Science.gov

Sample records for real event detection

  1. Real-time detection of traffic events using smart cameras

    NASA Astrophysics Data System (ADS)

    Macesic, M.; Jelaca, V.; Niño-Castaneda, J. O.; Prodanovic, N.; Panic, M.; Pizurica, A.; Crnojevic, V.; Philips, W.

    2012-01-01

    With rapid increase of number of vehicles on roads it is necessary to maintain close monitoring of traffic. For this purpose many surveillance cameras are placed along roads and on crossroads, creating a huge communication load between the cameras and the monitoring center. Therefore, the data needs to be processed on site and transferred to the monitoring centers in form of metadata or as a set of selected images. For this purpose it is necessary to detect events of interest already on the camera side, which implies using smart cameras as visual sensors. In this paper we propose a method for tracking of vehicles and analysis of vehicle trajectories to detect different traffic events. Kalman filtering is used for tracking, combining foreground and optical flow measurements. Obtained vehicle trajectories are used to detect different traffic events. Every new trajectory is compared with collection of normal routes and clustered accordingly. If the observed trajectory differs from all normal routes more than a predefined threshold, it is marked as abnormal and the alarm is raised. The system was developed and tested on Texas Instruments OMAP platform. Testing was done on four different locations, two locations in the city and two locations on the open road.

  2. A novel adaptive, real-time algorithm to detect gait events from wearable sensors.

    PubMed

    Chia Bejarano, Noelia; Ambrosini, Emilia; Pedrocchi, Alessandra; Ferrigno, Giancarlo; Monticone, Marco; Ferrante, Simona

    2015-05-01

    A real-time, adaptive algorithm based on two inertial and magnetic sensors placed on the shanks was developed for gait-event detection. For each leg, the algorithm detected the Initial Contact (IC), as the minimum of the flexion/extension angle, and the End Contact (EC) and the Mid-Swing (MS), as minimum and maximum of the angular velocity, respectively. The algorithm consisted of calibration, real-time detection, and step-by-step update. Data collected from 22 healthy subjects (21 to 85 years) walking at three self-selected speeds were used to validate the algorithm against the GaitRite system. Comparable levels of accuracy and significantly lower detection delays were achieved with respect to other published methods. The algorithm robustness was tested on ten healthy subjects performing sudden speed changes and on ten stroke subjects (43 to 89 years). For healthy subjects, F1-scores of 1 and mean detection delays lower than 14 ms were obtained. For stroke subjects, F1-scores of 0.998 and 0.944 were obtained for IC and EC, respectively, with mean detection delays always below 31 ms. The algorithm accurately detected gait events in real time from a heterogeneous dataset of gait patterns and paves the way for the design of closed-loop controllers for customized gait trainings and/or assistive devices. PMID:25069118

  3. Qualitative and event-specific real-time PCR detection methods for Bt brinjal event EE-1.

    PubMed

    Randhawa, Gurinder Jit; Sharma, Ruchi; Singh, Monika

    2012-01-01

    Bt brinjal event EE-1 with cry1Ac gene, expressing insecticidal protein against fruit and shoot borer, is the first genetically modified food crop in the pipeline for commercialization in India. Qualitative polymerase chain reaction (PCR) along with event-specific conventional as well as real-time PCR methods to characterize the event EE-1 is reported. A multiplex (pentaplex) PCR system simultaneously amplifying cry1Ac transgene, Cauliflower Mosaic Virus (CaMV) 35S promoter, nopaline synthase (nos) terminator, aminoglycoside adenyltransferase (aadA) marker gene, and a taxon-specific beta-fructosidase gene in event EE-1 has been developed. Furthermore, construct-specific PCR, targeting the approximate 1.8 kb region of inserted gene construct comprising the region of CaMV 35S promoter and cry1Ac gene has also been developed. The LOD of developed EE-1 specific conventional PCR assay is 0.01%. The method performance of the reported real-time PCR assay was consistent with the acceptance criteria of Codex Alimentarius Commission ALINORM 10/33/23, with the LOD and LOQ values of 0.05%. The developed detection methods would not only facilitate effective regulatory compliance for identification of genetic traits, risk assessment, management, and postrelease monitoring, but also address consumer concerns and resolution of legal disputes. PMID:23451391

  4. Real-time gait event detection for transfemoral amputees during ramp ascending and descending.

    PubMed

    Maqbool, H F; Husman, M A B; Awad, M I; Abouhossein, A; Dehghani-Sanij, A A

    2015-01-01

    Events and phases detection of the human gait are vital for controlling prosthesis, orthosis and functional electrical stimulation (FES) systems. Wearable sensors are inexpensive, portable and have fast processing capability. They are frequently used to assess spatio-temporal, kinematic and kinetic parameters of the human gait which in turn provide more details about the human voluntary control and ampute-eprosthesis interaction. This paper presents a reliable real-time gait event detection algorithm based on simple heuristics approach, applicable to signals from tri-axial gyroscope for lower limb amputees during ramp ascending and descending. Experimental validation is done by comparing the results of gyroscope signal with footswitches. For healthy subjects, the mean difference between events detected by gyroscope and footswitches is 14 ms and 10.5 ms for initial contact (IC) whereas for toe off (TO) it is -5 ms and -25 ms for ramp up and down respectively. For transfemoral amputee, the error is slightly higher either due to the placement of footswitches underneath the foot or the lack of proper knee flexion and ankle plantarflexion/dorsiflexion during ramp up and down. Finally, repeatability tests showed promising results. PMID:26737364

  5. Real-time detection of pathological cardiac events in the electrocardiogram.

    PubMed

    Iliev, Ivo; Krasteva, Vessela; Tabakov, Serafim

    2007-03-01

    The development of accurate and fast methods for real-time electrocardiogram (ECG) analysis is mandatory in handheld fully automated monitoring devices for high-risk cardiac patients. The present work describes a simple software method for fast detection of pathological cardiac events. It implements real-time procedures for QRS detection, interbeat RR-intervals analysis, QRS waveform evaluation and a decision-tree beat classifier. Two QRS descriptors are defined to assess (i) the RR interval deviation from the mean RR interval and (ii) the QRS waveform deviation from the QRS pattern of the sustained rhythm. The calculation of the second parameter requires a specific technique, in order to satisfy the demand for straight signal processing with minimum iterations and small memory size. This technique includes fast and resource efficient estimation of a histogram matrix, which accumulates dynamically the amplitude-temporal distribution of the successive QRS pattern waveforms. The pilot version of the method is developed in Matlab and it is tested with internationally recognized ECG databases. The assessment of the online single lead QRS detector showed sensitivity and positive predictivity of above 99%. The classification rules for detection of pathological ventricular beats were defined empirically by statistical analysis. The attained specificity and sensitivity are about 99.5% and 95.7% for all databases and about 99.81% and 98.87% for the noise free dataset. The method is applicable in low computational cost systems for long-term ECG monitoring, such as intelligent holters, automatic event/alarm recorders or personal devices with intermittent wireless data transfer to a central terminal. PMID:17322591

  6. Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France

    PubMed Central

    Abat, Cédric; Chaudet, Hervé; Colson, Philippe; Rolain, Jean-Marc

    2015-01-01

    Infectious diseases are a major threat to humanity, and accurate surveillance is essential. We describe how to implement a laboratory data–based surveillance system in a clinical microbiology laboratory. Two historical Microsoft Excel databases were implemented. The data were then sorted and used to execute the following 2 surveillance systems in Excel: the Bacterial real-time Laboratory-based Surveillance System (BALYSES) for monitoring the number of patients infected with bacterial species isolated at least once in our laboratory during the study periodl and the Marseille Antibiotic Resistance Surveillance System (MARSS), which surveys the primary β-lactam resistance phenotypes for 15 selected bacterial species. The first historical database contained 174,853 identifications of bacteria, and the second contained 12,062 results of antibiotic susceptibility testing. From May 21, 2013, through June 4, 2014, BALYSES and MARSS enabled the detection of 52 abnormal events for 24 bacterial species, leading to 19 official reports. This system is currently being refined and improved. PMID:26196165

  7. Real-time detection and classification of anomalous events in streaming data

    DOEpatents

    Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

    2016-04-19

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

  8. Characterization and event specific-detection by quantitative real-time PCR of T25 maize insert.

    PubMed

    Collonnier, Cécile; Schattner, Alexandra; Berthier, Georges; Boyer, Francine; Coué-Philippe, Géraldine; Diolez, Annick; Duplan, Marie-Noëlle; Fernandez, Sophie; Kebdani, Naïma; Kobilinsky, André; Romaniuk, Marcel; de Beuckeleer, Marc; de Loose, Marc; Windels, Pieter; Bertheau, Yves

    2005-01-01

    T25 is one of the 4 maize transformation events from which commercial lines have so far been authorized in Europe. It was created by polyethylene glycol-mediated transformation using a construct bearing one copy of the synthetic pat gene associated with both promoter and terminator of the 35S ribosomal gene from cauliflower mosaic virus. In this article, we report the sequencing of the whole T25 insert and the characterization of its integration site by using a genome walking strategy. Our results confirmed that one intact copy of the initial construct had been integrated in the plant genome. They also revealed, at the 5' junction of the insert, the presence of a second truncated 35S promoter, probably resulting from rearrangements which may have occurred before or during integration of the plasmid DNA. The analysis of the junction fragments showed that the integration site of the insert presented high homologies with the Huck retrotransposon family. By using one primer annealing in the maize genome and the other in the 5' end of the integrated DNA, we developed a reliable event-specific detection system for T25 maize. To provide means to comply with the European regulation, a real-time PCR test was designed for specific quantitation of T25 event by using Taqman chemistry. PMID:15859082

  9. Real-time detection of an extreme scattering event: Constraints on Galactic plasma lenses.

    PubMed

    Bannister, Keith W; Stevens, Jamie; Tuntsov, Artem V; Walker, Mark A; Johnston, Simon; Reynolds, Cormac; Bignall, Hayley

    2016-01-22

    Extreme scattering events (ESEs) are distinctive fluctuations in the brightness of astronomical radio sources caused by occulting plasma lenses in the interstellar medium. The inferred plasma pressures of the lenses are ~10(3) times the ambient pressure, challenging our understanding of gas conditions in the Milky Way. Using a new survey technique, we discovered an ESE while it was in progress. Here we report radio and optical follow-up observations. Modeling of the radio data demonstrates that the lensing structure is a density enhancement and the lens is diverging, ruling out one of two competing physical models. Our technique will uncover many more ESEs, addressing a long-standing mystery of the small-scale gas structure of our Galaxy. PMID:26798008

  10. Real-time detection of an extreme scattering event: Constraints on Galactic plasma lenses

    NASA Astrophysics Data System (ADS)

    Bannister, Keith W.; Stevens, Jamie; Tuntsov, Artem V.; Walker, Mark A.; Johnston, Simon; Reynolds, Cormac; Bignall, Hayley

    2016-01-01

    Extreme scattering events (ESEs) are distinctive fluctuations in the brightness of astronomical radio sources caused by occulting plasma lenses in the interstellar medium. The inferred plasma pressures of the lenses are ~103 times the ambient pressure, challenging our understanding of gas conditions in the Milky Way. Using a new survey technique, we discovered an ESE while it was in progress. Here we report radio and optical follow-up observations. Modeling of the radio data demonstrates that the lensing structure is a density enhancement and the lens is diverging, ruling out one of two competing physical models. Our technique will uncover many more ESEs, addressing a long-standing mystery of the small-scale gas structure of our Galaxy.

  11. Real-time automated 3D sensing, detection, and recognition of dynamic biological micro-organic events

    NASA Astrophysics Data System (ADS)

    Javidi, Bahram; Yeom, Seokwon; Moon, Inkyu; Daneshpanah, Mehdi

    2006-05-01

    In this paper, we present an overview of three-dimensional (3D) optical imaging techniques for real-time automated sensing, visualization, and recognition of dynamic biological microorganisms. Real time sensing and 3D reconstruction of the dynamic biological microscopic objects can be performed by single-exposure on-line (SEOL) digital holographic microscopy. A coherent 3D microscope-based interferometer is constructed to record digital holograms of dynamic micro biological events. Complex amplitude 3D images of the biological microorganisms are computationally reconstructed at different depths by digital signal processing. Bayesian segmentation algorithms are applied to identify regions of interest for further processing. A number of pattern recognition approaches are addressed to identify and recognize the microorganisms. One uses 3D morphology of the microorganisms by analyzing 3D geometrical shapes which is composed of magnitude and phase. Segmentation, feature extraction, graph matching, feature selection, and training and decision rules are used to recognize the biological microorganisms. In a different approach, 3D technique is used that are tolerant to the varying shapes of the non-rigid biological microorganisms. After segmentation, a number of sampling patches are arbitrarily extracted from the complex amplitudes of the reconstructed 3D biological microorganism. These patches are processed using a number of cost functions and statistical inference theory for the equality of means and equality of variances between the sampling segments. Also, we discuss the possibility of employing computational integral imaging for 3D sensing, visualization, and recognition of biological microorganisms illuminated under incoherent light. Experimental results with several biological microorganisms are presented to illustrate detection, segmentation, and identification of micro biological events.

  12. An Unsorted Spike-Based Pattern Recognition Method for Real-Time Continuous Sensory Event Detection from Dorsal Root Ganglion Recording.

    PubMed

    Han, Sungmin; Chu, Jun-Uk; Kim, Hyungmin; Choi, Kuiwon; Park, Jong Woong; Youn, Inchan

    2016-06-01

    In functional neuromuscular stimulation systems, sensory information-based closed-loop control can be useful for restoring lost function in patients with hemiplegia or quadriplegia. The goal of this study was to detect sensory events from tactile afferent signals continuously in real time using a novel unsorted spike-based pattern recognition method. The tactile afferent signals were recorded with a 16-channel microelectrode in the dorsal root ganglion, and unsorted spike-based feature vectors were extracted as a novel combination of the time and time-frequency domain features. Principal component analysis was used to reduce the dimensionality of the feature vectors, and a multilayer perceptron classifier was used to detect sensory events. The proposed method showed good performance for classification accuracy, and the processing time delay of sensory event detection was less than 200 ms. These results indicated that the proposed method could be applicable for sensory feedback in closed-loop control systems. PMID:26672029

  13. Near-Real-Time Detection and Monitoring of Dust Events by Satellite (SeaWIFS, MODIS, and TOMS)

    NASA Technical Reports Server (NTRS)

    Hsu, N. Christina; Tsay, Si-Chee; Herman, Jay R.; Kaufman, Yoram

    2002-01-01

    Over the last few years satellites have given us increasingly detailed information on the size, location, and duration of dust events around the world. These data not only provide valuable feedback to the modelling community as to the fidelity of their aerosol models but are also finding increasing use in near real-time applications. In particular, the ability to locate and track the development of aerosol dust clouds on a near real-time basis is being used by scientists and government to provide warning of air pollution episodes over major urban area. This ability has also become a crucial component of recent coordinated campaigns to study the characteristics of tropospheric aerosols such as dust and their effect on climate. One such recent campaign was ACE-Asia, which was designed to obtain the comprehensive set of ground, aircraft, and satellite data necessary to provide a detailed understanding of atmospheric aerosol particles over the Asian-Pacific region. As part of ACE-Asia, we developed a near real-time data processing and access system to provide satellite data from the polar-orbiting instruments Earth Probe TOMS (in the form of absorbing aerosol index) and SeaWiFS (in the form of aerosol optical thickness, AOT, and Angstrom exponent). The results were available via web access. The location and movement information provided by these data were used both in support of the day-to-day flight planning of ACE-Asia and as input into aerosol transport models. While near real-time SeaWiFS data processing can be performed using either the normal global data product or data obtained via direct broadcast to receiving stations close to the area of interest, near real-time MODIS processing of data to provide aerosol retrievals is currently only available using its direct broadcast capability. In this paper, we will briefly discuss the algorithms used to generate these data. The retrieved aerosol optical thickness and Angstrom exponent from SeaWiFS will be compared with

  14. SPR and SPR Imaging: Recent Trends in Developing Nanodevices for Detection and Real-Time Monitoring of Biomolecular Events.

    PubMed

    Puiu, Mihaela; Bala, Camelia

    2016-01-01

    In this paper we review the underlying principles of the surface plasmon resonance (SPR) technique, particularly emphasizing its advantages along with its limitations regarding the ability to discriminate between the specific binding response and the interfering effects from biological samples. While SPR sensors were developed almost three decades, SPR detection is not yet able to reduce the time-consuming steps of the analysis, and is hardly amenable for miniaturized, portable platforms required in point-of-care (POC) testing. Recent advances in near-field optics have emerged, resulting in the development of SPR imaging (SPRi) as a powerful optical, label-free monitoring tool for multiplexed detection and monitoring of biomolecular events. The microarrays design of the SPRi chips incorporating various metallic nanostructures make these optofluidic devices more suitable for diagnosis and near-patient testing than the traditional SPR sensors. The latest developments indicate SPRi detection as being the most promising surface plasmon-based technique fulfilling the demands for implementation in lab-on-a-chip (LOC) technologies. PMID:27314345

  15. SPR and SPR Imaging: Recent Trends in Developing Nanodevices for Detection and Real-Time Monitoring of Biomolecular Events

    PubMed Central

    Puiu, Mihaela; Bala, Camelia

    2016-01-01

    In this paper we review the underlying principles of the surface plasmon resonance (SPR) technique, particularly emphasizing its advantages along with its limitations regarding the ability to discriminate between the specific binding response and the interfering effects from biological samples. While SPR sensors were developed almost three decades, SPR detection is not yet able to reduce the time-consuming steps of the analysis, and is hardly amenable for miniaturized, portable platforms required in point-of-care (POC) testing. Recent advances in near-field optics have emerged, resulting in the development of SPR imaging (SPRi) as a powerful optical, label-free monitoring tool for multiplexed detection and monitoring of biomolecular events. The microarrays design of the SPRi chips incorporating various metallic nanostructures make these optofluidic devices more suitable for diagnosis and near-patient testing than the traditional SPR sensors. The latest developments indicate SPRi detection as being the most promising surface plasmon-based technique fulfilling the demands for implementation in lab-on-a-chip (LOC) technologies. PMID:27314345

  16. A novel quadruplex real-time PCR method for simultaneous detection of Cry2Ae and two genetically modified cotton events (GHB119 and T304-40)

    PubMed Central

    2014-01-01

    Background To date, over 150 genetically modified (GM) crops are widely cultivated. To comply with regulations developed for genetically modified organisms (GMOs), including labeling policies, many detection methods for GMO identification and quantification have been developed. Results To detect the entrance and exit of unauthorized GM crop events in China, we developed a novel quadruplex real-time PCR method for simultaneous detection and quantification of GM cotton events GHB119 and T304-40 in cotton-derived products (based on the 5′-flanking sequence) and the insect-resistance gene Cry2Ae. The limit of detection was 10 copies for GHB119 and Cry2Ae and 25 copies for T304-40. The limit of quantification was 25 copies for GHB119 and Cry2Ae and 50 copies for T304-40. Moreover, low bias and acceptable standard deviation and relative standard deviation values were obtained in quantification analysis of six blind samples containing different GHB119 and T304-40 ingredients. Conclusions The developed quadruplex quantitative method could be used for quantitative detection of two GM cotton events (GHB119 and T304-40) and Cry2Ae gene ingredient in cotton derived products. PMID:24884946

  17. A 300-mV 220-nW event-driven ADC with real-time QRS detection for wearable ECG sensors.

    PubMed

    Zhang, Xiaoyang; Lian, Yong

    2014-12-01

    This paper presents an ultra-low-power event-driven analog-to-digital converter (ADC) with real-time QRS detection for wearable electrocardiogram (ECG) sensors in wireless body sensor network (WBSN) applications. Two QRS detection algorithms, pulse-triggered (PUT) and time-assisted PUT (t-PUT), are proposed based on the level-crossing events generated from the ADC. The PUT detector achieves 97.63% sensitivity and 97.33% positive prediction in simulation on the MIT-BIH Arrhythmia Database. The t-PUT improves the sensitivity and positive prediction to 97.76% and 98.59% respectively. Fabricated in 0.13 μm CMOS technology, the ADC with QRS detector consumes only 220 nW measured under 300 mV power supply, making it the first nanoWatt compact analog-to-information (A2I) converter with embedded QRS detector. PMID:25608283

  18. Detection of anomalous events

    DOEpatents

    Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

    2016-06-07

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

  19. Detection of solar events

    SciTech Connect

    Fischbach, Ephraim; Jenkins, Jere

    2013-08-27

    A flux detection apparatus can include a radioactive sample having a decay rate capable of changing in response to interaction with a first particle or a field, and a detector associated with the radioactive sample. The detector is responsive to a second particle or radiation formed by decay of the radioactive sample. The rate of decay of the radioactive sample can be correlated to flux of the first particle or the field. Detection of the first particle or the field can provide an early warning for an impending solar event.

  20. Microelectrode Arrays of Diamond-Insulated Graphitic Channels for Real-Time Detection of Exocytotic Events from Cultured Chromaffin Cells and Slices of Adrenal Glands.

    PubMed

    Picollo, Federico; Battiato, Alfio; Bernardi, Ettore; Marcantoni, Andrea; Pasquarelli, Alberto; Carbone, Emilio; Olivero, Paolo; Carabelli, Valentina

    2016-08-01

    A microstructured graphitic 4 × 4 multielectrode array was embedded in a single-crystal diamond substrate (4 × 4 μG-SCD MEA) for real-time monitoring of exocytotic events from cultured chromaffin cells and adrenal slices. The current approach relies on the development of a parallel ion beam lithographic technique, which assures the time-effective fabrication of extended arrays with reproducible electrode dimensions. The reported device is suitable for performing amperometric and voltammetric recordings with high sensitivity and temporal resolution, by simultaneously acquiring data from 16 rectangularly shaped microelectrodes (20 × 3.5 μm(2)) separated by 200 μm gaps. Taking advantage of the array geometry we addressed the following specific issues: (i) detect both the spontaneous and KCl-evoked secretion simultaneously from several chromaffin cells directly cultured on the device surface, (ii) resolve the waveform of different subsets of exocytotic events, and (iii) monitoring quantal secretory events from thin slices of the adrenal gland. The frequency of spontaneous release was low (0.12 and 0.3 Hz, respectively, for adrenal slices and cultured cells) and increased up to 0.9 Hz after stimulation with 30 mM KCl in cultured cells. The spike amplitude as well as rise and decay time were comparable with those measured by carbon fiber microelectrodes and allowed to identify three different subsets of secretory events associated with "full fusion" events, "kiss-and-run" and "kiss-and-stay" exocytosis, confirming that the device has adequate sensitivity and time resolution for real-time recordings. The device offers the significant advantage of shortening the time to collect data by allowing simultaneous recordings from cell populations either in primary cell cultures or in intact tissues. PMID:27376596

  1. The spectral absorption coefficient at 254 nm as a real-time early warning proxy for detecting faecal pollution events at alpine karst water resources.

    PubMed

    Stadler, H; Klock, E; Skritek, P; Mach, R L; Zerobin, W; Farnleitner, A H

    2010-01-01

    Because spring water quality from alpine karst aquifers can change very rapidly during event situations, water abstraction management has to be performed in near real-time. Four summer events (2005-2008) at alpine karst springs were investigated in detail in order to evaluate the spectral absorption coefficient at 254 nm (SAC254) as a real-time early warning proxy for faecal pollution. For the investigation Low-Earth-Orbit (LEO) Satellite-based data communication between portable hydrometeorological measuring stations and an automated microbiological sampling device was used. The method for event triggered microbial sampling and analyzing was already established and described in a previous paper. Data analysis including on-line event characterisation (i.e. precipitation, discharge, turbidity, SAC254) and comprehensive E. coli determination (n>800) indicated that SAC254 is a useful early warning proxy. Irrespective of the studied event situations SAC254 always increased 3 to 6 hours earlier than the onset of faecal pollution, featuring different correlation phases. Furthermore, it seems also possible to use SAC254 as a real-time proxy parameter for estimating the extent of faecal pollution after establishing specific spring and event-type calibrations that take into consideration the variability of the occurrence and the transferability of faecal material It should be highlighted that diffuse faecal pollution from wildlife and live stock sources was responsible for spring water contamination at the investigated catchments. In this respect, the SAC254 can also provide useful information to support microbial source tracking efforts where different situations of infiltration have to be investigated. PMID:20962406

  2. Moving Average Convergence Divergence filter preprocessing for real-time event-related peak activity onset detection : application to fNIRS signals.

    PubMed

    Durantin, Gautier; Scannella, Sebastien; Gateau, Thibault; Delorme, Arnaud; Dehais, Frederic

    2014-01-01

    Real-time solutions for noise reduction and signal processing represent a central challenge for the development of Brain Computer Interfaces (BCI). In this paper, we introduce the Moving Average Convergence Divergence (MACD) filter, a tunable digital passband filter for online noise reduction and onset detection without preliminary learning phase, used in economic markets analysis. MACD performance was tested and benchmarked with other filters using data collected with functional Near Infrared Spectoscopy (fNIRS) during a digit sequence memorization task. This filter has a good performance on filtering and real-time peak activity onset detection, compared to other techniques. Therefore, MACD could be implemented for efficient BCI design using fNIRS. PMID:25570400

  3. Development, optimization, and single laboratory validation of an event-specific real-time PCR method for the detection and quantification of Golden Rice 2 using a novel taxon-specific assay.

    PubMed

    Jacchia, Sara; Nardini, Elena; Savini, Christian; Petrillo, Mauro; Angers-Loustau, Alexandre; Shim, Jung-Hyun; Trijatmiko, Kurniawan; Kreysa, Joachim; Mazzara, Marco

    2015-02-18

    In this study, we developed, optimized, and in-house validated a real-time PCR method for the event-specific detection and quantification of Golden Rice 2, a genetically modified rice with provitamin A in the grain. We optimized and evaluated the performance of the taxon (targeting rice Phospholipase D α2 gene)- and event (targeting the 3' insert-to-plant DNA junction)-specific assays that compose the method as independent modules, using haploid genome equivalents as unit of measurement. We verified the specificity of the two real-time PCR assays and determined their dynamic range, limit of quantification, limit of detection, and robustness. We also confirmed that the taxon-specific DNA sequence is present in single copy in the rice genome and verified its stability of amplification across 132 rice varieties. A relative quantification experiment evidenced the correct performance of the two assays when used in combination. PMID:25588469

  4. Automated Detection of Events of Scientific Interest

    NASA Technical Reports Server (NTRS)

    James, Mark

    2007-01-01

    A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

  5. Real-time measurements, rare events and photon economics

    NASA Astrophysics Data System (ADS)

    Jalali, B.; Solli, D. R.; Goda, K.; Tsia, K.; Ropers, C.

    2010-07-01

    Rogue events otherwise known as outliers and black swans are singular, rare, events that carry dramatic impact. They appear in seemingly unconnected systems in the form of oceanic rogue waves, stock market crashes, evolution, and communication systems. Attempts to understand the underlying dynamics of such complex systems that lead to spectacular and often cataclysmic outcomes have been frustrated by the scarcity of events, resulting in insufficient statistical data, and by the inability to perform experiments under controlled conditions. Extreme rare events also occur in ultrafast physical sciences where it is possible to collect large data sets, even for rare events, in a short time period. The knowledge gained from observing rare events in ultrafast systems may provide valuable insight into extreme value phenomena that occur over a much slower timescale and that have a closer connection with human experience. One solution is a real-time ultrafast instrument that is capable of capturing singular and randomly occurring non-repetitive events. The time stretch technology developed during the past 13 years is providing a powerful tool box for reaching this goal. This paper reviews this technology and discusses its use in capturing rogue events in electronic signals, spectroscopy, and imaging. We show an example in nonlinear optics where it was possible to capture rare and random solitons whose unusual statistical distribution resemble those observed in financial markets. The ability to observe the true spectrum of each event in real time has led to important insight in understanding the underlying process, which in turn has made it possible to control soliton generation leading to improvement in the coherence of supercontinuum light. We also show a new class of fast imagers which are being considered for early detection of cancer because of their potential ability to detect rare diseased cells (so called rogue cells) in a large population of healthy cells.

  6. Applications to Real World Time Series Event detection, multimodality and non-stationarity: Ordinal patterns, a tool to rule them all?

    NASA Astrophysics Data System (ADS)

    Arroyo, D.; Chamorro, P.; Amigó, J. M.; Rodríguez, F. B.; Varona, P.

    2013-06-01

    In this work, we apply ordinal analysis of time series to the characterisation of neuronal activity. Automatic event detection is performed by means of the so-called permutation entropy, along with the quantification of the relative cardinality of forbidden patterns. In addition, multivariate time series are characterised using the joint permutation entropy. In order to illustrate the suitability of the ordinal analysis for characterising neurophysiological data, we have compared the measures based on ordinal patterns of time series to the tools typically used in the context of neurophysiology.

  7. Event rates for WIMP detection

    SciTech Connect

    Vergados, J. D.; Moustakidis, Ch. C.; Oikonomou, V.

    2006-11-28

    The event rates for the direct detection of dark matter for various types of WIMPs are presented. In addition to the neutralino of SUSY models, we considered other candidates (exotic scalars as well as particles in Kaluza-Klein and technicolour theories) with masses in the TeV region. Then one finds reasonable branching ratios to excited states. Thus the detection of the WIMP can be made not only by recoil measurements, by measuring the de-excitation {gamma}-rays as well.

  8. GPU Accelerated Event Detection Algorithm

    Energy Science and Technology Software Center (ESTSC)

    2011-05-25

    Smart grid external require new algorithmic approaches as well as parallel formulations. One of the critical components is the prediction of changes and detection of anomalies within the power grid. The state-of-the-art algorithms are not suited to handle the demands of streaming data analysis. (i) need for events detection algorithms that can scale with the size of data, (ii) need for algorithms that can not only handle multi dimensional nature of the data, but alsomore » model both spatial and temporal dependencies in the data, which, for the most part, are highly nonlinear, (iii) need for algorithms that can operate in an online fashion with streaming data. The GAEDA code is a new online anomaly detection techniques that take into account spatial, temporal, multi-dimensional aspects of the data set. The basic idea behind the proposed approach is to (a) to convert a multi-dimensional sequence into a univariate time series that captures the changes between successive windows extracted from the original sequence using singular value decomposition (SVD), and then (b) to apply known anomaly detection techniques for univariate time series. A key challenge for the proposed approach is to make the algorithm scalable to huge datasets by adopting techniques from perturbation theory, incremental SVD analysis. We used recent advances in tensor decomposition techniques which reduce computational complexity to monitor the change between successive windows and detect anomalies in the same manner as described above. Therefore we propose to develop the parallel solutions on many core systems such as GPUs, because these algorithms involve lot of numerical operations and are highly data-parallelizable.« less

  9. Detecting Adverse Events Using Information Technology

    PubMed Central

    Bates, David W.; Evans, R. Scott; Murff, Harvey; Stetson, Peter D.; Pizziferri, Lisa; Hripcsak, George

    2003-01-01

    Context: Although patient safety is a major problem, most health care organizations rely on spontaneous reporting, which detects only a small minority of adverse events. As a result, problems with safety have remained hidden. Chart review can detect adverse events in research settings, but it is too expensive for routine use. Information technology techniques can detect some adverse events in a timely and cost-effective way, in some cases early enough to prevent patient harm. Objective: To review methodologies of detecting adverse events using information technology, reports of studies that used these techniques to detect adverse events, and study results for specific types of adverse events. Design: Structured review. Methodology: English-language studies that reported using information technology to detect adverse events were identified using standard techniques. Only studies that contained original data were included. Main Outcome Measures: Adverse events, with specific focus on nosocomial infections, adverse drug events, and injurious falls. Results: Tools such as event monitoring and natural language processing can inexpensively detect certain types of adverse events in clinical databases. These approaches already work well for some types of adverse events, including adverse drug events and nosocomial infections, and are in routine use in a few hospitals. In addition, it appears likely that these techniques will be adaptable in ways that allow detection of a broad array of adverse events, especially as more medical information becomes computerized. Conclusion: Computerized detection of adverse events will soon be practical on a widespread basis. PMID:12595401

  10. Phase-Space Detection of Cyber Events

    SciTech Connect

    Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J; Hively, Lee M

    2015-01-01

    Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The data analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.

  11. Asynchronous event-based corner detection and matching.

    PubMed

    Clady, Xavier; Ieng, Sio-Hoi; Benosman, Ryad

    2015-06-01

    This paper introduces an event-based luminance-free method to detect and match corner events from the output of asynchronous event-based neuromorphic retinas. The method relies on the use of space-time properties of moving edges. Asynchronous event-based neuromorphic retinas are composed of autonomous pixels, each of them asynchronously generating "spiking" events that encode relative changes in pixels' illumination at high temporal resolutions. Corner events are defined as the spatiotemporal locations where the aperture problem can be solved using the intersection of several geometric constraints in events' spatiotemporal spaces. A regularization process provides the required constraints, i.e. the motion attributes of the edges with respect to their spatiotemporal locations using local geometric properties of visual events. Experimental results are presented on several real scenes showing the stability and robustness of the detection and matching. PMID:25828960

  12. Crowd Event Detection on Optical Flow Manifolds.

    PubMed

    Rao, Aravinda S; Gubbi, Jayavardhana; Marusic, Slaven; Palaniswami, Marimuthu

    2016-07-01

    Analyzing crowd events in a video is key to understanding the behavioral characteristics of people (humans). Detecting crowd events in videos is challenging because of articulated human movements and occlusions. The aim of this paper is to detect the events in a probabilistic framework for automatically interpreting the visual crowd behavior. In this paper, crowd event detection and classification in optical flow manifolds (OFMs) are addressed. A new algorithm to detect walking and running events has been proposed, which uses optical flow vector lengths in OFMs. Furthermore, a new algorithm to detect merging and splitting events has been proposed, which uses Riemannian connections in the optical flow bundle (OFB). The longest vector from the OFB provides a key feature for distinguishing walking and running events. Using a Riemannian connection, the optical flow vectors are parallel transported to localize the crowd groups. The geodesic lengths among the groups provide a criterion for merging and splitting events. Dispersion and evacuation events are jointly modeled from the walking/running and merging/splitting events. Our results show that the proposed approach delivers a comparable model to detect crowd events. Using the performance evaluation of tracking and surveillance 2009 dataset, the proposed method is shown to produce the best results in merging, splitting, and dispersion events, and comparable results in walking, running, and evacuation events when compared with other methods. PMID:26219100

  13. Event oriented dictionary learning for complex event detection.

    PubMed

    Yan, Yan; Yang, Yi; Meng, Deyu; Liu, Gaowen; Tong, Wei; Hauptmann, Alexander G; Sebe, Nicu

    2015-06-01

    Complex event detection is a retrieval task with the goal of finding videos of a particular event in a large-scale unconstrained Internet video archive, given example videos and text descriptions. Nowadays, different multimodal fusion schemes of low-level and high-level features are extensively investigated and evaluated for the complex event detection task. However, how to effectively select the high-level semantic meaningful concepts from a large pool to assist complex event detection is rarely studied in the literature. In this paper, we propose a novel strategy to automatically select semantic meaningful concepts for the event detection task based on both the events-kit text descriptions and the concepts high-level feature descriptions. Moreover, we introduce a novel event oriented dictionary representation based on the selected semantic concepts. Toward this goal, we leverage training images (frames) of selected concepts from the semantic indexing dataset with a pool of 346 concepts, into a novel supervised multitask lp -norm dictionary learning framework. Extensive experimental results on TRECVID multimedia event detection dataset demonstrate the efficacy of our proposed method. PMID:25794390

  14. Adaptive noise estimation and suppression for improving microseismic event detection

    NASA Astrophysics Data System (ADS)

    Mousavi, S. Mostafa; Langston, Charles A.

    2016-09-01

    Microseismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. A noise level estimation and noise reduction algorithm is presented for microseismic data analysis based upon minimally controlled recursive averaging and neighborhood shrinkage estimators. The method might not be compared with more sophisticated and computationally expensive denoising algorithm in terms of preserving detailed features of seismic signal. However, it is fast and data-driven and can be applied in real-time processing of continuous data for event detection purposes. Results from application of this algorithm to synthetic and real seismic data show that it holds a great promise for improving microseismic event detection.

  15. Children's Eyewitness Memory for Multiple Real-Life Events

    ERIC Educational Resources Information Center

    Odegard, Timothy N.; Cooper, Crystal M.; Lampinen, James M.; Reyna, Valerie F.; Brainerd, Charles J.

    2009-01-01

    The present research examined the influence of prior knowledge on children's free recall, cued recall, recognition memory, and source memory judgments for a series of similar real-life events. Forty children (5-12 years old) attended 4 thematic birthday parties and were later interviewed about the events that transpired during the parties using…

  16. Detection of dominant flow and abnormal events in surveillance video

    NASA Astrophysics Data System (ADS)

    Kwak, Sooyeong; Byun, Hyeran

    2011-02-01

    We propose an algorithm for abnormal event detection in surveillance video. The proposed algorithm is based on a semi-unsupervised learning method, a kind of feature-based approach so that it does not detect the moving object individually. The proposed algorithm identifies dominant flow without individual object tracking using a latent Dirichlet allocation model in crowded environments. It can also automatically detect and localize an abnormally moving object in real-life video. The performance tests are taken with several real-life databases, and their results show that the proposed algorithm can efficiently detect abnormally moving objects in real time. The proposed algorithm can be applied to any situation in which abnormal directions or abnormal speeds are detected regardless of direction.

  17. Object detection in real-time

    NASA Astrophysics Data System (ADS)

    Solder, Ulrich; Graefe, Volker

    1991-03-01

    An algorithm working on monocular gray-scale image sequences for object detection combined with a road tracker is presented. This algorithm appropriate for the real-time demands of an autonomous car driving with speeds over 40 km/h may be used for triggering obstacle avoidance maneuvers such as coming to a safe stop automatically in front of an obstacle or following another car. Moving and static objects have been detected in real-world experiments on various types of roads even under unfavorable weather conditions. . Morgenthaler and

  18. Real-time hyperspectral detection and cuing

    NASA Astrophysics Data System (ADS)

    Stellman, Christopher M.; Hazel, Geoff; Bucholtz, Frank; Michalowicz, Joseph V.; Stocker, Alan D.; Schaaf, William

    2000-07-01

    The Dark HORSE 1 (Hyperspectral Overhead Reconnaissance and Surveillance Experiment 1) flight test has demonstrated autonomous, real-time visible hyperspectral detection of military ground targets with real-time cuing of a high- resolution framing camera. An overview of the Dark HORSE 1 hyperspectral sensor system is presented. The system hardware components are described in detail, with an emphasis on the visible hyperspectral sensor and the real- time processor. Descriptions of system software and processing methods are also provided. The recent field experiment in which the Dark HORSE 1 system was employed is described in detail along with an analysis of the collected data. The results evince per-pixel false-alarm rates on the order of 10-5/km2, and demonstrate the improved performance obtained by operating two detection algorithms simultaneously.

  19. Context-aware event detection smartphone application for first responders

    NASA Astrophysics Data System (ADS)

    Boddhu, Sanjay K.; Dave, Rakesh P.; McCartney, Matt; West, James A.; Williams, Robert L.

    2013-05-01

    The rise of social networking platforms like Twitter, Facebook, etc…, have provided seamless sharing of information (as chat, video and other media) among its user community on a global scale. Further, the proliferation of the smartphones and their connectivity networks has powered the ordinary individuals to share and acquire information regarding the events happening in his/her immediate vicinity in a real-time fashion. This human-centric sensed data being generated in "human-as-sensor" approach is tremendously valuable as it delivered mostly with apt annotations and ground truth that would be missing in traditional machine-centric sensors, besides high redundancy factor (same data thru multiple users). Further, when appropriately employed this real-time data can support in detecting localized events like fire, accidents, shooting, etc…, as they unfold and pin-point individuals being affected by those events. This spatiotemporal information, when made available for first responders in the event vicinity (or approaching it) can greatly assist them to make effective decisions to protect property and life in a timely fashion. In this vein, under SATE and YATE programs, the research team at AFRL Tec^Edge Discovery labs had demonstrated the feasibility of developing Smartphone applications, that can provide a augmented reality view of the appropriate detected events in a given geographical location (localized) and also provide an event search capability over a large geographic extent. In its current state, the application thru its backend connectivity utilizes a data (Text & Image) processing framework, which deals with data challenges like; identifying and aggregating important events, analyzing and correlating the events temporally and spatially and building a search enabled event database. Further, the smartphone application with its backend data processing workflow has been successfully field tested with live user generated feeds.

  20. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

    Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

  1. A real-time assessment of factors influencing medication events.

    PubMed

    Dollarhide, Adrian W; Rutledge, Thomas; Weinger, Matthew B; Fisher, Erin Stucky; Jain, Sonia; Wolfson, Tanya; Dresselhaus, Timothy R

    2014-01-01

    Reducing medical error is critical to improving the safety and quality of healthcare. Physician stress, fatigue, and excessive workload are performance-shaping factors (PSFs) that may influence medical events (actual administration errors and near misses), but direct relationships between these factors and patient safety have not been clearly defined. This study assessed the real-time influence of emotional stress, workload, and sleep deprivation on self-reported medication events by physicians in academic hospitals. During an 18-month study period, 185 physician participants working at four university-affiliated teaching hospitals reported medication events using a confidential reporting application on handheld computers. Emotional stress scores, perceived workload, patient case volume, clinical experience, total sleep, and demographic variables were also captured via the handheld computers. Medication event reports (n = 11) were then correlated with these demographic and PSFs. Medication events were associated with 36.1% higher perceived workload (p < .05), 38.6% higher inpatient caseloads (p < .01), and 55.9% higher emotional stress scores (p < .01). There was a trend for reported events to also be associated with less sleep (p = .10). These results confirm the effect of factors influencing medication events, and support attention to both provider and hospital environmental characteristics for improving patient safety. PMID:23551380

  2. Context and quality estimation in video for enhanced event detection

    NASA Astrophysics Data System (ADS)

    Irvine, John M.; Wood, Richard J.

    2015-05-01

    Numerous practical applications for automated event recognition in video rely on analysis of the objects and their associated motion, i.e., the kinematics of the scene. The ability to recognize events in practice depends on accurate tracking objects of interest in the video data and accurate recognition of changes relative to the background. Numerous factors can degrade the performance of automated algorithms. Our object detection and tracking algorithms estimate the object position and attributes within the context of a dynamic assessment of video quality, to provide more reliable event recognition under challenging conditions. We present an approach to robustly modeling the image quality which informs tuning parameters to use for a given video stream. The video quality model rests on a suite of image metrics computed in real-time from the video. We will describe the formulation of the image quality model. Results from a recent experiment will quantify the empirical performance for recognition of events of interest.

  3. Real Time Detection of Foodborne Pathogens

    NASA Astrophysics Data System (ADS)

    Velusamy, V.; Arshak, K.; Korostynka, O.; Vaseashta, Ashok; Adley, C.

    Contamination of foods by harmful bacteria by natural events or malicious intent poses a serious threat to public health and safety. This review introduces current technologies in detecting pathogens in food and foodborne illnesses. Causes of foodborne diseases and trends impacting foodborne diseases such as globalization and changes in micro-organisms, human populations, lifestyles, and climates are addressed. In addition, a review of the limitations in detecting pathogens with conventional technologies is presented. Finally, a review of nanostructured and nanomaterials based sensing technologies by pathogen, detection limits, and advantages is described.

  4. Children's eyewitness memory for multiple real-life events.

    PubMed

    Odegard, Timothy N; Cooper, Crystal M; Lampinen, James M; Reyna, Valerie F; Brainerd, Charles J

    2009-01-01

    The present research examined the influence of prior knowledge on children's free recall, cued recall, recognition memory, and source memory judgments for a series of similar real-life events. Forty children (5-12 years old) attended 4 thematic birthday parties and were later interviewed about the events that transpired during the parties using the National Institute of Child Health and Human Development protocol. Of the events, half were generic in that they could have occurred at any birthday party, and half were specific to the theme of the party. Older children demonstrated more evidence of using gist-based information to guide their memory performance than did younger children. However, younger children were able to use global gist to inform their source memory judgments, qualifying past word-learning research. PMID:19930357

  5. Phenological Event Detection from Multitemporal Image Data

    SciTech Connect

    Vatsavai, Raju

    2009-01-01

    Monitoring biomass over large geographic regions for seasonal changes in vegetation and crop phenology is important for many applications. In this paper we a present a novel clustering based change detection method using MODIS NDVI time series data. We used well known EM technique to find GMM parameters and Bayesian Information Criteria (BIC) for determining the number of clusters. KL Divergence measure is then used to establish the cluster correspondence across two years (2001 and 2006) to determine changes between these two years. The changes identied were further analyzed for understanding phenological events. This preliminary study shows interesting relationships between key phenological events such as onset, length, end of growing seasons.

  6. Global grid of master events for waveform cross-correlation: from testing to real time processing

    NASA Astrophysics Data System (ADS)

    Bobrov, Dmitry; Rozhkov, Mikhail; Kitov, Ivan

    2014-05-01

    Seismic monitoring of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) requires a globally uniform detection threshold, which is provided by geographical distribution of the Primary Seismic Network of the International Monitoring System (IMS). This detection threshold has to be as low as allowed by the entire set of real time and historical data recorded by the IMS. The International Data Centre (IDC) analyzes all relevant data in automatic processing and interactive review to issue a Reviewed Event Bulletin (REB), which includes all qualified events as obtained for the purpose of nuclear test monitoring. Since 2000, raw data, individual detections, and created events are saved in the IDC archive currently reaching tens of terabyte. In order to effectively use this archive in global monitoring we introduced the waveform cross correlation (matched filter) technique. Cross correlation between real time records at IMS stations and template waveforms is calculated for a dense (spacing of ~ 140 km) and regular grid of master events uniformly covering the globe. There are approximately 25,000 master events with 3 to 10 templates at IMS stations. In seismically active zones, we populate masters with real waveforms. For aseismic zones, we develop an extended set of synthetic templates for virtual master events. For optimal performance of cross correlation, the Principal and Independent Component Analysis are applied to the historical (from earthquakes and underground nuclear tests) and synthetic waveforms. Real waveform templates and selected PCA/ICA components are used in automatic processing for the production of a tentative cross-correlation standard event list (XSEL).

  7. Detection and recognition of indoor smoking events

    NASA Astrophysics Data System (ADS)

    Bien, Tse-Lun; Lin, Chang Hong

    2013-03-01

    Smoking in public indoor spaces has become prohibited in many countries since it not only affects the health of the people around you, but also increases the risk of fire outbreaks. This paper proposes a novel scheme to automatically detect and recognize smoking events by using exsiting surveillance cameras. The main idea of our proposed method is to detect human smoking events by recognizing their actions. In this scheme, the human pose estimation is introduced to analyze human actions from their poses. The human pose estimation method segments head and both hands from human body parts by using a skin color detection method. However, the skin color methods may fail in insufficient light conditions. Therefore, the lighting compensation is applied to help the skin color detection method become more accurate. Due to the human body parts may be covered by shadows, which may cause the human pose estimation to fail, the Kalman filter is applied to track the missed body parts. After that, we evaluate the probability features of hands approaching the head. The support vector machine (SVM) is applied to learn and recognize the smoking events by the probability features. To analysis the performance of proposed method, the datasets established in the survillance camera view under indoor enviroment are tested. The experimental results show the effectiveness of our proposed method with accuracy rate of 83.33%.

  8. Developing Situational Learning Events: A Practical Merger of Real-Life Events with Content Instruction.

    ERIC Educational Resources Information Center

    Salyer, B. Keith; Thyfault, Alberta

    This paper discusses the value of merging real-life events with content instruction and provides six sample lessons to illustrate such instruction. A brief review of the literature notes historic recognition of the importance of applied learning, the issue of retention and transfer of learning, the approach of using content relevant experiences…

  9. Real-Time Multimission Event Notification System for Mars Relay

    NASA Technical Reports Server (NTRS)

    Wallick, Michael N.; Allard, Daniel A.; Gladden, Roy E.; Wang, Paul; Hy, Franklin H.

    2013-01-01

    As the Mars Relay Network is in constant flux (missions and teams going through their daily workflow), it is imperative that users are aware of such state changes. For example, a change by an orbiter team can affect operations on a lander team. This software provides an ambient view of the real-time status of the Mars network. The Mars Relay Operations Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay Network. As part of MaROS, a feature set was developed that operates on several levels of the software architecture. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. The result is a real-time event notification and management system, so mission teams can track and act upon events on a moment-by-moment basis. This software retrieves events from MaROS and displays them to the end user. Updates happen in real time, i.e., messages are pushed to the user while logged into the system, and queued when the user is not online for later viewing. The software does not do away with the email notifications, but augments them with in-line notifications. Further, this software expands the events that can generate a notification, and allows user-generated notifications. Existing software sends a smaller subset of mission-generated notifications via email. A common complaint of users was that the system-generated e-mails often "get lost" with other e-mail that comes in. This software allows for an expanded set (including user-generated) of notifications displayed in-line of the program. By separating notifications, this can improve a user's workflow.

  10. Application of Kalman Filtering Techniques for Microseismic Event Detection

    NASA Astrophysics Data System (ADS)

    Baziw, E.; Weir-Jones, I.

    - Microseismic monitoring systems are generally installed in areas of induced seismicity caused by human activity. Induced seismicity results from changes in the state of stress which may occur as a result of excavation within the rock mass in mining (i.e., rockbursts), and changes in hydrostatic pressures and rock temperatures (e.g., during fluid injection or extraction) in oil exploitation, dam construction or fluid disposal. Microseismic monitoring systems determine event locations and important source parameters such as attenuation, seismic moment, source radius, static stress drop, peak particle velocity and seismic energy. An essential part of the operation of a microseismic monitoring system is the reliable detection of microseismic events. In the absence of reliable, automated picking techniques, operators rely upon manual picking. This is time-consuming, costly and, in the presence of background noise, very prone to error. The techniques described in this paper not only permit the reliable identification of events in cluttered signal environments they have also enabled the authors to develop reliable automated event picking procedures. This opens the way to use microseismic monitoring as a cost-effective production/operations procedure. It has been the experience of the authors that in certain noisy environments, the seismic monitoring system may trigger on and subsequently acquire substantial quantities of erroneous data, due to the high energy content of the ambient noise. Digital filtering techniques need to be applied on the microseismic data so that the ambient noise is removed and event detection simplified. The monitoring of seismic acoustic emissions is a continuous, real-time process and it is desirable to implement digital filters which can also be designed in the time domain and in real-time such as the Kalman Filter. This paper presents a real-time Kalman Filter which removes the statistically describable background noise from the recorded

  11. Real-Time Detection of Optical Transients with RAPTOR

    NASA Astrophysics Data System (ADS)

    Borozdin, Konstantin N.; Brumby, Steven P.; Galassi, Mark C.; McGowan, Katherine; Starr, Daniel; Vestrand, Thomas; White, Robert; Wozniak, Przemek; Wren, James A.

    2002-12-01

    Fast variability of optical objects is an interesting though poorly explored subject in modern astronomy. Real-time data processing and identification of transient celestial events in the images is very important for such study as it allows rapid follow-up with more sensitive instruments. We discuss an approach which we have developed for the RAPTOR project, a pioneering closed-loop system combining real-time transient detection with rapid follow-up. RAPTOR's data processing pipeline is able to identify and localize an optical transient within seconds after the observation. The testing we performed so far have been confirming the effectiveness of our method for the optical transient detection. The software pipeline we have developed for RAPTOR can easily be applied to the data from other experiments.

  12. Development of the IDC Infrasound Event Detection Pipeline

    NASA Astrophysics Data System (ADS)

    Mialle, P.; Bittner, P.; Brown, D.; Given, J. W.

    2012-12-01

    The first atmospheric event built only from infrasound arrivals was reported in the Reviewed Event Bulletin (REB) of the International Data Centre (IDC) of the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO) in 2003. In the subsequent decade, 45 infrasound stations from the International Monitoring System (IMS) have been installed and are transmitting continuous data to the IDC. The growing amount of infrasound data and detections produced by the automatic system challenges the station and network processing at the IDC and requires the Organization to improve the infrasound data processing. In 2010, the IDC began full-time operational automatic processing of infrasound data followed by interactive analysis. The detected and located events are systematically included in the analyst-reviewed Late Event Bulletin (LEB) and REB. Approximately 16% of SEL3 (Selected Event List 3, automatically produced 6 hours after real-time) events with associated infrasound signals pass interactive analysis and make it to the IDC bulletins. 41% of those SEL3 events rejected after review have only 2 associated infrasound phases (and possibly other seismic and hydro-acoustic detections). Therefore, the process whereby infrasound detections are associated with events needs to be investigated further. The objective of this study is to reduce the number of associated infrasound arrivals that are falsely associated during the creation of the SEL3. There are two parts to the study. First, the detection accuracy at the infrasound arrays is improved by improving the infrasound signal detector, which is based on the PMCC (Progressive Multi-Channel Correlation) algorithm. The second part focuses on improving the reliability of the association algorithm. The association algorithm is enhanced to include better characterization of the variable atmospheric phenomena, which profoundly affect the detection patterns of the infrasound signals. The algorithm is then further tuned to reduce the

  13. LAN attack detection using Discrete Event Systems.

    PubMed

    Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

    2011-01-01

    Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed. PMID:20804980

  14. WCEDS: A waveform correlation event detection system

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Trujillo, J.R.; Withers, M.M.; Aster, R.C.; Astiz, L.; Shearer, P.M.

    1995-08-01

    We have developed a working prototype of a grid-based global event detection system based on waveform correlation. The algorithm comes from a long-period detector but we have recast it in a full matrix formulation which can reduce the number of multiplications needed by better than two orders of magnitude for realistic monitoring scenarios. The reduction is made possible by eliminating redundant multiplications in the original formulation. All unique correlations for a given origin time are stored in a correlation matrix (C) which is formed by a full matrix product of a Master Image matrix (M) and a data matrix (D). The detector value at each grid point is calculated by following a different summation path through the correlation matrix. Master Images can be derived either empirically or synthetically. Our testing has used synthetic Master Images because their influence on the detector is easier to understand. We tested the system using the matrix formulation with continuous data from the IRIS (Incorporate Research Institutes for Seismology) broadband global network to monitor a 2 degree evenly spaced surface grid with a time discretization of 1 sps; we successfully detected the largest event in a two hour segment from October 1993. The output at the correct gridpoint was at least 33% larger than at adjacent grid points, and the output at the correct gridpoint at the correct origin time was more than 500% larger than the output at the same gridpoint immediately before or after. Analysis of the C matrix for the origin time of the event demonstrates that there are many significant ``false`` correlations of observed phases with incorrect predicted phases. These false correlations dull the sensitivity of the detector and so must be dealt with if our system is to attain detection thresholds consistent with a Comprehensive Test Ban Treaty (CTBT).

  15. Machine learning for real time remote detection

    NASA Astrophysics Data System (ADS)

    Labbé, Benjamin; Fournier, Jérôme; Henaff, Gilles; Bascle, Bénédicte; Canu, Stéphane

    2010-10-01

    Infrared systems are key to providing enhanced capability to military forces such as automatic control of threats and prevention from air, naval and ground attacks. Key requirements for such a system to produce operational benefits are real-time processing as well as high efficiency in terms of detection and false alarm rate. These are serious issues since the system must deal with a large number of objects and categories to be recognized (small vehicles, armored vehicles, planes, buildings, etc.). Statistical learning based algorithms are promising candidates to meet these requirements when using selected discriminant features and real-time implementation. This paper proposes a new decision architecture benefiting from recent advances in machine learning by using an effective method for level set estimation. While building decision function, the proposed approach performs variable selection based on a discriminative criterion. Moreover, the use of level set makes it possible to manage rejection of unknown or ambiguous objects thus preserving the false alarm rate. Experimental evidences reported on real world infrared images demonstrate the validity of our approach.

  16. Near Real Time Ship Detection Experiments

    NASA Astrophysics Data System (ADS)

    Brusch, S.; Lehner, S.; Schwarz, E.; Fritz, T.

    2010-04-01

    A new Near Real Time (NRT) ship detection processor SAINT (SAR AIS Integrated Toolbox) was developed in the framework of the ESA project MARISS. Data are received at DLRs ground segment DLR-BN (Neustrelitz, Germany). Results of the ship detection are available on ftp server within 30 min after the acquisition started. The detectability of ships on Synthetic Aperture Radar (SAR) ERS-2, ENVISAT ASAR and TerraSAR-X (TS-X) images is validated by coastal (live) AIS and space AIS. The monitoring areas chosen for surveillance are the North-, Baltic Sea, and Cape Town. The detectability in respect to environmental parameters like wind field, sea state, currents and changing coastlines due to tidal effects is investigated. In the South Atlantic a tracking experiment of the German research vessel Polarstern has been performed. Issues of piracy in particular in respect to ships hijacked at the Somali coast are discussed. Some examples using high resolution images from TerraSAR-X are given.

  17. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    DOE PAGESBeta

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events thatmore » generated the phase picks.« less

  18. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    SciTech Connect

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events that generated the phase picks.

  19. Rare Event Detection Algorithm Of Water Quality

    NASA Astrophysics Data System (ADS)

    Ungs, M. J.

    2011-12-01

    A novel method is presented describing the development and implementation of an on-line water quality event detection algorithm. An algorithm was developed to distinguish between normal variation in water quality parameters and changes in these parameters triggered by the presence of contaminant spikes. Emphasis is placed on simultaneously limiting the number of false alarms (which are called false positives) that occur and the number of misses (called false negatives). The problem of excessive false alarms is common to existing change detection algorithms. EPA's standard measure of evaluation for event detection algorithms is to have a false alarm rate of less than 0.5 percent and a false positive rate less than 2 percent (EPA 817-R-07-002). A detailed description of the algorithm's development is presented. The algorithm is tested using historical water quality data collected by a public water supply agency at multiple locations and using spiking contaminants developed by the USEPA, Water Security Division. The water quality parameters of specific conductivity, chlorine residual, total organic carbon, pH, and oxidation reduction potential are considered. Abnormal data sets are generated by superimposing water quality changes on the historical or baseline data. Eddies-ET has defined reaction expressions which specify how the peak or spike concentration of a particular contaminant affects each water quality parameter. Nine default contaminants (Eddies-ET) were previously derived from pipe-loop tests performed at EPA's National Homeland Security Research Center (NHSRC) Test and Evaluation (T&E) Facility. A contaminant strength value of approximately 1.5 is considered to be a significant threat. The proposed algorithm has been able to achieve a combined false alarm rate of less than 0.03 percent for both false positives and for false negatives using contaminant spikes of strength 2 or more.

  20. Real-time detection of optical transients with RAPTOR

    SciTech Connect

    Borozdin, K. N.; Brumby, Steven P.; Galassi, M. C.; McGowan, K. E.; Starr, D. L.; Vestrand, W. T.; White, R. R.; Wozniak, P. R.; Wren, J.

    2002-01-01

    Fast variability of optical objects is an interesting though poorly explored subject in modern astronomy. Real-time data processing and identification of transient, celestial events in the images is very important, for such study as it allows rapid follow-up with more sensitive instruments, We discuss an approach which we have chosen for the RAPTOR project which is a pioneering close-loop system combining real-time transient detection with rapid follow-up. Our data processing pipeline is able to identify and localize an optical transient within seconds after the observation. We describe the challenges we met, solutions we found and some results obtained in our search for fast optical transients. The software pipeline we have developed for RAPTOR can easily be applied to the data from other experiments.

  1. The waveform correlation event detection system project: Issues in system refinement, tuning, and operation

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Harris, J.M.; Moore, S.G.; Trujillo, J.R.; Withers, M.M.; Aster, R.C.

    1996-08-01

    The goal of the Waveform Correlation Event Detection System (WCEDS) Project at Sandia Labs has been to develop a prototype of a full-waveform correlation based seismic event detection system which could be used to assess potential usefulness for CTBT monitoring. The current seismic event detection system in use at the IDC is very sophisticated and provides good results but there is still significant room for improvement, particularly in reducing the number of false events (currently being nearly equal to the number of real events). Our first prototype was developed last year and since then we have used it for extensive testing from which we have gained considerable insight. The original prototype was based on a long-period detector designed by Shearer (1994), but it has been heavily modified to address problems encountered in application to a data set from the Incorporated Research Institutes for Seismology (IRIS) broadband global network. Important modifications include capabilities for event masking and iterative event detection, continuous near-real time execution, improved Master Image creation, and individualized station pre-processing. All have been shown to improve bulletin quality. In some cases the system has detected marginal events which may not be detectable by traditional detection systems, but definitive conclusions cannot be made without direct comparisons. For this reason future work will focus on using the system to process GSETT3 data for comparison with current event detection systems at the IDC.

  2. Nonthreshold-based event detection for 3d environment monitoring in sensor networks

    SciTech Connect

    Li, M.; Liu, Y.H.; Chen, L.

    2008-12-15

    Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.

  3. Real-Time Detection of a Virus Using Detection Dogs.

    PubMed

    Angle, T Craig; Passler, Thomas; Waggoner, Paul L; Fischer, Terrence D; Rogers, Bart; Galik, Patricia K; Maxwell, Herris S

    2015-01-01

    Viral infections are ubiquitous in humans, animals, and plants. Real-time methods to identify viral infections are limited and do not exist for use in harsh or resource-constrained environments. Previous research identified that tissues produce unique volatile organic compounds (VOC) and demonstrated that VOC concentrations change during pathologic states, including infection, neoplasia, or metabolic disease. Patterns of VOC expression may be pathogen specific and may be associated with an odor that could be used for disease detection. We investigated the ability of two trained dogs to detect cell cultures infected with bovine viral diarrhea virus (BVDV) and to discriminate BVDV-infected cell cultures from uninfected cell cultures and from cell cultures infected with bovine herpes virus 1 (BHV 1) and bovine parainfluenza virus 3 (BPIV 3). Dogs were trained to recognize cell cultures infected with two different biotypes of BVDV propagated in Madin-Darby bovine kidney cells using one of three culture media. For detection trials, one target and seven distractors were presented on a scent wheel by a dog handler unaware of the location of targets and distractors. Detection of BVDV-infected cell cultures by Dog 1 had a diagnostic sensitivity of 0.850 (95% CI: 0.701-0.942), which was lower than Dog 2 (0.967, 95% CI: 0.837-0.994). Both dogs exhibited very high diagnostic specificity (0.981, 95% CI: 0.960-0.993) and (0.993, 95% CI: 0.975-0.999), respectively. These findings demonstrate that trained dogs can differentiate between cultured cells infected with BVDV, BHV1, and BPIV3 and are a realistic real-time mobile pathogen sensing technology for viral pathogens. The ability to discriminate between target and distractor samples plausibly results from expression of unique VOC patterns in virus-infected and -uninfected cells. PMID:26779494

  4. Real-Time Detection of a Virus Using Detection Dogs

    PubMed Central

    Angle, T. Craig; Passler, Thomas; Waggoner, Paul L.; Fischer, Terrence D.; Rogers, Bart; Galik, Patricia K.; Maxwell, Herris S.

    2016-01-01

    Viral infections are ubiquitous in humans, animals, and plants. Real-time methods to identify viral infections are limited and do not exist for use in harsh or resource-constrained environments. Previous research identified that tissues produce unique volatile organic compounds (VOC) and demonstrated that VOC concentrations change during pathologic states, including infection, neoplasia, or metabolic disease. Patterns of VOC expression may be pathogen specific and may be associated with an odor that could be used for disease detection. We investigated the ability of two trained dogs to detect cell cultures infected with bovine viral diarrhea virus (BVDV) and to discriminate BVDV-infected cell cultures from uninfected cell cultures and from cell cultures infected with bovine herpes virus 1 (BHV 1) and bovine parainfluenza virus 3 (BPIV 3). Dogs were trained to recognize cell cultures infected with two different biotypes of BVDV propagated in Madin–Darby bovine kidney cells using one of three culture media. For detection trials, one target and seven distractors were presented on a scent wheel by a dog handler unaware of the location of targets and distractors. Detection of BVDV-infected cell cultures by Dog 1 had a diagnostic sensitivity of 0.850 (95% CI: 0.701–0.942), which was lower than Dog 2 (0.967, 95% CI: 0.837–0.994). Both dogs exhibited very high diagnostic specificity (0.981, 95% CI: 0.960–0.993) and (0.993, 95% CI: 0.975–0.999), respectively. These findings demonstrate that trained dogs can differentiate between cultured cells infected with BVDV, BHV1, and BPIV3 and are a realistic real-time mobile pathogen sensing technology for viral pathogens. The ability to discriminate between target and distractor samples plausibly results from expression of unique VOC patterns in virus-infected and -uninfected cells. PMID:26779494

  5. Real-time interpretation of novel events across childhood

    PubMed Central

    Borovsky, Arielle; Sweeney, Kim; Elman, Jeffrey L.; Fernald, Anne

    2014-01-01

    Despite extensive evidence that adults and children rapidly integrate world knowledge to generate expectancies for upcoming language, little work has explored how this knowledge is initially acquired and used. We explore this question in 3- to 10-year-old children and adults by measuring the degree to which sentences depicting recently learned connections between agents, actions and objects lead to anticipatory eye-movements to the objects. Combinatory information in sentences about agent and action elicited anticipatory eye-movements to the Target object in adults and older children. Our findings suggest that adults and school-aged children can quickly activate information about recently exposed novel event relationships in real-time language processing. However, there were important developmental differences in the use of this knowledge. Adults and school-aged children used the sentential agent and action to predict the sentence final theme, while preschool children’s fixations reflected a simple association to the currently spoken item. We consider several reasons for this developmental difference and possible extensions of this paradigm. PMID:24976677

  6. Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application.

    PubMed

    Mur, Angel; Dormido, Raquel; Vega, Jesús; Duro, Natividad; Dormido-Canto, Sebastian

    2016-01-01

    In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG) recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time. PMID:27120605

  7. Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application

    PubMed Central

    Mur, Angel; Dormido, Raquel; Vega, Jesús; Duro, Natividad; Dormido-Canto, Sebastian

    2016-01-01

    In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG) recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time. PMID:27120605

  8. Flexible algorithm for real-time convolution supporting dynamic event-related fMRI

    NASA Astrophysics Data System (ADS)

    Eaton, Brent L.; Frank, Randall J.; Bolinger, Lizann; Grabowski, Thomas J.

    2002-04-01

    An efficient algorithm for generation of the task reference function has been developed that allows real-time statistical analysis of fMRI data, within the framework of the general linear model, for experiments with event-related stimulus designs. By leveraging time-stamped data collection in the Input/Output time-aWare Architecture (I/OWA), we detect the onset time of a stimulus as it is delivered to a subject. A dynamically updated list of detected stimulus event times is maintained in shared memory as a data stream and delivered as input to a real-time convolution algorithm. As each image is acquired from the MR scanner, the time-stamp of its acquisition is delivered via a second dynamically updated stream to the convolution algorithm, where a running convolution of the events with an estimated hemodynamic response function is computed at the image acquisition time and written to a third stream in memory. Output is interpreted as the activation reference function and treated as the covariate of interest in the I/OWA implementation of the general linear model. Statistical parametric maps are computed and displayed to the I/OWA user interface in less than the time between successive image acquisitions.

  9. Real-Time Classification of Bladder Events for Effective Diagnosis and Treatment of Urinary Incontinence.

    PubMed

    Karam, Robert; Bourbeau, Dennis; Majerus, Steve; Makovey, Iryna; Goldman, Howard B; Damaser, Margot S; Bhunia, Swarup

    2016-04-01

    Diagnosis of lower urinary tract dysfunction with urodynamics has historically relied on data acquired from multiple sensors using nonphysiologically fast cystometric filling. In addition, state-of-the-art neuromodulation approaches to restore bladder function could benefit from a bladder sensor for closed-loop control, but a practical sensor and automated data analysis are not available. We have developed an algorithm for real-time bladder event detection based on a single in situ sensor, making it attractive for both extended ambulatory bladder monitoring and closed-loop control of stimulation systems for diagnosis and treatment of bladder overactivity. Using bladder pressure data acquired from 14 human subjects with neurogenic bladder, we developed context-aware thresholding, a novel, parameterized, user-tunable algorithmic framework capable of real-time classification of bladder events, such as detrusor contractions, from single-sensor bladder pressure data. We compare six event detection algorithms with both single-sensor and two-sensor systems using a metric termed Conditional Stimulation Score, which ranks algorithms based on projected stimulation efficacy and efficiency. We demonstrate that adaptive methods are more robust against day-to-day variations than static thresholding, improving sensitivity and specificity without parameter modifications. Relative to other methods, context-aware thresholding is fast, robust, highly accurate, noise-tolerant, and amenable to energy-efficient hardware implementation, which is important for mapping to an implant device. PMID:26292331

  10. Detecting seismic events using Benford's Law

    NASA Astrophysics Data System (ADS)

    Diaz, Jordi; Gallart, Josep; Ruiz, Mario

    2015-04-01

    The Benford's Law (BL) states that the distribution of first significant digits is not uniform but follows a logarithmic frequency distribution. Even if a remarkable wide range of natural and socioeconomical data sets, from stock market values to quantum phase transitions, fit this peculiar law, the conformity to it has deserved few scientific applications, being used mainly as a test to pinpoint anomalous or fraudulent data. We developed a procedure to detect the arrival of seismic waves based on the degree of conformity of the amplitude values in the raw seismic trace to the BL. The signal is divided in time windows of appropriate length and the fitting of the first digits distribution to BL is checked in each time window using a conformity estimator. We document that both teleseismic and local earthquakes can be clearly identified in this procedure and we compare its performance with respect to the classical STA/LTA approach. Moreover, we show that the conformity of the seismic record to the BL does not depend on the amplitude of the incoming series, as the occurrence of events with very different amplitudes result in quite similar degree of BL fitting. On the other hand, we show that natural or man-made quasi-monochromatic seismic signals, surface wave trains or engine-generated vibrations can be identified through their very low BL estimator values, when appropriate interval lengths are used. Therefore, we conclude that the degree of conformity of a seismic signal with the BL is primarily dependent on the frequency content of that signal.

  11. AESOP: Adaptive Event detection SOftware using Programming by example

    NASA Astrophysics Data System (ADS)

    Thangali, Ashwin; Prasad, Harsha; Kethamakka, Sai; Demirdjian, David; Checka, Neal

    2015-05-01

    This paper presents AESOP, a software tool for automatic event detection in video. AESOP employs a super- vised learning approach for constructing event models, given training examples from different event classes. A trajectory-based formulation is used for modeling events with an aim towards incorporating invariance to changes in the camera location and orientation parameters. The proposed formulation is designed to accommodate events that involve interactions between two or more entities over an extended period of time. AESOP's event models are formulated as HMMs to improve the event detection algorithm's robustness to noise in input data and to achieve computationally efficient algorithms for event model training and event detection. AESOP's performance is demonstrated on a wide range of different scenarios, including stationary camera surveillance and aerial video footage captured in land and maritime environments.

  12. Real-time gesture interface based on event-driven processing from stereo silicon retinas.

    PubMed

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael; Park, Paul K J; Shin, Chang-Woo; Ryu, Hyunsurk Eric; Kang, Byung Chang

    2014-12-01

    We propose a real-time hand gesture interface based on combining a stereo pair of biologically inspired event-based dynamic vision sensor (DVS) silicon retinas with neuromorphic event-driven postprocessing. Compared with conventional vision or 3-D sensors, the use of DVSs, which output asynchronous and sparse events in response to motion, eliminates the need to extract movements from sequences of video frames, and allows significantly faster and more energy-efficient processing. In addition, the rate of input events depends on the observed movements, and thus provides an additional cue for solving the gesture spotting problem, i.e., finding the onsets and offsets of gestures. We propose a postprocessing framework based on spiking neural networks that can process the events received from the DVSs in real time, and provides an architecture for future implementation in neuromorphic hardware devices. The motion trajectories of moving hands are detected by spatiotemporally correlating the stereoscopically verged asynchronous events from the DVSs by using leaky integrate-and-fire (LIF) neurons. Adaptive thresholds of the LIF neurons achieve the segmentation of trajectories, which are then translated into discrete and finite feature vectors. The feature vectors are classified with hidden Markov models, using a separate Gaussian mixture model for spotting irrelevant transition gestures. The disparity information from stereovision is used to adapt LIF neuron parameters to achieve recognition invariant of the distance of the user to the sensor, and also helps to filter out movements in the background of the user. Exploiting the high dynamic range of DVSs, furthermore, allows gesture recognition over a 60-dB range of scene illuminance. The system achieves recognition rates well over 90% under a variety of variable conditions with static and dynamic backgrounds with naïve users. PMID:25420246

  13. Seismic network detection probability assessment using waveforms and accounting to event association logic

    NASA Astrophysics Data System (ADS)

    Pinsky, Vladimir; Shapira, Avi

    2016-05-01

    The geographical area where a seismic event of magnitude M ≥ M t is detected by a seismic station network, for a defined probability is derived from a station probability of detection estimated as a function of epicentral distance. The latter is determined from both the bulletin data and the waveforms recorded by the station during the occurrence of the event with and without band-pass filtering. For simulating the real detection process, the waveforms are processed using the conventional Carl Johnson detection and association algorithm. The attempt is presented to account for the association time criterion in addition to the conventional approach adopted by the known PMC method.

  14. Real-time and reliable human detection in clutter scene

    NASA Astrophysics Data System (ADS)

    Tan, Yumei; Luo, Xiaoshu; Xia, Haiying

    2013-10-01

    To solve the problem that traditional HOG approach for human detection can not achieve real-time detection due to its time-consuming detection, an efficient algorithm based on first segmentation then identify method for real-time human detection is proposed to achieve real-time human detection in clutter scene. Firstly, the ViBe algorithm is used to segment all possible human target regions quickly, and more accurate moving objects is obtained by using the YUV color space to eliminate the shadow; secondly, using the body geometry knowledge can help to found the valid human areas by screening the regions of interest; finally, linear support vector machine (SVM) classifier and HOG are applied to train for human body classifier, to achieve accurate positioning of human body's locations. The results of our comparative experiments demonstrated that the approach proposed can obtain high accuracy, good real-time performance and strong robustness.

  15. Real-time detection of airborne chemicals

    NASA Astrophysics Data System (ADS)

    Hartenstein, Steven D.; Tremblay, Paul L. A.; Fryer, Michael O.; Kaser, Timothy

    1999-02-01

    Accurate, real time air quality measurements are difficult to make, because real time sensors for some gas species are not specific to a single gas. For example, some carbon dioxide sensors react to hydrogen sulfide. By combining the response of several types of real time gas sensors the Real-time Air Quality Monitoring System (RAQMS) accurately measures many different gases. The sensor suite for the INEEL's Real-time Air Quality Monitoring System (RAQMS) incudes seven, inexpensive, commercially-available chemical sensors for gases associated with air quality. These chemical sensors are marketed as devices to measure carbon dioxide, hydrogen sulfide, carbon monoxide, sulfur dioxide, nitrogen dioxide, water vapor and volatile organic compounds (VOC's). However, these chemical sensors respond to more than a single compound, e.g. both the VOC and the carbon dioxide sensors respond strongly to methane. This multiple sensor response to a given chemical is used to advantage in the RAQMS system, as patterns of responses by the sensors were found to be unique and distinguishable for several chemicals. Therefore, there is the potential that the seven sensors combined output can: (1) provide more accurate measurements of the advertized gases and (2) estimate the presence and quantity of additional gases. The patterns of sensor response can be thought of as clusters of data points in a seven dimensional space. One dimension for each sensor's output. For all of the gases tested, these clusters were separated enough that good quantitative results were obtained. As an example, the prototype RAQMS is able to distinguish methane from butane and predict accurate concentrations of both gases. A mathematical technique for estimating probability density functions from random samples is used to distinguish the data clusters from each other and to make gas concentration estimates. Bayes optimal estimates of gas concentration are calculated using the probability density function. The

  16. Barometric pressure and triaxial accelerometry-based falls event detection.

    PubMed

    Bianchi, Federico; Redmond, Stephen J; Narayanan, Michael R; Cerutti, Sergio; Lovell, Nigel H

    2010-12-01

    Falls and fall related injuries are a significant cause of morbidity, disability, and health care utilization, particularly among the age group of 65 years and over. The ability to detect falls events in an unsupervised manner would lead to improved prognoses for falls victims. Several wearable accelerometry and gyroscope-based falls detection devices have been described in the literature; however, they all suffer from unacceptable false positive rates. This paper investigates the augmentation of such systems with a barometric pressure sensor, as a surrogate measure of altitude, to assist in discriminating real fall events from normal activities of daily living. The acceleration and air pressure data are recorded using a wearable device attached to the subject's waist and analyzed offline. The study incorporates several protocols including simulated falls onto a mattress and simulated activities of daily living, in a cohort of 20 young healthy volunteers (12 male and 8 female; age: 23.7 ±3.0 years). A heuristically trained decision tree classifier is used to label suspected falls. The proposed system demonstrated considerable improvements in comparison to an existing accelerometry-based technique; showing an accuracy, sensitivity and specificity of 96.9%, 97.5%, and 96.5%, respectively, in the indoor environment, with no false positives generated during extended testing during activities of daily living. This is compared to 85.3%, 75%, and 91.5% for the same measures, respectively, when using accelerometry alone. The increased specificity of this system may enhance the usage of falls detectors among the elderly population. PMID:20805056

  17. Real time viability detection of bacterial spores

    DOEpatents

    Vanderberg, Laura A.; Herdendorf, Timothy J.; Obiso, Richard J.

    2003-07-29

    This invention relates to a process for detecting the presence of viable bacterial spores in a sample and to a spore detection system, the process including placing a sample in a germination medium for a period of time sufficient for commitment of any present viable bacterial spores to occur, mixing the sample with a solution of a lanthanide capable of forming a fluorescent complex with dipicolinic acid, and, measuring the sample for the presence of dipicolinic acid, and the system including a germination chamber having inlets from a sample chamber, a germinant chamber and a bleach chamber, the germination chamber further including an outlet through a filtering means, the outlet connected to a detection chamber, the detection chamber having an inlet from a fluorescence promoting metal chamber and the detection chamber including a spectral excitation source and a means of measuring emission spectra from a sample, the detection chamber further connected to a waste chamber. A germination reaction mixture useful for promoting commitment of any viable bacterial spores in a sample including a combination of L-alanine, L-asparagine and D-glucose is also described.

  18. System for detection of hazardous events

    DOEpatents

    Kulesz, James J.; Worley, Brian A.

    2006-05-23

    A system for detecting the occurrence of anomalies, includes a plurality of spaced apart nodes, with each node having adjacent nodes, each of the nodes having one or more sensors associated with the node and capable of detecting anomalies, and each of the nodes having a controller connected to the sensors associated with the node. The system also includes communication links between adjacent nodes, whereby the nodes form a network. Each controller is programmed to query its adjacent nodes to assess the status of the adjacent nodes and the communication links.

  19. System For Detection Of Hazardous Events

    DOEpatents

    Kulesz, James J [Oak Ridge, TN; Worley, Brian A [Knoxville, TN

    2005-08-16

    A system for detecting the occurrence of anomalies, includes a plurality of spaced apart nodes, with each node having adjacent nodes, each of the nodes having one or more sensors associated with the node and capable of detecting anomalies, and each of the nodes having a controller connected to the sensors associated with the node. The system also includes communication links between adjacent nodes, whereby the nodes form a network. Each controller is programmed to query its adjacent nodes to assess the status of the adjacent nodes and the communication links.

  20. Subsurface event detection and classification using Wireless Signal Networks.

    PubMed

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  1. Subsurface Event Detection and Classification Using Wireless Signal Networks

    PubMed Central

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  2. Why conventional detection methods fail in identifying the existence of contamination events.

    PubMed

    Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

    2016-04-15

    Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading. PMID:26905801

  3. Empirical study of crowd behavior during a real mass event

    NASA Astrophysics Data System (ADS)

    Zhang, X. L.; Weng, W. G.; Yuan, H. Y.

    2012-08-01

    The study of crowd behavior is essential for the safe organization of mass events. However, precise quantitative empirical data are insufficient due to the lack of mass event scenarios suitable for observation. In this paper, crowd behavior during a mass event in which many people go through a door and then pass a bridge is studied by a new method based on a flow field visualization algorithm widely used in fluid experiments. Two important movement phases, laminar flow on a bridge and stop-and-go waves in a bottleneck area, are investigated. The results show that the velocity profile on the bridge is similar to that of fully developed laminar flow in a pipe. Quantitative analysis of the stop-and-go wave in the bottleneck area shows that the dominant fluctuation frequencies are mainly below 0.1 Hz and the peak frequency is around 0.05 Hz the wave propagation speed is about - 0.69 m s-1. The absolute decrease in speed as the wave propagates is also indicated. By a combination of shock wave theory and a fundamental diagram, an analytical model of a shock wave in a crowd is established to theoretically investigate the stop-and-go wave, and the model can be used to explain the measurement results. This study provides a new method and fundamental data for understanding crowd behavior. The results are also expected to be useful for the design of crowd management strategies during mass events.

  4. Global Seismic Event Detection Using Surface Waves: 15 Possible Antarctic Glacial Sliding Events

    NASA Astrophysics Data System (ADS)

    Chen, X.; Shearer, P. M.; Walker, K. T.; Fricker, H. A.

    2008-12-01

    To identify overlooked or anomalous seismic events not listed in standard catalogs, we have developed an algorithm to detect and locate global seismic events using intermediate-period (35-70s) surface waves. We apply our method to continuous vertical-component seismograms from the global seismic networks as archived in the IRIS UV FARM database from 1997 to 2007. We first bandpass filter the seismograms, apply automatic gain control, and compute envelope functions. We then examine 1654 target event locations defined at 5 degree intervals and stack the seismogram envelopes along the predicted Rayleigh-wave travel times. The resulting function has spatial and temporal peaks that indicate possible seismic events. We visually check these peaks using a graphical user interface to eliminate artifacts and assign an overall reliability grade (A, B or C) to the new events. We detect 78% of events in the Global Centroid Moment Tensor (CMT) catalog. However, we also find 840 new events not listed in the PDE, ISC and REB catalogs. Many of these new events were previously identified by Ekstrom (2006) using a different Rayleigh-wave detection scheme. Most of these new events are located along oceanic ridges and transform faults. Some new events can be associated with volcanic eruptions such as the 2000 Miyakejima sequence near Japan and others with apparent glacial sliding events in Greenland (Ekstrom et al., 2003). We focus our attention on 15 events detected from near the Antarctic coastline and relocate them using a cross-correlation approach. The events occur in 3 groups which are well-separated from areas of cataloged earthquake activity. We speculate that these are iceberg calving and/or glacial sliding events, and hope to test this by inverting for their source mechanisms and examining remote sensing data from their source regions.

  5. Event Detection using Twitter: A Spatio-Temporal Approach

    PubMed Central

    Cheng, Tao; Wicks, Thomas

    2014-01-01

    Background Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor. Methods This paper suggests an alternative methodology for event detection using space-time scan statistics (STSS). This technique looks for clusters within the dataset across both space and time, regardless of tweet content. It is expected that clusters of tweets will emerge during spatio-temporally relevant events, as people will tweet more than expected in order to describe the event and spread information. The special event used as a case study is the 2013 London helicopter crash. Results and Conclusion A spatio-temporally significant cluster is found relating to the London helicopter crash. Although the cluster only remains significant for a relatively short time, it is rich in information, such as important key words and photographs. The method also detects other special events such as football matches, as well as train and flight delays from Twitter data. These findings demonstrate that STSS is an effective approach to analysing Twitter data for event detection. PMID:24893168

  6. SSME propellant path leak detection real-time

    NASA Technical Reports Server (NTRS)

    Crawford, R. A.; Smith, L. M.

    1994-01-01

    Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

  7. Real-time traffic jam detection and localization running on a smart camera

    NASA Astrophysics Data System (ADS)

    Lipetski, Yuriy; Loibner, Gernot; Ulm, Michael; Ponweiser, Wolfgang; Sidla, Oliver

    2014-03-01

    Reliable automatic detection of traffic jam occurrences is of big significance for traffic flow analysis related applications. We present our work aimed at the application of video based real-time traffic jam detection. Our method can handle both calibrated and un-calibrated scenarios, operating in world and in image coordinate systems respectively. The method is designed to be operated on a smart camera, but is also suitable for a standard personal computer. The combination of state-of-the-art algorithms for vehicle detections and velocity estimation allows robust long-term system operation in due to the high recall rate and very low false alarm rate. The proposed method not only detects traffic jam events in real-time, but also precisely localizes traffic jams by their start and end positions per road lane. We describe also our strategy in making computationally heavy algorithms real-time capable even on hardware with a limited computing power.

  8. Real-Time GPS Network Monitors Bayou Corne Sinkhole Event

    NASA Astrophysics Data System (ADS)

    Kent, Joshua D.; Dunaway, Larry

    2013-10-01

    In August 2012 a sinkhole developed in the swampy marshland near the rural community of Bayou Corne in Assumption Parish (i.e., county), Louisiana. The area was evacuated, and some residents have still not been able to return. The sinkhole—which now measures about 450 meters wide and is continuing to grow—is being monitored by multiple systems, including four rapid-response GPS continuously operating reference stations (CORS) called CORS911. The real-time data provided by this system are used by scientists and decision makers to help ensure public safety.

  9. Video Event Detection Framework on Large-Scale Video Data

    ERIC Educational Resources Information Center

    Park, Dong-Jun

    2011-01-01

    Detection of events and actions in video entails substantial processing of very large, even open-ended, video streams. Video data present a unique challenge for the information retrieval community because properly representing video events is challenging. We propose a novel approach to analyze temporal aspects of video data. We consider video data…

  10. Quantitative Detection of Spiroplasma Citri by Real Time PCR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    There is a need to develop an accurate and rapid method to detect Spiroplasma citri, the causal agent of citrus stubborn disease for use in epidemiology studies. Quantitative real-time PCR was developed for detection of S. citri. Two sets of primers based on sequences from the P58 putative adhesin ...

  11. Real-time 3D change detection of IEDs

    NASA Astrophysics Data System (ADS)

    Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

    2012-06-01

    Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

  12. Automatic detection of iceberg calving events using seismic observations

    NASA Astrophysics Data System (ADS)

    Andersen, M. L.; Larsen, T.; Hamilton, G. S.; Nettles, M.

    2014-12-01

    Iceberg calving at large, marine-terminating glaciers has been shown to be seismogenic. Seismic energy from these events is released slowly, resulting in characteristic low-frequency signals. The events therefore typically escape detection by traditional systematic methods. Here we show the results of a detection algorithm applied to data observed at two stations, both ~100 km from Helheim Glacier, South East Greenland, in 2007 and 2008 for the purpose of detecting calving-related seismic signals. The detector entails sliding a 150 s wide window over the observed vertical displacement seismograms at steps of one second. Relative power in the 1.1-3.3 s band is monitored, and the detector is activated when a pre-defined threshold is exceeded. We determine the threshold by calibrating the detector with a record of known events observed by time lapse cameras at Helheim Glacier and automatic detections of glacial earthquakes from the GSN (Global Seismic Network) stations. The resulting list of detections is then filtered for events overlapping with tectonic events, both local and global. We observe a clear periodicity in the detections, with most events occurring during the late summer and early fall, roughly coinciding with the end of the melt season. This apparent offset from peak melt intensity leads us to speculate that the pattern in calving is the result of a combination of the seasonal development of multiple physical properties of the glacier, i.e., surface crevassing, subglacial melt and crevassing, and the subglacial drainage system.

  13. An Organic Model for Detecting Cyber Events

    SciTech Connect

    Oehmen, Christopher S.; Peterson, Elena S.; Dowson, Scott T.

    2010-04-21

    Cyber entities in many ways mimic the behavior of organic systems. Individuals or groups compete for limited resources using a variety of strategies and effective strategies are re-used and refined in later ‘generations’. Traditionally this drift has made detection of malicious entities very difficult because 1) recognition systems are often built on exact matching to a pattern that can only be ‘learned’ after a malicious entity reveals itself and 2) the enormous volume and variation in benign entities is an overwhelming source of previously unseen entities that often confound detectors. To turn the tables of complexity on the would-be attackers, we have developed a method for mapping the sequence of behaviors in which cyber entities engage to strings of text and analyze these strings using modified bioinformatics algorithms. Bioinformatics algorithms optimize the alignment between text strings even in the presence of mismatches, insertions or deletions and do not require an a priori definition of the patterns one is seeking. Nor does it require any type of exact matching. This allows the data itself to suggest meaningful patterns that are conserved between cyber entities. We demonstrate this method on data generated from network traffic. The impact of this approach is that it can rapidly calculate similarity measures of previously unseen cyber entities in terms of well-characterized entities. These measures may also be used to organize large collections of data into families, making it possible to identify motifs indicative of each family.

  14. An integrated logit model for contamination event detection in water distribution systems.

    PubMed

    Housh, Mashor; Ostfeld, Avi

    2015-05-15

    The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. PMID:25770443

  15. Characteristics of near-death experiences memories as compared to real and imagined events memories.

    PubMed

    Thonnard, Marie; Charland-Verville, Vanessa; Brédart, Serge; Dehon, Hedwige; Ledoux, Didier; Laureys, Steven; Vanhaudenhuyse, Audrey

    2013-01-01

    Since the dawn of time, Near-Death Experiences (NDEs) have intrigued and, nowadays, are still not fully explained. Since reports of NDEs are proposed to be imagined events, and since memories of imagined events have, on average, fewer phenomenological characteristics than real events memories, we here compared phenomenological characteristics of NDEs reports with memories of imagined and real events. We included three groups of coma survivors (8 patients with NDE as defined by the Greyson NDE scale, 6 patients without NDE but with memories of their coma, 7 patients without memories of their coma) and a group of 18 age-matched healthy volunteers. Five types of memories were assessed using Memory Characteristics Questionnaire (MCQ--Johnson et al., 1988): target memories (NDE for NDE memory group, coma memory for coma memory group, and first childhood memory for no memory and control groups), old and recent real event memories and old and recent imagined event memories. Since NDEs are known to have high emotional content, participants were requested to choose the most emotionally salient memories for both real and imagined recent and old event memories. Results showed that, in NDE memories group, NDE memories have more characteristics than memories of imagined and real events (p<0.02). NDE memories contain more self-referential and emotional information and have better clarity than memories of coma (all ps<0.02). The present study showed that NDE memories contained more characteristics than real event memories and coma memories. Thus, this suggests that they cannot be considered as imagined event memories. On the contrary, their physiological origins could lead them to be really perceived although not lived in the reality. Further work is needed to better understand this phenomenon. PMID:23544039

  16. Characteristics of Near-Death Experiences Memories as Compared to Real and Imagined Events Memories

    PubMed Central

    Brédart, Serge; Dehon, Hedwige; Ledoux, Didier; Laureys, Steven; Vanhaudenhuyse, Audrey

    2013-01-01

    Since the dawn of time, Near-Death Experiences (NDEs) have intrigued and, nowadays, are still not fully explained. Since reports of NDEs are proposed to be imagined events, and since memories of imagined events have, on average, fewer phenomenological characteristics than real events memories, we here compared phenomenological characteristics of NDEs reports with memories of imagined and real events. We included three groups of coma survivors (8 patients with NDE as defined by the Greyson NDE scale, 6 patients without NDE but with memories of their coma, 7 patients without memories of their coma) and a group of 18 age-matched healthy volunteers. Five types of memories were assessed using Memory Characteristics Questionnaire (MCQ – Johnson et al., 1988): target memories (NDE for NDE memory group, coma memory for coma memory group, and first childhood memory for no memory and control groups), old and recent real event memories and old and recent imagined event memories. Since NDEs are known to have high emotional content, participants were requested to choose the most emotionally salient memories for both real and imagined recent and old event memories. Results showed that, in NDE memories group, NDE memories have more characteristics than memories of imagined and real events (p<0.02). NDE memories contain more self-referential and emotional information and have better clarity than memories of coma (all ps<0.02). The present study showed that NDE memories contained more characteristics than real event memories and coma memories. Thus, this suggests that they cannot be considered as imagined event memories. On the contrary, their physiological origins could lead them to be really perceived although not lived in the reality. Further work is needed to better understand this phenomenon. PMID:23544039

  17. Intelligent fuzzy controller for event-driven real time systems

    NASA Technical Reports Server (NTRS)

    Grantner, Janos; Patyra, Marek; Stachowicz, Marian S.

    1992-01-01

    Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.

  18. Detection of flood events in hydrological discharge time series

    NASA Astrophysics Data System (ADS)

    Seibert, S. P.; Ehret, U.

    2012-04-01

    The shortcomings of mean-squared-error (MSE) based distance metrics are well known (Beran 1999, Schaeffli & Gupta 2007) and the development of novel distance metrics (Pappenberger & Beven 2004, Ehret & Zehe 2011) and multi-criteria-approaches enjoy increasing popularity (Reusser 2009, Gupta et al. 2009). Nevertheless, the hydrological community still lacks metrics which identify and thus, allow signature based evaluations of hydrological discharge time series. Signature based information/evaluations are required wherever specific time series features, such as flood events, are of special concern. Calculation of event based runoff coefficients or precise knowledge on flood event characteristics (like onset or duration of rising limp or the volume of falling limp, etc.) are possible applications. The same applies for flood forecasting/simulation models. Directly comparing simulated and observed flood event features may reveal thorough insights into model dynamics. Compared to continuous space-and-time-aggregated distance metrics, event based evaluations may provide answers like the distributions of event characteristics or the percentage of the events which were actually reproduced by a hydrological model. It also may help to provide information on the simulation accuracy of small, medium and/or large events in terms of timing and magnitude. However, the number of approaches which expose time series features is small and their usage is limited to very specific questions (Merz & Blöschl 2009, Norbiato et al. 2009). We believe this is due to the following reasons: i) a generally accepted definition of the signature of interest is missing or difficult to obtain (in our case: what makes a flood event a flood event?) and/or ii) it is difficult to translate such a definition into a equation or (graphical) procedure which exposes the feature of interest in the discharge time series. We reviewed approaches which detect event starts and/or ends in hydrological discharge time

  19. Stable algorithm for event detection in event-driven particle dynamics: logical states

    NASA Astrophysics Data System (ADS)

    Strobl, Severin; Bannerman, Marcus N.; Pöschel, Thorsten

    2016-07-01

    Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to determine the interaction state of a particle in stepped potentials, such as the square-well model. To correctly predict the next event in these systems, the concept of an additional state that is tracked separately from the particle position is introduced and integrated into the stable algorithm for event detection.

  20. Pipeline Implementation of Real Time Event Cross Correlation for Nuclear Treaty Monitoring

    NASA Astrophysics Data System (ADS)

    Junek, W. N.; Wehlen, J. A., III

    2014-12-01

    The United States National Data Center (US NDC) is responsible for monitoring international compliance to nuclear test ban treaties. This mission is performed through real time acquisition, processing, and evaluation of data acquired by a global network of seismic, hydroacoustic, and infrasonic sensors. Automatic and human reviewed event solutions are stored in a data warehouse which contains over 15 years of alphanumeric information and waveform data. A significant effort is underway to employ the data warehouse in real time processing to improve the quality of automatic event solutions, reduce analyst burden, and supply decision makers with information regarding relevant historic events. To this end, the US NDC processing pipeline has been modified to automatically recognize events built in the past. Event similarity information and the most relevant historic solution are passed to the human analyst to assist their evaluation of automatically formed events. This is achieved through real time cross correlation of selected seismograms from automatically formed events against those stored in the data warehouse. Historic events used in correlation analysis are selected based on a set of user defined parameters, which are tuned to maintain pipeline timeliness requirements. Software architecture and database infrastructure were modified using a multithreaded design for increased processing speed, database connection pools for parallel queries, and Oracle spatial indexing to enhance query efficiency. This functionality allows the human analyst to spend more time studying anomalous events and less time rebuilding routine events.

  1. Real-time iris detection on rotated faces

    NASA Astrophysics Data System (ADS)

    Perez, Claudio A.; Lazcano, Vanel A.; Estevez, Pablo A.; Held, Claudio M.

    2003-10-01

    Real-time face and iris detection on video sequences has been used to study the eye function and in diverse applications such as drowsiness detection, virtual keyboard interfaces, face recognition and multimedia retrieval. A non-invasive real time iris detection method was developed and consists of three stages: coarse face detection, fine face detection and iris detection. Anthropometric templates are used in these three stages. Elliptical templates are used to locate the coarse face center. A set of anthropometric templates which are probabilistic maps for the eyebrows, nose and mouth are used to perform the fine face detection. Face rotations are considered by rotating the anthropometric templates in fixed angles in steps of 10 degrees. Iris position is then determined within the eye region using another template with concentric semi-circles to compute a line integral in the boundary iris-sclera. The position with the maximum value indicates the iris center. The new method was applied on 10 video sequences, with a total of 6470 frames, from different people rotating their faces in the coronal axis. Results of correct face detection on 8 video sequences was 100%, one reached 99.9% and one 98.2%. Results on correct iris detection are above 96% in 9 of the video sequences and one reached 77.8%. The method was implemented in real-time (30 frames per second) with a PC 1.8 GHz.

  2. Structuring an event ontology for disease outbreak detection

    PubMed Central

    Kawazoe, Ai; Chanlekha, Hutchatai; Shigematsu, Mika; Collier, Nigel

    2008-01-01

    Background This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is designed to support timely detection of disease outbreaks and rapid judgment of their alerting status by 1) bridging a gap between layman's language used in disease outbreak reports and public health experts' deep knowledge, and 2) making multi-lingual information available. Construction and content This event ontology integrates a model of experts' knowledge for disease surveillance, and at the same time sets of linguistic expressions which denote disease-related events, and formal definitions of events. In this ontology, rather general event classes, which are suitable for application to language-oriented tasks such as recognition of event expressions, are placed on the upper-level, and more specific events of the experts' interest are in the lower level. Each class is related to other classes which represent participants of events, and linked with multi-lingual synonym sets and axioms. Conclusions We consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them. The first version of the ontology, with about 40 concepts, will be available in March 2008. PMID:18426553

  3. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks.

    PubMed

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady. PMID:26694394

  4. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

    PubMed Central

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s). When sensory data are collected at sink node(s), the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady. PMID:26694394

  5. Monitoring Natural Events Globally in Near Real-Time Using NASA's Open Web Services and Tools

    NASA Technical Reports Server (NTRS)

    Boller, Ryan A.; Ward, Kevin Alan; Murphy, Kevin J.

    2015-01-01

    Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based missions, many of which can be useful for monitoring natural events. In recent years, these measurements have been made available in near real-time, making it possible to use them to also aid in managing the response to natural events. We present the challenges and ongoing solutions to using NASA satellite data for monitoring and managing these events.

  6. Method for Real-Time Model Based Structural Anomaly Detection

    NASA Technical Reports Server (NTRS)

    Smith, Timothy A. (Inventor); Urnes, James M., Sr. (Inventor); Reichenbach, Eric Y. (Inventor)

    2015-01-01

    A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

  7. Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

    NASA Technical Reports Server (NTRS)

    Martin, Rodney Alexander; Das, Santanu

    2010-01-01

    The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

  8. Detection of earth-approaching asteroids in near real time

    NASA Astrophysics Data System (ADS)

    Rabinowitz, D. L.

    1991-04-01

    Computer software, called the Moving Object Detection Program (MODP), is described which detects earth-approaching asteroids in near real time. The software runs on a workstation linked to the output of the drift-scanning CCD camera of the Spacewatch Telescope. MOPD recognizes trailed images, detects motion, and accurately determines angular positions and rates of motion for moving objects in the scan images. The results are obtained a few seconds after the image signals are shifted out of the CCD. During 2 months of trial observations with this system, 304 asteroids were detected down to a limiting apparent magnitude for untrailed images of V = 20.5.

  9. Detection of earth-approaching asteroids in near real time

    NASA Technical Reports Server (NTRS)

    Rabinowitz, D. L.

    1991-01-01

    Computer software, called the Moving Object Detection Program (MODP), is described which detects earth-approaching asteroids in near real time. The software runs on a workstation linked to the output of the drift-scanning CCD camera of the Spacewatch Telescope. MOPD recognizes trailed images, detects motion, and accurately determines angular positions and rates of motion for moving objects in the scan images. The results are obtained a few seconds after the image signals are shifted out of the CCD. During 2 months of trial observations with this system, 304 asteroids were detected down to a limiting apparent magnitude for untrailed images of V = 20.5.

  10. Data mining for signal detection of adverse event safety data.

    PubMed

    Chen, Hung-Chia; Tsong, Yi; Chen, James J

    2013-01-01

    The Adverse Event Reporting System (AERS) is the primary database designed to support the Food and Drug Administration (FDA) postmarketing safety surveillance program for all approved drugs and therapeutic biologic products. Most current disproportionality analysis focuses on the detection of potential adverse events (AE) involving a single drug and a single AE only. In this paper, we present a data mining biclustering technique based on the singular value decomposition to extract local regions of association for a safety study. The analysis consists of collection of biclusters, each representing an association between a set of drugs with the corresponding set of adverse events. Significance of each bicluster can be tested using disproportionality analysis. Individual drug-event combination can be further tested. A safety data set consisting of 193 drugs with 8453 adverse events is analyzed as an illustration. PMID:23331228

  11. Real time rectangular document detection on mobile devices

    NASA Astrophysics Data System (ADS)

    Skoryukina, Natalya; Nikolaev, Dmitry P.; Sheshkus, Alexander; Polevoy, Dmitry

    2015-02-01

    In this paper we propose an algorithm for real-time rectangular document borders detection in mobile device based applications. The proposed algorithm is based on combinatorial assembly of possible quadrangle candidates from a set of line segments and projective document reconstruction using the known focal length. Fast Hough Transform is used for line detection. 1D modification of edge detector is proposed for the algorithm.

  12. Method for early detection of cooling-loss events

    SciTech Connect

    Bermudez, Sergio A.; Hamann, Hendrik F.; Marianno, Fernando J.

    2015-12-22

    A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

  13. Method for early detection of cooling-loss events

    SciTech Connect

    Bermudez, Sergio A.; Hamann, Hendrik; Marianno, Fernando J.

    2015-06-30

    A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.

  14. Real-time surveillance for abnormal events: the case of influenza outbreaks.

    PubMed

    Rao, Yao; McCabe, Brendan

    2016-06-15

    This paper introduces a method of surveillance using deviations from probabilistic forecasts. Realised observations are compared with probabilistic forecasts, and the "deviation" metric is based on low probability events. If an alert is declared, the algorithm continues to monitor until an all-clear is announced. Specifically, this article addresses the problem of syndromic surveillance for influenza (flu) with the intention of detecting outbreaks, due to new strains of viruses, over and above the normal seasonal pattern. The syndrome is hospital admissions for flu-like illness, and hence, the data are low counts. In accordance with the count properties of the observations, an integer-valued autoregressive process is used to model flu occurrences. Monte Carlo evidence suggests the method works well in stylised but somewhat realistic situations. An application to real flu data indicates that the ideas may have promise. The model estimated on a short run of training data did not declare false alarms when used with new observations deemed in control, ex post. The model easily detected the 2009 H1N1 outbreak. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26782751

  15. Snow avalanche detection and identification for near real-time application

    NASA Astrophysics Data System (ADS)

    Havens, S.; Johnson, J. B.; Marshall, H.; Nicholson, B.; Trisca, G. O.

    2013-12-01

    A near real-time avalanche detection system will provide highway avalanche forecasters with a tool to remotely monitor major avalanche paths and provide information about regional avalanche activity and timing. For the last three winters, a network of infrasound arrays has been remotely monitoring both avalanche and non-avalanche events along a 10 mile section of Highway 21 in Idaho. To provide the best results to avalanche forecasters, the system must be robust and detect all major avalanche events of interest that affect the highway. Over the last three winters, the infrasound arrays recorded multiple avalanche cycles and we explore different methods of event detection for both large dry avalanches (strong infrasound signal) and small wet avalanches (weak infrasound signal). We compare the F-statistic and cross-correlation techniques (i.e. PMCC) to determine the most robust method and develop computationally efficient algorithms to implement in near-real time using parallel processing and GPU computing. Once an event has been detected, we use the artificial intelligence method of recursive neural networks to classify based on similar characteristics to past known signals.

  16. Unattended monitoring system at a static storage area with real-time event notification.

    SciTech Connect

    West, J. D.; Betts, S. E.; Michel, K. D.; Schanfein, M. J.; Ricketts, T. E.

    2005-01-01

    Domestic Safeguards at Los Alamos National Laboratory (LANL) and throughout the Department of Energy (DOE)/National Nuclear Security Administration (NNSA) complex has historically relied on administrative and non-integrated approaches to implement nuclear safeguards at its facilities. Besides the heavy cost born by the facility and the compliance oversight organization, the safeguards assurance is only periodic, potentially allowing an adversary a longer time before detection. Even after detection, the lack of situational awareness makes it difficult to assess events. By leveraging unattended monitoring systems (UMS) used by the International Atomic Energy Agency (IAEA), we have designed a baseline system that has high reliability through fault tolerant designs for both hardware and software. Applying IAEA design goals to assure no loss of data and using a dual containment strategy, this system is a first step in implementing modern safeguards monitoring systems at LANL and, hopefully, applications at other DOE/NNSA sites. This paper will review the design requirements and how they will be met, to provide a real-time event notification for a static storage location. The notification system triggers communications to pagers and email addresses for a fast response by facility personnel to the violation of a defined safeguards exclusion zone. Since the system has to be installed in an existing facility, the challenges to the designers will be presented. Aside from the initial baseline system that relies on surveillance cameras and seals, other optional upgrades will be detailed, showing both the power and the promise of unattended systems for domestic safeguards. We will also include a short discussion of the business obstacles to modernizing safeguards and how a UMS system may be applied to dynamic activities at a nuclear facility. Ultimately, the current lack of such modern monitoring systems reflects the many business obstacles internal to DOE/NNSA to the use of

  17. DETECTION OF FECAL ENTEROCOCCI USING A REAL TIME PCR METHOD

    EPA Science Inventory

    In spite of their importance in public health, the detection of fecal enterococci is performed via culturing methods that are time consuming and that are subject to inaccuracies that relate to their culturable status. In order to address these problems, a real time PCR (TaqMan) ...

  18. Detection of Abnormal Events via Optical Flow Feature Analysis

    PubMed Central

    Wang, Tian; Snoussi, Hichem

    2015-01-01

    In this paper, a novel algorithm is proposed to detect abnormal events in video streams. The algorithm is based on the histogram of the optical flow orientation descriptor and the classification method. The details of the histogram of the optical flow orientation descriptor are illustrated for describing movement information of the global video frame or foreground frame. By combining one-class support vector machine and kernel principal component analysis methods, the abnormal events in the current frame can be detected after a learning period characterizing normal behaviors. The difference abnormal detection results are analyzed and explained. The proposed detection method is tested on benchmark datasets, then the experimental results show the effectiveness of the algorithm. PMID:25811227

  19. A comparison of moving object detection methods for real-time moving object detection

    NASA Astrophysics Data System (ADS)

    Roshan, Aditya; Zhang, Yun

    2014-06-01

    Moving object detection has a wide variety of applications from traffic monitoring, site monitoring, automatic theft identification, face detection to military surveillance. Many methods have been developed across the globe for moving object detection, but it is very difficult to find one which can work globally in all situations and with different types of videos. The purpose of this paper is to evaluate existing moving object detection methods which can be implemented in software on a desktop or laptop, for real time object detection. There are several moving object detection methods noted in the literature, but few of them are suitable for real time moving object detection. Most of the methods which provide for real time movement are further limited by the number of objects and the scene complexity. This paper evaluates the four most commonly used moving object detection methods as background subtraction technique, Gaussian mixture model, wavelet based and optical flow based methods. The work is based on evaluation of these four moving object detection methods using two (2) different sets of cameras and two (2) different scenes. The moving object detection methods have been implemented using MatLab and results are compared based on completeness of detected objects, noise, light change sensitivity, processing time etc. After comparison, it is observed that optical flow based method took least processing time and successfully detected boundary of moving objects which also implies that it can be implemented for real-time moving object detection.

  20. Characterization and Analysis of Networked Array of Sensors for Event Detection (CANARY-EDS)

    Energy Science and Technology Software Center (ESTSC)

    2011-05-27

    CANARY -EDS provides probabilistic event detection based on analysis of time-series data from water quality or other sensors. CANARY also can compare patterns against a library of previously seen data to indicate that a certain pattern has reoccurred, suppressing what would otherwise be considered an event. CANARY can be configured to analyze previously recorded data from files or databases, or it can be configured to run in real-time mode directory from a database, or throughmore » the US EPA EDDIES software.« less

  1. Near real time vapor detection and enhancement using aerosol adsorption

    DOEpatents

    Novick, V.J.; Johnson, S.A.

    1999-08-03

    A vapor sample detection method is described where the vapor sample contains vapor and ambient air and surrounding natural background particles. The vapor sample detection method includes the steps of generating a supply of aerosol that have a particular effective median particle size, mixing the aerosol with the vapor sample forming aerosol and adsorbed vapor suspended in an air stream, impacting the suspended aerosol and adsorbed vapor upon a reflecting element, alternatively directing infrared light to the impacted aerosol and adsorbed vapor, detecting and analyzing the alternatively directed infrared light in essentially real time using a spectrometer and a microcomputer and identifying the vapor sample. 13 figs.

  2. Near real time vapor detection and enhancement using aerosol adsorption

    DOEpatents

    Novick, Vincent J.; Johnson, Stanley A.

    1999-01-01

    A vapor sample detection method where the vapor sample contains vapor and ambient air and surrounding natural background particles. The vapor sample detection method includes the steps of generating a supply of aerosol that have a particular effective median particle size, mixing the aerosol with the vapor sample forming aerosol and adsorbed vapor suspended in an air stream, impacting the suspended aerosol and adsorbed vapor upon a reflecting element, alternatively directing infrared light to the impacted aerosol and adsorbed vapor, detecting and analyzing the alternatively directed infrared light in essentially real time using a spectrometer and a microcomputer and identifying the vapor sample.

  3. Quantification and threshold detection in real-time hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Driver, Richard D.

    2009-05-01

    The technical challenges of applying hyperspectral imaging techniques to on-line real-time food monitoring is discussed. System optimization must be applied to the design of the hyperspectral imaging spectrograph, the choice and operation of the imaging detector, the design of the illumination system and finally the development of software algorithms to correctly quantify the hyperspectral images. The signal to noise limitation of hyperspectral detection is discussed with particular emphasis on the detection of moving objects at high measurement bandwidths. An example is given of the development of a simple but accurate algorithm for the detection and discrimination of rust particles on leaves.

  4. Parallel scheme for real-time detection of photosensitive seizures.

    PubMed

    Alzubaidi, Mohammad A; Otoom, Mwaffaq; Al-Tamimi, Abdel-Karim

    2016-03-01

    The production and distribution of videos and animations on gaming and self-authoring websites are booming. However, given this rise in self-authoring, there is increased concern for the health and safety of people who suffer from a neurological disorder called photosensitivity or photosensitive epilepsy. These people can suffer seizures from viewing video with hazardous content. This paper presents a spatiotemporal pattern detection algorithm that can detect hazardous content in streaming video in real time. A tool is developed for producing test videos with hazardous content, and then those test videos are used to evaluate the proposed algorithm, as well as an existing post-processing tool that is currently being used for detecting such patterns. To perform the detection in real time, the proposed algorithm was implemented on a dual core processor, using a pipelined/parallel software architecture. Results indicate that the proposed method provides better detection performance, allowing for the masking of seizure inducing patterns in real time. PMID:26829706

  5. Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

    NASA Astrophysics Data System (ADS)

    Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

    2012-09-01

    The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

  6. Summary of gas release events detected by hydrogen monitoring

    SciTech Connect

    MCCAIN, D.J.

    1999-05-18

    This paper summarizes the results of monitoring tank headspace for flammable gas release events. In over 40 tank years of monitoring the largest detected release in a single-shell tank is 2.4 cubic meters of Hydrogen. In the double-shell tanks the largest release is 19.3 cubic meters except in SY-101 pre mixer pump installation condition.

  7. Preferential Inspection of Recent Real-World Events Over Future Events: Evidence from Eye Tracking during Spoken Sentence Comprehension

    PubMed Central

    Knoeferle, Pia; Carminati, Maria Nella; Abashidze, Dato; Essig, Kai

    2011-01-01

    Eye-tracking findings suggest people prefer to ground their spoken language comprehension by focusing on recently seen events more than anticipating future events: When the verb in NP1-VERB-ADV-NP2 sentences was referentially ambiguous between a recently depicted and an equally plausible future clipart action, listeners fixated the target of the recent action more often at the verb than the object that hadn’t yet been acted upon. We examined whether this inspection preference generalizes to real-world events, and whether it is (vs. isn’t) modulated by how often people see recent and future events acted out. In a first eye-tracking study, the experimenter performed an action (e.g., sugaring pancakes), and then a spoken sentence either referred to that action or to an equally plausible future action (e.g., sugaring strawberries). At the verb, people more often inspected the pancakes (the recent target) than the strawberries (the future target), thus replicating the recent-event preference with these real-world actions. Adverb tense, indicating a future versus past event, had no effect on participants’ visual attention. In a second study we increased the frequency of future actions such that participants saw 50/50 future and recent actions. During the verb people mostly inspected the recent action target, but subsequently they began to rely on tense, and anticipated the future target more often for future than past tense adverbs. A corpus study showed that the verbs and adverbs indicating past versus future actions were equally frequent, suggesting long-term frequency biases did not cause the recent-event preference. Thus, (a) recent real-world actions can rapidly influence comprehension (as indexed by eye gaze to objects), and (b) people prefer to first inspect a recent action target (vs. an object that will soon be acted upon), even when past and future actions occur with equal frequency. A simple frequency-of-experience account cannot accommodate these

  8. Real-time potentiometric detection of bacteria in complex samples.

    PubMed

    Zelada-Guillén, Gustavo A; Bhosale, Suryakant V; Riu, Jordi; Rius, F Xavier

    2010-11-15

    Detecting and identifying pathogen bacteria is essential to ensure quality at all stages of the food chain and to diagnose and control microbial infections. Traditional detection methods, including those based on cell culturing, are tedious and time-consuming, and their further application in real samples generally implies more complex pretreatment steps. Even though state-of-the-art techniques for detecting microorganisms enable the quantification of very low concentrations of bacteria, to date it has been difficult to obtain successful results in real samples in a simple, reliable, and rapid manner. In this Article, we demonstrate that the label-free detection and identification of living bacteria in real samples can be carried out in a couple of minutes and in a direct, simple, and selective way at concentration levels as low as 6 colony forming units/mL (CFU) in complex matrices such as milk or 26 CFU/mL in apple juice where the pretreatment step of samples is extremely easy. We chose Escherichia coli ( E. coli ) CECT 675 cells as a model organism as a nonpathogenic surrogate for pathogenic E. coli O157:H7 to test the effectiveness of a potentiometric aptamer-based biosensor. This biosensor uses single-walled carbon nanotubes (SWCNT) as excellent ion-to-electron transducers and covalently immobilized aptamers as biorecognition elements. The selective aptamer-target interaction significantly changes the electrical potential, thus allowing for both interspecies and interstrain selectivity and enabling the direct detection of the target. This technique is therefore a powerful tool for the immediate identification and detection of microorganisms. We demonstrate the highly selective detection of living bacteria with an immediate linear response of up to 10(4) CFU/mL. The biosensor can be easily built and used, is regenerated without difficulty, and can be used at least five times with no loss in the minimum amount of detected bacteria. PMID:20961052

  9. A novel seizure detection algorithm informed by hidden Markov model event states

    NASA Astrophysics Data System (ADS)

    Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian

    2016-06-01

    Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h‑1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.

  10. Human visual system-based smoking event detection

    NASA Astrophysics Data System (ADS)

    Odetallah, Amjad D.; Agaian, Sos S.

    2012-06-01

    Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

  11. Fast and robust microseismic event detection using very fast simulated annealing

    NASA Astrophysics Data System (ADS)

    Velis, Danilo R.; Sabbione, Juan I.; Sacchi, Mauricio D.

    2013-04-01

    The study of microseismic data has become an essential tool in many geoscience fields, including oil reservoir geophysics, mining and CO2 sequestration. In hydraulic fracturing, microseismicity studies permit the characterization and monitoring of the reservoir dynamics in order to optimize the production and the fluid injection process itself. As the number of events is usually large and the signal-to-noise ratio is in general very low, fast, automated, and robust detection algorithms are required for most applications. Also, real-time functionality is commonly needed to control the fluid injection in the field. Generally, events are located by means of grid search algorithms that rely on some approximate velocity model. These techniques are very effective and accurate, but computationally intensive when dealing with large three or four-dimensional grids. Here, we present a fast and robust method that allows to automatically detect and pick an event in 3C microseismic data without any input information about the velocity model. The detection is carried out by means of a very fast simulated annealing (VFSA) algorithm. To this end, we define an objective function that measures the energy of a potential microseismic event along the multichannel signal. This objective function is based on the stacked energy of the envelope of the signals calculated within a predefined narrow time window that depends on the source position, receivers geometry and velocity. Once an event has been detected, the source location can be estimated, in a second stage, by inverting the corresponding traveltimes using a standard technique, which would naturally require some knowledge of the velocity model. Since the proposed technique focuses on the detection of the microseismic events only, the velocity model is not required, leading to a fast algorithm that carries out the detection in real-time. Besides, the strategy is applicable to data with very low signal-to-noise ratios, for it relies

  12. Automatic event detection based on artificial neural networks

    NASA Astrophysics Data System (ADS)

    Doubravová, Jana; Wiszniowski, Jan; Horálek, Josef

    2015-04-01

    The proposed algorithm was developed to be used for Webnet, a local seismic network in West Bohemia. The Webnet network was built to monitor West Bohemia/Vogtland swarm area. During the earthquake swarms there is a large number of events which must be evaluated automatically to get a quick estimate of the current earthquake activity. Our focus is to get good automatic results prior to precise manual processing. With automatic data processing we may also reach a lower completeness magnitude. The first step of automatic seismic data processing is the detection of events. To get a good detection performance we require low number of false detections as well as high number of correctly detected events. We used a single layer recurrent neural network (SLRNN) trained by manual detections from swarms in West Bohemia in the past years. As inputs of the SLRNN we use STA/LTA of half-octave filter bank fed by vertical and horizontal components of seismograms. All stations were trained together to obtain the same network with the same neuron weights. We tried several architectures - different number of neurons - and different starting points for training. Networks giving the best results for training set must not be the optimal ones for unknown waveforms. Therefore we test each network on test set from different swarm (but still with similar characteristics, i.e. location, focal mechanisms, magnitude range). We also apply a coincidence verification for each event. It means that we can lower the number of false detections by rejecting events on one station only and force to declare an event on all stations in the network by coincidence on two or more stations. In further work we would like to retrain the network for each station individually so each station will have its own coefficients (neural weights) set. We would also like to apply this method to data from Reykjanet network located in Reykjanes peninsula, Iceland. As soon as we have a reliable detection, we can proceed to

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

    NASA Astrophysics Data System (ADS)

    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.

  14. Event-specific quantitative detection of nine genetically modified maizes using one novel standard reference molecule.

    PubMed

    Yang, Litao; Guo, Jinchao; Pan, Aihu; Zhang, Haibo; Zhang, Kewei; Wang, Zhengming; Zhang, Dabing

    2007-01-10

    With the development of genetically modified organism (GMO) detection techniques, the Polymerase Chain Reaction (PCR) technique has been the mainstay for GMO detection, and real-time PCR is the most effective and important method for GMO quantification. An event-specific detection strategy based on the unique and specific integration junction sequences between the host plant genome DNA and the integrated gene is being developed for its high specificity. This study establishes the event-specific detection methods for TC1507 and CBH351 maizes. In addition, the event-specific TaqMan real-time PCR detection methods for another seven GM maize events (Bt11, Bt176, GA21, MON810, MON863, NK603, and T25) were systematically optimized and developed. In these PCR assays, the fluorescent quencher, TAMRA, was dyed on the T-base of the probe at the internal position to improve the intensity of the fluorescent signal. To overcome the difficulties in obtaining the certified reference materials of these GM maizes, one novel standard reference molecule containing all nine specific integration junction sequences of these GM maizes and the maize endogenous reference gene, zSSIIb, was constructed and used for quantitative analysis. The limits of detection of these methods were 20 copies for these different GM maizes, the limits of quantitation were about 20 copies, and the dynamic ranges for quantification were from 0.05 to 100% in 100 ng of DNA template. Furthermore, nine groups of the mixed maize samples of these nine GM maize events were quantitatively analyzed to evaluate the accuracy and precision. The accuracy expressed as bias varied from 0.67 to 28.00% for the nine tested groups of GM maize samples, and the precision expressed as relative standard deviations was from 0.83 to 26.20%. All of these indicated that the established event-specific real-time PCR detection systems and the reference molecule in this study are suitable for the identification and quantification of these GM

  15. On-line Machine Learning and Event Detection in Petascale Data Streams

    NASA Astrophysics Data System (ADS)

    Thompson, David R.; Wagstaff, K. L.

    2012-01-01

    Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data

  16. Ontologies to capture adverse events following immunisation (AEFI) from real world health data.

    PubMed

    Liyanage, Harshana; de Lusignan, Simon

    2014-01-01

    Immunisation is an important part of health care and adverse events following immunisation (AEFI) are relatively rare. AEFI can be detected through long term follow up of a cohort or from looking for signals from real world, routine data; from different health systems using a variety of clinical coding systems. Mapping these is a challenging aspect of integrating data across borders. Ontological representations of clinical concepts provide a method to map similar concepts, in this case AEFI across different coding systems. We describe a method using ontologies to be flag definite, probable or possible cases. We use Guillain-Barre syndrome (GBS) as an AEFI to illustrate this method, and the Brighton collaboration's case definition of GBS as the gold standard. Our method can be used to flag definite, probable or possible cases of GBS. Whilst there has been much research into the use of ontologies in immunisation these have focussed on database interrogation; where ours looks to identify varying signal strength. PMID:24743070

  17. Detecting rare gene transfer events in bacterial populations.

    PubMed

    Nielsen, Kaare M; Bøhn, Thomas; Townsend, Jeffrey P

    2014-01-01

    Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research. PMID:24432015

  18. Detecting rare gene transfer events in bacterial populations

    PubMed Central

    Nielsen, Kaare M.; Bøhn, Thomas; Townsend, Jeffrey P.

    2014-01-01

    Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research. PMID:24432015

  19. Comparison of Event Detection Methods for Centralized Sensor Networks

    NASA Technical Reports Server (NTRS)

    Sauvageon, Julien; Agogiono, Alice M.; Farhang, Ali; Tumer, Irem Y.

    2006-01-01

    The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

  20. Detection and interpretation of seismoacoustic events at German infrasound stations

    NASA Astrophysics Data System (ADS)

    Pilger, Christoph; Koch, Karl; Ceranna, Lars

    2016-04-01

    Three infrasound arrays with collocated or nearby installed seismometers are operated by the Federal Institute for Geosciences and Natural Resources (BGR) as the German National Data Center (NDC) for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Infrasound generated by seismoacoustic events is routinely detected at these infrasound arrays, but air-to-ground coupled acoustic waves occasionally show up in seismometer recordings as well. Different natural and artificial sources like meteoroids as well as industrial and mining activity generate infrasonic signatures that are simultaneously detected at microbarometers and seismometers. Furthermore, many near-surface sources like earthquakes and explosions generate both seismic and infrasonic waves that can be detected successively with both technologies. The combined interpretation of seismic and acoustic signatures provides additional information about the origin time and location of remote infrasound events or about the characterization of seismic events distinguishing man-made and natural origins. Furthermore, seismoacoustic studies help to improve the modelling of infrasound propagation and ducting in the atmosphere and allow quantifying the portion of energy coupled into ground and into air by seismoacoustic sources. An overview of different seismoacoustic sources and their detection by German infrasound stations as well as some conclusions on the benefit of a combined seismoacoustic analysis are presented within this study.

  1. Microcontroller-based real-time QRS detection.

    PubMed

    Sun, Y; Suppappola, S; Wrublewski, T A

    1992-01-01

    The authors describe the design of a system for real-time detection of QRS complexes in the electrocardiogram based on a single-chip microcontroller (Motorola 68HC811). A systematic analysis of the instrumentation requirements for QRS detection and of the various design techniques is also given. Detection algorithms using different nonlinear transforms for the enhancement of QRS complexes are evaluated by using the ECG database of the American Heart Association. The results show that the nonlinear transform involving multiplication of three adjacent, sign-consistent differences in the time domain gives a good performance and a quick response. When implemented with an appropriate sampling rate, this algorithm is also capable of rejecting pacemaker spikes. The eight-bit single-chip microcontroller provides sufficient throughput and shows a satisfactory performance. Implementation of multiple detection algorithms in the same system improves flexibility and reliability. The low chip count in the design also favors maintainability and cost-effectiveness. PMID:1450792

  2. Real-time PCR detection of ruminant DNA.

    PubMed

    Mendoza-Romero, Luis; Verkaar, Edward L C; Savelkoul, Paul H; Catsburg, Arnold; Aarts, Henk J M; Buntjer, Jaap B; Lenstra, Johannes A

    2004-03-01

    To control the spread of bovine spongiform encephalopathy, several DNA methods have been described for the detection of the species origin of meat and bone meal. Most of these methods are based on the amplification of a mitochondrial DNA segment. We have developed a semiquantitative method based on real-time PCR for detection of ruminant DNA, targeting an 88-bp segment of the ruminant short interspersed nuclear element Bov-A2. This method is specific for ruminants and is able to detect as little as 10 fg of bovine DNA. Autoclaving decreased the amount of detectable DNA, but positive signals were observed in feeding stuff containing 10% bovine material if this had not been rendered in accordance with the regulations, i.e., heated at 134 degrees C for 3 instead of 20 min. PMID:15035372

  3. Real-time pose invariant logo and pattern detection

    NASA Astrophysics Data System (ADS)

    Sidla, Oliver; Kottmann, Michal; Benesova, Wanda

    2011-01-01

    The detection of pose invariant planar patterns has many practical applications in computer vision and surveillance systems. The recognition of company logos is used in market studies to examine the visibility and frequency of logos in advertisement. Danger signs on vehicles could be detected to trigger warning systems in tunnels, or brand detection on transport vehicles can be used to count company-specific traffic. We present the results of a study on planar pattern detection which is based on keypoint detection and matching of distortion invariant 2d feature descriptors. Specifically we look at the keypoint detectors of type: i) Lowe's DoG approximation from the SURF algorithm, ii) the Harris Corner Detector, iii) the FAST Corner Detector and iv) Lepetit's keypoint detector. Our study then compares the feature descriptors SURF and compact signatures based on Random Ferns: we use 3 sets of sample images to detect and match 3 logos of different structure to find out which combinations of keypoint detector/feature descriptors work well. A real-world test tries to detect vehicles with a distinctive logo in an outdoor environment under realistic lighting and weather conditions: a camera was mounted on a suitable location for observing the entrance to a parking area so that incoming vehicles could be monitored. In this 2 hour long recording we can successfully detect a specific company logo without false positives.

  4. Real-time people and vehicle detection from UAV imagery

    NASA Astrophysics Data System (ADS)

    Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

    2011-01-01

    A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

  5. PMU Data Event Detection: A User Guide for Power Engineers

    SciTech Connect

    Allen, A.; Singh, M.; Muljadi, E.; Santoso, S.

    2014-10-01

    This user guide is intended to accompany a software package containing a Matrix Laboratory (MATLAB) script and related functions for processing phasor measurement unit (PMU) data. This package and guide have been developed by the National Renewable Energy Laboratory and the University of Texas at Austin. The objective of this data processing exercise is to discover events in the vast quantities of data collected by PMUs. This document attempts to cover some of the theory behind processing the data to isolate events as well as the functioning of the MATLAB scripts. The report describes (1) the algorithms and mathematical background that the accompanying MATLAB codes use to detect events in PMU data and (2) the inputs required from the user and the outputs generated by the scripts.

  6. Gait Event Detection during Stair Walking Using a Rate Gyroscope

    PubMed Central

    Formento, Paola Catalfamo; Acevedo, Ruben; Ghoussayni, Salim; Ewins, David

    2014-01-01

    Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. These applications often require detection of the initial contact (IC) of the foot with the floor and/or final contact or foot off (FO) from the floor during outdoor walking. Previous investigations have reported the use of a single gyroscope placed on the shank for detection of IC and FO on level ground and incline walking. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects ascending and descending a set of stairs. Performance was compared with a reference pressure measurement system. The absolute mean difference between the gyroscope and the reference was less than 45 ms for IC and better than 135 ms for FO for both activities. Detection success was over 93%. These results provide preliminary evidence supporting the use of a gyroscope for gait event detection when walking up and down stairs. PMID:24651724

  7. Integrated Seismic Event Detection and Location by Advanced Array Processing

    SciTech Connect

    Kvaerna, T; Gibbons, S J; Ringdal, F; Harris, D B

    2007-02-09

    The principal objective of this two-year study is to develop and test a new advanced, automatic approach to seismic detection/location using array processing. We address a strategy to obtain significantly improved precision in the location of low-magnitude events compared with current fully-automatic approaches, combined with a low false alarm rate. We have developed and evaluated a prototype automatic system which uses as a basis regional array processing with fixed, carefully calibrated, site-specific parameters in conjuction with improved automatic phase onset time estimation. We have in parallel developed tools for Matched Field Processing for optimized detection and source-region identification of seismic signals. This narrow-band procedure aims to mitigate some of the causes of difficulty encountered using the standard array processing system, specifically complicated source-time histories of seismic events and shortcomings in the plane-wave approximation for seismic phase arrivals at regional arrays.

  8. Real-time Monitoring Network to Characterize Anthropogenic and Natural Events Affecting the Hudson River, NY

    NASA Astrophysics Data System (ADS)

    Islam, M. S.; Bonner, J. S.; Fuller, C.; Kirkey, W.; Ojo, T.

    2011-12-01

    The Hudson River watershed spans 34,700 km2 predominantly in New York State, including agricultural, wilderness, and urban areas. The Hudson River supports many activities including shipping, supplies water for municipal, commercial, and agricultural uses, and is an important recreational resource. As the population increases within this watershed, so does the anthropogenic impact on this natural system. To address the impacts of anthropogenic and natural activities on this ecosystem, the River and Estuary Observatory Network (REON) is being developed through a joint venture between the Beacon Institute, Clarkson University, General Electric Inc. and IBM Inc. to monitor New York's Hudson and Mohawk Rivers in real-time. REON uses four sensor platform types with multiple nodes within the network to capture environmentally relevant episodic events. Sensor platform types include: 1) fixed robotic vertical profiler (FRVP); 2) mobile robotic undulating platform (MRUP); 3) fixed acoustic Doppler current profiler (FADCP) and 4) Autonomous Underwater Vehicle (AUV). The FRVP periodically generates a vertical profile with respect to water temperature, salinity, dissolved oxygen, particle concentration and size distribution, and fluorescence. The MRUP utilizes an undulating tow-body tethered behind a research vessel to measure the same set of water parameters as the FRVP, but does so 'synchronically' over a highly-resolved spatial regime. The fixed ADCP provides continuous water current profiles. The AUV maps four-dimensional (time, latitude, longitude, depth) variation of water quality, water currents and bathymetry along a pre-determined transect route. REON data can be used to identify episodic events, both anthropogenic and natural, that impact the Hudson River. For example, a strong heat signature associated with cooling water discharge from the Indian Point nuclear power plant was detected with the MRUP. The FRVP monitoring platform at Beacon, NY, located in the

  9. Comprehensive GMO detection using real-time PCR array: single-laboratory validation.

    PubMed

    Mano, Junichi; Harada, Mioko; Takabatake, Reona; Furui, Satoshi; Kitta, Kazumi; Nakamura, Kosuke; Akiyama, Hiroshi; Teshima, Reiko; Noritake, Hiromichi; Hatano, Shuko; Futo, Satoshi; Minegishi, Yasutaka; Iizuka, Tayoshi

    2012-01-01

    We have developed a real-time PCR array method to comprehensively detect genetically modified (GM) organisms. In the method, genomic DNA extracted from an agricultural product is analyzed using various qualitative real-time PCR assays on a 96-well PCR plate, targeting for individual GM events, recombinant DNA (r-DNA) segments, taxon-specific DNAs, and donor organisms of the respective r-DNAs. In this article, we report the single-laboratory validation of both DNA extraction methods and component PCR assays constituting the real-time PCR array. We selected some DNA extraction methods for specified plant matrixes, i.e., maize flour, soybean flour, and ground canola seeds, then evaluated the DNA quantity, DNA fragmentation, and PCR inhibition of the resultant DNA extracts. For the component PCR assays, we evaluated the specificity and LOD. All DNA extraction methods and component PCR assays satisfied the criteria set on the basis of previous reports. PMID:22649939

  10. Statistical language analysis for automatic exfiltration event detection.

    SciTech Connect

    Robinson, David Gerald

    2010-04-01

    This paper discusses the recent development a statistical approach for the automatic identification of anomalous network activity that is characteristic of exfiltration events. This approach is based on the language processing method eferred to as latent dirichlet allocation (LDA). Cyber security experts currently depend heavily on a rule-based framework for initial detection of suspect network events. The application of the rule set typically results in an extensive list of uspect network events that are then further explored manually for suspicious activity. The ability to identify anomalous network events is heavily dependent on the experience of the security personnel wading through the network log. Limitations f this approach are clear: rule-based systems only apply to exfiltration behavior that has previously been observed, and experienced cyber security personnel are rare commodities. Since the new methodology is not a discrete rule-based pproach, it is more difficult for an insider to disguise the exfiltration events. A further benefit is that the methodology provides a risk-based approach that can be implemented in a continuous, dynamic or evolutionary fashion. This permits uspect network activity to be identified early with a quantifiable risk associated with decision making when responding to suspicious activity.

  11. Case-based damage assessment of storm events in near real-time

    NASA Astrophysics Data System (ADS)

    Möhrle, Stella; Mühr, Bernhard

    2015-04-01

    Damage assessment in times of crisis is complex due to a highly dynamic environment and uncertainty in respect of available information. In order to assess the extent of a disaster in near real-time, historic events and their consequences may facilitate first estimations. Events of the past, which are in the same category or which have similar frame conditions like imminent or just occurring storms, might give preliminary information about possible damages. The challenge here is to identify useful historic events based on little information regarding the current event. This work investigates the potential of drawing conclusions about a current event based on similar historic disasters, exemplarily for storm events in Germany. Predicted wind speed and area affected can be used for roughly classifying a storm event. For this purpose, a grid of equidistant points can be used to split up the area of Germany. In combination with predicted wind speed at these points and the predicted number of points affected, respectively, a storm can be categorized in a fast manner. In contrast to investigate only data taken by the observation network, the grid approach is more objective, since stations are not equally distributed. Based on model data, the determined storm class provides one key factor for identifying similar historic events. Further aspects, such as region or specific event characteristics, complete knowledge about the potential storm scale and result in a similarity function, which automatically identifies useful events from the past. This work presents a case-based approach to estimate damages in the event of an extreme storm event in Germany. The focus in on the similarity function, which is based on model storm classes, particularly wind speed and area affected. In order to determine possible damages more precisely, event specific characteristics and region will be included. In the frame of determining similar storm events, neighboring storm classes will be

  12. Hidden Markov Models for Detecting Aseismic Events in Southern California

    NASA Astrophysics Data System (ADS)

    Granat, R.

    2004-12-01

    We employ a hidden Markov model (HMM) to segment surface displacement time series collection by the Southern California Integrated Geodetic Network (SCIGN). These segmented time series are then used to detect regional events by observing the number of simultaneous mode changes across the network; if a large number of stations change at the same time, that indicates an event. The hidden Markov model (HMM) approach assumes that the observed data has been generated by an unobservable dynamical statistical process. The process is of a particular form such that each observation is coincident with the system being in a particular discrete state, which is interpreted as a behavioral mode. The dynamics are the model are constructed so that the next state is directly dependent only on the current state -- it is a first order Markov process. The model is completely described by a set of parameters: the initial state probabilities, the first order Markov chain state-to-state transition probabilities, and the probability distribution of observable outputs associated with each state. The result of this approach is that our segmentation decisions are based entirely on statistical changes in the behavior of the observed daily displacements. In general, finding the optimal model parameters to fit the data is a difficult problem. We present an innovative model fitting method that is unsupervised (i.e., it requires no labeled training data) and uses a regularized version of the expectation-maximization (EM) algorithm to ensure that model solutions are both robust with respect to initial conditions and of high quality. We demonstrate the reliability of the method as compared to standard model fitting methods and show that it results in lower noise in the mode change correlation signal used to detect regional events. We compare candidate events detected by this method to the seismic record and observe that most are not correlated with a significant seismic event. Our analysis

  13. Towards real-time regional earthquake simulation I: real-time moment tensor monitoring (RMT) for regional events in Taiwan

    NASA Astrophysics Data System (ADS)

    Lee, Shiann-Jong; Liang, Wen-Tzong; Cheng, Hui-Wen; Tu, Feng-Shan; Ma, Kuo-Fong; Tsuruoka, Hiroshi; Kawakatsu, Hitoshi; Huang, Bor-Shouh; Liu, Chun-Chi

    2014-01-01

    We have developed a real-time moment tensor monitoring system (RMT) which takes advantage of a grid-based moment tensor inversion technique and real-time broad-band seismic recordings to automatically monitor earthquake activities in the vicinity of Taiwan. The centroid moment tensor (CMT) inversion technique and a grid search scheme are applied to obtain the information of earthquake source parameters, including the event origin time, hypocentral location, moment magnitude and focal mechanism. All of these source parameters can be determined simultaneously within 117 s after the occurrence of an earthquake. The monitoring area involves the entire Taiwan Island and the offshore region, which covers the area of 119.3°E to 123.0°E and 21.0°N to 26.0°N, with a depth from 6 to 136 km. A 3-D grid system is implemented in the monitoring area with a uniform horizontal interval of 0.1° and a vertical interval of 10 km. The inversion procedure is based on a 1-D Green's function database calculated by the frequency-wavenumber (fk) method. We compare our results with the Central Weather Bureau (CWB) catalogue data for earthquakes occurred between 2010 and 2012. The average differences between event origin time and hypocentral location are less than 2 s and 10 km, respectively. The focal mechanisms determined by RMT are also comparable with the Broadband Array in Taiwan for Seismology (BATS) CMT solutions. These results indicate that the RMT system is realizable and efficient to monitor local seismic activities. In addition, the time needed to obtain all the point source parameters is reduced substantially compared to routine earthquake reports. By connecting RMT with a real-time online earthquake simulation (ROS) system, all the source parameters will be forwarded to the ROS to make the real-time earthquake simulation feasible. The RMT has operated offline (2010-2011) and online (since January 2012 to present) at the Institute of Earth Sciences (IES), Academia Sinica

  14. An airborne real-time hyperspectral target detection system

    NASA Astrophysics Data System (ADS)

    Skauli, Torbjorn; Haavardsholm, Trym V.; Kåsen, Ingebjørg; Arisholm, Gunnar; Kavara, Amela; Opsahl, Thomas Olsvik; Skaugen, Atle

    2010-04-01

    An airborne system for hyperspectral target detection is described. The main sensor is a HySpex pushbroom hyperspectral imager for the visible and near-infrared spectral range with 1600 pixels across track, supplemented by a panchromatic line imager. An optional third sensor can be added, either a SWIR hyperspectral camera or a thermal camera. In real time, the system performs radiometric calibration and georeferencing of the images, followed by image processing for target detection and visualization. The current version of the system implements only spectral anomaly detection, based on normal mixture models. Image processing runs on a PC with a multicore Intel processor and an Nvidia graphics processing unit (GPU). The processing runs in a software framework optimized for large sustained data rates. The platform is a Cessna 172 aircraft based close to FFI, modified with a camera port in the floor.

  15. Real-time misfire detection via sliding mode observer

    NASA Astrophysics Data System (ADS)

    Wang, Yunsong; Chu, Fulei

    2005-07-01

    A new method to detect misfire in internal combustion engines is presented. It is based on the estimation of the cylinder deviation torque by using sliding mode observer. The input estimation problem is transformed into the control tracking problem. The sliding controller is utilised to continuously track the measured varying crank speed by changing the estimated deviation torque. During the process of tracking, the speed estimation errors decrease and the gradual stability of the dynamics is assured. The mean deviation torque during the power stroke derived from the estimated deviation torque can be employed to detect easily engine misfires. Experimental results for a four-cylinder engine indicate that the method is a suitable tool for real-time misfire detection on board vehicle under various working conditions.

  16. Jump point detection for real estate investment success

    NASA Astrophysics Data System (ADS)

    Hui, Eddie C. M.; Yu, Carisa K. W.; Ip, Wai-Cheung

    2010-03-01

    In the literature, studies on real estate market were mainly concentrating on the relation between property price and some key factors. The trend of the real estate market is a major concern. It is believed that changes in trend are signified by some jump points in the property price series. Identifying such jump points reveals important findings that enable policy-makers to look forward. However, not all jump points are observable from the plot of the series. This paper looks into the trend and introduces a new approach to the framework for real estate investment success. The main purpose of this paper is to detect jump points in the time series of some housing price indices and stock price index in Hong Kong by applying the wavelet analysis. The detected jump points reflect to some significant political issues and economic collapse. Moreover, the relations among properties of different classes and between stocks and properties are examined. It can be shown from the empirical result that a lead-lag effect happened between the prices of large-size property and those of small/medium-size property. However, there is no apparent relation or consistent lead in terms of change point measure between property price and stock price. This may be due to the fact that globalization effect has more impact on the stock price than the property price.

  17. Motor task event detection using Subthalamic Nucleus Local Field Potentials.

    PubMed

    Niketeghad, Soroush; Hebb, Adam O; Nedrud, Joshua; Hanrahan, Sara J; Mahoor, Mohammad H

    2015-08-01

    Deep Brain Stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson's disease. Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and DBS side effects. In such systems, DBS parameters are adjusted based on patient's behavior, which means that behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local Field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. A practical behavior detection method should be able to detect behaviors asynchronously meaning that it should not use any prior knowledge of behavior onsets. In this paper, we introduce a behavior detection method that is able to asynchronously detect the finger movements of Parkinson patients. As a result of this study, we learned that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We used non-linear regression method to measure this connectivity and use it to detect the finger movements. Performance of this method is evaluated using Receiver Operating Characteristic (ROC). PMID:26737550

  18. Lessons Learned from Real-Time, Event-Based Internet Science Communications

    NASA Technical Reports Server (NTRS)

    Phillips, T.; Myszka, E.; Gallagher, D. L.; Adams, M. L.; Koczor, R. J.; Whitaker, Ann F. (Technical Monitor)

    2001-01-01

    For the last several years the Science Directorate at Marshall Space Flight Center has carried out a diverse program of Internet-based science communication. The Directorate's Science Roundtable includes active researchers, NASA public relations, educators, and administrators. The Science@NASA award-winning family of Web sites features science, mathematics, and space news. The program includes extended stories about NASA science, a curriculum resource for teachers tied to national education standards, on-line activities for students, and webcasts of real-time events. The focus of sharing science activities in real-time has been to involve and excite students and the public about science. Events have involved meteor showers, solar eclipses, natural very low frequency radio emissions, and amateur balloon flights. In some cases, broadcasts accommodate active feedback and questions from Internet participants. Through these projects a pattern has emerged in the level of interest or popularity with the public. The pattern differentiates projects that include science from those that do not, All real-time, event-based Internet activities have captured public interest at a level not achieved through science stories or educator resource material exclusively. The worst event-based activity attracted more interest than the best written science story. One truly rewarding lesson learned through these projects is that the public recognizes the importance and excitement of being part of scientific discovery. Flying a camera to 100,000 feet altitude isn't as interesting to the public as searching for viable life-forms at these oxygen-poor altitudes. The details of these real-time, event-based projects and lessons learned will be discussed.

  19. Energy Reconstruction for Events Detected in TES X-ray Detectors

    NASA Astrophysics Data System (ADS)

    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.

  20. A handheld real time thermal cycler for bacterial pathogen detection.

    PubMed

    Higgins, James A; Nasarabadi, Shanavaz; Karns, Jeffrey S; Shelton, Daniel R; Cooper, Mary; Gbakima, Aiah; Koopman, Ronald P

    2003-08-15

    The handheld advanced nucleic acid analyzer (HANAA) is a portable real time thermal cycler unit that weighs under 1 kg and uses silicon and platinum-based thermalcycler units to conduct rapid heating and cooling of plastic reaction tubes. Two light emitting diodes (LED) provide greater than 1 mW of electrical power at wavelengths of 490 nm (blue) and 525 nm (green), allowing detection of the dyes FAM and JOE/TAMRA. Results are displayed in real time as bar graphs, and up to three, 4-sample assays can be run on the charge of the 12 V portable battery pack. The HANAA was evaluated for detection of defined Escherichia coli strains, and wild-type colonies isolated from stream water, using PCR for the lac Z and Tir genes. PCR reactions using SYBR Green dye allowed detection of E. coli ATCC 11775 and E. coli O157:H7 cells in under 30 min of assay time; however, background fluorescence associated with dye binding to nonspecific PCR products was present. DNA extracted from three isolates of Bacillus anthracis Ames, linked to a bioterrorism incident in Washington DC in October 2001, were also successfully tested on the HANAA using primers for the vrrA and capA genes. Positive results were observed at 32 and 22 min of assay time, respectively. A TaqMan probe specific to the aroQ gene of Erwinia herbicola was tested on the HANAA and when 500 cells were used as template, positive results were observed after only 7 min of assay time. Background fluorescence associated with the use of the probe was negligible. The HANAA is unique in offering real time PCR in a handheld format suitable for field use; a commercial version of the instrument, offering six reaction chambers, is available as of Fall 2002. PMID:12788554

  1. Feature selection of seismic waveforms for long period event detection at Cotopaxi Volcano

    NASA Astrophysics Data System (ADS)

    Lara-Cueva, R. A.; Benítez, D. S.; Carrera, E. V.; Ruiz, M.; Rojo-Álvarez, J. L.

    2016-04-01

    Volcano Early Warning Systems (VEWS) have become a research topic in order to preserve human lives and material losses. In this setting, event detection criteria based on classification using machine learning techniques have proven useful, and a number of systems have been proposed in the literature. However, to the best of our knowledge, no comprehensive and principled study has been conducted to compare the influence of the many different sets of possible features that have been used as input spaces in previous works. We present an automatic recognition system of volcano seismicity, by considering feature extraction, event classification, and subsequent event detection, in order to reduce the processing time as a first step towards a high reliability automatic detection system in real-time. We compiled and extracted a comprehensive set of temporal, moving average, spectral, and scale-domain features, for separating long period seismic events from background noise. We benchmarked two usual kinds of feature selection techniques, namely, filter (mutual information and statistical dependence) and embedded (cross-validation and pruning), each of them by using suitable and appropriate classification algorithms such as k Nearest Neighbors (k-NN) and Decision Trees (DT). We applied this approach to the seismicity presented at Cotopaxi Volcano in Ecuador during 2009 and 2010. The best results were obtained by using a 15 s segmentation window, feature matrix in the frequency domain, and DT classifier, yielding 99% of detection accuracy and sensitivity. Selected features and their interpretation were consistent among different input spaces, in simple terms of amplitude and spectral content. Our study provides the framework for an event detection system with high accuracy and reduced computational requirements.

  2. Real-time beyond the horizon vessel detection

    NASA Astrophysics Data System (ADS)

    Roarty, Hugh J.; Smith, Michael; Glenn, Scott M.; Barrick, Donald E.

    2013-05-01

    The marine transportation system (MTS) is a vital component of the United States Economy. Waterborne cargo accounts for more than $742 billion of the nation's economy and creates employment for 13 million citizens. A disruption in this system would have far reaching consequences to the security of the country. The US National High Frequency radar network, which comprises 130 radar stations around the country, became operational in May 2009. It provides hourly measurements of surface currents to the US Coast Guard for search and rescue (SAR). This system has the capability of being a dual use system providing information for environmental monitoring as well as vessel position information for maritime security. Real time vessel detection has been implemented at two of the radar stations outside New York Harbor. Several experiments were conducted to see the amount vessel traffic that the radar could capture. The radars were able to detect a majority of the vessels that are reporting via the Automatic Identification System (AIS) as well as 30 percent of mid to large size vessels that are not reporting via AIS. The radars were able to detect vessels out to 60 km from the coast. The addition of a vessel detection capability to the National HF radar network will provide valuable information to maritime security sector. This dual use capability will fill a gap in the current surveillance of US coastal waters. It will also provide longer-range situational awareness necessary to detect and track smaller size vessels in the large vessel clutter.

  3. Direct Real-Time Detection of Vapors from Explosive Compounds

    SciTech Connect

    Ewing, Robert G.; Clowers, Brian H.; Atkinson, David A.

    2013-10-03

    The real-time detection of vapors from low volatility explosives including PETN, tetryl, RDX and nitroglycerine along with various compositions containing these substances is demonstrated. This was accomplished with an atmospheric flow tube (AFT) using a non-radioactive ionization source and coupled to a mass spectrometer. Direct vapor detection was demonstrated in less than 5 seconds at ambient temperature without sample pre-concentration. The several seconds of residence time of analytes in the AFT provides a significant opportunity for reactant ions to interact with analyte vapors to achieve ionization. This extended reaction time, combined with the selective ionization using the nitrate reactant ions (NO3- and NO3-•HNO3), enables highly sensitive explosives detection. Observed signals from diluted explosive vapors indicate detection limits below 10 ppqv using selected ion monitoring (SIM) of the explosive-nitrate adduct at m/z 349, 378, 284 and 289 for tetryl, PETN, RDX and NG respectively. Also provided is a demonstration of the vapor detection from 10 different energetic formulations, including double base propellants, plastic explosives and commercial blasting explosives using SIM for the NG, PETN and RDX product ions.

  4. Direct real-time detection of vapors from explosive compounds.

    PubMed

    Ewing, Robert G; Clowers, Brian H; Atkinson, David A

    2013-11-19

    The real-time detection of vapors from low volatility explosives including PETN, tetryl, RDX, and nitroglycerine along with various compositions containing these substances was demonstrated. This was accomplished with an atmospheric flow tube (AFT) using a nonradioactive ionization source coupled to a mass spectrometer. Direct vapor detection was accomplished in less than 5 s at ambient temperature without sample preconcentration. The several seconds of residence time of analytes in the AFT provided a significant opportunity for reactant ions to interact with analyte vapors to achieve ionization. This extended reaction time, combined with the selective ionization using the nitrate reactant ions (NO3(-) and NO3(-)·HNO3), enabled highly sensitive explosives detection from explosive vapors present in ambient laboratory air. Observed signals from diluted explosive vapors indicated detection limits below 10 ppqv using selected ion monitoring (SIM) of the explosive-nitrate adduct at m/z 349, 378, 284, and 289 for tetryl, PETN, RDX, and NG, respectively. Also provided is a demonstration of the vapor detection from 10 different energetic formulations sampled in ambient laboratory air, including double base propellants, plastic explosives, and commercial blasting explosives using SIM for the NG, PETN, and RDX product ions. PMID:24090362

  5. The Value of Real-time High Resolution Satellite Precipitation in Capturing Extreme Rainfall Event

    NASA Astrophysics Data System (ADS)

    Imam, B.; Kuranjekar, P.; Behrangi, A.; Hsu, K.; Sorooshian, S.

    2008-05-01

    In many parts of the world, operational real-time flood and hydrologic forecasting are hindered by the lack of reliable real-time precipitation observations. The insufficient ground observations have made satellite-based precipitation estimates the only available source for wide coverage data. As the spatial and temporal resolution of satellite-based rainfall estimates continue to improve, assessing the usefulness of these products, particularly in capturing extreme precipitation events becomes an important issue. This presentation demonstrates and discusses a framework for evaluating real-time high resolution precipitation products in terms of their operational utility. As an example of operational high resolution precipitation products, the 3 hourly near real-time, 0.04°x0.04° Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) (Hong et. al., 2004) product is compared against gauge and NEXRAD observations of several heavy precipitation events including tropical storm Erin, which affected Texas and Oklahoma during the period of August 10-20, 2007. For each storm, a swath of precipitation along the storm track is analyzed using both real-time and quality controlled versions of the products. Traditional as well as threshold- based (e.g. verification) performance measures are used to describe differences between NEXRAD and Satellite observations' ability to capture severe storm characteristics within the target area and to assess possible shifts in rainfall amount spectrum. While not fully conclusive, the results indicate that for operational purposes, high resolution satellite-based precipitation estimates can fill in a much needed observational gap during severe storm events.

  6. Swarm intelligence for detecting interesting events in crowded environments.

    PubMed

    Kaltsa, Vagia; Briassouli, Alexia; Kompatsiaris, Ioannis; Hadjileontiadis, Leontios J; Strintzis, Michael Gerasimos

    2015-07-01

    This paper focuses on detecting and localizing anomalous events in videos of crowded scenes, i.e., divergences from a dominant pattern. Both motion and appearance information are considered, so as to robustly distinguish different kinds of anomalies, for a wide range of scenarios. A newly introduced concept based on swarm theory, histograms of oriented swarms (HOS), is applied to capture the dynamics of crowded environments. HOS, together with the well-known histograms of oriented gradients, are combined to build a descriptor that effectively characterizes each scene. These appearance and motion features are only extracted within spatiotemporal volumes of moving pixels to ensure robustness to local noise, increase accuracy in the detection of local, nondominant anomalies, and achieve a lower computational cost. Experiments on benchmark data sets containing various situations with human crowds, as well as on traffic data, led to results that surpassed the current state of the art (SoA), confirming the method's efficacy and generality. Finally, the experiments show that our approach achieves significantly higher accuracy, especially for pixel-level event detection compared to SoA methods, at a low computational cost. PMID:25769154

  7. Endmember detection in marine environment with oil spill event

    NASA Astrophysics Data System (ADS)

    Andreou, Charoula; Karathanassi, Vassilia

    2011-11-01

    Oil spill events are a crucial environmental issue. Detection of oil spills is important for both oil exploration and environmental protection. In this paper, investigation of hyperspectral remote sensing is performed for the detection of oil spills and the discrimination of different oil types. Spectral signatures of different oil types are very useful, since they may serve as endmembers in unmixing and classification models. Towards this direction, an oil spectral library, resulting from spectral measurements of artificial oil spills as well as of look-alikes in marine environment was compiled. Samples of four different oil types were used; two crude oils, one marine residual fuel oil, and one light petroleum product. Lookalikes comprise sea water, river discharges, shallow water and water with algae. Spectral measurements were acquired with spectro-radiometer GER1500. Moreover, oil and look-alikes spectral signatures have been examined whether they can be served as endmembers. This was accomplished by testifying their linear independence. After that, synthetic hyperspectral images based on the relevant oil spectral library were created. Several simplex-based endmember algorithms such as sequential maximum angle convex cone (SMACC), vertex component analysis (VCA), n-finder algorithm (N-FINDR), and automatic target generation process (ATGP) were applied on the synthetic images in order to evaluate their effectiveness for detecting oil spill events occurred from different oil types. Results showed that different types of oil spills with various thicknesses can be extracted as endmembers.

  8. Optimizing the real-time automatic location of the events produced in Romania using an advanced processing system

    NASA Astrophysics Data System (ADS)

    Neagoe, Cristian; Grecu, Bogdan; Manea, Liviu

    2016-04-01

    National Institute for Earth Physics (NIEP) operates a real time seismic network which is designed to monitor the seismic activity on the Romanian territory, which is dominated by the intermediate earthquakes (60-200 km) from Vrancea area. The ability to reduce the impact of earthquakes on society depends on the existence of a large number of high-quality observational data. The development of the network in recent years and an advanced seismic acquisition are crucial to achieving this objective. The software package used to perform the automatic real-time locations is Seiscomp3. An accurate choice of the Seiscomp3 setting parameters is necessary to ensure the best performance of the real-time system i.e., the most accurate location for the earthquakes and avoiding any false events. The aim of this study is to optimize the algorithms of the real-time system that detect and locate the earthquakes in the monitored area. This goal is pursued by testing different parameters (e.g., STA/LTA, filters applied to the waveforms) on a data set of representative earthquakes of the local seismicity. The results are compared with the locations from the Romanian Catalogue ROMPLUS.

  9. Close to real-time robust pedestrian detection and tracking

    NASA Astrophysics Data System (ADS)

    Lipetski, Y.; Loibner, G.; Sidla, O.

    2015-03-01

    Fully automated video based pedestrian detection and tracking is a challenging task with many practical and important applications. We present our work aimed to allow robust and simultaneously close to real-time tracking of pedestrians. The presented approach is stable to occlusions, lighting conditions and is generalized to be applied on arbitrary video data. The core tracking approach is built upon tracking-by-detections principle. We describe our cascaded HOG detector with successive CNN verification in detail. For the tracking and re-identification task, we did an extensive analysis of appearance based features as well as their combinations. The tracker was tested on many hours of video data for different scenarios; the results are presented and discussed.

  10. An Automated Visual Event Detection System for Cabled Observatory Video

    NASA Astrophysics Data System (ADS)

    Edgington, D. R.; Cline, D. E.; Mariette, J.

    2007-12-01

    The permanent presence of underwater cameras on oceanic cabled observatories, such as the Victoria Experimental Network Under the Sea (VENUS) and Eye-In-The-Sea (EITS) on Monterey Accelerated Research System (MARS), will generate valuable data that can move forward the boundaries of understanding the underwater world. However, sightings of underwater animal activities are rare, resulting in the recording of many hours of video with relatively few events of interest. The burden of video management and analysis often requires reducing the amount of video recorded and later analyzed. Sometimes enough human resources do not exist to analyze the video; the strains on human attention needed to analyze video demand an automated way to assist in video analysis. Towards this end, an Automated Visual Event Detection System (AVED) is in development at the Monterey Bay Aquarium Research Institute (MBARI) to address the problem of analyzing cabled observatory video. Here we describe the overall design of the system to process video data and enable science users to analyze the results. We present our results analyzing video from the VENUS observatory and test data from EITS deployments. This automated system for detecting visual events includes a collection of custom and open source software that can be run three ways: through a Web Service, through a Condor managed pool of AVED enabled compute servers, or locally on a single computer. The collection of software also includes a graphical user interface to preview or edit detected results and to setup processing options. To optimize the compute-intensive AVED algorithms, a parallel program has been implemented for high-data rate applications like the EITS instrument on MARS.

  11. Aircraft Fault Detection Using Real-Time Frequency Response Estimation

    NASA Technical Reports Server (NTRS)

    Grauer, Jared A.

    2016-01-01

    A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

  12. Use of sonification in the detection of anomalous events

    NASA Astrophysics Data System (ADS)

    Ballora, Mark; Cole, Robert J.; Kruesi, Heidi; Greene, Herbert; Monahan, Ganesh; Hall, David L.

    2012-06-01

    In this paper, we describe the construction of a soundtrack that fuses stock market data with information taken from tweets. This soundtrack, or auditory display, presents the numerical and text data in such a way that anomalous events may be readily detected, even by untrained listeners. The soundtrack generation is flexible, allowing an individual listener to create a unique audio mix from the available information sources. Properly constructed, the display exploits the auditory system's sensitivities to periodicities, to dynamic changes, and to patterns. This type of display could be valuable in environments that demand high levels of situational awareness based on multiple sources of incoming information.

  13. The waveform correlation event detection system global prototype software design

    SciTech Connect

    Beiriger, J.I.; Moore, S.G.; Trujillo, J.R.; Young, C.J.

    1997-12-01

    The WCEDS prototype software system was developed to investigate the usefulness of waveform correlation methods for CTBT monitoring. The WCEDS prototype performs global seismic event detection and has been used in numerous experiments. This report documents the software system design, presenting an overview of the system operation, describing the system functions, tracing the information flow through the system, discussing the software structures, and describing the subsystem services and interactions. The effectiveness of the software design in meeting project objectives is considered, as well as opportunities for code refuse and lessons learned from the development process. The report concludes with recommendations for modifications and additions envisioned for regional waveform-correlation-based detector.

  14. Real-time weed detection in outdoor field conditions

    NASA Astrophysics Data System (ADS)

    Steward, Brian L.; Tian, Lei F.

    1999-01-01

    Though most herbicide is applied uniformly in agronomic fields, there is strong evidence that weeds are not distributed uniformly within the crop fields. If an effective weed detection system were developed, both economic and environmental benefits would result from its use for site-specific weed management. Past work in this area has focused mainly on either low spatial resolution photo-detectors or off-line machine vision system. This study was undertaken to develop real-time machine vision weed detection for outdoor lighting conditions. The novel environmentally adaptive segmentation algorithm was developed with the objective of real-time operation on an on-board computer-based system. The EASA used cluster analysis to group pixels of homogeneous color regions of the image together which formed the basis for image segmentation. The performance of several variations of this algorithm was measured by comparing segmented field images produced by the EASA, fixed-color HSI region segmentation, and ISODATA clustering with hand-=segmented reference images. The time cost and questionable accuracy of hand- segmented reference images led to exploration of the use of computer-segmented reference images. Sensitivity and background sensitivity were used as performance measured. Significant differences were found between the means of sensitivity, background sensitivity, and overall performance across segmentation schemes. Similar results were obtained with computer-segmented reference images.

  15. Model-based approach to real-time target detection

    NASA Astrophysics Data System (ADS)

    Hackett, Jay K.; Gold, Ed V.; Long, Daniel T.; Cloud, Eugene L.; Duvoisin, Herbert A.

    1992-09-01

    Land mine detection and extraction from infra-red (IR) scenes using real-time parallel processing is of significant interest to ground based infantry. The mine detection algorithms consist of several sub-processes to progress from raw input IR imagery to feature based mine nominations. Image enhancement is first applied; this consists of noise and sensor artifact removal. Edge grouping is used to determine the boundary of the objects. The generalized Hough Transform tuned to the land mine signature acts as a model based matched nomination filter. Once the object is found, the model is used to guide the labeling of each pixel as background, object, or object boundary. Using these labels to identify object regions, feature primitives are extracted in a high speed parallel processor. A feature based screener then compares each object's feature primitives to acceptable values and rejects all objects that do not resemble mines. This operation greatly reduces the number of objects that must be passed from a real-time parallel processor to the classifier. We will discuss details of this model- based approach, including results from actual IR field test imagery.

  16. Real-time extreme weather event attribution with forecast seasonal SSTs

    NASA Astrophysics Data System (ADS)

    Haustein, K.; Otto, F. E. L.; Uhe, P.; Schaller, N.; Allen, M. R.; Hermanson, L.; Christidis, N.; McLean, P.; Cullen, H.

    2016-06-01

    Within the last decade, extreme weather event attribution has emerged as a new field of science and garnered increasing attention from the wider scientific community and the public. Numerous methods have been put forward to determine the contribution of anthropogenic climate change to individual extreme weather events. So far nearly all such analyses were done months after an event has happened. Here we present a new method which can assess the fraction of attributable risk of a severe weather event due to an external driver in real-time. The method builds on a large ensemble of atmosphere-only general circulation model simulations forced by seasonal forecast sea surface temperatures (SSTs). Taking the England 2013/14 winter floods as an example, we demonstrate that the change in risk for heavy rainfall during the England floods due to anthropogenic climate change, is of similar magnitude using either observed or seasonal forecast SSTs. Testing the dynamic response of the model to the anomalous ocean state for January 2014, we find that observed SSTs are required to establish a discernible link between a particular SST pattern and an atmospheric response such as a shift in the jetstream in the model. For extreme events occurring under strongly anomalous SST patterns associated with known low-frequency climate modes, however, forecast SSTs can provide sufficient guidance to determine the dynamic contribution to the event.

  17. Automatic adverse drug events detection using letters to the editor.

    PubMed

    Yang, Chao; Srinivasan, Padmini; Polgreen, Philip M

    2012-01-01

    We present and test the intuition that letters to the editor in journals carry early signals of adverse drug events (ADEs). Surprisingly these letters have not yet been exploited for automatic ADE detection unlike for example, clinical records and PubMed. Part of the challenge is that it is not easy to access the full-text of letters (for the most part these do not appear in PubMed). Also letters are likely underrated in comparison with full articles. Besides demonstrating that this intuition holds we contribute techniques for post market drug surveillance. Specifically, we test an automatic approach for ADE detection from letters using off-the-shelf machine learning tools. We also involve natural language processing for feature definitions. Overall we achieve high accuracy in our experiments and our method also works well on a second new test set. Our results encourage us to further pursue this line of research. PMID:23304379

  18. Automatic Adverse Drug Events Detection Using Letters to the Editor

    PubMed Central

    Yang, Chao; Srinivasan, Padmini; Polgreen, Philip M.

    2012-01-01

    We present and test the intuition that letters to the editor in journals carry early signals of adverse drug events (ADEs). Surprisingly these letters have not yet been exploited for automatic ADE detection unlike for example, clinical records and PubMed. Part of the challenge is that it is not easy to access the full-text of letters (for the most part these do not appear in PubMed). Also letters are likely underrated in comparison with full articles. Besides demonstrating that this intuition holds we contribute techniques for post market drug surveillance. Specifically, we test an automatic approach for ADE detection from letters using off-the-shelf machine learning tools. We also involve natural language processing for feature definitions. Overall we achieve high accuracy in our experiments and our method also works well on a second new test set. Our results encourage us to further pursue this line of research. PMID:23304379

  19. Detection and analysis of microseismic events using a Matched Filtering Algorithm (MFA)

    NASA Astrophysics Data System (ADS)

    Caffagni, Enrico; Eaton, David W.; Jones, Joshua P.; van der Baan, Mirko

    2016-07-01

    A new Matched Filtering Algorithm (MFA) is proposed for detecting and analysing microseismic events recorded by downhole monitoring of hydraulic fracturing. This method requires a set of well-located template (`parent') events, which are obtained using conventional microseismic processing and selected on the basis of high signal-to-noise (S/N) ratio and representative spatial distribution of the recorded microseismicity. Detection and extraction of `child' events are based on stacked, multichannel cross-correlation of the continuous waveform data, using the parent events as reference signals. The location of a child event relative to its parent is determined using an automated process, by rotation of the multicomponent waveforms into the ray-centred co-ordinates of the parent and maximizing the energy of the stacked amplitude envelope within a search volume around the parent's hypocentre. After correction for geometrical spreading and attenuation, the relative magnitude of the child event is obtained automatically using the ratio of stacked envelope peak with respect to its parent. Since only a small number of parent events require interactive analysis such as picking P- and S-wave arrivals, the MFA approach offers the potential for significant reduction in effort for downhole microseismic processing. Our algorithm also facilitates the analysis of single-phase child events, that is, microseismic events for which only one of the S- or P-wave arrivals is evident due to unfavourable S/N conditions. A real-data example using microseismic monitoring data from four stages of an open-hole slickwater hydraulic fracture treatment in western Canada demonstrates that a sparse set of parents (in this case, 4.6 per cent of the originally located events) yields a significant (more than fourfold increase) in the number of located events compared with the original catalogue. Moreover, analysis of the new MFA catalogue suggests that this approach leads to more robust interpretation

  20. Detection and analysis of microseismic events using a Matched Filtering Algorithm (MFA)

    NASA Astrophysics Data System (ADS)

    Caffagni, Enrico; Eaton, David W.; Jones, Joshua P.; van der Baan, Mirko

    2016-05-01

    A new Matched Filtering Algorithm (MFA) is proposed for detecting and analyzing microseismic events recorded by downhole monitoring of hydraulic fracturing. This method requires a set of well-located template (`parent') events, which are obtained using conventional microseismic processing and selected on the basis of high signal-to-noise (S/N) ratio and representative spatial distribution of the recorded microseismicity. Detection and extraction of `child' events are based on stacked, multi-channel cross-correlation of the continuous waveform data, using the parent events as reference signals. The location of a child event relative to its parent is determined using an automated process, by rotation of the multi-component waveforms into the ray-centered co-ordinates of the parent and maximizing the energy of the stacked amplitude envelope within a search volume around the parent's hypocentre. After correction for geometrical spreading and attenuation, the relative magnitude of the child event is obtained automatically using the ratio of stacked envelope peak with respect to its parent. Since only a small number of parent events require interactive analysis such as picking P- and S-wave arrivals, the MFA approach offers the potential for significant reduction in effort for downhole microseismic processing. Our algorithm also facilitates the analysis of single-phase child events, i.e. microseismic events for which only one of the S- or P-wave arrival is evident due to unfavorable S/N conditions. A real-data example using microseismic monitoring data from 4 stages of an open-hole slickwater hydraulic fracture treatment in western Canada demonstrates that a sparse set of parents (in this case, 4.6 per cent of the originally located events) yields a significant (more than four-fold increase) in the number of located events compared with the original catalog. Moreover, analysis of the new MFA catalog suggests that this approach leads to more robust interpretation of the

  1. Validation of real-time PCR assays for bioforensic detection of model plant pathogens.

    PubMed

    James, Mindy; Blagden, Trenna; Moncrief, Ian; Burans, James P; Schneider, Katherine; Fletcher, Jacqueline

    2014-03-01

    The U.S. agricultural sector is vulnerable to intentionally introduced microbial threats because of its wide and open distribution and economic importance. To investigate such events, forensically valid assays for plant pathogen detection are needed. In this work, real-time PCR assays were developed for three model plant pathogens: Pseudomonas syringae pathovar tomato, Xylella fastidiosa, and Wheat streak mosaic virus. Validation included determination of the linearity and range, limit of detection, sensitivity, specificity, and exclusivity of each assay. Additionally, positive control plasmids, distinguishable from native signature by restriction enzyme digestion, were developed to support forensic application of the assays. Each assay displayed linear amplification of target nucleic acid, detected 100 fg or less of target nucleic acid, and was specific to its target pathogen. Results obtained with these model pathogens provide the framework for development and validation of similar assays for other plant pathogens of high consequence. PMID:24261870

  2. Development and characterization of a microheater array device for real-time DNA mutation detection

    NASA Astrophysics Data System (ADS)

    Williams, Layne; Okandan, Murat; Chagovetz, Alex; Blair, Steve

    2008-04-01

    DNA analysis, specifically single nucleotide polymorphism (SNP) detection, is becoming increasingly important in rapid diagnostics and disease detection. Temperature is often controlled to help speed reaction rates and perform melting of hybridized oligonucleotides. The difference in melting temperatures, Tm, between wild-type and SNP sequences, respectively, to a given probe oligonucleotide, is indicative of the specificity of the reaction. We have characterized Tm's in solution and on a solid substrate of three sequences from known mutations associated with Cystic Fibrosis. Taking advantage of Tm differences, a microheater array device was designed to enable individual temperature control of up to 18 specific hybridization events. The device was fabricated at Sandia National Laboratories using surface micromachining techniques. The microheaters have been characterized using an IR camera at Sandia and show individual temperature control with minimal thermal cross talk. Development of the device as a real-time DNA detection platform, including surface chemistry and associated microfluidics, is described.

  3. Development and characterization of a microheater array device for real-time DNA mutation detection

    NASA Astrophysics Data System (ADS)

    Williams, Layne; Okandan, Murat; Chagovetz, Alex; Blair, Steve

    2008-02-01

    DNA analysis, specifically single nucleotide polymorphism (SNP) detection, is becoming increasingly important in rapid diagnostics and disease detection. Temperature is often controlled to help speed reaction rates and perform melting of hybridized oligonucleotides. The difference in melting temperatures, Tm, between wild-type and SNP sequences, respectively, to a given probe oligonucleotide, is indicative of the specificity of the reaction. We have characterized Tm's in solution and on a solid substrate of three sequences from known mutations associated with Cystic Fibrosis. Taking advantage of Tm differences, a microheater array device was designed to enable individual temperature control of up to 18 specific hybridization events. The device was fabricated at Sandia National Laboratories using surface micromachining techniques. The microheaters have been characterized using an IR camera at Sandia and show individual temperature control with minimal thermal cross talk. Development of the device as a real-time DNA detection platform, including surface chemistry and associated microfluidics, is described.

  4. Increased SERS detection efficiency for characterizing rare events in flow.

    PubMed

    Jacobs, Kevin T; Schultz, Zachary D

    2015-08-18

    Improved surface-enhanced Raman scattering (SERS) measurements of a flowing aqueous sample are accomplished by combining line focus optics with sheath-flow SERS detection. The straightforward introduction of a cylindrical lens into the optical path of the Raman excitation laser increases the efficiency of SERS detection and the reproducibility of SERS signals at low concentrations. The width of the line focus is matched to the width of the sample capillary from which the analyte elutes under hydrodynamic focusing conditions, allowing for increased collection across the SERS substrate while maintaining the power density below the damage threshold at any specific point. We show that a 4× increase in power spread across the line increases the signal-to-noise ratio by a factor of 2 for a variety of analytes, such as rhodamine 6G, amino acids, and lipid vesicles, without any detectable photodamage. COMSOL simulations and Raman maps elucidate the hydrodynamic focusing properties of the flow cell, providing a clearer picture of the confinement effects at the surface where the sample exits the capillary. The lipid vesicle results suggest that the combination of hydrodynamic focusing and increased optical collection enables the reproducible detection of rare events, in this case individual lipid vesicles. PMID:26168151

  5. Local Seismic Event Detection Using Image Processing Techniques

    NASA Astrophysics Data System (ADS)

    West, J. D.; Fouch, M. J.

    2013-12-01

    The large footprint of regularly-spaced broadband seismometers afforded by EarthScope's USArray Transportable Array (TA) [www.usarray.org] presents an unprecedented opportunity to develop novel seismic array processing methods. Here we report preliminary results from a new automated method for detecting small local seismic events within the footprint of the TA using image processing techniques. The overarching goal is to develop a new methodology for automated searches of large seismic datasets for signals that are difficult to detect by traditional means, such as STA/LTA triggering algorithms. We first process the raw broadband data for each station by bandpass filtering at 7-19 Hz and integrating the absolute value of the velocity waveform over a sequence of 5-second intervals. We further combine the integrated values of all three orthogonal channels into a single new time series with a 5-second sampling rate. This new time series is analogous to a measurement of the total seismic energy recorded at the station in each 5-second interval; we call this time series Integrated Ground Motion (IGM). Each sample is compared to a sliding longer-term average to remove diurnal and long-term noise effects. We create an image file by mapping each station location to an equivalent position in a blank image array, and use a modified Voronoi tessellation algorithm to assign each pixel in the image to the IGM value of the nearest station. We assign a value of zero if the pixel is more than a maximum distance from the nearest station. We apply 2-dimensional spatial image filtering techniques to remove large-scale features affecting much of the image, as we assume these likely result from teleseismic events. We also filter the time series to remove very small-scale features from noise spikes affecting a single seismic station. The resulting image contains only features of regional scale affecting 2 or more stations. For each of the remaining image features, we find the center

  6. Real-time detection of viable microorganisms by intracellular phototautomerism

    PubMed Central

    2010-01-01

    Background To date, the detection of live microorganisms present in the environment or involved in infections is carried out by enumeration of colony forming units on agar plates, which is time consuming, laborious and limited to readily cultivable microorganisms. Although cultivation-independent methods are available, they involve multiple incubation steps and do mostly not discriminate between dead or live microorganisms. We present a novel generic method that is able to specifically monitor living microorganisms in a real-time manner. Results The developed method includes exposure of cells to a weak acid probe at low pH. The neutral probe rapidly permeates the membrane and enters the cytosol. In dead cells no signal is obtained, as the cytosolic pH reflects that of the acidic extracellular environment. In live cells with a neutral internal pH, the probe dissociates into a fluorescent phototautomeric anion. After reaching peak fluorescence, the population of live cells decays. This decay can be followed real-time as cell death coincides with intracellular acidification and return of the probe to its uncharged non-fluorescent state. The rise and decay of the fluorescence signal depends on the probe structure and appears discriminative for bacteria, fungi, and spores. We identified 13 unique probes, which can be applied in the real-time viability method described here. Under the experimental conditions used in a microplate reader, the reported method shows a detection limit of 106 bacteria ml-1, while the frequently used LIVE/DEAD BacLight™ Syto9 and propidium iodide stains show detection down to 106 and 107 bacteria ml-1, respectively. Conclusions We present a novel fluorescence-based method for viability assessment, which is applicable to all bacteria and eukaryotic cell types tested so far. The RTV method will have a significant impact in many areas of applied microbiology including research on biocidal activity, improvement of preservation strategies and

  7. Real-time change detection for countering improvised explosive devices

    NASA Astrophysics Data System (ADS)

    van de Wouw, Dennis W. J. M.; van Rens, Kris; van Lint, Hugo; Jaspers, Egbert G. T.; de With, Peter H. N.

    2014-03-01

    We explore an automatic real-time change detection system to assist military personnel during transport and surveillance, by detection changes in the environment with respect to a previous operation. Such changes may indicate the presence of Improvised Explosive Devices (IEDs), which can then be bypassed. While driving, images of the scenes are acquired by the camera and stored with their GPS positions. At the same time, the best matching reference image (from a previous patrol) is retrieved and registered to the live image. Next a change mask is generated by differencing the reference and live image, followed by an adaptive thresholding technique. Post-processing steps such as Markov Random Fields, local texture comparisons and change tracking, further improve time- and space-consistency of changes and suppress noise. The resulting changes are visualized as an overlay on the live video content. The system has been extensively tested on 28 videos, containing over 10,000 manually annotated objects. The system is capable of detecting small test objects of 10 cm3 at a range of 40 meters. Although the system shows an acceptable performance in multiple cases, the performance degrades under certain circumstances for which extensions are discussed.

  8. Robust real-time change detection in high jitter.

    SciTech Connect

    Simonson, Katherine Mary; Ma, Tian J.

    2009-08-01

    A new method is introduced for real-time detection of transient change in scenes observed by staring sensors that are subject to platform jitter, pixel defects, variable focus, and other real-world challenges. The approach uses flexible statistical models for the scene background and its variability, which are continually updated to track gradual drift in the sensor's performance and the scene under observation. Two separate models represent temporal and spatial variations in pixel intensity. For the temporal model, each new frame is projected into a low-dimensional subspace designed to capture the behavior of the frame data over a recent observation window. Per-pixel temporal standard deviation estimates are based on projection residuals. The second approach employs a simple representation of jitter to generate pixelwise moment estimates from a single frame. These estimates rely on spatial characteristics of the scene, and are used gauge each pixel's susceptibility to jitter. The temporal model handles pixels that are naturally variable due to sensor noise or moving scene elements, along with jitter displacements comparable to those observed in the recent past. The spatial model captures jitter-induced changes that may not have been seen previously. Change is declared in pixels whose current values are inconsistent with both models.

  9. Protective materials with real-time puncture detection capability

    SciTech Connect

    Hermes, R.E.; Stampfer, J.F.; Valdez-Boyle, L.S.; Ramsey, D.R.

    1996-08-01

    The protection of workers from chemical, biological, or radiological hazards requires the use of protective materials that can maintain their integrity during use. An accidental puncture in the protective material can result in a significant exposure to the worker. A five ply material has been developed that incorporates two layers of an electrically conductive polymer sandwiched between three layers of a nonconductive polymer. A normally open circuit that is connected between the conductive layers will be closed by puncturing the material with either a conductive or nonconductive object. This can be used to activate an audible alarm or visual beacon to warn the worker of a breach in the integrity of the material. The worker is not connected to the circuit, and the puncture can be detected in real-time, even when caused by a nonconductor.

  10. Real time pre-detection dynamic range compression

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang (Inventor)

    1992-01-01

    A real time, pre-detection optical dynamic range compression system uses a photorefractive crystal, such as BaTiO3 or LiNbO3, in which light induced scattering from crystal inhomogeneities of the optical input occurs as a nonlinear function of the input intensity. The greater the intensity, the faster random interference gratings are created to scatter the incident light. The unscattered portion of the optical signal is therefore reduced in dynamic range over time. The amount or range of dynamic range compression may be controlled by adjusting the time of application of the unscattered crystal output to the photodetector with regard to the time of application of the optical input to the crystal.

  11. Real-time detection of neurite outgrowth using microfluidic device

    NASA Astrophysics Data System (ADS)

    Kim, Samhwan; Jang, Jongmoon; Choi, Hongsoo; Moon, Cheil

    2013-05-01

    We developed a simple method for real-time detection of the neurite outgrowth using microfluidic device. Our microfluidic device contains three compartmentalized channels which are for cell seeding, hydrogel and growth factors. Collagen gel is filled in the middle channel and pheochromocytoma (PC12) cells are seeded in the left channel. To induce differentiation of PC12 cells, 50 ng/ml to1000 ng/ml of nerve growth factor (NGF) is introduced into the right channel. After three days of NGF treatment, PC12 cells begin to extend neurites and formed neurite network from sixth day. Quantification of neurite outgrowth is analyzed by measuring the total area of neurites. On sixth day, the area is doubled compared to the area on third day and increases by 20 times on ninth day.

  12. Infrared luminescence for real time ionizing radiation detection

    SciTech Connect

    Veronese, Ivan Mattia, Cristina De; Cantone, Marie Claire; Fasoli, Mauro; Chiodini, Norberto; Vedda, Anna; Mones, Eleonora

    2014-08-11

    Radio-luminescence (RL) optical fiber sensors enable a remote, punctual, and real time detection of ionizing radiation. However, the employment of such systems for monitoring extended radiation fields with energies above the Cerenkov threshold is still challenging, since a spurious luminescence, namely, the “stem effect,” is also generated in the passive fiber portion exposed to radiation. Here, we present experimental measurements on Yb-doped silica optical fibers irradiated with photon fields of different energies and sizes. The results demonstrate that the RL of Yb{sup 3+}, displaying a sharp emission line at about 975 nm, is free from any spectral superposition with the spurious luminescence. This aspect, in addition with the suitable linearity, reproducibility, and sensitivity properties of the Yb-doped fibers, paves the way to their use in applications where an efficient stem effect removal is required.

  13. Real-time threat detection using magnetometer arrays

    NASA Astrophysics Data System (ADS)

    Prouty, Mark D.; Tchernychev, Mikhail

    2016-05-01

    In this paper we present a discussion of using an array of atomic magnetometers to locate the presence of ferrous materials, such as concealed weapons, in real time. Ferrous materials create magnetic field anomalies. In order to determine the location of such objects, readings from many positions must be analyzed. This field inversion is typically done in post processing, once readings over a survey area or region of interest have been gathered. With the recent development of small and low power sensors, the dozen or so sensors required to provide information for magnetic field inversion may be deployed. We have built such an array and present here the results of using a realtime inversion algorithm. The inversion algorithm accurately determines target properties at a rate of 10 times per second as objects move past the array. Accuracies are as good as those obtained with target inversion methods used in analyzing data for unexploded ordnance detection. While those methods are typically applied in post processing, we show here those methods work even better when applied in real-time. We further present some analyses of the predicted performance of arrays in various geometries to address issues in security, such as crowd or perimeter monitoring. Target inversion methods may be accurately simulated, allowing for the development and testing of algorithms in an efficient manner. Additional processing may be done using the time history of the inversion results to remove false alarms and enhance detection. The key step is to start with an inversion method, utilizing the mathematical properties of magnetic fields and the known geometry of the measurements.

  14. Improvements in atrial fibrillation detection for real-time monitoring.

    PubMed

    Babaeizadeh, Saeed; Gregg, Richard E; Helfenbein, Eric D; Lindauer, James M; Zhou, Sophia H

    2009-01-01

    Electrocardiographic (ECG) monitoring plays an important role in the management of patients with atrial fibrillation (AF). Automated real-time AF detection algorithm is an integral part of ECG monitoring during AF therapy. Before and after antiarrhythmic drug therapy and surgical procedures require ECG monitoring to ensure the success of AF therapy. This article reports our experience in developing a real-time AF monitoring algorithm and techniques to eliminate false-positive AF alarms. We start by designing an algorithm based on R-R intervals. This algorithm uses a Markov modeling approach to calculate an R-R Markov score. This score reflects the relative likelihood of observing a sequence of R-R intervals in AF episodes versus making the same observation outside AF episodes. Enhancement of the AF algorithm is achieved by adding atrial activity analysis. P-R interval variability and a P wave morphology similarity measure are used in addition to R-R Markov score in classification. A hysteresis counter is applied to eliminate short AF segments to reduce false AF alarms for better suitability in a monitoring environment. A large ambulatory Holter database (n = 633) was used for algorithm development and the publicly available MIT-BIH AF database (n = 23) was used for algorithm validation. This validation database allowed us to compare our algorithm performance with previously published algorithms. Although R-R irregularity is the main characteristic and strongest discriminator of AF rhythm, by adding atrial activity analysis and techniques to eliminate very short AF episodes, we have achieved 92% sensitivity and 97% positive predictive value in detecting AF episodes, and 93% sensitivity and 98% positive predictive value in quantifying AF segment duration. PMID:19608194

  15. Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use

    PubMed Central

    Moghaddam, Athena K.; Yuen, Hiu Kim; Archambault, Philippe S.; Routhier, François; Michaud, François; Boissy, Patrick

    2014-01-01

    Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. Unfortunately, PW incidents and accidents are not uncommon and their consequences can be serious. The objective of this paper is to develop technological tools that can be used to characterize a wheelchair user’s driving behavior under various settings. In the experiments conducted, PWs are outfitted with a datalogging platform that records, in real-time, the 3-D acceleration of the PW. Data collection was conducted over 35 different activities, designed to capture a spectrum of PW driving events performed at different speeds (collisions with fixed or moving objects, rolling on incline plane, and rolling across multiple types obstacles). The data was processed using time-series analysis and data mining techniques, to automatically detect and identify the different events. We compared the classification accuracy using four different types of time-series features: 1) time-delay embeddings; 2) time-domain characterization; 3) frequency-domain features; and 4) wavelet transforms. In the analysis, we compared the classification accuracy obtained when distinguishing between safe and unsafe events during each of the 35 different activities. For the purposes of this study, unsafe events were defined as activities containing collisions against objects at different speed, and the remainder were defined as safe events. We were able to accurately detect 98% of unsafe events, with a low (12%) false positive rate, using only five examples of each activity. This proof-of-concept study shows that the proposed approach has the potential of capturing, based on limited input from embedded sensors, contextual information on PW use, and of automatically characterizing a user’s PW driving behavior. PMID:27170879

  16. Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use.

    PubMed

    Pineau, Joelle; Moghaddam, Athena K; Yuen, Hiu Kim; Archambault, Philippe S; Routhier, François; Michaud, François; Boissy, Patrick

    2014-01-01

    Using a powered wheelchair (PW) is a complex task requiring advanced perceptual and motor control skills. Unfortunately, PW incidents and accidents are not uncommon and their consequences can be serious. The objective of this paper is to develop technological tools that can be used to characterize a wheelchair user's driving behavior under various settings. In the experiments conducted, PWs are outfitted with a datalogging platform that records, in real-time, the 3-D acceleration of the PW. Data collection was conducted over 35 different activities, designed to capture a spectrum of PW driving events performed at different speeds (collisions with fixed or moving objects, rolling on incline plane, and rolling across multiple types obstacles). The data was processed using time-series analysis and data mining techniques, to automatically detect and identify the different events. We compared the classification accuracy using four different types of time-series features: 1) time-delay embeddings; 2) time-domain characterization; 3) frequency-domain features; and 4) wavelet transforms. In the analysis, we compared the classification accuracy obtained when distinguishing between safe and unsafe events during each of the 35 different activities. For the purposes of this study, unsafe events were defined as activities containing collisions against objects at different speed, and the remainder were defined as safe events. We were able to accurately detect 98% of unsafe events, with a low (12%) false positive rate, using only five examples of each activity. This proof-of-concept study shows that the proposed approach has the potential of capturing, based on limited input from embedded sensors, contextual information on PW use, and of automatically characterizing a user's PW driving behavior. PMID:27170879

  17. Near real-time detection and characterization of landslides using broadband seismic networks

    NASA Astrophysics Data System (ADS)

    Manconi, Andrea; Coviello, Velio; De Santis, Francesca; Picozzi, Matteo

    2015-04-01

    Broadband seismic networks at regional, national, and global scale are usually deployed for a specific purpose, i.e. earthquake monitoring. However, it has been recently demonstrated that these networks are also capable to efficiently detect failure and transport processes related to landslide phenomena. Indeed, stations located several tens of kilometers away from the source areas can record the ground vibrations produced by large mass movements. In this work, we propose an integrated approach for the near real-time detection, location, and characterization of landslides, by considering data acquired from the Italian broadband seismic networks and available in the European Integrated Data Archive (EIDA). We use an automatic picking of first arrivals to identify significant seismic events recorded by the monitoring network. Secondly, waveforms relevant to landslide phenomena are selected by analyzing the spectral characteristics of seismic signals, which significantly differ from those related to earthquake events. Afterwards, in order to locate the landslide, we use a modified version of the real-time evolutionary location algorithm proposed for earthquakes, which relies on geometrical characteristics of the seismic network and on the relationships between triggered stations and not-triggered stations. Indeed, a first landslide location is roughly estimated as soon as the first station is triggered. The progressive increase over time in the number of triggered stations allows improving the accuracy on the most likely landslide location. Finally, we analyze the seismic energy released to infer an approximate value of the landslide volume in near real time. Here we present few examples relevant to recent well-known landslides where our method was successfully applied. Our results show how it is possible to extract precious information for landslide hazard assessment from seismic monitoring data, which in the field of earthquake warning would be discarded. Moreover

  18. A real time pipeline to link meteorological information and TGFs detected by AGILE

    NASA Astrophysics Data System (ADS)

    Ursi, Alessandro; Tavani, Marco; Dietrich, Stefano; Marisaldi, Martino; Casella, Daniele; Sanò, Paolo; Petracca, Marco; Argan, Andrea

    2015-04-01

    Terrestrial Gamma-ray Flashes (TGFs) are brief (detect TGFs, because of its very wide energy range (up to 100 MeV and beyond), its optimized triggering system and its equatorial orbit. We describe a new alert service that has been developed for the AGILE satellite, whose aim is to provide "real time" meteorological information about the detected TGFs. We take advantage of the Meteosat Second Generation (MSG) satellites data to promptly identify the possible individual thunderstorm or mesoscale convective system associated to the detected TGF event and to follow its evolution in space and time. Data from other meteorological satellites, for example the GPM mission, as well as ground measurements from lightning detection network, can be integrated in the pipeline. This allows us a prompt characterization of the ground meteorological conditions at TGF time which will provide instrument independent trigger validation, fill in a database for subsequent statistical analysis, and eventually, on a longer term perspective, serve as a real time alert system open to the community.

  19. Near-Real Time Anomaly Detection for Scientific Sensor Data

    NASA Astrophysics Data System (ADS)

    Gallegos, I.; Gates, A.; Tweedie, C. E.; goswami, S.; Jaimes, A.; Gamon, J. A.

    2011-12-01

    Environmental scientists use advanced sensor technology such as meteorological towers, wireless sensor networks and robotic trams equipped with sensors to perform data collection at remote research sites. Because the amount of environmental sensor data acquired in real time by such instruments is increasing, both the ability to evaluate the accuracy of the data at near-real time and check that the instrumentation is operating correctly are critical in order to not lose valuable time and information. The goal of the research is to define a software engineering-based solution that provides the foundation to define reusable templates for formally specifying data properties and automatically generate programming code that can monitor data streams to identify anomalies at near real-time. The research effort has resulted in a data property categorization that is based on a literature survey of 15 projects that collected environmental data from sensors and a case study conducted in the Arctic. More than 500 published data properties were manually extracted and analyzed from the surveyed projects. The data property categorization revealed recurrent data patterns. Using these patterns and the Specification and Pattern System (SPS) from the software-engineering community as a model, we developed the Data Specification and Pattern System (D-SPS) to capture data properties. D-SPS is the foundation for the Data Property Specification (DaProS) prototype tool that assists scientists in specification of sensor data properties. A series of experiments have been conducted in collaboration with experts working with Eddy covariance (EC) data from the Jornada Basin Experimental Range (JER) and with hyper-spectral data collected using robotic tram systems from the Arctic. The goal of the experiments were to determine if the approach for specifying data properties is effective for specifying data properties and identifying anomalies in sensor data. A complementary Sensor Data

  20. Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

    NASA Technical Reports Server (NTRS)

    Saeed, M.; Mark, R. G.

    2001-01-01

    Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

  1. Detecting Rare Events in the Time-Domain

    SciTech Connect

    Rest, A; Garg, A

    2008-10-31

    One of the biggest challenges in current and future time-domain surveys is to extract the objects of interest from the immense data stream. There are two aspects to achieving this goal: detecting variable sources and classifying them. Difference imaging provides an elegant technique for identifying new transients or changes in source brightness. Much progress has been made in recent years toward refining the process. We discuss a selection of pitfalls that can afflict an automated difference imagine pipeline and describe some solutions. After identifying true astrophysical variables, we are faced with the challenge of classifying them. For rare events, such as supernovae and microlensing, this challenge is magnified because we must balance having selection criteria that select for the largest number of objects of interest against a high contamination rate. We discuss considerations and techniques for developing classification schemes.

  2. Detecting and characterising ramp events in wind power time series

    NASA Astrophysics Data System (ADS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-12-01

    In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain.

  3. Reaching out for patients: public relations and events with real results.

    PubMed

    Kuechel, Marie Czenko

    2010-02-01

    In today's market, the aesthetic physician needs to connect with patients using methods that are personal, educational, and that will glean the interest of prospective patients whose attention and dollars are sought by countless facial plastic surgery competitors near and far. Public relations, or reaching your prospective patient without a direct solicitation (advertising) for services, are traditional means that include media relations and charitable and social events. With the added component of social media, today the opportunities to reach out for new patients and garner real results are more varied and more affordable than ever before. PMID:20094963

  4. Event Detection and Spatial Analysis for Characterizing Extreme Precipitation

    NASA Astrophysics Data System (ADS)

    Jeon, S.; Prabhat, M.; Byna, S.; Collins, W.; Wehner, M. F.

    2013-12-01

    Atmospheric Rivers (ARs) are large spatially coherent weather systems with high concentrations of elevated water vapor that often cause severe downpours and flooding over western coastal United States. With the availability of more atmospheric moisture in the future under global warming, we expect ARs to play an important role as a potential cause of extreme precipitation. We have recently developed TECA software for automatically identifying and tracking features in climate datasets. In particular, we are able to identify ARs that make landfall on the western coast of North America. This detection tool examines integrated water vapor field above a certain threshold and performs geometric analysis. Based on the detection procedure, we investigate impacts of ARs by exploring spatial extent of AR precipitation for CMIP5 simulations, and characterize spatial pattern of dependence for future projections under climate change within the framework of extreme value theory. The results show that AR events in RCP8.5 scenario (2076-2100) tend to produce heavier rainfall with higher frequency and longer duration than the events from historical run (1981-2005). Range of spatial dependence between extreme precipitations is concentrated on smaller localized area in California under the highest emission scenario than present day. Preliminary results are illustrated in Figure 1 and 2. Fig 1: Boxplot of annual max precipitation (left two) and max AR precipitation (right two) from GFDL-ESM2M during 25-year time period by station in California, US. Fig 2: Spatial dependence of max AR precipitation calculated from Station 4 (triangle) for historical run (left) and for future projections of RCP8.5 (right) from GFDL-ESM2M. Green and orange colors represent complete dependence and independence between two stations respectively.

  5. Identification of new events in Apollo 16 lunar seismic data by Hidden Markov Model-based event detection and classification

    NASA Astrophysics Data System (ADS)

    Knapmeyer-Endrun, Brigitte; Hammer, Conny

    2015-10-01

    Detection and identification of interesting events in single-station seismic data with little prior knowledge and under tight time constraints is a typical scenario in planetary seismology. The Apollo lunar seismic data, with the only confirmed events recorded on any extraterrestrial body yet, provide a valuable test case. Here we present the application of a stochastic event detector and classifier to the data of station Apollo 16. Based on a single-waveform example for each event class and some hours of background noise, the system is trained to recognize deep moonquakes, impacts, and shallow moonquakes and performs reliably over 3 years of data. The algorithm's demonstrated ability to detect rare events and flag previously undefined signal classes as new event types is of particular interest in the analysis of the first seismic recordings from a completely new environment. We are able to classify more than 50% of previously unclassified lunar events, and additionally find over 200 new events not listed in the current lunar event catalog. These events include deep moonquakes as well as impacts and could be used to update studies on temporal variations in event rate or deep moonquakes stacks used in phase picking for localization. No unambiguous new shallow moonquake was detected, but application to data of the other Apollo stations has the potential for additional new discoveries 40 years after the data were recorded. Besides, the classification system could be useful for future seismometer missions to other planets, e.g., the InSight mission to Mars.

  6. Towards Real-Time Detection of Freezing of Gait Using Wavelet Transform on Wireless Accelerometer Data.

    PubMed

    Rezvanian, Saba; Lockhart, Thurmon E

    2016-01-01

    Injuries associated with fall incidences continue to pose a significant burden to persons with Parkinson's disease (PD) both in terms of human suffering and economic loss. Freezing of gait (FOG), which is one of the symptoms of PD, is a common cause of falls in this population. Although a significant amount of work has been performed to characterize/detect FOG using both qualitative and quantitative methods, there remains paucity of data regarding real-time detection of FOG, such as the requirements for minimum sensor nodes, sensor placement locations, and appropriate sampling period and update time. Here, the continuous wavelet transform (CWT) is employed to define an index for correctly identifying FOG. Since the CWT method uses both time and frequency components of a waveform in comparison to other methods utilizing only the frequency component, we hypothesized that using this method could lead to a significant improvement in the accuracy of FOG detection. We tested the proposed index on the data of 10 PD patients who experience FOG. Two hundred and thirty seven (237) FOG events were identified by the physiotherapists. The results show that the index could discriminate FOG in the anterior-posterior axis better than other two axes, and is robust to the update time variability. These results suggest that real time detection of FOG may be realized by using CWT of a single shank sensor with window size of 2 s and update time of 1 s (82.1% and 77.1% for the sensitivity and specificity, respectively). Although implicated, future studies should examine the utility of this method in real-time detection of FOG. PMID:27049389

  7. Towards Real-Time Detection of Freezing of Gait Using Wavelet Transform on Wireless Accelerometer Data

    PubMed Central

    Rezvanian, Saba; Lockhart, Thurmon E.

    2016-01-01

    Injuries associated with fall incidences continue to pose a significant burden to persons with Parkinson’s disease (PD) both in terms of human suffering and economic loss. Freezing of gait (FOG), which is one of the symptoms of PD, is a common cause of falls in this population. Although a significant amount of work has been performed to characterize/detect FOG using both qualitative and quantitative methods, there remains paucity of data regarding real-time detection of FOG, such as the requirements for minimum sensor nodes, sensor placement locations, and appropriate sampling period and update time. Here, the continuous wavelet transform (CWT) is employed to define an index for correctly identifying FOG. Since the CWT method uses both time and frequency components of a waveform in comparison to other methods utilizing only the frequency component, we hypothesized that using this method could lead to a significant improvement in the accuracy of FOG detection. We tested the proposed index on the data of 10 PD patients who experience FOG. Two hundred and thirty seven (237) FOG events were identified by the physiotherapists. The results show that the index could discriminate FOG in the anterior–posterior axis better than other two axes, and is robust to the update time variability. These results suggest that real time detection of FOG may be realized by using CWT of a single shank sensor with window size of 2 s and update time of 1 s (82.1% and 77.1% for the sensitivity and specificity, respectively). Although implicated, future studies should examine the utility of this method in real-time detection of FOG. PMID:27049389

  8. High-throughput, low-cost, and event-specific polymerase chain reaction detection of herbicide tolerance in genetically modified soybean A2704-12.

    PubMed

    Ma, H; Li, H; Li, J; Wang, X F; Wei, P C; Li, L; Yang, J B

    2014-01-01

    The aim of this study was to develop an event-specific qualitative and real-time quantitative polymerase chain reaction (PCR) method for detection of herbicide-tolerance genetically modified (GM) soybean A2704-12. The event-specific PCR primers were designed, based on the 5'-flanking integration sequence in the soybean genome, to amplify the 239-bp target fragment. Employing the same event-specific primers, qualitative PCR and real-time quantitative PCR detection methods were successfully developed. The results showed that the A2704-12 event could be specifically distinguished from other GM soybean events. In the qualitative PCR assay, the limit of detection was 0.05%, and in the real-time quantitative PCR assay, the limit of detection was less than 0.01%. Moreover, our genomic DNA (gDNA) extraction protocol is high-throughput, safe, and low-cost. The event-specific PCR assay system is cost-efficient by using SYBR Green I in real-time PCR, and by using the same primers in both the qualitative and quantitative PCR assays. We therefore developed a high-throughput, low-cost, and event-specific qualitative and quantitative PCR detection method for GM soybean A2704-12. The method would be useful for market supervision and management of GM soybean A2704-12 due to its high specificity and sensitivity. PMID:24615034

  9. Empirical study of a unidirectional dense crowd during a real mass event

    NASA Astrophysics Data System (ADS)

    Zhang, X. L.; Weng, W. G.; Yuan, H. Y.; Chen, J. G.

    2013-06-01

    Many tragic crowd disasters have happened across the world in recent years, such as the Phnom Penh stampede in Cambodia, crowd disaster in Mina/Makkah, and the Love Parade disaster in Germany, showing that management of mass events is a tough task for organizers. The study of unidirectional flow, one of the most common forms of motion in mass activities, is essential for safe organization of such events. In this paper, the properties of unidirectional flow in a crowded street during a real mass event in China are quantitatively investigated with sophisticated active infrared counters and an image processing method. A complete dataset of flow rates during the whole celebration is recorded, and a time series analysis gives new insight into such activities. The spatial analysis shows that the velocity and density of the crowd are inhomogeneous due to the boundary effect, whereas the flux is uniform. The estimated capacity of the street indicates that the maximum flow rate under normal condition should be between 1.73 and 1.98 /m/s, which is in good agreement with several field studies available in the existing literature. In consideration of the significant deviation among different studies, fundamental diagrams of dense crowds are also re-verified, and the results here are consistent with those from other field studies of unidirectional flow, but different from the bidirectional and experimental results. It is suggested that the data from multidirectional flow and experiments cannot be directly applied to unidirectional dense flow in a real mass event. The results also imply that the density of a similar unidirectional marching crowd should be controlled to be under 5 /m2, which can produce optimal efficiency and have more possibility to ensure safety. The field study data given here provide a good example of a database for crowd studies.

  10. A Real-Time Satellite-Based Icing Detection System

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Smith, William L., Jr.; Nguyen, Louis; Khaiyer, Mandana M.; Spangenberg, Douglas A.; Heck, Patrick W.; Palikonda, Rabindra; Bernstein, Ben C.; McDonough, Frank

    2004-01-01

    Aircraft icing is one of the most dangerous weather conditions for general aviation. Currently, model forecasts and pilot reports (PIREPS) constitute much of the database available to pilots for assessing the icing conditions in a particular area. Such data are often uncertain or sparsely available. Improvements in the temporal and areal coverage of icing diagnoses and prognoses would mark a substantial enhancement of aircraft safety in regions susceptible to heavy supercooled liquid water clouds. The use of 3.9 microns data from meteorological satellite imagers for diagnosing icing conditions has long been recognized (e.g., Ellrod and Nelson, 1996) but to date, no explicit physically based methods have been implemented. Recent advances in cloud detection and cloud property retrievals using operational satellite imagery open the door for real-time objective applications of those satellite datasets for a variety of weather phenomena. Because aircraft icing is related to cloud macro- and microphysical properties (e.g., Cober et al. 1995), it is logical that the cloud properties from satellite data would be useful for diagnosing icing conditions. This paper describes the a prototype realtime system for detecting aircraft icing from space.

  11. A real-time robot arm collision detection system

    NASA Technical Reports Server (NTRS)

    Shaffer, Clifford A.; Herb, Gregory M.

    1990-01-01

    A data structure and update algorithm are presented for a prototype real time collision detection safety system for a multi-robot environment. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3-D space into eight equal cubic octants until each octant meets some decomposition criteria. The octree stores cylspheres (cylinders with spheres on each end) and rectangular solids as primitives (other primitives can easily be added as required). These primitives make up the two seven degrees-of-freedom robot arms and environment modeled by the system. Octree nodes containing more than a predetermined number N of primitives are decomposed. This rule keeps the octree small, as the entire environment for the application can be modeled using a few dozen primitives. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Incidents in which one robot arm comes too close to another arm or an object are reported. Cycle time for interpreting current joint angles, updating the octree, and detecting/reporting imminent collisions averages 30 milliseconds on an Intel 80386 processor running at 20 MHz.

  12. Detection of North American orthopoxviruses by real time-PCR

    PubMed Central

    2011-01-01

    The prevalence of North American orthopoxviruses in nature is unknown and may be more difficult to ascertain due to wide spread use of vaccinia virus recombinant vaccines in the wild. A real time PCR assay was developed to allow for highly sensitive and specific detection of North American orthopoxvirus DNA in animal tissues and bodily fluids. This method is based on the amplification of a 156 bp sequence within a myristylated protein, highly conserved within the North American orthopoxviruses but distinct from orthologous genes present in other orthopoxviruses. The analytical sensitivity was 1.1 fg for Volepox virus DNA, 1.99 fg for Skunkpox virus DNA, and 6.4 fg for Raccoonpox virus DNA with a 95% confidence interval. Our assay did not cross-react with other orthopoxviruses or ten diverse representatives of the Chordopoxvirinae subfamily. This new assay showed more sensitivity than tissue culture tests, and was capable of differentiating North American orthopoxviruses from other members of Orthopoxvirus. Thus, our assay is a promising tool for highly sensitive and specific detection of North American orthopoxviruses in the United States and abroad. PMID:21689420

  13. BioSense: implementation of a National Early Event Detection and Situational Awareness System.

    PubMed

    Bradley, Colleen A; Rolka, H; Walker, D; Loonsk, J

    2005-08-26

    BioSense is a CDC initiative to support enhanced early detection, quantification, and localization of possible biologic terrorism attacks and other events of public health concern on a national level. The goals of the BioSense initiative are to advance early detection by providing the standards, infrastructure, and data acquisition for near real-time reporting, analytic evaluation and implementation, and early event detection support for state and local public health officials. BioSense collects and analyzes Department of Defense and Department of Veterans Affairs ambulatory clinical diagnoses and procedures and Laboratory Corporation of America laboratory-test orders. The application summarizes and presents analytical results and data visualizations by source, day, and syndrome for each ZIP code, state, and metropolitan area through maps, graphs, and tables. An initial proof of a concept evaluation project was conducted before the system was made available to state and local users in April 2004. User recruitment involved identifying and training BioSense administrators and users from state and local health departments. User support has been an essential component of the implementation and enhancement process. CDC initiated the BioIntelligence Center (BIC) in June 2004 to conduct internal monitoring of BioSense national data daily. BIC staff have supported state and local system monitoring, conducted data anomaly inquiries, and communicated with state and local public health officials. Substantial investments will be made in providing regional, state, and local data for early event detection and situational awareness, test beds for data and algorithm evaluation, detection algorithm development, and data management technologies, while maintaining the focus on state and local public health needs. PMID:16177687

  14. Detecting Tidal Disruption Events (TDEs) with the Einstein Probe

    NASA Astrophysics Data System (ADS)

    Yuan, W.; Komossa, S.; Zhang, C.; Feng, H.; Zhang, S.; Osborne, J.; O'Brien, P.; Watson, M.; Fraser, G.

    2014-07-01

    Stars are tidally disrupted and accreted when they approach supermassive black holes (SMBHs) closely, producing a flare of electromagnetic radiation. The majority of the (approximately two dozen) tidal disruption events (TDEs) identified so far have been discovered by their luminous, transient X-ray emission. Once TDEs are detected in much larger numbers, in future dedicated transient surveys, a wealth of new applications will become possible. Including (1) TDE rate measurements in dependence of host galaxy types, (2) an assessment of the population of IMBHs, and (3) new probes of general relativity and accretion processes. Here, we present the proposed X-ray mission Einstein Probe}, which aims at detecting TDEs in large numbers. The mission consists of a wide-field micro-pore Lobster-eye imager (60deg x 60deg, or ˜1 ster), and is designed to carry out an all-sky transient survey at energies of 0.5-4 keV. It will also carry an X-ray telescope of the same micro-pore optics for follow-ups, with a smaller field-of-view. It will be capable of issuing public transient alerts rapidly.

  15. Communication of ALS Patients by Detecting Event-Related Potential

    NASA Astrophysics Data System (ADS)

    Kanou, Naoyuki; Sakuma, Kenji; Nakashima, Kenji

    Amyotrophic Lateral Sclerosis(ALS) patients are unable to successfully communicate their desires, although their mental capacity is the same as non-affected persons. Therefore, the authors put emphasis on Event-Related Potential(ERP) which elicits the highest outcome for the target visual and hearing stimuli. P300 is one component of ERP. It is positive potential that is elicited when the subject focuses attention on stimuli that appears infrequently. In this paper, the authors focused on P200 and N200 components, in addition to P300, for their great improvement in the rate of correct judgment in the target word-specific experiment. Hence the authors propose the algorithm that specifies target words by detecting these three components. Ten healthy subjects and ALS patient underwent the experiment in which a target word out of five words, was specified by this algorithm. The rates of correct judgment in nine of ten healthy subjects were more than 90.0%. The highest rate was 99.7%. The highest rate of ALS patient was 100.0%. Through these results, the authors found the possibility that ALS patients could communicate with surrounding persons by detecting ERP(P200, N200 and P300) as their desire.

  16. Real-Time Detection of Dust Devils from Pressure Readings

    NASA Technical Reports Server (NTRS)

    Wagstaff, Kiri

    2009-01-01

    A method for real-time detection of dust devils at a given location is based on identifying the abrupt, temporary decreases in atmospheric pressure that are characteristic of dust devils as they travel through that location. The method was conceived for use in a study of dust devils on the Martian surface, where bandwidth limitations encourage the transmission of only those blocks of data that are most likely to contain information about features of interest, such as dust devils. The method, which is a form of intelligent data compression, could readily be adapted to use for the same purpose in scientific investigation of dust devils on Earth. In this method, the readings of an atmospheric- pressure sensor are repeatedly digitized, recorded, and processed by an algorithm that looks for extreme deviations from a continually updated model of the current pressure environment. The question in formulating the algorithm is how to model current normal observations and what minimum magnitude deviation can be considered sufficiently anomalous as to indicate the presence of a dust devil. There is no single, simple answer to this question: any answer necessarily entails a compromise between false detections and misses. For the original Mars application, the answer was sought through analysis of sliding time windows of digitized pressure readings. Windows of 5-, 10-, and 15-minute durations were considered. The windows were advanced in increments of 30 seconds. Increments of other sizes can also be used, but computational cost increases as the increment decreases and analysis is performed more frequently. Pressure models were defined using a polynomial fit to the data within the windows. For example, the figure depicts pressure readings from a 10-minute window wherein the model was defined by a third-degree polynomial fit to the readings and dust devils were identified as negative deviations larger than both 3 standard deviations (from the mean) and 0.05 mbar in magnitude. An

  17. Apparatus and method for detecting full-capture radiation events

    DOEpatents

    Odell, Daniel M. C.

    1994-01-01

    An apparatus and method for sampling the output signal of a radiation detector and distinguishing full-capture radiation events from Compton scattering events. The output signal of a radiation detector is continuously sampled. The samples are converted to digital values and input to a discriminator where samples that are representative of events are identified. The discriminator transfers only event samples, that is, samples representing full-capture events and Compton events, to a signal processor where the samples are saved in a three-dimensional count matrix with time (from the time of onset of the pulse) on the first axis, sample pulse current amplitude on the second axis, and number of samples on the third axis. The stored data are analyzed to separate the Compton events from full-capture events, and the energy of the full-capture events is determined without having determined the energies of any of the individual radiation detector events.

  18. A Real-Time Web Services Hub to Improve Situation Awareness during Flash Flood Events

    NASA Astrophysics Data System (ADS)

    Salas, F. R.; Liu, F.; Maidment, D. R.; Hodges, B. R.

    2011-12-01

    The central Texas corridor is one of the most flash flood-prone regions in the United States. Over the years, flash floods have resulted in hundreds of flood fatalities and billions of dollars in property damage. In order to mitigate risk to residents and infrastructure during flood events, both citizens and emergency responders need to exhibit proactive behavior instead of reactive. Real-time and forecasted flood information is fairly limited and hard to come by at varying spatial scales. The University of Texas at Austin has collaborated with IBM Research-Austin and ESRI to build a distributed real-time flood information system through a framework that leverages large scale data management and distribution, Open Geospatial Consortium standardized web services, and smart map applications. Within this paradigm, observed precipitation data encoded in WaterML is ingested into HEC-HMS and then delivered to a high performance hydraulic routing software package developed by IBM that utilizes the latest advancements in VLSI design, numerical linear algebra and numerical integration techniques on contemporary multicore architecture to solve fully dynamic Saint Venant equations at both small and large scales. In this paper we present a real-time flood inundation map application that in conjunction with a web services Hub, seamlessly integrates hydrologic information available through both public and private data services, model services and mapping services. As a case study for this project, we demonstrate how this system has been implemented in the City of Austin, Texas.

  19. FRET microscopy for real-time monitoring of signaling events in live cells using unimolecular biosensors.

    PubMed

    Sprenger, Julia U; Perera, Ruwan K; Götz, Konrad R; Nikolaev, Viacheslav O

    2012-01-01

    Förster resonance energy transfer (FRET) microscopy continues to gain increasing interest as a technique for real-time monitoring of biochemical and signaling events in live cells and tissues. Compared to classical biochemical methods, this novel technology is characterized by high temporal and spatial resolution. FRET experiments use various genetically-encoded biosensors which can be expressed and imaged over time in situ or in vivo. Typical biosensors can either report protein-protein interactions by measuring FRET between a fluorophore-tagged pair of proteins or conformational changes in a single protein which harbors donor and acceptor fluorophores interconnected with a binding moiety for a molecule of interest. Bimolecular biosensors for protein-protein interactions include, for example, constructs designed to monitor G-protein activation in cells, while the unimolecular sensors measuring conformational changes are widely used to image second messengers such as calcium, cAMP, inositol phosphates and cGMP. Here we describe how to build a customized epifluorescence FRET imaging system from single commercially available components and how to control the whole setup using the Micro-Manager freeware. This simple but powerful instrument is designed for routine or more sophisticated FRET measurements in live cells. Acquired images are processed using self-written plug-ins to visualize changes in FRET ratio in real-time during any experiments before being stored in a graphics format compatible with the build-in ImageJ freeware used for subsequent data analysis. This low-cost system is characterized by high flexibility and can be successfully used to monitor various biochemical events and signaling molecules by a plethora of available FRET biosensors in live cells and tissues. As an example, we demonstrate how to use this imaging system to perform real-time monitoring of cAMP in live 293A cells upon stimulation with a β-adrenergic receptor agonist and blocker. PMID

  20. Robust cardiac event change detection method for long-term healthcare monitoring applications.

    PubMed

    Satija, Udit; Ramkumar, Barathram; Manikandan, M Sabarimalai

    2016-06-01

    A long-term continuous cardiac health monitoring system highly demands more battery power for real-time transmission of electrocardiogram (ECG) signals and increases bandwidth, treatment costs and traffic load of the diagnostic server. In this Letter, the authors present an automated low-complexity robust cardiac event change detection (CECD) method that can continuously detect specific changes in PQRST morphological patterns and heart rhythms and then enable transmission/storing of the recorded ECG signals. The proposed CECD method consists of four stages: ECG signal quality assessment, R-peak detection and beat waveform extraction, temporal and RR interval feature extraction and cardiac event change decision. The proposed method is tested and validated using both normal and abnormal ECG signals including different types of arrhythmia beats, heart rates and signal quality. Results show that the method achieves an average sensitivity of 99.76%, positive predictivity of 94.58% and overall accuracy of 94.32% in determining the changes in heartbeat waveforms of the ECG signals. PMID:27382480

  1. Advanced Geospatial Hydrodynamic Signals Analysis for Tsunami Event Detection and Warning

    NASA Astrophysics Data System (ADS)

    Arbab-Zavar, Banafshe; Sabeur, Zoheir

    2013-04-01

    Current early tsunami warning can be issued upon the detection of a seismic event which may occur at a given location offshore. This also provides an opportunity to predict the tsunami wave propagation and run-ups at potentially affected coastal zones by selecting the best matching seismic event from a database of pre-computed tsunami scenarios. Nevertheless, it remains difficult and challenging to obtain the rupture parameters of the tsunamigenic earthquakes in real time and simulate the tsunami propagation with high accuracy. In this study, we propose a supporting approach, in which the hydrodynamic signal is systematically analysed for traces of a tsunamigenic signal. The combination of relatively low amplitudes of a tsunami signal at deep waters and the frequent occurrence of background signals and noise contributes to a generally low signal to noise ratio for the tsunami signal; which in turn makes the detection of this signal difficult. In order to improve the accuracy and confidence of detection, a re-identification framework in which a tsunamigenic signal is detected via the scan of a network of hydrodynamic stations with water level sensing is performed. The aim is to attempt the re-identification of the same signatures as the tsunami wave spatially propagates through the hydrodynamic stations sensing network. The re-identification of the tsunamigenic signal is technically possible since the tsunami signal at the open ocean itself conserves its birthmarks relating it to the source event. As well as supporting the initial detection and improving the confidence of detection, a re-identified signal is indicative of the spatial range of the signal, and thereby it can be used to facilitate the identification of certain background signals such as wind waves which do not have as large a spatial reach as tsunamis. In this paper, the proposed methodology for the automatic detection of tsunamigenic signals has been achieved using open data from NOAA with a recorded

  2. An evaluation of generalized likelihood Ratio Outlier Detection to identification of seismic events in Western China

    SciTech Connect

    Taylor, S.R.; Hartse, H.E.

    1996-09-24

    The Generalized Likelihood Ratio Outlier Detection Technique for seismic event identification is evaluated using synthetic test data and frequency-dependent P{sub g}/L{sub g} measurements from western China. For most seismic stations that are to be part of the proposed International Monitoring System for the Comprehensive Test Ban Treaty, there will be few or no nuclear explosions in the magnitude range of interest (e.g. M{sub b} < 4) on which to base an event-identification system using traditional classification techniques. Outlier detection is a reasonable alternative approach to the seismic discrimination problem when no calibration explosions are available. Distance-corrected P{sub g}/L{sub g} data in seven different frequency bands ranging from 0.5 to 8 Hz from the Chinese Digital Seismic Station WMQ are used to evaluate the technique. The data are collected from 157 known earthquakes, 215 unknown events (presumed earthquakes and possibly some industrial explosions), and 18 known nuclear explosions (1 from the Chinese Lop Nor test site and 17 from the East Kazakh test site). A feature selection technique is used to find the best combination of discriminants to use for outlier detection. Good discrimination performance is found by combining a low-frequency (0.5 to 1 Hz) P{sub g}/L{sub g} ratio with high-frequency ratios (e.g. 2 to 4 and 4 to 8 Hz). Although the low-frequency ratio does not discriminate between earthquakes and nuclear explosions well by itself, it can be effectively combined with the high-frequency discriminants. Based on the tests with real and synthetic data, the outlier detection technique appears to be an effective approach to seismic monitoring in uncalibrated regions.

  3. APNEA list mode data acquisition and real-time event processing

    SciTech Connect

    Hogle, R.A.; Miller, P.; Bramblett, R.L.

    1997-11-01

    The LMSC Active Passive Neutron Examinations and Assay (APNEA) Data Logger is a VME-based data acquisition system using commercial-off-the-shelf hardware with the application-specific software. It receives TTL inputs from eighty-eight {sup 3}He detector tubes and eight timing signals. Two data sets are generated concurrently for each acquisition session: (1) List Mode recording of all detector and timing signals, timestamped to 3 microsecond resolution; (2) Event Accumulations generated in real-time by counting events into short (tens of microseconds) and long (seconds) time bins following repetitive triggers. List Mode data sets can be post-processed to: (1) determine the optimum time bins for TRU assay of waste drums, (2) analyze a given data set in several ways to match different assay requirements and conditions and (3) confirm assay results by examining details of the raw data. Data Logger events are processed and timestamped by an array of 15 TMS320C40 DSPs and delivered to an embedded controller (PowerPC604) for interim disk storage. Three acquisition modes, corresponding to different trigger sources are provided. A standard network interface to a remote host system (Windows NT or SunOS) provides for system control, status, and transfer of previously acquired data. 6 figs.

  4. AQUA: a very fast automatic reduction pipeline for near real-time GRBs early afterglow detection

    NASA Astrophysics Data System (ADS)

    Di Paola, Andrea; Antonelli, Lucio A.; Testa, Vincenzo; Patria, Giorgio

    2002-12-01

    AQUA (Automated QUick Analysis) is the fast reduction pipeline of the Near Infra-Red (NIR) images obtained by the REM telescope. REM (Rapid Eye Mount) is a robotic NIR/Optical 60cm telescope for fast detection of early afterglow of Gamma Ray Bursts (GRB). NIR observations of GRBs early afterglow are of crucial importance for GRBs science, revealing even optical obscured or high redshift events. On the technical side, they pose a series of problems: luminous background, bright sources (as the counterparts should be observed few seconds after the satellite trigger) and fast detection force high rate images acquisition. Even if the observational strategy will change during the same event observation depending on the counterpart characteristics, we will start with 1 second exposures at the fastest possible rate. The main guideline in the AQUA pipeline development is to allow such a data rate along all the night with nearly real-time results delivery. AQUA will start from the raw images and will deliver an alert with coordinates, photometry and colors to larger telescopes to allow prompt spectroscopic and polarimetric observations. Very fast processing for the raw 512×512 32bit images and variable sources detection with both sources catalogs and images comparison have been implemented to obtain a processing speed of at least 1 image/sec. AQUA is based on ANSI-C code optimized to run on a dual Athlon Linux PC with careful MMX and SSE instructions utilization.

  5. Detection of Local/Regional Events in Kuwait Using Next-Generation Detection Algorithms

    SciTech Connect

    Gok, M. Rengin; Al-Jerri, Farra; Dodge, Douglas; Al-Enezi, Abdullah; Hauk, Terri; Mellors, R.

    2014-12-10

    Seismic networks around the world use conventional triggering algorithms to detect seismic signals in order to locate local/regional seismic events. Kuwait National Seismological Network (KNSN) of Kuwait Institute of Scientific Research (KISR) is operating seven broad-band and short-period three-component stations in Kuwait. The network is equipped with Nanometrics digitizers and uses Antelope and Guralp acquisition software for processing and archiving the data. In this study, we selected 10 days of archived hourly-segmented continuous data of five stations (Figure 1) and 250 days of continuous recording at MIB. For the temporary deployment our selection criteria was based on KNSN catalog intensity for the period of time we test the method. An autonomous event detection and clustering framework is employed to test a more complete catalog of this short period of time. The goal is to illustrate the effectiveness of the technique and pursue the framework for longer period of time.

  6. Automatic detection of volcano-seismic events by modeling state and event duration in hidden Markov models

    NASA Astrophysics Data System (ADS)

    Bhatti, Sohail Masood; Khan, Muhammad Salman; Wuth, Jorge; Huenupan, Fernando; Curilem, Millaray; Franco, Luis; Yoma, Nestor Becerra

    2016-09-01

    In this paper we propose an automatic volcano event detection system based on Hidden Markov Model (HMM) with state and event duration models. Since different volcanic events have different durations, therefore the state and whole event durations learnt from the training data are enforced on the corresponding state and event duration models within the HMM. Seismic signals from the Llaima volcano are used to train the system. Two types of events are employed in this study, Long Period (LP) and Volcano-Tectonic (VT). Experiments show that the standard HMMs can detect the volcano events with high accuracy but generates false positives. The results presented in this paper show that the incorporation of duration modeling can lead to reductions in false positive rate in event detection as high as 31% with a true positive accuracy equal to 94%. Further evaluation of the false positives indicate that the false alarms generated by the system were mostly potential events based on the signal-to-noise ratio criteria recommended by a volcano expert.

  7. Exupery volcano fast response system - The event detection and waveform classification system

    NASA Astrophysics Data System (ADS)

    Hammer, Conny; Ohrnberger, Matthias

    2010-05-01

    Volcanic eruptions are often preceded by seismic activity which can be used to quantify the volcanic activity since the number and the size of certain types of seismic events usually increase before periods of volcanic crisis. The implementation of an automatic detection and classification system for seismic signals of volcanic origin allows not only for the processing of large amounts of data in short time, but also provides consistent and time-invariant results. Here, we have developed a system based upon a combination of different methods. To enable a first robust event detection in the continuous data stream different modules are implemented in the real time system Earthworm which is widely distributed in active volcano monitoring observatories worldwide. Among those software modules are classical trigger algorithm like STA/LTA and cross-correlation master event matching which is also used to detect different classes of signals. Furthermore an additional module is implemented in the real time system to compute continuous activity parameters which are also used to quantify the volcanic activity. Most automatic classification systems need a sufficiently large pre-classified data set for training the system. However in case of a volcanic crisis we are often confronted with a lack of training data due to insufficient prior observations because prior data acquisition might be carried out with different equipment at a low number of sites and due to the imminent crisis there might be no time for the time-consuming and tedious process of preparing a training data set. For this reason we have developed a novel seismic event spotting technique in order to be less dependent on the existence of previously acquired data bases of event classes. One main goal is therefore to provide observatory staff with a robust event classification based on a minimum number of reference waveforms. By using a "learning-while-recording" approach we are allowing for the fast build-up of a

  8. Real-time detection of apneas on a PDA.

    PubMed

    Burgos, Alfredo; Goñi, Alfredo; Illarramendi, Arantza; Bermúdez, Jesús

    2010-07-01

    Patients suspected of suffering sleep apnea and hypopnea syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as reducing both the number of sleep studies they need to undergo and the waiting times. Relating to this scenario, some research proposals and commercial products are appearing, but all of them record the physiological data of patients to portable devices and, in the morning, these data are loaded into hospital computers where physicians analyze them by making use of specialized software. In this paper, we present an alternative proposal that promotes not only a transmission of physiological data but also a real-time analysis of these data locally at a mobile device. For that, we have built a classifier that provides an accuracy of 93% and a receiver operating characteristic-area under the curve (ROC-AUC) of 98.5% on SpO(2) signals available in the annotated Apnea-ECG Database. This local analysis allows the detection of anomalous situations as soon as they are generated. The classifier has been implemented taking into consideration the restricted resources of mobile devices. PMID:19887328

  9. Direct phosphorescent detection of primary event of photodynamic action

    NASA Astrophysics Data System (ADS)

    Losev, Anatoly P.; Knukshto, Valentin N.; Zhuravkin, Ivan N.

    1994-07-01

    Highly phosphorescent photosensitizer Pd-tetra (o-methoxy-p-sulfo) phenyl porphyrin (Pd-MSPP) was used to follow the primary events of photodynamic action - quenching of triplet states by free oxygen in different systems: water solutions of proteins, cells and tissues in vivo and in vitro. The photosensitizer forms complexes with proteins in solutions and biosystems showing remarkable hypsochromic shifts of band and an increase of the quantum yield and lifetime of phosphorescence at the binding to proteins. In absence of oxygen the lifetime of phosphorescence is almost single exponential, and depends on the energy of lowest triplet state of the sensitizer. The photochemical quenching of the triplets by cell components is negligible. In presence of free oxygen the quenching of the sensitizer triplets takes place. The emission spectrum of singlet oxygen with maximum 1271 nm was recorded in water protein solutions and quantum yield of sensitized luminescence was measured. In the systems studied, oxygen consumption was detected and oxygen concentration was estimated in the course of photodynamics by an increase in photosensitizer phosphorescence lifetime, using laser flash photolysis technique. At least two exponential kinetics of the phosphorescence decay shows that the distribution of the free oxygen is not uniform in tissues.

  10. Visual traffic surveillance framework: classification to event detection

    NASA Astrophysics Data System (ADS)

    Ambardekar, Amol; Nicolescu, Mircea; Bebis, George; Nicolescu, Monica

    2013-10-01

    Visual traffic surveillance using computer vision techniques can be noninvasive, automated, and cost effective. Traffic surveillance systems with the ability to detect, count, and classify vehicles can be employed in gathering traffic statistics and achieving better traffic control in intelligent transportation systems. However, vehicle classification poses a difficult problem as vehicles have high intraclass variation and relatively low interclass variation. Five different object recognition techniques are investigated: principal component analysis (PCA)+difference from vehicle space, PCA+difference in vehicle space, PCA+support vector machine, linear discriminant analysis, and constellation-based modeling applied to the problem of vehicle classification. Three of the techniques that performed well were incorporated into a unified traffic surveillance system for online classification of vehicles, which uses tracking results to improve the classification accuracy. To evaluate the accuracy of the system, 31 min of traffic video containing multilane traffic intersection was processed. It was possible to achieve classification accuracy as high as 90.49% while classifying correctly tracked vehicles into four classes: cars, SUVs/vans, pickup trucks, and buses/semis. While processing a video, our system also recorded important traffic parameters such as the appearance, speed, trajectory of a vehicle, etc. This information was later used in a search assistant tool to find interesting traffic events.

  11. Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

    NASA Astrophysics Data System (ADS)

    Onken, Jeffrey

    This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

  12. Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

    NASA Astrophysics Data System (ADS)

    Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

    2015-04-01

    Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations

  13. State feedback control of real-time discrete event systems with infinite states

    NASA Astrophysics Data System (ADS)

    Park, Seong-Jin; Cho, Kwang-Hyun

    2015-05-01

    In this paper, we study a state feedback supervisory control of timed discrete event systems (TDESs) with infinite number of states modelled as timed automata. To this end, we represent a timed automaton with infinite number of untimed states (called locations) by a finite set of conditional assignment statements. Predicates and predicate transformers are employed to finitely represent the behaviour and specification of a TDES with infinite number of locations. In addition, the notion of clock regions in timed automata is used to identify the reachable states of a TDES with an infinite time space. For a real-time specification described as a predicate, we present the controllability condition for the existence of a state feedback supervisor that restricts the behaviour of the controlled TDES within the specification.

  14. Prediction of solar energetic particle event histories using real-time particle and solar wind measurements

    NASA Technical Reports Server (NTRS)

    Roelof, E. C.; Gold, R. E.

    1978-01-01

    The comparatively well-ordered magnetic structure in the solar corona during the decline of Solar Cycle 20 revealed a characteristic dependence of solar energetic particle injection upon heliographic longitude. When analyzed using solar wind mapping of the large scale interplanetary magnetic field line connection from the corona to the Earth, particle fluxes display an approximately exponential dependence on heliographic longitude. Since variations in the solar wind velocity (and hence the coronal connection longitude) can severely distort the simple coronal injection profile, the use of real-time solar wind velocity measurements can be of great aid in predicting the decay of solar particle events. Although such exponential injection profiles are commonplace during 1973-1975, they have also been identified earlier in Solar Cycle 20, and hence this structure may be present during the rise and maximum of the cycle, but somewhat obscured by greater temporal variations in particle injection.

  15. Applications and usage of the real-time neutron monitor database for solar particle events monitoring

    NASA Astrophysics Data System (ADS)

    Papaioannou, Athanasios

    A high-time resolution Neutron Monitor Database (NMDB) has started to be realized in the frame of the Seventh Framework Programme of the European Commission. This database will include cosmic ray data from at least eighteen Neutron Monitors distributed around the world and operated in real time. The implementation of the NMDB will provide the opportunity for several research applications most of which will be implemented in real-time. The first and most important one will be the establishment of an Alert signal when dangerous solar particle events are heading to the Earth, resulting into Ground Level Enhancements effects registered by Neutron Monitors. On top of which, the mapping of all ground level enhancement features in near real-time mode will provide an over all picture of these phenomena and will be used as an input for the calculation of the ionization of the atmosphere. The latter will be useful for radiation dose calculations within the atmosphere at several altitudes and will reveal the absorbed doses during flights. Moreover, special algorithms for anisotropy and pitch angle distribution of cosmic rays, which have been developed over the years, will also be set online offering the advantage of an extensive analysis of the interplanetary space. All of the applications will serve the needs of the modern world which relies at space environment and will turn the extensive network of Neutron Monitors into a multi directional spectrographic detector. A part of the NMDB project is also dedicated to the creation of a public outreach website with the scope to inform about cosmic rays and their possible effects on humans, technological systems and space-terrestrial environment. Therefore, NMDB will also stand as an informative gate on space research through neutron monitor's data usage.

  16. Online Least Squares One-Class Support Vector Machines-Based Abnormal Visual Event Detection

    PubMed Central

    Wang, Tian; Chen, Jie; Zhou, Yi; Snoussi, Hichem

    2013-01-01

    The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samples to provide a basic normal model, then updates the model through remaining data. In the sparse online scheme, the model complexity is controlled by the coherence criterion. The online LS-OC-SVM is adopted to handle the abnormal event detection problem. Each frame of the video is characterized by the covariance matrix descriptor encoding the moving information, then is classified into a normal or an abnormal frame. Experiments are conducted, on a two-dimensional synthetic distribution dataset and a benchmark video surveillance dataset, to demonstrate the promising results of the proposed online LS-OC-SVM method. PMID:24351629

  17. Large Time Projection Chambers for Rare Event Detection

    SciTech Connect

    Heffner, M

    2009-11-03

    The Time Projection Chamber (TPC) concept [add ref to TPC section] has been applied to many projects outside of particle physics and the accelerator based experiments where it was initially developed. TPCs in non-accelerator particle physics experiments are principally focused on rare event detection (e.g. neutrino and darkmater experiments) and the physics of these experiments can place dramatically different constraints on the TPC design (only extensions to the traditional TPCs are discussed here). The drift gas, or liquid, is usually the target or matter under observation and due to very low signal rates a TPC with the largest active mass is desired. The large mass complicates particle tracking of short and sometimes very low energy particles. Other special design issues include, efficient light collection, background rejection, internal triggering and optimal energy resolution. Backgrounds from gamma-rays and neutrons are significant design issues in the construction of these TPCs. They are generally placed deep underground to shield from cosmogenic particles and surrounded with shielding to reduce radiation from the local surroundings. The construction materials have to be carefully screened for radiopurity as they are in close contact with the active mass and can be a signification source of background events. The TPC excels in reducing this internal background because the mass inside the fieldcage forms one monolithic volume from which fiducial cuts can be made ex post facto to isolate quiet drift mass, and can be circulated and purified to a very high level. Self shielding in these large mass systems can be significant and the effect improves with density. The liquid phase TPC can obtain a high density at low pressure which results in very good self-shielding and compact installation with a lightweight containment. The down sides are the need for cryogenics, slower charge drift, tracks shorter than the typical electron diffusion, lower energy resolution (e

  18. Real-time detection, location, and characterization of rockslides using broadband regional seismic networks

    NASA Astrophysics Data System (ADS)

    Manconi, Andrea; Picozzi, Matteo; Coviello, Velio; De Santis, Francesca; Elia, Luca

    2016-07-01

    We propose a new real-time approach to detect, locate, and estimate the volume of rockslides by analyzing waveforms acquired from broadband regional seismic networks. The identification of signals generated by rockslides from other sources, such as natural and/or induced earthquakes, is accomplished by exploiting the ratio between local magnitudes (ML) and duration magnitudes (MD). We found that signals associated with rockslides have ML/MD < 0.8, while for earthquakes ML/MD ≅ 1. In addition, we derived an empirical relationship between MD and rockslide volumes, obtaining a preliminary characterization of rockslide volume within seconds after their occurrence. The key points of this study are presented by testing the hypothesis on a recent rockslide event that occurred in northern Italy. We discuss also the potential evolution of the methodology for early warning and/or rapid response purposes.

  19. GPU-based real-time detection and analysis of biological targets using solid-state nanopores.

    PubMed

    Hafeez, Abdul; Asghar, Waseem; Rafique, M Mustafa; Iqbal, Samir M; Butt, Ali R

    2012-06-01

    The emergence of nanoscale devices has provided robust interfaces to biomolecules that faithfully transduce and define fundamental interactions of living systems. Measuring single-event behavior of important targets like DNA, and diseased cells has been achieved with a number of devices and systems. An important dimension to these systems, often discounted, is real-time computational decision-making from measured data. This paper describes an adaptive approach that can record single-molecule or single-cell events in real-time and automatically analyze patterns from the measured data. The automated analysis of measured data is done using a static threshold technique and two variations of a dynamic threshold technique: baseline-tracker and moving average filtering. Dynamic techniques for threshold detection enable noise suppression in the measured data and precise detection of patterns, but at the cost of more complex software as compared to static technique. To mitigate the computational overhead, a real-time system is implemented that uses advanced I/O techniques to minimize the execution stalls, thus enabling the system to process data significantly faster than the electrical measurement setup. Furthermore, the algorithms are implemented on programmable graphics processing units for parallel pattern detection. Our implementation provides five times faster data acquisition and pattern detection than the maximum sampling rate of the electrical measurement setup. PMID:22447368

  20. Integrated sorting, concentration and real time PCR based detection system for sensitive detection of microorganisms

    PubMed Central

    Nayak, Monalisha; Singh, Deepak; Singh, Himanshu; Kant, Rishi; Gupta, Ankur; Pandey, Shashank Shekhar; Mandal, Swarnasri; Ramanathan, Gurunath; Bhattacharya, Shantanu

    2013-01-01

    The extremely low limit of detection (LOD) posed by global food and water safety standards necessitates the need to perform a rapid process of integrated detection with high specificity, sensitivity and repeatability. The work reported in this article shows a microchip platform which carries out an ensemble of protocols which are otherwise carried in a molecular biology laboratory to achieve the global safety standards. The various steps in the microchip include pre-concentration of specific microorganisms from samples and a highly specific real time molecular identification utilizing a q-PCR process. The microchip process utilizes a high sensitivity antibody based recognition and an electric field mediated capture enabling an overall low LOD. The whole process of counting, sorting and molecular identification is performed in less than 4 hours for highly dilute samples. PMID:24253282

  1. Integrated sorting, concentration and real time PCR based detection system for sensitive detection of microorganisms

    NASA Astrophysics Data System (ADS)

    Nayak, Monalisha; Singh, Deepak; Singh, Himanshu; Kant, Rishi; Gupta, Ankur; Pandey, Shashank Shekhar; Mandal, Swarnasri; Ramanathan, Gurunath; Bhattacharya, Shantanu

    2013-11-01

    The extremely low limit of detection (LOD) posed by global food and water safety standards necessitates the need to perform a rapid process of integrated detection with high specificity, sensitivity and repeatability. The work reported in this article shows a microchip platform which carries out an ensemble of protocols which are otherwise carried in a molecular biology laboratory to achieve the global safety standards. The various steps in the microchip include pre-concentration of specific microorganisms from samples and a highly specific real time molecular identification utilizing a q-PCR process. The microchip process utilizes a high sensitivity antibody based recognition and an electric field mediated capture enabling an overall low LOD. The whole process of counting, sorting and molecular identification is performed in less than 4 hours for highly dilute samples.

  2. REAL-TIME PCR METHOD TO DETECT ENTEROCOCCUS FAECALIS IN WATER

    EPA Science Inventory

    A 16S rDNA real-time PCR method was developed to detect Enterococcus faecalis in water samples. The dynamic range for cell detection spanned five logs and the detection limit was determined to be 6 cfu/reaction. The assay was capable of detecting E. faecalis cells added to biof...

  3. OGLE-2009-BLG-092/MOA-2009-BLG-137: A DRAMATIC REPEATING EVENT WITH THE SECOND PERTURBATION PREDICTED BY REAL-TIME ANALYSIS

    SciTech Connect

    Ryu, Y.-H.; Han, C.; Hwang, K.-H.; Street, R.; Udalski, A.; Sumi, T.; Fukui, A.; Abe, F.; Furusawa, K.; Hayashi, F.; Hosaka, S.; Itow, Y.; Kamiya, K.; Beaulieu, J.-P.; Gould, A.; Dominik, M.; Bennett, D. P.; Bond, I. A.; Botzler, C. S.; Hearnshaw, J. B.

    2010-11-01

    We report the result of the analysis of a dramatic repeating gravitational microlensing event OGLE-2009-BLG-092/MOA-2009-BLG-137, for which the light curve is characterized by two distinct peaks with perturbations near both peaks. We find that the event is produced by the passage of the source trajectory over the central perturbation regions associated with the individual components of a wide-separation binary. The event is special in the sense that the second perturbation, occurring {approx}100 days after the first, was predicted by the real-time analysis conducted after the first peak, demonstrating that real-time modeling can be routinely done for binary and planetary events. With the data obtained from follow-up observations covering the second peak, we are able to uniquely determine the physical parameters of the lens system. We find that the event occurred on a bulge clump giant and it was produced by a binary lens composed of a K- and M-type main-sequence stars. The estimated masses of the binary components are M{sub 1} = 0.69 {+-} 0.11 M{sub sun} and M{sub 2} = 0.36 {+-} 0.06 M{sub sun}, respectively, and they are separated in projection by r{sub perpendicular} = 10.9 {+-} 1.3 AU. The measured distance to the lens is D{sub L} = 5.6 {+-} 0.7 kpc. We also detect the orbital motion of the lens system.

  4. Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

    PubMed

    Oliker, Nurit; Ostfeld, Avi

    2015-09-01

    Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. PMID:25996752

  5. Real-time PCR assay for detection of a new simulant for poxvirus biothreat agents.

    PubMed

    Garnier, Laurence; Gaudin, Jean-Christophe; Bensadoun, Paul; Rebillat, Isabelle; Morel, Yannick

    2009-03-01

    Research and financial efforts spent on biodefense technologies highlight the current concern for biothreat event preparedness. Nonhazardous but relevant "simulant" microorganisms are typically used to simplify technological developments, testing, and staff training. The bacteriophage MS2, a small RNA virus, is classically used as the reference simulant for biothreat viruses within the biodefense community. However, variola virus, considered a major threat, displays very different features (size, envelope, and double-stranded DNA genome). The size parameter is critical for aerosol sampling, detection, and protection/filtration technologies. Therefore, a panel of relevant simulants should be used to cover the diversity of biothreat agents. Thus, we investigated a new virus model, the Cydia pomonella granulovirus (baculovirus), which is currently used as a biopesticide. It displays a size similar to that of poxviruses, is enveloped, and contains double-stranded DNA. To provide a molecular tool to detect and quantify this model virus, we developed an assay based on real-time PCR, with a limit of detection ranging from roughly 10 to a few tens of target copies per microl according to the sample matrix. The specificity of the assay against a large panel of potential cross-reactive microorganisms was checked, and the suitability of the assay for environmental samples, especially aerosol studies, was determined. In conclusion, we suggest that our PCR assay allows Cydia pomonella granulovirus to be used as a simulant for poxviruses. This assay may also be useful for environmental or crop treatment studies. PMID:19168659

  6. Real-Time Detection of Staphylococcus Aureus Using Whispering Gallery Mode Optical Microdisks.

    PubMed

    Ghali, Hala; Chibli, Hicham; Nadeau, Jay L; Bianucci, Pablo; Peter, Yves-Alain

    2016-01-01

    Whispering Gallery Mode (WGM) microresonators have recently been studied as a means to achieve real-time label-free detection of biological targets such as virus particles, specific DNA sequences, or proteins. Due to their high quality (Q) factors, WGM resonators can be highly sensitive. A biosensor also needs to be selective, requiring proper functionalization of its surface with the appropriate ligand that will attach the biomolecule of interest. In this paper, WGM microdisks are used as biosensors for detection of Staphylococcus aureus. The microdisks are functionalized with LysK, a phage protein specific for staphylococci at the genus level. A binding event on the surface shifts the resonance peak of the microdisk resonator towards longer wavelengths. This reactive shift can be used to estimate the surface density of bacteria that bind to the surface of the resonator. The limit of detection of a microdisk with a Q-factor around 10⁴ is on the order of 5 pg/mL, corresponding to 20 cells. No binding of Escherichia coli to the resonators is seen, supporting the specificity of the functionalization scheme. PMID:27153099

  7. Real-Time Detection of Staphylococcus Aureus Using Whispering Gallery Mode Optical Microdisks

    PubMed Central

    Ghali, Hala; Chibli, Hicham; Nadeau, Jay L.; Bianucci, Pablo; Peter, Yves-Alain

    2016-01-01

    Whispering Gallery Mode (WGM) microresonators have recently been studied as a means to achieve real-time label-free detection of biological targets such as virus particles, specific DNA sequences, or proteins. Due to their high quality (Q) factors, WGM resonators can be highly sensitive. A biosensor also needs to be selective, requiring proper functionalization of its surface with the appropriate ligand that will attach the biomolecule of interest. In this paper, WGM microdisks are used as biosensors for detection of Staphylococcus aureus. The microdisks are functionalized with LysK, a phage protein specific for staphylococci at the genus level. A binding event on the surface shifts the resonance peak of the microdisk resonator towards longer wavelengths. This reactive shift can be used to estimate the surface density of bacteria that bind to the surface of the resonator. The limit of detection of a microdisk with a Q-factor around 104 is on the order of 5 pg/mL, corresponding to 20 cells. No binding of Escherichia coli to the resonators is seen, supporting the specificity of the functionalization scheme. PMID:27153099

  8. The design and hardware implementation of a low-power real-time seizure detection algorithm

    NASA Astrophysics Data System (ADS)

    Raghunathan, Shriram; Gupta, Sumeet K.; Ward, Matthew P.; Worth, Robert M.; Roy, Kaushik; Irazoqui, Pedro P.

    2009-10-01

    Epilepsy affects more than 1% of the world's population. Responsive neurostimulation is emerging as an alternative therapy for the 30% of the epileptic patient population that does not benefit from pharmacological treatment. Efficient seizure detection algorithms will enable closed-loop epilepsy prostheses by stimulating the epileptogenic focus within an early onset window. Critically, this is expected to reduce neuronal desensitization over time and lead to longer-term device efficacy. This work presents a novel event-based seizure detection algorithm along with a low-power digital circuit implementation. Hippocampal depth-electrode recordings from six kainate-treated rats are used to validate the algorithm and hardware performance in this preliminary study. The design process illustrates crucial trade-offs in translating mathematical models into hardware implementations and validates statistical optimizations made with empirical data analyses on results obtained using a real-time functioning hardware prototype. Using quantitatively predicted thresholds from the depth-electrode recordings, the auto-updating algorithm performs with an average sensitivity and selectivity of 95.3 ± 0.02% and 88.9 ± 0.01% (mean ± SEα = 0.05), respectively, on untrained data with a detection delay of 8.5 s [5.97, 11.04] from electrographic onset. The hardware implementation is shown feasible using CMOS circuits consuming under 350 nW of power from a 250 mV supply voltage from simulations on the MIT 180 nm SOI process.

  9. Unsupervised spatio-temporal detection of brain functional activation based on hidden Markov multiple event sequence models

    NASA Astrophysics Data System (ADS)

    Faisan, Sylvain; Thoraval, Laurent; Armspach, Jean-Paul; Heitz, Fabrice; Foucher, Jack

    2005-04-01

    This paper presents a novel, completely unsupervised fMRI brain mapping approach that addresses the three problems of hemodynamic response function (HRF) shape variability, neural event timing, and fMRI response linearity. To make it robust, the method takes into account spatial and temporal information directly into the core of the activation detection process. In practice, activation detection is formulated in terms of temporal alignment between the sequence of hemodynamic response onsets (HROs) detected in the fMRI signal at υ and in the spatial neighbourhood of υ, and the sequence of "off-on" transitions observed in the input blocked stimulation paradigm (when considering epoch-related fMRI data), or the sequence of stimuli of the event-based paradigm (when considering event-related fMRI data). This multiple event sequence alignment problem, which comes under multisensor data fusion, is solved within the probabilistic framework of hidden Markov multiple event sequence models (HMMESMs), a special class of hidden Markov models. Results obtained on real and synthetic data compete with those obtained with the popular statistical parametric mapping (SPM) approach, but without necessitating any prior definition of the expected activation patterns, the HMMESM mapping approach being completely unsupervised.

  10. Detection of events of public health importance under the international health regulations: a toolkit to improve reporting of unusual events by frontline healthcare workers

    PubMed Central

    2011-01-01

    an implementation plan. The toolkit emphasizes what to report, the reporting process and the need for follow-up, supported by real examples. Conclusion This toolkit addresses the importance of mutual exchange of information between frontline healthcare workers and public health authorities. It may potentially increase frontline healthcare workers' awareness of their role in the detection of events of public health concern, improve communication channels and contribute to creating an enabling environment for event reporting. However, the effectiveness of the toolkit will depend on the national body responsible for dissemination and training. PMID:21936937

  11. A HANDHELD REAL TIME THERMAL CYCLER FOR BACTERIAL PATHOGEN DETECTION

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Handheld Advanced Nucleic Acid Analyzer (HANAA) is a portable real time thermal cycler unit that weighs under 1 kg and uses silicon and platinum-based thermalcycler units to conduct rapid heating and cooling of plastic reaction tubes. Two light emitting diodes (LED) provide greater than 1 mW of ...

  12. Method and apparatus for detecting and determining event characteristics with reduced data collection

    NASA Technical Reports Server (NTRS)

    Totman, Peter D. (Inventor); Everton, Randy L. (Inventor); Egget, Mark R. (Inventor); Macon, David J. (Inventor)

    2007-01-01

    A method and apparatus for detecting and determining event characteristics such as, for example, the material failure of a component, in a manner which significantly reduces the amount of data collected. A sensor array, including a plurality of individual sensor elements, is coupled to a programmable logic device (PLD) configured to operate in a passive state and an active state. A triggering event is established such that the PLD records information only upon detection of the occurrence of the triggering event which causes a change in state within one or more of the plurality of sensor elements. Upon the occurrence of the triggering event, the change in state of the one or more sensor elements causes the PLD to record in memory which sensor element detected the event and at what time the event was detected. The PLD may be coupled with a computer for subsequent downloading and analysis of the acquired data.

  13. Real time imaging of live cell ATP leaking or release events by chemiluminescence microscopy

    SciTech Connect

    Zhang, Yun

    2008-12-18

    The purpose of this research was to expand the chemiluminescence microscopy applications in live bacterial/mammalian cell imaging and to improve the detection sensitivity for ATP leaking or release events. We first demonstrated that chemiluminescence (CL) imaging can be used to interrogate single bacterial cells. While using a luminometer allows detecting ATP from cell lysate extracted from at least 10 bacterial cells, all previous cell CL detection never reached this sensitivity of single bacteria level. We approached this goal with a different strategy from before: instead of breaking bacterial cell membrane and trying to capture the transiently diluted ATP with the firefly luciferase CL assay, we introduced the firefly luciferase enzyme into bacteria using the modern genetic techniques and placed the CL reaction substrate D-luciferin outside the cells. By damaging the cell membrane with various antibacterial drugs including antibiotics such as Penicillins and bacteriophages, the D-luciferin molecules diffused inside the cell and initiated the reaction that produces CL light. As firefly luciferases are large protein molecules which are retained within the cells before the total rupture and intracellular ATP concentration is high at the millmolar level, the CL reaction of firefly luciferase, ATP and D-luciferin can be kept for a relatively long time within the cells acting as a reaction container to generate enough photons for detection by the extremely sensitive intensified charge coupled device (ICCD) camera. The result was inspiring as various single bacterium lysis and leakage events were monitored with 10-s temporal resolution movies. We also found a new way of enhancing diffusion D-luciferin into cells by dehydrating the bacteria. Then we started with this novel single bacterial CL imaging technique, and applied it for quantifying gene expression levels from individual bacterial cells. Previous published result in single cell gene expression quantification

  14. Reading Times and the Detection of Event Shift Processing

    ERIC Educational Resources Information Center

    Radvansky, Gabriel A.; Copeland, David E.

    2010-01-01

    When people read narratives, they often need to update their situation models as the described events change. Previous research has shown little to no increases in reading times for spatial shifts but consistent increases for temporal shifts. On this basis, researchers have suggested that spatial updating does not regularly occur, whereas temporal…

  15. Setting objective thresholds for rare event detection in flow cytometry.

    PubMed

    Richards, Adam J; Staats, Janet; Enzor, Jennifer; McKinnon, Katherine; Frelinger, Jacob; Denny, Thomas N; Weinhold, Kent J; Chan, Cliburn

    2014-07-01

    The accurate identification of rare antigen-specific cytokine positive cells from peripheral blood mononuclear cells (PBMC) after antigenic stimulation in an intracellular staining (ICS) flow cytometry assay is challenging, as cytokine positive events may be fairly diffusely distributed and lack an obvious separation from the negative population. Traditionally, the approach by flow operators has been to manually set a positivity threshold to partition events into cytokine-positive and cytokine-negative. This approach suffers from subjectivity and inconsistency across different flow operators. The use of statistical clustering methods does not remove the need to find an objective threshold between between positive and negative events since consistent identification of rare event subsets is highly challenging for automated algorithms, especially when there is distributional overlap between the positive and negative events ("smear"). We present a new approach, based on the Fβ measure, that is similar to manual thresholding in providing a hard cutoff, but has the advantage of being determined objectively. The performance of this algorithm is compared with results obtained by expert visual gating. Several ICS data sets from the External Quality Assurance Program Oversight Laboratory (EQAPOL) proficiency program were used to make the comparisons. We first show that visually determined thresholds are difficult to reproduce and pose a problem when comparing results across operators or laboratories, as well as problems that occur with the use of commonly employed clustering algorithms. In contrast, a single parameterization for the Fβ method performs consistently across different centers, samples, and instruments because it optimizes the precision/recall tradeoff by using both negative and positive controls. PMID:24727143

  16. Monitoring the data quality of the real-time event reconstruction in the ALICE High Level Trigger

    NASA Astrophysics Data System (ADS)

    Austrheim Erdal, Hege; Richther, Matthias; Szostak, Artur; Toia, Alberica

    2012-12-01

    ALICE is a dedicated heavy ion experiment at the CERN LHC. The ALICE High Level Trigger was designed to select events with desirable physics properties. Data from several of the major subdetectors in ALICE are processed by the HLT for real-time event reconstruction, for instance the Inner Tracking System, the Time Projection Chamber, the electromagnetc calorimeters, the Transition Radiation Detector and the muon spectrometer. The HLT reconstructs events in real-time and thus provides input for trigger algorithms. It is necessary to monitor the quality of the reconstruction where one focuses on track and event properties. Also, HLT implemented data compression for the TPC during the heavy ion data taking in 2011 to reduce the data rate from the ALICE detector. The key for the data compression is to store clusters (spacepoints) calculated by HLT rather than storing raw data. It is thus very important to monitor the cluster finder performance as a way to monitor the data compression. The data monitoring is divided into two stages. The first stage is performed during data taking. A part of the HLT production chain is dedicated to performing online monitoring and facilities are available in the HLT production cluster to have real-time access to the reconstructed events in the ALICE control room. This includes track and event properties, and in addition, this facility gives a way to display a small fraction of the reconstructed events in an online display. The second part of the monitoring is performed after the data has been transferred to permanent storage. After a post-process of the real-time reconstructed data, one can look in more detail at the cluster finder performance, the quality of the reconstruction of tracks, vertices and vertex position. The monitoring solution is presented in detail, with special attention to the heavy ion data taking of 2011.

  17. Real-time SAR change-detection using neural networks

    NASA Astrophysics Data System (ADS)

    Oliver, Christopher J.; White, Richard G.

    1990-11-01

    This paper describes the techniques evolved at RSRE for the production of undistorted, focused synthetic aperture radar (SAR) images, target detection using a neural network method and the automatic detection of changes between pairs of SAR images. All these processes are achievable in a single pipelined process operating on an input data rate in excess of 10 Mbytes/second.

  18. Rapid detection of Salmonella in bovine lymph nodes using a commercial real-time PCR system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rapid Salmonella detection is needed to help prevent the distribution of contaminated food products. Using traditional culture methods, Salmonella detection can take up to 3-5 days. Using an improved protocol and a commercial real-time PCR system, we have shortened the detection time to under 24 h...

  19. The GRACE satellites detect recent extreme climate events in China

    NASA Astrophysics Data System (ADS)

    Tang, Jingshi; Liu, Lin

    2012-07-01

    As the climate changes, the extreme climates are occurring more frequenly over the globe. In China, drought or flood recently strikes almost every year and there have been several disastrous events in these years. We show that some of the disastrous events are so strong that corresponding gravity change can be observed by geodetic satellies. We use the Gravity Recovery and Climate Experiment (GRACE), which is a joint mission between NASA and DLR. One primary job of GRACE is to map Earth temporal gravity field with high resolution. Over the years the twin satellites have observed the loss of mass in Antarctic and Greenland, strong earthquakes, severe climate change in South America and so on, which provides a unique way to study the geophysical or climatological process. In this report, the Level-2 product in recent few years from Center for Space Research is used and specific areas in China are focused on. It is shown that after decorrelation, filter and other processes, the gravity anomalies observed by GRACE match the extreme climate events and the hydrological data from the Global Land Data Assimilation System (GLDAS).

  20. Real-time detection of musical onsets with linear prediction and sinusoidal modeling

    NASA Astrophysics Data System (ADS)

    Glover, John; Lazzarini, Victor; Timoney, Joseph

    2011-12-01

    Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This article provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets.

  1. Quantitative Detection of Listeria monocytogenes in Biofilms by Real-Time PCR

    PubMed Central

    Guilbaud, Morgan; de Coppet, Pierre; Bourion, Fabrice; Rachman, Cinta; Prévost, Hervé; Dousset, Xavier

    2005-01-01

    A quantitative method based on a real-time PCR assay to enumerate Listeria monocytogenes in biofilms was developed. The specificity for L. monocytogenes of primers targeting the listeriolysin gene was demonstrated using a SYBR Green I real-time PCR assay. The number of L. monocytogenes detected growing in biofilms was 6 × 102 CFU/cm2. PMID:15812058

  2. Neuro-evolutionary event detection technique for downhole microseismic surveys

    NASA Astrophysics Data System (ADS)

    Maity, Debotyam; Salehi, Iraj

    2016-01-01

    Recent years have seen a significant increase in borehole microseismic data acquisition programs associated with unconventional reservoir developments such as hydraulic fracturing programs for shale oil and gas. The data so acquired is used for hydraulic fracture monitoring and diagnostics and therefore, the quality of the data in terms of resolution and accuracy has a significant impact on its value to the industry. Borehole microseismic data acquired in such environments typically suffer from propagation effects due to the presence of thin interbedded shale layers as well as noise and interference effects. Moreover, acquisition geometry has significant impact on detectability across portions of the sensor array. Our work focuses on developing robust first arrival detection and pick selection workflow for both P and S waves specifically designed for such environments. We introduce a novel workflow for refinement of picks with immunity towards significant noise artifacts and applicability over data with very low signal-to-noise ratio provided some accurate picks have already been made. This workflow utilizes multi-step hybrid detection and classification routine which makes use of a neural network based autopicker for initial picking and an evolutionary algorithm for pick refinement. We highlight the results from an actual field case study including multiple examples demonstrating immunity towards noise and compare the effectiveness of the workflow with two contemporary autopicking routines without the application of the shared detection/refinement procedure. Finally, we use a windowed waveform cross-correlation based uncertainty estimation method for potential quality control purposes. While the workflow was developed to work with the neural network based autopicker, it can be used with any other traditional autopicker and provides significant improvements in pick detection across seismic gathers.

  3. Automatic Event Detection and Characterization of solar events with IRIS, SDO/AIA and Hi-C

    NASA Astrophysics Data System (ADS)

    Alexander, Caroline; Fayock, Brian; Winebarger, Amy

    2016-05-01

    Dynamic, low-lying loops with peak temperatures <1 MK are observed throughout the solar transition region. These loops can be observed in SDO/AIA data due to some lower temperature spectral lines in the passbands, but have not been studied in great detail. We have developed a technique to automatically identify events (i.e., brightenings) on a pixel-by-pixel basis applying a set of selection criteria. The pixels are then grouped according to their proximity in space and relative progression of the event. This method allows us to characterize their overall lifetime and the rate at which these events occur. Our current progress includes identification of these groups of events in IRIS data, determination of their existence in AIA data, and characterization based on a comparison between the two. This technique has also been used on Hi-C data in preparation for the rocket re-flight in July 2016. Results on the success of this technique at identifying real structures and sources of heating will be shown.

  4. Spatial-temporal event detection in climate parameter imagery.

    SciTech Connect

    McKenna, Sean Andrew; Gutierrez, Karen A.

    2011-10-01

    Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to the earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.

  5. Detection of intermittent events in atmospheric time series

    NASA Astrophysics Data System (ADS)

    Paradisi, P.; Cesari, R.; Palatella, L.; Contini, D.; Donateo, A.

    2009-04-01

    The modeling approach in atmospheric sciences is based on the assumption that local fluxes of mass, momentum, heat, etc... can be described as linear functions of the local gradient of some intensive property (concentration, flow strain, temperature,...). This is essentially associated with Gaussian statistics and short range (exponential) correlations. However, the atmosphere is a complex dynamical system displaying a wide range of spatial and temporal scales. A global description of the atmospheric dynamics should include a great number of degrees of freedom, strongly interacting on several temporal and spatial scales, thus generating long range (power-law) correlations and non-Gaussian distribution of fluctuations (Lévy flights, Lévy walks, Continuous Time Random Walks) [1]. This is typically associated with anomalous diffusion and scaling, non-trivial memory features and correlation decays and, especially, with the emergence of flux-gradient relationships that are non-linear and/or non-local in time and/or space. Actually, the local flux-gradient relationship is greatly preferred due to a more clear physical meaning, allowing to perform direct comparisons with experimental data, and, especially, to smaller computational costs in numerical models. In particular, the linearity of this relationship allows to define a transport coefficient (e.g., turbulent diffusivity) and the modeling effort is usually focused on this coefficient. However, the validity of the local (and linear) flux-gradient model is strongly dependent on the range of spatial and temporal scales represented by the model and, consequently, by the sub-grid processes included in the flux-gradient relationship. In this work, in order to check the validity of local and linear flux-gradient relationships, an approach based on the concept of renewal critical events [2] is introduced. In fact, in renewal theory [2], the dynamical origin of anomalous behaviour and non-local flux-gradient relation is

  6. A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

    PubMed Central

    Zhang, Shukui; Chen, Hao; Zhu, Qiaoming

    2014-01-01

    The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690

  7. Profiling of molecular interactions in real time using acoustic detection.

    PubMed

    Godber, Benjamin; Frogley, Mark; Rehak, Marian; Sleptsov, Alexander; Thompson, Kevin S J; Uludag, Yildiz; Cooper, Matthew A

    2007-04-15

    Acoustic sensors that exploit resonating quartz crystals to directly detect the binding of an analyte to a receptor are finding increasing utility in the quantification of clinically relevant analytes. We have developed a novel acoustic detection technology, which we term resonant acoustic profiling (RAP). This technology builds on the fundamental basics of the "quartz crystal microbalance" or "QCM" with several key additional features including two- or four-channel automated sample delivery, in-line referencing and microfluidic sensor 'cassettes' that are pre-coated with easy-to-use surface chemistries. Example applications are described for the quantification of myoglobin concentration and its interaction kinetics, and for the ranking of enzyme-cofactor specificities. PMID:17129723

  8. Real-Time Detection of Terahertz Pulse Amplitude and Position

    NASA Astrophysics Data System (ADS)

    Pühringer, Harald; Nejim, Zeineb; Pfleger, Michael; Katletz, Stefan

    2016-02-01

    A novel and continuous detection scheme for the pulse amplitude and temporal position of a terahertz time domain system is presented. Currently, we have achieved a sampling time of 25 Hz and a resolution of less than 70 fs. The method is therefore very well suited for online measurements in production processes to monitor the thickness and inhomogeneities in the composition of non-conducting materials.

  9. Real-Time PCR: Revolutionizing Detection and Expression Analysis of Genes

    PubMed Central

    Deepak, SA; Kottapalli, KR; Rakwal, R; Oros, G; Rangappa, KS; Iwahashi, H; Masuo, Y; Agrawal, GK

    2007-01-01

    Invention of polymerase chain reaction (PCR) technology by Kary Mullis in 1984 gave birth to real-time PCR. Real-time PCR — detection and expression analysis of gene(s) in real-time — has revolutionized the 21st century biological science due to its tremendous application in quantitative genotyping, genetic variation of inter and intra organisms, early diagnosis of disease, forensic, to name a few. We comprehensively review various aspects of real-time PCR, including technological refinement and application in all scientific fields ranging from medical to environmental issues, and to plant. PMID:18645596

  10. Real Time Intelligent Target Detection and Analysis with Machine Vision

    NASA Technical Reports Server (NTRS)

    Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

    2000-01-01

    We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

  11. Architecture for event-driven real-time distributed computer systems

    SciTech Connect

    McDonald, J.E.

    1983-01-01

    The author describes a proposed preliminary system design that includes hardware and software for real-time distributed computer systems. This new system is appropriate as a digital avionics architecture or as a real-time multi-computer simulation system using a mixture of computers, mainframes to micros. The hardware contains a network that employs high-speed serial data transmission concepts in emulating a multicomputer shared memory system. The distributed multicomputer system then capitalizes on the attributes of the hardware by structuring the real-time software as the data-driven input-output system. The real-time software executes only on demand and not synchronously as in conventional real-time systems. Background information concerning multi-computer systems using serial and parallel data transmission networks is given. This information supports the design rationale of the proposed hardware system which is basically a technology blend of conventional serial and parallel transmission schemes. 2 references.

  12. Object-Oriented Query Language For Events Detection From Images Sequences

    NASA Astrophysics Data System (ADS)

    Ganea, Ion Eugen

    2015-09-01

    In this paper is presented a method to represent the events extracted from images sequences and the query language used for events detection. Using an object oriented model the spatial and temporal relationships between salient objects and also between events are stored and queried. This works aims to unify the storing and querying phases for video events processing. The object oriented language syntax used for events processing allow the instantiation of the indexes classes in order to improve the accuracy of the query results. The experiments were performed on images sequences provided from sport domain and it shows the reliability and the robustness of the proposed language. To extend the language will be added a specific syntax for constructing the templates for abnormal events and for detection of the incidents as the final goal of the research.

  13. Detection of Upper Airway Status and Respiratory Events by a Current Generation Positive Airway Pressure Device

    PubMed Central

    Li, Qing Yun; Berry, Richard B.; Goetting, Mark G.; Staley, Bethany; Soto-Calderon, Haideliza; Tsai, Sheila C.; Jasko, Jeffrey G.; Pack, Allan I.; Kuna, Samuel T.

    2015-01-01

    Study Objectives: To compare a positive airway pressure (PAP) device's detection of respiratory events and airway status during device-detected apneas with events scored on simultaneous polysomnography (PSG). Design: Prospective PSGs of patients with sleep apnea using a new-generation PAP device. Settings: Four clinical and academic sleep centers. Patients: Forty-five patients with obstructive sleep apnea (OSA) and complex sleep apnea (Comp SA) performed a PSG on PAP levels adjusted to induce respiratory events. Interventions: None. Measurements and Results: PAP device data identifying the type of respiratory event and whether the airway during a device-detected apnea was open or obstructed were compared to time-synced, manually scored respiratory events on simultaneous PSG recording. Intraclass correlation coefficients between device-detected and PSG scored events were 0.854 for apnea-hypopnea index (AHI), 0.783 for apnea index, 0.252 for hypopnea index, and 0.098 for respiratory event-related arousals index. At a device AHI (AHIFlow) of 10 events/h, area under the receiver operating characteristic curve was 0.98, with sensitivity 0.92 and specificity 0.84. AHIFlow tended to overestimate AHI on PSG at values less than 10 events/h. The device detected that the airway was obstructed in 87.4% of manually scored obstructive apneas. Of the device-detected apneas with clear airway, a minority (15.8%) were manually scored as obstructive apneas. Conclusions: A device-detected apnea-hypopnea index (AHIFlow) < 10 events/h on a positive airway pressure device is strong evidence of good treatment efficacy. Device-detected airway status agrees closely with the presumed airway status during polysomnography scored events, but should not be equated with a specific type of respiratory event. Citation: Li QY, Berry RB, Goetting MG, Staley B, Soto-Calderon H, Tsai SC, Jasko JG, Pack AI, Kuna ST. Detection of upper airway status and respiratory events by a current generation positive

  14. Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

    PubMed Central

    Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

    2014-01-01

    Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

  15. Find Your Manners: How Do Infants Detect the Invariant Manner of Motion in Dynamic Events?

    ERIC Educational Resources Information Center

    Pruden, Shannon M.; Goksun, Tilbe; Roseberry, Sarah; Hirsh-Pasek, Kathy; Golinkoff, Roberta M.

    2012-01-01

    To learn motion verbs, infants must be sensitive to the specific event features lexicalized in their language. One event feature important for the acquisition of English motion verbs is the manner of motion. This article examines when and how infants detect manners of motion across variations in the figure's path. Experiment 1 shows that 13- to…

  16. Novel real-time PCR detection assay for Brucella suis

    PubMed Central

    Hänsel, C.; Mertens, K.; Elschner, M. C.; Melzer, F.

    2015-01-01

    Introduction Brucella suis is the causative agent of brucellosis in suidae and is differentiated into five biovars (bv). Biovars 1 and 3 possess zoonotic potential and can infect humans, whereas biovar 2 represents the main source of brucellosis in feral and domestic pigs in Europe. Both aspects, the zoonotic threat and the economic loss, emphasize the necessity to monitor feral and domestic pig populations. Available serological or PCR based methods lack sensitivity and specificity. Results Here a bioinformatics approach was used to identify a B. suis specific 17 bp repeat on chromosome II (BS1330_II0657 locus). This repeat is common for B. suis bv 1 to 4 and was used to develop a TaqMan probe assay. The average PCR efficiency was determined as 95% and the limit of detection as 12,5 fg/µl of DNA, equally to 3.7 bacterial genomes. This assay has the highest sensitivity of all previously described B. suis specific PCR assays, making it possible to detect 3-4 bacterial genomes per 1 µl of sample. The assay was tested 100% specific for B. suis and negative for other Brucella spp. and closely related non-Brucella species. Conclusions This novel qPCR assay could become a rapid, inexpensive and reliable screening method for large sample pools of B. suis 1 to 4. This method will be applicable for field samples after validation. PMID:26392898

  17. MCD for detection of event-based landslides

    NASA Astrophysics Data System (ADS)

    Mondini, A. C.; Chang, K.; Guzzetti, F.

    2011-12-01

    Landslides play an important role in the landscape evolution of mountainous terrain. They also present a socioeconomic problem in terms of risk for people and properties. Landslide inventory maps are not available for many areas affected by slope instabilities, resulting in a lack of primary information for the comprehension of the phenomenon, evaluation of relative landslide statistics, and civil protection operations on large scales. Traditional methods for the preparation of landslide inventory maps are based on the geomorphological interpretation of stereoscopic aerial photography and field surveys. These methods are expensive and time consuming. The exploitation of new remote sensing data, in particular very high resolution (VHR) satellite images, and new dedicated methods present an alternative to the traditional methods and are at the forefront of modern landslide research. Recent studies have showed the possibility to produce accurate landslide maps, reducing the time and resources required for their compilation and systematic update. This paper presents the Multiple Change Detection (MCD) technique, a new method that has shown promising results in landslide mapping. Through supervised or unsupervised classifiers, MCD combines different algorithms of change detection metrics, such as change in Normalized Differential Vegetation Index, spectral angle, principal component analysis, and independent component analysis, and applies them to a multi-temporal set of VHR satellite images to distinguish new landslides from stable areas. MCD has been applied with success in different geographical areas and with different satellite images, suggesting it is a reliable and robust technique. The technique can distinguish old from new landslides and capture runout features. Results of these case studies will be presented in the conference. Also to be presented are new developments of MCD involving the introduction of a priori information on landslide susceptibility within

  18. Real-time RT-PCR Assay for Detection and Differentiation of Citrus Tristeza Virus Isolates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multiplex one step real time RT-PCR assays using TaqMan probes were developed for detection and strain differentiation of Citrus tristeza virus (CTV). For broad spectrum CTV detection, a TaqMan primer and Cy5-labeled probe were designed using CP gene sequences. An internal control was developed us...

  19. Bimetallic nanowires as electrocatalysts for nonenzymatic real-time impedancimetric detection of glucose.

    PubMed

    Mayorga-Martinez, Carmen C; Guix, Maria; Madrid, Rossana E; Merkoçi, Arben

    2012-02-01

    Gold-platinum nanowires are proposed as electrocatalysts for a real-time nonenzymatic impedancimetric detection of glucose. The electrochemical behavior of the obtained platform toward electrocatalytic oxidation of glucose, including a proposal for the detection mechanism, is shown. PMID:22183014

  20. Detection of Toxoplasma gondii oocysts in water sample concentrates by real-time PCR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    PCR techniques in combination with conventional parasite concentration procedures have potential for sensitive and specific detection of Toxoplasma gondii oocysts in water. Three real-time PCR assays based on the B1 gene and a 529-bp repetitive element were compared for detection of T. gondii tachyz...

  1. Line-scan hyperspectral imaging for real-time on-line poultry fecal detection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The preliminary results demonstrated that high speed line-scan hyperspectral imaging system has a potential for real-time online fecal detection during poultry processing. To improve detection accuracy, fully calibrated images both spatially and spectrally were acquired for further processing. In ad...

  2. Real-time RT-PCR assay for detection and differentiation of Citrus tristeza virus isolates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    For universal detection of Citrus tristeza virus (CTV) strains by real time RT-PCR, a protocol was developed based on a set of primers and a Cy5-labeled TaqMan probe. This test included primers and a TET-labeled TaqMan probe selected on the mitochondrial nad5 gene for the simultaneous detection of ...

  3. Line-scan hyperspectral imaging for real-time poultry fecal detection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The preliminary results demonstrated that high speed line-scan hyperspectral imaging system has a potential for real-time online fecal detection during poultry processing. To improve detection accuracy, fully calibrated images both spatially and spectrally were acquired for further processing. In ad...

  4. Comparison of the STA/LTA and power spectral density methods for microseismic event detection

    NASA Astrophysics Data System (ADS)

    Vaezi, Yoones; Van der Baan, Mirko

    2015-12-01

    Robust event detection and picking is a prerequisite for reliable (micro-) seismic interpretations. Detection of weak events is a common challenge among various available event detection algorithms. In this paper we compare the performance of two event detection methods, the short-term average/long-term average (STA/LTA) method, which is the most commonly used technique in industry, and a newly introduced method that is based on the power spectral density (PSD) measurements. We have applied both techniques to a 1-hr long segment of the vertical component of some raw continuous data recorded at a borehole geophone in a hydraulic fracturing experiment. The PSD technique outperforms the STA/LTA technique by detecting a higher number of weak events while keeping the number of false alarms at a reasonable level. The time-frequency representations obtained through the PSD method can also help define a more suitable bandpass filter which is usually required for the STA/LTA method. The method offers thus much promise for automated event detection in industrial, local, regional and global seismological data sets.

  5. Detecting EUV transients in near real time with ALEXIS

    SciTech Connect

    Roussel-Dupre`, D.; Bloch, J.J.; Theiler, J.; Pfafman, T.; Beauchesne, B.

    1995-12-31

    The Array of Low Energy X-ray Imaging Sensors (ALEXIS) experiment consists of a mini-satellite containing six wide angle EUV/ultrasoft X-ray telescopes (Priedhorsky et al. 1989, and Bloch et al. 1994). Its scientific objective is to map out the sky in three narrow ({Delta}E/E {approx} 5%) bandpasses around 66, 71, and 93 eV. During each 50 second satellite rotation period the six telescopes, each with a 30{degrees} field, of:view and a spatial resolution of 0.25{degrees}, scan most of the antisolar hemisphere of the sky. The project is a collaborative effort between Los Alamos National Laboratory, Sandia National Laboratory, and the University of California-Berkeley Space Sciences Laboratory. It is controlled entirely from a small ground station located at Los Alamos. The mission was launched on a Pegasus Air Launched Vehicle on April 25, 1993. An incident at launch delayed our ability to properly analyze the data until November of 1994. In January of 1995, we brought on line automated software to routinely carry out the transient search. After the data is downlinked from the satellite, the software processes and transforms it into sky maps that are automatically searched for new sources. The software then sends the results of these searches by e-mail to the science team within two hours of the downlink. This system has successfully detected the Cataclysmic Variables VW Hyi, U Gem and AR UMa in outburst, and has detected at least two unidentified short duration EUV transients (Roussel-Dupre et al 1995, Roussel-Dupre 1995).

  6. Probabilistic approaches to fault detection in networked discrete event systems.

    PubMed

    Athanasopoulou, Eleftheria; Hadjicostis, Christoforos N

    2005-09-01

    In this paper, we consider distributed systems that can be modeled as finite state machines with known behavior under fault-free conditions, and we study the detection of a general class of faults that manifest themselves as permanent changes in the next-state transition functionality of the system. This scenario could arise in a variety of situations encountered in communication networks, including faults occurred due to design or implementation errors during the execution of communication protocols. In our approach, fault diagnosis is performed by an external observer/diagnoser that functions as a finite state machine and which has access to the input sequence applied to the system but has only limited access to the system state or output. In particular, we assume that the observer/diagnoser is only able to obtain partial information regarding the state of the given system at intermittent time intervals that are determined by certain synchronizing conditions between the system and the observer/diagnoser. By adopting a probabilistic framework, we analyze ways to optimally choose these synchronizing conditions and develop adaptive strategies that achieve a low probability of aliasing, i.e., a low probability that the external observer/diagnoser incorrectly declares the system as fault-free. An application of these ideas in the context of protocol testing/classification is provided as an example. PMID:16252815

  7. The waveform correlation event detection system project, Phase I: Issues in prototype development and testing

    SciTech Connect

    Young, C.; Harris, M.; Beiriger, J.; Moore, S.; Trujillo, J.; Withers, M.; Aster, R.

    1996-08-01

    A study using long-period seismic data showed that seismic events can be detected and located based on correlations of processed waveform profiles with the profile expected for an event. In this technique both time and space are discretized and events are found by forming profiles and calculating correlations for all time-distance points. events are declared at points with large correlations. In the first phase of the Waveform Correlation Event Detection System (WCEDS) Project at Sandia Labs we have developed a prototype automatic event detection system based on Shearer`s work which shows promise for treaty monitoring applications. Many modifications have been made to meet the requirements of the monitoring environment. A new full matrix multiplication has been developed which can reduce the number of computations needed for the data correlation by as much as two orders of magnitude for large grids. New methodology has also been developed to deal with the problems caused by false correlations (sidelobes) generated during the correlation process. When an event has been detected, masking matrices are set up which will mask all correlation sidelobes due to the event, allowing other events with intermingled phases to be found. This process is repeated until a detection threshold is reached. The system was tested on one hour of Incorporated Research Institutions for Seismology (IRIS) broadband data and built all 4 of the events listed in the National Earthquake Information Center (NEIC) Preliminary Determination of Epicenters (PDE) which were observable by the IRIS network. A continuous execution scheme has been developed for the system but has not yet been implemented. Improvements to the efficiency of the code are in various stages of development. Many refinements would have to be made to the system before it could be used as part of an actual monitoring system, but at this stage we know of no clear barriers which would prevent an eventual implementation of the system.

  8. Video-based real-time on-street parking occupancy detection system

    NASA Astrophysics Data System (ADS)

    Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

    2013-10-01

    Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

  9. Interviewing children about real and fictitious events: revisiting the narrative elaboration procedure.

    PubMed

    Camparo, L B; Wagner, J T; Saywitz, K J

    2001-02-01

    Elementary school children participated in a staged event. Two weeks later they were randomly assigned to three interview conditions: (a) a streamlined version of the Narrative Elaboration (NE) procedure involving training in the use of reminder cue cards, (b) exposure to reminder cue cards without training in their use (cue card control group), and (c) a standard interview including no NE training or exposure to reminder cue cards (standard-interview control group). Children in each interview condition were questioned about the staged event and a fictitious event to determine whether children trained in the streamlined NE procedure would provide more information about a staged event than would children in the two control groups and whether the NE interview would result in increased reporting of false information when questioned about a fictitious event. Results indicated that children questioned with the NE interview reported a greater amount of accurate, but not a greater amount of inaccurate, information during cue-card presentation for the staged event than did the cue-card control group. Analyses further indicated that the NE-interview group did not report significantly more false information about the fictitious event than did children in the two control groups. Large standard deviations for the NE-interview children's cue-card recall indicate that the streamlined NE procedure was useful for many children in reporting the staged event, but may have contributed to a small number of children providing false information for the fictitious event. Further research is being conducted to determine which children may be more likely to be helped and which children may be more likely to provide false information regarding a fictitious event. PMID:11276862

  10. The First Ground-Level Enhancement of Solar Cycle 24 on 17 May 2012 and Its Real-Time Detection

    NASA Astrophysics Data System (ADS)

    Papaioannou, A.; Souvatzoglou, G.; Paschalis, P.; Gerontidou, M.; Mavromichalaki, H.

    2014-01-01

    Ground-level enhancements (GLEs) are defined as sudden increases in the recorded intensity of cosmic-ray particles, usually by neutron monitors (NMs). In this work we present a time-shifting analysis (TSA) for the first arriving particles that were detected at Earth by NMs. We also present an automated real-time GLE alert that has been developed and is operating via the Neutron Monitor Database (NMDB), which successfully identified the 17 May 2012 event, designated as GLE71. We discuss the time evolution of the real-time GLE alert that was issued for GLE71 and present the event onset-time for NMs that contributed to this GLE alert based on their archived data. A comparison with their real-time time-stamp was made to illustrate the necessity for high-resolution data ( e.g. 1-min time resolution) made available at every minute. The first results on the propagation of relativistic protons that have been recorded by NMs, as inferred by the TSA, imply that they are most probably accelerated by the coronal-mass-ejection-driven shock. Furthermore, the successful usage of NM data and the corresponding achievement of issuing a timely GLE alert are discussed.

  11. Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

    NASA Astrophysics Data System (ADS)

    Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

    2011-02-01

    Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

  12. Real-Time Label-Free Embolus Detection Using In Vivo Photoacoustic Flow Cytometry

    PubMed Central

    Juratli, Mazen A.; Menyaev, Yulian A.; Sarimollaoglu, Mustafa; Siegel, Eric R.; Nedosekin, Dmitry A.; Suen, James Y.; Melerzanov, Alexander V.; Juratli, Tareq A.; Galanzha, Ekaterina I.; Zharov, Vladimir P.

    2016-01-01

    Thromboembolic events are one of the world’s leading causes of death among patients. Embolus or clot formations have several etiologies including paraneoplastic, post-surgery, cauterization, transplantation, or extracorporeal circuits. Despite its medical significance, little progress has been made in early embolus detection, screening and control. The aim of our study is to test the utility of the in vivo photoacoustic (PA) flow cytometry (PAFC) technique for non-invasive embolus detection in real-time. Using in vivo PAFC, emboli were non-invasively monitored in the bloodstream of two different mouse models. The tumor-free mouse model consisted of two groups, one in which the limbs were clamped to produce vessel stasis (7 procedures), and one where the mice underwent surgery (7 procedures). The melanoma-bearing mouse model also consisted of two groups, one in which the implanted tumor underwent compression (8 procedures), and one where a surgical excision of the implanted tumor was performed (8 procedures). We demonstrated that the PAFC can detect a single embolus, and has the ability to distinguish between erythrocyte–rich (red) and leukocyte/platelet-rich (white) emboli in small vessels. We show that, in tumor-bearing mice, the level of circulating emboli was increased compared to tumor-free mice (p = 0.0013). The number of circulating emboli temporarily increased in the tumor-free control mice during vessel stasis (p = 0.033) and after surgical excisions (signed-rank p = 0.031). Similar observations were noted during tumor compression (p = 0.013) and after tumor excisions (p = 0.012). For the first time, it was possible to detect unlabeled emboli in vivo non-invasively, and to confirm the presence of pigmented tumor cells within circulating emboli. The insight on embolus dynamics during cancer progression and medical procedures highlight the clinical potential of PAFC for early detection of cancer and surgery-induced emboli to prevent the fatal

  13. The real-time complex cruise scene motion detection system based on DSP

    NASA Astrophysics Data System (ADS)

    Wu, Zhi-guo; Wang, Ming-jia

    2014-11-01

    Dynamic target recognition is an important issue in the field of image processing research. It is widely used in photoelectric detection, target tracking, video surveillance areas. Complex cruise scene of target detection, compared to the static background, since the target and background objects together and both are in motion, greatly increases the complexity of moving target detection and recognition. Based on the practical engineering applications, combining an embedded systems and real-time image detection technology, this paper proposes a real-time movement detection method on an embedded system based on the FPGA + DSP system architecture on an embedded system. The DSP digital image processing system takes high speed digital signal processor DSP TMS320C6416T as the main computing components. And we take large capacity FPGA as coprocessor. It is designed and developed a high-performance image processing card. The FPGA is responsible for the data receiving and dispatching, DSP is responsible for data processing. The FPGA collects image data and controls SDRAM according to the digital image sequence. The SDRAM realizes multiport image buffer. DSP reads real-time image through SDRAM and performs scene motion detection algorithm. Then we implement the data reception and data processing parallelization. This system designs and realizes complex cruise scene motion detection for engineering application. The image edge information has the anti-light change and the strong anti-interference ability. First of all, the adjacent frame and current frame image are processed by convolution operation, extract the edge images. Then we compute correlation strength and the value of movement offset. We can complete scene motion parameters estimation by the result, in order to achieve real-time accurate motion detection. We use images in resolution of 768 * 576 and 25Hz frame rate to do the real-time cruise experiment. The results show that the proposed system achieves real

  14. Development of a real-time PCR assay for detection and quantification of Anaplasma ovis infection.

    PubMed

    Chi, Q; Liu, Z; Li, Y; Yang, J; Chen, Z; Yue, C; Luo, J; Yin, H

    2013-11-01

    Anaplasma ovis is a tick-borne intra-erythrocytic rickettsial pathogen of small ruminants. Real-time PCR possesses merits of rapidity, accuracy, reliability, automation and ease of standardization, but has not been used for detection of A. ovis, to the best of our knowledge. In this study, a real-time PCR assay was developed for detection and quantification of A. ovis. Species-specific primers and TaqMan probe were designed based on the gltA gene. No cross-reactions were observed with Anaplasma marginale, Anaplasma bovis, Anaplasma phagocytophilum, Borrelia burgdorferi s. l., Chlamydia psittaci, Mycoplasma mycoides, Theileria luwenshuni and Babesia sp. Xinjiang isolate. Analytic sensitivity results revealed that real-time PCR could detect as few as 10 copies of the gltA gene. The performance of real-time PCR was assessed by testing 254 blood samples from goats and comparing with the results from conventional PCR. This demonstrated that the real-time PCR assay was significantly more sensitive than conventional PCR. Our results indicated that real-time PCR is a useful approach for detecting A. ovis infections and has potential as an alternative tool for ecological and epidemiological surveillance of ovine anaplasmosis. PMID:24589111

  15. Real-time road detection in infrared imagery

    NASA Astrophysics Data System (ADS)

    Andre, Haritini E.; McCoy, Keith

    1990-09-01

    Automatic road detection is an important part in many scene recognition applications. The extraction of roads provides a means of navigation and position update for remotely piloted vehicles or autonomous vehicles. Roads supply strong contextual information which can be used to improve the performance of automatic target recognition (ATh) systems by directing the search for targets and adjusting target classification confidences. This paper will describe algorithmic techniques for labeling roads in high-resolution infrared imagery. In addition, realtime implementation of this structural approach using a processor array based on the Martin Marietta Geometric Arithmetic Parallel Processor (GAPPTh) chip will be addressed. The algorithm described is based on the hypothesis that a road consists of pairs of line segments separated by a distance "d" with opposite gradient directions (antiparallel). The general nature of the algorithm, in addition to its parallel implementation in a single instruction, multiple data (SIMD) machine, are improvements to existing work. The algorithm seeks to identify line segments meeting the road hypothesis in a manner that performs well, even when the side of the road is fragmented due to occlusion or intersections. The use of geometrical relationships between line segments is a powerful yet flexible method of road classification which is independent of orientation. In addition, this approach can be used to nominate other types of objects with minor parametric changes.

  16. Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes

    PubMed Central

    Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

    2016-01-01

    Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb2+, and connecting our platform with pipelines of tap water and wastewater for real-time online Pb2+ detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques. PMID:26858435

  17. Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes.

    PubMed

    Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

    2016-02-23

    Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb(2+), and connecting our platform with pipelines of tap water and wastewater for real-time online Pb(2+) detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques. PMID:26858435

  18. Detection of salmonella using a real-time PCR based on molecular beacons

    NASA Astrophysics Data System (ADS)

    Chen, Wilfred; Martinez, Grisselle; Mulchandani, Ashok

    2000-03-01

    Molecular beacons are oligonucleotide probes that become fluorescent upon hybridization. We developed a new approach to detect the presence of Salmonella species using these fluorogenic reporter molecules and demonstrated their ability to discriminate between similar E. coli species in real-time PCR assays. A detection limit of 1 CFU per PCR reaction was obtained. The assays were carried out entirely in sealed PCR tubes, enabling fast and direct detection in a semiautomated format.

  19. Improving linear accelerator service response with a real- time electronic event reporting system.

    PubMed

    Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

    2014-01-01

    To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations. PMID

  20. Investigation of EMIC Waves During Balloon Detected Relativistic Electron Precipitation Events

    NASA Astrophysics Data System (ADS)

    Woodger, L. A.; Millan, R. M.

    2009-12-01

    Multiple relativistic electron precipitation (REP) events were detected by balloon-borne instrumentation during the MAXIS 2000 and MINIS 2005 campaigns. It has been suggested that resonance with EMIC waves caused these precipitation events (Lorentzen et al, 2000 and Millan et al, 2002) due to their location in the dusk sector. We present observations of dusk-side relativistic electron precipitation events, and use supporting satellite and theoretical data to investigate the relationship between EMIC waves and the detected REP. Satellite data can provide direct measurements of not only the waves themselves but also important resonance condition parameters. The data will be presented collectively with each event to showcase similarities and differences between events and the challenges that arise in trying to understand the relationship between dusk-side relativistic electron precipitation and EMIC waves.

  1. Event specific qualitative and quantitative polymerase chain reaction detection of genetically modified MON863 maize based on the 5'-transgene integration sequence.

    PubMed

    Yang, Litao; Xu, Songci; Pan, Aihu; Yin, Changsong; Zhang, Kewei; Wang, Zhenying; Zhou, Zhigang; Zhang, Dabing

    2005-11-30

    Because of the genetically modified organisms (GMOs) labeling policies issued in many countries and areas, polymerase chain reaction (PCR) methods were developed for the execution of GMO labeling policies, such as screening, gene specific, construct specific, and event specific PCR detection methods, which have become a mainstay of GMOs detection. The event specific PCR detection method is the primary trend in GMOs detection because of its high specificity based on the flanking sequence of the exogenous integrant. This genetically modified maize, MON863, contains a Cry3Bb1 coding sequence that produces a protein with enhanced insecticidal activity against the coleopteran pest, corn rootworm. In this study, the 5'-integration junction sequence between the host plant DNA and the integrated gene construct of the genetically modified maize MON863 was revealed by means of thermal asymmetric interlaced-PCR, and the specific PCR primers and TaqMan probe were designed based upon the revealed 5'-integration junction sequence; the conventional qualitative PCR and quantitative TaqMan real-time PCR detection methods employing these primers and probes were successfully developed. In conventional qualitative PCR assay, the limit of detection (LOD) was 0.1% for MON863 in 100 ng of maize genomic DNA for one reaction. In the quantitative TaqMan real-time PCR assay, the LOD and the limit of quantification were eight and 80 haploid genome copies, respectively. In addition, three mixed maize samples with known MON863 contents were detected using the established real-time PCR systems, and the ideal results indicated that the established event specific real-time PCR detection systems were reliable, sensitive, and accurate. PMID:16302741

  2. Real-time remote detection and measurement for airborne imaging spectroscopy: a case study with methane

    NASA Astrophysics Data System (ADS)

    Thompson, D. R.; Leifer, I.; Bovensmann, H.; Eastwood, M.; Fladeland, M.; Frankenberg, C.; Gerilowski, K.; Green, R. O.; Kratwurst, S.; Krings, T.; Luna, B.; Thorpe, A. K.

    2015-06-01

    Localized anthropogenic sources of atmospheric CH4 are highly uncertain and temporally variable. Airborne remote measurement is an effective method to detect and quantify these emissions. In a campaign context, the science yield can be dramatically increased by real-time retrievals that allow operators to coordinate multiple measurements of the most active areas. This can improve science outcomes for both single- and multiple-platform missions. We describe a case study of the NASA/ESA CO2 and Methane Experiment (COMEX) campaign in California during June and August/September 2014. COMEX was a multi-platform campaign to measure CH4 plumes released from anthropogenic sources including oil and gas infrastructure. We discuss principles for real-time spectral signature detection and measurement, and report performance on the NASA Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG). AVIRIS-NG successfully detected CH4 plumes in real-time at Gb s-1 data rates, characterizing fugitive releases in concert with other in situ and remote instruments. The teams used these real-time CH4 detections to coordinate measurements across multiple platforms, including airborne in situ, airborne non-imaging remote sensing, and ground-based in situ instruments. To our knowledge this is the first reported use of real-time trace gas signature detection in an airborne science campaign, and presages many future applications.

  3. Detection of infectious laryngotracheitis virus by real-time PCR in naturally and experimentally infected chickens.

    PubMed

    Zhao, Yan; Kong, Congcong; Cui, Xianlan; Cui, Hongyu; Shi, Xingming; Zhang, Xiaomin; Hu, Shunlei; Hao, Lianwei; Wang, Yunfeng

    2013-01-01

    Infectious laryngotracheitis (ILT) is an acute, highly contagious upper-respiratory infectious disease of chickens. In this study, a real-time PCR method was developed for fast and accurate detection and quantitation of ILTV DNA of chickens experimentally infected with ILTV strain LJS09 and naturally infected chickens. The detection lower limit of the assay was 10 copies of DNA. There were no cross reactions with the DNA and RNA of infectious bursal disease virus, chicken anemia virus, reticuloendotheliosis virus, avian reovirus, Newcastle disease virus, and Marek's disease virus. The real-time PCR was reproducible as the coefficients of variation of reproducibility of the intra-assay and the inter-assay were less than 2%. The real-time PCR was used to detect the levels of the ILTV DNA in the tissues of specific pathogen free (SPF) chickens infected with ILTV at different times post infection. ILTV DNA was detected by real-time PCR in the heart, liver, spleen, lung, kidney, larynx, tongue, thymus, glandular stomach, duodenum, pancreatic gland, small intestine, large intestine, cecum, cecal tonsil, bursa of Fabricius, and brain of chickens in the infection group and the contact-exposure group. The sensitivity, specificity, and reproducibility of the ILTV real-time PCR assay revealed its suitability for detection and quantitation of ILTV in the samples from clinically and experimentally ILTV infected chickens. PMID:23840745

  4. Detection of Infectious Laryngotracheitis Virus by Real-Time PCR in Naturally and Experimentally Infected Chickens

    PubMed Central

    Zhao, Yan; Kong, Congcong; Cui, Xianlan; Cui, Hongyu; Shi, Xingming; Zhang, Xiaomin; Hu, Shunlei; Hao, Lianwei; Wang, Yunfeng

    2013-01-01

    Infectious laryngotracheitis (ILT) is an acute, highly contagious upper-respiratory infectious disease of chickens. In this study, a real-time PCR method was developed for fast and accurate detection and quantitation of ILTV DNA of chickens experimentally infected with ILTV strain LJS09 and naturally infected chickens. The detection lower limit of the assay was 10 copies of DNA. There were no cross reactions with the DNA and RNA of infectious bursal disease virus, chicken anemia virus, reticuloendotheliosis virus, avian reovirus, Newcastle disease virus, and Marek's disease virus. The real-time PCR was reproducible as the coefficients of variation of reproducibility of the intra-assay and the inter-assay were less than 2%. The real-time PCR was used to detect the levels of the ILTV DNA in the tissues of specific pathogen free (SPF) chickens infected with ILTV at different times post infection. ILTV DNA was detected by real-time PCR in the heart, liver, spleen, lung, kidney, larynx, tongue, thymus, glandular stomach, duodenum, pancreatic gland, small intestine, large intestine, cecum, cecal tonsil, bursa of Fabricius, and brain of chickens in the infection group and the contact-exposure group. The sensitivity, specificity, and reproducibility of the ILTV real-time PCR assay revealed its suitability for detection and quantitation of ILTV in the samples from clinically and experimentally ILTV infected chickens. PMID:23840745

  5. Energy efficient data representation and aggregation with event region detection in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Banerjee, Torsha

    Unlike conventional networks, wireless sensor networks (WSNs) are limited in power, have much smaller memory buffers, and possess relatively slower processing speeds. These characteristics necessitate minimum transfer and storage of information in order to prolong the network lifetime. In this dissertation, we exploit the spatio-temporal nature of sensor data to approximate the current values of the sensors based on readings obtained from neighboring sensors and itself. We propose a Tree based polynomial REGression algorithm, (TREG) that addresses the problem of data compression in wireless sensor networks. Instead of aggregated data, a polynomial function (P) is computed by the regression function, TREG. The coefficients of P are then passed to achieve the following goals: (i) The sink can get attribute values in the regions devoid of sensor nodes, and (ii) Readings over any portion of the region can be obtained at one time by querying the root of the tree. As the size of the data packet from each tree node to its parent remains constant, the proposed scheme scales very well with growing network density or increased coverage area. Since physical attributes exhibit a gradual change over time, we propose an iterative scheme, UPDATE_COEFF, which obviates the need to perform the regression function repeatedly and uses approximations based on previous readings. Extensive simulations are performed on real world data to demonstrate the effectiveness of our proposed aggregation algorithm, TREG. Results reveal that for a network density of 0.0025 nodes/m2, a complete binary tree of depth 4 could provide the absolute error to be less than 6%. A data compression ratio of about 0.02 is achieved using our proposed algorithm, which is almost independent of the tree depth. In addition, our proposed updating scheme makes the aggregation process faster while maintaining the desired error bounds. We also propose a Polynomial-based scheme that addresses the problem of Event Region

  6. Detection of stick-slip events within the Whillans Ice Stream using an artificial neural network

    NASA Astrophysics Data System (ADS)

    Bernsen, S. P.

    2014-12-01

    Temporal changes in the periodic stick-slip events on the Whillans Ice Stream (WIS) help to understand the hydrosphere-cryosphere coupling in West Antarctica. Previous studies have shown that the periodic behavior has been ongoing for a number of years but the record of slip events is incomplete. Rayleigh waves from WIS grounding line events exhibit different patterns than events from the interior of the glacier. An algorithm using a backpropagation neural network is proposed to efficiently extract surface waves that are a result of stick slip events. A neural network approach has its advantages of machine learning, simplified mathematics, and eliminates the need for an analyst to correctly pick first arrivals. Training data has been assembled using 107 events occuring during the 2010 austral summer that were previously identified to correspond to stick slip events at the grounding line as well as the interior of the WIS. A 0.1 s moving window of 3 s of each of the preprocessed attributes is input into the neural network for automated surface wave detection. Following surface wave detection a much longer 30 minute sliding window is used to classify surface wave detections as grounding line, interior, or non-stick slip events. Similar to the automatic detection algorithms for body waves, preprocessing using STA/LTA ratio, degree of polarization, variance, and skewness exhibit obvious patterns during the onset of surface waves. The The automated event detection could lead to more cost effective means of data collection in future seismic experiments especially with an increase in array density in cold weather regions.

  7. Early snowmelt events: detection, distribution, and significance in a major sub-arctic watershed

    NASA Astrophysics Data System (ADS)

    Alese Semmens, Kathryn; Ramage, Joan; Bartsch, Annett; Liston, Glen E.

    2013-03-01

    High latitude drainage basins are experiencing higher average temperatures, earlier snowmelt onset in spring, and an increase in rain on snow (ROS) events in winter, trends that climate models project into the future. Snowmelt-dominated basins are most sensitive to winter temperature increases that influence the frequency of ROS events and the timing and duration of snowmelt, resulting in changes to spring runoff. Of specific interest in this study are early melt events that occur in late winter preceding melt onset in the spring. The study focuses on satellite determination and characterization of these early melt events using the Yukon River Basin (Canada/USA) as a test domain. The timing of these events was estimated using data from passive (Advanced Microwave Scanning Radiometer—EOS (AMSR-E)) and active (SeaWinds on Quick Scatterometer (QuikSCAT)) microwave remote sensors, employing detection algorithms for brightness temperature (AMSR-E) and radar backscatter (QuikSCAT). The satellite detected events were validated with ground station meteorological and hydrological data, and the spatial and temporal variability of the events across the entire river basin was characterized. Possible causative factors for the detected events, including ROS, fog, and positive air temperatures, were determined by comparing the timing of the events to parameters from SnowModel and National Centers for Environmental Prediction North American Regional Reanalysis (NARR) outputs, and weather station data. All melt events coincided with above freezing temperatures, while a limited number corresponded to ROS (determined from SnowModel and ground data) and a majority to fog occurrence (determined from NARR). The results underscore the significant influence that warm air intrusions have on melt in some areas and demonstrate the large temporal and spatial variability over years and regions. The study provides a method for melt detection and a baseline from which to assess future change.

  8. Event Detection and Visualization of Ocean Eddies based on SSH and Velocity Field

    NASA Astrophysics Data System (ADS)

    Matsuoka, Daisuke; Araki, Fumiaki; Inoue, Yumi; Sasaki, Hideharu

    2016-04-01

    Numerical studies of ocean eddies have been progressed using high-resolution ocean general circulation models. In order to understand ocean eddies from simulation results with large amount of information volume, it is necessary to visualize not only distribution of eddies of each time step, but also events or phenomena of eddies. However, previous methods cannot precisely detect eddies, especially, during the events such as eddies' amalgamation, bifurcation. In the present study, we propose a new approach of eddy's detection, tracking and event visualization based on sea surface height (SSH) and velocity field. The proposed method detects eddies region as well as streams and currents region, and classifies detected eddies into several types. By tracking the time-varying change of classified eddies, it is possible to detect not only eddies event such as amalgamation and bifurcation but also the interaction between eddy and ocean current. As a result of visualizing detected eddies and events, we succeeded in creating the movie which enables us to intuitively understand the region of interest.

  9. Wavelet based automated postural event detection and activity classification with single imu - biomed 2013.

    PubMed

    Lockhart, Thurmon E; Soangra, Rahul; Zhang, Jian; Wu, Xuefan

    2013-01-01

    Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person’s activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient’s home. In order to provide a low-cost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment – TEMPO (Technology Enabled Medical Precision Observation). Using this IMU system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection

  10. 3D-nanostructured Au electrodes for the event-specific detection of MON810 transgenic maize.

    PubMed

    Barroso, M Fátima; Freitas, Maria; Oliveira, M Beatriz P P; de-los-Santos-Álvarez, Noemí; Lobo-Castañón, María Jesús; Delerue-Matos, Cristina

    2015-03-01

    In the present work, the development of a genosensor for the event-specific detection of MON810 transgenic maize is proposed. Taking advantage of nanostructuration, a cost-effective three dimensional electrode was fabricated and a ternary monolayer containing a dithiol, a monothiol and the thiolated capture probe was optimized to minimize the unspecific signals. A sandwich format assay was selected as a way of precluding inefficient hybridization associated with stable secondary target structures. A comparison between the analytical performance of the Au nanostructured electrodes and commercially available screen-printed electrodes highlighted the superior performance of the nanostructured ones. Finally, the genosensor was effectively applied to detect the transgenic sequence in real samples, showing its potential for future quantitative analysis. PMID:25618653

  11. Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

    NASA Technical Reports Server (NTRS)

    Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.

    2006-01-01

    Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

  12. Thresholding for biological material detection in real-time multispectral imaging

    NASA Astrophysics Data System (ADS)

    Yoon, Seung Chul; Park, Bosoon; Lawrence, Kurt C.; Windham, William R.

    2005-09-01

    Recently, hyperspectral image analysis has proved successful for a target detection problem encountered in remote sensing as well as near sensing utilizing in situ instrumentation. The conventional global bi-level thresholding for target detection, such as the clustering-based Otsu's method, has been inadequate for the detection of biologically harmful material on foods that has a large degree of variability in size, location, color, shape, texture, and occurrence time. This paper presents multistep-like thresholding based on kernel density estimation for the real-time detection of harmful contaminants on a food product presented in multispectral images. We are particularly concerned with the detection of fecal contaminants on poultry carcasses in real-time. In the past, we identified 2 optimal wavelength bands and developed a real-time multispectral imaging system using a common aperture camera and a globally optimized thresholding method from a ratio of the optimal bands. This work extends our previous study by introducing a new decision rule to detect fecal contaminants on a single bird level. The underlying idea is to search for statistical separability along the two directions defined by the global optimal threshold vector and its orthogonal vector. Experimental results with real birds and fecal samples in different amounts are provided.

  13. An accurate assay for HCV based on real-time fluorescence detection of isothermal RNA amplification.

    PubMed

    Wu, Xuping; Wang, Jianfang; Song, Jinyun; Li, Jiayan; Yang, Yongfeng

    2016-09-01

    Hepatitis C virus (HCV) is one of the common reasons of liver fibrosis and hepatocellular carcinoma (HCC). Early, rapid and accurate HCV RNA detection is important to prevent and control liver disease. A simultaneous amplification and testing (SAT) assay, which is based on isothermal amplification of RNA and real-time fluorescence detection, was designed to optimize routine HCV RNA detection. In this study, HCV RNA and an internal control (IC) were amplified and analyzed simultaneously by SAT assay and detection of fluorescence using routine real-time PCR equipment. The assay detected as few as 10 copies of HCV RNA transcripts. We tested 705 serum samples with SAT, among which 96.4% (680/705) showed consistent results compared with routine real-time PCR. About 92% (23/25) discordant samples were confirmed to be same results as SAT-HCV by using a second real-time PCR. The sensitivity and specificity of SAT-HCV assay were 99.6% (461/463) and 100% (242/242), respectively. In conclusion, the SAT assay is an accurate test with a high specificity and sensitivity which may increase the detection rate of HCV. It is therefore a promising tool to diagnose HCV infection. PMID:27283884

  14. Early apoptosis real-time detection by label-free SERS based on externalized phosphatidylserine.

    PubMed

    Zhou, Haibo; Wang, Qiqin; Yuan, Detian; Wang, Jinyong; Huang, Yang; Wu, Huihui; Jian, Jingyi; Yang, Danting; Huang, Ning; Haisch, Christoph; Jiang, Zhengjin; Chen, Shanze

    2016-07-21

    Apoptosis is a tightly regulated cellular process that plays an essential role in the development, aging, cancer biology, immune response, and pathogenesis of various diseases. Herein, we report a new SERS sensing strategy for in vitro sensitive detection of early apoptotic cells. The principle of this method is to in situ synthesize silver nanoparticles (AgNPs) on the phosphatidylserine (PS) of the apoptotic cell membrane during the early apoptosis, which enables distinguishing normal and apoptotic cells. The total assay time of the presented method is only 10 min, thus being faster, cheaper and simpler than current techniques for the detection of apoptosis. The intrinsic mechanism was verified by different approaches based on externalized phosphatidylserine. In addition, the detection process is real-time and label-free; i.e., the intrinsic SERS spectra from the cellular membrane are directly employed for apoptosis real-time detection, which avoids using additional chemical or biological reagents as external signal indicators. Therefore, our SERS approach may serve as a potentially practical tool for sensitive and real-time detection of early cell apoptosis, complementing the state-of-the-art strategies, e.g. flow cytometry. While further investigation is required to better understand the intrinsic mechanism of the in situ coating method, the current results may provide another choice for real-time detection of early apoptosis. PMID:27181439

  15. Visual real-time detection, recognition and tracking of ground and airborne targets

    NASA Astrophysics Data System (ADS)

    Kovács, Levente; Benedek, Csaba

    2011-03-01

    This paper presents methods and algorithms for real-time visual target detection, recognition and tracking, both in the case of ground-based objects (surveyed from a moving airborne imaging sensor) and flying targets (observed from a ground-based or vehicle mounted sensor). The methods are highly parallelized and partially implemented on GPU, with the goal of real-time speeds even in the case of multiple target observations. Real-time applicability is in focus. The methods use single camera observations, providing a passive and expendable alternative for expensive and/or active sensors. Use cases involve perimeter defense and surveillance situations, where passive detection and observation is a priority (e.g. aerial surveillance of a compound, detection of reconnaissance drones, etc.).

  16. Isothermal target and probe amplification assay for the real-time rapid detection of Staphylococcus aureus.

    PubMed

    Shin, Hyewon; Kim, Minhwan; Yoon, Eunju; Kang, Gyoungwon; Kim, Seungyu; Song, Aelee; Kim, Jeongsoon

    2015-04-01

    Staphylococcus aureus, the species most commonly associated with staphylococcal food poisoning, is one of the most prevalent causes of foodborne disease in Korea and other parts of the world, with much damage inflicted to the health of individuals and economic losses estimated at $120 million. To reduce food poisoning outbreaks by implementing prevention methods, rapid detection of S. aureus in foods is essential. Various types of detection methods for S. aureus are available. Although each method has advantages and disadvantages, high levels of sensitivity and specificity are key aspects of a robust detection method. Here, we describe a novel real-time isothermal target and probe amplification (iTPA) method that allows the rapid and simultaneous amplification of target DNA (the S. aureus nuc gene) and a fluorescence resonance energy transfer-based signal probe under isothermal conditions at 61 °C or detection of S. aureus in real time. The assay was able to specifically detect all 91 S. aureus strains tested without nonspecific detection of 51 non-S. aureus strains. The real-time iTPA assay detected S. aureus at an initial level of 10(1) CFU in overnight cultures of preenriched food samples (kiwi dressing, soybean milk, and custard cream). The advantage of this detection system is that it does not require a thermal cycler, reducing the cost of the real-time PCR and its footprint. Combined with a miniaturized fluorescence detector, this system can be developed into a simplified quantitative hand-held real-time device, which is often required. The iTPA assay was highly reliable and therefore may be used as a rapid and sensitive means of identifying S. aureus in foods. PMID:25836397

  17. Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation.

    PubMed

    Hudson, Anna L; Navarro-Sune, Xavier; Martinerie, Jacques; Pouget, Pierre; Raux, Mathieu; Chavez, Mario; Similowski, Thomas

    2016-04-01

    The presence of a respiratory-related cortical activity during tidal breathing is abnormal and a hallmark of respiratory difficulties, but its detection requires superior discrimination and temporal resolution. The aim of this study was to validate a computational method using EEG covariance (or connectivity) matrices to detect a change in brain activity related to breathing. In 17 healthy subjects, EEG was recorded during resting unloaded breathing (RB), voluntary sniffs, and breathing against an inspiratory threshold load (ITL). EEG were analyzed by the specially developed covariance-based classifier, event-related potentials, and time-frequency (T-F) distributions. Nine subjects repeated the protocol. The classifier could accurately detect ITL and sniffs compared with the reference period of RB. For ITL, EEG-based detection was superior to airflow-based detection (P < 0.05). A coincident improvement in EEG-airflow correlation in ITL compared with RB (P < 0.05) confirmed that EEG detection relates to breathing. Premotor potential incidence was significantly higher before inspiration in sniffs and ITL compared with RB (P < 0.05), but T-F distributions revealed a significant difference between sniffs and RB only (P < 0.05). Intraclass correlation values ranged from poor (-0.2) to excellent (1.0). Thus, as for conventional event-related potential analysis, the covariance-based classifier can accurately predict a change in brain state related to a change in respiratory state, and given its capacity for near "real-time" detection, it is suitable to monitor the respiratory state in respiratory and critically ill patients in the development of a brain-ventilator interface. PMID:26864771

  18. Qualitative Characteristics of Memories for Real, Imagined, and Media-Based Events

    ERIC Educational Resources Information Center

    Gordon, Ruthanna; Gerrig, Richard J.; Franklin, Nancy

    2009-01-01

    People's memories must be able to represent experiences with multiple types of origins--including the real world and our own imaginations, but also printed texts (prose-based media), movies, and television (screen-based media). This study was intended to identify cues that distinguish prose- and screen-based media memories from each other, as well…

  19. Detection of gait events using an F-Scan in-shoe pressure measurement system.

    PubMed

    Catalfamo, Paola; Moser, David; Ghoussayni, Salim; Ewins, David

    2008-10-01

    A portable system capable of accurate detection of initial contact (IC) and foot off (FO) without adding encumbrance to the subject would be extremely useful in many gait analysis applications. Force platforms represent the gold standard method for determining these events and other methods including foot switches and kinematic data have also been proposed. These approaches, however, present limitations in terms of the number of steps that can be analysed per trial, the portability for outdoor measurements or the information needed beforehand. The purpose of this study was to evaluate the F-Scan((R)) Mobile pressure measurement system when detecting IC and FO. Two methods were used, one was the force detection (FD) in-built algorithm used by F-Scan software and a new area detection (AD) method using the loaded area during the gait cycle. Both methods were tested in ten healthy adults and compared with the detection provided by a kinetic detection (KT) algorithm. The absolute mean differences between KT and FD were (mean+/-standard deviation) 42+/-11 ms for IC and 37+/-11 ms for FO. The absolute mean differences between KT and AD were 22+/-9 ms for IC and 10+/-4 ms for FO. The AD method remained closer to KT detection for all subjects providing sufficiently accurate detection of both events and presenting advantages in terms of portability, number of steps analysed per trial and practicality as to make it a system of choice for gait event detection. PMID:18468441

  20. Network Event Recording Device: An automated system for Network anomaly detection, and notification. Draft

    SciTech Connect

    Simmons, D.G.; Wilkins, R.

    1994-09-01

    The goal of the Network Event Recording Device (NERD) is to provide a flexible autonomous system for network logging and notification when significant network anomalies occur. The NERD is also charged with increasing the efficiency and effectiveness of currently implemented network security procedures. While it has always been possible for network and security managers to review log files for evidence of network irregularities, the NERD provides real-time display of network activity, as well as constant monitoring and notification services for managers. Similarly, real-time display and notification of possible security breaches will provide improved effectiveness in combating resource infiltration from both inside and outside the immediate network environment.

  1. Study on APD real time compensation methods of laser Detection system

    NASA Astrophysics Data System (ADS)

    Ying, Feng; He, Zhang; Xiangjin, Zhang; Kun, Liu

    2011-02-01

    their operating principles. The constant false alarm rate compensation can't detect the pulse signal which comes randomly. Therefore real-time performance can't be realized. The noise compensation can meet the request of real-time performance. If it is used in the environment where background light is intense or changes acutely, there is a better effect. The temperature compensation can also achieve the real-time performance request. If it is used in the environment where temperature changes acutely, there is also a better effect. Aim at such problems, this paper presents that different APD real-time compensations should be adopt to adapt to different environments. The exiting temperature compensation adjusts output voltage by using variable resistance to regulate input voltage. Its structure is complex; the real-time performance is worse. In order to remedy these defects, a real-time temperature compensation which is based on switch on-off time of switching power supply is designed. Its feasibility and operating stability are confirmed by plate making and experiment. At last, the comparison experiments between the real-time noise compensation and the real-time temperature compensation is carried out in the environments where temperature is almost invariant and background light acutely changes from5lux to150lux . The result shows that the operating effect of the real-time noise compensation is better here, the noise minifies to a sixth of original noise. The comparison experiments between the real-time noise compensation and the real-time temperature compensation is carried out in darkroom where background light is 5lux and temperature almost rapidly changes from -20°C to 80°C. The result shows that the operating effect of the real-time temperature compensation is better here, the noise minifies to a seventh of original noise. Moreover, these methods can be applied to other type detection systems of weak photoelectric signal; they have high actual application value.

  2. Advanced detection, isolation, and accommodation of sensor failures in turbofan engines: Real-time microcomputer implementation

    NASA Technical Reports Server (NTRS)

    Delaat, John C.; Merrill, Walter C.

    1990-01-01

    The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming.

  3. Real-time, time-frequency mapping of event-related cortical activation

    NASA Astrophysics Data System (ADS)

    Cheung, Connie; Chang, Edward F.

    2012-08-01

    Functional mapping of eloquent cortex is a common and necessary component of neurosurgical operative planning. Current electrical stimulation-based techniques are inefficient, can evoke seizures and are prone to false-negative results. Here, we present a novel cortical mapping system that extracts event-related neural activity from passive electrocorticographic recordings to quickly and accurately localize sensory and motor cortices using the precise temporal properties of spectral alteration. This procedure generates a robust functional motor and sensory cortical map in seconds, and usually with less than five to ten trial events. Our algorithm demonstrates high concordance with results derived using independent electrical cortical stimulation mapping.

  4. Design and implementation of Cell-PREVEN: a real-time surveillance system for adverse events using cell phones in Peru.

    PubMed

    Curioso, Walter H; Karras, Bryant T; Campos, Pablo E; Buendia, Clara; Holmes, King K; Kimball, Ann Marie

    2005-01-01

    With more clinical trials involving evaluations of new drugs or vaccines, monitoring for early detection of adverse events is essential. The overall goal of this study was to develop an interactive-computer system using cell phones for real-time collection and transmission of adverse events related to metronidazole administration among female sex workers (FSW) in Peru. We developed an application for cell phones in Spanish, called Cell-PREVEN, based on a system from Voxiva Inc. We used cell phones to enter data collected by interviewers from FSW in three communities. Information was stored in an online database, where it could be immediately accessed worldwide and exported over a secure Internet connection. E-mail and text messages sent to mobile devices alerted key personnel to selected symptoms. This pilot project has demonstrated that it is feasible to develop a public-health-surveillance system based on cell phones to collect data in real-time in Peru (http://www.prevenperu.org). PMID:16779025

  5. A new PCR-CGE (size and color) method for simultaneous detection of genetically modified maize events.

    PubMed

    Nadal, Anna; Coll, Anna; La Paz, Jose-Luis; Esteve, Teresa; Pla, Maria

    2006-10-01

    We present a novel multiplex PCR assay for simultaneous detection of multiple transgenic events in maize. Initially, five PCR primers pairs specific to events Bt11, GA21, MON810, and NK603, and Zea mays L. (alcohol dehydrogenase) were included. The event specificity was based on amplification of transgene/plant genome flanking regions, i.e., the same targets as for validated real-time PCR assays. These short and similarly sized amplicons were selected to achieve high and similar amplification efficiency for all targets; however, its unambiguous identification was a technical challenge. We achieved a clear distinction by a novel CGE approach that combined the identification by size and color (CGE-SC). In one single step, all five targets were amplified and specifically labeled with three different fluorescent dyes. The assay was specific and displayed an LOD of 0.1% of each genetically modified organism (GMO). Therefore, it was adequate to fulfill legal thresholds established, e.g., in the European Union. Our CGE-SC based strategy in combination with an adequate labeling design has the potential to simultaneously detect higher numbers of targets. As an example, we present the detection of up to eight targets in a single run. Multiplex PCR-CGE-SC only requires a conventional sequencer device and enables automation and high throughput. In addition, it proved to be transferable to a different laboratory. The number of authorized GMO events is rapidly growing; and the acreage of genetically modified (GM) varieties cultivated and commercialized worldwide is rapidly increasing. In this context, our multiplex PCR-CGE-SC can be suitable for screening GM contents in food. PMID:16972302

  6. Combination of High Rate, Real-time GNSS and Accelerometer Observations - Preliminary Results Using a Shake Table and Historic Earthquake Events.

    NASA Astrophysics Data System (ADS)

    Jackson, Michael; Passmore, Paul; Zimakov, Leonid; Raczka, Jared

    2014-05-01

    One of the fundamental requirements of an Earthquake Early Warning (EEW) system (and other mission critical applications) is to quickly detect and process the information from the strong motion event, i.e. event detection and location, magnitude estimation, and the peak ground motion estimation at the defined targeted site, thus allowing the civil protection authorities to provide pre-programmed emergency response actions: Slow down or stop rapid transit trains and high-speed trains; shutoff of gas pipelines and chemical facilities; stop elevators at the nearest floor; send alarms to hospitals, schools and other civil institutions. An important question associated with the EEW system is: can we measure displacements in real time with sufficient accuracy? Scientific GNSS networks are moving towards a model of real-time data acquisition, storage integrity, and real-time position and displacement calculations. This new paradigm allows the integration of real-time, high-rate GNSS displacement information with acceleration and velocity data to create very high-rate displacement records. The mating of these two instruments allows the creation of a new, very high-rate (200 Hz) displacement observable that has the full-scale displacement characteristics of GNSS and high-precision dynamic motions of seismic technologies. It is envisioned that these new observables can be used for earthquake early warning studies and other mission critical applications, such as volcano monitoring, building, bridge and dam monitoring systems. REF TEK a Division of Trimble has developed the integrated GNSS/Accelerograph system, model 160-09SG, which consists of REF TEK's fourth generation electronics, a 147-01 high-resolution ANSS Class A accelerometer, and Trimble GNSS receiver and antenna capable of real time, on board Precise Point Positioning (PPP) techniques with satellite clock and orbit corrections delivered to the receiver directly via L-band satellite communications. The test we

  7. Real-time iris detection on faces with coronal and transversal axis rotation

    NASA Astrophysics Data System (ADS)

    Perez, Claudio A.; Lazcano, Vanel A.

    2005-12-01

    Real-time face and iris detection on video sequences is important in diverse applications such as, study of the eye function, drowsiness detection, man-machine interfaces, face recognition, security and multimedia retrieval. In this work we present and extension to our previous method to incorporate face and iris detection in faces with coronal and transversal axis rotations in real time. The method is based on anthropometric templates and consists of three stages: coarse face detection, fine face detection and iris detection. In the coarse face detection, a directional image is computed and the contribution of each directional vector is weighted into an accumulator. The highest score in the accumulator is taken as the coarse face position. Then, a high-resolution directional image is computed. Face templates were constructed off-line for face coronal and transversal rotation, using face features such as elliptical shape, location of the eyebrows, nose and lips. A line integral is computed using these templates over the fine directional image to find the actual face location, size and rotation angle. This information provides a region to search for the eyes and the iris boundary is detected within this region by a ratio among to line integrals using a semicircular template. Results computed on five video sequences which include coronal and transversal rotations with over 1900 frames show correct face detection rate above 92% and iris detection rate above 86%.

  8. Real-Time Fluorescence Loop Mediated Isothermal Amplification for the Detection of Acinetobacter baumannii

    PubMed Central

    Wang, Qinqin; Zhou, Yanbin; Li, Shaoli; Zhuo, Chao; Xu, Siqi; Huang, Lixia; Yang, Ling; Liao, Kang

    2013-01-01

    Background Detection of Acinetobacter baumannii has been relying primarily on bacterial culture that often fails to return useful results in time. Although DNA-based assays are more sensitive than bacterial culture in detecting the pathogen, the molecular results are often inconsistent and challenged by doubts on false positives, such as those due to system- and environment-derived contaminations. In addition, these molecular tools require expensive laboratory instruments. Therefore, establishing molecular tools for field use require simpler molecular platforms. The loop-mediated isothermal amplification method is relatively simple and can be improved for better use in a routine clinical bacteriology laboratory. A simple and portable device capable of performing both the amplification and detection (by fluorescence) of LAMP in the same platform has been developed in recent years. This method is referred to as real-time loop-mediated isothermal amplification. In this study, we attempted to utilize this method for rapid detection of A. baumannii. Methodology and Significant Findings Species-specific primers were designed to test the utility of this method. Clinical samples of A. baumannii were used to determine the sensitivity and specificity of this system compared to bacterial culture and a polymerase chain reaction method. All positive samples isolated from sputum were confirmed to be the species of Acinetobacter by 16S rRNA gene sequencing. The RealAmp method was found to be simpler and allowed real-time detection of DNA amplification, and could distinguish A. baumannii from Acinetobacter calcoaceticus and Acinetobacter genomic species 3. DNA was extracted by simple boiling method. Compared to bacterial culture, the sensitivity and specificity of RealAmp in detecting A. baumannii was 98.9% and 75.0%, respectively. Conclusion The RealAmp assay only requires a single unit, and the assay positivity can be verified by visual inspection. Therefore, this assay has

  9. DSP design for real-time hyperspectral target detection based on spatial-spectral information extraction

    NASA Astrophysics Data System (ADS)

    Yang, Wei; Zhang, Bing; Gao, Lianru; Wu, Yuanfeng

    2012-06-01

    Military target detection is an important application of hyperspectral remote sensing. It highly demands real-time or near real-time processing. However, the massive amount of hyperspectral image data seriously limits the processing speed. Real-time image processing based on hardware platform, such as digital signal processor (DSP), is one of recent developments in hyperspectral target detection. In hyperspectral target detection algorithms, correlation matrix or covariance matrix calculation is always used to whiten data, which is a very time-consuming process. In this paper, a strategy named spatial-spectral information extraction (SSIE) is presented to accelerate the speed of hyperspectral image processing. The strategy is composed of bands selection and sample covariance matrix estimation. Bands selection fully utilizes the high-spectral correlation in spectral image, while sample covariance matrix estimation fully utilizes the high-spatial correlation in remote sensing image. Meanwhile, this strategy is implemented on the hardware platform of DSP. The hardware implementation of constrained energy minimization (CEM) algorithm is composed of hardware architecture and software architecture. The hardware architecture contains chips and peripheral interfaces, and software architecture establishes a data transferring model to accomplish the communication between DSP and PC. In experiments, the performance on software of ENVI with that on hardware of DSP is compared. Results show that the processing speed and recognition result on DSP are better than those on ENVI. Detection results demonstrate that the strategy implemented by DSP is sufficient to enable near real-time supervised target detection.

  10. Real-Time Detection for Magnetic Island of Neoclassical Tearing Mode in EAST Plasma Control System

    NASA Astrophysics Data System (ADS)

    Liang, Shaoyong; Xiao, Bingjia; Zhang, Yang; Wang, Linfang; Yuan, Qiping; Luo, Zhengping; Shi, Tonghui; Ti, Ang

    2016-02-01

    Accurate detection of a magnetic island in real time is one of the important issues for the tearing mode (TM) and neoclassical tearing mode (NTM) control. This paper presents a real-time detection system for the magnetic island of NTM control in the EAST Plasma Control System (PCS). Diagnosis is based on magnetic periodic perturbation and electron temperature fluctuation caused by the magnetic island. Therefore, a Mirnov measurement has been selected to calculate the island's parameters, such as island width, frequency of island rotation, and toroidal number. The electron cyclotron emission (ECE) system can detect the island position, which is calculated by two fast detection algorithms called correlation analysis and Hilbert transform. For future NTM control, real-time equilibrium reconstruction (rt-EFIT) is needed to locate the rational q-surface where the island is detected. This fast detection system is able to detect an island within 3 ms. It can be integrated into PCS to provide effective parameters of the island for NTM control by using EC resonance heating (ECRH) in the next experiment of EAST. supported by the National Magnetic Confinement Fusion Science Program of China (Nos. 2014GB103000, 2012GB103000, and 2012GB103002), National Natural Science Foundation of China (No. 11205200)

  11. Wideband acoustic activation and detection of droplet vaporization events using a capacitive micromachined ultrasonic transducer.

    PubMed

    Novell, Anthony; Arena, Christopher B; Oralkan, Omer; Dayton, Paul A

    2016-06-01

    An ongoing challenge exists in understanding and optimizing the acoustic droplet vaporization (ADV) process to enhance contrast agent effectiveness for biomedical applications. Acoustic signatures from vaporization events can be identified and differentiated from microbubble or tissue signals based on their frequency content. The present study exploited the wide bandwidth of a 128-element capacitive micromachined ultrasonic transducer (CMUT) array for activation (8 MHz) and real-time imaging (1 MHz) of ADV events from droplets circulating in a tube. Compared to a commercial piezoelectric probe, the CMUT array provides a substantial increase of the contrast-to-noise ratio. PMID:27369143

  12. Nanopore Biosensor for Label-Free and Real-Time Detection of Anthrax Lethal Factor

    PubMed Central

    2015-01-01

    We report a label-free real-time nanopore sensing method for the detection of anthrax lethal factor, a component of the anthrax toxin, by using a complementary single-stranded DNA as a molecular probe. The method is rapid and sensitive: sub-nanomolar concentrations of the target anthrax lethal factor DNA could be detected in ∼1 min. Further, our method is selective, which can differentiate the target DNA from other single-stranded DNA molecules at the single-base resolution. This sequence-specific detection approach should find useful application in the development of nanopore sensors for the detection of other pathogens. PMID:24806593

  13. Loop-mediated isothermal amplification: rapid visual and real-time methods for detection of genetically modified crops.

    PubMed

    Randhawa, Gurinder Jit; Singh, Monika; Morisset, Dany; Sood, Payal; Zel, Jana

    2013-11-27

    A rapid, reliable, and sensitive loop-mediated isothermal amplification (LAMP) system was developed for screening of genetically modified organisms (GMOs). The optimized LAMP assays using designed primers target commonly employed promoters, i.e., Cauliflower Mosaic Virus 35S (P-35S) and Figwort Mosaic Virus promoter (P-FMV), and marker genes, i.e., aminoglycoside 3'-adenyltransferase (aadA), neomycin phosphotransferase II (nptII), and β-glucuronidase (uidA). The specificity and performance of the end-point and real-time LAMP assays were confirmed using eight genetically modified (GM) cotton events on four detection systems, employing two chemistries. LAMP assays on the isothermal real-time system were found to be most sensitive, detecting up to four target copies, within 35 min. The LAMP assays herein presented using alternate detection systems can be effectively utilized for rapid and cost-effective screening of the GM status of a sample, irrespective of the crop species or GM trait. These assays coupled with a fast and simple DNA extraction method may further facilitate on-site GMO screening. PMID:24188249

  14. Conceptual Integration of Arithmetic Operations with Real-World Knowledge: Evidence from Event-Related Potentials

    ERIC Educational Resources Information Center

    Guthormsen, Amy M.; Fisher, Kristie J.; Bassok, Miriam; Osterhout, Lee; DeWolf, Melissa; Holyoak, Keith J.

    2016-01-01

    Research on language processing has shown that the disruption of conceptual integration gives rise to specific patterns of event-related brain potentials (ERPs)--N400 and P600 effects. Here, we report similar ERP effects when adults performed cross-domain conceptual integration of analogous semantic and mathematical relations. In a problem-solving…

  15. "Are We 'Real' Americans?": Cultural Production of "Forever Foreigners" at a Diversity Event

    ERIC Educational Resources Information Center

    Park, Gilbert C.

    2011-01-01

    Although the history of Asian immigrants dates back to the 17th century, their status as authentic Americans is still questioned today. With this in mind, this article looks at how a diversity event at a racially diverse inner-city high school produces the image of Asian Americans as "forever foreigners." Using qualitative tools like observation…

  16. Real-time system for imaging and object detection with a multistatic GPR array

    SciTech Connect

    Paglieroni, David W; Beer, N Reginald; Bond, Steven W; Top, Philip L; Chambers, David H; Mast, Jeffrey E; Donetti, John G; Mason, Blake C; Jones, Steven M

    2014-10-07

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  17. A canonical correlation analysis based method for contamination event detection in water sources.

    PubMed

    Li, Ruonan; Liu, Shuming; Smith, Kate; Che, Han

    2016-06-15

    In this study, a general framework integrating a data-driven estimation model is employed for contamination event detection in water sources. Sequential canonical correlation coefficients are updated in the model using multivariate water quality time series. The proposed method utilizes canonical correlation analysis for studying the interplay between two sets of water quality parameters. The model is assessed by precision, recall and F-measure. The proposed method is tested using data from a laboratory contaminant injection experiment. The proposed method could detect a contamination event 1 minute after the introduction of 1.600 mg l(-1) acrylamide solution. With optimized parameter values, the proposed method can correctly detect 97.50% of all contamination events with no false alarms. The robustness of the proposed method can be explained using the Bauer-Fike theorem. PMID:27264637

  18. Detection of Zika virus by SYBR green one-step real-time RT-PCR.

    PubMed

    Xu, Ming-Yue; Liu, Si-Qing; Deng, Cheng-Lin; Zhang, Qiu-Yan; Zhang, Bo

    2016-10-01

    The ongoing Zika virus (ZIKV) outbreak has rapidly spread to new areas of Americas, which were the first transmissions outside its traditional endemic areas in Africa and Asia. Due to the link with newborn defects and neurological disorder, numerous infected cases throughout the world and various mosquito vectors, the virus has been considered to be an international public health emergency. In the present study, we developed a SYBR Green based one-step real-time RT-PCR assay for rapid detection of ZIKV. Our results revealed that the real-time assay is highly specific and sensitive in detection of ZIKV in cell samples. Importantly, the replication of ZIKV at different time points in infected cells could be rapidly monitored by the real-time RT-PCR assay. Specifically, the real-time RT-PCR showed acceptable performance in measurement of infectious ZIKV RNA. This assay could detect ZIKV at a titer as low as 1PFU/mL. The real-time RT-PCR assay could be a useful tool for further virology surveillance and diagnosis of ZIKV. PMID:27444120

  19. Evaluation of Five Real-Time PCR Assays for Detection of Mycoplasma pneumoniae

    PubMed Central

    Jacobs, Enno

    2014-01-01

    Four commercial real-time PCR assays to detect Mycoplasma pneumoniae were tested, and the results were compared with the results for an in-house approach. Despite differences of crossing threshold values of up to 4, assays were able to detect at least 20 CFU/5 μl (52 fg DNA/5 μl) of sample with the Diagenode kit showing the best clinical sensitivity. PMID:25210063

  20. Real-time remote detection and measurement for airborne imaging spectroscopy: a case study with methane

    NASA Astrophysics Data System (ADS)

    Thompson, D. R.; Leifer, I.; Bovensmann, H.; Eastwood, M.; Fladeland, M.; Frankenberg, C.; Gerilowski, K.; Green, R. O.; Kratwurst, S.; Krings, T.; Luna, B.; Thorpe, A. K.

    2015-10-01

    Localized anthropogenic sources of atmospheric CH4 are highly uncertain and temporally variable. Airborne remote measurement is an effective method to detect and quantify these emissions. In a campaign context, the science yield can be dramatically increased by real-time retrievals that allow operators to coordinate multiple measurements of the most active areas. This can improve science outcomes for both single- and multiple-platform missions. We describe a case study of the NASA/ESA CO2 and MEthane eXperiment (COMEX) campaign in California during June and August/September 2014. COMEX was a multi-platform campaign to measure CH4 plumes released from anthropogenic sources including oil and gas infrastructure. We discuss principles for real-time spectral signature detection and measurement, and report performance on the NASA Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG). AVIRIS-NG successfully detected CH4 plumes in real-time at Gb s-1 data rates, characterizing fugitive releases in concert with other in situ and remote instruments. The teams used these real-time CH4 detections to coordinate measurements across multiple platforms, including airborne in situ, airborne non-imaging remote sensing, and ground-based in situ instruments. To our knowledge this is the first reported use of real-time trace-gas signature detection in an airborne science campaign, and presages many future applications. Post-analysis demonstrates matched filter methods providing noise-equivalent (1σ) detection sensitivity for 1.0 % CH4 column enhancements equal to 141 ppm m.

  1. Comments concerning the real risk of sexual adverse events secondary to the use of 5-ARIs.

    PubMed

    Pirozzi Farina, Furio; Pischedda, Antonella

    2015-12-01

    Treatment-induced sexual dysfunctions (SD) are a recurrent and controversial topic in recent literature on the adverse events related to the use of 5-alpha-reductase inhibitors (5ARIs) (1, 2). In order to deal adequately with the various aspects of this topic, it is necessary to first cover some of the steps that allow a better definition and understanding of the subject. PMID:26766804

  2. A New Real-Time PCR Assay for Improved Detection of the Parasite Babesia microti

    PubMed Central

    Teal, Allen E.; Habura, Andrea; Ennis, Jill; Keithly, Janet S.

    2012-01-01

    Babesiosis is an emerging zoonosis with important public health implications, as the incidence of the disease has risen dramatically over the past decade. Because the current gold standard for detection of Babesia is microscopic examination of blood smears, accurate identification requires trained personnel. Species in the genus cannot be distinguished microscopically, and Babesia can also be confused with the early trophozoite stage (ring forms) of Plasmodium parasites. To allow more accurate diagnosis in a format that is accessible to a wider variety of laboratories, we developed a real-time PCR assay targeting the 18S rRNA gene of Babesia microti, the dominant babesiosis pathogen in the United States. The real-time PCR is performed on DNA extracted from whole-blood specimens and detects Babesia microti with a limit of detection of ∼100 gene copies in 5 μl of blood. The real-time PCR assay was shown to be 100% specific when tested against a panel of 24 organisms consisting of Babesia microti, other Babesia species, Plasmodium species, tick-borne and other pathogenic bacteria, and other blood-borne parasites. The results using clinical specimens show that the assay can detect infections of lower parasitemia than can be detected by microscopic examination. This method is therefore a rapid, sensitive, and accurate method for detection of Babesia microti in patient specimens. PMID:22170915

  3. High-throughput real-time electrochemical monitoring of LAMP for pathogenic bacteria detection.

    PubMed

    Safavieh, Mohammadali; Ahmed, Minhaz Uddin; Ng, Andy; Zourob, Mohammed

    2014-08-15

    One of the significant challenges in healthcare is the development of point-of-care (POC) diagnostics. POC diagnostics require low-cost devices that offer portability, simplicity in operation and the ability for high-throughput and quantitative analysis. Here, we present a novel roll-to-roll ribbon fluid-handling device for electrochemical real-time monitoring of nucleic acid (NA) amplification and bacteria detection. The device rendered loop-mediated isothermal amplification (LAMP) and real-time electrochemical detection based on the interaction between LAMP amplicon and the redox-reactive osmium complex. We have shown the detection of 30CFU/ml of Escherichia coli (in the range between 30 and 3×10(7)CFU/ml) and 200CFU/ml of Staphylococcus aureus (in the range of 200-2×10(5)CFU/ml) cultured samples in both real-time and end point detection. This device can be used for the detection of various Gram-negative and a number of Gram-positive bacterial pathogens with high sensitivity and specificity in a high-throughput format. Using a roll-to-roll cassette approach, we could detect 12 samples in one assay. Since the LAMP and electrochemical analysis are implemented within sealed flexible biochips, time-consuming processing steps are not required and the risk of contamination is significantly reduced. PMID:24632135

  4. [Real-time PCR kits for the detection of the African Swine Fever virus].

    PubMed

    Latyshev, O E; Eliseeva, O V; Grebennikova, T V; Verkhovskiĭ, O A; Tsibezov, V V; Chernykh, O Iu; Dzhailidi, G A; Aliper, T I

    2014-01-01

    The results obtained using the diagnostic kit based on real-time polymerase chain reaction to detect the DNA of the African Swine Fever in the pathological material, as well as in the culture fluid, are presented. A high sensitivity and specificity for detection of the DNA in the organs and tissues of animals was shown to be useful for detection in the European Union referentiality reagent kits for DNA detection by real time PCR of ASFV. More rapid and effective method of DNA extraction using columns mini spin Quick gDNA(TM) MiniPrep was suggested and compared to the method of DNA isolation on the inorganic sorbent. High correlation of the results of the DNA detection of ASFV by real-time PCR and antigen detection results ASFV by competitive ELISA obtained with the ELISA SEROTEST/INGEZIM COMRAC PPA was demonstrated. The kit can be used in the veterinary services for effective monitoring of ASFV to contain, eliminate and prevent further spread of the disease. PMID:25895212

  5. Method for detecting binding events using micro-X-ray fluorescence spectrometry

    DOEpatents

    Warner, Benjamin P.; Havrilla, George J.; Mann, Grace

    2010-12-28

    Method for detecting binding events using micro-X-ray fluorescence spectrometry. Receptors are exposed to at least one potential binder and arrayed on a substrate support. Each member of the array is exposed to X-ray radiation. The magnitude of a detectable X-ray fluorescence signal for at least one element can be used to determine whether a binding event between a binder and a receptor has occurred, and can provide information related to the extent of binding between the binder and receptor.

  6. Detecting, Monitoring, and Reporting Possible Adverse Drug Events Using an Arden-Syntax-based Rule Engine.

    PubMed

    Fehre, Karsten; Plössnig, Manuela; Schuler, Jochen; Hofer-Dückelmann, Christina; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2015-01-01

    The detection of adverse drug events (ADEs) is an important aspect of improving patient safety. The iMedication system employs predefined triggers associated with significant events in a patient's clinical data to automatically detect possible ADEs. We defined four clinically relevant conditions: hyperkalemia, hyponatremia, renal failure, and over-anticoagulation. These are some of the most relevant ADEs in internal medical and geriatric wards. For each patient, ADE risk scores for all four situations are calculated, compared against a threshold, and judged to be monitored, or reported. A ward-based cockpit view summarizes the results. PMID:26262252

  7. Goose Hemorrhagic polyomavirus detection in geese using real-time PCR assay.

    PubMed

    Leon, Olivier; Corrand, Léni; Bich, Tran Ngoc; Le Minor, Odile; Lemaire, Mylène; Guérin, Jean-Luc

    2013-12-01

    Goose hemorrhagic polyomavirus (GHPV) is the viral agent of hemorrhagic nephritis enteritis of geese (HNEG), a lethal disease of goslings. Although death is the most common outcome, geese that recover from HNEG are persistently infected. Here, we present the development of real-time SYBR Green real-time PCR targeted to GHPV and its use to assess the prevalence of GHPV infection in French geese flocks. When compared with classical end-point PCR, real-time PCR revealed a much better sensitivity and equivalent specificity. Real-time PCR could, therefore, be considered a gold standard for the detection of GHPV. Results of field investigations evidenced a very high prevalence of GHPV infections in French geese, largely associated with healthy carriage. PMID:24597124

  8. A Novel Real-Time DNA Detection System for Loop-Mediated Isothermal Amplification Method

    NASA Astrophysics Data System (ADS)

    Kakugawa, Koji; Yamada, Kenji; Maeda, Hiroshi; Takashiba, Shougo

    We developed a novel real-time DNA detection system for loop-mediated isothermal amplification (LAMP) method. Our prototype was composed of a thermostatic chamber, a hole slide glass, LED and a web camera. The reaction mixture was injected into the slide glass hole and the LAMP reaction was carried out at 63°C for 2 hours. To observe the DNA amplification, we monitored the fluorescence intensity of SYBR Green I that was excited by the blue LED. The captured BMP images were analyzed by NIH Image J software. The DNA amplification and amplification monitoring experiment was successful. Furthermore, quantitative accuracy was evaluated based on real-time PCR. The reaction time correlates well with the DNA concentration. These results indicate the successful development of a novel real-time DNA detection system for LAMP method.

  9. Ubiquitous health monitoring and real-time cardiac arrhythmias detection: a case study.

    PubMed

    Li, Jian; Zhou, Haiying; Zuo, Decheng; Hou, Kun-Mean; De Vaulx, Christophe

    2014-01-01

    As the symptoms and signs of heart diseases that cause sudden cardiac death, cardiac arrhythmia has attracted great attention. Due to limitations in time and space, traditional approaches to cardiac arrhythmias detection fail to provide a real-time continuous monitoring and testing service applicable in different environmental conditions. Integrated with the latest technologies in ECG (electrocardiograph) analysis and medical care, the pervasive computing technology makes possible the ubiquitous cardiac care services, and thus brings about new technical challenges, especially in the formation of cardiac care architecture and realization of the real-time automatic ECG detection algorithm dedicated to care devices. In this paper, a ubiquitous cardiac care prototype system is presented with its architecture framework well elaborated. This prototype system has been tested and evaluated in all the clinical-/home-/outdoor-care modes with a satisfactory performance in providing real-time continuous cardiac arrhythmias monitoring service unlimitedly adaptable in time and space. PMID:24211993

  10. Real-time DSP implementation for MRF-based video motion detection.

    PubMed

    Dumontier, C; Luthon, F; Charras, J P

    1999-01-01

    This paper describes the real time implementation of a simple and robust motion detection algorithm based on Markov random field (MRF) modeling, MRF-based algorithms often require a significant amount of computations. The intrinsic parallel property of MRF modeling has led most of implementations toward parallel machines and neural networks, but none of these approaches offers an efficient solution for real-world (i.e., industrial) applications. Here, an alternative implementation for the problem at hand is presented yielding a complete, efficient and autonomous real-time system for motion detection. This system is based on a hybrid architecture, associating pipeline modules with one asynchronous module to perform the whole process, from video acquisition to moving object masks visualization. A board prototype is presented and a processing rate of 15 images/s is achieved, showing the validity of the approach. PMID:18267406

  11. DETECTION AND QUANTITATION OF SOLENOPSIS INVICTA VIRUS IN FIRE ANTS BY REAL-TIME PCR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A quantitative real-time PCR (QPCR) method was developed to detect and quantify the amount of Solenopsis invicta virus (SINV) infecting individual ants of Solenopsis invicta. The two-step method utilized a gene-specific oligonucleotide primer targeting the SINV RNA-dependent RNA polymerase (RdRp) f...

  12. Ten hour real-time PCR technique for detection of Salmonella in meats

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We evaluated the efficacy of real-time PCR assays to detect low levels of Salmonella in meats following 8 h of pre-enrichment. The sensitivity and accuracy of molecular beacon and TaqMan probe PCR assays were compared with the conventional USDA microbiological procedure using artificially contaminat...

  13. Type-A influenza virus detection and quantitation by real-time RT-PCR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Real-time RT-PCR (RRT-PCR) is a relatively new technology which has been used for AIV detection since the early 2000’s for routine surveillance, during outbreaks and for research. Some of the advantages of RRT-PCR are: quantitative nature, scalability, cost, high sensitivity, high specificity, and ...

  14. DETECTION OF PHAKOPSORA PACHYRHIZI SPORES IN RAIN USING REAL-TIME PCR ASSAY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In 2005, rain samples were collected weekly at selected National Atmospheric Deposition Program (NADP) sites in the eastern and central US and screened for Phakopsora pachyrhizi (Asian soybean rust) spores. A nested real-time PCR assay was used to detect P. pachyrhizi DNA in the filter residue. A su...

  15. DEVELOPMENT OF A REAL-TIME FLUORESCENCE RESONANCE ENERGY TRANSFER (FRET) PCR TO DETECT ARCOBACTER SPECIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A real-time PCR targeting the gyrase A subunit gene outside the quinolone resistance-determining region has been developed to detect Arcobacter species. The species identification was made by probe hybridization and melting curve analysis, using the Fluorescence Resonance Energy Transfer technology...

  16. DEVELOPMENT OF A REAL-TIME FLUORESCENCE RESONANCE ENERGY TRANSFER PCR TO DETECT ARCOBACTER SPECIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A real-time PCR targeting the gyrase A subunit gene outside the quinolone resistance-determining region has been developed to detect Arcobacter species. The species identification was made by probe hybridization and melting curve analysis, using Fluorescence Resonance Energy Transfer technology. D...

  17. Evaluation of two commercial real-time PCR assays for detecting Campylobacter in broiler carcass rinses.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Traditional plating methods are reliable means for Campylobacter identification from poultry samples but automated gene-based detection systems now available can reduce assay time, data collection and analysis. Bio-Rad and DuPont Qualicon recently introduced Campylobacter assays for their real-time ...

  18. A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

    NASA Technical Reports Server (NTRS)

    Delaat, J. C.; Merrill, W. C.

    1983-01-01

    A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation.

  19. Development of a Multispectral Imaging Prototype for Real-Time Detection of Apple Fruit Firmness

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral scattering is a promising nondestructive technique for assessing the firmness of fruit. This paper reports on the development of a laser-based multispectral imaging prototype for real-time detection of apple fruit firmness. The prototype consisted of a common aperture multispectral ima...

  20. Single Laboratory Comparison of Quantitative Real-time PCR Assays for the Detection of Fecal Pollution

    EPA Science Inventory

    There are numerous quantitative real-time PCR (qPCR) assays available to detect and enumerate fecal pollution in ambient waters. Each assay employs distinct primers and probes that target different rRNA genes and microorganisms leading to potential variations in concentration es...

  1. Real-time detection of bacterial spores using coherent anti-Stokes Raman spectroscopy

    NASA Astrophysics Data System (ADS)

    Dogariu, A.; Goltsov, A.; Pestov, D.; Sokolov, A. V.; Scully, M. O.

    2008-02-01

    We demonstrate a realistic method for detection of anthrax-type spores in real time based on their chemical fingerprints using coherent anti-Stokes Raman scattering. Specifically, we demonstrate that coherent Raman scattering can be used to successfully identify spores with high accuracy and high selectivity in less than 50ms.

  2. Detection of shrimp-derived components in food by real-time fluorescent PCR.

    PubMed

    Cao, Jijuan; Yu, Bing; Ma, Lidan; Zheng, Qiuyue; Zhao, Xin; Xu, Junyi

    2011-10-01

    Crustaceans such as shrimp and crabs and their products are important allergens in food, and allergic reactions due to the consumption of shrimp and crabs are frequently reported. However, the chemical properties of shrimp-derived allergens, except for Pen a I, are still unclear. Therefore, it is important to establish a more sensitive and specific method for detecting the composition of foods containing shrimp. In the present study, we developed a real-time fluorescent PCR to identify the specific shrimp-derived components in food. The primers and TaqMan probes for real-time fluorescent PCR were designed based on 16S rRNA genes through comparing a large number of nucleic acid sequences from different species of shrimp that have been published by the National Center for Biotechnology Information. In total, 56 kinds of samples, including different kinds of shrimp, crab, fish, shellfish, and octopus, were subjected to detection by real-time PCR. The results indicated that real-time fluorescent PCR could successfully identify the shrimp-derived components. In order to explore the effect of food processing on detection sensitivity, fish powder containing shrimp powder was treated by heating at 133°C for 30 min. The limit of detection of shrimp-derived components in fish powder was 0.05% (wt/wt). PMID:22004830

  3. Real-time image processing for rapid contaminant detection on broiler carcasses

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Lawrence, Kurt C.; Windham, William R.; Snead, M. Preston

    2004-11-01

    Recently, the imaging research group at Russell Research Center, ARS in Athens, Georgia has developed a real-time multispectral imaging system for fecal and ingesta contaminant detection on broiler carcasses. The prototype system includes a common aperture camera with three optical trim filters (515.4, 566.4 and 631-nm wavelength), which were selected by visible/NIR spectroscopy and validated by a hyperspectral imaging system. The preliminary results showed that the multispectral imaging technique can be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses with a processing speed of 140 birds per minute. The accuracy for the detection of fecal and ingesta contaminates was 96%. However, the system contains many false positives including scabs, feathers, and boundaries. This paper demonstrates calibration of common aperture multispectral imaging hardware and real-time multispectral image processing software. The software design, especially the Unified Modeling Language (UML) design approach was used to develop real-time image processing software for on-line application. The UML models including class, object, activity, sequence, and collaboration diagram were discussed. Both hardware and software for a real-time fecal and ingesta contaminant detection were tested at the pilot-scale poultry processing line.

  4. Diagnosis of bacterial kidney disease by detection of Renibacterium salmoninarum by real-time PCR.

    PubMed

    Jansson, E; Lindberg, L; Säker, E; Aspán, A

    2008-10-01

    Bacterial kidney disease (BKD), caused by Renibacterium salmoninarum (Rs), is a serious threat to salmon in aquaculture as well as to wild populations. We have developed a real-time polymerase chain reaction (PCR) for detection of Rs in kidney samples. The PCR is based on detection of unique parts of the 16S rRNA gene of Rs and DNA equivalent to 1-10 Rs genomes was detected per reaction. No cross-reactivity with other fish pathogenic or related bacteria could be demonstrated. Analysis of individual kidney samples collected from BKD classified populations identified 39.9% of the fish as positive by real-time PCR compared with 28.0% by polyclonal enzyme-linked immunosorbent assay (ELISA). The real-time PCR assay was found to be well suited for complementary use with ELISA for diagnosis of BKD, with the ability to detect clinical as well as covert Rs infections. The infection level determined by the polyclonal ELISA and by real-time PCR was significantly correlated. PMID:18681904

  5. Real-time monitoring of seismicity and deformation during the Bárdarbunga rifting event and associated caldera subsidence

    NASA Astrophysics Data System (ADS)

    Jónsdóttir, Kristín; Ófeigsson, Benedikt; Vogfjörd, Kristín; Roberts, Matthew; Barsotti, Sara; Gudmundsson, Gunnar; Hensch, Martin; Bergsson, Bergur; Kjartansson, vilhjálmur; Erlendsson, Pálmi; Friðriksdóttir, Hildur; Hreinsdóttir, Sigrún; Guðmundsson, Magnús; Sigmundsson, Freysteinn; Árnadóttir, Thóra; Heimisson, Elías; Hjorleifsdóttir, Vala; Soring, Jón; Björnsson, Bogi; Oddsson, Björn

    2015-04-01

    We present a monitoring overview of a rifting event and associated caldera subsidence in a glaciated environment during the Bárðarbunga volcanic crisis. Following a slight increase in seismicity and a weak deformation signal, noticed a few months before the unrest by the SIL monitoring team, an intense seismic swarm began in the subglacial Bárðarbunga caldera on August 16 2014. During the following two weeks, a dyke intruded into the crust beneath the Vatnajökull ice cap, propagating 48 km from the caldera to the east-north-east and north of the glacier where an effusive eruption started in Holuhraun. The eruption is still ongoing at the time of writing and has become the largest eruption in over 200 years in Iceland. The dyke propagation was episodic with a variable rate and on several occasions low frequency seismic tremor was observed. Four ice cauldrons, manifestations of small subglacial eruptions, were detected. Soon after the swarm began the 7x11 km wide caldera started to subside and is still subsiding (although at slower rates) and has in total subsided over 60 meters. Unrest in subglacial volcanoes always calls for interdisciplinary efforts and teamwork plays a key role for efficient monitoring. Iceland has experienced six subglacial volcanic crises since modern digital monitoring started in the early 90s. With every crisis the monitoring capabilities, data interpretations, communication and information dissemination procedures have improved. The Civil Protection calls for a board of experts and scientists (Civil Protection Science Board, CPSB) to share their knowledge and provide up-to-date information on the current status of the volcano, the relevant hazards and most likely scenarios. The evolution of the rifting was monitored in real-time by the joint interpretation of seismic and cGPS data. The dyke propagation could be tracked and new, updated models of the dyke volume were presented at the CPSB meetings, often daily. In addition, deformation

  6. International ring trial for the validation of an event-specific Golden Rice 2 quantitative real-time polymerase chain reaction method.

    PubMed

    Jacchia, Sara; Nardini, Elena; Bassani, Niccolò; Savini, Christian; Shim, Jung-Hyun; Trijatmiko, Kurniawan; Kreysa, Joachim; Mazzara, Marco

    2015-05-27

    This article describes the international validation of the quantitative real-time polymerase chain reaction (PCR) detection method for Golden Rice 2. The method consists of a taxon-specific assay amplifying a fragment of rice Phospholipase D α2 gene, and an event-specific assay designed on the 3' junction between transgenic insert and plant DNA. We validated the two assays independently, with absolute quantification, and in combination, with relative quantification, on DNA samples prepared in haploid genome equivalents. We assessed trueness, precision, efficiency, and linearity of the two assays, and the results demonstrate that both the assays independently assessed and the entire method fulfill European and international requirements for methods for genetically modified organism (GMO) testing, within the dynamic range tested. The homogeneity of the results of the collaborative trial between Europe and Asia is a good indicator of the robustness of the method. PMID:25946377

  7. Detection of invisible and crucial events: from seismic fluctuations to the war against terrorism

    NASA Astrophysics Data System (ADS)

    Allegrini, Paolo; Fronzoni, Leone; Grigolini, Paolo; Latora, Vito; Mega, Mirko S.; Palatella, Luigi; Rapisarda, Andrea; Vinciguerra, Sergio

    2004-04-01

    We prove the efficiency of a new method for the detection of crucial events that might have useful applications to the war against terrorism. This has to do with the search for rare but significant events, a theme of research that has been made of extreme importance by the tragedy of September 11. This method is applied here to defining the statistics of seismic main-shocks, as done in cond-mat/0212529. The emphasis here is on the conceptual issues behind the results obtained in cond-mat/0212529 than on geophysics. This discussion suggests that the method has a wider range of validity. We support this general discussion with a dynamic model originally proposed in cond-mat/0107597 for purposes different from geophysical applications. However, it is a case where the crucial events to detect are under our control, thereby making it possible for us to check the accuracy of the method of detection of invisible and crucial events that we propose here for a general purpose, including the war against terrorism. For this model an analytical treatment has been recently found [cond-mat/0209038], supporting the claims that we make in this paper for the accuracy of the method of detection. For the reader's convenience, the results on the seismic fluctuations are suitably reviewed, and discussed in the light of the more general perspective of this paper. We also review the model for seismic fluctuations, proposed in the earlier work of cond-mat/0212529. This model shares with the model of cond-mat/0107597 the property that the crucial events are imbedded in a sea of secondary events, but it allows us to reveal with accuracy the statistics of the crucial events for different mathematical reasons.

  8. Fast and sensitive detection of mycotoxins in wheat using microfluidics based Real-time Electrochemical Profiling.

    PubMed

    Olcer, Zehra; Esen, Elif; Muhammad, Turghun; Ersoy, Aylin; Budak, Sinan; Uludag, Yıldız

    2014-12-15

    The objective of the study has been the development of a new sensing platform, called Real-time Electrochemical Profiling (REP) that relies on real-time electrochemical immunoassay detection. The proposed REP platform consists of new electrode arrays that are easy to fabricate, has a small imprint allowing microfluidic system integration, enables multiplexed amperometric measurements and performs well in terms of electrochemical immunoassay detection as shown through the deoxynivalenol detection assays. The deoxynivalenol detection has been conducted according to an optimised REP assay protocol using deoxynivalenol standards at varying concentrations and a standard curve was obtained (y=-20.33ln(x)+124.06; R(2)=0.97) with a limit of detection of 6.25 ng/ml. As both ELISA and REP detection methods use horse radish peroxidase as the label and 3.3',5.5'-Tetramethylbenzidine as the substrate, the performance of the REP platform as an ELISA reader has also been investigated and a perfect correlation between the deoxynivalenol concentration and the current response was obtained (y=-14.56ln(x)+101.02; R(2)=0.99). The calibration curves of both assays have been compared to conventional ELISA tests for confirmation. After assay optimisation using toxin spiked buffer, the deoxynivalenol detection assay has also been performed to detect toxins in wheat grain. PMID:24998314

  9. Developing a real-time emulation of multiresolutional control architectures for complex, discrete-event systems

    SciTech Connect

    Davis, W.J.; Macro, J.G.; Brook, A.L.

    1996-12-31

    This paper first discusses an object-oriented, control architecture and then applies the architecture to produce a real-time software emulator for the Rapid Acquisition of Manufactured Parts (RAMP) flexible manufacturing system (FMS). In specifying the control architecture, the coordinated object is first defined as the primary modeling element. These coordinated objects are then integrated into a Recursive, Object-Oriented Coordination Hierarchy. A new simulation methodology, the Hierarchical Object-Oriented Programmable Logic Simulator, is then employed to model the interactions among the coordinated objects. The final step in implementing the emulator is to distribute the models of the coordinated objects over a network of computers and to synchronize their operation to a real-time clock. The paper then introduces the Hierarchical Subsystem Controller as an intelligent controller for the coordinated object. The proposed approach to intelligent control is then compared to the concept of multiresolutional semiosis that has been developed by Dr. Alex Meystel. Finally, the plans for implementing an intelligent controller for the RAMP FMS are discussed.

  10. Development of an algorithm for automatic detection and rating of squeak and rattle events

    NASA Astrophysics Data System (ADS)

    Chandrika, Unnikrishnan Kuttan; Kim, Jay H.

    2010-10-01

    A new algorithm for automatic detection and rating of squeak and rattle (S&R) events was developed. The algorithm utilizes the perceived transient loudness (PTL) that approximates the human perception of a transient noise. At first, instantaneous specific loudness time histories are calculated over 1-24 bark range by applying the analytic wavelet transform and Zwicker loudness transform to the recorded noise. Transient specific loudness time histories are then obtained by removing estimated contributions of the background noise from instantaneous specific loudness time histories. These transient specific loudness time histories are summed to obtain the transient loudness time history. Finally, the PTL time history is obtained by applying Glasberg and Moore temporal integration to the transient loudness time history. Detection of S&R events utilizes the PTL time history obtained by summing only 18-24 barks components to take advantage of high signal-to-noise ratio in the high frequency range. A S&R event is identified when the value of the PTL time history exceeds the detection threshold pre-determined by a jury test. The maximum value of the PTL time history is used for rating of S&R events. Another jury test showed that the method performs much better if the PTL time history obtained by summing all frequency components is used. Therefore, r ating of S&R events utilizes this modified PTL time history. Two additional jury tests were conducted to validate the developed detection and rating methods. The algorithm developed in this work will enable automatic detection and rating of S&R events with good accuracy and minimum possibility of false alarm.

  11. Designing Adverse Event Forms for Real-World Reporting: Participatory Research in Uganda

    PubMed Central

    Innocent, Simeon H. S.; Kalumuna, Charles; Terlouw, Dianne J.; Lalloo, David G.; Staedke, Sarah G.; Haaland, Ane

    2012-01-01

    The wide-scale roll-out of artemisinin combination therapies (ACTs) for the treatment of malaria should be accompanied by continued surveillance of their safety. Post-marketing pharmacovigilance (PV) relies on adverse event (AE) reporting by clinicians, but as a large proportion of treatments are provided by non-clinicians in low-resource settings, the effectiveness of such PV systems is limited. To facilitate reporting, AE forms should be easily completed; however, most are challenging for lower-level health workers and non-clinicians to complete. Through participatory research, we sought to develop user-friendly AE report forms to capture information on events associated with ACTs. Following situation analysis, we undertook workshops with community medicine distributors and health workers in Jinja, Uganda, to develop a reporting form based on experiences and needs of users, and communication and visual perception principles. Participants gave feedback for revisions of subsequent versions. We then conducted 8 pretesting sessions with 77 potential end users to test and refine passive and active versions of the form. The development process resulted in a form that included a pictorial storyboard to communicate the rationale for the information needed and facilitate rapport between the reporter and the respondent, and a diary format to record the drug administration and event details in chronological relation to each other. Successive rounds of pretesting used qualitative and quantitative feedback to refine the form, with the final round showing over 80% of the form completed correctly by potential end users. We developed novel AE report forms that can be used by non-clinicians to capture pharmacovigilance data for anti-malarial drugs. The participatory approach was effective for developing forms that are intuitive for reporters, and motivating for respondents. The forms, or their key components, could be adapted for use in other low-literacy settings to improve

  12. Designing adverse event forms for real-world reporting: participatory research in Uganda.

    PubMed

    Davies, Emma C; Chandler, Clare I R; Innocent, Simeon H S; Kalumuna, Charles; Terlouw, Dianne J; Lalloo, David G; Staedke, Sarah G; Haaland, Ane

    2012-01-01

    The wide-scale roll-out of artemisinin combination therapies (ACTs) for the treatment of malaria should be accompanied by continued surveillance of their safety. Post-marketing pharmacovigilance (PV) relies on adverse event (AE) reporting by clinicians, but as a large proportion of treatments are provided by non-clinicians in low-resource settings, the effectiveness of such PV systems is limited. To facilitate reporting, AE forms should be easily completed; however, most are challenging for lower-level health workers and non-clinicians to complete. Through participatory research, we sought to develop user-friendly AE report forms to capture information on events associated with ACTs.Following situation analysis, we undertook workshops with community medicine distributors and health workers in Jinja, Uganda, to develop a reporting form based on experiences and needs of users, and communication and visual perception principles. Participants gave feedback for revisions of subsequent versions. We then conducted 8 pretesting sessions with 77 potential end users to test and refine passive and active versions of the form.The development process resulted in a form that included a pictorial storyboard to communicate the rationale for the information needed and facilitate rapport between the reporter and the respondent, and a diary format to record the drug administration and event details in chronological relation to each other. Successive rounds of pretesting used qualitative and quantitative feedback to refine the form, with the final round showing over 80% of the form completed correctly by potential end users.We developed novel AE report forms that can be used by non-clinicians to capture pharmacovigilance data for anti-malarial drugs. The participatory approach was effective for developing forms that are intuitive for reporters, and motivating for respondents. The forms, or their key components, could be adapted for use in other low-literacy settings to improve quality

  13. Detection of Histoplasma capsulatum from clinical specimens by cycling probe-based real-time PCR and nested real-time PCR.

    PubMed

    Muraosa, Yasunori; Toyotome, Takahito; Yahiro, Maki; Watanabe, Akira; Shikanai-Yasuda, Maria Aparecida; Kamei, Katsuhiko

    2016-05-01

    We developed new cycling probe-based real-time PCR and nested real-time PCR assays for the detection of Histoplasma capsulatum that were designed to detect the gene encoding N-acetylated α-linked acidic dipeptidase (NAALADase), which we previously identified as an H. capsulatum antigen reacting with sera from patients with histoplasmosis. Both assays specifically detected the DNAs of all H. capsulatum strains but not those of other fungi or human DNA. The limited of detection (LOD) of the real-time PCR assay was 10 DNA copies when using 10-fold serial dilutions of the standard plasmid DNA and 50 DNA copies when using human serum spiked with standard plasmid DNA. The nested real-time PCR improved the LOD to 5 DNA copies when using human serum spiked with standard plasmid DNA, which represents a 10-fold higher than that observed with the real-time PCR assay. To assess the ability of the two assays to diagnose histoplasmosis, we analyzed a small number of clinical specimens collected from five patients with histoplasmosis, such as sera (n = 4), formalin-fixed paraffin-embedded (FFPE) tissue (n = 4), and bronchoalveolar lavage fluid (BALF) (n = 1). Although clinical sensitivity of the real-time PCR assay was insufficiently sensitive (33%), the nested real-time PCR assay increased the clinical sensitivity (77%), suggesting it has a potential to be a useful method for detecting H. capsulatum DNA in clinical specimens. PMID:26705837

  14. Advanced detection, isolation and accommodation of sensor failures: Real-time evaluation

    NASA Technical Reports Server (NTRS)

    Merrill, Walter C.; Delaat, John C.; Bruton, William M.

    1987-01-01

    The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundacy to detect sensor failures. The results of a real time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

  15. Advanced detection, isolation, and accommodation of sensor failures - Real-time evaluation

    NASA Technical Reports Server (NTRS)

    Merrill, Walter C.; Delaat, John C.; Bruton, William M.

    1988-01-01

    The objective of the Advanced Detection, Isolation, and Accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines by using analytical redundancy to detect sensor failures. The results of a real-time hybrid computer evaluation of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 engine control system are determined. Also included are details about the microprocessor implementation of the algorithm as well as a description of the algorithm itself.

  16. Real-time detection and elimination of nonorthogonality error in interference fringe processing

    SciTech Connect

    Hu Haijiang; Zhang Fengdeng

    2011-05-20

    In the measurement system of interference fringe, the nonorthogonality error is a main error source that influences the precision and accuracy of the measurement system. The detection and elimination of the error has been an important target. A novel method that only uses the cross-zero detection and the counting is proposed to detect and eliminate the nonorthogonality error in real time. This method can be simply realized by means of the digital logic device, because it does not invoke trigonometric functions and inverse trigonometric functions. And it can be widely used in the bidirectional subdivision systems of a Moire fringe and other optical instruments.

  17. Real-Time Curvature Defect Detection on Outer Surfaces Using Best-Fit Polynomial Interpolation

    PubMed Central

    Golkar, Ehsan; Prabuwono, Anton Satria; Patel, Ahmed

    2012-01-01

    This paper presents a novel, real-time defect detection system, based on a best-fit polynomial interpolation, that inspects the conditions of outer surfaces. The defect detection system is an enhanced feature extraction method that employs this technique to inspect the flatness, waviness, blob, and curvature faults of these surfaces. The proposed method has been performed, tested, and validated on numerous pipes and ceramic tiles. The results illustrate that the physical defects such as abnormal, popped-up blobs are recognized completely, and that flames, waviness, and curvature faults are detected simultaneously. PMID:23202186

  18. Design and implement of infrared small target real-time detection system based on pipeline technology

    NASA Astrophysics Data System (ADS)

    Sun, Lihui; Wang, Yongzhong; He, Yongqiang

    2007-01-01

    The detection for motive small target in infrared image sequence has become a hot topic nowadays. Background suppress algorithm based on minim gradient median filter and temporal recursion target detection algorithm are introduced. On the basis of contents previously mentioned, a four stages pipeline structure infrared small target detection process system, which aims at characters of algorithm complexity, large amounts of data to process, high frame frequency and exigent real-time character in this kind of application, is designed and implemented. The logical structure of the system was introduced and the function and signals flows are programmed. The system is composed of two FPGA chips and two DSP chips of TI. According to the function of each part, the system is divided into image preprocess stage, target detection stage, track relation stage and image output stage. The experiment of running algorithms on the system presented in this paper proved that the system could meet acquisition and process of 50Hz 240x320 digital image and the system could real time detect small target with a signal-noise ratio more than 3 reliably. The system achieves the characters of large amount of memory, high real-time processing, excellent extension and favorable interactive interface.

  19. Real Time Detection of Defects in GFRP Bridge Decks Using Infrared Thermography

    NASA Astrophysics Data System (ADS)

    Klinkhachorn, P.; Lonkar, G. M.; Halabe, Udaya B.; GangaRao, Hota V. S.

    2006-03-01

    This work is aimed at building a real time system to detect subsurface defects in GFRP bridge decks using infrared thermography. The issues addressed are: (a) development of a real time defect detection system, and (b) image mosaicking to build a composite image map. In the tests conducted, a turn key system was built in Matlab environment using the FLIR SDK to acquire image from the ThermaCAM S60 infrared camera. The images were then analyzed by defect detection algorithms. Efforts were made to minimize the time to detect defects in a captured image. In the second phase, image mosaicking was used to build a "composite image" that combines all the infrared images to form a single image. The location of defects in the "composite image" leads to a system that will be able to point out defects in the bridge as a whole. The study creates a base that can be used for real time defect detection in GFRP bridge decks.

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

    SciTech Connect

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

    1998-04-01

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

  1. Automated detection of asteroids in real-time with the Spacewatch telescope

    NASA Technical Reports Server (NTRS)

    Scotti, James Vernon; Gehrels, T.; Rabinowitz, David L.

    1992-01-01

    The Spacewatch telescope on Kitt Peak is being used to survey for near-earth asteroids using a Tektronix TK2048 CCD in scanning mode. We hope to identify suitable low delta v candidates amongst the near-earth asteroid population as possible exploration targets, to identify those objects which pose a danger to life on earth, and to study the physical properties of the objects in near-earth space. Between Sep. 1990 and Jun. 1991, 14 new earth-approaching asteroids including 1 Aten, 9 Apollo, and 4 Amor type asteroids were detected by automated software and discriminated by their angular rates from the rest of the detected asteroids in near-real time by the observer. The average of about 1.5 earth-approaching asteroids per month is comparable to the total number found by all other observatories combined. One other Apollo type asteroid was detected by the observer as a long trailed image. The positions of this last object were measured and the object was tracked by the observer in real time. This object was determined to be a 5-10 meter diameter object which passed within 170,000 kilometers of earth. Of the 14 automatically detected earth-approaching asteroids, 10 have been found at distances in excess of 0.5 AU from earth. An average of more than 2000 asteroids are detected each month. Positions, angular rates, and brightnesses are determined for each of these asteroids in real-time.

  2. Real time heart ischemia detection in the smart home care system.

    PubMed

    Pang, L; Tchoudovski, I; Bolz, A; Braecklein, M; Egorouchkina, K; Kellermann, W

    2005-01-01

    In this paper, a novel real-time algorithm for detecting ischemia in the ECG signal is proposed. The goal of this research is to meet the requirements of some smart cardiac home care devices, which can automatically diagnose the ECG and detect the heart risks outside the hospital, especially heart ischemia without symptoms in their early stages. The algorithm is developed based on a real time R peak detector, time domain traditional ECG parameters, the advanced morphologic parameters from Karhunen-Loève transform, and the adaptive neurofuzzy logic classification. Besides, in order to improve the reliability of our algorithm, several significant constraints of the ECG signal are considered. As a result, the ischemia episodes can be detected if the ischemic alteration persists longer than one minute in the ECG signal. PMID:17281031

  3. Vision-based real-time obstacle detection and tracking for autonomous vehicle guidance

    NASA Astrophysics Data System (ADS)

    Yang, Ming; Yu, Qian; Wang, Hong; Zhang, Bo

    2002-03-01

    The ability of obstacles detection and tracking is essential for safe visual guidance of autonomous vehicles, especially in urban environments. In this paper, we first overview different plane projective transformation (PPT) based obstacle detection approaches under the planar ground assumption. Then, we give a simple proof of this approach with relative affine, a unified framework that includes the Euclidean, projective and affine frameworks by generalization and specialization. Next, we present a real-time hybrid obstacle detection method, which combined the PPT based method with the region segmentation based method to provide more accurate locations of obstacles. At last, with the vehicle's position information, a Kalman Filter is applied to track obstacles from frame to frame. This method has been tested on THMR-V (Tsinghua Mobile Robot V). Through various experiments we successfully demonstrate its real-time performance, high accuracy, and high robustness.

  4. Detection of the Pinewood Nematode, Bursaphelenchus xylophilus, Using a Real-Time Polymerase Chain Reaction Assay.

    PubMed

    Cao, A X; Liu, X Z; Zhu, S F; Lu, B S

    2005-05-01

    ABSTRACT The pinewood nematode, Bursaphelenchus xylophilus, has caused significant damage to pine plantations both in East Asia and North America and is an important quarantine organism. A real-time polymerase chain reaction (PCR) assay was developed to detect B. xylophilus. A set of primers and probe specific for B. xylophilus was designed to target the ribosomal DNA internal transcribed spacer region. Optimal primer concentration, Mg(2+) concentration, and extension temperature were 400 nM, 3.0 mM, and 60 degrees C, respectively. The assay was highly specific and sensitive, detecting as little as 0.01 ng of B. xylophilus DNA. The real-time PCR assay also successfully detected B. xylophilus in field samples, and it should be very useful for quarantine purposes. PMID:18943323

  5. Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

    PubMed

    Tafinine, Farid; Mokrani, Karim

    2012-11-01

    A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor. PMID:23145702

  6. Real-time computational processing and implementation for concealed object detection

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Su; Yeom, Seokwon; Chang, YuShin; Lee, Mun-Kyo; Jung, Sang-Won

    2012-07-01

    Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable computational processing would be required for automatic analysis of the images. The authors present statistical and computational algorithms and their implementations for real-time concealed object detection. The histogram of the image is modeled as a Gaussian mixture distribution, and hidden object areas are segmented by a multilevel scheme involving the expectation-maximization algorithm. The complete algorithm has been implemented in both MATLAB and C++. Experimental and simulation results confirm that the implemented system can achieve real-time detection of concealed objects.

  7. Wenchuan Event Detection And Localization Using Waveform Correlation Coupled With Double Difference

    NASA Astrophysics Data System (ADS)

    Slinkard, M.; Heck, S.; Schaff, D. P.; Young, C. J.; Richards, P. G.

    2014-12-01

    The well-studied Wenchuan aftershock sequence triggered by the May 12, 2008, Ms 8.0, mainshock offers an ideal test case for evaluating the effectiveness of using waveform correlation coupled with double difference relocation to detect and locate events in a large aftershock sequence. We use Sandia's SeisCorr detector to process 3 months of data recorded by permanent IRIS and temporary ASCENT stations using templates from events listed in a global catalog to find similar events in the raw data stream. Then we take the detections and relocate them using the double difference method. We explore both the performance that can be expected with using just a small number of stations, and, the benefits of reprocessing a well-studied sequence such as this one using waveform correlation to find even more events. We benchmark our results against previously published results describing relocations of regional catalog data. Before starting this project, we had examples where with just a few stations at far-regional distances, waveform correlation combined with double difference did and impressive job of detection and location events with precision at the few hundred and even tens of meters level.

  8. Ultra-high throughput real-time instruments for capturing fast signals and rare events

    NASA Astrophysics Data System (ADS)

    Buckley, Brandon Walter

    Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and

  9. Trajectories of experience of real life events. A semiotic approach to the dynamics of positioning.

    PubMed

    Rosa, Alberto; González, Fernanda

    2013-12-01

    This paper is devoted to the study of experience as a semiotic process of constructing the personal meaning of the situation lived. Its main purpose is to devise a semiotic methodology capable of describing and explaining the dynamics of positioning when facing personal lived experiences in real life contexts. Twenty four young adults were exposed to a simulated conflict and then asked to write a narrative of their understanding of the incident and a self-report of their personal experiences. Results show how narratives and trajectories of experience present different forms in each participant, which could be related to: a) the understanding of the situation lived and the position taken regarding the conflict; and b) the position each participant takes regarding the reports they had to produce for the researchers. The incorporation of reflexivity into the applied method allows identification of how the dynamics of double positioning leave traces in the records produced. PMID:23943095

  10. Continuous flow real-time PCR device using multi-channel fluorescence excitation and detection.

    PubMed

    Hatch, Andrew C; Ray, Tathagata; Lintecum, Kelly; Youngbull, Cody

    2014-02-01

    High throughput automation is greatly enhanced using techniques that employ conveyor belt strategies with un-interrupted streams of flow. We have developed a 'conveyor belt' analog for high throughput real-time quantitative Polymerase Chain Reaction (qPCR) using droplet emulsion technology. We developed a low power, portable device that employs LED and fiber optic fluorescence excitation in conjunction with a continuous flow thermal cycler to achieve multi-channel fluorescence detection for real-time fluorescence measurements. Continuously streaming fluid plugs or droplets pass through tubing wrapped around a two-temperature zone thermal block with each wrap of tubing fluorescently coupled to a 64-channel multi-anode PMT. This work demonstrates real-time qPCR of 0.1-10 μL droplets or fluid plugs over a range of 7 orders of magnitude concentration from 1 × 10(1) to 1 × 10(7). The real-time qPCR analysis allows dynamic range quantification as high as 1 × 10(7) copies per 10 μL reaction, with PCR efficiencies within the range of 90-110% based on serial dilution assays and a limit of detection of 10 copies per rxn. The combined functionality of continuous flow, low power thermal cycling, high throughput sample processing, and real-time qPCR improves the rates at which biological or environmental samples can be continuously sampled and analyzed. PMID:24297040

  11. Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection

    PubMed Central

    Liu, Changyu; Li, Huiling

    2014-01-01

    We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches. PMID:25147840

  12. A real-time, event-triggered storm surge forecasting system for the state of North Carolina

    NASA Astrophysics Data System (ADS)

    Mattocks, Craig; Forbes, Cristina

    A new real-time, event-triggered storm surge prediction system has been developed for the State of North Carolina to assist emergency managers, policy-makers and other government officials with evacuation planning, decision-making and resource deployment during tropical storm landfall and flood inundation events. The North Carolina Forecast System (NCFS) was designed and built to provide a rapid response assessment of hurricane threat, accomplished by driving a high-resolution, two-dimensional, depth-integrated version of the ADCIRC (Advanced Circulation) coastal ocean model with winds from a synthetic asymmetric gradient wind vortex. These parametric winds, calculated at exact finite-element mesh node locations and directly coupled to the ocean model at every time step, are generated from National Hurricane Center (NHC) forecast advisories the moment they are inserted into the real-time weather data stream, maximizing the number of hours of forecast utility. Tidal harmonic constituents are prescribed at the open water boundaries and applied as tidal potentials in the interior of the ocean model domain. A directional surface roughness parameterization that modulates the wind speed at a given location based on the types of land cover encountered upwind, a forest canopy sheltering effect, and a spatially varying distribution of Manning's-n friction coefficient used for computing the bottom/channel bed friction are also included in the storm surge model. Comparisons of the simulated wind speeds and phases against their real meteorological counterparts, of model elevations against actual sea surface elevations measured by NOAA tide gauges along the NC coast, and of simulated depth-averaged current velocities against Acoustic Doppler Current Profiler (ADCP) data, indicate that this new system produces remarkably realistic predictions of winds and storm surge.

  13. [Real-time PCR Detection Method for the Reston Subtype of the Ebola Virus].

    PubMed

    Xu, Lili; Bao, Linlin; Gu, Songzhi; Qin, Chuan

    2015-05-01

    We aimed to develop a real-time polymerase chain reaction (PCR) detection method for the Reston subtype of the Ebola virus. The NP gene of the Reston subtype of the Ebola virus was selected as the detection object. Sequences of different subtypes of Ebola viruses were aligned using Clustal W software. The most unique and conserved regions of the Reston subtype of the Ebola virus were recruited as candidate sequences for specific primers. Primer Express and Primer Premier 5. 0 software were used to filter the optimal pair of primers for detection. Real-time PCR was carried out using optimized parameters and positive DNA prepared by serial (tenfold) dilution of a recombinant plasmid and by plotting a standard curve. In addition, the reproducibility, accuracy, and specificity of the assay were tested. Results showed that the sensitivity of detection of the Reston subtype of the Ebola virus by real-time PCR could reached 10(2) copies/microL. The linear relationship (R2) reached 0.997, the slope of the standard curve was -0.3101, and amplification efficiency was 110.145%. A sharp and narrow melting peak appeared at 79.94 degrees C for all standards in different dilutions. In conclusion, a fast and sensitive real-time PCR detection system for the Reston subtype of the Ebola virus was developed. This system could be used as a supplementary diagnostic and monitoring approach for basic and clinical studies on the Reston subtype of the Ebola virus. The detection system does not require expensive technology or specialist operators. PMID:26470534

  14. Testing the ability of different seismic detections approaches to monitor aftershocks following a moderate magnitude event.

    NASA Astrophysics Data System (ADS)

    Romero, Paula; Díaz, Jordi; Ruiz, Mario; Cantavella, Juan Vicente; Gomez-García, Clara

    2016-04-01

    The detection and picking of seismic events is a permanent concern for seismic surveying, in particular when dealing with aftershocks of moderate magnitude events. Many efforts have been done to find the balance between computer efficiency and the robustness of the detection methods. In this work, data recorded by a high density seismic network deployed following a 5.2 magnitude event located close to Albacete, SE Spain, is used to test the ability of classical and recently proposed detection methodologies. Two days after the main shock, occurred the 23th February, a network formed by 11 stations from ICTJA-CSIC and 2 stations from IGN were deployed over the region, with inter-station distances ranging between 5 and 10 km. The network remained in operation until April 6th, 2015 and allowed to manually identify up to 552 events with magnitudes from 0.2 to 3.5 located in an area of just 25 km2 inside the network limits. The detection methods here studied applied are the classical STA/LTA, a power spectral method, a detector based in the Benford's law and a waveform similarity method. The STA/LTA method, based in the comparison of background noise and seismic signal amplitudes, is taken as a reference to evaluate the results arising from the other approaches. The power spectral density method is based in the inspection of the characteristic frequency pattern associated to seismic events. The Benford's Law detector analyses the distribution of the first-digit of displacement count in the histogram of a seismic waveform, considering that only the windows containing seismic wave arrivals will match the logarithmic law. Finally, the waveform similarity method is based in the analysis of the normalized waveform amplitude, detecting those events with waveform similar to a previously defined master event. The aim of this contribution is to inspect the ability of the different approaches to accurately detect the aftershocks events for this kind of seismic crisis and to

  15. Detecting Continuity Violations in Infancy: A New Account and New Evidence from Covering and Tube Events

    ERIC Educational Resources Information Center

    Wang, S.h.; Baillargeon, R.; Paterson, S.

    2005-01-01

    Recent research on infants' responses to occlusion and containment events indicates that, although some violations of the continuity principle are detected at an early age e.g. Aguiar, A., & Baillargeon, R. (1999). 2.5-month-old infants' reasoning about when objects should and should not be occluded. Cognitive Psychology 39, 116-157; Hespos, S.…

  16. Integrated micro-optofluidic platform for real-time detection of airborne microorganisms.

    PubMed

    Choi, Jeongan; Kang, Miran; Jung, Jae Hee

    2015-01-01

    We demonstrate an integrated micro-optofluidic platform for real-time, continuous detection and quantification of airborne microorganisms. Measurements of the fluorescence and light scattering from single particles in a microfluidic channel are used to determine the total particle number concentration and the microorganism number concentration in real-time. The system performance is examined by evaluating standard particle measurements with various sample flow rates and the ratios of fluorescent to non-fluorescent particles. To apply this method to real-time detection of airborne microorganisms, airborne Escherichia coli, Bacillus subtilis, and Staphylococcus epidermidis cells were introduced into the micro-optofluidic platform via bioaerosol generation, and a liquid-type particle collection setup was used. We demonstrate successful discrimination of SYTO82-dyed fluorescent bacterial cells from other residue particles in a continuous and real-time manner. In comparison with traditional microscopy cell counting and colony culture methods, this micro-optofluidic platform is not only more accurate in terms of the detection efficiency for airborne microorganisms but it also provides additional information on the total particle number concentration. PMID:26522006

  17. Integrated micro-optofluidic platform for real-time detection of airborne microorganisms

    PubMed Central

    Choi, Jeongan; Kang, Miran; Jung, Jae Hee

    2015-01-01

    We demonstrate an integrated micro-optofluidic platform for real-time, continuous detection and quantification of airborne microorganisms. Measurements of the fluorescence and light scattering from single particles in a microfluidic channel are used to determine the total particle number concentration and the microorganism number concentration in real-time. The system performance is examined by evaluating standard particle measurements with various sample flow rates and the ratios of fluorescent to non-fluorescent particles. To apply this method to real-time detection of airborne microorganisms, airborne Escherichia coli, Bacillus subtilis, and Staphylococcus epidermidis cells were introduced into the micro-optofluidic platform via bioaerosol generation, and a liquid-type particle collection setup was used. We demonstrate successful discrimination of SYTO82-dyed fluorescent bacterial cells from other residue particles in a continuous and real-time manner. In comparison with traditional microscopy cell counting and colony culture methods, this micro-optofluidic platform is not only more accurate in terms of the detection efficiency for airborne microorganisms but it also provides additional information on the total particle number concentration. PMID:26522006

  18. Integrated micro-optofluidic platform for real-time detection of airborne microorganisms

    NASA Astrophysics Data System (ADS)

    Choi, Jeongan; Kang, Miran; Jung, Jae Hee

    2015-11-01

    We demonstrate an integrated micro-optofluidic platform for real-time, continuous detection and quantification of airborne microorganisms. Measurements of the fluorescence and light scattering from single particles in a microfluidic channel are used to determine the total particle number concentration and the microorganism number concentration in real-time. The system performance is examined by evaluating standard particle measurements with various sample flow rates and the ratios of fluorescent to non-fluorescent particles. To apply this method to real-time detection of airborne microorganisms, airborne Escherichia coli, Bacillus subtilis, and Staphylococcus epidermidis cells were introduced into the micro-optofluidic platform via bioaerosol generation, and a liquid-type particle collection setup was used. We demonstrate successful discrimination of SYTO82-dyed fluorescent bacterial cells from other residue particles in a continuous and real-time manner. In comparison with traditional microscopy cell counting and colony culture methods, this micro-optofluidic platform is not only more accurate in terms of the detection efficiency for airborne microorganisms but it also provides additional information on the total particle number concentration.

  19. European validation of Real-Time PCR method for detection of Salmonella spp. in pork meat.

    PubMed

    Delibato, Elisabetta; Rodriguez-Lazaro, David; Gianfranceschi, Monica; De Cesare, Alessandra; Comin, Damiano; Gattuso, Antonietta; Hernandez, Marta; Sonnessa, Michele; Pasquali, Frédérique; Sreter-Lancz, Zuzsanna; Saiz-Abajo, María-José; Pérez-De-Juan, Javier; Butrón, Javier; Prukner-Radovcic, Estella; Horvatek Tomic, Danijela; Johannessen, Gro S; Jakočiūnė, Džiuginta; Olsen, John E; Chemaly, Marianne; Le Gall, Francoise; González-García, Patricia; Lettini, Antonia Anna; Lukac, Maja; Quesne, Segolénè; Zampieron, Claudia; De Santis, Paola; Lovari, Sarah; Bertasi, Barbara; Pavoni, Enrico; Proroga, Yolande T R; Capuano, Federico; Manfreda, Gerardo; De Medici, Dario

    2014-08-01

    The classical microbiological method for detection of Salmonella spp. requires more than five days for final confirmation, and consequently there is a need for an alternative methodology for detection of this pathogen particularly in those food categories with a short shelf-life. This study presents an international (at European level) ISO 16140-based validation study of a non-proprietary Real-Time PCR-based method that can generate final results the day following sample analysis. It is based on an ISO compatible enrichment coupled to an easy and inexpensive DNA extraction and a consolidated Real-Time PCR assay. Thirteen laboratories from seven European Countries participated to this trial, and pork meat was selected as food model. The limit of detection observed was down to 10 CFU per 25 g of sample, showing excellent concordance and accordance values between samples and laboratories (100%). In addition, excellent values were obtained for relative accuracy, specificity and sensitivity (100%) when the results obtained for the Real-Time PCR-based methods were compared to those of the ISO 6579:2002 standard method. The results of this international trial demonstrate that the evaluated Real-Time PCR-based method represents an excellent alternative to the ISO standard. In fact, it shows an equal and solid performance as well as it reduces dramatically the extent of the analytical process, and can be easily implemented routinely by the Competent Authorities and Food Industry laboratories. PMID:24513055

  20. DNA detection of Clostridium difficile infection based on real-time resistance measurement.

    PubMed

    Liu, C; Jiang, D N; Xiang, G M; Luo, F K; Liu, L L; Yu, J C; Pu, X Y

    2013-01-01

    We used a newly developed electrochemical method, real-time resistance measurement, based on loop-mediated isothermal amplification (LAMP), with real-time resistance monitoring and derivative analysis. DNA extracted from specimens was amplified through LAMP reaction. The 2 products of LAMP, DNA and pyrophosphate, both are negative ions; they combine with positive dye (crystal violet) and positive ions (Mg(2+)), which leads to an increase in the resistivity of the reaction liquid. The changes of resistivity were measured in real-time with a specially designed resistance electrode, to detect Clostridium difficile DNA. We found that electrochemical detection of C. difficile could be completed in 0.5-1 h, with a detection limit of 10(2) CFU/mL, with high accuracy (95.0%), sensitivity (91.1%), and specificity (97.3%) compared to PCR methods. C. difficile is commonly associated with antibiotic-induced diarrhea. Due to the difficulty in performing anaerobic culture and cytotoxicity neutralization assays, a simple, rapid, sensitive, and accurate method is preferred. We conclude that real-time resistance measurement is a rapid, sensitive, and stable method for the diagnosis of C. difficile infection that could be applied to gene chips and pocket instruments. PMID:24065671

  1. Development and Application of Real-Time PCR for Detection of Subgroup J Avian Leukosis Virus

    PubMed Central

    Qin, Liting; Gao, Yulong; Ni, Wei; Sun, Meiyu; Wang, Yongqiang; Yin, Chunhong; Qi, Xiaole; Gao, Honglei

    2013-01-01

    Subgroup J avian leukosis virus (ALV-J) is an avian retrovirus that causes severe economic losses in the poultry industry. The early identification and removal of virus-shedding birds are important to reduce the spread of congenital and contact infections. In this study, a TaqMan-based real-time PCR method for the rapid detection and quantification of ALV-J with proviral DNA was developed. This method exhibited a high specificity for ALV-J. Moreover, the detection limit was as low as 10 viral DNA copies. The coefficients of variation (CVs) of both interassay and intra-assay reproducibility were less than 1%. The growth curves of ALV-J in DF-1 cells were measured by real-time PCR, yielding a trend line similar to those determined by 50% tissue culture infective dose (TCID50) and p27 antigen detection. Tissue samples suspected of ALV infection were evaluated using real-time PCR, virus isolation, and routine PCR, and the positivity rates were 60.1%, 41.6% and 44.5%, respectively. Our data indicated that the real-time PCR method provides a sensitive, specific, and reproducible diagnostic tool for the identification and quantification of ALV-J for clinical diagnosis and in laboratory research. PMID:23100340

  2. Real-time target detection in hyperspectral images based on spatial-spectral information extraction

    NASA Astrophysics Data System (ADS)

    Zhang, Bing; Yang, Wei; Gao, Lianru; Chen, Dongmei

    2012-12-01

    Recently, real-time image data processing is a popular research area for hyperspectral remote sensing. In particular, target detection surveillance, which is an important military application of hyperspectral remote sensing, demands real-time or near real-time processing. The massive amount of hyperspectral image data seriously limits the processing speed. In this article, a strategy named spatial-spectral information extraction (SSIE) is presented to accelerate hyperspectral image processing. SSIE is composed of band selection and sample covariance matrix estimation. Band selection fully utilizes the high-spectral correlation in spectral image, while sample covariance matrix estimation fully utilizes the high-spatial correlation in remote sensing image. To overcome the inconsistent and irreproducible shortage of random distribution, we present an effective scalar method to select sample pixels. Meanwhile, we have implemented this target detection algorithm based on the SSIE strategy on the hardware of a digital signal processor (DSP). The implementation of a constrained energy minimization algorithm is composed of hardware and software architectures. The hardware architecture contains chips and peripheral interfaces, while software architecture contains a data transferring model. In the experiments, we compared the performance of hardware of DSP with that of Environment for Visualizing Images software. DSP speed up the data processing and also results in more effective in terms of recognition rate, which demonstrate that the SSIE implemented by DSP is sufficient to enable near real-time supervised target detection.

  3. Fast joint detection-estimation of evoked brain activity in event-related FMRI using a variational approach

    PubMed Central

    Chaari, Lotfi; Vincent, Thomas; Forbes, Florence; Dojat, Michel; Ciuciu, Philippe

    2013-01-01

    In standard within-subject analyses of event-related fMRI data, two steps are usually performed separately: detection of brain activity and estimation of the hemodynamic response. Because these two steps are inherently linked, we adopt the so-called region-based Joint Detection-Estimation (JDE) framework that addresses this joint issue using a multivariate inference for detection and estimation. JDE is built by making use of a regional bilinear generative model of the BOLD response and constraining the parameter estimation by physiological priors using temporal and spatial information in a Markovian model. In contrast to previous works that use Markov Chain Monte Carlo (MCMC) techniques to sample the resulting intractable posterior distribution, we recast the JDE into a missing data framework and derive a Variational Expectation-Maximization (VEM) algorithm for its inference. A variational approximation is used to approximate the Markovian model in the unsupervised spatially adaptive JDE inference, which allows automatic fine-tuning of spatial regularization parameters. It provides a new algorithm that exhibits interesting properties in terms of estimation error and computational cost compared to the previously used MCMC-based approach. Experiments on artificial and real data show that VEM-JDE is robust to model mis-specification and provides computational gain while maintaining good performance in terms of activation detection and hemodynamic shape recovery. PMID:23096056

  4. Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field.

    PubMed

    Jeong, Myeong-Hun; Duckham, Matt

    2015-01-01

    This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes' coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks. PMID:26343672

  5. Efficient, Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field

    PubMed Central

    Jeong, Myeong-Hun; Duckham, Matt

    2015-01-01

    This paper describes an efficient, decentralized algorithm to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field. Four fundamental types of event (appearance, disappearance, movement and switch) are defined. Our algorithm is designed to rely purely on qualitative information about the neighborhoods of nodes in the sensor network and does not require information about nodes’ coordinate positions. Experimental investigations confirm that our algorithm is efficient, with O(n) overall communication complexity (where n is the number of nodes in the sensor network), an even load balance and low operational latency. The accuracy of event detection is comparable to established centralized algorithms for the identification of critical points of a surface network. Our algorithm is relevant to a broad range of environmental monitoring applications of sensor networks. PMID:26343672

  6. Species-specific real-time PCR assay for the detection of Streptococcus suis from clinical specimens.

    PubMed

    Srinivasan, Velusamy; McGee, Lesley; Njanpop-Lafourcade, Berthe-Marie; Moïsi, Jennifer; Beall, Bernard

    2016-06-01

    A real-time polymerase chain reaction was developed to detect all known strains of Streptococcus suis. The assay was highly specific, and sensitivity was <10 copies/assay for S. suis detection from clinical samples. PMID:27041105

  7. Post-event processing in social anxiety disorder after real-life social situations - An ambulatory assessment study.

    PubMed

    Helbig-Lang, Sylvia; von Auer, Maxie; Neubauer, Karolin; Murray, Eileen; Gerlach, Alexander L

    2016-09-01

    Excessive post-mortem processing after social situations, a core symptom of social anxiety disorder (SAD), is thought to contribute to the perpetuation of social anxiety by consolidating negative self-schemata. Empirical findings on actual mechanisms underlying this so-called Post-Event Processing (PEP) are still scarce. The present study sought to identify variables associated with the experience of PEP after real-life social situations in a sample of 49 individuals diagnosed with SAD. Using an ambulatory assessment approach, individuals were asked to report on each distressing social event experienced during one week. A total of 192 events were captured. Hierarchical linear modeling indicated that next to trait social anxiety, the type of social situation (performance vs. interaction situations), self-focused attention, safety behavior use, and negative affect predicted levels of PEP after social situations. These findings add to the growing literature that emphasizes the importance of situational factors for the experience of PEP, and highlight potential venues to prevent it. PMID:27442226

  8. High-rate real-time GPS network at Parkfield: Utility for detecting fault slip and seismic displacements

    USGS Publications Warehouse

    Langbein, J.; Bock, Y.

    2004-01-01

    A network of 13 continuous GPS stations near Parkfield, California has been converted from 30 second to 1 second sampling with positions of the stations estimated in real-time relative to a master station. Most stations are near the trace of the San Andreas fault, which exhibits creep. The noise spectra of the instantaneous 1 Hz positions show flicker noise at high frequencies and change to frequency independence at low frequencies; the change in character occurs between 6 to 8 hours. Our analysis indicates that 1-second sampled GPS can estimate horizontal displacements of order 6 mm at the 99% confidence level from a few seconds to a few hours. High frequency GPS can augment existing measurements in capturing large creep events and postseismic slip that would exceed the range of existing creepmeters, and can detect large seismic displacements. Copyright 2004 by the American Geophysical Union.

  9. Development of highly sensitive handheld device for real-time detection of bacteria in food

    NASA Astrophysics Data System (ADS)

    Zhang, Kewei; Zhang, Anxue; Fu, Liling; Chin, Bryan A.; Cheng, Z.-Y.

    2010-04-01

    To ensure the safety of food, a detection device, which can detect/monitor the present of bacteria in a real-time manner and can be easily used for in-field tests, is highly desirable. Recently, magnetostrictive particles (MSPs) as a new type of high-performance biosensor have been developed. The detection of various bacteria and spores in food with high sensitivity has already been experimentally demonstrated. To fully use the technique for food safety, two miniaturized interrogation systems based on frequency-domain and time-domain technique are developed to fabricate a handheld detection device. The detection of Salmonella typhimurium (S. typhimurium) in liquid using a time-domain based interrogation system was demonstrated.

  10. Detection, tracking and event localization of interesting features in 4-D atmospheric data

    NASA Astrophysics Data System (ADS)

    Limbach, S.; Schömer, E.; Wernli, H.

    2011-11-01

    We introduce a novel algorithm for the efficient detection and tracking of interesting features in spatial-temporal atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. The algorithm is based on the well-known region growing segmentation method. We extended the basic idea towards the analysis of the complete 4-D dataset, identifying segments representing the spatial features and their development over time. Each segment consists of one set of distinct 3-D features per time step. The algorithm keeps track of the successors of each 3-D feature, constructing the so-called event graph of each segment. The precise localization of the splitting events is based on a search for all grid points inside the initial 3-D feature which have a similar distance to all successive 3-D features of the next time step. The merging event is localized analogously considering inverted direction of time. We tested the implementation on a four-dimensional field of wind speed data from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses and computed a climatology of upper-tropospheric jet streams and their events. We compare our results with a previous climatology, investigate the statistical distribution of the merging and splitting events, and illustrate the meteorological significance of the jet splitting events with a case study. A brief outlook is given on additional potential applications of the 4-D data segmentation technique.

  11. Molecular detection of Puccinia horiana in Chrysanthemum x morifolium through conventional and real-time PCR.

    PubMed

    Alaei, Hossein; Baeyen, Steve; Maes, Martine; Höfte, Monica; Heungens, Kurt

    2009-02-01

    Puccinia horiana Henn. is a quarantine organism and one of the most important fungal pathogens of Chrysanthemum x morifolium cultivars grown for cut flower or potted plant production (florist's chrysanthemum) in several regions of the world. Highly specific primer pairs were identified for conventional, nested, and real-time PCR detection of P. horiana based on the specific and sensitive PCR amplification of selected regions in the internal transcribed spacers (ITS1 and ITS2) of the nuclear ribosomal DNA (rDNA). Using these different PCR versions, 10 pg, 10 fg, and 5 fg genomic DNA could be detected, respectively. When using cloned target DNA as template, the detection limits were 5000, 50, and 5 target copies, respectively. These detection limits were not affected by a background of chrysanthemum plant DNA. The DNA extraction method was optimized to maximize the recoverability of the pathogen from infected plant tissue. A CTAB extraction protocol or a selection of commercial DNA extraction methods allowed the use of 10 ng total (plant+pathogen) DNA without interference of PCR inhibitors. Due to the specificity of the primers, SYBR Green I technology enabled reliable real time PCR signal detection. However, an efficient TaqMan probe is available. The lowest proportion of infected plant material that could still be detected when mixed with healthy plant material was 0.001%. The real-time PCR assay could detect as few as eight pure P. horiana basidiospores, demonstrating the potential of the technique for aerial detection of the pathogen. The amount of P. horiana DNA in plant tissue was determined at various time points after basidiospore inoculation. Using the real-time PCR protocol, it was possible to detect the pathogen immediately after the inoculation period, even though the accumulation of pathogen DNA was most pronounced near the end of the latent period. The detection system proved to be accurate and sensitive and could help not only in pathogen diagnosis but

  12. Line-scan hyperspectral imaging for real-time poultry fecal detection

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Yoon, Seung-Chul; Windham, William R.; Lawrence, Kurt C.; Heitschmidt, G. W.; Kim, Moon S.; Chao, Kaunglin

    2010-04-01

    The ARS multispectral imaging system with three-band common aperture camera was able to inspect fecal contaminants in real-time mode during poultry processing. Recent study has demonstrated several image processing methods including binning, cuticle removal filter, median filter, and morphological analysis in real-time mode could remove false positive errors. The ARS research groups and their industry partner are now merging the fecal detection and systemically disease detection systems onto a common platform using line-scan hyperspectral imaging system. This system will aid in commercialization by creating one hyperspectral imaging system with user-defined wavelengths that can be installed in different locations of the processing line to solve significant food safety problems. Therefore, this research demonstrated the feasibility of line-scan hyperspectral imaging system in terms of processing speed and detection accuracy for a real-time, on-line fecal detection at current processing speed (140 birds per minute) of commercial poultry plant. The newly developed line-scan hyperspectral imaging system could improve Food Safety Inspection Service (FSIS)'s poultry safety inspection program significantly.

  13. Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

    PubMed Central

    Akram, M. Usman; Khan, Shoab A.; Javed, Muhammad Younus

    2014-01-01

    National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. PMID:25136674

  14. Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection

    PubMed Central

    Olson, Sarah H.; Benedum, Corey M.; Mekaru, Sumiko R.; Preston, Nicholas D.; Mazet, Jonna A.K.; Joly, Damien O.

    2015-01-01

    The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data. PMID:26196106

  15. Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection.

    PubMed

    Olson, Sarah H; Benedum, Corey M; Mekaru, Sumiko R; Preston, Nicholas D; Mazet, Jonna A K; Joly, Damien O; Brownstein, John S

    2015-08-01

    The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data. PMID:26196106

  16. Multiple Influences of Semantic Memory on Sentence Processing: Distinct Effects of Semantic Relatedness on Violations of Real-World Event/State Knowledge and Animacy Selection Restrictions

    ERIC Educational Resources Information Center

    Paczynski, Martin; Kuperberg, Gina R.

    2012-01-01

    We aimed to determine whether semantic relatedness between an incoming word and its preceding context can override expectations based on two types of stored knowledge: real-world knowledge about the specific events and states conveyed by a verb, and the verb's broader selection restrictions on the animacy of its argument. We recorded event-related…

  17. Talking about Real-Life Events: An Investigation into the Ability of People with Intellectual Disabilities to Make Links between Their Beliefs and Emotions within Dialogue

    ERIC Educational Resources Information Center

    Hebblethwaite, Amy; Jahoda, Andrew; Dagnan, Dave

    2011-01-01

    Background: This study compares how people with and without intellectual disabilities talk about events, beliefs and emotions in dialogues about real-life, emotive events and in a structured task assessing understanding of cognitive mediation. Materials and Methods: A cognitive-emotive interview was used to assist 19 adults with intellectual…

  18. Sparse conditional mixture model: late fusion with missing scores for multimedia event detection

    NASA Astrophysics Data System (ADS)

    Nallapati, Ramesh; Yeh, Eric; Myers, Gregory

    2013-03-01

    The problem of event detection in multimedia clips is typically handled by modeling each of the component modalities independently, then combining their detection scores in a late fusion approach. One of the problems of a late fusion model in the multimedia setting is that the detection scores may be missing from one or more components for a given clip; e.g., when there is no speech in the clip; or when there is no overlay text. Standard fusion techniques typically address this problem by assuming a default backoff score for a component when its detection score is missing for a clip. This may potentially bias the fusion model, especially if there are many missing detections from a given component. In this work, we present the Sparse Conditional Mixture Model (SCMM) which models only the observed detection scores for each example, thereby avoiding making any assumptions about the distributions of the scores that are made by backoff models. Our experiments in multi-media event detection using the TRECVID-2011 corpus demonstrates that SCMM achieves statistically significant performance gains over standard late fusion techniques. The SCMM model is very general and is applicable to fusion problems with missing data in any domain.

  19. Mass detection on real and synthetic mammograms: human observer templates and local statistics

    NASA Astrophysics Data System (ADS)

    Castella, Cyril; Kinkel, Karen; Verdun, Francis R.; Eckstein, Miguel P.; Abbey, Craig K.; Bochud, François O.

    2007-03-01

    In this study we estimated human observer templates associated with the detection of a realistic mass signal superimposed on real and simulated but realistic synthetic mammographic backgrounds. Five trained naÃve observers participated in two-alternative forced-choice (2-AFC) experiments in which they were asked to detect a spherical mass signal extracted from a mammographic phantom. This signal was superimposed on statistically stationary clustered lumpy backgrounds (CLB) in one instance, and on nonstationary real mammographic backgrounds in another. Human observer linear templates were estimated using a genetic algorithm. An additional 2-AFC experiment was conducted with twin noise in order to determine which local statistical properties of the real backgrounds influenced the ability of the human observers to detect the signal. Results show that the estimated linear templates are not significantly different for stationary and nonstationary backgrounds. The estimated performance of the linear template compared with the human observer is within 5% in terms of percent correct (Pc) for the 2-AFC task. Detection efficiency is significantly higher on nonstationary real backgrounds than on globally stationary synthetic CLB. Using the twin-noise experiment and a new method to relate image features to observers trial to trial decisions, we found that the local statistical properties preventing or making the detection task easier were the standard deviation and three features derived from the neighborhood gray-tone difference matrix: coarseness, contrast and strength. These statistical features showed a dependency with the human performance only when they are estimated within an area sufficiently small around the searched location. These findings emphasize that nonstationary backgrounds need to be described by their local statistics and not by global ones like the noise Wiener spectrum.

  20. Real-time detection of lipid bilayer assembly and detergent-initiated solubilization using optical cavities

    NASA Astrophysics Data System (ADS)

    Sun, V.; Armani, A. M.

    2015-02-01

    The cellular membrane governs numerous fundamental biological processes. Therefore, developing a comprehensive understanding of its structure and function is critical. However, its inherent biological complexity gives rise to numerous inter-dependent physical phenomena. In an attempt to develop a model, two different experimental approaches are being pursued in parallel: performing single cell experiments (top down) and using biomimetic structures (bottom up), such as lipid bilayers. One challenge in many of these experiments is the reliance on fluorescent probes for detection which can create confounds in this already complex system. In the present work, a label-free detection method based on an optical resonant cavity is used to detect one of the fundamental physical phenomena in the system: assembly and solubilization of the lipid bilayer. The evanescent field of the cavity strongly interacts with the lipid bilayer, enabling the detection of the bilayer behavior in real-time. Two independent detection mechanisms confirm the formation and detergent-assisted solubilization of the lipid bilayers: (1) a refractive index change and (2) a material loss change. Both mechanisms can be monitored in parallel, on the same device, thus allowing for cross-confirmation of the results. To verify the proposed method, we have detected the formation of self-assembled phosphatidylcholine lipid bilayers from small unilamellar vesicles on the device surface in real-time. Subsequently, we exposed the bilayers to two different detergents (non-ionic Triton X-100 and anionic sodium dodecyl sulfate) to initiate solubilization, and this process was also detected in real-time. After the bilayer solubilization, the device returned to its initial state, exhibiting minimal hysteresis. The experimental wash-off was also collected and analyzed using dynamic light scattering.

  1. Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.

    2012-01-01

    This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

  2. Event Detection and Location of Earthquakes Using the Cascadia Initiative Dataset

    NASA Astrophysics Data System (ADS)

    Morton, E.; Bilek, S. L.; Rowe, C. A.

    2015-12-01

    The Cascadia subduction zone (CSZ) produces a range of slip behavior along the plate boundary megathrust, from great earthquakes to episodic slow slip and tremor (ETS). Unlike other subduction zones that produce great earthquakes and ETS, the CSZ is notable for the lack of small and moderate magnitude earthquakes recorded. The seismogenic zone extent is currently estimated to be primarily offshore, thus the lack of observed small, interplate earthquakes may be partially due to the use of only land seismometers. The Cascadia Initiative (CI) community seismic experiment seeks to address this issue by including ocean bottom seismometers (OBS) deployed directly over the locked seismogenic zone, in addition to land seismometers. We use these seismic data to explore whether small magnitude earthquakes are occurring on the plate interface, but have gone undetected by the land-based seismic networks. We select a subset of small magnitude (M0.1-3.7) earthquakes from existing earthquake catalogs, based on land seismic data, whose preliminary hypocentral locations suggest they may have occurred on the plate interface. We window the waveforms on CI OBS and land seismometers around the phase arrival times for these earthquakes to generate templates for subspace detection, which allows for additional flexibility over traditional matched filter detection methods. Here we present event detections from the first year of CI deployment and preliminary locations for the detected events. Initial results of scanning the first year of the CI deployment using one cluster of template events, located near a previously identified subducted seamount, include 473 detections on OBS station M08A (~61.6 km offshore) and 710 detections on OBS station J25A (~44.8 km northeast of M08A). Ongoing efforts include detection using additional OBS stations along the margin, as well as determining locations of clusters detected in the first year of deployment.

  3. Real-time automatic small infrared target detection using local spectral filtering in the frequency

    NASA Astrophysics Data System (ADS)

    Chen, Hao; Zhang, Hong; Li, Jiafeng; Yuan, Ding; Sun, Mingui

    2014-11-01

    Accurate and fast detection of small infrared target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanism, an automatic detection algorithm for small infrared target is presented. In this paper, instead of searching for infrared targets, we model regular patches that do not attract much attention by our visual system. This is inspired by the property that the regular patches in spatial domain turn out to correspond to the spikes in the amplitude spectrum. Unlike recent approaches using global spectral filtering, we define the concept of local maxima suppression using local spectral filtering to smooth the spikes in the amplitude spectrum, thereby producing the pop-out of the infrared targets. In the proposed method, we firstly compute the amplitude spectrum of an input infrared image. Second, we find the local maxima of the amplitude spectrum using cubic facet model. Third, we suppress the local maxima using the convolution of the local spectrum with a low-pass Gaussian kernel of an appropriate scale. At last, the detection result in spatial domain is obtained by reconstructing the 2D signal using the original phase and the log amplitude spectrum by suppressing local maxima. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be further used for real-time detection and tracking.

  4. Real-time multiple plane area detection using a self-organizing map

    NASA Astrophysics Data System (ADS)

    Kim, Jeong-Hyun; Teng, Zhu; Kang, Dong-Joong

    2012-01-01

    Plane detection in 3-D space is a core function of the autonomous mobile robot. A representative technique for plane detection is the Hough transform method. The Hough transform is robust to noise and makes accurate plane detection possible. However, a common problem in methods based on the Hough transform is that too much time is required to calculate parameters, which adds computational cost and memory requirements for parameter voting to find the distribution of mixed multiple planes in the parameter space. Furthermore, real-time processing for sequential image sequences is challenging, because the whole process must be repetitively performed for the next detection. We extend the conventional self-organizing map by introducing a real-time clustering method and by detecting multiple planes through the creation, extinction, renewal, and merging of plane parameter data, which are input sequentially. The proposed method is also based on reliable plane detection through a planarity evaluation during data sampling. The results of experiments conducted under various conditions with an unmanned vehicle demonstrate that the proposed method is more accurate and faster than conventional methods.

  5. Real-time detection of generic objects using objectness estimation and locally adaptive regression kernels matching

    NASA Astrophysics Data System (ADS)

    Zheng, Zhihui; Gao, Lei; Xiao, Liping; Zhou, Bin; Gao, Shibo

    2015-12-01

    Our purpose is to develop a detection algorithm capable of searching for generic interest objects in real time without large training sets and long-time training stages. Instead of the classical sliding window object detection paradigm, we employ an objectness measure to produce a small set of candidate windows efficiently using Binarized Normed Gradients and a Laplacian of Gaussian-like filter. We then extract Locally Adaptive Regression Kernels (LARKs) as descriptors both from a model image and the candidate windows which measure the likeness of a pixel to its surroundings. Using a matrix cosine similarity measure, the algorithm yields a scalar resemblance map, indicating the likelihood of similarity between the model and the candidate windows. By employing nonparametric significance tests and non-maxima suppression, we detect the presence of objects similar to the given model. Experiments show that the proposed detection paradigm can automatically detect the presence, the number, as well as location of similar objects to the given model. The high quality and efficiency of our method make it suitable for real time multi-category object detection applications.

  6. Real-time discriminatory sensors for water contamination events :LDRD 52595 final report.

    SciTech Connect

    Borek, Theodore Thaddeus III; Carrejo-Simpkins, Kimberly; Wheeler, David Roger; Adkins, Douglas Ray; Robinson, Alex Lockwood; Irwin, Adriane Nadine; Lewis, Patrick Raymond; Goodin, Andrew M.; Shelmidine, Gregory J.; Dirk, Shawn M.; Chambers, William Clayton; Mowry, Curtis Dale; Showalter, Steven Kedrick

    2005-10-01

    The gas-phase {mu}ChemLab{trademark} developed by Sandia can detect volatile organics and semi-volatiles organics via gas phase sampling . The goal of this three year Laboratory Directed Research and Development (LDRD) project was to adapt the components and concepts used by the {mu}ChemLab{trademark} system towards the analysis of water-borne chemicals of current concern. In essence, interfacing the gas-phase {mu}ChemLab{trademark} with water to bring the significant prior investment of Sandia and the advantages of microfabrication and portable analysis to a whole new world of important analytes. These include both chemical weapons agents and their hydrolysis products and disinfection by-products such as Trihalomethanes (THMs) and haloacetic acids (HAAs). THMs and HAAs are currently regulated by EPA due to health issues, yet water utilities do not have rapid on-site methods of detection that would allow them to adjust their processes quickly; protecting consumers, meeting water quality standards, and obeying regulations more easily and with greater confidence. This report documents the results, unique hardware and devices, and methods designed during the project toward the goal stated above. It also presents and discusses the portable field system to measure THMs developed in the course of this project.

  7. Event-related potential signatures of perceived and imagined emotional and food real-life photos.

    PubMed

    Marmolejo-Ramos, Fernando; Hellemans, Kim; Comeau, Amy; Heenan, Adam; Faulkner, Andrew; Abizaid, Alfonso; D'Angiulli, Amedeo

    2015-06-01

    Although food and affective pictures share similar emotional and motivational characteristics, the relationship between the neuronal responses to these stimuli is unclear. Particularly, it is not known whether perceiving and imagining food and affective stimuli elicit similar event-related potential (ERP) patterns. In this study, two ERP correlates, the early posterior negativity (EPN) and the late positive potential (LPP) for perceived and imagined emotional and food photographs were investigated. Thirteen healthy volunteers were exposed to a set of food photos, as well as unpleasant, pleasant, and neutral photos from the International Affective Picture System. In each trial, participants were first asked to view a photo (perception condition), and then to create a visual mental image of it and to rate its vividness (imagery condition). The results showed that during perception, brain regions corresponding to sensorimotor and parietal motivational (defensive and appetitive) systems were activated to different extents, producing a graded pattern of EPN and LPP responses specific to the photo content - more prominent for unpleasant than pleasant and food content. Also, an EPN signature occurred in both conditions for unpleasant content, suggesting that, compared to food or pleasant content, unpleasant content may be attended to more intensely during perception and may be represented more distinctly during imagery. Finally, compared to LLP activation during perception, as well as imagery and perception of all other content, LPP activation was significantly reduced during imagery of unpleasant photos, suggesting inhibition of unwanted memories. Results are framed within a neurocognitive working model of embodied emotions. PMID:25895000

  8. Multiplex polymerase chain reaction-capillary gel electrophoresis: a promising tool for GMO screening--assay for simultaneous detection of five genetically modified cotton events and species.

    PubMed

    Nadal, Anna; Esteve, Teresa; Pla, Maria

    2009-01-01

    A multiplex polymerase chain reaction assay coupled to capillary gel electrophoresis for amplicon identification by size and color (multiplex PCR-CGE-SC) was developed for simultaneous detection of cotton species and 5 events of genetically modified (GM) cotton. Validated real-time-PCR reactions targeting Bollgard, Bollgard II, Roundup Ready, 3006-210-23, and 281-24-236 junction sequences, and the cotton reference gene acp1 were adapted to detect more than half of the European Union-approved individual or stacked GM cotton events in one reaction. The assay was fully specific (<1.7% of false classification rate), with limit of detection values of 0.1% for each event, which were also achieved with simulated mixtures at different relative percentages of targets. The assay was further combined with a second multiplex PCR-CGE-SC assay to allow simultaneous detection of 6 cotton and 5 maize targets (two endogenous genes and 9 GM events) in two multiplex PCRs and a single CGE, making the approach more economic. Besides allowing simultaneous detection of many targets with adequate specificity and sensitivity, the multiplex PCR-CGE-SC approach has high throughput and automation capabilities, while keeping a very simple protocol, e.g., amplification and labeling in one step. Thus, it is an easy and inexpensive tool for initial screening, to be complemented with quantitative assays if necessary. PMID:19610365

  9. Detection, tracking and event localization of jet stream features in 4-D atmospheric data

    NASA Astrophysics Data System (ADS)

    Limbach, S.; Schömer, E.; Wernli, H.

    2012-04-01

    We introduce a novel algorithm for the efficient detection and tracking of features in spatiotemporal atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. The algorithm works on data given on a four-dimensional structured grid. Feature selection and clustering are based on adjustable local and global criteria, feature tracking is predominantly based on spatial overlaps of the feature's full volumes. The resulting 3-D features and the identified correspondences between features of consecutive time steps are represented as the nodes and edges of a directed acyclic graph, the event graph. Merging and splitting events appear in the event graph as nodes with multiple incoming or outgoing edges, respectively. The precise localization of the splitting events is based on a search for all grid points inside the initial 3-D feature that have a similar distance to two successive 3-D features of the next time step. The merging event is localized analogously, operating backward in time. As a first application of our method we present a climatology of upper-tropospheric jet streams and their events, based on four-dimensional wind speed data from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. We compare our results with a climatology from a previous study, investigate the statistical distribution of the merging and splitting events, and illustrate the meteorological significance of the jet splitting events with a case study. A brief outlook is given on additional potential applications of the 4-D data segmentation technique.

  10. Signal Detection of Adverse Drug Reaction of Amoxicillin Using the Korea Adverse Event Reporting System Database.

    PubMed

    Soukavong, Mick; Kim, Jungmee; Park, Kyounghoon; Yang, Bo Ram; Lee, Joongyub; Jin, Xue Mei; Park, Byung Joo

    2016-09-01

    We conducted pharmacovigilance data mining for a β-lactam antibiotics, amoxicillin, and compare the adverse events (AEs) with the drug labels of 9 countries including Korea, USA, UK, Japan, Germany, Swiss, Italy, France, and Laos. We used the Korea Adverse Event Reporting System (KAERS) database, a nationwide database of AE reports, between December 1988 and June 2014. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-AE pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was defined as a signal. The KAERS database contained a total of 807,582 AE reports, among which 1,722 reports were attributed to amoxicillin. Among the 192,510 antibiotics-AE pairs, the number of amoxicillin-AE pairs was 2,913. Among 241 AEs, 52 adverse events were detected as amoxicillin signals. Comparing the drug labels of 9 countries, 12 adverse events including ineffective medicine, bronchitis, rhinitis, sinusitis, dry mouth, gastroesophageal reflux, hypercholesterolemia, gastric carcinoma, abnormal crying, induration, pulmonary carcinoma, and influenza-like symptoms were not listed on any of the labels of nine countries. In conclusion, we detected 12 new signals of amoxicillin which were not listed on the labels of 9 countries. Therefore, it should be followed by signal evaluation including causal association, clinical significance, and preventability. PMID:27510377

  11. Signal Detection of Adverse Drug Reaction of Amoxicillin Using the Korea Adverse Event Reporting System Database

    PubMed Central

    2016-01-01

    We conducted pharmacovigilance data mining for a β-lactam antibiotics, amoxicillin, and compare the adverse events (AEs) with the drug labels of 9 countries including Korea, USA, UK, Japan, Germany, Swiss, Italy, France, and Laos. We used the Korea Adverse Event Reporting System (KAERS) database, a nationwide database of AE reports, between December 1988 and June 2014. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-AE pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was defined as a signal. The KAERS database contained a total of 807,582 AE reports, among which 1,722 reports were attributed to amoxicillin. Among the 192,510 antibiotics-AE pairs, the number of amoxicillin-AE pairs was 2,913. Among 241 AEs, 52 adverse events were detected as amoxicillin signals. Comparing the drug labels of 9 countries, 12 adverse events including ineffective medicine, bronchitis, rhinitis, sinusitis, dry mouth, gastroesophageal reflux, hypercholesterolemia, gastric carcinoma, abnormal crying, induration, pulmonary carcinoma, and influenza-like symptoms were not listed on any of the labels of nine countries. In conclusion, we detected 12 new signals of amoxicillin which were not listed on the labels of 9 countries. Therefore, it should be followed by signal evaluation including causal association, clinical significance, and preventability. PMID:27510377

  12. Comparison of different real-time PCR chemistries and their suitability for detection and quantification of genetically modified organisms

    PubMed Central

    Buh Gašparič, Meti; Cankar, Katarina; Žel, Jana; Gruden, Kristina

    2008-01-01

    Background The real-time polymerase chain reaction is currently the method of choice for quantifying nucleic acids in different DNA based quantification applications. It is widely used also for detecting and quantifying genetically modified components in food and feed, predominantly employing TaqMan® and SYBR® Green real-time PCR chemistries. In our study four alternative chemistries: Lux™, Plexor™, Cycling Probe Technology and LNA® were extensively evaluated and compared using TaqMan® chemistry as a reference system. Results Amplicons were designed on the maize invertase gene and the 5'-junction of inserted transgene and plant genomic DNA in MON 810 event. Real-time assays were subsequently compared for their efficiency in PCR amplification, limits of detection and quantification, repeatability and accuracy to test the performance of the assays. Additionally, the specificity of established assays was checked on various transgenic and non-transgenic plant species. The overall applicability of the designed assays was evaluated, adding practicability and costs issues to the performance characteristics. Conclusion Although none of the chemistries significantly outperformed the others, there are certain characteristics that suggest that LNA® technology is an alternative to TaqMan® when designing assays for quantitative analysis. Because LNA® probes are much shorter they might be especially appropriate when high specificity is required and where the design of a common TaqMan® probe is difficult or even impossible due to sequence characteristics. Plexor™ on the other hand might be a method of choice for qualitative analysis when sensitivity, low cost and simplicity of use prevail. PMID:18325084

  13. Real-time prediction of acute cardiovascular events using hardware-implemented Bayesian networks.

    PubMed

    Tylman, Wojciech; Waszyrowski, Tomasz; Napieralski, Andrzej; Kamiński, Marek; Trafidło, Tamara; Kulesza, Zbigniew; Kotas, Rafał; Marciniak, Paweł; Tomala, Radosław; Wenerski, Maciej

    2016-02-01

    This paper presents a decision support system that aims to estimate a patient׳s general condition and detect situations which pose an immediate danger to the patient׳s health or life. The use of this system might be especially important in places such as accident and emergency departments or admission wards, where a small medical team has to take care of many patients in various general conditions. Particular stress is laid on cardiovascular and pulmonary conditions, including those leading to sudden cardiac arrest. The proposed system is a stand-alone microprocessor-based device that works in conjunction with a standard vital signs monitor, which provides input signals such as temperature, blood pressure, pulseoxymetry, ECG, and ICG. The signals are preprocessed and analysed by a set of artificial intelligence algorithms, the core of which is based on Bayesian networks. The paper focuses on the construction and evaluation of the Bayesian network, both its structure and numerical specification. PMID:26456181

  14. Ultra-rapid real-time PCR for the detection of Paenibacillus larvae, the causative agent of American Foulbrood (AFB).

    PubMed

    Han, Sang-Hoon; Lee, Do-Bu; Lee, Dong-Woo; Kim, Eul-Hwan; Yoon, Byoung-Su

    2008-09-01

    A novel micro-PCR-based detection method, termed ultra-rapid real-time PCR, was applied to the development of a rapid detection for Paenibacillus larvae (P. larvae) which is the causative agent of American Foulbrood (AFB). This method was designed to detect the 16S rRNA gene of P. larvae with a micro-scale chip-based real-time PCR system, GenSpector TMC-1000, which has uncommonly fast heating and cooling rates (10 degrees C per second) and small reaction volume (6microl). In the application of ultra-rapid real-time PCR detection to an AFB-infected larva, the minimum detection time was 7 min and 54s total reaction time (30 cycles), including the melting temperature analysis. To the best of our knowledge, this novel detection method is one of the most rapid real-time PCR-based detection tools. PMID:18571197

  15. Adaptive error detection for HDR/PDR brachytherapy: Guidance for decision making during real-time in vivo point dosimetry

    SciTech Connect

    Kertzscher, Gustavo Andersen, Claus E.; Tanderup, Kari

    2014-05-15

    Purpose: This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction of the dosimeter position. Instead, the treatment is judged based on dose rate comparisons between measurements and calculations of the most viable dosimeter position provided by the AEDA in a data driven approach. As a result, the AEDA compensates for false error cases related to systematic effects of the dosimeter position reconstruction. Given its nearly exclusive dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods: In the event of a measured potential treatment error, the AEDA proposes the most viable dosimeter position out of alternatives to the original reconstruction by means of a data driven matching procedure between dose rate distributions. If measured dose rates do not differ significantly from the most viable alternative, the initial error indication may be attributed to a mispositioned or misreconstructed dosimeter (false error). However, if the error declaration persists, no viable dosimeter position can be found to explain the error, hence the discrepancy is more likely to originate from a misplaced or misreconstructed source applicator or from erroneously connected source guide tubes (true error). Results: The AEDA applied on twoin vivo dosimetry implementations for pulsed dose rate BT demonstrated that the AEDA correctly described effects responsible for initial error indications. The AEDA was able to correctly identify the major part of all permutations of simulated guide tube swap errors and simulated shifts of individual needles from the original reconstruction. Unidentified errors corresponded to scenarios where the dosimeter position was

  16. Rapid Quantitative Detection of Lactobacillus sakei in Meat and Fermented Sausages by Real-Time PCR

    PubMed Central

    Martín, Belén; Jofré, Anna; Garriga, Margarita; Pla, Maria; Aymerich, Teresa

    2006-01-01

    A quick and simple method for quantitative detection of Lactobacillus sakei in fermented sausages was successfully developed. It is based on Chelex-100-based DNA purification and real-time PCR enumeration using a TaqMan fluorescence probe. Primers and probes were designed in the L. sakei 16S-23S rRNA intergenic transcribed spacer region, and the assay was evaluated using L. sakei genomic DNA and an artificially inoculated sausage model. The detection limit of this technique was approximately 3 cells per reaction mixture using both purified DNA and the inoculated sausage model. The quantification limit was established at 30 cells per reaction mixture in both models. The assay was then applied to enumerate L. sakei in real samples, and the results were compared to the MRS agar count method followed by confirmation of the percentage of L. sakei colonies. The results obtained by real-time PCR were not statistically significantly different than those obtained by plate count on MRS agar (P > 0.05), showing a satisfactory agreement between both methods. Therefore, the real-time PCR assay developed can be considered a promising rapid alternative method for the quantification of L. sakei and evaluation of the implantation of starter strains of L. sakei in fermented sausages. PMID:16957227

  17. Development and validation of a real-time PCR assay for the detection of Aeromonas salmonicida.

    PubMed

    Keeling, S E; Brosnahan, C L; Johnston, C; Wallis, R; Gudkovs, N; McDonald, W L

    2013-05-01

    A real-time PCR assay using a molecular beacon was developed and validated to detect the vapA (surface array protein) gene in the fish pathogen, Aeromonas salmonicida. The assay had 100% analytical specificity and analytical sensitivities of 5 ± 0 fg (DNA), 2.2 × 10(4) ± 1 × 10(4) CFU g(-1) (without enrichment) and 40 ± 10 CFU g(-1) (with enrichment) in kidney tissue. The assay was highly repeatable and proved to be robust following equivalency testing using a different real-time PCR platform. Following analytical validation, diagnostic specificity was determined using New Zealand farmed Chinook salmon, Oncorhynchus tshawytscha (Walbaum), (n = 750) and pink shubunkin, Carassius auratus (L.) (n = 157). The real-time PCR was run in parallel with culture and all fish tested were found to be negative by both methods for A. salmonicida, resulting in 100% diagnostic specificity (95% confidence interval). The molecular beacon real-time PCR system is specific, sensitive and a reproducible method for the detection of A. salmonicida. It can be used for diagnostic testing, health certification and active surveillance programmes. PMID:23121198

  18. A method for detecting and locating geophysical events using groups of arrays

    NASA Astrophysics Data System (ADS)

    de Groot-Hedlin, Catherine D.; Hedlin, Michael A. H.

    2015-11-01

    We have developed a novel method to detect and locate geophysical events that makes use of any sufficiently dense sensor network. This method is demonstrated using acoustic sensor data collected in 2013 at the USArray Transportable Array (TA). The algorithm applies Delaunay triangulation to divide the sensor network into a mesh of three-element arrays, called triads. Because infrasound waveforms are incoherent between the sensors within each triad, the data are transformed into envelopes, which are cross-correlated to find signals that satisfy a consistency criterion. The propagation azimuth, phase velocity and signal arrival time are computed for each signal. Triads with signals that are consistent with a single source are bundled as an event group. The ensemble of arrival times and azimuths of detected signals within each group are used to locate a common source in space and time. A total of 513 infrasonic stations that were active for part or all of 2013 were divided into over 2000 triads. Low (0.5-2 Hz) and high (2-8 Hz) catalogues of infrasonic events were created for the eastern USA. The low-frequency catalogue includes over 900 events and reveals several highly active source areas on land that correspond with coal mining regions. The high-frequency catalogue includes over 2000 events, with most occurring offshore. Although their cause is not certain, most events are clearly anthropogenic as almost all occur during regular working hours each week. The regions to which the TA is most sensitive vary seasonally, with the direction of reception dependent on the direction of zonal winds. The catalogue has also revealed large acoustic events that may provide useful insight into the nature of long-range infrasound propagation in the atmosphere.

  19. A Heuristic Indication and Warning Staging Model for Detection and Assessment of Biological Events

    PubMed Central

    Wilson, James M.; Polyak, Marat G.; Blake, Jane W.; Collmann, Jeff

    2008-01-01

    Objective This paper presents a model designed to enable rapid detection and assessment of biological threats that may require swift intervention by the international public health community. Design We utilized Strauss’ grounded theory to develop an expanded model of social disruption due to biological events based on retrospective and prospective case studies. We then applied this model to the temporal domain and propose a heuristic staging model, the Wilson–Collmann Scale for assessing biological event evolution. Measurements We retrospectively and manually examined hard copy archival local media reports in the native vernacular for three biological events associated with substantial social disruption. The model was then tested prospectively through media harvesting based on keywords corresponding to the model parameters. Results Our heuristic staging model provides valuable information about the features of a biological event that can be used to determine the level of concern warranted, such as whether the pathogen in question is responding to established public health disease control measures, including the use of antimicrobials or vaccines; whether the public health and medical infrastructure of the country involved is adequate to mount the necessary response; whether the country’s officials are providing an appropriate level of information to international public health authorities; and whether the event poses a international threat. The approach is applicable for monitoring open-source (public-domain) media for indications and warnings of such events, and specifically for markers of the social disruption that commonly occur as these events unfold. These indications and warnings can then be used as the basis for staging the biological threat in the same manner that the United States National Weather Service currently uses storm warning models (such as the Saffir-Simpson Hurricane Scale) to detect and assess threatening weather conditions. Conclusion

  20. Real-time billboard trademark detection and recognition in sports video

    NASA Astrophysics Data System (ADS)

    Bu, Jiang; Lao, Song-Yan; Bai, Liang

    2013-03-01

    Nowadays, different applications like automatic video indexing, keyword based video search and TV commercials can be developed by detecting and recognizing the billboard trademark. We propose a hierarchical solution for real-time billboard trademark recognition in various sports video, billboard frames are detected in the first level, fuzzy decision tree with easily-computing features are employed to accelerate the process, while in the second level, color and regional SIFT features are combined for the first time to describe the appearance of trademarks, and the shared nearest neighbor (SNN) clustering with x2 distance is utilized instead of traditional K-means clustering to construct the SIFT vocabulary, at last, Latent Semantic Analysis (LSA) based SIFT vocabulary matching is performed on the template trademark and the candidate regions in billboard frame. The preliminary experiments demonstrate the effectiveness of the hierarchical solution, and real time constraints are also met by our solution.

  1. On-loom, real-time, noncontact detection of fabric defects by ultrasonic imaging.

    SciTech Connect

    Chien, H. T.

    1998-09-08

    A noncontact, on-loom ultrasonic inspection technique was developed for real-time 100% defect inspection of fabrics. A prototype was built and tested successfully on loom. The system is compact, rugged, low cost, requires minimal maintenance, is not sensitive to fabric color and vibration, and can easily be adapted to current loom configurations. Moreover, it can detect defects in both the pick and warp directions. The system is capable of determining the size, location, and orientation of each defect. To further improve the system, air-coupled transducers with higher efficiency and sensitivity need to be developed. Advanced detection algorithms also need to be developed for better classification and categorization of defects in real-time.

  2. CTBT infrasound network performance to detect the 2013 Russian fireball event

    NASA Astrophysics Data System (ADS)

    Pilger, Christoph; Ceranna, Lars; Ross, J. Ole; Le Pichon, Alexis; Mialle, Pierrick; Garcés, Milton A.

    2015-04-01

    The explosive fragmentation of the 2013 Chelyabinsk meteorite generated a large airburst with an equivalent yield of 500 kT TNT. It is the most energetic event recorded by the infrasound component of the Comprehensive Nuclear-Test-Ban Treaty-International Monitoring System (CTBT-IMS), globally detected by 20 out of 42 operational stations. This study performs a station-by-station estimation of the IMS detection capability to explain infrasound detections and nondetections from short to long distances, using the Chelyabinsk meteorite as global reference event. Investigated parameters influencing the detection capability are the directivity of the line source signal, the ducting of acoustic energy, and the individual noise conditions at each station. Findings include a clear detection preference for stations perpendicular to the meteorite trajectory, even over large distances. Only a weak influence of stratospheric ducting is observed for this low-frequency case. Furthermore, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.

  3. myBlackBox: Blackbox Mobile Cloud Systems for Personalized Unusual Event Detection

    PubMed Central

    Ahn, Junho; Han, Richard

    2016-01-01

    We demonstrate the feasibility of constructing a novel and practical real-world mobile cloud system, called myBlackBox, that efficiently fuses multimodal smartphone sensor data to identify and log unusual personal events in mobile users’ daily lives. The system incorporates a hybrid architectural design that combines unsupervised classification of audio, accelerometer and location data with supervised joint fusion classification to achieve high accuracy, customization, convenience and scalability. We show the feasibility of myBlackBox by implementing and evaluating this end-to-end system that combines Android smartphones with cloud servers, deployed for 15 users over a one-month period. PMID:27223292

  4. myBlackBox: Blackbox Mobile Cloud Systems for Personalized Unusual Event Detection.

    PubMed

    Ahn, Junho; Han, Richard

    2016-01-01

    We demonstrate the feasibility of constructing a novel and practical real-world mobile cloud system, called myBlackBox, that efficiently fuses multimodal smartphone sensor data to identify and log unusual personal events in mobile users' daily lives. The system incorporates a hybrid architectural design that combines unsupervised classification of audio, accelerometer and location data with supervised joint fusion classification to achieve high accuracy, customization, convenience and scalability. We show the feasibility of myBlackBox by implementing and evaluating this end-to-end system that combines Android smartphones with cloud servers, deployed for 15 users over a one-month period. PMID:27223292

  5. A real-time implementation of an advanced sensor failure detection, isolation, and accommodation algorithm

    NASA Technical Reports Server (NTRS)

    Delaat, J. C.; Merrill, W. C.

    1984-01-01

    A sensor failure detection, isolation, and accommodation algorithm was developed which incorporates analytic sensor redundancy through software. This algorithm was implemented in a high level language on a microprocessor based controls computer. Parallel processing and state-of-the-art 16-bit microprocessors are used along with efficient programming practices to achieve real-time operation. Previously announced in STAR as N84-13140

  6. Resolution of Ion Mobility Spectra for the Detection of Hazardous Substances in Real Sampling Conditions

    SciTech Connect

    Montoliu, I.; Kalms, A.; Pardo, A.; Pomareda, V.; Marco, S.; Goebel, J.; Kessler, M.; Mueller, G.

    2009-05-23

    This work presents the possibilities offered by a blind source separation method such Multivariate Curve Resolution- Alternating Least Squares (MCR-ALS) in the analysis of Ion Mobility Spectra (IMS). Two security applications are analyzed in this context: the detection of TNT both in synthetic and real samples. Results obtained show the possibilities offered by the direct analysis of the drift time spectra when an appropriate resolution method is used.

  7. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO)

    PubMed Central

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-01-01

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073

  8. Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO).

    PubMed

    Yan, Lixin; Zhang, Yishi; He, Yi; Gao, Song; Zhu, Dunyao; Ran, Bin; Wu, Qing

    2016-01-01

    The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1) the Markov blanket (MB) algorithm is employed to extract the main factors associated with hazardous traffic events; (2) a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle's speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G) have significant influences on hazardous traffic events. The sequential minimal optimization (SMO) algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles. PMID:27420073

  9. Collaborative-Comparison Learning for Complex Event Detection Using Distributed Hierarchical Graph Neuron (DHGN) Approach in Wireless Sensor Network

    NASA Astrophysics Data System (ADS)

    Muhamad Amin, Anang Hudaya; Khan, Asad I.

    Research trends in existing event detection schemes using Wireless Sensor Network (WSN) have mainly focused on routing and localisation of nodes for optimum coordination when retrieving sensory information. Efforts have also been put in place to create schemes that are able to provide learning mechanisms for event detection using classification or clustering approaches. These schemes entail substantial communication and computational overheads owing to the event-oblivious nature of data transmissions. In this paper, we present an event detection scheme that has the ability to distribute detection processes over the resource-constrained wireless sensor nodes and is suitable for events with spatio-temporal characteristics. We adopt a pattern recognition algorithm known as Distributed Hierarchical Graph Neuron (DHGN) with collaborative-comparison learning for detecting critical events in WSN. The scheme demonstrates good accuracy for binary classification and offers low-complexity and high-scalability in terms of its processing requirements.

  10. Data-Driven Multimodal Sleep Apnea Events Detection : Synchrosquezing Transform Processing and Riemannian Geometry Classification Approaches.

    PubMed

    Rutkowski, Tomasz M

    2016-07-01

    A novel multimodal and bio-inspired approach to biomedical signal processing and classification is presented in the paper. This approach allows for an automatic semantic labeling (interpretation) of sleep apnea events based the proposed data-driven biomedical signal processing and classification. The presented signal processing and classification methods have been already successfully applied to real-time unimodal brainwaves (EEG only) decoding in brain-computer interfaces developed by the author. In the current project the very encouraging results are obtained using multimodal biomedical (brainwaves and peripheral physiological) signals in a unified processing approach allowing for the automatic semantic data description. The results thus support a hypothesis of the data-driven and bio-inspired signal processing approach validity for medical data semantic interpretation based on the sleep apnea events machine-learning-related classification. PMID:27194241

  11. Support Vector Machine Model for Automatic Detection and Classification of Seismic Events

    NASA Astrophysics Data System (ADS)

    Barros, Vesna; Barros, Lucas

    2016-04-01

    The automated processing of multiple seismic signals to detect, localize and classify seismic events is a central tool in both natural hazards monitoring and nuclear treaty verification. However, false detections and missed detections caused by station noise and incorrect classification of arrivals are still an issue and the events are often unclassified or poorly classified. Thus, machine learning techniques can be used in automatic processing for classifying the huge database of seismic recordings and provide more confidence in the final output. Applied in the context of the International Monitoring System (IMS) - a global sensor network developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) - we propose a fully automatic method for seismic event detection and classification based on a supervised pattern recognition technique called the Support Vector Machine (SVM). According to Kortström et al., 2015, the advantages of using SVM are handleability of large number of features and effectiveness in high dimensional spaces. Our objective is to detect seismic events from one IMS seismic station located in an area of high seismicity and mining activity and classify them as earthquakes or quarry blasts. It is expected to create a flexible and easily adjustable SVM method that can be applied in different regions and datasets. Taken a step further, accurate results for seismic stations could lead to a modification of the model and its parameters to make it applicable to other waveform technologies used to monitor nuclear explosions such as infrasound and hydroacoustic waveforms. As an authorized user, we have direct access to all IMS data and bulletins through a secure signatory account. A set of significant seismic waveforms containing different types of events (e.g. earthquake, quarry blasts) and noise is being analysed to train the model and learn the typical pattern of the signal from these events. Moreover, comparing the performance of the support

  12. Detection of individual atoms in helium buffer gas and observation of their real-time motion

    NASA Technical Reports Server (NTRS)

    Pan, C. L.; Prodan, J. V.; Fairbank, W. M., Jr.; She, C. Y.

    1980-01-01

    Single atoms are detected and their motion measured for the first time to our knowledge by the fluorescence photon-burst method in the presence of large quantities of buffer gas. A single-clipped digital correlator records the photon burst in real time and displays the atom's transit time across the laser beam. A comparison is made of the special requirements for single-atom detection in vacuum and in a buffer gas. Finally, the probability distribution of the bursts from many atoms is measured. It further proves that the bursts observed on resonance are due to single atoms and not simply to noise fluctuations.

  13. DSP implementation of wavelet transform for real time ECG wave forms detection and heart rate analysis.

    PubMed

    Bahoura, M; Hassani, M; Hubin, M

    1997-01-01

    An algorithm based on wavelet transform (WTs) suitable for real time implementation has been developed in order to detect ECG characteristics. In particular, QRS complexes, P and T waves may be distinguished from noise, baseline drift or artefacts. This algorithm is implemented in a DSP (SPROC-1400) with a 50 MHz frequency clock. The performance of this algorithm is discussed, its accuracy is evaluated and a comparison is made with a similar algorithm implemented in C language. For the standard MIT/BIH arrhythmia database, this algorithm correctly detects 99.7% of the QRS complexes. PMID:9034668

  14. Multiple-Threshold Event Detection and Other Enhancements to the Virtual Seismologist (VS) Earthquake Early Warning Algorithm

    NASA Astrophysics Data System (ADS)

    Fischer, M.; Caprio, M.; Cua, G. B.; Heaton, T. H.; Clinton, J. F.; Wiemer, S.

    2009-12-01

    The Virtual Seismologist (VS) algorithm is a Bayesian approach to earthquake early warning (EEW) being implemented by the Swiss Seismological Service at ETH Zurich. The application of Bayes’ theorem in earthquake early warning states that the most probable source estimate at any given time is a combination of contributions from a likelihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS algorithm was one of three EEW algorithms involved in the California Integrated Seismic Network (CISN) real-time EEW testing and performance evaluation effort. Its compelling real-time performance in California over the last three years has led to its inclusion in the new USGS-funded effort to develop key components of CISN ShakeAlert, a prototype EEW system that could potentially be implemented in California. A significant portion of VS code development was supported by the SAFER EEW project in Europe. We discuss recent enhancements to the VS EEW algorithm. We developed and continue to test a multiple-threshold event detection scheme, which uses different association / location approaches depending on the peak amplitudes associated with an incoming P pick. With this scheme, an event with sufficiently high initial amplitudes can be declared on the basis of a single station, maximizing warning times for damaging events for which EEW is most relevant. Smaller, non-damaging events, which will have lower initial amplitudes, will require more picks to be declared an event to reduce false alarms. This transforms the VS codes from a regional EEW approach reliant on traditional location estimation (and it requirement of at least 4 picks as implemented by the Binder Earthworm phase associator) to a hybrid on-site/regional approach capable of providing a continuously evolving stream of EEW

  15. A Multi-Scale Algorithm for Graffito Advertisement Detection from Images of Real Estate

    NASA Astrophysics Data System (ADS)

    Yang, Jun; Zhu, Shi-Jiao

    There is a significant need to detect and extract the graffito advertisement embedded in the housing images automatically. However, it is a hard job to separate the advertisement region well since housing images generally have complex background. In this paper, a detecting algorithm which uses multi-scale Gabor filters to identify graffito regions is proposed. Firstly, multi-scale Gabor filters with different directions are applied to housing images, then the approach uses these frequency data to find likely graffito regions using the relationship of different channels, it exploits the ability of different filters technique to solve the detection problem with low computational efforts. Lastly, the method is tested on several real estate images which are embedded graffito advertisement to verify its robustness and efficiency. The experiments demonstrate graffito regions can be detected quite well.

  16. Simultaneous Detection of Ricin and Abrin DNA by Real-Time PCR (qPCR)

    PubMed Central

    Felder, Eva; Mossbrugger, Ilona; Lange, Mirko; Wölfel, Roman

    2012-01-01

    Ricin and abrin are two of the most potent plant toxins known and may be easily obtained in high yield from the seeds using rather simple technology. As a result, both toxins are potent and available toxins for criminal or terrorist acts. However, as the production of highly purified ricin or abrin requires sophisticated equipment and knowledge, it may be more likely that crude extracts would be used by non-governmental perpetrators. Remaining plant-specific nucleic acids in these extracts allow the application of a real-time PCR (qPCR) assay for the detection and identification of abrin or ricin genomic material. Therefore, we have developed a duplex real-time PCR assays for simultaneous detection of ricin and abrin DNA based on the OmniMix HS bead PCR reagent mixture. Novel primers and hybridization probes were designed for detection on a SmartCycler instrument by using 5′-nuclease technology. The assay was thoroughly optimized and validated in terms of analytical sensitivity. Evaluation of the assay sensitivity by probit analysis demonstrated a 95% probability of detection at 3 genomes per reaction for ricin DNA and 1.2 genomes per reaction for abrin DNA. The suitability of the assays was exemplified by detection of ricin and abrin contaminations in a food matrix. PMID:23105972

  17. A practical real-time detection visual system for driver's eye closure state tracking

    NASA Astrophysics Data System (ADS)

    Zhan, Tong; Li, Zheng-ming; Zhang, Jin

    2012-01-01

    We use an onboard computer and a smart webcam built a practical real-time detection visual system. Installed in a driving cabin in a specific way, it is able to determine the degree of closure of the driver's eyelids for further study of detecting and mitigating driver drowsiness and fatigue. For a practical real-time application, both the temporal resolution and the image resolution of video processing are key performances. Instead of the traditional video processing strategy which detects face in the first frame and keep tracking in the following, a frame-by-frame detecting and locating strategy is adopted, which firstly locates face region in a size-reduced image, secondly face region in original image is located by linear mapping calculation, thirdly eye region is located in face region according to the characteristics of a facial geometric model, this model allows personal calibration intuitively in run-time according to different individuals. A novel combination of several practical methods proved effective in computer vision is proposed, including capturing and resizing frames, face and eye localization, adaptive-threshold segmentation, mathematical morphology etc. Experiments show that the proposed system achieves a performance of image resolution of 640×480 pixels, temporal resolution of 53 frames / second, average eye-blink detection accuracy of 96% under various illumination conditions.

  18. A practical real-time detection visual system for driver's eye closure state tracking

    NASA Astrophysics Data System (ADS)

    Zhan, Tong; Li, Zheng-Ming; Zhang, Jin

    2011-12-01

    We use an onboard computer and a smart webcam built a practical real-time detection visual system. Installed in a driving cabin in a specific way, it is able to determine the degree of closure of the driver's eyelids for further study of detecting and mitigating driver drowsiness and fatigue. For a practical real-time application, both the temporal resolution and the image resolution of video processing are key performances. Instead of the traditional video processing strategy which detects face in the first frame and keep tracking in the following, a frame-by-frame detecting and locating strategy is adopted, which firstly locates face region in a size-reduced image, secondly face region in original image is located by linear mapping calculation, thirdly eye region is located in face region according to the characteristics of a facial geometric model, this model allows personal calibration intuitively in run-time according to different individuals. A novel combination of several practical methods proved effective in computer vision is proposed, including capturing and resizing frames, face and eye localization, adaptive-threshold segmentation, mathematical morphology etc. Experiments show that the proposed system achieves a performance of image resolution of 640×480 pixels, temporal resolution of 53 frames / second, average eye-blink detection accuracy of 96% under various illumination conditions.

  19. Visual detectability of elastic contrast in real-time ultrasound images

    NASA Astrophysics Data System (ADS)

    Miller, Naomi R.; Bamber, Jeffery C.; Doyley, Marvin M.; Leach, Martin O.

    1997-04-01

    Elasticity imaging (EI) has recently been proposed as a technique for imaging the mechanical properties of soft tissue. However, dynamic features, known as compressibility and mobility, are already employed to distinguish between different tissue types in ultrasound breast examination. This method, which involves the subjective interpretation of tissue motion seen in real-time B-mode images during palpation, is hereafter referred to as differential motion imaging (DMI). The purpose of this study was to develop the methodology required to perform a series of perception experiments to measure elastic lesion detectability by means of DMI and to obtain preliminary results for elastic contrast thresholds for different lesion sizes. Simulated sequences of real-time B-scans of tissue moving in response to an applied force were generated. A two-alternative forced choice (2-AFC) experiment was conducted and the measured contrast thresholds were compared with published results for lesions detected by EI. Although the trained observer was found to be quite skilled at the task of differential motion perception, it would appear that lesion detectability is improved when motion information is detected by computer processing and converted to gray scale before presentation to the observer. In particular, for lesions containing fewer than eight speckle cells, a signal detection rate of 100% could not be achieved even when the elastic contrast was very high.

  20. Toward Real-Time Automated Detection of Turns during Gait Using Wearable Inertial Measurement Units

    PubMed Central

    Novak, Domen; Goršič, Maja; Podobnik, Janez; Munih, Marko

    2014-01-01

    Previous studies have presented algorithms for detection of turns during gait using wearable sensors, but those algorithms were not built for real-time use. This paper therefore investigates the optimal approach for real-time detection of planned turns during gait using wearable inertial measurement units. Several different sensor positions (head, back and legs) and three different detection criteria (orientation, angular velocity and both) are compared with regard to their ability to correctly detect turn onset. Furthermore, the different sensor positions are compared with regard to their ability to predict the turn direction and amplitude. The evaluation was performed on ten healthy subjects who performed left/right turns at three amplitudes (22, 45 and 90 degrees). Results showed that turn onset can be most accurately detected with sensors on the back and using a combination of orientation and angular velocity. The same setup also gives the best prediction of turn direction and amplitude. Preliminary measurements with a single amputee were also performed and highlighted important differences such as slower turning that need to be taken into account. PMID:25310470

  1. Real-time DNA Amplification and Detection System Based on a CMOS Image Sensor.

    PubMed

    Wang, Tiantian; Devadhasan, Jasmine Pramila; Lee, Do Young; Kim, Sanghyo

    2016-01-01

    In the present study, we developed a polypropylene well-integrated complementary metal oxide semiconductor (CMOS) platform to perform the loop mediated isothermal amplification (LAMP) technique for real-time DNA amplification and detection simultaneously. An amplification-coupled detection system directly measures the photon number changes based on the generation of magnesium pyrophosphate and color changes. The photon number decreases during the amplification process. The CMOS image sensor observes the photons and converts into digital units with the aid of an analog-to-digital converter (ADC). In addition, UV-spectral studies, optical color intensity detection, pH analysis, and electrophoresis detection were carried out to prove the efficiency of the CMOS sensor based the LAMP system. Moreover, Clostridium perfringens was utilized as proof-of-concept detection for the new system. We anticipate that this CMOS image sensor-based LAMP method will enable the creation of cost-effective, label-free, optical, real-time and portable molecular diagnostic devices. PMID:27302586

  2. Real-time Bacterial Detection by Single Cell Based Sensors UsingSynchrotron FTIR Spectromicroscopy

    SciTech Connect

    Veiseh, Mandana; Veiseh, Omid; Martin, Michael C.; Bertozzi,Carolyn; Zhang, Miqin

    2005-08-10

    Microarrays of single macrophage cell based sensors weredeveloped and demonstrated for real time bacterium detection bysynchrotron FTIR microscopy. The cells were patterned on gold-SiO2substrates via a surface engineering technique by which the goldelectrodes were immobilized with fibronectin to mediate cell adhesion andthe silicon oxide background were passivated with PEG to resist proteinadsorption and cell adhesion. Cellular morphology and IR spectra ofsingle, double, and triple cells on gold electrodes exposed tolipopolysaccharide (LPS) of different concentrations were compared toreveal the detection capabilities of these biosensors. The single-cellbased sensors were found to generate the most significant IR wave numbervariation and thus provide the highest detection sensitivity. Changes inmorphology and IR spectrum for single cells exposed to LPS were found tobe time- and concentration-dependent and correlated with each other verywell. FTIR spectra from single cell arrays of gold electrodes withsurface area of 25 mu-m2, 100 mu-m2, and 400 mu-m2 were acquired usingboth synchrotron and conventional FTIR spectromicroscopes to study thesensitivity of detection. The results indicated that the developedsingle-cell platform can be used with conventional FTIRspectromicroscopy. This technique provides real-time, label-free, andrapid bacterial detection, and may allow for statistic and highthroughput analyses, and portability.

  3. Detection and Differentiation of Bordetella spp. by Real-Time PCR▿

    PubMed Central

    Koidl, Christoph; Bozic, Michael; Burmeister, Anja; Hess, Markus; Marth, Egon; Kessler, Harald H.

    2007-01-01

    Molecular detection of Bordetella pertussis DNA is a sensitive and specific method for the rapid diagnosis of pertussis. In this study, a new molecular assay for the detection and differentiation of Bordetella spp. based on automated DNA extraction and real-time PCR was evaluated. The analytical sensitivity of the new assay was determined by Probit analysis of serial dilutions of both cloned PCR products IS481 and IS1001 and cell suspensions of B. pertussis, B. parapertussis, and B. bronchiseptica. The specificity was analyzed by testing a number of pathogens producing respiratory infections. Moreover, a total of 92 clinical samples were investigated. The results were compared to those obtained by an in-house assay based on manual DNA extraction, followed by real-time PCR and detection of IS481. The analytical sensitivity of the new assay for the detection of IS481 and IS1001 was determined to be 2.2 and 1.2 genome equivalents/μl, respectively. The analytical sensitivity for the detection of B. pertussis, B. parapertussis, and B. bronchiseptica was determined to be 1.6, 1.0, and 2.7 genome equivalents/μl, respectively. When clinical specimens were tested with the new assay, 46 of 92 were found to be positive for Bordetella DNA. With the in-house assay, 45 samples tested positive. The new molecular assay proved to be suitable for the rapid diagnosis of pertussis in the routine diagnostic laboratory. PMID:17151212

  4. A fast-saliency method for real-time infrared small target detection

    NASA Astrophysics Data System (ADS)

    Qi, Shengxiang; Xu, Guojing; Mou, Zhiying; Huang, Dayu; Zheng, Xueli

    2016-07-01

    Infrared small target detection plays an important role in applications including military reconnaissance, early warning and terminal guidance. In this paper, we present a fast method, called fast-saliency, with very low computational complexity, for real-time small target detection in single image frame under various complex backgrounds. Different from traditional algorithms, the proposed method is inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, which is able to delineate regions of small targets in infrared images. Concisely, there are only four simple steps contained in fast-saliency. In order, they are gradient operation, square computation, Gaussian smoothing and automatic thresholding, representing the four procedures as highpass filtering, target enhancement, noise suppression and target segmentation, respectively. Especially, for the most crucial step, gradient operation, we innovatively propose a 5 × 5 facet kernel operator that holds the key for separating the small targets from backgrounds. To verify the effectiveness of our proposed method, a set of real infrared images covering typical backgrounds with sea, sky and ground clutters are tested in experiments. The results demonstrate that it outperforms the state-of-the-art methods not only in detection accuracy, but also in computation efficiency.

  5. Real-Time Plasma Process Condition Sensing and Abnormal Process Detection

    PubMed Central

    Yang, Ryan; Chen, Rongshun

    2010-01-01

    The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools. PMID:22219683

  6. Wavelet Transform for Real-Time Detection of Action Potentials in Neural Signals

    PubMed Central

    Quotb, Adam; Bornat, Yannick; Renaud, Sylvie

    2011-01-01

    We present a study on wavelet detection methods of neuronal action potentials (APs). Our final goal is to implement the selected algorithms on custom integrated electronics for on-line processing of neural signals; therefore we take real-time computing as a hard specification and silicon area as a price to pay. Using simulated neural signals including APs, we characterize an efficient wavelet method for AP extraction by evaluating its detection rate and its implementation cost. We compare software implementation for three methods: adaptive threshold, discrete wavelet transform (DWT), and stationary wavelet transform (SWT). We evaluate detection rate and implementation cost for detection functions dynamically comparing a signal with an adaptive threshold proportional to its SD, where the signal is the raw neural signal, respectively: (i) non-processed; (ii) processed by a DWT; (iii) processed by a SWT. We also use different mother wavelets and test different data formats to set an optimal compromise between accuracy and silicon cost. Detection accuracy is evaluated together with false negative and false positive detections. Simulation results show that for on-line AP detection implemented on a configurable digital integrated circuit, APs underneath the noise level can be detected using SWT with a well-selected mother wavelet, combined to an adaptive threshold. PMID:21811455

  7. Real time corner detection for miniaturized electro-optical sensors onboard small unmanned aerial systems.

    PubMed

    Forlenza, Lidia; Carton, Patrick; Accardo, Domenico; Fasano, Giancarmine; Moccia, Antonio

    2012-01-01

    This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d'Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed. PMID:22368499

  8. Real Time Corner Detection for Miniaturized Electro-Optical Sensors Onboard Small Unmanned Aerial Systems

    PubMed Central

    Forlenza, Lidia; Carton, Patrick; Accardo, Domenico; Fasano, Giancarmine; Moccia, Antonio

    2012-01-01

    This paper describes the target detection algorithm for the image processor of a vision-based system that is installed onboard an unmanned helicopter. It has been developed in the framework of a project of the French national aerospace research center Office National d’Etudes et de Recherches Aérospatiales (ONERA) which aims at developing an air-to-ground target tracking mission in an unknown urban environment. In particular, the image processor must detect targets and estimate ground motion in proximity of the detected target position. Concerning the target detection function, the analysis has dealt with realizing a corner detection algorithm and selecting the best choices in terms of edge detection methods, filtering size and type and the more suitable criterion of detection of the points of interest in order to obtain a very fast algorithm which fulfills the computation load requirements. The compared criteria are the Harris-Stephen and the Shi-Tomasi, ones, which are the most widely used in literature among those based on intensity. Experimental results which illustrate the performance of the developed algorithm and demonstrate that the detection time is fully compliant with the requirements of the real-time system are discussed. PMID:22368499

  9. Surface-Wave Multiple-Event Relocation and Detection of Earthquakes along the Romanche Fracture Zone

    NASA Astrophysics Data System (ADS)

    Cleveland, M.; Ammon, C. J.; VanDeMark, T. F.

    2011-12-01

    The Romanche Transform system, located along the equatorial Mid-Atlantic Ridge, is approximately 900 km in length and separates plates moving with a relative plate speed of three cm/yr. We use cross-correlation of globally recorded Rayleigh waves to estimate precise relative epicentroids of moderate-size earthquakes along the Romanche Fracture Zone system. The Romanche transform has an even distribution of large events along its entire length that provide a good base of events with excellent signal-to-noise observations. Two distinct moderate-magnitude event clusters occur along the eastern half of the transform and the region between the clusters hosted a large event in the last decade. Based on initial results (Van DeMark, 2006), unlike those of shorter transform systems, the events along the Romanche do not follow narrow features, the event clusters seem to spread perpendicular as well as laterally to the transform trend. These patterns are consistent with parallel, en echelon and/or braided fault systems, which have been previously observed on the Romanche through the use of side scanning sonar (Parson and Searle, 1986). We also explore the character and potential of seismic body waves to extend the method to help improve relative event depth estimates. Relying on a good base of larger and moderate-magnitude seismicity, we attempt to extend the analysis by processing continuous data streams through processes measuring waveform similarity (e.g. cross-correlation) in an attempt to detect smaller events using a subset of nearest seismic stations.

  10. Detection of Unusual Events and Trends in Complex Non-Stationary Data Streams

    SciTech Connect

    Perez, Rafael B; Protopopescu, Vladimir A; Worley, Brian Addison; Perez, Cristina

    2006-01-01

    The search for unusual events and trends hidden in multi-component, nonlinear, non-stationary, noisy signals is extremely important for a host of different applications, ranging from nuclear power plant and electric grid operation to internet traffic and implementation of non-proliferation protocols. In the context of this work, we define an unusual event as a local signal disturbance and a trend as a continuous carrier of information added to and different from the underlying baseline dynamics. The goal of this paper is to investigate the feasibility of detecting hidden intermittent events inside non-stationary signal data sets corrupted by high levels of noise, by using the Hilbert-Huang empirical mode decomposition method.

  11. Use of a clinical event monitor to prevent and detect medication errors.

    PubMed Central

    Payne, T. H.; Savarino, J.; Marshall, R.; Hoey, C. T.

    2000-01-01

    Errors in health care facilities are common and often unrecognized. We have used our clinical event monitor to prevent and detect medication errors by scrutinizing electronic messages sent to it when any medication order is written in our facility. A growing collection of medication safety rules covering dose limit errors, laboratory monitoring, and other topics may be applied to each medication order message to provide an additional layer of protection beyond existing order checks, reminders, and alerts available within our computer-based record system. During a typical day the event monitor receives 4802 messages, of which 4719 pertain to medication orders. We have found the clinical event monitor to be a valuable tool for clinicians and quality management groups charged with improving medication safety. PMID:11079962

  12. Detection of Severe Rain on Snow events using passive microwave remote sensing

    NASA Astrophysics Data System (ADS)

    Grenfell, T. C.; Putkonen, J.

    2007-12-01

    Severe wintertime rain-on-snow (ROS) events create a strong ice layer or layers in the snow on arctic tundra that act as a barrier to ungulate grazing. These events are linked with large-scale ungulate herd declines via starvation and reduced calf production rate when the animals are unable to penetrate through the resulting ice layer. ROS events also produce considerable perturbation in the mean wintertime soil temperature beneath the snow pack. ROS is a sporadic but well-known and significant phenomenon that is currently very poorly documented. Characterization of the distribution and occurrence of severe rain-on-snow events is based only on anecdotal evidence, indirect observations of carcasses found adjacent to iced snow packs, and irregular detection by a sparse observational weather network. We have analyzed in detail a particular well-identified ROS event that took place on Banks Island in early October 2003 that resulted in the death of 20,000 musk oxen. We make use of multifrequency passive microwave imagery from the special sensing microwave imager satellite sensor suite (SSM/I) in conjunction with a strong-fluctuation-theory (SFT) emissivity model. We show that a combination of time series analysis and cluster analysis based on microwave spectral gradients and polarization ratios provides a means to detect the stages of the ROS event resulting from the modification of the vertical structure of the snow pack, specifically wetting the snow, the accumulation of liquid water at the base of the snow during the rain event, and the subsequent modification of the snowpack after refreezing. SFT model analysis provides quantitative confirmation of our interpretation of the evolution of the microwave properties of the snowpack as a result of the ROS event. In particular, in addition to the grain coarsening due to destructive metamorphism, we detect the presence of the internal water and ice layers, directly identifying the physical properties producing the

  13. Detection and analysis of high-temperature events in the BIRD mission

    NASA Astrophysics Data System (ADS)

    Zhukov, Boris; Briess, Klaus; Lorenz, Eckehard; Oertel, Dieter; Skrbek, Wolfgang

    2005-01-01

    The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite is detection and quantitative analysis of high-temperature events like fires and volcanoes. An absence of saturation in the BIRD infrared channels makes it possible to improve false alarm rejection as well as to retrieve quantitative characteristics of hot targets, including their effective fire temperature, area and the radiative energy release. Examples are given of detection and analysis of wild and coal seam fires, of volcanic activity as well as of oil fires in Iraq. The smallest fires detected by BIRD, which were verified on ground, had an area of 12m2 at daytime and 4m2 at night.

  14. Assessing Reliability of Medical Record Reviews for the Detection of Hospital Adverse Events

    PubMed Central

    Ock, Minsu; Lee, Sang-il; Jo, Min-Woo; Lee, Jin Yong; Kim, Seon-Ha

    2015-01-01

    Objectives: The purpose of this study was to assess the inter-rater reliability and intra-rater reliability of medical record review for the detection of hospital adverse events. Methods: We conducted two stages retrospective medical records review of a random sample of 96 patients from one acute-care general hospital. The first stage was an explicit patient record review by two nurses to detect the presence of 41 screening criteria (SC). The second stage was an implicit structured review by two physicians to identify the occurrence of adverse events from the positive cases on the SC. The inter-rater reliability of two nurses and that of two physicians were assessed. The intra-rater reliability was also evaluated by using test-retest method at approximately two weeks later. Results: In 84.2% of the patient medical records, the nurses agreed as to the necessity for the second stage review (kappa, 0.68; 95% confidence interval [CI], 0.54 to 0.83). In 93.0% of the patient medical records screened by nurses, the physicians agreed about the absence or presence of adverse events (kappa, 0.71; 95% CI, 0.44 to 0.97). When assessing intra-rater reliability, the kappa indices of two nurses were 0.54 (95% CI, 0.31 to 0.77) and 0.67 (95% CI, 0.47 to 0.87), whereas those of two physicians were 0.87 (95% CI, 0.62 to 1.00) and 0.37 (95% CI, -0.16 to 0.89). Conclusions: In this study, the medical record review for detecting adverse events showed intermediate to good level of inter-rater and intra-rater reliability. Well organized training program for reviewers and clearly defining SC are required to get more reliable results in the hospital adverse event study. PMID:26429290

  15. Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

    2013-05-01

    It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

  16. A TaqMan-based real-time polymerase chain reaction for the detection of porcine parvovirus.

    PubMed

    Chen, Hong-Ying; Li, Xiao-Kang; Cui, Bao-An; Wei, Zhan-Yong; Li, Xin-Sheng; Wang, Yan-Bin; Zhao, Li; Wang, Zhen-Ya

    2009-03-01

    A real-time polymerase chain reaction (PCR) using a TaqMan probe was developed to detect porcine parvovirus (PPV). Real-time PCR was optimized to quantify PPV using a detection system (Rotor Gene 2000 detector) and a dual-labeled fluorogenic probe. The gene-specific labeled fluorogenic probe for the VP2 gene of PPV was used to detect PPV. Quantitation of PPV was accomplished by a standard curve plotting cycle threshold values (Ct) against each dilution of standard plasmids. When the specificity of the assay using specific PPV primers was evaluated by testing the PPV standard strain and other viruses, no cross-reactions were detected with non-PPV reference viruses. The detection limit of real-time PCR for PPV was 2.08log10 genome copy equivalent (gce). In this study, a real-time PCR assay was performed on 80 clinical samples and compared with a conventional PCR assay. In 48 of 80 samples, PPV DNA was detected by the conventional PCR assay. All samples positive for PPV DNA by the conventional PCR assay were also positive by the real-time PCR assay, and 12 of 32 samples that tested negative for PPV DNA by the conventional method tested positive by the real-time PCR assay. Using the real-time PCR assay, the number of samples in which PPV was detected increased by 15%. Therefore, it is considered to be a useful tool for the detection of PPV. PMID:19041671

  17. How unusual are the "unusual events" detected by control chart techniques in healthcare settings?

    PubMed

    Borckardt, Jeffrey J; Nash, Michael R; Hardesty, Susan; Herbert, Joan; Cooney, Harriet; Pelic, Christopher

    2006-01-01

    Statistical process control (SPC) charts have become widely implemented tools for quality monitoring and assurance in healthcare settings across the United States. SPC methods have been successfully used in industrial settings to track the quality of products manufactured by machines and to detect deviations from acceptable Levels of product quality. However, problems may arise when SPC methods are used to evaluate human behavior. Specifically, when human behavior is tracked over time, the data stream generated usually exhibits periodicity and gradualism with respect to behavioral changes over time. These tendencies can be quantified and are recognized in the statistical field as autocorrelation. When autocorrelation is present, conventional SPC methods too often identify events as "unusuaL" when they really should be understood as products of random fluctuation. This article discusses the concept of autocorrelation and demonstrates the negative impact of autocorrelation on traditional SPC methods, with a specific focus on the use of SPC charts to detect unusual events. PMID:16944647

  18. A multivariate based event detection method and performance comparison with two baseline methods.

    PubMed

    Liu, Shuming; Smith, Kate; Che, Han

    2015-09-01

    Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate. PMID:25996758

  19. Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence

    PubMed Central

    Ohyama, Junji; Watanabe, Katsumi

    2016-01-01

    We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images. PMID:26869966

  20. Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence.

    PubMed

    Ohyama, Junji; Watanabe, Katsumi

    2016-01-01

    We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images. PMID:26869966

  1. Testing the waveform correlation event detection system: Teleseismic, regional, and local distances

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Harris, J.M.

    1997-08-01

    Waveform Correlation Event Detection System (WCEDS) prototypes have now been developed for both global and regional networks and the authors have extensively tested them to assess the potential usefulness of this technology for CTBT (Comprehensive Test Ban Treaty) monitoring. In this paper they present the results of tests on data sets from the IDC (International Data Center) Primary Network and the New Mexico Tech Seismic Network. The data sets span a variety of event types and noise conditions. The results are encouraging at both scales but show particular promise for regional networks. The global system was developed at Sandia Labs and has been tested on data from the IDC Primary Network. The authors have found that for this network the system does not perform at acceptable levels for either detection or location unless directional information (azimuth and slowness) is used. By incorporating directional information, however, both areas can be improved substantially suggesting that WCEDS may be able to offer a global detection capability which could complement that provided by the GA (Global Association) system in use at the IDC and USNDC (United States National Data Center). The local version of WCEDS (LWCEDS) has been developed and tested at New Mexico Tech using data from the New Mexico Tech Seismic Network (NMTSN). Results indicate that the WCEDS technology works well at this scale, despite the fact that the present implementation of LWCEDS does not use directional information. The NMTSN data set is a good test bed for the development of LWCEDS because of a typically large number of observed local phases and near network-wide recording of most local and regional events. Detection levels approach those of trained analysts, and locations are within 3 km of manually determined locations for local events.

  2. Real-time isothermal detection of Shiga toxin-producing Escherichia coli using recombinase polymerase amplification.

    PubMed

    Murinda, Shelton E; Ibekwe, A Mark; Zulkaffly, Syaizul; Cruz, Andrew; Park, Stanley; Razak, Nur; Paudzai, Farah Md; Ab Samad, Liana; Baquir, Khairul; Muthaiyah, Kokilah; Santiago, Brenna; Rusli, Amirul; Balkcom, Sean

    2014-07-01

    Shiga toxin-producing Escherichia coli (STEC) are a major family of foodborne pathogens of public health, zoonotic, and economic significance in the United States and worldwide. To date, there are no published reports on use of recombinase polymerase amplification (RPA) for STEC detection. The primary goal of this study was to assess the potential application of RPA in detection of STEC. This study focused on designing and evaluating RPA primers and fluorescent probes for isothermal (39°C) detection of STEC. Compatible sets of candidate primers and probes were designed for detection of Shiga toxin 1 and 2 (Stx1 and 2), respectively. The sets were evaluated for specificity and sensitivity against STEC (n=12) of various stx genotypes (stx1/stx2, stx1, or stx2, respectively), including non-Stx-producing E. coli (n=28) and other genera (n=7). The primers and probes that were designed targeted amplification of the subunit A moiety of stx1 and stx2. The assay detected STEC in real time (within 5-10 min at 39°C) with high sensitivity (93.5% vs. 90%; stx1 vs. stx2), specificity (99.1% vs. 100%; stx1 vs. stx2), and predictive value (97.9% for both stx1 vs. stx2). Limits of detection of ∼ 5-50 colony-forming units/mL were achieved in serially diluted cultures grown in brain heart infusion broth. This study successfully demonstrated for the first time that RPA can be used for isothermal real-time detection of STEC. PMID:24749488

  3. Event Detection for Hydrothermal Plumes: A case study at Grotto Vent

    NASA Astrophysics Data System (ADS)

    Bemis, K. G.; Ozer, S.; Xu, G.; Rona, P. A.; Silver, D.

    2012-12-01

    Evidence is mounting that geologic events such as volcanic eruptions (and intrusions) and earthquakes (near and far) influence the flow rates and temperatures of hydrothermal systems. Connecting such suppositions to observations of hydrothermal output is challenging, but new ongoing time series have the potential to capture such events. This study explores using activity detection, a technique modified from computer vision, to identify pre-defined events within an extended time series recorded by COVIS (Cabled Observatory Vent Imaging Sonar) and applies it to a time series, with gaps, from Sept 2010 to the present; available measurements include plume orientation, plume rise rate, and diffuse flow area at the NEPTUNE Canada Observatory at Grotto Vent, Main Endeavour Field, Juan de Fuca Ridge. Activity detection is the process of finding a pattern (activity) in a data set containing many different types of patterns. Among many approaches proposed to model and detect activities, we have chosen a graph-based technique, Petri Nets, as they do not require training data to model the activity. They use the domain expert's knowledge to build the activity as a combination of feature states and their transitions (actions). Starting from a conceptual model of how hydrothermal plumes respond to daily tides, we have developed a Petri Net based detection algorithm that identifies deviations from the specified response. Initially we assumed that the orientation of the plume would change smoothly and symmetrically in a consistent daily pattern. However, results indicate that the rate of directional changes varies. The present Petri Net detects unusually large and rapid changes in direction or amount of bending; however inspection of Figure 1 suggests that many of the events detected may be artifacts resulting from gaps in the data or from the large temporal spacing. Still, considerable complexity overlies the "normal" tidal response pattern (the data has a dominant frequency of

  4. Detection and quantification of Histomonas meleagridis by real-time PCR targeting single copy genes.

    PubMed

    Hussain, Imtiaz; Jaskulska, Barbara; Hess, Michael; Bilic, Ivana

    2015-09-15

    Histomonas meleagridis, a protozoan parasite that can infect gallinaceous birds, affects mainly the liver and caeca of infected birds. As a consequence of the recent ban of chemotherapeuticals in Europe and the USA, histomonosis gained somewhat more attention due to its re-emergence and the fact that there is no effective treatment available. Therefore, special attention is now also given towards the diagnosis and the control of the disease. In the actual study we report the development of highly specific and sensitive real-time PCR methods for detection and quantification of the parasite, based on two protein coding genes, Fe-hydrogenase (FeHYD) and rpb1. Both genes seem to be in a single copy in H. meleagridis as shown by southern blotting and absolute quantification using real-time PCRs on samples containing a known amount of the parasite. The real-time PCR assays based on FeHYD and rpb1 genes were found to be an efficient method for the quantification and detection of H. meleagridis in in vitro grown cultures, tissues of infected birds and in faecal samples. Both real-time PCRs were able to detect up to a single cell in in vitro cultures of H. meleagridis and in fecal samples spiked with H. meleagridis. Finally, qPCR assays were shown to be highly specific for H. meleagridis as samples containing either of the two H. meleagridis genotypes were positive, whereas samples containing other protozoa such as Tetratrichomonas gallinarum, Trichomonas gallinae, Simplicimonas sp., Tritrichomonas sp., Parahistomonas wenrichi, Dientamoebidae sp. and Blastocystis sp. were all negative. PMID:26319200

  5. Real-time ground-based optical detection system for space debris

    NASA Astrophysics Data System (ADS)

    Marchant, Jonathan; Green, Simon; Dick, James

    1996-10-01

    There are many advantages to supplementing ground based radar debris detection systems with optical systems. For example: objects with a low radar signature can still be optically bright (and vice versa); in the field of space debris optical detection is less sensitive to range; the minimum detectable debris size for a given range is less than that for radar. Destructive debris can be as small as 1 cm, so any improvement in detection sensitivity towards this standard is important. To improve the accuracy of debris orbital elements, a real-time detection system might be preferable in contrast to one in which images are stored for post-observation ('daytime') analysis. This is because more than one telescope is needed to lengthen the observing baseline and so increase the detected fraction of the debris orbit. Therefore, any software based at one telescope that recognizes debris in its field of view, produces a first approximation of its orbit elements and alerts extra telescopes along track, must process its data quickly, and preferably during the same pass. A prototype of such a software system under development for use with a CCD camera at the Royal Greenwich Observatory's satellite laser ranger at Herstmonceux, East Sussex, England, is outlined. The methods which the detection algorithm employs to handle data from the camera system are described, along with the limitations that the hardware and processing time impose on the physical nature of the problem.

  6. Resolution Enhanced Magnetic Sensing System for Wide Coverage Real Time UXO Detection

    NASA Astrophysics Data System (ADS)

    Zalevsky, Zeev; Bregman, Yuri; Salomonski, Nizan; Zafrir, Hovav

    2012-09-01

    In this paper we present a new high resolution automatic detection algorithm based upon a Wavelet transform and then validate it in marine related experiments. The proposed approach allows obtaining an automatic detection in a very low signal to noise ratios. The amount of calculations is reduced, the magnetic trend is depressed and the probability of detection/ false alarm rate can easily be controlled. Moreover, the algorithm enables to distinguish between close targets. In the algorithm we use the physical dependence of the magnetic field of a magnetic dipole in order to define a Wavelet mother function that later on can detect magnetic targets modeled as dipoles and embedded in noisy surrounding, at improved resolution. The proposed algorithm was realized on synthesized targets and then validated in field experiments involving a marine surface-floating system for wide coverage real time unexploded ordinance (UXO) detection and mapping. The detection probability achieved in the marine experiment was above 90%. The horizontal radial error of most of the detected targets was only 16 m and two baseline targets that were immersed about 20 m one to another could easily be distinguished.

  7. Quantitative Detection of Clostridium perfringens in the Broiler Fowl Gastrointestinal Tract by Real-Time PCR

    PubMed Central

    Wise, Mark G.; Siragusa, Gregory R.

    2005-01-01

    Strains of Clostridium perfringens are a frequent cause of food-borne disease and gas gangrene and are also associated with necrotic enteritis in chickens. To detect and quantify the levels of C. perfringens in the chicken gastrointestinal tract, a quantitative real-time PCR assay utilizing a fluorogenic, hydrolysis-type probe was developed and utilized to assay material retrieved from the broiler chicken cecum and ileum. Primers and probe were selected following an alignment of 16S rDNA sequences from members of cluster I of the genus Clostridium, and proved to be specific for C. perfringens. The assay could detect approximately 50 fg of C. perfringens genomic DNA and approximately 20 cells in pure culture. Measurements of the analytical sensitivity determined with spiked intestinal contents indicated that the consistent limit of detection with ileal samples was approximately 102 CFU/g of ileal material, but only about 104 CFU/g of cecal samples. The decreased sensitivity with the cecal samples was due to the presence of an unidentified chemical PCR inhibitor(s) in the cecal DNA purifications. The assay was utilized to rapidly detect and quantify C. perfringens levels in the gut tract of broiler chickens reared without supplementary growth-promoting antibiotics that manifested symptoms of necrotic enteritis. The results illustrated that quantitative real-time PCR correlates well with quantification via standard plate counts in samples taken from the ileal region of the gastrointestinal tract. PMID:16000804

  8. Surface plasmon resonance biosensors for highly sensitive detection in real samples

    NASA Astrophysics Data System (ADS)

    Sepúlveda, B.; Carrascosa, L. G.; Regatos, D.; Otte, M. A.; Fariña, D.; Lechuga, L. M.

    2009-08-01

    In this work we summarize the main results obtained with the portable surface plasmon resonance (SPR) device developed in our group (commercialised by SENSIA, SL, Spain), highlighting its applicability for the real-time detection of extremely low concentrations of toxic pesticides in environmental water samples. In addition, we show applications in clinical diagnosis as, on the one hand, the real-time and label-free detection of DNA hybridization and single point mutations at the gene BRCA-1, related to the predisposition in women to develop an inherited breast cancer and, on the other hand, the analysis of protein biomarkers in biological samples (urine, serum) for early detection of diseases. Despite the large number of applications already proven, the SPR technology has two main drawbacks: (i) not enough sensitivity for some specific applications (where pM-fM or single-molecule detection are needed) (ii) low multiplexing capabilities. In order solve such drawbacks, we work in several alternative configurations as the Magneto-optical Surface Plasmon Resonance sensor (MOSPR) based on a combination of magnetooptical and ferromagnetic materials, to improve the SPR sensitivity, or the Localized Surface Plasmon Resonance (LSPR) based on nanostructures (nanoparticles, nanoholes,...), for higher multiplexing capabilities.

  9. Algorithms for real-time fault detection of the Space Shuttle Main Engine

    NASA Astrophysics Data System (ADS)

    Ruiz, C. A.; Hawman, M. W.; Galinaitis, W. S.

    1992-07-01

    This paper reports on the results of a program to develop and demonstrate concepts related to a realtime health management system (HMS) for the Space Shuttle Main Engine (SSME). An HMS framework was developed on the basis of a top-down analysis of the current rocket engine failure modes and the engine monitoring requirements. One result of Phase I of this program was the identification of algorithmic approaches for detecting failures of the SSME. Three different analytical techniques were developed which demonstrated the capability to detect failures significantly earlier than the existing redlines. Based on promising initial results, Phase II of the program was initiated to further validate and refine the fault detection strategy on a large data base of 140 SSME test firings, and implement the resultant algorithms in real time. The paper begins with an overview of the refined algorithms used to detect failures during SSME start-up and main-stage operation. Results of testing these algorithms on a data base of nominal and off-nominal SSME test firings is discussed. The paper concludes with a discussion of the performance of the algorithms operating on a real-time computer system.

  10. Bifunctional electro-optical nanoprobe to real-time detect local biochemical processes in single cells.

    PubMed

    Zheng, Xin Ting; Hu, Weihua; Wang, Houxiao; Yang, Hongbin; Zhou, Wei; Li, Chang Ming

    2011-07-15

    A bifunctional electro-optical nanoprobe with integrated nanoring electrode and optical nanotip was fabricated and investigated to simultaneously detect both electrical and optical signals in real-time with high spatial resolution. Concurrent measurements of the oxidant generation and the intracellular antioxidant