Science.gov

Sample records for real event detection

  1. Polygraph lie detection on real events in a laboratory setting.

    PubMed

    Bradley, M T; Cullen, M C

    1993-06-01

    This laboratory study dealt with real-life intense emotional events. Subjects generated embarrassing stories from their experience, then submitted to polygraph testing and, by lying, denied their stories and, by telling the truth, denied a randomly assigned story. Money was given as an incentive to be judged innocent on each story. An interrogator, blind to the stories, used Control Question Tests and found subjects more deceptive when lying than when truthful. Stories interacted with order such that lying on the second story was more easily detected than lying on the first. Embarrassing stories provide an alternative to the use of mock crimes to study lie detection in the laboratory.

  2. 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

  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.

  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.

  5. 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

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

    PubMed

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

    2015-08-01

    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.

  7. Exploiting semantics for scheduling real-time data collection from sensors to maximize event detection

    NASA Astrophysics Data System (ADS)

    Vaisenberg, Ronen; Mehrotra, Sharad; Ramanan, Deva

    2009-01-01

    A distributed camera network allows for many compelling applications such as large-scale tracking or event detection. In most practical systems, resources are constrained. Although one would like to probe every camera at every time instant and store every frame, this is simply not feasible. Constraints arise from network bandwidth restrictions, I/O and disk usage from writing images, and CPU usage needed to extract features from the images. Assume that, due to resource constraints, only a subset of sensors can be probed at any given time unit. This paper examines the problem of selecting the "best" subset of sensors to probe under some user-specified objective - e.g., detecting as much motion as possible. With this objective, we would like to probe a camera when we expect motion, but would not like to waste resources on a non-active camera. The main idea behind our approach is the use of sensor semantics to guide the scheduling of resources. We learn a dynamic probabilistic model of motion correlations between cameras, and use the model to guide resource allocation for our sensor network. Although previous work has leveraged probabilistic models for sensor-scheduling, our work is distinct in its focus on real-time building-monitoring using a camera network. We validate our approach on a sensor network of a dozen cameras spread throughout a university building, recording measurements of unscripted human activity over a two week period. We automatically learnt a semantic model of typical behaviors, and show that one can significantly improve effciency of resource allocation by exploiting this model.

  8. 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.

  9. A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits.

    PubMed

    Gouwanda, Darwin; Gopalai, Alpha Agape

    2015-02-01

    Gait events detection allows clinicians and biomechanics researchers to determine timing of gait events, to estimate duration of stance phase and swing phase and to segment gait data. It also aids biomedical engineers to improve the design of orthoses and FES (functional electrical stimulation) systems. In recent years, researchers have resorted to using gyroscopes to determine heel-strike (HS) and toe-off (TO) events in gait cycles. However, these methods are subjected to significant delays when implemented in real-time gait monitoring devices, orthoses, and FES systems. Therefore, the work presented in this paper proposes a method that addresses these delays, to ensure real-time gait event detection. The proposed algorithm combines the use of heuristics and zero-crossing method to identify HS and TO. Experiments involving: (1) normal walking; (2) walking with knee brace; and (3) walking with ankle brace for overground walking and treadmill walking were designed to verify and validate the identified HS and TO. The performance of the proposed method was compared against the established gait detection algorithms. It was observed that the proposed method produced detection rate that was comparable to earlier reported methods and recorded reduced time delays, at an average of 100 ms.

  10. A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits.

    PubMed

    Gouwanda, Darwin; Gopalai, Alpha Agape

    2015-02-01

    Gait events detection allows clinicians and biomechanics researchers to determine timing of gait events, to estimate duration of stance phase and swing phase and to segment gait data. It also aids biomedical engineers to improve the design of orthoses and FES (functional electrical stimulation) systems. In recent years, researchers have resorted to using gyroscopes to determine heel-strike (HS) and toe-off (TO) events in gait cycles. However, these methods are subjected to significant delays when implemented in real-time gait monitoring devices, orthoses, and FES systems. Therefore, the work presented in this paper proposes a method that addresses these delays, to ensure real-time gait event detection. The proposed algorithm combines the use of heuristics and zero-crossing method to identify HS and TO. Experiments involving: (1) normal walking; (2) walking with knee brace; and (3) walking with ankle brace for overground walking and treadmill walking were designed to verify and validate the identified HS and TO. The performance of the proposed method was compared against the established gait detection algorithms. It was observed that the proposed method produced detection rate that was comparable to earlier reported methods and recorded reduced time delays, at an average of 100 ms. PMID:25619613

  11. Comparison of real-time PCR detection chemistries and cycling modes using Mon810 event-specific assays as model.

    PubMed

    La Paz, José Luis; Esteve, Teresa; Pla, Maria

    2007-05-30

    The most widely accepted methods for accurate quantitative detection of genetically modified organisms rely on real-time PCR. Various detection chemistries are available for real-time PCR. They include sequence-unspecific DNA labeling dyes such SYBR-Green I and the use of both universal (e.g., AmpliFluor) and sequence-specific double-labeled probes, the latter comprising hybridization (e.g., Molecular Beacon) and hydrolysis (e.g., TaqMan or MGB) probes. Also, new real-time PCR devices and reagents allowing fast cycling reactions exist. Five Mon810 real-time PCR assays were developed in which the event specificity was based on the detection of transgene and plant rearranged sequences found to 3' flank the insertion site. Every assay was specifically designed for one particular detection chemistry, that is, AmpliFluor, Molecular Beacon, MGB, TaqMan, and SYBR-Green I. When possible, the assays were adapted to fast cycling mode. All assays displayed satisfactory performance parameters, although Molecular Beacon, MGB, and TaqMan chemistries were the most suitable for quantification purposes in both conventional and fast cycling modes.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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

  20. A real-time quantitative PCR detection method specific to widestrike transgenic cotton (event 281-24-236/3006-210-23).

    PubMed

    Baeumler, Stefan; Wulff, Dörte; Tagliani, Laura; Song, Ping

    2006-09-01

    In compliance with global regulations on transgenic crops, a real-time quantitative PCR method specific to Widestrike transgenic cotton (event 281-24-236/3006-210-23, OECD Unique Identifier DAS-24236-5/DAS-21023-5) was established on the basis of the DNA sequences in the junction between the transgene insert and cotton genome. The optimized method consists of a DNA extraction method for cotton seeds and three PCR systems corresponding to a cotton-specific endogenous reference DNA sequence SAH7 (Sinapis Arabidopsis Homolog 7) and specific detection of event 281-24-236 and event 3006-210-23. The method performance including specificity, sensitivity, accuracy, and precision was determined at a dynamic range of Widestrike DNA levels from 0.04% to 5.0%. The limits of detection (LOD) and quantification (LOQ) were < or =0.04% and < or =0.09%, respectively, at 100 ng of DNA sample per reaction. The quantification results using either the event 281-24-236 or 3006-210-23 system were consistent, and the relative deviation from the expected (true) value was in the range of +/-25%. The robustness of the method was demonstrated by a series of tests with deviations from the optimized assay parameters such as annealing temperature, extension time, PCR instrument, interlaboratory transferability, etc. All the measurements from these tests met the criteria set by EU JRC-CRL (European Commission Joint Research Centre-Community Reference Lab). This real-time quantitative PCR method is accurate and robust, and is recommended as a global benchmark method for the detection and quantification of Widestrike cotton. The method including description, protocol, and performance results is available on the JRC-CRL website (http://gmo-crl.jrc.it/statusofdoss.htm). PMID:16939306

  1. A real-time quantitative PCR detection method specific to widestrike transgenic cotton (event 281-24-236/3006-210-23).

    PubMed

    Baeumler, Stefan; Wulff, Dörte; Tagliani, Laura; Song, Ping

    2006-09-01

    In compliance with global regulations on transgenic crops, a real-time quantitative PCR method specific to Widestrike transgenic cotton (event 281-24-236/3006-210-23, OECD Unique Identifier DAS-24236-5/DAS-21023-5) was established on the basis of the DNA sequences in the junction between the transgene insert and cotton genome. The optimized method consists of a DNA extraction method for cotton seeds and three PCR systems corresponding to a cotton-specific endogenous reference DNA sequence SAH7 (Sinapis Arabidopsis Homolog 7) and specific detection of event 281-24-236 and event 3006-210-23. The method performance including specificity, sensitivity, accuracy, and precision was determined at a dynamic range of Widestrike DNA levels from 0.04% to 5.0%. The limits of detection (LOD) and quantification (LOQ) were < or =0.04% and < or =0.09%, respectively, at 100 ng of DNA sample per reaction. The quantification results using either the event 281-24-236 or 3006-210-23 system were consistent, and the relative deviation from the expected (true) value was in the range of +/-25%. The robustness of the method was demonstrated by a series of tests with deviations from the optimized assay parameters such as annealing temperature, extension time, PCR instrument, interlaboratory transferability, etc. All the measurements from these tests met the criteria set by EU JRC-CRL (European Commission Joint Research Centre-Community Reference Lab). This real-time quantitative PCR method is accurate and robust, and is recommended as a global benchmark method for the detection and quantification of Widestrike cotton. The method including description, protocol, and performance results is available on the JRC-CRL website (http://gmo-crl.jrc.it/statusofdoss.htm).

  2. 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.

  3. Detection of solar events

    DOEpatents

    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.

  4. Event-specific detection of stacked genetically modified maize Bt11 x GA21 by UP-M-PCR and real-time PCR.

    PubMed

    Xu, Wentao; Yuan, Yanfang; Luo, Yunbo; Bai, Weibin; Zhang, Chunjiao; Huang, Kunlun

    2009-01-28

    More and more stacked GMOs have been developed for more improved functional properties and/or a stronger intended characteristic, such as antipest, improved product efficiency etc. Bt11 x GA21 is a new kind of stacked GM maize developed by Monsanto Company. Since there are no unique flanking sequences in stacked GMOs, up to now, no appropriate method has been reported to accurately detect them. In this passage, a novel universal primer multiplex PCR (UP-M-PCR) was developed and applied as a rapid screening method for the simultaneous detection of five target sequences (NOS, 35S, Bt11 event, GA21 event, and IVR) in maize Bt11 x GA21. This method overcame the disadvantages rooted deeply in conventional multiplex PCR such as complex manipulation, lower sensitivity, self-inhibition and amplification disparity resulting from different primers. What's more, it got a high specificity and had a detection limit of 0.1% (approximates to 38 haploid genome copies). Furthermore, real-time PCR combined with multivariate statistical analysis was used for accurate quantification of stacked GM maize Bt11 x GA21 in 100% GM maize mixture (Bt11 x GA21, Bt11 and GA21). Detection results showed that this method could accurately validate the content of Bt11, GA21 and Bt11 x GA21 in 100% GM mixture with a detection limit of 0.5% (approximates to 200 haploid genome copies) and a low relative standard deviation <5%. All the data proved that this method may be widely applied in event-specific detection of other stacked GMOs in GM-mixture.

  5. 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

  6. 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.

  7. Infrasound ray tracing models for real events

    NASA Astrophysics Data System (ADS)

    Averbuch, Gil; Applbaum, David; Price, Colin; Ben Horin, Yochai

    2015-04-01

    Infrasound ray tracing models for real events C. Price1, G. Averbuch1, D. Applbaum1, Y. Ben Horin2 (1) Department of Geosciences, Tel Aviv University, Israel (2) Soreq Nuclear Research Center, Yavne, Israel Ray tracing models for infrasound propagation require two atmospheric parameters: the speed of sound profile and the wind profile. The usage of global atmospheric models for the speed of sound and wind profiles raises a fundamental question: can these models provide accurate results for modeling real events that have been detected by the infrasound arrays? Moreover, can these models provide accurate results for events that occurred during extreme weather conditions? We use 2D and 3D ray tracing models based on a modified Hamiltonian for a moving medium. Radiosonde measurements enable us to update the first 20 km of both speed of sound and wind profiles. The 2009 and 2011 Sayarim calibration experiments in Israel served us as a test for the models. In order to answer the question regarding the accuracy of the model during extreme weather conditions, we simulate infrasound sprite signals that were detected by the infrasound array in Mt. Meron, Israel. The results from modeling the Sayarim experiment provided us sufficient insight to conclude that ray tracing modeling can provide accurate results for real events that occurred during fair weather conditions. We conclude that the time delay in the model of the 2009 experiment is due to lack of accuracy in the wind and speed of sound profiles. Perturbed profiles provide accurate results. Earlier arrivals in 2011 are a result of the assumption that the earth is flat (no topography) and the use of local radiosonde measurements for the entire model. Using local radiosonde measurements only for part of the model and neglecting them on other parts prevents the early arrivals. We were able to determine which sprite is the one that got detected in the infrasound array as well as providing a height range for the sprite

  8. Detection of Saharan dust and biomass burning events using near-real-time intensive aerosol optical properties in the north-western Mediterranean

    NASA Astrophysics Data System (ADS)

    Ealo, Marina; Alastuey, Andrés; Ripoll, Anna; Pérez, Noemí; Cruz Minguillón, María; Querol, Xavier; Pandolfi, Marco

    2016-10-01

    The study of Saharan dust events (SDEs) and biomass burning (BB) emissions are both topics of great scientific interest since they are frequent and important polluting scenarios affecting air quality and climate. The main aim of this work is evaluating the feasibility of using near-real-time in situ aerosol optical measurements for the detection of these atmospheric events in the western Mediterranean Basin (WMB). With this aim, intensive aerosol optical properties (SAE: scattering Ångström exponent, AAE: absorption Ångström exponent, SSAAE: single scattering albedo Ångström exponent and g: asymmetry parameter) were derived from multi-wavelength aerosol light scattering, hemispheric backscattering and absorption measurements performed at regional (Montseny; MSY, 720 m a.s.l.) and continental (Montsec; MSA, 1570 m a.s.l.) background sites in the WMB. A sensitivity study aiming at calibrating the measured intensive optical properties for SDEs and BB detection is presented and discussed. The detection of SDEs by means of the SSAAE parameter and Ångström matrix (made up by SAE and AAE) depended on the altitude of the measurement station and on SDE intensity. At MSA (mountain-top site) SSAAE detected around 85 % of SDEs compared with 50 % at the MSY station, where pollution episodes dominated by fine anthropogenic particles frequently masked the effect of mineral dust on optical properties during less intense SDEs. Furthermore, an interesting feature of SSAAE was its capability to detect the presence of mineral dust after the end of SDEs. Thus, resuspension processes driven by summer regional atmospheric circulations and dry conditions after SDEs favoured the accumulation of mineral dust at regional level having important consequences for air quality. On average, SAE, AAE and g ranged between -0.7 and 1, 1.3 and 2.5 and 0.5 and 0.75 respectively during SDEs. Based on the aethalometer model, BB contribution to equivalent black carbon (BC) accounted for 36 and 40

  9. 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

  10. 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.

  11. 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.

  12. GPU Accelerated Event Detection Algorithm

    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

  13. GPU Accelerated Event Detection Algorithm

    SciTech Connect

    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 also 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.

  14. 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.

  15. 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

  16. 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…

  17. How to accurately detect autobiographical events.

    PubMed

    Sartori, Giuseppe; Agosta, Sara; Zogmaister, Cristina; Ferrara, Santo Davide; Castiello, Umberto

    2008-08-01

    We describe a new method, based on indirect measures of implicit autobiographical memory, that allows evaluation of which of two contrasting autobiographical events (e.g., crimes) is true for a given individual. Participants were requested to classify sentences describing possible autobiographical events by pressing one of two response keys. Responses were faster when sentences related to truly autobiographical events shared the same response key with other sentences reporting true events and slower when sentences related to truly autobiographical events shared the same response key with sentences reporting false events. This method has possible application in forensic settings and as a lie-detection technique.

  18. 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.

  19. Efficient method for events detection in phonocardiographic signals

    NASA Astrophysics Data System (ADS)

    Martinez-Alajarin, Juan; Ruiz-Merino, Ramon

    2005-06-01

    The auscultation of the heart is still the first basic analysis tool used to evaluate the functional state of the heart, as well as the first indicator used to submit the patient to a cardiologist. In order to improve the diagnosis capabilities of auscultation, signal processing algorithms are currently being developed to assist the physician at primary care centers for adult and pediatric population. A basic task for the diagnosis from the phonocardiogram is to detect the events (main and additional sounds, murmurs and clicks) present in the cardiac cycle. This is usually made by applying a threshold and detecting the events that are bigger than the threshold. However, this method usually does not allow the detection of the main sounds when additional sounds and murmurs exist, or it may join several events into a unique one. In this paper we present a reliable method to detect the events present in the phonocardiogram, even in the presence of heart murmurs or additional sounds. The method detects relative maxima peaks in the amplitude envelope of the phonocardiogram, and computes a set of parameters associated with each event. Finally, a set of characteristics is extracted from each event to aid in the identification of the events. Besides, the morphology of the murmurs is also detected, which aids in the differentiation of different diseases that can occur in the same temporal localization. The algorithms have been applied to real normal heart sounds and murmurs, achieving satisfactory results.

  20. Detecting Extreme Events in Gridded Climate Data

    SciTech Connect

    Ramachandra, Bharathkumar; Gadiraju, Krishna; Vatsavai, Raju; Kaiser, Dale Patrick; Karnowski, Thomas Paul

    2016-01-01

    Detecting and tracking extreme events in gridded climatological data is a challenging problem on several fronts: algorithms, scalability, and I/O. Successful detection of these events will give climate scientists an alternate view of the behavior of different climatological variables, leading to enhanced scientific understanding of the impacts of events such as heat and cold waves, and on a larger scale, the El Nin o Southern Oscillation. Recent advances in computing power and research in data sciences enabled us to look at this problem with a different perspective from what was previously possible. In this paper we present our computationally efficient algorithms for anomalous cluster detection on climate change big data. We provide results on detection and tracking of surface temperature and geopotential height anomalies, a trend analysis, and a study of relationships between the variables. We also identify the limitations of our approaches, future directions for research and alternate approaches.

  1. 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

  2. Semantic Context Detection Using Audio Event Fusion

    NASA Astrophysics Data System (ADS)

    Chu, Wei-Ta; Cheng, Wen-Huang; Wu, Ja-Ling

    2006-12-01

    Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs) are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model) and discriminative (support vector machine (SVM)) approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.

  3. 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.

  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. Subnoise detection of a fast random event.

    PubMed

    Ataie, V; Esman, D; Kuo, B P-P; Alic, N; Radic, S

    2015-12-11

    Observation of random, nonrepetitive phenomena is of critical importance in astronomy, spectroscopy, biology, and remote sensing. Heralded by weak signals, hidden in noise, they pose basic detection challenges. In contrast to repetitive waveforms, a single-instance signal cannot be separated from noise through averaging. Here, we show that a fast, randomly occurring event can be detected and extracted from a noisy background without conventional averaging. An isolated 80-picosecond pulse was received with confidence level exceeding 99%, even when accompanied by noise. Our detector relies on instantaneous spectral cloning and a single-step, coherent field processor. The ability to extract fast, subnoise events is expected to increase detection sensitivity in multiple disciplines. Additionally, the new spectral-cloning receiver can potentially intercept communication signals that are presently considered secure. PMID:26659052

  6. 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…

  7. 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.

  8. 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.

  9. 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.

  10. Multimedia event detection using visual concept signatures

    NASA Astrophysics Data System (ADS)

    Younessian, Ehsan; Quinn, Michael; Mitamura, Teruko; Hauptmann, Alex

    2013-03-01

    Multimedia Event Detection (MED) is a multimedia retrieval task with the goal of finding videos of a particular event in a large-scale Internet video archive, given example videos and text descriptions. In this paper, we mainly focus on an 'ad-hoc' scenario in MED where we do not use any example video. We aim to retrieve test videos based on their visual semantics using a Visual Concept Signature (VCS) generated for each event only derived from the event description provided as the query. Visual semantics are described using the Semantic INdexing (SIN) feature which represents the likelihood of predefined visual concepts in a video. To generate a VCS for an event, we project the given event description to a visual concept list using the proposed textual semantic similarity. Exploring SIN feature properties, we harmonize the generated visual concept signature and the SIN feature to improve retrieval performance. We conduct different experiments to assess the quality of generated visual concept signatures with respect to human expectation, and in the context of the MED task to retrieve the SIN feature of videos in the test dataset when we have no or only very few training videos.

  11. 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%.

  12. 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

  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.

  14. 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

  15. 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.

  16. Accelerated forgetting of real-life events in Transient Epileptic Amnesia.

    PubMed

    Muhlert, N; Milton, F; Butler, C R; Kapur, N; Zeman, A Z

    2010-09-01

    Transient Epileptic Amnesia (TEA) is a form of temporal lobe epilepsy associated with ictal and interictal memory disturbance. Some patients with TEA exhibit Accelerated Long-term Forgetting (ALF), in which memory for verbal and non-verbal material is retained normally over short delays but fades at an unusually rapid rate over days to weeks. This study addresses three questions about ALF in TEA: (i) whether real-life events undergo ALF in a similar fashion to laboratory-based stimuli; (ii) whether ALF can be detected within 24h; (iii) whether procedural memories are susceptible to ALF. Eleven patients with TEA and eleven matched healthy controls wore a novel, automatic camera, SenseCam, while visiting a local attraction. Memory for images of events was assessed on the same day and after delays of one day, one week, and three weeks. Forgetting of real-life events was compared with forgetting of a word list and with performance on a procedural memory task. On the day of their excursion, patients and controls recalled similar numbers of primary events, associated secondary details (contiguous events, thoughts and sensory information) and items from the word list. In contrast, patients showed ALF for primary events over three weeks, with ALF for contiguous events, thoughts and words over the first day. Retention on the procedural memory task was normal over three weeks. The results indicate that accelerated forgetting in TEA: (i) affects memory for real-life events as well as laboratory stimuli; (ii) is maximal over the first day; and (iii) is specific to declarative memories.

  17. Real-time probing of radical events with sulfide molecules

    NASA Astrophysics Data System (ADS)

    Gauduel, Yann A.; Glinec, Yannick; Malka, Victor

    2007-02-01

    The physio-pathological roles of sulfide biomolecules in cellular environments involves redox processes and radical reactions that alter or protect the functional properties of enzymatic systems, proteins and nucleic acids repair. We focus on micromolar monitoring of sulfur-centered radical anions produced by direct electron attachment, using sulfide molecules (a thioether and a disulfide biomolecule) and two complementary spectroscopic approaches: low energy radiation femtochemistry (1-8 eV) and high energy radiation femtochemistry (2.5-15 MeV). The early step of a disulfide bond making RS∴SR from thiol molecules involves a very-short lived odd-electron bonded intermediate for which an excess electron is transiently localized by a preexisting two sulfide monomers complex. The reactive center of oxidized glutathione (cystamine), a major cytoplasmic disulfide biomolecule, is also used as sensor for the real-time IR investigation of effective reaction radius r eff in homogenous aqueous environments and interfacial water of biomimetic systems. Femtosecond high-energy electrons beams, typically in the 2.5 - 15 MeV range, may conjecture the picosecond observation of primary radical events in nanometric radiation spurs. The real-time investigation of sulfide and disulfide molecules opens exciting opportunities for sensitisation of confined environments (aqueous groove of DNA, protein pockets, sub-cellular systems) to ionizing radiation. Low and high-energy femtoradical probing foreshadow the development of new applications in radiobiology (low dose effect at the nanometric scale) and anticancer radiotherapy (pro-drogue activation).

  18. 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.

  19. 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.

  20. Application of real time recurrent neural network for detection of small natural earthquakes in Poland

    NASA Astrophysics Data System (ADS)

    Wiszniowski, Jan; Plesiewicz, Beata; Trojanowski, Jacek

    2014-06-01

    This study is an application of a Real Time Recurrent Neural Network (RTRN) in the detection of small natural seismic events in Poland. Most of the events studied are from the Podhale region with a magnitude of 0.4 to 2.5. The population distribution of the region required that seismic signals be recorded using temporary stations deployed in populated areas. As a consequence, the high level of seismic noise that cannot be removed by filtration made it impossible to detect small events by STA/LTA based algorithms. The presence of high noise requires an alternate method of seismic detection capable of recognizing small seismic events. We applied the RTRN, which potentially can detect seismic signals in the frequency domain as well as in the phase arrival times. Data results of small local seismic events showed that the RTRN has the ability to correctly detect most of the events with fewer false detections than STA/LTA methods.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. Video event detection: from subvolume localization to spatiotemporal path search.

    PubMed

    Tran, Du; Yuan, Junsong; Forsyth, David

    2014-02-01

    Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatiotemporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intraclass variations of the event. Compared to event detection using spatiotemporal sliding windows, the spatiotemporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video data sets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible with different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. PMID:24356358

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG

    PubMed Central

    Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A.

    2016-01-01

    Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies. PMID:27799907

  13. Real-time logo detection and tracking in video

    NASA Astrophysics Data System (ADS)

    George, M.; Kehtarnavaz, N.; Rahman, M.; Carlsohn, M.

    2010-05-01

    This paper presents a real-time implementation of a logo detection and tracking algorithm in video. The motivation of this work stems from applications on smart phones that require the detection of logos in real-time. For example, one application involves detecting company logos so that customers can easily get special offers in real-time. This algorithm uses a hybrid approach by initially running the Scale Invariant Feature Transform (SIFT) algorithm on the first frame in order to obtain the logo location and then by using an online calibration of color within the SIFT detected area in order to detect and track the logo in subsequent frames in a time efficient manner. The results obtained indicate that this hybrid approach allows robust logo detection and tracking to be achieved in real-time.

  14. Real-time PCR detection chemistry.

    PubMed

    Navarro, E; Serrano-Heras, G; Castaño, M J; Solera, J

    2015-01-15

    Real-time PCR is the method of choice in many laboratories for diagnostic and food applications. This technology merges the polymerase chain reaction chemistry with the use of fluorescent reporter molecules in order to monitor the production of amplification products during each cycle of the PCR reaction. Thus, the combination of excellent sensitivity and specificity, reproducible data, low contamination risk and reduced hand-on time, which make it a post-PCR analysis unnecessary, has made real-time PCR technology an appealing alternative to conventional PCR. The present paper attempts to provide a rigorous overview of fluorescent-based methods for nucleic acid analysis in real-time PCR described in the literature so far. Herein, different real-time PCR chemistries have been classified into two main groups; the first group comprises double-stranded DNA intercalating molecules, such as SYBR Green I and EvaGreen, whereas the second includes fluorophore-labeled oligonucleotides. The latter, in turn, has been divided into three subgroups according to the type of fluorescent molecules used in the PCR reaction: (i) primer-probes (Scorpions, Amplifluor, LUX, Cyclicons, Angler); (ii) probes; hydrolysis (TaqMan, MGB-TaqMan, Snake assay) and hybridization (Hybprobe or FRET, Molecular Beacons, HyBeacon, MGB-Pleiades, MGB-Eclipse, ResonSense, Yin-Yang or displacing); and (iii) analogues of nucleic acids (PNA, LNA, ZNA, non-natural bases: Plexor primer, Tiny-Molecular Beacon). In addition, structures, mechanisms of action, advantages and applications of such real-time PCR probes and analogues are depicted in this review.

  15. 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.

  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 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

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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'.

  8. Real-time head motion detection system

    NASA Astrophysics Data System (ADS)

    Mase, Kenji; Watanabe, Yasuhiko; Suenaga, Yasuhito

    1990-01-01

    We present a three-dimensional head motion detection system called a realtime headreader. This headreader analyzes the head motion picture sequences taken by a TV-camera, and extracts the motion parameters in realtime, i.e. 3-d rotations and translations. We used a simple but very fast algorithm, which exploits the contrast of hair and face to recognize face orientation. The system extracts the head and face area, then estimates the head motion parameters from the change in position of each area's centroids. The head motion is computed at nearly 10 frames per second on a SUN4 workstation and the motion parameters are sent to an IRIS workstation at a 2.5 Kbps. The IRIS generates a head motion sequence that duplicates the original head motion. The entire motion detection program is written in C language. No special image processing hardware is used, except for a video digitizer. Our head motion detection system will enhance man-machine interactions by providing a new visual eue. An operator will be able to point to a target by just looking at it thus a mouse or 3-d tracking device is not needed. The eventual goal of this research is to build an intelligent video communication system that codes the information in terms of high level language rather than compressed video signals.

  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. 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.

  11. 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.

  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. Detection of magnetising inrush current using real time integration method

    NASA Astrophysics Data System (ADS)

    Ling, P. C. Y.; Basak, A.

    1990-01-01

    A technique of predicting magnetising inrush currents in transformers is described. Computed results show an inconsistency in second harmonic decay resulting detection failure while using conventional second harmonic techniques. A new detection scheme using real time integration values of the inrush current is proposed to provide reliable relay operation.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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

  20. 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

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

    PubMed

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

    2015-12-15

    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.

  2. Real-Time Road Sign Detection Using Fuzzy-Boosting

    NASA Astrophysics Data System (ADS)

    Yoon, Changyong; Lee, Heejin; Kim, Euntai; Park, Mignon

    This paper describes a vision-based and real-time system for detecting road signs from within a moving vehicle. The system architecture which is proposed in this paper consists of two parts, the learning and the detection part of road sign images. The proposed system has the standard architecture with adaboost algorithm. Adaboost is a popular algorithm which used to detect an object in real time. To improve the detection rate of adaboost algorithm, this paper proposes a new combination method of classifiers in every stage. In the case of detecting road signs in real environment, it can be ambiguous to decide to which class input images belong. To overcome this problem, we propose a method that applies fuzzy measure and fuzzy integral which use the importance and the evaluated values of classifiers within one stage. It is called fuzzy-boosting in this paper. Also, to improve the speed of a road sign detection algorithm using adaboost at the detection step, we propose a method which chooses several candidates by using MC generator. In this paper, as the sub-windows of chosen candidates pass classifiers which are made from fuzzy-boosting, we decide whether a road sign is detected or not. Using experiment result, we analyze and compare the detection speed and the classification error rate of the proposed algorithm applied to various environment and condition.

  3. 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.

  4. Performance evaluation for three pollution detection methods using data from a real contamination accident.

    PubMed

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

    2015-09-15

    Early warning systems have been widely deployed to safeguard water security. Many contamination detection methods have been developed and evaluated in the past decades. Although encouraging detection performance has been obtained and reported, these evaluations mainly used artificial or laboratory data. The evaluation of detection performance with data from real contamination accidents has rarely been conducted. Implementation of contamination event methods without full assessment using field data might lead to failure of an early warning system. In this paper, the detection performance of three contamination detection methods, a Pearson correlation Euclidean distance (PE) based detection method, a multivariate Euclidean distance (MED) method and a linear prediction filter (LPF) method, was evaluated using data from a real contamination accident. Results improve understanding of the implementation of detection methods to field situations and show that all methods are prone to yielding worse detection performance when applied to data from a real contamination accident. They also revealed that the Pearson correlation Euclidean distance based method is more capable of differentiating between equipment noise and presence of contamination and has greater potential to be used in real field situations than the MED and LPF methods.

  5. 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.

  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. Virtual and Real World Adaptation for Pedestrian Detection.

    PubMed

    Vázquez, David; López, Antonio M; Marín, Javier; Ponsa, Daniel; Gerónimo, David

    2014-04-01

    Pedestrian detection is of paramount interest for many applications. Most promising detectors rely on discriminatively learnt classifiers, i.e., trained with annotated samples. However, the annotation step is a human intensive and subjective task worth to be minimized. By using virtual worlds we can automatically obtain precise and rich annotations. Thus, we face the question: can a pedestrian appearance model learnt in realistic virtual worlds work successfully for pedestrian detection in real-world images? Conducted experiments show that virtual-world based training can provide excellent testing accuracy in real world, but it can also suffer the data set shift problem as real-world based training does. Accordingly, we have designed a domain adaptation framework, V-AYLA, in which we have tested different techniques to collect a few pedestrian samples from the target domain (real world) and combine them with the many examples of the source domain (virtual world) in order to train a domain adapted pedestrian classifier that will operate in the target domain. V-AYLA reports the same detection accuracy than when training with many human-provided pedestrian annotations and testing with real-world images of the same domain. To the best of our knowledge, this is the first work demonstrating adaptation of virtual and real worlds for developing an object detector.

  8. Bayesian-network-based soccer video event detection and retrieval

    NASA Astrophysics Data System (ADS)

    Sun, Xinghua; Jin, Guoying; Huang, Mei; Xu, Guangyou

    2003-09-01

    This paper presents an event based soccer video retrieval method, where the scoring even is detected based on Bayesian network from six kinds of cue information including gate, face, audio, texture, caption and text. The topology within the Bayesian network is predefined by hand according to the domain knowledge and the probability distributions are learned in the case of the known structure and full observability. The resulting event probability from the Bayesian network is used as the feature vector to perform the video retrieval. Experiments show that the true and false detection rations for the scoring event are about 90% and 16.67% respectively, and that the video retrieval result based on event is superior to that based on low-level features in the human visual perception.

  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. Detection of Energetic Particle Events with SOHO Space Observatory

    NASA Astrophysics Data System (ADS)

    Rodríguez Frías, D.; Gómez Herrero, R.; Gutiérrez, J.; Del Peral, L.

    2004-09-01

    An analysis of eighteen solar energetic particle (SEP) events measured with the EPHIN instrument on board the SOHO spacecraft has been performed. Via parametrization of temporal profiles, differences among events have been shown by the temporal profile parameters obtained. The detected differences are found to depend on the particle acceleration, the magnetic connection with the acceleration zone and the interplanetary physical characteristics transport to the observing point.

  11. 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

  12. Detection of a second ντ event

    NASA Astrophysics Data System (ADS)

    Ishiguro, Katsumi

    2014-08-01

    OPERA is a neutrino oscillation experiment aiming to prove the tau neutrino appearance for the first time. A tau decay is identified by the detection of its characteristic decay topologies in nuclear emulsion films. OPERA reported the detection of a first tau neutrino event in 2010. We recently detected a second tau neutrino event in the 2011 run sample. The primary vertex has two charged particles of which one exhibits a three-prong vertex in the plastic base of a film after a flight length of 1.54 mm. It satisfies all the selection criteria to be a tau neutrino interaction. Especially the azimuthal angle in the transverse plane between the tau candidate track and the primary track is almost 180 degrees. The number of tau to 3π signal events expected in the analyzed sample is 0.18, the number of background events is 0.05. Considering all modes, the signal expectation is 1.91 events and the background 0.18 events.

  13. Method for early detection of cooling-loss events

    DOEpatents

    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.

  14. Method for early detection of cooling-loss events

    DOEpatents

    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.

  15. Detection of atypical seismic events on a regional scale

    NASA Astrophysics Data System (ADS)

    Solano-Hernandez, E. A.; Hjorleifsdottir, V.; Perez-Campos, X.; Iglesias, A.

    2013-12-01

    We propose an event-detection algorithm to locate seismic events on a regional scale. Our goal is to identify non-impulsive or 'atypical' events which are not detected by regional or global networks, due to their low P-wave amplitude. Ekstrom (2006) has developed and implemented a method to detect and locate sources of long-period seismic surface waves on a global scale. Atypical events are generated by, for example, rapid glacial movements (Ekstrom, et al., 2003; Ekstrom, et al., 2006), volcanic events (Schuler and Ekstrom, 2009) and landslides (Ekstrom and Stark, 2013). Furthermore, non-impulsive earthquakes have been located on oceanic transform faults (Abercrombie and Ekstrom, 2001). The current method (Ekstrom, 2006), that is applied on the scale of the globe, routinely detects events with magnitudes around Mw 5 and larger. In this work we wish to lower the detection threshold by using shorter period records registered by regional networks. The difficulty lies in that the shorter period records are strongly influenced by the heterogeneous crust and upper mantle, which need to be accounted for in the modeling process. Our proposed method involves first computing full waveforms, Green's functions or moment tensor responses, between a grid of test locations and existing seismic stations in a 3D medium. We then effectively back propagate observed data through cross correlation with the responses, obtaining a function that localizes in time and space at the source. Our method is a variant of the timereversal method presented by, for example, McMechan (1982), Tromp et al. (2005), Larmat et al. (2006), Gajewski and Tessmer (2005) and Kim et al. (2010). To calibrate the various parameters used by the detection method, we use the aftershocks sequence of the March 20, 2012 Ometepec, Guerrero, Mexico earthquake, recorded by the SSN (Mexican National Network). The lively aftershock sequence provided us with many events of different magnitudes, all occurring approximately

  16. 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.

  17. Slimhole early kick detection by real-time drilling analysis

    SciTech Connect

    Swanson, B.W.; Gardner, A.G.; Brown, N.P.; Murray, P.J.

    1997-03-01

    Early kick detection has been identified as being of primary importance in slimhole wellbores. Small annular volumes means that, to maintain the integrity of the well, allowable kick volumes must be small. Gas influxes must therefore be detected and shut in rapidly. This paper describes an early kick-detection system developed for slimholes to detect and confirm the presence of an influx rapidly. This system has been run successfully on a number of slimhole operations. The early kick-detection (EKD) system is based on real-time analysis of drilling data obtained directly from a comprehensive mud-logging system on the rig. The analysis technique compares predictions of mud flow out and standpipe pressure from a dynamic wellbore model with corresponding values from the rig. The predicted values are derived from a model driven in real time by rig data such as pump rate and pipe rotation rate. Kick detection is based on deviations between measured data and idealized model predictions. The EKD system has been incorporated into an operational engineer-oriented graphical interface, which has provided easy access to the model for both input and output of data, and for the interpretation of results. This paper describes the design considerations and technology behind the EKD system and the engineering interface. The paper also presents examples of the system running in real time at a slimhole rig site.

  18. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Gonzalez-Gaitan, S.; Medina, G.; Pignata, G.; Galbany, L.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Jaeger, Th. de; Martinez, J.; Munoz, R.; Vera, E.; Perez, C.

    2015-02-01

    HiTS, the High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115, #7122, #7131, #7132), reports the discovery of 5 additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  19. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Pignata, G.; Martinez, J.; Medina, G.; Galbany, L.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Munoz, R.; Vera, E.; Perez, C.

    2015-02-01

    Body: HiTS: The High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115) reports the discovery of 9 additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  20. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Galbany, L.; de Jaeger, Th.; Martinez, J.; Cabrera, G.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Anderson, J.; Bufano, F.; Pignata, G.; Medina, G.; Munoz, R.; Vera, E.

    2015-02-01

    HiTS: The High Cadence Transient Survey (ATELs #5949, #5956, #7099) reports the discovery of one additional supernova candidate detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  1. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Pignata, G.; Gonzalez-Gaitan, S.; Medina, G.; Martinez, J.; Galbany, L.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Jaeger, Th. de; Munoz, R.; Vera, E.; Perez, C.

    2015-02-01

    HiTS: The High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115, #7122, #7131) reports the discovery of 9 additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  2. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Pignata, G.; Gonzalez-Gaitan, S.; Medina, G.; Martinez, J.; Galbany, Â. L.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Jaeger, Th. de; Munoz, R.; Vera, E.; Perez, C.

    2015-02-01

    HiTS: The High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115, #7122) reports the discovery of 9 additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  3. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Gonzalez-Gaitan, S.; Medina, G.; Galbany, L.; Martinez, J.; San Martin, J.; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Pignata, G.; de Jaeger, Th.; Munoz, R.; Vera, E.; Perez, C.; Points, S.

    2015-03-01

    HiTS, the High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115, #7122, #7131, #7146, #7148, #7149), reports the discovery of additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  4. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Galbany, L.; De Jaeger, Th.; Gonzalez-Gaitan, S.; Martinez, J.; Cabrera, G.; San Martin, J.; Hamuy, M.; Estevez, P.; Smith, R. C.,; Vivas, K.; Flores, S.; Huijse, P.; Anderson, J.; Bufano, F.; Pignata, G.; Medina, G.; Munoz, R.; Vera, E.

    2015-02-01

    HiTS: The High Cadence Transient Survey (ATELs #5949, #5956, #7099) reports the discovery of 4 additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  5. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Gonzalez-Gaitan, S.; Medina, G.; Galbany, L.; Martinez, J.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Pignata, G.; Jaeger, Th. de; Munoz, R.; Vera, E.; Perez, C.

    2015-02-01

    HiTS, the High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115, #7122, #7131, #7146, #7148), reports the discovery of additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  6. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Gonzalez-Gaitan, S.; Medina, G.; Galbany, L.; Martinez, J.; Martin, J. San; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Cabrera, G.; Anderson, J.; Bufano, F.; Pignata, G.; Jaeger, Th. de; Munoz, R.; Vera, E.; Perez, C.

    2015-02-01

    HiTS, the High Cadence Transient Survey (see ATELs #5949, #5956, #7099, #7108, #7115, #7122, #7131, #7146), reports the discovery of additional supernova candidates detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  7. HiTS real-time supernova detections

    NASA Astrophysics Data System (ADS)

    Forster, F.; Maureira, J. C.; Galbany, L.; De Jaeger, Th.; Gonzalez-Gaitan, S.; Martinez, J.; Cabrera, G.; San Martin, J.; Hamuy, M.; Estevez, P.; Smith, R. C.; Vivas, K.; Flores, S.; Huijse, P.; Anderson, J.; Bufano, F.; Pignata, G.; Medina, G.; Munoz, R.; Vera, E.

    2015-02-01

    HiTS: The High Cadence Transient Survey (ATELs #5949, #5956) reports the discovery of 4 possible supernova explosions detected using a novel real-time high-cadence image subtraction / classification pipeline developed at the Center for Mathematical Modelling (CMM) in collaboration with the Millennium Institute for Astrophysics (MAS).

  8. 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) ...

  9. Human Rights Event Detection from Heterogeneous Social Media Graphs.

    PubMed

    Chen, Feng; Neill, Daniel B

    2015-03-01

    Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions. PMID:27442843

  10. Human Rights Event Detection from Heterogeneous Social Media Graphs.

    PubMed

    Chen, Feng; Neill, Daniel B

    2015-03-01

    Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions.

  11. Detection of abnormal events via optical flow feature analysis.

    PubMed

    Wang, Tian; Snoussi, Hichem

    2015-03-24

    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.

  12. 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

  13. Molecular beacon real-time PCR detection of swine viruses.

    PubMed

    McKillen, John; Hjertner, Bernt; Millar, Andrena; McNeilly, Francis; Belák, Sándor; Adair, Brian; Allan, Gordon

    2007-03-01

    Rapid and reliable detection of viral pathogens is critical for the management of the diseases threatening the economic competitiveness of the swine farming industry worldwide. Molecular beacon assays are one type of real-time polymerase chain reaction (PCR) technology capable of fast, specific, sensitive, and reliable viral detection. In this paper, the development of molecular beacon assays as novel tools for the rapid detection of Aujeszky's disease virus, African swine fever virus, porcine circovirus type 2 and porcine parvovirus is described. The assays are capable of rapidly detecting 2 x 10(1) copies of target and are linear between 2 x 10(9) and 2 x 10(2) copies. They can detect virus specifically in clinical samples such as whole blood, serum and tissue. In comparison to conventional PCR they are either as sensitive or more sensitive. As such these molecular beacon assays represent a powerful tool for the detection of these viruses in swine.

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

    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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Terahertz real-time imaging for nondestructive detection

    NASA Astrophysics Data System (ADS)

    Zhang, LiangLiang; Karpowicz, Nick; Zhang, CunLin; Zhao, YueJin; Zhang, XiCheng

    2008-03-01

    We present a real time imaging measurement in the terahertz (THz) frequency region. The dynamic subtraction technique is used to reduce long-term optical background drift. The reflective images of two targets, a Nikon camera's lens cap and a plastic toy gun, are obtained. For the lens cap, the image data were processed to be false color images. For the toy gun, we show that even under an optically opaque canvas bag, a clear terahertz image is obtained. It is shown that terahertz real time imaging can be used to nondestructively detect concealed objects.

  2. 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.

  3. 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.

  4. Approaching near real-time biosensing: microfluidic microsphere based biosensor for real-time analyte detection.

    PubMed

    Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania

    2015-04-15

    In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. A coincidence detection system based on real-time software

    NASA Astrophysics Data System (ADS)

    Ayuso, Sindulfo; José Blanco, Juan; Medina, José; Gómez-Herrero, Raúl; García-Población, Oscar; García Tejedor, Ignacio

    2016-09-01

    Conventional real-time coincidence systems use electronic circuitry to detect coincident pulses (hardware coincidence). In this work, a new concept of coincidence system based on real-time software (software coincidence) is presented. This system is based on the recurrent supervision of the analogue-to-digital converters status, which is described in detail. A prototype has been designed and built using a low-cost development platform. It has been applied to two different experimental sets for cosmic ray muon detection. Experimental muon measurements recorded simultaneously using conventional hardware coincidence and our software coincidence system have been compared, yielding identical results. These measurements have also been validated using simultaneous neutron monitor observations. This new software coincidence system provides remarkable advantages such as higher simplicity of interconnection and adjusting. Thus, our system replaces, at least, three Nuclear Instrument Modules (NIMs) required by conventional coincidence systems, reducing its cost by a factor of 40 and eliminating pulse delay adjustments.

  16. Real-Time EEG-Based Happiness Detection System

    PubMed Central

    2013-01-01

    We propose to use real-time EEG signal to classify happy and unhappy emotions elicited by pictures and classical music. We use PSD as a feature and SVM as a classifier. The average accuracies of subject-dependent model and subject-independent model are approximately 75.62% and 65.12%, respectively. Considering each pair of channels, temporal pair of channels (T7 and T8) gives a better result than the other area. Considering different frequency bands, high-frequency bands (Beta and Gamma) give a better result than low-frequency bands. Considering different time durations for emotion elicitation, that result from 30 seconds does not have significant difference compared with the result from 60 seconds. From all of these results, we implement real-time EEG-based happiness detection system using only one pair of channels. Furthermore, we develop games based on the happiness detection system to help user recognize and control the happiness. PMID:24023532

  17. 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

  18. 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

  19. 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.

  20. 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

  1. 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%.

  2. 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.

  3. Weakly supervised learning of a classifier for unusual event detection.

    PubMed

    Jäger, Mark; Knoll, Christian; Hamprecht, Fred A

    2008-09-01

    In this paper, we present an automatic classification framework combining appearance based features and hidden Markov models (HMM) to detect unusual events in image sequences. One characteristic of the classification task is that anomalies are rare. This reflects the situation in the quality control of industrial processes, where error events are scarce by nature. As an additional restriction, class labels are only available for the complete image sequence, since frame-wise manual scanning of the recorded sequences for anomalies is too expensive and should, therefore, be avoided. The proposed framework reduces the feature space dimension of the image sequences by employing subspace methods and encodes characteristic temporal dynamics using continuous hidden Markov models (CHMMs). The applied learning procedure is as follows. 1) A generative model for the regular sequences is trained (one-class learning). 2) The regular sequence model (RSM) is used to locate potentially unusual segments within error sequences by means of a change detection algorithm (outlier detection). 3) Unusual segments are used to expand the RSM to an error sequence model (ESM). The complexity of the ESM is controlled by means of the Bayesian Information Criterion (BIC). The likelihood ratio of the data given the ESM and the RSM is used for the classification decision. This ratio is close to one for sequences without error events and increases for sequences containing error events. Experimental results are presented for image sequences recorded from industrial laser welding processes. We demonstrate that the learning procedure can significantly reduce the user interaction and that sequences with error events can be found with a small false positive rate. It has also been shown that a modeling of the temporal dynamics is necessary to reach these low error rates.

  4. Gait event detection during stair walking using a rate gyroscope.

    PubMed

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

    2014-03-19

    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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  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.

  10. 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

  11. 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.

  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. Real-time Monitoring of Discrete Synaptic Release Events and Excitatory Potentials within Self-reconstructed Neuromuscular Junctions.

    PubMed

    Li, Yu-Tao; Zhang, Shu-Hui; Wang, Xue-Ying; Zhang, Xin-Wei; Oleinick, Alexander I; Svir, Irina; Amatore, Christian; Huang, Wei-Hua

    2015-08-01

    Chemical synaptic transmission is central to the brain functions. In this regard, real-time monitoring of chemical synaptic transmission during neuronal communication remains a great challenge. In this work, in vivo-like oriented neural networks between superior cervical ganglion (SCG) neurons and their effector smooth muscle cells (SMC) were assembled in a microfluidic device. This allowed amperometric detection of individual neurotransmitter release events inside functional SCG-SMC synapse with carbon fiber nanoelectrodes as well as recording of postsynaptic potential using glass nanopipette electrodes. The high vesicular release activities essentially involved complex events arising from flickering fusion pores as quantitatively established based on simulations. This work allowed for the first time monitoring in situ chemical synaptic transmission under conditions close to those found in vivo, which may yield important and new insights into the nature of neuronal communications. PMID:26079517

  14. Real-Time Analytics for the Healthcare Industry: Arrhythmia Detection.

    PubMed

    Agneeswaran, Vijay Srinivas; Mukherjee, Joydeb; Gupta, Ashutosh; Tonpay, Pranay; Tiwari, Jayati; Agarwal, Nitin

    2013-09-01

    It is time for the healthcare industry to move from the era of "analyzing our health history" to the age of "managing the future of our health." In this article, we illustrate the importance of real-time analytics across the healthcare industry by providing a generic mechanism to reengineer traditional analytics expressed in the R programming language into Storm-based real-time analytics code. This is a powerful abstraction, since most data scientists use R to write the analytics and are not clear on how to make the data work in real-time and on high-velocity data. Our paper focuses on the applications necessary to a healthcare analytics scenario, specifically focusing on the importance of electrocardiogram (ECG) monitoring. A physician can use our framework to compare ECG reports by categorization and consequently detect Arrhythmia. The framework can read the ECG signals and uses a machine learning-based categorizer that runs within a Storm environment to compare different ECG signals. The paper also presents some performance studies of the framework to illustrate the throughput and accuracy trade-off in real-time analytics.

  15. 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

  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. 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.

  18. 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.

  19. 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.

  20. Pre-trained D-CNN models for detecting complex events in unconstrained videos

    NASA Astrophysics Data System (ADS)

    Robinson, Joseph P.; Fu, Yun

    2016-05-01

    Rapid event detection faces an emergent need to process large videos collections; whether surveillance videos or unconstrained web videos, the ability to automatically recognize high-level, complex events is a challenging task. Motivated by pre-existing methods being complex, computationally demanding, and often non-replicable, we designed a simple system that is quick, effective and carries minimal overhead in terms of memory and storage. Our system is clearly described, modular in nature, replicable on any Desktop, and demonstrated with extensive experiments, backed by insightful analysis on different Convolutional Neural Networks (CNNs), as stand-alone and fused with others. With a large corpus of unconstrained, real-world video data, we examine the usefulness of different CNN models as features extractors for modeling high-level events, i.e., pre-trained CNNs that differ in architectures, training data, and number of outputs. For each CNN, we use 1-fps from all training exemplar to train one-vs-rest SVMs for each event. To represent videos, frame-level features were fused using a variety of techniques. The best being to max-pool between predetermined shot boundaries, then average-pool to form the final video-level descriptor. Through extensive analysis, several insights were found on using pre-trained CNNs as off-the-shelf feature extractors for the task of event detection. Fusing SVMs of different CNNs revealed some interesting facts, finding some combinations to be complimentary. It was concluded that no single CNN works best for all events, as some events are more object-driven while others are more scene-based. Our top performance resulted from learning event-dependent weights for different CNNs.

  1. Towards perception awareness: Perceptual event detection for Brain computer interfaces.

    PubMed

    Nejati, Hossein; Tsourides, Kleovoulos; Pomponiu, Victor; Ehrenberg, Evan C; Ngai-Man Cheung; Sinha, Pawan

    2015-08-01

    Brain computer interface (BCI) technology is becoming increasingly popular in many domains such as entertainment, mental state analysis, and rehabilitation. For robust performance in these domains, detecting perceptual events would be a vital ability, enabling adaptation to and act on the basis of user's perception of the environment. Here we present a framework to automatically mine spatiotemporal characteristics of a given perceptual event. As this "signature" is derived directly from subject's neural behavior, it can serve as a representation of the subject's perception of the targeted scenario, which in turn allows a BCI system to gain a new level of context awareness: perception awareness. As a proof of concept, we show the application of the proposed framework on MEG signal recordings from a face perception study, and the resulting temporal and spatial characteristics of the derived neural signature, as well as it's compatibility with the neuroscientific literature on face perception.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Pulsed illumination, closed circuit television system for real-time viewing of unsteady (> 1 micros) events.

    PubMed

    Marden, W W; Steinberger, R L; Bracco, F V

    1978-10-01

    A pulsed illumination closed circuit television system is described whereby fast (times <33 ms), unsteady events can be observed in real time. A low-power helium-neon laser beam is modulated to send a short duration light pulse through the unsteady test medium. The light is refracted according to the instantaneous optical properties of the medium. The refracted light travels to a solid state television camera, known as a charge injection device (CID), in which the sensor array is charged within microseconds. The scanning of the charged array then follows, requiring the standard 33 ms for information transfer to video tape and a TV monitor. The image is thus formed during the laser pulse duration (which presently is 10 to 100 micros, but shorter duration pulses are possible with more powerful lasers), but no more than one image every 33 ms can be observed and recorded. Thus this method is particularly suited for the investigation of high frequency periodic events in which one can observe both a single image, or an ensemble average of as many as 100 images, occurring at corresponding times in different cycles. The reported applications include the recording of steady and transient propane torch flames, of the transient fuel injection process in a motored internal combustion engine, and of the propagation of a flame under firing conditions in the engine. In the shadowgraph and Schlieren modes the method is particularly suited for application to periodic combustion events such as those occurring in internal combustion engines. The method then presents the following advantages over high-speed filming (> 3000 pictures/s); real-time observation and recording of chamber events at any crankangle; real-time observation and recording of the effects of changes in the engine variables (speed, load, spark timing, injection pressure and duration, chamber swirl, etc.) on the combustion events; real-time observation and recording of ensemble averages and cycle-to-cycle variations

  11. 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.

  12. 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.

  13. Using real-world healthcare data for pharmacovigilance signal detection - the experience of the EU-ADR project.

    PubMed

    Patadia, Vaishali K; Coloma, Preciosa; Schuemie, Martijn J; Herings, Ron; Gini, Rosa; Mazzaglia, Giampiero; Picelli, Gino; Fornari, Carla; Pedersen, Lars; van der Lei, Johan; Sturkenboom, Miriam; Trifirò, Gianluca

    2015-01-01

    A prospective pharmacovigilance signal detection study, comparing the real-world healthcare data (EU-ADR) and two spontaneous reporting system (SRS) databases, US FDA's Adverse Event Reporting System and WHO's Vigibase is reported. The study compared drug safety signals found in the EU-ADR and SRS databases. The potential for signal detection in the EU-ADR system was found to be dependent on frequency of the event and utilization of drugs in the general population. The EU-ADR system may have a greater potential for detecting signals for events occurring at higher frequency in general population and those that are commonly not considered as potentially a drug-induced event. Factors influencing various differences between the datasets are discussed along with potential limitations and applications to pharmacovigilance practice.

  14. Real-time prediction of clinical trial enrollment and event counts: A review.

    PubMed

    Heitjan, Daniel F; Ge, Zhiyun; Ying, Gui-Shuang

    2015-11-01

    Clinical trial planning involves the specification of a projected duration of enrollment and follow-up needed to achieve the targeted study power. If pre-trial estimates of enrollment and event rates are inaccurate, projections can be faulty, leading potentially to inadequate power or other mis-allocation of resources. Recent years have witnessed the development of methods that use the accumulating data from the trial itself to create improved predictions in real time. We review these methods, taking as a case study REMATCH, a trial that compared a left-ventricular assist device to optimal medical management in the treatment of end-stage heart failure. REMATCH provided the motivation and test bed for the first real-time clinical trial prediction model. Our review summarizes developments to date and points to unresolved issues and open research opportunities. PMID:26188165

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events.

    PubMed

    Lacour, C; Joannis, C; Gromaire, M-C; Chebbo, G

    2009-01-01

    Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification and common parameters, such as the antecedent dry weather period, total event volume per impervious hectare and both the mean and maximum hydraulic flow for each event, was also studied. Moreover, the dynamics of flow and turbidity signals were compared at the event scale. No simple relation between turbidity responses, hydraulic flow dynamics and the chosen parameters was derived from this effort. Knowledge of turbidity dynamics could therefore potentially improve wet weather management, especially when using pollution-based real-time control (P-RTC) since turbidity contains information not included in hydraulic flow dynamics and not readily predictable from such dynamics.

  7. 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.

  8. Detection of Saccharopolyspora rectivirgula by quantitative real-time PCR.

    PubMed

    Schäfer, Jenny; Kämpfer, Peter; Jäckel, Udo

    2011-07-01

    The thermophilic actinomycete species Saccharopolyspora rectivirgula has been associated with the exogen allergic alveolitis (EAA). EAA is caused by the inhalation of high amounts of airborne spores that can be found for example in environments of agricultural production, compost facilities, mushroom cultivation rooms, or rooms with technical air moistening. Because of the medical relevance of S. rectivirgula, a reliable detection system is needed. Therefore, a quantitative real-time polymerase chain reaction (qPCR) primer system was designed, targeting the 16S rRNA gene of the type strain S. rectivirgula DSM 43747(T) and six other S. rectivirgula reference strains. Our investigation showed that S. rectivirgula presumably own four operons of the 16S rRNA gene, which has to be considered for estimation of cell equivalents. Furthermore, the DNA recovery efficiency from these strains was tested in combination with bioaerosol or material sample as well as the influence of non-target DNA to the recovery rate. Results showed a recovery DNA efficiency of 7-55%. The recovery rate of DNA in a mixture with non-target DNA resulted in ∼87%. In summary, a high amplification efficiency using real-time PCR was found, for which estimated concentrations revealed cell numbers of 2.7 × 10(5) cells m(-3) in bioaerosol and 2.8 × 10(6) cells g(-1) fw(-1) in material samples from a duck house. The specificity of the new developed quantification system was shown by generation of two clone libraries from bioarosol samples, from a duck house, and from a composting plant. Totally, the results clearly show the specificity and practicability of the established qPCR assay for detection of S. rectivirgula.

  9. 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

  10. Prediction models for early risk detection of cardiovascular event.

    PubMed

    Purwanto; Eswaran, Chikkannan; Logeswaran, Rajasvaran; Abdul Rahman, Abdul Rashid

    2012-04-01

    Cardiovascular disease (CVD) is the major cause of death globally. More people die of CVDs each year than from any other disease. Over 80% of CVD deaths occur in low and middle income countries and occur almost equally in male and female. In this paper, different computational models based on Bayesian Networks, Multilayer Perceptron,Radial Basis Function and Logistic Regression methods are presented to predict early risk detection of the cardiovascular event. A total of 929 (626 male and 303 female) heart attack data are used to construct the models.The models are tested using combined as well as separate male and female data. Among the models used, it is found that the Multilayer Perceptron model yields the best accuracy result.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. A Patch-Based Method for Repetitive and Transient Event Detection in Fluorescence Imaging

    PubMed Central

    Boulanger, Jérôme; Gidon, Alexandre; Kervran, Charles; Salamero, Jean

    2010-01-01

    Automatic detection and characterization of molecular behavior in large data sets obtained by fast imaging in advanced light microscopy become key issues to decipher the dynamic architectures and their coordination in the living cell. Automatic quantification of the number of sudden and transient events observed in fluorescence microscopy is discussed in this paper. We propose a calibrated method based on the comparison of image patches expected to distinguish sudden appearing/vanishing fluorescent spots from other motion behaviors such as lateral movements. We analyze the performances of two statistical control procedures and compare the proposed approach to a frame difference approach using the same controls on a benchmark of synthetic image sequences. We have then selected a molecular model related to membrane trafficking and considered real image sequences obtained in cells stably expressing an endocytic-recycling trans-membrane protein, the Langerin-YFP, for validation. With this model, we targeted the efficient detection of fast and transient local fluorescence concentration arising in image sequences from a data base provided by two different microscopy modalities, wide field (WF) video microscopy using maximum intensity projection along the axial direction and total internal reflection fluorescence microscopy. Finally, the proposed detection method is briefly used to statistically explore the effect of several perturbations on the rate of transient events detected on the pilot biological model. PMID:20976222

  17. Evaluation of real-time PCR detection methods for detecting rice products contaminated by rice genetically modified with a CpTI-KDEL-T-nos transgenic construct.

    PubMed

    Nakamura, Kosuke; Akiyama, Hiroshi; Kawano, Noriaki; Kobayashi, Tomoko; Yoshimatsu, Kayo; Mano, Junichi; Kitta, Kazumi; Ohmori, Kiyomi; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko

    2013-12-01

    Genetically modified (GM) rice (Oryza sativa) lines, such as insecticidal Kefeng and Kemingdao, have been developed and found unauthorised in processed rice products in many countries. Therefore, qualitative detection methods for the GM rice are required for the GM food regulation. A transgenic construct for expressing cowpea (Vigna unguiculata) trypsin inhibitor (CpTI) was detected in some imported processed rice products contaminated with Kemingdao. The 3' terminal sequence of the identified transgenic construct for expression of CpTI included an endoplasmic reticulum retention signal coding sequence (KDEL) and nopaline synthase terminator (T-nos). The sequence was identical to that in a report on Kefeng. A novel construct-specific real-time polymerase chain reaction (PCR) detection method for detecting the junction region sequence between the CpTI-KDEL and T-nos was developed. The imported processed rice products were evaluated for the contamination of the GM rice using the developed construct-specific real-time PCR methods, and detection frequency was compared with five event-specific detection methods. The construct-specific detection methods detected the GM rice at higher frequency than the event-specific detection methods. Therefore, we propose that the construct-specific detection method is a beneficial tool for screening the contamination of GM rice lines, such as Kefeng, in processed rice products for the GM food regulation.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

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

    DOEpatents

    Odell, D.M.C.

    1994-10-11

    An apparatus and method are disclosed 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. 4 figs.

  7. Ambulatory REACT: real-time seizure detection with a DSP microprocessor.

    PubMed

    McEvoy, Robert P; Faul, Stephen; Marnane, William P

    2010-01-01

    REACT (Real-Time EEG Analysis for event deteCTion) is a Support Vector Machine based technology which, in recent years, has been successfully applied to the problem of automated seizure detection in both adults and neonates. This paper describes the implementation of REACT on a commercial DSP microprocessor; the Analog Devices Blackfin®. The primary aim of this work is to develop a prototype system for use in ambulatory or in-ward automated EEG analysis. Furthermore, the complexity of the various stages of the REACT algorithm on the Blackfin processor is analysed; in particular the EEG feature extraction stages. This hardware profile is used to select a reduced, platform-aware feature set, in order to evaluate the seizure classification accuracy of a lower-complexity, lower-power REACT system.

  8. Gait event detection for use in FES rehabilitation by radial and tangential foot accelerations.

    PubMed

    Rueterbories, Jan; Spaich, Erika G; Andersen, Ole K

    2014-04-01

    Gait rehabilitation by Functional Electrical Stimulations (FESs) requires a reliable trigger signal to start the stimulations. This could be obtained by a simple switch under the heel or by means of an inertial sensor system. This study provides an algorithm to detect gait events in differential acceleration signals of the foot. The key feature of differential measurements is that they compensate the impact of gravity. The real time detection capability of a rule based algorithm in healthy and hemiparetic individuals was investigated. Detection accuracy and precision compared to signals from foot switches were evaluated. The algorithm detected curve features of the vectorial sum of radial and tangential accelerations and mapped those to discrete gait states. The results showed detection rates for healthy and hemiparetic gait ranging form 84.2% to 108.5%. The sensitivity was between 0.81 and 1, and the specificity between 0.85 and 1, depending on gait phase and group of subjects. The algorithm detected gait phase changes earlier than the reference. Differential acceleration signals combined with the proposed algorithm have the potential to be implemented in a future FES system.

  9. Balloon-Borne Infrasound Detection of Energetic Bolide Events

    NASA Astrophysics Data System (ADS)

    Young, Eliot F.; Ballard, Courtney; Klein, Viliam; Bowman, Daniel; Boslough, Mark

    2016-10-01

    Infrasound is usually defined as sound waves below 20 Hz, the nominal limit of human hearing. Infrasound waves propagate over vast distances through the Earth's atmosphere: the CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organization) has 48 installed infrasound-sensing stations around the world to detect nuclear detonations and other disturbances. In February 2013, several CTBTO infrasound stations detected infrasound signals from a large bolide that exploded over Chelyabinsk, Russia. Some stations recorded signals that had circumnavigated the Earth, over a day after the original event. The goal of this project is to improve upon the sensitivity of the CTBTO network by putting microphones on small, long-duration super-pressure balloons, with the overarching goal of studying the small end of the NEO population by using the Earth's atmosphere as a witness plate.A balloon-borne infrasound sensor is expected to have two advantages over ground-based stations: a lack of wind noise and a concentration of infrasound energy in the "stratospheric duct" between roughly 5 - 50 km altitude. To test these advantages, we have built a small balloon payload with five calibrated microphones. We plan to fly this payload on a NASA high-altitude balloon from Ft Sumner, NM in August 2016. We have arranged for three large explosions to take place in Socorro, NM while the balloon is aloft to assess the sensitivity of balloon-borne vs. ground-based infrasound sensors. We will report on the results from this test flight and the prospects for detecting/characterizing small bolides in the stratosphere.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Real-time detection of epileptic seizures in animal models using reservoir computing.

    PubMed

    Buteneers, Pieter; Verstraeten, David; Nieuwenhuyse, Bregt Van; Stroobandt, Dirk; Raedt, Robrecht; Vonck, Kristl; Boon, Paul; Schrauwen, Benjamin

    2013-02-01

    In recent years, an increasing number of studies have investigated the effects of closed-loop anti-epileptic treatments. Most of the current research still is very labour intensive: real-time treatment is manually triggered and conclusions can only be drawn after multiple days of manual review and annotation of the electroencephalogram (EEG). In this paper we propose a technique based on reservoir computing (RC) to automatically and in real-time detect epileptic seizures in the intra-cranial EEG (iEEG) of epileptic rats in order to immediately trigger seizure treatment. The performance of the system is evaluated in two different seizure types: absence seizures from genetic absence epilepsy rats from Strasbourg (GAERS) and limbic seizures from post status epilepticus (PSE) rats. The dataset consists of 452 hours iEEG from 23 GAERS and 2083 hours iEEG from 22 PSE rats. In the default set-up the system detects 0.09 and 0.13 false positives per seizure and misses 0.07 and 0.005 events per seizure for GAERS and PSE rats respectively. It achieves an average detection delay below 1s in GAERS and less than 10s in the PSE data. This detection delay and the number of missed seizures can be further decreased when a higher false positive rate is allowed. Our method outperforms state-of-the-art detection techniques and only a few parameters require optimization on a limited training set. It is therefore suited for automatic seizure detection based on iEEG and may serve as a useful tool for epilepsy researchers. The technique avoids the time-consuming manual review and annotation of EEG and can be incorporated in a closed-loop treatment strategy.

  16. 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

  17. 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.

  18. Real-time anomaly detection in full motion video

    NASA Astrophysics Data System (ADS)

    Konowicz, Glenn; Li, Jiang

    2012-06-01

    Improvement in sensor technology such as charge-coupled devices (CCD) as well as constant incremental improvements in storage space has enabled the recording and storage of video more prevalent and lower cost than ever before. However, the improvements in the ability to capture and store a wide array of video have required additional manpower to translate these raw data sources into useful information. We propose an algorithm for automatically detecting anomalous movement patterns within full motion video thus reducing the amount of human intervention required to make use of these new data sources. The proposed algorithm tracks all of the objects within a video sequence and attempts to cluster each object's trajectory into a database of existing trajectories. Objects are tracked by first differentiating them from a Gaussian background model and then tracked over subsequent frames based on a combination of size and color. Once an object is tracked over several frames, its trajectory is calculated and compared with other trajectories earlier in the video sequence. Anomalous trajectories are differentiated by their failure to cluster with other well-known movement patterns. Adding the proposed algorithm to an existing surveillance system could increase the likelihood of identifying an anomaly and allow for more efficient collection of intelligence data. Additionally, by operating in real-time, our algorithm allows for the reallocation of sensing equipment to those areas most likely to contain movement that is valuable for situational awareness.

  19. BIRD detection and analysis of high-temperature events: first results

    NASA Astrophysics Data System (ADS)

    Zhukov, Boris; Briess, Klaus; Lorenz, Eckehard; Oertel, Dieter; Skrbek, Wolfgang

    2003-03-01

    The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite, which was put in a 570 km circular sun-synchronous orbit on 22 October 2001, is detection and quantitative analysis of high-temperature events (HTE) like fires and volcanoes. A unique feature of the BIRD mid- and thermal infrared channels is a real-time adjustment of their integration time that allows a HTE observation without sensor saturation, preserving a good radiometric resolution of 0.1-0.2 K for pixels at normal temperatures. This makes it possible: (a) to improve false alarm rejection capability and (b) to estimate HTE temperature, area and radiative energy release. Due to a higher spatial resolution, BIRD can detect an order of magnitude smaller HTE than AVHRR and MODIS. The smallest verified fire that was detected in the BIRD data had an area of ~12 m2. The first BIRD HTE detection and analysis results are presented including bush fires in Australia, forest fires in Russia, coal seam fires in China, and a time-varying thermal activity at Etna.

  20. 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.

  1. 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

  2. Using REDItools to Detect RNA Editing Events in NGS Datasets.

    PubMed

    Picardi, Ernesto; D'Erchia, Anna Maria; Montalvo, Antonio; Pesole, Graziano

    2015-03-09

    RNA editing is a post-transcriptional/co-transcriptional molecular phenomenon whereby a genetic message is modified from the corresponding DNA template by means of substitutions, insertions, and/or deletions. It occurs in a variety of organisms and different cellular locations through evolutionally and biochemically unrelated proteins. RNA editing has a plethora of biological effects including the modulation of alternative splicing and fine-tuning of gene expression. RNA editing events by base substitutions can be detected on a genomic scale by NGS technologies through the REDItools package, an ad hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq data or RNA-Seq data alone. REDItools implement effective filters to minimize biases due to sequencing errors, mapping errors, and SNPs. The package is freely available at Google Code repository (http://code.google.com/p/reditools/) and released under the MIT license. In the present unit we show three basic protocols corresponding to three main REDItools scripts.

  3. 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.

  4. Real-time NASBA detection of SARS-associated coronavirus and comparison with real-time reverse transcription-PCR.

    PubMed

    Keightley, Maria Cristina; Sillekens, Peter; Schippers, Wim; Rinaldo, Charles; George, Kirsten St

    2005-12-01

    Severe acute respiratory syndrome (SARS) exhibits a high mortality rate and the potential for rapid epidemic spread. Additionally, it has a poorly defined clinical presentation, and no known treatment or prevention methods. Collectively, these factors underscore the need for early diagnosis. Molecular tests have been developed to detect SARS coronavirus (SARS-CoV) RNA using real time reverse transcription polymerase chain reaction (RT-PCR) with varying levels of sensitivity. However, RNA amplification methods have been demonstrated to be more sensitive for the detection of some RNA viruses. We therefore developed a real-time nucleic acid sequence-based amplification (NASBA) test for SARS-CoV. A number of primer/beacon sets were designed to target different regions of the SARS-CoV genome, and were tested for sensitivity and specificity. The performance of the assays was compared with RT-PCR assays. A multi-target real-time NASBA application was developed for detection of SARS-CoV polymerase (Pol) and nucleocapsid (N) genes. The N targets were found to be consistently more sensitive than the Pol targets, and the real-time NASBA assay demonstrates equivalent sensitivity when compared to testing by real-time RT-PCR. A multi-target real-time NASBA assay has been successfully developed for the sensitive detection of SARS-CoV.

  5. A new method for centralised and modular supervisory control of real-time discrete event systems

    NASA Astrophysics Data System (ADS)

    Ouédraogo, Lucien; Khoumsi, Ahmed; Nourelfath, Mustapha

    2010-01-01

    This article deals with the problem of controlling a plant described as a real-time discrete event system (RTDES). In particular, automata-based supervisory control of RTDES is addressed. The aim of supervisory control is to restrict the behaviour (using a supervisor) of an uncontrolled plant in order to conform to a given specification. First, we propose a centralised method for the synthesis of a supervisor that forces a given plant to conform to a given specification. Then, we extend this centralised method to the modular case, that is, for the synthesis of n supervisors that force the plant to conform to n given specifications, respectively. Timed automata (TA) with invariants is the model used to describe the plant and the specification(s). The synthesis approach is based on the transformation of the control problem into a non-real-time form, using a transformation of TA into equivalent particular finite state automata called Set-Exp-Automata. This transformation allows to adapt the theory of Ramadge and Wonham, and is justified by the fact that it reduces the state space explosion problem compared to other transformation methods such as the transformation of TA into region automata. Moreover, the Set-Exp-Automata model provides a suitable control architecture for implementation. The proposed approach allows to obtain the solution to both the centralised and modular supervisory control problem, by identifying the solvability conditions and giving a step-by-step computation procedure of the solution.

  6. Video Event Detection: From Subvolume Localization To Spatio-Temporal Path Search.

    PubMed

    Tran, Du; Yuan, Junsong; Forsyth, David

    2013-07-23

    Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatio-temporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intra-class variations of the event. Compared to event detection using spatio-temporal sliding windows, the spatio-temporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video datasets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible to different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. PMID:23898011

  7. 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

  8. Online least squares one-class support vector machines-based abnormal visual event detection.

    PubMed

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

    2013-12-12

    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.

  9. Online least squares one-class support vector machines-based abnormal visual event detection.

    PubMed

    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

  10. 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

  11. DADA: Data Assimilation for the Detection and Attribution of Weather and Climate-related Events

    NASA Astrophysics Data System (ADS)

    Hannart, Alexis; Bocquet, Marc; Carrassi, Alberto; Ghil, Michael; Naveau, Philippe; Pulido, Manuel; Ruiz, Juan; Tandeo, Pierre

    2015-04-01

    We describe a new approach allowing for near real time, systematic causal attribution of weather and climate-related events. The method is purposely designed to allow its operability at meteorological centers by synergizing causal attribution with data treatments that are routinely performed when numerically forecasting the weather, thereby taking advantage of their powerful computational and observational capacity. Namely, we show that causal attribution can be obtained as a by-product of the so-called data assimilation procedures that are run on a daily basis to update the meteorological model with new atmospheric observations. We explain the theoretical rationale of this approach and sketch the most prominent features of a "data assimilation-based detection and attribution" (DADA) procedure. The proposal is illustrated in the context of the 3-variables Lorenz model. Several practical and theoretical research questions that need to be addressed to make the proposal readily operational within weather forecasting centers are finally laid out.

  12. 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.

  13. Detection of infectious salmon anaemia virus by real-time nucleic acid sequence based amplification.

    PubMed

    Starkey, William G; Smail, David A; Bleie, Hogne; Muir, K Fiona; Ireland, Jacqueline H; Richards, Randolph H

    2006-10-17

    We have developed a real-time nucleic acid sequence based amplification (NASBA) procedure for detection of infectious salmon anaemia virus (ISAV). Primers were designed to target a 124 nucleotide region of ISAV genome segment 8. Amplification products were detected in real-time with a molecular beacon (carboxyfluorescin [FAM]-labelled and methyl-red quenched) that recognised an internal region of the target amplicon. Amplification and detection were performed at 41 degrees C for 90 min in a Corbett Research Rotorgene. The real-time NASBA assay was compared to a conventional RT-PCR for ISAV detection. From a panel of 45 clinical samples, both assays detected ISAV in the same 19 samples. Based on the detection of a synthetic RNA target, the real-time NASBA procedure was approximately 100x more sensitive than conventional RT-PCR. These results suggest that real-time NASBA may represent a useful diagnostic procedure for ISAV.

  14. A computational method for reliable gait event detection and abnormality detection for feedback in rehabilitation.

    PubMed

    Senanayake, Chathuri; Senanayake, S M N Arosha

    2011-10-01

    In this paper, a gait event detection algorithm is presented that uses computer intelligence (fuzzy logic) to identify seven gait phases in walking gait. Two inertial measurement units and four force-sensitive resistors were used to obtain knee angle and foot pressure patterns, respectively. Fuzzy logic is used to address the complexity in distinguishing gait phases based on discrete events. A novel application of the seven-dimensional vector analysis method to estimate the amount of abnormalities detected was also investigated based on the two gait parameters. Experiments were carried out to validate the application of the two proposed algorithms to provide accurate feedback in rehabilitation. The algorithm responses were tested for two cases, normal and abnormal gait. The large amount of data required for reliable gait-phase detection necessitate the utilisation of computer methods to store and manage the data. Therefore, a database management system and an interactive graphical user interface were developed for the utilisation of the overall system in a clinical environment.

  15. 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

  16. 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.

  17. 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...

  18. 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.

  19. 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

    2016-05-03

    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.

  20. 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

  1. 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

  2. A model of human event detection in multiple process monitoring situations

    NASA Technical Reports Server (NTRS)

    Greenstein, J. S.; Rouse, W. B.

    1978-01-01

    It is proposed that human decision making in many multi-task situations might be modeled in terms of the manner in which the human detects events related to his tasks and the manner in which he allocates his attention among his tasks once he feels events have occurred. A model of human event detection performance in such a situation is presented. An assumption of the model is that, in attempting to detect events, the human generates the probability that events have occurred. Discriminant analysis is used to model the human's generation of these probabilities. An experimental study of human event detection performance in a multiple process monitoring situation is described and the application of the event detection model to this situation is addressed. The experimental study employed a situation in which subjects simulataneously monitored several dynamic processes for the occurrence of events and made yes/no decisions on the presence of events in each process. Input to the event detection model of the information displayed to the experimental subjects allows comparison of the model's performance with the performance of the subjects.

  3. 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.

  4. 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.

  5. Interlaboratory study of DNA extraction from multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for individual kernel detection system of genetically modified maize.

    PubMed

    Akiyama, Hiroshi; Sakata, Kozue; Makiyma, Daiki; Nakamura, Kosuke; Teshima, Reiko; Nakashima, Akie; Ogawa, Asako; Yamagishi, Toru; Futo, Satoshi; Oguchi, Taichi; Mano, Junichi; Kitta, Kazumi

    2011-01-01

    In many countries, the labeling of grains, feed, and foodstuff is mandatory if the genetically modified (GM) organism content exceeds a certain level of approved GM varieties. We previously developed an individual kernel detection system consisting of grinding individual kernels, DNA extraction from the individually ground kernels, GM detection using multiplex real-time PCR, and GM event detection using multiplex qualitative PCR to analyze the precise commingling level and varieties of GM maize in real sample grains. We performed the interlaboratory study of the DNA extraction with multiple ground samples, multiplex real-time PCR detection, and multiplex qualitative PCR detection to evaluate its applicability, practicality, and ruggedness for the individual kernel detection system of GM maize. DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR were evaluated by five laboratories in Japan, and all results from these laboratories were consistent with the expected results in terms of the commingling level and event analysis. Thus, the DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for the individual kernel detection system is applicable and practicable in a laboratory to regulate the commingling level of GM maize grain for GM samples, including stacked GM maize.

  6. Interlaboratory study of DNA extraction from multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for individual kernel detection system of genetically modified maize.

    PubMed

    Akiyama, Hiroshi; Sakata, Kozue; Makiyma, Daiki; Nakamura, Kosuke; Teshima, Reiko; Nakashima, Akie; Ogawa, Asako; Yamagishi, Toru; Futo, Satoshi; Oguchi, Taichi; Mano, Junichi; Kitta, Kazumi

    2011-01-01

    In many countries, the labeling of grains, feed, and foodstuff is mandatory if the genetically modified (GM) organism content exceeds a certain level of approved GM varieties. We previously developed an individual kernel detection system consisting of grinding individual kernels, DNA extraction from the individually ground kernels, GM detection using multiplex real-time PCR, and GM event detection using multiplex qualitative PCR to analyze the precise commingling level and varieties of GM maize in real sample grains. We performed the interlaboratory study of the DNA extraction with multiple ground samples, multiplex real-time PCR detection, and multiplex qualitative PCR detection to evaluate its applicability, practicality, and ruggedness for the individual kernel detection system of GM maize. DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR were evaluated by five laboratories in Japan, and all results from these laboratories were consistent with the expected results in terms of the commingling level and event analysis. Thus, the DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for the individual kernel detection system is applicable and practicable in a laboratory to regulate the commingling level of GM maize grain for GM samples, including stacked GM maize. PMID:22165018

  7. Fall incidents unraveled: a series of 26 video-based real-life fall events in three frail older persons

    PubMed Central

    2013-01-01

    Background For prevention and detection of falls, it is essential to unravel the way in which older people fall. This study aims to provide a description of video-based real-life fall events and to examine real-life falls using the classification system by Noury and colleagues, which divides a fall into four phases (the prefall, critical, postfall and recovery phase). Methods Observational study of three older persons at high risk for falls, residing in assisted living or residential care facilities: a camera system was installed in each participant’s room covering all areas, using a centralized PC platform in combination with standard Internet Protocol (IP) cameras. After a fall, two independent researchers analyzed recorded images using the camera position with the clearest viewpoint. Results A total of 30 falls occurred of which 26 were recorded on camera over 17 months. Most falls happened in the morning or evening (62%), when no other persons were present (88%). Participants mainly fell backward (initial fall direction and landing configuration) on the pelvis or torso and none could get up unaided. In cases where a call alarm was used (54%), an average of 70 seconds (SD=64; range 15–224) was needed to call for help. Staff responded to the call after an average of eight minutes (SD=8.4; range 2–33). Mean time on the ground was 28 minutes (SD=25.4; range 2–59) without using a call alarm compared to 11 minutes (SD=9.2; range 3–38) when using a call alarm (p=0.445). The real life falls were comparable with the prefall and recovery phase of Noury’s classification system. The critical phase, however, showed a prolonged duration in all falls. We suggest distinguishing two separate phases: a prolonged loss of balance phase and the actual descending phase after failure to recover balance, resulting in the impact of the body on the ground. In contrast to the theoretical description, the postfall phase was not typically characterized by inactivity; this

  8. Real-time Flare Detection in Ground-Based Hα Imaging at Kanzelhöhe Observatory

    NASA Astrophysics Data System (ADS)

    Pötzi, W.; Veronig, A. M.; Riegler, G.; Amerstorfer, U.; Pock, T.; Temmer, M.; Polanec, W.; Baumgartner, D. J.

    2015-03-01

    Kanzelhöhe Observatory (KSO) regularly performs high-cadence full-disk imaging of the solar chromosphere in the Hα and Ca ii K spectral lines as well as in the solar photosphere in white light. In the frame of ESA's (European Space Agency) Space Situational Awareness (SSA) program, a new system for real-time Hα data provision and automatic flare detection was developed at KSO. The data and events detected are published in near real-time at ESA's SSA Space Weather portal (http://swe.ssa.esa.int/web/guest/kso-federated). In this article, we describe the Hα instrument, the image-recognition algorithms we developed, and the implementation into the KSO Hα observing system. We also present the evaluation results of the real-time data provision and flare detection for a period of five months. The Hα data provision worked in 99.96 % of the images, with a mean time lag of four seconds between image recording and online provision. Within the given criteria for the automatic image-recognition system (at least three Hα images are needed for a positive detection), all flares with an area ≥ 50 micro-hemispheres that were located within 60° of the solar center and occurred during the KSO observing times were detected, a number of 87 events in total. The automatically determined flare importance and brightness classes were correct in ˜ 85 %. The mean flare positions in heliographic longitude and latitude were correct to within ˜ 1°. The median of the absolute differences for the flare start and peak times from the automatic detections in comparison with the official NOAA (and KSO) visual flare reports were 3 min (1 min).

  9. Contamination event detection using multiple types of conventional water quality sensors in source water.

    PubMed

    Liu, Shuming; Che, Han; Smith, Kate; Chen, Lei

    2014-08-01

    Early warning systems are often used to detect deliberate and accidental contamination events in a water system. Conventional methods normally detect a contamination event by comparing the predicted and observed water quality values from one sensor. This paper proposes a new method for event detection by exploring the correlative relationships between multiple types of conventional water quality sensors. The performance of the proposed method was evaluated using data from contaminant injection experiments in a laboratory. Results from these experiments demonstrated the correlative responses of multiple types of sensors. It was observed that the proposed method could detect a contamination event 9 minutes after the introduction of lead nitrate solution with a concentration of 0.01 mg L(-1). The proposed method employs three parameters. Their impact on the detection performance was also analyzed. The initial analysis showed that the correlative response is contaminant-specific, which implies that it can be utilized not only for contamination detection, but also for contaminant identification.

  10. Improved detection of event-related functional MRI signals using probability functions.

    PubMed

    Hagberg, G E; Zito, G; Patria, F; Sanes, J N

    2001-11-01

    Selecting an optimal event distribution for experimental use in event-related fMRI studies can require the generation of large numbers of event sequences with characteristics hard to control. The use of known probability distributions offers the possibility to control event timing and constrain the search space for finding optimal event sequences. We investigated different probability distributions in terms of response estimation (estimation efficiency), detectability (detection power, parameter estimation efficiency, sensitivity to true positives), and false-positive activation. Numerous simulated event sequences were generated selecting interevent intervals (IEI) from the uniform, uniform permuted, Latin square, exponential, binomial, Poisson, chi(2), geometric, and bimodal probability distributions and fixed IEI. Event sequences from the bimodal distribution, like block designs, had the best performance for detection and the poorest for estimation, while high estimation and detectability occurred for the long-decay exponential distribution. The uniform distribution also yielded high estimation efficiency, but probability functions with a long tail toward higher IEI, such as the geometric and the chi(2) distributions, had superior detectability. The distributions with the best detection performance also had a relatively high incidence of false positives, in contrast to the ordered distributions (Latin square and uniform permuted). The predictions of improved sensitivities for distributions with long tails were confirmed with empirical data. Moreover, the Latin square design yielded detection of activated voxels similar to the chi(2) distribution. These results indicate that high detection and suitable behavioral designs have compatibility for application of functional MRI methods to experiments requiring complex designs.

  11. Power System Extreme Event Detection: The VulnerabilityFrontier

    SciTech Connect

    Lesieutre, Bernard C.; Pinar, Ali; Roy, Sandip

    2007-10-17

    In this work we apply graph theoretic tools to provide aclose bound on a frontier relating the number of line outages in a gridto the power disrupted by the outages. This frontier describes theboundary of a space relating the possible severity of a disturbance interms of power disruption, from zero to some maximum on the boundary, tothe number line outages involved in the event. We present the usefulnessof this analysis with a complete analysis of a 30 bus system, and presentresults for larger systems.

  12. Falls event detection using triaxial accelerometry and barometric pressure measurement.

    PubMed

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

    2009-01-01

    A falls detection system, employing a Bluetooth-based wearable device, containing a triaxial accelerometer and a barometric pressure sensor, is described. The aim of this study is to evaluate the use of barometric pressure measurement, as a surrogate measure of altitude, to augment previously reported accelerometry-based falls detection algorithms. The accelerometry and barometric pressure signals obtained from the waist-mounted device are analyzed by a signal processing and classification algorithm to discriminate falls from activities of daily living. This falls detection algorithm has been compared to two existing algorithms which utilize accelerometry signals alone. A set of laboratory-based simulated falls, along with other tasks associated with activities of daily living (16 tests) were performed by 15 healthy volunteers (9 male and 6 female; age: 23.7 +/- 2.9 years; height: 1.74 +/- 0.11 m). The algorithm incorporating pressure information detected falls with the highest sensitivity (97.8%) and the highest specificity (96.7%).

  13. 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.

  14. Quantitative detection of Listeria monocytogenes in biofilms by real-time PCR.

    PubMed

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

    2005-04-01

    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 x 10(2) CFU/cm2.

  15. 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.

  16. Real-time nucleic acid sequence-based amplification assay for detection of hepatitis A virus.

    PubMed

    Abd el-Galil, Khaled H; el-Sokkary, M A; Kheira, S M; Salazar, Andre M; Yates, Marylynn V; Chen, Wilfred; Mulchandani, Ashok

    2005-11-01

    A nucleic acid sequence-based amplification (NASBA) assay in combination with a molecular beacon was developed for the real-time detection and quantification of hepatitis A virus (HAV). A 202-bp, highly conserved 5' noncoding region of HAV was targeted. The sensitivity of the real-time NASBA assay was tested with 10-fold dilutions of viral RNA, and a detection limit of 1 PFU was obtained. The specificity of the assay was demonstrated by testing with other environmental pathogens and indicator microorganisms, with only HAV positively identified. When combined with immunomagnetic separation, the NASBA assay successfully detected as few as 10 PFU from seeded lake water samples. Due to its isothermal nature, its speed, and its similar sensitivity compared to the real-time RT-PCR assay, this newly reported real-time NASBA method will have broad applications for the rapid detection of HAV in contaminated food or water.

  17. 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.

  18. 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

  19. 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

  20. Near real-time fluorescence detection of beryllium

    SciTech Connect

    McCleskey, T. M.; Ehler, D. S.; Minogue, E. M.; Collis, G. E.; Keizer, T. S.; Burrell, A. K.; Sauer, N. N.; John, K. D.

    2004-01-01

    We report on a fluorescent test for beryllium designed for analyzing swipes. The detection is rapid, quantitative and deployable in the field with $5,000 portable fluorimeter. Swipes are placed in a vial and a dilution solution is added. The vials are then rotated for 30 minutes and then syringe filtered. An aliquot of 100 pL is added to a detector solution and fluorescence measured with a portable ocean optics unit. We can readily detect down to 0.02 {micro}g on a filter paper. Interference studies have been carried out with various metals including Al, Fe, Pb, U, Ca, W, Ni, Co and Cu. The technique has proven to be successful under various conditions including a variety of surfaces both in the lab and in field. It is a user-friendly, cost effective method.

  1. 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%.

  2. 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

  3. [Research progress of real-time quantitative PCR method for group A rotavirus detection].

    PubMed

    Guo, Yan-Qing; Li, Dan-Di; Duan, Zhao-Jun

    2013-11-01

    Group A rotavirus is one of the most significant etiological agents which causes acute gastroenteritis among infants and young children worldwide. So far, several method which includes electron microscopy (EM), enzyme immunoassay (EIA), reverse transcription-polymerase chain reaction (RT-PCR)and Real-time Quantitative PCR has been established for the detection of rotavirus. Compared with other methods, Real-time quantitative PCR have advantages in specificity, sensitivity, genotyping and quantitative accuracy. This article shows a overview of the application of real-time quantitative PCR technique to detecte group A rotavirus.

  4. Detection of Toxoplasma gondii Oocysts in Water Sample Concentrates by Real-Time PCR▿

    PubMed Central

    Yang, Wenli; Lindquist, H. D. Alan; Cama, Vitaliano; Schaefer, Frank W.; Villegas, Eric; Fayer, Ronald; Lewis, Earl J.; Feng, Yaoyu; Xiao, Lihua

    2009-01-01

    PCR techniques in combination with conventional parasite concentration procedures have potential for the 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 analyzed for the detection of T. gondii tachyzoites and oocysts. Lower sensitivity and specificity were obtained with the B1 gene-based PCR than with the 529-bp repeat-based PCR. New procedures for the real-time PCR detection of T. gondii oocysts in concentrates of surface water were developed and tested in conjunction with a method for the direct extraction of inhibitor-free DNA from water. This technique detected as few as one oocyst seeded to 0.5 ml of packed pellets from water samples concentrated by Envirocheck filters. Thus, this real-time PCR may provide a detection method alternative to the traditional mouse assay and microscopy. PMID:19363083

  5. 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.

  6. 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

  7. 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.

  8. 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…

  9. 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

  10. Event-specific qualitative and quantitative PCR methods for the detection of genetically modified rapeseed Oxy-235.

    PubMed

    Wu, Gang; Wu, Yuhua; Xiao, Ling; Lu, Changming

    2008-10-01

    Oxy-235 is an oxynil-tolerant genetically modified rapeseed approved for commercialized planting in Canada. The aim of this study was to establish event-specific qualitative and quantitative detection methods for Oxy-235. Both the 5'- and 3'-junction sequences spanning the plant DNA and the integrated gene construct of the Oxy-235 event were isolated, sequenced and analyzed. A 1298-bp deletion of the rapeseed genomic DNA that showed a high similarity to the mRNA sequence of Arabidopsis thaliana was found in the integration site of the insert DNA. Event-specific qualitative PCR methods were established, with one method producing a 105-bp product specific for the 5'-integration junction and the other method producing a 124-bp product specific for the 3'-junction. The absolute detection limits for the qualitative PCR were determined to be 100 initial template copies for the 5'-junction and ten for the 3'-junction. Quantitative methods were also developed that targeted both of the junction fragments. The limit of detection of the quantitative PCR analysis was ten initial template copies for either the 5'- or 3'-junction, while the limit of quantification was determined to be approximately 50 initial template copies. The real-time PCR systems so established were examined with two mixed rapeseed samples with known Oxy-235 contents and found to obtain the expected results.

  11. 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

    2014-09-08

    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.

  12. 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

  13. 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.

  14. Molecular-beacon multiplex real-time PCR assay for detection of Vibrio cholerae.

    PubMed

    Gubala, Aneta J; Proll, David F

    2006-09-01

    A multiplex real-time PCR assay was developed using molecular beacons for the detection of Vibrio cholerae by targeting four important virulence and regulatory genes. The specificity and sensitivity of this assay, when tested with pure culture and spiked environmental water samples, were high, surpassing those of currently published PCR assays for the detection of this organism.

  15. Use of real-time quantitative PCR to detect Chlamydophila felis infection.

    PubMed

    Helps, C; Reeves, N; Tasker, S; Harbour, D

    2001-07-01

    A real-time PCR assay was developed to detect and quantify Chlamydophila felis infection of cats. The assay uses a molecular beacon to specifically identify the major outer membrane protein gene, is highly reproducible, and is able to detect fewer than 10 genomic copies.

  16. Quality control in cloth production: a new system for real-time defect detection

    NASA Astrophysics Data System (ADS)

    Baldassare, Antonio; De Lucia, Maurizio; Rossi, Francesca; Vannucci, Massimiliano

    2001-02-01

    Real time defect detection on fine cloth is an urgent problem to solve: detecting a long and serious defect on a roll, as soon as it is produced, can reduce damages to the roll, and the consequent decrement of price. The paper describes the work performed at the Department of Energy Engineering `Sergio Stecco' of the University of Florence, in collaboration with well-known high quality wool cloth manufacturers (Marzotto) and machine builders (Sulzer, Benninger). The main goal has been to obtain a new and innovative production line, endowed with a system (based on image processing techniques) for detecting defects in real- time and thus for controlling the production process. The system is based on image processing techniques with a special attention to the real-time constraints. An architecture separating an on-line defect detection and an off-line classification has been proposed. An intelligent optical head, assembled on the loom, acquires images and detects the defects in real-time. A server has the offline task to classify each defect detected by the head. The system has been tested on a real loom, with good results in terms of reliability, false alarms and stability.

  17. 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.

  18. Quantitative detection of Aspergillus spp. by real-time nucleic acid sequence-based amplification.

    PubMed

    Zhao, Yanan; Perlin, David S

    2013-01-01

    Rapid and quantitative detection of Aspergillus from clinical samples may facilitate an early diagnosis of invasive pulmonary aspergillosis (IPA). As nucleic acid-based detection is a viable option, we demonstrate that Aspergillus burdens can be rapidly and accurately detected by a novel real-time nucleic acid assay other than qPCR by using the combination of nucleic acid sequence-based amplification (NASBA) and the molecular beacon (MB) technology. Here, we detail a real-time NASBA assay to determine quantitative Aspergillus burdens in lungs and bronchoalveolar lavage (BAL) fluids of rats with experimental IPA.

  19. 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.

  20. 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.

  1. Real-Time Imaging of Discrete Exocytic Events Mediating Surface Delivery of AMPA Receptors

    PubMed Central

    Yudowski, Guillermo A.; Puthenveedu, Manojkumar A.; Leonoudakis, Dmitri; Panicker, Sandip; Thorn, Kurt S.; Beattie, Eric C.; von Zastrow, Mark

    2011-01-01

    We directly resolved discrete exocytic fusion events mediating insertion of AMPA-type glutamate receptors (AMPARs) to the somatodendritic surface of rat hippocampal pyramidal neurons, in slice and dissociated cultures, using protein tagging with a pH-sensitive GFP (green fluorescent protein) variant and rapid (10 frames/s) fluorescence microscopy. AMPAR-containing exocytic events occurred under basal culture conditions in both the cell body and dendrites; potentiating chemical stimuli produced an NMDA receptor-dependent increase in the frequency of individual exocytic events. The number of AMPARs inserted per exocytic event, estimated using single-molecule analysis, was quite uniform but individual events differed significantly in kinetic properties affecting the subsequent surface distribution of receptors. “Transient” events, from which AMPARs dispersed laterally immediately after surface insertion, generated a pronounced but short-lived (dissipating within ~1 s) increase in surface AMPAR fluorescence extending locally (2–5µm) from the site of exocytosis. “Persistent” events, from which inserted AMPARs dispersed slowly (typically over 5–10 s), affected local surface receptor concentration to a much smaller degree. Both modes of exocytic insertion occurred throughout the dendritic shaft, but remarkably, neither mode of insertion was observed directly into synaptic spines. AMPARs entered spines preferentially from transient events occurring in the adjoining dendritic shaft, driven apparently by mass action and short-range lateral diffusion, and locally delivered AMPARs remained mostly in the mobile fraction. These results suggest a highly dynamic mechanism for both constitutive and activity-dependent surface delivery of AMPARs, mediated by kinetically distinct exocytic modes that differ in propensity to drive lateral entry of receptors to nearby synapses. PMID:17928453

  2. 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.

  3. Supervisory control design based on hybrid systems and fuzzy events detection. Application to an oxichlorination reactor.

    PubMed

    Altamiranda, Edmary; Torres, Horacio; Colina, Eliezer; Chacón, Edgar

    2002-10-01

    This paper presents a supervisory control scheme based on hybrid systems theory and fuzzy events detection. The fuzzy event detector is a linguistic model, which synthesizes complex relations between process variables and process events incorporating experts' knowledge about the process operation. This kind of detection allows the anticipation of appropriate control actions, which depend upon the selected membership functions used to characterize the process under scrutiny. The proposed supervisory control scheme was successfully implemented for an oxichlorination reactor in a vinyl monomer plant. This implementation has allowed improvement of reactor stability and reduction of raw material consumption. PMID:12398279

  4. 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

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

    PubMed

    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 thromboembolic

  6. 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

  7. 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

  8. 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

  9. Viola-Jones based hybrid framework for real-time object detection in multispectral images

    NASA Astrophysics Data System (ADS)

    Kuznetsova, E.; Shvets, E.; Nikolaev, D.

    2015-12-01

    This paper describes a method for real-time object detection based on a hybrid of a Viola-Jones cascade with a convolutional neural network. This scheme allows flexible trade-offs between detection quality and computational performance. We also propose a generalization of this method to multispectral images that effectively and efficiently utilizes information from each spectral channel. The new scheme is experimentally compared to traditional Viola-Jones, showing improved detection quality with adjustable performance.

  10. 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.

  11. 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.

  12. A Real-time Auto-detection Method for Random Telegraph Signal (RTS) Noise Detection in CMOS Active pixel sensors

    NASA Astrophysics Data System (ADS)

    Zheng, R.; Zhao, R.; Ma, Y.; Li, B.; Wei, X.; Wang, J.; Gao, W.; Wei, T.; Gao, D.; Hu, Y.

    2015-07-01

    CMOS Active pixel sensors (CMOS APS) are attractive for use in the innermost layers of charged particle trackers, due to their good tradeoffs among the key performances. However, CMOS APS can be greatly influenced by random telegraph signal (RTS) noise, which can cause particle tracking or energy calculation failures. In-depth research of pixels' RTS behavior stimulates the interest of the methods for RTS noise detection, reconstruction and parameters extraction. In this paper, a real-time auto-detection method is proposed, using real-time Gaussian noise standard deviation as the detection threshold. Experimental results show that, compared with current methods using signal standard deviation as the thresholds, the proposed method is more sensitive in multi-level RTS detection and more effective in the case of RTS noise degradation.

  13. 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…

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. Multiplex SYBR Green Real-Time PCR Assay for Detection of Respiratory Viruses

    PubMed Central

    Sultani, Mozhdeh; Mokhtari Azad, Talat; Eshragian, Mohammadreza; Shadab, Azadeh; Naseri, Maryam; Eilami, Owrang; Yavarian, Jila

    2015-01-01

    Background: It is often difficult for a physician to distinguish between viral and bacterial causes of respiratory infections and this may result in overuse of antibiotics. In many cases of community-acquired respiratory infections, clinicians treat patients empirically. The development of molecular methods for direct detection of viruses has been progressed recently. Objectives: The objective of this study was recognizing the panel of respiratory RNA viruses by multiplex SYBR Green real-time polymerase chain reaction (PCR). Materials and Methods: Randomized 172 influenza-negative respiratory specimens of all age groups of hospitalized patients were collected. After RNA extraction, cDNA was synthesized. Three SYBR Green multiplex real-time PCR assays were developed for simultaneous detection of 12 respiratory RNA viruses. Each set of multiplex methods detected four viruses, the first set: respiratory syncytial virus, human metapneumovirus, rhinovirus, enterovirus; the second set: parainfluenza viruses 1 - 4 (PIV1-4); the third set: coronaviruses NL63, 229E, severe acute respiratory syndrome (SARS), and OC43. Results: Application of the multiplex SYBR Green real-time PCR in clinical samples from 172 patients in a one-year study resulted in detection of 19 (11.04%) PIV3, 9 (5.23%) PIV4, and 1 (0.58%) coronavirus NL63. All the positive samples were detected during December to March (2011 - 2012). Conclusions: Multiplex SYBR Green real-time PCR is a rapid and relatively inexpensive method for detection of respiratory viruses. PMID:26468358

  3. 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).

  4. 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…

  5. "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…

  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. Cooperative object tracking and composite event detection with wireless embedded smart cameras.

    PubMed

    Wang, Youlu; Velipasalar, Senem; Casares, Mauricio

    2010-10-01

    Embedded smart cameras have limited processing power, memory, energy, and bandwidth. Thus, many system- and algorithm-wise challenges remain to be addressed to have operational, battery-powered wireless smart-camera networks. We present a wireless embedded smart-camera system for cooperative object tracking and detection of composite events spanning multiple camera views. Each camera is a CITRIC mote consisting of a camera board and wireless mote. Lightweight and robust foreground detection and tracking algorithms are implemented on the camera boards. Cameras exchange small-sized data wirelessly in a peer-to-peer manner. Instead of transferring or saving every frame or trajectory, events of interest are detected. Simpler events are combined in a time sequence to define semantically higher-level events. Event complexity can be increased by increasing the number of primitives and/or number of camera views they span. Examples of consistently tracking objects across different cameras, updating location of occluded/lost objects from other cameras, and detecting composite events spanning two or three camera views, are presented. All the processing is performed on camera boards. Operating current plots of smart cameras, obtained when performing different tasks, are also presented. Power consumption is analyzed based upon these measurements. PMID:20551001

  8. 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.

  9. Detection of piscine nodaviruses by real-time nucleic acid sequence based amplification (NASBA).

    PubMed

    Starkey, William G; Millar, Rose Mary; Jenkins, Mary E; Ireland, Jacqueline H; Muir, K Fiona; Richards, Randolph H

    2004-05-01

    Nucleic acid sequence based amplification (NASBA) is an isothermal nucleic acid amplification procedure based on target-specific primers and probes, and the co-ordinated activity of 3 enzymes: AMV reverse transcriptase, RNase H, and T7 RNA polymerase. We have developed a real-time NASBA procedure for detection of piscine nodaviruses, which have emerged as major pathogens of marine fish. Viral RNA was isolated by guanidine thiocyanate lysis followed by purification on silica particles. Primers were designed to target sequences in the nodavirus capsid protein gene, yielding an amplification product of 120 nucleotides. Amplification products were detected in real-time with a molecular beacon (FAM labelled/methyl-red quenched) that recognised an internal region of the target amplicon. Amplification and detection were performed at 41 degrees C for 90 min in a Corbett Research Rotorgene. Based on the detection of cell culture-derived nodavirus, and a synthetic RNA target, the real-time NASBA procedure was approximately 100-fold more sensitive than single-tube RT-PCR. When used to test a panel of 37 clinical samples (negative, n = 18; positive, n = 19), the real-time NASBA assay correctly identified all 18 negative and 19 positive samples. In comparison, the RT-PCR procedure identified all 18 negative samples, but only 16 of the positive samples. These results suggest that real-time NASBA may represent a sensitive and specific diagnostic procedure for piscine nodaviruses.

  10. Assessing the Probability of Detection of Horizontal Gene Transfer Events in Bacterial Populations

    PubMed Central

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

    2012-01-01

    Experimental approaches to identify horizontal gene transfer (HGT) events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modeling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genetic material, such as antibiotic resistance genes or transgenes present in genetically modified organisms. Due to the long time scales involved and the exponential growth of bacteria with differing fitness, quantitative analyses incorporating bacterial generation time, and levels of selection, such as the one presented here, will be a necessary component of any future experimental design and analysis of HGT as it occurs in natural settings. PMID:22363321

  11. Assessing the probability of detection of horizontal gene transfer events in bacterial populations.

    PubMed

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

    2012-01-01

    Experimental approaches to identify horizontal gene transfer (HGT) events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modeling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genetic material, such as antibiotic resistance genes or transgenes present in genetically modified organisms. Due to the long time scales involved and the exponential growth of bacteria with differing fitness, quantitative analyses incorporating bacterial generation time, and levels of selection, such as the one presented here, will be a necessary component of any future experimental design and analysis of HGT as it occurs in natural settings.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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%.

  18. 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

  19. 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)

  20. Recent developments and applications of a real-time tool to detect magma migration in different volcanic settings

    NASA Astrophysics Data System (ADS)

    Taisne, Benoit; Caudron, Corentin; Aoki, Yosuke

    2014-05-01

    Triggering mechanism of a seismic swarm has to be identified with great confidence in real time. Crisis response will not be the same whether magma is involved or not. The recent developments of the method based on the Seismic Amplitude Ratio Analysis enable a rapid and unambiguous diagnosis to detect migrating micro-seismicity. Combined with other measurements, this migrating seismicity could be linked to complex motions of magma within the volcanic edifice. The beauty of this method lies in the fact that the ratio of seismic energy, recorded at different stations, is independent of the seismic energy radiated at the source and depends only on the location of the source and attenuation of the medium. Since drastic changes in attenuation are unlikely to occur at the time scale of magma intrusion, temporal evolutions in the measured ratio have to be explained by a change in the source location. Based on simple assumptions this technique can be used to assess the potential of existing monitoring seismic network to detect migrating events in real-time. It can also be used to design monitoring seismic network based on the available number of sensors as well as from field constraints. Network capability will depend on the noise level at each station, therefore this noise is used to define the magnitude threshold that can be detected as a function of the distance. A basic set of parameters will be implemented in this tool to tackle magma migration in basaltic systems, as well as acidic ones.

  1. 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

  2. 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.

  3. [Clinical evaluation of ECG at the onset subjective symptoms using real-time analysis electrocardiograph (event recorder)].

    PubMed

    Takizawa, Yoshinori; Shimetani, Naoto; Uchiyama, Kenji; Takayanagi, Kan; Mori, Mikio

    2005-05-01

    Examination of patient complaining of palpitation, chest pain and chest discomfort is usually performed by 12-lead electrocardiograph. However, the recording time is short and there are few opportunities to capture an ECG demonstrating conditions during subjective symptoms. To investigate the cause, we need to obtain an ECG during subjective symptoms. Thus, we frequently use a Holter ECG, which can be recorded for 24 hours. However, some patients have a low frequency of subjective symptoms, which may not appear during a 24-hour examination. We used a real-time electrocardiograph (Event Recorder CG-6106 made by Card Guard Scientific Survival Limited) as a monitor during subjective symptoms. Thereafter, ECG findings at the onset of subjective symptoms could be analyzed in 30 patients who did not have a clear cardiac disease. In this examination, arrhythmia was recorded in 25 of 30 cases. Although in these cases ECG during subjective symptoms could not be captured even when Holter examination was performed several times ECG during subjective symptoms was captured using an Event Recorder. This method using an Event Recorder is simple and convenient, moreover, is considered very useful for investigation of subjective symptoms. In the future, the use of an Event Recorder for heart-health-care in the daily life of healthy people and/or cardiac disease patient is highly anticipated.

  4. 3He-Rich SEP Events Detected by EPHIN 1996-2000

    NASA Astrophysics Data System (ADS)

    Gómez-Herrero, R.; Rodríguez-Frías, D.; Del Peral, L.; Sequeiros, J.; Gutiérrez, J.; Müller-Mellin, R.; Kunow, H.

    2003-07-01

    Thirteen 3 He-rich impulsive events have been identified in EPHIN data between 1996 and 2000. Energy spectra, abundance ratios, and association with solar activity have been evaluated. association with radio bursts I I I-type has been observed for all of them, but solar flare association has been found only for 8 of them. No acceleration above 30 MeV/nucleon has been appreciated. No deuterium has been detected for any event under study.

  5. Detection of viable Salmonella in lettuce by propidium monoazide real-time PCR.

    PubMed

    Liang, Ningjian; Dong, Jin; Luo, Laixin; Li, Yong

    2011-05-01

    Contamination of lettuce by Salmonella has caused serious public health problems. Polymerase chain reaction (PCR) allows rapid detection of pathogenic bacteria in food, but it is inaccurate as it might amplify DNA from dead target cells as well. This study aimed to investigate the stability of DNA of dead Salmonella cells in lettuce and to develop an approach to detecting viable Salmonella in lettuce. Salmonella-free lettuce was inoculated with heat-killed Salmonella Typhimurium cells and stored at 4 °C. Bacterial DNA extracted from the sample was amplified by real-time PCR targeting the invA gene. Our results indicate that DNA from the dead cells remained stable in lettuce for at least 8 d. To overcome this limitation, propidium monoazide (PMA), a dye that can selectively penetrate dead bacterial cells and cross-link their DNA upon light exposure, was combined with real-time PCR. Lettuce samples inoculated with different levels of dead or viable S. Typhimurium cells were treated or untreated with PMA before DNA extraction. Real-time PCR suggests that PMA treatment effectively prevented PCR amplification from as high as 10(8) CFU/g dead S. Typhimurium cells in lettuce. The PMA real-time PCR assay could detect viable Salmonella at as low as 10(2) CFU/mL in pure culture and 10(3) CFU/g in lettuce. With 12-h enrichment, S. Typhimurium of 10(1) CFU/g in lettuce was detectable. In conclusion, the PMA real-time PCR assay provides an alternative to real-time PCR assay for accurate detection of Salmonella in food.

  6. 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

  7. 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

  8. Detecting deception in children: an experimental study of the effect of event familiarity on CBCA ratings.

    PubMed

    Blandon-Gitlin, Iris; Pezdek, Kathy; Rogers, Martha; Brodie, Laura

    2005-04-01

    The CBCA is the most commonly used deception detection. technique worldwide. Pezdek et al. (2004) used a quasi-experimental design to assess children's accounts of a traumatic medical procedure; CBCA ratings were higher for descriptions of familiar than unfamiliar events. This study tested this effect using an experimental design and assessed the joint effect of familiarity and veracity on CBCA ratings. Children described a true or a fabricated event. Half described a familiar event; half described an unfamiliar event. Two CBCA-trained judges rated transcripts of the descriptions. CBCA scores were more strongly influenced by the familiarity than the actual veracity of the event, and CBCA scores were significantly correlated with age. CBCA results were compared with results from other measures. Together with the results of K. Pezdek et al. (2004) these findings suggest that in its current form, CBCA is of limited utility as a credibility assessment tool. PMID:15912723

  9. Vision-based real-time road detection in urban traffic

    NASA Astrophysics Data System (ADS)

    Lu, Jianye; Yang, Ming; Wang, Hong; Zhang, Bo

    2002-03-01

    Road detection is the major task of autonomous vehicle guidance. We notice that feature lines, which are parallel to the road boundaries, are reliable cues for road detection in urban traffic. Therefore we present a real-time method that extracts the most likely road model using a set of feature-line-pairs (FLPs). Unlike the traditional methods that extract a single line, we extract the feature lines in pairs. Working with a linearly parameterized road model, FLP appears some geometrical consistency, which allows us to detect each of them with a Kalman filter tracking scheme. Since each FLP determines a road model, we apply regression diagnostics technique to robustly estimate the parameters of the whole road model from all FLPs. Another Kalman filter is used to track road model from frame to frame to provide a more precise and more robust detection result. Experimental results in urban traffic demonstrate real-time processing ability and high robustness.

  10. Detection of allergen walnut component in food by an improved real-time PCR method.

    PubMed

    Wang, Haiyan; Yuan, Fei; Wu, Yajun; Yang, Hairong; Xu, Baoliang; Liu, Zhongxue; Chen, Ying

    2009-11-01

    A real-time PCR method aimed at the gene sequence of the walnut vicilin-like seed storage protein was established for the detection of the allergen walnut in food. The primers and probe were designed based on published methods. The method provided positive results for walnut and negative results for other tested agricultural plant materials including pecan. The intrinsic detection limit of the method was 0.00125 ng of walnut DNA, and the practical detection limit was 0.001% (wt/wt) walnut content in wheat; both of these values are lower than that of previously published methods. Therefore, this real-time PCR method is sufficiently specific and sensitive for the detection of walnut component in food.

  11. Real-time system for imaging and object detection with a multistatic GPR array

    DOEpatents

    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.

  12. Anomalous optical events detected by rocket-borne sensor in the WIPP campaign

    NASA Technical Reports Server (NTRS)

    Li, Ya QI; Holzworth, Robert H.; Hu, Hua; Mccarthy, Michael; Massey, R. Dayle

    1991-01-01

    This paper describes the instruments used in the Wave Induced Particle Precipitation campaign in 1987, in which one rocket and four balloons were launched near thunderstorms from the NASA Wallops Flight Facility. Examples of both the lightning events and the anomalous optical events (AOEs) detected on July 31, 1987 are presented. It is shown that the signatures of these AOEs differ from those of well-known optical sources in the atmosphere. It was found that AOEs were sometimes associated with subionospheric VLF signal perturbations (Trimpi events), suggesting a possibility that AOEs might be linked to a disturbance of the electron concentration in the high-altitude atmosphere or lower ionosphere.

  13. Quantitative detection of hazelnut (Corylus avellana) in cookies: ELISA versus real-time PCR.

    PubMed

    Platteau, Céline; De Loose, Marc; De Meulenaer, Bruno; Taverniers, Isabel

    2011-11-01

    Hazelnuts (Corylus avellana) are used widely in the food industry, especially in confectionery, where they are used raw, roasted, or in a processed formulation (e.g., praline paste and hazelnut oil). Hazelnuts contain multiple allergenic proteins, which can induce an allergic reaction associated with symptoms ranging from mild irritation to life-threatening anaphylactic shock. To date, immunochemical (e.g., ELISA or dipstick) and PCR-based analyses are the only methods available that can be applied as routine tests. The aim of this study is to make a comparative evaluation of the effectiveness of ELISA and real-time PCR in detecting and correctly quantifying hazelnut in food model systems. To this end, the performances of two commercial ELISAs were compared to those of two commercial and one in-house-developed real-time PCR assays. The results showed that although ELISA seemed to be more sensitive compared to real-time PCR, both detection techniques suffered from matrix effects and lacked robustness with regard to food processing. As these impacts were highly variable among the different evaluated assays (both ELISA and real-time PCR), no firm conclusion can be made as to which technique is suited best to detect hazelnut in (processed) food products. In this regard, the current lack of appropriate DNA calibrators to quantify an allergenic ingredient by means of real-time PCR is highlighted.

  14. 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

  15. 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.

  16. Automated detection of apnea/hypopnea events in healthy children polysomnograms: preliminary results.

    PubMed

    Held, Claudio M; Causa, Leonardo; Jaillet, Fabrice; Chamorro, Rodrigo; Garrido, Marcelo; Algarin, Cecilia; Peirano, Patricio

    2013-01-01

    A methodology to detect sleep apnea/hypopnea events in the respiratory signals of polysomnographic recordings is presented. It applies empirical mode decomposition (EMD), Hilbert-Huang transform (HHT), fuzzy logic and signal preprocessing techniques for feature extraction, expert criteria and context analysis. EMD, HHT and fuzzy logic are used for artifact detection and preliminary detection of respiration signal zones with significant variations in the amplitude of the signal; feature extraction, expert criteria and context analysis are used to characterize and validate the respiratory events. An annotated database of 30 all-night polysomnographic recordings, acquired from 30 healthy ten-year-old children, was divided in a training set of 15 recordings (485 sleep apnea/hypopnea events), a validation set of five recordings (109 sleep apnea/hypopnea events), and a testing set of ten recordings (281 sleep apnea/hypopnea events). The overall detection performance on the testing data set was 89.7% sensitivity and 16.3% false-positive rate. The next step is to include discrimination among apneas, hypopneas and respiratory pauses.

  17. A Real-Time PCR for Detection and Quantification of Mycoplasma ovipneumoniae

    PubMed Central

    YANG, Falong; DAO, Xiaofang; RODRIGUEZ-PALACIOS, Alex; FENG, Xufei; TANG, Cheng; YANG, Xiaonong; YUE, Hua

    2014-01-01

    A real-time PCR for detection and quantification of M. ovipneumoniae was developed using 9 recently sequenced M. ovipneumoniae genomes and primers targeting a putative adhesin gene p113. The assay proved to be specific and sensitive (with a detection limit of 22 genomic DNA) and could quantify M. ovipneumoniae DNA over a wide linear range, from 2.2 × 102 to 2.2 × 107 genomes. PMID:25649947

  18. A real-time PCR for detection and quantification of Mycoplasma ovipneumoniae.

    PubMed

    Yang, Falong; Dao, Xiaofang; Rodriguez-Palacios, Alex; Feng, Xufei; Tang, Cheng; Yang, Xiaonong; Yue, Hua

    2014-12-01

    A real-time PCR for detection and quantification of M. ovipneumoniae was developed using 9 recently sequenced M. ovipneumoniae genomes and primers targeting a putative adhesin gene p113. The assay proved to be specific and sensitive (with a detection limit of 22 genomic DNA) and could quantify M. ovipneumoniae DNA over a wide linear range, from 2.2 × 10(2) to 2.2 × 10(7) genomes.

  19. Real-time image analysis for nondestructive detection of metal sliver in packed food

    NASA Astrophysics Data System (ADS)

    Chen, Xin; Jing, Hansong; Tao, Yang; Cheng, Xuemei

    2005-11-01

    Foreign materials such as metal slivers and stones in packed food are listed safety hazards, which could lead to severe health problems. In this paper, a real time X-ray imaging inspection method is investigated for foreign material detection in chili packages. A new image segmentation method combining edge detection and region growing was successfully applied to address the challenges due to the uneven thickness of chili package.

  20. 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

  1. 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.

  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.

    2015-10-01

    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.

  3. 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

  4. Impulsive 3He-rich Solar Energetic Particle Events detected with EPHIN

    NASA Astrophysics Data System (ADS)

    Rodriguez-Frias, M. D.; Gomez-Herrero, R.; del Peral, L.; Sequeiros, J.; Kunow, H.; Mueller-Mellin, R.

    2001-08-01

    We report observation of 3 He-rich solar energetic particles (SEP) events detected by Electron Proton and Helium Instrument (EPHIN) aboard the Solar and Heliospheric Observatory (SOHO) spacecraft. EPHIN has been detecting Helium isotopes in the energy range 4-53 MeV/n since December 1995 using a ˜E-E sensor system with solid-state detectors. In this paper we concentrate on observations of SEP with excess in the 3 He abundance. The abundances 3 He/4 He and 4 He/1 H have been obtained and compared among different events. Energy spectra of protons, 3 He, 4 He have been studied.

  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. 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.

  7. [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.

  8. 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.

  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. 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.

  11. 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.

  12. A portable device for real time drowsiness detection using novel active dry electrode system.

    PubMed

    Tsai, Pai-Yuan; Hu, Weichih; Kuo, Terry B J; Shyu, Liang-Yu

    2009-01-01

    Electroencephalogram (EEG) signals give important information about the vigilance states of a subject. Therefore, this study constructs a real-time EEG-based system for detecting a drowsy driver. The proposed system uses a novel six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses a TMS320VC5510 DSP chip as the algorithm processor, and a MSP430F149 chip as a controller to achieve a real-time portable system. This study implements stationary wavelet transform to extract two features of EEG signal: integral of EEG and zero crossings as the input to a back propagation neural network for vigilance states classification. This system can discriminate alertness and drowsiness in real-time. The accuracy of the system is 79.1% for alertness and 90.91% for drowsiness states. When the system detects drowsiness, it will warn drivers by using a vibrator and a beeper.

  13. 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...

  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. 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...

  16. 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.

  17. Real-time detection of moving objects in a dynamic scene from moving robotic vehicles

    NASA Technical Reports Server (NTRS)

    Ansar, A.; Talukder, S.; Goldberg, L.; Matthies, A.

    2003-01-01

    Dynamic scene perception is currently limited to detection of moving objects from a static platform or scenes with flat backgrounds. We discuss novel methods to segment moving objects in the motion field formed by a moving camera/robotic platform in real time.

  18. 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...

  19. 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.

  20. Real-time PCR assay for rapid qualitative and quantitative detection of Entamoeba histolytica.

    PubMed

    Orosz, Erika; Perkátai, Katalin; Kapusinszky, Beatrix; Farkas, Agnes; Kucsera, István

    2012-12-01

    Simple real-time PCR assay with one set of primer and probe for rapid, sensitive qualitative and quantitative detection of Entamoeba histolytica has been used. Consensus sequences were used to amplify a species-specific region of the 16S rRNA gene, and fluorescence resonance energy transfer hybridization probes were used for detection in a LightCycler platform (Roche). The anchor probe sequence was designed to be a perfect match for the 16S rRNA gene of Entamoeba species, while the acceptor probe sequence was designed for Entamoeba histolytica, which allowed differentiation. The performed characteristics of the real-time PCR assay were compared with ELISA antigen and microscopical detection from 77 samples of individuals with suspected clinical diagnosis of imported E. histolytica infection. Stool and liver abscess pus samples were examined with analytical sensitivity of 5 parasites per PCR reaction. The melting curve means Tms (standard deviation) in clinical isolates were 54°C. The real-time assay was 100% sensitive and specific for differentiation of Entamoeba histolytica, compared with conventional ELISA or microscopy. This real-time PCR assay with melting curve analysis is rapid, and specific for the detection and differentiation of Entamoeba histolytica. The suitability for routine use of this assay in clinical diagnostic laboratories is discussed.

  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. 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...

  4. 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).

  5. 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

  6. 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

  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. Evaluation of real-time loop-mediated isothermal amplification (RealAmp) for rapid detection of Mycobacterium tuberculosis from sputum samples.

    PubMed

    Li, Yiming; Shi, Lei; Pan, Anqi; Cao, Weiwei; Chen, Xun; Meng, Hecheng; Yan, He; Miyoshi, Shin-ichi; Ye, Lei

    2014-09-01

    Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) leads to serious health problems as a chronic respiratory infectious disease. Here we established a real-time fluorescence loop-mediated isothermal amplification assay (RealAmp) using a portable ESE Quant tube scanner as a convenient rapid detection method for MTB. The method efficacy from sputum samples was further investigated, and the reaction time was only 20min with the detection limit low to 10(2)CFU/ml concentration of MTB. We assessed a total of 1067 samples by the RealAmp assay, comparing the results with smear microscopy and conventional culture methods. To examine whether the failure to detect TB by culturing is due to low sensitivity or true absence, we examined the culture negative samples by commercial real time PCR MTB detection kit, and the results were compared with RealAmp. The data showed that RealAmp assay had a higher positive rate than that of sputum smear and culture methods. RealAmp had a sensitivity of 96.70% and a specificity of 91.55% when compared with culture. In addition, its sensitivity and specificity were 95.29% and 86.88% respectively compared with examination of smear samples using light microscopy. The sensitivity of RealAmp in comparison to real time PCR was 98.25% and specificity was 99.11% in validation of culture negative samples. The present study revealed the newly established RealAmp assay as a convenient, efficient, sensitive and specific method that could be an alternative for rapid detection of MTB and a tool to validate culture and smear negative samples. Furthermore, the portability of the ESE Quant tube scanner also contributed to the promising application for grassroots and field detection of MTB.

  9. Real-Time PCR Detection of Phaeomoniella chlamydospora and Phaeoacremonium aleophilum

    PubMed Central

    Cobos, Rebeca; Martín, Laura; López-Enríquez, Lorena

    2012-01-01

    Phaeomoniella chlamydospora and Phaeoacremonium aleophilum are the two main fungal causal agents of Petri disease and esca. Both diseases cause significant economic losses to viticulturalists. Since no curative control measures are known, proactive defensive measures must be taken. An important aspect of current research is the development of sensitive and time-saving protocols for the detection and identification of these pathogens. Real-time PCR based on the amplification of specific sequences is now being used for the identification and quantification of many infective agents. The present work reports real-time PCR protocols for identification of P. chlamydospora and P. aleophilum. Specificity was demonstrated against purified DNA from 60 P. chlamydospora isolates or 61 P. aleophilum isolates, and no amplification was obtained with 54 nontarget DNAs. The limits of detection (i.e., DNA detectable in 95% of reactions) were around 100 fg for P. chlamydospora and 50 fg for P. aleophilum. Detection was specific and sensitive for P. chlamydospora and P. aleophilum. Spores of P. chlamydospora and P. aleophilum were detected without the need for DNA purification. The established protocols detected these fungi in wood samples after DNA purification. P. chlamydospora was detectable without DNA purification and isolation in 67% of reactions. The detection of these pathogens in wood samples has great potential for use in pathogen-free certification schemes. PMID:22447605

  10. Real-time PCR detection of Phaeomoniella chlamydospora and Phaeoacremonium aleophilum.

    PubMed

    Martín, Maria Teresa; Cobos, Rebeca; Martín, Laura; López-Enríquez, Lorena

    2012-06-01

    Phaeomoniella chlamydospora and Phaeoacremonium aleophilum are the two main fungal causal agents of Petri disease and esca. Both diseases cause significant economic losses to viticulturalists. Since no curative control measures are known, proactive defensive measures must be taken. An important aspect of current research is the development of sensitive and time-saving protocols for the detection and identification of these pathogens. Real-time PCR based on the amplification of specific sequences is now being used for the identification and quantification of many infective agents. The present work reports real-time PCR protocols for identification of P. chlamydospora and P. aleophilum. Specificity was demonstrated against purified DNA from 60 P. chlamydospora isolates or 61 P. aleophilum isolates, and no amplification was obtained with 54 nontarget DNAs. The limits of detection (i.e., DNA detectable in 95% of reactions) were around 100 fg for P. chlamydospora and 50 fg for P. aleophilum. Detection was specific and sensitive for P. chlamydospora and P. aleophilum. Spores of P. chlamydospora and P. aleophilum were detected without the need for DNA purification. The established protocols detected these fungi in wood samples after DNA purification. P. chlamydospora was detectable without DNA purification and isolation in 67% of reactions. The detection of these pathogens in wood samples has great potential for use in pathogen-free certification schemes.

  11. 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.

  12. 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

  13. Autonomous Detection of Eruptions, Plumes, and Other Transient Events in the Outer Solar System

    NASA Astrophysics Data System (ADS)

    Bunte, M. K.; Lin, Y.; Saripalli, S.; Bell, J. F.

    2012-12-01

    The outer solar system abounds with visually stunning examples of dynamic processes such as eruptive events that jettison materials from satellites and small bodies into space. The most notable examples of such events are the prominent volcanic plumes of Io, the wispy water jets of Enceladus, and the outgassing of comet nuclei. We are investigating techniques that will allow a spacecraft to autonomously detect those events in visible images. This technique will allow future outer planet missions to conduct sustained event monitoring and automate prioritization of data for downlink. Our technique detects plumes by searching for concentrations of large local gradients in images. Applying a Scale Invariant Feature Transform (SIFT) to either raw or calibrated images identifies interest points for further investigation based on the magnitude and orientation of local gradients in pixel values. The interest points are classified as possible transient geophysical events when they share characteristics with similar features in user-classified images. A nearest neighbor classification scheme assesses the similarity of all interest points within a threshold Euclidean distance and classifies each according to the majority classification of other interest points. Thus, features marked by multiple interest points are more likely to be classified positively as events; isolated large plumes or multiple small jets are easily distinguished from a textured background surface due to the higher magnitude gradient of the plume or jet when compared with the small, randomly oriented gradients of the textured surface. We have applied this method to images of Io, Enceladus, and comet Hartley 2 from the Voyager, Galileo, New Horizons, Cassini, and Deep Impact EPOXI missions, where appropriate, and have successfully detected up to 95% of manually identifiable events that our method was able to distinguish from the background surface and surface features of a body. Dozens of distinct features

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Secure access control and large scale robust representation for online multimedia event detection.

    PubMed

    Liu, Changyu; Lu, Bin; 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.

  1. 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.

  2. 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.

  3. Molecular beacon probes combined with amplification by NASBA enable homogeneous, real-time detection of RNA.

    PubMed

    Leone, G; van Schijndel, H; van Gemen, B; Kramer, F R; Schoen, C D

    1998-05-01

    Molecular beacon probes can be employed in a NASBA amplicon detection system to generate a specific fluorescent signal concomitantly with amplification. A molecular beacon, designed to hybridize within the target sequence, was introduced into NASBA reactions that amplify the genomic RNA of potato leafroll virus (PLRV). During amplification, the probe anneals to the antisense RNA amplicon generated by NASBA, producing a specific fluorescent signal that can be monitored in real-time. The assay is rapid, sensitive and specific. As RNA amplification and detection can be carried out in unopened vessels, it minimizes the risk of carry-over contaminations. Robustness has been verified on real-world samples. This homogeneous assay, called AmpliDet RNA, is a significant improvement over current detection methods for NASBA amplicons and is suitable for one-tube applications ranging from high-throughput diagnostics to in vivo studies of biological activities.

  4. Development of real-time PCR assay for differential detection of Bordetella bronchiseptica and Bordetella parapertussis.

    PubMed

    Tizolova, Anette; Brun, Delphine; Guiso, Nicole; Guillot, Sophie

    2014-04-01

    Bordetella parapertussis is a causative agent of whooping cough in humans, and B. bronchiseptica is causing wide variety of respiratory infections in mammals, including humans. Specific diagnostic tests are not currently available. Our first objective was to develop a real-time PCR test for the specific detection of B. bronchiseptica based on the previously described end-point PCR, targeting an intergenomic sequence of the fla gene locus, but it has not been reached. However, there is cross-reactivity between B. parapertussis and B. bronchiseptica. Therefore, the targeted region of several clinical isolates of both species was sequenced, and alignment of the sequences allowed the development of a 2-step real-time PCR assay. The first PCR assay detected the DNA of all clinical isolates of both B. bronchiseptica and B. parapertussis tested. The second PCR assay detected only the DNA of B. parapertussis clinical isolates, thereby allowing discrimination between B. parapertussis and B. bronchiseptica.

  5. 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

  6. 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

  7. Detection and identification of multiple genetically modified events using DNA insert fingerprinting.

    PubMed

    Raymond, Philippe; Gendron, Louis; Khalf, Moustafa; Paul, Sylvianne; Dibley, Kim L; Bhat, Somanath; Xie, Vicki R D; Partis, Lina; Moreau, Marie-Eve; Dollard, Cheryl; Coté, Marie-José; Laberge, Serge; Emslie, Kerry R

    2010-03-01

    Current screening and event-specific polymerase chain reaction (PCR) assays for the detection and identification of genetically modified organisms (GMOs) in samples of unknown composition or for the detection of non-regulated GMOs have limitations, and alternative approaches are required. A transgenic DNA fingerprinting methodology using restriction enzyme digestion, adaptor ligation, and nested PCR was developed where individual GMOs are distinguished by the characteristic fingerprint pattern of the fragments generated. The inter-laboratory reproducibility of the amplified fragment sizes using different capillary electrophoresis platforms was compared, and reproducible patterns were obtained with an average difference in fragment size of 2.4 bp. DNA insert fingerprints for 12 different maize events, including two maize hybrids and one soy event, were generated that reflected the composition of the transgenic DNA constructs. Once produced, the fingerprint profiles were added to a database which can be readily exchanged and shared between laboratories. This approach should facilitate the process of GMO identification and characterization.

  8. 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.…

  9. [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

  10. 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…

  11. 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…

  12. Comparative detection of rabies RNA by NASBA, real-time PCR and conventional PCR.

    PubMed

    Wacharapluesadee, Supaporn; Phumesin, Patta; Supavonwong, Pornpun; Khawplod, Pakamatz; Intarut, Nirun; Hemachudha, Thiravat

    2011-08-01

    Five methods for the RNA detection of rabies virus were directly compared in this study. These included conventional nucleic acid sequence-based amplification with electrochemiluminescence (NASBA-ECL) assay, reverse transcription (RT)-heminested (hn) polymerase chain reaction (PCR) and TaqMan real-time RT-PCR using protocols as described previously. The first two methods have been routinely utilised for ante-mortem diagnosis of human rabies in Thailand and other rabies-endemic Asian and African countries. In addition, two real-time NASBA assays based on the use of a NucliSens EasyQ analyser (NASBA-Beacon-EQ) and LightCycler real-time PCR machine (NASBA-Beacon-LC) were studied in parallel. All methods target the N gene, whereas the L gene is used for RT-hnPCR. Using serial dilutions of purified RNA from rabies-infected dog brain tissue to assess sensitivity, all five methods had comparable degrees of sensitivities of detection. However, both real-time NASBA assays had slightly lower sensitivities by 10-fold than the other three assays. This finding was also true (except for TaqMan real-time RT-PCR due to a mismatch between the target and probe sequences) when laboratory-adapted (challenge virus standard-11) virus was used in the assays. Testing on previously NASBA-ECL positive clinical samples from 10 rabies patients (saliva [6] and brain [4]) and 10 rabies-infected dog brain tissues, similar results were obtained among the five methods; real-time NASBA assays yielded false-negative results on 2 saliva samples. None of the assays showed positive results on cerebrospinal fluid specimens of 10 patients without rabies encephalitis. Due to the unavailability of the NASBA-ECL assay, the results show that TaqMan real-time RT-PCR and RT-hnPCR can be useful for ante- and post-mortem diagnosis of rabies.

  13. 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

  14. Real-time EEG-based detection of fatigue driving danger for accident prediction.

    PubMed

    Wang, Hong; Zhang, Chi; Shi, Tianwei; Wang, Fuwang; Ma, Shujun

    2015-03-01

    This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of driver fatigue was analyzed. The functional brain networks were employed to track the fatigue impact on processing capacity of brain. The results show the overall functional connectivity of the subjects is weakened after long time driving tasks. The regularity is summarized as the fatigue convergence phenomenon. Based on the fatigue convergence phenomenon, we combined both the input and global synchronizations of brain together to calculate the residual amount of the information processing capacity of brain to obtain the dangerous points in real time. Finally, the danger detection system of the driver fatigue based on the neural mechanism was validated using accident EEG. The time distributions of the output danger points of the system have a good agreement with those of the real accident points.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. Development and validation of real-time PCR for the detection of Yersinia ruckeri.

    PubMed

    Keeling, S E; Johnston, C; Wallis, R; Brosnahan, C L; Gudkovs, N; McDonald, W L

    2012-02-01

    Yersiniosis (enteric red mouth disease) is a contagious bacterial disease caused by Yersinia ruckeri, which primarily affects salmonids. A real-time PCR assay using a molecular beacon has been developed and validated to improve the detection of the causative biotypes of Y. ruckeri. The assay, which targets the glnA (glutamine synthetase) gene, proved to have 100% analytical specificity and analytical sensitivities of 5 fg and 3 × 10(3) CFU g(-1) for DNA and seeded kidney tissue, respectively. The assay was highly repeatable with low % CV for intra- and inter-run experiments, and the optimized parameters transferred easily between different real-time PCR platforms. Following analytical validation, diagnostic specificity was determined using New Zealand farmed Chinook salmon (n = 750) from 10 farms during 2007/08. The real-time PCR was run in parallel with the bacterial culture detection method, and all fish tested were found to be negative by both methods for Y. ruckeri, resulting in 100% diagnostic specificity (95% confidence interval). The molecular beacon real-time PCR system is specific, sensitive, reproducible and a rapid method for the detection of Y. ruckeri and has the potential to be used for routine diagnostic testing, health certification and active surveillance programmes.

  20. 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.

  1. 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

  2. Low time resolution analysis of polar ice cores cannot detect impulsive nitrate events

    NASA Astrophysics Data System (ADS)

    Smart, D. F.; Shea, M. A.; Melott, A. L.; Laird, C. M.

    2014-12-01

    Ice cores are archives of climate change and possibly large solar proton events (SPEs). Wolff et al. (2012) used a single event, a nitrate peak in the GISP2-H core, which McCracken et al. (2001a) time associated with the poorly quantified 1859 Carrington event, to discredit SPE-produced, impulsive nitrate deposition in polar ice. This is not the ideal test case. We critique the Wolff et al. analysis and demonstrate that the data they used cannot detect impulsive nitrate events because of resolution limitations. We suggest reexamination of the top of the Greenland ice sheet at key intervals over the last two millennia with attention to fine resolution and replicate sampling of multiple species. This will allow further insight into polar depositional processes on a subseasonal scale, including atmospheric sources, transport mechanisms to the ice sheet, postdepositional interactions, and a potential SPE association.

  3. 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.

  4. Detection and quantification of Enterococcus gilvus in cheese by real-time PCR.

    PubMed

    Zago, Miriam; Bonvini, Barbara; Carminati, Domenico; Giraffa, Giorgio

    2009-10-01

    The objective of this work was to investigate the occurrence of Enterococcus gilvus in cheese. For this purpose, a real-time PCR protocol using phenylalanyl-tRNA synthase (pheS) as a target gene was optimized to evaluate the presence and abundance of this microorganism in Italian artisan cheeses. The real-time assay unequivocally distinguished E. gilvus from 25 non-target LAB and non-LAB species, demonstrating its absolute specificity. The assay performed well not only with purified DNA but also with DNA extracted from cheese samples artificially contaminated with E. gilvus. The dynamic range of target determination of the method in the cheese matrix (from 10(7) to 10(4) cfu/ml, covering three orders of magnitude) was lower and the detection limit higher than in vitro conditions, but still high enough to obtain an excellent quantification accuracy in cheese. Twenty commercially available cheeses were analyzed by real-time PCR and approximately 40% of the cheese samples contained E. gilvus at levels ranging from 4.17+/-0.10 to 6.75+/-0.01 log cfu/g. Such levels represented 0.1-10% of the total enterococci counted on kanamycin aesculin azide agar (KAA) from the corresponding cheeses. The successful isolation of E. gilvus from cheeses containing high loads of this species, as detected by real-time PCR, provided definitive proof on both assay specificity and presence of this organism in cheeses. Despite the relatively low sensitivity in cheese (> or =4 log cfu/g), the real-time PCR described here may, however, be useful to detect E. gilvus rapidly when present at (sub)dominant levels within the enterococcal cheese microflora. The assay may be helpful to detect and quantify E. gilvus strains from food, thus enabling a better understanding of technological role, ecological and safety aspects in cheeses and other fermented food products of this infrequent species. PMID:19625150

  5. Remote monitoring of cardiovascular implantable devices in the pediatric population improves detection of adverse events.

    PubMed

    Malloy, Lindsey E; Gingerich, Jean; Olson, Mark D; Atkins, Dianne L

    2014-02-01

    With the exponential growth of cardiovascular implantable electronic devices (CIEDs) in pediatric patients, a new method of long-term surveillance, remote monitoring (RM), has become the standard of care. The purpose of this study was to determine the usefulness of RM as a monitoring tool in the pediatric population. A retrospective review was performed of 198 patients at the University of Iowa Children's Hospital who had CIEDs. Data transmitted by RM were analyzed. The following data were examined: patient demographics; median interval between transmissions; detection of adverse events requiring corrective measures, including detection of lead failure; detection of arrhythmias and device malfunctions independent of symptoms; time gained in the detection of events using RM versus standard practice; the validity of RM; and the impact of RM on data management. Of 198 patients, 162 submitted 615 RM transmissions. The median time between remote transmissions was 91 days. Of 615 total transmissions, 16 % had true adverse events with 11 % prompting clinical intervention. Of those events requiring clinical response, 61 % of patients reported symptoms. The median interval between last follow-up and occurrence of events detected by RM was 46 days, representing a gain of 134 days for patients followed-up at 6-month intervals and 44 days for patients followed-up at 3 month-intervals. The sensitivity and specificity of RM were found to be 99 and 72 %, respectively. The positive and negative predictive values were found to be 41 and 99 %, respectively. RM allows for early identification of arrhythmias and device malfunctions, thus prompting earlier corrective measures and improving care and safety in pediatric patients.

  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. 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.

  8. [Analytical performances of real-time PCR by Abbott RealTime CMV with m2000 for the detection of cytomegalovirus in urine].

    PubMed

    De Monte, Anne; Cannavo, Isabelle; Caramella, Anne; Ollier, Laurence; Giordanengo, Valérie

    2016-01-01

    Congenital cytomegalovirus (CMV) infection is the leading cause of sensoneurinal disability due to infectious congenital disease. The diagnosis of congenital CMV infection is based on the search of CMV in the urine within the first two weeks of life. Viral culture of urine is the gold standard. However, the PCR is highly sensitive and faster. It is becoming an alternative choice. The objective of this study is the validation of real-time PCR by Abbott RealTime CMV with m2000 for the detection of cytomegalovirus in urine. Repeatability, reproducibility, detection limit and inter-sample contamination were evaluated. Urine samples from patients (n=141) were collected and analyzed simultaneously in culture and PCR in order to assess the correlation of these two methods. The sensitivity and specificity of PCR were also calculated. The Abbott RealTime CMV PCR in urine is an automated and sensitive method (detection limit 200 UI/mL). Fidelity is very good (standard deviation of repeatability: 0.08 to 0.15 LogUI/mL and reproducibility 0.18 LogUI/mL). We can note a good correlation between culture and Abbott RealTime CMV PCR (kappa 96%). When considering rapid culture as reference, real-time PCR was highly sensitive (100%) and specific (98.2%). The real-time PCR by Abbott RealTime CMV with m2000 is optimal for CMV detection in urine.

  9. Nonlinear real-life signal detection with a supervised principal components analysis.

    PubMed

    Zhou, C T; Cai, T X; Cai, T F

    2007-03-01

    A novel strategy named supervised principal components analysis for the detection of a target signal of interest embedded in an unknown noisy environment has been investigated. There are two channels in our detection scheme. Each channel consists of a nonlinear phase-space reconstructor (for embedding a data matrix using the received time series) and a principal components analyzer (for feature extraction), respectively. The output error time series, which results from the difference of both eigenvectors of the correlation data matrices from these two channels, is then analyzed using time-frequency tools, for example, frequency spectrum or Wigner-Ville distribution. Experimental results based on real-life electromagnetic data are presented to demonstrate the detection performance of our algorithm. It is found that weak signals hidden beneath the noise floor can be detected. Furthermore, the robustness of the detection performance clearly illustrated that signal frequencies can be extracted when the signal power is not too low.

  10. 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

  11. 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

  12. Effects of performing two visual tasks on single-trial detection of event-related potentials.

    PubMed

    Cecotti, Hubert; Eckstein, Miguel P; Giesbrecht, Barry

    2012-01-01

    The detection of event-related potentials (ERPs) in brain-computer interface (BCI) depends on the ability of the subject to pay attention to specific stimuli presented during the BCI task. For healthy users, a BCI shall be used as a complement to other existing devices, which involve the response to other tasks. Those tasks may impair selective attention, particularly if the stimuli have the same modality e.g. visual. It is therefore critical to analyze how single-trial detection of brain evoked response is impaired by the addition of tasks concerning the same modality. We tested 10 healthy participants using an application that has two visual target detection tasks. The first one corresponds to a rapid serial visual presentation paradigm where target detection is achieved by brain-evoked single-trial detection in the recorded electroencephalogram (EEG) signal. The second task is the detection of a visual event on a tactical map by a behavioral response. These tasks were tested individually (single task) and in parallel (dual-task). Whereas the performance of single-trial detection was not impaired between single and dual-task conditions, the behavioral performance decreased during the dual-task condition. These results quantify the performance drop that can occur in a dual-task system using both brain-evoked responses and behavioral responses. PMID:23366242

  13. 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

  14. Real-time vision-based traffic flow measurements and incident detection

    NASA Astrophysics Data System (ADS)

    Fishbain, Barak; Ideses, Ianir; Mahalel, David; Yaroslavsky, Leonid

    2009-02-01

    Visual surveillance for traffic systems requires short processing time, low processing cost and high reliability. Under those requirements, image processing technologies offer a variety of systems and methods for Intelligence Transportation Systems (ITS) as a platform for traffic Automatic Incident Detection (AID). There exist two classes of AID methods mainly studied: one is based on inductive loops, radars, infrared sonar and microwave detectors and the other is based on video images. The first class of methods suffers from drawbacks in that they are expensive to install and maintain and they are unable to detect slow or stationary vehicles. Video sensors, on the other hand, offer a relatively low installation cost with little traffic disruption during maintenance. Furthermore, they provide wide area monitoring allowing analysis of traffic flows and turning movements, speed measurement, multiple-point vehicle counts, vehicle classification and highway state assessment, based on precise scene motion analysis. This paper suggests the utilization of traffic models for real-time vision-based traffic analysis and automatic incident detection. First, the traffic flow variables, are introduced. Then, it is described how those variables can be measured from traffic video streams in real-time. Having the traffic variables measured, a robust automatic incident detection scheme is suggested. The results presented here, show a great potential for integration of traffic flow models into video based intelligent transportation systems. The system real time performance is achieved by utilizing multi-core technology using standard parallelization algorithms and libraries (OpenMP, IPP).

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. A universal real-time assay for the detection of Lyssaviruses.

    PubMed

    Hayman, David T S; Banyard, Ashley C; Wakeley, Philip R; Harkess, Graeme; Marston, Denise; Wood, James L N; Cunningham, Andrew A; Fooks, Anthony R

    2011-10-01

    Rabies virus (RABV) is enzootic throughout most of the world. It is now widely accepted that RABV had its origins in bats. Ten of the 11 Lyssavirus species recognised, including RABV, have been isolated from bats. There is, however, a lack of understanding regarding both the ecology and host reservoirs of Lyssaviruses. A real-time PCR assay for the detection of all Lyssaviruses using universal primers would be beneficial for Lyssavirus surveillance. It was shown that using SYBR(®) Green, a universal real-time PCR primer pair previously demonstrated to detect European bat Lyssaviruses 1 and 2, and RABV, was able to detect reverse transcribed RNA for each of the seven virus species available to us. Target sequences of bat derived virus species unavailable for analysis were synthesized to produce oligonucleotides. Lagos Bat-, Duvenhage- and Mokola virus full nucleoprotein gene clones enabled a limit of 5-50 plasmid copies to be detected. Five copies of each of the synthetic DNA oligonucleotides of Aravan-, Khujand-, Irkut-, West Caucasian bat- and Shimoni bat virus were detected. The single universal primer pair was therefore able to detect each of the most divergent known Lyssaviruses with great sensitivity. PMID:21777619

  2. Detection of Thielaviopsis basicola in soil with real-time quantitative PCR assays.

    PubMed

    Huang, Junli; Kang, Zhenhui

    2010-07-20

    Thielaviopsis basicola is a soil-borne fungus with a wide host range and a cosmopolitan distribution. It causes disease on many agricultural crops and in China it is the causal agent of black root rot on tobacco plant. Early diagnosis and detection of the pathogen in soil are critical to control this disease in field. The objective of this study was to develop sensitive and effective methods suitable for large-scale detection and quantification of T. basicola. Based on the nucleotide sequences of the internal transcribed spacer (ITS) regions of rDNA genes of Thielaviopsis spp, primers and TaqMan probe were designed specifically to amplify DNA from T. basicola and real-time, quantitative PCR (qPCR) assays were developed for rapid, specific and sensitive detection and quantification of T. basicola. It was sensitive with the detection limit of 100 fg microl(-1) genomic DNA of T. basicola in qPCR assays. By combining the qPCR assays with the efficient protocol to extract DNA from soil, it was possible to achieve real-time detection of T. basicola in soil in 4-5 h and the detection limit of 3 conidia per reaction in qPCR was recorded. The assays were applied to survey soils from tobacco fields in China for the presence of T. basicola and the analyses of naturally infested soil showed the reliability of the qPCR assays.

  3. Long-Duration Neutron Production in Solar Eruptive Events Detected with the MESSENGER Neutron Spectrometer

    NASA Astrophysics Data System (ADS)

    Feldman, W. C.; Lawrence, D. J.; Vestrand, W. T.; Peplowski, P. N.

    2014-12-01

    Nine long-duration neutron solar eruptive events (SEEs) between 31 December 2007 and 16 March 2013 appear to be excellent candidates for detection of fast neutrons from the Sun by the MESSENGER Neutron Spectrometer (NS). One event (on 4 June 2011) is the cleanest example, because it was not accompanied by energetic ions at MESSENGER having energies greater than 50±10 MeV/nuc. The purpose of this study is to assemble a set of conditions common to all events that can help identify the physical conditions at their origin. We classified the nine events into three categories: (1) those having tight magnetic connection to the Sun as well as to spacecraft at 1 AU that can separately measure the energetic proton, alpha particle, and electron flux spectra, (2) those with sufficiently close connection that the energetic flux spectra can be compared, (3) those that have only marginal connections, and (4) those that are also seen at Earth. Four events fall into category (1), three into category (2), two into category (3), and parts of four events overlapped neutron events also seen by the scintillation FIBer solar neutron telescope (FIB) detector placed on the International Space Station in 2009. Seven of the nine events that have either tight or marginal magnetic connection have alpha particle abundances less than 2%. For each event, we modeled expected fast neutron count rates from the 1 AU ion spectrum, a process that accounts for the transport of the neutrons through the spacecraft to the NS. The ratios of measured to predicted fast-neutron counts range between 2.0 and 12.1.

  4. 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.

  5. 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

  6. Challenges in real-life emotion annotation and machine learning based detection.

    PubMed

    Devillers, Laurence; Vidrascu, Laurence; Lamel, Lori

    2005-05-01

    Since the early studies of human behavior, emotion has attracted the interest of researchers in many disciplines of Neurosciences and Psychology. More recently, it is a growing field of research in computer science and machine learning. We are exploring how the expression of emotion is perceived by listeners and how to represent and automatically detect a subject's emotional state in speech. In contrast with most previous studies, conducted on artificial data with archetypal emotions, this paper addresses some of the challenges faced when studying real-life non-basic emotions. We present a new annotation scheme allowing the annotation of emotion mixtures. Our studies of real-life spoken dialogs from two call center services reveal the presence of many blended emotions, dependent on the dialog context. Several classification methods (SVM, decision trees) are compared to identify relevant emotional states from prosodic, disfluency and lexical cues extracted from the real-life spoken human-human interactions.

  7. Ontology-based knowledge management for personalized adverse drug events detection.

    PubMed

    Cao, Feng; Sun, Xingzhi; Wang, Xiaoyuan; Li, Bo; Li, Jing; Pan, Yue

    2011-01-01

    Since Adverse Drug Event (ADE) has become a leading cause of death around the world, there arises high demand for helping clinicians or patients to identify possible hazards from drug effects. Motivated by this, we present a personalized ADE detection system, with the focus on applying ontology-based knowledge management techniques to enhance ADE detection services. The development of electronic health records makes it possible to automate the personalized ADE detection, i.e., to take patient clinical conditions into account during ADE detection. Specifically, we define the ADE ontology to uniformly manage the ADE knowledge from multiple sources. We take advantage of the rich semantics from the terminology SNOMED-CT and apply it to ADE detection via the semantic query and reasoning. PMID:21893837

  8. 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

  9. Automated detection of instantaneous gait events using time frequency analysis and manifold embedding.

    PubMed

    Aung, Min S H; Thies, Sibylle B; Kenney, Laurence P J; Howard, David; Selles, Ruud W; Findlow, Andrew H; Goulermas, John Y

    2013-11-01

    Accelerometry is a widely used sensing modality in human biomechanics due to its portability, non-invasiveness, and accuracy. However, difficulties lie in signal variability and interpretation in relation to biomechanical events. In walking, heel strike and toe off are primary gait events where robust and accurate detection is essential for gait-related applications. This paper describes a novel and generic event detection algorithm applicable to signals from tri-axial accelerometers placed on the foot, ankle, shank or waist. Data from healthy subjects undergoing multiple walking trials on flat and inclined, as well as smooth and tactile paving surfaces is acquired for experimentation. The benchmark timings at which heel strike and toe off occur, are determined using kinematic data recorded from a motion capture system. The algorithm extracts features from each of the acceleration signals using a continuous wavelet transform over a wide range of scales. A locality preserving embedding method is then applied to reduce the high dimensionality caused by the multiple scales while preserving salient features for classification. A simple Gaussian mixture model is then trained to classify each of the time samples into heel strike, toe off or no event categories. Results show good detection and temporal accuracies for different sensor locations and different walking terrains. PMID:23322764

  10. 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

  11. 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.

  12. Automatic Acoustic Events Detection, Classification, and Semantic Annotation for Persistent Surveillance Applications

    NASA Astrophysics Data System (ADS)

    Alkilani, Amjad H. I.

    Acoustic surveillance and human behavior analysis represent some of the ongoing research topics in signal processing. Acoustic sensors offer a promising sensing modality, primarily because they can capture a huge amount of information from the environment. Moreover, they can be rapidly deployed and are low-cost. In the past, significant efforts have been devoted to detecting sounds of individual objects or events. However, the issue of understanding human activities based on sporadic acoustic sound events has received unequal attention in the literature and hence is not well understood. This dissertation presents an extensive literature survey on this topic and discusses existing advanced techniques for acoustic signal processing and pattern recognition. A novel theoretic framework (Acoustic Events Detection, Classification, and Annotation (AEDCA)) is proposed which accommodates sound events ontology for improved human activities recognition. Based on a generalized taxonomy, three sound categories signifying interaction of human with each other, with vehicles, and with other objects are introduced. In order to understand different type of human interactions salient sound events are preliminarily identified and classified based on trained set of data. To interlink salient events representing an ontology-based hypothesis, a Hidden Markov Model-Acoustic Activity Recognizer (HMM-AAR) is modeled to recognize spatiotemporally correlated events. Once such a connection is established, an annotation of perceived sound activity is generated. The performance of the AEDCA system was tested and measured experimentally in both indoor and outdoor environments. Appropriate confusion matrices are developed for the assessment of performance reliability, and computational efficiency of the AEDCA system. The obtained results are very promising and strongly demonstrate the AEDCA is both reliable and effective, and can be extended to future surveillance applications.

  13. Exploring the limits of waveform correlation event detection as applied to three earthquake aftershock sequences.

    SciTech Connect

    Resor, Megan E.; Carr, Dorthe Bame; Young, Christopher John

    2010-05-01

    Swarms of earthquakes and/or aftershock sequences can dramatically increase the level of seismicity in a region for a period of time lasting from days to months, depending on the swarm or sequence. Such occurrences can provide a large amount of useful information to seismologists. For those who monitor seismic events for possible nuclear explosions, however, these swarms/sequences are a nuisance. In an explosion monitoring system, each event must be treated as a possible nuclear test until it can be proven, to a high degree of confidence, not to be. Seismic events recorded by the same station with highly correlated waveforms almost certainly have a similar location and source type, so clusters of events within a swarm can quickly be identified as earthquakes. We have developed a number of tools that can be used to exploit the high degree of waveform similarity expected to be associated with swarms/sequences. Dendro Tool measures correlations between known events. The Waveform Correlation Detector is intended to act as a detector, finding events in raw data which correlate with known events. The Self Scanner is used to find all correlated segments within a raw data steam and does not require an event library. All three techniques together provide an opportunity to study the similarities of events in an aftershock sequence in different ways. To comprehensively characterize the benefits and limits of waveform correlation techniques, we studied 3 aftershock sequences, using our 3 tools, at multiple stations. We explored the effects of station distance and event magnitudes on correlation results. Lastly, we show the reduction in detection threshold and analyst workload offered by waveform correlation techniques compared to STA/LTA based detection. We analyzed 4 days of data from each aftershock sequence using all three methods. Most known events clustered in a similar manner across the toolsets. Up to 25% of catalogued events were found to be a member of a cluster. In

  14. First real-time detection on surface dust detection in tokamaks

    NASA Astrophysics Data System (ADS)

    Skinner, C. H.; Roquemore, L.; Kugel, H. W.; Rais, B.

    2010-11-01

    Dust generated from plasma surface interactions has important consequences for the operation and safety of next-step devices and local measurements of dust are part of the ITER dust strategy. The first real-time measurements of surface dust in the NSTX vessel have been successfully made using an novel electrostatic surface dust detector. Impinging dust particles create a temporary short circuit on fine grid of interlocking circuit traces that is biased to 50 v and the resulting current pulse is recorded by counting electronics. Techniques used to increase the sensitivity to match NSTX dust levels while suppressing electrical pickup will be presented. The detector has been calibrated with both carbon and lithium particles. In a separate experiment a probe with ITER scale castellation gaps was filled with dust particles and exposed to an intentional disruption in NSTX. Results on the mobilization of dust from the castellations will be reported.

  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. 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

  17. myBlackBox: Blackbox Mobile Cloud Systems for Personalized Unusual Event Detection.

    PubMed

    Ahn, Junho; Han, Richard

    2016-05-23

    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.

  18. 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

  19. 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

  20. Rapid quantitative detection of Lactobacillus sakei in meat and fermented sausages by real-time PCR.

    PubMed

    Martín, Belén; Jofré, Anna; Garriga, Margarita; Pla, Maria; Aymerich, Teresa

    2006-09-01

    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.

  1. Development of real-time PCR assays for detection of megalocytiviruses in imported ornamental fish.

    PubMed

    Gias, E; Johnston, C; Keeling, S; Spence, R P; McDonald, W L

    2011-08-01

    Megalocytiviruses have been associated globally with severe systemic disease and economic loss in farmed food fish and ornamental fish. The viruses have been spread internationally by translocation of live fish. In New Zealand, megalocytiviruses are regarded as exotic. A potential pathway for introduction has been identified, namely imported ornamental fish. In the present study, real-time PCR assays were developed for detection of megalocytiviruses using a conserved major capsid protein gene. A SYBR green assay was developed to target all known megalocytiviruses. A second real-time PCR assay using a molecular beacon was developed to specifically target gourami, Trichogaster trichopterus, iridovirus, a species of iridovirus previously linked to ornamental fish imports in Australia. The analytical sensitivity for the SYBR green and molecular beacon assays were 10 and 100 fg, respectively. The analytical specificity of the real-time PCR assays determined using genomic DNA templates from three target viruses, 12 non-target viruses and 25 aquatic bacterial species were 100%. The intra-run and inter-run coefficients of variation of both assays were <5%. The real-time PCR assays developed in this study provide rapid, sensitive, and specific detection of megalocytiviruses and gourami iridovirus.

  2. 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.

  3. Incremental activation detection for real-time fMRI series using robust Kalman filter.

    PubMed

    Li, Liang; Yan, Bin; Tong, Li; Wang, Linyuan; Li, Jianxin

    2014-01-01

    Real-time functional magnetic resonance imaging (rt-fMRI) is a technique that enables us to observe human brain activations in real time. However, some unexpected noises that emerged in fMRI data collecting, such as acute swallowing, head moving and human manipulations, will cause much confusion and unrobustness for the activation analysis. In this paper, a new activation detection method for rt-fMRI data is proposed based on robust Kalman filter. The idea is to add a variation to the extended kalman filter to handle the additional sparse measurement noise and a sparse noise term to the measurement update step. Hence, the robust Kalman filter is designed to improve the robustness for the outliers and can be computed separately for each voxel. The algorithm can compute activation maps on each scan within a repetition time, which meets the requirement for real-time analysis. Experimental results show that this new algorithm can bring out high performance in robustness and in real-time activation detection.

  4. 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

  5. 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.

  6. 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.

  7. Detection and quantification of cultured marine Alexandrium species by real-time PCR.

    PubMed

    Zhang, Fengli; Li, Zhiyong

    2012-12-01

    The occurrence of harmful algal blooms (HABs) throughout the world has increased and poses a large threat to human health, fishery resources and tourism industries. The genus Alexandrium includes a number of toxic species associated with HABs. Therefore, it is very important to rapidly detect and monitor the harmful algae, such as Alexandrium genus. In this study, a standard curve of plasmid containing 18S rDNA-28S rDNA region from Alexandrium catenella was constructed and 5.8S rDNA sequence served as the primer of the real-time PCR. Cultured A. catenella, Alexandrium affine, Alexandrium lusitanicum and Alexandrium minutum samples were analyzed by real-time PCR using the same set of primers simultaneously. Using microscopy cells counts, 5.8S rDNA copies per cell and total DNA per cell were estimated. This assay method is promising for rapid detection of large number of Alexandrium samples. PMID:22864601

  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

    2016-07-13

    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.

  9. Detection of seismic events triggered by P-waves from the 2011 Tohoku-Oki earthquake

    NASA Astrophysics Data System (ADS)

    Miyazawa, Masatoshi

    2012-12-01

    Large-amplitude surface waves from the 2011 Tohoku-Oki earthquake triggered many seismic events across Japan, while the smaller amplitude P-wave triggering remains unclear. A spectral method was used to detect seismic events triggered by the first arriving P-waves over Japan. This method uses a reference event to correct for source and propagation effects, so that the local response near the station can be examined in detail. P-wave triggering was found in the regions where triggered non-volcanic tremor (NVT) has been observed, and some seismic and volcanic regions. The triggering strain due to P-waves is of the order of 10-8 to 10-7, which is 1 to 2 orders of magnitude smaller than the triggering strain necessary for the surface wave triggering. In the regions of NVT, the triggered event was not identified with slow events, but with other seismic events such as tectonic earthquakes. The sequence of triggering in the regions started with P-wave arrivals. The subsequent surface waves contributed to triggering of NVT, possibly together with slow slip, which resulted in the large amplitude of the NVT.

  10. 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

  11. 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

  12. 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.

  13. Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis

    PubMed Central

    Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul

    2011-01-01

    Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238

  14. A One-Step, Real-Time PCR Assay for Rapid Detection of Rhinovirus

    PubMed Central

    Do, Duc H.; Laus, Stella; Leber, Amy; Marcon, Mario J.; Jordan, Jeanne A.; Martin, Judith M.; Wadowsky, Robert M.

    2010-01-01

    One-step, real-time PCR assays for rhinovirus have been developed for a limited number of PCR amplification platforms and chemistries, and some exhibit cross-reactivity with genetically similar enteroviruses. We developed a one-step, real-time PCR assay for rhinovirus by using a sequence detection system (Applied Biosystems; Foster City, CA). The primers were designed to amplify a 120-base target in the noncoding region of picornavirus RNA, and a TaqMan (Applied Biosystems) degenerate probe was designed for the specific detection of rhinovirus amplicons. The PCR assay had no cross-reactivity with a panel of 76 nontarget nucleic acids, which included RNAs from 43 enterovirus strains. Excellent lower limits of detection relative to viral culture were observed for the PCR assay by using 38 of 40 rhinovirus reference strains representing different serotypes, which could reproducibly detect rhinovirus serotype 2 in viral transport medium containing 10 to 10,000 TCID50 (50% tissue culture infectious dose endpoint) units/ml of the virus. However, for rhinovirus serotypes 59 and 69, the PCR assay was less sensitive than culture. Testing of 48 clinical specimens from children with cold-like illnesses for rhinovirus by the PCR and culture assays yielded detection rates of 16.7% and 6.3%, respectively. For a batch of 10 specimens, the entire assay was completed in 4.5 hours. This real-time PCR assay enables detection of many rhinovirus serotypes with the Applied Biosystems reagent-instrument platform. PMID:19948820

  15. 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

  16. Women's perceptions of events impeding or facilitating the detection, investigation and treatment of breast cancer.

    PubMed

    Bairati, I; Fillion, L; Meyer, F A; Héry, C; Larochelle, M

    2006-05-01

    An integrated network is currently being implemented in the province of Quebec in order to improve the cancer care continuum. In this context, formal trajectories for cancer patients through healthcare services are being established. The investigation of patients' perceptions of the healthcare continuum is essential as it allows us to identify the issue of continuity/discontinuity of health services. In addition, patients' perceptions of continuity of cancer care should be documented since they could influence the implementation of optimal trajectories through the healthcare services. An exploratory qualitative study was conducted in order to identify events, based on the perceptions of women with breast cancer, that made the patient progress more rapidly, facilitating events, or more slowly, impeding events, within the cancer care continuum. Two consecutive series of women receiving adjuvant radiation therapy in 2002 and 2003 at the University Hospital of Quebec City were recruited, for a total of 120 participants. A semi-structured interview was administered in order to identify women's perceptions regarding impeding and facilitating events during the detection, investigation and treatment periods of cancer, as well as the actors and reasons involved. Overall, 64% of women reported having at least one impeding event, while 68% reported at least one facilitating event. The periods most frequently affected by impeding or facilitating events were the investigation period, followed by the treatment period. The main stages affected by impeding or facilitating events were the scheduling of an appointment, during the investigation period, and the onset of treatment. Impeding events particularly affected the scheduling of mammography, the initial exam of the investigation for breast cancer, as well as the onset of radiation treatment. On the other hand, facilitating events mainly occurred at the time of the scheduling of medical consultations with specialists, during the

  17. 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.

  18. Near Real-Time Dust Aerosol Detection with Support Vector Machines for Regression

    NASA Astrophysics Data System (ADS)

    Rivas-Perea, P.; Rivas-Perea, P. E.; Cota-Ruiz, J.; Aragon Franco, R. A.

    2015-12-01

    Remote sensing instruments operating in the near-infrared spectrum usually provide the necessary information for further dust aerosol spectral analysis using statistical or machine learning algorithms. Such algorithms have proven to be effective in analyzing very specific case studies or dust events. However, very few make the analysis open to the public on a regular basis, fewer are designed specifically to operate in near real-time to higher resolutions, and almost none give a global daily coverage. In this research we investigated a large-scale approach to a machine learning algorithm called "support vector regression". The algorithm uses four near-infrared spectral bands from NASA MODIS instrument: B20 (3.66-3.84μm), B29 (8.40-8.70μm), B31 (10.78-11.28μm), and B32 (11.77-12.27μm). The algorithm is presented with ground truth from more than 30 distinct reported dust events, from different geographical regions, at different seasons, both over land and sea cover, in the presence of clouds and clear sky, and in the presence of fires. The purpose of our algorithm is to learn to distinguish the dust aerosols spectral signature from other spectral signatures, providing as output an estimate of the probability of a data point being consistent with dust aerosol signatures. During modeling with ground truth, our algorithm achieved more than 90% of accuracy, and the current live performance of the algorithm is remarkable. Moreover, our algorithm is currently operating in near real-time using NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) servers, providing a high resolution global overview including 64, 32, 16, 8, 4, 2, and 1km. The near real-time analysis of our algorithm is now available to the general public at http://dust.reev.us and archives of the results starting from 2012 are available upon request.

  19. 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

  20. 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.

  1. 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.

  2. Seven phases of gait detected in real-time using shank attached gyroscopes.

    PubMed

    Behboodi, A; Wright, H; Zahradka, N; Lee, S C K

    2015-08-01

    A new gyroscope-based gait phase detection system (GPDS) with ability to detect all seven phases of gait was proposed in this study. Gyroscopes were attached to each shank. Shank angular velocity, about the medio-lateral axis, was streamed to a PC and a rule-based algorithm was used to identify characteristics of the signals. Five subjects were asked to walk on treadmill at their self-selected speed while using this system. All 7 phases of gait: LR, MSt, TSt, PSw, ISw, MSw, and TSw were detected in real-time using only shank angular velocities. To quantify system performance, sensor data was compared to simultaneously collected motion capture data. Average gait phase detection delays of the system were less than 40ms except TSw (74ms). The present system, consisting of minimal sensors and decreased processing, is precise, cosmetic, economical, and a good alternative for portable stand-alone applications. PMID:26737544

  3. Seven phases of gait detected in real-time using shank attached gyroscopes.

    PubMed

    Behboodi, A; Wright, H; Zahradka, N; Lee, S C K

    2015-08-01

    A new gyroscope-based gait phase detection system (GPDS) with ability to detect all seven phases of gait was proposed in this study. Gyroscopes were attached to each shank. Shank angular velocity, about the medio-lateral axis, was streamed to a PC and a rule-based algorithm was used to identify characteristics of the signals. Five subjects were asked to walk on treadmill at their self-selected speed while using this system. All 7 phases of gait: LR, MSt, TSt, PSw, ISw, MSw, and TSw were detected in real-time using only shank angular velocities. To quantify system performance, sensor data was compared to simultaneously collected motion capture data. Average gait phase detection delays of the system were less than 40ms except TSw (74ms). The present system, consisting of minimal sensors and decreased processing, is precise, cosmetic, economical, and a good alternative for portable stand-alone applications.

  4. Detection of peanut (Arachis hypogaea) allergen by Real-time PCR method with internal amplification control.

    PubMed

    Zhang, Wen-Ju; Cai, Qin; Guan, Xiao; Chen, Qin

    2015-05-01

    Specific primer sets were designed based on the DNA sequence of Ara h 1, one of the major peanut (Arachis hypogaea) allergens, and a competitive internal amplification control (IAC) was designed by compound primer technology. By choosing 314 copies/PCR as the IAC dosage, a Real-time PCR method with IAC was established for detecting peanut allergen Ara h 1 DNA. The method showed high specificity with a detection limit of 0.005% peanut. A series of commercial food products with/without peanut components were tested. Among these products, the peanut allergen Ara h 1 DNA could be detected in 12 products labelled containing peanut ingredients, in two without a declaration of peanut and one labelled that was produced in a facility that produced peanut-containing foods. This indicates that the method is highly sensitive for the detection of peanut ingredients in foods.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Adaptive method for real-time gait phase detection based on ground contact forces.

    PubMed

    Yu, Lie; Zheng, Jianbin; Wang, Yang; Song, Zhengge; Zhan, Enqi

    2015-01-01

    A novel method is presented to detect real-time gait phases based on ground contact forces (GCFs) measured by force sensitive resistors (FSRs). The traditional threshold method (TM) sets a threshold to divide the GCFs into on-ground and off-ground statuses. However, TM is neither an adaptive nor real-time method. The threshold setting is based on body weight or the maximum and minimum GCFs in the gait cycles, resulting in different thresholds needed for different walking conditions. Additionally, the maximum and minimum GCFs are only obtainable after data processing. Therefore, this paper proposes a proportion method (PM) that calculates the sums and proportions of GCFs wherein the GCFs are obtained from FSRs. A gait analysis is then implemented by the proposed gait phase detection algorithm (GPDA). Finally, the PM reliability is determined by comparing the detection results between PM and TM. Experimental results demonstrate that the proposed PM is highly reliable in all walking conditions. In addition, PM could be utilized to analyze gait phases in real time. Finally, PM exhibits strong adaptability to different walking conditions.

  12. Real-time PCR with internal amplification control for detecting tuberculosis: method design and validation.

    PubMed

    Flores, E; Rodríguez, J C; Garcia-Pachón, E; Soto, J L; Ruiz, M; Escribano, I; Royo, G

    2009-08-01

    Real-time PCR has been a major development in the diagnosis of tuberculosis. However, most tests do not include an internal amplification control (IAC), which therefore limits it clinical application. In this study a new, easy to perform real-time PCR test with IAC was designed and validated in clinical samples. The primers amplified a 163-bp fragment of IS6110 of Mycobacterium tuberculosis and the IAC was designed with a fragment of a different microorganism (Chlamydia trachomatis). The interassay and intraassay variation of this test were very low (0.45-1.65% and 0.18-1.80%, respectively). The detection accuracy was validated in 50 samples (25 urine, 25 sputum) with different concentrations of M. tuberculosis, 18 clinical isolates of non-tuberculous mycobacteria and 148 samples with clinical suspicion of pulmonary tuberculosis. The specificity was 100%. The detection limit of this PCR test without IAC was approximately 15 bacteria and with IAC approximately 32 bacteria. This real-time PCR with IAC assay can improve the detection of M. tuberculosis and contribute to standardization of this diagnostic technique.

  13. A real-time method for autonomous passive acoustic detection-classification of humpback whales.

    PubMed

    Abbot, Ted A; Premus, Vincent E; Abbot, Philip A

    2010-05-01

    This paper describes a method for real-time, autonomous, joint detection-classification of humpback whale vocalizations. The approach adapts the spectrogram correlation method used by Mellinger and Clark [J. Acoust. Soc. Am. 107, 3518-3529 (2000)] for bowhead whale endnote detection to the humpback whale problem. The objective is the implementation of a system to determine the presence or absence of humpback whales with passive acoustic methods and to perform this classification with low false alarm rate in real time. Multiple correlation kernels are used due to the diversity of humpback song. The approach also takes advantage of the fact that humpbacks tend to vocalize repeatedly for extended periods of time, and identification is declared only when multiple song units are detected within a fixed time interval. Humpback whale vocalizations from A