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online data analysis at the ESRF bioSAXS beamline, BM29

JOURNAL OF APPLIED CRYSTALLOGRAPHY 2016年第1期49卷 203-212页

作者： Brennich, Martha Elisabeth Kieffer, Jerome Bonamis, Guillaume Antolinos, Alejandro De Maria Hutin, Stephanie Pernot, Petra Round, Adam European Synchrotron Radiat Facil 71 Ave MartyrsCS 40220 F-38043 Grenoble France European Mol Biol Lab Grenoble Outstn 71 Ave MartyrsCS 90181 F-38042 Grenoble France Univ Grenoble Alpes EMBL CNRS Unit Virus Host Cell Interact 71 Ave MartyrsCS 90181 F-38042 Grenoble France Keele Univ Fac Nat Sci Keele ST5 5BG Staffs England

High-throughput small-angle X-ray scattering on proteins in solution (bioSAXS) at synchrotron sources is a commonly used technique in structural biology, which relies on highly automated data acquisition. data reduction and primary analysis for bioSAXS experiments consist of a well defined series of individual tasks, the automation of which allows a first easy assessment of the quality of collected data and the adjustment of collection strategies if necessary. This article describes both the logic and the technical implementation of the automated processing pipeline for bioSAXS data at the ESRF BM29 beamline using the EDNA framework.

关键词： online data analysis solution scattering proteins

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OnDA: online data analysis and feedback for serial X-ray imaging

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JOURNAL OF APPLIED CRYSTALLOGRAPHY 2016年第3期49卷 1073-1080页

作者： Mariani, Valerio Morgan, Andrew Yoon, Chun Hong Lane, Thomas J. White, Thomas A. O'Grady, Christopher Kuhn, Manuela Aplin, Steve Koglin, Jason Barty, Anton Chapman, Henry N. DESY Ctr Free Electron Laser Sci Notkestr 85 D-22607 Hamburg Germany DESY Notkestr 85 D-22607 Hamburg Germany European XFEL GmbH Albert Einstein Ring 19 D-22761 Hamburg Germany SLAC Natl Accelerator Lab Linac Coherent Light Source 2575 Sand Hill Rd Menlo Pk CA 94025 USA Univ Hamburg Dept Phys Luruper Chaussee 149 D-22761 Hamburg Germany Ctr Ultrafast Imaging Luruper Chaussee 149 D-22761 Hamburg Germany

This article describes a free and open-source data analysis utility designed for fast online feedback during serial X-ray diffraction and scattering experiments: OnDA (online data analysis). Three complete real-time monitors for common types of serial X-ray imaging experiments are presented. These monitors are capable of providing the essential information required for quick decision making in the face of extreme rates of data collection. In addition, a set of modules, functions and algorithms that allow developers to modify the provided monitors or develop new ones are provided. The emphasis here is on simple, modular and scalable code that is based on open-source libraries and protocols. OnDA monitors have already proven to be invaluable tools in several experiments, especially for scoring and monitoring of diffraction data during serial crystallography experiments at both free-electron laser and synchrotron facilities. It is felt that in the future the kind of fast feedback that OnDA monitors provide will help researchers to deal with the expected very high throughput data flow at next-generation facilities such as the European X-ray free-electron laser.

关键词： online data analysis free-electron lasers serial femtosecond crystallography computer programs

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EDNA: a framework for plugin-based applications applied to X-ray experiment online data analysis

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JOURNAL OF SYNCHROTRON RADIATION 2009年第6期16卷 872-879页

作者： Incardona, Marie-Francoise Bourenkov, Gleb P. Levik, Karl Pieritz, Romeu A. Popov, Alexander N. Svensson, Olof European Synchrotron Radiat Facil F-38043 Grenoble France DESY EMBL Hamburg Outstn D-22607 Hamburg Germany Diamond Light Source Ltd Didcot OX11 0DE Oxon England

EDNA is a framework for developing plugin-based applications especially for online data analysis in the X-ray experiments field. This article describes the features provided by the EDNA framework to ease the development of extensible scientific applications. This framework includes a plugins class hierarchy, configuration and application facilities, a mechanism to generate data classes and a testing framework. These utilities allow rapid development and integration in which robustness and quality play a fundamental role. A first prototype, designed for macromolecular crystallography experiments and tested at several synchrotrons, is presented.

关键词： online data analysis beamline automation data collection

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PlanetServer: Innovative approaches for the online analysis of hyperspectral satellite data from Mars

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ADVANCES IN SPACE RESEARCH 2014年第12期53卷 1858-1871页

作者： Oosthoek, J. H. P. Flahaut, J. Rossi, A. P. Baumann, P. Misev, D. Campalani, P. Unnithan, V. Jacobs Univ Bremen D-28759 Bremen Germany Univ Paris 11 CNRS IAS F-91405 Orsay France ENDIF I-44122 Ferrara Italy

PlanetServer is a WebGIS system, currently under development, enabling the online analysis of Compact Reconnaissance Imaging Spectrometer (CRISM) hyperspectral data from Mars. It is part of the EarthServer project which builds infrastructure for online access and analysis of huge Earth Science datasets. Core functionality consists of the rasdaman Array database Management System (DBMS) for storage, and the Open Geospatial Consortium (OGC) Web Coverage Processing Service (WCPS) for data querying. Various WCPS queries have been designed to access spatial and spectral subsets of the CRISM data. The client WebGIS, consisting mainly of the OpenLayers javascript library, uses these queries to enable online spatial and spectral analysis. Currently the PlanetServer demonstration consists of two CRISM Full Resolution Target (FRT) observations, surrounding the NASA Curiosity rover landing site. A detailed analysis of one of these observations is performed in the Case Study section. The current PlanetServer functionality is described step by step, and is tested by focusing on detecting mineralogical evidence described in earlier Gale crater studies. Both the PlanetServer methodology and its possible use for mineralogical studies will be further discussed. Future work includes batch ingestion of CRISM data and further development of the WebGIS and analysis tools. (c) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

关键词： online data analysis CRISM Hyperspectral Mars Earth Server Rasdaman

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It takes two (seconds): decreasing encoding time for two-choice functional near-infrared spectroscopy brain-computer interface communication

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NEUROPHOTONICS 2023年第4期10卷 045005页

作者： Vorreuther, Anna Bastian, Lisa Andonegui, Amaia Benitez Evenblij, Danielle Riecke, Lars Luhrs, Michael Sorger, Bettina Maastricht Univ Dept Cognit Neurosci Maastricht Netherlands Univ Stuttgart Inst Human Factors & Technol Management IAT Appl Neurocognit Syst Stuttgart Germany Univ Tubingen Inst Med Psychol & Behav Neurobiol Tubingen Germany Int Max Planck Res Sch Grad Training Ctr Neurosci Tubingen Germany NIH MEG Core Facil Natl Inst Mental Hlth Bethesda MD USA Brain Innovat BV Res Dept Maastricht Netherlands

Significance: Brain-computer interfaces (BCIs) can provide severely motorimpaired patients with a motor-independent communication channel. Functional near-infrared spectroscopy (fNIRS) constitutes a promising BCI-input modality given its high mobility, safety, user comfort, cost-efficiency, and relatively low motion sensitivity. Aim: The present study aimed at developing an efficient and convenient two-choice fNIRS communication BCI by implementing a relatively short encoding time (2 s), considerably increasing communication speed, and decreasing the cognitive load of BCI users. Approach: To encode binary answers to 10 biographical questions, 10 healthy adults repeatedly performed a combined motor-speech imagery task within 2 different time windows guided by auditory instructions. Each answer-encoding run consisted of 10 trials. Answers were decoded during the ongoing experiment from the time course of the individually identified most-informative fNIRS channel-bychromophore combination. Results: The answers of participants were decoded online with an accuracy of 85.8% (run-based group mean). Post-hoc analysis yielded an average single-trial accuracy of 68.1%. analysis of the effect of number of trial repetitions showed that the best information-transfer rate could be obtained by combining four encoding trials. Conclusions: The study demonstrates that an encoding time as short as 2 s can enable immediate, efficient, and convenient fNIRS-BCI communication.

关键词： motor disability '' locked-in '' syndrome brain-based communication brain-computer interface fNIRS mental imagery online data analysis

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A FM-CW radar proximity sensor for use in mechatronic products

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MECHATRONICS 2001年第2期11卷 119-130页

作者： Jackson, MR Parkin, RM Tao, B Univ Loughborough Wolfson Sch Mech & Mfg Engn Mechatron Res Grp Loughborough LE11 3TU Leics England

The need for a low cost medium range proximity sensor for use in mechatronic products is identified and discussed with particular reference to automotive applications. One candidate solution to this need, a 27 GHz frequency modulated continuous wave radar system, is presented for use as a range finder. The method of releasing the range information from the returned signal is described together with the results from off-line data analysis. A real-time system for implementation in a typical product is outlined. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： online data analysis frequency-modulated-continuous-wave radar Proximity sensors return signal

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RDMA data transfer and GPU acceleration methods for high-throughput online processing of serial crystallography images

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JOURNAL OF SYNCHROTRON RADIATION 2020年第5期27卷 1297-1306页

作者： Ponsard, Raphael Janvier, Nicolas Kieffer, Jerome Houzet, Dominique Fristot, Vincent ESRF European Synchrotron 71 Ave Martyrs F-38000 Grenoble France Grenoble Alpes Univ GIPSALAB 11 Rue Math F-38400 St Martin Dheres France

The continual evolution of photon sources and high-performance detectors drives cutting-edge experiments that can produce very high throughput data streams and generate large data volumes that are challenging to manage and store. In these cases, efficient data transfer and processing architectures that allow online image correction, data reduction or compression become fundamental. This work investigates different technical options and methods for data placement from the detector head to the processing computing infrastructure, taking into account the particularities of modern modular high-performance detectors. In order to compare realistic figures, the future ESRF beamline dedicated to macromolecular X-ray crystallography, EBSL8, is taken as an example, which will use a PSI JUNGFRAU 4M detector generating up to 16 GB of data per second, operating continuously during several minutes. Although such an experiment seems possible at the target speed with the 100 Gb s(-1) network cards that are currently available, the simulations generated highlight some potential bottlenecks when using a traditional software stack. An evaluation of solutions is presented that implements remote direct memory access (RDMA) over converged ethernet techniques. A synchronization mechanism is proposed between a RDMA network interface card (RNIC) and a graphics processing unit (GPU) accelerator in charge of the online data processing. The placement of the detector images onto the GPU is made to overlap with the computation carried out, potentially hiding the transfer latencies. As a proof of concept, a detector simulator and a backend GPU receiver with a rejection and compression algorithm suitable for a synchrotron serial crystallography (SSX) experiment are developed. It is concluded that the available transfer throughput from the RNIC to the GPU accelerator is at present the major bottleneck in online processing for SSX experiments.

关键词： online data processing RDMA RoCEv2 GPU SSX online data analysis

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online Prediction and Improvement of Reliability for Service Oriented Systems

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IEEE TRANSACTIONS ON RELIABILITY 2016年第3期65卷 1133-1148页

作者： Ding, Zuohua Xu, Ting Ye, Tiantian Zhou, Yuan Zhejiang Sci Tech Univ Lab Intelligent Comp & Software Engn Hangzhou 310018 Peoples R China Zhejiang Sci Tech Univ Sch Informat Sci & Technol Hangzhou 310018 Peoples R China

Reliability is an important metric for measuring the quality of software. Many methods have been proposed for online predicting and improving software reliability, but most of them have the following weakness: they are not able to predict software reliability on different time intervals and to locate the faulty components that cause the declining of the reliability either. This paper proposes a new method for online improvement of reliability of service composition. We use monitored failure data at ports of services to predict the reliabilities of service composition on different time intervals. If the predicted reliability is lower than the expected value, then we locate the faulty components that cause the declining of the reliability by using an improved spectrum-fault-localization (SFL) technique. The system can be automatically reconfigured to improve the system reliability by adding a component replica or replacing the faulty component. An online Shop example is used to demonstrate the effectiveness of our method.

关键词： online data analysis reliability improvement reliability prediction spectrum-based localization system reconfiguration

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data acquisition architecture and online processing system for the HAWC gamma-ray observatory

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2018年 888卷 138-146页

作者： Abeysekara, A. U. Alfaro, R. Alvarez, C. Alvarez, J. D. Arceo, R. Arteaga-Velazquez, J. C. Solares, H. A. Ayala Barber, A. S. Baughman, B. M. Bautista-Elivar, N. Gonzalez, J. Becerra Belmont-Moreno, E. BenZvi, S. Y. Berley, D. Bonilla Rosales, M. Braun, J. Caballero-Lopez, R. A. Caballero-Mora, K. S. Carraminana, A. Castillo, M. Cotti, U. Cotzomi, J. de la Fuente, E. De Leon, C. DeYoung, T. Diaz-Cruz, J. Diaz Hernandez, R. Diaz-Velez, J. C. Dingus, B. L. DuVernois, M. A. Ellsworth, R. W. Fiorino, D. W. Fraija, N. Galindo, A. Garfias, F. Gonzalez, M. M. Goodman, J. A. Grabski, V. Gussert, M. Hampel-Arias, Z. Harding, J. P. Hui, C. M. Huntemeyer, P. Imran, A. Iriarte, A. Karn, P. Kieda, D. Kunde, G. J. Lara, A. Lauer, R. J. Lee, W. H. Lennarz, D. Leon Vargas, H. Linares, E. C. Linnemann, J. T. Proper, M. Longo Luna-Garcia, R. Malone, K. Marinelli, A. Marinelli, S. S. Martinez, O. Martinez-Castro, J. Martinez-Huerta, H. Matthews, J. A. J. McEnery, J. Mendoza Torres, E. Miranda-Romagnoli, P. Moreno, E. Mostafa, M. Nellen, L. Newbold, M. Noriega-Papaqui, R. Oceguera-Becerra, T. Patricelli, B. Pelayo, R. Perez-Perez, E. G. Pretz, J. Riviere, C. Rosa-Gonzalez, D. Ruiz-Velasco, E. Ryan, J. Salazar, H. Greus, F. Salesa Sanchez, F. E. Sandoval, A. Schneider, M. Silich, S. Sinnis, G. Smith, A. J. Woodle, K. Sparks Springer, R. W. Taboada, I. Toale, P. A. Tollefson, K. Torres, I. Ukwatta, T. N. Villasenor, L. Weisgarber, T. Westerhoff, S. Wisher, I. G. Wood, J. Yapici, T. Yodh, G. B. Younk, P. W. Zaborov, D. Zepeda, A. Zhou, H. Univ Utah Dept Phys & Astron Salt Lake City UT USA Univ Nacl Autonoma Mexico Inst Fis Mexico City DF Mexico Univ Autonoma Chiapas Tuxtla Gutierrez Chiapas Mexico Univ Michoacana Inst Fis & Matemat Morelia Michoacan Mexico Michigan Technol Univ Dept Phys Houghton MI 49931 USA Univ Maryland Dept Phys College Pk MD 20742 USA Univ Politecn Pachuca Pachuca Hidalgo Mexico NASA Goddard Space Flight Ctr Greenbelt MD USA Univ Rochester Dept Phys & Astron Rochester NY 14627 USA Inst Nacl Astrofis Opt & Electr Puebla Mexico Univ Wisconsin Dept Phys 1150 Univ Ave Madison WI 53706 USA Univ Nacl Autonoma Mexico Inst Geofis Mexico City DF Mexico Benemerita Univ Autonoma Puebla Fac Ciencias Fis Matemat Puebla Mexico Univ Guadalajara LAM Dpto Fis Dpto Elect CUCEI IT Phd CUCEAPhys Mat Phd CUVALLES Guadalajara Jalisco Mexico Michigan State Univ Dept Phys & Astron E Lansing MI 48824 USA Los Alamos Natl Lab Div Phys Los Alamos NM USA George Mason Univ Sch Phys Astron & Computat Sci Fairfax VA USA Univ Nacl Autonoma Mexico Inst Astron Mexico City DF Mexico Colorado State Univ Dept Phys Ft Collins CO 80523 USA NASA Marshall Space Flight Ctr Astrophys Off Huntsville AL USA Univ Calif Irvine Dept Phys & Astron Irvine CA USA Univ New Mexico Dept Phys & Astron Albuquerque NM 87131 USA Georgia Inst Technol Sch Phys Atlanta GA 30332 USA Georgia Inst Technol Ctr Relativist Astrophys Atlanta GA 30332 USA Ctr Invest Computac Inst Politecn Nacl Mexico City DF Mexico Penn State Univ Dept Phys 104 Davey Lab University Pk PA 16802 USA IPN Dept Phys Ctr Invest & Estudios Avanzados Mexico City DF Mexico Univ Autonoma Estado Hidalgo Pachuca Hidalgo Mexico Univ Nacl Autonoma Mexico Inst Ciencias Nucl Mexico City DF Mexico Inst Politecn Nacl Unidad Profes Interdisciplinaria Ingn & Tecnol Av Mexico City DF Mexico Univ New Hampshire Ctr Space Sci Durham NH 03824 USA IFJ PAN Inst Fizyki Jadrowej Henryka Niewodniczanskiego Polskiej Akad Nauk Krakow

The High Altitude Water Cherenkov observatory (HAWC) is an air shower array devised for TeV gamma-ray astronomy. HAWC is located at an altitude of 4100 m a.s.l. in Sierra Negra, Mexico. HAWC consists of 300 Water Cherenkov Detectors, each instrumented with 4 photomultiplier tubes (PMTs). HAWC re-uses the Front-End Boards from the Milagro experiment to receive the PMT signals. These boards are used in combination with Time to Digital Converters (TDCs) to record the time and the amount of light in each PMT hit (light flash). A set of VME TDC modules (128 channels each) is operated in a continuous (dead time free) mode. The TDCs are read out via the VME bus by Single-Board Computers (SBCs), which in turn are connected to a gigabit Ethernet network. The complete system produces approximate to 500 MB/s of raw data. A high-throughput data processing system has been designed and built to enable real-time data analysis. The system relies on off-the-shelf hardware components, an open-source software technology for data transfers (ZeroMQ) and a custom software framework for data analysis (AERIE). Multiple trigger and reconstruction algorithms can be combined and run on blocks of data in a parallel fashion, producing a set of output data streams which can be analyzed in real time with minimal latency (<5 s). This paper provides an overview of the hardware set-up and an in-depth description of the software design, covering both the TDC data acquisition system and the real-time data processing system. The performance of these systems is also discussed. (C) 2018 Elsevier B.V. All rights reserved.

关键词： data acquisition Real time data processing online data analysis Gamma-ray observatory

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online dependence clustering of multivariate streaming data using one-class SVMs

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INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 2022年第6期37卷 3682-3708页

作者： Lee, Geonseok Lee, Kichun Hanyang Univ Dept Ind Engn 222 Wangsimni Ro Seoul 04763 South Korea

online clustering of multivariate streaming data has attracted considerable interest in recent years due to the abundance of data sources. Numerous studies in this field have been performed, but they usually suffer from the practical problems associated with discovering arbitrary-shaped clusters, specifying major parameters in advance, and detecting aberrant observations. Addressing these issues is important for online-clustering tasks, where data arrive in continuous streams and group behaviors change simultaneously. In this paper, we propose a kernel-based online dependence clustering, namely, KODC, that not only estimates the cluster membership using one-class support vector machines (OC-SVMs), but also detects outliers distant from the identified clusters by aggregating OC-SVM decisions in a realtime basis. At the base level, we use a new measure of connective dependence that forms the graph connected via modified Markovian transitions to enable large-scale clustering. The proposed framework introduces the coherence threshold to extract data points, which can represent a cluster to which they belong, thus controlling the computational complexity without degrading the clustering performance. To track the pattern evolution over time, KODC also updates the classifier configuration maximizing the total group connective dependence. We evaluate this framework on both several synthetic and real-world data sets involving multivariate streaming data, and compare it experimentally with other popular online-clustering methods in terms of four evaluation metrics. The results show that our framework effectively identifies the clusters and outliers, especially in various shaped data subject to change over time, without requiring any prior knowledge of the data.

关键词： dependence clustering one-class support vector machine online data analysis outlier detection unsupervised learning

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