Science.gov

Sample records for real event detection

  1. Real-time gait event detection for normal subjects from lower trunk accelerations.

    PubMed

    González, Rafael C; López, Antonio M; Rodriguez-Uría, Javier; Alvarez, Diego; Alvarez, Juan C

    2010-03-01

    In this paper we report on a novel algorithm for the real-time detection and timing of initial (IC) and final contact (FC) gait events. We process the vertical and antero-posterior accelerations registered at the lower trunk (L3 vertebra). The algorithm is based on a set of heuristic rules extracted from a set of 1719 steps. An independent experiment was conducted to compare the results of our algorithms with those obtained from a Digimax force platform. The results show small deviations from times of occurrence of events recorded from the platform (13+/-35 ms for IC and 9+/-54 ms for FC). Results for the FC timing are especially relevant in this field, as no previous work has addressed its temporal location through the processing of lower trunk accelerations. The delay in the real-time detection of the IC is 117+/-39 ms and 34+/-72 ms for the FC, improving previously reported results for real-time detection of events from lower trunk accelerations.

  2. Real-time gait event detection for lower limb amputees using a single wearable sensor.

    PubMed

    Maqbool, H F; Husman, M A B; Awad, M I; Abouhossein, A; Mehryar, P; Iqbal, N; Dehghani-Sanij, A A

    2016-08-01

    This paper presents a rule-based real-time gait event/phase detection system (R-GEDS) using a shank mounted inertial measurement unit (IMU) for lower limb amputees during the level ground walking. Development of the algorithm is based on the shank angular velocity in the sagittal plane and linear acceleration signal in the shank longitudinal direction. System performance was evaluated with four control subjects (CS) and one transfemoral amputee (TFA) and the results were validated with four FlexiForce footswitches (FSW). The results showed a data latency for initial contact (IC) and toe off (TO) within a range of ± 40 ms for both CS and TFA. A delay of about 3.7 ± 62 ms for a foot-flat start (FFS) and an early detection of -9.4 ± 66 ms for heel-off (HO) was found for CS. Prosthetic side showed an early detection of -105 ± 95 ms for FFS whereas intact side showed a delay of 141 ±73 ms for HO. The difference in the kinematics of the TFA and CS is one of the potential reasons for high variations in the time difference. Overall, detection accuracy was 99.78% for all the events in both groups. Based on the validated results, the proposed system can be used to accurately detect the temporal gait events in real-time that leads to the detection of gait phase system and therefore, can be utilized in gait analysis applications and the control of lower limb prostheses.

  3. Visual and Real-Time Event-Specific Loop-Mediated Isothermal Amplification Based Detection Assays for Bt Cotton Events MON531 and MON15985.

    PubMed

    Randhawa, Gurinder Jit; Chhabra, Rashmi; Bhoge, Rajesh K; Singh, Monika

    2015-01-01

    Bt cotton events MON531 and MON15985 are authorized for commercial cultivation in more than 18 countries. In India, four Bt cotton events have been commercialized; more than 95% of total area under genetically modified (GM) cotton cultivation comprises events MON531 and MON15985. The present study reports on the development of efficient event-specific visual and real-time loop-mediated isothermal amplification (LAMP) assays for detection and identification of cotton events MON531 and MON15985. Efficiency of LAMP assays was compared with conventional and real-time PCR assays. Real-time LAMP assay was found time-efficient and most sensitive, detecting up to two target copies within 35 min. The developed real-time LAMP assays, when combined with efficient DNA extraction kit/protocol, may facilitate onsite GM detection to check authenticity of Bt cotton seeds.

  4. Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm

    PubMed Central

    Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

    2016-01-01

    Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses. PMID:27706086

  5. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    DOEpatents

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

    2016-04-19

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

  8. 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.

  9. Decaplex and real-time PCR based detection of MON531 and MON15985 Bt cotton events.

    PubMed

    Randhawa, Gurinder Jit; Chhabra, Rashmi; Singh, Monika

    2010-09-22

    The genetically modified (GM) Bt crops expressing delta-endotoxins from Bacillus thuringiensis provide protection against a wide range of lepidopteron insect pests throughout the growing season of the plant. Bt cotton is the only commercialized crop in India that is planted on an area of 7.6 million hectares. With the increase in development and commercialization of transgenic crops, it is necessary to develop appropriate qualitative and quantitative methods for detection of different transgenic events. The present study reports on the development of a decaplex polymerase chain reaction (PCR) assay for simultaneous detection of transgene sequences, specific transgene constructs, and endogenous stearoyl acyl desaturase (Sad1) gene in two events of Bt cotton, i.e., MON531 and MON15985. The decaplex PCR assay is an efficient tool to identify and discriminate the two major commercialized events of Bt cotton, i.e., MON531 and MON15985, in India. Real-time PCR assays were also developed for quantification of cry1Ac and cry2Ab genes being employed in these two events. The quantitative method was developed using seven serial dilutions containing different levels of Bt cotton DNA mixed with a non-Bt counterpart ranging from 0.01 to 100%. The results revealed that the biases from the true value and the relative standard deviations were all within the range of ±20%. The limit of quantification (LOQ) of the developed real-time PCR method has also been established up to 0.01%.

  10. Near Real-Time Event Detection & Prediction Using Intelligent Software Agents

    DTIC Science & Technology

    2006-03-01

    recognition. While domain-specific methodologies have garnered varying success levels, a general approach for this complex task has yet to be found...robust event pattern recognition. While domain-specific methodologies have garnered varying success levels, a general approach for this complex...task has yet to be found and therefore motivates this research effort. The overall research goal is to develop, test, and validate a robust generic

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-05-01

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

  13. Interlaboratory validation study of an event-specific real-time polymerase chain reaction detection method for genetically modified 55-1 papaya.

    PubMed

    Noguchi, Akio; Nakamura, Kosuke; Sakata, Kozue; Kobayashi, Tomoko; Akiyama, Hiroshi; Kondo, Kazunari; Teshima, Reiko; Ohmori, Kiyomi; Kasahara, Masaki; Takabatake, Reona; Kitta, Kazumi

    2013-01-01

    Genetically modified (GM) papaya line 55-1 (55-1) is resistant to papaya ringspot virus infection, and is commercially available in several countries. A specific detection method for 55-1 is required for mandatory labeling regulations. An event-specific real-time PCR method was developed by our laboratory. To validate the method, interlaboratory validation of event-specific qualitative real-time PCR analysis for 55-1 was performed in collaboration with 12 laboratories. DNA extraction and real-time PCR reaction methods were evaluated using 12 blind samples: six non-GM papayas and six GM papayas in each laboratory. Genomic DNA was highly purified from all papayas using an ion-exchange column, and the resulting DNA sample was analyzed using real-time PCR. Papaya endogenous reference gene chymopapain (CHY) and the event-specific 55-1 targeted sequence were detected in GM papayas whereas CHYalone was detected in non-GM papayas in all laboratories. The cycle threshold values of CHYand the 55-1 targeted sequence showed high repeatability (RSD, 0.6-0.8%) and reproducibility (RSDR 2.2-3.6%). This study demonstrates that the 55-1 real-time PCR detection method is a useful and reliable method to monitor 55-1 papaya in foods.

  14. Real-time detection of organic contamination events in water distribution systems by principal components analysis of ultraviolet spectral data.

    PubMed

    Zhang, Jian; Hou, Dibo; Wang, Ke; Huang, Pingjie; Zhang, Guangxin; Loáiciga, Hugo

    2017-04-01

    The detection of organic contaminants in water distribution systems is essential to protect public health from potential harmful compounds resulting from accidental spills or intentional releases. Existing methods for detecting organic contaminants are based on quantitative analyses such as chemical testing and gas/liquid chromatography, which are time- and reagent-consuming and involve costly maintenance. This study proposes a novel procedure based on discrete wavelet transform and principal component analysis for detecting organic contamination events from ultraviolet spectral data. Firstly, the spectrum of each observation is transformed using discrete wavelet with a coiflet mother wavelet to capture the abrupt change along the wavelength. Principal component analysis is then employed to approximate the spectra based on capture and fusion features. The significant value of Hotelling's T(2) statistics is calculated and used to detect outliers. An alarm of contamination event is triggered by sequential Bayesian analysis when the outliers appear continuously in several observations. The effectiveness of the proposed procedure is tested on-line using a pilot-scale setup and experimental data.

  15. Event-Driven Collaboration through Publish/Subscribe Messaging Services for Near-Real- Time Environmental Sensor Anomaly Detection and Management

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Downey, S.; Minsker, B.; Myers, J. D.; Wentling, T.; Marini, L.

    2006-12-01

    One of the challenges in designing cyberinfrastructure for national environmental observatories is how to provide integrated cyberenvironment which not only provides a standardized pipeline for streaming data from sensors into the observatory for archiving and distribution, but also makes raw data and identified events available in real-time for use in individual and group research efforts. This aspect of observatories is critical for promoting efficient collaboration and innovation among scientists and engineers and enabling observatories to serve as a focus that directly supports the broad community. The National Center for Supercomputing Applications' Environmental Cyberinfrastructure Demo (ECID) project has adopted an event-driven architecture and developed a CyberCollaboratory to facilitate event-driven, near-real-time collaboration and management of sensors and workflows for bringing data from environmental observatories into local research contexts. The CyberCollaboratory's event broker uses publish-subscribe service powered by JMS (Java Messaging Service) with semantics-enhanced messages using RDF (Resource Description Framework) triples to allow exchange of contextual information about the event between the event generators and the event consumers. Non-scheduled, event-driven collaboration effectively reduces the barrier to collaboration for scientists and engineers and promotes much faster turn-around time for critical environmental events. This is especially useful for real-time adaptive monitoring and modeling of sensor data in environmental observatories. In this presentation, we illustrate our system using a sensor anomaly detection event as an example where near-real- time data streams from field sensor in Corpus Christi Bay, Texas, trigger monitoring/anomaly alerts in the CyberCollaboratory's CyberDashboard and collaborative activities in the CyberCollaboratory. The CyberDashboard is a Java application where users can monitor various events

  16. 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

  17. 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

  18. Detection of anomalous events

    DOEpatents

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

    2016-06-07

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

  19. 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

    2006-09-06

    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).

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-07-01

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

  6. 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.

  7. Acoustic Event Detection and Classification

    NASA Astrophysics Data System (ADS)

    Temko, Andrey; Nadeu, Climent; Macho, Dušan; Malkin, Robert; Zieger, Christian; Omologo, Maurizio

    The human activity that takes place in meeting rooms or classrooms is reflected in a rich variety of acoustic events (AE), produced either by the human body or by objects handled by humans, so the determination of both the identity of sounds and their position in time may help to detect and describe that human activity. Indeed, speech is usually the most informative sound, but other kinds of AEs may also carry useful information, for example, clapping or laughing inside a speech, a strong yawn in the middle of a lecture, a chair moving or a door slam when the meeting has just started. Additionally, detection and classification of sounds other than speech may be useful to enhance the robustness of speech technologies like automatic speech recognition.

  8. Detectability of Discrete Event Systems with Dynamic Event Observation

    PubMed Central

    Shu, Shaolong; Lin, Feng

    2009-01-01

    Our previous work considers detectability of discrete event systems which is to determine the current state and subsequent states of a system based on event observation. We assume that event observation is static, that is, if an event is observable, then all its occurrences are observable. However, in practical systems such as sensor networks, event observation often needs to be dynamic, that is, the occurrences of same events may or may not be observable, depending on the state of the system. In this paper, we generalize static event observation into dynamic event observation and consider the detectability problem under dynamic event observation. We define four types of detectabilities. To check detectabilities, we construct the observer with exponential complexity. To reduce computational complexity, we can also construct a detector with polynomial complexity to check strong detectabilities. Dynamic event observation can be implemented in two possible ways: a passive observation and an active observation. For the active observation, we discuss how to find minimal event observation policies that preserve four types of detectabilities respectively. PMID:20161618

  9. Memory characteristics of recently imagined events and real events experienced previously.

    PubMed

    Stern, E R; Rotello, C M

    2000-01-01

    In two experiments, we evaluated the memory characteristics of real and imagined events as they changed over time. Memories of real events were richer than memories of imagined events, and memories of recent events were richer than of events from a week earlier. These differences interacted such that memories of real events performed in week 1 were very similar to memories of events that were imagined in week 2. Source monitoring was tested and implications for the repressed or recovered memory debate are considered.

  10. Phase-Space Detection of Cyber Events

    SciTech Connect

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

    2015-01-01

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

  11. 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.

  12. A Framework of Simple Event Detection in Surveillance Video

    NASA Astrophysics Data System (ADS)

    Xu, Weiguang; Zhang, Yafei; Lu, Jianjiang; Tian, Yulong; Wang, Jiabao

    Video surveillance is playing more and more important role in people's social life. Real-time alerting of threaten events and searching interesting content in stored large scale video footage needs human operator to pay full attention on monitor for long time. The labor intensive mode has limit the effectiveness and efficiency of the system. A framework of simple event detection is presented advance the automation of video surveillance. An improved inner key point matching approach is used to compensate motion of background in real-time; frame difference are used to detect foreground; HOG based classifiers are used to classify foreground object into people and car; mean-shift is used to tracking the recognized objects. Events are detected based on predefined rules. The maturity of the algorithms guarantee the robustness of the framework, and the improved approach and the easily checked rules enable the framework to work in real-time. Future works to be done are also discussed.

  13. 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…

  14. 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.

  15. A new real-time tsunami detection algorithm

    NASA Astrophysics Data System (ADS)

    Chierici, Francesco; Embriaco, Davide; Pignagnoli, Luca

    2017-01-01

    Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection based on the real-time tide removal and real-time band-pass filtering of seabed pressure recordings. The algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability with respect to the most widely used tsunami detection algorithm, while containing the computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. Pressure data sets acquired by Bottom Pressure Recorders in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event which occurred at Haida Gwaii on 28 October 2012 using data recorded by the Bullseye underwater node of Ocean Networks Canada. The algorithm successfully ran for test purpose in year-long missions onboard abyssal observatories, deployed in the Gulf of Cadiz and in the Western Ionian Sea.

  16. Generalized Detectability for Discrete Event Systems

    PubMed Central

    Shu, Shaolong; Lin, Feng

    2011-01-01

    In our previous work, we investigated detectability of discrete event systems, which is defined as the ability to determine the current and subsequent states of a system based on observation. For different applications, we defined four types of detectabilities: (weak) detectability, strong detectability, (weak) periodic detectability, and strong periodic detectability. In this paper, we extend our results in three aspects. (1) We extend detectability from deterministic systems to nondeterministic systems. Such a generalization is necessary because there are many systems that need to be modeled as nondeterministic discrete event systems. (2) We develop polynomial algorithms to check strong detectability. The previous algorithms are based on observer whose construction is of exponential complexity, while the new algorithms are based on a new automaton called detector. (3) We extend detectability to D-detectability. While detectability requires determining the exact state of a system, D-detectability relaxes this requirement by asking only to distinguish certain pairs of states. With these extensions, the theory on detectability of discrete event systems becomes more applicable in solving many practical problems. PMID:21691432

  17. Detecting unitary events without discretization of time.

    PubMed

    Grün, S; Diesmann, M; Grammont, F; Riehle, A; Aertsen, A

    1999-12-15

    In earlier studies we developed the 'Unitary Events' analysis (Grün S. Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance and Interpretation. Reihe Physik, Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.) to detect the presence of conspicuous spike coincidences in multiple single unit recordings and to evaluate their statistical significance. The method enabled us to study the relation between spike synchronization and behavioral events (Riehle A, Grün S, Diesmann M, Aertsen A. Spike synchronization and rate modulation differentially involved in motor cortical function. Science 1997;278:1950-1953.). There is recent experimental evidence that the timing accuracy of coincident spiking events, which might be relevant for higher brain function, may be in the range of 1-5 ms. To detect coincidences on that time scale, we sectioned the observation interval into short disjunct time slices ('bins'). Unitary Events analysis of this discretized process demonstrated that coincident events can indeed be reliably detected. However, the method looses sensitivity for higher temporal jitter of the events constituting the coincidences (Grün S. Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection, Significance and Interpretation. Reihe Physik, Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.). Here we present a new approach, the 'multiple shift' method (MS), which overcomes the need for binning and treats the data in their (original) high time resolution (typically 1 ms, or better). Technically, coincidences are detected by shifting the spike trains against each other over the range of allowed coincidence width and integrating the number of exact coincidences (on the time resolution of the data) over all shifts. We found that the new method enhances the sensitivity for coincidences with temporal jitter. Both methods are outlined and compared on the basis of their analytical description and their application on

  18. 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.

  19. Detection of goal events in soccer videos

    NASA Astrophysics Data System (ADS)

    Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

    2004-12-01

    In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

  20. Detection of goal events in soccer videos

    NASA Astrophysics Data System (ADS)

    Kim, Hyoung-Gook; Roeber, Steffen; Samour, Amjad; Sikora, Thomas

    2005-01-01

    In this paper, we present an automatic extraction of goal events in soccer videos by using audio track features alone without relying on expensive-to-compute video track features. The extracted goal events can be used for high-level indexing and selective browsing of soccer videos. The detection of soccer video highlights using audio contents comprises three steps: 1) extraction of audio features from a video sequence, 2) event candidate detection of highlight events based on the information provided by the feature extraction Methods and the Hidden Markov Model (HMM), 3) goal event selection to finally determine the video intervals to be included in the summary. For this purpose we compared the performance of the well known Mel-scale Frequency Cepstral Coefficients (MFCC) feature extraction method vs. MPEG-7 Audio Spectrum Projection feature (ASP) extraction method based on three different decomposition methods namely Principal Component Analysis( PCA), Independent Component Analysis (ICA) and Non-Negative Matrix Factorization (NMF). To evaluate our system we collected five soccer game videos from various sources. In total we have seven hours of soccer games consisting of eight gigabytes of data. One of five soccer games is used as the training data (e.g., announcers' excited speech, audience ambient speech noise, audience clapping, environmental sounds). Our goal event detection results are encouraging.

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

    PubMed

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

    2014-01-01

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

  2. 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.

  3. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

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

  4. Bi-Level Semantic Representation Analysis for Multimedia Event Detection.

    PubMed

    Chang, Xiaojun; Ma, Zhigang; Yang, Yi; Zeng, Zhiqiang; Hauptmann, Alexander G

    2016-03-28

    Multimedia event detection has been one of the major endeavors in video event analysis. A variety of approaches have been proposed recently to tackle this problem. Among others, using semantic representation has been accredited for its promising performance and desirable ability for human-understandable reasoning. To generate semantic representation, we usually utilize several external image/video archives and apply the concept detectors trained on them to the event videos. Due to the intrinsic difference of these archives, the resulted representation is presumable to have different predicting capabilities for a certain event. Notwithstanding, not much work is available for assessing the efficacy of semantic representation from the source-level. On the other hand, it is plausible to perceive that some concepts are noisy for detecting a specific event. Motivated by these two shortcomings, we propose a bi-level semantic representation analyzing method. Regarding source-level, our method learns weights of semantic representation attained from different multimedia archives. Meanwhile, it restrains the negative influence of noisy or irrelevant concepts in the overall concept-level. In addition, we particularly focus on efficient multimedia event detection with few positive examples, which is highly appreciated in the real-world scenario. We perform extensive experiments on the challenging TRECVID MED 2013 and 2014 datasets with encouraging results that validate the efficacy of our proposed approach.

  5. 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…

  6. 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.

  7. Detection and recognition of indoor smoking events

    NASA Astrophysics Data System (ADS)

    Bien, Tse-Lun; Lin, Chang Hong

    2013-03-01

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

  8. Optimizing master event templates for CTBT monitoring with dimensionality reduction techniques: real waveforms vs. synthetics.

    NASA Astrophysics Data System (ADS)

    Rozhkov, Mikhail; Bobrov, Dmitry; Kitov, Ivan

    2014-05-01

    The Master Event technique is a powerful tool for Expert Technical Analysis within the CTBT framework as well as for real-time monitoring with the waveform cross-correlation (CC) (match filter) approach. The primary goal of CTBT monitoring is detection and location of nuclear explosions. Therefore, the cross-correlation monitoring should be focused on finding such events. The use of physically adequate waveform templates may significantly increase the number of valid, both natural and manmade, events in the Reviewed Event Bulletin (REB) of the International Data Centre. Inadequate templates for master events may increase the number of CTBT irrelevant events in REB and reduce the sensitivity of the CC technique to valid events. In order to cover the entire earth, including vast aseismic territories, with the CC based nuclear test monitoring we conducted a thorough research and defined the most appropriate real and synthetic master events representing underground explosion sources. A procedure was developed on optimizing the master event template simulation and narrowing the classes of CC templates used in detection and location process based on principal and independent component analysis (PCA and ICA). Actual waveforms and metadata from the DTRA Verification Database were used to validate our approach. The detection and location results based on real and synthetic master events were compared. The prototype of CC-based Global Grid monitoring system developed in IDC during last year was populated with different hybrid waveform templates (synthetics, synthetics components, and real components) and its performance was assessed with the world seismicity data flow, including the DPRK-2013 event. The specific features revealed in this study for the P-waves from the DPRK underground nuclear explosions (UNEs) can reduce the global detection threshold of seismic monitoring under the CTBT by 0.5 units of magnitude. This corresponds to the reduction in the test yield by a

  9. 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.

  10. Facing a real person: an event-related potential study.

    PubMed

    Pönkänen, Laura M; Hietanen, Jari K; Peltola, Mikko J; Kauppinen, Pasi K; Haapalainen, Antti; Leppänen, Jukka M

    2008-03-05

    Although faces are typically perceived in the context of human interaction, face processing is commonly studied by displaying faces on a computer screen. This study on event-related potential examined whether the processing of faces differs depending on whether participants are viewing faces live or on a computer screen. In both the conditions, the participants were shown a real face, a dummy face, and a control object. N170 and early posterior negativity discriminated between faces and control object in both the conditions. Interestingly, early posterior negativity differentiated between the real face and the dummy face only in the live condition. The results indicate that a live face, as a potentially interacting stimulus, is processed differently than an inanimate face already at the early processing stages.

  11. Application of Kalman Filtering Techniques for Microseismic Event Detection

    NASA Astrophysics Data System (ADS)

    Baziw, E.; Weir-Jones, I.

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

  12. WCEDS: A waveform correlation event detection system

    SciTech Connect

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

    1995-08-01

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

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

    DOE PAGES

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; ...

    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

  14. 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.

  15. Integrating event detection system operation characteristics into sensor placement optimization.

    SciTech Connect

    Hart, William Eugene; McKenna, Sean Andrew; Phillips, Cynthia Ann; Murray, Regan Elizabeth; Hart, David Blaine

    2010-05-01

    We consider the problem of placing sensors in a municipal water network when we can choose both the location of sensors and the sensitivity and specificity of the contamination warning system. Sensor stations in a municipal water distribution network continuously send sensor output information to a centralized computing facility, and event detection systems at the control center determine when to signal an anomaly worthy of response. Although most sensor placement research has assumed perfect anomaly detection, signal analysis software has parameters that control the tradeoff between false alarms and false negatives. We describe a nonlinear sensor placement formulation, which we heuristically optimize with a linear approximation that can be solved as a mixed-integer linear program. We report the results of initial experiments on a real network and discuss tradeoffs between early detection of contamination incidents, and control of false alarms.

  16. Machine learning for real time remote detection

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

  17. Near Real Time Ship Detection Experiments

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  18. 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.

  19. Near-real-time attribution of extreme weather events

    NASA Astrophysics Data System (ADS)

    Allen, M. R.; Pall, P.; Stone, D.; Stott, P.; Lohmann, D.

    2007-12-01

    As the impacts of global climate change become increasingly evident, there is growing demand for a quantitative and objective answer the the question of what is "to blame" for observed extreme weather phenomena. In addition to considerable public interest, understanding how external drivers, particularly secular trends such as anthropogenic greenhouse gas forcing, is important for the correct quantification of current weather-related risks for the insurance industry. We propose a method of quantifying the contribution of external drivers to weather-related risks based on a twinned ensemble design. Under this approach, a large ensemble of simulations with a forecast-resolution atmospheric model is driven with observed sea surface temperatures and atmospheric composition over the period of interest. A second ensemble is then generated with the influence of a particular external agent, such as anthropogenic greenhouse gases, removed through modification of composition and surface temperatures. Conventional detection and attribution techniques are used to allow for uncertainty in the magnitude and pattern of the signal removed. The frequency of occurrence of the weather event in question can then be compared between the two ensembles. For the exploration of changing risks of the most extreme events, very large ensembles (thousands of members, unprecedented for a model of this resolution) are needed, requiring a novel distributed computing approach, relying on computing resources donated by the general public: see http://attribution.cpdn.org. We focus as an example on the events of Autumn 2000 which brought widespread flooding to many regions of the UK. Precipitation from the twin ensembles is used to force an empirical run-off model to provide an estimate of its contribution to flood risk. Results are summarized in the form of an estimated fraction attributable risk for the anthropogenic contribution to the flooding events of that year.

  20. Real-time detection of optical transients with RAPTOR

    SciTech Connect

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

    2002-01-01

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

  1. Multitarget real-time PCR-based system: monitoring for unauthorized genetically modified events in India.

    PubMed

    Randhawa, Gurinder Jit; Singh, Monika; Sood, Payal; Bhoge, Rajesh K

    2014-07-23

    A multitarget TaqMan real-time PCR (RTi-PCR) based system was developed to monitor unauthorized genetically modified (GM) events in India. Most of the GM events included in this study are either authorized for commercial cultivation or field trials, which were indigenously developed or imported for research purposes. The developed system consists of a 96-well prespotted plate with lyophilized primers and probes, for simultaneous detection of 47 targets in duplicate, including 21 event-specific sequences, 5 construct regions, 15 for transgenic elements, and 6 taxon-specific targets for cotton, eggplant, maize, potato, rice, and soybean. Limit of detection (LOD) of assays ranged from 0.1 to 0.01% GM content for different targets. Applicability, robustness, and practical utility of the developed system were verified with stacked GM cotton event, powdered samples of proficiency testing and two unknown test samples. This user-friendly multitarget approach can be efficiently utilized for monitoring the unauthorized GM events in an Indian context.

  2. 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

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

    PubMed

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

    2015-01-01

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

  4. 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.

  5. 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.

  6. A Unified Framework for Event Summarization and Rare Event Detection from Multiple Views.

    PubMed

    Kwon, Junseok; Lee, Kyoung Mu

    2015-09-01

    A novel approach for event summarization and rare event detection is proposed. Unlike conventional methods that deal with event summarization and rare event detection independently, our method solves them in a single framework by transforming them into a graph editing problem. In our approach, a video is represented by a graph, each node of which indicates an event obtained by segmenting the video spatially and temporally. The edges between nodes describe the relationship between events. Based on the degree of relations, edges have different weights. After learning the graph structure, our method finds subgraphs that represent event summarization and rare events in the video by editing the graph, that is, merging its subgraphs or pruning its edges. The graph is edited to minimize a predefined energy model with the Markov Chain Monte Carlo (MCMC) method. The energy model consists of several parameters that represent the causality, frequency, and significance of events. We design a specific energy model that uses these parameters to satisfy each objective of event summarization and rare event detection. The proposed method is extended to obtain event summarization and rare event detection results across multiple videos captured from multiple views. For this purpose, the proposed method independently learns and edits each graph of individual videos for event summarization or rare event detection. Then, the method matches the extracted multiple graphs to each other, and constructs a single composite graph that represents event summarization or rare events from multiple views. Experimental results show that the proposed approach accurately summarizes multiple videos in a fully unsupervised manner. Moreover, the experiments demonstrate that the approach is advantageous in detecting rare transition of events.

  7. Extensions to Real-time Hierarchical Mine Detection Algorithm

    DTIC Science & Technology

    2002-09-01

    Extensions to Real-Time Hierarchical Mine Detection Algorithm System Number: Patron Number: Requester: Notes: DSIS Use only: Deliver to: DK...Recherche et developpement pour Ia defense Canada Extensions to Real-Time Hierarchical Mine Detection Algorithm Final Report Sinh Duong and Mabo R. Ito...EXTENSIONS TO REAL-TIME HIERARCHICAL MINE DETECTION ALGORITHM FINAL REPORT by Smh Duong and Mabo R Ito The Univer~ity of Bntl~h Columbia Vancouver

  8. Diagnosis of delay-deadline failures in real time discrete event models.

    PubMed

    Biswas, Santosh; Sarkar, Dipankar; Bhowal, Prodip; Mukhopadhyay, Siddhartha

    2007-10-01

    In this paper a method for fault detection and diagnosis (FDD) of real time systems has been developed. A modeling framework termed as real time discrete event system (RTDES) model is presented and a mechanism for FDD of the same has been developed. The use of RTDES framework for FDD is an extension of the works reported in the discrete event system (DES) literature, which are based on finite state machines (FSM). FDD of RTDES models are suited for real time systems because of their capability of representing timing faults leading to failures in terms of erroneous delays and deadlines, which FSM-based ones cannot address. The concept of measurement restriction of variables is introduced for RTDES and the consequent equivalence of states and indistinguishability of transitions have been characterized. Faults are modeled in terms of an unmeasurable condition variable in the state map. Diagnosability is defined and the procedure of constructing a diagnoser is provided. A checkable property of the diagnoser is shown to be a necessary and sufficient condition for diagnosability. The methodology is illustrated with an example of a hydraulic cylinder.

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

    NASA Astrophysics Data System (ADS)

    Pinsky, Vladimir; Shapira, Avi

    2017-01-01

    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.

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

    PubMed

    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.

  11. 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

  12. Robust event detection scheme for complex scenes in video surveillance

    NASA Astrophysics Data System (ADS)

    Chen, Erkang; Xu, Yi; Yang, Xiaokang; Zhang, Wenjun

    2011-07-01

    Event detection for video surveillance is a difficult task due to many challenges: cluttered background, illumination variations, scale variations, occlusions among people, etc. We propose an effective and efficient event detection scheme in such complex situations. Moving shadows due to illumination are tackled with a segmentation method with shadow detection, and scale variations are taken care of using the CamShift guided particle filter tracking algorithm. For event modeling, hidden Markov models are employed. The proposed scheme also reduces the overall computational cost by combing two human detection algorithms and using tracking information to aid human detection. Experimental results on TRECVid event detection evaluation demonstrate the efficacy of the proposed scheme. It is robust, especially to moving shadows and scale variations. Employing the scheme, we achieved the best run results for two events in the TRECVid benchmarking evaluation.

  13. Chapter 8: Spatiotemporal dynamics in bacterial cells: real-time studies with single-event resolution.

    PubMed

    Golding, Ido; Cox, Edward C

    2008-01-01

    To produce a quantitative picture of cellular life, one has to study the processes comprising it in individual living cells, quantifying intracellular dynamics with sufficient resolution to describe individual events in space and time. To perform such studies, we have recently developed a novel measurement approach, based on quantitative fluorescence microscopy, and applied it to the study of transcription in Escherichia coli and of the spatiotemporal dynamics of individual mRNA molecules in the cell (Golding and Cox, 2004, 2006a; Golding et al., 2005). The ability to detect individual events in real time depends on the engineering of an endogenous cellular process for amplifying the biological signal, in a way which allows signal detection to be independent of slow and highly stochastic cellular processes (Golding and Cox, 2006a). In this chapter, we describe the ingredients of our system and the way data is acquired and analyzed. We attempt to give general lessons for researchers who wish to implement a similar approach for the study of transcription in other organisms and, more generally, for the study of cellular processes with single-event resolution.

  14. Detecting plastic events in emulsions simulations

    NASA Astrophysics Data System (ADS)

    Lulli, Matteo; Matteo Lulli, Massimo Bernaschi, Mauro Sbragaglia Team

    2016-11-01

    Emulsions are complex systems which are formed by a number of non-coalescing droplets dispersed in a solvent leading to non-trivial effects in the overall flowing dynamics. Such systems possess a yield stress below which an elastic response to an external forcing occurs, while above the yield stress the system flows as a non-Newtonian fluid, i.e. the stress is not proportional to the shear. In the solid-like regime the network of the droplets interfaces stores the energy coming from the work exerted by an external forcing, which can be used to move the droplets in a non-reversible way, i.e. causing plastic events. The Kinetic-Elasto-Plastic (KEP) theory is an effective theory describing some features of the flowing regime relating the rate of plastic events to a scalar field called fluidity f =γ˙/σ , i.e. the inverse of an effective viscosity. Boundary conditions have a non-trivial role not captured by the KEP description. In this contribution we will compare numerical results against experiments concerning the Poiseuille flow of emulsions in microchannels with complex boundary geometries. Using an efficient computational tool we can show non-trivial results on plastic events for different realizations of the rough boundaries. The research leading to these results has received funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007- 2013)/ERC Grant Agreement no. [279004].

  15. Casi real-time surface-laid mine detection system

    NASA Astrophysics Data System (ADS)

    Ivanco, Tyler; Achal, Stephen B.; McFee, John E.; Anger, Clifford D.

    2001-10-01

    A ground vehicle-based, real-time, surface mine detection system, utilizing a Compact Airborne Spectrographic Image (casi), efficient mine detection algorithms, and real-time processing systems, was designed and tested. The combined real-time system was capable of 'learning' the in-situ spectra of various mines, thus providing a spectral library for the detection algorithms. The real-time processing of the casi data involved three steps. The first step was the radiometric correction of the raw data. The second step involved the application of the mine detection algorithms to the corrected data, referencing the spectral library. In the final step, the results of the real-time processes were stored and displayed, usually within a few frame times of the data acquisition. To the authors knowledge, this system represents the first hyperspectral imager to detect mines in real-time. This paper describes the generation of the in-situ mine spectral library, the collection of the scene data, the real-time processing of the scene data and the subsequent display and recording of the detection data. The limitation and expansion capabilities of the real-time system are discussed as well as various techniques that were implemented to achieve the goals. Planned future improvements that have been identified to create a more robust and higher performance, yet simpler processing systems are also discussed.

  16. 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

  17. 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.

  18. Saliency-based abnormal event detection in crowded scenes

    NASA Astrophysics Data System (ADS)

    Shi, Yanjiao; Liu, Yunxiang; Zhang, Qing; Yi, Yugen; Li, Wenju

    2016-11-01

    Abnormal event detection plays a critical role for intelligent video surveillance, and detection in crowded scenes is a challenging but more practical task. We present an abnormal event detection method for crowded video. Region-wise modeling is proposed to address the inconsistent detected motion of the same object due to different depths of field. Comparing to traditional block-wise modeling, the region-wise method not only can reduce heavily the number of models to be built but also can enrich the samples for training the normal events model. In order to reduce the computational burden and make the region-based anomaly detection feasible, a saliency detection technique is adopted in this paper. By identifying the salient parts of the image sequences, the irrelevant blocks are ignored, which removes the disturbance and improves the detection performance further. Experiments on the benchmark dataset and comparisons with the state-of-the-art algorithms validate the advantages of the proposed method.

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

    NASA Astrophysics Data System (ADS)

    Tan, Yumei; Luo, Xiaoshu; Xia, Haiying

    2013-10-01

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

  20. Facial landmark detection in real-time with correlation filtering

    NASA Astrophysics Data System (ADS)

    Contreras, Viridiana; Díaz-Ramírez, Víctor H.

    2016-09-01

    An algorithm for facial landmark detection based on template matched filtering is presented. The algorithm is able to detect and estimate the position of a set of prespecified landmarks by employing a bank of linear filters. Each filter in the bank is trained to detect a single landmark that is located in a small region of the input face image. The filter bank is implemented in parallel on a graphics processing unit to perform facial landmark detection in real-time. Computer simulation results obtained with the proposed algorithm are presented and discussed in terms of detection rate, accuracy of landmark location estimation, and real-time efficiency.

  1. 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

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

    PubMed

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

    2016-04-15

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

  3. Detection and Real Time Spectroscopy of Charged Particles with the TimePix Pixel Detector

    NASA Astrophysics Data System (ADS)

    Granja, Carlos; Jakubek, Jan; Platkevic, Michal; Pospisil, Stanislav; Vykydal, Zdenek

    2010-01-01

    We tested the position—, spectral— and time—resolution capability of the TimePix semiconductor detector together with the USB readout interface and Pixelman control and DAQ software tool for detection and visualization of particles. Event—by—event spectroscopy can be achieved by real time analysis of the characteristic tracks and specific response of different radiation in the pixel detector.

  4. 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.

  5. 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.

  6. An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data.

    PubMed

    Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

    2016-01-01

    This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems.

  7. An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

    PubMed Central

    Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

    2015-01-01

    This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

  8. 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…

  9. 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.

  10. 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.

  11. 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.

  12. 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'.

  13. 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.

  14. Service oriented architecture to support real-time implementation of artifact detection in critical care monitoring.

    PubMed

    Nizami, Shermeen; Green, James Robert; McGregor, Carolyn

    2011-01-01

    The quality of automated real-time critical care monitoring is impacted by the degree of signal artifact present in clinical data. This is further complicated when different clinical rules applied for disease detection require source data at different frequencies and different signal quality. This paper proposes a novel multidimensional framework based on service oriented architecture to support real-time implementation of clinical artifact detection in critical care settings. The framework is instantiated through a Neonatal Intensive Care case study which assesses signal quality of physiological data streams prior to detection of late-onset neonatal sepsis. In this case study requirements and provisions of artifact and clinical event detection are determined for real-time clinical implementation, which forms the second important contribution of this paper.

  15. 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

  16. 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.

  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. 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.

  19. 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.

  20. 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.

  1. Abnormal events detection in crowded scenes by trajectory cluster

    NASA Astrophysics Data System (ADS)

    Zhou, Shifu; Zhang, Zhijiang; Zeng, Dan; Shen, Wei

    2015-02-01

    Abnormal events detection in crowded scenes has been a challenge due to volatility of the definitions for both normality and abnormality, the small number of pixels on the target, appearance ambiguity resulting from the dense packing, and severe inter-object occlusions. A novel framework was proposed for the detection of unusual events in crowded scenes using trajectories produced by moving pedestrians based on an intuition that the motion patterns of usual behaviors are similar to these of group activity, whereas unusual behaviors are not. First, spectral clustering is used to group trajectories with similar spatial patterns. Different trajectory clusters represent different activities. Then, unusual trajectories can be detected using these patterns. Furthermore, behavior of a mobile pedestrian can be defined by comparing its direction with these patterns, such as moving in the opposite direction of the group or traversing the group. Experimental results indicated that the proposed algorithm could be used to reliably locate the abnormal events in crowded scenes.

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

    PubMed

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

    2013-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

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

    PubMed Central

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

    2011-01-01

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

  8. 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

  9. Planning in the real world: preschool children's scripts and plans for familiar events.

    PubMed

    Hudson, J A; Shapiro, L R; Sosa, B B

    1995-08-01

    3-, 4-, and 5-year-olds reported either scripts or verbal plans for 2 familiar events, going grocery shopping and going to the beach, and also constructed plans to remedy and prevent mishaps that might occur for each event. With increasing age, children reported more information, focused more on onset activities, and mentioned more specific planning activities in their plans than in their scripts. Although children at all ages provided adequate remedy plans, only 5-year-olds provided adequate prevention plans. In general, children were better at planning for the beach than for grocery shopping. Results indicate that developmental differences in event knowledge, in the ability to reflect upon event knowledge, and the event that they are planning for affect preschoolers' planning for real-world events.

  10. November 2004 space weather events: Real-time observations and forecasts

    NASA Astrophysics Data System (ADS)

    Trichtchenko, L.; Zhukov, A.; van der Linden, R.; Stankov, S. M.; Jakowski, N.; StanisłAwska, I.; Juchnikowski, G.; Wilkinson, P.; Patterson, G.; Thomson, A. W. P.

    2007-06-01

    Space weather events with their solar origin and their distribution through the heliosphere affect the whole magnetosphere-ionosphere-Earth system. Their real-time monitoring and forecasting are important for science and technology. Here we discuss one of the largest space weather events of Solar Cycle 23, in November 2004, which was also one of the most difficult periods to forecast. Nine halo coronal mass ejections (CMEs), interacting on their way through the interplanetary medium and forming two geoeffective interplanetary structures, exemplify the complexity of the event. Real-time and quasi-real-time observations of the ground geomagnetic field show rapid and extensive expansion of the auroral oval to 55° in geomagnetic latitude accompanied by great variability of the ionosphere. Geomagnetically induced currents (GICs) seen in ground networks, such as power grids and pipelines, were significant during the event, although no problems were reported. Forecasts of the CME propagation, global and local ground geomagnetic activity, and ionospheric parameters, issued by several regional warning centers, revealed certain deficiencies in predictions of the interplanetary characteristics of the CME, size of the geomagnetic disturbances, and complexity of the ionospheric variations produced by this event. This paper is a collective report based on the materials presented at the splinter session on November 2004 events during the first European Space Weather Week.

  11. Automatic microseismic event detection by band-limited phase-only correlation

    NASA Astrophysics Data System (ADS)

    Wu, Shaojiang; Wang, Yibo; Zhan, Yi; Chang, Xu

    2016-12-01

    Identification and detection of microseismic events is a significant issue in source locations and source mechanism analysis. The number of the records is notably large, especially in the case of some real-time monitoring, and while the majority of microseismic events are highly weak and sparse, automatic algorithms are indispensable. In this study, we introduce an effective method for the identification and detection of microseismic events by judging whether the P-wave phase exists in a local segment from a single three-component microseismic records. The new judging algorithm consists primarily of the following key steps: 1) transform the waveform time series into time-varying spectral representations using the S-transform; 2) calculate the similarity of the frequency content in the time-frequency domain using the phase-only correlation function; and 3) identify the P-phase by the combination analysis between any two components. The proposed algorithm is compared to a similar approach using the cross-correlation in the time domain between any two components and later tested with synthetic microseismic datasets and real field-recorded datasets. The results indicate that the proposed algorithm is able to distinguish similar and dissimilar waveforms, even for low signal noise ratio and emergent events, which is important for accurate and rapid selection of microseismic events from a large number of records. This method can be applied to other geophysical analyses based on the waveform data.

  12. 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) ...

  13. 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.

  14. 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.

  15. Discrete-event requirements model for sensor fusion to provide real-time diagnostic feedback

    NASA Astrophysics Data System (ADS)

    Rokonuzzaman, Mohd; Gosine, Raymond G.

    1998-06-01

    Minimally-invasive surgical techniques reduce the size of the access corridor and affected zones resulting in limited real-time perceptual information available to the practitioners. A real-time feedback system is required to offset deficiencies in perceptual information. This feedback system acquires data from multiple sensors and fuses these data to extract pertinent information within defined time windows. To perform this task, a set of computing components interact with each other resulting in a discrete event dynamic system. In this work, a new discrete event requirements model for sensor fusion has been proposed to ensure logical and temporal correctness of the operation of the real-time diagnostic feedback system. This proposed scheme models system requirements as a Petri net based discrete event dynamic machine. The graphical representation and quantitative analysis of this model has been developed. Having a natural graphical property, this Petri net based model enables the requirements engineer to communicate intuitively with the client to avoid faults in the early phase of the development process. The quantitative analysis helps justify the logical and temporal correctness of the operation of the system. It has been shown that this model can be analyzed to check the presence of deadlock, reachability, and repetitiveness of the operation of the sensor fusion system. This proposed novel technique to model the requirements of sensor fusion as a discrete event dynamic system has the potential to realize highly reliable real-time diagnostic feedback system for many applications, such as minimally invasive instrumentation.

  16. Aseismic events in Southern California: Detection with InSAR

    NASA Astrophysics Data System (ADS)

    Lohman, R. B.; McGuire, J. J.; Lundgren, P.

    2007-05-01

    Aseismic slow slip events are usually studied using data types that have a dense temporal sampling rate, such as continuous GPS or tremor analysis using seismic data. However, even the sparser temporal coverage of InSAR data can further our understanding of these events in three significant ways - First, in areas where aseismic transients have been detected on geodetic arrays, InSAR may be able to provide a spatially denser image of the extent and magnitude of deformation. Second, InSAR observations are complementary to GPS because of the differing sensitivities to horizontal and vertical motions. Thirdly, in areas with no ground-based geodetic instrumentation, InSAR can be used in survey mode to detect deformation signals that are not associated with any observed seismicity. The temporal constraints on such signals may not be tight enough to allow for dynamics models of how aseismic transients occur, but InSAR-only detections can improve our understanding of the spatial extent of these types of events and can also identify key areas for future instrumentation and observation. Here, I summarize some of the contributions of InSAR observations of slow slip events, including data spanning the 2005 Obsidian Buttes swam in the Salton Trough, CA, and InSAR time-series results for the Salton Trough using both traditional interferometry and the persistent scatterer method.

  17. 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.

  18. Near real time detection of hazardous airborne substances.

    PubMed

    Leppert, J; Horner, G; Rietz, F; Ringer, J; Schulze Lammers, P; Boeker, P

    2012-11-15

    A fast near real-time monitoring system for hazardous airborne substances, such as chemical warfare agents (CWA) is presented and limits of detection (LOD) for five CW simulants are determined. A tandem thermal desorber (TTD) continuously collects and pre-concentrates air. The pre-concentrated samples are then separated in a fast gas chromatographic (GC) run of 6.9min. and detected by a time-of-flight mass spectrometer (TOFMS). The GC-TOFMS signals are evaluated using chemometric methods for deconvolution and target identification. The high toxicity of nerve agents requires extremely low detection limits; for some as low as 100 ng/m(3) (10 ppt). The combination of TTD, TOFMS and chemometric data evaluation methods enables the system to fulfill this requirement. Calibration measurements for five different CWA simulants show lower limits of detection in the range of 10 ng/m(3)-60 ng/m(3) (1-11 ppt). In addition, the ability to detect trace concentrations of real CWA is demonstrated with a measurement of 30 pg Sarin on column. Several other real CWA measurements are shown, like sulfur mustard in diesel, lewisite under humid conditions and VX. As part of this work the influence of stationary film thickness on peak tailing of organophosphates is investigated for peak shape optimization.

  19. 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.

  20. 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.

  1. 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

  2. Real-time system for road following and obstacle detection

    NASA Astrophysics Data System (ADS)

    Denasi, Sandra; Lanzone, Claudio; Martinese, Paolo; Pettiti, Giuseppe; Quaglia, Giorgio; Viglione, Luca

    1994-10-01

    Path planning of a vehicle running in a structured environment requires road boundaries evaluation for mapping its position and reducing the search area for obstacle detection. This paper describes a real time system that has been developed in the framework of the EUREKA PROMETHEUS European project and is presently under test on a Mobile Laboratory (MOBLAB). The road boundaries are detected by highlighting the large homogeneous region that lies in the bottom of the image, in front of the vehicle. Edge detection, local thresholding and morphological filtering techniques are used to define this region. Its boundaries are tracked in the sequence, relying on hypotheses of continuity of color and shape of the road to overcome drawbacks due to shadows, intersections, hidden boundaries. The proposed technique has been implemented on an integrated system based on a real time imaging processor and a workstation.

  3. A methodology for detecting routing events in discrete flow networks.

    SciTech Connect

    Garcia, H. E.; Yoo, T.; Nuclear Technology

    2004-01-01

    A theoretical framework for formulating and implementing model-based monitoring of discrete flow networks is discussed. Possible flows of items are described as the sequence of discrete-event (DE) traces. Each trace defines the DE sequence(s) that are triggered when an entity follows a given flow-path and visits tracking locations distributed within the monitored system. Given the set of possible discrete flows, a possible-behavior model - an interacting set of automata - is constructed, where each automaton models the discrete flow of items at each tracking location. Event labels or symbols contain all the information required to unambiguously distinguish each discrete flow. Within the possible behavior, there is a special sub-behavior whose occurrence is required to be detected. The special behavior may be specified by the occurrence of routing events, such as faults. These intermittent or non-persistent events may occur repeatedly. An observation mask is then defined, characterizing the actual observation configuration available for collecting item tracking data. The analysis task is then to determine whether this observation configuration is capable of detecting the identified special behavior. The assessment is accomplished by evaluating several observability notions, such as detectability and diagnosability. If the corresponding property is satisfied, associated formal observers are constructed to perform the monitoring task at hand. The synthesis of an optimal observation mask may also be conducted to suggest an appropriate observation configuration guaranteeing the detection of the special events and to construct associated monitoring agents. The proposed framework, modeling methodology, and supporting techniques for discrete flow networks monitoring are presented and illustrated with an example.

  4. 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

  5. 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.

  6. 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.

  7. C4: a real-time object detection framework.

    PubMed

    Wu, Jianxin; Liu, Nini; Geyer, Christopher; Rehg, James M

    2013-10-01

    A real-time and accurate object detection framework, C(4), is proposed in this paper. C(4) achieves 20 fps speed and the state-of-the-art detection accuracy, using only one processing thread without resorting to special hardware such as GPU. The real-time accurate object detection is made possible by two contributions. First, we conjecture (with supporting experiments) that contour is what we should capture and signs of comparisons among neighboring pixels are the key information to capture contour cues. Second, we show that the CENTRIST visual descriptor is suitable for contour based object detection, because it encodes the sign information and can implicitly represent the global contour. When CENTRIST and linear classifier are used, we propose a computational method that does not need to explicitly generate feature vectors. It involves no image preprocessing or feature vector normalization, and only requires O(1) steps to test an image patch. C(4) is also friendly to further hardware acceleration. It has been applied to detect objects such as pedestrians, faces, and cars on benchmark data sets. It has comparable detection accuracy with state-of-the-art methods, and has a clear advantage in detection speed.

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

    PubMed

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

    2010-11-15

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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. Detecting modification of biomedical events using a deep parsing approach

    PubMed Central

    2012-01-01

    Background This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. analysis of IkappaBalpha phosphorylation, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. inhibition of IkappaBalpha phosphorylation, where phosphorylation did not occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser. Method To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the RASP parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm. Results Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features. Conclusions Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification. PMID:22595089

  15. 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.

  16. 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.

  17. A microarray scanner for the real-time quantitative detection

    NASA Astrophysics Data System (ADS)

    Liu, Quanjun; Zhuang, Ying; Wu, Lingwei; Wu, Zhongwei; Hu, Song; Lu, Zuhong

    2007-05-01

    The real-time and quantitative detection assay is important for the gene detection. With the TaqMan probes for the detection based polymerase chain reaction (PCR), four targets could be checked in a single process in solution assay. A new method is developed to immobilize the TaqMan probes on a microarray, which could be used to the multi-target gene fragment quantitative detection with PCR. A new type microarray scanner is designed for the assay. A thermocycler system was built into the scanner platform. A new type of the vessel sealed with the gene amplification solution which could perform the thermo-cycling and scanning. To decrease the background intensity a confocal system was used as the fluorescent intensity detection in the scanner. To calculate the gene quantity, a standard liner graph was draw with the fluorescent intensity versus the cycles. From the standard liner, the quantity of the original gene fragment could be calculated in time with the cycles. This scanner offers the great advantage of real-time quantitative detection of DNA targets in a microarray.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  19. 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

  20. 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.

  1. Real-time EEG-based happiness detection system.

    PubMed

    Jatupaiboon, Noppadon; Pan-ngum, Setha; Israsena, Pasin

    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.

  2. 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.

  3. Microcontroller-based real-time QRS detection.

    PubMed

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

    1992-01-01

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

  4. A new approach to measure single-event related brain activity using real-time fMRI: feasibility of sensory, motor, and higher cognitive tasks.

    PubMed

    Posse, S; Binkofski, F; Schneider, F; Gembris, D; Frings, W; Habel, U; Salloum, J B; Mathiak, K; Wiese, S; Kiselev, V; Graf, T; Elghahwagi, B; Grosse-Ruyken, M L; Eickermann, T

    2001-01-01

    Real-time fMRI is a rapidly emerging methodology that enables monitoring changes in brain activity during an ongoing experiment. In this article we demonstrate the feasibility of performing single-event sensory, motor, and higher cognitive tasks in real-time on a clinical whole-body scanner. This approach requires sensitivity optimized fMRI methods: Using statistical parametric mapping we quantified the spatial extent of BOLD contrast signal changes as a function of voxel size and demonstrate that sacrificing spatial resolution and readout bandwidth improves the detection of signal changes in real time. Further increases in BOLD contrast sensitivity were obtained by using real-time multi-echo EPI. Real-time image analysis was performed using our previously described Functional Imaging in REal time (FIRE) software package, which features real-time motion compensation, sliding window correlation analysis, and automatic reference vector optimization. This new fMRI methodology was validated using single-block design paradigms of standard visual, motor, and auditory tasks. Further, we demonstrate the sensitivity of this method for online detection of higher cognitive functions during a language task using single-block design paradigms. Finally, we used single-event fMRI to characterize the variability of the hemodynamic impulse response in primary and supplementary motor cortex in consecutive trials using single movements. Real-time fMRI can improve reliability of clinical and research studies and offers new opportunities for studying higher cognitive functions.

  5. 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.

  6. 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.

  7. Detection of red tide events in the Ariake Sound, Japan

    NASA Astrophysics Data System (ADS)

    Ishizaka, Joji

    2003-05-01

    High resolution SeaWiFS data was used to detect a red tide event occurred in the Ariake Sound, Japan, in winter of 2000 to 2001. The area is small embayment surrounding by tidal flat, and it is known as one of the most productive areas in coast of Japan. The red tide event damaged to seaweed (Nori) culture, and the relation to the reclamation at the Isahaya Bay in the Sound has been discussed. SeaWiFS chlorophyll data showed the red tide started early December 2000, from the Isahaya Bay, although direct relationship to the reclamation was not clear. The red tide persisted to the end of February. Monthly average of SeaWiFS data from May 1998 to December 2001 indicated that the chlorophyll increased twice a year, early summer and fall after the rain. The red tide event was part of the fall bloom which started later and continued longer than other years. Ocean color is useful to detect the red tide; however, it is required to improve the algorithms to accurately estimate chlorophyll in high turbid water and to discriminate toxic flagellates.

  8. Miniaturized holographic imaging system for real-time cellular detection

    NASA Astrophysics Data System (ADS)

    Song, Jun; Im, Hyungsoon; Liong, Monty; Fexon, Lioubov; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho

    2013-03-01

    We herein present a miniaturized holographic imaging system for high throughput cellular detection. The system consists of an imager chip with a microfluidic channel built on top. Clinical samples (e.g., blood) are introduced into the fluidic channel, and holographic images of cells are recorded by the imager chip. We then perform computational reconstruction of original cell images, retrieving both the intensity and phase information. For fast image reconstruction, we have implemented parallel computing software and utilized multicore GPU (graphics processing unit) chips. The resulting imaging system enabled high throughput cellular detection; up to 1000 cells/ μL could be imaged over a wide detection area (20 mm2), and cellular images could be reconstructed in real time (20 frames/sec). Furthermore, assays can be performed without extra dilution and washing steps, which significantly simplifies the diagnosis process. This cost-effective, real-time holographic imaging system can be used for target cell detection in point-of-care applications.

  9. High Probabilities of Planet Detection during Microlensing Events.

    NASA Astrophysics Data System (ADS)

    Peale, S. J.

    2000-10-01

    The averaged probability of detecting a planetary companion of a lensing star during a gravitational microlensing event toward the Galactic center when the planet-lens mass ratio is 0.001 is shown to have a maximum exceeding 20% for a distribution of source-lens impact parameters that is determined by the efficiency of event detection, and a maximum exceeding 10% for a uniform distribution of impact parameters. The probability varies as the square root of the planet-lens mass ratio. A planet is assumed detectable if the perturbation of the light curve exceeds 2/(S/N) for a significant number of data points, where S/N is the signal-to noise ratio for the photometry of the source. The probability peaks at a planetary semimajor axis a that is close to the mean Einstein ring radius of the lenses of about 2 AU along the line of sight, and remains significant for 0.6<= a<= 10 AU. The low value of the mean Einstein ring radius results from the dominance of M stars in the mass function of the lenses. The probability is averaged over the distribution of the projected position of the planet onto the lens plane, over the lens mass function, over the distribution of impact parameters, over the distribution of lens along the line of sight to the source star, over the I band luminosity function of the sources adjusted for the source distance, and over the source distribution along the line of sight. If two or more parameters of the lensing event are known, such as the I magnitude of the source and the impact parameter, the averages over these parameters can be omitted and the probability of detection determined for a particular event. The calculated probabilities behave as expected with variations in the line of sight, the mass function of the lenses, the extinction and distance to and magnitude of the source, and with a more demanding detection criterion. The relatively high values of the probabilities are robust to plausible variations in the assumptions. The high

  10. 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.

  11. Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

    NASA Astrophysics Data System (ADS)

    Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

    2016-12-01

    Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  17. 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.

  18. Data mining to generate adverse drug events detection rules.

    PubMed

    Chazard, Emmanuel; Ficheur, Grégoire; Bernonville, Stéphanie; Luyckx, Michel; Beuscart, Régis

    2011-11-01

    Adverse drug events (ADEs) are a public health issue. Their detection usually relies on voluntary reporting or medical chart reviews. The objective of this paper is to automatically detect cases of ADEs by data mining. 115,447 complete past hospital stays are extracted from six French, Danish, and Bulgarian hospitals using a common data model including diagnoses, drug administrations, laboratory results, and free-text records. Different kinds of outcomes are traced, and supervised rule induction methods (decision trees and association rules) are used to discover ADE detection rules, with respect to time constraints. The rules are then filtered, validated, and reorganized by a committee of experts. The rules are described in a rule repository, and several statistics are automatically computed in every medical department, such as the confidence, relative risk, and median delay of outcome appearance. 236 validated ADE-detection rules are discovered; they enable to detect 27 different kinds of outcomes. The rules use a various number of conditions related to laboratory results, diseases, drug administration, and demographics. Some rules involve innovative conditions, such as drug discontinuations.

  19. Microfluidic Arrayed Lab-On-A-Chip for Electrochemical Capacitive Detection of DNA Hybridization Events.

    PubMed

    Ben-Yoav, Hadar; Dykstra, Peter H; Bentley, William E; Ghodssi, Reza

    2017-01-01

    A microfluidic electrochemical lab-on-a-chip (LOC) device for DNA hybridization detection has been developed. The device comprises a 3 × 3 array of microelectrodes integrated with a dual layer microfluidic valved manipulation system that provides controlled and automated capabilities for high throughput analysis of microliter volume samples. The surface of the microelectrodes is functionalized with single-stranded DNA (ssDNA) probes which enable specific detection of complementary ssDNA targets. These targets are detected by a capacitive technique which measures dielectric variation at the microelectrode-electrolyte interface due to DNA hybridization events. A quantitative analysis of the hybridization events is carried out based on a sensing modeling that includes detailed analysis of energy storage and dissipation components. By calculating these components during hybridization events the device is able to demonstrate specific and dose response sensing characteristics. The developed microfluidic LOC for DNA hybridization detection offers a technology for real-time and label-free assessment of genetic markers outside of laboratory settings, such as at the point-of-care or in-field environmental monitoring.

  20. Use of sonification in the detection of anomalous events

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

  1. Real-Time Walk Light Detection with a Mobile Phone.

    PubMed

    Ivanchenko, Volodymyr; Coughlan, James; Shen, Huiying

    2010-07-01

    Crossing an urban traffic intersection is one of the most dangerous activities of a blind or visually impaired person's travel. Building on past work by the authors on the issue of proper alignment with the crosswalk, this paper addresses the complementary issue of knowing when it is time to cross. We describe a prototype portable system that alerts the user in real time once the Walk light is illuminated. The system runs as a software application on an off-the-shelf Nokia N95 mobile phone, using computer vision algorithms to analyze video acquired by the built-in camera to determine in real time if a Walk light is currently visible. Once a Walk light is detected, an audio tone is sounded to alert the user. Experiments with a blind volunteer subject at urban traffic intersections demonstrate proof of concept of the system, which successfully alerted the subject when the Walk light appeared.

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

    PubMed

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

    2012-01-01

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

  3. Two Neurocognitive Mechanisms of Semantic Integration during the Comprehension of Visual Real-world Events

    PubMed Central

    Sitnikova, Tatiana; Holcomb, Phillip J.; Kiyonaga, Kristi A.; Kuperberg, Gina R.

    2009-01-01

    How do comprehenders build up overall meaning representations of visual real-world events? This question was examined by recording event-related potentials (ERPs) while participants viewed short, silent movie clips depicting everyday events. In two experiments, it was demonstrated that presentation of the contextually inappropriate information in the movie endings evoked an anterior negativity. This effect was similar to the N400 component whose amplitude has been previously reported to inversely correlate with the strength of semantic relationship between the context and the eliciting stimulus in word and static picture paradigms. However, a second, somewhat later, ERP component—a posterior late positivity—was evoked specifically when target objects presented in the movie endings violated goal-related requirements of the action constrained by the scenario context (e.g., an electric iron that does not have a sharp-enough edge was used in place of a knife in a cutting bread scenario context). These findings suggest that comprehension of the visual real world might be mediated by two neurophysiologically distinct semantic integration mechanisms. The first mechanism, reflected by the anterior N400-like negativity, maps the incoming information onto the connections of various strengths between concepts in semantic memory. The second mechanism, reflected by the posterior late positivity, evaluates the incoming information against the discrete requirements of real-world actions. We suggest that there may be a tradeoff between these mechanisms in their utility for integrating across people, objects, and actions during event comprehension, in which the first mechanism is better suited for familiar situations, and the second mechanism is better suited for novel situations. PMID:18416681

  4. 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

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

    PubMed

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

    2003-08-15

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

  6. Detectability of GW150914-like events by gravitational microlensing

    NASA Astrophysics Data System (ADS)

    Eilbott, Daniel; Riley, Alexander; Cohn, Jonathan; Kesden, Michael H.; King, Lindsay J.

    2017-01-01

    The recent discovery of gravitational waves from stellar-mass binary black holes (BBHs) provided direct evidence of the existence of these systems. These BBHs would have gravitational microlensing signatures that are, due to their large masses and small separations, distinct from single-lens signals. We apply Bayesian statistics to examine the distinguishability of BBH microlensing events from single-lens events under ideal observing conditions, using modern photometric and astrometric capabilities. Given one year of ideal observations, a source star at the Galactic center, a GW150914-like BBH lens (total mass 65 M⊙, mass ratio 0.8) at half that distance, and an impact parameter of 0.4 Einstein radii, we find that BBH separations down to 0.00634 Einstein radii are detectable, which is < 0.00716 Einstein radii, the limit at which the BBH would merge within the age of the universe. We encourage analyses of LSST data to search for similar modulation in all long-duration events, providing a new channel for the discovery of short-period BBHs in our Galaxy.

  7. Bio-inspired WSN architecture: event detection and loacalization in a fault tolerant WSN

    NASA Astrophysics Data System (ADS)

    Alayev, Yosef; Damarla, Thyagaraju

    2009-05-01

    One can think of human body as a sensory network. In particular, skin has several neurons that provide the sense of touch with different sensitivities, and neurons for communicating the sensory signals to the brain. Even though skin might occasionally experience some lacerations, it performs remarkably well (fault tolerant) with the failure of some sensors. One of the challenges in collaborative wireless sensor networks (WSN) is fault tolerant detection and localization of targets. In this paper we present a biologically inspired architecture model for WSN. Diagnosis of sensors in WSN model presented here is derived from the concept of the immune system. We present an architecture for WSN for detection and localization of multiple targets inspired by human nervous system. We show that the advantages of such bio-inspired networks are reduced data for communication, self-diagnosis to detect faulty sensors in real-time and the ability to localize events. We present the results of our algorithms on simulation data.

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

    PubMed

    Jacobs, Kevin T; Schultz, Zachary D

    2015-08-18

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

  9. Real time electrocardiogram QRS detection using combined adaptive threshold

    PubMed Central

    Christov, Ivaylo I

    2004-01-01

    Background QRS and ventricular beat detection is a basic procedure for electrocardiogram (ECG) processing and analysis. Large variety of methods have been proposed and used, featuring high percentages of correct detection. Nevertheless, the problem remains open especially with respect to higher detection accuracy in noisy ECGs Methods A real-time detection method is proposed, based on comparison between absolute values of summed differentiated electrocardiograms of one of more ECG leads and adaptive threshold. The threshold combines three parameters: an adaptive slew-rate value, a second value which rises when high-frequency noise occurs, and a third one intended to avoid missing of low amplitude beats. Two algorithms were developed: Algorithm 1 detects at the current beat and Algorithm 2 has an RR interval analysis component in addition. The algorithms are self-adjusting to the thresholds and weighting constants, regardless of resolution and sampling frequency used. They operate with any number L of ECG leads, self-synchronize to QRS or beat slopes and adapt to beat-to-beat intervals. Results The algorithms were tested by an independent expert, thus excluding possible author's influence, using all 48 full-length ECG records of the MIT-BIH arrhythmia database. The results were: sensitivity Se = 99.69 % and specificity Sp = 99.65 % for Algorithm 1 and Se = 99.74 % and Sp = 99.65 % for Algorithm 2. Conclusion The statistical indices are higher than, or comparable to those, cited in the scientific literature. PMID:15333132

  10. 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.

  11. 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.

  12. Detection measures in real-life criminal guilty knowledge tests.

    PubMed

    Elaad, E; Ginton, A; Jungman, N

    1992-10-01

    The present study provides a first attempt to compare the validity of the respiration line length (RLL) and skin resistance response (SRR) amplitude in real-life criminal guilty knowledge tests (GKTs). GKT records of 40 innocent and 40 guilty Ss, for whom actual truth was established by confession, were assessed for their accuracy. When a predefined decision rule was used and inconclusive decisions were excluded, 97.4% of the innocent Ss and 53.3% of the guilty Ss were correctly classified with the SRR measure. For the RLL measure, the respective results were 97.2% and 53.1%. The combination of both measures improved detection of guilty Ss to 75.8% and decreased detection of innocent Ss to 94.1%. The combined measure seems to be a more useful means of identifying guilty suspects than each physiological measure alone. The results elaborate and extend those obtained in a previous field study conducted by Elaad (1990).

  13. 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.

  14. Change and Anomaly Detection in Real-Time GPS Data

    NASA Astrophysics Data System (ADS)

    Granat, R.; Pierce, M.; Gao, X.; Bock, Y.

    2008-12-01

    The California Real-Time Network (CRTN) is currently generating real-time GPS position data at a rate of 1-2Hz at over 80 locations. The CRTN data presents the possibility of studying dynamical solid earth processes in a way that complements existing seismic networks. To realize this possibility we have developed a prototype system for detecting changes and anomalies in the real-time data. Through this system, we can can correlate changes in multiple stations in order to detect signals with geographical extent. Our approach involves developing a statistical model for each GPS station in the network, and then using those models to segment the time series into a number of discrete states described by the model. We use a hidden Markov model (HMM) to describe the behavior of each station; fitting the model to the data requires neither labeled training examples nor a priori information about the system. As such, HMMs are well suited to this problem domain, in which the data remains largely uncharacterized. There are two main components to our approach. The first is the model fitting algorithm, regularized deterministic annealing expectation- maximization (RDAEM), which provides robust, high-quality results. The second is a web service infrastructure that connects the data to the statistical modeling analysis and allows us to easily present the results of that analysis through a web portal interface. This web service approach facilitates the automatic updating of station models to keep pace with dynamical changes in the data. Our web portal interface is critical to the process of interpreting the data. A Google Maps interface allows users to visually interpret state changes not only on individual stations but across the entire network. Users can drill down from the map interface to inspect detailed results for individual stations, download the time series data, and inspect fitted models. Alternatively, users can use the web portal look at the evolution of changes on the

  15. 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.

  16. 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.

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

    PubMed

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

    2014-03-01

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

  18. 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.

  19. 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.

  20. 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.

  1. 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

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

    NASA Astrophysics Data System (ADS)

    Gallego, Cristóbal; Cuerva, Álvaro; Costa, Alexandre

    2014-12-01

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

  3. 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.

  4. Seismic Event Identification Using Scanning Detection: A Comparison of Denoising and Classification Methods

    NASA Astrophysics Data System (ADS)

    Rowe, C. A.; MacCarthy, J. K.; Giudicepietro, F.

    2005-12-01

    Automatic detection and classification methods are increasingly important in observatory operations, as the volume and rate of incoming data exceed the capacity of human analysis staff to process the data in near-real-time. We explore the success of scanning detection for similar event identification in a variety of seismic waveform catalogs. Several waveform pre-processing methods are applied to previously recorded events which are scanned through triggered and continuous waveform catalogs to determine the success and false alarm rate for detections of repeating signals. Pre-processing approaches include adaptive, cross-coherency filtering, adaptive, auto-associative neural network filtering, discrete wavelet package decomposition and linear predictive coding as well as suites of standard bandpass filters. Classification / detection methods for the various pre-processed signals are applied to investigate the robustness of the individual and combined approaches. The classifiers as applied to the processed waveforms include dendrogram-based clustering and neural network classifiers. We will present findings for the various combinations of methods as applied to tectonic earthquakes, mine blasts and volcanic seismicity.

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

    PubMed Central

    2010-01-01

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

  6. Implementation and performance results of neural network for power quality event detection

    NASA Astrophysics Data System (ADS)

    Huang, Weijian; Tian, Wenzhi

    2008-10-01

    A novel method to detect power quality event in distributed power system combing wavelet network with the improved back-propagation algorithm is presented. The paper tries to explain to design complex supported orthogonal wavelets by compactly supported orthogonal real wavelets, and then explore the extraction of disturbance signal to obtain the feature information, and finally propose several novel wavelet combined information to analyze the disturbance signal, superior to real wavelet analysis result. The feature obtained from WT coefficients are inputted into wavelet network for power quality disturbance pattern recognition. The power quality disturbance recognition model is established and the improved back-propagation algorithm is used to fulfill the network parameter initialization. By means of choosing enough samples to train the recognition model, the type of disturbance can be obtained when signal representing fault is inputted to the trained network. The results of simulation analysis show that the complex wavelet transform combined with wavelet network are more sensitive to signal singularity, and found to be significant improvement over current methods in real-time detection.

  7. Real-Time PCR Method for Detection of Zygomycetes ▿

    PubMed Central

    Hata, D. Jane; Buckwalter, Seanne P.; Pritt, Bobbi S.; Roberts, Glenn D.; Wengenack, Nancy L.

    2008-01-01

    Zygomycete infections can be devastating in immunocompromised hosts. Difficulties in the histopathologic differentiation of this class from other filamentous fungi (e.g., Aspergillus spp., Fusarium spp.) may lead to delays in diagnosis and initiation of appropriate treatment, thereby significantly affecting patient outcome. A real-time PCR assay was developed to detect species of the zygomycete genera Absidia, Apophysomyces, Cunninghamella, Mucor, Rhizopus, and Saksenaea in culture and tissue samples. Primers and fluorescence resonance energy transfer hybridization probes were designed to detect a 167-bp conserved region of the multicopy zygomycete cytochrome b gene. A plasmid containing target sequence from Mucor racemosus was constructed as a positive control. The analytical sensitivity of the assay is 10 targets/μl, and a specificity panel consisting of other filamentous fungi, yeasts (Candida spp.), and bacteria demonstrated no cross-reactivity in the assay. The clinical sensitivity and specificity of the assay from culture isolates were 100% (39/39) and 92% (59/64), respectively. Sensitivity and specificity determined using a limited number of fresh tissue specimens were both 100% (2/2). The sensitivity seen with formalin-fixed, paraffin-embedded tissues was 56% (35/62), and the specificity was 100% (19/19). The speed, sensitivity, and specificity of the PCR assay indicate that it is useful for the rapid and accurate detection of zygomycetes. PMID:18480229

  8. A new real time tsunami detection algorithm for bottom pressure measurements in open ocean: characterization and benchmarks

    NASA Astrophysics Data System (ADS)

    Embriaco, D.; Chierici, F.; Pignagnoli, L.

    2009-04-01

    In the last decades the use of the Bottom Pressure Recorder (BPR) in a deep ocean environment for tsunami detection has had a relevant development. A key role for an early warning system based on BPRs is played by the tsunami detection algorithms running in real time on the BPR itself or at installation site. We present a new algorithm for tsunami detection that is based on real time pressure data analysis, consisting in tide removing, spike removing, low pass filtering and linear prediction: the output is then matched against a given pressure threshold allowing the detection of anomalous events. Different configurations of the algorithm, consisting for instance in a real time band pass filtering of the pressure signal in place of linear prediction, are also tested for comparison. The algorithm is designed to be used in an autonomous early warning system, with a finite set of input parameters that can be reconfigured in real time. A realistic benchmark scheme is developed in order to characterize the algorithm features with particular regards to false alarm probability, sensitivity to the amplitude and wavelength of the tsunami and detection earliness. The algorithm behaviour in real operation is numerically estimated performing statistical simulations where a large number of synthetic tsunami waves with various amplitude, period, shape and phase is generated and superimposed to time series of real pressure data recorded in different environmental conditions and locations.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Infrared luminescence for real time ionizing radiation detection

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

    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 Yb3+, 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.

  14. 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.

  15. 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.

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

    PubMed

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

    2005-08-26

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

  17. 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.

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  4. 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.

  5. 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.

  6. 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

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

    PubMed

    Rezvanian, Saba; Lockhart, Thurmon E

    2016-04-02

    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.

  8. 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.

  9. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  11. Early and Real-Time Detection of Seasonal Influenza Onset

    PubMed Central

    Marques-Pita, Manuel

    2017-01-01

    Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases. PMID:28158192

  12. Early and Real-Time Detection of Seasonal Influenza Onset.

    PubMed

    Won, Miguel; Marques-Pita, Manuel; Louro, Carlota; Gonçalves-Sá, Joana

    2017-02-01

    Every year, influenza epidemics affect millions of people and place a strong burden on health care services. A timely knowledge of the onset of the epidemic could allow these services to prepare for the peak. We present a method that can reliably identify and signal the influenza outbreak. By combining official Influenza-Like Illness (ILI) incidence rates, searches for ILI-related terms on Google, and an on-call triage phone service, Saúde 24, we were able to identify the beginning of the flu season in 8 European countries, anticipating current official alerts by several weeks. This work shows that it is possible to detect and consistently anticipate the onset of the flu season, in real-time, regardless of the amplitude of the epidemic, with obvious advantages for health care authorities. We also show that the method is not limited to one country, specific region or language, and that it provides a simple and reliable signal that can be used in early detection of other seasonal diseases.

  13. 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.

  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. 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

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

    SciTech Connect

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

    1996-09-24

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

  17. DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

    PubMed Central

    Lawhern, Vernon; Hairston, W. David; Robbins, Kay

    2013-01-01

    Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration. PMID:23638169

  18. 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

  19. 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.

  20. 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

  1. Adverse drug events and medication errors: detection and classification methods.

    PubMed

    Morimoto, T; Gandhi, T K; Seger, A C; Hsieh, T C; Bates, D W

    2004-08-01

    Investigating the incidence, type, and preventability of adverse drug events (ADEs) and medication errors is crucial to improving the quality of health care delivery. ADEs, potential ADEs, and medication errors can be collected by extraction from practice data, solicitation of incidents from health professionals, and patient surveys. Practice data include charts, laboratory, prescription data, and administrative databases, and can be reviewed manually or screened by computer systems to identify signals. Research nurses, pharmacists, or research assistants review these signals, and those that are likely to represent an ADE or medication error are presented to reviewers who independently categorize them into ADEs, potential ADEs, medication errors, or exclusions. These incidents are also classified according to preventability, ameliorability, disability, severity, stage, and responsible person. These classifications, as well as the initial selection of incidents, have been evaluated for agreement between reviewers and the level of agreement found ranged from satisfactory to excellent (kappa = 0.32-0.98). The method of ADE and medication error detection and classification described is feasible and has good reliability. It can be used in various clinical settings to measure and improve medication safety.

  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. Visual traffic surveillance framework: classification to event detection

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  4. 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.

  5. Real-time measurements of spontaneous breathers and rogue wave events in optical fibre modulation instability

    PubMed Central

    Närhi, Mikko; Wetzel, Benjamin; Billet, Cyril; Toenger, Shanti; Sylvestre, Thibaut; Merolla, Jean-Marc; Morandotti, Roberto; Dias, Frederic; Genty, Goëry; Dudley, John M.

    2016-01-01

    Modulation instability is a fundamental process of nonlinear science, leading to the unstable breakup of a constant amplitude solution of a physical system. There has been particular interest in studying modulation instability in the cubic nonlinear Schrödinger equation, a generic model for a host of nonlinear systems including superfluids, fibre optics, plasmas and Bose–Einstein condensates. Modulation instability is also a significant area of study in the context of understanding the emergence of high amplitude events that satisfy rogue wave statistical criteria. Here, exploiting advances in ultrafast optical metrology, we perform real-time measurements in an optical fibre system of the unstable breakup of a continuous wave field, simultaneously characterizing emergent modulation instability breather pulses and their associated statistics. Our results allow quantitative comparison between experiment, modelling and theory, and are expected to open new perspectives on studies of instability dynamics in physics. PMID:27991513

  6. Real-time measurements of spontaneous breathers and rogue wave events in optical fibre modulation instability

    NASA Astrophysics Data System (ADS)

    Närhi, Mikko; Wetzel, Benjamin; Billet, Cyril; Toenger, Shanti; Sylvestre, Thibaut; Merolla, Jean-Marc; Morandotti, Roberto; Dias, Frederic; Genty, Goëry; Dudley, John M.

    2016-12-01

    Modulation instability is a fundamental process of nonlinear science, leading to the unstable breakup of a constant amplitude solution of a physical system. There has been particular interest in studying modulation instability in the cubic nonlinear Schrödinger equation, a generic model for a host of nonlinear systems including superfluids, fibre optics, plasmas and Bose-Einstein condensates. Modulation instability is also a significant area of study in the context of understanding the emergence of high amplitude events that satisfy rogue wave statistical criteria. Here, exploiting advances in ultrafast optical metrology, we perform real-time measurements in an optical fibre system of the unstable breakup of a continuous wave field, simultaneously characterizing emergent modulation instability breather pulses and their associated statistics. Our results allow quantitative comparison between experiment, modelling and theory, and are expected to open new perspectives on studies of instability dynamics in physics.

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

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  8. Real-time measurements of spontaneous breathers and rogue wave events in optical fibre modulation instability.

    PubMed

    Närhi, Mikko; Wetzel, Benjamin; Billet, Cyril; Toenger, Shanti; Sylvestre, Thibaut; Merolla, Jean-Marc; Morandotti, Roberto; Dias, Frederic; Genty, Goëry; Dudley, John M

    2016-12-19

    Modulation instability is a fundamental process of nonlinear science, leading to the unstable breakup of a constant amplitude solution of a physical system. There has been particular interest in studying modulation instability in the cubic nonlinear Schrödinger equation, a generic model for a host of nonlinear systems including superfluids, fibre optics, plasmas and Bose-Einstein condensates. Modulation instability is also a significant area of study in the context of understanding the emergence of high amplitude events that satisfy rogue wave statistical criteria. Here, exploiting advances in ultrafast optical metrology, we perform real-time measurements in an optical fibre system of the unstable breakup of a continuous wave field, simultaneously characterizing emergent modulation instability breather pulses and their associated statistics. Our results allow quantitative comparison between experiment, modelling and theory, and are expected to open new perspectives on studies of instability dynamics in physics.

  9. A real time QRS detection using delay-coordinate mapping for the microcontroller implementation.

    PubMed

    Lee, Jeong-Whan; Kim, Kyeong-Seop; Lee, Bongsoo; Lee, Byungchae; Lee, Myoung-Ho

    2002-01-01

    In this article, we propose a new algorithm using the characteristics of reconstructed phase portraits by delay-coordinate mapping utilizing lag rotundity for a real-time detection of QRS complexes in ECG signals. In reconstructing phase portrait the mapping parameters, time delay, and mapping dimension play important roles in shaping of portraits drawn in a new dimensional space. Experimentally, the optimal mapping time delay for detection of QRS complexes turned out to be 20 ms. To explore the meaning of this time delay and the proper mapping dimension, we applied a fill factor, mutual information, and autocorrelation function algorithm that were generally used to analyze the chaotic characteristics of sampled signals. From these results, we could find the fact that the performance of our proposed algorithms relied mainly on the geometrical property such as an area of the reconstructed phase portrait. For the real application, we applied our algorithm for designing a small cardiac event recorder. This system was to record patients' ECG and R-R intervals for 1 h to investigate HRV characteristics of the patients who had vasovagal syncope symptom and for the evaluation, we implemented our algorithm in C language and applied to MIT/BIH arrhythmia database of 48 subjects. Our proposed algorithm achieved a 99.58% detection rate of QRS complexes.

  10. Prediction and Characterization of High-Activity Events in Social Media Triggered by Real-World News.

    PubMed

    Kalyanam, Janani; Quezada, Mauricio; Poblete, Barbara; Lanckriet, Gert

    2016-01-01

    On-line social networks publish information on a high volume of real-world events almost instantly, becoming a primary source for breaking news. Some of these real-world events can end up having a very strong impact on on-line social networks. The effect of such events can be analyzed from several perspectives, one of them being the intensity and characteristics of the collective activity that it produces in the social platform. We research 5,234 real-world news events encompassing 43 million messages discussed on the Twitter microblogging service for approximately 1 year. We show empirically that exogenous news events naturally create collective patterns of bursty behavior in combination with long periods of inactivity in the network. This type of behavior agrees with other patterns previously observed in other types of natural collective phenomena, as well as in individual human communications. In addition, we propose a methodology to classify news events according to the different levels of intensity in activity that they produce. In particular, we analyze the most highly active events and observe a consistent and strikingly different collective reaction from users when they are exposed to such events. This reaction is independent of an event's reach and scope. We further observe that extremely high-activity events have characteristics that are quite distinguishable at the beginning stages of their outbreak. This allows us to predict with high precision, the top 8% of events that will have the most impact in the social network by just using the first 5% of the information of an event's lifetime evolution. This strongly implies that high-activity events are naturally prioritized collectively by the social network, engaging users early on, way before they are brought to the mainstream audience.

  11. Getting to know your neighbors: unsupervised learning of topography from real-world, event-based input.

    PubMed

    Boerlin, Martin; Delbruck, Tobi; Eng, Kynan

    2009-01-01

    Biological neural systems must grow their own connections and maintain topological relations between elements that are related to the sensory input surface. Artificial systems have traditionally prewired such maps, but the sensor arrangement is not always known and can be expensive to specify before run time. Here we present a method for learning and updating topographic maps in systems comprising modular, event-based elements. Using an unsupervised neural spike-timing-based learning rule combined with Hebbian learning, our algorithm uses the spatiotemporal coherence of the external world to train its network. It improves on existing algorithms by not assuming a known topography of the target map and includes a novel method for automatically detecting edge elements. We show how, for stimuli that are small relative to the sensor resolution, the temporal learning window parameters can be determined without using any user-specified constants. For stimuli that are larger relative to the sensor resolution, we provide a parameter extraction method that generally outperforms the small-stimulus method but requires one user-specified constant. The algorithm was tested on real data from a 64 x 64-pixel section of an event-based temporal contrast silicon retina and a 360-tile tactile luminous floor. It learned 95.8% of the correct neighborhood relations for the silicon retina within about 400 seconds of real-world input from a driving scene and 98.1% correct for the sensory floor after about 160 minutes of human pedestrian traffic. Residual errors occurred in regions receiving little or ambiguous input, and the learned topological representations were able to update automatically in response to simulated damage. Our algorithm has applications in the design of modular autonomous systems in which the interfaces between components are learned during operation rather than at design time.

  12. Signal detection to identify serious adverse events (neuropsychiatric events) in travelers taking mefloquine for chemoprophylaxis of malaria

    PubMed Central

    Naing, Cho; Aung, Kyan; Ahmed, Syed Imran; Mak, Joon Wah

    2012-01-01

    Background For all medications, there is a trade-off between benefits and potential for harm. It is important for patient safety to detect drug-event combinations and analyze by appropriate statistical methods. Mefloquine is used as chemoprophylaxis for travelers going to regions with known chloroquine-resistant Plasmodium falciparum malaria. As such, there is a concern about serious adverse events associated with mefloquine chemoprophylaxis. The objective of the present study was to assess whether any signal would be detected for the serious adverse events of mefloquine, based on data in clinicoepidemiological studies. Materials and methods We extracted data on adverse events related to mefloquine chemoprophylaxis from the two published datasets. Disproportionality reporting of adverse events such as neuropsychiatric events and other adverse events was presented in the 2 × 2 contingency table. Reporting odds ratio and corresponding 95% confidence interval [CI] data-mining algorithm was applied for the signal detection. The safety signals are considered significant when the ROR estimates and the lower limits of the corresponding 95% CI are ≥2. Results Two datasets addressing adverse events of mefloquine chemoprophylaxis (one from a published article and one from a Cochrane systematic review) were included for analyses. Reporting odds ratio 1.58, 95% CI: 1.49–1.68 based on published data in the selected article, and 1.195, 95% CI: 0.94–1.44 based on data in the selected Cochrane review. Overall, in both datasets, the reporting odds ratio values of lower 95% CI were less than 2. Conclusion Based on available data, findings suggested that signals for serious adverse events pertinent to neuropsychiatric event were not detected for mefloquine. Further studies are needed to substantiate this. PMID:22936859

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

    NASA Astrophysics Data System (ADS)

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

    2002-12-01

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

  14. 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

  15. 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

  16. 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.

  17. Transient Evoked Potential in a Critical Event Detection Task.

    DTIC Science & Technology

    1984-02-01

    Vigilance and Discrimination: A Reassessment," Science, 164:326-328, 1969. 38. Fabiani , Monica and others. "Individual Differences in the von Restorff...implies that events which elicit a P300 are more likely to be remembered than events which do not 2-23 .... . . ... invoke a P300 (15:507-510). Fabiani

  18. Prediction and Characterization of High-Activity Events in Social Media Triggered by Real-World News

    PubMed Central

    Kalyanam, Janani; Quezada, Mauricio; Poblete, Barbara; Lanckriet, Gert

    2016-01-01

    On-line social networks publish information on a high volume of real-world events almost instantly, becoming a primary source for breaking news. Some of these real-world events can end up having a very strong impact on on-line social networks. The effect of such events can be analyzed from several perspectives, one of them being the intensity and characteristics of the collective activity that it produces in the social platform. We research 5,234 real-world news events encompassing 43 million messages discussed on the Twitter microblogging service for approximately 1 year. We show empirically that exogenous news events naturally create collective patterns of bursty behavior in combination with long periods of inactivity in the network. This type of behavior agrees with other patterns previously observed in other types of natural collective phenomena, as well as in individual human communications. In addition, we propose a methodology to classify news events according to the different levels of intensity in activity that they produce. In particular, we analyze the most highly active events and observe a consistent and strikingly different collective reaction from users when they are exposed to such events. This reaction is independent of an event’s reach and scope. We further observe that extremely high-activity events have characteristics that are quite distinguishable at the beginning stages of their outbreak. This allows us to predict with high precision, the top 8% of events that will have the most impact in the social network by just using the first 5% of the information of an event’s lifetime evolution. This strongly implies that high-activity events are naturally prioritized collectively by the social network, engaging users early on, way before they are brought to the mainstream audience. PMID:27992437

  19. wayGoo recommender system: personalized recommendations for events scheduling, based on static and real-time information

    NASA Astrophysics Data System (ADS)

    Thanos, Konstantinos-Georgios; Thomopoulos, Stelios C. A.

    2016-05-01

    wayGoo is a fully functional application whose main functionalities include content geolocation, event scheduling, and indoor navigation. However, significant information about events do not reach users' attention, either because of the size of this information or because some information comes from real - time data sources. The purpose of this work is to facilitate event management operations by prioritizing the presented events, based on users' interests using both, static and real - time data. Through the wayGoo interface, users select conceptual topics that are interesting for them. These topics constitute a browsing behavior vector which is used for learning users' interests implicitly, without being intrusive. Then, the system estimates user preferences and return an events list sorted from the most preferred one to the least. User preferences are modeled via a Naïve Bayesian Network which consists of: a) the `decision' random variable corresponding to users' decision on attending an event, b) the `distance' random variable, modeled by a linear regression that estimates the probability that the distance between a user and each event destination is not discouraging, ` the seat availability' random variable, modeled by a linear regression, which estimates the probability that the seat availability is encouraging d) and the `relevance' random variable, modeled by a clustering - based collaborative filtering, which determines the relevance of each event users' interests. Finally, experimental results show that the proposed system contribute essentially to assisting users in browsing and selecting events to attend.

  20. Detection Method of Three Events to Window and Key Using Light Sensor for Crime Prevention

    NASA Astrophysics Data System (ADS)

    Yamawaki, Akira; Katakami, Takayuki; Kitazono, Yuhki; Serikawa, Seiichi

    The three events to the window and the key occurring when a thief attempts to intrude into the house are detected by the different sensors conventionally. This paper proposes a method detecting the three events by using the simple light-sensor consisting of an infrared LED and a photodiode. In the experiments, the light sensor shows the different tendencies that can detect each event. This fact indicates that our proposal can realize a sensor module more efficiently instead of using different sensors.

  1. Development of a Detection Algorithm for Use with Reflectance-Based, Real-Time Chemical Sensing

    PubMed Central

    Malanoski, Anthony P.; Johnson, Brandy J.; Erickson, Jeffrey S.; Stenger, David A.

    2016-01-01

    Here, we describe our efforts focused on development of an algorithm for identification of detection events in a real-time sensing application relying on reporting of color values using commercially available color sensing chips. The effort focuses on the identification of event occurrence, rather than target identification, and utilizes approaches suitable to onboard device incorporation to facilitate portable and autonomous use. The described algorithm first excludes electronic noise generated by the sensor system and determines response thresholds. This automatic adjustment provides the potential for use with device variations as well as accommodating differing indicator behaviors. Multiple signal channels (RGB) as well as multiple indicator array elements are combined for reporting of an event with a minimum of false responses. While the method reported was developed for use with paper-supported porphyrin and metalloporphyrin indicators, it should be equally applicable to other colorimetric indicators. Depending on device configurations, receiver operating characteristic (ROC) sensitivities of 1 could be obtained with specificities of 0.87 (threshold 160 ppb, ethanol). PMID:27854335

  2. Migration Based Event Detection and Automatic P- and S-Phase Picking in Hengill, Southwest Iceland

    NASA Astrophysics Data System (ADS)

    Wagner, F.; Tryggvason, A.; Gudmundsson, O.; Roberts, R.; Bodvarsson, R.; Fehler, M.

    2015-12-01

    Automatic detection of seismic events is a complicated process. Common procedures depend on the detection of seismic phases (e.g. P and S) in single trace analyses and their correct association with locatable point sources. The event detection threshold is thus directly related to the single trace detection threshold. Highly sensitive phase detectors detect low signal-to-noise ratio (S/N) phases but also produce a low percentage of locatable events. Short inter-event times of only a few seconds, which is not uncommon during seismic or volcanic crises, is a complication to any event association algorithm. We present an event detection algorithm based on seismic migration of trace attributes into an a-priori three-dimensional (3D) velocity model. We evaluate its capacity as automatic detector compared to conventional methods. Detecting events using seismic migration removes the need for phase association. The event detector runs on a stack of time shifted traces, which increases S/N and thus allows for a low detection threshold. Detected events come with an origin time and a location estimate, enabling a focused trace analysis, including P- and S-phase recognition, to discard false detections and build a basis for accurate automatic phase picking. We apply the migration based detection algorithm to data from a semi-permanent seismic network at Hengill, an active volcanic region with several geothermal production sites in southwest Iceland. The network includes 26 stations with inter-station distances down to 5 km. Results show a high success rate compared to the manually picked catalogue (up to 90% detected). New detections, that were missed by the standard detection routine, show a generally good ratio of true to false alarms, i.e. most of the new events are locatable.

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

    PubMed

    Oliker, Nurit; Ostfeld, Avi

    2015-09-01

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

  4. Real-time quantitative PCR detection of genetically modified Maximizer maize and Roundup Ready soybean in some representative foods.

    PubMed

    Vaïtilingom, M; Pijnenburg, H; Gendre, F; Brignon, P

    1999-12-01

    A fast and quantitative method was developed to detect transgenic "Maximizer" maize "event 176" (Novartis) and "Roundup Ready" soybean (Monsanto) in food by real-time quantitative PCR. The use of the ABI Prism 7700 sequence detection system allowed the determination of the amplified product accumulation through a fluorogenic probe (TaqMan). Fluorescent dyes were chosen in such a way as to coamplify total and transgenic DNA in the same tube. Using real-time quantitative PCR, 2 pg of transgenic or total DNA per gram of starting sample was detected in 3 h after DNA extraction and the relative amounts of "Maximizer" maize and "Roundup Ready" soybean in some representative food products were quantified.

  5. Toward real-time particle tracking using an event-based dynamic vision sensor

    NASA Astrophysics Data System (ADS)

    Drazen, David; Lichtsteiner, Patrick; Häfliger, Philipp; Delbrück, Tobi; Jensen, Atle

    2011-11-01

    Optically based measurements in high Reynolds number fluid flows often require high-speed imaging techniques. These cameras typically record data internally and thus are limited by the amount of onboard memory available. A novel camera technology for use in particle tracking velocimetry is presented in this paper. This technology consists of a dynamic vision sensor in which pixels operate in parallel, transmitting asynchronous events only when relative changes in intensity of approximately 10% are encountered with a temporal resolution of 1 μs. This results in a recording system whose data storage and bandwidth requirements are about 100 times smaller than a typical high-speed image sensor. Post-processing times of data collected from this sensor also increase to about 10 times faster than real time. We present a proof-of-concept study comparing this novel sensor with a high-speed CMOS camera capable of recording up to 2,000 fps at 1,024 × 1,024 pixels. Comparisons are made in the ability of each system to track dense (ρ >1 g/cm3) particles in a solid-liquid two-phase pipe flow. Reynolds numbers based on the bulk velocity and pipe diameter up to 100,000 are investigated.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. Detection of severe weather events using new remote sensing methods

    NASA Astrophysics Data System (ADS)

    Choy, S.; Wang, C.; Zhang, K.; Kuleshov, Y.

    2012-04-01

    The potential of using ground- and space-based Global Positioning System (GPS) observations for studying severe weather events is presented using the March 2010 Melbourne storm as a case study. This event generated record rainfall and flash flooding across the state of Victoria, Australia. The Victorian GPSnet is the only state-wide and densest ground-based GPS infrastructure in Australia. This provides a unique opportunity to study the spatial and temporal variations in precipitable water vapour (PWV) as the storm passed over the network. The results show strong spatial and temporal correlation between variations of the ground-based GPS-PWV estimates and the thunderstorm passage. This finding demonstrates that the ground-based GPS techniques can supplement conventional meteorological observations in studying, monitoring, and potentially predicting severe weather events. The advantage of using ground-based GPS technique is that it is capable of providing continuous observation of the storm passage with high temporal resolution; while the spatial resolution of the distribution of water vapour is dependent on the geographical location and density of the GPS stations. The results from the space-based GPS radio occultation (RO) technique, on the other hand, are not as robust. Although GPS RO can capture the dynamics of the atmosphere with high vertical resolution, its limited geographical coverage in a local region and its temporal resolution over a short period of time raise an important question about its potential for monitoring severe weather events, particularly local thunderstorms which have a relatively short life-span. GPS RO technique will be more suitable for long-term climatology studies over a large area. It is anticipated that the findings from this study will encourage further research into using GPS meteorology technique for monitoring and forecasting severe weather events in the Australian region.

  11. 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...

  12. 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.

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

    PubMed

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

    2009-10-01

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

  14. Mark 3 real-time fringe detection system

    NASA Technical Reports Server (NTRS)

    Levine, J. I.; Whitney, A. R.

    1980-01-01

    A RAM memory built into the Mark 3 decoder module allows the capture of 1 Megabit of data. Data may be collected either in real time or from a pre-recorded tape. Once collected, the data may be retrieved using a standard EIA serial data link. The data may be transmitted to a remote computer for cross correlation processing with similar data from other stations to verify fringes in real time. The data may also be analyzed by a local computer to verify phase calibration, bandpass, format, etc., during a Mark 3 observing session.

  15. A Dynamically Configurable Log-based Distributed Security Event Detection Methodology using Simple Event Correlator

    DTIC Science & Technology

    2010-06-01

    from SANS Whitepaper - "... Detecting Attacks on Web Applications from Log Files" #look for image tags type=Single continue=TakeNext ptype=RegExp...shellcmd /home/user/sec -2.5.3/ common/syslogclient "... Synthetic : " "$2|$1|xss detected in image tag: $3" #send the raw log type=Single ptype=RegExp...Expressions taken from SANS Whitepaper - "... Detecting Attacks on Web Applications from Log Files" #look for image tags type=Single continue=TakeNext

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Data-mining-based detection of adverse drug events.

    PubMed

    Chazard, Emmanuel; Preda, Cristian; Merlin, Béatrice; Ficheur, Grégoire; Beuscart, Régis

    2009-01-01

    Every year adverse drug events (ADEs) are known to be responsible for 98,000 deaths in the USA. Classical methods rely on report statements, expert knowledge, and staff operated record review. One of our objectives, in the PSIP project framework, is to use data mining (e.g., decision trees) to electronically identify situations leading to risk of ADEs. 10,500 hospitalization records from Denmark and France were used. 500 rules were automatically obtained, which are currently being validated by experts. A decision support system to prevent ADEs is then to be developed. The article examines a decision tree and the rules in the field of vitamin K antagonists.

  1. Fall detection algorithms for real-world falls harvested from lumbar sensors in the elderly population: a machine learning approach.

    PubMed

    Bourke, Alan K; Klenk, Jochen; Schwickert, Lars; Aminian, Kamiar; Ihlen, Espen A F; Mellone, Sabato; Helbostad, Jorunn L; Chiari, Lorenzo; Becker, Clemens

    2016-08-01

    Automatic fall detection will promote independent living and reduce the consequences of falls in the elderly by ensuring people can confidently live safely at home for linger. In laboratory studies inertial sensor technology has been shown capable of distinguishing falls from normal activities. However less than 7% of fall-detection algorithm studies have used fall data recorded from elderly people in real life. The FARSEEING project has compiled a database of real life falls from elderly people, to gain new knowledge about fall events and to develop fall detection algorithms to combat the problems associated with falls. We have extracted 12 different kinematic, temporal and kinetic related features from a data-set of 89 real-world falls and 368 activities of daily living. Using the extracted features we applied machine learning techniques and produced a selection of algorithms based on different feature combinations. The best algorithm employs 10 different features and produced a sensitivity of 0.88 and a specificity of 0.87 in classifying falls correctly. This algorithm can be used distinguish real-world falls from normal activities of daily living in a sensor consisting of a tri-axial accelerometer and tri-axial gyroscope located at L5.

  2. 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.

  3. A Real-Time System for Abusive Network Traffic Detection

    DTIC Science & Technology

    2011-03-01

    modular architecture, SpamAssassin can be extended to include other filtering techniques, such as real-time blackhole lists (RBLs), whitelists...lookups in blackhole lists (RBL), collaborative filtering with Ryzor [30], Pyzor [53], and DCC [33]), because our virtual environment was insulated from...realtime blackhole list (RBL). Available: http://www.mail-abuse.com/pdf/WP_MAPS_RBL_060104.pdf. [13] J. Postel. (1981, September). Internet

  4. 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.

  5. 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.

  6. Multi-Detection Events, Probability Density Functions, and Reduced Location Area

    SciTech Connect

    Eslinger, Paul W.; Schrom, Brian T.

    2016-03-01

    Abstract Several efforts have been made in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) community to assess the benefits of combining detections of radionuclides to improve the location estimates available from atmospheric transport modeling (ATM) backtrack calculations. We present a Bayesian estimation approach rather than a simple dilution field of regard approach to allow xenon detections and non-detections to be combined mathematically. This system represents one possible probabilistic approach to radionuclide event formation. Application of this method to a recent interesting radionuclide event shows a substantial reduction in the location uncertainty of that event.

  7. 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

  8. Simple Movement and Detection in Discrete Event Simulation

    DTIC Science & Technology

    2005-12-01

    with a description of uniform linear motion in the following section. We will then con- sider the simplest kind of sensing, the “ cookie -cutter.” A... cookie -cutter sensor sees everything that is within its range R, and must be notified at the precise time a target enters it range. In a time-step...simulation, cookie -cutter detection is very easy. Simply compute the distance between the sensor and the target at each time step. If the target is

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. Detecting and Locating Seismic Events Without Phase Picks or Velocity Models

    NASA Astrophysics Data System (ADS)

    Arrowsmith, S.; Young, C. J.; Ballard, S.; Slinkard, M.

    2015-12-01

    The standard paradigm for seismic event monitoring is to scan waveforms from a network of stations and identify the arrival time of various seismic phases. A signal association algorithm then groups the picks to form events, which are subsequently located by minimizing residuals between measured travel times and travel times predicted by an Earth model. Many of these steps are prone to significant errors which can lead to erroneous arrival associations and event locations. Here, we revisit a concept for event detection that does not require phase picks or travel time curves and fuses detection, association and location into a single algorithm. Our pickless event detector exploits existing catalog and waveform data to build an empirical stack of the full regional seismic wavefield, which is subsequently used to detect and locate events at a network level using correlation techniques. Because the technique uses more of the information content of the original waveforms, the concept is particularly powerful for detecting weak events that would be missed by conventional methods. We apply our detector to seismic data from the University of Utah Seismograph Stations network and compare our results with the earthquake catalog published by the University of Utah. We demonstrate that the pickless detector can detect and locate significant numbers of events previously missed by standard data processing techniques.

  11. 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

  12. The Power to Detect Recent Fragmentation Events Using Genetic Differentiation Methods

    PubMed Central

    Lloyd, Michael W.; Campbell, Lesley; Neel, Maile C.

    2013-01-01

    Habitat loss and fragmentation are imminent threats to biological diversity worldwide and thus are fundamental issues in conservation biology. Increased isolation alone has been implicated as a driver of negative impacts in populations associated with fragmented landscapes. Genetic monitoring and the use of measures of genetic divergence have been proposed as means to detect changes in landscape connectivity. Our goal was to evaluate the sensitivity of Wright’s Fst, Hedrick’ G’st, Sherwin’s MI, and Jost’s D to recent fragmentation events across a range of population sizes and sampling regimes. We constructed an individual-based model, which used a factorial design to compare effects of varying population size, presence or absence of overlapping generations, and presence or absence of population sub-structuring. Increases in population size, overlapping generations, and population sub-structuring each reduced Fst, G’st, MI, and D. The signal of fragmentation was detected within two generations for all metrics. However, the magnitude of the change in each was small in all cases, and when Ne was >100 individuals it was extremely small. Multi-generational sampling and population estimates are required to differentiate the signal of background divergence from changes in Fst, G’st, MI, and D associated with fragmentation. Finally, the window during which rapid change in Fst, G’st, MI, and D between generations occurs can be small, and if missed would lead to inconclusive results. For these reasons, use of Fst, G’st, MI, or D for detecting and monitoring changes in connectivity is likely to prove difficult in real-world scenarios. We advocate use of genetic monitoring only in conjunction with estimates of actual movement among patches such that one could compare current movement with the genetic signature of past movement to determine there has been a change. PMID:23704965

  13. Effects of life-event stress and hardiness on peripheral vision in a real-life stress situation.

    PubMed

    Rogers, Tracie J; Alderman, Brandon L; Landers, Daniel M

    2003-01-01

    Previous research has only examined perceptual deficits that are hypothesized in a model of stress and injury under laboratory-induced stress conditions. The generalizability of findings from such induced-stress conditions is limited beyond the laboratory. The current research examined the influence of life-event stress and hardiness on peripheral narrowing in a real-life stress situation. Athletes completed life-stress and hardiness questionnaires, along with measures of state anxiety and peripheral vision. The stress condition was obtained by assessing the athletes within 2 hours of a competition. The real-life stress condition had a larger effect on state anxiety and peripheral narrowing than the laboratory-induced situations used in previous research, with effect sizes twice and three times as large as those reported in the literature. All athletes experienced significant reductions in peripheral vision prior to competition, regardless of life-event stress or hardiness levels.

  14. Real-Time Nucleic Acid Sequence-Based Amplification Assay for Detection of Hepatitis A Virus

    PubMed Central

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

    2005-01-01

    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. PMID:16269748

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

    PubMed Central

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

    2015-01-01

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

  16. Event-related complexity analysis and its application in the detection of facial attractiveness.

    PubMed

    Deng, Zhidong; Zhang, Zimu

    2014-11-01

    In this study, an event-related complexity (ERC) analysis method is proposed and used to explore the neural correlates of facial attractiveness detection in the context of a cognitive experiment. The ERC method gives a quantitative index for measuring the diverse brain activation properties that represent the neural correlates of event-related responses. This analysis reveals distinct effects of facial attractiveness processing and also provides further information that could not have been achieved from event-related potential alone.

  17. An adaptive fault-tolerant event detection scheme for wireless sensor networks.

    PubMed

    Yim, Sung-Jib; Choi, Yoon-Hwa

    2010-01-01

    In this paper, we present an adaptive fault-tolerant event detection scheme for wireless sensor networks. Each sensor node detects an event locally in a distributed manner by using the sensor readings of its neighboring nodes. Confidence levels of sensor nodes are used to dynamically adjust the threshold for decision making, resulting in consistent performance even with increasing number of faulty nodes. In addition, the scheme employs a moving average filter to tolerate most transient faults in sensor readings, reducing the effective fault probability. Only three bits of data are exchanged to reduce the communication overhead in detecting events. Simulation results show that event detection accuracy and false alarm rate are kept very high and low, respectively, even in the case where 50% of the sensor nodes are faulty.

  18. 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

  19. Real Time Detection of Sodium in Size-Segregated Marine Aerosols

    DTIC Science & Technology

    2002-09-30

    Real Time Measurement of Sea- Salt Aerosol during the SEAS Campaign: Comparison of Emission based Sodium Detection with an Aerosol Volatility Technique. Submitted to the Journal of Atmospheric and Oceanic Technology. ...Real Time Detection of Sodium in Size-Segregated Marine Aerosols Anthony J. Hynes Rosenstiel School of Marine and Atmospheric Science 4600...this capability for sodium and a prototype has been deployed as part of an ONR-sponsored field campaign (SEAS). The ultimate goal of the project is to

  20. MCD for detection of event-based landslides

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  1. Significance of "Not Detected but Amplified" Results by Real-Time PCR Method for HPV DNA Detection.

    PubMed

    Kim, Taek Soo; Lim, Mi Suk; Hong, Yun Ji; Hwang, Sang Mee; Park, Kyoung Un; Song, Junghan; Kim, Eui-Chong

    2016-01-01

    Human papillomavirus (HPV) infection is an important etiologic factor in cervical carcinogenesis. Various HPV DNA detection methods have been evaluated for clinicopathological level. For the specimens with normal cytological finding, discrepancies among the detection methods were frequently found and adequate interpretation can be difficult. 6,322 clinical specimens were submitted and evaluated for real-time PCR and Hybrid Capture 2 (HC2). 573 positive or "Not Detected but Amplified" (NDBA) specimens by real-time PCR were additionally tested using genetic analyzer. For the reliability of real-time PCR, 325 retests were performed. Optimal cut-off cycle threshold (CT ) value was evaluated also. 78.7% of submitted specimens showed normal or nonspecific cytological finding. The distributions of HPV types by real-time PCR were not different between positive and NDBA cases. For positive cases by fragment analysis, concordance rates with real-time PCR and HC2 were 94.2% and 84.2%. In NDBA cases, fragment analysis and real-time PCR showed identical results in 77.0% and HC2 revealed 27.6% of concordance with fragment analysis. Optimal cut-off CT value was different for HPV types. NDBA results in real-time PCR should be regarded as equivocal, not negative. The adjustment of cut-off CT value for HPV types will be helpful for the appropriate result interpretation.

  2. Significance of “Not Detected but Amplified” Results by Real-Time PCR Method for HPV DNA Detection

    PubMed Central

    Kim, Taek Soo; Lim, Mi Suk; Hwang, Sang Mee; Song, Junghan; Kim, Eui-Chong

    2016-01-01

    Human papillomavirus (HPV) infection is an important etiologic factor in cervical carcinogenesis. Various HPV DNA detection methods have been evaluated for clinicopathological level. For the specimens with normal cytological finding, discrepancies among the detection methods were frequently found and adequate interpretation can be difficult. 6,322 clinical specimens were submitted and evaluated for real-time PCR and Hybrid Capture 2 (HC2). 573 positive or “Not Detected but Amplified” (NDBA) specimens by real-time PCR were additionally tested using genetic analyzer. For the reliability of real-time PCR, 325 retests were performed. Optimal cut-off cycle threshold (CT) value was evaluated also. 78.7% of submitted specimens showed normal or nonspecific cytological finding. The distributions of HPV types by real-time PCR were not different between positive and NDBA cases. For positive cases by fragment analysis, concordance rates with real-time PCR and HC2 were 94.2% and 84.2%. In NDBA cases, fragment analysis and real-time PCR showed identical results in 77.0% and HC2 revealed 27.6% of concordance with fragment analysis. Optimal cut-off CT value was different for HPV types. NDBA results in real-time PCR should be regarded as equivocal, not negative. The adjustment of cut-off CT value for HPV types will be helpful for the appropriate result interpretation. PMID:28097135

  3. Fractal analysis of GPS time series for early detection of disastrous seismic events

    NASA Astrophysics Data System (ADS)

    Filatov, Denis M.; Lyubushin, Alexey A.

    2017-03-01

    A new method of fractal analysis of time series for estimating the chaoticity of behaviour of open stochastic dynamical systems is developed. The method is a modification of the conventional detrended fluctuation analysis (DFA) technique. We start from analysing both methods from the physical point of view and demonstrate the difference between them which results in a higher accuracy of the new method compared to the conventional DFA. Then, applying the developed method to estimate the measure of chaoticity of a real dynamical system - the Earth's crust, we reveal that the latter exhibits two distinct mechanisms of transition to a critical state: while the first mechanism has already been known due to numerous studies of other dynamical systems, the second one is new and has not previously been described. Using GPS time series, we demonstrate efficiency of the developed method in identification of critical states of the Earth's crust. Finally we employ the method to solve a practically important task: we show how the developed measure of chaoticity can be used for early detection of disastrous seismic events and provide a detailed discussion of the numerical results, which are shown to be consistent with outcomes of other researches on the topic.

  4. 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

    2014-09-01

    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. PACS

  5. 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.

  6. 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.

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

    PubMed

    Athanasopoulou, Eleftheria; Hadjicostis, Christoforos N

    2005-09-01

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

  8. Real-time Microseismic Processing for Induced Seismicity Hazard Detection

    SciTech Connect

    Matzel, Eric M.

    2016-10-31

    Induced seismicity is inherently associated with underground fluid injections. If fluids are injected in proximity to a pre-existing fault or fracture system, the resulting elevated pressures can trigger dynamic earthquake slip, which could both damage surface structures and create new migration pathways. The goal of this research is to develop a fundamentally better approach to geological site characterization and early hazard detection. We combine innovative techniques for analyzing microseismic data with a physics-based inversion model to forecast microseismic cloud evolution. The key challenge is that faults at risk of slipping are often too small to detect during the site characterization phase. Our objective is to devise fast-running methodologies that will allow field operators to respond quickly to changing subsurface conditions.

  9. 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.

  10. Flexible Computing Architecture for Real Time Skin Detection

    DTIC Science & Technology

    2010-03-01

    1-2 Figure 2. Example of Melanin Estimation on Skin Detections .................................................. 1-2 Figure 3...Comparision of a Hyperspectral Cube to a Multispectral Image ................................ 2-2 Figure 4. Human Skin Model Showing Effect of Melanin ...entire person to be exposed, just a single pixel of skin. The same body of work also presented the capability to estimate the melanin content of skin

  11. Event-specific qualitative and quantitative detection of five genetically modified rice events using a single standard reference molecule.

    PubMed

    Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Shin, Min-Ki; Moon, Gui-Im; Hong, Jin-Hwan; Kim, Hae-Yeong

    2017-07-01

    One novel standard reference plasmid, namely pUC-RICE5, was constructed as a positive control and calibrator for event-specific qualitative and quantitative detection of genetically modified (GM) rice (Bt63, Kemingdao1, Kefeng6, Kefeng8, and LLRice62). pUC-RICE5 contained fragments of a rice-specific endogenous reference gene (sucrose phosphate synthase) as well as the five GM rice events. An existing qualitative PCR assay approach was modified using pUC-RICE5 to create a quantitative method with limits of detection correlating to approximately 1-10 copies of rice haploid genomes. In this quantitative PCR assay, the square regression coefficients ranged from 0.993 to 1.000. The standard deviation and relative standard deviation values for repeatability ranged from 0.02 to 0.22 and 0.10% to 0.67%, respectively. The Ministry of Food and Drug Safety (Korea) validated the method and the results suggest it could be used routinely to identify five GM rice events.

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

    PubMed

    Deepak, Sa; Kottapalli, Kr; Rakwal, R; Oros, G; Rangappa, Ks; Iwahashi, H; Masuo, Y; Agrawal, Gk

    2007-06-01

    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 21(st) 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.

  13. 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

  14. 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%.

  15. Detecting cardiac events - state-of-the-art.

    PubMed

    Collinson, Paul

    2015-11-01

    Cardiac biomarker measurement currently addresses two key questions in patient management: the differential diagnosis of chest pain and the differential diagnosis of the patient with breathlessness. There are currently three major themes in the strategies for the differential diagnosis of chest pain. The first is to undertake troponin measurement in patients selected to be at lower risk, hence to have a low prior probability of disease. The second is the introduction of high-sensitivity cardiac troponin (hs cTn) assays into routine clinical use with measurement at 0 and 3 h from admission. Two other approaches that utilize the diagnostic characteristics of these assays have also been suggested. The first is to use the limit of detection or limit of blank of the assay as the diagnostic discriminant. The second approach is to use the low imprecision of the assay within the reference interval and combine a discriminant value with an absolute rate of change (delta value). The third is the use of additional biomarkers to allow early discharge from the emergency department. The concept is to measure high-sensitivity cardiac troponin plus the extra marker on admission. The role of measurement of B-type natriuretic peptide or its N-terminal prohormone, N-terminal pro-B-type natriuretic peptide, has been accepted and incorporated into guidelines for chronic heart failure for some time. More recently, guidelines for acute heart failure can also recommend a single measurement of B-type natriuretic peptide or N-terminal pro-B-type natriuretic peptide in people presenting with new suspected acute heart failure.

  16. Detection and quantification of Aeromonas salmonicida in fish tissue by real-time PCR.

    PubMed

    Bartkova, S; Kokotovic, B; Skall, H F; Lorenzen, N; Dalsgaard, I

    2017-02-01

    Furunculosis, a septicaemic infection caused by the bacterium Aeromonas salmonicida subsp. salmonicida, currently causes problems in Danish seawater rainbow trout production. Detection has mainly been achieved by bacterial culture, but more rapid and sensitive methods are needed. A previously developed real-time PCR assay targeting the plasmid encoded aopP gene of A. salmonicida was, in parallel with culturing, used for the examination of five organs of 40 fish from Danish freshwater and seawater farms. Real-time PCR showed overall a higher frequency of positives than culturing (65% of positive fish by real-time PCR compared to 30% by a culture approach). Also, no real-time PCR-negative samples were found positive by culturing. A. salmonicida was detected by real-time PCR, though not by culturing, in freshwater fish showing no signs of furunculosis, indicating possible presence of carrier fish. In seawater fish examined after an outbreak and antibiotics treatment, real-time PCR showed the presence of the bacterium in all examined organs (1-482 genomic units mg(-1) ). With a limit of detection of 40 target copies (1-2 genomic units) per reaction, a high reproducibility and an excellent efficiency, the present real-time PCR assay provides a sensitive tool for the detection of A. salmonicida.

  17. 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.

  18. Seismicity Detection off Kushiro-Tokachi Using JAMSTEC Real-time Cabled Seafloor Earthquake Observation System

    NASA Astrophysics Data System (ADS)

    Otsuka, R.; Hirata, K.; Sugioka, H.; Fujie, G.; Morita, S.; Mikada, H.

    2001-12-01

    The off-Kushiro and Tokachi area, the land ward slope area of Kuril Trench, is characterized by its active seismicity, which is directly related to the subduction process of the Pacific plate. From the land observations, however, it is difficult to obtain the detailed seaward seismicity which provides us with important information on plate subduction beneath the Okhotsk (North American) plate. In July 1999, Japan Marine Science and Technology Center (JAMSTEC) established a real time seafloor cabled observation system off Kushiro and Tokachi. This system is composed of three OBS_¢A_ªr, two Tsumani gauges, a set of deep sea floor environmental sensors, and two branch MUX_¢A_ªrs. The OBS_¢A_ªrs are installed to form a tripartite network for the hypocenter determination of minor seismic events right around the cabled system. We can also estimate hypocenters of earthquakes with much accuracy by combining data from the OBS_¢A_ªrs with land data than those from land data only. Since the installation of the system, we relocated about 1500 events from February to June 2001 using the OBS data and land network data. These events were chosen under a condition that they are triggered at least at one OBS location. For obtaining the accuracy enhancement in hypocenter determination by combining the OBS data, locations of these seismic events were determined only with the land data, too. It turned out that estimate error in hypocenters after the combination was reduced to range around a few km. We also found out that a seismically active area is located along the Kushiro-submarine valley that has been suspected as a structural discontinuity. We would like to demonstrate, (1) the great improvement in the detection of earthquakes around off Kushiro-Tokachi seismogenic zone after the deployment of the cabled sea floor observatories and (2) associate understandings on the seismicity led from the relocated earthquake hypocenters. These results implies the importance of cabled

  19. Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

    PubMed

    Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

    2016-12-08

    This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

  20. Real-time defect detection on highly reflective curved surfaces

    NASA Astrophysics Data System (ADS)

    Rosati, G.; Boschetti, G.; Biondi, A.; Rossi, A.

    2009-03-01

    This paper presents an automated defect detection system for coated plastic components for the automotive industry. This research activity came up as an evolution of a previous study which employed a non-flat mirror to illuminate and inspect high reflective curved surfaces. According to this method, the rays emitted from a light source are conveyed on the surface under investigation by means of a suitably curved mirror. After the reflection on the surface, the light rays are collected by a CCD camera, in which the coating defects appear as shadows of various shapes and dimensions. In this paper we present an evolution of the above-mentioned method, introducing a simplified mirror set-up in order to reduce the costs and the complexity of the defect detection system. In fact, a set of plane mirrors is employed instead of the curved one. Moreover, the inspection of multiple bend radius parts is investigated. A prototype of the machine vision system has been developed in order to test this simplified method. This device is made up of a light projector, a set of plane mirrors for light rays reflection, a conveyor belt for handling components, a CCD camera and a desktop PC which performs image acquisition and processing. Like in the previous system, the defects are identified as shadows inside a high brightness image. At the end of the paper, first experimental results are presented.

  1. 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

  2. Real-time PCR for the detection of precise transgene copy number in durum wheat.

    PubMed

    Gadaleta, Agata; Giancaspro, Angelica; Cardone, Maria Francesca; Blanco, Antonio

    2011-12-01

    Recent results obtained in various crops indicate that real-time PCR could be a powerful tool for the detection and characterization of transgene locus structures. The determination of transgenic locus number through real-time PCR overcomes the problems linked to phenotypic segregation analysis (i.e. lack of detectable expression even when the transgenes are present) and can analyse hundreds of samples in a day, making it an efficient method for estimating gene copy number. Despite these advantages, many authors speak of "estimating" copy number by real-time PCR, and this is because the detection of a precise number of transgene depends on how well real-time PCR performs.This study was conducted to determine transgene copy number in transgenic wheat lines and to investigate potential variability in sensitivity and resolution of real-time chemistry by TaqMan probes. We have applied real-time PCR to a set of four transgenic durum wheat lines previously obtained. A total of 24 experiments (three experiments for two genes in each transgenic line) were conducted and standard curves were obtained from serial dilutions of the plasmids containing the genes of interest. The correlation coefficients ranged from 0.95 to 0.97. By using TaqMan quantitative real-time PCR we were able to detect 1 to 41 copies of transgenes per haploid genome in the DNA of homozygous T4 transformants. Although a slight variability was observed among PCR experiments, in our study we found real-time PCR to be a fast, sensitive and reliable method for the detection of transgene copy number in durum wheat, and a useful adjunct to Southern blot and FISH analyses to detect the presence of transgenic DNA in plant material.

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

    NASA Astrophysics Data System (ADS)

    Banerjee, Torsha

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  5. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Molecular-Beacon Multiplex Real-Time PCR Assay for Detection of Vibrio cholerae

    PubMed Central

    Gubala, Aneta J.; Proll, David F.

    2006-01-01

    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. PMID:16957277

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. 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…

  10. Evaluation of various real-time reverse transcription quantitative PCR assays for norovirus detection.

    PubMed

    Yoo, Ju Eun; Lee, Cheonghoon; Park, SungJun; Ko, GwangPyo

    2017-02-01

    Human noroviruses are widespread and contagious viruses causing nonbacterial gastroenteritis. Real-time reverse transcription quantitative PCR (real-time RT-qPCR) is currently the gold standard for sensitive and accurate detection for these pathogens and serves as a critical tool in outbreak prevention and control. Different surveillance teams, however, may use different assays and variability in specimen conditions may lead to disagreement in results. Furthermore, the norovirus genome is highly variable and continuously evolving. These issues necessitate the re-examination of the real-time RT-qPCR's robustness in the context of accurate detection as well as the investigation of practical strategies to enhance assay performance. Four widely referenced real-time RT-qPCR assays (Assay A-D) were simultaneously performed to evaluate characteristics such as PCR efficiency, detection limit, as well as sensitivity and specificity with RT-PCR, and to assess the most accurate method for detecting norovirus genogroups I and II. Overall, Assay D was evaluated to be the most precise and accurate assay in this study. A Zen internal quencher, which decreases nonspecific fluorescence during the PCR reaction, was added to Assay D's probe which further improved assay performance. This study compared several detection assays for noroviruses and an improvement strategy based on such comparisons provided useful characterizations of a highly optimized real-time RT-qPCR assay for norovirus detection.

  11. Using machine learning to detect events in eye-tracking data.

    PubMed

    Zemblys, Raimondas; Niehorster, Diederick C; Komogortsev, Oleg; Holmqvist, Kenneth

    2017-02-23

    Event detection is a challenging stage in eye movement data analysis. A major drawback of current event detection methods is that parameters have to be adjusted based on eye movement data quality. Here we show that a fully automated classification of raw gaze samples as belonging to fixations, saccades, or other oculomotor events can be achieved using a machine-learning approach. Any already manually or algorithmically detected events can be used to train a classifier to produce similar classification of other data without the need for a user to set parameters. In this study, we explore the application of random forest machine-learning technique for the detection of fixations, saccades, and post-saccadic oscillations (PSOs). In an effort to show practical utility of the proposed method to the applications that employ eye movement classification algorithms, we provide an example where the method is employed in an eye movement-driven biometric application. We conclude that machine-learning techniques lead to superior detection compared to current state-of-the-art event detection algorithms and can reach the performance of manual coding.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Optimizing Biosurveillance Systems that Use Threshold-based Event Detection Methods

    DTIC Science & Technology

    2009-06-01

    Optimizing Biosurveillance Systems that Use Threshold-based Event Detection Methods Ronald D. Fricker, Jr.∗ and David Banschbach† June 1, 2009...Abstract We describe a methodology for optimizing a threshold detection-based biosurveillance system. The goal is to maximize the system-wide probability of...Using this approach, pub- lic health officials can “tune” their biosurveillance systems to optimally detect various threats, thereby allowing

  1. "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…

  2. 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…

  3. 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.

  4. 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.

  5. 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

  6. Observing quantum gases in real time: Single-atom detection on a chip

    SciTech Connect

    Guenther, A.; Bender, H.; Stibor, A.; Fortagh, J.; Zimmermann, C.

    2009-07-15

    Single magnetically trapped {sup 87}Rb atoms on an atom chip are detected with 67{+-}12 % efficiency by three photon ionization and subsequent ion detection in a channel electron multiplier. State selective detection of single atoms and high-resolution optical spectroscopy on trapped atom clouds are demonstrated. The temperature and particle density of a trapped atomic gas is monitored in situ and in real time with negligible atom loss due to ionization below 5%.

  7. Real-time detection of transients in OGLE-IV with application of machine learning

    NASA Astrophysics Data System (ADS)

    Klencki, Jakub; Wyrzykowski, Łukasz

    2016-06-01

    The current bottleneck of transient detection in most surveys is the problem of rejecting numerous artifacts from detected candidates. We present a triple-stage hierarchical machine learning system for automated artifact filtering in difference imaging, based on self-organizing maps. The classifier, when tested on the OGLE-IV Transient Detection System, accepts 97% of real transients while removing up to 97.5% of artifacts.

  8. 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.

  9. 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.

  10. Adverse event detection in drug development: recommendations and obligations beyond phase 3.

    PubMed

    Berlin, Jesse A; Glasser, Susan C; Ellenberg, Susan S

    2008-08-01

    Premarketing studies of drugs, although large enough to demonstrate efficacy and detect common adverse events, cannot reliably detect an increased incidence of rare adverse events or events with significant latency. For most drugs, only about 500 to 3000 participants are studied, for relatively short durations, before a drug is marketed. Systems for assessment of postmarketing adverse events include spontaneous reports, computerized claims or medical record databases, and formal postmarketing studies. We briefly review the strengths and limitations of each. Postmarketing surveillance is essential for developing a full understanding of the balance between benefits and adverse effects. More work is needed in analysis of data from spontaneous reports of adverse effects and automated databases, design of ad hoc studies, and design of economically feasible large randomized studies.

  11. 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.

  12. 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.

  13. Detection of Food Allergens by Taqman Real-Time PCR Methodology.

    PubMed

    García, Aina; Madrid, Raquel; García, Teresa; Martín, Rosario; González, Isabel

    2017-01-01

    Real-time PCR (polymerase chain reaction) has shown to be a very effective technology for the detection of food allergens. The protocol described herein consists on a real-time PCR assay targeting the plant ITS (Internal Transcribed Spacer) region, using species-specific primers and hydrolysis probes (Taqman) dual labeled with a reporter fluorophore at the 5' end (6-carboxyfluorescein, FAM) and a quencher fluorophore at the 3' end (Blackberry, BBQ). The species-specific real-time PCR systems (primers/probe) described in this work allowed the detection of different nuts (peanut, hazelnut, pistachio, almond, cashew, macadamia, walnut and pecan), common allergens present in commercial food products, with a detection limit of 0.1 mg/kg.

  14. Miniature real time PCR on chip with multi-channel fiber optical fluorescence detection module.

    PubMed

    Xiang, Q; Xu, B; Li, D

    2007-08-01

    This paper presents the design and implementation of a miniature real time PCR system consisting of a disposable reactor chip, a miniature thermal cycler, and a multi-channel fiber optical fluorescence excitation/detection module. The disposable PCR chip is fabricated by using soft photolithography by PDMS (Polydimethylsiloxane) and glass. The miniature thermal cycler has a thin film heater for heating and a fan for rapid cooling. The fiber optical detection module consists of laser, filter cube, photo-detector and 1x4 fiber optical switch. It is capable of four-well real time PCR analysis. Real-time PCR detection of E. coli stx1 has been demonstrated successfully with this system.

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

    PubMed

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

    2015-04-01

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

  16. 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

  17. 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

  18. Detection of bubble nucleation event in superheated drop detector by the pressure sensor

    NASA Astrophysics Data System (ADS)

    Das, Mala; Biswas, Nilanjan

    2017-01-01

    Superheated drop detector consisting of drops of superheated liquid suspended in polymer or gel matrix is of great demand, mainly because of its insensitivity to ß-particles and ?-rays and also because of the low cost. The bubble nucleation event is detected by measuring the acoustic shock wave released during the nucleation process. The present work demonstrates the detection of bubble nucleation events by using the pressure sensor. The associated circuits for the measurement are described in this article. The detection of events is verified by measuring the events with the acoustic sensor. The measurement was done using drops of various sizes to study the effect of the size of the drop on the pressure recovery time. Probability of detection of events has increased for larger size of the superheated drops and lesser volume of air in contact with the gel matrix. The exponential decay fitting to the pressure sensor signals shows the dead time for pressure recovery of such a drop detector to be a few microseconds.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Visual sensor based abnormal event detection with moving shadow removal in home healthcare applications.

    PubMed

    Lee, Young-Sook; Chung, Wan-Young

    2012-01-01

    Vision-based abnormal event detection for home healthcare systems can be greatly improved using visual sensor-based techniques able to detect, track and recognize objects in the scene. However, in moving object detection and tracking processes, moving cast shadows can be misclassified as part of objects or moving objects. Shadow removal is an essential step for developing video surveillance systems. The goal of the primary is to design novel computer vision techniques that can extract objects more accurately and discriminate between abnormal and normal activities. To improve the accuracy of object detection and tracking, our proposed shadow removal algorithm is employed. Abnormal event detection based on visual sensor by using shape features variation and 3-D trajectory is presented to overcome the low fall detection rate. The experimental results showed that the success rate of detecting abnormal events was 97% with a false positive rate of 2%. Our proposed algorithm can allow distinguishing diverse fall activities such as forward falls, backward falls, and falling asides from normal activities.

  4. 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.

  5. 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.

  6. A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

    PubMed Central

    Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

    2017-01-01

    Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

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

    NASA Astrophysics Data System (ADS)

    Perez, Claudio A.; Lazcano, Vanel A.

    2005-12-01

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

  8. Ultra-high throughput real-time instruments for capturing fast signals and rare events

    NASA Astrophysics Data System (ADS)

    Buckley, Brandon Walter

    Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and

  9. 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.

  10. Using Atmospheric Circulation Patterns to Detect and Attribute Changes in the Risk of Extreme Climate Events

    NASA Astrophysics Data System (ADS)

    Diffenbaugh, N. S.; Horton, D. E.; Singh, D.; Swain, D. L.; Touma, D. E.; Mankin, J. S.

    2015-12-01

    Because of the high cost of extreme events and the growing evidence that global warming is likely to alter the statistical distribution of climate variables, detection and attribution of changes in the probability of extreme climate events has become a pressing topic for the scientific community, elected officials, and the public. While most of the emphasis has thus far focused on analyzing the climate variable of interest (most often temperature or precipitation, but also flooding and drought), there is an emerging emphasis on applying detection and attribution analysis techniques to the underlying physical causes of individual extreme events. This approach is promising in part because the underlying physical causes (such as atmospheric circulation patterns) can in some cases be more accurately represented in climate models than the more proximal climate variable (such as precipitation). In addition, and more scientifically critical, is the fact that the most extreme events result from a rare combination of interacting causes, often referred to as "ingredients". Rare events will therefore always have a strong influence of "natural" variability. Analyzing the underlying physical mechanisms can therefore help to test whether there have been changes in the probability of the constituent conditions of an individual event, or whether the co-occurrence of causal conditions cannot be distinguished from random chance. This presentation will review approaches to applying detection/attribution analysis to the underlying physical causes of extreme events (including both "thermodynamic" and "dynamic" causes), and provide a number of case studies, including the role of frequency of atmospheric circulation patterns in the probability of hot, cold, wet and dry events.

  11. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Abdeljaber, Osama; Avci, Onur; Kiranyaz, Serkan; Gabbouj, Moncef; Inman, Daniel J.

    2017-02-01

    Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

  12. 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)

  13. Developing assessment system for wireless capsule endoscopy videos based on event detection

    NASA Astrophysics Data System (ADS)

    Chen, Ying-ju; Yasen, Wisam; Lee, Jeongkyu; Lee, Dongha; Kim, Yongho

    2009-02-01

    Along with the advancing of technology in wireless and miniature camera, Wireless Capsule Endoscopy (WCE), the combination of both, enables a physician to diagnose patient's digestive system without actually perform a surgical procedure. Although WCE is a technical breakthrough that allows physicians to visualize the entire small bowel noninvasively, the video viewing time takes 1 - 2 hours. This is very time consuming for the gastroenterologist. Not only it sets a limit on the wide application of this technology but also it incurs considerable amount of cost. Therefore, it is important to automate such process so that the medical clinicians only focus on interested events. As an extension from our previous work that characterizes the motility of digestive tract in WCE videos, we propose a new assessment system for energy based events detection (EG-EBD) to classify the events in WCE videos. For the system, we first extract general features of a WCE video that can characterize the intestinal contractions in digestive organs. Then, the event boundaries are identified by using High Frequency Content (HFC) function. The segments are classified into WCE event by special features. In this system, we focus on entering duodenum, entering cecum, and active bleeding. This assessment system can be easily extended to discover more WCE events, such as detailed organ segmentation and more diseases, by using new special features. In addition, the system provides a score for every WCE image for each event. Using the event scores, the system helps a specialist to speedup the diagnosis process.

  14. Improving Magnitude Detection Thresholds Using Multi-Station Multi-Event, and Multi-Phase Methods

    DTIC Science & Technology

    2008-07-31

    applied to different tectonic settings and for what percentage of the seismicity. 111 million correlations were performed on Lg-waves for the events in...a significant detection spike. 30 24. Figure 24. Example of an aftershock (spike at 2400 samples) detected after a mainshock (spike at 1500...false alarms in 36 days for a SNR of 0.32. The significant result of this study is that a correlation detector has more than an order of magnitude

  15. A Real-Time System for Lane Detection Based on FPGA and DSP

    NASA Astrophysics Data System (ADS)

    Xiao, Jing; Li, Shutao; Sun, Bin

    2016-12-01

    This paper presents a real-time lane detection system including edge detection and improved Hough Transform based lane detection algorithm and its hardware implementation with field programmable gate array (FPGA) and digital signal processor (DSP). Firstly, gradient amplitude and direction information are combined to extract lane edge information. Then, the information is used to determine the region of interest. Finally, the lanes are extracted by using improved Hough Transform. The image processing module of the system consists of FPGA and DSP. Particularly, the algorithms implemented in FPGA are working in pipeline and processing in parallel so that the system can run in real-time. In addition, DSP realizes lane line extraction and display function with an improved Hough Transform. The experimental results show that the proposed system is able to detect lanes under different road situations efficiently and effectively.

  16. High-throughput pooling and real-time PCR-based strategy for malaria detection.

    PubMed

    Taylor, Steve M; Juliano, Jonathan J; Trottman, Paul A; Griffin, Jennifer B; Landis, Sarah H; Kitsa, Paluku; Tshefu, Antoinette K; Meshnick, Steven R

    2010-02-01

    Molecular assays can provide critical information for malaria diagnosis, speciation, and drug resistance, but their cost and resource requirements limit their application to clinical malaria studies. This study describes the application of a resource-conserving testing algorithm employing sample pooling for real-time PCR assays for malaria in a cohort of 182 pregnant women in Kinshasa. A total of 1,268 peripheral blood samples were collected during the study. Using a real-time PCR assay that detects all Plasmodium species, microscopy-positive samples were amplified individually; the microscopy-negative samples were amplified after pooling the genomic DNA (gDNA) of four samples prior to testing. Of 176 microscopy-positive samples, 74 were positive by the real-time PCR assay; the 1,092 microscopy-negative samples were initially amplified in 293 pools, and subsequently, 35 samples were real-time PCR positive (3%). With the real-time PCR result as the referent standard, microscopy was 67.9% sensitive (95% confidence interval [CI], 58.3% to 76.5%) and 91.2% specific (95% CI, 89.4% to 92.8%) for malaria. In total, we detected 109 parasitemias by real-time PCR and, by pooling samples, obviated over 50% of reactions and halved the cost of testing. Our study highlights both substantial discordance between malaria diagnostics and the utility and parsimony of employing a sample pooling strategy for molecular diagnostics in clinical and epidemiologic malaria studies.

  17. Seizure detection methods using a cascade architecture for real-time implantable devices.

    PubMed

    Kim, Taehoon; Artan, N Sertac; Selesnick, Ivan W; Chao, H Jonathan

    2013-01-01

    Implantable high-accuracy, and low-power seizure detection is a challenge. In this paper, we propose a cascade architecture to combine different seizure detection algorithms to optimize power and accuracy of the overall seizure detection system. The proposed architecture consists of a cascade of two seizure detection stages. In the first-stage detector, a lightweight (low-power) algorithm is used to detect seizure candidates with the understanding that there will be a high number of false positives. In the second-stage detector-and only for the seizure candidates detected in the first detector-a high-accuracy algorithm is used to eliminate the false positives. We show that the proposed cascade architecture can reduce power consumption of seizure detection by 80% with high accuracy, offering a suitable option for real-time implantable seizure detectors.

  18. 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.

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

    PubMed

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

    2011-11-09

    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.

  20. 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.

  1. 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.

  2. 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

  3. Gold nanoparticle-enabled real-time ligation chain reaction for ultrasensitive detection of DNA.

    PubMed

    Shen, Wei; Deng, Huimin; Gao, Zhiqiang

    2012-09-12

    A simple and ultrasensitive colorimetric DNA assay based on the detection of the product of a ligation chain reaction (LCR) and the use of gold nanoparticles (AuNPs) as signal generators has been developed. During LCR, the AuNPs were ligated together, resulting in a distinct color change in real time after a sufficient number of thermal cycles. The cumulative nature of the protocol produced a detection limit of 20 aM with a selectivity factor of 10(3).

  4. 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.

  5. Final Scientific Report, Integrated Seismic Event Detection and Location by Advanced Array Processing

    SciTech Connect

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

    2007-01-30

    In the field of nuclear explosion monitoring, it has become a priority to detect, locate, and identify seismic events down to increasingly small magnitudes. The consideration of smaller seismic events has implications for a reliable monitoring regime. Firstly, the number of events to be considered increases greatly; an exponential increase in naturally occurring seismicity is compounded by large numbers of seismic signals generated by human activity. Secondly, the signals from smaller events become more difficult to detect above the background noise and estimates of parameters required for locating the events may be subject to greater errors. Thirdly, events are likely to be observed by a far smaller number of seismic stations, and the reliability of event detection and location using a very limited set of observations needs to be quantified. For many key seismic stations, detection lists may be dominated by signals from routine industrial explosions which should be ascribed, automatically and with a high level of confidence, to known sources. This means that expensive analyst time is not spent locating routine events from repeating seismic sources and that events from unknown sources, which could be of concern in an explosion monitoring context, are more easily identified and can be examined with due care. We have obtained extensive lists of confirmed seismic events from mining and other artificial sources which have provided an excellent opportunity to assess the quality of existing fully-automatic event bulletins and to guide the development of new techniques for online seismic processing. Comparing the times and locations of confirmed events from sources in Fennoscandia and NW Russia with the corresponding time and location estimates reported in existing automatic bulletins has revealed substantial mislocation errors which preclude a confident association of detected signals with known industrial sources. The causes of the errors are well understood and are

  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. 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. Real time fabric defect detection system on an embedded DSP platform

    NASA Astrophysics Data System (ADS)

    Raheja, Jagdish Lal; Ajay, Bandla; Chaudhary, Ankit

    2013-11-01

    In industrial fabric productions, automated real time systems are needed to find out the minor defects. It will save the cost by not transporting defected products and also would help in making compmay image of quality fabrics by sending out only undefected products. A real time fabric defect detection system (FDDS), implementd on an embedded DSP platform is presented here. Textural features of fabric image are extracted based on gray level co-occurrence matrix (GLCM). A sliding window technique is used for defect detection where window moves over the whole image computing a textural energy from the GLCM of the fabric image. The energy values are compared to a reference and the deviations beyond a threshold are reported as defects and also visually represented by a window. The implementation is carried out on a TI TMS320DM642 platform and programmed using code composer studio software. The real time output of this implementation was shown on a monitor.

  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.

  10. 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.

  11. 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.…

  12. [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.

  13. Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection

    PubMed Central

    Li, Shih-Hong; Lin, Bor-Shing; Tsai, Chen-Han; Yang, Cheng-Ta; Lin, Bor-Shyh

    2017-01-01

    In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis. PMID:28106747

  14. Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection.

    PubMed

    Li, Shih-Hong; Lin, Bor-Shing; Tsai, Chen-Han; Yang, Cheng-Ta; Lin, Bor-Shyh

    2017-01-17

    In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis.

  15. Development of a real-time PCR for Bartonella spp. detection, a current emerging microorganism.

    PubMed

    Parra, Elena; Segura, Ferran; Tijero, Jessica; Pons, Imma; Nogueras, Maria-Mercedes

    2017-04-01

    A real-time PCR assay using SYBR Green was optimized to detect those Bartonella that are most frequently described as pathogens. The assay was genus-specific. Sequencing allowed to distinguish species. Assay sensitivity was determined using 10-fold serial dilutions of genomic DNA. Dynamic range was 100 ng-100 fg and sensitivity was 50 copies/reaction.

  16. Avian influenza virus detection and quantitation by real-time RT-PCR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Real-time RT-PCR (rRT-PCR) has been used for avian influenza virus (AIV) detection since the early 2000’s for routine surveillance, during outbreaks and for research. Some of the advantages of rRT-PCR are: high sensitivity, high specificity, rapid time-to-result, scalability, cost, and its inherentl...

  17. 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.

  18. 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...

  19. 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...

  20. 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.

  1. Real-time detection and data acquisition system for the left ventricular outline

    NASA Technical Reports Server (NTRS)

    Reiber, J. H. C.

    1975-01-01

    A data acquisition system for the left ventricular outline which has potential for online use is described and basic principles of the contour detector are presented in detail. It is concluded that the data acquisition system for real time, online detection of left ventricular outlines has many advantages over presently used manual or semi-automatic procedures in a clinical investigative environment.

  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).

  3. 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.

  4. Real time detection of live microbes using a highly sensitive bioluminescent nitroreductase probe.

    PubMed

    Wong, Roger H F; Kwong, Thomas; Yau, Kwok-Hei; Au-Yeung, Ho Yu

    2015-03-14

    A highly sensitive and selective nitroreductase probe, showing a rapid and strong bioluminescence enhancement (>100-fold in 5 minutes), and its initial application in the real time detection of both Gram positive and Gram negative live bacteria and monitoring of their growth has been reported.

  5. PCR real time assays for the early detection of BKV-DNA in immunocompromised patients.

    PubMed

    Marinelli, Katia; Bagnarelli, Patrizia; Gaffi, Gianni; Trappolini, Silvia; Leoni, Pietro; Paggi, Alessandra Mataloni; Della Vittoria, Agnese; Scalise, Giorgio; Varaldo, Pietro Emanuele; Menzo, Stefano

    2007-07-01

    Testing for viral BKV-DNA in urine is a non-invasive early detection and monitoring tool in the diagnostic of BKV-related pathologies: quantitative analysis by Real-Time PCR can provide useful information in addition to cytologic analysis, although our study suggests that high BKV viruria is not necessarily associated with kidney or bladder damage.

  6. Evaluation of two commercial real-time PCR assays for detecting Campylobacter in broiler carcass rinses.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Traditional plating methods are reliable means for Campylobacter identification from poultry samples but automated gene-based detection systems now available can reduce assay time, data collection and analysis. Bio-Rad and DuPont Qualicon recently introduced Campylobacter assays for their real-time ...

  7. Real-time detection of blaKPC in clinical samples and surveillance specimens.

    PubMed

    Mangold, Kathy A; Santiano, Kristine; Broekman, Ronit; Krafft, Catherine A; Voss, Barbara; Wang, Vivien; Hacek, Donna M; Usacheva, Elena A; Thomson, Richard B; Kaul, Karen L; Peterson, Lance R

    2011-09-01

    A real-time PCR assay was developed targeting the bla(KPC) responsible for Klebsiella pneumoniae carbapenemase (KPC)-mediated carbapenem resistance and was validated for testing colonies or enrichment broth cultures. The assay accurately detects KPC-containing strains with high analytical specificity and sensitivity.

  8. 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…

  9. 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…

  10. Adverse drug reactions – examples of detection of rare events using databases

    PubMed Central

    Chan, Esther W; Liu, Kirin Q L; Chui, Celine S L; Sing, Chor-Wing; Wong, Lisa Y L; Wong, Ian C K

    2015-01-01

    It is recognised that randomised controlled trials are not feasible for capturing rare adverse events. There is an increasing trend towards observational research methodologies using large population-based health databases. These databases offer more scope for adequate sample sizes, allowing for comprehensive patient characterisation and assessment of the associated factors. While direct causality cannot be established and confounders cannot be ignored, databases present an opportunity to explore and quantify rare events. The use of databases for the detection of rare adverse events in the following conditions, sudden death associated with attention deficit hyperactivity disorder (ADHD) treatment, retinal detachment associated with the use of fluoroquinolones and toxic epidermal necrolysis associated with drug exposure, are discussed as examples. In general, rare adverse events tend to have immediate and important clinical implications and may be life-threatening. An understanding of the causative factors is therefore important, in addition to the research methodologies and database platforms that enable the undertaking of the research. PMID:25060360

  11. Successful Detection of Floods in Real Time Onboard EO1 Through NASA's ST6 Autonomous Sciencecraft Experiment (ASE)

    NASA Astrophysics Data System (ADS)

    Ip, F.; Dohm, J. M.; Baker, V. R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Doggett, T.; Greeley, R.

    2004-12-01

    For the first time, a spacecraft has the ability to autonomously detect and react to flood events. Flood detection and the investigation of flooding dynamics in real time from space have never been done before at least not until now. Part of the challenge for the hydrological community has been the difficulty of obtaining cloud-free scenes from orbit at sufficient temporal and spatial resolutions to accurately assess flooding. In addition, the large spatial extent of drainage networks coupled with the size of the data sets necessary to be downlinked from satellites add to the difficulty of monitoring flooding from space. Technology developed as part of the Autonomous Sciencecraft Experiment (ASE) creates the new capability to autonomously detect, assess, and react to dynamic events, thereby enabling the monitoring of transient processes such as flooding in real time. In addition to being able to autonomously process the imaged data onboard the spacecraft for the first time and search the data for specific spectral features, the ASE Science Team has developed and tested change detection algorithms for the Hyperion spectrometer on EO-1. For flood events, if a change is detected in the onboard processed image (i.e. an increase in the number of ¡wet¡" pixels relative to a baseline image where the system is in normal flow condition or relatively dry), the spacecraft is autonomously retasked to obtain additional scenes. For instance, in February 2004 a rare flooding of the Australian Diamantina River was captured by EO-1. In addition, in August during ASE onboard testing a Zambezi River scene in Central Africa was successfully triggered by the classifier to autonomously take another observation. Yet another successful trigger-response flooding test scenario of the Yellow River in China was captured by ASE on 8/18/04. These exciting results pave the way for future smart reconnaissance missions of transient processes on Earth and beyond. Acknowledgments: We are grateful

  12. Assessment of a Solid Phase Matrix for the Neutralization and Real-Time PCR Detection of Bacillus anthracis

    DTIC Science & Technology

    2006-12-01

    for the Neutralization and Real - Time PCR Detection of Bacillus anthracis D.E. Bader, G.R. Fisher and C.W. Stratilo DRDC Suffield Technical Memorandum...Matrix for the Neutralization and Real - Time PCR Detection of Bacillus anthracis D.E. Bader, G.R. Fisher, and C.W. Stratilo Defence R&D Canada - Suffield...evaluated for their neutralization ability, based on cell culture analysis, and were also analyzed using real - time PCR detection assays designed to

  13. Event-related potential signatures of perceived and imagined emotional and food real-life photos.

    PubMed

    Marmolejo-Ramos, Fernando; Hellemans, Kim; Comeau, Amy; Heenan, Adam; Faulkner, Andrew; Abizaid, Alfonso; D'Angiulli, Amedeo

    2015-06-01

    Although food and affective pictures share similar emotional and motivational characteristics, the relationship between the neuronal responses to these stimuli is unclear. Particularly, it is not known whether perceiving and imagining food and affective stimuli elicit similar event-related potential (ERP) patterns. In this study, two ERP correlates, the early posterior negativity (EPN) and the late positive potential (LPP) for perceived and imagined emotional and food photographs were investigated. Thirteen healthy volunteers were exposed to a set of food photos, as well as unpleasant, pleasant, and neutral photos from the International Affective Picture System. In each trial, participants were first asked to view a photo (perception condition), and then to create a visual mental image of it and to rate its vividness (imagery condition). The results showed that during perception, brain regions corresponding to sensorimotor and parietal motivational (defensive and appetitive) systems were activated to different extents, producing a graded pattern of EPN and LPP responses specific to the photo content - more prominent for unpleasant than pleasant and food content. Also, an EPN signature occurred in both conditions for unpleasant content, suggesting that, compared to food or pleasant content, unpleasant content may be attended to more intensely during perception and may be represented more distinctly during imagery. Finally, compared to LLP activation during perception, as well as imagery and perception of all other content, LPP activation was significantly reduced during imagery of unpleasant photos, suggesting inhibition of unwanted memories. Results are framed within a neurocognitive working model of embodied emotions.

  14. Conceptual Integration of Arithmetic Operations With Real-World Knowledge: Evidence From Event-Related Potentials.

    PubMed

    Guthormsen, Amy M; Fisher, Kristie J; Bassok, Miriam; Osterhout, Lee; DeWolf, Melissa; Holyoak, Keith J

    2016-04-01

    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 task, when participants generated labeled answers to semantically aligned and misaligned arithmetic problems (e.g., 6 roses + 2 tulips = ? vs. 6 roses + 2 vases = ?), the second object label in misaligned problems yielded an N400 effect for addition (but not division) problems. In a verification task, when participants judged arithmetically correct but semantically misaligned problem sentences to be "unacceptable," the second object label in misaligned sentences elicited a P600 effect. Thus, depending on task constraints, misaligned problems can show either of two ERP signatures of conceptual disruption. These results show that well-educated adults can integrate mathematical and semantic relations on the rapid timescale of within-domain ERP effects by a process akin to analogical mapping.

  15. Conceptual Integration of Arithmetic Operations with Real-World Knowledge: Evidence from Event-Related Potentials

    PubMed Central

    Guthormsen, Amy M.; Fisher, Kristie J.; Bassok, Miriam; Osterhout, Lee; DeWolf, Melissa; Holyoak, Keith J.

    2015-01-01

    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 task, when participants generated labeled answers to semantically aligned and misaligned arithmetic problems (e.g., 6 roses + 2 tulips = ? vs. 6 roses + 2 vases = ?), the second object label in misaligned problems yielded an N400 effect for addition (but not division) problems. In a verification task, when participants judged arithmetically-correct but semantically misaligned problem sentences to be “unacceptable”, the second object label in misaligned sentences elicited a P600 effect. Thus depending on task constraints, misaligned problems can show either of two ERP signatures of conceptual disruption. These results show that well-educated adults can integrate mathematical and semantic relations on the rapid timescale of within-domain ERP effects by a process akin to analogical mapping. PMID:25864403

  16. 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

  17. 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.

  18. 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

  19. Drivers of Emerging Infectious Disease Events as a Framework for Digital Detection.

    PubMed

    Olson, Sarah H; Benedum, Corey M; Mekaru, Sumiko R; Preston, Nicholas D; Mazet, Jonna A K; Joly, Damien O; Brownstein, John S

    2015-08-01

    The growing field of digital disease detection, or epidemic intelligence, attempts to improve timely detection and awareness of infectious disease (ID) events. Early detection remains an important priority; thus, the next frontier for ID surveillance is to improve the recognition and monitoring of drivers (antecedent conditions) of ID emergence for signals that precede disease events. These data could help alert public health officials to indicators of elevated ID risk, thereby triggering targeted active surveillance and interventions. We believe that ID emergence risks can be anticipated through surveillance of their drivers, just as successful warning systems of climate-based, meteorologically sensitive diseases are supported by improved temperature and precipitation data. We present approaches to driver surveillance, gaps in the current literature, and a scientific framework for the creation of a digital warning system. Fulfilling the promise of driver surveillance will require concerted action to expand the collection of appropriate digital driver data.

  20. EO/IR satellite constellations for the early detection and tracking of collision events

    NASA Astrophysics Data System (ADS)

    Zatezalo, A.; El-Fallah, A.; Mahler, R.; Mehra, R. K.; Pham, K.

    2010-04-01

    The detection and tracking of collision events involving existing Low Earth Orbit (LEO) Resident Space Objects (RSOs) is becoming increasingly important with the higher LEO space objects traffic volume which is anticipated to increase even further in the near future. Changes in velocity that can lead to a collision are hard to detect early on time, and before the collision happens. Several collision events can happen at the same time and continuous monitoring of the LEO orbit is necessary in order to determine and implement collision avoidance strategies. We present a simulation of a constellation system consisting of multiple platforms carrying EO/IR sensors for the detection of such collisions. The presented simulation encompasses the full complexity of LEO trajectories changes which can collide with currently operating satellites. Efficient multitarget filter with information-theoretic multisensor management is implemented and evaluated on different constellations.

  1. 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

  2. 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.

  3. Real Time Intrusion Detection (la detection des intrusions en temps reel)

    DTIC Science & Technology

    2003-06-01

    modelled by extended finite state machines . They examined the performance of these techniques, for real-time monitoring of communication networks, from both...widely used to avoid side -effect “Denial Of Service” attacks. The third presentation (Massicotte, Whalen and Bilodeau) was on a prototype network... machines , indicates the state and shows configuration information about the hosts and their connectivity. To query network components, the tool uses

  4. 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.

  5. Automated detection of asteroids in real-time with the Spacewatch telescope

    NASA Technical Reports Server (NTRS)

    Scotti, James Vernon; Gehrels, T.; Rabinowitz, David L.

    1992-01-01

    The Spacewatch telescope on Kitt Peak is being used to survey for near-earth asteroids using a Tektronix TK2048 CCD in scanning mode. We hope to identify suitable low delta v candidates amongst the near-earth asteroid population as possible exploration targets, to identify those objects which pose a danger to life on earth, and to study the physical properties of the objects in near-earth space. Between Sep. 1990 and Jun. 1991, 14 new earth-approaching asteroids including 1 Aten, 9 Apollo, and 4 Amor type asteroids were detected by automated software and discriminated by their angular rates from the rest of the detected asteroids in near-real time by the observer. The average of about 1.5 earth-approaching asteroids per month is comparable to the total number found by all other observatories combined. One other Apollo type asteroid was detected by the observer as a long trailed image. The positions of this last object were measured and the object was tracked by the observer in real time. This object was determined to be a 5-10 meter diameter object which passed within 170,000 kilometers of earth. Of the 14 automatically detected earth-approaching asteroids, 10 have been found at distances in excess of 0.5 AU from earth. An average of more than 2000 asteroids are detected each month. Positions, angular rates, and brightnesses are determined for each of these asteroids in real-time.

  6. 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.

  7. Microneedle Biosensor: A Method for Direct Label-free Real Time Protein Detection

    PubMed Central

    Esfandyarpour, Rahim; Esfandyarpour, Hesaam; Javanmard, Mehdi; Harris, James S.; Davis, Ronald W.

    2012-01-01

    Here we present the development of an array of electrical micro-biosensors in a microfluidic channel, called microneedle biosensors. A microneedle biosensor is a real-time, label-free, direct electrical detection platform, which is capable of high sensitivity detection, measuring the change in ionic current and impedance modulation, due to the presence or reaction of biomolecules such as proteins and nucleic acids. In this study, we successfully fabricated and electrically characterized the sensors and demonstrated successful detection of target protein. In this study, we used biotinylated bovine serum albumin as the receptor and streptavidin as the target analyte PMID:23355762

  8. Real-time detection and elimination of nonorthogonality error in interference fringe processing

    SciTech Connect

    Hu Haijiang; Zhang Fengdeng

    2011-05-20

    In the measurement system of interference fringe, the nonorthogonality error is a main error source that influences the precision and accuracy of the measurement system. The detection and elimination of the error has been an important target. A novel method that only uses the cross-zero detection and the counting is proposed to detect and eliminate the nonorthogonality error in real time. This method can be simply realized by means of the digital logic device, because it does not invoke trigonometric functions and inverse trigonometric functions. And it can be widely used in the bidirectional subdivision systems of a Moire fringe and other optical instruments.

  9. Real-time detection and elimination of nonorthogonality error in interference fringe processing.

    PubMed

    Hu, Haijiang; Zhang, Fengdeng

    2011-05-20

    In the measurement system of interference fringe, the nonorthogonality error is a main error source that influences the precision and accuracy of the measurement system. The detection and elimination of the error has been an important target. A novel method that only uses the cross-zero detection and the counting is proposed to detect and eliminate the nonorthogonality error in real time. This method can be simply realized by means of the digital logic device, because it does not invoke trigonometric functions and inverse trigonometric functions. And it can be widely used in the bidirectional subdivision systems of a Moiré fringe and other optical instruments.

  10. 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.

  11. 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.

  12. 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.

  13. Real-time detection and data acquisition system for the left ventricular outline

    NASA Technical Reports Server (NTRS)

    Reiber, J. H. C.

    1975-01-01

    The paper describes the design and capabilities of a computer-interfaced angiocardiographic automated border recognizer for real-time detection and data acquisition regarding the left ventricular outline. The contour detection is based on a thresholding technique that uses an analog comparator to compare the video signal with a constant reference level, which can be used satisfactorily only if the brightness level is roughly constant along a ventricular border. The use of dynamic reference level is described for achieving a marked improvement by having the reference level dynamically adjusted according to local brightness levels on a line-to-line basis. Also discussed are the features of the computer interface designed and implemented for the real-time on-line storage of the obtained border coordinates. Results to date indicate that the system provides an accurate left ventricular contour even in pictures with relatively low contrast. Application of the threshold detection technique to echocardiography is briefly discussed.

  14. 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.

  15. Rapid detection of Salmonella in pet food: design and evaluation of integrated methods based on real-time PCR detection.

    PubMed

    Balachandran, Priya; Friberg, Maria; Vanlandingham, V; Kozak, K; Manolis, Amanda; Brevnov, Maxim; Crowley, Erin; Bird, Patrick; Goins, David; Furtado, Manohar R; Petrauskene, Olga V; Tebbs, Robert S; Charbonneau, Duane

    2012-02-01

    Reducing the risk of Salmonella contamination in pet food is critical for both companion animals and humans, and its importance is reflected by the substantial increase in the demand for pathogen testing. Accurate and rapid detection of foodborne pathogens improves food safety, protects the public health, and benefits food producers by assuring product quality while facilitating product release in a timely manner. Traditional culture-based methods for Salmonella screening are laborious and can take 5 to 7 days to obtain definitive results. In this study, we developed two methods for the detection of low levels of Salmonella in pet food using real-time PCR: (i) detection of Salmonella in 25 g of dried pet food in less than 14 h with an automated magnetic bead-based nucleic acid extraction method and (ii) detection of Salmonella in 375 g of composite dry pet food matrix in less than 24 h with a manual centrifugation-based nucleic acid preparation method. Both methods included a preclarification step using a novel protocol that removes food matrix-associated debris and PCR inhibitors and improves the sensitivity of detection. Validation studies revealed no significant differences between the two real-time PCR methods and the standard U.S. Food and Drug Administration Bacteriological Analytical Manual (chapter 5) culture confirmation method.

  16. Signal Detection of Adverse Drug Reaction of Amoxicillin Using the Korea Adverse Event Reporting System Database.

    PubMed

    Soukavong, Mick; Kim, Jungmee; Park, Kyounghoon; Yang, Bo Ram; Lee, Joongyub; Jin, Xue Mei; Park, Byung Joo

    2016-09-01

    We conducted pharmacovigilance data mining for a β-lactam antibiotics, amoxicillin, and compare the adverse events (AEs) with the drug labels of 9 countries including Korea, USA, UK, Japan, Germany, Swiss, Italy, France, and Laos. We used the Korea Adverse Event Reporting System (KAERS) database, a nationwide database of AE reports, between December 1988 and June 2014. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-AE pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was defined as a signal. The KAERS database contained a total of 807,582 AE reports, among which 1,722 reports were attributed to amoxicillin. Among the 192,510 antibiotics-AE pairs, the number of amoxicillin-AE pairs was 2,913. Among 241 AEs, 52 adverse events were detected as amoxicillin signals. Comparing the drug labels of 9 countries, 12 adverse events including ineffective medicine, bronchitis, rhinitis, sinusitis, dry mouth, gastroesophageal reflux, hypercholesterolemia, gastric carcinoma, abnormal crying, induration, pulmonary carcinoma, and influenza-like symptoms were not listed on any of the labels of nine countries. In conclusion, we detected 12 new signals of amoxicillin which were not listed on the labels of 9 countries. Therefore, it should be followed by signal evaluation including causal association, clinical significance, and preventability.

  17. 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

  18. Detections of Planets in Binaries Through the Channel of Chang–Refsdal Gravitational Lensing Events

    NASA Astrophysics Data System (ADS)

    Han, Cheongho; Shin, In-Gu; Jung, Youn Kil

    2017-02-01

    Chang–Refsdal (C–R) lensing, which refers to the gravitational lensing of a point mass perturbed by a constant external shear, provides a good approximation in describing lensing behaviors of either a very wide or a very close binary lens. C–R lensing events, which are identified by short-term anomalies near the peak of high-magnification lensing light curves, are routinely detected from lensing surveys, but not much attention is paid to them. In this paper, we point out that C–R lensing events provide an important channel to detect planets in binaries, both in close and wide binary systems. Detecting planets through the C–R lensing event channel is possible because the planet-induced perturbation occurs in the same region of the C–R lensing-induced anomaly and thus the existence of the planet can be identified by the additional deviation in the central perturbation. By presenting the analysis of the actually observed C–R lensing event OGLE-2015-BLG-1319, we demonstrate that dense and high-precision coverage of a C–R lensing-induced perturbation can provide a strong constraint on the existence of a planet in a wide range of planet parameters. The sample of an increased number of microlensing planets in binary systems will provide important observational constraints in giving shape to the details of planet formation, which have been restricted to the case of single stars to date.

  19. [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.

  20. Taqman real-time PCR assays for rapid detection of avian pathogenic Escherichia coli isolates.

    PubMed

    Ikuta, Nilo; De Oliveira Solla Sobral, Fabiana; Lehmann, Fernanda Kieling Moreira; da Silveira, Proença Vinicius; de Carli, Silvia; Casanova, Yara Silva; Celmer, Álvaro José; Fonseca, André Salvador Kazantzi; Lunge, Vagner Ricardo

    2014-12-01

    Avian pathogenic Escherichia coli (APEC) isolates are currently differentiated from nonpathogenic strains by classical PCR of virulence genes. This study improves the detection of the five main virulence genes used for APEC detection with the development of duplex and single Taqman real-time PCR to these targets. Primers and probes targeted to ompT, hlyF, iroN, iutA, and iss genes were designed and used in the implementation of single (iss) and duplex (hlyF/ompT and iroN/iutA) Taqman PCR assays. All five virulence genes of E coli strains were successfully detected by classical and Taqman real-time (single and duplex) PCR. A panel of 111 E coli isolates, obtained from avian samples collected in different Brazilian regions between 2010 and 2011, were further tested by both assays. Complete agreement was observed in the detection of four genes, ompT, hlyF, iron, iutA, but not for iss. This issue was addressed by combining the forward primer of the classical PCR to the new iss reverse primer and probe, resulting in complete agreement for all five genes. In total, 61 (55%) Brazilian E. coli isolates were detected as APEC, and the remaining 50 (45%) as avian fecal E. coli (AFEC). In conclusion, classical and Taqman real-time PCR presented exactly the same analytical performance for the differentiation of APEC and AFEC isolates. The developed real-time Taqman PCR assays could be used for the detection and differentiation of APEC isolates.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Exploring the Limits of Waveform Correlation Event Detection as Applied to Three Earthquake Aftershock Sequences

    NASA Astrophysics Data System (ADS)

    Young, C. J.; Carr, D.; Resor, M.; Duffey, S.

    2009-12-01

    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

  7. Wave-induced burst precipitation events detected with a digital ionosonde

    SciTech Connect

    Jarvis, M.J.; Smith, A.J. ); Berkey, F.T. ); Carpenter, D.L. )

    1990-01-01

    Initial results are presented from two methods whereby burst precipitation events in the lower ionosphere, almost certainly induced by VLF wave-particle interactions in the magnetosphere, have been detected using a ground-based digital ionosonde. In the first method, HF echoes are received above the critical frequency of the surrounding plasma; particle energies and the location and extent of the plasma enhancement may be deduced. In the second method, a rapid decrease in the phase of ionospheric echoes is observed due to refractive index changes along the echo path; particle energies, the duration of the precipitation event and the precipitation energy flux can be estimated.

  8. Composite Event Specification and Detection for Supporting Active Capability in an OODBMS: Semantics Architecture and Implementation.

    DTIC Science & Technology

    1995-03-01

    For all outgoing edges i from ’n’ propagate parameters in node ’n’ to the nodei connected by edge i activate-operator-node( nodej ); Delete propagated...El E2 Figure 6: Detection of X in recent mode PROCEDURE activate-operator-node( nodej ) /* Recent Context */ CASE nodei is of type a primitive or...composite event has been signalled to nodej */ AND(E1, E2): if left event el is signalled if E2’s list is not empty Pass <e2, el> to the parent Replace el in

  9. Detecting adverse drug events in discharge summaries using variations on the simple Bayes model.

    PubMed

    Visweswaran, Shyam; Hanbury, Paul; Saul, Melissa; Cooper, Gregory F

    2003-01-01

    Detection and prevention of adverse events and, in particular, adverse drug events (ADEs), is an important problem in health care today. We describe the implementation and evaluation of four variations on the simple Bayes model for identifying ADE-related discharge summaries. Our results show that these probabilistic techniques achieve an ROC curve area of up to 0.77 in correctly determining which patient cases should be assigned an ADE-related ICD-9-CM code. These results suggest a potential for these techniques to contribute to the development of an automated system that helps identify ADEs, as a step toward further understanding and preventing them.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Inclusivity, exclusivity and limit of detection of commercially available real-time PCR assays for the detection of Salmonella.

    PubMed

    Margot, H; Stephan, R; Guarino, S; Jagadeesan, B; Chilton, D; O'Mahony, E; Iversen, C

    2013-08-01

    The traditional cultural detection of Salmonella spp. is both time- and labour-intensive. Salmonella is often a release criterion for the food industry and time to result is therefore an important factor. Storage of finished products and raw materials can be costly and may adversely impact available shelf-life. The application of real-time PCR for the detection of Salmonella spp. in food samples enables a potential time-saving of up to four days. The advancement of real-time PCR coupled with the development of commercially available systems in different formats has made this technology accessible for laboratories in an industrial environment. Ideally these systems are reliable and rapid as well as easy to use. The current study represents a comparative evaluation of seven commercial real-time PCR systems for the detection of Salmonella. Forty-nine target and twenty-nine non-target strains were included in the study to assess inclusivity and exclusivity. The limit of detection for each of the method was determined in four different food products. All systems evaluated were able to correctly identify the 49 Salmonella strains. Nevertheless, false positive results (Citrobacter spp.) were obtained with four of the seven systems. In milk powder and bouillon powder, the limit of detection was similar for all systems, suggesting a minimal matrix effect with these samples. Conversely, for black tea and cocoa powder some systems were prone to inhibition from matrix components. Up to 100% of the samples were inhibited using the proprietary extracts but inhibition could be reduced considerably by application of a DNA clean-up kit.

  18. Evaluation of accelerometer-based fall detection algorithms on real-world falls.

    PubMed

    Bagalà, Fabio; Becker, Clemens; Cappello, Angelo; Chiari, Lorenzo; Aminian, Kamiar; Hausdorff, Jeffrey M; Zijlstra, Wiebren; Klenk, Jochen

    2012-01-01

    Despite extensive preventive efforts, falls continue to be a major source of morbidity and mortality among elderly. Real-time detection of falls and their urgent communication to a telecare center may enable rapid medical assistance, thus increasing the sense of security of the elderly and reducing some of the negative consequences of falls. Many different approaches have been explored to automatically detect a fall using inertial sensors. Although previously published algorithms report high sensitivity (SE) and high specificity (SP), they have usually been tested on simulated falls performed by healthy volunteers. We recently collected acceleration data during a number of real-world falls among a patient population with a high-fall-risk as part of the SensAction-AAL European project. The aim of the present study is to benchmark the performance of thirteen published fall-detection algorithms when they are applied to the database of 29 real-world falls. To the best of our knowledge, this is the first systematic comparison of fall detection algorithms tested on real-world falls. We found that the SP average of the thirteen algorithms, was (mean ± std) 83.0% ± 30.3% (maximum value = 98%). The SE was considerably lower (SE = 57.0% ± 27.3%, maximum value = 82.8%), much lower than the values obtained on simulated falls. The number of false alarms generated by the algorithms during 1-day monitoring of three representative fallers ranged from 3 to 85. The factors that affect the performance of the published algorithms, when they are applied to the real-world falls, are also discussed. These findings indicate the importance of testing fall-detection algorithms in real-life conditions in order to produce more effective automated alarm systems with higher acceptance. Further, the present results support the idea that a large, shared real-world fall database could, potentially, provide an enhanced understanding of the fall process and the information needed to design and

  19. An algorithm to detect low incidence arrhythmic events in electrocardiographic records from ambulatory patients.

    PubMed

    Hungenahally, S K; Willis, R J

    1994-11-01

    An algorithm was devised to detect low incidence arrhythmic events in electrocardiograms obtained during ambulatory monitoring. The algorithm incorporated baseline correction and R wave detection. The RR interval was used to identify tachycardia, bradycardia, and premature ventricular beats. Only a few beats before and after the arrhythmic event were stored. The software was evaluated on a prototype hardware system which consisted of an Intel 86/30 single board computer with a suitable analog pre-processor and an analog to digital converter. The algorithm was used to determine the incidence and type of arrhythmia in records from an ambulatory electrocardiogram (ECG) database and from a cardiac exercise laboratory. These results were compared to annotations on the records which were assumed to be correct. Standard criteria used previously to evaluate algorithms designed for arrhythmia detection were sensitivity, specificity, and diagnostic accuracy. Sensitivities ranging from 77 to 100%, specificities from 94 to 100%, and diagnostic accuracies from 92 to 100% were obtained on the different data sets. These results compare favourably with published results based on more elaborate algorithms. By circumventing the need to make a continuous record of the ECG, the algorithm could form the basis for a compact monitoring device for the detection of arrhythmic events which are so infrequent that standard 24-h Holter monitoring is insufficient.

  20. 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.

  1. 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

  2. [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.

  3. Development of highly sensitive handheld device for real-time detection of bacteria in food

    NASA Astrophysics Data System (ADS)

    Zhang, Kewei; Zhang, Anxue; Fu, Liling; Chin, Bryan A.; Cheng, Z.-Y.

    2010-04-01

    To ensure the safety of food, a detection device, which can detect/monitor the present of bacteria in a real-time manner and can be easily used for in-field tests, is highly desirable. Recently, magnetostrictive particles (MSPs) as a new type of high-performance biosensor have been developed. The detection of various bacteria and spores in food with high sensitivity has already been experimentally demonstrated. To fully use the technique for food safety, two miniaturized interrogation systems based on frequency-domain and time-domain technique are developed to fabricate a handheld detection device. The detection of Salmonella typhimurium (S. typhimurium) in liquid using a time-domain based interrogation system was demonstrated.

  4. Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions

    PubMed Central

    Li, Zuojin; Li, Shengbo Eben; Li, Renjie; Cheng, Bo; Shi, Jinliang

    2017-01-01

    This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEn) features from fixed sliding windows on real-time steering wheel angles time series. After that, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: “wake” and “drowsy”. The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the “awake” state, and 15.15% false detections of the “drowsy” state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue. PMID:28257094

  5. Duplex real-time PCR assay for rapid detection of ampicillin-resistant Enterococcus faecium.

    PubMed

    Mohn, Stein Christian; Ulvik, Arve; Jureen, Roland; Willems, Rob J L; Top, Janetta; Leavis, Helen; Harthug, Stig; Langeland, Nina

    2004-02-01

    Rapid and accurate identification of carriers of resistant microorganisms is an important aspect of efficient infection control in hospitals. Traditional identification methods of antibiotic-resistant bacteria usually take at least 3 to 4 days after sampling. A duplex real-time PCR assay was developed for rapid detection of ampicillin-resistant Enterococcus faecium (ARE). Primers and probes that are used in this assay specifically detected the D-Ala-D-Ala ligase gene of E. faecium and the modified penicillin-binding protein 5 gene (pbp5) carrying the Glu-to-Val substitution at position 629 (Val-629) in a set of 129 tested E. faecium strains with known pbp5 sequence. Presence of the Val-629 in the strain set from 11 different countries was highly correlated with ampicillin resistance. In a screening of hospitalized patients, the real-time PCR assay yielded a sensitivity and a specificity for the detection of ARE colonization of 95% and 100%, respectively. The results were obtained 4 h after samples were harvested from overnight broth of rectal swab samples, identifying both species and the resistance marker mutation in pbp5. This novel assay reliably identifies ARE 2 to 3 days more quickly than traditional culture methods, thereby increasing laboratory throughput, making it useful for rectal screening of ARE. The assay demonstrates the advantages of real-time PCR for detection of nosocomial pathogens.

  6. Simultaneous multiple target detection in real-time loop-mediated isothermal amplification.

    PubMed

    Tanner, Nathan A; Zhang, Yinhua; Evans, Thomas C

    2012-08-01

    Loop-mediated isothermal amplification (LAMP) is a rapid and reliable sequence-specific isothermal nucleic acid amplification technique. To date, all reported real-time detection methods for LAMP have been restricted to single targets, limiting the utility of this technique. Here, we adapted standard LAMP primers to contain a quencher-fluorophore duplex region that upon strand separation results in a gain of fluorescent signal. This approach permitted the real-time detection of 1-4 target sequences in a single LAMP reaction tube utilizing a standard real-time fluorimeter. The methodology was highly reproducible and sensitive, detecting below 100 copies of human genomic DNA. It was also robust, with a 7-order of magnitude dynamic range of detectable targets. Furthermore, using a new strand-displacing DNA polymerase or its warm-start version, Bst 2.0 or Bst 2.0 WarmStart DNA polymerases, resulted in 50% faster amplification signals than wild-type Bst DNA polymerase, large fragment in this new multiplex LAMP procedure. The coupling of this new multiplex technique with next generation isothermal DNA polymerases should increase the utility of the LAMP method for molecular diagnostics.

  7. Real-time reporting of baleen whale passive acoustic detections from ocean gliders.

    PubMed

    Baumgartner, Mark F; Fratantoni, David M; Hurst, Thomas P; Brown, Moira W; Cole, Tim V N; Van Parijs, Sofie M; Johnson, Mark

    2013-09-01

    In the past decade, much progress has been made in real-time passive acoustic monitoring of marine mammal occurrence and distribution from autonomous platforms (e.g., gliders, floats, buoys), but current systems focus primarily on a single call type produced by a single species, often from a single location. A hardware and software system was developed to detect, classify, and report 14 call types produced by 4 species of baleen whales in real time from ocean gliders. During a 3-week deployment in the central Gulf of Maine in late November and early December 2012, two gliders reported over 25,000 acoustic detections attributed to fin, humpback, sei, and right whales. The overall false detection rate for individual calls was 14%, and for right, humpback, and fin whales, false predictions of occurrence during 15-min reporting periods were 5% or less. Transmitted pitch tracks--compact representations of sounds--allowed unambiguous identification of both humpback and fin whale song. Of the ten cases when whales were sighted during aerial or shipboard surveys and a glider was within 20 km of the sighting location, nine were accompanied by real-time acoustic detections of the same species by the glider within ±12 h of the sighting time.

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

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Yoon, Seung-Chul; Windham, William R.; Lawrence, Kurt C.; Heitschmidt, G. W.; Kim, Moon S.; Chao, Kaunglin

    2010-04-01

    The ARS multispectral imaging system with three-band common aperture camera was able to inspect fecal contaminants in real-time mode during poultry processing. Recent study has demonstrated several image processing methods including binning, cuticle removal filter, median filter, and morphological analysis in real-time mode could remove false positive errors. The ARS research groups and their industry partner are now merging the fecal detection and systemically disease detection systems onto a common platform using line-scan hyperspectral imaging system. This system will aid in commercialization by creating one hyperspectral imaging system with user-defined wavelengths that can be installed in different locations of the processing line to solve significant food safety problems. Therefore, this research demonstrated the feasibility of line-scan hyperspectral imaging system in terms of processing speed and detection accuracy for a real-time, on-line fecal detection at current processing speed (140 birds per minute) of commercial poultry plant. The newly developed line-scan hyperspectral imaging system could improve Food Safety Inspection Service (FSIS)'s poultry safety inspection program significantly.

  9. Development of a multiplex real-time PCR assay for the detection of ruminant DNA.

    PubMed

    Ekins, Jason; Peters, Sharla M; Jones, Yolanda L; Swaim, Heidi; Ha, Tai; La Neve, Fabio; Civera, Tiziana; Blackstone, George; Vickery, Michael C L; Marion, Bill; Myers, Michael J; Yancy, Haile F

    2012-06-01

    The U.S. Food and Drug Administration (FDA) has previously validated a real-time PCR-based assay that is currently being used by the FDA and several state laboratories as the official screening method. Due to several shortcomings to the assay, a multiplex real-time PCR assay (MRTA) to detect three ruminant species (bovine, caprine, and ovine) was developed using a lyophilized bead design. The assay contained two primer or probe sets: a "ruminant" set to detect bovine-, caprine-, and ovine-derived materials and a second set to serve as an internal PCR control, formatted using a lyophilized bead design. Performance of the assay was evaluated against stringent acceptance criteria developed by the FDA's Center for Veterinary Medicine's Office of Research. The MRTA for the detection of ruminant DNA passed the stringent acceptance criteria for specificity, sensitivity, and selectivity. The assay met sensitivity and reproducibility requirements by detecting 30 of 30 complete feed samples fortified with meals at 0.1 % (wt/wt) rendered material from each of the three ruminant species. The MRTA demonstrated 100 % selectivity (0.0 % false positives) for negative controls throughout the assessment period. The assay showed ruggedness in both sample selection and reagent preparation. Second and third analyst trials confirmed the quality of the written standard operating procedure with consistency of results. An external laboratory participating in a peer-verification trial demonstrated 100 % specificity in identifying bovine meat and bone meal, while exhibiting a 0.03 % rate of false positives. The assay demonstrated equal levels of sensitivity and reproducibility compared with the FDA's current validated real-time PCR assay. The assay detected three prohibited species in less than 1.5 h of total assay time, a significant improvement over the current real-time assay. These results demonstrated this assay's suitability for routine regulatory use both as a primary screening tool

  10. Synthesis of hydrophobic nanoparticles for real-time lysozyme detection using surface plasmon resonance sensor.

    PubMed

    Saylan, Yeşeren; Yılmaz, Fatma; Derazshamshir, Ali; Yılmaz, Erkut; Denizli, Adil

    2017-03-21

    Diagnostic biomarkers such as proteins and enzymes are generally hard to detect because of the low abundance in biological fluids. To solve this problem, the advantages of surface plasmon resonance (SPR) and nanomaterial technologies have been combined. The SPR sensors are easy to prepare, no requirement of labelling and can be detected in real time. In addition, they have high specificity and sensitivity with low cost. The nanomaterials have also crucial functions such as efficiency improvement, selectivity, and sensitivity of the detection systems. In this report, an SPR-based sensor is developed to detect lysozyme with hydrophobic poly (N-methacryloyl-(L)-phenylalanine) (PMAPA) nanoparticles. The SPR sensor was first characterized by attenuated total reflection-Fourier transform infrared, atomic force microscope, and water contact angle measurements and performed with aqueous lysozyme solutions. Various concentrations of lysozyme solution were used to calculate kinetic and affinity coefficients. The equilibrium and adsorption isotherm models of interactions between lysozyme solutions and SPR sensor were determined and the maximum reflection, association, and dissociation constants were calculated by Langmuir model as 4.87, 0.019 nM(-1) , and 54 nM, respectively. The selectivity studies of SPR sensor were investigated with competitive agents, hemoglobin, and myoglobin. Also, the SPR sensor was used four times in adsorption/desorption/recovery cycles and results showed that, the combination of optical SPR sensor with hydrophobic ionizable PMAPA nanoparticles in one mode enabled the detection of lysozyme molecule with high accuracy, good sensivity, real-time, label-free, and a low-detection limit of 0.66 nM from lysozyme solutions. Lysozyme detection in a real sample was performed by using chicken egg white to evaluate interfering molecules present in the medium.

  11. 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.

  12. 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.

  13. Towards real-time change detection in videos based on existing 3D models

    NASA Astrophysics Data System (ADS)

    Ruf, Boitumelo; Schuchert, Tobias

    2016-10-01

    Image based change detection is of great importance for security applications, such as surveillance and reconnaissance, in order to find new, modified or removed objects. Such change detection can generally be performed by co-registration and comparison of two or more images. However, existing 3d objects, such as buildings, may lead to parallax artifacts in case of inaccurate or missing 3d information, which may distort the results in the image comparison process, especially when the images are acquired from aerial platforms like small unmanned aerial vehicles (UAVs). Furthermore, considering only intensity information may lead to failures in detection of changes in the 3d structure of objects. To overcome this problem, we present an approach that uses Structure-from-Motion (SfM) to compute depth information, with which a 3d change detection can be performed against an existing 3d model. Our approach is capable of the change detection in real-time. We use the input frames with the corresponding camera poses to compute dense depth maps by an image-based depth estimation algorithm. Additionally we synthesize a second set of depth maps, by rendering the existing 3d model from the same camera poses as those of the image-based depth map. The actual change detection is performed by comparing the two sets of depth maps with each other. Our method is evaluated on synthetic test data with corresponding ground truth as well as on real image test data.

  14. Detection of real-time dynamics of drug-target interactions by ultralong nanowalls.

    PubMed

    Menzel, Andreas; Gübeli, Raphael J; Güder, Firat; Weber, Wilfried; Zacharias, Margit

    2013-11-07

    Detecting drug-target interactions in real-time is a powerful approach for drug discovery and analytics. We show here for the first time the ultra fast electrical real-time detection and quantification of antibiotics using a novel biohybrid nanosensor. The biomolecular sensing is performed on ultralong (mm range) high aspect ratio nanowall (50 nm width) surfaces functionalized with operator DNA tetO which is specifically bound by the sensor protein TetR. This sensor protein is released from the operator DNA in a dose dependent manner by exposing the device functionalized with this bound DNA-protein complex to tetracycline antibiotics. As a result, the electrical conductance is accordingly modulated by these surface net charge changes. The switching mechanism of sensor proteins attached at the functionalized surfaces and releasing them again by antibiotics is demonstrated. With the here presented device the detection limit is below the limits of prevailing detection methods. Moreover, the study is extended to detect antibiotic residues in spiked organic milk from cows far below the maximum residual level of the European Union. In spiked milk samples a detection limit for tetracycline concentrations in the 100 fM level was achieved. The nanowall devices are fabricated by atomic layer deposition-based spacer lithography on full wafer scale which is a simple approach capable for mass production.

  15. Real-time detection of generic objects using objectness estimation and locally adaptive regression kernels matching

    NASA Astrophysics Data System (ADS)

    Zheng, Zhihui; Gao, Lei; Xiao, Liping; Zhou, Bin; Gao, Shibo

    2015-12-01

    Our purpose is to develop a detection algorithm capable of searching for generic interest objects in real time without large training sets and long-time training stages. Instead of the classical sliding window object detection paradigm, we employ an objectness measure to produce a small set of candidate windows efficiently using Binarized Normed Gradients and a Laplacian of Gaussian-like filter. We then extract Locally Adaptive Regression Kernels (LARKs) as descriptors both from a model image and the candidate windows which measure the likeness of a pixel to its surroundings. Using a matrix cosine similarity measure, the algorithm yields a scalar resemblance map, indicating the likelihood of similarity between the model and the candidate windows. By employing nonparametric significance tests and non-maxima suppression, we detect the presence of objects similar to the given model. Experiments show that the proposed detection paradigm can automatically detect the presence, the number, as well as location of similar objects to the given model. The high quality and efficiency of our method make it suitable for real time multi-category object detection applications.

  16. Use of a clinical event monitor to prevent and detect medication errors.

    PubMed Central

    Payne, T. H.; Savarino, J.; Marshall, R.; Hoey, C. T.

    2000-01-01

    Errors in health care facilities are common and often unrecognized. We have used our clinical event monitor to prevent and detect medication errors by scrutinizing electronic messages sent to it when any medication order is written in our facility. A growing collection of medication safety rules covering dose limit errors, laboratory monitoring, and other topics may be applied to each medication order message to provide an additional layer of protection beyond existing order checks, reminders, and alerts available within our computer-based record system. During a typical day the event monitor receives 4802 messages, of which 4719 pertain to medication orders. We have found the clinical event monitor to be a valuable tool for clinicians and quality management groups charged with improving medication safety. PMID:11079962

  17. 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.

  18. FACS-style detection for real-time cell viscoelastic cytometry.

    PubMed

    Kasukurti, A; Eggleton, C D; Desai, S A; Marr, D W M

    Cell mechanical properties have been established as a label-free biophysical marker of cell viability and health; however, real-time methods with significant throughput for accurately and non-destructively measuring these properties remain widely unavailable. Without appropriate labels for use with fluorescence activated cell sorters (FACS), easily implemented real-time technology for tracking cell-level mechanical properties remains a current need. Employing modulated optical forces and enabled by a low-dimensional FACS-style detection method introduced here, we present a viscoelasticity cytometer (VC) capable of real-time and continuous measurements. We demonstrate the utility of this approach by tracking the high-frequency cell physical properties of populations of chemically-modified cells at rates of ~ 1 s(-1) and explain observations within the context of a simple theoretical model.

  19. Assessment and validation of a simple automated method for the detection of gait events and intervals.

    PubMed

    Ghoussayni, Salim; Stevens, Christopher; Durham, Sally; Ewins, David

    2004-12-01

    A simple and rapid automatic method for detection of gait events at the foot could speed up and possibly increase the repeatability of gait analysis and evaluations of treatments for pathological gaits. The aim of this study was to compare and validate a kinematic-based algorithm used in the detection of four gait events, heel contact, heel rise, toe contact and toe off. Force platform data is often used to obtain start and end of contact phases, but not usually heel rise and toe contact events. For this purpose synchronised kinematic, kinetic and video data were captured from 12 healthy adult subjects walking both barefoot and shod at slow and normal self-selected speeds. The data were used to determine the gait events using three methods: force, visual inspection and algorithm methods. Ninety percent of all timings given by the algorithm were within one frame (16.7 ms) when compared to visual inspection. There were no statistically significant differences between the visual and algorithm timings. For both heel and toe contact the differences between the three methods were within 1.5 frames, whereas for heel rise and toe off the differences between the force on one side and the visual and algorithm on the other were higher and more varied (up to 175 ms). In addition, the algorithm method provided the duration of three intervals, heel contact to toe contact, toe contact to heel rise and heel rise to toe off, which are not readily available from force platform data. The ability to automatically and reliably detect the timings of these four gait events and three intervals using kinematic data alone is an asset to clinical gait analysis.

  20. Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

    2013-05-01

    It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

  1. Residual Events during Use of CPAP: Prevalence, Predictors, and Detection Accuracy

    PubMed Central

    Reiter, Joel; Zleik, Bashar; Bazalakova, Mihaela; Mehta, Pankaj; Thomas, Robert Joseph

    2016-01-01

    Study Objectives: To assess the frequency, severity, and determinants of residual respiratory events during continuous positive airway therapy (CPAP) for obstructive sleep apnea (OSA) as determined by device output. Methods: Subjects were consecutive OSA patients at an American Academy of Sleep Medicine accredited multidisciplinary sleep center. Inclusion criteria included CPAP use for a minimum of 3 months, and a minimum nightly use of 4 hours. Compliance metrics and waveform data from 217 subjects were analyzed retrospectively. Events were scored manually when there was a clear reduction of amplitude (≥ 30%) or flow-limitation with 2–3 larger recovery breaths. Automatically detected versus manually scored events were subjected to statistical analyses included Bland-Altman plots, correlation coefficients, and logistic regression exploring predictors of residual events. Results: The mean patient age was 54.7 ± 14.2 years; 63% were males. All patients had a primary diagnosis of obstructive sleep apnea, 26% defined as complex sleep apnea. Residual flow measurement based apnea-hypopnea index (AHIFLOW) > 5, 10, and 15/h was seen in 32.3%, 9.7%, and 1.8% vs. 60.8%, 23%, and 7.8% of subjects based on automated vs. manual scoring of waveform data. Automatically detected versus manually scored average AHIFLOW was 4.4 ± 3.8 vs. 7.3 ± 5.1 per hour. In a logistic regression analysis, the only predictors for a manual AHIFLOW > 5/h were the absolute central apnea index (CAI), (odds ratio [OR]: 1.5, p: 0.01, CI: 1.1–2.0), or using a CAI threshold of 5/h of sleep (OR: 5.0, p: < 0.001, CI: 2.2–13.8). For AHIFLOW > 10/h, the OR was 1.14, p: 0.03 (CI: 1.1–1.3) per every CAI unit of 1/hour. Conclusions: Residual respiratory events are common during CPAP treatment, may be missed by automated device detection and predicted by a high central apnea index on the baseline diagnostic study. Direct visualization of flow data is generally available and improves detection

  2. 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

  3. Real-time forecasting and predictability of catastrophic failure events: from rock failure to volcanoes and earthquakes

    NASA Astrophysics Data System (ADS)

    Main, I. G.; Bell, A. F.; Naylor, M.; Atkinson, M.; Filguera, R.; Meredith, P. G.; Brantut, N.

    2012-12-01

    Accurate prediction of catastrophic brittle failure in rocks and in the Earth presents a significant challenge on theoretical and practical grounds. The governing equations are not known precisely, but are known to produce highly non-linear behavior similar to those of near-critical dynamical systems, with a large and irreducible stochastic component due to material heterogeneity. In a laboratory setting mechanical, hydraulic and rock physical properties are known to change in systematic ways prior to catastrophic failure, often with significant non-Gaussian fluctuations about the mean signal at a given time, for example in the rate of remotely-sensed acoustic emissions. The effectiveness of such signals in real-time forecasting has never been tested before in a controlled laboratory setting, and previous work has often been qualitative in nature, and subject to retrospective selection bias, though it has often been invoked as a basis in forecasting natural hazard events such as volcanoes and earthquakes. Here we describe a collaborative experiment in real-time data assimilation to explore the limits of predictability of rock failure in a best-case scenario. Data are streamed from a remote rock deformation laboratory to a user-friendly portal, where several proposed physical/stochastic models can be analysed in parallel in real time, using a variety of statistical fitting techniques, including least squares regression, maximum likelihood fitting, Markov-chain Monte-Carlo and Bayesian analysis. The results are posted and regularly updated on the web site prior to catastrophic failure, to ensure a true and and verifiable prospective test of forecasting power. Preliminary tests on synthetic data with known non-Gaussian statistics shows how forecasting power is likely to evolve in the live experiments. In general the predicted failure time does converge on the real failure time, illustrating the bias associated with the 'benefit of hindsight' in retrospective analyses

  4. Using Structured Telephone Follow-up Assessments to Improve Suicide-related Adverse Event Detection

    PubMed Central

    Arias, Sarah A.; Zhang, Zi; Hillerns, Carla; Sullivan, Ashley F.; Boudreaux, Edwin D.; Miller, Ivan; Camargo, Carlos A.

    2014-01-01

    Adverse event (AE) detection and reporting practices were compared during the first phase of the Emergency Department Safety Assessment and Follow-up Evaluation (ED-SAFE), a suicide intervention study. Data were collected using a combination of chart reviews and structured telephone follow-up assessments post-enrollment. Beyond chart reviews, structured telephone follow-up assessments identified 45% of the total AEs in our study. Notably, detection of suicide attempts significantly varied by approach with 53 (18%) detected by chart review, 173 (59%) by structured telephone follow-up assessments, and 69 (23%) marked as duplicates. Findings provide support for utilizing multiple methods for more robust AE detection in suicide research. PMID:24588679

  5. [Detection and subgrouping of respiratory syncytial virus RNA by real-time RT-PCR].

    PubMed

    Yokoi, Hajime; Tanaka, Toshimitsu; Mizumura, Ayano; Kitahashi, Tomoko

    2012-09-01

    The TaqMan-based quantitative real-time RT-PCR assay we developed uses specific probes to identify respiratory syncytial virus (RSV) and to distinguish RSV subgroups A (RSV-A) and B (RSV-B). We selected conserved regions of the F gene as assay targets and designed new primers and TaqMan MGB probes to detect RSV-A and B. RSV-A and B control plasmids confirmed real-time reverse transcription polymerase chain reaction (RT-PCR) reactivity whose efficiency was 2.5 x 10(1) to 2.5 x 10(7) copies/tube. The assay detection limit was 10 to 10(2) times higher than that of the conventional RT-PCR assay and was equal to the nested PCR assay. No cross-reactions occurred against other respiratory viruses, including influenza virus, metapneumovirus, measles virus, coxsackievirus, enterovirus, echovirus, mumps virus, parainfluenza virus, and rhinovirus. Of 154 clinical specimens derived from subjects with acute respiratory infection and tested by using both real-time RT-PCR and nested PCR, 40 were RSV-positive in both assays. Of these, 25 were identified as RSV-A and 15 as RSV-B by both assays. There was 100% concordance in RSV subgroup identification between real-time RT-PCR and nested PCR assays. These results indicate that our real-time RT-PCR assay can be used for rapid detection, quantitative analysis and subgrouping of RSV-A and RSV-B.

  6. A Method for Automated Detection of Usability Problems from Client User Interface Events

    PubMed Central

    Saadawi, Gilan M.; Legowski, Elizabeth; Medvedeva, Olga; Chavan, Girish; Crowley, Rebecca S.

    2005-01-01

    Think-aloud usability analysis provides extremely useful data but is very time-consuming and expensive to perform because of the extensive manual video analysis that is required. We describe a simple method for automated detection of usability problems from client user interface events for a developing medical intelligent tutoring system. The method incorporates (1) an agent-based method for communication that funnels all interface events and system responses to a centralized database, (2) a simple schema for representing interface events and higher order subgoals, and (3) an algorithm that reproduces the criteria used for manual coding of usability problems. A correction factor was empirically determining to account for the slower task performance of users when thinking aloud. We tested the validity of the method by simultaneously identifying usability problems using TAU and manually computing them from stored interface event data using the proposed algorithm. All usability problems that did not rely on verbal utterances were detectable with the proposed method. PMID:16779121

  7. Temporal and Spatial Predictability of an Irrelevant Event Differently Affect Detection and Memory of Items in a Visual Sequence.

    PubMed

    Ohyama, Junji; Watanabe, Katsumi

    2016-01-01

    We examined how the temporal and spatial predictability of a task-irrelevant visual event affects the detection and memory of a visual item embedded in a continuously changing sequence. Participants observed 11 sequentially presented letters, during which a task-irrelevant visual event was either present or absent. Predictabilities of spatial location and temporal position of the event were controlled in 2 × 2 conditions. In the spatially predictable conditions, the event occurred at the same location within the stimulus sequence or at another location, while, in the spatially unpredictable conditions, it occurred at random locations. In the temporally predictable conditions, the event timing was fixed relative to the order of the letters, while in the temporally unpredictable condition; it could not be predicted from the letter order. Participants performed a working memory task and a target detection reaction time (RT) task. Memory accuracy was higher for a letter simultaneously presented at the same location as the event in the temporally unpredictable conditions, irrespective of the spatial predictability of the event. On the other hand, the detection RTs were only faster for a letter simultaneously presented at the same location as the event when the event was both temporally and spatially predictable. Thus, to facilitate ongoing detection processes, an event must be predictable both in space and time, while memory processes are enhanced by temporally unpredictable (i.e., surprising) events. Evidently, temporal predictability has differential effects on detection and memory of a visual item embedded in a sequence of images.

  8. Nanoporous niobium oxide for label-free detection of DNA hybridization events.

    PubMed

    Choi, Jinsub; Lim, Jae Hoon; Rho, Sangchul; Jahng, Deokjin; Lee, Jaeyoung; Kim, Kyung Ja

    2008-01-15

    We found that DNA probes can be immobilized on anodically prepared porous niobium oxide without a chemical modification of both the DNA probes and the substrate. By using the porous niobium oxide with a positive surface charge, DNA hybridization events are detected on the basis of the blue-shift of a maximum absorption peak in UV-vis-NIR spectroscopy. The blue-shift is ascribed to the change of surface charge upon single- or double-stranded DNA. The method does not require a label and shows high sensitivity with the detection limit of the concentration of 1nM.

  9. A multivariate based event detection method and performance comparison with two baseline methods.

    PubMed

    Liu, Shuming; Smith, Kate; Che, Han

    2015-09-01

    Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate.

  10. Development of real-time PCR for detection and quantitation of Streptococcus parauberis.

    PubMed

    Nguyen, T L; Lim, Y J; Kim, D-H; Austin, B

    2016-01-01

    Streptococcus parauberis is an increasing threat to aquaculture of olive flounder, Paralichthys olivaceus Temminck & Schlegel, in South Korea. We developed a real-time polymerase chain reaction (PCR) method using the TaqMan probe assay to detect and quantify S. parauberis by targeting the gyrB gene sequences, which are effective for molecular analysis of the genus Streptococcus. Our real-time PCR assay is capable of detecting 10 fg of genomic DNA per reaction. The intra- and interassay coefficient of variation (CV) values ranged from 0.42-1.95%, demonstrating that the assay has good reproducibility. There was not any cross-reactivity to Streptococcus iniae or to other streptococcal/lactococcal fish pathogens, such as S. agalactiae and Lactococcus garvieae, indicating that the assay is highly specific to S. parauberis. The results of the real-time PCR assay corresponded well to those of conventional culture assays for S. parauberis from inoculated tissue homogenates (r = 0.957; P < 0.05). Hence, this sensitive and specific real-time PCR is a valuable tool for diagnostic quantitation of S. parauberis in clinical samples.

  11. 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.

  12. Quantitative detection of residual porcine host cell DNA by real-time PCR.

    PubMed

    Chang, Jen-Ting; Chen, Yu-Chen; Chou, Yu-Chi; Wang, Shih-Rong

    2014-03-01

    All biological products are derived from complex living systems and are often mixed with large numbers of impurities. For reasons of safety, residual host-cell DNA must be eliminated during processing. To assay host-cell DNA content in biopharmaceutical products derived from porcine sources, this study applies the quantitative real-time polymerase chain reaction (Q-PCR) method. The optimized assay in this study is based on the pol region of the porcine endogenous retrovirus (PERV). Assay validation results demonstrate that the proposed assay has appropriate accuracy, preciseness, reproducibility, and sensitivity. Primer and probe specificity are evaluated in real-time Q-PCR reactions using genomic DNA from rabbit, mouse, cat, hamster, monkey, human cell, yeast, and Escherichia coli as templates. The sensitivity of real-time Q-PCR is determined using genomic DNA from the porcine kidney cell line. The reliable detection range is within 0.5-10(5) pg/reaction. The limit of quantitation is 500 fg. The sensitivity of the assay meets the authority criterion. Moreover, the assay is applied to determine the level of host-cell DNA in recombinant human coagulation factor IX (rhFIX) from transgenic pigs. The real-time Q-PCR assay is thus a promising new tool for quantitative detection and clearance validation of residual porcine DNA when manufacturing recombinant therapeutics.

  13. Event Detection for Hydrothermal Plumes: A case study at Grotto Vent

    NASA Astrophysics Data System (ADS)

    Bemis, K. G.; Ozer, S.; Xu, G.; Rona, P. A.; Silver, D.

    2012-12-01

    Evidence is mounting that geologic events such as volcanic eruptions (and intrusions) and earthquakes (near and far) influence the flow rates and temperatures of hydrothermal systems. Connecting such suppositions to observations of hydrothermal output is challenging, but new ongoing time series have the potential to capture such events. This study explores using activity detection, a technique modified from computer vision, to identify pre-defined events within an extended time series recorded by COVIS (Cabled Observatory Vent Imaging Sonar) and applies it to a time series, with gaps, from Sept 2010 to the present; available measurements include plume orientation, plume rise rate, and diffuse flow area at the NEPTUNE Canada Observatory at Grotto Vent, Main Endeavour Field, Juan de Fuca Ridge. Activity detection is the process of finding a pattern (activity) in a data set containing many different types of patterns. Among many approaches proposed to model and detect activities, we have chosen a graph-based technique, Petri Nets, as they do not require training data to model the activity. They use the domain expert's knowledge to build the activity as a combination of feature states and their transitions (actions). Starting from a conceptual model of how hydrothermal plumes respond to daily tides, we have developed a Petri Net based detection algorithm that identifies deviations from the specified response. Initially we assumed that the orientation of the plume would change smoothly and symmetrically in a consistent daily pattern. However, results indicate that the rate of directional changes varies. The present Petri Net detects unusually large and rapid changes in direction or amount of bending; however inspection of Figure 1 suggests that many of the events detected may be artifacts resulting from gaps in the data or from the large temporal spacing. Still, considerable complexity overlies the "normal" tidal response pattern (the data has a dominant frequency of

  14. Real-time PCR detection of aldoxime dehydratase genes in nitrile-degrading microorganisms.

    PubMed

    Dooley-Cullinane, Tríona Marie; O'Reilly, Catherine; Coffey, Lee

    2017-02-01

    Aldoxime dehydratase catalyses the conversion of aldoximes to their corresponding nitriles. Utilization of the aldoxime-nitrile metabolising enzyme pathway can facilitate the move towards a greener chemistry. In this work, a real-time PCR assay was developed for the detection of aldoxime dehydratase genes in aldoxime/nitrile metabolising microorganisms which have been purified from environmental sources. A conventional PCR assay was also designed allowing gene confirmation via sequencing. Aldoxime dehydratase genes were identified in 30 microorganisms across 11 genera including some not previously shown to harbour the gene. The assay displayed a limit of detection of 1 pg/μL DNA or 7 CFU/reaction. This real-time PCR assay should prove valuable in the high-throughput screening of micro-organisms for novel aldoxime dehydratase genes towards pharmaceutical and industrial applications.

  15. 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.

  16. 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.

  17. Application of a real-time biosensor to detect bacteria in platelet concentrates.

    PubMed

    Rotman, Boris; Cote, Mindy A

    2003-01-03

    A spore-based biosensor for detecting low levels of bacteria in real-time has been recently developed. The system (termed LEXSAS, label-free exponential signal-amplification system) exploits spore's ability to produce fluorescence when sensing neighboring bacterial cells. We studied the LEXSAS as a possible approach for identifying bacterially contaminated platelet concentrates prior to transfusion because the system offers rapid analysis, high sensitivity, and low cost. If successful, this approach could reduce the risk of morbidity and mortality from transfusion-related bacteremia and sepsis. In this study, we used the LEXSAS for detecting bacteria in platelet concentrates spiked with Bacillus cereus, Enterobacter cloacae, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, or Streptococcus pyogenes. Bacteria were separated from platelets using a 2-min procedure based on bacterial resistance to detergents and osmotic shock. The results indicate that the LEXSAS could be used to design a practical biosensor for identifying bacterially contaminated platelets in real-time.

  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. Adverse event detection (AED) system for continuously monitoring and evaluating structural health status

    NASA Astrophysics Data System (ADS)

    Yun, Jinsik; Ha, Dong Sam; Inman, Daniel J.; Owen, Robert B.

    2011-03-01

    Structural damage for spacecraft is mainly due to impacts such as collision of meteorites or space debris. We present a structural health monitoring (SHM) system for space applications, named Adverse Event Detection (AED), which integrates an acoustic sensor, an impedance-based SHM system, and a Lamb wave SHM system. With these three health-monitoring methods in place, we can determine the presence, location, and severity of damage. An acoustic sensor continuously monitors acoustic events, while the impedance-based and Lamb wave SHM systems are in sleep mode. If an acoustic sensor detects an impact, it activates the impedance-based SHM. The impedance-based system determines if the impact incurred damage. When damage is detected, it activates the Lamb wave SHM system to determine the severity and location of the damage. Further, since an acoustic sensor dissipates much less power than the two SHM systems and the two systems are activated only when there is an acoustic event, our system reduces overall power dissipation significantly. Our prototype system demonstrates the feasibility of the proposed concept.

  20. Early detection of cell activation events by means of attenuated total reflection Fourier transform infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Titus, Jitto; Filfili, Chadi; Hilliard, Julia K.; Ward, John A.; Unil Perera, A. G.

    2014-06-01

    Activation of Jurkat T-cells in culture following treatment with anti-CD3 (Cluster of Differentiation 3) antibody is detectable by interrogating the treated T-cells using the Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy technique. Cell activation was detected within 75 min after the cells encountered specific immunoglobulin molecules. Spectral markers noted following ligation of the CD3 receptor with anti CD3 antibody provides proof-of-concept that ATR-FTIR spectroscopy is a sensitive measure of molecular events subsequent to cells interacting with anti-CD3 Immunoglobulin G. The resultant ligation of the CD3 receptor results in the initiation of well defined, specific signaling pathways that parallel the measurable molecular events detected using ATR-FTIR. Paired t-test with post-hoc Bonferroni corrections for multiple comparisons has resulted in the identification of statistically significant spectral markers (p < 0.02) at 1367 and 1358 cm-1. Together, these data demonstrate that early treatment-specific cellular events can be measured by ATR-FTIR and that this technique can be used to identify specific agents via the responses of the cell biosensor at different time points postexposure.

  1. Development of quantitative real-time PCR for detection and enumeration of Enterobacteriaceae.

    PubMed

    Takahashi, Hajime; Saito, Rumi; Miya, Satoko; Tanaka, Yuichiro; Miyamura, Natsumi; Kuda, Takashi; Kimura, Bon

    2017-04-04

    The family Enterobacteriaceae, members of which are widely distributed in the environment, includes many important human pathogens. In this study, a rapid real-time PCR method targeting rplP, coding for L16 protein, a component of the ribosome large subunit, was developed for enumerating Enterobacteriaceae strains, and its efficiency was evaluated using naturally contaminated food products. The rplP-targeted real-time PCR amplified Enterobacteriaceae species with Ct values of 14.0-22.8, whereas the Ct values for non-Enterobacteriaceae species were >30, indicating the specificity of this method for the Enterobacteriaceae. Using a calibration curve of Ct=-3.025 (log CFU/g)+37.35, which was calculated from individual plots of the cell numbers in different concentrations of 5 Enterobacteriaceae species, the rplP-targeted real-time PCR was applied to 51 food samples. A <1log difference between the real-time PCR and culture methods was obtained in a majority of the food samples (81.8%), with good correlation (r(2)=0.8285). This study demonstrated that the rplP-targeted real-time PCR method could detect and enumerate Enterobacteriaceae species in foods rapidly and accurately, and therefore, it can be used for the microbiological risk analysis of foods.

  2. Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System.

    PubMed

    Wang, Yu-Long; Shi, Peng; Lim, Cheng-Chew; Liu, Yuan

    2016-12-01

    This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.

  3. Method for the depth corrected detection of ionizing events from a co-planar grids sensor

    DOEpatents

    De Geronimo, Gianluigi; Bolotnikov, Aleksey E.; Carini, Gabriella

    2009-05-12

    A method for the detection of ionizing events utilizing a co-planar grids sensor comprising a semiconductor substrate, cathode electrode, collecting grid and non-collecting grid. The semiconductor substrate is sensitive to ionizing radiation. A voltage less than 0 Volts is applied to the cathode electrode. A voltage greater than the voltage applied to the cathode is applied to the non-collecting grid. A voltage greater than the voltage applied to the non-collecting grid is applied to the collecting grid. The collecting grid and the non-collecting grid are summed and subtracted creating a sum and difference respectively. The difference and sum are divided creating a ratio. A gain coefficient factor for each depth (distance between the ionizing event and the collecting grid) is determined, whereby the difference between the collecting electrode and the non-collecting electrode multiplied by the corresponding gain coefficient is the depth corrected energy of an ionizing event. Therefore, the energy of each ionizing event is the difference between the collecting grid and the non-collecting grid multiplied by the corresponding gain coefficient. The depth of the ionizing event can also be determined from the ratio.

  4. Selective Real-time Detection of Gaseous Nerve Agent Simulants Using Multiwavelength Photoacoustics

    DTIC Science & Technology

    2012-08-15

    Selective real-time detection of gaseous nerve agent simulants using multiwavelength photoacoustics Kristan P. Gurton,* Melvin Felton, and Richard...concentrations. The technique is based on a modified version of conventional laser photoacoustic (PA) spectroscopy, in which optical absorption is typically...spec- troscopic approach [1–4]. One of the more direct methods to implement in prac- tice (without sacrificing sensitivity) is laser photoacoustic

  5. On the Implementation of Iterative Detection in Real-World MIMO Wireless Systems

    DTIC Science & Technology

    2003-12-01

    Iterative Detection in Real-World MIMO Wireless Systems Yvo de Jong DISTRIBUTION STATEMENT A Approved for Public Release Distribution Unlimited The work...remarkably high spectral efficiency as compared to conventional, single-antenna systems. This report identi- fies a number of problems which need to be...multientr~es et multisorties (MIMO) permettent une exploitation remarquable du spectre comparativement aux syst~mes traditionnels A antenne unique

  6. A specific real-time PCR assay for the detection of Bordetella pertussis.

    PubMed

    Vincart, Benoit; De Mendonça, Ricardo; Rottiers, Sylvianne; Vermeulen, Françoise; Struelens, Marc J; Denis, Olivier

    2007-07-01

    A novel real-time PCR (RT-PCR) assay was developed for detection of Bordetella pertussis in respiratory specimens by targeting the pertactin gene. In vitro evaluation with reference strains and quality control samples showed analytical sensitivity equivalent to and specificity superior to those of PCR assays which target the IS481 element. The pertactin-based RT-PCR assay offers better discrimination between B. pertussis and other Bordetella species than previously described assays.

  7. Generation of a Solar Cycle of Sunspot Metadata Using the AIA Event Detection Framework - A Test of the System

    NASA Astrophysics Data System (ADS)

    Slater, G. L.; Zharkov, S.

    2008-12-01

    The soon-to-be-launched Solar Dynamics Observatory (SDO) will generate roughly 2 TB of image data per day, far more than previous solar missions. Because of the difficulty of widely distributing this enormous volume of data and in order to maximize discovery and scientific return, a sophisticated automated metadata extraction system is being developed at Stanford University and Lockheed Martin Solar and Astrophysics Laboratory in Palo Alto, CA. A key component in this system is the Event Detection System, which will supervise the execution of a set of feature and event extraction algorithms running in parallel, in real time, on all images recorded by the four telescopes of the key imaging instrument, the Atmospheric Imaging Assembly (AIA). The system will run on a beowulf cluster of 160 processors. As a test of the new system, we will run feature extraction software developed under the European Grid of Solar Observatories (EGSO) program to extract sunspot metadata from the 12 year SOHO MDI mission archive of full disk continuum and magnetogram images and also from the TRACE high resolution image archive. Although the main goal will be to test the performance of the production line framework, the resulting database will have applications for both research and space weather prediction. We examine some of these applications and compare the databases generated with others currently available.

  8. 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.

  9. 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.

  10. Real-time multi-sensor based vehicle detection using MINACE filters

    NASA Astrophysics Data System (ADS)

    Topiwala, Pankaj; Nehemiah, Avinash

    2007-04-01

    A system to detect vehicles (cars, trucks etc) in electro-optic (EO) and infrared (IR) imagery is presented. We present the use of the minimum noise and correlation (MINACE) distortion invariant filter (DIF) for this problem. The selection of the MINACE filter parameter c is automated using a training and validation set. A new set of correlation plane post processing methods that improve detection accuracies and reduce false alarms are presented. The system is tested on real life imagery of traffic in parking lots and roads obtained using a multi-sensor EO/IR platform.