Z materials, has a high enough energy to deeply penetrate large amounts of shielding, and does not lead to any health risks and danger above background. We developed a 2-D muon detector and designed a muon tomography system employing four detector modules. Two top and two bottom detectors are, respectively, employed to record the incident and the scattered muon trajectories. The detector module for the muon tomography system consists of a plastic scintillator, wavelength-shifting (WLS) fiber arrays placed orthogonally on the top and the bottom of the scintillator, and a position-sensitive photomultiplier (PSPMT). The WLS fiber arrays absorb light photons emitted by the plastic scintillator and re-emit green lights guided to the PSPMT. The light distribution among the WLS fiber arrays determines the position of the muon interaction; consequently, 3-D tomographic images can be obtained by extracting the crossing points of the individual muon trajectories by using a point-of-closest-approach algorithm. The goal of this study is to optimize the design parameters of a muon tomography system by using the Geant4 code and to experimentally evaluate the performance of the prototype detector. Images obtained by the prototype detector with a 420-nm laser light source showed good agreement with the simulation results. This indicates that the proposed detector is feasible for use in a muon tomography system and can be used to verify the Z-discrimination capability of the muon tomography system.

  9. Identification of Different Varieties of Sesame Oil Using Near-Infrared Hyperspectral Imaging and Chemometrics Algorithms

    PubMed Central

    Xie, Chuanqi; Wang, Qiaonan; He, Yong

    2014-01-01

    This study investigated the feasibility of using near infrared hyperspectral imaging (NIR-HSI) technique for non-destructive identification of sesame oil. Hyperspectral images of four varieties of sesame oil were obtained in the spectral region of 874–1734 nm. Reflectance values were extracted from each region of interest (ROI) of each sample. Competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA) and x-loading weights (x-LW) were carried out to identify the most significant wavelengths. Based on the sixty-four, seven and five wavelengths suggested by CARS, SPA and x-LW, respectively, two classified models (least squares-support vector machine, LS-SVM and linear discriminant analysis,LDA) were established. Among the established models, CARS-LS-SVM and CARS-LDA models performed well with the highest classification rate (100%) in both calibration and prediction sets. SPA-LS-SVM and SPA-LDA models obtained better results (95.59% and 98.53% of classification rate in prediction set) with only seven wavelengths (938, 1160, 1214, 1406, 1656, 1659 and 1663 nm). The x-LW-LS-SVM and x-LW-LDA models also obtained satisfactory results (>80% of classification rate in prediction set) with the only five wavelengths (921, 925, 995, 1453 and 1663 nm). The results showed that NIR-HSI technique could be used to identify the varieties of sesame oil rapidly and non-destructively, and CARS, SPA and x-LW were effective wavelengths selection methods. PMID:24879306

  10. DiME: A Scalable Disease Module Identification Algorithm with Application to Glioma Progression

    PubMed Central

    Liu, Yunpeng; Tennant, Daniel A.; Zhu, Zexuan; Heath, John K.; Yao, Xin; He, Shan

    2014-01-01

    Disease module is a group of molecular components that interact intensively in the disease specific biological network. Since the connectivity and activity of disease modules may shed light on the molecular mechanisms of pathogenesis and disease progression, their identification becomes one of the most important challenges in network medicine, an emerging paradigm to study complex human disease. This paper proposes a novel algorithm, DiME (Disease Module Extraction), to identify putative disease modules from biological networks. We have developed novel heuristics to optimise Community Extraction, a module criterion originally proposed for social network analysis, to extract topological core modules from biological networks as putative disease modules. In addition, we have incorporated a statistical significance measure, B-score, to evaluate the quality of extracted modules. As an application to complex diseases, we have employed DiME to investigate the molecular mechanisms that underpin the progression of glioma, the most common type of brain tumour. We have built low (grade II) - and high (GBM) - grade glioma co-expression networks from three independent datasets and then applied DiME to extract potential disease modules from both networks for comparison. Examination of the interconnectivity of the identified modules have revealed changes in topology and module activity (expression) between low- and high- grade tumours, which are characteristic of the major shifts in the constitution and physiology of tumour cells during glioma progression. Our results suggest that transcription factors E2F4, AR and ETS1 are potential key regulators in tumour progression. Our DiME compiled software, R/C++ source code, sample data and a tutorial are available at http://www.cs.bham.ac.uk/~szh/DiME. PMID:24523864

  11. A component-level failure detection and identification algorithm based on open-loop and closed-loop state estimators

    NASA Astrophysics Data System (ADS)

    You, Seung-Han; Cho, Young Man; Hahn, Jin-Oh

    2013-04-01

    This study presents a component-level failure detection and identification (FDI) algorithm for a cascade mechanical system subsuming a plant driven by an actuator unit. The novelty of the FDI algorithm presented in this study is that it is able to discriminate failure occurring in the actuator unit, the sensor measuring the output of the actuator unit, and the plant driven by the actuator unit. The proposed FDI algorithm exploits the measurement of the actuator unit output together with its estimates generated by open-loop (OL) and closed-loop (CL) estimators to enable FDI at the component's level. In this study, the OL estimator is designed based on the system identification of the actuator unit. The CL estimator, which is guaranteed to be stable against variations in the plant, is synthesized based on the dynamics of the entire cascade system. The viability of the proposed algorithm is demonstrated using a hardware-in-the-loop simulation (HILS), which shows that it can detect and identify target failures reliably in the presence of plant uncertainties.

  12. Processor core for real time background identification of HD video based on OpenCV Gaussian mixture model algorithm

    NASA Astrophysics Data System (ADS)

    Genovese, Mariangela; Napoli, Ettore

    2013-05-01

    The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.

  13. Fukushima Daiichi Muon Imaging

    NASA Astrophysics Data System (ADS)

    Miyadera, Haruo

    2015-10-01

    Japanese government announced cold-shutdown condition of the reactors at Fukushima Daiichi by the end of 2011, and mid- and long-term roadmap towards decommissioning has been drawn. However, little is known for the conditions of the cores because access to the reactors has been limited by the high radiation environment. The debris removal from the Unit 1 - 3 is planned to start as early as 2020, but the dismantlement is not easy without any realistic information of the damage to the cores, and the locations and amounts of the fuel debris. Soon after the disaster of Fukushima Daiichi, several teams in the US and Japan proposed to apply muon transmission or scattering imagings to provide information of the Fukushima Daiichi reactors without accessing inside the reactor building. GEANT4 modeling studies of Fukushima Daiichi Unit 1 and 2 showed clear superiority of the muon scattering method over conventional transmission method. The scattering method was demonstrated with a research reactor, Toshiba Nuclear Critical Assembly (NCA), where a fuel assembly was imaged with 3-cm resolution. The muon scattering imaging of Fukushima Daiichi was approved as a national project and is aiming at installing muon trackers to Unit 2. A proposed plan includes installation of muon trackers on the 2nd floor (operation floor) of turbine building, and in front of the reactor building. Two 7mx7m detectors were assembled at Toshiba and tested.

  14. Precision muon physics

    NASA Astrophysics Data System (ADS)

    Gorringe, T. P.; Hertzog, D. W.

    2015-09-01

    The muon is playing a unique role in sub-atomic physics. Studies of muon decay both determine the overall strength and establish the chiral structure of weak interactions, as well as setting extraordinary limits on charged-lepton-flavor-violating processes. Measurements of the muon's anomalous magnetic moment offer singular sensitivity to the completeness of the standard model and the predictions of many speculative theories. Spectroscopy of muonium and muonic atoms gives unmatched determinations of fundamental quantities including the magnetic moment ratio μμ /μp, lepton mass ratio mμ /me, and proton charge radius rp. Also, muon capture experiments are exploring elusive features of weak interactions involving nucleons and nuclei. We will review the experimental landscape of contemporary high-precision and high-sensitivity experiments with muons. One focus is the novel methods and ingenious techniques that achieve such precision and sensitivity in recent, present, and planned experiments. Another focus is the uncommonly broad and topical range of questions in atomic, nuclear and particle physics that such experiments explore.

  15. ISPTM: an iterative search algorithm for systematic identification of post-translational modifications from complex proteome mixtures.

    PubMed

    Huang, Xin; Huang, Lin; Peng, Hong; Guru, Ashu; Xue, Weihua; Hong, Sang Yong; Liu, Miao; Sharma, Seema; Fu, Kai; Caprez, Adam P; Swanson, David R; Zhang, Zhixin; Ding, Shi-Jian

    2013-09-01

    Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear matrix proteins with unknown modifications. ISPTM revealed that many chemical PTMs were introduced by urea and iodoacetamide during sample preparation and many biological PTMs, including dimethylation of arginine and lysine, were significantly activated by Adriamycin treatment in nuclear matrix associated proteins. ISPTM increased the MS/MS spectral identification rate substantially, displayed significantly better sensitivity for systematic PTM identification compared with that of the conventional all-in-one search approach, and offered PTM identification results that were complementary to InsPecT and MODa, both of which are established PTM identification algorithms. In summary, ISPTM is a new and powerful tool for unbiased identification of many different PTMs with high confidence from complex proteome mixtures. PMID:23919725

  16. A comparison of direction finding results from an FFT peak identification technique with those from the music algorithm

    NASA Astrophysics Data System (ADS)

    Montbriand, L. E.

    1991-07-01

    A peak identification technique which uses the fast Fourier transform (FFT) algorithm is presented for unambiguously identifying up to three sources in signals received by the sampled aperture receiving array (SARA) of the Communications Research Center. The technique involves removing phase rotations resulting from the FFT and the data configuration and interpreting this result as the direction cosine distribution of the received signal. The locations and amplitudes of all peaks for one array arm are matched with those in a master list for a single source in order to identify actual sources. The identification of actual sources was found to be subject to the limitations of the FFT in that there was an inherent bias for the secondary and tertiary sources to appear at the side-lobe positions of the strongest source. There appears to be a limit in the ratio of the magnitude of a weaker source to that of the strongest source, below which it becomes too difficult to reliably identify true sources. For the SARA array this ratio is near-10 dB. Some of the data were also analyzed using the more complex MUSIC algorithm which yields a narrower directional peak for the sources than the FFT. For the SARA array, using ungroomed data, the largest side and grating lobes that the MUSIC algorithm produces are some 10 dB below the largest side and grating lobes that are produced using the FFT algorithm. Consequently the source-separation problem is less than that encountered using the FFT algorithm, but is not eliminated.

  17. Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

    NASA Technical Reports Server (NTRS)

    Bell, Jordan R.; Molthan, Andrew L.; Schultz, Kori A.; McGrath, Kevin M.; Burks, Jason E.

    2015-01-01

    Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the

  18. THE DEVELOPMENT OF A PARAMETERIZED SCATTER REMOVAL ALGORITHM FOR NUCLEAR MATERIALS IDENTIFICATION SYSTEM IMAGING

    SciTech Connect

    Grogan, Brandon R

    2010-05-01

    This report presents a novel method for removing scattering effects from Nuclear Materials Identification System (NMIS) imaging. The NMIS uses fast neutron radiography to generate images of the internal structure of objects nonintrusively. If the correct attenuation through the object is measured, the positions and macroscopic cross sections of features inside the object can be determined. The cross sections can then be used to identify the materials, and a 3D map of the interior of the object can be reconstructed. Unfortunately, the measured attenuation values are always too low because scattered neutrons contribute to the unattenuated neutron signal. Previous efforts to remove the scatter from NMIS imaging have focused on minimizing the fraction of scattered neutrons that are misidentified as directly transmitted by electronically collimating and time tagging the source neutrons. The parameterized scatter removal algorithm (PSRA) approaches the problem from an entirely new direction by using Monte Carlo simulations to estimate the point scatter functions (PScFs) produced by neutrons scattering in the object. PScFs have been used to remove scattering successfully in other applications, but only with simple 2D detector models. This work represents the first time PScFs have ever been applied to an imaging detector geometry as complicated as the NMIS. By fitting the PScFs using a Gaussian function, they can be parameterized, and the proper scatter for a given problem can be removed without the need for rerunning the simulations each time. In order to model the PScFs, an entirely new method for simulating NMIS measurements was developed for this work. The development of the new models and the codes required to simulate them are presented in detail. The PSRA was used on several simulated and experimental measurements, and chi-squared goodness of fit tests were used to compare the corrected values to the ideal values that would be expected with no scattering. Using the

  19. The Development of a Parameterized Scatter Removal Algorithm for Nuclear Materials Identification System Imaging

    SciTech Connect

    Grogan, Brandon R

    2010-03-01

    This dissertation presents a novel method for removing scattering effects from Nuclear Materials Identification System (NMIS) imaging. The NMIS uses fast neutron radiography to generate images of the internal structure of objects non-intrusively. If the correct attenuation through the object is measured, the positions and macroscopic cross-sections of features inside the object can be determined. The cross sections can then be used to identify the materials and a 3D map of the interior of the object can be reconstructed. Unfortunately, the measured attenuation values are always too low because scattered neutrons contribute to the unattenuated neutron signal. Previous efforts to remove the scatter from NMIS imaging have focused on minimizing the fraction of scattered neutrons which are misidentified as directly transmitted by electronically collimating and time tagging the source neutrons. The parameterized scatter removal algorithm (PSRA) approaches the problem from an entirely new direction by using Monte Carlo simulations to estimate the point scatter functions (PScFs) produced by neutrons scattering in the object. PScFs have been used to remove scattering successfully in other applications, but only with simple 2D detector models. This work represents the first time PScFs have ever been applied to an imaging detector geometry as complicated as the NMIS. By fitting the PScFs using a Gaussian function, they can be parameterized and the proper scatter for a given problem can be removed without the need for rerunning the simulations each time. In order to model the PScFs, an entirely new method for simulating NMIS measurements was developed for this work. The development of the new models and the codes required to simulate them are presented in detail. The PSRA was used on several simulated and experimental measurements and chi-squared goodness of fit tests were used to compare the corrected values to the ideal values that would be expected with no scattering. Using

  20. A wavelet based algorithm for the identification of oscillatory event-related potential components.

    PubMed

    Aniyan, Arun Kumar; Philip, Ninan Sajeeth; Samar, Vincent J; Desjardins, James A; Segalowitz, Sidney J

    2014-08-15

    Event related potentials (ERPs) are very feeble alterations in the ongoing electroencephalogram (EEG) and their detection is a challenging problem. Based on the unique time-based parameters derived from wavelet coefficients and the asymmetry property of wavelets a novel algorithm to separate ERP components in single-trial EEG data is described. Though illustrated as a specific application to N170 ERP detection, the algorithm is a generalized approach that can be easily adapted to isolate different kinds of ERP components. The algorithm detected the N170 ERP component with a high level of accuracy. We demonstrate that the asymmetry method is more accurate than the matching wavelet algorithm and t-CWT method by 48.67 and 8.03 percent, respectively. This paper provides an off-line demonstration of the algorithm and considers issues related to the extension of the algorithm to real-time applications. PMID:24931710

  1. The LHCb Muon System

    SciTech Connect

    Baldini, W.

    2005-10-12

    In this paper is described the design, the construction and the performances of several Multi Wire Proportional Chamber prototypes built for the LHCb Muon system. In particular we report results for detection efficiency, time resolution, high rate performances and ageing effect measured at the CERN T11 test beam area and at the high irradiation ENEA Casaccia Calliope Facility.

  2. Identification of individuals with ADHD using the Dean-Woodcock sensory motor battery and a boosted tree algorithm.

    PubMed

    Finch, Holmes W; Davis, Andrew; Dean, Raymond S

    2015-03-01

    The accurate and early identification of individuals with pervasive conditions such as attention deficit hyperactivity disorder (ADHD) is crucial to ensuring that they receive appropriate and timely assistance and treatment. Heretofore, identification of such individuals has proven somewhat difficult, typically involving clinical decision making based on descriptions and observations of behavior, in conjunction with the administration of cognitive assessments. The present study reports on the use of a sensory motor battery in conjunction with a recursive partitioning computer algorithm, boosted trees, to develop a prediction heuristic for identifying individuals with ADHD. Results of the study demonstrate that this method is able to do so with accuracy rates of over 95 %, much higher than the popular logistic regression model against which it was compared. Implications of these results for practice are provided. PMID:24771321

  3. Industrial experience of process identification and set-point decision algorithm in a full-scale treatment plant.

    PubMed

    Yoo, Changkyoo; Kim, Min Han

    2009-06-01

    This paper presents industrial experience of process identification, monitoring, and control in a full-scale wastewater treatment plant. The objectives of this study were (1) to apply and compare different process-identification methods of proportional-integral-derivative (PID) autotuning for stable dissolved oxygen (DO) control, (2) to implement a process monitoring method that estimates the respiration rate simultaneously during the process-identification step, and (3) to propose a simple set-point decision algorithm for determining the appropriate set point of the DO controller for optimal operation of the aeration basin. The proposed method was evaluated in the industrial wastewater treatment facility of an iron- and steel-making plant. Among the process-identification methods, the control signal of the controller's set-point change was best for identifying low-frequency information and enhancing the robustness to low-frequency disturbances. Combined automatic control and set-point decision method reduced the total electricity consumption by 5% and the electricity cost by 15% compared to the fixed gain PID controller, when considering only the surface aerators. Moreover, as a result of improved control performance, the fluctuation of effluent quality decreased and overall effluent water quality was better. PMID:19428173

  4. Identification of Transport Parameters and Pollution Sources for a Physically Based Groundwater Contaminant Transport Model: A Comparison of Algorithms

    NASA Astrophysics Data System (ADS)

    Yin, Y.; Sykes, J. F.

    2006-12-01

    Transport parameter estimation and contaminant source identification are critical steps in the development of a physically based groundwater contaminant transport model. For most transient field scale problems, the high computational burden required by parameter identification algorithms combined with sparse data sets often limits calibration. However, when data are available, a high performance computing system and parallel computing may make the calibration process feasible. The selection of the optimization algorithm is also critical. In this paper, the contaminant transport and source parameters were estimated and compared using optimization with two heuristic search algorithms (a dynamically dimensioned search and a parallelized micro genetic algorithm) and a gradient based multi-start PEST algorithm which were implemented on the Shared Hierarchical Academic Research Computing Network (Sharcnet). The case study is located in New Jersey where improper waste disposal resulted in the contamination of down gradient public water supply wells. Using FRAC3DVS, a physically based transient three-dimensional groundwater flow model with spatially and temporally varying recharge was developed and calibrated using both approximately 9 years of head data from continuous well records and data over a period of approximately 30 years from traditional monitoring wells. For the contaminant system, the parameters that were estimated include source leaching rate, source concentration, dispersivities, and retardation coefficient. The groundwater domain was discretized using 214,520 elements. With highly changing pump rates at the 7 municipal wells, time increments over the approximately 30 year simulation period varied dynamically between several days and 3 months. On Sharcnet, one forward simulation on a single processor of both transient flow and contaminant transport takes approximately 3 to 4 hours. The contaminant transport model calibration results indicate that overall

  5. Applicability of data mining algorithms in the identification of beach features/patterns on high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Teodoro, Ana C.

    2015-01-01

    The available beach classification algorithms and sediment budget models are mainly based on in situ parameters, usually unavailable for several coastal areas. A morphological analysis using remotely sensed data is a valid alternative. This study focuses on the application of data mining techniques, particularly decision trees (DTs) and artificial neural networks (ANNs) to an IKONOS-2 image in order to identify beach features/patterns in a stretch of the northwest coast of Portugal. Based on knowledge of the coastal features, five classes were defined. In the identification of beach features/patterns, the ANN algorithm presented an overall accuracy of 98.6% and a kappa coefficient of 0.97. The best DTs algorithm (with pruning) presents an overall accuracy of 98.2% and a kappa coefficient of 0.97. The results obtained through the ANN and DTs were in agreement. However, the ANN presented a classification more sensitive to rip currents. The use of ANNs and DTs for beach classification from remotely sensed data resulted in an increased classification accuracy when compared with traditional classification methods. The association of remotely sensed high-spatial resolution data and data mining algorithms is an effective methodology with which to identify beach features/patterns.

  6. A fast U-D factorization-based learning algorithm with applications to nonlinear system modeling and identification.

    PubMed

    Zhang, Y; Li, X R

    1999-01-01

    A fast learning algorithm for training multilayer feedforward neural networks (FNN's) by using a fading memory extended Kalman filter (FMEKF) is presented first, along with a technique using a self-adjusting time-varying forgetting factor. Then a U-D factorization-based FMEKF is proposed to further improve the learning rate and accuracy of the FNN. In comparison with the backpropagation (BP) and existing EKF-based learning algorithms, the proposed U-D factorization-based FMEKF algorithm provides much more accurate learning results, using fewer hidden nodes. It has improved convergence rate and numerical stability (robustness). In addition, it is less sensitive to start-up parameters (e.g., initial weights and covariance matrix) and the randomness in the observed data. It also has good generalization ability and needs less training time to achieve a specified learning accuracy. Simulation results in modeling and identification of nonlinear dynamic systems are given to show the effectiveness and efficiency of the proposed algorithm. PMID:18252590

  7. A parallel implementation of the network identification by multiple regression (NIR) algorithm to reverse-engineer regulatory gene networks.

    PubMed

    Gregoretti, Francesco; Belcastro, Vincenzo; di Bernardo, Diego; Oliva, Gennaro

    2010-01-01

    The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR) algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications. PMID:20422008

  8. Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm

    NASA Astrophysics Data System (ADS)

    Swayze, Gregg A.; Clark, Roger N.; Goetz, Alexander F. H.; Chrien, Thomas G.; Gorelick, Noel S.

    2003-09-01

    Estimates of spectrometer band pass, sampling interval, and signal-to-noise ratio required for identification of pure minerals and plants were derived using reflectance spectra convolved to AVIRIS, HYDICE, MIVIS, VIMS, and other imaging spectrometers. For each spectral simulation, various levels of random noise were added to the reflectance spectra after convolution, and then each was analyzed with the Tetracorder spectral identification algorithm [Clark et al., 2003]. The outcome of each identification attempt was tabulated to provide an estimate of the signal-to-noise ratio at which a given percentage of the noisy spectra were identified correctly. Results show that spectral identification is most sensitive to the signal-to-noise ratio at narrow sampling interval values but is more sensitive to the sampling interval itself at broad sampling interval values because of spectral aliasing, a condition when absorption features of different materials can resemble one another. The band pass is less critical to spectral identification than the sampling interval or signal-to-noise ratio because broadening the band pass does not induce spectral aliasing. These conclusions are empirically corroborated by analysis of mineral maps of AVIRIS data collected at Cuprite, Nevada, between 1990 and 1995, a period during which the sensor signal-to-noise ratio increased up to sixfold. There are values of spectrometer sampling and band pass beyond which spectral identification of materials will require an abrupt increase in sensor signal-to-noise ratio due to the effects of spectral aliasing. Factors that control this threshold are the uniqueness of a material's diagnostic absorptions in terms of shape and wavelength isolation, and the spectral diversity of the materials found in nature and in the spectral library used for comparison. Array spectrometers provide the best data for identification when they critically sample spectra. The sampling interval should not be broadened to

  9. Effects of spectrometer band pass, sampling, and signal-to-noise ratio on spectral identification using the Tetracorder algorithm

    USGS Publications Warehouse

    Swayze, G.A.; Clark, R.N.; Goetz, A.F.H.; Chrien, T.H.; Gorelick, N.S.

    2003-01-01

    Estimates of spectrometer band pass, sampling interval, and signal-to-noise ratio required for identification of pure minerals and plants were derived using reflectance spectra convolved to AVIRIS, HYDICE, MIVIS, VIMS, and other imaging spectrometers. For each spectral simulation, various levels of random noise were added to the reflectance spectra after convolution, and then each was analyzed with the Tetracorder spectra identification algorithm [Clark et al., 2003]. The outcome of each identification attempt was tabulated to provide an estimate of the signal-to-noise ratio at which a given percentage of the noisy spectra were identified correctly. Results show that spectral identification is most sensitive to the signal-to-noise ratio at narrow sampling interval values but is more sensitive to the sampling interval itself at broad sampling interval values because of spectral aliasing, a condition when absorption features of different materials can resemble one another. The band pass is less critical to spectral identification than the sampling interval or signal-to-noise ratio because broadening the band pass does not induce spectral aliasing. These conclusions are empirically corroborated by analysis of mineral maps of AVIRIS data collected at Cuprite, Nevada, between 1990 and 1995, a period during which the sensor signal-to-noise ratio increased up to sixfold. There are values of spectrometer sampling and band pass beyond which spectral identification of materials will require an abrupt increase in sensor signal-to-noise ratio due to the effects of spectral aliasing. Factors that control this threshold are the uniqueness of a material's diagnostic absorptions in terms of shape and wavelength isolation, and the spectral diversity of the materials found in nature and in the spectral library used for comparison. Array spectrometers provide the best data for identification when they critically sample spectra. The sampling interval should not be broadened to

  10. On muon energy spectrum in muon groups underground

    NASA Technical Reports Server (NTRS)

    Bakatanov, V. N.; Chudakov, A. E.; Novoseltsev, Y. F.; Novoseltseva, M. V.; Stenkin, Y. V.

    1985-01-01

    A method is described which was used to measure muon energy spectrum characteristics in muon groups underground using mu-e decays recording. The Baksan Telescope's experimental data on mu-e decays intensity in muon groups of various multiplicities are analyzed. The experimental data indicating very flat spectrum does not however represent the total spectrum in muon groups. Obviously the muon energy spectrum depends strongly on a distance from the group axis. The core attraction effect makes a significant distortion, making the spectrum flatter. After taking this into account and making corrections for this effect the integral total spectrum index in groups has a very small depencence on muon multiplicity and agrees well with expected one: beta=beta (sub expected) = 1.75.

  11. Muon capture for the front end of a muon collider

    SciTech Connect

    Neuffer, D.; Yoshikawa, C.; /MUONS Inc., Batavia

    2011-03-01

    We discuss the design of the muon capture front end for a {mu}{sup +}-{mu}{sup -} Collider. In the front end, a proton bunch on a target creates secondary pions that drift into a capture transport channel, decaying into muons. A sequence of rf cavities forms the resulting muon beams into strings of bunches of differing energies, aligns the bunches to (nearly) equal central energies, and initiates ionization cooling. The muons are then cooled and accelerated to high energy into a storage ring for high-energy high luminosity collisions. Our initial design is based on the somewhat similar front end of the International Design Study (IDS) neutrino factory.

  12. Muon collider progress

    SciTech Connect

    Noble, Robert J. FNAL

    1998-08-01

    Recent progress in the study of muon colliders is presented. An international collaboration consisting of over 100 individuals is involved in calculations and experiments to demonstrate the feasibility of this new type of lepton collider. Theoretical efforts are now concentrated on low-energy colliders in the 100 to 500 GeV center-of-mass energy range. Credible machine designs are emerging for much of a hypothetical complex from proton source to the final collider. Ionization cooling has been the most difficult part of the concept, and more powerful simulation tools are now in place to develop workable schemes. A collaboration proposal for a muon cooling experiment has been presented to the Fermilab Physics Advisory Committee, and a proposal for a targetry and pion collection channel experiment at Brookhaven National Laboratory is in preparation. Initial proton bunching and space-charge compensation experiments at existing hadron facilities have occurred to demonstrate proton driver feasibility.

  13. Muon spin rotation studies

    NASA Technical Reports Server (NTRS)

    1984-01-01

    The bulk of the muon spin rotation research work centered around the development of the muon spin rotation facility at the Alternating Gradient Synchrotron (AGS) of Brookhaven National Laboratory (BNL). The collimation system was both designed and fabricated at Virginia State University. This improved collimation system, plus improvements in detectors and electronics enabled the acquisition of spectra free of background out to 15 microseconds. There were two runs at Brookhaven in 1984, one run was devoted primarily to beam development and the other run allowed several successful experiments to be performed. The effect of uniaxial strain on an Fe(Si) crystal at elevated temperature (360K) was measured and the results are incorporated herein. A complete analysis of Fe pulling data taken earlier is included.

  14. The US Muon Accelerator Program

    SciTech Connect

    Torun, Y.; Kirk, H.; Bross, A.; Geer, Steve; Shiltsev, Vladimir; Zisman, M.; /LBL, Berkeley

    2010-05-01

    An accelerator complex that can produce ultra-intense beams of muons presents many opportunities to explore new physics. A facility of this type is unique in that, in a relatively straightforward way, it can present a physics program that can be staged and thus move forward incrementally, addressing exciting new physics at each step. At the request of the US Department of Energy's Office of High Energy Physics, the Neutrino Factory and Muon Collider Collaboration (NFMCC) and the Fermilab Muon Collider Task Force (MCTF) have recently submitted a proposal to create a Muon Accelerator Program that will have, as a primary goal, to deliver a Design Feasibility Study for an energy-frontier Muon Collider by the end of a 7 year R&D program. This paper presents a description of a Muon Collider facility and gives an overview of the proposal.

  15. Muon cherenkov telescope

    NASA Astrophysics Data System (ADS)

    Malamova, E.; Angelov, I.; Kalapov, I.; Davidkov, K.; Stamenov, J.

    2001-08-01

    : The Muon Cerenkov Telescope is a system of water cerenkov detectors, using the coincidence technique to register cosmic ray muons. It is constructed in order to study the variations of cosmic rays and their correlation with solar activity and processes in the Earth magnetosphere. 1 Basic design of the Muon Cerenkov Telescope The telescope has 18 water cerenkov detectors / 0.25 m2 each /, situated in two parallel planes. / Fig. 1/ Each detector /fig. 2/ consists of a container with dimensions 50x50x12.5 cm made of 3mm thick glass with mirror cover of the outer side. The container is filled with distilled water to 10cm level. A photomultiplier is attached to a transparent circle at the floor of the container and the discriminator is placed in its housing. When a charged particle with energy greater than the threshold energy for cerenkov radiation generation passes the radiator, cerenkov photons are initiated and a part of them reach the PMT cathode after multiple reflections from the mirror sides of the container.

  16. A Fast Robot Identification and Mapping Algorithm Based on Kinect Sensor

    PubMed Central

    Zhang, Liang; Shen, Peiyi; Zhu, Guangming; Wei, Wei; Song, Houbing

    2015-01-01

    Internet of Things (IoT) is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB) method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN) k-Nearest Neighbor (KNN) algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC) estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP) is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS) algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University’s datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy. PMID:26287198

  17. A Fast Robot Identification and Mapping Algorithm Based on Kinect Sensor.

    PubMed

    Zhang, Liang; Shen, Peiyi; Zhu, Guangming; Wei, Wei; Song, Houbing

    2015-01-01

    Internet of Things (IoT) is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB) method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN) k-Nearest Neighbor (KNN) algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC) estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP) is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS) algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University's datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy. PMID:26287198

  18. Muon Colliders and Neutrino Factories

    SciTech Connect

    Geer, Steve; /Fermilab

    2009-11-01

    Over the past decade, there has been significant progress in developing the concepts and technologies needed to produce, capture, and accelerate {Omicron}(10{sup 21}) muons per year. These developments have paved the way for a new type of neutrino source (neutrino factory) and a new type of very high energy lepton-antilepton collider (muon collider). This article reviews the motivation, design, and research and development for future neutrino factories and muon colliders.

  19. Muon colliders and neutrino factories

    SciTech Connect

    Geer, S.; /Fermilab

    2010-09-01

    Over the last decade there has been significant progress in developing the concepts and technologies needed to produce, capture and accelerate {Omicron}(10{sup 21}) muons/year. This development prepares the way for a new type of neutrino source (Neutrino Factory) and a new type of very high energy lepton-antilepton collider (Muon Collider). This article reviews the motivation, design and R&D for Neutrino Factories and Muon Colliders.

  20. Muon Colliders and Neutrino Factories *

    NASA Astrophysics Data System (ADS)

    Geer, Steve

    2009-11-01

    Over the past decade, there has been significant progress in developing the concepts and technologies needed to produce, capture, and accelerate O(1021) muons per year. These developments have paved the way for a new type of neutrino source (neutrino factory) and a new type of very high energy lepton-antilepton collider (muon collider). This article reviews the motivation, design, and research and development for future neutrino factories and muon colliders.

  1. Application of Gauss algorithm and Monte Carlo simulation to the identification of aquifer parameters

    USGS Publications Warehouse

    Durbin, Timothy J.

    1983-01-01

    The Gauss optimization technique can be used to identify the parameters of a model of a groundwater system for which the parameter identification problem is formulated as a least squares comparison between the response of the prototype and the response of the model. Unavoidable uncertainty in the true stress on the prototype and in the true response of the prototype to that stress will introduce errors into the parameter identification problem. A method for evaluating errors in the predictions of future water levels due to errors in recharge estimates was demonstrated. The method involves a Monte Carlo simulation of the parameter identification problem and of the prediction problem. The steps in the method are: (1) to prescribe the distribution of the recharge estimates; (2) to use this distribution to generate random sets of recharge estimates; (3) to use the Gauss optimization technique to identify the corresponding set of parameter estimates for each set of recharge estimates; (4) to make the corresponding set of hydraulic head predictions for each set of parameter estimates; and (5) to examine the distribution of hydraulic head predictions and to draw appropriate conclusions. Similarly, the method can be used independently or simultaneously to estimate the effect on hydraulic head predictions of errors in the measured water levels that are used in the parameter identification problem. The fit of the model to the data that are used to identify parameters is not a good indicator of these errors. A Monte Carlo simulation of the parameter identification problem can be used, however, to evaluate the effects on water level predictions of errors in the recharge (and pumpage) data used in the parameter identification problem. (Lantz-PTT)

  2. A novel method based on physicochemical properties of amino acids and one class classification algorithm for disease gene identification.

    PubMed

    Yousef, Abdulaziz; Charkari, Nasrollah Moghadam

    2015-08-01

    Identifying the genes that cause disease is one of the most challenging issues to establish the diagnosis and treatment quickly. Several interesting methods have been introduced for disease gene identification for a decade. In general, the main differences between these methods are the type of data used as a prior-knowledge, as well as machine learning (ML) methods used for identification. The disease gene identification task has been commonly viewed by ML methods as a binary classification problem (whether any gene is disease or not). However, the nature of the data (since there is no negative data available for training or leaners) creates a major problem which affect the results. In this paper, sequence-based, one class classification method is introduced to assign genes to disease class (yes, no). First, to generate feature vector, the sequences of proteins (genes) are initially transformed to numerical vector using physicochemical properties of amino acid. Second, as there is no definite approach to define non-disease genes (negative data); we have attempted to model solely disease genes (positive data) to make a prediction by employing Support Vector Data Description algorithm. The experimental results confirm the efficiency of the method with precision, recall and F-measure of 79.3%, 82.6% and 80.9%, respectively. PMID:26146156

  3. Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinION(TM) sequencing.

    PubMed

    Cao, Minh Duc; Ganesamoorthy, Devika; Elliott, Alysha G; Zhang, Huihui; Cooper, Matthew A; Coin, Lachlan J M

    2016-01-01

    The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This has great potential to shorten the sample-to-results time and is likely to have benefits such as rapid diagnosis of bacterial infection and identification of drug resistance. However, there are few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, strain typing and antibiotic resistance profile identification. Using four culture isolate samples, as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 min of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 h. While strain identification with multi-locus sequence typing required more than 15x coverage to generate confident assignments, our novel gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer. PMID:27457073

  4. Unsupervised algorithms for intrusion detection and identification in wireless ad hoc sensor networks

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2009-05-01

    In previous work by the author, parameters across network protocol layers were selected as features in supervised algorithms that detect and identify certain intrusion attacks on wireless ad hoc sensor networks (WSNs) carrying multisensor data. The algorithms improved the residual performance of the intrusion prevention measures provided by any dynamic key-management schemes and trust models implemented among network nodes. The approach of this paper does not train algorithms on the signature of known attack traffic, but, instead, the approach is based on unsupervised anomaly detection techniques that learn the signature of normal network traffic. Unsupervised learning does not require the data to be labeled or to be purely of one type, i.e., normal or attack traffic. The approach can be augmented to add any security attributes and quantified trust levels, established during data exchanges among nodes, to the set of cross-layer features from the WSN protocols. A two-stage framework is introduced for the security algorithms to overcome the problems of input size and resource constraints. The first stage is an unsupervised clustering algorithm which reduces the payload of network data packets to a tractable size. The second stage is a traditional anomaly detection algorithm based on a variation of support vector machines (SVMs), whose efficiency is improved by the availability of data in the packet payload. In the first stage, selected algorithms are adapted to WSN platforms to meet system requirements for simple parallel distributed computation, distributed storage and data robustness. A set of mobile software agents, acting like an ant colony in securing the WSN, are distributed at the nodes to implement the algorithms. The agents move among the layers involved in the network response to the intrusions at each active node and trustworthy neighborhood, collecting parametric values and executing assigned decision tasks. This minimizes the need to move large amounts

  5. Blind identification and restoration of turbulence degraded images based on the nonnegativity and support constraints recursive inverse filtering algorithm

    NASA Astrophysics Data System (ADS)

    Li, Dongxing; Zhao, Yan; Dong, Xu

    2008-03-01

    In general image restoration, the point spread function (PSF) of the imaging system, and the observation noise, are known a priori information. The aero-optics effect is yielded when the objects ( e.g, missile, aircraft etc.) are flying in high speed or ultrasonic speed. In this situation, the PSF and the observation noise are unknown a priori. The identification and the restoration of the turbulence degraded images is a challenging problem in the world. The algorithm based on the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) is proposed in order to identify and restore the turbulence degraded images. The NAS-RIF technique applies to situations in which the scene consists of a finite support object against a uniformly black, grey, or white background. The restoration procedure of NAS-RIF involves recursive filtering of the blurred image to minimize a convex cost function. The algorithm proposed in this paper is that the turbulence degraded image is filtered before it passes the recursive filter. The conjugate gradient minimization routine was used for minimization of the NAS-RIF cost function. The algorithm based on the NAS-RIF is used to identify and restore the wind tunnel tested images. The experimental results show that the restoration effect is improved obviously.

  6. From Neutrino Factory to Muon Collider

    SciTech Connect

    Geer, S.; /Fermilab

    2010-01-01

    Both Muon Colliders and Neutrino Factories require a muon source capable of producing and capturing {Omicron}(10{sup 21}) muons/year. This paper reviews the similarities and differences between Neutrino Factory and Muon Collider accelerator complexes, the ongoing R&D needed for a Muon Collider that goes beyond Neutrino Factory R&D, and some thoughts about how a Neutrino Factory on the CERN site might eventually be upgraded to a Muon Collider.

  7. Peptide identification via constrained multi-objective optimization: Pareto-based genetic algorithms

    SciTech Connect

    Malard, Joel M.; Heredia-Langner, Alejandro; Cannon, William R.; Mooney, Ryan W.; Baxter, Douglas J.

    2005-12-10

    Automatic data-base independent peptide identification from collision-induced dissociation tandem mass spectrometry data is made difficult by large plateaus in the fitness landscapes of scoring functions and the fuzzy nature of the constraints that is due to noise in the data. Two different scoring functions are combined into a parallel multi-objective optimization framework.

  8. A novel protein complex identification algorithm based on Connected Affinity Clique Extension (CACE).

    PubMed

    Li, Peng; He, Tingting; Hu, Xiaohua; Zhao, Junmin; Shen, Xianjun; Zhang, Ming; Wang, Yan

    2014-06-01

    A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity which is inferred from protein complexes is interpreted as the reliability and possibility of interaction. The protein interaction network is constructed as a weighted graph, and the weight is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effectively and accurately when compared with other state-of-art algorithms CPM and IPC-MCE. PMID:24803142

  9. Solar collector parameter identification from unsteady data by a discrete-gradient optimization algorithm

    NASA Technical Reports Server (NTRS)

    Hotchkiss, G. B.; Burmeister, L. C.; Bishop, K. A.

    1980-01-01

    A discrete-gradient optimization algorithm is used to identify the parameters in a one-node and a two-node capacitance model of a flat-plate collector. Collector parameters are first obtained by a linear-least-squares fit to steady state data. These parameters, together with the collector heat capacitances, are then determined from unsteady data by use of the discrete-gradient optimization algorithm with less than 10 percent deviation from the steady state determination. All data were obtained in the indoor solar simulator at the NASA Lewis Research Center.

  10. The D0 muon system and early results on its performance

    SciTech Connect

    Hedin, D. . Dept. of Physics)

    1992-10-01

    The D0 detector is a large, general-purpose detector designed to take full advantage of the 2 TeV energy of the Fermilab collider. The design of the experiment emphasizes accurate identification, complete angular acceptance, and precise measurement of the decay products of W and Z bosons: charged leptons (both electrons and muons), quarks and gluons, which emerge as collimated jets of particles, and noninteracting particles, such as neutrinos. The primary physics goals of D0 include searching for new phenomena, such as the top quark or particles outside the standard model, and high-precision studies of the W and Z bosons. In addition, the excellent muon identification will allow the study of b-quark production and decay. This report will describe D0's muon system, give preliminary measurements of chamber and trigger rates, and discuss muon identification.

  11. The D0 muon system and early results on its performance

    SciTech Connect

    Hedin, D.; The D0 Collaboration

    1992-10-01

    The D0 detector is a large, general-purpose detector designed to take full advantage of the 2 TeV energy of the Fermilab collider. The design of the experiment emphasizes accurate identification, complete angular acceptance, and precise measurement of the decay products of W and Z bosons: charged leptons (both electrons and muons), quarks and gluons, which emerge as collimated jets of particles, and noninteracting particles, such as neutrinos. The primary physics goals of D0 include searching for new phenomena, such as the top quark or particles outside the standard model, and high-precision studies of the W and Z bosons. In addition, the excellent muon identification will allow the study of b-quark production and decay. This report will describe D0`s muon system, give preliminary measurements of chamber and trigger rates, and discuss muon identification.

  12. Physical applications of muon catalysis: Muon capture in hydrogen

    NASA Astrophysics Data System (ADS)

    Filchenkov, V. V.

    2016-07-01

    Results of theoretical and experimental research on capture of negative muons in hydrogen are reported with an emphasis on the accompanying phenomenon of muon catalysis in hydrogen and subtleties of the experimental method. A conclusion is drawn that precise determination of the capture rate is important for refining the standard model.

  13. Validation of coding algorithms for the identification of patients with primary biliary cirrhosis using administrative data

    PubMed Central

    Myers, Robert P; Shaheen, Abdel Aziz M; Fong, Andrew; Wan, Alex F; Swain, Mark G; Hilsden, Robert J; Sutherland, Lloyd; Quan, Hude

    2010-01-01

    BACKGROUND: Large-scale epidemiological studies of primary biliary cirrhosis (PBC) have been hindered by difficulties in case ascertainment. OBJECTIVE: To develop coding algorithms for identifying PBC patients using administrative data – a widely available data source. METHODS: Population-based administrative databases were used to identify patients with a diagnosis code for PBC from 1994 to 2002. Coding algorithms for confirmed PBC (two or more of antimitochondrial antibody positivity, cholestatic liver biochemistry and/or compatible liver histology) were derived using chart abstraction data as the reference. Patients with a recorded PBC diagnosis but insufficient confirmatory data were classified as ‘suspected PBC’. RESULTS: Of 189 potential PBC cases, 119 (60%) had confirmed PBC and 28 (14%) had suspected PBC. The optimal algorithm including two or more uses of a PBC code had a sensitivity of 94% (95% CI 71% to 100%) and positive predictive values of 73% (95% CI 61% to 75%) for confirmed PBC, and 89% (95% CI 82% to 94%) for confirmed or suspected PBC. Sensitivity analyses revealed greater accuracy among women, and with the use of multiple data sources and one or more years of data. Inclusion of diagnosis codes for conditions frequently misclassified as PBC did not improve algorithm performance. CONCLUSIONS: Administrative databases can reliably identify patients with PBC and may facilitate epidemiological investigations of this condition. PMID:20352146

  14. A Clustering Algorithm for Ecological Stream Segment Identification from Spatially Extensive Digital Databases

    NASA Astrophysics Data System (ADS)

    Brenden, T. O.; Clark, R. D.; Wiley, M. J.; Seelbach, P. W.; Wang, L.

    2005-05-01

    Remote sensing and geographic information systems have made it possible to attribute variables for streams at increasingly detailed resolutions (e.g., individual river reaches). Nevertheless, management decisions still must be made at large scales because land and stream managers typically lack sufficient resources to manage on an individual reach basis. Managers thus require a method for identifying stream management units that are ecologically similar and that can be expected to respond similarly to management decisions. We have developed a spatially-constrained clustering algorithm that can merge neighboring river reaches with similar ecological characteristics into larger management units. The clustering algorithm is based on the Cluster Affinity Search Technique (CAST), which was developed for clustering gene expression data. Inputs to the clustering algorithm are the neighbor relationships of the reaches that comprise the digital river network, the ecological attributes of the reaches, and an affinity value, which identifies the minimum similarity for merging river reaches. In this presentation, we describe the clustering algorithm in greater detail and contrast its use with other methods (expert opinion, classification approach, regular clustering) for identifying management units using several Michigan watersheds as a backdrop.

  15. Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

    PubMed

    Huang, X N; Ren, H P

    2016-01-01

    Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043

  16. Muon Spin Rotation Spectroscopy - Utilizing Muons in Solid State Physics

    SciTech Connect

    Suter, Andreas

    2012-10-17

    Over the past decades muon spin rotation techniques (mSR) have established themselves as an invaluable tool to study a variety of static and dynamic phenomena in bulk solid state physics and chemistry. Common to all these approaches is that the muon is utilized as a spin microprobe and/or hydrogen-like probe, implanted in the material under investigation. Recent developments extend the range of application to near surface phenomena, thin film and super-lattice studies. After briefly summarizing the production of so called surface muons used for bulk studies, and discussing the principle differences between pulsed and continuous muon beams, the production of keV-energy muon sources will be discussed. A few topical examples from different active research fields will be presented to demonstrate the power of these techniques.

  17. An intense low energy muon source for the muon collider

    SciTech Connect

    Taqqu, D.

    1996-05-01

    A scheme for obtaining an intense source of low energy muons is described. It is based on the production of pions in a high field magnetic bottle trap. By ensuring efficient slowing down and extraction of the decay muons an intense intermediate energy muon beam is obtained. For the specific case of negative muons a novel technique called frictional accumulation provides efficient conversion into a 10 keV{mu}{sup {minus}} beam whose emittance is then reduced in a configuration providing extended frictional cooling. The result is a beam of very small transverse and longitudinal emittance that can be used together with an equivalent {mu}{sup +} beam as compact intense muon source for the {mu}{sup +}{mu}{sup {minus}} collider. A final luminosity around 10{sup 34} cm{sup {minus}2}s{sup {minus}1} is expected to be obtained at 2 TeV. {copyright} {ital 1996 American Institute of Physics.}

  18. An Efficient Algorithm for Stiffness Identification of Truss Structures Through Distributed Local Computation

    NASA Astrophysics Data System (ADS)

    Zhang, G.; Burgueño, R.; Elvin, N. G.

    2010-02-01

    This paper presents an efficient stiffness identification technique for truss structures based on distributed local computation. Sensor nodes on each element are assumed to collect strain data and communicate only with sensors on neighboring elements. This can significantly reduce the energy demand for data transmission and the complexity of transmission protocols, thus enabling a simplified wireless implementation. Element stiffness parameters are identified by simple low order matrix inversion at a local level, which reduces the computational energy, allows for distributed computation and makes parallel data processing possible. The proposed method also permits addressing the problem of missing data or faulty sensors. Numerical examples, with and without missing data, are presented and the element stiffness parameters are accurately identified. The computation efficiency of the proposed method is n2 times higher than previously proposed global damage identification methods.

  19. RBRIdent: An algorithm for improved identification of RNA-binding residues in proteins from primary sequences.

    PubMed

    Xiong, Dapeng; Zeng, Jianyang; Gong, Haipeng

    2015-06-01

    Rapid and correct identification of RNA-binding residues based on the protein primary sequences is of great importance. In most prevalent machine-learning-based identification methods; however, either some features are inefficiently represented, or the redundancy between features is not effectively removed. Both problems may weaken the performance of a classifier system and raise its computational complexity. Here, we addressed the above problems and developed a better classifier (RBRIdent) to identify the RNA-binding residues. In an independent benchmark test, RBRIdent achieved an accuracy of 76.79%, Matthews correlation coefficient of 0.3819 and F-measure of 75.58%, remarkably outperforming all prevalent methods. These results suggest the necessity of proper feature description and the essential role of feature selection in this project. All source data and codes are freely available at http://166.111.152.91/RBRIdent. PMID:25846271

  20. Muon Cooling—emittance exchange

    NASA Astrophysics Data System (ADS)

    Parsa, Zohreh

    2001-05-01

    Muon Cooling is the key factor in building of a Muon collider, (to a less degree) Muon storage ring, and a Neutrino Factory. Muon colliders potential to provide a probe for fundamental particle physics is very interesting, but may take a considerable time to realize, as much more work and study is needed. Utilizing high intensity Muon sources-Neutrino Factories, and other intermediate steps are very important and will greatly expand our abilities and confidence in the credibility of high energy muon colliders. To obtain the needed collider luminosity, the phase-space volume must be greatly reduced within the muon life time. The Ionization cooling is the preferred method used to compress the phase space and reduce the emittance to obtain high luminosity muon beams. We note that, the ionization losses results not only in damping, but also heating. The use of alternating solenoid lattices has been proposed, where the emittance are large. We present an overview of the cooling and discuss formalism, solenoid magnets and some beam dynamics.

  1. High luminosity muon collider design

    SciTech Connect

    Palmer, R.; Gallardo, J.

    1996-10-01

    Muon Colliders have unique technical and physics advantages and disadvantages when compared with both hadron and electron machines. They should be regarded as complementary. Parameters are given of 4 TeV high luminosity {mu}{sup +}{mu}{sup {minus}} collider, and of a 0.5 TeV lower luminosity demonstration machine. We discuss the various systems in such muon colliders.

  2. Advancements in robust algorithm formulation for speaker identification of whispered speech

    NASA Astrophysics Data System (ADS)

    Fan, Xing

    Whispered speech is an alternative speech production mode from neutral speech, which is used by talkers intentionally in natural conversational scenarios to protect privacy and to avoid certain content from being overheard/made public. Due to the profound differences between whispered and neutral speech in production mechanism and the absence of whispered adaptation data, the performance of speaker identification systems trained with neutral speech degrades significantly. This dissertation therefore focuses on developing a robust closed-set speaker recognition system for whispered speech by using no or limited whispered adaptation data from non-target speakers. This dissertation proposes the concept of "High''/"Low'' performance whispered data for the purpose of speaker identification. A variety of acoustic properties are identified that contribute to the quality of whispered data. An acoustic analysis is also conducted to compare the phoneme/speaker dependency of the differences between whispered and neutral data in the feature domain. The observations from those acoustic analysis are new in this area and also serve as a guidance for developing robust speaker identification systems for whispered speech. This dissertation further proposes two systems for speaker identification of whispered speech. One system focuses on front-end processing. A two-dimensional feature space is proposed to search for "Low''-quality performance based whispered utterances and separate feature mapping functions are applied to vowels and consonants respectively in order to retain the speaker's information shared between whispered and neutral speech. The other system focuses on speech-mode-independent model training. The proposed method generates pseudo whispered features from neutral features by using the statistical information contained in a whispered Universal Background model (UBM) trained from extra collected whispered data from non-target speakers. Four modeling methods are proposed

  3. A modified differential evolution algorithm for damage identification in submerged shell structures

    NASA Astrophysics Data System (ADS)

    Reed, H. M.; Nichols, J. M.; Earls, C. J.

    2013-08-01

    Obtaining good estimates of structural parameters from observed data is a particularly challenging task owing to the complex (often multi-modal) likelihood functions that often accompany such problems. As a result, sophisticated optimization routines are typically required to produce maximum likelihood estimates of the desired parameters. Evolutionary algorithms comprise one such approach, whereby nature-inspired mutation and crossover operations allow the sensible exploration of even multi-modal functions, in search of a global maximum. The challenge, of course, is to balance broad coverage in parameter space with the speed required to obtain such estimates. This work focuses directly on this problem by proposing a modified version of the Differential Evolution algorithm. The idea is to adjust both mutation and cross-over rates, during the optimization, in a manner that increases the convergence rate to the desired solution. Performance is demonstrated on the challenging problem of identifying imperfections in submerged shell structures.

  4. Algorithm Summary and Evaluation: Automatic Implementation of Ringdown Analysis for Electromechanical Mode Identification from Phasor Measurements

    SciTech Connect

    Zhou, Ning; Huang, Zhenyu; Tuffner, Francis K.; Jin, Shuangshuang; Lin, Jenglung; Hauer, Matthew L.

    2010-02-28

    Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper develops a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detecting ringdown data, the proposed method helps guarantee that Prony analysis is applied properly and timely on the ringdown data. Thus, the mode estimation results can be performed reliably and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis. In addition, the proposed method is applied to field measurement data from WECC to show the performance of the proposed algorithm.

  5. Muon collider design

    SciTech Connect

    Palmer, R. |; Sessler, A.; Skrinsky, A.

    1996-03-01

    The possibility of muon colliders was introduced by Skrinsky et al., Neuffer, and others. More recently, several workshops and collaboration meetings have greatly increased the level of discussion. In this paper we present scenarios for 4 TeV and 0.5 TeV colliders based on an optimally designed proton source, and for a lower luminosity 0.5 TeV demonstration based on an upgraded version of the AGS. It is assumed that a demonstration version based on upgrades of the FERMILAB machines would also be possible. 53 refs., 25 figs., 8 tabs.

  6. Identification of viruses and viroids by next-generation sequencing and homology-dependent and homology-independent algorithms.

    PubMed

    Wu, Qingfa; Ding, Shou-Wei; Zhang, Yongjiang; Zhu, Shuifang

    2015-01-01

    A fast, accurate, and full indexing of viruses and viroids in a sample for the inspection and quarantine services and disease management is desirable but was unrealistic until recently. This article reviews the rapid and exciting recent progress in the use of next-generation sequencing (NGS) technologies for the identification of viruses and viroids in plants. A total of four viroids/viroid-like RNAs and 49 new plant RNA and DNA viruses from 18 known or unassigned virus families have been identified from plants since 2009. A comparison of enrichment strategies reveals that full indexing of RNA and DNA viruses as well as viroids in a plant sample at single-nucleotide resolution is made possible by one NGS run of total small RNAs, followed by data mining with homology-dependent and homology-independent computational algorithms. Major challenges in the application of NGS technologies to pathogen discovery are discussed. PMID:26047558

  7. Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)

    USGS Publications Warehouse

    Kokaly, R.F.; King, T.V.V.; Hoefen, T.M.

    2011-01-01

    Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager), robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral-feature based analysis of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described in this paper. The core concepts and calculations of MICA are presented. A MICA command file has been developed and applied to map minerals in the full-country coverage of the 2007 Afghanistan HyMap hyperspectral data. ?? 2011 IEEE.

  8. Tail Catcher Muon Tracker For The CALICE Test Beam

    SciTech Connect

    Dyshkant, Alexander

    2006-10-27

    Results on the construction and commissioning of the CALICE Tail-catcher/Muon Tracker (TCMT) are presented. The {approx}1 m3 prototype uses extruded scintillating strips mated to silicon-photomultipliers and is located behind the CALICE hadron calorimeter. The TCMT will provide a snapshot of the tail end of hadron showers, which is crucial to the validation of hadronic Monte Carlo. It will also serve as a prototype muon system for any Linear Collider Detector (ILC) and will facilitate studies of muon tracking and identification within the particle flow reconstruction framework. Additionally, the TCMT will provide valuable practical experience with hadronic leakage and punch-through from thin calorimeters, as are envisaged for the ILC detector, and the impact of the coil in correcting for this leakage.

  9. Identification of anovulation and transient luteal function using a urinary pregnanediol-3-glucuronide ratio algorithm.

    PubMed Central

    Kassam, A; Overstreet, J W; Snow-Harter, C; De Souza, M J; Gold, E B; Lasley, B L

    1996-01-01

    The sensitivity and specificity of a urinary pregnanediol-3-glucuronide (PdG) ratio algorithm to identify anovulatory cycles was studied prospectively in two independent populations of women. Urinary hormone data from the first group was used to develop the algorithm, and data from the second group was used for its validation. PdG ratios were calculated by a cycles method in which daily PdG concentrations indexed by creatinine (CR) from cycle day 11 onward were divided by a baseline PdG (average PdG/Cr concentration for cycle days 6-10). In the interval method, daily PdG/CR concentrations from day 1 onward were divided by baseline PdG (lowest 5-day average of PdG/CR values throughout the collection period). Evaluation of the first study population (n = 6) resulted in cycles with PdG ratios > or = 3 for > or = 3 consecutive days being classified as ovulatory; otherwise they were anovulatory. The sensitivity and specificity of the PdG ratio algorithm to identify anovulatory cycles in the second population were 75% and 89.5%, respectively, for all cycles (n = 88); 50% and 88.3% for first cycles (n = 40) using the cycles method; 75% and 92.2%, respectively, for all cycles (n = 89); and 50% and 94.1% for first cycles (n = 40) using the interval method. The "gold standard" for anovulation was weekly serum samples < or = 2 ng/ml progesterone. The sensitivity values for all cycles and for the first cycle using both methods were underestimated because of apparent misclassification of cycles using serum progesterone due to infrequent blood collection. Blood collection more than once a week would have greatly improved the sensitivity and modestly improved the specificity of the algorithm. The PdG ratio algorithm provides an efficient approach for screening urine samples collected in epidemiologic studies of reproductive health in women. Images Figure 1. A Figure 1. B Figure 1. C Figure 2. A Figure 2. B PMID:8732951

  10. MUON STORAGE RINGS - NEUTRINO FACTORIES

    SciTech Connect

    PARSA,Z.

    2000-05-30

    The concept of a muon storage ring based Neutrino Source (Neutrino Factory) has sparked considerable interest in the High Energy Physics community. Besides providing a first phase of a muon collider facility, it would generate more intense and well collimated neutrino beams than currently available. The BNL-AGS or some other proton driver would provide an intense proton beam that hits a target, produces pions that decay into muons. The muons must be cooled, accelerated and injected into a storage ring with a long straight section where they decay. The decays occurring in the straight sections of the ring would generate neutrino beams that could be directed to detectors located thousands of kilometers away, allowing studies of neutrino oscillations with precisions not currently accessible. For example, with the neutrino source at BNL, detectors at Soudan, Minnesota (1,715 km), and Gran Sasso, Italy (6,527 km) become very interesting possibilities. The feasibility of constructing and operating such a muon-storage-ring based Neutrino-Factory, including geotechnical questions related to building non-planar storage rings (e.g. at 8{degree} angle for BNL-Soudan, and 3{degree} angle for BNL-Gran Sasso) along with the design of the muon capture, cooling, acceleration, and storage ring for such a facility is being explored by the growing Neutrino Factory and Muon Collider Collaboration (NFMCC). The authors present overview of Neutrino Factory concept based on a muon storage ring, its components, physics opportunities, possible upgrade to a full muon collider, latest simulations of front-end, and a new bowtie-muon storage ring design.