NOvA Event Building, Buffering and Data-Driven Triggering From Within the DAQ System

International Nuclear Information System (INIS)

Fischler, M; Rechenmacher, R; Green, C; Kowalkowski, J; Norman, A; Paterno, M

2012-01-01

The NOvA experiment is a long baseline neutrino experiment design to make precision probes of the structure of neutrino mixing. The experiment features a unique deadtimeless data acquisition system that is capable acquiring and building an event data stream from the continuous readout of the more than 360,000 far detector channels. In order to achieve its physics goals the experiment must be able to buffer, correlate and extract the data in this stream with the beam-spills that occur that Fermilab. In addition the NOvA experiment seeks to enhance its data collection efficiencies for rare class of event topologies that are valuable for calibration through the use of data driven triggering. The NOvA-DDT is a prototype Data-Driven Triggering system. NOvA-DDT has been developed using the Fermilab artdaq generic DAQ/Event-building toolkit. This toolkit provides the advantages of sharing online software infrastructure with other Intensity Frontier experiments, and of being able to use any offline analysis module-unchanged-as a component of the online triggering decisions. We have measured the performance and overhead of NOvA-DDT framework using a Hough transform based trigger decision module developed for the NOvA detector to identify cosmic rays. The results of these tests which were run on the NOvA prototype near detector, yielded a mean processing time of 98 ms per event, while consuming only 1/16th of the available processing capacity. These results provide a proof of concept that a NOvA-DDT based processing system is a viable strategy for data acquisition and triggering for the NOvA far detector.

DD4Hep based event reconstruction

CERN Document Server

AUTHOR|(SzGeCERN)683529; Frank, Markus; Gaede, Frank-Dieter; Hynds, Daniel; Lu, Shaojun; Nikiforou, Nikiforos; Petric, Marko; Simoniello, Rosa; Voutsinas, Georgios Gerasimos

The DD4HEP detector description toolkit offers a flexible and easy-to-use solution for the consistent and complete description of particle physics detectors in a single system. The sub-component DDREC provides a dedicated interface to the detector geometry as needed for event reconstruction. With DDREC there is no need to define an additional, separate reconstruction geometry as is often done in HEP, but one can transparently extend the existing detailed simulation model to be also used for the reconstruction. Based on the extension mechanism of DD4HEP, DDREC allows one to attach user defined data structures to detector elements at all levels of the geometry hierarchy. These data structures define a high level view onto the detectors describing their physical properties, such as measurement layers, point resolutions, and cell sizes. For the purpose of charged particle track reconstruction, dedicated surface objects can be attached to every volume in the detector geometry. These surfaces provide the measuremen...

Determination of the τ-lepton reconstruction and identification efficiency using Z → ττ events in first data at ATLAS

International Nuclear Information System (INIS)

Fischer, Gordon

2011-05-01

The Large Hadron Collider (LHC) at CERN started operation in November 2009. At the same time the ATLAS experiment started data taking. Since this time a large number of Z-bosons is produced. An important decay channel of the Z-boson is the decay into two τ -leptons. The large mass of the τ-lepton allows the decay into pions or kaons. In many models considering new physics the τ-lepton is an important final state. The LHC is a proton-proton collider and for that reason, the hadronic τ-lepton decay is difficult to distinguish from QCD multi-jet background. For the selection of hadronically decaying τ-leptons, reconstruction and identification algorithms were developed in order to suppress this background. In order to measure the Z-boson production cross section or possible new particles decaying into τ-leptons, the estimation of the τ-lepton reconstruction and identification efficiency is required. Furthermore, for detector calibration the Z-boson as well as the τ-lepton are helpful probes. In this thesis two methods are discussed which provide an estimation of τ-lepton reconstruction and identification efficiencies from data. The full selection of Z → ττ events including data-driven techniques for background extraction is discussed. The semi-leptonic Z → ττ channel promises a good QCD multi-jet suppression because of the selected additional lepton. For that reason also the leptonically decaying τ-lepton is discussed. The Z-boson production cross section can be calculated with the estimated efficiencies. (orig.) environment. (orig.)

Determination of the {tau}-lepton reconstruction and identification efficiency using Z {yields} {tau}{tau} events in first data at ATLAS

Energy Technology Data Exchange (ETDEWEB)

Fischer, Gordon

2011-10-15

The Large Hadron Collider (LHC) at CERN started operation in November 2009. At the same time the ATLAS experiment started data taking. Since this time a large number of Z-bosons is produced. An important decay channel of the Z-boson is the decay into two {tau} -leptons. The large mass of the {tau}-lepton allows the decay into pions or kaons. In many models considering new physics the {tau}-lepton is an important final state. The LHC is a proton-proton collider and for that reason, the hadronic {tau}-lepton decay is difficult to distinguish from QCD multi-jet background. For the selection of hadronically decaying {tau}-leptons, reconstruction and identification algorithms were developed in order to suppress this background. In order to measure the Z-boson production cross section or possible new particles decaying into {tau}-leptons, the estimation of the {tau}-lepton reconstruction and identification efficiency is required. Furthermore, for detector calibration the Z-boson as well as the {tau}-lepton are helpful probes. In this thesis two methods are discussed which provide an estimation of {tau}-lepton reconstruction and identification efficiencies from data. The full selection of Z {yields} {tau}{tau} events including data-driven techniques for background extraction is discussed. The semi-leptonic Z {yields} {tau}{tau} channel promises a good QCD multi-jet suppression because of the selected additional lepton. For that reason also the leptonically decaying {tau}-lepton is discussed. The Z-boson production cross section can be calculated with the estimated efficiencies. (orig.)

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

Science.gov (United States)

Ramachandran, Rahul; Kulkarni, Ajinkya; Maskey, Manil; Bakare, Rohan; Basyal, Sabin; Li, Xiang; Flynn, Shannon

2014-01-01

Approaches used in Earth science research such as case study analysis and climatology studies involve discovering and gathering diverse data sets and information to support the research goals. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. In cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. This paper presents a specialized search, aggregation and curation tool for Earth science to address these challenges. The search rool automatically creates curated 'Data Albums', aggregated collections of information related to a specific event, containing links to relevant data files [granules] from different instruments, tools and services for visualization and analysis, and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non relevant information and data.

Automated Testing of Event-Driven Applications

DEFF Research Database (Denmark)

Jensen, Casper Svenning

may be tested by selecting an interesting input (i.e. a sequence of events), and deciding if a failure occurs when the selected input is applied to the event-driven application under test. Automated testing promises to reduce the workload for developers by automatically selecting interesting inputs...... and detect failures. However, it is non-trivial to conduct automated testing of event-driven applications because of, for example, infinite input spaces and the absence of specifications of correct application behavior. In this PhD dissertation, we identify a number of specific challenges when conducting...... automated testing of event-driven applications, and we present novel techniques for solving these challenges. First, we present an algorithm for stateless model-checking of event-driven applications with partial-order reduction, and we show how this algorithm may be used to systematically test web...

Data driven processor 'Vertex Trigger' for B experiments

International Nuclear Information System (INIS)

Hartouni, E.P.

1993-01-01

Data Driven Processors (DDP's) are specialized computation engines configured to solve specific numerical problems, such as vertex reconstruction. The architecture of the DDP which is the subject of this talk was designed and implemented by W. Sippach and B.C. Knapp at Nevis Lab. in the early 1980's. This particular implementation allows multiple parallel streams of data to provide input to a heterogenous collection of simple operators whose interconnection form an algorithm. The local data flow control allows this device to execute algorithms extremely quickly provided that care is taken in the layout of the algorithm. I/O rates of several hundred megabytes/second are routinely achieved thus making DDP's attractive candidates for complex online calculations. The original question was open-quote can a DDP reconstruct tracks in a Silicon Vertex Detector, find events with a separated vertex and do it fast enough to be used as an online trigger?close-quote Restating this inquiry as three questions and describing the answers to the questions will be the subject of this talk. The three specific questions are: (1) Can an algorithm be found which reconstructs tracks in a planar geometry and no magnetic field; (2) Can separated vertices be recognized in some way; (3) Can the algorithm be implemented in the Nevis-UMass and DDP and execute in 10-20 μs?

Measurement of the double-vertex reconstruction efficiency of the inclusive vertex finder with accidentally overlapping b-jets in ttbar events

Energy Technology Data Exchange (ETDEWEB)

Marchesini, Ivan; Nowatschin, Dominik; Ott, Jochen; Schmidt, Alexander; Tholen, Heiner [University of Hamburg (Germany)

2015-07-01

In LHC Run II, CMS b-tagging algorithms will employ a new core algorithm, named Inclusive Vertex Finder (IVF). The IVF is designed to perform decay vertex reconstruction of long-lived particles, such as B hadrons. Using only tracks from the silicon tracker, it does not depend on jet clustering and allows for higher reconstruction efficiency of decay vertices, which particularly applies to topologies with two or more decay vertices at low distance. Thus, the IVF will offer increased sensitivity for SM measurements (e.g. angular correlations), but also for the search of BSM physics (e.g. final states with boosted Higgs bosons decaying into b-quarks). For the first time, the dependence of the IVF reconstruction efficiency on the distance of vertices in the η-φ plane is investigated with a data-driven approach. We use a clean set of top quark pair events, selected from data recorded in 2012 in pp-collisions at 8 TeV with the CMS detector, and perform a template fit to a 2D-distribution of the masses of the vertices in an event. Correction factors are derived for the application to simulated events. We conclude that our technique will enable precise calibration of double vertexing with the IVF in the LHC Run II.

Event Reconstruction in the PandaRoot framework

International Nuclear Information System (INIS)

Spataro, Stefano

2012-01-01

The PANDA experiment will study the collisions of beams of anti-protons, with momenta ranging from 2-15 GeV/c, with fixed proton and nuclear targets in the charm energy range, and will be built at the FAIR facility. In preparation for the experiment, the PandaRoot software framework is under development for detector simulation, reconstruction and data analysis, running on an Alien2-based grid. The basic features are handled by the FairRoot framework, based on ROOT and Virtual Monte Carlo, while the PANDA detector specifics and reconstruction code are implemented inside PandaRoot. The realization of Technical Design Reports for the tracking detectors has pushed the finalization of the tracking reconstruction code, which is complete for the Target Spectrometer, and of the analysis tools. Particle Identification algorithms are currently implemented using Bayesian approach and compared to Multivariate Analysis methods. Moreover, the PANDA data acquisition foresees a triggerless operation in which events are not defined by a hardware 1st level trigger decision, but all the signals are stored with time stamps requiring a deconvolution by the software. This has led to a redesign of the software from an event basis to a time-ordered structure. In this contribution, the reconstruction capabilities of the Panda spectrometer will be reported, focusing on the performances of the tracking system and the results for the analysis of physics benchmark channels, as well as the new (and challenging) concept of time-based simulation and its implementation.

Simulation and reconstruction of free-streaming data in CBM

International Nuclear Information System (INIS)

Friese, Volker

2011-01-01

The CBM experiment will investigate heavy-ion reactions at the FAIR facility at unprecedented interaction rates. This implies a novel read-out and data acquisition concept with self-triggered front-end electronics and free-streaming data. Event association must be performed in software on-line, and may require four-dimensional reconstruction routines. In order to study the problem of event association and to develop proper algorithms, simulations must be performed which go beyond the normal event-by-event processing as available from most experimental simulation frameworks. In this article, we discuss the challenges and concepts for the reconstruction of such free-streaming data and present first steps for a time-based simulation which is necessary for the development and validation of the reconstruction algorithms, and which requires modifications to the current software framework FAIRROOT as well as to the data model.

Second-Order Multiagent Systems with Event-Driven Consensus Control

Directory of Open Access Journals (Sweden)

Jiangping Hu

2013-01-01

Full Text Available Event-driven control scheduling strategies for multiagent systems play a key role in future use of embedded microprocessors of limited resources that gather information and actuate the agent control updates. In this paper, a distributed event-driven consensus problem is considered for a multi-agent system with second-order dynamics. Firstly, two kinds of event-driven control laws are, respectively, designed for both leaderless and leader-follower systems. Then, the input-to-state stability of the closed-loop multi-agent system with the proposed event-driven consensus control is analyzed and the bound of the inter-event times is ensured. Finally, some numerical examples are presented to validate the proposed event-driven consensus control.

Time-based Reconstruction of Free-streaming Data in CBM

Science.gov (United States)

Akishina, Valentina; Kisel, Ivan; Vassiliev, Iouri; Zyzak, Maksym

2018-02-01

Traditional latency-limited trigger architectures typical for conventional experiments are inapplicable for the CBM experiment. Instead, CBM will ship and collect time-stamped data into a readout buffer in a form of a time-slice of a certain length and deliver it to a large computer farm, where online event reconstruction and selection will be performed. Grouping measurements into physical collisions must be performed in software and requires reconstruction not only in space, but also in time, the so-called 4-dimensional track reconstruction and event building. The tracks, reconstructed with 4D Cellular Automaton track finder, are combined into event-corresponding clusters according to the estimated time in the target position and the errors, obtained with the Kalman Filter method. The reconstructed events are given as inputs to the KF Particle Finder package for short-lived particle reconstruction. The results of time-based reconstruction of simulated collisions in CBM are presented and discussed in details.

Org.Lcsim: Event Reconstruction in Java

International Nuclear Information System (INIS)

Graf, Norman

2011-01-01

Maximizing the physics performance of detectors being designed for the International Linear Collider, while remaining sensitive to cost constraints, requires a powerful, efficient, and flexible simulation, reconstruction and analysis environment to study the capabilities of a large number of different detector designs. The preparation of Letters Of Intent for the International Linear Collider involved the detailed study of dozens of detector options, layouts and readout technologies; the final physics benchmarking studies required the reconstruction and analysis of hundreds of millions of events. We describe the Java-based software toolkit (org.lcsim) which was used for full event reconstruction and analysis. The components are fully modular and are available for tasks from digitization of tracking detector signals through to cluster finding, pattern recognition, track-fitting, calorimeter clustering, individual particle reconstruction, jet-finding, and analysis. The detector is defined by the same xml input files used for the detector response simulation, ensuring the simulation and reconstruction geometries are always commensurate by construction. We discuss the architecture as well as the performance.

Task-driven image acquisition and reconstruction in cone-beam CT

International Nuclear Information System (INIS)

Gang, Grace J; Stayman, J Webster; Siewerdsen, Jeffrey H; Ehtiati, Tina

2015-01-01

This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d′) is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d′ for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d′ by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the

Vertex Reconstruction and Performance in ATLAS

CERN Document Server

Whitmore, Ben William; The ATLAS collaboration

2017-01-01

Efficient and precise reconstruction of the primary vertices in LHC collisions is essential in both the reconstruction of the full kinematic properties of a hard-scatter event and of soft interactions as a measure of the amount of pile-up. The reconstruction of the primary vertices in the busy, high pile up environment of the LHC is a challenging task. The challenges and novel methods developed by the ATLAS experiment to reconstruct vertices in such environments will be presented. The performance of the current vertexing algorithms using Run-2 data will be presented and compared to results from simulation. Additionally, data-driven methods to evaluate vertex resolution, and details of upgrades to the ATLAS inner detector will be presented.

Sawtooth events and O+ in the plasma sheet and boundary layer: CME- and SIR-driven events

Science.gov (United States)

Lund, E. J.; Nowrouzi, N.; Kistler, L. M.; Cai, X.; Liao, J.

2017-12-01

The role of ionospheric ions in sawtooth events is an open question. Simulations[1,2,3] suggest that O+ from the ionosphere produces a feedback mechanism for driving sawtooth events. However, observational evidence[4,5] suggest that the presence of O+ in the plasma sheet is neither necessary nor sufficient. In this study we investigate whether the solar wind driver of the geomagnetic storm has an effect on the result. Building on an earlier study[4] that used events for which Cluster data is available in the plasma sheet and boundary layer, we perform a superposed epoch analysis for coronal mass ejection (CME) driven storms and streaming interaction region (SIR) driven storms separately, to investigate the hypothesis that ionospheric O+ is an important contributor for CME-driven storms but not SIR-driven storms[2]. [1]O. J. Brambles et al. (2011), Science 332, 1183.[2]O. J. Brambles et al. (2013), JGR 118, 6026.[3]R. H. Varney et al. (2016), JGR 121, 9688.[4]J. Liao et al. (2014), JGR 119, 1572.[5]E. J. Lund et al. (2017), JGR, submitted.

Program package for data preparation of RISK events

International Nuclear Information System (INIS)

Denes, E.; Wagner, I.; Nagy, J.

1980-01-01

A FORTRAN program package written for the CDC-6500 computer is presented. The SMHV program is designed to transform data obtained from events of RISK streamer chamber by means of measuring SAMET or PUOS devices to the HEVAS data tormat format needed by the geometrical reconstruction program. Such a transformation provides the standartization of measurement data procession inside the RISK collaboration and capability of the direct input into program of event geometrical reconstruction registered on a film of RISK streamer chamber

Data logging and online reconstruction in H1

International Nuclear Information System (INIS)

Fuhrmann, P.; Gerhards, R.; Kruener-Marquis, U.; Olsson, J.E.; Szkutnik, Z.

1994-01-01

In spring 1992, the H1 detector at the HERA electron proton collider at DESY came into operation. The high bunch crossing rate and, correspondingly, the large data volumes are placing demanding requirements on the data logging and event reconstruction. Both tasks are performed on an SGI Challenge series computer. This note reviews the development and the experience with the data logging and online reconstruction in H1

Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

Science.gov (United States)

Gang, Grace J; Siewerdsen, Jeffrey H; Stayman, J Webster

2017-12-01

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index ( ) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum by at least 17.8%, but yielded higher over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed . The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.

Prompt data reconstruction at the ATLAS experiment

International Nuclear Information System (INIS)

Andrew Stewart, Graeme; Boyd, Jamie; Unal, Guillaume; Firmino da Costa, João; Tuggle, Joseph

2012-01-01

The ATLAS experiment at the LHC collider recorded more than 5 fb −1 data of pp collisions at a centre-of-mass energy of 7 TeV during 2011. The recorded data are promptly reconstructed in two steps at a large computing farm at CERN to provide fast access to high quality data for physics analysis. In the first step, a subset of the data, corresponding to the express stream and having 10Hz of events, is processed in parallel with data taking. Data quality, detector calibration constants, and the beam spot position are determined using the reconstructed data within 48 hours. In the second step all recorded data are processed with the updated parameters. The LHC significantly increased the instantaneous luminosity and the number of interactions per bunch crossing in 2011; the data recording rate by ATLAS exceeds 400 Hz. To cope with these challenges the performance and reliability of the ATLAS reconstruction software have been improved. In this paper we describe how the prompt data reconstruction system quickly and stably provides high quality data to analysers.

Data driven analysis of rain events: feature extraction, clustering, microphysical /macro physical relationship

Science.gov (United States)

Djallel Dilmi, Mohamed; Mallet, Cécile; Barthes, Laurent; Chazottes, Aymeric

2017-04-01

that a rain time series can be considered by an alternation of independent rain event and no rain period. The five selected feature are used to perform a hierarchical clustering of the events. The well-known division between stratiform and convective events appears clearly. This classification into two classes is then refined in 5 fairly homogeneous subclasses. The data driven analysis performed on whole rain events instead of fixed length samples allows identifying strong relationships between macrophysics (based on rain rate) and microphysics (based on raindrops) features. We show that among the 5 identified subclasses some of them have specific microphysics characteristics. Obtaining information on microphysical characteristics of rainfall events from rain gauges measurement suggests many implications in development of the quantitative precipitation estimation (QPE), for the improvement of rain rate retrieval algorithm in remote sensing context.

Tree-ring based reconstruction of the seasonal timing, major events and origin of rockfall on a case-study slope in the Swiss Alps

Directory of Open Access Journals (Sweden)

D. M. Schneuwly

2008-03-01

Full Text Available Tree-ring analysis has been used to reconstruct 22 years of rockfall behavior on an active rockfall slope near Saas Balen (Swiss Alps. We analyzed 32 severely injured trees (L. decidua, P. abies and P. cembra and investigated cross-sections of 154 wounds.

The intra-annual position of callus tissue and of tangential rows of traumatic resin ducts was determined in order to reconstruct the seasonality of past rockfall events. Results indicate strong intra- and inter-annual variations of rockfall activity, with a peak (76% observed in the dormant season (early October – end of May. Within the growth season, rockfall regularly occurs between the end of May and mid July (21.4%, whereas events later in the season appear to be quite rare (2.6%. Findings suggest that rockfall activity at the study site is driven by annual thawing processes and the circulation of melt water in preexisting fissures. Data also indicate that 43% of all rockfall events occurred in 1995, when two major precipitation events are recorded in nearby meteorological stations. Finally, data on impact angles are in very good agreement with the geomorphic situation in the field.

A distributed real-time system for event-driven control and dynamic data acquisition on a fusion plasma experiment

International Nuclear Information System (INIS)

Sousa, J.; Combo, A.; Batista, A.; Correia, M.; Trotman, D.; Waterhouse, J.; Varandas, C.A.F.

2000-01-01

A distributed real-time trigger and timing system, designed in a tree-type topology and implemented in VME and CAMAC versions, has been developed for a magnetic confinement fusion experiment. It provides sub-microsecond time latencies for the transport of small data objects allowing event-driven discharge control with failure counteraction, dynamic pre-trigger sampling and event recording as well as accurate simultaneous triggers and synchronism on all nodes with acceptable optimality and predictability of timeliness. This paper describes the technical characteristics of the hardware components (central unit composed by one or more reflector crates, event and synchronism reflector cards, event and pulse node module, fan-out and fan-in modules) as well as software for both tests and integration on a global data acquisition system. The results of laboratory operation for several configurations and the overall performance of the system are presented and analysed

Direct reconstruction of parametric images for brain PET with event-by-event motion correction: evaluation in two tracers across count levels

Science.gov (United States)

Germino, Mary; Gallezot, Jean-Dominque; Yan, Jianhua; Carson, Richard E.

2017-07-01

Parametric images for dynamic positron emission tomography (PET) are typically generated by an indirect method, i.e. reconstructing a time series of emission images, then fitting a kinetic model to each voxel time activity curve. Alternatively, ‘direct reconstruction’, incorporates the kinetic model into the reconstruction algorithm itself, directly producing parametric images from projection data. Direct reconstruction has been shown to achieve parametric images with lower standard error than the indirect method. Here, we present direct reconstruction for brain PET using event-by-event motion correction of list-mode data, applied to two tracers. Event-by-event motion correction was implemented for direct reconstruction in the Parametric Motion-compensation OSEM List-mode Algorithm for Resolution-recovery reconstruction. The direct implementation was tested on simulated and human datasets with tracers [11C]AFM (serotonin transporter) and [11C]UCB-J (synaptic density), which follow the 1-tissue compartment model. Rigid head motion was tracked with the Vicra system. Parametric images of K 1 and distribution volume (V T  =  K 1/k 2) were compared to those generated by the indirect method by regional coefficient of variation (CoV). Performance across count levels was assessed using sub-sampled datasets. For simulated and real datasets at high counts, the two methods estimated K 1 and V T with comparable accuracy. At lower count levels, the direct method was substantially more robust to outliers than the indirect method. Compared to the indirect method, direct reconstruction reduced regional K 1 CoV by 35-48% (simulated dataset), 39-43% ([11C]AFM dataset) and 30-36% ([11C]UCB-J dataset) across count levels (averaged over regions at matched iteration); V T CoV was reduced by 51-58%, 54-60% and 30-46%, respectively. Motion correction played an important role in the dataset with larger motion: correction increased regional V T by 51% on average in the [11C

$xy$ Position Reconstruction in DarkSide-50

Energy Technology Data Exchange (ETDEWEB)

Brodsky, Jason Philip [Princeton Univ., NJ (United States)

2015-01-01

The DarkSide-50 experiment seeks to directly detect dark matter in a liquid argon time projection chamber. In this dissertation, I present an algorithm of my design that determines the position of particle interactions with the liquid argon. This position reconstruction algorithm will be used by DarkSide-50 to reject backgrounds, particularly backgrounds from radioactive elements on the detector surface. The position reconstruction algorithm functions by constructing light response functions (LRFs) that map locations in the detector to the expected distribution of signal in DarkSide-50's 38 photomultiplier tubes. Accurate LRFs cannot be produced by simulations of DarkSide-50's optics because such simulations are known to be awed. Instead, this algorithm constructs LRFs using an iterative process driven by data. Initial, awed LRFs are produced using simulated events but then used to produce new LRFs from data events. Multiple generations of LRFs are created from data with each generation driven to better satisfy a known feature of the detector: the dominant argon-39 background is uniformly distributed. I also discuss a method of discriminating against surface background as an alternative to the common approach of ducialization. This method considers the di erence in goodnessof- t between the best- t reconstructed position and the best- t position at the detector's surface. I conclude by presenting results on the performance and validity of this algorithm, including some discussion of reconstruction errors.

Event Reconstruction in the NOvA Experiment

Energy Technology Data Exchange (ETDEWEB)

Behera, Biswaranjan [Indian Inst. Tech., Hyderabad; Davies, Gavin [Indiana U.; Psihas, Fernanda [Indiana U.

2017-10-10

The NOvA experiment observes oscillations in two channels (electron-neutrino appearance and muon-neutrino disappearance) using a predominantly muon-neutrino NuMI beam. The Near Detector records multiple overlapping neutrino interactions in each event and the Far Detector has a large background of cosmic rays due to being located on the surface. The oscillation analyses rely on the accurate reconstruction of neutrino interactions in order to precisely measure the neutrino energy and identify the neutrino flavor and interaction mode. Similarly, measurements of neutrino cross sections using the Near Detector require accurate identification of the particle content of each interaction. A series of pattern recognition techniques have been developed to split event records into individual spatially and temporally separated interactions, to estimate the interaction vertex, and to isolate and classify individual particles within the event. This combination of methods to achieve full event reconstruction in the NOvA detectors has discussed.

Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network

CERN Document Server

Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel

2016-01-01

We present an iterative and incremental development methodology for simulation models in network engineering projects. Driven by the DEVS (Discrete Event Systems Specification) formal framework for modeling and simulation we assist network design, test, analysis and optimization processes. A practical application of the methodology is presented for a case study in the ATLAS particle physics detector, the largest scientific experiment built by man where scientists around the globe search for answers about the origins of the universe. The ATLAS data network convey real-time information produced by physics detectors as beams of particles collide. The produced sub-atomic evidences must be filtered and recorded for further offline scrutiny. Due to the criticality of the transported data, networks and applications undergo careful engineering processes with stringent quality of service requirements. A tight project schedule imposes time pressure on design decisions, while rapid technology evolution widens the palett...

THE USE OF EVENT DATA RECORDER (EDR – BLACK BOX

Directory of Open Access Journals (Sweden)

Gabriel Nowacki

2014-03-01

Full Text Available The paper refers to the registration of road events by a modern device called EDR – black box for all types of the motor vehicles. The device records data concerning vehicle’s technical condition, the way it was driven and RTS. The recorder may be used in private and commercial cars, taxies, buses and trucks. The recorder may serve the purpose of a neutral witness for the police, courts and insurance firms, for which it will facilitate making the reconstruction of the road accidents events and will provide a proof for those who caused them. The device will bring efficient driving, which will significantly contribute to decreasing the number of road accidents and limiting the environmental pollution. In the end in the last year German parliament backed a proposal to the European Commission to put black boxes, which gather information from vehicles involved in accidents, in all the new cars from 2015 on.

Data-driven sensor placement from coherent fluid structures

Science.gov (United States)

Manohar, Krithika; Kaiser, Eurika; Brunton, Bingni W.; Kutz, J. Nathan; Brunton, Steven L.

2017-11-01

Optimal sensor placement is a central challenge in the prediction, estimation and control of fluid flows. We reinterpret sensor placement as optimizing discrete samples of coherent fluid structures for full state reconstruction. This permits a drastic reduction in the number of sensors required for faithful reconstruction, since complex fluid interactions can often be described by a small number of coherent structures. Our work optimizes point sensors using the pivoted matrix QR factorization to sample coherent structures directly computed from flow data. We apply this sampling technique in conjunction with various data-driven modal identification methods, including the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). In contrast to POD-based sensors, DMD demonstrably enables the optimization of sensors for prediction in systems exhibiting multiple scales of dynamics. Finally, reconstruction accuracy from pivot sensors is shown to be competitive with sensors obtained using traditional computationally prohibitive optimization methods.

Muon Reconstruction and Identification for the Event Filter of the ATLAS experiment

CERN Document Server

Ventura, A; Armstrong, S; Baines, J T M; Bee, C P; Bellomo, M; Biglietti, M; Bogaerts, J A C; Bosman, M; Carlino, G; Caron, B; Casado, M P; Cataldi, G; Cavalli, D; Comune, G; Conde, P; Conventi, F; Crone, G; Damazio, D; De Santo, A; Díaz-Gómez, M; Di Mattia, A; Ellis, Nick; Emeliyanov, D; Epp, B; Falciano, S; Garitaonandia, H; George, S; Ghete, V; Goncalo, R; Gorini, E; Grancagnolo, S; Haller, J; Kabana, S; Khomich, A; Kilvington, G; Kirk, N; Konstantinidis, N P; Kootz, A; Lankford, A J; Lowe, A; Luminari, L; Maeno, T; Masik, J; Meessen, C; Mello, A G; Moore, R; Morettini, P; Negri, A; Nikitin, N; Nisati, A; Osuna, C; Padilla, C; Panikashvili, N; Parodi, F; Pasqualucci, E; Pérez-Réale, V; Pinfold, J L; Pinto, P; Primavera, M; Qian, Z; Resconi, S; Rosati, S; Sánchez, C; Santamarina-Rios, C; Scannicchio, D A; Schiavi, C; Segura, E; De Seixas, J M; Sidoti, A; Siragusa, G; Sivoklokov, S Yu; Sobreira, A; Soluk, R A; Spagnolo, S; Stefanidis, E; Sushkov, S; Sutton, M; Tapprogge, S; Tarem, S; Thomas, E; Touchard, F; Usai, G; Venda-Pinto, B; Vercesi, V; Wengler, T; Werner, P; Wheeler, S J; Wickens, F J; Wiedenmann, W; Wielers, M; Zobernig, G; 9th ICATPP Conference on Astroparticle, Particle, Space Physics, Detectors and Medical Physics Applications

2005-01-01

The ATLAS Trigger requires high efficiency and selectivity in order to keep the full physics potential of the experiment and to reject uninteresting processes from the 40 MHz event production rate of the LHC. These goals are achieved with a trigger composed of three sequential levels of increasing accuracy that have to reduce the output event rate down to ~100 Hz. This work focuses on muon reconstruction and identification for the third level (Event Filter), for which specific algorithms from the off-line environment have been adapted to work in the trigger framework. Two different strategies for accessing data (wrapped and seeded modes) are described and their reconstruction potential is then shown in terms of efficiencies, resolutions and fake muon rejection power.

CLARA: CLAS12 Reconstruction and Analysis Framework

Energy Technology Data Exchange (ETDEWEB)

Gyurjyan, Vardan [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Matta, Sebastian Mancilla [Santa Maria U., Valparaiso, Chile; Oyarzun, Ricardo [Santa Maria U., Valparaiso, Chile

2016-11-01

In this paper we present SOA based CLAS12 event Reconstruction and Analyses (CLARA) framework. CLARA design focus is on two main traits: real-time data stream processing, and service-oriented architecture (SOA) in a flow based programming (FBP) paradigm. Data driven and data centric architecture of CLARA presents an environment for developing agile, elastic, multilingual data processing applications. The CLARA framework presents solutions capable of processing large volumes of data interactively and substantially faster than batch systems.

Development of a data-driven algorithm to determine the W+jets background in t anti t events in ATLAS

Energy Technology Data Exchange (ETDEWEB)

Mehlhase, Sascha

2010-07-12

The physics of the top quark is one of the key components in the physics programme of the ATLAS experiment at the Large Hadron Collider at CERN. In this thesis, general studies of the jet trigger performance for top quark events using fully simulated Monte Carlo samples are presented and two data-driven techniques to estimate the multi-jet trigger efficiency and the W+Jets background in top pair events are introduced to the ATLAS experiment. In a tag-and-probe based method, using a simple and common event selection and a high transverse momentum lepton as tag object, the possibility to estimate the multijet trigger efficiency from data in ATLAS is investigated and it is shown that the method is capable of estimating the efficiency without introducing any significant bias by the given tag selection. In the second data-driven analysis a new method to estimate the W+Jets background in a top-pair event selection is introduced to ATLAS. By defining signal and background dominated regions by means of the jet multiplicity and the pseudo-rapidity distribution of the lepton in the event, the W+Jets contribution is extrapolated from the background dominated into the signal dominated region. The method is found to estimate the given background contribution as a function of the jet multiplicity with an accuracy of about 25% for most of the top dominated region with an integrated luminosity of above 100 pb{sup -1} at {radical}(s) = 10 TeV. This thesis also covers a study summarising the thermal behaviour and expected performance of the Pixel Detector of ATLAS. All measurements performed during the commissioning phase of 2008/09 yield results within the specification of the system and the performance is expected to stay within those even after several years of running under LHC conditions. (orig.)

Development of a data-driven algorithm to determine the W+jets background in t anti t events in ATLAS

International Nuclear Information System (INIS)

Mehlhase, Sascha

2010-01-01

The physics of the top quark is one of the key components in the physics programme of the ATLAS experiment at the Large Hadron Collider at CERN. In this thesis, general studies of the jet trigger performance for top quark events using fully simulated Monte Carlo samples are presented and two data-driven techniques to estimate the multi-jet trigger efficiency and the W+Jets background in top pair events are introduced to the ATLAS experiment. In a tag-and-probe based method, using a simple and common event selection and a high transverse momentum lepton as tag object, the possibility to estimate the multijet trigger efficiency from data in ATLAS is investigated and it is shown that the method is capable of estimating the efficiency without introducing any significant bias by the given tag selection. In the second data-driven analysis a new method to estimate the W+Jets background in a top-pair event selection is introduced to ATLAS. By defining signal and background dominated regions by means of the jet multiplicity and the pseudo-rapidity distribution of the lepton in the event, the W+Jets contribution is extrapolated from the background dominated into the signal dominated region. The method is found to estimate the given background contribution as a function of the jet multiplicity with an accuracy of about 25% for most of the top dominated region with an integrated luminosity of above 100 pb -1 at √(s) = 10 TeV. This thesis also covers a study summarising the thermal behaviour and expected performance of the Pixel Detector of ATLAS. All measurements performed during the commissioning phase of 2008/09 yield results within the specification of the system and the performance is expected to stay within those even after several years of running under LHC conditions. (orig.)

Data acquisition, reconstruction, and display

International Nuclear Information System (INIS)

Huesman, R.H.

1981-01-01

A special emphasis of the Research Medicine program is the development of methods for acquiring and manipulating data from the Donner 280-crystal positron emission tomograph. This past year, development of a system capable of taking 1 million events per second while simultaneously correcting for unwanted accidental coincidence events was completed. The system permits the simultaneous acquisition of data for eight different time-slices of the cardiac cycle. A microprocessor responds to the patient's electrocardiogram (EKG) signal, routing data to the histogram memory corresponding to the phase of the cardiac cycle indicated by the signal. Additional work completed this year includes quantitation of the signal-to-noise ratio to be expected when imaging the human head. Effort is continuing on the more complicated problem of noise propagation in reconstructions of the human thorax

Analytic 3D image reconstruction using all detected events

International Nuclear Information System (INIS)

Kinahan, P.E.; Rogers, J.G.

1988-11-01

We present the results of testing a previously presented algorithm for three-dimensional image reconstruction that uses all gamma-ray coincidence events detected by a PET volume-imaging scanner. By using two iterations of an analytic filter-backprojection method, the algorithm is not constrained by the requirement of a spatially invariant detector point spread function, which limits normal analytic techniques. Removing this constraint allows the incorporation of all detected events, regardless of orientation, which improves the statistical quality of the final reconstructed image

Event reconstruction with MarlinReco at the International Linear ...

Indian Academy of Sciences (India)

event reconstruction system, based on the particle flow concept. Version 00-02 contains the following processors: Tracker hit digitisation: For the vertex system there are two different digitisers available. A simple digitiser translates simulated .... of showers in the calorimeter. The Fortran-based simulation and reconstruction.

Primary Vertex Reconstruction at the ATLAS Experiment

CERN Document Server

Grimm, Kathryn; The ATLAS collaboration

2016-01-01

Efficient and precise reconstruction of the primary vertex in an LHC collision is essential in both the reconstruction of the full kinematic properties of a hard-scatter event and of soft interactions as a measure of the amount of pile-up. The reconstruction of primary vertices in the busy, high pile-up environment of Run-2 of the LHC is a challenging task. New methods have been developed by the ATLAS experiment to reconstruct vertices in such environments. Advances in vertex seeding include methods taken from medical imaging, which allow for reconstruction of multiple vertices with small spatial separation. The adoption of this new seeding algorithm within the ATLAS adaptive vertex finding and fitting procedure will be discussed, and the first results of the new techniques from Run-2 data will be presented. Additionally, data-driven methods to evaluate vertex resolution will be presented with special focus on correct methods to evaluate the effect of the beam spot constraint; results from these methods in Ru...

Cellular automaton and elastic net for event reconstruction in the NEMO-2 experiment

International Nuclear Information System (INIS)

Kisel, I.; Kovalenko, V.; Laplanche, F.

1997-01-01

A cellular automaton for track searching combined with an elastic net for charged particle trajectory fitting is presented. The advantages of the methods are: the simplicity of the algorithms, the fast and stable convergency to real tracks, and a good reconstruction efficiency. The combination of techniques have been used with success for event reconstruction on the data of the NEMO-2 double-beta (ββ) decay experiments. (orig.)

How to integrate proxy data from two informants in life event assessment in psychological autopsy.

Science.gov (United States)

Zhang, Jie; Wang, Youqing; Fang, Le

2018-04-27

Life event assessment is an important part in psychological autopsy, and how to integrate its proxy data from two informants is a major methodological issue which needs solving. Totally 416 living subjects and their two informants were interviewed by psychological autopsy, and life events were assessed with Paykel's Interview for Recent Life Events. Validities of integrated proxy data using six psychological autopsy information reconstruction methods were evaluated, with living subjects' self-reports used as gold-standard criteria. For all the life events, average value of Youden Indexes for proxy data by type C information reconstruction method (choosing positive value from two informants) was larger than other five methods'. For family life related events, proxy data by type 1st information reconstruction method were not significantly different from living subjects' self-reports (P = 0.828). For all other life events, proxy data by type C information reconstruction method were not significantly different from the gold-standard. Choosing positive value is a relatively better method for integrating dichotomous (positive vs. negative) proxy data from two informants in life event assessment in psychological autopsy, except for family life related events. In that case, using information provided by 1st informants (mainly family member) is recommended.

An Operational Implementation of a CBRN Sensor-Driven Modeling Paradigm for Stochastic Event Reconstruction

Science.gov (United States)

2010-05-01

operationnelle pour la reconstruction de sources, au systeme de model- isation urbaine multi echelle integre mis en oeuvre dans !’infrastructure informatique...or urbanLS, respectively. However, for the Bayesian inversion of concentration data to be practical , fast and efficient techniques are required for...sensitivity and/or uncertainty analysis methods that have been used to quantify and reduce them. In this paper , all the various error contributions to

Parallel computing for event reconstruction in high-energy physics

International Nuclear Information System (INIS)

Wolbers, S.

1993-01-01

Parallel computing has been recognized as a solution to large computing problems. In High Energy Physics offline event reconstruction of detector data is a very large computing problem that has been solved with parallel computing techniques. A review of the parallel programming package CPS (Cooperative Processes Software) developed and used at Fermilab for offline reconstruction of Terabytes of data requiring the delivery of hundreds of Vax-Years per experiment is given. The Fermilab UNIX farms, consisting of 180 Silicon Graphics workstations and 144 IBM RS6000 workstations, are used to provide the computing power for the experiments. Fermilab has had a long history of providing production parallel computing starting with the ACP (Advanced Computer Project) Farms in 1986. The Fermilab UNIX Farms have been in production for over 2 years with 24 hour/day service to experimental user groups. Additional tools for management, control and monitoring these large systems will be described. Possible future directions for parallel computing in High Energy Physics will be given

Synchronous diversification of Sulawesi's iconic artiodactyls driven by recent geological events.

Science.gov (United States)

Frantz, Laurent A F; Rudzinski, Anna; Nugraha, Abang Mansyursyah Surya; Evin, Allowen; Burton, James; Hulme-Beaman, Ardern; Linderholm, Anna; Barnett, Ross; Vega, Rodrigo; Irving-Pease, Evan K; Haile, James; Allen, Richard; Leus, Kristin; Shephard, Jill; Hillyer, Mia; Gillemot, Sarah; van den Hurk, Jeroen; Ogle, Sharron; Atofanei, Cristina; Thomas, Mark G; Johansson, Friederike; Mustari, Abdul Haris; Williams, John; Mohamad, Kusdiantoro; Damayanti, Chandramaya Siska; Wiryadi, Ita Djuwita; Obbles, Dagmar; Mona, Stephano; Day, Hally; Yasin, Muhammad; Meker, Stefan; McGuire, Jimmy A; Evans, Ben J; von Rintelen, Thomas; Ho, Simon Y W; Searle, Jeremy B; Kitchener, Andrew C; Macdonald, Alastair A; Shaw, Darren J; Hall, Robert; Galbusera, Peter; Larson, Greger

2018-04-11

The high degree of endemism on Sulawesi has previously been suggested to have vicariant origins, dating back to 40 Ma. Recent studies, however, suggest that much of Sulawesi's fauna assembled over the last 15 Myr. Here, we test the hypothesis that more recent uplift of previously submerged portions of land on Sulawesi promoted diversification and that much of its faunal assemblage is much younger than the island itself. To do so, we combined palaeogeographical reconstructions with genetic and morphometric datasets derived from Sulawesi's three largest mammals: the babirusa, anoa and Sulawesi warty pig. Our results indicate that although these species most likely colonized the area that is now Sulawesi at different times (14 Ma to 2-3 Ma), they experienced an almost synchronous expansion from the central part of the island. Geological reconstructions indicate that this area was above sea level for most of the last 4 Myr, unlike most parts of the island. We conclude that emergence of land on Sulawesi (approx. 1-2 Myr) may have allowed species to expand synchronously. Altogether, our results indicate that the establishment of the highly endemic faunal assemblage on Sulawesi was driven by geological events over the last few million years. © 2018 The Authors.

Dynamically adaptive data-driven simulation of extreme hydrological flows

Science.gov (United States)

Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

2018-02-01

Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

Dynamically adaptive data-driven simulation of extreme hydrological flows

KAUST Repository

Kumar Jain, Pushkar

2017-12-27

Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

Event-driven processing for hardware-efficient neural spike sorting

Science.gov (United States)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

NEBULAS A High Performance Data-Driven Event-Building Architecture based on an Asynchronous Self-Routing Packet-Switching Network

CERN Multimedia

Costa, M; Letheren, M; Djidi, K; Gustafsson, L; Lazraq, T; Minerskjold, M; Tenhunen, H; Manabe, A; Nomachi, M; Watase, Y

2002-01-01

RD31 : The project is evaluating a new approach to event building for level-two and level-three processor farms at high rate experiments. It is based on the use of commercial switching fabrics to replace the traditional bus-based architectures used in most previous data acquisition sytems. Switching fabrics permit the construction of parallel, expandable, hardware-driven event builders that can deliver higher aggregate throughput than the bus-based architectures. A standard industrial switching fabric technology is being evaluated. It is based on Asynchronous Transfer Mode (ATM) packet-switching network technology. Commercial, expandable ATM switching fabrics and processor interfaces, now being developed for the future Broadband ISDN infrastructure, could form the basis of an implementation. The goals of the project are to demonstrate the viability of this approach, to evaluate the trade-offs involved in make versus buy options, to study the interfacing of the physics frontend data buffers to such a fabric, a...

Towards community-driven paleogeographic reconstructions: integrating open-access paleogeographic and paleobiology data with plate tectonics

Directory of Open Access Journals (Sweden)

N. Wright

2013-03-01

Full Text Available A variety of paleogeographic reconstructions have been published, with applications ranging from paleoclimate, ocean circulation and faunal radiation models to resource exploration; yet their uncertainties remain difficult to assess as they are generally presented as low-resolution static maps. We present a methodology for ground-truthing the digital Palaeogeographic Atlas of Australia by linking the GPlates plate reconstruction tool to the global Paleobiology Database and a Phanerozoic plate motion model. We develop a spatio-temporal data mining workflow to validate the Phanerozoic Palaeogeographic Atlas of Australia with paleoenvironments derived from fossil data. While there is general agreement between fossil data and the paleogeographic model, the methodology highlights key inconsistencies. The Early Devonian paleogeographic model of southeastern Australia insufficiently describes the Emsian inundation that may be refined using biofacies distributions. Additionally, the paleogeographic model and fossil data can be used to strengthen numerical models, such as the dynamic topography and the associated inundation of eastern Australia during the Cretaceous. Although paleobiology data provide constraints only for paleoenvironments with high preservation potential of organisms, our approach enables the use of additional proxy data to generate improved paleogeographic reconstructions.

Dynamically adaptive data-driven simulation of extreme hydrological flows

KAUST Repository

Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

2017-01-01

evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses

Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves.

Science.gov (United States)

Guyot, Patricia; Ades, A E; Ouwens, Mario J N M; Welton, Nicky J

2012-02-01

The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated. We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios) with statistics based on repeated reconstructions by multiple observers. The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported. The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.

State-of-the-art Machine Learning in event reconstruction and object identification

CERN Document Server

Kagan, Michael; The ATLAS collaboration

2017-01-01

Recent advances in deep learning have seen great success in the realms of computer vision, natural language processing, and broadly in data science. However, these new ideas are only just beginning to be applied to the analysis of High Energy Physics data. In this talk, I will discuss developments in the application of computer vision and deep learning techniques for event reconstruction and particle identification for the LHC .

Optimizing access to conditions data in ATLAS event data processing

CERN Document Server

Rinaldi, Lorenzo; The ATLAS collaboration

2018-01-01

The processing of ATLAS event data requires access to conditions data which is stored in database systems. This data includes, for example alignment, calibration, and configuration information that may be characterized by large volumes, diverse content, and/or information which evolves over time as refinements are made in those conditions. Additional layers of complexity are added by the need to provide this information across the world-wide ATLAS computing grid and the sheer number of simultaneously executing processes on the grid, each demanding a unique set of conditions to proceed. Distributing this data to all the processes that require it in an efficient manner has proven to be an increasing challenge with the growing needs and number of event-wise tasks. In this presentation, we briefly describe the systems in which we have collected information about the use of conditions in event data processing. We then proceed to explain how this information has been used to refine not only reconstruction software ...

Data-driven motion correction in brain SPECT

International Nuclear Information System (INIS)

Kyme, A.Z.; Hutton, B.F.; Hatton, R.L.; Skerrett, D.W.

2002-01-01

Patient motion can cause image artifacts in SPECT despite restraining measures. Data-driven detection and correction of motion can be achieved by comparison of acquired data with the forward-projections. By optimising the orientation of the reconstruction, parameters can be obtained for each misaligned projection and applied to update this volume using a 3D reconstruction algorithm. Digital and physical phantom validation was performed to investigate this approach. Noisy projection data simulating at least one fully 3D patient head movement during acquisition were constructed by projecting the digital Huffman brain phantom at various orientations. Motion correction was applied to the reconstructed studies. The importance of including attenuation effects in the estimation of motion and the need for implementing an iterated correction were assessed in the process. Correction success was assessed visually for artifact reduction, and quantitatively using a mean square difference (MSD) measure. Physical Huffman phantom studies with deliberate movements introduced during the acquisition were also acquired and motion corrected. Effective artifact reduction in the simulated corrupt studies was achieved by motion correction. Typically the MSD ratio between the corrected and reference studies compared to the corrupted and reference studies was > 2. Motion correction could be achieved without inclusion of attenuation effects in the motion estimation stage, providing simpler implementation and greater efficiency. Moreover the additional improvement with multiple iterations of the approach was small. Improvement was also observed in the physical phantom data, though the technique appeared limited here by an object symmetry. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

Methods of reconstruction of multi-particle events in the new coordinate-tracking setup

Science.gov (United States)

Vorobyev, V. S.; Shutenko, V. V.; Zadeba, E. A.

2018-01-01

At the Unique Scientific Facility NEVOD (MEPhI), a large coordinate-tracking detector based on drift chambers for investigations of muon bundles generated by ultrahigh energy primary cosmic rays is being developed. One of the main characteristics of the bundle is muon multiplicity. Three methods of reconstruction of multiple events were investigated: the sequential search method, method of finding the straight line and method of histograms. The last method determines the number of tracks with the same zenith angle in the event. It is most suitable for the determination of muon multiplicity: because of a large distance to the point of generation of muons, their trajectories are quasiparallel. The paper presents results of application of three reconstruction methods to data from the experiment, and also first results of the detector operation.

Particle-flow reconstruction and global event description with the CMS detector

Energy Technology Data Exchange (ETDEWEB)

Sirunyan, Albert M; et al.

2017-06-15

The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic tau decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8 TeV show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions.

Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

Directory of Open Access Journals (Sweden)

Guyot Patricia

2012-02-01

Full Text Available Abstract Background The results of Randomized Controlled Trials (RCTs on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated. Methods We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios with statistics based on repeated reconstructions by multiple observers. Results The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported. Conclusion The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.

Supporting Beacon and Event-Driven Messages in Vehicular Platoons through Token-Based Strategies.

Science.gov (United States)

Balador, Ali; Uhlemann, Elisabeth; Calafate, Carlos T; Cano, Juan-Carlos

2018-03-23

Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC) method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications.

Supporting Beacon and Event-Driven Messages in Vehicular Platoons through Token-Based Strategies

Directory of Open Access Journals (Sweden)

Ali Balador

2018-03-01

Full Text Available Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications.

Live event reconstruction in an optically read out GEM-based TPC

Science.gov (United States)

Brunbauer, F. M.; Galgóczi, G.; Gonzalez Diaz, D.; Oliveri, E.; Resnati, F.; Ropelewski, L.; Streli, C.; Thuiner, P.; van Stenis, M.

2018-04-01

Combining strong signal amplification made possible by Gaseous Electron Multipliers (GEMs) with the high spatial resolution provided by optical readout, highly performing radiation detectors can be realized. An optically read out GEM-based Time Projection Chamber (TPC) is presented. The device permits 3D track reconstruction by combining the 2D projections obtained with a CCD camera with timing information from a photomultiplier tube. Owing to the intuitive 2D representation of the tracks in the images and to automated control, data acquisition and event reconstruction algorithms, the optically read out TPC permits live display of reconstructed tracks in three dimensions. An Ar/CF4 (80/20%) gas mixture was used to maximize scintillation yield in the visible wavelength region matching the quantum efficiency of the camera. The device is integrated in a UHV-grade vessel allowing for precise control of the gas composition and purity. Long term studies in sealed mode operation revealed a minor decrease in the scintillation light intensity.

Practical aspects of data-driven motion correction approach for brain SPECT

International Nuclear Information System (INIS)

Kyme, A.Z.; Hutton, B.F.; Hatton, R.L.; Skerrett, D.; Barnden, L.

2002-01-01

Full text: Patient motion can cause image artifacts in SPECT despite restraining measures. Data-driven detection and correction of motion can be achieved by comparison of acquired data with the forward-projections. By optimising the orientation of a partial reconstruction, parameters can be obtained for each misaligned projection and applied to update this volume using a 3D reconstruction algorithm. Phantom validation was performed to explore practical aspects of this approach. Noisy projection datasets simulating a patient undergoing at least one fully 3D movement during acquisition were compiled from various projections of the digital Hoffman brain phantom. Motion correction was then applied to the reconstructed studies. Correction success was assessed visually and quantitatively. Resilience with respect to subset order and missing data in the reconstruction and updating stages, detector geometry considerations, and the need for implementing an iterated correction were assessed in the process. Effective correction of the corrupted studies was achieved. Visually, artifactual regions in the reconstructed slices were suppressed and/or removed. Typically the ratio of mean square difference between the corrected and reference studies compared to that between the corrupted and reference studies was > 2. Although components of the motions are missed using a single-head implementation, improvement was still evident in the correction. The need for multiple iterations in the approach was small due to the bulk of misalignment errors being corrected in the first pass. Dispersion of subsets for reconstructing and updating the partial reconstruction appears to give optimal correction. Further validation is underway using triple-head physical phantom data. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

Strategies and knowledge used when reconstructing the dates of autobiographical events

DEFF Research Database (Denmark)

Holm, Tine; Thomsen, Dorthe Kirkegaard

Strategies and knowledge used when reconstructing the dates of autobiographical events. Tine Holm and Dorthe Kierkegaard Thomsen Individuals rarely remember the dates of specific memories. Rather they reconstruct dates using a variety of strategies and knowledge. In this study, we examined how...... often individuals use and combine different types of strategies and knowledge. Forty-five participants were each presented with diary descriptions of approximately 42 events from their first term at university that they had written 3 ½ years prior and were asked to date remembered events while...... they thought out loud. The results revealed that participants most frequently used period knowledge as a strategy in dating events. Other frequently used strategies were temporal schemas and temporal landmarks. Participants often combined strategies. Most frequently they combined period knowledge and temporal...

Event-driven simulation of neural population synchronization facilitated by electrical coupling.

Science.gov (United States)

Carrillo, Richard R; Ros, Eduardo; Barbour, Boris; Boucheny, Christian; Coenen, Olivier

2007-02-01

Most neural communication and processing tasks are driven by spikes. This has enabled the application of the event-driven simulation schemes. However the simulation of spiking neural networks based on complex models that cannot be simplified to analytical expressions (requiring numerical calculation) is very time consuming. Here we describe briefly an event-driven simulation scheme that uses pre-calculated table-based neuron characterizations to avoid numerical calculations during a network simulation, allowing the simulation of large-scale neural systems. More concretely we explain how electrical coupling can be simulated efficiently within this computation scheme, reproducing synchronization processes observed in detailed simulations of neural populations.

A reconstructed melanoma data set for evaluating differential treatment benefit according to biomarker subgroups

Directory of Open Access Journals (Sweden)

Jaya M. Satagopan

2017-06-01

Full Text Available The data presented in this article are related to the research article entitled “Measuring differential treatment benefit across marker specific subgroups: the choice of outcome scale” (Satagopan and Iasonos, 2015 [1]. These data were digitally reconstructed from figures published in Larkin et al. (2015 [2]. This article describes the steps to digitally reconstruct patient-level data on time-to-event outcome and treatment and biomarker groups using published Kaplan-Meier survival curves. The reconstructed data set and the corresponding computer programs are made publicly available to enable further statistical methodology research.

Solar wind reconstruction from magnetosheath data using an adjoint approach

International Nuclear Information System (INIS)

Nabert, C.; Othmer, C.

2015-01-01

We present a new method to reconstruct solar wind conditions from spacecraft data taken during magnetosheath passages, which can be used to support, e.g., magnetospheric models. The unknown parameters of the solar wind are used as boundary conditions of an MHD (magnetohydrodynamics) magnetosheath model. The boundary conditions are varied until the spacecraft data matches the model predictions. The matching process is performed using a gradient-based minimization of the misfit between data and model. To achieve this time-consuming procedure, we introduce the adjoint of the magnetosheath model, which allows efficient calculation of the gradients. An automatic differentiation tool is used to generate the adjoint source code of the model. The reconstruction method is applied to THEMIS (Time History of Events and Macroscale Interactions during Substorms) data to calculate the solar wind conditions during spacecraft magnetosheath transitions. The results are compared to actual solar wind data. This allows validation of our reconstruction method and indicates the limitations of the MHD magnetosheath model used.

Solar wind reconstruction from magnetosheath data using an adjoint approach

Energy Technology Data Exchange (ETDEWEB)

Nabert, C.; Othmer, C. [Technische Univ. Braunschweig (Germany). Inst. fuer Geophysik und extraterrestrische Physik; Glassmeier, K.H. [Technische Univ. Braunschweig (Germany). Inst. fuer Geophysik und extraterrestrische Physik; Max Planck Institute for Solar System Research, Goettingen (Germany)

2015-07-01

We present a new method to reconstruct solar wind conditions from spacecraft data taken during magnetosheath passages, which can be used to support, e.g., magnetospheric models. The unknown parameters of the solar wind are used as boundary conditions of an MHD (magnetohydrodynamics) magnetosheath model. The boundary conditions are varied until the spacecraft data matches the model predictions. The matching process is performed using a gradient-based minimization of the misfit between data and model. To achieve this time-consuming procedure, we introduce the adjoint of the magnetosheath model, which allows efficient calculation of the gradients. An automatic differentiation tool is used to generate the adjoint source code of the model. The reconstruction method is applied to THEMIS (Time History of Events and Macroscale Interactions during Substorms) data to calculate the solar wind conditions during spacecraft magnetosheath transitions. The results are compared to actual solar wind data. This allows validation of our reconstruction method and indicates the limitations of the MHD magnetosheath model used.

TH-EF-BRA-03: Assessment of Data-Driven Respiratory Motion-Compensation Methods for 4D-CBCT Image Registration and Reconstruction Using Clinical Datasets

Energy Technology Data Exchange (ETDEWEB)

Riblett, MJ; Weiss, E; Hugo, GD [Virginia Commonwealth University, Richmond, VA (United States); Christensen, GE [University of Iowa, Iowa City, IA (United States)

2016-06-15

method. Conclusion: Data-driven groupwise registration and motion-compensated reconstruction have the potential to improve the quality of 4D-CBCT images acquired under clinical conditions. For clinical image datasets, the addition of motion compensation after groupwise registration visibly reduced artifact impact. This work was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA166119. Hugo and Weiss hold a research agreement with Philips Healthcare and license agreement with Varian Medical Systems. Weiss receives royalties from UpToDate. Christensen receives funds from Roger Koch to support research.

TH-EF-BRA-03: Assessment of Data-Driven Respiratory Motion-Compensation Methods for 4D-CBCT Image Registration and Reconstruction Using Clinical Datasets

International Nuclear Information System (INIS)

Riblett, MJ; Weiss, E; Hugo, GD; Christensen, GE

2016-01-01

method. Conclusion: Data-driven groupwise registration and motion-compensated reconstruction have the potential to improve the quality of 4D-CBCT images acquired under clinical conditions. For clinical image datasets, the addition of motion compensation after groupwise registration visibly reduced artifact impact. This work was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA166119. Hugo and Weiss hold a research agreement with Philips Healthcare and license agreement with Varian Medical Systems. Weiss receives royalties from UpToDate. Christensen receives funds from Roger Koch to support research.

Event Reconstruction Techniques in NOvA

Science.gov (United States)

Baird, M.; Bian, J.; Messier, M.; Niner, E.; Rocco, D.; Sachdev, K.

2015-12-01

The NOvA experiment is a long-baseline neutrino oscillation experiment utilizing the NuMI beam generated at Fermilab. The experiment will measure the oscillations within a muon neutrino beam in a 300 ton Near Detector located underground at Fermilab and a functionally-identical 14 kiloton Far Detector placed 810 km away. The detectors are liquid scintillator tracking calorimeters with a fine-grained cellular structure that provides a wealth of information for separating the different particle track and shower topologies. Each detector has its own challenges with the Near Detector seeing multiple overlapping neutrino interactions in each event and the Far Detector having a large background of cosmic rays due to being located on the surface. A series of pattern recognition techniques have been developed to go from event records, to spatially and temporally separating individual interactions, to vertexing and tracking, and particle identification. This combination of methods to achieve the full event reconstruction will be discussed.

Peripheral visual feedback: a powerful means of supporting effective attention allocation in event-driven, data-rich environments.

Science.gov (United States)

Nikolic, M I; Sarter, N B

2001-01-01

Breakdowns in human-automation coordination in data-rich, event-driven domains such as aviation can be explained in part by a mismatch between the high degree of autonomy yet low observability of modern technology. To some extent, the latter is the result of an increasing reliance in feedback design on foveal vision--an approach that fails to support pilots in tracking system-induced changes and events in parallel with performing concurrent flight-related tasks. One possible solution to the problem is the distribution of tasks and information across sensory modalities and processing channels. A simulator study is presented that compared the effectiveness of current foveal feedback and two implementations of peripheral visual feedback for keeping pilots informed about uncommanded changes in the status of an automated cockpit system. Both peripheral visual displays resulted in higher detection rates and faster response times, without interfering with the performance of concurrent visual tasks any more than does currently available automation feedback. Potential applications include improved display designs that support effective attention allocation in a variety of complex dynamic environments, such as aviation, process control, and medicine.

System on chip module configured for event-driven architecture

Science.gov (United States)

Robbins, Kevin; Brady, Charles E.; Ashlock, Tad A.

2017-10-17

A system on chip (SoC) module is described herein, wherein the SoC modules comprise a processor subsystem and a hardware logic subsystem. The processor subsystem and hardware logic subsystem are in communication with one another, and transmit event messages between one another. The processor subsystem executes software actors, while the hardware logic subsystem includes hardware actors, the software actors and hardware actors conform to an event-driven architecture, such that the software actors receive and generate event messages and the hardware actors receive and generate event messages.

Athena X-IFU event reconstruction software: SIRENA

Science.gov (United States)

Ceballos, Maria Teresa; Cobo, Beatriz; Peille, Philippe; Wilms, Joern; Brand, Thorsten; Dauser, Thomas; Bandler, Simon; Smith, Stephen

2015-09-01

This contribution describes the status and technical details of the SIRENA package, the software currently in development to perform the on board event energy reconstruction for the Athena calorimeter X-IFU. This on board processing will be done in the X-IFU DRE unit and it will consist in an initial triggering of event pulses followed by an analysis (with the SIRENA package) to determine the energy content of such events.The current algorithm used by SIRENA is the optimal filtering technique (also used by ASTRO-H processor) although some other algorithms are also being tested.Here we present these studies and some preliminary results about the energy resolution of the instrument based on simulations done with the SIXTE simulator (http://www.sternwarte.uni-erlangen.de/research/sixte/) in which SIRENA is integrated.

Data driven CAN node reliability assessment for manufacturing system

Science.gov (United States)

Zhang, Leiming; Yuan, Yong; Lei, Yong

2017-01-01

The reliability of the Controller Area Network(CAN) is critical to the performance and safety of the system. However, direct bus-off time assessment tools are lacking in practice due to inaccessibility of the node information and the complexity of the node interactions upon errors. In order to measure the mean time to bus-off(MTTB) of all the nodes, a novel data driven node bus-off time assessment method for CAN network is proposed by directly using network error information. First, the corresponding network error event sequence for each node is constructed using multiple-layer network error information. Then, the generalized zero inflated Poisson process(GZIP) model is established for each node based on the error event sequence. Finally, the stochastic model is constructed to predict the MTTB of the node. The accelerated case studies with different error injection rates are conducted on a laboratory network to demonstrate the proposed method, where the network errors are generated by a computer controlled error injection system. Experiment results show that the MTTB of nodes predicted by the proposed method agree well with observations in the case studies. The proposed data driven node time to bus-off assessment method for CAN networks can successfully predict the MTTB of nodes by directly using network error event data.

An event driven algorithm for fractal cluster formation

NARCIS (Netherlands)

González, S.; Gonzalez Briones, Sebastián; Thornton, Anthony Richard; Luding, Stefan

2011-01-01

A new cluster based event-driven algorithm is developed to simulate the formation of clusters in a two dimensional gas: particles move freely until they collide and "stick" together irreversibly. These clusters aggregate into bigger structures in an isotompic way, forming fractal structures whose

An event driven algorithm for fractal cluster formation

NARCIS (Netherlands)

González, S.; Thornton, Anthony Richard; Luding, Stefan

2010-01-01

A new cluster based event-driven algorithm is developed to simulate the formation of clusters in a two dimensional gas: particles move freely until they collide and "stick" together irreversibly. These clusters aggregate into bigger structures in an isotompic way, forming fractal structures whose

Iterative CT reconstruction with small pixel size: distance-driven forward projector versus Joseph's

Science.gov (United States)

Hahn, K.; Rassner, U.; Davidson, H. C.; Schöndube, H.; Stierstorfer, K.; Hornegger, J.; Noo, F.

2015-03-01

Over the last few years, iterative reconstruction methods have become an important research topic in x-ray CT imaging. This effort is motivated by increasing evidence that such methods may enable significant savings in terms of dose imparted to the patient. Conceptually, iterative reconstruction methods involve two important ingredients: the statistical model, which includes the forward projector, and a priori information in the image domain, which is expressed using a regularizer. Most often, the image pixel size is chosen to be equal (or close) to the detector pixel size (at field-of-view center). However, there are applications for which a smaller pixel size is desired. In this investigation, we focus on reconstruction with a pixel size that is twice smaller than the detector pixel size. Using such a small pixel size implies a large increase in computational effort when using the distance-driven method for forward projection, which models the detector size. On the other hand, the more efficient method of Joseph will create imbalances in the reconstruction of each pixel, in the sense that there will be large differences in the way each projection contributes to the pixels. The purpose of this work is to evaluate the impact of these imbalances on image quality in comparison with utilization of the distance-driven method. The evaluation involves computational effort, bias and noise metrics, and LROC analysis using human observers. The results show that Joseph's method largely remains attractive.

Views of CMS Event Data Objects, Files, Collections, Virtual Data Products

CERN Document Server

Holtman, Koen

2001-01-01

The CMS data grid system will store many types of data maintained by the CMS collaboration. An important type of data is the event data, which is defined in this note as all data that directly represents simulated, raw, or reconstructed CMS physics events. Many views on this data will exist simultaneously. To a CMS physics code implementer this data will appear as C++ objects, to a tape robot operator the data will appear as files. This note identifies different views that can exist, describes each of them, and interrelates them by placing them into a vertical stack. This particular stack integrates several existing architectural structures, and is therefore a plausible basis for further prototyping and architectural work. This document is intended as a contribution to, and as common (terminological) reference material for, the CMS architectural efforts and for the Grid projects PPDG, GriPhyN, and the EU DataGrid.

WE-G-BRA-02: SafetyNet: Automating Radiotherapy QA with An Event Driven Framework

International Nuclear Information System (INIS)

Hadley, S; Kessler, M; Litzenberg, D; Lee, C; Irrer, J; Chen, X; Acosta, E; Weyburne, G; Lam, K; Younge, K; Matuszak, M; Keranen, W; Covington, E; Moran, J

2015-01-01

Purpose: Quality assurance is an essential task in radiotherapy that often requires many manual tasks. We investigate the use of an event driven framework in conjunction with software agents to automate QA and eliminate wait times. Methods: An in house developed subscription-publication service, EventNet, was added to the Aria OIS to be a message broker for critical events occurring in the OIS and software agents. Software agents operate without user intervention and perform critical QA steps. The results of the QA are documented and the resulting event is generated and passed back to EventNet. Users can subscribe to those events and receive messages based on custom filters designed to send passing or failing results to physicists or dosimetrists. Agents were developed to expedite the following QA tasks: Plan Revision, Plan 2nd Check, SRS Winston-Lutz isocenter, Treatment History Audit, Treatment Machine Configuration. Results: Plan approval in the Aria OIS was used as the event trigger for plan revision QA and Plan 2nd check agents. The agents pulled the plan data, executed the prescribed QA, stored the results and updated EventNet for publication. The Winston Lutz agent reduced QA time from 20 minutes to 4 minutes and provided a more accurate quantitative estimate of radiation isocenter. The Treatment Machine Configuration agent automatically reports any changes to the Treatment machine or HDR unit configuration. The agents are reliable, act immediately, and execute each task identically every time. Conclusion: An event driven framework has inverted the data chase in our radiotherapy QA process. Rather than have dosimetrists and physicists push data to QA software and pull results back into the OIS, the software agents perform these steps immediately upon receiving the sentinel events from EventNet. Mr Keranen is an employee of Varian Medical Systems. Dr. Moran’s institution receives research support for her effort for a linear accelerator QA project from

WE-G-BRA-02: SafetyNet: Automating Radiotherapy QA with An Event Driven Framework

Energy Technology Data Exchange (ETDEWEB)

Hadley, S; Kessler, M [The University of Michigan, Ann Arbor, MI (United States); Litzenberg, D [Univ Michigan, Ann Arbor, MI (United States); Lee, C; Irrer, J; Chen, X; Acosta, E; Weyburne, G; Lam, K; Younge, K; Matuszak, M [University of Michigan, Ann Arbor, MI (United States); Keranen, W [Varian Medical Systems, Palo Alto, CA (United States); Covington, E [University of Michigan Hospital and Health System, Ann Arbor, MI (United States); Moran, J [Univ Michigan Medical Center, Ann Arbor, MI (United States)

2015-06-15

Purpose: Quality assurance is an essential task in radiotherapy that often requires many manual tasks. We investigate the use of an event driven framework in conjunction with software agents to automate QA and eliminate wait times. Methods: An in house developed subscription-publication service, EventNet, was added to the Aria OIS to be a message broker for critical events occurring in the OIS and software agents. Software agents operate without user intervention and perform critical QA steps. The results of the QA are documented and the resulting event is generated and passed back to EventNet. Users can subscribe to those events and receive messages based on custom filters designed to send passing or failing results to physicists or dosimetrists. Agents were developed to expedite the following QA tasks: Plan Revision, Plan 2nd Check, SRS Winston-Lutz isocenter, Treatment History Audit, Treatment Machine Configuration. Results: Plan approval in the Aria OIS was used as the event trigger for plan revision QA and Plan 2nd check agents. The agents pulled the plan data, executed the prescribed QA, stored the results and updated EventNet for publication. The Winston Lutz agent reduced QA time from 20 minutes to 4 minutes and provided a more accurate quantitative estimate of radiation isocenter. The Treatment Machine Configuration agent automatically reports any changes to the Treatment machine or HDR unit configuration. The agents are reliable, act immediately, and execute each task identically every time. Conclusion: An event driven framework has inverted the data chase in our radiotherapy QA process. Rather than have dosimetrists and physicists push data to QA software and pull results back into the OIS, the software agents perform these steps immediately upon receiving the sentinel events from EventNet. Mr Keranen is an employee of Varian Medical Systems. Dr. Moran’s institution receives research support for her effort for a linear accelerator QA project from

Simulating the energy deposits of particles in the KASCADE-grande detector stations as a preliminary step for EAS event reconstruction

International Nuclear Information System (INIS)

Toma, G.; Brancus, I.M.; Mitrica, B.; Sima, O.; Rebel, H.; Haungs, A.

2005-01-01

The study of primary cosmic rays with energies higher than 10 14 eV is done mostly by indirect observation techniques such as the study of Extensive Air Showers (EAS). In the much larger framework effort of inferring data on the mass and energy of the primaries from EAS observables, the present study aims at developing a versatile method and software tool that will be used to reconstruct lateral particle densities from the energy deposits of particles in the KASCADE-Grande detector stations. The study has been performed on simulated events, by taking into account the interaction of the EAS components with the detector array (energy deposits). The energy deposits have been simulated using the GEANT code and then the energy deposits have been parametrized for different incident energies and angles of EAS particles. Thus the results obtained for simulated events have the same level of consistency as the experimental data. This technique will allow an increased speed of lateral particle density reconstruction when studying real events detected by the KASCADE-Grande array. The particle densities in detectors have been reconstructed from the energy deposits. A correlation between lateral particle density and primary mass and primary energy (at ∼600 m from shower core) has been established. The study puts great emphasis on the quality of reconstruction and also on the speed of the technique. The data obtained from the study on simulated events creates the basis for the next stage of the study, the study of real events detected by the KASCADE-Grande array. (authors)

An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

Directory of Open Access Journals (Sweden)

Evangelos Stromatias

2017-06-01

Full Text Available This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN System capable of yielding good classification results when using both synthetic input data and real data captured from Dynamic Vision Sensor (DVS chips. The proposed supervised method uses the spiking activity provided by an arbitrary topology of prior SNN layers to build histograms and train the classifier in the frame domain using the stochastic gradient descent algorithm. In addition, this approach can cope with leaky integrate-and-fire neuron models within the SNN, a desirable feature for real-world SNN applications, where neural activation must fade away after some time in the absence of inputs. Consequently, this way of building histograms captures the dynamics of spikes immediately before the classifier. We tested our method on the MNIST data set using different synthetic encodings and real DVS sensory data sets such as N-MNIST, MNIST-DVS, and Poker-DVS using the same network topology and feature maps. We demonstrate the effectiveness of our approach by achieving the highest classification accuracy reported on the N-MNIST (97.77% and Poker-DVS (100% real DVS data sets to date with a spiking convolutional network. Moreover, by using the proposed method we were able to retrain the output layer of a previously reported spiking neural network and increase its performance by 2%, suggesting that the proposed classifier can be used as the output layer in works where features are extracted using unsupervised spike-based learning methods. In addition, we also analyze SNN performance figures such as total event activity and network latencies, which are relevant for eventual hardware implementations. In summary, the paper aggregates unsupervised-trained SNNs with a supervised-trained SNN classifier, combining and applying them to heterogeneous sets of benchmarks, both synthetic and from real DVS chips.

An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data.

Science.gov (United States)

Stromatias, Evangelos; Soto, Miguel; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabé

2017-01-01

This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN) System capable of yielding good classification results when using both synthetic input data and real data captured from Dynamic Vision Sensor (DVS) chips. The proposed supervised method uses the spiking activity provided by an arbitrary topology of prior SNN layers to build histograms and train the classifier in the frame domain using the stochastic gradient descent algorithm. In addition, this approach can cope with leaky integrate-and-fire neuron models within the SNN, a desirable feature for real-world SNN applications, where neural activation must fade away after some time in the absence of inputs. Consequently, this way of building histograms captures the dynamics of spikes immediately before the classifier. We tested our method on the MNIST data set using different synthetic encodings and real DVS sensory data sets such as N-MNIST, MNIST-DVS, and Poker-DVS using the same network topology and feature maps. We demonstrate the effectiveness of our approach by achieving the highest classification accuracy reported on the N-MNIST (97.77%) and Poker-DVS (100%) real DVS data sets to date with a spiking convolutional network. Moreover, by using the proposed method we were able to retrain the output layer of a previously reported spiking neural network and increase its performance by 2%, suggesting that the proposed classifier can be used as the output layer in works where features are extracted using unsupervised spike-based learning methods. In addition, we also analyze SNN performance figures such as total event activity and network latencies, which are relevant for eventual hardware implementations. In summary, the paper aggregates unsupervised-trained SNNs with a supervised-trained SNN classifier, combining and applying them to heterogeneous sets of benchmarks, both synthetic and from real DVS chips.

A general algorithm for the reconstruction of jet events in e+e- annihilation

International Nuclear Information System (INIS)

Goddard, M.C.

1981-01-01

A general method is described to reconstruct a predetermined number of jets. It can reconstruct the jet axes as accurately as any existing algorithm and is up to one hundred times faster. Results are shown from the reconstruction of 2-jet, 3-jet and 4-jet Monte Carlo events. (author)

Capacity builders for governance: community-driven reconstruction in the eastern Democratic Republic of Congo

NARCIS (Netherlands)

Kyamusugulwa, P.M.; Hilhorst, D.; Haar, van der G.

2014-01-01

Community-driven reconstruction (CDR) has become a new paradigm in post-conflict development. It combines infrastructure restoration with introducing good governance at the local level. Recent evaluations show that governance objectives are not easily met and significant change cannot be

The Convolutional Visual Network for Identification and Reconstruction of NOvA Events

Energy Technology Data Exchange (ETDEWEB)

Psihas, Fernanda [Indiana U.

2017-11-22

In 2016 the NOvA experiment released results for the observation of oscillations in the vμ and ve channels as well as ve cross section measurements using neutrinos from Fermilab’s NuMI beam. These and other measurements in progress rely on the accurate identification and reconstruction of the neutrino flavor and energy recorded by our detectors. This presentation describes the first application of convolutional neural network technology for event identification and reconstruction in particle detectors like NOvA. The Convolutional Visual Network (CVN) Algorithm was developed for identification, categorization, and reconstruction of NOvA events. It increased the selection efficiency of the ve appearance signal by 40% and studies show potential impact to the vμ disappearance analysis.

Polynomials, Riemann surfaces, and reconstructing missing-energy events

CERN Document Server

Gripaios, Ben; Webber, Bryan

2011-01-01

We consider the problem of reconstructing energies, momenta, and masses in collider events with missing energy, along with the complications introduced by combinatorial ambiguities and measurement errors. Typically, one reconstructs more than one value and we show how the wrong values may be correlated with the right ones. The problem has a natural formulation in terms of the theory of Riemann surfaces. We discuss examples including top quark decays in the Standard Model (relevant for top quark mass measurements and tests of spin correlation), cascade decays in models of new physics containing dark matter candidates, decays of third-generation leptoquarks in composite models of electroweak symmetry breaking, and Higgs boson decay into two tau leptons.

An asynchronous data-driven event-building scheme based on ATM switching fabrics

International Nuclear Information System (INIS)

Letheren, M.; Christiansen, J.; Mandjavidze, I.; Verhille, H.; De Prycker, M.; Pauwels, B.; Petit, G.; Wright, S.; Lumley, J.

1994-01-01

The very high data rates expected in experiments at the next generation of high luminosity hadron colliders will be handled by pipelined front-end readout electronics and multiple levels (2 or 3) of triggering. A variety of data acquisition architectures have been proposed for use downstream of the first level trigger. Depending on the architecture, the aggregate bandwidths required for event building are expected to be of the order 10--100 Gbit/s. Here, an Asynchronous Transfer Mode (ATM) packet-switching network technology is proposed as the interconnect for building high-performance, scalable data acquisition architectures. This paper introduces the relevant characteristics of ATM and describes components for the construction of an ATM-based event builder: (1) a multi-path, self-routing, scalable ATM switching fabric, (2) an experimental high performance workstation ATM-interface, and (3) a VMEbus ATM-interface. The requirement for traffic shaping in ATM-based event-builders is discussed and an analysis of the performance of several such schemes is presented

Complications and Adverse Events of a Randomized Clinical Trial Comparing 3 Graft Types for ACL Reconstruction.

Science.gov (United States)

Mohtadi, Nicholas; Barber, Rhamona; Chan, Denise; Paolucci, Elizabeth Oddone

2016-05-01

Complications/adverse events of anterior cruciate ligament (ACL) surgery are underreported, despite pooled level 1 data in systematic reviews. All adverse events/complications occurring within a 2-year postoperative period after primary ACL reconstruction, as part of a large randomized clinical trial (RCT), were identified and described. Prospective, double-blind randomized clinical trial. Patients and the independent trained examiner were blinded to treatment allocation. University-based orthopedic referral practice. Three hundred thirty patients (14-50 years; 183 males) with isolated ACL deficiency were intraoperatively randomized to ACL reconstruction with 1 autograft type. Graft harvest and arthroscopic portal incisions were identical. Patients were equally distributed to patellar tendon (PT), quadruple-stranded hamstring tendon (HT), and double-bundle (DB) hamstring autograft ACL reconstruction. Adverse events/complications were patient reported, documented, and diagnoses confirmed. Two major complications occurred: pulmonary embolism and septic arthritis. Twenty-four patients (7.3%) required repeat surgery, including 25 separate operations: PT = 7 (6.4%), HT = 9 (8.2%), and DB = 8 (7.3%). Repeat surgery was performed for meniscal tears (3.6%; n = 12), intra-articular scarring (2.7%; n = 9), chondral pathology (0.6%; n = 2), and wound dehiscence (0.3%; n = 1). Other complications included wound problems, sensory nerve damage, muscle tendon injury, tibial periostitis, and suspected meniscal tears and chondral lesions. Overall, more complications occurred in the HT/DB groups (PT = 24; HT = 31; DB = 45), but more PT patients complained of moderate or severe kneeling pain (PT = 17; HT = 9; DB = 4) at 2 years. Overall, ACL reconstructive surgery is safe. Major complications were uncommon. Secondary surgery was necessary 7.3% of the time for complications/adverse events (excluding graft reinjury or revisions) within the first 2 years. Level 1 (therapeutic studies

The column architecture -- A novel architecture for event driven 2D pixel imagers

International Nuclear Information System (INIS)

Millaud, J.; Nygren, D.

1996-01-01

The authors describe an electronic architecture for two-dimensional pixel arrays that permits very large increases in rate capability for event- or data-driven applications relative to conventional x-y architectures. The column architecture also permits more efficient use of silicon area in applications requiring local buffering, frameless data acquisition, and it avoids entirely the problem of ambiguities that may arise in conventional approaches. Two examples of active implementation are described: high energy physics and protein crystallography

External radioactive markers for PET data-driven respiratory gating in positron emission tomography.

Science.gov (United States)

Büther, Florian; Ernst, Iris; Hamill, James; Eich, Hans T; Schober, Otmar; Schäfers, Michael; Schäfers, Klaus P

2013-04-01

Respiratory gating is an established approach to overcoming respiration-induced image artefacts in PET. Of special interest in this respect are raw PET data-driven gating methods which do not require additional hardware to acquire respiratory signals during the scan. However, these methods rely heavily on the quality of the acquired PET data (statistical properties, data contrast, etc.). We therefore combined external radioactive markers with data-driven respiratory gating in PET/CT. The feasibility and accuracy of this approach was studied for [(18)F]FDG PET/CT imaging in patients with malignant liver and lung lesions. PET data from 30 patients with abdominal or thoracic [(18)F]FDG-positive lesions (primary tumours or metastases) were included in this prospective study. The patients underwent a 10-min list-mode PET scan with a single bed position following a standard clinical whole-body [(18)F]FDG PET/CT scan. During this scan, one to three radioactive point sources (either (22)Na or (18)F, 50-100 kBq) in a dedicated holder were attached the patient's abdomen. The list mode data acquired were retrospectively analysed for respiratory signals using established data-driven gating approaches and additionally by tracking the motion of the point sources in sinogram space. Gated reconstructions were examined qualitatively, in terms of the amount of respiratory displacement and in respect of changes in local image intensity in the gated images. The presence of the external markers did not affect whole-body PET/CT image quality. Tracking of the markers led to characteristic respiratory curves in all patients. Applying these curves for gated reconstructions resulted in images in which motion was well resolved. Quantitatively, the performance of the external marker-based approach was similar to that of the best intrinsic data-driven methods. Overall, the gain in measured tumour uptake from the nongated to the gated images indicating successful removal of respiratory motion

The potential of satellite data to study individual wildfire events

Science.gov (United States)

Benali, Akli; López-Saldana, Gerardo; Russo, Ana; Sá, Ana C. L.; Pinto, Renata M. S.; Nikos, Koutsias; Owen, Price; Pereira, Jose M. C.

2014-05-01

Large wildfires have important social, economic and environmental impacts. In order to minimize their impacts, understand their main drivers and study their dynamics, different approaches have been used. The reconstruction of individual wildfire events is usually done by collection of field data, interviews and by implementing fire spread simulations. All these methods have clear limitations in terms of spatial and temporal coverage, accuracy, subjectivity of the collected information and lack of objective independent validation information. In this sense, remote sensing is a promising tool with the potential to provide relevant information for stakeholders and the research community, by complementing or filling gaps in existing information and providing independent accurate quantitative information. In this work we show the potential of satellite data to provide relevant information regarding the dynamics of individual large wildfire events, filling an important gap in wildfire research. We show how MODIS active-fire data, acquired up to four times per day, and satellite-derived burnt perimeters can be combined to extract relevant information wildfire events by describing the methods involved and presenting results for four regions of the world: Portugal, Greece, SE Australia and California. The information that can be retrieved encompasses the start and end date of a wildfire event and its ignition area. We perform an evaluation of the information retrieved by comparing the satellite-derived parameters with national databases, highlighting the strengths and weaknesses of both and showing how the former can complement the latter leading to more complete and accurate datasets. We also show how the spatio-temporal distribution of wildfire spread dynamics can be reconstructed using satellite-derived active-fires and how relevant descriptors can be extracted. Applying graph theory to satellite active-fire data, we define the major fire spread paths that yield

Efficient, symmetry-driven SIMD access patterns for 3D PET image reconstruction applicable for CPUs and GPUs

Energy Technology Data Exchange (ETDEWEB)

Scheins, J.J.; Garcia Lucio, L.F.; Herzog, H.; Shah, N.J. [Forschungszentrum Juelich GmbH (Germany). Inst. of Neuroscience and Medicine (INM-4)

2011-07-01

Fully 3D PET image reconstruction still remains a challenging computational task due to the tremendous number of registered Lines-of-Response. Typically, billions of geometrical weights have to be repeatedly calculated and evaluated for iterative algorithms. In this context, the reconstruction software PRESTO (PET REconstruction Software TOolkit) provides accurate geometrical weighting schemes for the forward projection and backward projection, e.g. Volume-of-Intersection, while using all measured LORs separately. PRESTO exploits redundancies to realise a strongly compressed, memory-resident system matrix. Consequently, the needed time to calculate matrix weights no longer influences the reconstruction time. Very high compression factors (>300) are achieved by using unconventional non-cartesian voxel patterns. However, in the original implementation the addressing of matrix weights, projection values and voxel values happens in disfavoured memory access patterns. This causes severe computational inefficiencies due to the limited memory bandwidth using CPUs. In this work, the image data and projection data in memory as well as the order of mathematical operations have been completely re-organised to provide an optimal merit for the Single Instruction Multiple Data (SIMD) approach. This reorganisation is directly driven by the induced symmetries of PRESTO. A global speedup factor of 15 for has been achieved for the CPU-based implementation while obtaining identical results. In addition, a GPU-based implementation using CUDA on Nvidia TESLA C1060/S1070 hardware provides another speed up factor of 4 compared to single core CPU processing. (orig.)

Efficient, symmetry-driven SIMD access patterns for 3D PET image reconstruction applicable for CPUs and GPUs

International Nuclear Information System (INIS)

Scheins, J.J.; Garcia Lucio, L.F.; Herzog, H.; Shah, N.J.

2011-01-01

Fully 3D PET image reconstruction still remains a challenging computational task due to the tremendous number of registered Lines-of-Response. Typically, billions of geometrical weights have to be repeatedly calculated and evaluated for iterative algorithms. In this context, the reconstruction software PRESTO (PET REconstruction Software TOolkit) provides accurate geometrical weighting schemes for the forward projection and backward projection, e.g. Volume-of-Intersection, while using all measured LORs separately. PRESTO exploits redundancies to realise a strongly compressed, memory-resident system matrix. Consequently, the needed time to calculate matrix weights no longer influences the reconstruction time. Very high compression factors (>300) are achieved by using unconventional non-cartesian voxel patterns. However, in the original implementation the addressing of matrix weights, projection values and voxel values happens in disfavoured memory access patterns. This causes severe computational inefficiencies due to the limited memory bandwidth using CPUs. In this work, the image data and projection data in memory as well as the order of mathematical operations have been completely re-organised to provide an optimal merit for the Single Instruction Multiple Data (SIMD) approach. This reorganisation is directly driven by the induced symmetries of PRESTO. A global speedup factor of 15 for has been achieved for the CPU-based implementation while obtaining identical results. In addition, a GPU-based implementation using CUDA on Nvidia TESLA C1060/S1070 hardware provides another speed up factor of 4 compared to single core CPU processing. (orig.)

Polar cap flow channel events: spontaneous and driven responses

Directory of Open Access Journals (Sweden)

P. E. Sandholt

2010-11-01

Full Text Available We present two case studies of specific flow channel events appearing at the dusk and/or dawn polar cap boundary during passage at Earth of interplanetary (IP coronal mass ejections (ICMEs on 10 January and 25 July 2004. The channels of enhanced (>1 km/s antisunward convection are documented by SuperDARN radars and dawn-dusk crossings of the polar cap by the DMSP F13 satellite. The relationship with Birkeland currents (C1–C2 located poleward of the traditional R1–R2 currents is demonstrated. The convection events are manifest in ground magnetic deflections obtained from the IMAGE (International Monitor for Auroral Geomagnetic Effects Svalbard chain of ground magnetometer stations located within 71–76° MLAT. By combining the ionospheric convection data and the ground magnetograms we are able to study the temporal behaviour of the convection events. In the two ICME case studies the convection events belong to two different categories, i.e., directly driven and spontaneous events. In the 10 January case two sharp southward turnings of the ICME magnetic field excited corresponding convection events as detected by IMAGE and SuperDARN. We use this case to determine the ground magnetic signature of enhanced flow channel events (the NH-dusk/By<0 variant. In the 25 July case a several-hour-long interval of steady southwest ICME field (Bz<0; By<0 gave rise to a long series of spontaneous convection events as detected by IMAGE when the ground stations swept through the 12:00–18:00 MLT sector. From the ground-satellite conjunction on 25 July we infer the pulsed nature of the polar cap ionospheric flow channel events in this case. The typical duration of these convection enhancements in the polar cap is 10 min.

Data-driven batch schuduling

Energy Technology Data Exchange (ETDEWEB)

Bent, John [Los Alamos National Laboratory; Denehy, Tim [GOOGLE; Arpaci - Dusseau, Remzi [UNIV OF WISCONSIN; Livny, Miron [UNIV OF WISCONSIN; Arpaci - Dusseau, Andrea C [NON LANL

2009-01-01

In this paper, we develop data-driven strategies for batch computing schedulers. Current CPU-centric batch schedulers ignore the data needs within workloads and execute them by linking them transparently and directly to their needed data. When scheduled on remote computational resources, this elegant solution of direct data access can incur an order of magnitude performance penalty for data-intensive workloads. Adding data-awareness to batch schedulers allows a careful coordination of data and CPU allocation thereby reducing the cost of remote execution. We offer here new techniques by which batch schedulers can become data-driven. Such systems can use our analytical predictive models to select one of the four data-driven scheduling policies that we have created. Through simulation, we demonstrate the accuracy of our predictive models and show how they can reduce time to completion for some workloads by as much as 80%.

Data-Driven Problems in Elasticity

Science.gov (United States)

Conti, S.; Müller, S.; Ortiz, M.

2018-01-01

We consider a new class of problems in elasticity, referred to as Data-Driven problems, defined on the space of strain-stress field pairs, or phase space. The problem consists of minimizing the distance between a given material data set and the subspace of compatible strain fields and stress fields in equilibrium. We find that the classical solutions are recovered in the case of linear elasticity. We identify conditions for convergence of Data-Driven solutions corresponding to sequences of approximating material data sets. Specialization to constant material data set sequences in turn establishes an appropriate notion of relaxation. We find that relaxation within this Data-Driven framework is fundamentally different from the classical relaxation of energy functions. For instance, we show that in the Data-Driven framework the relaxation of a bistable material leads to material data sets that are not graphs.

Polaron-Driven Surface Reconstructions

Directory of Open Access Journals (Sweden)

Michele Reticcioli

2017-09-01

Full Text Available Geometric and electronic surface reconstructions determine the physical and chemical properties of surfaces and, consequently, their functionality in applications. The reconstruction of a surface minimizes its surface free energy in otherwise thermodynamically unstable situations, typically caused by dangling bonds, lattice stress, or a divergent surface potential, and it is achieved by a cooperative modification of the atomic and electronic structure. Here, we combined first-principles calculations and surface techniques (scanning tunneling microscopy, non-contact atomic force microscopy, scanning tunneling spectroscopy to report that the repulsion between negatively charged polaronic quasiparticles, formed by the interaction between excess electrons and the lattice phonon field, plays a key role in surface reconstructions. As a paradigmatic example, we explain the (1×1 to (1×2 transition in rutile TiO_{2}(110.

A Multi-mission Event-Driven Component-Based System for Support of Flight Software Development, ATLO, and Operations first used by the Mars Science Laboratory (MSL) Project

Science.gov (United States)

Dehghani, Navid; Tankenson, Michael

2006-01-01

This paper details an architectural description of the Mission Data Processing and Control System (MPCS), an event-driven, multi-mission ground data processing components providing uplink, downlink, and data management capabilities which will support the Mars Science Laboratory (MSL) project as its first target mission. MPCS is developed based on a set of small reusable components, implemented in Java, each designed with a specific function and well-defined interfaces. An industry standard messaging bus is used to transfer information among system components. Components generate standard messages which are used to capture system information, as well as triggers to support the event-driven architecture of the system. Event-driven systems are highly desirable for processing high-rate telemetry (science and engineering) data, and for supporting automation for many mission operations processes.

Accurate Sample Time Reconstruction of Inertial FIFO Data

Directory of Open Access Journals (Sweden)

Sebastian Stieber

2017-12-01

Full Text Available In the context of modern cyber-physical systems, the accuracy of underlying sensor data plays an increasingly important role in sensor data fusion and feature extraction. The raw events of multiple sensors have to be aligned in time to enable high quality sensor fusion results. However, the growing number of simultaneously connected sensor devices make the energy saving data acquisition and processing more and more difficult. Hence, most of the modern sensors offer a first-in-first-out (FIFO interface to store multiple data samples and to relax timing constraints, when handling multiple sensor devices. However, using the FIFO interface increases the negative influence of individual clock drifts—introduced by fabrication inaccuracies, temperature changes and wear-out effects—onto the sampling data reconstruction. Furthermore, additional timing offset errors due to communication and software latencies increases with a growing number of sensor devices. In this article, we present an approach for an accurate sample time reconstruction independent of the actual clock drift with the help of an internal sensor timer. Such timers are already available in modern sensors, manufactured in micro-electromechanical systems (MEMS technology. The presented approach focuses on calculating accurate time stamps using the sensor FIFO interface in a forward-only processing manner as a robust and energy saving solution. The proposed algorithm is able to lower the overall standard deviation of reconstructed sampling periods below 40 μ s, while run-time savings of up to 42% are achieved, compared to single sample acquisition.

GPU's for event reconstruction in the FairRoot framework

International Nuclear Information System (INIS)

Al-Turany, M; Uhlig, F; Karabowicz, R

2010-01-01

FairRoot is the simulation and analysis framework used by CBM and PANDA experiments at FAIR/GSI. The use of graphics processor units (GPUs) for event reconstruction in FairRoot will be presented. The fact that CUDA (Nvidia's Compute Unified Device Architecture) development tools work alongside the conventional C/C++ compiler, makes it possible to mix GPU code with general-purpose code for the host CPU, based on this some of the reconstruction tasks can be send to the graphic cards. Moreover, tasks that run on the GPU's can also run in emulation mode on the host CPU, which has the advantage that the same code is used on both CPU and GPU.

Track Reconstruction with Cosmic Ray Data at the Tracker Integration Facility

CERN Document Server

Adam, Wolfgang; Dragicevic, Marko; Friedl, Markus; Fruhwirth, R; Hansel, S; Hrubec, Josef; Krammer, Manfred; Oberegger, Margit; Pernicka, Manfred; Schmid, Siegfried; Stark, Roland; Steininger, Helmut; Uhl, Dieter; Waltenberger, Wolfgang; Widl, Edmund; Van Mechelen, Pierre; Cardaci, Marco; Beaumont, Willem; de Langhe, Eric; de Wolf, Eddi A; Delmeire, Evelyne; Hashemi, Majid; Bouhali, Othmane; Charaf, Otman; Clerbaux, Barbara; Elgammal, J.-P. Dewulf. S; Hammad, Gregory Habib; de Lentdecker, Gilles; Marage, Pierre Edouard; Vander Velde, Catherine; Vanlaer, Pascal; Wickens, John; Adler, Volker; Devroede, Olivier; De Weirdt, Stijn; D'Hondt, Jorgen; Goorens, Robert; Heyninck, Jan; Maes, Joris; Mozer, Matthias Ulrich; Tavernier, Stefaan; Van Lancker, Luc; Van Mulders, Petra; Villella, Ilaria; Wastiels, C; Bonnet, Jean-Luc; Bruno, Giacomo; De Callatay, Bernard; Florins, Benoit; Giammanco, Andrea; Gregoire, Ghislain; Keutgen, Thomas; Kcira, Dorian; Lemaitre, Vincent; Michotte, Daniel; Militaru, Otilia; Piotrzkowski, Krzysztof; Quertermont, L; Roberfroid, Vincent; Rouby, Xavier; Teyssier, Daniel; Daubie, Evelyne; Anttila, Erkki; Czellar, Sandor; Engstrom, Pauli; Harkonen, J; Karimaki, V; Kostesmaa, J; Kuronen, Auli; Lampen, Tapio; Linden, Tomas; Luukka, Panja-Riina; Maenpaa, T; Michal, Sebastien; Tuominen, Eija; Tuominiemi, Jorma; Ageron, Michel; Baulieu, Guillaume; Bonnevaux, Alain; Boudoul, Gaelle; Chabanat, Eric; Chabert, Eric Christian; Chierici, Roberto; Contardo, Didier; Della Negra, Rodolphe; Dupasquier, Thierry; Gelin, Georges; Giraud, Noël; Guillot, Gérard; Estre, Nicolas; Haroutunian, Roger; Lumb, Nicholas; Perries, Stephane; Schirra, Florent; Trocme, Benjamin; Vanzetto, Sylvain; Agram, Jean-Laurent; Blaes, Reiner; Drouhin, Frédéric; Ernenwein, Jean-Pierre; Fontaine, Jean-Charles; Berst, Jean-Daniel; Brom, Jean-Marie; Didierjean, Francois; Goerlach, Ulrich; Graehling, Philippe; Gross, Laurent; Hosselet, J; Juillot, Pierre; Lounis, Abdenour; Maazouzi, Chaker; Olivetto, Christian; Strub, Roger; Van Hove, Pierre; Anagnostou, Georgios; Brauer, Richard; Esser, Hans; Feld, Lutz; Karpinski, Waclaw; Klein, Katja; Kukulies, Christoph; Olzem, Jan; Ostapchuk, Andrey; Pandoulas, Demetrios; Pierschel, Gerhard; Raupach, Frank; Schael, Stefan; Schwering, Georg; Sprenger, Daniel; Thomas, Maarten; Weber, Markus; Wittmer, Bruno; Wlochal, Michael; Beissel, Franz; Bock, E; Flugge, G; Gillissen, C; Hermanns, Thomas; Heydhausen, Dirk; Jahn, Dieter; Kaussen, Gordon; Linn, Alexander; Perchalla, Lars; Poettgens, Michael; Pooth, Oliver; Stahl, Achim; Zoeller, Marc Henning; Buhmann, Peter; Butz, Erik; Flucke, Gero; Hamdorf, Richard Helmut; Hauk, Johannes; Klanner, Robert; Pein, Uwe; Schleper, Peter; Steinbruck, G; Blum, P; De Boer, Wim; Dierlamm, Alexander; Dirkes, Guido; Fahrer, Manuel; Frey, Martin; Furgeri, Alexander; Hartmann, Frank; Heier, Stefan; Hoffmann, Karl-Heinz; Kaminski, Jochen; Ledermann, Bernhard; Liamsuwan, Thiansin; Muller, S; Muller, Th; Schilling, Frank-Peter; Simonis, Hans-Jürgen; Steck, Pia; Zhukov, Valery; Cariola, P; De Robertis, Giuseppe; Ferorelli, Raffaele; Fiore, Luigi; Preda, M; Sala, Giuliano; Silvestris, Lucia; Tempesta, Paolo; Zito, Giuseppe; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Giordano, Domenico; Maggi, Giorgio; Manna, Norman; My, Salvatore; Selvaggi, Giovanna; Albergo, Sebastiano; Chiorboli, Massimiliano; Costa, Salvatore; Galanti, Mario; Giudice, Nunzio; Guardone, Nunzio; Noto, Francesco; Potenza, Renato; Saizu, Mirela Angela; Sparti, V; Sutera, Concetta; Tricomi, Alessia; Tuve, Cristina; Brianzi, Mirko; Civinini, Carlo; Maletta, Fernando; Manolescu, Florentina; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Broccolo, B; Ciulli, Vitaliano; Focardi, R. D'Alessandro. E; Frosali, Simone; Genta, Chiara; Landi, Gregorio; Lenzi, Piergiulio; Macchiolo, Anna; Magini, Nicolo; Parrini, Giuliano; Scarlini, Enrico; Cerati, Giuseppe Benedetto; Azzi, Patrizia; Bacchetta, Nicola; Candelori, Andrea; Dorigo, Tommaso; Kaminsky, A; Karaevski, S; Khomenkov, Volodymyr; Reznikov, Sergey; Tessaro, Mario; Bisello, Dario; De Mattia, Marco; Giubilato, Piero; Loreti, Maurizio; Mattiazzo, Serena; Nigro, Massimo; Paccagnella, Alessandro; Pantano, Devis; Pozzobon, Nicola; Tosi, Mia; Bilei, Gian Mario; Checcucci, Bruno; Fano, Livio; Servoli, Leonello; Ambroglini, Filippo; Babucci, Ezio; Benedetti, Daniele; Biasini, Maurizio; Caponeri, Benedetta; Covarelli, Roberto; Giorgi, Marco; Lariccia, Paolo; Mantovani, Giancarlo; Marcantonini, Marta; Postolache, Vasile; Santocchia, Attilio; Spiga, Daniele; Bagliesi, Giuseppe; Balestri, Gabriele; Berretta, Luca; Bianucci, S; Boccali, Tommaso; Bosi, Filippo; Bracci, Fabrizio; Castaldi, Rino; Ceccanti, Marco; Cecchi, Roberto; Cerri, Claudio; Cucoanes, Andi Sebastian; Dell'Orso, Roberto; Dobur, Didar; Dutta, Suchandra; Giassi, Alessandro; Giusti, Simone; Kartashov, Dmitry; Kraan, Aafke; Lomtadze, Teimuraz; Lungu, George-Adrian; Magazzu, Guido; Mammini, Paolo; Mariani, Filippo; Martinelli, Giovanni; Moggi, Andrea; Palla, Fabrizio; Palmonari, Francesco; Petragnani, Giulio; Profeti, Alessandro; Raffaelli, Fabrizio; Rizzi, Domenico; Sanguinetti, Giulio; Sarkar, Subir; Sentenac, Daniel; Serban, Alin Titus; Slav, Adrian; Soldani, A; Spagnolo, Paolo; Tenchini, Roberto; Tolaini, Sergio; Venturi, Andrea; Verdini, Piero Giorgio; Vos, Marcel; Zaccarelli, Luciano; Avanzini, Carlo; Basti, Andrea; Benucci, Leonardo; Bocci, Andrea; Cazzola, Ugo; Fiori, Francesco; Linari, Stefano; Massa, Maurizio; Messineo, Alberto; Segneri, Gabriele; Tonelli, Guido; Azzurri, Paolo; Bernardini, Jacopo; Borrello, Laura; Calzolari, Federico; Foa, Lorenzo; Gennai, Simone; Ligabue, Franco; Petrucciani, Giovanni; Rizzi, Andrea; Yang, Zong-Chang; Benotto, Franco; Demaria, Natale; Dumitrache, Floarea; Farano, R; Borgia, Maria Assunta; Castello, Roberto; Costa, Marco; Migliore, Ernesto; Romero, Alessandra; Abbaneo, Duccio; Abbas, M; Ahmed, Ijaz; Akhtar, I; Albert, Eric; Bloch, Christoph; Breuker, Horst; Butt, Shahid Aleem; Buchmuller, Oliver; Cattai, Ariella; Delaere, Christophe; Delattre, Michel; Edera, Laura Maria; Engstrom, Pauli; Eppard, Michael; Gateau, Maryline; Gill, Karl; Giolo-Nicollerat, Anne-Sylvie; Grabit, Robert; Honma, Alan; Huhtinen, Mika; Kloukinas, Kostas; Kortesmaa, Jarmo; Kottelat, Luc-Joseph; Kuronen, Auli; Leonardo, Nuno; Ljuslin, Christer; Mannelli, Marcello; Masetti, Lorenzo; Marchioro, Alessandro; Mersi, Stefano; Michal, Sebastien; Mirabito, Laurent; Muffat-Joly, Jeannine; Onnela, Antti; Paillard, Christian; Pal, Imre; Pernot, Jean-Francois; Petagna, Paolo; Petit, Patrick; Piccut, C; Pioppi, Michele; Postema, Hans; Ranieri, Riccardo; Ricci, Daniel; Rolandi, Gigi; Ronga, Frederic Jean; Sigaud, Christophe; Syed, A; Siegrist, Patrice; Tropea, Paola; Troska, Jan; Tsirou, Andromachi; Vander Donckt, Muriel; Vasey, François; Alagoz, Enver; Amsler, Claude; Chiochia, Vincenzo; Regenfus, Christian; Robmann, Peter; Rochet, Jacky; Rommerskirchen, Tanja; Schmidt, Alexander; Steiner, Stefan; Wilke, Lotte; Church, Ivan; Cole, Joanne; Coughlan, John A; Gay, Arnaud; Taghavi, S; Tomalin, Ian R; Bainbridge, Robert; Cripps, Nicholas; Fulcher, Jonathan; Hall, Geoffrey; Noy, Matthew; Pesaresi, Mark; Radicci, Valeria; Raymond, David Mark; Sharp, Peter; Stoye, Markus; Wingham, Matthew; Zorba, Osman; Goitom, Israel; Hobson, Peter R; Reid, Ivan; Teodorescu, Liliana; Hanson, Gail; Jeng, Geng-Yuan; Liu, Haidong; Pasztor, Gabriella; Satpathy, Asish; Stringer, Robert; Mangano, Boris; Affolder, K; Affolder, T; Allen, Andrea; Barge, Derek; Burke, Samuel; Callahan, D; Campagnari, Claudio; Crook, A; D'Alfonso, Mariarosaria; Dietch, J; Garberson, Jeffrey; Hale, David; Incandela, H; Incandela, Joe; Jaditz, Stephen; Kalavase, Puneeth; Kreyer, Steven Lawrence; Kyre, Susanne; Lamb, James; Mc Guinness, C; Mills, C; Nguyen, Harold; Nikolic, Milan; Lowette, Steven; Rebassoo, Finn; Ribnik, Jacob; Richman, Jeffrey; Rubinstein, Noah; Sanhueza, S; Shah, Yousaf Syed; Simms, L; Staszak, D; Stoner, J; Stuart, David; Swain, Sanjay Kumar; Vlimant, Jean-Roch; White, Dean; Ulmer, Keith; Wagner, Stephen Robert; Bagby, Linda; Bhat, Pushpalatha C; Burkett, Kevin; Cihangir, Selcuk; Gutsche, Oliver; Jensen, Hans; Johnson, Mark; Luzhetskiy, Nikolay; Mason, David; Miao, Ting; Moccia, Stefano; Noeding, Carsten; Ronzhin, Anatoly; Skup, Ewa; Spalding, William J; Spiegel, Leonard; Tkaczyk, Slawek; Yumiceva, Francisco; Zatserklyaniy, Andriy; Zerev, E; Anghel, Ioana Maria; Bazterra, Victor Eduardo; Gerber, Cecilia Elena; Khalatian, S; Shabalina, Elizaveta; Baringer, Philip; Bean, Alice; Chen, Jie; Hinchey, Carl Louis; Martin, Christophe; Moulik, Tania; Robinson, Richard; Gritsan, Andrei; Lae, Chung Khim; Tran, Nhan Viet; Everaerts, Pieter; Hahn, Kristan Allan; Harris, Philip; Nahn, Steve; Rudolph, Matthew; Sung, Kevin; Betchart, Burton; Demina, Regina; Gotra, Yury; Korjenevski, Sergey; Miner, Daniel Carl; Orbaker, Douglas; Christofek, Leonard; Hooper, Ryan; Landsberg, Greg; Nguyen, Duong; Narain, Meenakshi; Speer, Thomas; Tsang, Ka Vang

2008-01-01

The subsystems of the CMS silicon strip tracker were integrated and commissioned at the Tracker Integration Facility (TIF) in the period from November 2006 to July 2007. As part of the commissioning, large samples of cosmic ray data were recorded under various running conditions in the absence of a magnetic field. Cosmic rays detected by scintillation counters were used to trigger the readout of up to 15\\,\\% of the final silicon strip detector, and over 4.7~million events were recorded. This document describes the cosmic track reconstruction and presents results on the performance of track and hit reconstruction as from dedicated analyses.

Using a data-centric event-driven architecture approach in the integration of real-time systems at DTP2

International Nuclear Information System (INIS)

Tuominen, Janne; Viinikainen, Mikko; Alho, Pekka; Mattila, Jouni

2014-01-01

Integration of heterogeneous and distributed systems is a challenging task, because they might be running on different platforms and written with different implementation languages by multiple organizations. Data-centricity and event-driven architecture (EDA) are concepts that help to implement versatile and well-scaling distributed systems. This paper focuses on the implementation of inter-subsystem communication in a prototype distributed remote handling control system developed at Divertor Test Platform 2 (DTP2). The control system consists of a variety of heterogeneous subsystems, including a client–server web application and hard real-time controllers. A standardized middleware solution (Data Distribution Services (DDS)) that supports a data-centric EDA approach is used to integrate the system. One of the greatest challenges in integrating a system with a data-centric EDA approach is in defining the global data space model. The selected middleware is currently only used for non-deterministic communication. For future application, we evaluated the performance of point-to-point communication with and without the presence of additional network load to ensure applicability to real-time systems. We found that, under certain limitations, the middleware can be used for soft real-time communication. Hard real-time use will require more validation with a more suitable environment

Using a data-centric event-driven architecture approach in the integration of real-time systems at DTP2

Energy Technology Data Exchange (ETDEWEB)

Tuominen, Janne, E-mail: janne.m.tuominen@tut.fi; Viinikainen, Mikko; Alho, Pekka; Mattila, Jouni

2014-10-15

Integration of heterogeneous and distributed systems is a challenging task, because they might be running on different platforms and written with different implementation languages by multiple organizations. Data-centricity and event-driven architecture (EDA) are concepts that help to implement versatile and well-scaling distributed systems. This paper focuses on the implementation of inter-subsystem communication in a prototype distributed remote handling control system developed at Divertor Test Platform 2 (DTP2). The control system consists of a variety of heterogeneous subsystems, including a client–server web application and hard real-time controllers. A standardized middleware solution (Data Distribution Services (DDS)) that supports a data-centric EDA approach is used to integrate the system. One of the greatest challenges in integrating a system with a data-centric EDA approach is in defining the global data space model. The selected middleware is currently only used for non-deterministic communication. For future application, we evaluated the performance of point-to-point communication with and without the presence of additional network load to ensure applicability to real-time systems. We found that, under certain limitations, the middleware can be used for soft real-time communication. Hard real-time use will require more validation with a more suitable environment.

Task-based data-acquisition optimization for sparse image reconstruction systems

Science.gov (United States)

Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

2017-03-01

Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

Data Driven Economic Model Predictive Control

Directory of Open Access Journals (Sweden)

Masoud Kheradmandi

2018-04-01

Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

Science.gov (United States)

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

Science.gov (United States)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Raw-data display and visual reconstruction validation in ALICE

International Nuclear Information System (INIS)

Tadel, M

2008-01-01

ALICE Event Visualization Environment (AliEVE) is based on ROOT and its GUI, 2D and 3D graphics classes. A small application kernel provides for registration and management of visualization objects. CINT scripts are used as an extensible mechanism for data extraction, selection and processing as well as for steering of frequent event-related tasks. AliEVE is used for event visualization in offline and high-level trigger frameworks. Mechanisms and base-classes provided for visual representation of raw-data for different detector-types are described. Common infrastructure for thresholding and color-coding of signal/time information, placement of detector-modules in various 2D/3D layouts and for user-interaction with displayed data is presented. Methods for visualization of raw-data on different levels of detail are discussed as they are expected to play an important role during early detector operation with poorly understood detector calibration, occupancy and noise-levels. Since September 2006 ALICE applies a regular visual-scanning procedure to simulated proton-proton data to detect any shortcomings in cluster finding, tracking and primary and secondary vertex reconstruction. A high-level of interactivity is required to allow in-depth exploration of event-structure. Navigation back to simulation records is supported for debugging purposes. Standard 2D projections and transformations are available for clusters, tracks and simplified detector geometry

Multiscale vision model for event detection and reconstruction in two-photon imaging data

DEFF Research Database (Denmark)

Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke

2014-01-01

on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities....

Measurement of Event Background Fluctuations for Charged Particle Jet Reconstruction in Pb-Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV

OpenAIRE

Abelev, Betty; Adam, Jaroslav; Adamova, Dagmar; Adare, Andrew Marshall; Aggarwal, Madan; Aglieri Rinella, Gianluca; Agocs, Andras Gabor; Agostinelli, Andrea; Aguilar Salazar, Saul; Ahammed, Zubayer; Ahmad, Arshad; Ahmad, Nazeer; Ahn, Sang Un; Akindinov, Alexander; Aleksandrov, Dmitry

2012-01-01

The effect of event background fluctuations on charged particle jet reconstruction in Pb-Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV has been measured with the ALICE experiment. The main sources of non-statistical fluctuations are characterized based purely on experimental data with an unbiased method, as well as by using single high p_t particles and simulated jets embedded into real Pb-Pb events and reconstructed with the anti-kt jet finder. The influence of a low transverse momentum cut-of...

Simulation and event reconstruction inside the PandaRoot framework

International Nuclear Information System (INIS)

Spataro, S

2008-01-01

The PANDA detector will be located at the future GSI accelerator FAIR. Its primary objective is the investigation of strong interaction with anti-proton beams, in the range up to 15 GeV/c as momentum of the incoming anti-proton. The PANDA offline simulation framework is called 'PandaRoot', as it is based upon the ROOT 5.14 package. It is characterized by a high versatility; it allows to perform simulation and analysis, to run different event generators (EvtGen, Pluto, UrQmd), different transport models (Geant3, Geant4, Fluka) with the same code, thus to compare the results simply by changing few macro lines without recompiling at all. Moreover auto-configuration scripts allow installing the full framework easily in different Linux distributions and with different compilers (the framework was installed and tested in more than 10 Linux platforms) without further manipulation. The final data are in a tree format, easily accessible and readable through simple clicks on the root browsers. The presentation will report on the actual status of the computing development inside the PandaRoot framework, in terms of detector implementation and event reconstruction

Event reconstruction in the RICH detector of the CBM experiment at FAIR

International Nuclear Information System (INIS)

Adamczewski, J.; Becker, K.-H.; Belogurov, S.; Boldyreva, N.; Chernogorov, A.; Deveaux, C.; Dobyrn, V.; Dürr, M.; Eom, J.; Eschke, J.; Höhne, C.; Kampert, K.-H.; Kleipa, V.; Kochenda, L.; Kolb, B.; Kopfer, J.; Kravtsov, P.; Lebedev, S.; Lebedeva, E.; Leonova, E.

2014-01-01

The Compressed Baryonic Matter (CBM) experiment at the future FAIR facility will investigate the QCD phase diagram at high net-baryon densities and moderate temperatures. One of the key signatures will be di-leptons emitted from the hot and dense phase in heavy-ion collisions. Measuring di-electrons, a high purity of identified electrons is required in order to suppress the background. Electron identification in CBM will be performed by a Ring Imaging Cherenkov (RICH) detector and Transition Radiation Detectors (TRD). In order to access the foreseen rare probes, the detector and the data acquisition have to handle interaction rates up to 10 MHz. Therefore, the development of fast and efficient event reconstruction algorithms is an important and challenging task in CBM. In this contribution event reconstruction and electron identification algorithms in the RICH detector are presented. So far they have been developed on simulated data but could already be tested on real data from a RICH prototype testbeam experiment at the CERN-PS. Efficient and fast ring recognition algorithms in the CBM-RICH are based on the Hough Transform method. Due to optical distortions of the rings, an ellipse fitting algorithm was elaborated to improve the ring radius resolution. An efficient algorithm based on the Artificial Neural Network was implemented for electron identification in RICH. All algorithms were significantly optimized to achieve maximum speed and minimum memory consumption. - Highlights: • Ring Imaging Cherenkov detector will serve for electron identification in CBM. • We present efficient ring recognition algorithm based on the Hough Transform method. • Developed algorithms were significantly optimized to achieve maximum speed up. • Electron identification algorithm in RICH based on the Artificial Neural Network. • Developed algorithms were successfully tested on real data from the RICH prototype

Event reconstruction in the RICH detector of the CBM experiment at FAIR

Energy Technology Data Exchange (ETDEWEB)

Adamczewski, J. [GSI Darmstadt (Germany); Becker, K.-H. [University Wuppertal (Germany); Belogurov, S. [ITEP Moscow (Russian Federation); Boldyreva, N. [PNPI Gatchina (Russian Federation); Chernogorov, A. [ITEP Moscow (Russian Federation); Deveaux, C. [University Gießen (Germany); Dobyrn, V. [PNPI Gatchina (Russian Federation); Dürr, M. [University Gießen (Germany); Eom, J. [Pusan National University (Korea, Republic of); Eschke, J. [GSI Darmstadt (Germany); Höhne, C. [University Gießen (Germany); Kampert, K.-H. [University Wuppertal (Germany); Kleipa, V. [GSI Darmstadt (Germany); Kochenda, L. [PNPI Gatchina (Russian Federation); Kolb, B. [GSI Darmstadt (Germany); Kopfer, J. [University Wuppertal (Germany); Kravtsov, P. [PNPI Gatchina (Russian Federation); Lebedev, S., E-mail: s.lebedev@gsi.de [University Gießen (Germany); Lebedeva, E. [University Gießen (Germany); Leonova, E. [PNPI Gatchina (Russian Federation); and others

2014-12-01

The Compressed Baryonic Matter (CBM) experiment at the future FAIR facility will investigate the QCD phase diagram at high net-baryon densities and moderate temperatures. One of the key signatures will be di-leptons emitted from the hot and dense phase in heavy-ion collisions. Measuring di-electrons, a high purity of identified electrons is required in order to suppress the background. Electron identification in CBM will be performed by a Ring Imaging Cherenkov (RICH) detector and Transition Radiation Detectors (TRD). In order to access the foreseen rare probes, the detector and the data acquisition have to handle interaction rates up to 10 MHz. Therefore, the development of fast and efficient event reconstruction algorithms is an important and challenging task in CBM. In this contribution event reconstruction and electron identification algorithms in the RICH detector are presented. So far they have been developed on simulated data but could already be tested on real data from a RICH prototype testbeam experiment at the CERN-PS. Efficient and fast ring recognition algorithms in the CBM-RICH are based on the Hough Transform method. Due to optical distortions of the rings, an ellipse fitting algorithm was elaborated to improve the ring radius resolution. An efficient algorithm based on the Artificial Neural Network was implemented for electron identification in RICH. All algorithms were significantly optimized to achieve maximum speed and minimum memory consumption. - Highlights: • Ring Imaging Cherenkov detector will serve for electron identification in CBM. • We present efficient ring recognition algorithm based on the Hough Transform method. • Developed algorithms were significantly optimized to achieve maximum speed up. • Electron identification algorithm in RICH based on the Artificial Neural Network. • Developed algorithms were successfully tested on real data from the RICH prototype.

SIRENA software for Athena X-IFU event reconstruction

Science.gov (United States)

Ceballos, M. T.; Cobo, B.; Peille, P.; Wilms, J.; Brand, T.; Dauser, T.; Bandler, S.; Smith, S.

2017-03-01

The X-ray Observatory Athena was proposed in April 2014 as the mission to implement the science theme "The Hot and Energetic Universe" selected by ESA for L2 (the second Large-class mission in ESA’s Cosmic Vision science programme). One of the two X-ray detectors designed to be onboard Athena is X-IFU, a cryogenic microcalorimeter based on Transition Edge Sensor (TES) technology that will provide spatially resolved high-resolution spectroscopy. X-IFU will be developed by an international consortium led by IRAP (PI), SRON (co-PI) and IAPS/INAF (co-PI) and involving ESA Member States, Japan and the United States. In Spain, IFCA (CSIC-UC) has an anticipated contribution to X-IFU through the Digital Readout Electronics (DRE) unit, in particular in the Event Processor Subsystem. For this purpose and in collaboration with the Athena end-to-end simulations team, we are currently developing the SIRENA package as part of the publicly available SIXTE end-to-end simulator. SIRENA comprises a set of processing algorithms aimed at recognizing, from a noisy signal, the intensity pulses generated by the absorption of the X-ray photons, to lately reconstruct their energy, position and arrival time. This poster describes the structure of the package and the different algorithms currently implemented as well as their comparative performance in the energy resolution achieved in the reconstruction of the instrument events.

Authoring Data-Driven Videos with DataClips.

Science.gov (United States)

Amini, Fereshteh; Riche, Nathalie Henry; Lee, Bongshin; Monroy-Hernandez, Andres; Irani, Pourang

2017-01-01

Data videos, or short data-driven motion graphics, are an increasingly popular medium for storytelling. However, creating data videos is difficult as it involves pulling together a unique combination of skills. We introduce DataClips, an authoring tool aimed at lowering the barriers to crafting data videos. DataClips allows non-experts to assemble data-driven "clips" together to form longer sequences. We constructed the library of data clips by analyzing the composition of over 70 data videos produced by reputable sources such as The New York Times and The Guardian. We demonstrate that DataClips can reproduce over 90% of our data videos corpus. We also report on a qualitative study comparing the authoring process and outcome achieved by (1) non-experts using DataClips, and (2) experts using Adobe Illustrator and After Effects to create data-driven clips. Results indicated that non-experts are able to learn and use DataClips with a short training period. In the span of one hour, they were able to produce more videos than experts using a professional editing tool, and their clips were rated similarly by an independent audience.

Data-driven storytelling

CERN Document Server

Hurter, Christophe; Diakopoulos, Nicholas ed.; Carpendale, Sheelagh

2018-01-01

This book is an accessible introduction to data-driven storytelling, resulting from discussions between data visualization researchers and data journalists. This book will be the first to define the topic, present compelling examples and existing resources, as well as identify challenges and new opportunities for research.

Combining geomorphic and documentary flood evidence to reconstruct extreme events in Mediterranean basins

Science.gov (United States)

Thorndycraft, V. R.; Benito, G.; Barriendos, M.; Rico, M.; Sánchez-Moya, Y.; Sopeña, A.; Casas, A.

2009-09-01

Palaeoflood hydrology is the reconstruction of flood magnitude and frequency using geomorphological flood evidence and is particularly valuable for extending the record of extreme floods prior to the availability of instrumental data series. This paper will provide a review of recent developments in palaeoflood hydrology and will be presented in three parts: 1) an overview of the key methodological approaches used in palaeoflood hydrology and the use of historical documentary evidence for reconstructing extreme events; 2) a summary of the Llobregat River palaeoflood case study (Catalonia, NE Spain); and 3) analysis of the AD 1617 flood and its impacts across Catalonia (including the rivers Llobregat, Ter and Segre). The key findings of the Llobregat case study were that at least eight floods occurred with discharges significantly larger than events recorded in the instrumental record, for example at the Pont de Vilomara study reach the palaeodischarges of these events were 3700-4300 m3/s compared to the 1971 flood, the largest on record, of 2300 m3/s. Five of these floods were dated to the last 3000 years and the three events directly dated by radiocarbon all occurred during cold phases of global climate. Comparison of the palaeoflood record with documentary evidence indicated that one flood, radiocarbon dated to cal. AD 1540-1670, was likely to be the AD 1617 event, the largest flood of the last 700 years. Historical records indicate that this event was caused by rainfall occurring from the 2nd to 6th November and the resultant flooding caused widespread socio-economic impacts including the destruction of at least 389 houses, 22 bridges and 17 water mills. Discharges estimated from palaeoflood records and historical flood marks indicate that the Llobregat (4680 m3/s) and Ter (2700-4500 m3/s) rivers witnessed extreme discharges in comparison to observed floods in the instrumental record (2300 and 2350 m3/s, respectively); whilst further east in the Segre River

Motion compensation for fully 4D PET reconstruction using PET superset data

Energy Technology Data Exchange (ETDEWEB)

Verhaeghe, J; Gravel, P; Mio, R; Fukasawa, R; Rosa-Neto, P; Soucy, J-P; Thompson, C J; Reader, A J, E-mail: jeroen.verhaeghe@mcgill.c [Montreal Neurological Institute, McGill University, Montreal (Canada)

2010-07-21

Fully 4D PET image reconstruction is receiving increasing research interest due to its ability to significantly reduce spatiotemporal noise in dynamic PET imaging. However, thus far in the literature, the important issue of correcting for subject head motion has not been considered. Specifically, as a direct consequence of using temporally extensive basis functions, a single instance of movement propagates to impair the reconstruction of multiple time frames, even if no further movement occurs in those frames. Existing 3D motion compensation strategies have not yet been adapted to 4D reconstruction, and as such the benefits of 4D algorithms have not yet been reaped in a clinical setting where head movement undoubtedly occurs. This work addresses this need, developing a motion compensation method suitable for fully 4D reconstruction methods which exploits an optical tracking system to measure the head motion along with PET superset data to store the motion compensated data. List-mode events are histogrammed as PET superset data according to the measured motion, and a specially devised normalization scheme for motion compensated reconstruction from the superset data is required. This work proceeds to propose the corresponding time-dependent normalization modifications which are required for a major class of fully 4D image reconstruction algorithms (those which use linear combinations of temporal basis functions). Using realistically simulated as well as real high-resolution PET data from the HRRT, we demonstrate both the detrimental impact of subject head motion in fully 4D PET reconstruction and the efficacy of our proposed modifications to 4D algorithms. Benefits are shown both for the individual PET image frames as well as for parametric images of tracer uptake and volume of distribution for {sup 18}F-FDG obtained from Patlak analysis.

An evaluation of data-driven motion estimation in comparison to the usage of external-surrogates in cardiac SPECT imaging

International Nuclear Information System (INIS)

Mukherjee, Joyeeta Mitra; Johnson, Karen L; Pretorius, P Hendrik; King, Michael A; Hutton, Brian F

2013-01-01

Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference, mutual information, normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation and entropy of the difference. Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the

CLARA: A Contemporary Approach to Physics Data Processing

Energy Technology Data Exchange (ETDEWEB)

V Gyurjyan, D Abbott, J Carbonneau, G Gilfoyle, D Heddle, G Heyes, S Paul, C Timmer, D Weygand, E Wolin

2011-12-01

In traditional physics data processing (PDP) systems, data location is static and is accessed by analysis applications. In comparison, CLARA (CLAS12 Reconstruction and Analysis framework) is an environment where data processing algorithms filter continuously flowing data. In CLARA's domain of loosely coupled services, data is not stored, but rather flows from one service to another, mutating constantly along the way. Agents, performing event processing, can then subscribe to particular data/events at any stage of the data transformation, and make intricate decisions (e.g. particle ID) by correlating events from multiple, parallel data streams and/or services. This paper presents a PDP application development framework based on service oriented and event driven architectures. This system allows users to design (Java, C++, and Python languages are supported) and deploy data processing services, as well as dynamically compose PDP applications using available services. The PDP service bus provides a layer on top of a distributed pub-sub middleware implementation, which allows complex service composition and integration without writing code. Examples of service creation and deployment, along with the CLAS12 track reconstruction application design will be presented.

Temporal Data-Driven Sleep Scheduling and Spatial Data-Driven Anomaly Detection for Clustered Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Gang Li

2016-09-01

Full Text Available The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs. Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data.

Notification Event Architecture for Traveler Screening: Predictive Traveler Screening Using Event Driven Business Process Management

Science.gov (United States)

Lynch, John Kenneth

2013-01-01

Using an exploratory model of the 9/11 terrorists, this research investigates the linkages between Event Driven Business Process Management (edBPM) and decision making. Although the literature on the role of technology in efficient and effective decision making is extensive, research has yet to quantify the benefit of using edBPM to aid the…

Seabed resident event driven profiling system (SREP). Concept, design and tests

Digital Repository Service at National Institute of Oceanography (India)

Mascarenhas, A.A.M.Q.; Afzulpurkar, S.; Maurya, P.K.; Fernandes, L.; Madhan, R.; Desa, E.S.; Dabolkar, N.A.; Navelkar, G.S.; Naik, L.; Shetye, V.G.; Shetty, N.B.; Prabhudesai, S.P.; Nagvekar, S.; Vimalakumari, D.

The seabed resident event driven profiling system (SREP) described here offers a novel, optimized approach to profiling in coastal waters from seabed to sea surface during the rough seas encountered in the southwest monsoon season (June...

Commissioning of the ATLAS Reconstruction Software with First Data

CERN Document Server

Gibson, A

2008-01-01

Looking towards first LHC collisions, the ATLAS detector is being commissioned using all types of physics data available: cosmic rays, beam-halo and beam-gas events produced during the expected LHC single beam operation period prior to proton collisions. In addition to putting in place the trigger and data acquisition chains, commissioning of the full software chain is a main goal. This is interesting not only to ensure that the reconstruction, monitoring and simulation chains are ready to deal with LHC physics data, but also to understand the detector performance in view of achieving the physics requirements. Cosmic rays have allowed us to study the ATLAS detector in terms of efficiencies, resolutions, channel integrity and alignment and calibrations. They have also allowed us to test and optimize the muon combined performance algorithms. Single beam events will allow increasing the statistics in the endcap region and to study the detector performance at the expected LHC beam crossing rate.

Selection of initial events of accelerator driven subcritical system

International Nuclear Information System (INIS)

Wang Qianglong; Hu Liqin; Wang Jiaqun; Li Yazhou; Yang Zhiyi

2013-01-01

The Probabilistic Safety Assessment (PSA) is an important tool in reactor safety analysis and a significant reference to the design and operation of reactor. It is the origin and foundation of the PSA for a reactor to select the initial events. Accelerator Driven Subcritical System (ADS) has advanced design characteristics, complicated subsystems and little engineering and operating experience, which makes it much more difficult to identify the initial events of ADS. Based on the current design project of ADS, the system's safety characteristics and special issues were analyzed in this article. After a series of deductions with Master Logic Diagram (MLD) and considering the relating experience of other advanced research reactors, a preliminary initial events was listed finally, which provided the foundation for the next safety assessment. (authors)

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.

Science.gov (United States)

Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

Event-driven charge-coupled device design and applications therefor

Science.gov (United States)

Doty, John P. (Inventor); Ricker, Jr., George R. (Inventor); Burke, Barry E. (Inventor); Prigozhin, Gregory Y. (Inventor)

2005-01-01

An event-driven X-ray CCD imager device uses a floating-gate amplifier or other non-destructive readout device to non-destructively sense a charge level in a charge packet associated with a pixel. The output of the floating-gate amplifier is used to identify each pixel that has a charge level above a predetermined threshold. If the charge level is above a predetermined threshold the charge in the triggering charge packet and in the charge packets from neighboring pixels need to be measured accurately. A charge delay register is included in the event-driven X-ray CCD imager device to enable recovery of the charge packets from neighboring pixels for accurate measurement. When a charge packet reaches the end of the charge delay register, control logic either dumps the charge packet, or steers the charge packet to a charge FIFO to preserve it if the charge packet is determined to be a packet that needs accurate measurement. A floating-diffusion amplifier or other low-noise output stage device, which converts charge level to a voltage level with high precision, provides final measurement of the charge packets. The voltage level is eventually digitized by a high linearity ADC.

Sampled-data consensus in switching networks of integrators based on edge events

Science.gov (United States)

Xiao, Feng; Meng, Xiangyu; Chen, Tongwen

2015-02-01

This paper investigates the event-driven sampled-data consensus in switching networks of multiple integrators and studies both the bidirectional interaction and leader-following passive reaction topologies in a unified framework. In these topologies, each information link is modelled by an edge of the information graph and assigned a sequence of edge events, which activate the mutual data sampling and controller updates of the two linked agents. Two kinds of edge-event-detecting rules are proposed for the general asynchronous data-sampling case and the synchronous periodic event-detecting case. They are implemented in a distributed fashion, and their effectiveness in reducing communication costs and solving consensus problems under a jointly connected topology condition is shown by both theoretical analysis and simulation examples.

Consistent data-driven computational mechanics

Science.gov (United States)

González, D.; Chinesta, F.; Cueto, E.

2018-05-01

We present a novel method, within the realm of data-driven computational mechanics, to obtain reliable and thermodynamically sound simulation from experimental data. We thus avoid the need to fit any phenomenological model in the construction of the simulation model. This kind of techniques opens unprecedented possibilities in the framework of data-driven application systems and, particularly, in the paradigm of industry 4.0.

Combination of various data analysis techniques for efficient track reconstruction in very high multiplicity events

Science.gov (United States)

Siklér, Ferenc

2017-08-01

A novel combination of established data analysis techniques for reconstructing charged-particles in high energy collisions is proposed. It uses all information available in a collision event while keeping competing choices open as long as possible. Suitable track candidates are selected by transforming measured hits to a binned, three- or four-dimensional, track parameter space. It is accomplished by the use of templates taking advantage of the translational and rotational symmetries of the detectors. Track candidates and their corresponding hits, the nodes, form a usually highly connected network, a bipartite graph, where we allow for multiple hit to track assignments, edges. In order to get a manageable problem, the graph is cut into very many minigraphs by removing a few of its vulnerable components, edges and nodes. Finally the hits are distributed among the track candidates by exploring a deterministic decision tree. A depth-limited search is performed maximizing the number of hits on tracks, and minimizing the sum of track-fit χ2. Simplified but realistic models of LHC silicon trackers including the relevant physics processes are used to test and study the performance (efficiency, purity, timing) of the proposed method in the case of single or many simultaneous proton-proton collisions (high pileup), and for single heavy-ion collisions at the highest available energies.

Development of requirements and functional specifications for crash event data recorders : final report

Science.gov (United States)

2004-12-01

The U.S. DOT has conducted research on the requirements for a Crash Event Data Recorder to facilitate the reconstruction of commercial motor vehicle crashes. This report documents the work performed on the Development of Requirements and Functiona...

Spatiotemporal Features for Asynchronous Event-based Data

Directory of Open Access Journals (Sweden)

Xavier eLagorce

2015-02-01

Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

Applying Bayesian neural networks to event reconstruction in reactor neutrino experiments

International Nuclear Information System (INIS)

Xu Ye; Xu Weiwei; Meng Yixiong; Zhu Kaien; Xu Wei

2008-01-01

A toy detector has been designed to simulate central detectors in reactor neutrino experiments in the paper. The electron samples from the Monte-Carlo simulation of the toy detector have been reconstructed by the method of Bayesian neural networks (BNNs) and the standard algorithm, a maximum likelihood method (MLD), respectively. The result of the event reconstruction using BNN has been compared with the one using MLD. Compared to MLD, the uncertainties of the electron vertex are not improved, but the energy resolutions are significantly improved using BNN. And the improvement is more obvious for the high energy electrons than the low energy ones

Automated track recognition and event reconstruction in nuclear emulsion

International Nuclear Information System (INIS)

Deines-Jones, P.; Aranas, A.; Cherry, M.L.; Dugas, J.; Kudzia, D.; Nilsen, B.S.; Sengupta, K.; Waddington, C.J.; Wefel, J.P.; Wilczynska, B.; Wilczynski, H.; Wosiek, B.

1997-01-01

The major advantages of nuclear emulsion for detecting charged particles are its submicron position resolution and sensitivity to minimum ionizing particles. These must be balanced, however, against the difficult manual microscope measurement by skilled observers required for the analysis. We have developed an automated system to acquire and analyze the microscope images from emulsion chambers. Each emulsion plate is analyzed independently, allowing coincidence techniques to be used in order to reject background and estimate error rates. The system has been used to analyze a sample of high-multiplicity Pb-Pb interactions (charged particle multiplicities ∝ 1100) produced by the 158 GeV/c per nucleon 208 Pb beam at CERN. Automatically measured events agree with our best manual measurements on 97% of all the tracks. We describe the image analysis and track reconstruction techniques, and discuss the measurement and reconstruction uncertainties. (orig.)

The Forensics Aspects of Event Data Recorders

Directory of Open Access Journals (Sweden)

Jeremy S. Daily

2008-09-01

Full Text Available The proper generation and preservation of digital data from Event Data Recorders (EDRs can provide invaluable evidence to automobile crash reconstruction investigations. However, data collected from the EDR can be difficult to use and authenticate, complicating the presentation of such information as evidence in legal proceedings. Indeed, current techniques for removing and preserving such data do not meet the court’s standards for electronic evidence. Experimentation with an EDR unit from a 2001 GMC Sierra pickup truck highlighted particular issues with repeatability of results. Fortunately, advances in the digital forensics field and memory technology can be applied to EDR analysis in order to provide more complete and usable data. The presented issues should assist in the identification and development of a model for forensically sound collection and investigation techniques for EDRs.

Measurement of Event Background Fluctuations for Charged Particle Jet Reconstruction in Pb-Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV

CERN Document Server

Abelev, Betty; Adamova, Dagmar; Adare, Andrew Marshall; Aggarwal, Madan; Aglieri Rinella, Gianluca; Agocs, Andras Gabor; Agostinelli, Andrea; Aguilar Salazar, Saul; Ahammed, Zubayer; Ahmad, Arshad; Ahmad, Nazeer; Ahn, Sang Un; Akindinov, Alexander; Aleksandrov, Dmitry; Alessandro, Bruno; Alfaro Molina, Jose Ruben; Alici, Andrea; Alkin, Anton; Almaraz Avina, Erick Jonathan; Alt, Torsten; Altini, Valerio; Altinpinar, Sedat; Altsybeev, Igor; Andrei, Cristian; Andronic, Anton; Anguelov, Venelin; Anielski, Jonas; Anson, Christopher Daniel; Anticic, Tome; Antinori, Federico; Antonioli, Pietro; Aphecetche, Laurent Bernard; Appelshauser, Harald; Arbor, Nicolas; Arcelli, Silvia; Arend, Andreas; Armesto, Nestor; Arnaldi, Roberta; Aronsson, Tomas Robert; Arsene, Ionut Cristian; Arslandok, Mesut; Asryan, Andzhey; Augustinus, Andre; Averbeck, Ralf Peter; Awes, Terry; Aysto, Juha Heikki; Azmi, Mohd Danish; Bach, Matthias Jakob; Badala, Angela; Baek, Yong Wook; Bailhache, Raphaelle Marie; Bala, Renu; Baldini Ferroli, Rinaldo; Baldisseri, Alberto; Baldit, Alain; Baltasar Dos Santos Pedrosa, Fernando; Ban, Jaroslav; Baral, Rama Chandra; Barbera, Roberto; Barile, Francesco; Barnafoldi, Gergely Gabor; Barnby, Lee Stuart; Barret, Valerie; Bartke, Jerzy Gustaw; Basile, Maurizio; Bastid, Nicole; Bathen, Bastian; Batigne, Guillaume; Batyunya, Boris; Baumann, Christoph Heinrich; Bearden, Ian Gardner; Beck, Hans; Belikov, Iouri; Bellini, Francesca; Bellwied, Rene; Belmont-Moreno, Ernesto; Beole, Stefania; Berceanu, Ionela; Bercuci, Alexandru; Berdnikov, Yaroslav; Berenyi, Daniel; Bergmann, Cyrano; Berzano, Dario; Betev, Latchezar; Bhasin, Anju; Bhati, Ashok Kumar; Bianchi, Nicola; Bianchi, Livio; Bianchin, Chiara; Bielcik, Jaroslav; Bielcikova, Jana; Bilandzic, Ante; Blanco, Francesco; Blanco, F.; Blau, Dmitry; Blume, Christoph; Boccioli, Marco; Bock, Nicolas; Bogdanov, Alexey; Boggild, Hans; Bogolyubsky, Mikhail; Boldizsar, Laszlo; Bombara, Marek; Book, Julian; Borel, Herve; Borissov, Alexander; 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De Gruttola, Daniele; Delagrange, Hugues; Del Castillo Sanchez, Eduardo; Deloff, Andrzej; Demanov, Vyacheslav; De Marco, Nora; Denes, Ervin; De Pasquale, Salvatore; Deppman, Airton; D'Erasmo, Ginevra; de Rooij, Raoul Stefan; Di Bari, Domenico; Dietel, Thomas; Di Giglio, Carmelo; Di Liberto, Sergio; Di Mauro, Antonio; Di Nezza, Pasquale; Divia, Roberto; Djuvsland, Oeystein; Dobrin, Alexandru Florin; Dobrowolski, Tadeusz Antoni; Dominguez, Isabel; Donigus, Benjamin; Dordic, Olja; Driga, Olga; Dubey, Anand Kumar; Ducroux, Laurent; Dupieux, Pascal; Dutta Majumdar, A.K.; Dutta Majumdar, Mihir Ranjan; Elia, Domenico; Emschermann, David Philip; Engel, Heiko; Erdal, Hege Austrheim; Espagnon, Bruno; Estienne, Magali Danielle; Esumi, Shinichi; Evans, David; Eyyubova, Gyulnara; Fabris, Daniela; Faivre, Julien; Falchieri, Davide; Fantoni, Alessandra; Fasel, Markus; Fearick, Roger Worsley; Fedunov, Anatoly; Fehlker, Dominik; Feldkamp, Linus; Felea, Daniel; Feofilov, Grigory; Fernandez Tellez, Arturo; 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Grigoras, Costin; Grigoriev, Vladislav; Grigoryan, Ara; Grigoryan, Smbat; Grinyov, Boris; Grion, Nevio; Gros, Philippe; Grosse-Oetringhaus, Jan Fiete; Grossiord, Jean-Yves; Grosso, Raffaele; Guber, Fedor; Guernane, Rachid; Guerra Gutierrez, Cesar; Guerzoni, Barbara; Guilbaud, Maxime Rene Joseph; Gulbrandsen, Kristjan Herlache; Gunji, Taku; Gupta, Anik; Gupta, Ramni; Gutbrod, Hans; Haaland, Oystein Senneset; Hadjidakis, Cynthia Marie; Haiduc, Maria; Hamagaki, Hideki; Hamar, Gergoe; Han, Byounghee; Hanratty, Luke David; Hansen, Alexander; Harmanova, Zuzana; Harris, John William; Hartig, Matthias; Hasegan, Dumitru; Hatzifotiadou, Despoina; Hayrapetyan, Arsen; Heckel, Stefan Thomas; Heide, Markus Ansgar; Helstrup, Haavard; Herghelegiu, Andrei Ionut; Herrera Corral, Gerardo Antonio; Herrmann, Norbert; Hetland, Kristin Fanebust; Hicks, Bernard; Hille, Per Thomas; Hippolyte, Boris; Horaguchi, Takuma; Hori, Yasuto; Hristov, Peter Zahariev; Hrivnacova, Ivana; Huang, Meidana; Huber, Sebastian Bernd; Humanic, Thomas; Hwang, Dae Sung; Ichou, Raphaelle; Ilkaev, Radiy; Ilkiv, Iryna; Inaba, Motoi; Incani, Elisa; Innocenti, Gian Michele; Innocenti, Pier Giorgio; Ippolitov, Mikhail; Irfan, Muhammad; Ivan, Cristian George; Ivanov, Marian; Ivanov, Andrey; Ivanov, Vladimir; Ivanytskyi, Oleksii; Jacholkowski, Adam Wlodzimierz; Jacobs, Peter; Jancurova, Lucia; Jang, Haeng Jin; Jangal, Swensy Gwladys; Janik, Malgorzata Anna; Janik, Rudolf; Jayarathna, Sandun; Jena, Satyajit; Jimenez Bustamante, Raul Tonatiuh; Jirden, Lennart; Jones, Peter Graham; Jung, Hyung Taik; Jung, Won Woong; Jusko, Anton; Kaidalov, Alexei; Kakoyan, Vanik; Kalcher, Sebastian; Kalinak, Peter; Kalisky, Matus; Kalliokoski, Tuomo Esa Aukusti; Kalweit, Alexander Philipp; Kanaki, Kalliopi; Kang, Ju Hwan; Kaplin, Vladimir; Karasu Uysal, Ayben; Karavichev, Oleg; Karavicheva, Tatiana; Karpechev, Evgeny; Kazantsev, Andrey; Kebschull, Udo Wolfgang; Keidel, Ralf; Khan, Shuaib Ahmad; Khan, Mohisin Mohammed; Khan, Palash; Khanzadeev, Alexei; Kharlov, Yury; Kileng, Bjarte; Kim, Minwoo; Kim, Taesoo; Kim, Se Yong; Kim, Dong Jo; Kim, Jonghyun; Kim, Jin Sook; Kim, Seon Hee; Kim, Do Won; Kim, Beomkyu; Kirsch, Stefan; Kisel, Ivan; Kiselev, Sergey; Kisiel, Adam Ryszard; Klay, Jennifer Lynn; Klein, Jochen; Klein-Bosing, Christian; Kliemant, Michael; Kluge, Alexander; Knichel, Michael Linus; Koch, Kathrin; Kohler, Markus; Kolojvari, Anatoly; Kondratiev, Valery; Kondratyeva, Natalia; Konevskih, Artem; Korneev, Andrey; Kottachchi Kankanamge Don, Chamath; Kour, Ravjeet; Kowalski, Marek; Kox, Serge; Koyithatta Meethaleveedu, Greeshma; Kral, Jiri; Kralik, Ivan; Kramer, Frederick; Kraus, Ingrid Christine; Krawutschke, Tobias; Krelina, Michal; Kretz, Matthias; Krivda, Marian; Krizek, Filip; Krus, Miroslav; Kryshen, Evgeny; Krzewicki, Mikolaj; Kucheriaev, Yury; Kuhn, Christian Claude; Kuijer, Paul; Kurashvili, Podist; Kurepin, A.B.; Kurepin, A.; Kuryakin, Alexey; Kushpil, Vasily; Kushpil, Svetlana; Kvaerno, Henning; Kweon, Min Jung; Kwon, Youngil; 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Schweda, Kai Oliver; Scioli, Gilda; Scomparin, Enrico; Scott, Patrick Aaron; Scott, Rebecca; Segato, Gianfranco; Selyuzhenkov, Ilya; Senyukov, Serhiy; Seo, Jeewon; Serci, Sergio; Serradilla, Eulogio; Sevcenco, Adrian; Sgura, Irene; Shabetai, Alexandre; Shabratova, Galina; Shahoyan, Ruben; Sharma, Natasha; Sharma, Satish; Shigaki, Kenta; Shimomura, Maya; Shtejer, Katherin; Sibiriak, Yury; Siciliano, Melinda; Sicking, Eva; Siddhanta, Sabyasachi; Siemiarczuk, Teodor; Silvermyr, David Olle Rickard; Simonetti, Giuseppe; Singaraju, Rama Narayana; Singh, Ranbir; Singha, Subhash; Sinha, Bikash; Sinha, Tinku; Sitar, Branislav; Sitta, Mario; Skaali, Bernhard; Skjerdal, Kyrre; Smakal, Radek; Smirnov, Nikolai; Snellings, Raimond; Sogaard, Carsten; Soltz, Ron Ariel; Son, Hyungsuk; Song, Jihye; Song, Myunggeun; Soos, Csaba; Soramel, Francesca; Sputowska, Iwona; Spyropoulou-Stassinaki, Martha; Srivastava, Brijesh Kumar; Stachel, Johanna; Stan, Ionel; Stefanek, Grzegorz; Stefanini, Giorgio; Steinbeck, Timm Morten; Steinpreis, Matthew; Stenlund, Evert Anders; Steyn, Gideon Francois; Stocco, Diego; Stolpovskiy, Mikhail; Strabykin, Kirill; Strmen, Peter; Suaide, Alexandre Alarcon do Passo; Subieta Vasquez, Martin Alfonso; Sugitate, Toru; Suire, Christophe Pierre; Sukhorukov, Mikhail; Sultanov, Rishat; Sumbera, Michal; Susa, Tatjana; Szanto de Toledo, Alejandro; Szarka, Imrich; Szostak, Artur Krzysztof; Tagridis, Christos; Takahashi, Jun; Tapia Takaki, Daniel Jesus; Tauro, Arturo; Tejeda Munoz, Guillermo; Telesca, Adriana; Terrevoli, Cristina; Thader, Jochen Mathias; Thomas, Deepa; Thomas, Jim; Tieulent, Raphael Noel; Timmins, Anthony; Tlusty, David; Toia, Alberica; Torii, Hisayuki; Toscano, Luca; Tosello, Flavio; Traczyk, Tomasz; Trzaska, Wladyslaw Henryk; Tsuji, Tomoya; Tumkin, Alexandr; Turrisi, Rosario; Tveter, Trine Spedstad; Ulery, Jason Glyndwr; Ullaland, Kjetil; Ulrich, Jochen; Uras, Antonio; Urban, Jozef; Urciuoli, Guido Marie; Usai, Gianluca; Vajzer, Michal; Vala, Martin; Valencia Palomo, Lizardo; Vallero, Sara; van der Kolk, Naomi; Vande Vyvre, Pierre; van Leeuwen, Marco; Vannucci, Luigi; Vargas, Aurora Diozcora; Varma, Raghava; Vasileiou, Maria; Vasiliev, Andrey; Vechernin, Vladimir; Veldhoen, Misha; Venaruzzo, Massimo; Vercellin, Ermanno; Vergara, Sergio; Vernekohl, Don Constantin; Vernet, Renaud; Verweij, Marta; Vickovic, Linda; Viesti, Giuseppe; Vikhlyantsev, Oleg; Vilakazi, Zabulon; Villalobos Baillie, Orlando; Vinogradov, Alexander; Vinogradov, Leonid; Vinogradov, Yury; Virgili, Tiziano; Viyogi, Yogendra; Vodopianov, Alexander; Voloshin, Kirill; Voloshin, Sergey; Volpe, Giacomo; von Haller, Barthelemy; Vranic, Danilo; Øvrebekk, Gaute; Vrlakova, Janka; Vulpescu, Bogdan; Vyushin, Alexey; Wagner, Boris; Wagner, Vladimir; Wan, Renzhuo; Wang, Dong; Wang, Mengliang; Wang, Yifei; Wang, Yaping; Watanabe, Kengo; Wessels, Johannes; Westerhoff, Uwe; Wiechula, Jens; Wikne, Jon; Wilde, Martin Rudolf; Wilk, Grzegorz Andrzej; Wilk, Alexander; Williams, Crispin; Windelband, Bernd Stefan; Xaplanteris Karampatsos, Leonidas; Yang, Hongyan; Yang, Shiming; Yasnopolsky, Stanislav; Yi, JunGyu; Yin, Zhongbao; Yokoyama, Hiroki; Yoo, In-Kwon; Yoon, Jongik; Yu, Weilin; Yuan, Xianbao; Yushmanov, Igor; Zach, Cenek; Zampolli, Chiara; Zaporozhets, Sergey; Zarochentsev, Andrey; Zavada, Petr; Zaviyalov, Nikolai; Zbroszczyk, Hanna Paulina; Zelnicek, Pierre; Zgura, Sorin Ion; Zhalov, Mikhail; Zhang, Xiaoming; Zhou, You; Zhou, Daicui; Zhou, Fengchu; Zhu, Xiangrong; Zichichi, Antonino; Zimmermann, Alice; Zinovjev, Gennady; Zoccarato, Yannick Denis; Zynovyev, Mykhaylo

2012-01-01

The effect of event background fluctuations on charged particle jet reconstruction in Pb-Pb collisions at $\\sqrt{s_{NN}}$ = 2.76 TeV has been measured with the ALICE experiment. The main sources of non-statistical fluctuations are characterized based purely on experimental data with an unbiased method, as well as by using single high p_t particles and simulated jets embedded into real Pb-Pb events and reconstructed with the anti-kt jet finder. The influence of a low transverse momentum cut-off on particles used in the jet reconstruction is quantified by varying the minimum track p_t between 0.15 GeV/c and 2 GeV/c. For embedded jets reconstructed from charged particles with $p_t$ > 0.15 GeV/c, the uncertainty in the reconstructed jet transverse momentum due to the heavy-ion background is measured to be 11.3 GeV/c (standard deviation) for the 10% most central Pb-Pb collisions, slightly larger than the value of 11.0 GeV/c measured using the unbiased method. For a higher particle transverse momentum threshold of ...

The Event-Driven Software Library for YARP—With Algorithms and iCub Applications

Directory of Open Access Journals (Sweden)

Arren Glover

2018-01-01

Full Text Available Event-driven (ED cameras are an emerging technology that sample the visual signal based on changes in the signal magnitude, rather than at a fixed-rate over time. The change in paradigm results in a camera with a lower latency, that uses less power, has reduced bandwidth, and higher dynamic range. Such cameras offer many potential advantages for on-line, autonomous, robots; however, the sensor data do not directly integrate with current “image-based” frameworks and software libraries. The iCub robot uses Yet Another Robot Platform (YARP as middleware to provide modular processing and connectivity to sensors and actuators. This paper introduces a library that incorporates an event-based framework into the YARP architecture, allowing event cameras to be used with the iCub (and other YARP-based robots. We describe the philosophy and methods for structuring events to facilitate processing, while maintaining low-latency and real-time operation. We also describe several processing modules made available open-source, and three example demonstrations that can be run on the neuromorphic iCub.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Science.gov (United States)

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Directory of Open Access Journals (Sweden)

Zhong Yi Wan

Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more

Reconstruction of dynamical systems from interspike intervals

International Nuclear Information System (INIS)

Sauer, T.

1994-01-01

Attractor reconstruction from interspike interval (ISI) data is described, in rough analogy with Taken's theorem for attractor reconstruction from time series. Assuming a generic integrate-and-fire model coupling the dynamical system to the spike train, there is a one-to-one correspondence between the system states and interspike interval vectors of sufficiently large dimension. The correspondence has an important implication: interspike intervals can be forecast from past history. We show that deterministically driven ISI series can be distinguished from stochastically driven ISI series on the basis of prediction error

Neutrino energy reconstruction from one-muon and one-proton events

Energy Technology Data Exchange (ETDEWEB)

Furmanski, Andrew P.; Sobczyk, Jan T.

2017-06-01

We propose a method of selecting a high-purity sample of charged current quasielastic neutrino interactions to obtain a precise reconstruction of the neutrino energy. The performance of the method was verified with several tests using genie, neut, and nuwro Monte Carlo event generators with both carbon and argon targets. The method can be useful in neutrino oscillation studies with beams of a few GeV.

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

International Nuclear Information System (INIS)

Gang, G; Siewerdsen, J; Stayman, J

2016-01-01

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

Energy Technology Data Exchange (ETDEWEB)

Gang, G; Siewerdsen, J; Stayman, J [Johns Hopkins University, Baltimore, MD (United States)

2016-06-15

Purpose: There has been increasing interest in integrating fluence field modulation (FFM) devices with diagnostic CT scanners for dose reduction purposes. Conventional FFM strategies, however, are often either based on heuristics or the analysis of filtered-backprojection (FBP) performance. This work investigates a prospective task-driven optimization of FFM for model-based iterative reconstruction (MBIR) in order to improve imaging performance at the same total dose as conventional strategies. Methods: The task-driven optimization framework utilizes an ultra-low dose 3D scout as a patient-specific anatomical model and a mathematical formation of the imaging task. The MBIR method investigated is quadratically penalized-likelihood reconstruction. The FFM objective function uses detectability index, d’, computed as a function of the predicted spatial resolution and noise in the image. To optimize performance throughout the object, a maxi-min objective was adopted where the minimum d’ over multiple locations is maximized. To reduce the dimensionality of the problem, FFM is parameterized as a linear combination of 2D Gaussian basis functions over horizontal detector pixels and projection angles. The coefficients of these bases are found using the covariance matrix adaptation evolution strategy (CMA-ES) algorithm. The task-driven design was compared with three other strategies proposed for FBP reconstruction for a calcification cluster discrimination task in an abdomen phantom. Results: The task-driven optimization yielded FFM that was significantly different from those designed for FBP. Comparing all four strategies, the task-based design achieved the highest minimum d’ with an 8–48% improvement, consistent with the maxi-min objective. In addition, d’ was improved to a greater extent over a larger area within the entire phantom. Conclusion: Results from this investigation suggests the need to re-evaluate conventional FFM strategies for MBIR. The task

Knowledge-Driven Versus Data-Driven Logics

Czech Academy of Sciences Publication Activity Database

Dubois, D.; Hájek, Petr; Prade, H.

2000-01-01

Roč. 9, č. 1 (2000), s. 65-89 ISSN 0925-8531 R&D Projects: GA AV ČR IAA1030601 Grant - others:CNRS(FR) 4008 Institutional research plan: AV0Z1030915 Keywords : epistemic logic * possibility theory * data-driven reasoning * deontic logic Subject RIV: BA - General Mathematics

Combining engineering and data-driven approaches

DEFF Research Database (Denmark)

Fischer, Katharina; De Sanctis, Gianluca; Kohler, Jochen

2015-01-01

Two general approaches may be followed for the development of a fire risk model: statistical models based on observed fire losses can support simple cost-benefit studies but are usually not detailed enough for engineering decision-making. Engineering models, on the other hand, require many assump...... to the calibration of a generic fire risk model for single family houses to Swiss insurance data. The example demonstrates that the bias in the risk estimation can be strongly reduced by model calibration.......Two general approaches may be followed for the development of a fire risk model: statistical models based on observed fire losses can support simple cost-benefit studies but are usually not detailed enough for engineering decision-making. Engineering models, on the other hand, require many...... assumptions that may result in a biased risk assessment. In two related papers we show how engineering and data-driven modelling can be combined by developing generic risk models that are calibrated to statistical data on observed fire events. The focus of the present paper is on the calibration procedure...

Measurement of the underlying event using track-based event shapes in Z→l{sup +}l{sup -} events with ATLAS

Energy Technology Data Exchange (ETDEWEB)

Schulz, Holger

2014-09-11

This thesis describes a measurement of hadron-collider event shapes in proton-proton collisions at a centre of momentum energy of 7 TeV at the Large Hadron Collider (LHC) at CERN (Conseil Europeenne pour la Recherche Nucleaire) located near Geneva (Switzerland). The analysed data (integrated luminosity: 1.1 fb{sup -1}) was recorded in 2011 with the ATLAS-experiment. Events where a Z-boson was produced in the hard sub-process which subsequently decays into an electron-positron or muon-antimuon pair were selected for this analysis. The observables are calculated using all reconstructed tracks of charged particles within the acceptance of the inner detector of ATLAS except those of the leptons of the Z-decay. Thus, this is the first measurement of its kind. The observables were corrected for background processes using data-driven methods. For the correction of so-called ''pile-up'' (multiple overlapping proton-proton collisions) a novel technique was developed and successfully applied. The data was further unfolded to correct for remaining detector effects. The obtained distributions are especially sensitive to the so-called ''Underlying Event'' and can be compared with predictions of Monte-Carlo event-generators directly, i.e. without the necessity of running time-consuming simulations of the ATLAS-detector. Finally, it was tried to improve the predictions of the event generators Pythia8 and Sherpa by finding an optimised setting of relevant model parameters in a technique called ''Tuning''. It became apparent, however, that the underlying Sjoestrand-Zijl model is unable to give a good description of the measured event-shape distributions.

Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

Directory of Open Access Journals (Sweden)

Yiwen Mei

2016-03-01

Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

Data-driven architectural production and operation

NARCIS (Netherlands)

Bier, H.H.; Mostafavi, S.

2014-01-01

Data-driven architectural production and operation as explored within Hyperbody rely heavily on system thinking implying that all parts of a system are to be understood in relation to each other. These relations are increasingly established bi-directionally so that data-driven architecture is not

Effect of PYTHIA8 tunes on event shapes and top-quark reconstruction in e$^+$e$^-$ annihilation at CLIC

CERN Document Server

Chekanov, Sergei; Fischer, Andrew; Zhang, Jinlong

2017-01-01

This paper describes the effect of PYTHIA8 tunes on event simulation of e$^+$e$^-$ collisions with center-of-mass (CM) energies of 380 GeV and 3 TeV at the proposed CLIC collider. Event shapes, such as thrust, thrust major, thrust minor, oblateness, as well as particle multiplicities have been analyzed and relative differences with respect to the default PYTHIA8 tune were determined. The effect of tunes on top-mass reconstruction in the resolved and boosted regimes was analyzed. No statistically significant variation for reconstructed top masses using invariant masses of three jets was found for events with a CM energy of 380 GeV. For the fully boosted top reconstruction at a CM energy of 3 TeV, a significant shift in reconstructed top mass of about 700 MeV for the "Montull" tune was observed. This shift correlates with an increase in particle multiplicity compared to all other PYTHIA8 tunes.

Technical Note: Correcting for signal attenuation from noisy proxy data in climate reconstructions

KAUST Repository

Ammann, C. M.

2010-04-20

Regression-based climate reconstructions scale one or more noisy proxy records against a (generally) short instrumental data series. Based on that relationship, the indirect information is then used to estimate that particular measure of climate back in time. A well-calibrated proxy record(s), if stationary in its relationship to the target, should faithfully preserve the mean amplitude of the climatic variable. However, it is well established in the statistical literature that traditional regression parameter estimation can lead to substantial amplitude attenuation if the predictors carry significant amounts of noise. This issue is known as "Measurement Error" (Fuller, 1987; Carroll et al., 2006). Climate proxies derived from tree-rings, ice cores, lake sediments, etc., are inherently noisy and thus all regression-based reconstructions could suffer from this problem. Some recent applications attempt to ward off amplitude attenuation, but implementations are often complex (Lee et al., 2008) or require additional information, e.g. from climate models (Hegerl et al., 2006, 2007). Here we explain the cause of the problem and propose an easy, generally applicable, data-driven strategy to effectively correct for attenuation (Fuller, 1987; Carroll et al., 2006), even at annual resolution. The impact is illustrated in the context of a Northern Hemisphere mean temperature reconstruction. An inescapable trade-off for achieving an unbiased reconstruction is an increase in variance, but for many climate applications the change in mean is a core interest.

Technical Note: Correcting for signal attenuation from noisy proxy data in climate reconstructions

Directory of Open Access Journals (Sweden)

C. M. Ammann

2010-04-01

Full Text Available Regression-based climate reconstructions scale one or more noisy proxy records against a (generally short instrumental data series. Based on that relationship, the indirect information is then used to estimate that particular measure of climate back in time. A well-calibrated proxy record(s, if stationary in its relationship to the target, should faithfully preserve the mean amplitude of the climatic variable. However, it is well established in the statistical literature that traditional regression parameter estimation can lead to substantial amplitude attenuation if the predictors carry significant amounts of noise. This issue is known as "Measurement Error" (Fuller, 1987; Carroll et al., 2006. Climate proxies derived from tree-rings, ice cores, lake sediments, etc., are inherently noisy and thus all regression-based reconstructions could suffer from this problem. Some recent applications attempt to ward off amplitude attenuation, but implementations are often complex (Lee et al., 2008 or require additional information, e.g. from climate models (Hegerl et al., 2006, 2007. Here we explain the cause of the problem and propose an easy, generally applicable, data-driven strategy to effectively correct for attenuation (Fuller, 1987; Carroll et al., 2006, even at annual resolution. The impact is illustrated in the context of a Northern Hemisphere mean temperature reconstruction. An inescapable trade-off for achieving an unbiased reconstruction is an increase in variance, but for many climate applications the change in mean is a core interest.

Extending the FairRoot framework to allow for simulation and reconstruction of free streaming data

International Nuclear Information System (INIS)

Al-Turany, M; Klein, D; Manafov, A; Rybalchenko, A; Uhlig, F

2014-01-01

The FairRoot framework is the standard framework for simulation, reconstruction and data analysis for the FAIR experiments. The framework is designed to optimise the accessibility for beginners and developers, to be flexible and to cope with future developments. FairRoot enhances the synergy between the different physics experiments. As a first step toward simulation of free streaming data, the time based simulation was introduced to the framework. The next step is the event source simulation. This is achieved via a client server system. After digitization the so called 'samplers' can be started, where sampler can read the data of the corresponding detector from the simulation files and make it available for the reconstruction clients. The system makes it possible to develop and validate the online reconstruction algorithms. In this work, the design and implementation of the new architecture and the communication layer will be described.

Implementation and integration in the L3 experimentation of a level-2 trigger with event building, based on C104 data driven cross-bar switches and on T9000 transputers

International Nuclear Information System (INIS)

Masserot, A.

1995-01-01

This thesis describes the new level-2 trigger system. It has been developed to fit the L3 requirements induced by the LEP phase 2 conditions. At each beam crossing, the system memorizes the trigger data, builds-up the events selected by the level-1 hard-wired processors and finally rejects on-line the background identified by algorithms coded in Fortran. Based on T9000 Transputers and on C104 data driven cross-bar switches, the system uses prototypes designed by INMOS/SGS THOMSON for parallel processing applications. Emphasis is set on a new event building technic, on its integration in L3 and on performance. (author). 38 refs., 68 figs., 36 tabs

NEW FERMI-LAT EVENT RECONSTRUCTION REVEALS MORE HIGH-ENERGY GAMMA RAYS FROM GAMMA-RAY BURSTS

Energy Technology Data Exchange (ETDEWEB)

Atwood, W. B. [Santa Cruz Institute for Particle Physics, Department of Physics and Department of Astronomy and Astrophysics, University of California at Santa Cruz, Santa Cruz, CA 95064 (United States); Baldini, L. [Universita di Pisa and Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa (Italy); Bregeon, J.; Pesce-Rollins, M.; Sgro, C.; Tinivella, M. [Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa (Italy); Bruel, P. [Laboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Palaiseau (France); Chekhtman, A. [Center for Earth Observing and Space Research, College of Science, George Mason University, Fairfax, VA 22030 (United States); Cohen-Tanugi, J. [Laboratoire Univers et Particules de Montpellier, Universite Montpellier 2, CNRS/IN2P3, F-34095 Montpellier (France); Drlica-Wagner, A.; Omodei, N.; Rochester, L. S.; Usher, T. L. [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States); Granot, J. [Department of Natural Sciences, The Open University of Israel, 1 University Road, P.O. Box 808, Ra' anana 43537 (Israel); Longo, F. [Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, I-34127 Trieste (Italy); Razzaque, S. [Department of Physics, University of Johannesburg, Auckland Park 2006 (South Africa); Zimmer, S., E-mail: melissa.pesce.rollins@pi.infn.it, E-mail: nicola.omodei@stanford.edu, E-mail: granot@openu.ac.il [Department of Physics, Stockholm University, AlbaNova, SE-106 91 Stockholm (Sweden)

2013-09-01

Based on the experience gained during the four and a half years of the mission, the Fermi-LAT Collaboration has undertaken a comprehensive revision of the event-level analysis going under the name of Pass 8. Although it is not yet finalized, we can test the improvements in the new event reconstruction with the special case of the prompt phase of bright gamma-ray bursts (GRBs), where the signal-to-noise ratio is large enough that loose selection cuts are sufficient to identify gamma rays associated with the source. Using the new event reconstruction, we have re-analyzed 10 GRBs previously detected by the Large Area Telescope (LAT) for which an X-ray/optical follow-up was possible and found four new gamma rays with energies greater than 10 GeV in addition to the seven previously known. Among these four is a 27.4 GeV gamma ray from GRB 080916C, which has a redshift of 4.35, thus making it the gamma ray with the highest intrinsic energy ({approx}147 GeV) detected from a GRB. We present here the salient aspects of the new event reconstruction and discuss the scientific implications of these new high-energy gamma rays, such as constraining extragalactic background light models, Lorentz invariance violation tests, the prompt emission mechanism, and the bulk Lorentz factor of the emitting region.

Parallelization of an existing high energy physics event reconstruction software package

International Nuclear Information System (INIS)

Schiefer, R.; Francis, D.

1996-01-01

Software parallelization allows an efficient use of available computing power to increase the performance of applications. In a case study the authors have investigated the parallelization of high energy physics event reconstruction software in terms of costs (effort, computing resource requirements), benefits (performance increase) and the feasibility of a systematic parallelization approach. Guidelines facilitating a parallel implementation are proposed for future software development

Data-driven discovery of Koopman eigenfunctions using deep learning

Science.gov (United States)

Lusch, Bethany; Brunton, Steven L.; Kutz, J. Nathan

2017-11-01

Koopman operator theory transforms any autonomous non-linear dynamical system into an infinite-dimensional linear system. Since linear systems are well-understood, a mapping of non-linear dynamics to linear dynamics provides a powerful approach to understanding and controlling fluid flows. However, finding the correct change of variables remains an open challenge. We present a strategy to discover an approximate mapping using deep learning. Our neural networks find this change of variables, its inverse, and a finite-dimensional linear dynamical system defined on the new variables. Our method is completely data-driven and only requires measurements of the system, i.e. it does not require derivatives or knowledge of the governing equations. We find a minimal set of approximate Koopman eigenfunctions that are sufficient to reconstruct and advance the system to future states. We demonstrate the method on several dynamical systems.

Data-driven forward model inference for EEG brain imaging

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

2016-01-01

Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

A Full Parallel Event Driven Readout Technique for Area Array SPAD FLIM Image Sensors

Directory of Open Access Journals (Sweden)

Kaiming Nie

2016-01-01

Full Text Available This paper presents a full parallel event driven readout method which is implemented in an area array single-photon avalanche diode (SPAD image sensor for high-speed fluorescence lifetime imaging microscopy (FLIM. The sensor only records and reads out effective time and position information by adopting full parallel event driven readout method, aiming at reducing the amount of data. The image sensor includes four 8 × 8 pixel arrays. In each array, four time-to-digital converters (TDCs are used to quantize the time of photons’ arrival, and two address record modules are used to record the column and row information. In this work, Monte Carlo simulations were performed in Matlab in terms of the pile-up effect induced by the readout method. The sensor’s resolution is 16 × 16. The time resolution of TDCs is 97.6 ps and the quantization range is 100 ns. The readout frame rate is 10 Mfps, and the maximum imaging frame rate is 100 fps. The chip’s output bandwidth is 720 MHz with an average power of 15 mW. The lifetime resolvability range is 5–20 ns, and the average error of estimated fluorescence lifetimes is below 1% by employing CMM to estimate lifetimes.

Effective Data-Driven Calibration for a Galvanometric Laser Scanning System Using Binocular Stereo Vision.

Science.gov (United States)

Tu, Junchao; Zhang, Liyan

2018-01-12

A new solution to the problem of galvanometric laser scanning (GLS) system calibration is presented. Under the machine learning framework, we build a single-hidden layer feedforward neural network (SLFN）to represent the GLS system, which takes the digital control signal at the drives of the GLS system as input and the space vector of the corresponding outgoing laser beam as output. The training data set is obtained with the aid of a moving mechanism and a binocular stereo system. The parameters of the SLFN are efficiently solved in a closed form by using extreme learning machine (ELM). By quantitatively analyzing the regression precision with respective to the number of hidden neurons in the SLFN, we demonstrate that the proper number of hidden neurons can be safely chosen from a broad interval to guarantee good generalization performance. Compared to the traditional model-driven calibration, the proposed calibration method does not need a complex modeling process and is more accurate and stable. As the output of the network is the space vectors of the outgoing laser beams, it costs much less training time and can provide a uniform solution to both laser projection and 3D-reconstruction, in contrast with the existing data-driven calibration method which only works for the laser triangulation problem. Calibration experiment, projection experiment and 3D reconstruction experiment are respectively conducted to test the proposed method, and good results are obtained.

Effective Data-Driven Calibration for a Galvanometric Laser Scanning System Using Binocular Stereo Vision

Directory of Open Access Journals (Sweden)

Junchao Tu

2018-01-01

Full Text Available A new solution to the problem of galvanometric laser scanning (GLS system calibration is presented. Under the machine learning framework, we build a single-hidden layer feedforward neural network (SLFN）to represent the GLS system, which takes the digital control signal at the drives of the GLS system as input and the space vector of the corresponding outgoing laser beam as output. The training data set is obtained with the aid of a moving mechanism and a binocular stereo system. The parameters of the SLFN are efficiently solved in a closed form by using extreme learning machine (ELM. By quantitatively analyzing the regression precision with respective to the number of hidden neurons in the SLFN, we demonstrate that the proper number of hidden neurons can be safely chosen from a broad interval to guarantee good generalization performance. Compared to the traditional model-driven calibration, the proposed calibration method does not need a complex modeling process and is more accurate and stable. As the output of the network is the space vectors of the outgoing laser beams, it costs much less training time and can provide a uniform solution to both laser projection and 3D-reconstruction, in contrast with the existing data-driven calibration method which only works for the laser triangulation problem. Calibration experiment, projection experiment and 3D reconstruction experiment are respectively conducted to test the proposed method, and good results are obtained.

Reconstruction of Clear-PEM data with STIR

CERN Document Server

Martins, M V; Rodrigues, P; Trindade, A; Oliveira, N; Correia, M; Cordeiro, H; Ferreira, N C; Varela, J; Almeida, P

2006-01-01

The Clear-PEM scanner is a device based on planar detectors that is currently under development within the Crystal Clear Collaboration, at CERN. The basis for 3D image reconstruction in Clear-PEM is the software for tomographic image reconstruction (STIR). STIR is an open source object-oriented library that efficiently deals with the 3D positron emission tomography data sets. This library was originally designed for the traditional cylindrical scanners. In order to make its use compatible with planar scanner data, new functionalities were introduced into the library's framework. In this work, Monte Carlo simulations of the Clear-PEM scanner acquisitions were used as input for image reconstruction with the 3D OSEM algorithm available in STIR. The results presented indicate that dual plate PEM data can be accurately reconstructed using the enhanced STIR framework.

KNMI DataLab experiences in serving data-driven innovations

Science.gov (United States)

Noteboom, Jan Willem; Sluiter, Raymond

2016-04-01

Climate change research and innovations in weather forecasting rely more and more on (Big) data. Besides increasing data from traditional sources (such as observation networks, radars and satellites), the use of open data, crowd sourced data and the Internet of Things (IoT) is emerging. To deploy these sources of data optimally in our services and products, KNMI has established a DataLab to serve data-driven innovations in collaboration with public and private sector partners. Big data management, data integration, data analytics including machine learning and data visualization techniques are playing an important role in the DataLab. Cross-domain data-driven innovations that arise from public-private collaborative projects and research programmes can be explored, experimented and/or piloted by the KNMI DataLab. Furthermore, advice can be requested on (Big) data techniques and data sources. In support of collaborative (Big) data science activities, scalable environments are offered with facilities for data integration, data analysis and visualization. In addition, Data Science expertise is provided directly or from a pool of internal and external experts. At the EGU conference, gained experiences and best practices are presented in operating the KNMI DataLab to serve data-driven innovations for weather and climate applications optimally.

Jini service to reconstruct tomographic data

Science.gov (United States)

Knoll, Peter; Mirzaei, S.; Koriska, K.; Koehn, H.

2002-06-01

A number of imaging systems rely on the reconstruction of a 3- dimensional model from its projections through the process of computed tomography (CT). In medical imaging, for example magnetic resonance imaging (MRI), positron emission tomography (PET), and Single Computer Tomography (SPECT) acquire two-dimensional projections of a three dimensional projections of a three dimensional object. In order to calculate the 3-dimensional representation of the object, i.e. its voxel distribution, several reconstruction algorithms have been developed. Currently, mainly two reconstruct use: the filtered back projection(FBP) and iterative methods. Although the quality of iterative reconstructed SPECT slices is better than that of FBP slices, such iterative algorithms are rarely used for clinical routine studies because of their low availability and increased reconstruction time. We used Jini and a self-developed iterative reconstructions algorithm to design and implement a Jini reconstruction service. With this service, the physician selects the patient study from a database and a Jini client automatically discovers the registered Jini reconstruction services in the department's Intranet. After downloading the proxy object the this Jini service, the SPECT acquisition data are reconstructed. The resulting transaxial slices are visualized using a Jini slice viewer, which can be used for various imaging modalities.

An iterative reconstruction from truncated projection data

International Nuclear Information System (INIS)

Anon.

1985-01-01

Various methods have been proposed for tomographic reconstruction from truncated projection data. In this paper, a reconstructive method is discussed which consists of iterations of filtered back-projection, reprojection and some nonlinear processings. First, the method is so constructed that it converges to a fixed point. Then, to examine its effectiveness, comparisons are made by computer experiments with two existing reconstructive methods for truncated projection data, that is, the method of extrapolation based on the smooth assumption followed by filtered back-projection, and modified additive ART

Triggerless Readout with Time and Amplitude Reconstruction of Event Based on Deconvolution Algorithm

International Nuclear Information System (INIS)

Kulis, S.; Idzik, M.

2011-01-01

In future linear colliders like CLIC, where the period between the bunch crossings is in a sub-nanoseconds range ( 500 ps), an appropriate detection technique with triggerless signal processing is needed. In this work we discuss a technique, based on deconvolution algorithm, suitable for time and amplitude reconstruction of an event. In the implemented method the output of a relatively slow shaper (many bunch crossing periods) is sampled and digitalised in an ADC and then the deconvolution procedure is applied to digital data. The time of an event can be found with a precision of few percent of sampling time. The signal to noise ratio is only slightly decreased after passing through the deconvolution filter. The performed theoretical and Monte Carlo studies are confirmed by the results of preliminary measurements obtained with the dedicated system comprising of radiation source, silicon sensor, front-end electronics, ADC and further digital processing implemented on a PC computer. (author)

Data-Driven and Expectation-Driven Discovery of Empirical Laws.

Science.gov (United States)

1982-10-10

occurred in small integer proportions to each other. In 1809, Joseph Gay- Lussac found evidence for his law of combining volumes, which stated that a...of Empirical Laws Patrick W. Langley Gary L. Bradshaw Herbert A. Simon T1he Robotics Institute Carnegie-Mellon University Pittsburgh, Pennsylvania...Subtitle) S. TYPE OF REPORT & PERIOD COVERED Data-Driven and Expectation-Driven Discovery Interim Report 2/82-10/82 of Empirical Laws S. PERFORMING ORG

Ballooning-mirror instability and internally driven Pc 4--5 wave events

International Nuclear Information System (INIS)

Cheng, C.Z.; Qian, Q.; Takahashi, K.; Lui, A.T.Y.

1994-03-01

A kinetic-MHD field-aligned eigenmode stability analysis of low frequency ballooning-mirror instabilities has been performed for anisotropic pressure plasma sin the magnetosphere. The ballooning mode is mainly a transverse wave driven unstable by pressure gradient in the bad curvature region. The mirror mode with a dominant compressional magnetic field perturbation is excited when the product of plasma beta and pressure anisotropy (P perpendicular /P parallel > 1) is large. From the AMPTE/CCE particle and magnetic field data observed during Pc 4--5 wave events the authors compute the ballooning-mirror instability parameters and perform a correlation study with the theoretical instability threshold. They find that compressional Pc 5 waves approximately satisfy the ballooning-mirror instability condition, and transverse Pc 4--5 waves are probably related to resonant ballooning instabilities with small pressure anisotropy

Sharing adverse drug event data using business intelligence technology.

Science.gov (United States)

Horvath, Monica M; Cozart, Heidi; Ahmad, Asif; Langman, Matthew K; Ferranti, Jeffrey

2009-03-01

Duke University Health System uses computerized adverse drug event surveillance as an integral part of medication safety at 2 community hospitals and an academic medical center. This information must be swiftly communicated to organizational patient safety stakeholders to find opportunities to improve patient care; however, this process is encumbered by highly manual methods of preparing the data. Following the examples of other industries, we deployed a business intelligence tool to provide dynamic safety reports on adverse drug events. Once data were migrated into the health system data warehouse, we developed census-adjusted reports with user-driven prompts. Drill down functionality enables navigation from aggregate trends to event details by clicking report graphics. Reports can be accessed by patient safety leadership either through an existing safety reporting portal or the health system performance improvement Web site. Elaborate prompt screens allow many varieties of reports to be created quickly by patient safety personnel without consultation with the research analyst. The reduction in research analyst workload because of business intelligence implementation made this individual available to additional patient safety projects thereby leveraging their talents more effectively. Dedicated liaisons are essential to ensure clear communication between clinical and technical staff throughout the development life cycle. Design and development of the business intelligence model for adverse drug event data must reflect the eccentricities of the operational system, especially as new areas of emphasis evolve. Future usability studies examining the data presentation and access model are needed.

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

Science.gov (United States)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2017-06-01

The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

FIREDATA, Nuclear Power Plant Fire Event Data Base

International Nuclear Information System (INIS)

Wheelis, W.T.

2001-01-01

1 - Description of program or function: FIREDATA contains raw fire event data from 1965 through June 1985. These data were obtained from a number of reference sources including the American Nuclear Insurers, Licensee Event Reports, Nuclear Power Experience, Electric Power Research Institute Fire Loss Data and then collated into one database developed in the personal computer database management system, dBASE III. FIREDATA is menu-driven and asks interactive questions of the user that allow searching of the database for various aspects of a fire such as: location, mode of plant operation at the time of the fire, means of detection and suppression, dollar loss, etc. Other features include the capability of searching for single or multiple criteria (using Boolean 'and' or 'or' logical operations), user-defined keyword searches of fire event descriptions, summary displays of fire event data by plant name of calendar date, and options for calculating the years of operating experience for all commercial nuclear power plants from any user-specified date and the ability to display general plant information. 2 - Method of solution: The six database files used to store nuclear power plant fire event information, FIRE, DESC, SUM, OPEXPER, OPEXBWR, and EXPERPWR, are accessed by software to display information meeting user-specified criteria or to perform numerical calculations (e.g., to determine the operating experience of a nuclear plant). FIRE contains specific searchable data relating to each of 354 fire events. A keyword concept is used to search each of the 31 separate entries or fields. DESC contains written descriptions of each of the fire events. SUM holds basic plant information for all plants proposed, under construction, in operation, or decommissioned. This includes the initial criticality and commercial operation dates, the physical location of the plant, and its operating capacity. OPEXPER contains date information and data on how various plant locations are

A novel String Banana Template Method for Tracks Reconstruction in High Multiplicity Events with significant Multiple Scattering and its Firmware Implementation

CERN Document Server

Kulinich, P; Krylov, V

2004-01-01

Novel String Banana Template Method (SBTM) for track reconstruction in difficult conditions is proposed and implemented for off-line analysis of relativistic heavy ion collision events. The main idea of the method is in use of features of ensembles of tracks selected by 3-fold coincidence. Two steps model of track is used: the first one - averaged over selected ensemble and the second - per event dependent. It takes into account Multiple Scattering (MS) for this particular track. SBTM relies on use of stored templates generated by precise Monte Carlo simulation, so it's more time efficient for the case of 2D spectrometer. All data required for track reconstruction in such difficult conditions could be prepared in convenient format for fast use. Its template based nature and the fact that the SBTM track model is actually very close to the hits implies that it can be implemented in a firmware processor. In this report a block diagram of firmware based pre-processor for track reconstruction in CMS-like Si tracke...

Tool for Constructing Data Albums for Significant Weather Events

Science.gov (United States)

Kulkarni, A.; Ramachandran, R.; Conover, H.; McEniry, M.; Goodman, H.; Zavodsky, B. T.; Braun, S. A.; Wilson, B. D.

2012-12-01

Case study analysis and climatology studies are common approaches used in Atmospheric Science research. Research based on case studies involves a detailed description of specific weather events using data from different sources, to characterize physical processes in play for a given event. Climatology-based research tends to focus on the representativeness of a given event, by studying the characteristics and distribution of a large number of events. To gather relevant data and information for case studies and climatology analysis is tedious and time consuming; current Earth Science data systems are not suited to assemble multi-instrument, multi mission datasets around specific events. For example, in hurricane science, finding airborne or satellite data relevant to a given storm requires searching through web pages and data archives. Background information related to damages, deaths, and injuries requires extensive online searches for news reports and official storm summaries. We will present a knowledge synthesis engine to create curated "Data Albums" to support case study analysis and climatology studies. The technological challenges in building such a reusable and scalable knowledge synthesis engine are several. First, how to encode domain knowledge in a machine usable form? This knowledge must capture what information and data resources are relevant and the semantic relationships between the various fragments of information and data. Second, how to extract semantic information from various heterogeneous sources including unstructured texts using the encoded knowledge? Finally, how to design a structured database from the encoded knowledge to store all information and to support querying? The structured database must allow both knowledge overviews of an event as well as drill down capability needed for detailed analysis. An application ontology driven framework is being used to design the knowledge synthesis engine. The knowledge synthesis engine is being

Brief communication: 3-D reconstruction of a collapsed rock pillar from Web-retrieved images and terrestrial lidar data - the 2005 event of the west face of the Drus (Mont Blanc massif)

Science.gov (United States)

Guerin, Antoine; Abellán, Antonio; Matasci, Battista; Jaboyedoff, Michel; Derron, Marc-Henri; Ravanel, Ludovic

2017-07-01

In June 2005, a series of major rockfall events completely wiped out the Bonatti Pillar located in the legendary Drus west face (Mont Blanc massif, France). Terrestrial lidar scans of the west face were acquired after this event, but no pre-event point cloud is available. Thus, in order to reconstruct the volume and the shape of the collapsed blocks, a 3-D model has been built using photogrammetry (structure-from-motion (SfM) algorithms) based on 30 pictures collected on the Web. All these pictures were taken between September 2003 and May 2005. We then reconstructed the shape and volume of the fallen compartment by comparing the SfM model with terrestrial lidar data acquired in October 2005 and November 2011. The volume is calculated to 292 680 m3 (±5.6 %). This result is close to the value previously assessed by Ravanel and Deline (2008) for this same rock avalanche (265 000 ± 10 000 m3). The difference between these two estimations can be explained by the rounded shape of the volume determined by photogrammetry, which may lead to a volume overestimation. However it is not excluded that the volume calculated by Ravanel and Deline (2008) is slightly underestimated, the thickness of the blocks having been assessed manually from historical photographs.

Minimizing cache misses in an event-driven network server: A case study of TUX

DEFF Research Database (Denmark)

Bhatia, Sapan; Consel, Charles; Lawall, Julia Laetitia

2006-01-01

We analyze the performance of CPU-bound network servers and demonstrate experimentally that the degradation in the performance of these servers under high-concurrency workloads is largely due to inefficient use of the hardware caches. We then describe an approach to speeding up event-driven network...... servers by optimizing their use of the L2 CPU cache in the context of the TUX Web server, known for its robustness to heavy load. Our approach is based on a novel cache-aware memory allocator and a specific scheduling strategy that together ensure that the total working data set of the server stays...

Reconstruction efficiency and precision for the events detected by the BIS-2 installation using the Perun pattern recognition program

International Nuclear Information System (INIS)

Burilkov, D.T.; Genchev, V.I.; Markov, P.K.; Likhachev, M.F.; Takhtamyshev, G.G.; Todorov, P.T.; Trayanov, P.K.

1982-01-01

Results of studying the efficiency and accuracy of the track and event reconstruction with the Perun pattern recognition program used in the experiments carried out at the BIS-2 installation are presented. The Monte Carlo method is used for simulating the processes of neutron interactions with matter. The con-- clusion is made that the Perun program correctly, with good accuracy and high efficiency reconstructs complex multiparticle events [ru

The FEDRA-Framework for emulsion data reconstruction and analysis in the OPERA experiment

International Nuclear Information System (INIS)

Tioukov, V.; Kreslo, I.; Petukhov, Y.; Sirri, G.

2006-01-01

OPERA is a massive lead/emulsion target for a long-baseline neutrino oscillation search. More than 90% of the useful experimental data in OPERA will be produced by the scanning of emulsion plates with the automatic microscopes. The main goal of the data processing in OPERA will be the search, analysis and identification of primary and secondary vertices produced by neutrino in lead-emulsion target. The volume of middle- and high-level data to be analysed and stored is expected to be of the order of several Gb per event. The storage, calibration, reconstruction, analysis and visualization of this data is the task of FEDRA system written in C ++ and based on ROOT framework. The system is now actively used for processing of test beams and simulation data. Several interesting algorithmic solutions permits us to make effective code for fast pattern recognition in heavy signal/noise conditions. The system consists of the storage part, intercalibration and segments linking part, track finding and fitting, vertex finding and fitting and kinematical analysis parts. Kalman Filtering technique is used for tracks and vertex fitting. ROOT-based event display is used for interactive analysis of the special events. iltering technique is used for tracks and vertex fitting. ROOT-based event display is used for interactive analysis of the special events

Data-driven modeling of nano-nose gas sensor arrays

DEFF Research Database (Denmark)

Alstrøm, Tommy Sonne; Larsen, Jan; Nielsen, Claus Højgård

2010-01-01

We present a data-driven approach to classification of Quartz Crystal Microbalance (QCM) sensor data. The sensor is a nano-nose gas sensor that detects concentrations of analytes down to ppm levels using plasma polymorized coatings. Each sensor experiment takes approximately one hour hence...... the number of available training data is limited. We suggest a data-driven classification model which work from few examples. The paper compares a number of data-driven classification and quantification schemes able to detect the gas and the concentration level. The data-driven approaches are based on state...

Event-Driven Control for Networked Control Systems With Quantization and Markov Packet Losses.

Science.gov (United States)

Yang, Hongjiu; Xu, Yang; Zhang, Jinhui

2016-05-23

In this paper, event-driven is used in a networked control system (NCS) which is subjected to the effect of quantization and packet losses. A discrete event-detector is used to monitor specific events in the NCS. Both an arbitrary region quantizer and Markov jump packet losses are also considered for the NCS. Based on zoom strategy and Lyapunov theory, a complete proof is given to guarantee mean square stability of the closed-loop system. Stabilization of the NCS is ensured by designing a feedback controller. Lastly, an inverted pendulum model is given to show the advantages and effectiveness of the proposed results.

Extension of a data-driven gating technique to 3D, whole body PET studies

International Nuclear Information System (INIS)

Schleyer, Paul J; O'Doherty, Michael J; Marsden, Paul K

2011-01-01

Respiratory gating can be used to separate a PET acquisition into a series of near motion-free bins. This is typically done using additional gating hardware; however, software-based methods can derive the respiratory signal from the acquired data itself. The aim of this work was to extend a data-driven respiratory gating method to acquire gated, 3D, whole body PET images of clinical patients. The existing method, previously demonstrated with 2D, single bed-position data, uses a spectral analysis to find regions in raw PET data which are subject to respiratory motion. The change in counts over time within these regions is then used to estimate the respiratory signal of the patient. In this work, the gating method was adapted to only accept lines of response from a reduced set of axial angles, and the respiratory frequency derived from the lung bed position was used to help identify the respiratory frequency in all other bed positions. As the respiratory signal does not identify the direction of motion, a registration-based technique was developed to align the direction for all bed positions. Data from 11 clinical FDG PET patients were acquired, and an optical respiratory monitor was used to provide a hardware-based signal for comparison. All data were gated using both the data-driven and hardware methods, and reconstructed. The centre of mass of manually defined regions on gated images was calculated, and the overall displacement was defined as the change in the centre of mass between the first and last gates. The mean displacement was 10.3 mm for the data-driven gated images and 9.1 mm for the hardware gated images. No significant difference was found between the two gating methods when comparing the displacement values. The adapted data-driven gating method was demonstrated to successfully produce respiratory gated, 3D, whole body, clinical PET acquisitions.

Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

International Nuclear Information System (INIS)

Chen Jian-Lin; Li Lei; Wang Lin-Yuan; Cai Ai-Long; Xi Xiao-Qi; Zhang Han-Ming; Li Jian-Xin; Yan Bin

2015-01-01

The projection matrix model is used to describe the physical relationship between reconstructed object and projection. Such a model has a strong influence on projection and backprojection, two vital operations in iterative computed tomographic reconstruction. The distance-driven model (DDM) is a state-of-the-art technology that simulates forward and back projections. This model has a low computational complexity and a relatively high spatial resolution; however, it includes only a few methods in a parallel operation with a matched model scheme. This study introduces a fast and parallelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations. Our proposed model has been implemented on a GPU (graphic processing unit) platform and has achieved satisfactory computational efficiency with no approximation. The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop, respectively, with an image size of 256×256×256 and 360 projections with a size of 512×512. We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation. The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction. (paper)

On the Role of Ionospheric Ions in Sawtooth Events

Science.gov (United States)

Lund, E. J.; Nowrouzi, N.; Kistler, L. M.; Cai, X.; Frey, H. U.

2018-01-01

Simulations have suggested that feedback of heavy ions originating in the ionosphere is an important mechanism for driving sawtooth injections. However, this feedback may only be necessary for events driven by coronal mass ejections (CMEs), whereas in events driven by streaming interaction regions (SIRs), solar wind variability may suffice to drive these injections. Here we present case studies of two sawtooth events for which in situ data are available in both the magnetotail (Cluster) and the nightside auroral region (FAST), as well as global auroral images (IMAGE). One event, on 1 October 2001, was driven by a CME; the other, on 24 October 2002, was driven by an SIR. The available data do not support the hypothesis that heavy ion feedback is necessary to drive either event. This result is consistent with simulations of the SIR-driven event but disagrees with simulation results for a different CME-driven event. We also find that in an overwhelming majority of the sawtooth injections for which Cluster tail data are available, the O+ observed in the tail comes from the cusp rather than the nightside auroral region, which further casts doubt on the hypothesis that ionospheric heavy ion feedback is the cause of sawtooth injections.

Calibration of the electromagnetic calorimeter of the Atlas detector: reconstruction of events with non-pointing photons in the frame of a GMSB supersymmetric model; Etalonnage du calorimetre electromagnetique du detecteur Atlas: reconstruction des evenements avec des photons non pointants das le cadre d'un modele supersymetrique GMSB

Energy Technology Data Exchange (ETDEWEB)

Prieur, D

2005-04-15

The analysis of test-beam data is focused on the calibration of the ATLAS electromagnetic calorimeter. An electrical model has been developed to predict the shape of the physics pulse out of the calibration signal in order to produce optimal filtering coefficients. They are used to compute energy while minimizing electronic noise and getting rid of any possible time shift. Using these coefficients, the uniformity response is 0.6%, in agreement with the 0.7% global constant term required for the whole calorimeter. The study of non pointing photon is driven by the detection of long lived neutralinos predicted by GMSB SUSY models. A systematic study with a detailed simulation of the ATLAS detector was performed to determine the electromagnetic calorimeter angular resolution for such photons. Results were used to parametrized the detector response and to reconstruct SUSY events from this model. (author)

Three-dimensional dictionary-learning reconstruction of (23)Na MRI data.

Science.gov (United States)

Behl, Nicolas G R; Gnahm, Christine; Bachert, Peter; Ladd, Mark E; Nagel, Armin M

2016-04-01

To reduce noise and artifacts in (23)Na MRI with a Compressed Sensing reconstruction and a learned dictionary as sparsifying transform. A three-dimensional dictionary-learning compressed sensing reconstruction algorithm (3D-DLCS) for the reconstruction of undersampled 3D radial (23)Na data is presented. The dictionary used as the sparsifying transform is learned with a K-singular-value-decomposition (K-SVD) algorithm. The reconstruction parameters are optimized on simulated data, and the quality of the reconstructions is assessed with peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The performance of the algorithm is evaluated in phantom and in vivo (23)Na MRI data of seven volunteers and compared with nonuniform fast Fourier transform (NUFFT) and other Compressed Sensing reconstructions. The reconstructions of simulated data have maximal PSNR and SSIM for an undersampling factor (USF) of 10 with numbers of averages equal to the USF. For 10-fold undersampling, the PSNR is increased by 5.1 dB compared with the NUFFT reconstruction, and the SSIM by 24%. These results are confirmed by phantom and in vivo (23)Na measurements in the volunteers that show markedly reduced noise and undersampling artifacts in the case of 3D-DLCS reconstructions. The 3D-DLCS algorithm enables precise reconstruction of undersampled (23)Na MRI data with markedly reduced noise and artifact levels compared with NUFFT reconstruction. Small structures are well preserved. © 2015 Wiley Periodicals, Inc.

Maximum entropy reconstruction of poloidal magnetic field and radial electric field profiles in tokamaks

Science.gov (United States)

Chen, Yihang; Xiao, Chijie; Yang, Xiaoyi; Wang, Tianbo; Xu, Tianchao; Yu, Yi; Xu, Min; Wang, Long; Lin, Chen; Wang, Xiaogang

2017-10-01

The Laser-driven Ion beam trace probe (LITP) is a new diagnostic method for measuring poloidal magnetic field (Bp) and radial electric field (Er) in tokamaks. LITP injects a laser-driven ion beam into the tokamak, and Bp and Er profiles can be reconstructed using tomography methods. A reconstruction code has been developed to validate the LITP theory, and both 2D reconstruction of Bp and simultaneous reconstruction of Bp and Er have been attained. To reconstruct from experimental data with noise, Maximum Entropy and Gaussian-Bayesian tomography methods were applied and improved according to the characteristics of the LITP problem. With these improved methods, a reconstruction error level below 15% has been attained with a data noise level of 10%. These methods will be further tested and applied in the following LITP experiments. Supported by the ITER-CHINA program 2015GB120001, CHINA MOST under 2012YQ030142 and National Natural Science Foundation Abstract of China under 11575014 and 11375053.

Dynamic Data-Driven UAV Network for Plume Characterization

Science.gov (United States)

2016-05-23

AFRL-AFOSR-VA-TR-2016-0203 Dynamic Data-Driven UAV Network for Plume Characterization Kamran Mohseni UNIVERSITY OF FLORIDA Final Report 05/23/2016...AND SUBTITLE Dynamic Data-Driven UAV Network for Plume Characterization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-13-1-0090 5c.  PROGRAM ELEMENT...studied a dynamic data driven (DDD) approach to operation of a heterogeneous team of unmanned aerial vehicles ( UAVs ) or micro/miniature aerial

Data-parallel tomographic reconstruction : A comparison of filtered backprojection and direct Fourier reconstruction

NARCIS (Netherlands)

Roerdink, J.B.T.M.; Westenberg, M.A

1998-01-01

We consider the parallelization of two standard 2D reconstruction algorithms, filtered backprojection and direct Fourier reconstruction, using the data-parallel programming style. The algorithms are implemented on a Connection Machine CM-5 with 16 processors and a peak performance of 2 Gflop/s.

Direct maximum parsimony phylogeny reconstruction from genotype data

OpenAIRE

Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell

2007-01-01

Abstract Background Maximum parsimony phylogenetic tree reconstruction from genetic variation data is a fundamental problem in computational genetics with many practical applications in population genetics, whole genome analysis, and the search for genetic predictors of disease. Efficient methods are available for reconstruction of maximum parsimony trees from haplotype data, but such data are difficult to determine directly for autosomal DNA. Data more commonly is available in the form of ge...

Direct maximum parsimony phylogeny reconstruction from genotype data.

Science.gov (United States)

Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell

2007-12-05

Maximum parsimony phylogenetic tree reconstruction from genetic variation data is a fundamental problem in computational genetics with many practical applications in population genetics, whole genome analysis, and the search for genetic predictors of disease. Efficient methods are available for reconstruction of maximum parsimony trees from haplotype data, but such data are difficult to determine directly for autosomal DNA. Data more commonly is available in the form of genotypes, which consist of conflated combinations of pairs of haplotypes from homologous chromosomes. Currently, there are no general algorithms for the direct reconstruction of maximum parsimony phylogenies from genotype data. Hence phylogenetic applications for autosomal data must therefore rely on other methods for first computationally inferring haplotypes from genotypes. In this work, we develop the first practical method for computing maximum parsimony phylogenies directly from genotype data. We show that the standard practice of first inferring haplotypes from genotypes and then reconstructing a phylogeny on the haplotypes often substantially overestimates phylogeny size. As an immediate application, our method can be used to determine the minimum number of mutations required to explain a given set of observed genotypes. Phylogeny reconstruction directly from unphased data is computationally feasible for moderate-sized problem instances and can lead to substantially more accurate tree size inferences than the standard practice of treating phasing and phylogeny construction as two separate analysis stages. The difference between the approaches is particularly important for downstream applications that require a lower-bound on the number of mutations that the genetic region has undergone.

Direct maximum parsimony phylogeny reconstruction from genotype data

Directory of Open Access Journals (Sweden)

Ravi R

2007-12-01

Full Text Available Abstract Background Maximum parsimony phylogenetic tree reconstruction from genetic variation data is a fundamental problem in computational genetics with many practical applications in population genetics, whole genome analysis, and the search for genetic predictors of disease. Efficient methods are available for reconstruction of maximum parsimony trees from haplotype data, but such data are difficult to determine directly for autosomal DNA. Data more commonly is available in the form of genotypes, which consist of conflated combinations of pairs of haplotypes from homologous chromosomes. Currently, there are no general algorithms for the direct reconstruction of maximum parsimony phylogenies from genotype data. Hence phylogenetic applications for autosomal data must therefore rely on other methods for first computationally inferring haplotypes from genotypes. Results In this work, we develop the first practical method for computing maximum parsimony phylogenies directly from genotype data. We show that the standard practice of first inferring haplotypes from genotypes and then reconstructing a phylogeny on the haplotypes often substantially overestimates phylogeny size. As an immediate application, our method can be used to determine the minimum number of mutations required to explain a given set of observed genotypes. Conclusion Phylogeny reconstruction directly from unphased data is computationally feasible for moderate-sized problem instances and can lead to substantially more accurate tree size inferences than the standard practice of treating phasing and phylogeny construction as two separate analysis stages. The difference between the approaches is particularly important for downstream applications that require a lower-bound on the number of mutations that the genetic region has undergone.

Data mining, knowledge discovery and data-driven modelling

NARCIS (Netherlands)

Solomatine, D.P.; Velickov, S.; Bhattacharya, B.; Van der Wal, B.

2003-01-01

The project was aimed at exploring the possibilities of a new paradigm in modelling - data-driven modelling, often referred as "data mining". Several application areas were considered: sedimentation problems in the Port of Rotterdam, automatic soil classification on the basis of cone penetration

Data-driven outbreak forecasting with a simple nonlinear growth model.

Science.gov (United States)

Lega, Joceline; Brown, Heidi E

2016-12-01

Recent events have thrown the spotlight on infectious disease outbreak response. We developed a data-driven method, EpiGro, which can be applied to cumulative case reports to estimate the order of magnitude of the duration, peak and ultimate size of an ongoing outbreak. It is based on a surprisingly simple mathematical property of many epidemiological data sets, does not require knowledge or estimation of disease transmission parameters, is robust to noise and to small data sets, and runs quickly due to its mathematical simplicity. Using data from historic and ongoing epidemics, we present the model. We also provide modeling considerations that justify this approach and discuss its limitations. In the absence of other information or in conjunction with other models, EpiGro may be useful to public health responders. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Simulating flaring events in complex active regions driven by observed magnetograms

Science.gov (United States)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

2011-05-01

Context. We interpret solar flares as events originating in active regions that have reached the self organized critical state, by using a refined cellular automaton model with initial conditions derived from observations. Aims: We investigate whether the system, with its imposed physical elements, reaches a self organized critical state and whether well-known statistical properties of flares, such as scaling laws observed in the distribution functions of characteristic parameters, are reproduced after this state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy and event duration follow the expected scaling laws, we first applied a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent loading and relaxation steps lead the system to self organized criticality, after which the statistical properties of the simulated events are examined. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately imposed on all elements of the model. Results: Our results show that self organized criticality is indeed reached when applying specific loading and relaxation rules. Power-law indices obtained from the distribution functions of the modeled flaring events are in good agreement with observations. Single power laws (peak and total flare energy) are obtained, as are power laws with exponential cutoff and double power laws (flare duration). The results are also compared with observational X-ray data from the GOES satellite for our active-region sample. Conclusions: We conclude that well-known statistical properties of flares are reproduced after the system has

Energy Reconstruction for Events Detected in TES X-ray Detectors

Science.gov (United States)

Ceballos, M. T.; Cardiel, N.; Cobo, B.

2015-09-01

The processing of the X-ray events detected by a TES (Transition Edge Sensor) device (such as the one that will be proposed in the ESA AO call for instruments for the Athena mission (Nandra et al. 2013) as a high spectral resolution instrument, X-IFU (Barret et al. 2013)), is a several step procedure that starts with the detection of the current pulses in a noisy signal and ends up with their energy reconstruction. For this last stage, an energy calibration process is required to convert the pseudo energies measured in the detector to the real energies of the incoming photons, accounting for possible nonlinearity effects in the detector. We present the details of the energy calibration algorithm we implemented as the last part of the Event Processing software that we are developing for the X-IFU instrument, that permits the calculation of the calibration constants in an analytical way.

Authentic execution of distributed event-driven applications with a small TCB

OpenAIRE

Noorman, Job; Mühlberg, Tobias; Piessens, Frank

2017-01-01

This paper presents an approach to provide strong assurance of the secure execution of distributed event-driven applications on shared infrastructures, while relying on a small Trusted Computing Base. We build upon and extend security primitives provided by a Protected Module Architecture (PMA) to guarantee authenticity and integrity properties of applications, and to secure control of input and output devices used by these applications. More specifically, we want to guarantee that if an outp...

Crime event 3D reconstruction based on incomplete or fragmentary evidence material--case report.

Science.gov (United States)

Maksymowicz, Krzysztof; Tunikowski, Wojciech; Kościuk, Jacek

2014-09-01

Using our own experience in 3D analysis, the authors will demonstrate the possibilities of 3D crime scene and event reconstruction in cases where originally collected material evidence is largely insufficient. The necessity to repeat forensic evaluation is often down to the emergence of new facts in the course of case proceedings. Even in cases when a crime scene and its surroundings have undergone partial or complete transformation, with regard to elements significant to the course of the case, or when the scene was not satisfactorily secured, it is still possible to reconstruct it in a 3D environment based on the originally-collected, even incomplete, material evidence. In particular cases when no image of the crime scene is available, its partial or even full reconstruction is still potentially feasible. Credibility of evidence for such reconstruction can still satisfy the evidence requirements in court. Reconstruction of the missing elements of the crime scene is still possible with the use of information obtained from current publicly available databases. In the study, we demonstrate that these can include Google Maps(®*), Google Street View(®*) and available construction and architecture archives. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ahmadreza Vajdi

2018-05-01

Full Text Available We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP. Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks.

Science.gov (United States)

Vajdi, Ahmadreza; Zhang, Gongxuan; Zhou, Junlong; Wei, Tongquan; Wang, Yongli; Wang, Tianshu

2018-05-04

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

Science.gov (United States)

Zhang, Gongxuan; Wang, Yongli; Wang, Tianshu

2018-01-01

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach. PMID:29734718

The Run 2 ATLAS Analysis Event Data Model

CERN Document Server

SNYDER, S; The ATLAS collaboration; NOWAK, M; EIFERT, T; BUCKLEY, A; ELSING, M; GILLBERG, D; MOYSE, E; KOENEKE, K; KRASZNAHORKAY, A

2014-01-01

During the LHC's first Long Shutdown (LS1) ATLAS set out to establish a new analysis model, based on the experience gained during Run 1. A key component of this is a new Event Data Model (EDM), called the xAOD. This format, which is now in production, provides the following features: A separation of the EDM into interface classes that the user code directly interacts with, and data storage classes that hold the payload data. The user sees an Array of Structs (AoS) interface, while the data is stored in a Struct of Arrays (SoA) format in memory, thus making it possible to efficiently auto-vectorise reconstruction code. A simple way of augmenting and reducing the information saved for different data objects. This makes it possible to easily decorate objects with new properties during data analysis, and to remove properties that the analysis does not need. A persistent file format that can be explored directly with ROOT, either with or without loading any additional libraries. This allows fast interactive naviga...

Reconstruction of point cross-section from ENDF data file for Monte Carlo applications

International Nuclear Information System (INIS)

Kumawat, H.; Saxena, A.; Carminati, F.; )

2016-12-01

Monte Carlo neutron transport codes are one of the best tools to simulate complex systems like fission and fusion reactors, Accelerator Driven Sub-critical systems, radio-activity management of spent fuel and waste, optimization and characterization of neutron detectors, optimization of Boron Neutron Capture Therapy, imaging etc. The neutron cross-section and secondary particle emission properties are the main input parameters of such codes. The fission, capture and elastic scattering cross-sections have complex resonating structures. Evaluated Nuclear Data File (ENDF) contains these cross-sections and secondary parameters. We report the development of reconstruction procedure to generate point cross-sections and probabilities from ENDF data file. The cross-sections are compared with the values obtained from PREPRO and in some cases NJOY codes. The results are in good agreement. (author)

Science to Support Management of Receiving Waters in an Event-Driven Ecosystem: From Land to River to Sea

Directory of Open Access Journals (Sweden)

Stuart E. Bunn

2013-06-01

Full Text Available Managing receiving-water quality, ecosystem health and ecosystem service delivery is challenging in regions where extreme rainfall and runoff events occur episodically, confounding and often intensifying land-degradation impacts. We synthesize the approaches used in river, reservoir and coastal water management in the event-driven subtropics of Australia, and the scientific research underpinning them. Land-use change has placed the receiving waters of Moreton Bay, an internationally-significant coastal wetland, at risk of ecological degradation through increased nutrient and sediment loads. The event-driven climate exacerbates this issue, as the waterways and ultimately Moreton Bay receive large inputs of nutrients and sediment during events, well above those received throughout stable climatic periods. Research on the water quality and ecology of the region’s rivers and coastal waters has underpinned the development of a world-renowned monitoring program and, in combination with catchment-source tracing methods and modeling, has revealed the key mechanisms and management strategies by which receiving-water quality, ecosystem health and ecosystem services can be maintained and improved. These approaches provide a useful framework for management of water bodies in other regions driven by episodic events, or where novel stressors are involved (e.g., climate change, urbanization, to support sustained ecosystem service delivery and restoration of aquatic ecosystems.

Data filtering and expected muon and neutrino event rates in the KM3NeT neutrino telescope

Energy Technology Data Exchange (ETDEWEB)

Shanidze, Rezo [ECAP, University of Erlangen-Nuremberg, Erwin-Rommel-Str.1, 91058 Erlangen (Germany); Collaboration: ANTARES-KM3NeT-Erlangen-Collaboration

2011-07-01

KM3NeT is a future Mediterranean deep sea neutrino telescope with an instrumented volume of several cubic kilometres. The neutrino and muon events in KM3NeT will be reconstructed from the signals collected from the telescope's photo detectors. However, in the deep sea the dominant source of photon signals are the decays of K40 nuclei and bioluminescence. The selection of neutrino and muon events requires the implementation of fast and efficient data filtering algorithms for the reduction of accidental background event rates. Possible data filtering and triggering schemes for the KM3NeT neutrino telescope and expected muon and neutrino event rates are discussed.

The processor farm for online triggering and full event reconstruction of the HERA-B experiment at HERA

International Nuclear Information System (INIS)

Gellrich, A.; Dippel, R.; Gensch, U.; Kowallik, R.; Legrand, I.C.; Leich, H.; Sun, F.; Wegner, P.

1996-01-01

The main goal of the HERA-B experiment which start taking data in 1988 is to study CP violation in B decays. This article describes the concept and the planned implementation of a multi-processor system, called processor farm,as the last part of the data acquisition and trigger system of the HERA B experiment. The third level trigger task and a full online event reconstruction will be performed on this processor farm, consisting of more then 100 powerful RISC processors which are based on commercial hardware boards. The controlling will be done by a real-time operating system which provides a software development environment, including FORTRAN and C compilers. (author)

Using Two Different Approaches to Assess Dietary Patterns: Hypothesis-Driven and Data-Driven Analysis

Directory of Open Access Journals (Sweden)

Ágatha Nogueira Previdelli

2016-09-01

Full Text Available The use of dietary patterns to assess dietary intake has become increasingly common in nutritional epidemiology studies due to the complexity and multidimensionality of the diet. Currently, two main approaches have been widely used to assess dietary patterns: data-driven and hypothesis-driven analysis. Since the methods explore different angles of dietary intake, using both approaches simultaneously might yield complementary and useful information; thus, we aimed to use both approaches to gain knowledge of adolescents’ dietary patterns. Food intake from a cross-sectional survey with 295 adolescents was assessed by 24 h dietary recall (24HR. In hypothesis-driven analysis, based on the American National Cancer Institute method, the usual intake of Brazilian Healthy Eating Index Revised components were estimated. In the data-driven approach, the usual intake of foods/food groups was estimated by the Multiple Source Method. In the results, hypothesis-driven analysis showed low scores for Whole grains, Total vegetables, Total fruit and Whole fruits, while, in data-driven analysis, fruits and whole grains were not presented in any pattern. High intakes of sodium, fats and sugars were observed in hypothesis-driven analysis with low total scores for Sodium, Saturated fat and SoFAA (calories from solid fat, alcohol and added sugar components in agreement, while the data-driven approach showed the intake of several foods/food groups rich in these nutrients, such as butter/margarine, cookies, chocolate powder, whole milk, cheese, processed meat/cold cuts and candies. In this study, using both approaches at the same time provided consistent and complementary information with regard to assessing the overall dietary habits that will be important in order to drive public health programs, and improve their efficiency to monitor and evaluate the dietary patterns of populations.

Distributed processing and analysis of ATLAS experimental data

CERN Document Server

Barberis, D; The ATLAS collaboration

2011-01-01

The ATLAS experiment is taking data steadily since Autumn 2009, collecting close to 1 fb-1 of data (several petabytes of raw and reconstructed data per year of data-taking). Data are calibrated, reconstructed, distributed and analysed at over 100 different sites using the World-wide LHC Computing Grid and the tools produced by the ATLAS Distributed Computing project. In addition to event data, ATLAS produces a wealth of information on detector status, luminosity, calibrations, alignments, and data processing conditions. This information is stored in relational databases, online and offline, and made transparently available to analysers of ATLAS data world-wide through an infrastructure consisting of distributed database replicas and web servers that exploit caching technologies. This paper reports on the experience of using this distributed computing infrastructure with real data and in real time, on the evolution of the computing model driven by this experience, and on the system performance during the first...

Distributed processing and analysis of ATLAS experimental data

CERN Document Server

Barberis, D; The ATLAS collaboration

2011-01-01

The ATLAS experiment is taking data steadily since Autumn 2009, and collected so far over 5 fb-1 of data (several petabytes of raw and reconstructed data per year of data-taking). Data are calibrated, reconstructed, distributed and analysed at over 100 different sites using the World-wide LHC Computing Grid and the tools produced by the ATLAS Distributed Computing project. In addition to event data, ATLAS produces a wealth of information on detector status, luminosity, calibrations, alignments, and data processing conditions. This information is stored in relational databases, online and offline, and made transparently available to analysers of ATLAS data world-wide through an infrastructure consisting of distributed database replicas and web servers that exploit caching technologies. This paper reports on the experience of using this distributed computing infrastructure with real data and in real time, on the evolution of the computing model driven by this experience, and on the system performance during the...

An Event-Driven Hybrid Molecular Dynamics and Direct Simulation Monte Carlo Algorithm

Energy Technology Data Exchange (ETDEWEB)

Donev, A; Garcia, A L; Alder, B J

2007-07-30

A novel algorithm is developed for the simulation of polymer chains suspended in a solvent. The polymers are represented as chains of hard spheres tethered by square wells and interact with the solvent particles with hard core potentials. The algorithm uses event-driven molecular dynamics (MD) for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in event-driven algorithms, rather, the momentum and energy exchange in the solvent is determined stochastically using the Direct Simulation Monte Carlo (DSMC) method. The coupling between the solvent and the solute is consistently represented at the particle level, however, unlike full MD simulations of both the solvent and the solute, the spatial structure of the solvent is ignored. The algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard wall subjected to uniform shear. The algorithm closely reproduces full MD simulations with two orders of magnitude greater efficiency. Results do not confirm the existence of periodic (cycling) motion of the polymer chain.

Optical image reconstruction using DC data: simulations and experiments

International Nuclear Information System (INIS)

Huabei Jiang; Paulsen, K.D.; Oesterberg, U.L.

1996-01-01

In this paper, we explore optical image formation using a diffusion approximation of light propagation in tissue which is modelled with a finite-element method for optically heterogeneous media. We demonstrate successful image reconstruction based on absolute experimental DC data obtained with a continuous wave 633 nm He-Ne laser system and a 751 nm diode laser system in laboratory phantoms having two optically distinct regions. The experimental systems used exploit a tomographic type of data collection scheme that provides information from which a spatially variable optical property map is deduced. Reconstruction of scattering coefficient only and simultaneous reconstruction of both scattering and absorption profiles in tissue-like phantoms are obtained from measured and simulated data. Images with different contrast levels between the heterogeneity and the background are also reported and the results show that although it is possible to obtain qualitative visual information on the location and size of a heterogeneity, it may not be possible to quantitatively resolve contrast levels or optical properties using reconstructions from DC data only. Sensitivity of image reconstruction to noise in the measurement data is investigated through simulations. The application of boundary constraints has also been addressed. (author)

Temporal integration: intentional sound discrimination does not modulate stimulus-driven processes in auditory event synthesis.

Science.gov (United States)

Sussman, Elyse; Winkler, István; Kreuzer, Judith; Saher, Marieke; Näätänen, Risto; Ritter, Walter

2002-12-01

Our previous study showed that the auditory context could influence whether two successive acoustic changes occurring within the temporal integration window (approximately 200ms) were pre-attentively encoded as a single auditory event or as two discrete events (Cogn Brain Res 12 (2001) 431). The aim of the current study was to assess whether top-down processes could influence the stimulus-driven processes in determining what constitutes an auditory event. Electroencepholagram (EEG) was recorded from 11 scalp electrodes to frequently occurring standard and infrequently occurring deviant sounds. Within the stimulus blocks, deviants either occurred only in pairs (successive feature changes) or both singly and in pairs. Event-related potential indices of change and target detection, the mismatch negativity (MMN) and the N2b component, respectively, were compared with the simultaneously measured performance in discriminating the deviants. Even though subjects could voluntarily distinguish the two successive auditory feature changes from each other, which was also indicated by the elicitation of the N2b target-detection response, top-down processes did not modify the event organization reflected by the MMN response. Top-down processes can extract elemental auditory information from a single integrated acoustic event, but the extraction occurs at a later processing stage than the one whose outcome is indexed by MMN. Initial processes of auditory event-formation are fully governed by the context within which the sounds occur. Perception of the deviants as two separate sound events (the top-down effects) did not change the initial neural representation of the same deviants as one event (indexed by the MMN), without a corresponding change in the stimulus-driven sound organization.

Data-driven architectural design to production and operation

NARCIS (Netherlands)

Bier, H.H.; Mostafavi, S.

2015-01-01

Data-driven architectural production and operation explored within Hyperbody rely heavily on system thinking implying that all parts of a system are to be understood in relation to each other. These relations are established bi-directionally so that data-driven architecture is not only produced

The Structural Consequences of Big Data-Driven Education.

Science.gov (United States)

Zeide, Elana

2017-06-01

Educators and commenters who evaluate big data-driven learning environments focus on specific questions: whether automated education platforms improve learning outcomes, invade student privacy, and promote equality. This article puts aside separate unresolved-and perhaps unresolvable-issues regarding the concrete effects of specific technologies. It instead examines how big data-driven tools alter the structure of schools' pedagogical decision-making, and, in doing so, change fundamental aspects of America's education enterprise. Technological mediation and data-driven decision-making have a particularly significant impact in learning environments because the education process primarily consists of dynamic information exchange. In this overview, I highlight three significant structural shifts that accompany school reliance on data-driven instructional platforms that perform core school functions: teaching, assessment, and credentialing. First, virtual learning environments create information technology infrastructures featuring constant data collection, continuous algorithmic assessment, and possibly infinite record retention. This undermines the traditional intellectual privacy and safety of classrooms. Second, these systems displace pedagogical decision-making from educators serving public interests to private, often for-profit, technology providers. They constrain teachers' academic autonomy, obscure student evaluation, and reduce parents' and students' ability to participate or challenge education decision-making. Third, big data-driven tools define what "counts" as education by mapping the concepts, creating the content, determining the metrics, and setting desired learning outcomes of instruction. These shifts cede important decision-making to private entities without public scrutiny or pedagogical examination. In contrast to the public and heated debates that accompany textbook choices, schools often adopt education technologies ad hoc. Given education

Reconstruction of network topology using status-time-series data

Science.gov (United States)

Pandey, Pradumn Kumar; Badarla, Venkataramana

2018-01-01

Uncovering the heterogeneous connection pattern of a networked system from the available status-time-series (STS) data of a dynamical process on the network is of great interest in network science and known as a reverse engineering problem. Dynamical processes on a network are affected by the structure of the network. The dependency between the diffusion dynamics and structure of the network can be utilized to retrieve the connection pattern from the diffusion data. Information of the network structure can help to devise the control of dynamics on the network. In this paper, we consider the problem of network reconstruction from the available status-time-series (STS) data using matrix analysis. The proposed method of network reconstruction from the STS data is tested successfully under susceptible-infected-susceptible (SIS) diffusion dynamics on real-world and computer-generated benchmark networks. High accuracy and efficiency of the proposed reconstruction procedure from the status-time-series data define the novelty of the method. Our proposed method outperforms compressed sensing theory (CST) based method of network reconstruction using STS data. Further, the same procedure of network reconstruction is applied to the weighted networks. The ordering of the edges in the weighted networks is identified with high accuracy.

Spectrotemporal CT data acquisition and reconstruction at low dose

International Nuclear Information System (INIS)

Clark, Darin P.; Badea, Cristian T.; Lee, Chang-Lung; Kirsch, David G.

2015-01-01

Purpose: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D + dual energy + time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. Methods: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction

A scheme for PET data normalization in event-based motion correction

International Nuclear Information System (INIS)

Zhou, Victor W; Kyme, Andre Z; Fulton, Roger; Meikle, Steven R

2009-01-01

Line of response (LOR) rebinning is an event-based motion-correction technique for positron emission tomography (PET) imaging that has been shown to compensate effectively for rigid motion. It involves the spatial transformation of LORs to compensate for motion during the scan, as measured by a motion tracking system. Each motion-corrected event is then recorded in the sinogram bin corresponding to the transformed LOR. It has been shown previously that the corrected event must be normalized using a normalization factor derived from the original LOR, that is, based on the pair of detectors involved in the original coincidence event. In general, due to data compression strategies (mashing), sinogram bins record events detected on multiple LORs. The number of LORs associated with a sinogram bin determines the relative contribution of each LOR. This paper provides a thorough treatment of event-based normalization during motion correction of PET data using LOR rebinning. We demonstrate theoretically and experimentally that normalization of the corrected event during LOR rebinning should account for the number of LORs contributing to the sinogram bin into which the motion-corrected event is binned. Failure to account for this factor may cause artifactual slice-to-slice count variations in the transverse slices and visible horizontal stripe artifacts in the coronal and sagittal slices of the reconstructed images. The theory and implementation of normalization in conjunction with the LOR rebinning technique is described in detail, and experimental verification of the proposed normalization method in phantom studies is presented.

Reconstruction of networks from one-step data by matching positions

Science.gov (United States)

Wu, Jianshe; Dang, Ni; Jiao, Yang

2018-05-01

It is a challenge in estimating the topology of a network from short time series data. In this paper, matching positions is developed to reconstruct the topology of a network from only one-step data. We consider a general network model of coupled agents, in which the phase transformation of each node is determined by its neighbors. From the phase transformation information from one step to the next, the connections of the tail vertices are reconstructed firstly by the matching positions. Removing the already reconstructed vertices, and repeatedly reconstructing the connections of tail vertices, the topology of the entire network is reconstructed. For sparse scale-free networks with more than ten thousands nodes, we almost obtain the actual topology using only the one-step data in simulations.

Investigating the Use of the Intel Xeon Phi for Event Reconstruction

Science.gov (United States)

Sherman, Keegan; Gilfoyle, Gerard

2014-09-01

The physics goal of Jefferson Lab is to understand how quarks and gluons form nuclei and it is being upgraded to a higher, 12-GeV beam energy. The new CLAS12 detector in Hall B will collect 5-10 terabytes of data per day and will require considerable computing resources. We are investigating tools, such as the Intel Xeon Phi, to speed up the event reconstruction. The Kalman Filter is one of the methods being studied. It is a linear algebra algorithm that estimates the state of a system by combining existing data and predictions of those measurements. The tools required to apply this technique (i.e. matrix multiplication, matrix inversion) are being written using C++ intrinsics for Intel's Xeon Phi Coprocessor, which uses the Many Integrated Cores (MIC) architecture. The Intel MIC is a new high-performance chip that connects to a host machine through the PCIe bus and is built to run highly vectorized and parallelized code making it a well-suited device for applications such as the Kalman Filter. Our tests of the MIC optimized algorithms needed for the filter show significant increases in speed. For example, matrix multiplication of 5x5 matrices on the MIC was able to run up to 69 times faster than the host core. The physics goal of Jefferson Lab is to understand how quarks and gluons form nuclei and it is being upgraded to a higher, 12-GeV beam energy. The new CLAS12 detector in Hall B will collect 5-10 terabytes of data per day and will require considerable computing resources. We are investigating tools, such as the Intel Xeon Phi, to speed up the event reconstruction. The Kalman Filter is one of the methods being studied. It is a linear algebra algorithm that estimates the state of a system by combining existing data and predictions of those measurements. The tools required to apply this technique (i.e. matrix multiplication, matrix inversion) are being written using C++ intrinsics for Intel's Xeon Phi Coprocessor, which uses the Many Integrated Cores (MIC

Data-driven workflows for microservices

DEFF Research Database (Denmark)

Safina, Larisa; Mazzara, Manuel; Montesi, Fabrizio

2016-01-01

Microservices is an architectural style inspired by service-oriented computing that has recently started gainingpopularity. Jolie is a programming language based on the microservices paradigm: the main building block of Jolie systems are services, in contrast to, e.g., functions or objects....... The primitives offered by the Jolie language elicit many of the recurring patterns found in microservices, like load balancers and structured processes. However, Jolie still lacks some useful constructs for dealing with message types and data manipulation that are present in service-oriented computing......). We show the impact of our implementation on some of the typical scenarios found in microservice systems. This shows how computation can move from a process-driven to a data-driven approach, and leads to the preliminary identification of recurring communication patterns that can be shaped as design...

Phylogenetic reconstruction of transmission events from individuals with acute HIV infection: toward more-rigorous epidemiological definitions

NARCIS (Netherlands)

Brown, Alison E.; Gifford, Robert J.; Clewley, Jonathan P.; Kucherer, Claudia; Masquelier, Bernard; Porter, Kholoud; Balotta, Claudia; Back, Nicole K. T.; Jorgensen, Louise Bruun; de Mendoza, Carmen; Bhaskaran, Krishnan; Gill, O. Noel; Johnson, Anne M.; Pillay, Deenan; del Amo, Julia; Meyer, Laurence; Bucher, Heiner; Chene, Genevieve; Prins, Maria; Rosinska, Magda; Sabin, Caroline; Touloumi, Giota; Lodi, Sara; Walker, Sarah; Babiker, Abdel; Darbyshire, Janet; de Luca, Andrea; Fisher, Martin; Muga, Roberto; Kaldor, John; Kelleher, Tony; Ramacciotti, Tim; Gelgor, Linda; Cooper, David; Smith, Don; Gill, John; Nielsen, Claus; Pedersen, Court; Lutsar, Irja; Dabis, Francois; Thiebaut, Rodolphe; Costagliola, Dominique; Guiguet, Marguerite; Vanhems, Philippe; Boufassa, Faroudy; Hamouda, Osamah; Pantazis, Nikos; Hatzakis, Angelos; Geskus, Ronald; Coutinho, Roel

2009-01-01

Phylogenetic reconstructions of transmission events from individuals with acute human immunodeficiency virus (HIV) infection are conducted to illustrate this group's heightened infectivity. Varied definitions of acute infection and assumptions about observed phylogenetic clusters may produce

Challenges of Data-driven Healthcare Management

DEFF Research Database (Denmark)

Bossen, Claus; Danholt, Peter; Ubbesen, Morten Bonde

This paper describes the new kind of data-work involved in developing data-driven healthcare based on two cases from Denmark: The first case concerns a governance infrastructure based on Diagnose-Related Groups (DRG), which was introduced in Denmark in the 1990s. The DRG-system links healthcare...... activity and financing and relies of extensive data entry, reporting and calculations. This has required the development of new skills, work and work roles. The second case concerns a New Governance project aimed at developing new performance indicators for healthcare delivery as an alternative to DRG....... Here, a core challenge is select indicators and actually being able to acquire data upon them. The two cases point out that data-driven healthcare requires more and new kinds of work for which new skills, functions and work roles have to be developed....

Improving Filtered Backprojection Reconstruction by Data-Dependent Filtering

NARCIS (Netherlands)

D.M. Pelt (Daniël); K.J. Batenburg (Joost)

2014-01-01

htmlabstractFiltered backprojection, one of the most widely used reconstruction methods in tomography, requires a large number of low-noise projections to yield accurate reconstructions. In many applications of tomography, complete projection data of high quality cannot be obtained, because of

An improved reconstruction of May-June precipitation using tree-ring data from western Turkey and its links to volcanic eruptions.

Science.gov (United States)

Köse, Nesibe; Akkemik, Unal; Güner, H Tuncay; Dalfes, H Nüzhet; Grissino-Mayer, Henri D; Ozeren, M Sinan; Kındap, Tayfun

2013-09-01

We developed a high quality reconstruction of May-June precipitation for the interior region of southwestern Turkey using regional tree-ring data calibrated with meteorological data from Burdur. In this study, three new climate sensitive black pine chronologies were built. In addition to new chronologies, four previously published black pine chronologies were used for the reconstruction. Two separate reconstructions were developed. The first reconstruction used all site chronologies over the common interval AD 1813-2004. The second reconstruction used four of the chronologies with a common interval AD 1692-2004. R² values of the reconstructions were 0.64 and 0.51 with RE values of 0.63 and 0.51, respectively. During the period AD 1692-1938, 41 dry and 48 wet events were found. Very dry years occurred in AD 1725, 1814, 1851, 1887, 1916, and 1923, while very wet years occurred in AD 1736, 1780, 1788, 1803, and 1892. The longest dry period was 16 years long between 1860 and 1875. We then explored relationships between the reconstructed rainfall patterns and major volcanic eruptions, and discovered that wetter than normal years occurred during or immediately after the years with the largest volcanic eruptions.

LCP method for a planar passive dynamic walker based on an event-driven scheme

Science.gov (United States)

Zheng, Xu-Dong; Wang, Qi

2018-06-01

The main purpose of this paper is to present a linear complementarity problem (LCP) method for a planar passive dynamic walker with round feet based on an event-driven scheme. The passive dynamic walker is treated as a planar multi-rigid-body system. The dynamic equations of the passive dynamic walker are obtained by using Lagrange's equations of the second kind. The normal forces and frictional forces acting on the feet of the passive walker are described based on a modified Hertz contact model and Coulomb's law of dry friction. The state transition problem of stick-slip between feet and floor is formulated as an LCP, which is solved with an event-driven scheme. Finally, to validate the methodology, four gaits of the walker are simulated: the stance leg neither slips nor bounces; the stance leg slips without bouncing; the stance leg bounces without slipping; the walker stands after walking several steps.

Apparatus and method for reconstructing data

International Nuclear Information System (INIS)

Pavkovich, J.M.

1977-01-01

The apparatus and method for reconstructing data are described. A fan beam of radiation is passed through an object, the beam lying in the same quasi-plane as the object slice to be examined. Radiation not absorbed in the object slice is recorded on oppositely situated detectors aligned with the source of radiation. Relative rotation is provided between the source-detector configuration and the object. Reconstruction means are coupled to the detector means, and may comprise a general purpose computer, a special purpose computer, and control logic for interfacing between said computers and controlling the respective functioning thereof for performing a convolution and back projection based upon non-absorbed radiation detected by said detector means, whereby the reconstruction means converts values of the non-absorbed radiation into values of absorbed radiation at each of an arbitrarily large number of points selected within the object slice. Display means are coupled to the reconstruction means for providing a visual or other display or representation of the quantities of radiation absorbed at the points considered in the object. (Auth.)

Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

Directory of Open Access Journals (Sweden)

Emre eNeftci

2014-01-01

Full Text Available Restricted Boltzmann Machines (RBMs and Deep Belief Networks have been demonstrated to perform efficiently in variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The reverberating activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP carries out the weight updates in an online, asynchronous fashion.We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

Event-driven contrastive divergence for spiking neuromorphic systems.

Science.gov (United States)

Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

2013-01-01

Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

Adaptive algorithms of position and energy reconstruction in Anger-camera type detectors: experimental data processing in ANTS

Energy Technology Data Exchange (ETDEWEB)

Morozov, A; Fraga, F A F; Fraga, M M F R; Margato, L M S; Pereira, L [LIP-Coimbra and Departamento de Física, Universidade de Coimbra, Rua Larga, Coimbra (Portugal); Defendi, I; Jurkovic, M [Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II), TUM, Lichtenbergstr. 1, Garching (Germany); Engels, R; Kemmerling, G [Zentralinstitut für Elektronik, Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, Jülich (Germany); Gongadze, A; Guerard, B; Manzin, G; Niko, H; Peyaud, A; Piscitelli, F [Institut Laue Langevin, 6 Rue Jules Horowitz, Grenoble (France); Petrillo, C; Sacchetti, F [Istituto Nazionale per la Fisica della Materia, Unità di Perugia, Via A. Pascoli, Perugia (Italy); Raspino, D; Rhodes, N J; Schooneveld, E M, E-mail: andrei@coimbra.lip.pt [Science and Technology Facilities Council, Rutherford Appleton Laboratory, Harwell Oxford, Didcot (United Kingdom); others, and

2013-05-01

The software package ANTS (Anger-camera type Neutron detector: Toolkit for Simulations), developed for simulation of Anger-type gaseous detectors for thermal neutron imaging was extended to include a module for experimental data processing. Data recorded with a sensor array containing up to 100 photomultiplier tubes (PMT) or silicon photomultipliers (SiPM) in a custom configuration can be loaded and the positions and energies of the events can be reconstructed using the Center-of-Gravity, Maximum Likelihood or Least Squares algorithm. A particular strength of the new module is the ability to reconstruct the light response functions and relative gains of the photomultipliers from flood field illumination data using adaptive algorithms. The performance of the module is demonstrated with simulated data generated in ANTS and experimental data recorded with a 19 PMT neutron detector. The package executables are publicly available at http://coimbra.lip.pt/∼andrei/.

Fast image reconstruction for Compton camera using stochastic origin ensemble approach.

Science.gov (United States)

Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna

2011-01-01

Compton camera has been proposed as a potential imaging tool in astronomy, industry, homeland security, and medical diagnostics. Due to the inherent geometrical complexity of Compton camera data, image reconstruction of distributed sources can be ineffective and/or time-consuming when using standard techniques such as filtered backprojection or maximum likelihood-expectation maximization (ML-EM). In this article, the authors demonstrate a fast reconstruction of Compton camera data using a novel stochastic origin ensembles (SOE) approach based on Markov chains. During image reconstruction, the origins of the measured events are randomly assigned to locations on conical surfaces, which are the Compton camera analogs of lines-of-responses in PET. Therefore, the image is defined as an ensemble of origin locations of all possible event origins. During the course of reconstruction, the origins of events are stochastically moved and the acceptance of the new event origin is determined by the predefined acceptance probability, which is proportional to the change in event density. For example, if the event density at the new location is higher than in the previous location, the new position is always accepted. After several iterations, the reconstructed distribution of origins converges to a quasistationary state which can be voxelized and displayed. Comparison with the list-mode ML-EM reveals that the postfiltered SOE algorithm has similar performance in terms of image quality while clearly outperforming ML-EM in relation to reconstruction time. In this study, the authors have implemented and tested a new image reconstruction algorithm for the Compton camera based on the stochastic origin ensembles with Markov chains. The algorithm uses list-mode data, is parallelizable, and can be used for any Compton camera geometry. SOE algorithm clearly outperforms list-mode ML-EM for simple Compton camera geometry in terms of reconstruction time. The difference in computational time

Reconstruction of multiple-pinhole micro-SPECT data using origin ensembles.

Science.gov (United States)

Lyon, Morgan C; Sitek, Arkadiusz; Metzler, Scott D; Moore, Stephen C

2016-10-01

The authors are currently developing a dual-resolution multiple-pinhole microSPECT imaging system based on three large NaI(Tl) gamma cameras. Two multiple-pinhole tungsten collimator tubes will be used sequentially for whole-body "scout" imaging of a mouse, followed by high-resolution (hi-res) imaging of an organ of interest, such as the heart or brain. Ideally, the whole-body image will be reconstructed in real time such that data need only be acquired until the area of interest can be visualized well-enough to determine positioning for the hi-res scan. The authors investigated the utility of the origin ensemble (OE) algorithm for online and offline reconstructions of the scout data. This algorithm operates directly in image space, and can provide estimates of image uncertainty, along with reconstructed images. Techniques for accelerating the OE reconstruction were also introduced and evaluated. System matrices were calculated for our 39-pinhole scout collimator design. SPECT projections were simulated for a range of count levels using the MOBY digital mouse phantom. Simulated data were used for a comparison of OE and maximum-likelihood expectation maximization (MLEM) reconstructions. The OE algorithm convergence was evaluated by calculating the total-image entropy and by measuring the counts in a volume-of-interest (VOI) containing the heart. Total-image entropy was also calculated for simulated MOBY data reconstructed using OE with various levels of parallelization. For VOI measurements in the heart, liver, bladder, and soft-tissue, MLEM and OE reconstructed images agreed within 6%. Image entropy converged after ∼2000 iterations of OE, while the counts in the heart converged earlier at ∼200 iterations of OE. An accelerated version of OE completed 1000 iterations in <9 min for a 6.8M count data set, with some loss of image entropy performance, whereas the same dataset required ∼79 min to complete 1000 iterations of conventional OE. A combination of the two

Matrix completion-based reconstruction for undersampled magnetic resonance fingerprinting data.

Science.gov (United States)

Doneva, Mariya; Amthor, Thomas; Koken, Peter; Sommer, Karsten; Börnert, Peter

2017-09-01

An iterative reconstruction method for undersampled magnetic resonance fingerprinting data is presented. The method performs the reconstruction entirely in k-space and is related to low rank matrix completion methods. A low dimensional data subspace is estimated from a small number of k-space locations fully sampled in the temporal direction and used to reconstruct the missing k-space samples before MRF dictionary matching. Performing the iterations in k-space eliminates the need for applying a forward and an inverse Fourier transform in each iteration required in previously proposed iterative reconstruction methods for undersampled MRF data. A projection onto the low dimensional data subspace is performed as a matrix multiplication instead of a singular value thresholding typically used in low rank matrix completion, further reducing the computational complexity of the reconstruction. The method is theoretically described and validated in phantom and in-vivo experiments. The quality of the parameter maps can be significantly improved compared to direct matching on undersampled data. Copyright © 2017 Elsevier Inc. All rights reserved.

Reconstruction method for data protection in telemedicine systems

Science.gov (United States)

Buldakova, T. I.; Suyatinov, S. I.

2015-03-01

In the report the approach to protection of transmitted data by creation of pair symmetric keys for the sensor and the receiver is offered. Since biosignals are unique for each person, their corresponding processing allows to receive necessary information for creation of cryptographic keys. Processing is based on reconstruction of the mathematical model generating time series that are diagnostically equivalent to initial biosignals. Information about the model is transmitted to the receiver, where the restoration of physiological time series is performed using the reconstructed model. Thus, information about structure and parameters of biosystem model received in the reconstruction process can be used not only for its diagnostics, but also for protection of transmitted data in telemedicine complexes.

Event reconstruction using the radio-interferometric technique in the frame of AERA

Energy Technology Data Exchange (ETDEWEB)

Rogozin, Dmytro [Institut fuer Experimentelle Kernphysik, Karlsruher Institut fuer Technologie (KIT) (Germany); Collaboration: Pierre-Auger-Collaboration

2016-07-01

It is a well-known fact that there is coherent radio emission induced by extensive air-showers. This fact is exploited in the Auger Engineering Radio Array (AERA), the radio extension of the Pierre Auger Observatory. This is a unique radio experiment due to its world-largest size of 17 km{sup 2}, and due to its precise nanosecond timing calibration. These features become crucial for detection of highly inclined air-showers with their very large foot-prints, and for the ability to apply interferometric reconstruction techniques. The standard reconstruction techniques typically treat all radio stations as separate detectors. Nevertheless there is a possibility to do an interferometric analysis. This means combining all detected signals from all antennas in a specific way. In this talk we present a beam-forming interferometric technique and its application to AERA. According to the definition of the beam-forming quantities one can expect its correlation with the shower parameters such as energy of the primary particle and distance to the shower maximum. At the first step, Monte-Carlo simulations of AERA events including the noise from measured events were used to test these dependencies. The results and the future perspectives of this method are discussed with a particular emphasis on very inclined air-showers where the aforementioned correlations are assumed to be strongest.

Underlying Event and B-Hadron Decays in $t\\overline{t}$ Events

CERN Document Server

INSPIRE-00175000

2014-01-01

We present exploratory studies of the underlying event activity and of fragmentation and hadronization of b quarks using $t\\overline{t}$ candidate events in proton-proton collision data acquired by the CMS experiment. We reconstruct charm mesons in fully charged decay channels from the reconstructed tracks associated with the hadronization of b quarks from the top decay, and study their kinematics relative to the mother jet. A good agreement is found using MadGraph plus the Pythia 6 Tune Z2* simulation. The effects predicted by alternative settings and generators for the characterization of the underlying event are also explored. These results are expected to contribute in the future to more precise measurements in the top quark sector in particular of the top quark mass by either constraining systematic uncertainties related to the modeling of the underlying event in $t\\overline{t}$ events or by paving the way for alternative mass measurement methods.

Method for position emission mammography image reconstruction

Science.gov (United States)

Smith, Mark Frederick

2004-10-12

An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.

Quantitation of PET data with the EM reconstruction technique

International Nuclear Information System (INIS)

Rosenqvist, G.; Dahlbom, M.; Erikson, L.; Bohm, C.; Blomqvist, G.

1989-01-01

The expectation maximization (EM) algorithm offers high spatial resolution and excellent noise reduction with low statistics PET data, since it incorporates the Poisson nature of the data. The main difficulties are long computation times, difficulties to find appropriate criteria to terminate the reconstruction and to quantify the resulting image data. In the present work a modified EM algorithm has been implements on a VAX 11/780. Its capability to quantify image data has been tested in phantom studies and in two clinical cases, cerebral blood flow studies and dopamine D2-receptor studies. Data from phantom studies indicate the superiority of images reconstructed with the EM technique compared to images reconstructed with the conventional filtered back-projection (FB) technique in areas with low statistics. At higher statistics the noise characteristics of the two techniques coincide. Clinical data support these findings

Staged Event-Driven Architecture As A Micro-Architecture Of Distributed And Pluginable Crawling Platform

Directory of Open Access Journals (Sweden)

Leszek Siwik

2013-01-01

Full Text Available There are many crawling systems available on the market but they are rather close systems dedicated for performing particular kind and class of tasks with predefined set of scope, strategy etc. In real life however there are meaningful groups of users (e.g. marketing, criminal or governmental analysts requiring not just a yet another crawling system dedicated for performing predefined tasks. They need rather easy-to-use, user friendly all-in-one studio for not only executing and running internet robots and crawlers, but also for (graphical (redefining and (recomposing crawlers according to dynamically changing requirements and use-cases. To realize the above-mentioned idea, Cassiopeia framework has been designed and developed. One has to remember, however, that enormous size and unimaginable structural complexity of WWW network are the reasons that, from a technical and architectural point of view, developing effective internet robots – and the more so developing a framework supporting graphical robots’ composition – becomes a really challenging task. The crucial aspect in the context of crawling efficiency and scalability is concurrency model applied. There are two the most typical concurrency management models i.e. classical concurrency based on the pool of threads and processes and event-driven concurrency. None of them are ideal approaches. That is why, research on alternative models is still conducted to propose efficient and convenient architecture for concurrent and distributed applications. One of promising models is staged event-driven architecture mixing to some extent both of above mentioned classical approaches and providing some additional benefits such as splitting application into separate stages connected by events queues – what is interesting taking requirements about crawler (recomposition into account. The goal of this paper is to present the idea and the PoC  implementation of Cassiopeia framework, with the special

Data driven marketing for dummies

CERN Document Server

Semmelroth, David

2013-01-01

Embrace data and use it to sell and market your products Data is everywhere and it keeps growing and accumulating. Companies need to embrace big data and make it work harder to help them sell and market their products. Successful data analysis can help marketing professionals spot sales trends, develop smarter marketing campaigns, and accurately predict customer loyalty. Data Driven Marketing For Dummies helps companies use all the data at their disposal to make current customers more satisfied, reach new customers, and sell to their most important customer segments more efficiently. Identifyi

Tropical climate and vegetation changes during Heinrich Event 1: a model-data comparison

Directory of Open Access Journals (Sweden)

D. Handiani

2012-01-01

Full Text Available Abrupt climate changes from 18 to 15 thousand years before present (kyr BP associated with Heinrich Event 1 (HE1 had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic Earth System-Climate Model (ESCM with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM, and a Heinrich-like event with two different climate backgrounds (interglacial and glacial. We calculated mega-biomes from the plant-functional types (PFTs generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions.

Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America.

The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote

PHYCAA: Data-driven measurement and removal of physiological noise in BOLD fMRI

DEFF Research Database (Denmark)

Churchill, Nathan W.; Yourganov, Grigori; Spring, Robyn

2012-01-01

, autocorrelated physiological noise sources with reproducible spatial structure, using an adaptation of Canonical Correlation Analysis performed in a split-half resampling framework. The technique is able to identify physiological effects with vascular-linked spatial structure, and an intrinsic dimensionality...... with physiological noise, and real data-driven model prediction and reproducibility, for both block and event-related task designs. This is demonstrated compared to no physiological noise correction, and to the widely used RETROICOR (Glover et al., 2000) physiological denoising algorithm, which uses externally...

A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

Science.gov (United States)

Figueiredo, Carlos M. S.; Nakamura, Eduardo F.; Loureiro, Antonio A. F.

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption. PMID:22423207

Jet mass reconstruction with the ATLAS Detector in early Run 2 data

CERN Document Server

The ATLAS collaboration

2016-01-01

This note presents the details of the ATLAS jet mass reconstruction for groomed large-radius jets. The jet mass scale calibrations are determined from Monte Carlo simulation. An alternative jet mass definition that incorporates tracking information called the track-assisted jet mass is introduced and its performance is compared to the traditional calorimeter-based jet mass definition. Events enriched in boosted $W$, $Z$ boson and top quark jets are used to directly compare the jet mass scale and jet mass resolution between data and simulation. This in-situ technique is also extended to constrain the jet energy scale and resolution.

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2.

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Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; Abidi, S H; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adachi, S; Adamczyk, L; Adelman, J; Adersberger, M; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agheorghiesei, C; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akatsuka, S; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albicocco, P; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alshehri, A A; Alstaty, M; Alvarez Gonzalez, B; Álvarez Piqueras, D; Alviggi, M G; Amadio, B T; Amaral Coutinho, Y; Amelung, C; Amidei, D; Santos, S P Amor Dos; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; 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2017-01-01

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 [Formula: see text] for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb[Formula: see text] of data collected by the ATLAS experiment and simulation of proton-proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 [Formula: see text]. The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 [Formula: see text] is quantified using a novel, data-driven, method. The method uses the energy loss, [Formula: see text], to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is [Formula: see text] and [Formula: see text] for jet transverse momenta of 200-400 [Formula: see text] and 1400-1600 [Formula: see text], respectively.

Event Reconstruction and Analysis in the R3BRoot Framework

International Nuclear Information System (INIS)

Kresan, Dmytro; Al-Turany, Mohammad; Bertini, Denis; Karabowicz, Radoslaw; Manafov, Anar; Rybalchenko, Alexey; Uhlig, Florian

2014-01-01

The R 3 B experiment (Reaction studies with Relativistic Radioactive Beams) will be built within the future FAIR / GSI (Facility for Antiproton and Ion Research) in Darmstadt, Germany. The international collaboration R 3 B has a scientific program devoted to the physics of stable and radioactive beams at energies between 150 MeV and 1.5 GeV per nucleon. In preparation for the experiment, the R3BRoot software framework is under development, it deliver detector simulation, reconstruction and data analysis. The basic functionalities of the framework are handled by the FairRoot framework which is used also by the other FAIR experiments (CBM, PANDA, ASYEOS, etc) while the R 3 B detector specifics and reconstruction code are implemented inside R3BRoot. In this contribution first results of data analysis from the detector prototype test in November 2012 will be reported, moreover, comparison of the tracker performance versus experimental data, will be presented

Performance of CMS Muon Reconstruction in Cosmic-Ray Events

CERN Document Server

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Bourilkov, D; Chen, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; Field, R D; Fu, Y; Furic, I K; Gartner, J; Holmes, D; Kim, B; Klimenko, S; Konigsberg, J; Korytov, A; Kotov, K; Kropivnitskaya, A; Kypreos, T; Madorsky, A; Matchev, K; Mitselmakher, G; Pakhotin, Y; Piedra Gomez, J; Prescott, C; Rapsevicius, V; Remington, R; Schmitt, M; Scurlock, B; Wang, D; Yelton, J; Ceron, C; Gaultney, V; Kramer, L; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, T; Askew, A; Baer, H; Bertoldi, M; Chen, J; Dharmaratna, W G D; Gleyzer, S V; Haas, J; Hagopian, S; Hagopian, V; Jenkins, M; Johnson, K F; Prettner, E; Prosper, H; Sekmen, S; Baarmand, M M; Guragain, S; Hohlmann, M; Kalakhety, H; Mermerkaya, H; Ralich, R; Vodopiyanov, I; Abelev, B; Adams, M R; Anghel, I M; Apanasevich, L; Bazterra, V E; Betts, R R; Callner, J; Castro, M A; Cavanaugh, R; Dragoiu, C; Garcia-Solis, E J; Gerber, C E; Hofman, D J; Khalatian, S; Mironov, C; Shabalina, E; Smoron, A; Varelas, N; Akgun, U; Albayrak, E A; Ayan, A S; Bilki, B; Briggs, R; Cankocak, K; Chung, K; Clarida, W; Debbins, P; Duru, F; Ingram, F D; Lae, C K; McCliment, E; Merlo, J P; Mestvirishvili, A; Miller, M J; Moeller, A; Nachtman, J; Newsom, C R; Norbeck, E; Olson, J; Onel, Y; Ozok, F; Parsons, J; Schmidt, I; Sen, S; Wetzel, J; Yetkin, T; Yi, K; Barnett, B A; Blumenfeld, B; Bonato, A; Chien, C Y; Fehling, D; Giurgiu, G; Gritsan, A V; Guo, Z J; Maksimovic, P; Rappoccio, S; Swartz, M; Tran, N V; Zhang, Y; Baringer, P; Bean, A; Grachov, O; Murray, M; Radicci, V; Sanders, S; Wood, J S; Zhukova, V; Bandurin, D; Bolton, T; Kaadze, K; Liu, A; Maravin, Y; Onoprienko, D; Svintradze, I; Wan, Z; Gronberg, J; Hollar, J; Lange, D; Wright, D; Baden, D; Bard, R; Boutemeur, M; Eno, S C; Ferencek, D; Hadley, N J; Kellogg, R G; Kirn, M; Kunori, S; Rossato, K; Rumerio, P; Santanastasio, F; Skuja, A; Temple, J; Tonjes, M B; Tonwar, S C; Toole, T; Twedt, E; Alver, B; Bauer, G; Bendavid, J; Busza, W; Butz, E; Cali, I A; Chan, M; D'Enterria, D; Everaerts, P; Gomez Ceballos, G; Hahn, K A; Harris, P; Jaditz, S; Kim, Y; Klute, M; Lee, Y J; Li, W; Loizides, C; Ma, T; Miller, M; Nahn, S; Paus, C; Roland, C; Roland, G; Rudolph, M; Stephans, G; Sumorok, K; Sung, K; Vaurynovich, S; Wenger, E A; Wyslouch, B; Xie, S; Yilmaz, Y; Yoon, A S; Bailleux, D; Cooper, S I; Cushman, P; Dahmes, B; De Benedetti, A; Dolgopolov, A; Dudero, P R; Egeland, R; Franzoni, G; Haupt, J; Inyakin, A; Klapoetke, K; Kubota, Y; Mans, J; Mirman, N; Petyt, D; Rekovic, V; Rusack, R; Schroeder, M; Singovsky, A; Zhang, J; Cremaldi, L M; Godang, R; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Sonnek, P; Summers, D; Bloom, K; Bockelman, B; Bose, S; Butt, J; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kelly, T; Kravchenko, I; Lazo-Flores, J; Lundstedt, C; Malbouisson, H; Malik, S; Snow, G R; Baur, U; Iashvili, I; Kharchilava, A; Kumar, A; Smith, K; Strang, M; Alverson, G; Barberis, E; Boeriu, O; Eulisse, G; Govi, G; McCauley, T; Musienko, Y; Muzaffar, S; Osborne, I; Paul, T; Reucroft, S; Swain, J; Taylor, L; Tuura, L; Anastassov, A; Gobbi, B; Kubik, A; Ofierzynski, R A; Pozdnyakov, A; Schmitt, M; Stoynev, S; Velasco, M; Won, S; Antonelli, L; Berry, D; Hildreth, M; Jessop, C; Karmgard, D J; Kolberg, T; Lannon, K; Lynch, S; Marinelli, N; Morse, D M; Ruchti, R; Slaunwhite, J; Warchol, J; Wayne, M; Bylsma, B; Durkin, L S; Gilmore, J; Gu, J; Killewald, P; Ling, T Y; Williams, G; Adam, N; Berry, E; Elmer, P; Garmash, A; Gerbaudo, D; Halyo, V; Hunt, A; Jones, J; Laird, E; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Stickland, D; Tully, C; Werner, J S; Wildish, T; Xie, Z; Zuranski, A; Acosta, J G; Bonnett Del Alamo, M; Huang, X T; Lopez, A; Mendez, H; Oliveros, S; Ramirez Vargas, J E; Santacruz, N; Zatzerklyany, A; Alagoz, E; Antillon, E; Barnes, V E; Bolla, G; Bortoletto, D; Everett, A; Garfinkel, A F; Gecse, Z; Gutay, L; Ippolito, N; Jones, M; Koybasi, O; Laasanen, A T; Leonardo, N; Liu, C; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Sedov, A; Shipsey, I; Yoo, H D; Zheng, Y; Jindal, P; Parashar, N; Cuplov, V; Ecklund, K M; Geurts, F J M; Liu, J H; Maronde, D; Matveev, M; Padley, B P; Redjimi, R; Roberts, J; Sabbatini, L; Tumanov, A; Betchart, B; Bodek, A; Budd, H; Chung, Y S; de Barbaro, P; Demina, R; Flacher, H; Gotra, Y; Harel, A; Korjenevski, S; Miner, D C; Orbaker, D; Petrillo, G; Vishnevskiy, D; Zielinski, M; Bhatti, A; Demortier, L; Goulianos, K; Hatakeyama, K; Lungu, G; Mesropian, C; Yan, M; Atramentov, O; Bartz, E; Gershtein, Y; Halkiadakis, E; Hits, D; Lath, A; Rose, K; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Watts, T L; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Asaadi, J; Aurisano, A; Eusebi, R; Golyash, A; Gurrola, A; Kamon, T; Nguyen, C N; Pivarski, J; Safonov, A; Sengupta, S; Toback, D; Weinberger, M; Akchurin, N; Berntzon, L; Gumus, K; Jeong, C; Kim, H; Lee, S W; Popescu, S; Roh, Y; Sill, A; Volobouev, I; Washington, E; Wigmans, R; Yazgan, E; Engh, D; Florez, C; Johns, W; Pathak, S; Sheldon, P; Andelin, D; Arenton, M W; Balazs, M; Boutle, S; Buehler, M; Conetti, S; Cox, B; Hirosky, R; Ledovskoy, A; Neu, C; Phillips II, D; Ronquest, M; Yohay, R; Gollapinni, S; Gunthoti, K; Harr, R; Karchin, P E; Mattson, M; Sakharov, A; Anderson, M; Bachtis, M; Bellinger, J N; Carlsmith, D; Crotty, I; Dasu, S; Dutta, S; Efron, J; Feyzi, F; Flood, K; Gray, L; Grogg, K S; Grothe, M; Hall-Wilton, R; Jaworski, M; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Loveless, R; Magrans de Abril, M; Mohapatra, A; Ott, G; Polese, G; Reeder, D; Savin, A; Smith, W H; Sourkov, A; Swanson, J; Weinberg, M; Wenman, D; Wensveen, M; White, A

2010-01-01

The performance of muon reconstruction in CMS is evaluated using a large data sample of cosmic-ray muons recorded in 2008. Efficiencies of various high-level trigger, identification, and reconstruction algorithms have been measured for a broad range of muon momenta, and were found to be in good agreement with expectations from Monte Carlo simulation. The relative momentum resolution for muons crossing the barrel part of the detector is better than 1% at 10 GeV/c and is about 8% at 500 GeV/c, the latter being only a factor of two worse than expected with ideal alignment conditions. Muon charge misassignment ranges from less than 0.01% at 10 GeV/c to about 1% at 500 GeV/c.

Quartet-based methods to reconstruct phylogenetic networks.

Science.gov (United States)

Yang, Jialiang; Grünewald, Stefan; Xu, Yifei; Wan, Xiu-Feng

2014-02-20

Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate. We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China. QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses.

Upgrade trigger & reconstruction strategy: 2017 milestone

CERN Document Server

Albrecht, Johannes; Campora Perez, Daniel Hugo; Cattaneo, Marco; Marco, Clemencic; Couturier, Ben; Dziurda, Agnieszka; Fitzpatrick, Conor; Fontana, Marianna; Grillo, Lucia; Hasse, Christoph; Hill, Donal; Jones, Christopher Rob; Lemaitre, Florian; Lupton, Olli; Matev, Rosen; Pearce, Alex; Polci, Francesco; Promberger, Laura; Ponce, Sebastien; Quagliani, Renato; Raven, Gerhard; Sciascia, Barbara; Schiller, Manuel Tobias; Stahl, Sascha; Szymanski, Maciej Pawel; Chefdeville, Maximilien

2018-01-01

The LHCb collaboration is currently preparing an update of the experiment to take data in Run 3 of the LHC. The dominant feature of this upgrade is a trigger-less readout of the full detector followed by a full software trigger. To make optimal use of the collected data, the events are reconstructed at the inelastic collision rate of 30 MHz. This document presents the baseline trigger and reconstruction strategy as of the end of 2017.

Application of process monitoring to anomaly detection in nuclear material processing systems via system-centric event interpretation of data from multiple sensors of varying reliability

International Nuclear Information System (INIS)

Garcia, Humberto E.; Simpson, Michael F.; Lin, Wen-Chiao; Carlson, Reed B.; Yoo, Tae-Sic

2017-01-01

Highlights: • Process monitoring can strengthen nuclear safeguards and material accountancy. • Assessment is conducted at a system-centric level to improve safeguards effectiveness. • Anomaly detection is improved by integrating process and operation relationships. • Decision making is benefited from using sensor and event sequence information. • Formal framework enables optimization of sensor and data processing resources. - Abstract: In this paper, we apply an advanced safeguards approach and associated methods for process monitoring to a hypothetical nuclear material processing system. The assessment regarding the state of the processing facility is conducted at a system-centric level formulated in a hybrid framework. This utilizes architecture for integrating both time- and event-driven data and analysis for decision making. While the time-driven layers of the proposed architecture encompass more traditional process monitoring methods based on time series data and analysis, the event-driven layers encompass operation monitoring methods based on discrete event data and analysis. By integrating process- and operation-related information and methodologies within a unified framework, the task of anomaly detection is greatly improved. This is because decision-making can benefit from not only known time-series relationships among measured signals but also from known event sequence relationships among generated events. This available knowledge at both time series and discrete event layers can then be effectively used to synthesize observation solutions that optimally balance sensor and data processing requirements. The application of the proposed approach is then implemented on an illustrative monitored system based on pyroprocessing and results are discussed.

An optical study of multiple NEIAL events driven by low energy electron precipitation

Directory of Open Access Journals (Sweden)

J. M. Sullivan

2008-08-01

Full Text Available Optical data are compared with EISCAT radar observations of multiple Naturally Enhanced Ion-Acoustic Line (NEIAL events in the dayside cusp. This study uses narrow field of view cameras to observe small-scale, short-lived auroral features. Using multiple-wavelength optical observations, a direct link between NEIAL occurrences and low energy (about 100 eV optical emissions is shown. This is consistent with the Langmuir wave decay interpretation of NEIALs being driven by streams of low-energy electrons. Modelling work connected with this study shows that, for the measured ionospheric conditions and precipitation characteristics, growth of unstable Langmuir (electron plasma waves can occur, which decay into ion-acoustic wave modes. The link with low energy optical emissions shown here, will enable future studies of the shape, extent, lifetime, grouping and motions of NEIALs.

Position reconstruction in LUX

Science.gov (United States)

Akerib, D. S.; Alsum, S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Brás, P.; Byram, D.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; Dobi, A.; Druszkiewicz, E.; Edwards, B. N.; Fallon, S. R.; Fan, A.; Fiorucci, S.; Gaitskell, R. J.; Genovesi, J.; Ghag, C.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Jacobsen, R. G.; Ji, W.; Kamdin, K.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Manalaysay, A.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O'Sullivan, K.; Oliver-Mallory, K. C.; Palladino, K. J.; Pease, E. K.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Solmaz, M.; Solovov, V. N.; Sorensen, P.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W. C.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Velan, V.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Xu, J.; Yazdani, K.; Young, S. K.; Zhang, C.

2018-02-01

The (x, y) position reconstruction method used in the analysis of the complete exposure of the Large Underground Xenon (LUX) experiment is presented. The algorithm is based on a statistical test that makes use of an iterative method to recover the photomultiplier tube (PMT) light response directly from the calibration data. The light response functions make use of a two dimensional functional form to account for the photons reflected on the inner walls of the detector. To increase the resolution for small pulses, a photon counting technique was employed to describe the response of the PMTs. The reconstruction was assessed with calibration data including 83mKr (releasing a total energy of 41.5 keV) and 3H (β- with Q = 18.6 keV) decays, and a deuterium-deuterium (D-D) neutron beam (2.45 MeV) . Within the detector's fiducial volume, the reconstruction has achieved an (x, y) position uncertainty of σ = 0.82 cm and σ = 0.17 cm for events of only 200 and 4,000 detected electroluminescence photons respectively. Such signals are associated with electron recoils of energies ~0.25 keV and ~10 keV, respectively. The reconstructed position of the smallest events with a single electron emitted from the liquid surface (22 detected photons) has a horizontal (x, y) uncertainty of 2.13 cm.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.

Science.gov (United States)

Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy

2014-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Multivariate modeling of complications with data driven variable selection: Guarding against overfitting and effects of data set size

International Nuclear Information System (INIS)

Schaaf, Arjen van der; Xu Chengjian; Luijk, Peter van; Veld, Aart A. van’t; Langendijk, Johannes A.; Schilstra, Cornelis

2012-01-01

Purpose: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. Materials and methods: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. Results: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small

Microenvironment temperature prediction between body and seat interface using autoregressive data-driven model.

Science.gov (United States)

Liu, Zhuofu; Wang, Lin; Luo, Zhongming; Heusch, Andrew I; Cascioli, Vincenzo; McCarthy, Peter W

2015-11-01

There is a need to develop a greater understanding of temperature at the skin-seat interface during prolonged seating from the perspectives of both industrial design (comfort/discomfort) and medical care (skin ulcer formation). Here we test the concept of predicting temperature at the seat surface and skin interface during prolonged sitting (such as required from wheelchair users). As caregivers are usually busy, such a method would give them warning ahead of a problem. This paper describes a data-driven model capable of predicting thermal changes and thus having the potential to provide an early warning (15- to 25-min ahead prediction) of an impending temperature that may increase the risk for potential skin damages for those subject to enforced sitting and who have little or no sensory feedback from this area. Initially, the oscillations of the original signal are suppressed using the reconstruction strategy of empirical mode decomposition (EMD). Consequentially, the autoregressive data-driven model can be used to predict future thermal trends based on a shorter period of acquisition, which reduces the possibility of introducing human errors and artefacts associated with longer duration "enforced" sitting by volunteers. In this study, the method had a maximum predictive error of body insensitivity and disability requiring them to be immobile in seats for prolonged periods. Copyright © 2015 Tissue Viability Society. Published by Elsevier Ltd. All rights reserved.

GPU-based online track reconstruction for PANDA and application to the analysis of D→Kππ

Energy Technology Data Exchange (ETDEWEB)

Herten, Andreas

2015-07-02

The PANDA experiment is a new hadron physics experiment which is being built for the FAIR facility in Darmstadt, Germany. PANDA will employ a novel scheme of data acquisition: the experiment will reconstruct the full stream of events in realtime to make trigger decisions based on the event topology. An important part of this online event reconstruction is online track reconstruction. Online track reconstruction algorithms need to reconstruct particle trajectories in nearly realtime. This work uses the high-throughput devices of Graphics Processing Units to benchmark different online track reconstruction algorithms. The reconstruction of D{sup ±}→K{sup -+}π{sup ±}π{sup ±} is studied extensively and one online track reconstruction algorithm applied.

Reconstruction of incorrect sensor data : from failure to success

OpenAIRE

Os, van, E.A.; Bontsema, J.; Janssen, H.J.J.; Kempkes, F.L.K.; Marcelis, L.F.M.

2009-01-01

Experimental research on crop performance or climate control in greenhouses requires accurate measurement of climate conditions. Despite the use of calibrated sensors, afterwards it may appear that the collected climate data are incorrect. Then the question arises whether we need to repeat the experiment or whether we can reconstruct the correct climate data from the incorrect measurements. In this paper we show how correct data of temperature and air humidity could be reconstructed from inco...

Reconstruction of ribosomal RNA genes from metagenomic data.

Directory of Open Access Journals (Sweden)

Lu Fan

Full Text Available Direct sequencing of environmental DNA (metagenomics has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.

Utilization of FADC for reconstruction and analysis of the background data in the Chooz neutrino experiment

International Nuclear Information System (INIS)

Veron, Didier

1997-01-01

This thesis describes a particular contribution to the Chooz experiment. The latter looks for the oscillations, over a distance of 1 km, of antineutrons emitted by two nuclear reactors. The electron-type antineutrinos are detected through their inverse beta interaction with a target's proton. The neutron is detected through its capture by a gadolinium nucleus revealed by an 8 MeV gamma emission. In the first part we describe the reconstruction of events as simulated by the GIANT software. We show that the positron's and neutron's stopping point can actually be reconstructed with an accuracy of 10 and 20 cm respectively. In the second part, we proceed to the analysis of the calibration's data as recorded with Fast Wave Form Digitizers. This confirms the reliability of the Monte-Carlo results and allows measurement of both the neutrons' capture probability and time by the target gadolinium. The last part deals with the background (reactor turned off) data analysis and the pin-pointing of its various sources. In order to reduce their contribution, we define spatial cuts. These cuts' reliability is validated by analysis of data obtained not only with a neutron source, but also with neutrons issued from cosmic rays. We end up with a background contribution of two to three events per day, about ten times less than the expected neutrino rate at full reactor power. (author)

The Orion GN and C Data-Driven Flight Software Architecture for Automated Sequencing and Fault Recovery

Science.gov (United States)

King, Ellis; Hart, Jeremy; Odegard, Ryan

2010-01-01

The Orion Crew Exploration Vehicle (CET) is being designed to include significantly more automation capability than either the Space Shuttle or the International Space Station (ISS). In particular, the vehicle flight software has requirements to accommodate increasingly automated missions throughout all phases of flight. A data-driven flight software architecture will provide an evolvable automation capability to sequence through Guidance, Navigation & Control (GN&C) flight software modes and configurations while maintaining the required flexibility and human control over the automation. This flexibility is a key aspect needed to address the maturation of operational concepts, to permit ground and crew operators to gain trust in the system and mitigate unpredictability in human spaceflight. To allow for mission flexibility and reconfrgurability, a data driven approach is being taken to load the mission event plan as well cis the flight software artifacts associated with the GN&C subsystem. A database of GN&C level sequencing data is presented which manages and tracks the mission specific and algorithm parameters to provide a capability to schedule GN&C events within mission segments. The flight software data schema for performing automated mission sequencing is presented with a concept of operations for interactions with ground and onboard crew members. A prototype architecture for fault identification, isolation and recovery interactions with the automation software is presented and discussed as a forward work item.

Data-driven models of dominantly-inherited Alzheimer's disease progression.

Science.gov (United States)

Oxtoby, Neil P; Young, Alexandra L; Cash, David M; Benzinger, Tammie L S; Fagan, Anne M; Morris, John C; Bateman, Randall J; Fox, Nick C; Schott, Jonathan M; Alexander, Daniel C

2018-03-22

Dominantly-inherited Alzheimer's disease is widely hoped to hold the key to developing interventions for sporadic late onset Alzheimer's disease. We use emerging techniques in generative data-driven disease progression modelling to characterize dominantly-inherited Alzheimer's disease progression with unprecedented resolution, and without relying upon familial estimates of years until symptom onset. We retrospectively analysed biomarker data from the sixth data freeze of the Dominantly Inherited Alzheimer Network observational study, including measures of amyloid proteins and neurofibrillary tangles in the brain, regional brain volumes and cortical thicknesses, brain glucose hypometabolism, and cognitive performance from the Mini-Mental State Examination (all adjusted for age, years of education, sex, and head size, as appropriate). Data included 338 participants with known mutation status (211 mutation carriers in three subtypes: 163 PSEN1, 17 PSEN2, and 31 APP) and a baseline visit (age 19-66; up to four visits each, 1.1 ± 1.9 years in duration; spanning 30 years before, to 21 years after, parental age of symptom onset). We used an event-based model to estimate sequences of biomarker changes from baseline data across disease subtypes (mutation groups), and a differential equation model to estimate biomarker trajectories from longitudinal data (up to 66 mutation carriers, all subtypes combined). The two models concur that biomarker abnormality proceeds as follows: amyloid deposition in cortical then subcortical regions (∼24 ± 11 years before onset); phosphorylated tau (17 ± 8 years), tau and amyloid-β changes in cerebrospinal fluid; neurodegeneration first in the putamen and nucleus accumbens (up to 6 ± 2 years); then cognitive decline (7 ± 6 years), cerebral hypometabolism (4 ± 4 years), and further regional neurodegeneration. Our models predicted symptom onset more accurately than predictions that used familial estimates: root mean squared error of 1

Image reconstruction by domain-transform manifold learning

Science.gov (United States)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development

Compton scatter and randoms corrections for origin ensembles 3D PET reconstructions

Energy Technology Data Exchange (ETDEWEB)

Sitek, Arkadiusz [Harvard Medical School, Boston, MA (United States). Dept. of Radiology; Brigham and Women' s Hospital, Boston, MA (United States); Kadrmas, Dan J. [Utah Univ., Salt Lake City, UT (United States). Utah Center for Advanced Imaging Research (UCAIR)

2011-07-01

In this work we develop a novel approach to correction for scatter and randoms in reconstruction of data acquired by 3D positron emission tomography (PET) applicable to tomographic reconstruction done by the origin ensemble (OE) approach. The statistical image reconstruction using OE is based on calculation of expectations of the numbers of emitted events per voxel based on complete-data space. Since the OE estimation is fundamentally different than regular statistical estimators such those based on the maximum likelihoods, the standard methods of implementation of scatter and randoms corrections cannot be used. Based on prompts, scatter, and random rates, each detected event is graded in terms of a probability of being a true event. These grades are utilized by the Markov Chain Monte Carlo (MCMC) algorithm used in OE approach for calculation of the expectation over the complete-data space of the number of emitted events per voxel (OE estimator). We show that the results obtained with the OE are almost identical to results obtained by the maximum likelihood-expectation maximization (ML-EM) algorithm for reconstruction for experimental phantom data acquired using Siemens Biograph mCT 3D PET/CT scanner. The developed correction removes artifacts due to scatter and randoms in investigated 3D PET datasets. (orig.)

A RISC multiprocessor event trigger for the data acquisition system of the H1 experiment at HERA

International Nuclear Information System (INIS)

Campbell, A.J.

1992-01-01

In late 1991 HERA will collide for the first time stored beams of electrons and protons. This paper describes the multiple RISC processor system for online event filtering and reconstruction installed within the data acquisition system of the H1 experiment. Data is processed at a continuous average rate of ∼6 Mbytes/s in parallel by ∼20 R3000 VMEbus based monoboard computers providing some 400 MIPS computing power

Event Reconstruction Algorithms for the ATLAS Trigger

Energy Technology Data Exchange (ETDEWEB)

Fonseca-Martin, T.; /CERN; Abolins, M.; /Michigan State U.; Adragna, P.; /Queen Mary, U. of London; Aleksandrov, E.; /Dubna, JINR; Aleksandrov, I.; /Dubna, JINR; Amorim, A.; /Lisbon, LIFEP; Anderson, K.; /Chicago U., EFI; Anduaga, X.; /La Plata U.; Aracena, I.; /SLAC; Asquith, L.; /University Coll. London; Avolio, G.; /CERN; Backlund, S.; /CERN; Badescu, E.; /Bucharest, IFIN-HH; Baines, J.; /Rutherford; Barria, P.; /Rome U. /INFN, Rome; Bartoldus, R.; /SLAC; Batreanu, S.; /Bucharest, IFIN-HH /CERN; Beck, H.P.; /Bern U.; Bee, C.; /Marseille, CPPM; Bell, P.; /Manchester U.; Bell, W.H.; /Glasgow U. /Pavia U. /INFN, Pavia /Regina U. /CERN /Annecy, LAPP /Paris, IN2P3 /Royal Holloway, U. of London /Napoli Seconda U. /INFN, Naples /Argonne /CERN /UC, Irvine /Barcelona, IFAE /Barcelona, Autonoma U. /CERN /Montreal U. /CERN /Glasgow U. /Michigan State U. /Bucharest, IFIN-HH /Napoli Seconda U. /INFN, Naples /New York U. /Barcelona, IFAE /Barcelona, Autonoma U. /Salento U. /INFN, Lecce /Pisa U. /INFN, Pisa /Bucharest, IFIN-HH /UC, Irvine /CERN /Glasgow U. /INFN, Genoa /Genoa U. /Lisbon, LIFEP /Napoli Seconda U. /INFN, Naples /UC, Irvine /Valencia U. /Rio de Janeiro Federal U. /University Coll. London /New York U.; /more authors..

2011-11-09

The ATLAS experiment under construction at CERN is due to begin operation at the end of 2007. The detector will record the results of proton-proton collisions at a center-of-mass energy of 14 TeV. The trigger is a three-tier system designed to identify in real-time potentially interesting events that are then saved for detailed offline analysis. The trigger system will select approximately 200 Hz of potentially interesting events out of the 40 MHz bunch-crossing rate (with 10{sup 9} interactions per second at the nominal luminosity). Algorithms used in the trigger system to identify different event features of interest will be described, as well as their expected performance in terms of selection efficiency, background rejection and computation time per event. The talk will concentrate on recent improvements and on performance studies, using a very detailed simulation of the ATLAS detector and electronics chain that emulates the raw data as it will appear at the input to the trigger system.

Event reconstruction algorithms for the ATLAS trigger

Energy Technology Data Exchange (ETDEWEB)

F-Martin, T; Avolio, G; Backlund, S [European Laboratory for Particle Physics (CERN), Geneva (Switzerland); Abolins, M [Michigan State University, Department of Physics and Astronomy, East Lansing, Michigan (United States); Adragna, P [Department of Physics, Queen Mary and Westfield College, University of London, London (United Kingdom); Aleksandrov, E; Aleksandrov, I [Joint Institute for Nuclear Research, Dubna (Russian Federation); Amorim, A [Laboratorio de Instrumentacao e Fisica Experimental, Lisboa (Portugal); Anderson, K [University of Chicago, Enrico Fermi Institute, Chicago, Illinois (United States); Anduaga, X [National University of La Plata, La Plata (United States); Aracena, I; Bartoldus, R [Stanford Linear Accelerator Center (SLAC), Stanford (United States); Asquith, L [Department of Physics and Astronomy, University College London, London (United Kingdom); Badescu, E [National Institute for Physics and Nuclear Engineering, Institute of Atomic Physics, Bucharest (Romania); Baines, J [Rutherford Appleton Laboratory, Chilton, Didcot (United Kingdom); Beck, H P [Laboratory for High Energy Physics, University of Bern, Bern (Switzerland); Bee, C [Centre de Physique des Particules de Marseille, IN2P3-CNRS, Marseille (France); Bell, P [Department of Physics and Astronomy, University of Manchester, Manchester (United Kingdom); Barria, P; Batreanu, S [and others

2008-07-01

The ATLAS experiment under construction at CERN is due to begin operation at the end of 2007. The detector will record the results of proton-proton collisions at a center-of-mass energy of 14 TeV. The trigger is a three-tier system designed to identify in real-time potentially interesting events that are then saved for detailed offline analysis. The trigger system will select approximately 200 Hz of potentially interesting events out of the 40 MHz bunch-crossing rate (with 10{sup 9} interactions per second at the nominal luminosity). Algorithms used in the trigger system to identify different event features of interest will be described, as well as their expected performance in terms of selection efficiency, background rejection and computation time per event. The talk will concentrate on recent improvements and on performance studies, using a very detailed simulation of the ATLAS detector and electronics chain that emulates the raw data as it will appear at the input to the trigger system.

Event reconstruction algorithms for the ATLAS trigger

International Nuclear Information System (INIS)

F-Martin, T; Avolio, G; Backlund, S; Abolins, M; Adragna, P; Aleksandrov, E; Aleksandrov, I; Amorim, A; Anderson, K; Anduaga, X; Aracena, I; Bartoldus, R; Asquith, L; Badescu, E; Baines, J; Beck, H P; Bee, C; Bell, P; Barria, P; Batreanu, S

2008-01-01

The ATLAS experiment under construction at CERN is due to begin operation at the end of 2007. The detector will record the results of proton-proton collisions at a center-of-mass energy of 14 TeV. The trigger is a three-tier system designed to identify in real-time potentially interesting events that are then saved for detailed offline analysis. The trigger system will select approximately 200 Hz of potentially interesting events out of the 40 MHz bunch-crossing rate (with 10 9 interactions per second at the nominal luminosity). Algorithms used in the trigger system to identify different event features of interest will be described, as well as their expected performance in terms of selection efficiency, background rejection and computation time per event. The talk will concentrate on recent improvements and on performance studies, using a very detailed simulation of the ATLAS detector and electronics chain that emulates the raw data as it will appear at the input to the trigger system

Scenario driven data modelling: a method for integrating diverse sources of data and data streams

Science.gov (United States)

2011-01-01

Background Biology is rapidly becoming a data intensive, data-driven science. It is essential that data is represented and connected in ways that best represent its full conceptual content and allows both automated integration and data driven decision-making. Recent advancements in distributed multi-relational directed graphs, implemented in the form of the Semantic Web make it possible to deal with complicated heterogeneous data in new and interesting ways. Results This paper presents a new approach, scenario driven data modelling (SDDM), that integrates multi-relational directed graphs with data streams. SDDM can be applied to virtually any data integration challenge with widely divergent types of data and data streams. In this work, we explored integrating genetics data with reports from traditional media. SDDM was applied to the New Delhi metallo-beta-lactamase gene (NDM-1), an emerging global health threat. The SDDM process constructed a scenario, created a RDF multi-relational directed graph that linked diverse types of data to the Semantic Web, implemented RDF conversion tools (RDFizers) to bring content into the Sematic Web, identified data streams and analytical routines to analyse those streams, and identified user requirements and graph traversals to meet end-user requirements. Conclusions We provided an example where SDDM was applied to a complex data integration challenge. The process created a model of the emerging NDM-1 health threat, identified and filled gaps in that model, and constructed reliable software that monitored data streams based on the scenario derived multi-relational directed graph. The SDDM process significantly reduced the software requirements phase by letting the scenario and resulting multi-relational directed graph define what is possible and then set the scope of the user requirements. Approaches like SDDM will be critical to the future of data intensive, data-driven science because they automate the process of converting

Comparison of instrumental and interpolated meteorological data-based summer temperature reconstructions on Mt. Taibai in the Qinling Mountains, northwestern China

Science.gov (United States)

Qin, Jin; Bai, Hongying; Su, Kai; Liu, Rongjuan; Zhai, Danping; Wang, Jun; Li, Shuheng; Zhou, Qi; Li, Bin

2018-01-01

Previous dendroclimatical studies have been based on the relationship between tree growth and instrumental climate data recorded at lower land meteorological stations, but the climate conditions somehow differ between sampling sites and distant population centers. Thus, in this study, we performed a comparison between the 152-year reconstruction of June to July mean air temperature on the basis of interpolated meteorological data and instrumental meteorological data. The reconstruction explained 38.7% of the variance in the interpolated temperature data (37.2% after the degrees of freedom were adjusted) and 39.6% of the variance in the instrumental temperature data (38.4% after adjustment for loss of degrees of freedom) during the period 1962-2013 AD. The first global warming (the 1920s) and recent warming (1990-2013) found from the reconstructed temperature series match reasonably well with two other reported summer temperature reconstructions from north-central China. Cold periods occurred three times during 1866-1885, 1901-1921, and 1981-2000, while hot periods occurred four times during 1886-1900, 1922-1933, 1953-1966, and 2001-2007. The extreme warm (cold) years are coherent with the documentary drought (flood) events. Significant 31-22-year, 22-18-year, and 12-8-year cycles indicate major fluctuations in regional temperatures may reflect large-scale climatic shifts.

EM for phylogenetic topology reconstruction on nonhomogeneous data.

Science.gov (United States)

Ibáñez-Marcelo, Esther; Casanellas, Marta

2014-06-17

The reconstruction of the phylogenetic tree topology of four taxa is, still nowadays, one of the main challenges in phylogenetics. Its difficulties lie in considering not too restrictive evolutionary models, and correctly dealing with the long-branch attraction problem. The correct reconstruction of 4-taxon trees is crucial for making quartet-based methods work and being able to recover large phylogenies. We adapt the well known expectation-maximization algorithm to evolutionary Markov models on phylogenetic 4-taxon trees. We then use this algorithm to estimate the substitution parameters, compute the corresponding likelihood, and to infer the most likely quartet. In this paper we consider an expectation-maximization method for maximizing the likelihood of (time nonhomogeneous) evolutionary Markov models on trees. We study its success on reconstructing 4-taxon topologies and its performance as input method in quartet-based phylogenetic reconstruction methods such as QFIT and QuartetSuite. Our results show that the method proposed here outperforms neighbor-joining and the usual (time-homogeneous continuous-time) maximum likelihood methods on 4-leaved trees with among-lineage instantaneous rate heterogeneity, and perform similarly to usual continuous-time maximum-likelihood when data satisfies the assumptions of both methods. The method presented in this paper is well suited for reconstructing the topology of any number of taxa via quartet-based methods and is highly accurate, specially regarding largely divergent trees and time nonhomogeneous data.

Real-time digital filtering, event triggering, and tomographic reconstruction of JET soft x-ray data (abstract)

Science.gov (United States)

Edwards, A. W.; Blackler, K.; Gill, R. D.; van der Goot, E.; Holm, J.

1990-10-01

Based upon the experience gained with the present soft x-ray data acquisition system, new techniques are being developed which make extensive use of digital signal processors (DSPs). Digital filters make 13 further frequencies available in real time from the input sampling frequency of 200 kHz. In parallel, various algorithms running on further DSPs generate triggers in response to a range of events in the plasma. The sawtooth crash can be detected, for example, with a delay of only 50 μs from the onset of the collapse. The trigger processor interacts with the digital filter boards to ensure data of the appropriate frequency is recorded throughout a plasma discharge. An independent link is used to pass 780 and 24 Hz filtered data to a network of transputers. A full tomographic inversion and display of the 24 Hz data is carried out in real time using this 15 transputer array. The 780 Hz data are stored for immediate detailed playback following the pulse. Such a system could considerably improve the quality of present plasma diagnostic data which is, in general, sampled at one fixed frequency throughout a discharge. Further, it should provide valuable information towards designing diagnostic data acquisition systems for future long pulse operation machines when a high degree of real-time processing will be required, while retaining the ability to detect, record, and analyze events of interest within such long plasma discharges.

Historical Chronology of ENSO Events Based Upon Documentary Data From South America: Strengths and Limitations

Science.gov (United States)

Luc, O.

2007-05-01

The first reconstructions of past El Niño occurrences were proposed by W. Quinn twenty years ago. They were based on documentary evidence of anomalous rainfall episodes, destructive floods and other possible impacts of El Niño conditions in Peru and other South-American countries. It has been shown, later, that the El Niño chronological sequence covering the last four and a half centuries produced by Quinn needed a thorough revision since many so-called EN events had not occurred while some others had been overlooked. Beside the classical methodological problems met in historical climatology studies (reliability of data, confidence in the sources, primary and secondary information), the reconstruction of former EN events faces specific difficulties dealing with the significance of the indicators and their spatial location. For instance, strong precipitation anomalies during summer in Southern Ecuador and northern Peru and precipitation excess recorded in the preceding winter in central Chile constitute quite reliable proxies of El Niño conditions, in modern times. However this observed teleconnection pattern, which is useful to reinforce the interpretation of past EN occurrences, seems to have been inoperative before the early nineteenth century. It is interpreted that atmospheric circulation features during the Little Ice Age interfered with the teleconnection system linking the EN impacts in northern Peru and central Chile. As a consequence, how should be evaluated the significance of documented winter precipitation excess in central Chile in years during which there is drought evidence in northern Peru, during the sixteenth to eighteenth century? And vice versa, are former evidences for precipitation excess in northern Peru (prior to the nineteenth century) quite reliable indicators for EN conditions, even if the preceding winter was dry in the Valparaiso-Santiago region? Other specific problems met in the building-up of a consolidated EN chronological

Comparison among tomographic reconstruction with limited data

International Nuclear Information System (INIS)

Oliveira, Eric F.; Dantas, Carlos C.; Vasconcelos, Daniel A.A.; Cadiz, Luis F.; Melo, Silvio B.

2011-01-01

Nowadays there is a continuing interest in applying computed tomography (CT) techniques in non-destructive testing and inspection of many industrial products. These applications of CT usually require a differentiated analysis when there are strong limitations in acquiring a sufficiently large amount of projection data. The use of a low number of tomographic data normally degrades the quality of the reconstructed image, highlighting the formation of artifacts and noise. This work investigates the reconstruction methods most commonly used (FBP, ART, SIRT, MART, SMART) and shows the performance of each one in this limited scenario. For this purpose, all methods were implemented and tested with a phantom of uniform density with well-known distribution, with measures of transmission of gamma radiation in a first generation CT scanner. The phantom is a concentric stainless steel tube coupled with a half - cylinder of aluminum. The measurements were made with an highest root mean square error, with the formation of visible artifacts. The artifacts are diminished but still visible in the ART and SIRT techniques, and the best performance was observed with the techniques MART and SMART. The technical superiority of these multiplicative methods is clearly seen in the reconstructed image quality, endorsing their application to situations of limited input data. (author)

GPU accelerated CT reconstruction for clinical use: quality driven performance

Science.gov (United States)

Vaz, Michael S.; Sneyders, Yuri; McLin, Matthew; Ricker, Alan; Kimpe, Tom

2007-03-01

We present performance and quality analysis of GPU accelerated FDK filtered backprojection for cone beam computed tomography (CBCT) reconstruction. Our implementation of the FDK CT reconstruction algorithm does not compromise fidelity at any stage and yields a result that is within 1 HU of a reference C++ implementation. Our streaming implementation is able to perform reconstruction as the images are acquired; it addresses low latency as well as fast throughput, which are key considerations for a "real-time" design. Further, it is scaleable to multiple GPUs for increased performance. The implementation does not place any constraints on image acquisition; it works effectively for arbitrary angular coverage with arbitrary angular spacing. As such, this GPU accelerated CT reconstruction solution may easily be used with scanners that are already deployed. We are able to reconstruct a 512 x 512 x 340 volume from 625 projections, each sized 1024 x 768, in less than 50 seconds. The quoted 50 second timing encompasses the entire reconstruction using bilinear interpolation and includes filtering on the CPU, uploading the filtered projections to the GPU, and also downloading the reconstructed volume from GPU memory to system RAM.

A biomechanical modeling-guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

Science.gov (United States)

Huang, Xiaokun; Zhang, You; Wang, Jing

2018-02-01

Reconstructing four-dimensional cone-beam computed tomography (4D-CBCT) images directly from respiratory phase-sorted traditional 3D-CBCT projections can capture target motion trajectory, reduce motion artifacts, and reduce imaging dose and time. However, the limited numbers of projections in each phase after phase-sorting decreases CBCT image quality under traditional reconstruction techniques. To address this problem, we developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, an iterative method that can reconstruct higher quality 4D-CBCT images from limited projections using an inter-phase intensity-driven motion model. However, the accuracy of the intensity-driven motion model is limited in regions with fine details whose quality is degraded due to insufficient projection number, which consequently degrades the reconstructed image quality in corresponding regions. In this study, we developed a new 4D-CBCT reconstruction algorithm by introducing biomechanical modeling into SMEIR (SMEIR-Bio) to boost the accuracy of the motion model in regions with small fine structures. The biomechanical modeling uses tetrahedral meshes to model organs of interest and solves internal organ motion using tissue elasticity parameters and mesh boundary conditions. This physics-driven approach enhances the accuracy of solved motion in the organ’s fine structures regions. This study used 11 lung patient cases to evaluate the performance of SMEIR-Bio, making both qualitative and quantitative comparisons between SMEIR-Bio, SMEIR, and the algebraic reconstruction technique with total variation regularization (ART-TV). The reconstruction results suggest that SMEIR-Bio improves the motion model’s accuracy in regions containing small fine details, which consequently enhances the accuracy and quality of the reconstructed 4D-CBCT images.

Tunka-Rex: energy reconstruction with a single antenna station

Science.gov (United States)

Hiller, R.; Bezyazeekov, P. A.; Budnev, N. M.; Fedorov, O.; Gress, O. A.; Haungs, A.; Huege, T.; Kazarina, Y.; Kleifges, M.; Korosteleva, E. E.; Kostunin, D.; Krömer, O.; Kungel, V.; Kuzmichev, L. A.; Lubsandorzhiev, N.; Mirgazov, R. R.; Monkhoev, R.; Osipova, E. A.; Pakhorukov, A.; Pankov, L.; Prosin, V. V.; Rubtsov, G. I.; Schröder, F. G.; Wischnewski, R.; Zagorodnikov, A.

2017-03-01

The Tunka-Radio extension (Tunka-Rex) is a radio detector for air showers in Siberia. From 2012 to 2014, Tunka-Rex operated exclusively together with its host experiment, the air-Cherenkov array Tunka-133, which provided trigger, data acquisition, and an independent air-shower reconstruction. It was shown that the air-shower energy can be reconstructed by Tunka-Rex with a precision of 15% for events with signal in at least 3 antennas, using the radio amplitude at a distance of 120 m from the shower axis as an energy estimator. Using the reconstruction from the host experiment Tunka-133 for the air-shower geometry (shower core and direction), the energy estimator can in principle already be obtained with measurements from a single antenna, close to the reference distance. We present a method for event selection and energy reconstruction, requiring only one antenna, and achieving a precision of about 20%. This method increases the effective detector area and lowers thresholds for zenith angle and energy, resulting in three times more events than in the standard reconstruction.

Volume reconstruction optimization for tomo-PIV algorithms applied to experimental data

Science.gov (United States)

Martins, Fabio J. W. A.; Foucaut, Jean-Marc; Thomas, Lionel; Azevedo, Luis F. A.; Stanislas, Michel

2015-08-01

Tomographic PIV is a three-component volumetric velocity measurement technique based on the tomographic reconstruction of a particle distribution imaged by multiple camera views. In essence, the performance and accuracy of this technique is highly dependent on the parametric adjustment and the reconstruction algorithm used. Although synthetic data have been widely employed to optimize experiments, the resulting reconstructed volumes might not have optimal quality. The purpose of the present study is to offer quality indicators that can be applied to data samples in order to improve the quality of velocity results obtained by the tomo-PIV technique. The methodology proposed can potentially lead to significantly reduction in the time required to optimize a tomo-PIV reconstruction, also leading to better quality velocity results. Tomo-PIV data provided by a six-camera turbulent boundary-layer experiment were used to optimize the reconstruction algorithms according to this methodology. Velocity statistics measurements obtained by optimized BIMART, SMART and MART algorithms were compared with hot-wire anemometer data and velocity measurement uncertainties were computed. Results indicated that BIMART and SMART algorithms produced reconstructed volumes with equivalent quality as the standard MART with the benefit of reduced computational time.

Volume reconstruction optimization for tomo-PIV algorithms applied to experimental data

International Nuclear Information System (INIS)

Martins, Fabio J W A; Foucaut, Jean-Marc; Stanislas, Michel; Thomas, Lionel; Azevedo, Luis F A

2015-01-01

Tomographic PIV is a three-component volumetric velocity measurement technique based on the tomographic reconstruction of a particle distribution imaged by multiple camera views. In essence, the performance and accuracy of this technique is highly dependent on the parametric adjustment and the reconstruction algorithm used. Although synthetic data have been widely employed to optimize experiments, the resulting reconstructed volumes might not have optimal quality. The purpose of the present study is to offer quality indicators that can be applied to data samples in order to improve the quality of velocity results obtained by the tomo-PIV technique. The methodology proposed can potentially lead to significantly reduction in the time required to optimize a tomo-PIV reconstruction, also leading to better quality velocity results. Tomo-PIV data provided by a six-camera turbulent boundary-layer experiment were used to optimize the reconstruction algorithms according to this methodology. Velocity statistics measurements obtained by optimized BIMART, SMART and MART algorithms were compared with hot-wire anemometer data and velocity measurement uncertainties were computed. Results indicated that BIMART and SMART algorithms produced reconstructed volumes with equivalent quality as the standard MART with the benefit of reduced computational time. (paper)

Data-Driven Methods to Diversify Knowledge of Human Psychology

OpenAIRE

Jack, Rachael E.; Crivelli, Carlos; Wheatley, Thalia

2017-01-01

open access article Psychology aims to understand real human behavior. However, cultural biases in the scientific process can constrain knowledge. We describe here how data-driven methods can relax these constraints to reveal new insights that theories can overlook. To advance knowledge we advocate a symbiotic approach that better combines data-driven methods with theory.

A variational study on BRDF reconstruction in a structured light scanner

DEFF Research Database (Denmark)

Nielsen, Jannik Boll; Stets, Jonathan Dyssel; Lyngby, Rasmus Ahrenkiel

2017-01-01

Time-efficient acquisition of reflectance behavior together with surface geometry is a challenging problem. In this study, we investigate the impact of system parameter uncertainties when incorporating a data-driven BRDF reconstruction approach into the standard pipeline of a structured light...... setup. Results show that while uncertainties in vertex positions and normals have a high impact on the quality of reconstructed BRDFs, object geometry and light source properties have very little influence on the reconstructed BRDFs. With this analysis, practitioners now have insight in the tolerances...... required for accurate BRDF acquisition to work....

DIRAC data production management

CERN Document Server

Smith, A C

2008-01-01

The LHCb Computing Model describes the dataflow for all stages in the processing of real and simulated events, and defines the role of LHCb associated Tier-1 and Tier-2 computing centers. The WLCG 'Dress Rehearsal' exercise aims to allow LHC experiments to deploy the full chain of their Computing Models, making use of all underlying WLCG services and resources, in preparation for real data taking. During this exercise simulated RAW physics data, matching the properties of eventual real data, will be uploaded from the LHCb Online storage system to Grid enabled storage. This data will then be replicated to LHCb Tier-1 centers and subsequently processed (reconstructed and stripped). The product of this processing is user analysis data that are distributed to all LHCb Tier-1 centers. DIRAC, LHCbs Workload and Data Management System, supports the implementation of the Computing Model in a data driven, real time and coordinated fashion.

PHYLOGEOrec: A QGIS plugin for spatial phylogeographic reconstruction from phylogenetic tree and geographical information data

Science.gov (United States)

Nashrulloh, Maulana Malik; Kurniawan, Nia; Rahardi, Brian

2017-11-01

The increasing availability of genetic sequence data associated with explicit geographic and environment (including biotic and abiotic components) information offers new opportunities to study the processes that shape biodiversity and its patterns. Developing phylogeography reconstruction, by integrating phylogenetic and biogeographic knowledge, provides richer and deeper visualization and information on diversification events than ever before. Geographical information systems such as QGIS provide an environment for spatial modeling, analysis, and dissemination by which phylogenetic models can be explicitly linked with their associated spatial data, and subsequently, they will be integrated with other related georeferenced datasets describing the biotic and abiotic environment. We are introducing PHYLOGEOrec, a QGIS plugin for building spatial phylogeographic reconstructions constructed from phylogenetic tree and geographical information data based on QGIS2threejs. By using PHYLOGEOrec, researchers can integrate existing phylogeny and geographical information data, resulting in three-dimensional geographic visualizations of phylogenetic trees in the Keyhole Markup Language (KML) format. Such formats can be overlaid on a map using QGIS and finally, spatially viewed in QGIS by means of a QGIS2threejs engine for further analysis. KML can also be viewed in reputable geobrowsers with KML-support (i.e., Google Earth).

A High-Speed, Event-Driven, Active Pixel Sensor Readout for Photon-Counting Microchannel Plate Detectors

Science.gov (United States)

Kimble, Randy A.; Pain, Bedabrata; Norton, Timothy J.; Haas, J. Patrick; Oegerle, William R. (Technical Monitor)

2002-01-01

Silicon array readouts for microchannel plate intensifiers offer several attractive features. In this class of detector, the electron cloud output of the MCP intensifier is converted to visible light by a phosphor; that light is then fiber-optically coupled to the silicon array. In photon-counting mode, the resulting light splashes on the silicon array are recognized and centroided to fractional pixel accuracy by off-chip electronics. This process can result in very high (MCP-limited) spatial resolution while operating at a modest MCP gain (desirable for dynamic range and long term stability). The principal limitation of intensified CCD systems of this type is their severely limited local dynamic range, as accurate photon counting is achieved only if there are not overlapping event splashes within the frame time of the device. This problem can be ameliorated somewhat by processing events only in pre-selected windows of interest of by using an addressable charge injection device (CID) for the readout array. We are currently pursuing the development of an intriguing alternative readout concept based on using an event-driven CMOS Active Pixel Sensor. APS technology permits the incorporation of discriminator circuitry within each pixel. When coupled with suitable CMOS logic outside the array area, the discriminator circuitry can be used to trigger the readout of small sub-array windows only when and where an event splash has been detected, completely eliminating the local dynamic range problem, while achieving a high global count rate capability and maintaining high spatial resolution. We elaborate on this concept and present our progress toward implementing an event-driven APS readout.

Understanding extreme rainfall events in Australia through historical data

Science.gov (United States)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this

Order reconstruction phenomena and temperature-driven dynamics in a 3D zenithally bistable device

KAUST Repository

Raisch, A.

2014-07-01

We model the zenithally bistable device (ZBD) in three dimensions (3D), within the Landau-de Gennes theory, and find three stable static states in 3D without an applied field: the vertically aligned nematic (VAN) state, the hybrid aligned nematic (HAN) state and a third, high-tilt state, which we call the THAN state, with an interior and a surface defect. We recover the order reconstruction (OR) phenomenon around the defects in the HAN and THAN states and the 3D THAN and HAN solutions exhibit stable biaxial cylinders connecting defects on opposite faces of the ZBD device. We demonstrate a two-way temperature-driven switching between high-tilt and low-tilt states through controlled heating and cooling procedures in two dimensions (2D), with no applied fields. © CopyrightEPLA, 2014.

Component-Based Data-Driven Predictive Maintenance to Reduce Unscheduled Maintenance Events

NARCIS (Netherlands)

Verhagen, W.J.C.; Curran, R.; de Boer, L.W.M.; Chen, C.H.; Trappey, A.C.; Peruzzini, M.; Stjepandić, J.; Wognum, N.

2017-01-01

Costs associated with unscheduled and preventive maintenance can contribute significantly to an airline's expenditure. Reliability analysis can help to identify and plan for maintenance events. Reliability analysis in industry is often limited to statistically based

Research on a Hierarchical Dynamic Automatic Voltage Control System Based on the Discrete Event-Driven Method

Directory of Open Access Journals (Sweden)

Yong Min

2013-06-01

Full Text Available In this paper, concepts and methods of hybrid control systems are adopted to establish a hierarchical dynamic automatic voltage control (HD-AVC system, realizing the dynamic voltage stability of power grids. An HD-AVC system model consisting of three layers is built based on the hybrid control method and discrete event-driven mechanism. In the Top Layer, discrete events are designed to drive the corresponding control block so as to avoid solving complex multiple objective functions, the power system’s characteristic matrix is formed and the minimum amplitude eigenvalue (MAE is calculated through linearized differential-algebraic equations. MAE is applied to judge the system’s voltage stability and security and construct discrete events. The Middle Layer is responsible for management and operation, which is also driven by discrete events. Control values of the control buses are calculated based on the characteristics of power systems and the sensitivity method. Then control values generate control strategies through the interface block. In the Bottom Layer, various control devices receive and implement the control commands from the Middle Layer. In this way, a closed-loop power system voltage control is achieved. Computer simulations verify the validity and accuracy of the HD-AVC system, and verify that the proposed HD-AVC system is more effective than normal voltage control methods.

Track Reconstruction and b-Jet Identification for the ATLAS Trigger System

CERN Document Server

Coccaro, A; The ATLAS collaboration

2011-01-01

A sophisticated trigger system, capable of real-time track reconstruction, is in place in the ATLAS experiment, to reject most of the events containing uninteresting background collisions while preserving as much as possible the interesting physics signals. The strategy adopted for fast reconstruction of charged tracks and in particular its application to the selection of jets from the hadronization of b-quarks is reviewed. Track reconstruction is routinely used for selection based on various physics objects while b-jet triggers are actively selecting events from the beginning of the 2011 LHC data-taking campaign.

Data-Driven Innovation through Open Government Data

DEFF Research Database (Denmark)

Jetzek, Thorhildur; Avital, Michel; Bjørn-Andersen, Niels

2014-01-01

The exponentially growing production of data and the social trend towards openness and sharing are power-ful forces that are changing the global economy and society. Governments around the world have become active participants in this evolution, opening up their data for access and reuse by public...... and private agents alike. The phenomenon of Open Government Data has spread around the world in the last four years, driven by the widely held belief that use of Open Government Data has the ability to generate both economic and social value. However, a cursory review of the popular press, as well...... as an investigation of academic research and empirical data, reveals the need to further understand the relationship between Open Government Data and value. In this paper, we focus on how use of Open Government Data can bring about new innovative solutions that can generate social and economic value. We apply...

Data-driven Simulations of Magnetic Connectivity in Behind-the-Limb Gamma-ray Flares and Associated Coronal Mass Ejections

Science.gov (United States)

Jin, M.; Petrosian, V.; Liu, W.; Nitta, N.; Omodei, N.; Rubio da Costa, F.; Effenberger, F.; Li, G.; Pesce-Rollins, M.

2017-12-01

Recent Fermi detection of high-energy gamma-ray emission from the behind-the-limb (BTL) solar flares pose a puzzle on the particle acceleration and transport mechanisms in such events. Due to the large separation between the flare site and the location of gamma-ray emission, it is believed that the associated coronal mass ejections (CMEs) play an important role in accelerating and subsequently transporting particles back to the Sun to produce obseved gamma-rays. We explore this scenario by simulating the CME associated with a well-observed flare on 2014 September 1 about 40 degrees behind the east solar limb and by comparing the simulation and observational results. We utilize a data-driven global magnetohydrodynamics model (AWSoM: Alfven-wave Solar Model) to track the dynamical evolution of the global magnetic field during the event and investigate the magnetic connectivity between the CME/CME-driven shock and the Fermi emission region. Moreover, we derive the time-varying shock parameters (e.g., compression ratio, Alfven Mach number, and ThetaBN) over the area that is magnetically connected to the visible solar disk where Fermi gamma-ray emission originates. Our simulation shows that the visible solar disk develops connections both to the flare site and to the CME-driven shock during the eruption, which indicate that the CME's interaction with the global solar corona is critical for understanding such Fermi BTL events and gamma-ray flares in general. We discuss the causes and implications of Fermi BTL events, in the framework of a potential shift of paradigm on particle acceleration in solar flares/CMEs.

GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume

Directory of Open Access Journals (Sweden)

Xing Zhao

2009-01-01

Full Text Available Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.

HEP Community White Paper on Software Trigger and Event Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Albrecht, Johannes; et al.

2018-02-23

Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments over the next 10 years will require the HEP community to address a number of challenges in the area of software and computing. For this reason, the HEP software community has engaged in a planning process over the past two years, with the objective of identifying and prioritizing the research and development required to enable the next generation of HEP detectors to fulfill their full physics potential. The aim is to produce a Community White Paper which will describe the community strategy and a roadmap for software and computing research and development in HEP for the 2020s. The topics of event reconstruction and software triggers were considered by a joint working group and are summarized together in this document.

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2

Energy Technology Data Exchange (ETDEWEB)

Aaboud, M. [Univ. Mohamed Premier et LPTPM, Oujda (Morocco). Faculte des Sciences; Aad, G. [CPPM, Aix-Marseille Univ. et CNRS/IN2P3, Marseille (France); Abbott, B. [Oklahoma Univ., Norman, OK (United States). Homer L. Dodge Dept. of Physics and Astronomy; Collaboration: ATLAS Collaboration; and others

2017-10-15

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb{sup -1} of data collected by the ATLAS experiment and simulation of proton-proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is 0.061 ± 0.006(stat.) ± 0.014(syst.) and 0.093 ± 0.017(stat.) ± 0.021(syst.) for jet transverse momenta of 200-400 GeV and 1400-1600 GeV, respectively. (orig.)

Intensity-based bayesian framework for image reconstruction from sparse projection data

International Nuclear Information System (INIS)

Rashed, E.A.; Kudo, Hiroyuki

2009-01-01

This paper presents a Bayesian framework for iterative image reconstruction from projection data measured over a limited number of views. The classical Nyquist sampling rule yields the minimum number of projection views required for accurate reconstruction. However, challenges exist in many medical and industrial imaging applications in which the projection data is undersampled. Classical analytical reconstruction methods such as filtered backprojection (FBP) are not a good choice for use in such cases because the data undersampling in the angular range introduces aliasing and streak artifacts that degrade lesion detectability. In this paper, we propose a Bayesian framework for maximum likelihood-expectation maximization (ML-EM)-based iterative reconstruction methods that incorporates a priori knowledge obtained from expected intensity information. The proposed framework is based on the fact that, in tomographic imaging, it is often possible to expect a set of intensity values of the reconstructed object with relatively high accuracy. The image reconstruction cost function is modified to include the l 1 norm distance to the a priori known information. The proposed method has the potential to regularize the solution to reduce artifacts without missing lesions that cannot be expected from the a priori information. Numerical studies showed a significant improvement in image quality and lesion detectability under the condition of highly undersampled projection data. (author)

Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Jaewook Jung

2017-03-01

Full Text Available With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL combined with Hypothesize and Test (HAT. The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International

Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data.

Science.gov (United States)

Jung, Jaewook; Jwa, Yoonseok; Sohn, Gunho

2017-03-19

With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS) data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP) technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL) combined with Hypothesize and Test (HAT). The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International Society for

Analyzing direct dark matter detection data with unrejected background events by the AMIDAS website

International Nuclear Information System (INIS)

Shan, Chung-Lin

2012-01-01

In this talk I have presented the data analysis results of extracting properties of halo WIMPs: the mass and the (ratios between the) spin-independent and spin-dependent couplings/cross sections on nucleons by the AMIDAS website by taking into account possible unrejected background events in the analyzed data sets. Although non-standard astronomical setup has been used to generate pseudodata sets for our analyses, it has been found that, without prior information/assumption about the local density and velocity distribution of halo Dark Matter, these WIMP properties have been reconstructed with ∼ 2% to ∼< 30% deviations from the input values.

[The application of forensic medical knowledge for the reconstruction of historical events].

Science.gov (United States)

Kovalev, A V; Molin, Yu A; Gorshkov, A N; Smolyanitsky, A G; Mazurova, E A; Vorontsov, G A

2015-01-01

The objective of the present study was to summarize the results of many year investigations on the application of forensic medical methods and experience for the reconstruction of historical events including identification of the ancient Russian saints' hallows and statesmen's remains, elucidation of the genuine causes of death of the members of the Russian Imperial House of Romanovs based on the recently discovered archival materials, restoration of the character of the injuries suffered by Aleksander II, M.I. Kutuzov, P. Demidov, G. Gapon., and G. Rasputin, the attribution A.S. Pushkin's memorial belongings based on the biological traces, and the like.

Apparatus and method for reconstructing data

International Nuclear Information System (INIS)

1981-01-01

A method and apparatus is described for constructing a two-dimensional picture of an object slice from linear projections of radiation not absorbed or scattered by the object, using convolution methods of data reconstruction, useful in the fields of medical radiology, microscopy, and non-destructive testing. (U.K.)

Direct 2-D reconstructions of conductivity and permittivity from EIT data on a human chest.

Science.gov (United States)

Herrera, Claudia N L; Vallejo, Miguel F M; Mueller, Jennifer L; Lima, Raul G

2015-01-01

A novel direct D-bar reconstruction algorithm is presented for reconstructing a complex conductivity distribution from 2-D EIT data. The method is applied to simulated data and archival human chest data. Permittivity reconstructions with the aforementioned method and conductivity reconstructions with the previously existing nonlinear D-bar method for real-valued conductivities depicting ventilation and perfusion in the human chest are presented. This constitutes the first fully nonlinear D-bar reconstructions of human chest data and the first D-bar permittivity reconstructions of experimental data. The results of the human chest data reconstructions are compared on a circular domain versus a chest-shaped domain.

Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP.

Science.gov (United States)

Wei, Qinglai; Song, Ruizhuo; Yan, Pengfei

2016-02-01

This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for continuous-time unknown nonlinear systems with disturbance. According to the input-output data of the nonlinear system, an effective recurrent neural network is introduced to reconstruct the dynamics of the nonlinear system. Considering the system disturbance as a control input, a two-player zero-sum optimal control problem is established. Adaptive dynamic programming (ADP) is developed to obtain the optimal control under the worst case of the disturbance. Three single-layer neural networks, including one critic and two action networks, are employed to approximate the performance index function, the optimal control law, and the disturbance, respectively, for facilitating the implementation of the ADP method. Convergence properties of the ADP method are developed to show that the system state will converge to a finite neighborhood of the equilibrium. The weight matrices of the critic and the two action networks are also convergent to finite neighborhoods of their optimal ones. Finally, the simulation results will show the effectiveness of the developed data-driven ADP methods.

System architecture for high speed reconstruction in time-of-flight positron tomography

International Nuclear Information System (INIS)

Campagnolo, R.E.; Bouvier, A.; Chabanas, L.; Robert, C.

1985-06-01

A new generation of Time Of Flight (TOF) positron tomograph with high resolution and high count rate capabilities is under development in our group. After a short recall of the data acquisition process and image reconstruction in a TOF PET camera, we present the data acquisition system which achieves a data transfer rate of 0.8 mega events per second or more if necessary in list mode. We describe the reconstruction process based on a five stages pipe line architecture using home made processors. The expected performance with this architecture is a time reconstruction of six seconds per image (256x256 pixels) of one million events. This time could be reduce to 4 seconds. We conclude with the future developments of the system

Grammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data

Science.gov (United States)

Yu, Q.; Helmholz, P.; Belton, D.; West, G.

2014-04-01

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.

Data Driven Constraints for the SVM

DEFF Research Database (Denmark)

Darkner, Sune; Clemmensen, Line Katrine Harder

2012-01-01

We propose a generalized data driven constraint for support vector machines exemplified by classification of paired observations in general and specifically on the human ear canal. This is particularly interesting in dynamic cases such as tissue movement or pathologies developing over time. Assum...

A RISC multiprocessor event trigger for the data acquisition system of the H1 experiment at HERA

International Nuclear Information System (INIS)

Campbell, A.J.

1991-09-01

In late 1991 HERA will for the first time collide stored beams of electrons and protons. This paper describes the multiple (RISC) modern reduced instruction set processor system for online event filtering and reconstruction installed within the data acquisition system of the H1 experiment. Data is processed at a continuous average rate of ∼ 6 Mbytes/s in parallel by ∼ 20 R3000 VMEbus based monoboard computers providing some 400 mips computing power. (author)

3D Fractal reconstruction of terrain profile data based on digital elevation model

International Nuclear Information System (INIS)

Huang, Y.M.; Chen, C.-J.

2009-01-01

Digital Elevation Model (DEM) often makes it difficult for terrain reconstruction and data storage due to the failure in acquisition of details with higher resolution. If original terrain of DEM can be simulated, resulting in geographical details can be represented precisely while reducing the data size, then an effective reconstruction scheme is essential. This paper adopts two sets of real-world 3D terrain profile data to proceed data reducing, i.e. data sampling randomly, then reconstruct them through 3D fractal reconstruction. Meanwhile, the quantitative and qualitative difference generated from different reduction rates were evaluated statistically. The research results show that, if 3D fractal interpolation method is applied to DEM reconstruction, the higher reduction rate can be obtained for DEM of larger data size with respect to that of smaller data size under the assumption that the entire terrain structure is still maintained.

Object specific reconstruction using compressively sensed data

International Nuclear Information System (INIS)

Mahalanobis, Abhijit

2008-01-01

Compressed sensing holds the promise for radically novel sensors that can perfectly reconstruct images using considerably less samples of data than required by the otherwise general Shannon sampling theorem. In surveillance systems however, it is also desirable to cue regions of the image where objects of interest may exist. Thus in this paper, we are interested in imaging interesting objects in a scene, without necessarily seeking perfect reconstruction of the whole image. We show that our goals are achieved by minimizing a modified L2-norm criterion with good results when the reconstruction of only specific objects is of interest. The method yields a simple closed form analytical solution that does not require iterative processing. Objects can be meaningfully sensed in considerable detail while heavily compressing the scene elsewhere. Essentially, this embeds the object detection and clutter discrimination function in the sensing and imaging process.

Data-driven regionalization of housing markets

NARCIS (Netherlands)

Helbich, M.; Brunauer, W.; Hagenauer, J.; Leitner, M.

2013-01-01

This article presents a data-driven framework for housing market segmentation. Local marginal house price surfaces are investigated by means of mixed geographically weighted regression and are reduced to a set of principal component maps, which in turn serve as input for spatial regionalization. The

Profile reconstruction from neutron reflectivity data and a priori knowledge

International Nuclear Information System (INIS)

Leeb, H.

2008-01-01

The problem of incomplete and noisy information in profile reconstruction from neutron reflectometry data is considered. In particular methods of Bayesian statistics in combination with modelling or inverse scattering techniques are considered in order to properly include the required a priori knowledge to obtain quantitatively reliable estimates of the reconstructed profiles. Applying Bayes theorem the results of different experiments on the same sample can be consistently included in the profile reconstruction

Data-Driven Baseline Estimation of Residential Buildings for Demand Response

Directory of Open Access Journals (Sweden)

Saehong Park

2015-09-01

Full Text Available The advent of advanced metering infrastructure (AMI generates a large volume of data related with energy service. This paper exploits data mining approach for customer baseline load (CBL estimation in demand response (DR management. CBL plays a significant role in measurement and verification process, which quantifies the amount of demand reduction and authenticates the performance. The proposed data-driven baseline modeling is based on the unsupervised learning technique. Specifically we leverage both the self organizing map (SOM and K-means clustering for accurate estimation. This two-level approach efficiently reduces the large data set into representative weight vectors in SOM, and then these weight vectors are clustered by K-means clustering to find the load pattern that would be similar to the potential load pattern of the DR event day. To verify the proposed method, we conduct nationwide scale experiments where three major cities’ residential consumption is monitored by smart meters. Our evaluation compares the proposed solution with the various types of day matching techniques, showing that our approach outperforms the existing methods by up to a 68.5% lower error rate.

Baseline Preferences for Daily, Event-Driven, or Periodic HIV Pre-Exposure Prophylaxis among Gay and Bisexual Men in the PRELUDE Demonstration Project

Directory of Open Access Journals (Sweden)

Stefanie J. Vaccher

2017-12-01

Full Text Available IntroductionThe effectiveness of daily pre-exposure prophylaxis (PrEP is well established. However, there has been increasing interest in non-daily dosing schedules among gay and bisexual men (GBM. This paper explores preferences for PrEP dosing schedules among GBM at baseline in the PRELUDE demonstration project.Materials and methodsIndividuals at high-risk of HIV were enrolled in a free PrEP demonstration project in New South Wales, Australia, between November 2014 and April 2016. At baseline, they completed an online survey containing detailed behavioural, demographic, and attitudinal questions, including their ideal way to take PrEP: daily (one pill taken every day, event-driven (pills taken only around specific risk events, or periodic (daily dosing during periods of increased risk.ResultsOverall, 315 GBM (98% of study sample provided a preferred PrEP dosing schedule at baseline. One-third of GBM expressed a preference for non-daily PrEP dosing: 20% for event-driven PrEP, and 14% for periodic PrEP. Individuals with a trade/vocational qualification were more likely to prefer periodic to daily PrEP [adjusted odds ratio (aOR = 4.58, 95% confidence intervals (95% CI: (1.68, 12.49], compared to individuals whose highest level of education was high school. Having an HIV-positive main regular partner was associated with strong preference for daily, compared to event-driven PrEP [aOR = 0.20, 95% CI: (0.04, 0.87]. Participants who rated themselves better at taking medications were more likely to prefer daily over periodic PrEP [aOR = 0.39, 95% CI: (0.20, 0.76].DiscussionIndividuals’ preferences for PrEP schedules are associated with demographic and behavioural factors that may impact on their ability to access health services and information about PrEP and patterns of HIV risk. At the time of data collection, there were limited data available about the efficacy of non-daily PrEP schedules, and clinicians only recommended daily PrEP to

Locative media and data-driven computing experiments

Directory of Open Access Journals (Sweden)

Sung-Yueh Perng

2016-06-01

Full Text Available Over the past two decades urban social life has undergone a rapid and pervasive geocoding, becoming mediated, augmented and anticipated by location-sensitive technologies and services that generate and utilise big, personal, locative data. The production of these data has prompted the development of exploratory data-driven computing experiments that seek to find ways to extract value and insight from them. These projects often start from the data, rather than from a question or theory, and try to imagine and identify their potential utility. In this paper, we explore the desires and mechanics of data-driven computing experiments. We demonstrate how both locative media data and computing experiments are ‘staged’ to create new values and computing techniques, which in turn are used to try and derive possible futures that are ridden with unintended consequences. We argue that using computing experiments to imagine potential urban futures produces effects that often have little to do with creating new urban practices. Instead, these experiments promote Big Data science and the prospect that data produced for one purpose can be recast for another and act as alternative mechanisms of envisioning urban futures.

Deep Convolutional Networks for Event Reconstruction and Particle Tagging on NOvA and DUNE

CERN Multimedia

CERN. Geneva

2017-01-01

Deep Convolutional Neural Networks (CNNs) have been widely applied in computer vision to solve complex problems in image recognition and analysis. In recent years many efforts have emerged to extend the use of this technology to HEP applications, including the Convolutional Visual Network (CVN), our implementation for identification of neutrino events. In this presentation I will describe the core concepts of CNNs, the details of our particular implementation in the Caffe framework and our application to identify NOvA events. NOvA is a long baseline neutrino experiment whose main goal is the measurement of neutrino oscillations. This relies on the accurate identification and reconstruction of the neutrino flavor in the interactions we observe. In 2016 the NOvA experiment released results for the observation of oscillations in the ν μ → ν e channel, the first HEP result employing CNNs. I will also discuss our approach at event identification on NOvA as well as recent developments in the application of CNN...

Writing through Big Data: New Challenges and Possibilities for Data-Driven Arguments

Science.gov (United States)

Beveridge, Aaron

2017-01-01

As multimodal writing continues to shift and expand in the era of Big Data, writing studies must confront the new challenges and possibilities emerging from data mining, data visualization, and data-driven arguments. Often collected under the broad banner of "data literacy," students' experiences of data visualization and data-driven…

Design, development and deployment of the ALICE experiment data processing for simulation, reconstruction and analysis

International Nuclear Information System (INIS)

Carminati, Federico

2013-01-01

The ALICE (A Large Ion Collider Experiment) at the CERN (Conseil Europeen pour la Recherche Nucleaire) LHC (Large Hadron Collider) facility uses an integrated software framework for the design of the experimental apparatus, the evaluation of its performance and the processing of the experimental data. The author has designed this framework. It includes the event generators and the algorithms for particle transport describing the details of the interaction particles - matter (designed and implemented by the author), the reconstruction of the particle trajectories and the final physics analysis. (author) [fr

Some comments on reconstructing the historical climate of California, USA

International Nuclear Information System (INIS)

Mock, C.J.

2006-01-01

This paper describes some examples of historical climate reconstruction pertaining to California, USA, focusing mostly on winter climate given the expected strongest teleconnection signals for this season. Climatic data consist of early instrumental data from the US Army Surgeon General at military forts, observers of the Smithsonian Institution, the Signal Service, and some private observers. Documentary (non-instrumental) data were also used in assessing extreme events. Original daily records of these data were carefully assessed for discontinuities from examining diurnal temperature ranges and daily precipitation amounts. The climatic reconstructions conducted were as follows: 1) winter precipitation time series for selected locations since 1850, particularly for Sacramento and San Francisco, 2) winter temperature time series for selected locations since 1850, and 3) analyses of an extreme flooding event in January 1862 and a landfalling tropical cyclone of September 1939. Results indicate distinctive wetter winters for central and northern California in the late nineteenth century, and some of these wetter years correspond to well-known very strong El Ni no events. Connections to weaker El Nino and La Nina events, however, are not clearly evident. The flood of January 1862 is considered unprecedented when compared to other floods of the last 130 years. The reconstruction of a landfalling tropical cyclone for September 1939 near Los Angeles suggests its intensity at just below hurricane strength

Reconstructing the 2015 Flash Flood event of Salgar Colombia, The Case of a Poor Gauged Basin

Science.gov (United States)

Velasquez, N.; Zapata, E.; Hoyos Ortiz, C. D.; Velez, J. I.

2017-12-01

Flash floods events associated with severe precipitation events are highly destructive, often resulting in significant human and economic losses. Due to their nature, flash floods trend to occur in medium to small basins located within complex high mountainous regions. In the Colombian Andean region these basins are very common, with the aggravating factor that the vulnerability is considerably high as some important human settlements are located within these basins, frequently occupating flood plains and other flash-flood prone areas. During the dawn of May 18 of 2015 two severe rainfall events generated a flash flood event in the municipality ofSalgar, La Liboriana basin, locatedin the northwestern Colombian Andes, resulting in more than 100 human casualties and significant economic losses. The present work is a reconstruction of the hydrological processes that took place before and during the Liboriana flash flood event, analyzed as a case of poorly gauged basin.The event conditions where recreated based on radar retrievals and a hydrological distributed model, linked with a proposed 1D hydraulic model and simple shallow landslide model. Results suggest that the flash flood event was caused by the occurrence of two successive severe convective events over the same basin, with an important modulation associated with soil characteristics and water storage.Despite of its simplicity, the proposed hydraulic model achieves a good representation of the flooded area during the event, with limitations due to the adopted spatial scale (12.7 meters, from ALOS PALSAR images). Observed landslides were obtained from satellite images; for this case the model simulates skillfully the landslide occurrence regions with small differences in the exact locations.To understand this case, radar data shows to be key due to specific convective cores location and rainfall intensity estimation.In mountainous regions, there exists a significant number of settlements with similar

Reconstruction of t anti tH (H → bb) events using deep neural networks with the CMS detector

Energy Technology Data Exchange (ETDEWEB)

Rieger, Marcel; Erdmann, Martin; Fischer, Benjamin; Fischer, Robert; Heidemann, Fabian; Quast, Thorben; Rath, Yannik [III. Physikalisches Institut A, RWTH Aachen University (Germany)

2016-07-01

The measurement of Higgs boson production in association with top-quark pairs (t anti tH) is an important goal of Run 2 of the LHC as it allows for a direct measurement of the underlying Yukawa coupling. Due to the complex final state, however, the analysis of semi-leptonic t anti tH events with the Higgs boson decaying into a pair of bottom-quarks is challenging. A promising method for tackling jet parton associations are Deep Neural Networks (DNN). While being a widely spread machine learning algorithm in modern industry, DNNs are on the way to becoming established in high energy physics. We present a study on the reconstruction of the final state using DNNs, comparing to Boosted Decision Trees (BDT) as benchmark scenario. This is accomplished by generating permutations of simulated events and comparing them with truth information to extract reconstruction efficiencies.

Validity of proxy data obtained by different psychological autopsy information reconstruction techniques.

Science.gov (United States)

Fang, L; Zhang, J

2010-01-01

Two informants were interviewed for each of 416 living controls (individuals sampled from the normal population) interviewed in a Chinese case-control psychological autopsy study. The validity of proxy data, obtained using seven psychological autopsy information reconstruction techniques (types 1, 2 and A - E), was evaluated, with living controls' self reports used as the gold-standard. Proxy data for reconstruction technique types 1, 2 and D on the Impulsivity Inventory Scale (total impulsivity score) were no different from the living controls' self report gold standard, whereas data for types A and E were smaller than data from living controls. On the 'acceptance or resignation' sub-scale of the avoidance coping dimension of the Moos Coping Response Inventory, information obtained by reconstruction technique types 1 and D was not significantly different from the living controls' self reports, whereas proxy data from types 2, A and E were smaller than those from the living controls. No statistically significant differences were identified for other proxy data obtained by reconstruction technique types 1, 2, A, D and E. These results indicate that using a second informant does not significantly enhance information reconstruction for the target.

Late Holocene environmental reconstructions and their implications on flood events, typhoon, and agricultural activities in NE Taiwan

Science.gov (United States)

Wang, L.-C.; Behling, H.; Lee, T.-Q.; Li, H.-C.; Huh, C.-A.; Shiau, L.-J.; Chang, Y.-P.

2014-10-01

We reconstructed paleoenvironmental changes from a sediment archive of a lake in the floodplain of the Ilan Plain of NE Taiwan on multi-decadal resolution for the last ca. 1900 years. On the basis of pollen and diatom records, we evaluated past floods, typhoons, and agricultural activities in this area which are sensitive to the hydrological conditions in the western Pacific. Considering the high sedimentation rates with low microfossil preservations in our sedimentary record, multiple flood events were. identified during the period AD 100-1400. During the Little Ice Age phase 1 (LIA 1 - AD 1400-1620), the abundant occurrences of wetland plant (Cyperaceae) and diatom frustules imply less flood events under stable climate conditions in this period. Between AD 500 and 700 and the Little Ice Age phase 2 (LIA 2 - AD 1630-1850), the frequent typhoons were inferred by coarse sediments and planktonic diatoms, which represented more dynamical climate conditions than in the LIA 1. By comparing our results with the reconstructed changes in tropical hydrological conditions, we suggested that the local hydrology in NE Taiwan is strongly influenced by typhoon-triggered heavy rainfalls, which could be influenced by the variation of global temperature, the expansion of the Pacific warm pool, and the intensification of El Niño-Southern Oscillation (ENSO) events.

Three-dimensional focus of attention for iterative cone-beam micro-CT reconstruction

International Nuclear Information System (INIS)

Benson, T M; Gregor, J

2006-01-01

Three-dimensional iterative reconstruction of high-resolution, circular orbit cone-beam x-ray CT data is often considered impractical due to the demand for vast amounts of computer cycles and associated memory. In this paper, we show that the computational burden can be reduced by limiting the reconstruction to a small, well-defined portion of the image volume. We first discuss using the support region defined by the set of voxels covered by all of the projection views. We then present a data-driven preprocessing technique called focus of attention that heuristically separates both image and projection data into object and background before reconstruction, thereby further reducing the reconstruction region of interest. We present experimental results for both methods based on mouse data and a parallelized implementation of the SIRT algorithm. The computational savings associated with the support region are substantial. However, the results for focus of attention are even more impressive in that only about one quarter of the computer cycles and memory are needed compared with reconstruction of the entire image volume. The image quality is not compromised by either method

Retrospective data-driven respiratory gating for PET/CT

International Nuclear Information System (INIS)

Schleyer, Paul J; O'Doherty, Michael J; Barrington, Sally F; Marsden, Paul K

2009-01-01

Respiratory motion can adversely affect both PET and CT acquisitions. Respiratory gating allows an acquisition to be divided into a series of motion-reduced bins according to the respiratory signal, which is typically hardware acquired. In order that the effects of motion can potentially be corrected for, we have developed a novel, automatic, data-driven gating method which retrospectively derives the respiratory signal from the acquired PET and CT data. PET data are acquired in listmode and analysed in sinogram space, and CT data are acquired in cine mode and analysed in image space. Spectral analysis is used to identify regions within the CT and PET data which are subject to respiratory motion, and the variation of counts within these regions is used to estimate the respiratory signal. Amplitude binning is then used to create motion-reduced PET and CT frames. The method was demonstrated with four patient datasets acquired on a 4-slice PET/CT system. To assess the accuracy of the data-derived respiratory signal, a hardware-based signal was acquired for comparison. Data-driven gating was successfully performed on PET and CT datasets for all four patients. Gated images demonstrated respiratory motion throughout the bin sequences for all PET and CT series, and image analysis and direct comparison of the traces derived from the data-driven method with the hardware-acquired traces indicated accurate recovery of the respiratory signal.

Quantitative SPECT reconstruction of iodine-123 data

International Nuclear Information System (INIS)

Gilland, D.R.; Jaszczak, R.J.; Greer, K.L.; Coleman, R.E.

1991-01-01

Many clinical and research studies in nuclear medicine require quantitation of iodine-123 ( 123 I) distribution for the determination of kinetics or localization. The objective of this study was to implement several reconstruction methods designed for single-photon emission computed tomography (SPECT) using 123 I and to evaluate their performance in terms of quantitative accuracy, image artifacts, and noise. The methods consisted of four attenuation and scatter compensation schemes incorporated into both the filtered backprojection/Chang (FBP) and maximum likelihood-expectation maximization (ML-EM) reconstruction algorithms. The methods were evaluated on data acquired of a phantom containing a hot sphere of 123 I activity in a lower level background 123 I distribution and nonuniform density media. For both reconstruction algorithms, nonuniform attenuation compensation combined with either scatter subtraction or Metz filtering produced images that were quantitatively accurate to within 15% of the true value. The ML-EM algorithm demonstrated quantitative accuracy comparable to FBP and smaller relative noise magnitude for all compensation schemes

Reconstruction of March-June precipitation from tree rings in central Liaoning, China

Science.gov (United States)

Wang, Yanchao; Liu, Yu

2017-11-01

A dendrochronological profile was generated from Chinese pines ( Pinus tabulaeformis Carr.) in the Qianshan Mountains in northeastern China. Based on correlation analyses, the pattern of precipitation from March to June ( P 36 ) was reconstructed using a simple linear model, which explained 42.7% of the total variance in observed precipitation from 1951 to 2012. The reconstructed P 36 series revealed a consistently increasing trend in precipitation during the twentieth century in the Qianshan Mountains. The reconstructed data showed trends that were similar to those in the variation in trends for March-June precipitation observed at the Shenyang station, the reconstructed January-May precipitation trends in Shenyang City, and the reconstructed average June-September relative humidity for Yiwulü Mountain. The reconstructed data also showed good agreement with the droughts reported in historical documents and recorded by meteorological stations in Liaoning. Spatial correlation analyses show that the reconstructed data reflect the variability in precipitation that occurs over much of northeastern China. In addition, our reconstruction showed a significant periodicity. The significant correlations between the reconstructed P 36 and the El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and sunspot numbers indicate that precipitation variability in the Qianshan Mountain region is probably driven by extensive atmosphere-sea interactions and solar activities.

Image reconstruction from limited angle Compton camera data

International Nuclear Information System (INIS)

Tomitani, T.; Hirasawa, M.

2002-01-01

The Compton camera is used for imaging the distributions of γ ray direction in a γ ray telescope for astrophysics and for imaging radioisotope distributions in nuclear medicine without the need for collimators. The integration of γ rays on a cone is measured with the camera, so that some sort of inversion method is needed. Parra found an analytical inversion algorithm based on spherical harmonics expansion of projection data. His algorithm is applicable to the full set of projection data. In this paper, six possible reconstruction algorithms that allow image reconstruction from projections with a finite range of scattering angles are investigated. Four algorithms have instability problems and two others are practical. However, the variance of the reconstructed image diverges in these two cases, so that window functions are introduced with which the variance becomes finite at a cost of spatial resolution. These two algorithms are compared in terms of variance. The algorithm based on the inversion of the summed back-projection is superior to the algorithm based on the inversion of the summed projection. (author)

Muon reconstruction efficiency, momentum scale and resolution in pp collisions at 8TeV with ATLAS

CERN Document Server

Dimitrievska, A; The ATLAS collaboration

2014-01-01

The ATLAS experiment identifies and reconstructs muons with two high precision tracking systems, the Inner Detector and the Muon Spectrometer, which provide independent measurements of the muon momentum. This poster summarizes the performance of the combined muon reconstruction in terms of reconstruction efficiency, momentum scale and resolution. Data-driven techniques are used to derive corrections to be applied to simulation in order to reproduce the reconstruction efficiency, momentum scale and resolution as observed in experimental data, and to asses systematic uncertainties on these quantities. The analysed dataset corresponds to an integrated luminosity of 20.4 fb−1 from 8 TeV pp collisions recorded in 2012.

Self-Adaptive Event-Driven Simulation of Multi-Scale Plasma Systems

Science.gov (United States)

Omelchenko, Yuri; Karimabadi, Homayoun

2005-10-01

Multi-scale plasmas pose a formidable computational challenge. The explicit time-stepping models suffer from the global CFL restriction. Efficient application of adaptive mesh refinement (AMR) to systems with irregular dynamics (e.g. turbulence, diffusion-convection-reaction, particle acceleration etc.) may be problematic. To address these issues, we developed an alternative approach to time stepping: self-adaptive discrete-event simulation (DES). DES has origin in operations research, war games and telecommunications. We combine finite-difference and particle-in-cell techniques with this methodology by assuming two caveats: (1) a local time increment, dt for a discrete quantity f can be expressed in terms of a physically meaningful quantum value, df; (2) f is considered to be modified only when its change exceeds df. Event-driven time integration is self-adaptive as it makes use of causality rules rather than parametric time dependencies. This technique enables asynchronous flux-conservative update of solution in accordance with local temporal scales, removes the curse of the global CFL condition, eliminates unnecessary computation in inactive spatial regions and results in robust and fast parallelizable codes. It can be naturally combined with various mesh refinement techniques. We discuss applications of this novel technology to diffusion-convection-reaction systems and hybrid simulations of magnetosonic shocks.

Application of AI techniques to a voice-actuated computer system for reconstructing and displaying magnetic resonance imaging data

Science.gov (United States)

Sherley, Patrick L.; Pujol, Alfonso, Jr.; Meadow, John S.

1990-07-01

To provide a means of rendering complex computer architectures languages and input/output modalities transparent to experienced and inexperienced users research is being conducted to develop a voice driven/voice response computer graphics imaging system. The system will be used for reconstructing and displaying computed tomography and magnetic resonance imaging scan data. In conjunction with this study an artificial intelligence (Al) control strategy was developed to interface the voice components and support software to the computer graphics functions implemented on the Sun Microsystems 4/280 color graphics workstation. Based on generated text and converted renditions of verbal utterances by the user the Al control strategy determines the user''s intent and develops and validates a plan. The program type and parameters within the plan are used as input to the graphics system for reconstructing and displaying medical image data corresponding to that perceived intent. If the plan is not valid the control strategy queries the user for additional information. The control strategy operates in a conversation mode and vocally provides system status reports. A detailed examination of the various AT techniques is presented with major emphasis being placed on their specific roles within the total control strategy structure. 1.

Vertex Reconstruction for AEGIS’ FACT Detector

CERN Document Server

Themistokleous, Neofytos

2017-01-01

My project dealt with the development of a vertex reconstruction technique to discriminate antihydrogen from background signals in the AEGIS apparatus. It involved the creation of a Toy Monte-Carlo to simulate particle annihilation events, and a vertex reconstruction utility based on the Bayesian theory of probability. The first results based on 107 generated events with single track in the detector are encouraging. For such events, the algorithm can reconstruct the z-coordinate accurately , while for the r-coordinate the result is less accurate.

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

International Nuclear Information System (INIS)

Xu, Shiyu; Chen, Ying; Lu, Jianping; Zhou, Otto

2015-01-01

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

Energy Technology Data Exchange (ETDEWEB)

Xu, Shiyu, E-mail: shiyu.xu@gmail.com; Chen, Ying, E-mail: adachen@siu.edu [Department of Electrical and Computer Engineering, Southern Illinois University Carbondale, Carbondale, Illinois 62901 (United States); Lu, Jianping; Zhou, Otto [Department of Physics and Astronomy and Curriculum in Applied Sciences and Engineering, University of North Carolina Chapel Hill, Chapel Hill, North Carolina 27599 (United States)

2015-09-15

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.

Parametric image reconstruction using spectral analysis of PET projection data

International Nuclear Information System (INIS)

Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat

1998-01-01

Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)

Telling and measuring urban floods: event reconstruction by means of public-domain media

Science.gov (United States)

Macchia, S.; Gallo, E.; Claps, P.

2012-04-01

In the last decade, the diffusion of mobile telephones and ond of low-cost digital cameras have changed the public approach to catastrophes. As regards floods, it has become widespread the availability of images and videos taken in urban areas. Searching into Youtube or Youreporter, for example, one can understand how often citizen are considering to report even scary events. Nowadays these amateurs videos are often used in news world reports, which often increase or dampen the public perception of flood risk. More importantly, these amateur videos can play a crucial role in a didactic and technical representation of media flooding problems. The question so arise: why don't use the amateur videos for civil protection purposes? This work shows a new way to use flood images and videos to obtain technical data and spread safety information. Specifically, we show how to determine the height and speed of water flow, which have been achieved in some places during Genoa flood - 4th November 2011 - For this event we have downloaded more than 50 videos from different websites, where the authors have provided information about the time of recording, the geographical coordinates and the height above ground of the point of recording. The support by Google tools, such as Google maps and StreetWiew © has allowed us to geographically locate the recording points, so to put together shots and slides necessary to put together a whole reconstruction of the event. Future research will be in the direction of using these videos to generate a tool for the Google platforms, in order to address an easily achievable, yet accurate, information to the public, so to warn people on how to behave in front of imminent floods.

Event-driven control of a speed varying digital displacement machine

DEFF Research Database (Denmark)

Pedersen, Niels Henrik; Johansen, Per; Andersen, Torben O.

2017-01-01

. The controller synthesis is carried out as a discrete optimal deterministic problem with full state feedback. Based on a linear analysis of the feedback control system, stability is proven in a pre-specified operation region. Simulation of a non-linear evaluation model with the controller implemented shows great...... be treated as a Discrete Linear Time Invariant control problem with synchronous sampling rate. To make synchronous linear control theory applicable for a variable speed digital displacement machine, a method based on event-driven control is presented. Using this method, the time domain differential equations...... are converted into the spatial (position) domain to obtain a constant sampling rate and thus allowing for use of classical control theory. The method is applied to a down scaled digital fluid power motor, where the motor speed is controlled at varying references under varying pressure and load torque conditions...

Reconstructing Methane Emission Events in the Arctic Ocean: Observations from the Past to Present

Science.gov (United States)

Panieri, G.; Mienert, J.; Fornari, D. J.; Torres, M. E.; Lepland, A.

2015-12-01

Methane hydrates are ice-like crystals that are present along continental margins, occurring in the pore space of deep sediments or as massive blocks near the seafloor. They form in high pressure and low temperature environments constrained by thermodynamic stability, and supply of methane. In the Arctic, gas hydrates are abundant, and the methane released by their destabilization can affect local to global carbon budgets and cycles, ocean acidification, and benthic community survival. With the aim to locate in space and time the periodicity of methane venting, CAGE is engaged in a vast research program in the Arctic, a component of which comprises the analyses of numerous sediment cores and correlative geophysical and geochemical data from different areas. Here we present results from combined analyses of biogenic carbonate archives along the western Svalbard Margin, which reveal past methane venting events in this region. The reconstruction of paleo-methane discharge is complicated by precipitation of secondary carbonate on foraminifera shells, driven by an increase in alkalinity during anaerobic oxidation of methane (AOM). The biogeochemical processes involved in methane cycling and processes that drive methane migration affect the depth where AOM occurs, with relevance to secondary carbonate formation. Our results show the value and complexity of separating primary vs. secondary signals in bioarchives with relevance to understanding fluid-burial history in methane seep provinces. Results from our core analyses are integrated with observations made during the CAGE15-2 cruise in May 2015, when we deployed a towed vehicle equipped with camera, multicore and water sampling capabilities. The instrument design was based on the Woods Hole Oceanographic Institution (WHOI) MISO TowCam sled equipped with a deep-sea digital camera and CTD real-time system. Sediment sampling was visually-guided using this system. In one of the pockmarks along the Vestnesa Ridge where high

Data-Driven Learning of Q-Matrix

Science.gov (United States)

Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2012-01-01

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known "Q"-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the "Q"-matrix and estimation of…

Event-by-Event Elliptic Flow Fluctuations from PHOBOS

Science.gov (United States)

Wosiek, B.; Alver, B.; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Busza, W.; Carroll, A.; Chai, Z.; Chetluru, V.; Decowski, M. P.; García, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Halliwell, C.; Hamblen, J.; Harnarine, I.; Hauer, M.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Hołyński, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Khan, N.; Kulinich, P.; Kuo, C. M.; Li, W.; Lin, W. T.; Loizides, C.; Manly, S.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Reed, C.; Richardson, E.; Roland, C.; Roland, G.; Sagerer, J.; Seals, H.; Sedykh, I.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Szostak, A.; Tonjes, M. B.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Walters, P.; Wenger, E.; Willhelm, D.; Wolfs, F. L. H.; Woźniak, K.; Wyngaardt, S.; Wysłouch, B.

2009-04-01

Recently PHOBOS has focused on the study of fluctuations and correlations in particle production in heavy-ion collisions at the highest energies delivered by the Relativistic Heavy Ion Collider (RHIC). In this report, we present results on event-by-event elliptic flow fluctuations in (Au+Au) collisions at sqrt {sNN}=200 GeV. A data-driven method was used to estimate the dominant contribution from non-flow correlations. Over the broad range of collision centralities, the observed large elliptic flow fluctuations are in agreement with the fluctuations in the initial source eccentricity.

Late Holocene environmental reconstructions and the implications on flood events, typhoon patterns, and agriculture activities in NE Taiwan

Science.gov (United States)

Wang, L.-C.; Behling, H.; Lee, T.-Q.; Li, H.-C.; Huh, C.-A.; Shiau, L.-J.; Chang, Y.-P.

2014-05-01

In this study, we reconstructed the paleoenvironmental changes from a sediment archive of the floodplain lake in Ilan Plain of NE Taiwan on multi-decadal resolution for the last ca. 1900 years. On the basis of pollen and diatom records, we evaluated the record of past vegetation, floods, typhoons and agriculture activities of this area, which is sensitive to the hydrological conditions of the West Pacific. High sedimentation rates with low microfossil preservations reflected multiple flood events and humid climatic conditions during 100-1400 AD. A shortly interrupted dry phase can be found during 940-1010 AD. The driest phase corresponds to the Little Ice Age phase 1 (LIA1, 1400-1620 AD) with less disturbance by flood events, which enhanced the occurrence of wetlands (Cyperaceae) and diatom depositions. Humid phases with frequent typhoons are inferred by high percentages of Lagerstroemia and high ratios of planktonic/benthic diatoms, respectively, during 500-700 AD and Little Ice Age phase 2 (LIA2, 1630-1850 AD). The occurrences of cultivated Poaceae (Oryza) during 1250-1300 AD and the last ~400 years, reflect agriculture activities, which seems to implicate strongly with the environmental stability. Finally, we found flood events which dominated during the El Niño-like stage, but dry events as well as frequent typhoon events happened during the La Niña-like stage. After comparing our results with the reconstructed proxy for tropical hydrological conditions, we suggested that the local hydrology in coastal East Asia were strongly affected by the typhoon-triggered heavy rainfalls which were influenced by the variation of global temperature, expansion of the Pacific warm pool and intensification of ENSO events.

Improving parallel imaging by jointly reconstructing multi-contrast data.

Science.gov (United States)

Bilgic, Berkin; Kim, Tae Hyung; Liao, Congyu; Manhard, Mary Kate; Wald, Lawrence L; Haldar, Justin P; Setsompop, Kawin

2018-08-01

To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition. We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction. We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error. JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

A Model-Driven Approach for 3D Modeling of Pylon from Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Qingquan Li

2015-09-01

Full Text Available Reconstructing three-dimensional model of the pylon from LiDAR (Light Detection And Ranging point clouds automatically is one of the key techniques for facilities management GIS system of high-voltage nationwide transmission smart grid. This paper presents a model-driven three-dimensional pylon modeling (MD3DM method using airborne LiDAR data. We start with constructing a parametric model of pylon, based on its actual structure and the characteristics of point clouds data. In this model, a pylon is divided into three parts: pylon legs, pylon body and pylon head. The modeling approach mainly consists of four steps. Firstly, point clouds of individual pylon are detected and segmented from massive high-voltage transmission corridor point clouds automatically. Secondly, an individual pylon is divided into three relatively simple parts in order to reconstruct different parts with different strategies. Its position and direction are extracted by contour analysis of the pylon body in this stage. Thirdly, the geometric features of the pylon head are extracted, from which the head type is derived with a SVM (Support Vector Machine classifier. After that, the head is constructed by seeking corresponding model from pre-build model library. Finally, the body is modeled by fitting the point cloud to planes. Experiment results on several point clouds data sets from China Southern high-voltage nationwide transmission grid from Yunnan Province to Guangdong Province show that the proposed approach can achieve the goal of automatic three-dimensional modeling of the pylon effectively.

Reconstruction of reflectance data using an interpolation technique.

Science.gov (United States)

Abed, Farhad Moghareh; Amirshahi, Seyed Hossein; Abed, Mohammad Reza Moghareh

2009-03-01

A linear interpolation method is applied for reconstruction of reflectance spectra of Munsell as well as ColorChecker SG color chips from the corresponding colorimetric values under a given set of viewing conditions. Hence, different types of lookup tables (LUTs) have been created to connect the colorimetric and spectrophotometeric data as the source and destination spaces in this approach. To optimize the algorithm, different color spaces and light sources have been used to build different types of LUTs. The effects of applied color datasets as well as employed color spaces are investigated. Results of recovery are evaluated by the mean and the maximum color difference values under other sets of standard light sources. The mean and the maximum values of root mean square (RMS) error between the reconstructed and the actual spectra are also calculated. Since the speed of reflectance reconstruction is a key point in the LUT algorithm, the processing time spent for interpolation of spectral data has also been measured for each model. Finally, the performance of the suggested interpolation technique is compared with that of the common principal component analysis method. According to the results, using the CIEXYZ tristimulus values as a source space shows priority over the CIELAB color space. Besides, the colorimetric position of a desired sample is a key point that indicates the success of the approach. In fact, because of the nature of the interpolation technique, the colorimetric position of the desired samples should be located inside the color gamut of available samples in the dataset. The resultant spectra that have been reconstructed by this technique show considerable improvement in terms of RMS error between the actual and the reconstructed reflectance spectra as well as CIELAB color differences under the other light source in comparison with those obtained from the standard PCA technique.

A First-level Event Selector for the CBM Experiment at FAIR

International Nuclear Information System (INIS)

Cuveland, J de; Lindenstruth, V

2011-01-01

The CBM experiment at the upcoming FAIR accelerator aims to create highest baryon densities in nucleus-nucleus collisions and to explore the properties of super-dense nuclear matter. Event rates of 10 MHz are needed for high-statistics measurements of rare probes, while event selection requires complex global triggers like secondary vertex search. To meet these demands, the CBM experiment uses self-triggered detector front-ends and a data push readout architecture. The First-level Event Selector (FLES) is the central physics selection system in CBM. It receives all hits and performs online event selection on the 1 TByte/s input data stream. The event selection process requires high-throughput event building and full event reconstruction using fast, vectorized track reconstruction algorithms. The current FLES architecture foresees a scalable high-performance computer. To achieve the high throughput and computation efficiency, all available computing devices will have to be used, in particular FPGAs at the first stages of the system and heterogeneous many-core architectures such as CPUs for efficient track reconstruction. A high-throughput network infrastructure and flow control in the system are other key aspects. In this paper, we present the foreseen architecture of the First-level Event Selector.

Electrons for Neutrinos: Using Electron Scattering to Develop New Energy Reconstruction for Future Deuterium-Based Neutrino Detectors

Science.gov (United States)

Silva, Adrian; Schmookler, Barak; Papadopoulou, Afroditi; Schmidt, Axel; Hen, Or; Khachatryan, Mariana; Weinstein, Lawrence

2017-09-01

Using wide phase-space electron scattering data, we study a novel technique for neutrino energy reconstruction for future neutrino oscillation experiments. Accelerator-based neutrino oscillation experiments require detailed understanding of neutrino-nucleus interactions, which are complicated by the underlying nuclear physics that governs the process. One area of concern is that neutrino energy must be reconstructed event-by-event from the final-state kinematics. In charged-current quasielastic scattering, Fermi motion of nucleons prevents exact energy reconstruction. However, in scattering from deuterium, the momentum of the electron and proton constrain the neutrino energy exactly, offering a new avenue for reducing systematic uncertainties. To test this approach, we analyzed d (e ,e' p) data taken with the CLAS detector at Jefferson Lab Hall B and made kinematic selection cuts to obtain quasielastic events. We estimated the remaining inelastic background by using d (e ,e' pπ-) events to produce a simulated dataset of events with an undetected π-. These results demonstrate the feasibility of energy reconstruction in a hypothetical future deuterium-based neutrino detector. Supported by the Paul E. Gray UROP Fund, MIT.

Collaborative Event-Driven Coverage and Rate Allocation for Event Miss-Ratio Assurances in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ozgur Sanli H

2010-01-01

Full Text Available Wireless sensor networks are often required to provide event miss-ratio assurance for a given event type. To meet such assurances along with minimum energy consumption, this paper shows how a node's activation and rate assignment is dependent on its distance to event sources, and proposes a practical coverage and rate allocation (CORA protocol to exploit this dependency in realistic environments. Both uniform event distribution and nonuniform event distribution are considered and the notion of ideal correlation distance around a clusterhead is introduced for on-duty node selection. In correlation distance guided CORA, rate assignment assists coverage scheduling by determining which nodes should be activated for minimizing data redundancy in transmission. Coverage scheduling assists rate assignment by controlling the amount of overlap among sensing regions of neighboring nodes, thereby providing sufficient data correlation for rate assignment. Extensive simulation results show that CORA meets the required event miss-ratios in realistic environments. CORA's joint coverage scheduling and rate allocation reduce the total energy expenditure by 85%, average battery energy consumption by 25%, and the overhead of source coding up to 90% as compared to existing rate allocation techniques.

New insights on historic droughts in the UK: Analysis of 200 river flow reconstructions for 1890-2015

Science.gov (United States)

Parry, Simon; Barker, Lucy; Hannaford, Jamie; Prudhomme, Christel; Smith, Katie; Svensson, Cecilia; Tanguy, Maliko

2017-04-01

Hydrological droughts of the last 50 years in the UK have been well characterised owing to a relatively dense hydrometric network. Prior to this, observed river flow data were generally limited in their spatial coverage and often subject to considerable uncertainty. Whilst qualitative records indicate the occurrence of severe droughts in the late 19th and early 20th centuries, including scenarios which may cause substantial impacts to contemporary water supply systems, existing observations are not sufficient to describe their spatio-temporal characteristics. As such, insights on drought in the UK are constrained and a range of stakeholders including water companies and regulators would benefit from a more thorough assessment of historic drought characteristics and their variability. The multi-disciplinary Historic Droughts project aims to rigorously characterise droughts in the UK to inform improved drought management and communication. Driven by rainfall and potential evapotranspiration data that have been extended using recovered records, lumped catchment hydrological models are used to reconstruct daily river flows from 1890 to 2015 for more than 200 catchments across the UK. The reconstructions are derived within a state-of-the-art modelling framework which allows a comprehensive assessment of model, structure and parameter uncertainty. Standardised and threshold-based indicators are applied to the river flow reconstructions to identify and characterise hydrological drought events. The reconstructions are most beneficial in comprehensively describing well known but poorly quantified late 19th and early 20th century droughts, placing the spatial and temporal footprint of these often extreme events within the context of modern episodes for the first time. Oscillations between drought-rich and drought-poor periods are shown not to be limited to the recent observational past, providing an increased sample size of events against which to test a range of airflow and

A study of reconstruction artifacts in cone beam tomography using filtered backprojection and iterative EM algorithms

International Nuclear Information System (INIS)

Zeng, G.L.; Gullberg, G.T.

1990-01-01

Reconstruction artifacts in cone beam tomography are studied for filtered backprojection (Feldkamp) and iterative EM algorithms. The filtered backprojection algorithm uses a voxel-driven, interpolated backprojection to reconstruct the cone beam data; whereas, the iterative EM algorithm performs ray-driven projection and backprojection operations for each iteration. Two weight in schemes for the projection and backprojection operations in the EM algorithm are studied. One weights each voxel by the length of the ray through the voxel and the other equates the value of a voxel to the functional value of the midpoint of the line intersecting the voxel, which is obtained by interpolating between eight neighboring voxels. Cone beam reconstruction artifacts such as rings, bright vertical extremities, and slice-to slice cross talk are not found with parallel beam and fan beam geometries

Sparse regularization for EIT reconstruction incorporating structural information derived from medical imaging.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Mueller-Lisse, Ullrich; Moeller, Knut

2016-06-01

Electrical impedance tomography (EIT) reconstructs the conductivity distribution of a domain using electrical data on its boundary. This is an ill-posed inverse problem usually solved on a finite element mesh. For this article, a special regularization method incorporating structural information of the targeted domain is proposed and evaluated. Structural information was obtained either from computed tomography images or from preliminary EIT reconstructions by a modified k-means clustering. The proposed regularization method integrates this structural information into the reconstruction as a soft constraint preferring sparsity in group level. A first evaluation with Monte Carlo simulations indicated that the proposed solver is more robust to noise and the resulting images show fewer artifacts. This finding is supported by real data analysis. The structure based regularization has the potential to balance structural a priori information with data driven reconstruction. It is robust to noise, reduces artifacts and produces images that reflect anatomy and are thus easier to interpret for physicians.

A Data-driven Concept Schema for Defining Clinical Research Data Needs

Science.gov (United States)

Hruby, Gregory W.; Hoxha, Julia; Ravichandran, Praveen Chandar; Mendonça, Eneida A.; Hanauer, David A; Weng, Chunhua

2016-01-01

OBJECTIVES The Patient, Intervention, Control/Comparison, and Outcome (PICO) framework is an effective technique for framing a clinical question. We aim to develop the counterpart of PICO to structure clinical research data needs. METHODS We use a data-driven approach to abstracting key concepts representing clinical research data needs by adapting and extending an expert-derived framework originally developed for defining cancer research data needs. We annotated clinical trial eligibility criteria, EHR data request logs, and data queries to electronic health records (EHR), to extract and harmonize concept classes representing clinical research data needs. We evaluated the class coverage, class preservation from the original framework, schema generalizability, schema understandability, and schema structural correctness through a semi-structured interview with eight multidisciplinary domain experts. We iteratively refined the schema based on the evaluations. RESULTS Our data-driven schema preserved 68% of the 63 classes from the original framework and covered 88% (73/82) of the classes proposed by evaluators. Class coverage for participants of different backgrounds ranged from 60% to 100% with a median value of 95% agreement among the individual evaluators. The schema was found understandable and structurally sound. CONCLUSIONS Our proposed schema may serve as the counterpart to PICO for improving the research data needs communication between researchers and informaticians. PMID:27185504

Performance of Missing Transverse Momentum Reconstruction in Proton-Proton Collisions at $\\sqrt{s}$ = 7 TeV with ATLAS

CERN Document Server

Aad, Georges; Abdallah, Jalal; Abdelalim, Ahmed Ali; Abdesselam, Abdelouahab; Abdinov, Ovsat; Abi, Babak; Abolins, Maris; Abramowicz, Halina; Abreu, Henso; Acerbi, Emilio; Acharya, Bobby Samir; Adams, David; Addy, Tetteh; Adelman, Jahred; Aderholz, Michael; Adomeit, Stefanie; Adragna, Paolo; Adye, Tim; Aefsky, Scott; Aguilar-Saavedra, Juan Antonio; Aharrouche, Mohamed; Ahlen, Steven; Ahles, Florian; Ahmad, Ashfaq; Ahsan, Mahsana; Aielli, Giulio; Akdogan, Taylan; Akesson, Torsten Paul; Akimoto, Ginga; Akimov, Andrei; Akiyama, Kunihiro; Alam, Mohammad; Alam, Muhammad Aftab; Albert, Justin; Albrand, Solveig; Aleksa, Martin; Aleksandrov, Igor; Alessandria, Franco; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Aliev, Malik; Alimonti, Gianluca; Alison, John; Aliyev, Magsud; Allport, Phillip; Allwood-Spiers, Sarah; Almond, John; Aloisio, Alberto; Alon, Raz; Alonso, Alejandro; Alviggi, Mariagrazia; Amako, Katsuya; Amaral, Pedro; Amelung, Christoph; Ammosov, Vladimir; Amorim, Antonio; Amoros, Gabriel; Amram, Nir; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Andrieux, Marie-Laure; Anduaga, Xabier; Angerami, Aaron; Anghinolfi, Francis; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoun, Sahar; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Arce, Ayana; Archambault, John-Paul; Arfaoui, Samir; Arguin, Jean-Francois; Arik, Engin; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnault, Christian; Artamonov, Andrei; Artoni, Giacomo; Arutinov, David; Asai, Shoji; Asfandiyarov, Ruslan; Ask, Stefan; Asman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astbury, Alan; Astvatsatourov, Anatoli; Atoian, Grigor; Aubert, Bernard; Auerbach, Benjamin; Auge, Etienne; Augsten, Kamil; Aurousseau, Mathieu; Austin, Nicholas; Avolio, Giuseppe; Avramidou, Rachel Maria; Axen, David; Ay, Cano; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baccaglioni, Giuseppe; Bacci, Cesare; Bach, Andre; Bachacou, Henri; Bachas, Konstantinos; Bachy, Gerard; Backes, Moritz; Backhaus, Malte; Badescu, Elisabeta; Bagnaia, Paolo; Bahinipati, Seema; Bai, Yu; Bailey, David; Bain, Travis; Baines, John; Baker, Oliver Keith; Baker, Mark; Baker, Sarah; Banas, Elzbieta; Banerjee, Piyali; Banerjee, Swagato; Banfi, Danilo; Bangert, Andrea Michelle; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barashkou, Andrei; Galtieri, Angela Barbaro; Barber, Tom; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Bardin, Dmitri; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimaraes da Costa, Joao; Barrillon, Pierre; Bartoldus, Rainer; Barton, Adam Edward; Bartsch, Detlef; Bartsch, Valeria; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Andreas; Battistin, Michele; Battistoni, Giuseppe; Bauer, Florian; Bawa, Harinder Singh; Beare, Brian; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Beckingham, Matthew; Becks, Karl-Heinz; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Begel, Michael; Behar Harpaz, Silvia; Behera, Prafulla; Beimforde, Michael; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellina, Francesco; Bellomo, Massimiliano; Belloni, Alberto; Beloborodova, Olga; Belotskiy, Konstantin; Beltramello, Olga; Ben Ami, Sagi; Benary, Odette; Benchekroun, Driss; Benchouk, Chafik; Bendel, Markus; Benekos, Nektarios; Benhammou, Yan; Benjamin, Douglas; Benoit, Mathieu; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Berglund, Elina; Beringer, Jurg; Bernardet, Karim; Bernat, Pauline; Bernhard, Ralf; Bernius, Catrin; Berry, Tracey; Bertin, Antonio; Bertinelli, Francesco; Bertolucci, Federico; Besana, Maria Ilaria; Besson, Nathalie; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Biscarat, Catherine; Bitenc, Urban; Black, Kevin; Blair, Robert; Blanchard, Jean-Baptiste; Blanchot, Georges; Blazek, Tomas; Blocker, Craig; Blocki, Jacek; Blondel, Alain; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Boddy, Christopher Richard; Boehler, Michael; Boek, Jennifer; Boelaert, Nele; Boser, Sebastian; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Bolnet, Nayanka Myriam; Bona, Marcella; Bondarenko, Valery; Boonekamp, Maarten; 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Caramarcu, Costin; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Bryan; Caron, Sascha; Montoya, German D.Carrillo; Carter, Antony; Carter, Janet; Carvalho, Joao; Casadei, Diego; Casado, Maria Pilar; Cascella, Michele; Caso, Carlo; Castaneda Hernandez, Alfredo Martin; Castaneda-Miranda, Elizabeth; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Cataldi, Gabriella; Cataneo, Fernando; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cauz, Diego; Cavalleri, Pietro; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cetin, Serkant Ali; Cevenini, Francesco; Chafaq, Aziz; Chakraborty, Dhiman; Chan, Kevin; Chapleau, Bertrand; Chapman, John Derek; Chapman, John Wehrley; Chareyre, Eve; Charlton, Dave; Chavda, Vikash; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Shenjian; Chen, Tingyang; Chen, Xin; Cheng, Shaochen; Cheplakov, Alexander; Chepurnov, Vladimir; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Cheung, Sing-Leung; Chevalier, Laurent; Chiefari, Giovanni; Chikovani, Leila; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chizhov, Mihail; Choudalakis, Georgios; Chouridou, Sofia; Christidi, Illectra-Athanasia; Christov, Asen; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Ciapetti, Guido; Ciba, Krzysztof; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciobotaru, Matei Dan; Ciocca, Claudia; Ciocio, Alessandra; Cirilli, Manuela; Ciubancan, Mihai; Clark, Allan G.; Clark, Philip James; Cleland, Bill; Clemens, Jean-Claude; Clement, Benoit; Clement, Christophe; Clifft, Roger; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H.; Coe, Paul; Cogan, Joshua Godfrey; Coggeshall, James; Cogneras, Eric; Cojocaru, Claudiu; Colas, Jacques; Colijn, Auke-Pieter; Collard, Caroline; Collins, Neil; Collins-Tooth, Christopher; Collot, Johann; Colon, German; Conde Muino, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Consonni, Michele; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conventi, Francesco; Cook, James; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, Maria Jose; Costanzo, Davide; Costin, Tudor; Cote, David; Coura Torres, Rodrigo; Courneyea, Lorraine; Cowan, Glen; Cowden, Christopher; Cox, Brian; Cranmer, Kyle; Crescioli, Francesco; Cristinziani, Markus; Crosetti, Giovanni; Crupi, Roberto; Crepe-Renaudin, Sabine; Cuciuc, Constantin-Mihai; Cuenca Almenar, Cristobal; Donszelmann, Tulay Cuhadar; Curatolo, Maria; Curtis, Chris; Cwetanski, Peter; Czirr, Hendrik; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; D'Orazio, Alessia; Da Silva, Paulo Vitor; Da Via, Cinzia; Dabrowski, Wladyslaw; Dai, Tiesheng; Dallapiccola, Carlo; Dam, Mogens; Dameri, Mauro; Damiani, Daniel; Danielsson, Hans Olof; Dannheim, Dominik; Dao, Valerio; Darbo, Giovanni; Darlea, Georgiana Lavinia; Daum, Cornelis; Dauvergne, Jean-Pierre; Davey, Will; Davidek, Tomas; Davidson, Nadia; Davidson, Ruth; Davies, Eleanor; Davies, Merlin; Davison, Adam; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Dawson, John; Daya, Rozmin; De, Kaushik; De Asmundis, Riccardo; De Castro, Stefano; De Castro Faria Salgado, Pedro; De Cecco, Sandro; de Graat, Julien; De Groot, Nicolo; de Jong, Paul; de la Taille, Christophe; de la Torre, Hector; De Lotto, Barbara; De Mora, Lee; De Nooij, Lucie; De Oliveira Branco, Miguel; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; de Vivie De Regie, Jean-Baptiste; Dean, Simon; Dedovich, Dmitri; Degenhardt, James; Dehchar, Mohamed; del Papa, Carlo; del Peso, Jose; del Prete, Tarcisio; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delpierre, Pierre; Delruelle, Nicolas; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demirkoz, Bilge; Deng, Jianrong; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Devetak, Erik; Deviveiros, Pier-Olivier; Dewhurst, Alastair; DeWilde, Burton; Dhaliwal, Saminder; Dhullipudi, Ramasudhakar; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Luise, Silvestro; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Diaz, Marco Aurelio; Diblen, Faruk; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Yagci, Kamile Dindar; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, Andre; Doan, Thi Kieu Oanh; Dobbs, Matt; Dobinson, Robert; Dobos, Daniel; Dobson, Ellie; Dobson, Marc; Dodd, Jeremy; Doglioni, Caterina; Doherty, Tom; Doi, Yoshikuni; Dolejsi, Jiri; Dolenc, Irena; Dolezal, Zdenek; Dolgoshein, Boris; Dohmae, Takeshi; Donadelli, Marisilvia; Donega, Mauro; Donini, Julien; Dopke, Jens; Doria, Alessandra; dos Anjos, Andre; Dosil, Mireia; Dotti, Andrea; Dova, Maria-Teresa; Dowell, John; Doxiadis, Alexander; Doyle, Tony; Drasal, Zbynek; Drees, Jurgen; Dressnandt, Nandor; Drevermann, Hans; Driouichi, Chafik; Dris, Manolis; Dubbert, Jorg; Dubbs, Tim; Dube, Sourabh; Duchovni, Ehud; Duckeck, Guenter; Dudarev, Alexey; Dudziak, Fanny; Duhrssen, Michael; Duerdoth, Ian; Duflot, Laurent; Dufour, Marc-Andre; Dunford, Monica; Duran Yildiz, Hatice; Duxfield, Robert; Dwuznik, Michal; Dydak, Friedrich; Dzahini, Daniel; Duren, Michael; Ebenstein, William; Ebke, Johannes; Eckert, Simon; Eckweiler, Sebastian; Edmonds, Keith; Edwards, Clive; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Ehrich, Thies; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Eisenhandler, Eric; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Katherine; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Engelmann, Roderich; Engl, Albert; Epp, Brigitte; Eppig, Andrew; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Escobar, Carlos; Espinal Curull, Xavier; Esposito, Bellisario; Etienne, Francois; Etienvre, Anne-Isabelle; Etzion, Erez; Evangelakou, Despoina; Evans, Hal; Fabbri, Laura; Fabre, Caroline; Fakhrutdinov, Rinat; Falciano, Speranza; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farley, Jason; Farooque, Trisha; Farrington, Sinead; Farthouat, Philippe; Fassnacht, Patrick; Fassouliotis, Dimitrios; Fatholahzadeh, Baharak; Favareto, Andrea; Fayard, Louis; Fazio, Salvatore; Febbraro, Renato; Federic, Pavol; Fedin, Oleg; Fedorko, Woiciech; Fehling-Kaschek, Mirjam; Feligioni, Lorenzo; Fellmann, Denis; Felzmann, Ulrich; Feng, Cunfeng; Feng, Eric; Fenyuk, Alexander; Ferencei, Jozef; Ferland, Jonathan; Fernando, Waruna; Ferrag, Samir; Ferrando, James; Ferrara, Valentina; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferrer, Antonio; Ferrer, Maria Lorenza; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipcic, Andrej; Filippas, Anastasios; Filthaut, Frank; Fincke-Keeler, Margret; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Gordon; Fischer, Peter; Fisher, Matthew; Fisher, Steve; Flechl, Martin; Fleck, Ivor; Fleckner, Johanna; Fleischmann, Philipp; Fleischmann, Sebastian; Flick, Tobias; Flores Castillo, Luis; Flowerdew, Michael; Fokitis, Manolis; Fonseca Martin, Teresa; Forbush, David Alan; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Foster, Joe; Fournier, Daniel; Foussat, Arnaud; Fowler, Andrew; Fowler, Ken; Fox, Harald; Francavilla, Paolo; Franchino, Silvia; Francis, David; Frank, Tal; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; Fratina, Sasa; French, Sky; Friedrich, Felix; Froeschl, Robert; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gadfort, Thomas; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Gallas, Elizabeth; Gallas, Manuel; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Galyaev, Eugene; Gan, K.K.; Gao, Yongsheng; Gapienko, Vladimir; Gaponenko, Andrei; Garberson, Ford; Garcia-Sciveres, Maurice; Garcia, Carmen; Garcia Navarro, Jose Enrique; Gardner, Robert; Garelli, Nicoletta; Garitaonandia, Hegoi; Garonne, Vincent; Garvey, John; Gatti, Claudio; Gaudio, Gabriella; Gaumer, Olivier; Gaur, Bakul; Gauthier, Lea; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gayde, Jean-Christophe; Gazis, Evangelos; Ge, Peng; Gee, Norman; Geerts, Dani\\|{e}l Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Helene; Gentile, Simonetta; George, Matthias; George, Simon; Gerlach, Peter; Gershon, Avi; Geweniger, Christoph; Ghazlane, Hamid; Ghez, Philippe; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giakoumopoulou, Victoria; Giangiobbe, Vincent; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Adam; Gibson, Stephen; Gilbert, Laura; Gilchriese, Murdock; Gilewsky, Valentin; Gillberg, Dag; Gillman, Tony; Gingrich, Douglas; Ginzburg, Jonatan; Giokaris, Nikos; Giordano, Raffaele; Giorgi, Francesco Michelangelo; Giovannini, Paola; Giraud, Pierre-Francois; Giugni, Danilo; Giunta, Michele; Giusti, Paolo; Gjelsten, Borge Kile; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glazov, Alexandre; Glitza, Karl-Walter; Glonti, George; Godfrey, Jennifer; Godlewski, Jan; Goebel, Martin; Gopfert, Thomas; Goeringer, Christian; Gossling, Claus; Gottfert, Tobias; Goldfarb, Steven; Goldin, Daniel; Golling, Tobias; Golovnia, Serguei; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Goncalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; Gonidec, Allain; Gonzalez, Saul; Gonzalez de la Hoz, Santiago; Gonzalez Silva, Laura; Gonzalez-Sevilla, Sergio; Goodson, Jeremiah Jet; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorfine, Grant; Gorini, Benedetto; Gorini, Edoardo; Gorisek, Andrej; Gornicki, Edward; Gorokhov, Serguei; Goryachev, Vladimir; Gosdzik, Bjoern; Gosselink, Martijn; Gostkin, Mikhail Ivanovitch; Gough Eschrich, Ivo; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Grabowska-Bold, Iwona; Grabski, Varlen; Grafstrom, Per; Grah, Christian; Grahn, Karl-Johan; Grancagnolo, Francesco; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Grau, Nathan; Gray, Heather; Gray, Julia Ann; Graziani, Enrico; Grebenyuk, Oleg; Greenfield, Debbie; Greenshaw, Timothy; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grigalashvili, Nugzar; Grillo, Alexander; Grinstein, Sebastian; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grognuz, Joel; Groh, Manfred; Gross, Eilam; Grosse-Knetter, Joern; Groth-Jensen, Jacob; Grybel, Kai; Guarino, Victor; Guest, Daniel; Guicheney, Christophe; Guida, Angelo; Guillemin, Thibault; Guindon, Stefan; Guler, Hulya; Gunther, Jaroslav; Guo, Bin; Guo, Jun; Gupta, Ambreesh; Gusakov, Yury; Gushchin, Vladimir; Gutierrez, Andrea; Gutierrez, Phillip; Guttman, Nir; Gutzwiller, Olivier; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haas, Stefan; Haber, Carl; Hackenburg, Robert; Hadavand, Haleh Khani; Hadley, David; Haefner, Petra; Hahn, Ferdinand; Haider, Stefan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haller, Johannes; Hamacher, Klaus; Hamal, Petr; Hamilton, Andrew; Hamilton, Samuel; Han, Hongguang; Han, Liang; Hanagaki, Kazunori; Hance, Michael; Handel, Carsten; Hanke, Paul; Hansen, John Renner; Hansen, Jorgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hansson, Per; Hara, Kazuhiko; Hare, Gabriel; Harenberg, Torsten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Karl; Hartert, Jochen; Hartjes, Fred; Haruyama, Tomiyoshi; Harvey, Alex; Hasegawa, Satoshi; Hasegawa, Yoji; Hassani, Samira; Hatch, Mark; Hauff, Dieter; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawes, Brian; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Donovan; Hayakawa, Takashi; Hayden, Daniel; Hayward, Helen; Haywood, Stephen; Hazen, Eric; He, Mao; Head, Simon; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heinemann, Beate; Heisterkamp, Simon; Helary, Louis; Heller, Mathieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, Robert; Henke, Michael; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Henry-Couannier, Frederic; Hensel, Carsten; Henss, Tobias; Medina Hernandez, Carlos; Hernandez Jimenez, Yesenia; Herrberg, Ruth; Hershenhorn, Alon David; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hessey, Nigel; Hidvegi, Attila; Higon-Rodriguez, Emilio; Hill, Daniel; Hill, John; Hill, Norman; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirsch, Florian; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hohlfeld, Marc; Holder, Martin; Holmgren, Sven-Olof; Holy, Tomas; Holzbauer, Jenny; Homma, Yasuhiro; Hong, Tae Min; Hooft van Huysduynen, Loek; Horazdovsky, Tomas; Horn, Claus; Horner, Stephan; Horton, Katherine; Hostachy, Jean-Yves; Hou, Suen; Houlden, Michael; Hoummada, Abdeslam; Howarth, James; Howell, David; Hristova, Ivana; Hrivnac, Julius; Hruska, Ivan; Hryn'ova, Tetiana; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Huang, Guang Shun; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Hughes-Jones, Richard; Huhtinen, Mika; Hurst, Peter; Hurwitz, Martina; Husemann, Ulrich; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibbotson, Michael; Ibragimov, Iskander; Ichimiya, Ryo; Iconomidou-Fayard, Lydia; Idarraga, John; Idzik, Marek; Iengo, Paolo; Igonkina, Olga; Ikegami, Yoichi; Ikeno, Masahiro; Ilchenko, Yuri; Iliadis, Dimitrios; Ilic, Nikolina; Imbault, Didier; Imhaeuser, Martin; Imori, Masatoshi; Ince, Tayfun; Inigo-Golfin, Joaquin; Ioannou, Pavlos; Iodice, Mauro; Ionescu, Gelu; Irles Quiles, Adrian; Ishii, Koji; Ishikawa, Akimasa; Ishino, Masaya; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Ivashin, Anton; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, John; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakubek, Jan; Jana, Dilip; Jankowski, Ernest; Jansen, Eric; Jantsch, Andreas; Janus, Michel; Jarlskog, Goran; Jeanty, Laura; Jelen, Kazimierz; Jen-La Plante, Imai; Jenni, Peter; Jeremie, Andrea; Jez, Pavel; Jezequel, Stephane; Jha, Manoj Kumar; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Ge; Jin, Shan; Jinnouchi, Osamu; Joergensen, Morten Dam; Joffe, David; Johansen, Lars; Johansen, Marianne; Johansson, Erik; Johansson, Per; Johnert, Sebastian; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tegid; Jones, Tim; Jonsson, Ove; Joram, Christian; Jorge, Pedro; Joseph, John; Jovin, Tatjana; Ju, Xiangyang; Juranek, Vojtech; Jussel, Patrick; Juste Rozas, Aurelio; Kabachenko, Vasily; Kabana, Sonja; Kaci, Mohammed; Kaczmarska, Anna; Kadlecik, Peter; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kaiser, Steffen; Kajomovitz, Enrique; Kalinin, Sergey; Kalinovskaya, Lidia; Kama, Sami; Kanaya, Naoko; Kaneda, Michiru; Kanno, Takayuki; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kaplon, Jan; Kar, Deepak; Karagoz, Muge; Karnevskiy, Mikhail; Karr, Kristo; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasmi, Azzedine; Kass, Richard; Kastanas, Alex; Kataoka, Mayuko; Kataoka, Yousuke; Katsoufis, Elias; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kayl, Manuel; Kazanin, Vassili; Kazarinov, Makhail; Keates, James Robert; Keeler, Richard; Kehoe, Robert; Keil, Markus; Kekelidze, George; Kelly, Marc; Kennedy, John; Kenney, Christopher John; Kenyon, Mike; Kepka, Oldrich; Kerschen, Nicolas; Kersevan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Ketterer, Christian; Keung, Justin; Khakzad, Mohsen; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Kharchenko, Dmitri; Khodinov, Alexander; Kholodenko, Anatoli; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Nikolai; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hyeon Jin; Kim, Min Suk; Kim, Peter; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; Kirk, Julie; Kirsch, Guillaume; Kirsch, Lawrence; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kittelmann, Thomas; Kiver, Andrey; Kiyamura, Hironori; Kladiva, Eduard; Klaiber-Lodewigs, Jonas; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klemetti, Miika; Klier, Amit; Klimentov, Alexei; Klingenberg, Reiner; Klinkby, Esben; Klioutchnikova, Tatiana; Klok, Peter; Klous, Sander; Kluge, Eike-Erik; Kluge, Thomas; Kluit, Peter; Kluth, Stefan; Knecht, Neil; Kneringer, Emmerich; Knobloch, Juergen; Knoops, Edith; Knue, Andrea; Ko, Byeong Rok; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kocnar, Antonin; Kodys, Peter; Koneke, Karsten; Konig, Adriaan; Koenig, Sebastian; Kopke, Lutz; Koetsveld, Folkert; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kohn, Fabian; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kokott, Thomas; Kolachev, Guennady; Kolanoski, Hermann; Kolesnikov, Vladimir; Koletsou, Iro; Koll, James; Kollar, Daniel; Kollefrath, Michael; Kolya, Scott; Komar, Aston; Komaragiri, Jyothsna Rani; Komori, Yuto; Kondo, Takahiko; Kono, Takanori; Kononov, Anatoly; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kootz, Andreas; Koperny, Stefan; Kopikov, Sergey; Korcyl, Krzysztof; Kordas, Kostantinos; Koreshev, Victor; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotamaki, Miikka Juhani; Kotov, Sergey; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, James; Kreisel, Arik; Krejci, Frantisek; Kretzschmar, Jan; Krieger, Nina; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Kruger, Hans; Kruker, Tobias; Krumshteyn, Zinovii; Kruth, Andre; Kubota, Takashi; Kuehn, Susanne; Kugel, Andreas; Kuhl, Thorsten; Kuhn, Dietmar; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kummer, Christian; Kuna, Marine; Kundu, Nikhil; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurata, Masakazu; Kurochkin, Yurii; Kus, Vlastimil; Kuykendall, William; Kuze, Masahiro; Kuzhir, Polina; Kvita, Jiri; Kwee, Regina; La Rosa, Alessandro; La Rotonda, Laura; Labarga, Luis; Labbe, Julien; Lablak, Said; Lacasta, Carlos; Lacava, Francesco; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramon; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laisne, Emmanuel; Lamanna, Massimo; Lampen, Caleb; Lampl, Walter; Lancon, Eric; Landgraf, Ulrich; Landon, Murrough; Landsman, Hagar; Lane, Jenna; Lange, Clemens; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Larionov, Anatoly; Larner, Aimee; Lasseur, Christian; Lassnig, Mario; Laurelli, Paolo; Lavorato, Antonia; Lavrijsen, Wim; Laycock, Paul; Lazarev, Alexandre; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Maner, Christophe; Le Menedeu, Eve; Lebel, Celine; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Michel; Legendre, Marie; Leger, Annie; LeGeyt, Benjamin; Legger, Federica; Leggett, Charles; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Leltchouk, Mikhail; Lemmer, Boris; Lendermann, Victor; Leney, Katharine; Lenz, Tatiana; Lenzen, Georg; Lenzi, Bruno; Leonhardt, Kathrin; Leontsinis, Stefanos; Leroy, Claude; Lessard, Jean-Raphael; Lesser, Jonas; Lester, Christopher; Leung Fook Cheong, Annabelle; Leveque, Jessica; Levin, Daniel; Levinson, Lorne; Levitski, Mikhail; Lewandowska, Marta; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bo; Li, Haifeng; Li, Shu; Li, Xuefei; Liang, Zhihua; Liang, Zhijun; Liberti, Barbara; Lichard, Peter; Lichtnecker, Markus; Lie, Ki; Liebig, Wolfgang; Lifshitz, Ronen; Lilley, Joseph; Limbach, Christian; Limosani, Antonio; Limper, Maaike; Lin, Simon; Linde, Frank; Linnemann, James; Lipeles, Elliot; Lipinsky, Lukas; Lipniacka, Anna; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Chuanlei; Liu, Dong; Liu, Hao; Liu, Jianbei; Liu, Minghui; Liu, Shengli; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Lockwitz, Sarah; Loddenkoetter, Thomas; Loebinger, Fred; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Loken, James; Lombardo, Vincenzo Paolo; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Losada, Marta; Loscutoff, Peter; Sterzo, Francesco Lo; Losty, Michael; Lou, Xinchou; Lounis, Abdenour; Loureiro, Karina; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Ludwig, Andreas; Ludwig, Dorthe; Ludwig, Inga; Ludwig, Jens; Luehring, Frederick; Luijckx, Guy; Lumb, Debra; Luminari, Lamberto; Lund, Esben; Lund-Jensen, Bengt; Lundberg, Bjorn; Lundberg, Johan; Lundquist, Johan; Lungwitz, Matthias; Lupi, Anna; Lutz, Gerhard; Lynn, David; Lys, Jeremy; Lytken, Else; Ma, Hong; Ma, Lian Liang; Macana Goia, Jorge Andres; Maccarrone, Giovanni; Macchiolo, Anna; Macek, Bostjan; Machado Miguens, Joana; Mackeprang, Rasmus; Madaras, Ronald; Mader, Wolfgang; Maenner, Reinhard; Maeno, Tadashi; Mattig, Peter; Mattig, Stefan; Magalhaes Martins, Paulo Jorge; Magnoni, Luca; Magradze, Erekle; Mahalalel, Yair; Mahboubi, Kambiz; Mahout, Gilles; Maiani, Camilla; Maidantchik, Carmen; Maio, Amelia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malecki, Pawel; Malecki, Piotr; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mameghani, Raphael; Mamuzic, Judita; Manabe, Atsushi; Mandelli, Luciano; Mandic, Igor; Mandrysch, Rocco; Maneira, Jose; Mangeard, Pierre-Simon; Manjavidze, Ioseb; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Manz, Andreas; Mapelli, Alessandro; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchese, Fabrizio; Marchiori, Giovanni; Marcisovsky, Michal; Marin, Alexandru; Marino, Christopher; Marroquim, Fernando; Marshall, Robin; Marshall, Zach; Martens, Kalen; Marti-Garcia, Salvador; Martin, Andrew; Martin, Brian; Martin, Brian Thomas; Martin, Franck Francois; Martin, Jean-Pierre; Martin, Philippe; Martin, Tim; Martin Dit Latour, Bertrand; Martin--Haugh, Stewart; Martinez, Mario; Martinez Outschoorn, Verena; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massaro, Graziano; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mathes, Markus; Matricon, Pierre; Matsumoto, Hiroshi; Matsunaga, Hiroyuki; Matsushita, Takashi; Mattravers, Carly; Maugain, Jean-Marie; Maxfield, Stephen; Maximov, Dmitriy; May, Edward; Mayne, Anna; Mazini, Rachid; Mazur, Michael; Mazzanti, Marcello; Mazzoni, Enrico; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; McGlone, Helen; Mchedlidze, Gvantsa; McLaren, Robert Andrew; Mclaughlan, Tom; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Mechtel, Markus; Medinnis, Mike; Meera-Lebbai, Razzak; Meguro, Tatsuma; Mehdiyev, Rashid; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meinhardt, Jens; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Mendoza Navas, Luis; Meng, Zhaoxia; Mengarelli, Alberto; Menke, Sven; Menot, Claude; Meoni, Evelin; Mercurio, Kevin Michael; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meuser, Stefan; Meyer, Carsten; Meyer, Jean-Pierre; Meyer, Jochen; Meyer, Joerg; Meyer, Thomas Christian; Meyer, W.Thomas; Miao, Jiayuan; Michal, Sebastien; Micu, Liliana; Middleton, Robin; Miele, Paola; Migas, Sylwia; Mijovic, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuz, Marko; Miller, David; Miller, Robert; Mills, Bill; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Minano, Mercedes; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Miralles Verge, Lluis; Misiejuk, Andrzej; Mitrevski, Jovan; Mitrofanov, Gennady; Mitsou, Vasiliki A.; Mitsui, Shingo; Miyagawa, Paul; Miyazaki, Kazuki; Mjornmark, Jan-Ulf; Moa, Torbjoern; Mockett, Paul; Moed, Shulamit; Moeller, Victoria; Monig, Klaus; Moser, Nicolas; Mohapatra, Soumya; Mohr, Wolfgang; Mohrdieck-Mock, Susanne; Moisseev, Artemy; Moles-Valls, Regina; Molina-Perez, Jorge; Monk, James; Monnier, Emmanuel; Montesano, Simone; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moorhead, Gareth; Mora Herrera, Clemencia; Moraes, Arthur; Morange, Nicolas; Morel, Julien; Morello, Gianfranco; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morii, Masahiro; Morin, Jerome; Morita, Youhei; Morley, Anthony Keith; Mornacchi, Giuseppe; Morozov, Sergey; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Mudrinic, Mihajlo; Mueller, Felix; Mueller, James; Mueller, Klemens; Muller, Thomas; Muenstermann, Daniel; Muir, Alex; Munwes, Yonathan; Murray, Bill; Mussche, Ido; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nadal, Jordi; Nagai, Koichi; Nagano, Kunihiro; Nagasaka, Yasushi; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakano, Itsuo; Nanava, Gizo; Napier, Austin; Nash, Michael; Nation, Nigel; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Neal, Homer; Nebot, Eduardo; Nechaeva, Polina; Negri, Andrea; Negri, Guido; Nektarijevic, Snezana; Nelson, Silke; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Nesterov, Stanislav; Neubauer, Mark; Neusiedl, Andrea; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Hong, Van Nguyen Thi; Nickerson, Richard; Nicolaidou, Rosy; Nicolas, Ludovic; Nicquevert, Bertrand; Niedercorn, Francois; Nielsen, Jason; Niinikoski, Tapio; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolaev, Kirill; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsen, Henrik; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nishiyama, Tomonori; Nisius, Richard; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Nordberg, Markus; Nordkvist, Bjoern; Norton, Peter; Novakova, Jana; Nozaki, Mitsuaki; Nozicka, Miroslav; Nozka, Libor; Nugent, Ian Michael; Nuncio-Quiroz, Adriana-Elizabeth; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nyman, Tommi; O'Brien, Brendan Joseph; O'Neale, Steve; O'Neil, Dugan; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Ocariz, Jose; Ochi, Atsuhiko; Oda, Susumu; Odaka, Shigeru; Odier, Jerome; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohshima, Takayoshi; 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Pravahan, Rishiraj; Prell, Soeren; Pretzl, Klaus Peter; Pribyl, Lukas; Price, Darren; Price, Lawrence; Price, Michael John; Prichard, Paul; Prieur, Damien; Primavera, Margherita; Prokofiev, Kirill; Prokoshin, Fedor; Protopopescu, Serban; Proudfoot, James; Prudent, Xavier; Przysiezniak, Helenka; Psoroulas, Serena; Ptacek, Elizabeth; Pueschel, Elisa; Purdham, John; Purohit, Milind; Puzo, Patrick; Pylypchenko, Yuriy; Qian, Jianming; Qian, Zuxuan; Qin, Zhonghua; Quadt, Arnulf; Quarrie, David; Quayle, William; Quinonez, Fernando; Raas, Marcel; Radescu, Voica; Radics, Balint; Rador, Tonguc; Ragusa, Francesco; Rahal, Ghita; Rahimi, Amir; Rahm, David; Rajagopalan, Srinivasan; Rammensee, Michael; Rammes, Marcus; Ramstedt, Magnus; Randle-Conde, Aidan Sean; Randrianarivony, Koloina; Ratoff, Peter; Rauscher, Felix; Rauter, Emanuel; Raymond, Michel; Read, Alexander Lincoln; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Reichold, Armin; Reinherz-Aronis, Erez; 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Sampsonidis, Dimitrios; Samset, Bjorn Hallvard; Sanchez, Arturo; Sandaker, Heidi; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sandvoss, Stephan; Sankey, Dave; Sansoni, Andrea; Santamarina Rios, Cibran; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Saraiva, Joao; Sarangi, Tapas; Sarkisyan-Grinbaum, Edward; Sarri, Francesca; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Takashi; Sasao, Noboru; Satsounkevitch, Igor; Sauvage, Gilles; Sauvan, Emmanuel; Sauvan, Jean-Baptiste; Savard, Pierre; Savinov, Vladimir; Savu, Dan Octavian; Savva, Panagiota; Sawyer, Lee; Saxon, David; Says, Louis-Pierre; Sbarra, Carla; Sbrizzi, Antonio; Scallon, Olivia; Scannicchio, Diana; Schaarschmidt, Jana; Schacht, Peter; Schafer, Uli; Schaepe, Steffen; Schaetzel, Sebastian; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R. Dean; Schamov, Andrey; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schioppa, Marco; Schlenker, Stefan; Schlereth, James; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Sebastian; Schmitz, Martin; Schoning, Andre; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schram, Malachi; Schroeder, Christian; Schroer, Nicolai; Schuh, Silvia; Schuler, Georges; Schultes, Joachim; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Jan; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwanenberger, Christian; Schwartzman, Ariel; Schwemling, Philippe; Schwienhorst, Reinhard; Schwierz, Rainer; Schwindling, Jerome; Schwindt, Thomas; Scott, Bill; Searcy, Jacob; Sedykh, Evgeny; Segura, Ester; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, Jose; Sekhniaidze, Givi; Seliverstov, Dmitry; Sellden, Bjoern; Sellers, Graham; Seman, Michal; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Seuster, Rolf; Severini, Horst; Sevior, Martin; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shank, James; Shao, Qi Tao; Shapiro, Marjorie; Shatalov, Pavel; Shaver, Leif; Shaw, Kate; Sherman, Daniel; Sherwood, Peter; Shibata, Akira; Shichi, Hideharu; Shimizu, Shima; Shimojima, Makoto; Shin, Taeksu; Shmeleva, Alevtina; Shochet, Mel; Short, Daniel; Shupe, Michael; Sicho, Petr; Sidoti, Antonio; Siebel, Anca-Mirela; Siegert, Frank; Siegrist, James; Sijacki, Djordje; Silbert, Ohad; Silva, Jose; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simmons, Brinick; Simoniello, Rosa; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjolin, Jorgen; Sjursen, Therese; Skinnari, Louise Anastasia; Skovpen, Kirill; Skubic, Patrick; Skvorodnev, Nikolai; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Sloan, Terrence; Sloper, John erik; Smakhtin, Vladimir; Smirnov, Sergei; Smirnova, Lidia; Smirnova, Oxana; Smith, Ben Campbell; Smith, Douglas; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snow, Steve; Snow, Joel; Snuverink, Jochem; Snyder, Scott; Soares, Mara; Sobie, Randall; Sodomka, Jaromir; Soffer, Abner; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Solovyanov, Oleg; Sondericker, John; Soni, Nitesh; Sopko, Vit; Sopko, Bruno; Sorbi, Massimo; Sosebee, Mark; Soukharev, Andrey; Spagnolo, Stefania; Spano, Francesco; Spighi, Roberto; Spigo, Giancarlo; Spila, Federico; Spiriti, Eleuterio; Spiwoks, Ralf; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St. Denis, Richard Dante; Stahl, Thorsten; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staude, Arnold; Stavina, Pavel; Stavropoulos, Georgios; Steele, Genevieve; Steinbach, Peter; Steinberg, Peter; Stekl, Ivan; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stevenson, Kyle; Stewart, Graeme; Stillings, Jan Andre; Stockmanns, Tobias; Stockton, Mark; Stoerig, Kathrin; Stoicea, Gabriel; Stonjek, Stefan; Strachota, Pavel; Stradling, Alden; Straessner, Arno; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strang, Michael; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Strohmer, Raimund; Strom, David; Strong, John; Stroynowski, Ryszard; Strube, Jan; Stugu, Bjarne; Stumer, Iuliu; Stupak, John; Sturm, Philipp; Soh, Dart-yin; Su, Dong; Subramania, Halasya Siva; Succurro, Antonella; Sugaya, Yorihito; Sugimoto, Takuya; Suhr, Chad; Suita, Koichi; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Sushkov, Serge; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Suzuki, Yuta; Svatos, Michal; Sviridov, Yuri; Swedish, Stephen; Sykora, Ivan; Sykora, Tomas; Szeless, Balazs; Sanchez, Javier; Ta, Duc; Tackmann, Kerstin; Taffard, Anyes; Tafirout, Reda; Taga, Adrian; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Talby, Mossadek; Talyshev, Alexey; Tamsett, Matthew; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanaka, Yoshito; Tani, Kazutoshi; Tannoury, Nancy; Tappern, Geoffrey; Tapprogge, Stefan; Tardif, Dominique; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tassi, Enrico; Tatarkhanov, Mous; Taylor, Christopher; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teinturier, Marthe; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Terada, Susumu; Terashi, Koji; Terron, Juan; Terwort, Mark; Testa, Marianna; Teuscher, Richard; Thadome, Jocelyn; Therhaag, Jan; Theveneaux-Pelzer, Timothee; Thioye, Moustapha; Thoma, Sascha; Thomas, Juergen; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomson, Evelyn; Thomson, Mark; Thun, Rudolf; Tian, Feng; Tic, Tom\\'{a}\\v{s}; Tikhomirov, Vladimir; Tikhonov, Yury; Timmermans, Charles; Tipton, Paul; Viegas, Florbela De Jes Tique Aires; Tisserant, Sylvain; Tobias, Jurgen; Toczek, Barbara; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokar, Stanislav; Tokunaga, Kaoru; Tokushuku, Katsuo; Tollefson, Kirsten; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Tong, Guoliang; Tonoyan, Arshak; Topfel, Cyril; Topilin, Nikolai; Torchiani, Ingo; Torrence, Eric; Torres, Heberth; Torro Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Traynor, Daniel; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alesandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Trinh, Thi Nguyet; Tripiana, Martin; Trischuk, William; Trivedi, Arjun; Trocme, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiakiris, Menelaos; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsung, Jieh-Wen; Tsuno, Soshi; Tsybychev, Dmitri; Tua, Alan; Tuggle, Joseph; Turala, Michal; Turecek, Daniel; Turk Cakir, Ilkay; Turlay, Emmanuel; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Tyrvainen, Harri; Tzanakos, George; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ugland, Maren; Uhlenbrock, Mathias; Uhrmacher, Michael; Ukegawa, Fumihiko; Unal, Guillaume; Underwood, David; Undrus, Alexander; Unel, Gokhan; Unno, Yoshinobu; Urbaniec, Dustin; Urkovsky, Evgeny; Urrejola, Pedro; Usai, Giulio; Uslenghi, Massimiliano; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Vahsen, Sven; Valenta, Jan; Valente, Paolo; Valentinetti, Sara; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Ferrer, Juan Antonio Valls; Van der Graaf, Harry; van der Kraaij, Erik; van der Leeuw, Robin; van der Poel, Egge; van der Ster, Daniel; Van Eijk, Bob; van Eldik, Niels; Van Gemmeren, Peter; van Kesteren, Zdenko; Van Vulpen, Ivo; Vandelli, Wainer; Vandoni, Giovanna; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Varela Rodriguez, Fernando; Vari, Riccardo; Varnes, Erich; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vassilakopoulos, Vassilios; Vazeille, Francois; Vegni, Guido; Veillet, Jean-Jacques; Vellidis, Constantine; Veloso, Filipe; Veness, Raymond; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Vichou, Irene; Vickey, Trevor; Viehhauser, Georg; Viel, Simon; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinek, Elisabeth; Vinogradov, Vladimir; Virchaux, Marc; Virzi, Joseph; Vitells, Ofer; Viti, Michele; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vlasak, Michal; Vlasov, Nikolai; Vogel, Adrian; Vokac, Petr; Volpi, Guido; Volpi, Matteo; Volpini, Giovanni; von der Schmitt, Hans; von Loeben, Joerg; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vorobiev, Alexander; Vorwerk, Volker; Vos, Marcel; Voss, Rudiger; Voss, Thorsten Tobias; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Anh, Tuan Vu; Vuillermet, Raphael; Vukotic, Ilija; Wagner, Wolfgang; Wagner, Peter; Wahlen, Helmut; Wakabayashi, Jun; Walbersloh, Jorg; Walch, Shannon; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Wang, Chiho; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Joshua C.; Wang, Rui; Wang, Song-Ming; Warburton, Andreas; Ward, Patricia; Warsinsky, Markus; Watkins, Peter; Watson, Alan; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Anthony; Waugh, Ben; Weber, Jens; Weber, Marc; Weber, Michele; Weber, Pavel; Weidberg, Anthony; Weigell, Philipp; Weingarten, Jens; Weiser, Christian; Wellenstein, Hermann; Wells, Phillippa; Wen, Mei; Wenaus, Torre; Wendler, Shanti; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Per; Werth, Michael; Wessels, Martin; Weydert, Carole; Whalen, Kathleen; Wheeler-Ellis, Sarah Jane; Whitaker, Scott; White, Andrew; White, Martin; Whitehead, Samuel Robert; Whiteson, Daniel; Whittington, Denver; Wicek, Francois; Wicke, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilhelm, Ivan; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Eric; Williams, Hugh; Willis, William; Willocq, Stephane; Wilson, John; Wilson, Michael Galante; Wilson, Alan; Wingerter-Seez, Isabelle; Winkelmann, Stefan; Winklmeier, Frank; Wittgen, Matthias; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wong, Wei-Cheng; Wooden, Gemma; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wraight, Kenneth; Wright, Catherine; Wrona, Bozydar; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wunstorf, Renate; Wynne, Benjamin; Xaplanteris, Leonidas; Xella, Stefania; Xie, Song; Xie, Yigang; Xu, Chao; Xu, Da; Xu, Guofa; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamaoka, Jared; Yamazaki, Takayuki; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Un-Ki; Yang, Yi; Yang, Yi; Yang, Zhaoyu; Yanush, Serguei; Yao, Weiming; Yao, Yushu; Yasu, Yoshiji; Ybeles Smit, Gabriel Valentijn; Ye, Jingbo; Ye, Shuwei; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Riktura; Young, Charles; Youssef, Saul; Yu, Dantong; Yu, Jaehoon; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Zaets, Vassilli; Zaidan, Remi; Zaitsev, Alexander; Zajacova, Zuzana; Zalite, Youris; Zanello, Lucia; Zarzhitsky, Pavel; Zaytsev, Alexander; Zeitnitz, Christian; Zeller, Michael; Zeman, Martin; Zemla, Andrzej; Zendler, Carolin; Zenin, Oleg; Zenis, Tibor; Zenonos, Zenonas; Zenz, Seth; Zerwas, Dirk; Zevi Della Porta, Giovanni; Zhan, Zhichao; Zhang, Dongliang; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Long; Zhao, Tianchi; Zhao, Zhengguo; Zhemchugov, Alexey; Zheng, Shuchen; Zhong, Jiahang; Zhou, Bing; Zhou, Ning; Zhou, Yue; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhuravlov, Vadym; Zieminska, Daria; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Ziolkowski, Michael; Zitoun, Robert; Zivkovic, Lidija; Zmouchko, Viatcheslav; Zobernig, Georg; Zoccoli, Antonio; Zolnierowski, Yves; Zsenei, Andras; zur Nedden, Martin; Zutshi, Vishnu; Zwalinski, Lukasz

2012-01-03

The measurement of missing transverse momentum in the ATLAS detector, described in this paper, makes use of the full event reconstruction and a calibration based on reconstructed physics objects. The performance of the missing transverse momentum reconstruction is evaluated using data collected in pp collisions at a centre-of-mass energy of 7 TeV in 2010. Minimum bias events and events with jets of hadrons are used from data samples corresponding to an integrated luminosity of about 0.3 inverse nb and 600 inverse nb, together with events containing a Z boson decaying to two leptons (electrons or muons) or a W boson decaying to a lepton (electron or muon) and a neutrino, from a data sample corresponding to an integrated luminosity of about 36 inverse pb. An estimate of the systematic uncertainty on the missing transverse momentum scale is presented.

Data storage and data access at H1

International Nuclear Information System (INIS)

Gerhards, R.; Kleinwort, C.; Kruener-Marquis, U.; Niebergall, F.

1996-01-01

The electron proton collider HERA at the DESY laboratory in Hamburg and the H1 experiment are now in successful operation for more than three years. The H1 experiment is logging data at an average rate of 500KB/s which results in a yearly raw data volume of several Terabytes. The data are reconstructed with a delay of only a few hours, also yielding several Terabytes of reconstructed data after physics oriented event classification. Physics analysis is performed on a SGI Challenge computer, equipped with about 500 GB of disk and, since a couple of months, direct access to a Storage Tek ACS 4400 silo. The disk space is mainly devoted to store the reconstructed data in very compressed format (typically 5 to 10 KB per event). This allows for very efficient and fast physics analysis. Monte Carlo data, on the other hand, are kept in the ACS silo and staged to disk on demand. (author)

R and D on a Fast LXe TPC with real-time event reconstruction

Energy Technology Data Exchange (ETDEWEB)

Dussoni, S., E-mail: simeone.dussoni@pi.infn.it [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Baldini, A. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Galli, L. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Paul Scherrer Institute PSI, CH-5232 Villigen (Switzerland); Cerri, C.; Grassi, M. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy); Papa, A. [Paul Scherrer Institute PSI, CH-5232 Villigen (Switzerland); Signorelli, G. [INFN Sezione di Pisa, Largo B. Pontecorvo 3, 56127 Pisa (Italy)

2013-12-21

The FOXFIRE project (Feasibility Of a Xenon detector with Front-end for Ionization Real-time Extraction) aims at the realization of a Liquid Xenon TPC optimized for high rate particle physics experiments, in particular in the field of rare event searches, with particles in the 10–100 MeV energy range. Liquid Xenon has several attractive properties to be exploited resulting in superior time and energy resolution, by using the scintillation light readout with suitable photo-detectors. A novel approach with a complementary TPC readout scheme can improve the space resolution to a level of a few hundred microns. We are studying both the feasibility of a light readout with higher granularity by means of Silicon PhotoMultipliers optimized for the Xenon emission spectrum as well as on an innovative micro-fabricated device capable of charge multiplication in liquid phase. The detector will be equipped with a readout electronics capable of online reconstruction of events, allowing the detector to sustain a high rate of interactions.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

Science.gov (United States)

McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

2017-06-01

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

Muon reconstruction efficiency, momentum scale and resolution in pp collisions at 8TeV with ATLAS

CERN Document Server

Dimitrievska, A; The ATLAS collaboration; Sforza, F

2014-01-01

The ATLAS experiment identifies and reconstructs muons with two high precision tracking systems, the inner detector and the muon spectrometer, which provide independent measurements of the muon momentum. This poster summarizes the performance of the combined muon reconstruction in terms of reconstruction efficiency, momentum scale and resolution. Data-driven techniques are used to derive corrections to be applied to simulation in order to reproduce the reconstruction efficiency, momentum scale and resolution as observed in experimental data, and to asses systematic uncertainties on these quantities. The analysed dataset corresponds to an integrated luminosity of 20.4 fb−1 from pp collisions at center of mass enegy of 8 TeV recorded in 2012.

Extreme flood event reconstruction spanning the last century in the El Bibane Lagoon (southeastern Tunisia: a multi-proxy approach

Directory of Open Access Journals (Sweden)

A. Affouri

2017-06-01

Full Text Available Climate models project that rising atmospheric carbon dioxide concentrations will increase the frequency and the severity of some extreme weather events. The flood events represent a major risk for populations and infrastructures settled on coastal lowlands. Recent studies of lagoon sediments have enhanced our knowledge on extreme hydrological events such as palaeo-storms and on their relation with climate change over the last millennium. However, few studies have been undertaken to reconstruct past flood events from lagoon sediments. Here, the past flood activity was investigated using a multi-proxy approach combining sedimentological and geochemical analysis of surfaces sediments from a southeastern Tunisian catchment in order to trace the origin of sediment deposits in the El Bibane Lagoon. Three sediment sources were identified: marine, fluvial and aeolian. When applying this multi-proxy approach on core BL12-10, recovered from the El Bibane Lagoon, we can see that finer material, a high content of the clay and silt, and a high content of the elemental ratios (Fe ∕ Ca and Ti ∕ Ca characterise the sedimentological signature of the palaeo-flood levels identified in the lagoonal sequence. For the last century, which is the period covered by the BL12-10 short core, three palaeo-flood events were identified. The age of these flood events have been determined by 210Pb and 137Cs chronology and give ages of AD 1995 ± 6, 1970 ± 9 and 1945 ± 9. These results show a good temporal correlation with historical flood events recorded in southern Tunisia in the last century (AD 1932, 1969, 1979 and 1995. Our finding suggests that reconstruction of the history of the hydrological extreme events during the upper Holocene is possible in this location through the use of the sedimentary archives.

Integration of knowledge to support automatic object reconstruction from images and 3D data

International Nuclear Information System (INIS)

Boochs, F.; Truong, H; Marbs, A.; Karmacharya, A.; Cruz, C.; Habed, A.; Nicolle, C.; Voisin, Y.

2011-01-01

Object reconstruction is a important task in many fields of application as it allows to generate digital representations of our physical world used as base for analysis, planning, construction, visualization or other aims. A reconstruction itself normally is based on reliable data (images, 3D point clouds for example) expressing the object in his complete extension. This data then has to be compiled and analyzed in order to extract all necessary geometrical elements, which represent the object and form a digital copy of it. Traditional strategies are largely based on manual interaction and interpretation, because with increasing complexity of objects human understanding is inevitable to achieve acceptable and reliable results. But human interaction is time consuming and expensive, why many research has already been invested to integrate algorithmic support, what allows to speed up the process and reduce manual work load. Presently most such algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. By means of these models, which normally will represent geometrical (flatness, roughness, for example) or physical features (color, texture), the data is classified and analyzed. This is succesful for objects with a limited complexity, but gets to its limits with increasing complexity of objects. Then purely numerical strategies are not able to sufficiently model the reality. Therefore, the intention of our approach is to take human cogni-tive strategy as an example, and to simulate extraction processes based on available knowledge for the objects of interest. Such processes will introduce a semantic structure for the objects and guide the algorithms used to detect and recognize objects, which will yield a higher effectiveness. Hence, our research proposes an approach using knowledge to guide the algorithms in 3D point cloud and image processing.

Reconstruction and numerical modelling of a flash flood event: Atrani 2010

Science.gov (United States)

Ciervo, F.; Papa, M. N.; Medina, V.; Bateman, A.

2012-04-01

The work intends to reproduce the flash-flood event that occurred in Atrani (Amalfi Coast - Southern Italy) on the 9 September 2010. In the days leading up to the event, intense low pressure system affected the North Europe attracting hot humid air masses from the Mediterranean areas and pushing them to the southern regions of Italy. These conditions contributed to the development of strong convective storm systems, Mesoscale Convective Systems (MCS) type. The development of intense convective rain cells, over an extremely confined areas, leaded to a cumulative daily rainfall of 129.2 mm; the maximum precipitation in 1hr was 19.4mm. The Dragone river is artificially forced to flow underneath the urban estate of Atrani through a culvert until it finally flows out into the sea. In correspondence of the culvert inlet a minor fraction of the water discharge (5.9m^3/s), skimming over the channel cover, flowed on the street and invaded the village. The channelized flow generated overpressure involving the breaking of the cover of culvert slab and caused a new discharge inlet (20 m^3/s) on the street modifying the downstream flood dynamics. Information acquired, soon after the event, through the local people interviews and the field measurements significantly contributed to the rainfall event reconstruction and to the characterization of the induced effects. In absence of hydrometric data, the support of the amateur videos was of crucial importance for the hydraulic model development and calibration. A geomorphology based rainfall-runoff model, WFIUH type (Instantaneous Unit Hydrograph Width Function), is implemented to extract the hydrograph of the hydrological event. All analysis are performed with GIS support basing on a Digital Terrain System (DTM) 5x5m. Two parameters have been used to calibrate the model: the average watershed velocity (Vmean = 0.08m/s) and hydrodynamic diffusivity (D=10E^-6 m^2/s). The model is calibrated basing on the peak discharge assessed value

Accident or homicide--virtual crime scene reconstruction using 3D methods.

Science.gov (United States)

Buck, Ursula; Naether, Silvio; Räss, Beat; Jackowski, Christian; Thali, Michael J

2013-02-10

The analysis and reconstruction of forensically relevant events, such as traffic accidents, criminal assaults and homicides are based on external and internal morphological findings of the injured or deceased person. For this approach high-tech methods are gaining increasing importance in forensic investigations. The non-contact optical 3D digitising system GOM ATOS is applied as a suitable tool for whole body surface and wound documentation and analysis in order to identify injury-causing instruments and to reconstruct the course of event. In addition to the surface documentation, cross-sectional imaging methods deliver medical internal findings of the body. These 3D data are fused into a whole body model of the deceased. Additional to the findings of the bodies, the injury inflicting instruments and incident scene is documented in 3D. The 3D data of the incident scene, generated by 3D laser scanning and photogrammetry, is also included into the reconstruction. Two cases illustrate the methods. In the fist case a man was shot in his bedroom and the main question was, if the offender shot the man intentionally or accidentally, as he declared. In the second case a woman was hit by a car, driving backwards into a garage. It was unclear if the driver drove backwards once or twice, which would indicate that he willingly injured and killed the woman. With this work, we demonstrate how 3D documentation, data merging and animation enable to answer reconstructive questions regarding the dynamic development of patterned injuries, and how this leads to a real data based reconstruction of the course of event. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Big Data Tools as Applied to ATLAS Event Data

Science.gov (United States)

Vukotic, I.; Gardner, R. W.; Bryant, L. A.

2017-10-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Logfiles, database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and associated analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data. Such modes would simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning environments and tools like Spark, Jupyter, R, SciPy, Caffe, TensorFlow, etc. Machine learning challenges such as the Higgs Boson Machine Learning Challenge, the Tracking challenge, Event viewers (VP1, ATLANTIS, ATLASrift), and still to be developed educational and outreach tools would be able to access the data through a simple REST API. In this preliminary investigation we focus on derived xAOD data sets. These are much smaller than the primary xAODs having containers, variables, and events of interest to a particular analysis. Being encouraged with the performance of Elasticsearch for the ADC analytics platform, we developed an algorithm for indexing derived xAOD event data. We have made an appropriate document mapping and have imported a full set of standard model W/Z datasets. We compare the disk space efficiency of this approach to that of standard ROOT files, the performance in simple cut flow type of data analysis, and will present preliminary results on its scaling

Analysis and reconstructed modelling of the debris flow event of the 21st of July 2012 of St. Lorenzen (Styria, Austira)

Science.gov (United States)

Janu, Stefan; Mehlhorn, Susanne; Moser, Markus

2013-04-01

Torrent and Avalanche Control, a great number of protection measures have in the past been realized in the Lorenz torrent, which with certainty contributed significantly to an even greater amount of damage in the St. Lorenz residential area having been prevented. Attempts at reconstructing the event processes as well simulating the debris flow in 2D were undertaken in the course of the event documentation and analysis. The thus obtained discharge heights, flow velocities and impact pressure values corresponded with the well documented event. The two dimensional simulations were carried out with the program FLO-2D, which is capable of simulating debris flows. The rheological parameters of the debris flow material were determined with the aid of a viscometer and a debris rotation drum. The debris flow hydrograph, bedload and bedload ratio were reconstructed using data from the event documentation, such as difference models, geological mapping, wetted perimeters, witness's statements, etc. The aim of the very detailed event documentation and analysis was to reconstruct the extreme process sequence along with the damaging effects that they had in the build-up area of St. Lorenzen. There was a large media interest in this event. The results should therefore serve to answer the multitude of questions about this event that lie in the public as well political interests. Additional and substantial protection measures were also planned for the village of St. Lorenzen on the basis of these event analysis results. These are comprised of two debris flow barriers in the lower gorge streches with a capacity of 15,000 m³ each as well as a bedload retention basin directly above, with a capacity of 30,000 m³. Construction of these technical protection measures has already begun. Authoŕs adresses: DI Stefan Janu Fachbereich Wildbachprozesse Austrian Service for Torrent and Avalanche Control, GBL Ennstal und Salzatal Schönaustraße 50 8940 Liezen Dipl.Geogr. Susanne Mehlhorn Fachbereich

CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system

Science.gov (United States)

Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao

2016-09-01

Hydrological forecasting is complicated by flow regime alterations in a coupled socio-hydrologic system, encountering increasingly non-stationary, nonlinear and irregular changes, which make decision support difficult for future water resources management. Currently, many hybrid data-driven models, based on the decomposition-prediction-reconstruction principle, have been developed to improve the ability to make predictions of annual streamflow. However, there exist many problems that require further investigation, the chief among which is the direction of trend components decomposed from annual streamflow series and is always difficult to ascertain. In this paper, a hybrid data-driven model was proposed to capture this issue, which combined empirical mode decomposition (EMD), radial basis function neural networks (RBFNN), and external forces (EF) variable, also called the CEREF model. The hybrid model employed EMD for decomposition and RBFNN for intrinsic mode function (IMF) forecasting, and determined future trend component directions by regression with EF as basin water demand representing the social component in the socio-hydrologic system. The Wuding River basin was considered for the case study, and two standard statistical measures, root mean squared error (RMSE) and mean absolute error (MAE), were used to evaluate the performance of CEREF model and compare with other models: the autoregressive (AR), RBFNN and EMD-RBFNN. Results indicated that the CEREF model had lower RMSE and MAE statistics, 42.8% and 7.6%, respectively, than did other models, and provided a superior alternative for forecasting annual runoff in the Wuding River basin. Moreover, the CEREF model can enlarge the effective intervals of streamflow forecasting compared to the EMD-RBFNN model by introducing the water demand planned by the government department to improve long-term prediction accuracy. In addition, we considered the high-frequency component, a frequent subject of concern in EMD

Amplitude-based data selection for optimal retrospective reconstruction in micro-SPECT

Science.gov (United States)

Breuilly, M.; Malandain, G.; Guglielmi, J.; Marsault, R.; Pourcher, T.; Franken, P. R.; Darcourt, J.

2013-04-01

Respiratory motion can blur the tomographic reconstruction of positron emission tomography or single-photon emission computed tomography (SPECT) images, which subsequently impair quantitative measurements, e.g. in the upper abdomen area. Respiratory signal phase-based gated reconstruction addresses this problem, but deteriorates the signal-to-noise ratio (SNR) and other intensity-based quality measures. This paper proposes a 3D reconstruction method dedicated to micro-SPECT imaging of mice. From a 4D acquisition, the phase images exhibiting motion are identified and the associated list-mode data are discarded, which enables the reconstruction of a 3D image without respiratory artefacts. The proposed method allows a motion-free reconstruction exhibiting both satisfactory count statistics and accuracy of measures. With respect to standard 3D reconstruction (non-gated 3D reconstruction) without breathing motion correction, an increase of 14.6% of the mean standardized uptake value has been observed, while, with respect to a gated 4D reconstruction, up to 60% less noise and an increase of up to 124% of the SNR have been demonstrated.

A Model-Driven Methodology for Big Data Analytics-as-a-Service

OpenAIRE

Damiani, Ernesto; Ardagna, Claudio Agostino; Ceravolo, Paolo; Bellandi, Valerio; Bezzi, Michele; Hebert, Cedric

2017-01-01

The Big Data revolution has promised to build a data-driven ecosystem where better decisions are supported by enhanced analytics and data management. However, critical issues still need to be solved in the road that leads to commodization of Big Data Analytics, such as the management of Big Data complexity and the protection of data security and privacy. In this paper, we focus on the first issue and propose a methodology based on Model Driven Engineering (MDE) that aims to substantially lowe...

Comparing and improving reconstruction methods for proxies based on compositional data

Science.gov (United States)

Nolan, C.; Tipton, J.; Booth, R.; Jackson, S. T.; Hooten, M.

2017-12-01

Many types of studies in paleoclimatology and paleoecology involve compositional data. Often, these studies aim to use compositional data to reconstruct an environmental variable of interest; the reconstruction is usually done via the development of a transfer function. Transfer functions have been developed using many different methods. Existing methods tend to relate the compositional data and the reconstruction target in very simple ways. Additionally, the results from different methods are rarely compared. Here we seek to address these two issues. First, we introduce a new hierarchical Bayesian multivariate gaussian process model; this model allows for the relationship between each species in the compositional dataset and the environmental variable to be modeled in a way that captures the underlying complexities. Then, we compare this new method to machine learning techniques and commonly used existing methods. The comparisons are based on reconstructing the water table depth history of Caribou Bog (an ombrotrophic Sphagnum peat bog in Old Town, Maine, USA) from a new 7500 year long record of testate amoebae assemblages. The resulting reconstructions from different methods diverge in both their resulting means and uncertainties. In particular, uncertainty tends to be drastically underestimated by some common methods. These results will help to improve inference of water table depth from testate amoebae. Furthermore, this approach can be applied to test and improve inferences of past environmental conditions from a broad array of paleo-proxies based on compositional data

Reconstruction of driving forces through recurrence plots

International Nuclear Information System (INIS)

Tanio, Masaaki; Hirata, Yoshito; Suzuki, Hideyuki

2009-01-01

We consider the problem of reconstructing one-dimensional driving forces only from the observations of driven systems. We extend the approach presented in a seminal paper [M.C. Casdagli, Physica D 108 (1997) 12] and propose a method that is robust and has wider applicability. By reinterpreting the work of Thiel et al. [M. Thiel, M.C. Romano, J. Kurths, Phys. Lett. A 330 (2004) 343], we formulate the reconstruction problem as a combinatorial optimization problem and relax conditions by assuming that a driving force is continuous. The method is demonstrated by using a tent map driven by an external force.

General Purpose Data-Driven Monitoring for Space Operations

Science.gov (United States)

Iverson, David L.; Martin, Rodney A.; Schwabacher, Mark A.; Spirkovska, Liljana; Taylor, William McCaa; Castle, Joseph P.; Mackey, Ryan M.

2009-01-01

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault

Bias in iterative reconstruction of low-statistics PET data: benefits of a resolution model

Energy Technology Data Exchange (ETDEWEB)

Walker, M D; Asselin, M-C; Julyan, P J; Feldmann, M; Matthews, J C [School of Cancer and Enabling Sciences, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Talbot, P S [Mental Health and Neurodegeneration Research Group, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Jones, T, E-mail: matthew.walker@manchester.ac.uk [Academic Department of Radiation Oncology, Christie Hospital, University of Manchester, Manchester M20 4BX (United Kingdom)

2011-02-21

Iterative image reconstruction methods such as ordered-subset expectation maximization (OSEM) are widely used in PET. Reconstructions via OSEM are however reported to be biased for low-count data. We investigated this and considered the impact for dynamic PET. Patient listmode data were acquired in [{sup 11}C]DASB and [{sup 15}O]H{sub 2}O scans on the HRRT brain PET scanner. These data were subsampled to create many independent, low-count replicates. The data were reconstructed and the images from low-count data were compared to the high-count originals (from the same reconstruction method). This comparison enabled low-statistics bias to be calculated for the given reconstruction, as a function of the noise-equivalent counts (NEC). Two iterative reconstruction methods were tested, one with and one without an image-based resolution model (RM). Significant bias was observed when reconstructing data of low statistical quality, for both subsampled human and simulated data. For human data, this bias was substantially reduced by including a RM. For [{sup 11}C]DASB the low-statistics bias in the caudate head at 1.7 M NEC (approx. 30 s) was -5.5% and -13% with and without RM, respectively. We predicted biases in the binding potential of -4% and -10%. For quantification of cerebral blood flow for the whole-brain grey- or white-matter, using [{sup 15}O]H{sub 2}O and the PET autoradiographic method, a low-statistics bias of <2.5% and <4% was predicted for reconstruction with and without the RM. The use of a resolution model reduces low-statistics bias and can hence be beneficial for quantitative dynamic PET.

iLAP: a workflow-driven software for experimental protocol development, data acquisition and analysis

Directory of Open Access Journals (Sweden)

McNally James

2009-01-01

Full Text Available Abstract Background In recent years, the genome biology community has expended considerable effort to confront the challenges of managing heterogeneous data in a structured and organized way and developed laboratory information management systems (LIMS for both raw and processed data. On the other hand, electronic notebooks were developed to record and manage scientific data, and facilitate data-sharing. Software which enables both, management of large datasets and digital recording of laboratory procedures would serve a real need in laboratories using medium and high-throughput techniques. Results We have developed iLAP (Laboratory data management, Analysis, and Protocol development, a workflow-driven information management system specifically designed to create and manage experimental protocols, and to analyze and share laboratory data. The system combines experimental protocol development, wizard-based data acquisition, and high-throughput data analysis into a single, integrated system. We demonstrate the power and the flexibility of the platform using a microscopy case study based on a combinatorial multiple fluorescence in situ hybridization (m-FISH protocol and 3D-image reconstruction. iLAP is freely available under the open source license AGPL from http://genome.tugraz.at/iLAP/. Conclusion iLAP is a flexible and versatile information management system, which has the potential to close the gap between electronic notebooks and LIMS and can therefore be of great value for a broad scientific community.

Enhancing temporal correlations in EOF expansions for the reconstruction of missing data using DINEOF

Directory of Open Access Journals (Sweden)

A. Alvera-Azcárate

2009-10-01

Full Text Available DINEOF (Data Interpolating Empirical Orthogonal Functions is an EOF-based technique for the reconstruction of missing data in geophysical fields, such as those produced by clouds in sea surface temperature satellite images. A technique to reduce spurious time variability in DINEOF reconstructions is presented. The reconstruction of these images within a long time series using DINEOF can lead to large discontinuities in the reconstruction. Filtering the temporal covariance matrix allows to reduce this spurious variability and therefore more realistic reconstructions are obtained. The approach is tested in a three years sea surface temperature data set over the Black Sea. The effect of the filter in the temporal EOFs is presented, as well as some examples of the improvement achieved with the filtering in the SST reconstruction, both compared to the DINEOF approach without filtering.

Visual pattern discovery in timed event data

Science.gov (United States)

Schaefer, Matthias; Wanner, Franz; Mansmann, Florian; Scheible, Christian; Stennett, Verity; Hasselrot, Anders T.; Keim, Daniel A.

2011-01-01

Business processes have tremendously changed the way large companies conduct their business: The integration of information systems into the workflows of their employees ensures a high service level and thus high customer satisfaction. One core aspect of business process engineering are events that steer the workflows and trigger internal processes. Strict requirements on interval-scaled temporal patterns, which are common in time series, are thereby released through the ordinal character of such events. It is this additional degree of freedom that opens unexplored possibilities for visualizing event data. In this paper, we present a flexible and novel system to find significant events, event clusters and event patterns. Each event is represented as a small rectangle, which is colored according to categorical, ordinal or intervalscaled metadata. Depending on the analysis task, different layout functions are used to highlight either the ordinal character of the data or temporal correlations. The system has built-in features for ordering customers or event groups according to the similarity of their event sequences, temporal gap alignment and stacking of co-occurring events. Two characteristically different case studies dealing with business process events and news articles demonstrate the capabilities of our system to explore event data.

Sea level reconstruction from satellite altimetry and tide gauge data

DEFF Research Database (Denmark)

Svendsen, Peter Limkilde; Andersen, Ole Baltazar; Nielsen, Allan Aasbjerg

2012-01-01

Ocean satellite altimetry has provided global sets of sea level data for the last two decades, allowing determination of spatial patterns in global sea level. For reconstructions going back further than this period, tide gauge data can be used as a proxy. We examine different methods of combining...... for better sensitivity analysis with respect to spatial distribution, and tide gauge data are available around the Arctic Ocean, which may be important for a later high-latitude reconstruction....... satellite altimetry and tide gauge data using optimal weighting of tide gauge data, linear regression and EOFs, including automatic quality checks of the tide gauge time series. We attempt to augment the model using various proxies such as climate indices like the NAO and PDO, and investigate alternative...

Integration of expression data in genome-scale metabolic network reconstructions

Directory of Open Access Journals (Sweden)

Anna S. Blazier

2012-08-01

Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

Data-Driven H∞ Control for Nonlinear Distributed Parameter Systems.

Science.gov (United States)

Luo, Biao; Huang, Tingwen; Wu, Huai-Ning; Yang, Xiong

2015-11-01

The data-driven H∞ control problem of nonlinear distributed parameter systems is considered in this paper. An off-policy learning method is developed to learn the H∞ control policy from real system data rather than the mathematical model. First, Karhunen-Loève decomposition is used to compute the empirical eigenfunctions, which are then employed to derive a reduced-order model (ROM) of slow subsystem based on the singular perturbation theory. The H∞ control problem is reformulated based on the ROM, which can be transformed to solve the Hamilton-Jacobi-Isaacs (HJI) equation, theoretically. To learn the solution of the HJI equation from real system data, a data-driven off-policy learning approach is proposed based on the simultaneous policy update algorithm and its convergence is proved. For implementation purpose, a neural network (NN)- based action-critic structure is developed, where a critic NN and two action NNs are employed to approximate the value function, control, and disturbance policies, respectively. Subsequently, a least-square NN weight-tuning rule is derived with the method of weighted residuals. Finally, the developed data-driven off-policy learning approach is applied to a nonlinear diffusion-reaction process, and the obtained results demonstrate its effectiveness.

Scalable data-driven short-term traffic prediction

NARCIS (Netherlands)

Friso, K.; Wismans, L. J.J.; Tijink, M. B.

2017-01-01

Short-term traffic prediction has a lot of potential for traffic management. However, most research has traditionally focused on either traffic models-which do not scale very well to large networks, computationally-or on data-driven methods for freeways, leaving out urban arterials completely. Urban

Application of Al techniques to a voice actuated computer system for reconstructing and displaying magnetic resonance imaging data

International Nuclear Information System (INIS)

Sherley, P.L.; Pujol, A. Jr.; Meadow, J.S.

1990-01-01

This paper reports that to provide a means of rendering complex computer architectures, languages, and input/output modalities transparent to experienced and inexperienced users, research is being conducted to develop a voice driven/voice response computer graphics imaging system. The system will be used for reconstructing and displaying computed tomography and magnetic resonance imaging scan data. In conjunction with this study, an artificial intelligence (AI) control strategy was developed to interface the voice components and support software to the computer graphics functions implemented on the Sun Microsystems 4/280 color graphics workstation. Based on generated text and converted renditions of verbal utterances by the user, the AI control strategy determines the user's intent and develops and validates a plan. The program type and parameters within the plan are used as input to the graphics system for reconstructing and displaying medical image data corresponding to that perceived intent. If the plan is not valid, the control strategy queries the user for additional informaiton. The control strategy operates in a conversation mode and vocally provides system status reports. A detailed examination of the various AI techniques is presented with major emphasis being placed on their specific roles within the total control strategy structure

Measurement of Reconstructed Charged Particle Multiplicities of Neutrino Interactions in MicroBooNE

Energy Technology Data Exchange (ETDEWEB)

Rafique, Aleena [Kansas State Univ., Manhattan, KS (United States)

2017-09-25

Here, we compare the observed charged particle multiplicity distributions in the MicroBooNE liquid argon time projection chamber from neutrino interactions in a restricted final state phase space to predictions of this distribution from several GENIE models. The measurement uses a data sample consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2015-2016 with the Fermilab Booster Neutrino Beam (BNB), which has an average neutrino energy of 800 MeV, using an exposure corresponding to 5e19 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to determine the contribution to each multiplicity bin from neutrino interactions and cosmic-induced backgrounds. The restricted phase space employed makes the measurement most sensitive to the higher-energy charged particles expected from primary neutrino-argon collisions and less sensitive to lower energy protons expected to be produced in final state interactions of collision products with the target argon nucleus.

Direct Parametric Reconstruction With Joint Motion Estimation/Correction for Dynamic Brain PET Data.

Science.gov (United States)

Jiao, Jieqing; Bousse, Alexandre; Thielemans, Kris; Burgos, Ninon; Weston, Philip S J; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Markiewicz, Pawel; Ourselin, Sebastien

2017-01-01

Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [ 11 C]raclopride data using the Zubal brain phantom and real clinical [ 18 F]florbetapir data of a patient with Alzheimer's disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion.

Data-driven haemodynamic response function extraction using Fourier-wavelet regularised deconvolution

Directory of Open Access Journals (Sweden)

Roerdink Jos BTM

2008-04-01

Full Text Available Abstract Background We present a simple, data-driven method to extract haemodynamic response functions (HRF from functional magnetic resonance imaging (fMRI time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD technique. HRF data are required for many fMRI applications, such as defining region-specific HRFs, effciently representing a general HRF, or comparing subject-specific HRFs. Results ForWaRD is applied to fMRI time signals, after removing low-frequency trends by a wavelet-based method, and the output of ForWaRD is a time series of volumes, containing the HRF in each voxel. Compared to more complex methods, this extraction algorithm requires few assumptions (separability of signal and noise in the frequency and wavelet domains and the general linear model and it is fast (HRF extraction from a single fMRI data set takes about the same time as spatial resampling. The extraction method is tested on simulated event-related activation signals, contaminated with noise from a time series of real MRI images. An application for HRF data is demonstrated in a simple event-related experiment: data are extracted from a region with significant effects of interest in a first time series. A continuous-time HRF is obtained by fitting a nonlinear function to the discrete HRF coeffcients, and is then used to analyse a later time series. Conclusion With the parameters used in this paper, the extraction method presented here is very robust to changes in signal properties. Comparison of analyses with fitted HRFs and with a canonical HRF shows that a subject-specific, regional HRF significantly improves detection power. Sensitivity and specificity increase not only in the region from which the HRFs are extracted, but also in other regions of interest.

Data-Driven Planning: Using Assessment in Strategic Planning

Science.gov (United States)

Bresciani, Marilee J.

2010-01-01

Data-driven planning or evidence-based decision making represents nothing new in its concept. For years, business leaders have claimed they have implemented planning informed by data that have been strategically and systematically gathered. Within higher education and student affairs, there may be less evidence of the actual practice of…

The CBM first-level event selector

Energy Technology Data Exchange (ETDEWEB)

Cuveland, Jan de; Lindenstruth, Volker [Frankfurt Institute for Advanced Studies, Goethe University, Frankfurt (Germany)

2015-07-01

The CBM experiment currently under construction at GSI/FAIR is designed to study QCD predictions at high baryon densities. The CBM First-Level Event Selector (FLES) is the central event selection system of the experiment. Designed as a high-performance computer cluster, its task is an online analysis of the physics data including full event reconstruction at an incoming data rate exceeding 1 TByte/s. The CBM detector systems are free-running and self-triggered, delivering time-stamped data streams. As there is no inherent event separation, traditional approaches for global event building and event selection are not directly applicable. Instead of event building, the FLES combines the data from approximately 1000 input links to self-contained, overlapping processing intervals and distributes them to compute nodes. It employs a high-bandwidth InfiniBand network as well as dedicated custom FPGA input boards providing time-addressed access to buffered data. Subsequently, specialized event selection algorithms analyze these processing intervals in 4-D, identify events, and select those relevant for storage depending on the chosen CBM setup and selection scenario. This presentation outlines the design of the CBM First-level Event Selector and summarizes the results from first prototype systems.

Surface Management System Departure Event Data Analysis

Science.gov (United States)

Monroe, Gilena A.

2010-01-01

This paper presents a data analysis of the Surface Management System (SMS) performance of departure events, including push-back and runway departure events.The paper focuses on the detection performance, or the ability to detect departure events, as well as the prediction performance of SMS. The results detail a modest overall detection performance of push-back events and a significantly high overall detection performance of runway departure events. The overall detection performance of SMS for push-back events is approximately 55%.The overall detection performance of SMS for runway departure events nears 100%. This paper also presents the overall SMS prediction performance for runway departure events as well as the timeliness of the Aircraft Situation Display for Industry data source for SMS predictions.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data

International Nuclear Information System (INIS)

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-01-01

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy. (paper)

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

Science.gov (United States)

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Population Analysis of Adverse Events in Different Age Groups Using Big Clinical Trials Data.

Science.gov (United States)

Luo, Jake; Eldredge, Christina; Cho, Chi C; Cisler, Ron A

2016-10-17

Understanding adverse event patterns in clinical studies across populations is important for patient safety and protection in clinical trials as well as for developing appropriate drug therapies, procedures, and treatment plans. The objective of our study was to conduct a data-driven population-based analysis to estimate the incidence, diversity, and association patterns of adverse events by age of the clinical trials patients and participants. Two aspects of adverse event patterns were measured: (1) the adverse event incidence rate in each of the patient age groups and (2) the diversity of adverse events defined as distinct types of adverse events categorized by organ system. Statistical analysis was done on the summarized clinical trial data. The incident rate and diversity level in each of the age groups were compared with the lowest group (reference group) using t tests. Cohort data was obtained from ClinicalTrials.gov, and 186,339 clinical studies were analyzed; data were extracted from the 17,853 clinical trials that reported clinical outcomes. The total number of clinical trial participants was 6,808,619, and total number of participants affected by adverse events in these trials was 1,840,432. The trial participants were divided into eight different age groups to support cross-age group comparison. In general, children and older patients are more susceptible to adverse events in clinical trial studies. Using the lowest incidence age group as the reference group (20-29 years), the incidence rate of the 0-9 years-old group was 31.41%, approximately 1.51 times higher (P=.04) than the young adult group (20-29 years) at 20.76%. The second-highest group is the 50-59 years-old group with an incidence rate of 30.09%, significantly higher (Pgroup. The adverse event diversity also increased with increase in patient age. Clinical studies that recruited older patients (older than 40 years) were more likely to observe a diverse range of adverse events (Page group (older

NEVESIM: event-driven neural simulation framework with a Python interface.

Science.gov (United States)

Pecevski, Dejan; Kappel, David; Jonke, Zeno

2014-01-01

NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies.

Enabling Data-Driven Methodologies Across the Data Lifecycle and Ecosystem

Science.gov (United States)

Doyle, R. J.; Crichton, D.

2017-12-01

NASA has unlocked unprecedented scientific knowledge through exploration of the Earth, our solar system, and the larger universe. NASA is generating enormous amounts of data that are challenging traditional approaches to capturing, managing, analyzing and ultimately gaining scientific understanding from science data. New architectures, capabilities and methodologies are needed to span the entire observing system, from spacecraft to archive, while integrating data-driven discovery and analytic capabilities. NASA data have a definable lifecycle, from remote collection point to validated accessibility in multiple archives. Data challenges must be addressed across this lifecycle, to capture opportunities and avoid decisions that may limit or compromise what is achievable once data arrives at the archive. Data triage may be necessary when the collection capacity of the sensor or instrument overwhelms data transport or storage capacity. By migrating computational and analytic capability to the point of data collection, informed decisions can be made about which data to keep; in some cases, to close observational decision loops onboard, to enable attending to unexpected or transient phenomena. Along a different dimension than the data lifecycle, scientists and other end-users must work across an increasingly complex data ecosystem, where the range of relevant data is rarely owned by a single institution. To operate effectively, scalable data architectures and community-owned information models become essential. NASA's Planetary Data System is having success with this approach. Finally, there is the difficult challenge of reproducibility and trust. While data provenance techniques will be part of the solution, future interactive analytics environments must support an ability to provide a basis for a result: relevant data source and algorithms, uncertainty tracking, etc., to assure scientific integrity and to enable confident decision making. Advances in data science offer

Reconstruction of Daily 30 m Data from HJ CCD, GF-1 WFV, Landsat, and MODIS Data for Crop Monitoring

Directory of Open Access Journals (Sweden)

Mingquan Wu

2015-12-01

Full Text Available With the recent launch of new satellites and the developments of spatiotemporal data fusion methods, we are entering an era of high spatiotemporal resolution remote-sensing analysis. This study proposed a method to reconstruct daily 30 m remote-sensing data for monitoring crop types and phenology in two study areas located in Xinjiang Province, China. First, the Spatial and Temporal Data Fusion Approach (STDFA was used to reconstruct the time series high spatiotemporal resolution data from the Huanjing satellite charge coupled device (HJ CCD, Gaofen satellite no. 1 wide field-of-view camera (GF-1 WFV, Landsat, and Moderate Resolution Imaging Spectroradiometer (MODIS data. Then, the reconstructed time series were applied to extract crop phenology using a Hybrid Piecewise Logistic Model (HPLM. In addition, the onset date of greenness increase (OGI and greenness decrease (OGD were also calculated using the simulated phenology. Finally, crop types were mapped using the phenology information. The results show that the reconstructed high spatiotemporal data had a high quality with a proportion of good observations (PGQ higher than 0.95 and the HPLM approach can simulate time series Normalized Different Vegetation Index (NDVI very well with R2 ranging from 0.635 to 0.952 in Luntai and 0.719 to 0.991 in Bole, respectively. The reconstructed high spatiotemporal data were able to extract crop phenology in single crop fields, which provided a very detailed pattern relative to that from time series MODIS data. Moreover, the crop types can be classified using the reconstructed time series high spatiotemporal data with overall accuracy equal to 0.91 in Luntai and 0.95 in Bole, which is 0.028 and 0.046 higher than those obtained by using multi-temporal Landsat NDVI data.

Collecting operational event data for statistical analysis

International Nuclear Information System (INIS)

Atwood, C.L.

1994-09-01

This report gives guidance for collecting operational data to be used for statistical analysis, especially analysis of event counts. It discusses how to define the purpose of the study, the unit (system, component, etc.) to be studied, events to be counted, and demand or exposure time. Examples are given of classification systems for events in the data sources. A checklist summarizes the essential steps in data collection for statistical analysis