Development of real time visual evaluation system for sodium transient thermohydraulic experiments

International Nuclear Information System (INIS)

Tanigawa, Shingo

1990-01-01

A real time visual evaluation system, the Liquid Metal Visual Evaluation System (LIVES), has been developed for the Plant Dynamics Test Loop facility at O-arai Engineering Center. This facility is designed to provide sodium transient thermohydraulic experimental data not only in a fuel subassembly but also in a plant wide system simulating abnormal or accident conditions in liquid metal fast breeder reactors. Since liquid metal sodium is invisible, measurements to obtain experimental data are mainly conducted by numerous thermo couples installed at various locations in the test sections and the facility. The transient thermohydraulic phenomena are a result of complicated interactions among global and local scale three-dimensional phenomena, and short- and long-time scale phenomena. It is, therefore, difficult to grasp intuitively thermohydraulic behaviors and to observe accurately both temperature distribution and flow condition solely by digital data or various types of analog data in evaluating the experimental results. For effectively conducting sodium transient experiments and for making it possible to observe exactly thermohydraulic phenomena, the real time visualization technique for transient thermohydraulics has been developed using the latest Engineering Work Station. The system makes it possible to observe and compare instantly the experiment and analytical results while experiment or analysis is in progress. The results are shown by not only the time trend curves but also the graphic animations. This paper shows an outline of the system and sample applications of the system. (author)

realfast: Real-time, Commensal Fast Transient Surveys with the Very Large Array

Science.gov (United States)

Law, C. J.; Bower, G. C.; Burke-Spolaor, S.; Butler, B. J.; Demorest, P.; Halle, A.; Khudikyan, S.; Lazio, T. J. W.; Pokorny, M.; Robnett, J.; Rupen, M. P.

2018-05-01

Radio interferometers have the ability to precisely localize and better characterize the properties of sources. This ability is having a powerful impact on the study of fast radio transients, where a few milliseconds of data is enough to pinpoint a source at cosmological distances. However, recording interferometric data at millisecond cadence produces a terabyte-per-hour data stream that strains networks, computing systems, and archives. This challenge mirrors that of other domains of science, where the science scope is limited by the computational architecture as much as the physical processes at play. Here, we present a solution to this problem in the context of radio transients: realfast, a commensal, fast transient search system at the Jansky Very Large Array. realfast uses a novel architecture to distribute fast-sampled interferometric data to a 32-node, 64-GPU cluster for real-time imaging and transient detection. By detecting transients in situ, we can trigger the recording of data for those rare, brief instants when the event occurs and reduce the recorded data volume by a factor of 1000. This makes it possible to commensally search a data stream that would otherwise be impossible to record. This system will search for millisecond transients in more than 1000 hr of data per year, potentially localizing several Fast Radio Bursts, pulsars, and other sources of impulsive radio emission. We describe the science scope for realfast, the system design, expected outcomes, and ways in which real-time analysis can help in other fields of astrophysics.

Automatic parquet block sorting using real-time spectral classification

Science.gov (United States)

Astrom, Anders; Astrand, Erik; Johansson, Magnus

1999-03-01

This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

Real-time classification of auditory sentences using evoked cortical activity in humans

Science.gov (United States)

Moses, David A.; Leonard, Matthew K.; Chang, Edward F.

2018-06-01

Objective. Recent research has characterized the anatomical and functional basis of speech perception in the human auditory cortex. These advances have made it possible to decode speech information from activity in brain regions like the superior temporal gyrus, but no published work has demonstrated this ability in real-time, which is necessary for neuroprosthetic brain-computer interfaces. Approach. Here, we introduce a real-time neural speech recognition (rtNSR) software package, which was used to classify spoken input from high-resolution electrocorticography signals in real-time. We tested the system with two human subjects implanted with electrode arrays over the lateral brain surface. Subjects listened to multiple repetitions of ten sentences, and rtNSR classified what was heard in real-time from neural activity patterns using direct sentence-level and HMM-based phoneme-level classification schemes. Main results. We observed single-trial sentence classification accuracies of 90% or higher for each subject with less than 7 minutes of training data, demonstrating the ability of rtNSR to use cortical recordings to perform accurate real-time speech decoding in a limited vocabulary setting. Significance. Further development and testing of the package with different speech paradigms could influence the design of future speech neuroprosthetic applications.

An analysis of feature relevance in the classification of astronomical transients with machine learning methods

Science.gov (United States)

D'Isanto, A.; Cavuoti, S.; Brescia, M.; Donalek, C.; Longo, G.; Riccio, G.; Djorgovski, S. G.

2016-04-01

The exploitation of present and future synoptic (multiband and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation. In this work, using data extracted from the Catalina Real Time Transient Survey (CRTS), we investigate the classification performance of some well tested methods: Random Forest, MultiLayer Perceptron with Quasi Newton Algorithm and K-Nearest Neighbours, paying special attention to the feature selection phase. In order to do so, several classification experiments were performed. Namely: identification of cataclysmic variables, separation between galactic and extragalactic objects and identification of supernovae.

Investigation of the Adaptability of Transient Stability Assessment Methods to Real-Time Operation

OpenAIRE

Weckesser, Johannes Tilman Gabriel; Jóhannsson, Hjörtur; Sommer, Stefan; Østergaard, Jacob

2012-01-01

In this paper, an investigation of the adaptability of available transient stability assessment methods to real-time operation and their real-time performance is carried out. Two approaches based on Lyapunov’s method and the equal area criterion are analyzed. The results allow to determine the runtime of each method with respect to the number of inputs. Furthermore, it allows to identify, which method is preferable in case of changes in the power system such as the integration of distributed ...

Real-time, resource-constrained object classification on a micro-air vehicle

Science.gov (United States)

Buck, Louis; Ray, Laura

2013-12-01

A real-time embedded object classification algorithm is developed through the novel combination of binary feature descriptors, a bag-of-visual-words object model and the cortico-striatal loop (CSL) learning algorithm. The BRIEF, ORB and FREAK binary descriptors are tested and compared to SIFT descriptors with regard to their respective classification accuracies, execution times, and memory requirements when used with CSL on a 12.6 g ARM Cortex embedded processor running at 800 MHz. Additionally, the effect of x2 feature mapping and opponent-color representations used with these descriptors is examined. These tests are performed on four data sets of varying sizes and difficulty, and the BRIEF descriptor is found to yield the best combination of speed and classification accuracy. Its use with CSL achieves accuracies between 67% and 95% of those achieved with SIFT descriptors and allows for the embedded classification of a 128x192 pixel image in 0.15 seconds, 60 times faster than classification with SIFT. X2 mapping is found to provide substantial improvements in classification accuracy for all of the descriptors at little cost, while opponent-color descriptors are offer accuracy improvements only on colorful datasets.

Transient response of a five-region nonequilibrium real-time pressurizer model

International Nuclear Information System (INIS)

Fakory, M.R.; Seifaee, F.

1987-01-01

Recent accidents at nuclear power plants in the US and abroad have prompted accurate analysis and simulation of the plant systems and the training of reactor operators on plant-specific simulators that are equipped with the simulation models. Consequently, several models for real-time and off-time simulation of nuclear reactor systems, with various levels of accuracy and simulation fidelity, have been introduced. Experience with power plant simulation demonstrates that in order to realistically predict and simulate reactor responses during unanticipated transients, it is necessary to equip the simulation model with a multielement pressurizer model. The objective of this paper is to present the results of a five-region drift-flux-based pressurizer model, which has been developed for integration with real-time training simulators. A comparison between the plant data and the results of the nonequilibrium pressurizer model demonstrates that the model is well capable of close simulation of dynamic behavior of the pressurizer system

Understanding chemical-potential-related transient pore-pressure response to improve real-time borehole (in)stability predictions

Energy Technology Data Exchange (ETDEWEB)

Tare, U. A.; Mody, F. K.; Mese, A. I. [Haliburton Energy Services, TX (United States)

2002-07-01

In order to develop a real-time wellbore (in)stability modelling capability, experimental work was carried out to investigate the role of the chemical potential of drilling fluids on transient pore pressure and time-dependent rock property alterations of shale formations. Time-dependent alterations in the pore pressure, acoustic and rock properties of formations subjected to compressive tri-axial test were recorded during the experiments involving the Pore Pressure Transmission (PPT) test. Based on the transient pore pressure of shale exposed to the test fluid presented here, the 20 per cent calcium chloride showed a very low membrane efficiency of 4.45 per cent. The need for a thorough understanding of the drilling fluid/shale interaction prior to applying any chemical potential wellbore (in)stability model to real-time drilling operations was emphasized. 9 refs., 5 figs.

Real-time full-field characterization of transient dissipative soliton dynamics in a mode-locked laser

Science.gov (United States)

Ryczkowski, P.; Närhi, M.; Billet, C.; Merolla, J.-M.; Genty, G.; Dudley, J. M.

2018-04-01

Dissipative solitons are remarkably localized states of a physical system that arise from the dynamical balance between nonlinearity, dispersion and environmental energy exchange. They are the most universal form of soliton that can exist, and are seen in far-from-equilibrium systems in many fields, including chemistry, biology and physics. There has been particular interest in studying their properties in mode-locked lasers, but experiments have been limited by the inability to track the dynamical soliton evolution in real time. Here, we use simultaneous dispersive Fourier transform and time-lens measurements to completely characterize the spectral and temporal evolution of ultrashort dissipative solitons as their dynamics pass through a transient unstable regime with complex break-up and collisions before stabilization. Further insight is obtained from reconstruction of the soliton amplitude and phase and calculation of the corresponding complex-valued eigenvalue spectrum. These findings show how real-time measurements provide new insights into ultrafast transient dynamics in optics.

Mid-level image representations for real-time heart view plane classification of echocardiograms.

Science.gov (United States)

Penatti, Otávio A B; Werneck, Rafael de O; de Almeida, Waldir R; Stein, Bernardo V; Pazinato, Daniel V; Mendes Júnior, Pedro R; Torres, Ricardo da S; Rocha, Anderson

2015-11-01

In this paper, we explore mid-level image representations for real-time heart view plane classification of 2D echocardiogram ultrasound images. The proposed representations rely on bags of visual words, successfully used by the computer vision community in visual recognition problems. An important element of the proposed representations is the image sampling with large regions, drastically reducing the execution time of the image characterization procedure. Throughout an extensive set of experiments, we evaluate the proposed approach against different image descriptors for classifying four heart view planes. The results show that our approach is effective and efficient for the target problem, making it suitable for use in real-time setups. The proposed representations are also robust to different image transformations, e.g., downsampling, noise filtering, and different machine learning classifiers, keeping classification accuracy above 90%. Feature extraction can be performed in 30 fps or 60 fps in some cases. This paper also includes an in-depth review of the literature in the area of automatic echocardiogram view classification giving the reader a through comprehension of this field of study. Copyright © 2015 Elsevier Ltd. All rights reserved.

New technique for real-time distortion-invariant multiobject recognition and classification

Science.gov (United States)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

A study on the development of a real-time intelligent system for ultrasonic flaw classification

International Nuclear Information System (INIS)

Song, Sung Jin; Kim, Hak Joon; Lee, Hyun; Lee, Seung Seok

1998-01-01

In spite of significant progress in research on ultrasonic pattern recognition it is not widely used in many practical field inspection in weldments. For the convenience of field application of this methodology, following four key issues have to be suitably addressed; 1) a software where the ultrasonic pattern recognition algorithm is efficiently implemented, 2) a real-time ultrasonic testing system which can capture the digitized ultrasonic flaw signal so the pattern recognition software can be applied in a real-time fashion, 3) database of ultrasonic flaw signals in weldments, which is served as a foundation of the ultrasonic pattern recognition algorithm, and finally, 4) ultrasonic features which should be invariant to operational variables of the ultrasonic test system. Presented here is the recent progress in the development of a real-time ultrasonic flaw classification by the novel combination of followings; an intelligent software for ultrasonic flaw classification in weldments, a computer-base real-time ultrasonic nondestructive evaluation system, database of ultrasonic flaw signals, and invariant ultrasonic features called 'normalized features.'

Performance of real-time strain elastography, transient elastography, and aspartate-to-platelet ratio index in the assessment of fibrosis in chronic hepatitis C.

Science.gov (United States)

Ferraioli, Giovanna; Tinelli, Carmine; Malfitano, Antonello; Dal Bello, Barbara; Filice, Gaetano; Filice, Carlo; Above, Elisabetta; Barbarini, Giorgio; Brunetti, Enrico; Calderon, Willy; Di Gregorio, Marta; Lissandrin, Raffaella; Ludovisi, Serena; Maiocchi, Laura; Michelone, Giuseppe; Mondelli, Mario; Patruno, Savino F A; Perretti, Alessandro; Poma, Gianluigi; Sacchi, Paolo; Zaramella, Marco; Zicchetti, Mabel

2012-07-01

The purpose of this article is to evaluate the diagnostic performance of transient elastography, real-time strain elastography, and aspartate-to-platelet ratio index in assessing fibrosis in patients with chronic hepatitis C by using histologic Metavir scores as reference standard. Consecutive patients with chronic hepatitis C scheduled for liver biopsy were enrolled. Liver biopsy was performed on the same day as transient elastography and real-time strain elastography. Transient elastography and real-time strain elastography were performed in the same patient encounter by a single investigator using a medical device based on elastometry and an ultrasound machine, respectively. Diagnostic performance was assessed by using receiver operating characteristic curves and area under the receiver operating characteristic curve (AUC) analysis. One hundred thirty patients (91 men and 39 women) were analyzed. The cutoff values for transient elastography, real-time strain elastography, and aspartate-to-platelet ratio index were 6.9 kPa, 1.82, and 0.37, respectively, for fibrosis score of 2 or higher; 7.3 kPa, 1.86, and 0.70, respectively, for fibrosis score of 3 or higher; and 9.3 kPa, 2.33, and 0.70, respectively, for fibrosis score of 4. AUC values of transient elastography, real-time strain elastography, aspartate-to-platelet ratio index were 0.88, 0.74, and 0.86, respectively, for fibrosis score of 2 or higher; 0.95, 0.80, and 0.89, respectively, for fibrosis score of 3 or higher; and 0.97, 0.80, and 0.84, respectively, for fibrosis score of 4. A combination of the three methods, when two of three were in agreement, showed AUC curves of 0.93, 0.95, and 0.95 for fibrosis scores of 2 or higher, 3 or higher, and 4, respectively. Transient elastography, real-time strain elastography, and aspartate-to-platelet ratio index values were correlated with histologic stages of fibrosis. Transient elastography offered excellent diagnostic performance in assessing severe fibrosis and

Predicting decisions in human social interactions using real-time fMRI and pattern classification.

Science.gov (United States)

Hollmann, Maurice; Rieger, Jochem W; Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes

2011-01-01

Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

Predicting decisions in human social interactions using real-time fMRI and pattern classification.

Directory of Open Access Journals (Sweden)

Maurice Hollmann

Full Text Available Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

Automatic classification of transient ischaemic and transient non-ischaemic heart-rate related ST segment deviation episodes in ambulatory ECG records

International Nuclear Information System (INIS)

Faganeli, J; Jager, F

2010-01-01

In ambulatory ECG records, besides transient ischaemic ST segment deviation episodes, there are also transient non-ischaemic heart-rate related ST segment deviation episodes present, which appear only due to a change in heart rate and thus complicate automatic detection of true ischaemic episodes. The goal of this work was to automatically classify these two types of episodes. The tested features to classify the ST segment deviation episodes were changes of heart rate, changes of the Mahalanobis distance of the first five Karhunen–Loève transform (KLT) coefficients of the QRS complex, changes of time-domain morphologic parameters of the ST segment and changes of the Legendre orthonormal polynomial coefficients of the ST segment. We chose Legendre basis functions because they best fit typical shapes of the ST segment morphology, thus allowing direct insight into the ST segment morphology changes through the feature space. The classification was performed with the help of decision trees. We tested the classification method using all records of the Long-Term ST Database on all ischaemic and all non-ischaemic heart-rate related deviation episodes according to annotation protocol B. In order to predict the real-world performance of the classification we used second-order aggregate statistics, gross and average statistics, and the bootstrap method. We obtained the best performance when we combined the heart-rate features, the Mahalanobis distance and the Legendre orthonormal polynomial coefficient features, with average sensitivity of 98.1% and average specificity of 85.2%

Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.

Directory of Open Access Journals (Sweden)

Neethu Robinson

Full Text Available Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS for developing Brain-Computer Interface (BCI by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM, so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity.

Extending an emergency classification expert system to the real-time environment

International Nuclear Information System (INIS)

Greene, K.R.; Robinson, A.H.

1990-01-01

The process of determining emergency action level (EAL) during real or simulated emergencies at the Trojan nuclear power plant was automated in 1988 with development of the EM-CLASS expert system. This system serves to replace the manual flip-chart method of determining the EAL. While the task of performing the classification is more reliable when using EM-CLASS, it still takes as long to determine the appropriate EAL with EM-CLASS as it does with the flowchart tracing method currently in use. During a plant emergency, an environment will exist where there are not enough resources to complete all of the desired tasks. To change this condition, some tasks must be accomplished with greater efficiency. The EM-CLASS application may be improved by taking advantage of the fact that most of the responses to the questions in the emergency classification procedure, EP-001, are available directly from plant measurements. This information could be passed to the expert system electronically. A prototype demonstration of a real-time emergency classification expert system has been developed. It repetitively performs the consultation, acquiring the necessary data electronically when possible and from the user when electronic data are unavailable. The expert system is being tested with scenarios from the drills and graded exercises that have taken place at the Trojan nuclear power plant. The goal of this project is to install the system on the plant simulator and/or the plant computer

Real-time simulation of thermal stresses and creep in plates subjected to transient heat input

DEFF Research Database (Denmark)

Hattel, Jesper Henri; Jacobsen, Torben Krogsdal; Hansen, P.N.

1997-01-01

-difference approach. It applies a general formulation which takes into account nonconstant material properties (e.g. temperature, material, or time dependency), heat-transfer coefficients, and creep. The temperature calculation applies a one-dimensional numerical model, whereas the stress analysis is semi......This paper presents a novel numerical technique for solving the temperature and stress fields in a plate subjected to arbitrarily varying transient boundary conditions (transient temperature and heat-flux variations) on a surface. The numerical method is based on the control-volume finite......-two-dimensional. Both plane stress and plane strain conditions are considered as extreme cases. It is shown that, by using the developed numerical technique, very fast real-time simulations can be performed. The method has proved its applicability in e.g. high-pressure die-casting, and applications to this industrial...

Feasibility of transient elastography versus real-time two-dimensional shear wave elastography in difficult-to-scan patients

DEFF Research Database (Denmark)

Staugaard, Benjamin; Christensen, Peer Brehm; Mössner, Belinda

2016-01-01

BACKGROUND AND AIMS: Transient elastography (TE) is hampered in some patients by failures and unreliable results. We hypothesized that real time two-dimensional shear wave elastography (2D-SWE), the FibroScan XL probe, and repeated TE exams, could be used to obtain reliable liver stiffness...

Leveraging Long-term Seismic Catalogs for Automated Real-time Event Classification

Science.gov (United States)

Linville, L.; Draelos, T.; Pankow, K. L.; Young, C. J.; Alvarez, S.

2017-12-01

We investigate the use of labeled event types available through reviewed seismic catalogs to produce automated event labels on new incoming data from the crustal region spanned by the cataloged events. Using events cataloged by the University of Utah Seismograph Stations between October, 2012 and June, 2017, we calculate the spectrogram for a time window that spans the duration of each event as seen on individual stations, resulting in 110k event spectrograms (50% local earthquakes examples, 50% quarry blasts examples). Using 80% of the randomized example events ( 90k), a classifier is trained to distinguish between local earthquakes and quarry blasts. We explore variations of deep learning classifiers, incorporating elements of convolutional and recurrent neural networks. Using a single-layer Long Short Term Memory recurrent neural network, we achieve 92% accuracy on the classification task on the remaining 20K test examples. Leveraging the decisions from a group of stations that detected the same event by using the median of all classifications in the group increases the model accuracy to 96%. Additional data with equivalent processing from 500 more recently cataloged events (July, 2017), achieves the same accuracy as our test data on both single-station examples and multi-station medians, suggesting that the model can maintain accurate and stable classification rates on real-time automated events local to the University of Utah Seismograph Stations, with potentially minimal levels of re-training through time.

Interactive real-time nuclear plant simulations on a UNIX based supercomputer

International Nuclear Information System (INIS)

Behling, S.R.

1990-01-01

Interactive real-time nuclear plant simulations are critically important to train nuclear power plant engineers and operators. In addition, real-time simulations can be used to test the validity and timing of plant technical specifications and operational procedures. To accurately and confidently simulate a nuclear power plant transient in real-time, sufficient computer resources must be available. Since some important transients cannot be simulated using preprogrammed responses or non-physical models, commonly used simulation techniques may not be adequate. However, the power of a supercomputer allows one to accurately calculate the behavior of nuclear power plants even during very complex transients. Many of these transients can be calculated in real-time or quicker on the fastest supercomputers. The concept of running interactive real-time nuclear power plant transients on a supercomputer has been tested. This paper describes the architecture of the simulation program, the techniques used to establish real-time synchronization, and other issues related to the use of supercomputers in a new and potentially very important area. (author)

Nuclear reactors transients identification and classification system

International Nuclear Information System (INIS)

Bianchi, Paulo Henrique

2008-01-01

This work describes the study and test of a system capable to identify and classify transients in thermo-hydraulic systems, using a neural network technique of the self-organizing maps (SOM) type, with the objective of implanting it on the new generations of nuclear reactors. The technique developed in this work consists on the use of multiple networks to do the classification and identification of the transient states, being each network a specialist at one respective transient of the system, that compete with each other using the quantization error, that is a measure given by this type of neural network. This technique showed very promising characteristics that allow the development of new functionalities in future projects. One of these characteristics consists on the potential of each network, besides responding what transient is in course, could give additional information about that transient. (author)

REAL-TIME INTELLIGENT MULTILAYER ATTACK CLASSIFICATION SYSTEM

Directory of Open Access Journals (Sweden)

T. Subbhulakshmi

2014-01-01

Full Text Available Intrusion Detection Systems (IDS takes the lion’s share of the current security infrastructure. Detection of intrusions is vital for initiating the defensive procedures. Intrusion detection was done by statistical and distance based methods. A threshold value is used in these methods to indicate the level of normalcy. When the network traffic crosses the level of normalcy then above which it is flagged as anomalous. When there are occurrences of new intrusion events which are increasingly a key part of system security, the statistical techniques cannot detect them. To overcome this issue, learning techniques are used which helps in identifying new intrusion activities in a computer system. The objective of the proposed system designed in this paper is to classify the intrusions using an Intelligent Multi Layered Attack Classification System (IMLACS which helps in detecting and classifying the intrusions with improved classification accuracy. The intelligent multi layered approach contains three intelligent layers. The first layer involves Binary Support Vector Machine classification for detecting the normal and attack. The second layer involves neural network classification to classify the attacks into classes of attacks. The third layer involves fuzzy inference system to classify the attacks into various subclasses. The proposed IMLACS can be able to detect an intrusion behavior of the networks since the system contains a three intelligent layer classification and better set of rules. Feature selection is also used to improve the time of detection. The experimental results show that the IMLACS achieves the Classification Rate of 97.31%.

Real-time classification and sensor fusion with a spiking deep belief network.

Science.gov (United States)

O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

2013-01-01

Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input.

Towards a Molecular Movie: Real Time Observation of Hydrogen Bond Breaking by Transient 2D-IR Spectroscopy in a Cyclic Peptide

Science.gov (United States)

Kolano, Christoph; Helbing, Jan; Sander, Wolfram; Hamm, Peter

Transient two-dimensional infrared spectroscopy (T2D-IR) has been used to observe in real time the non-equilibrium structural dynamics of intramolecular hydrogen bond breaking in a small cyclic disulfide-bridged peptide.

Real-time classification of humans versus animals using profiling sensors and hidden Markov tree model

Science.gov (United States)

Hossen, Jakir; Jacobs, Eddie L.; Chari, Srikant

2015-07-01

Linear pyroelectric array sensors have enabled useful classifications of objects such as humans and animals to be performed with relatively low-cost hardware in border and perimeter security applications. Ongoing research has sought to improve the performance of these sensors through signal processing algorithms. In the research presented here, we introduce the use of hidden Markov tree (HMT) models for object recognition in images generated by linear pyroelectric sensors. HMTs are trained to statistically model the wavelet features of individual objects through an expectation-maximization learning process. Human versus animal classification for a test object is made by evaluating its wavelet features against the trained HMTs using the maximum-likelihood criterion. The classification performance of this approach is compared to two other techniques; a texture, shape, and spectral component features (TSSF) based classifier and a speeded-up robust feature (SURF) classifier. The evaluation indicates that among the three techniques, the wavelet-based HMT model works well, is robust, and has improved classification performance compared to a SURF-based algorithm in equivalent computation time. When compared to the TSSF-based classifier, the HMT model has a slightly degraded performance but almost an order of magnitude improvement in computation time enabling real-time implementation.

The Raptor Real-Time Processing Architecture

Science.gov (United States)

Galassi, M.; Starr, D.; Wozniak, P.; Brozdin, K.

The primary goal of Raptor is ambitious: to identify interesting optical transients from very wide field of view telescopes in real time, and then to quickly point the higher resolution Raptor ``fovea'' cameras and spectrometer to the location of the optical transient. The most interesting of Raptor's many applications is the real-time search for orphan optical counterparts of Gamma Ray Bursts. The sequence of steps (data acquisition, basic calibration, source extraction, astrometry, relative photometry, the smarts of transient identification and elimination of false positives, telescope pointing feedback, etc.) is implemented with a ``component'' approach. All basic elements of the pipeline functionality have been written from scratch or adapted (as in the case of SExtractor for source extraction) to form a consistent modern API operating on memory resident images and source lists. The result is a pipeline which meets our real-time requirements and which can easily operate as a monolithic or distributed processing system. Finally, the Raptor architecture is entirely based on free software (sometimes referred to as ``open source'' software). In this paper we also discuss the interplay between various free software technologies in this type of astronomical problem.

A Real-Time Systems Symposium Preprint.

Science.gov (United States)

1983-09-01

Real - Time Systems Symposium Preprint Interim Tech...estimate of the occurence of the error. Unclassii ledSECUqITY CLASSIF’ICA T" NO MI*IA If’ inDI /’rrd erter for~~ble. ’Corrputnqg A REAL - TIME SYSTEMS SYMPOSIUM...ABSTRACT This technical report contains a preprint of a paper accepted for presentation at the REAL - TIME SYSTEMS SYMPOSIUM, Arlington,

A real-time classification algorithm for EEG-based BCI driven by self-induced emotions.

Science.gov (United States)

Iacoviello, Daniela; Petracca, Andrea; Spezialetti, Matteo; Placidi, Giuseppe

2015-12-01

The aim of this paper is to provide an efficient, parametric, general, and completely automatic real time classification method of electroencephalography (EEG) signals obtained from self-induced emotions. The particular characteristics of the considered low-amplitude signals (a self-induced emotion produces a signal whose amplitude is about 15% of a really experienced emotion) require exploring and adapting strategies like the Wavelet Transform, the Principal Component Analysis (PCA) and the Support Vector Machine (SVM) for signal processing, analysis and classification. Moreover, the method is thought to be used in a multi-emotions based Brain Computer Interface (BCI) and, for this reason, an ad hoc shrewdness is assumed. The peculiarity of the brain activation requires ad-hoc signal processing by wavelet decomposition, and the definition of a set of features for signal characterization in order to discriminate different self-induced emotions. The proposed method is a two stages algorithm, completely parameterized, aiming at a multi-class classification and may be considered in the framework of machine learning. The first stage, the calibration, is off-line and is devoted at the signal processing, the determination of the features and at the training of a classifier. The second stage, the real-time one, is the test on new data. The PCA theory is applied to avoid redundancy in the set of features whereas the classification of the selected features, and therefore of the signals, is obtained by the SVM. Some experimental tests have been conducted on EEG signals proposing a binary BCI, based on the self-induced disgust produced by remembering an unpleasant odor. Since in literature it has been shown that this emotion mainly involves the right hemisphere and in particular the T8 channel, the classification procedure is tested by using just T8, though the average accuracy is calculated and reported also for the whole set of the measured channels. The obtained

Combined Approach of PNN and Time-Frequency as the Classifier for Power System Transient Problems

Directory of Open Access Journals (Sweden)

Aslam Pervez Memon

2013-04-01

Full Text Available The transients in power system cause serious disturbances in the reliability, safety and economy of the system. The transient signals possess the nonstationary characteristics in which the frequency as well as varying time information is compulsory for the analysis. Hence, it is vital, first to detect and classify the type of transient fault and then to mitigate them. This article proposes time-frequency and FFNN (Feedforward Neural Network approach for the classification of power system transients problems. In this work it is suggested that all the major categories of transients are simulated, de-noised, and decomposed with DWT (Discrete Wavelet and MRA (Multiresolution Analysis algorithm and then distinctive features are extracted to get optimal vector as input for training of PNN (Probabilistic Neural Network classifier. The simulation results of proposed approach prove their simplicity, accurateness and effectiveness for the automatic detection and classification of PST (Power System Transient types

Classification methods for noise transients in advanced gravitational-wave detectors II: performance tests on Advanced LIGO data

International Nuclear Information System (INIS)

Powell, Jade; Heng, Ik Siong; Torres-Forné, Alejandro; Font, José A; Lynch, Ryan; Trifirò, Daniele; Cuoco, Elena; Cavaglià, Marco

2017-01-01

The data taken by the advanced LIGO and Virgo gravitational-wave detectors contains short duration noise transients that limit the significance of astrophysical detections and reduce the duty cycle of the instruments. As the advanced detectors are reaching sensitivity levels that allow for multiple detections of astrophysical gravitational-wave sources it is crucial to achieve a fast and accurate characterization of non-astrophysical transient noise shortly after it occurs in the detectors. Previously we presented three methods for the classification of transient noise sources. They are Principal Component Analysis for Transients (PCAT), Principal Component LALInference Burst (PC-LIB) and Wavelet Detection Filter with Machine Learning (WDF-ML). In this study we carry out the first performance tests of these algorithms on gravitational-wave data from the Advanced LIGO detectors. We use the data taken between the 3rd of June 2015 and the 14th of June 2015 during the 7th engineering run (ER7), and outline the improvements made to increase the performance and lower the latency of the algorithms on real data. This work provides an important test for understanding the performance of these methods on real, non stationary data in preparation for the second advanced gravitational-wave detector observation run, planned for later this year. We show that all methods can classify transients in non stationary data with a high level of accuracy and show the benefits of using multiple classifiers. (paper)

Super-transient scaling in time-delay autonomous Boolean network motifs

Energy Technology Data Exchange (ETDEWEB)

D' Huys, Otti, E-mail: otti.dhuys@phy.duke.edu; Haynes, Nicholas D. [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Lohmann, Johannes [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin (Germany); Gauthier, Daniel J. [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Department of Physics, The Ohio State University, Columbus, Ohio 43210 (United States)

2016-09-15

Autonomous Boolean networks are commonly used to model the dynamics of gene regulatory networks and allow for the prediction of stable dynamical attractors. However, most models do not account for time delays along the network links and noise, which are crucial features of real biological systems. Concentrating on two paradigmatic motifs, the toggle switch and the repressilator, we develop an experimental testbed that explicitly includes both inter-node time delays and noise using digital logic elements on field-programmable gate arrays. We observe transients that last millions to billions of characteristic time scales and scale exponentially with the amount of time delays between nodes, a phenomenon known as super-transient scaling. We develop a hybrid model that includes time delays along network links and allows for stochastic variation in the delays. Using this model, we explain the observed super-transient scaling of both motifs and recreate the experimentally measured transient distributions.

Integrated inertial sensors and mobile computing for real-time cycling performance guidance via pedaling profile classification.

Science.gov (United States)

Xu, James Y; Nan, Xiaomeng; Ebken, Victor; Wang, Yan; Pottie, Greg J; Kaiser, William J

2015-03-01

Today, the bicycle is utilized as a daily commute tool, a physical rehabilitation asset, and sporting equipment, prompting studies into the biomechanics of cycling. Of the number of important parameters that affect cycling efficiency, the foot angle profile is one of the most important as it correlates directly with the effective force applied to the bike. However, there has been no compact and portable solution for measuring the foot angle and for providing the cyclist with real-time feedback due to a number of difficulties of the current tracking and sensing technologies and the myriad types of bikes available. This paper presents a novel sensing and mobile computing system for classifying the foot angle profiles during cycling and for providing real-time guidance to the user to achieve the correct profile. Continuous foot angle tracking is firstly converted into a discrete problem requiring only recognition of acceleration profiles of the foot using a single shoe mounted tri-axial accelerometer during each pedaling cycle. A classification method is then applied to identify the pedaling profile. Finally, a mobile solution is presented to provide real-time signal processing and guidance.

Nuclear reactors transients identification and classification system; Sistema de identificacao e classificacao de transientes em reatores nucleares

Energy Technology Data Exchange (ETDEWEB)

Bianchi, Paulo Henrique

2008-07-01

This work describes the study and test of a system capable to identify and classify transients in thermo-hydraulic systems, using a neural network technique of the self-organizing maps (SOM) type, with the objective of implanting it on the new generations of nuclear reactors. The technique developed in this work consists on the use of multiple networks to do the classification and identification of the transient states, being each network a specialist at one respective transient of the system, that compete with each other using the quantization error, that is a measure given by this type of neural network. This technique showed very promising characteristics that allow the development of new functionalities in future projects. One of these characteristics consists on the potential of each network, besides responding what transient is in course, could give additional information about that transient. (author)

Deep neural networks to enable real-time multimessenger astrophysics

Science.gov (United States)

George, Daniel; Huerta, E. A.

2018-02-01

Gravitational wave astronomy has set in motion a scientific revolution. To further enhance the science reach of this emergent field of research, there is a pressing need to increase the depth and speed of the algorithms used to enable these ground-breaking discoveries. We introduce Deep Filtering—a new scalable machine learning method for end-to-end time-series signal processing. Deep Filtering is based on deep learning with two deep convolutional neural networks, which are designed for classification and regression, to detect gravitational wave signals in highly noisy time-series data streams and also estimate the parameters of their sources in real time. Acknowledging that some of the most sensitive algorithms for the detection of gravitational waves are based on implementations of matched filtering, and that a matched filter is the optimal linear filter in Gaussian noise, the application of Deep Filtering using whitened signals in Gaussian noise is investigated in this foundational article. The results indicate that Deep Filtering outperforms conventional machine learning techniques, achieves similar performance compared to matched filtering, while being several orders of magnitude faster, allowing real-time signal processing with minimal resources. Furthermore, we demonstrate that Deep Filtering can detect and characterize waveform signals emitted from new classes of eccentric or spin-precessing binary black holes, even when trained with data sets of only quasicircular binary black hole waveforms. The results presented in this article, and the recent use of deep neural networks for the identification of optical transients in telescope data, suggests that deep learning can facilitate real-time searches of gravitational wave sources and their electromagnetic and astroparticle counterparts. In the subsequent article, the framework introduced herein is directly applied to identify and characterize gravitational wave events in real LIGO data.

Real-Time Food Authentication Using a Miniature Mass Spectrometer.

Science.gov (United States)

Gerbig, Stefanie; Neese, Stephan; Penner, Alexander; Spengler, Bernhard; Schulz, Sabine

2017-10-17

Food adulteration is a threat to public health and the economy. In order to determine food adulteration efficiently, rapid and easy-to-use on-site analytical methods are needed. In this study, a miniaturized mass spectrometer in combination with three ambient ionization methods was used for food authentication. The chemical fingerprints of three milk types, five fish species, and two coffee types were measured using electrospray ionization, desorption electrospray ionization, and low temperature plasma ionization. Minimum sample preparation was needed for the analysis of liquid and solid food samples. Mass spectrometric data was processed using the laboratory-built software MS food classifier, which allows for the definition of specific food profiles from reference data sets using multivariate statistical methods and the subsequent classification of unknown data. Applicability of the obtained mass spectrometric fingerprints for food authentication was evaluated using different data processing methods, leave-10%-out cross-validation, and real-time classification of new data. Classification accuracy of 100% was achieved for the differentiation of milk types and fish species, and a classification accuracy of 96.4% was achieved for coffee types in cross-validation experiments. Measurement of two milk mixtures yielded correct classification of >94%. For real-time classification, the accuracies were comparable. Functionality of the software program and its performance is described. Processing time for a reference data set and a newly acquired spectrum was found to be 12 s and 2 s, respectively. These proof-of-principle experiments show that the combination of a miniaturized mass spectrometer, ambient ionization, and statistical analysis is suitable for on-site real-time food authentication.

Real-time classification of signals from three-component seismic sensors using neural nets

Science.gov (United States)

Bowman, B. C.; Dowla, F.

1992-05-01

Adaptive seismic data acquisition systems with capabilities of signal discrimination and event classification are important in treaty monitoring, proliferation, and earthquake early detection systems. Potential applications include monitoring underground chemical explosions, as well as other military, cultural, and natural activities where characteristics of signals change rapidly and without warning. In these applications, the ability to detect and interpret events rapidly without falling behind the influx of the data is critical. We developed a system for real-time data acquisition, analysis, learning, and classification of recorded events employing some of the latest technology in computer hardware, software, and artificial neural networks methods. The system is able to train dynamically, and updates its knowledge based on new data. The software is modular and hardware-independent; i.e., the front-end instrumentation is transparent to the analysis system. The software is designed to take advantage of the multiprocessing environment of the Unix operating system. The Unix System V shared memory and static RAM protocols for data access and the semaphore mechanism for interprocess communications were used. As the three-component sensor detects a seismic signal, it is displayed graphically on a color monitor using X11/Xlib graphics with interactive screening capabilities. For interesting events, the triaxial signal polarization is computed, a fast Fourier Transform (FFT) algorithm is applied, and the normalized power spectrum is transmitted to a backpropagation neural network for event classification. The system is currently capable of handling three data channels with a sampling rate of 500 Hz, which covers the bandwidth of most seismic events. The system has been tested in laboratory setting with artificial events generated in the vicinity of a three-component sensor.

Image-based deep learning for classification of noise transients in gravitational wave detectors

Science.gov (United States)

Razzano, Massimiliano; Cuoco, Elena

2018-05-01

The detection of gravitational waves has inaugurated the era of gravitational astronomy and opened new avenues for the multimessenger study of cosmic sources. Thanks to their sensitivity, the Advanced LIGO and Advanced Virgo interferometers will probe a much larger volume of space and expand the capability of discovering new gravitational wave emitters. The characterization of these detectors is a primary task in order to recognize the main sources of noise and optimize the sensitivity of interferometers. Glitches are transient noise events that can impact the data quality of the interferometers and their classification is an important task for detector characterization. Deep learning techniques are a promising tool for the recognition and classification of glitches. We present a classification pipeline that exploits convolutional neural networks to classify glitches starting from their time-frequency evolution represented as images. We evaluated the classification accuracy on simulated glitches, showing that the proposed algorithm can automatically classify glitches on very fast timescales and with high accuracy, thus providing a promising tool for online detector characterization.

Real-time ultrasound image classification for spine anesthesia using local directional Hadamard features.

Science.gov (United States)

Pesteie, Mehran; Abolmaesumi, Purang; Ashab, Hussam Al-Deen; Lessoway, Victoria A; Massey, Simon; Gunka, Vit; Rohling, Robert N

2015-06-01

Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for

VLITE-Fast: A Real-time, 350 MHz Commensal VLA Survey for Fast Transients

Science.gov (United States)

Kerr, Matthew; Ray, Paul S.; Kassim, Namir E.; Clarke, Tracy; Deneva, Julia; Polisensky, Emil

2018-01-01

The VLITE (VLA Low Band Ionosphere and Transient Experiment; http://vlite.nrao.edu) program operates commensally during all Very Large Array observations, collecting data from 320 to 384 MHz. Recently expanded to include 16 antennas, the large field of view and huge time on sky offer good coverage of the transient, low-frequency sky. We describe the VLITE-Fast system, a GPU-based signal processor capable of detecting short (system, techniques for mitigating interference, and initial results from searches for FRBs.

Transient Go: A Mobile App for Transient Astronomy Outreach

Science.gov (United States)

Crichton, D.; Mahabal, A.; Djorgovski, S. G.; Drake, A.; Early, J.; Ivezic, Z.; Jacoby, S.; Kanbur, S.

2016-12-01

Augmented Reality (AR) is set to revolutionize human interaction with the real world as demonstrated by the phenomenal success of `Pokemon Go'. That very technology can be used to rekindle the interest in science at the school level. We are in the process of developing a prototype app based on sky maps that will use AR to introduce different classes of astronomical transients to students as they are discovered i.e. in real-time. This will involve transient streams from surveys such as the Catalina Real-time Transient Survey (CRTS) today and the Large Synoptic Survey Telescope (LSST) in the near future. The transient streams will be combined with archival and latest image cut-outs and other auxiliary data as well as historical and statistical perspectives on each of the transient types being served. Such an app could easily be adapted to work with various NASA missions and NSF projects to enrich the student experience.

Classification of Physical Activity: Information to Artificial Pancreas Control Systems in Real Time.

Science.gov (United States)

Turksoy, Kamuran; Paulino, Thiago Marques Luz; Zaharieva, Dessi P; Yavelberg, Loren; Jamnik, Veronica; Riddell, Michael C; Cinar, Ali

2015-10-06

Physical activity has a wide range of effects on glucose concentrations in type 1 diabetes (T1D) depending on the type (ie, aerobic, anaerobic, mixed) and duration of activity performed. This variability in glucose responses to physical activity makes the development of artificial pancreas (AP) systems challenging. Automatic detection of exercise type and intensity, and its classification as aerobic or anaerobic would provide valuable information to AP control algorithms. This can be achieved by using a multivariable AP approach where biometric variables are measured and reported to the AP at high frequency. We developed a classification system that identifies, in real time, the exercise intensity and its reliance on aerobic or anaerobic metabolism and tested this approach using clinical data collected from 5 persons with T1D and 3 individuals without T1D in a controlled laboratory setting using a variety of common types of physical activity. The classifier had an average sensitivity of 98.7% for physiological data collected over a range of exercise modalities and intensities in these subjects. The classifier will be added as a new module to the integrated multivariable adaptive AP system to enable the detection of aerobic and anaerobic exercise for enhancing the accuracy of insulin infusion strategies during and after exercise. © 2015 Diabetes Technology Society.

Energy-aware embedded classifier design for real-time emotion analysis.

Science.gov (United States)

Padmanabhan, Manoj; Murali, Srinivasan; Rincon, Francisco; Atienza, David

2015-01-01

Detection and classification of human emotions from multiple bio-signals has a wide variety of applications. Though electronic devices are available in the market today that acquire multiple body signals, the classification of human emotions in real-time, adapted to the tight energy budgets of wearable embedded systems is a big challenge. In this paper we present an embedded classifier for real-time emotion classification. We propose a system that operates at different energy budgeted modes, depending on the available energy, where each mode is constrained by an operating energy bound. The classifier has an offline training phase where feature selection is performed for each operating mode, with an energy-budget aware algorithm that we propose. Across the different operating modes, the classification accuracy ranges from 95% - 75% and 89% - 70% for arousal and valence respectively. The accuracy is traded off for less power consumption, which results in an increased battery life of up to 7.7 times (from 146.1 to 1126.9 hours).

A Dynamic Time Warping Approach to Real-Time Activity Recognition for Food Preparation

Science.gov (United States)

Pham, Cuong; Plötz, Thomas; Olivier, Patrick

We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.

Spectroscopic Classifications of Optical Transients with the Lick Shane 3-m telescope

Science.gov (United States)

Dimitriadis, G.; Foley, R. J.

2018-05-01

We report the following classifications of optical transients from spectroscopic observations with the Kast spectrograph on the Shane 3-m telescope. Targets were supplied by ATLAS, ASAS-SN, and the KEGS K2 SN search.

Transient classification for the IRIS reactor using self-organized maps built in free platform

International Nuclear Information System (INIS)

Doraskevicius Junior, Waldemar

2005-01-01

Kohonen's Self Organized Maps (SOM) were tested with data from several operational conditions of the nuclear reactor IRIS (International Reactor Innovative and Secure) to develop an effective tool in the classification and transient identification in nuclear reactors. The data were derived from 56 simulations of the operation of IRIS, from steady-state conditions to accidents. The digital system built for the tests was based on the JAVA platform for the portability and scalability, and for being one of the free development platforms. Satisfactory results of operation classification were obtained with reasonable processing time in personal computers; about two to five minutes were spent for ordination and convergence of the learning on the data base. The methodology of this work was extended to the supervision of logistics of natural gas for Brazilian pipelines, showing satisfactory results for the classification of deliveries for simultaneous measurement in several points. (author)

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

Science.gov (United States)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

A Framework for Real-Time Collection, Analysis, and Classification of Ubiquitous Infrasound Data

Science.gov (United States)

Christe, A.; Garces, M. A.; Magana-Zook, S. A.; Schnurr, J. M.

2015-12-01

Traditional infrasound arrays are generally expensive to install and maintain. There are ~10^3 infrasound channels on Earth today. The amount of data currently provided by legacy architectures can be processed on a modest server. However, the growing availability of low-cost, ubiquitous, and dense infrasonic sensor networks presents a substantial increase in the volume, velocity, and variety of data flow. Initial data from a prototype ubiquitous global infrasound network is already pushing the boundaries of traditional research server and communication systems, in particular when serving data products over heterogeneous, international network topologies. We present a scalable, cloud-based approach for capturing and analyzing large amounts of dense infrasonic data (>10^6 channels). We utilize Akka actors with WebSockets to maintain data connections with infrasound sensors. Apache Spark provides streaming, batch, machine learning, and graph processing libraries which will permit signature classification, cross-correlation, and other analytics in near real time. This new framework and approach provide significant advantages in scalability and cost.

Energy-efficient fault tolerance in multiprocessor real-time systems

Science.gov (United States)

Guo, Yifeng

The recent progress in the multiprocessor/multicore systems has important implications for real-time system design and operation. From vehicle navigation to space applications as well as industrial control systems, the trend is to deploy multiple processors in real-time systems: systems with 4 -- 8 processors are common, and it is expected that many-core systems with dozens of processing cores will be available in near future. For such systems, in addition to general temporal requirement common for all real-time systems, two additional operational objectives are seen as critical: energy efficiency and fault tolerance. An intriguing dimension of the problem is that energy efficiency and fault tolerance are typically conflicting objectives, due to the fact that tolerating faults (e.g., permanent/transient) often requires extra resources with high energy consumption potential. In this dissertation, various techniques for energy-efficient fault tolerance in multiprocessor real-time systems have been investigated. First, the Reliability-Aware Power Management (RAPM) framework, which can preserve the system reliability with respect to transient faults when Dynamic Voltage Scaling (DVS) is applied for energy savings, is extended to support parallel real-time applications with precedence constraints. Next, the traditional Standby-Sparing (SS) technique for dual processor systems, which takes both transient and permanent faults into consideration while saving energy, is generalized to support multiprocessor systems with arbitrary number of identical processors. Observing the inefficient usage of slack time in the SS technique, a Preference-Oriented Scheduling Framework is designed to address the problem where tasks are given preferences for being executed as soon as possible (ASAP) or as late as possible (ALAP). A preference-oriented earliest deadline (POED) scheduler is proposed and its application in multiprocessor systems for energy-efficient fault tolerance is

A space-based classification system for RF transients

International Nuclear Information System (INIS)

Moore, K.R.; Call, D.; Johnson, S.; Payne, T.; Ford, W.; Spencer, K.; Wilkerson, J.F.; Baumgart, C.

1993-01-01

The FORTE (Fast On-Orbit Recording of Transient Events) small satellite is scheduled for launch in mid 1995. The mission is to measure and classify VHF (30--300 MHz) electromagnetic pulses, primarily due to lightning, within a high noise environment dominated by continuous wave carriers such as TV and FM stations. The FORTE Event Classifier will use specialized hardware to implement signal processing and neural network algorithms that perform onboard classification of RF transients and carriers. Lightning events will also be characterized with optical data telemetered to the ground. A primary mission science goal is to develop a comprehensive understanding of the correlation between the optical flash and the VHF emissions from lightning. By combining FORTE measurements with ground measurements and/or active transmitters, other science issues can be addressed. Examples include the correlation of global precipitation rates with lightning flash rates and location, the effects of large scale structures within the ionosphere (such as traveling ionospheric disturbances and horizontal gradients in the total electron content) on the propagation of broad bandwidth RF signals, and various areas of lightning physics. Event classification is a key feature of the FORTE mission. Neural networks are promising candidates for this application. The authors describe the proposed FORTE Event Classifier flight system, which consists of a commercially available digital signal processing board and a custom board, and discuss work on signal processing and neural network algorithms

Real-Time Monitoring of Low-Level Mixed-Waste Loading during Polyethylene Microencapsulation using Transient Infrared Spectroscopy

International Nuclear Information System (INIS)

Jones, Roger W.; Kalb, Paul D.; McClelland, John F.; Ochiai, Shukichi

1999-01-01

In polyethylene microencapsulation, low-level mixed waste (LLMW) is homogenized with molten polyethylene and extruded into containers, resulting in a lighter, lower-volume waste form than cementation and grout methods produce. Additionally, the polyethylene-based waste form solidifies by cooling, with no risk of the waste interfering with cure, as may occur with cementation and grout processes. We have demonstrated real-time monitoring of the polyethylene encapsulation process stream using a noncontact device based on transient infrared spectroscopy (TIRS). TIRS can acquire mid-infrared spectra from solid or viscous liquid process streams, such as the molten, waste-loaded polyethylene stream that exits the microencapsulation extruder. The waste loading in the stream was determined from the TIRS spectra using partial least squares techniques. The monitor has been demonstrated during the polyethylene microencapsulation of nitrate-salt LLMW and its surrogate, molten salt oxidation LLMW and its surrogate, and flyash. The monitor typically achieved a standard error of prediction for the waste loading of about 1% by weight with an analysis time under 1 minute

Real-time beam profile imaging system for actinotherapy accelerator

International Nuclear Information System (INIS)

Lin Yong; Wang Jingjin; Song Zheng; Zheng Putang; Wang Jianguo

2003-01-01

This paper describes a real-time beam profile imaging system for actinotheraphy accelerator. With the flash X-ray imager and the technique of digital image processing, a real-time 3-dimension dosage image is created from the intensity profile of the accelerator beam in real time. This system helps to obtain all the physical characters of the beam in any section plane, such as FWHM, penumbra, peak value, symmetry and homogeneity. This system has been used to acquire a 3-dimension dosage distribution of dynamic wedge modulator and the transient process of beam dosage. The system configure and the tested beam profile images are also presented

Real-time face and gesture analysis for human-robot interaction

Science.gov (United States)

Wallhoff, Frank; Rehrl, Tobias; Mayer, Christoph; Radig, Bernd

2010-05-01

Human communication relies on a large number of different communication mechanisms like spoken language, facial expressions, or gestures. Facial expressions and gestures are one of the main nonverbal communication mechanisms and pass large amounts of information between human dialog partners. Therefore, to allow for intuitive human-machine interaction, a real-time capable processing and recognition of facial expressions, hand and head gestures are of great importance. We present a system that is tackling these challenges. The input features for the dynamic head gestures and facial expressions are obtained from a sophisticated three-dimensional model, which is fitted to the user in a real-time capable manner. Applying this model different kinds of information are extracted from the image data and afterwards handed over to a real-time capable data-transferring framework, the so-called Real-Time DataBase (RTDB). In addition to the head and facial-related features, also low-level image features regarding the human hand - optical flow, Hu-moments are stored into the RTDB for the evaluation process of hand gestures. In general, the input of a single camera is sufficient for the parallel evaluation of the different gestures and facial expressions. The real-time capable recognition of the dynamic hand and head gestures are performed via different Hidden Markov Models, which have proven to be a quick and real-time capable classification method. On the other hand, for the facial expressions classical decision trees or more sophisticated support vector machines are used for the classification process. These obtained results of the classification processes are again handed over to the RTDB, where other processes (like a Dialog Management Unit) can easily access them without any blocking effects. In addition, an adjustable amount of history can be stored by the RTDB buffer unit.

Inverse Transient Analysis for Classification of Wall Thickness Variations in Pipelines

Directory of Open Access Journals (Sweden)

Jeffrey Tuck

2013-12-01

Full Text Available Analysis of transient fluid pressure signals has been investigated as an alternative method of fault detection in pipeline systems and has shown promise in both laboratory and field trials. The advantage of the method is that it can potentially provide a fast and cost effective means of locating faults such as leaks, blockages and pipeline wall degradation within a pipeline while the system remains fully operational. The only requirement is that high speed pressure sensors are placed in contact with the fluid. Further development of the method requires detailed numerical models and enhanced understanding of transient flow within a pipeline where variations in pipeline condition and geometry occur. One such variation commonly encountered is the degradation or thinning of pipe walls, which can increase the susceptible of a pipeline to leak development. This paper aims to improve transient-based fault detection methods by investigating how changes in pipe wall thickness will affect the transient behaviour of a system; this is done through the analysis of laboratory experiments. The laboratory experiments are carried out on a stainless steel pipeline of constant outside diameter, into which a pipe section of variable wall thickness is inserted. In order to detect the location and severity of these changes in wall conditions within the laboratory system an inverse transient analysis procedure is employed which considers independent variations in wavespeed and diameter. Inverse transient analyses are carried out using a genetic algorithm optimisation routine to match the response from a one-dimensional method of characteristics transient model to the experimental time domain pressure responses. The accuracy of the detection technique is evaluated and benefits associated with various simplifying assumptions and simulation run times are investigated. It is found that for the case investigated, changes in the wavespeed and nominal diameter of the

Inverse Transient Analysis for Classification of Wall Thickness Variations in Pipelines

Science.gov (United States)

Tuck, Jeffrey; Lee, Pedro

2013-01-01

Analysis of transient fluid pressure signals has been investigated as an alternative method of fault detection in pipeline systems and has shown promise in both laboratory and field trials. The advantage of the method is that it can potentially provide a fast and cost effective means of locating faults such as leaks, blockages and pipeline wall degradation within a pipeline while the system remains fully operational. The only requirement is that high speed pressure sensors are placed in contact with the fluid. Further development of the method requires detailed numerical models and enhanced understanding of transient flow within a pipeline where variations in pipeline condition and geometry occur. One such variation commonly encountered is the degradation or thinning of pipe walls, which can increase the susceptible of a pipeline to leak development. This paper aims to improve transient-based fault detection methods by investigating how changes in pipe wall thickness will affect the transient behaviour of a system; this is done through the analysis of laboratory experiments. The laboratory experiments are carried out on a stainless steel pipeline of constant outside diameter, into which a pipe section of variable wall thickness is inserted. In order to detect the location and severity of these changes in wall conditions within the laboratory system an inverse transient analysis procedure is employed which considers independent variations in wavespeed and diameter. Inverse transient analyses are carried out using a genetic algorithm optimisation routine to match the response from a one-dimensional method of characteristics transient model to the experimental time domain pressure responses. The accuracy of the detection technique is evaluated and benefits associated with various simplifying assumptions and simulation run times are investigated. It is found that for the case investigated, changes in the wavespeed and nominal diameter of the pipeline are both important

Classification of non-simple C*-algebras of real rank zero

DEFF Research Database (Denmark)

Arklint, Sara Esther

for real rank zero graph algebras over primitive ideal spaces that admit classification. As a consequence of completeness of filtered K-theory combined with this range result, one can conclude that real rank zero extensions of stabilized Cuntz-Krieger algebras are stabilized Cuntz-Krieger algebras......This thesis deals with classification of nonsimple C-algebras of real rank zero, and whether filtered K-theory is a suitable invariant for this purpose. As a consequence of the result of E. Kirchberg for purely infinite, nuclear C-algebras with a finite primitive ideal space, it suffices to lift...... the thesis is the following: is it possible to achieve the desired classification result for arbitrary finite primitive ideal spaces by restricting to C-algebras of real rank zero that possibly satisfy further restrictions on K-theory? The thesis consists of an account of the relevant theory and the relevant...

The fast transient sky with Gaia

Science.gov (United States)

Wevers, Thomas; Jonker, Peter G.; Hodgkin, Simon T.; Kostrzewa-Rutkowska, Zuzanna; Harrison, Diana L.; Rixon, Guy; Nelemans, Gijs; Roelens, Maroussia; Eyer, Laurent; van Leeuwen, Floor; Yoldas, Abdullah

2018-01-01

The ESA Gaia satellite scans the whole sky with a temporal sampling ranging from seconds and hours to months. Each time a source passes within the Gaia field of view, it moves over 10 charge coupled devices (CCDs) in 45 s and a light curve with 4.5 s sampling (the crossing time per CCD) is registered. Given that the 4.5 s sampling represents a virtually unexplored parameter space in optical time domain astronomy, this data set potentially provides a unique opportunity to open up the fast transient sky. We present a method to start mining the wealth of information in the per CCD Gaia data. We perform extensive data filtering to eliminate known onboard and data processing artefacts, and present a statistical method to identify sources that show transient brightness variations on ≲2 h time-scales. We illustrate that by using the Gaia photometric CCD measurements, we can detect transient brightness variations down to an amplitude of 0.3 mag on time-scales ranging from 15 s to several hours. We search an area of ∼23.5 deg2 on the sky and find four strong candidate fast transients. Two candidates are tentatively classified as flares on M-dwarf stars, while one is probably a flare on a giant star and one potentially a flare on a solar-type star. These classifications are based on archival data and the time-scales involved. We argue that the method presented here can be added to the existing Gaia Science Alerts infrastructure for the near real-time public dissemination of fast transient events.

Low-cost real-time automatic wheel classification system

Science.gov (United States)

Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

1992-11-01

This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

Real-Time Classification of Patients with Balance Disorders vs. Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor

Directory of Open Access Journals (Sweden)

Bhargava Teja Nukala

2016-11-01

Full Text Available Gait analysis using wearable wireless sensors can be an economical, convenient and effective way to provide diagnostic and clinical information for various health-related issues. In this work, our custom designed low-cost wireless gait analysis sensor that contains a basic inertial measurement unit (IMU was used to collect the gait data for four patients diagnosed with balance disorders and additionally three normal subjects, each performing the Dynamic Gait Index (DGI tests while wearing the custom wireless gait analysis sensor (WGAS. The small WGAS includes a tri-axial accelerometer integrated circuit (IC, two gyroscopes ICs and a Texas Instruments (TI MSP430 microcontroller and is worn by each subject at the T4 position during the DGI tests. The raw gait data are wirelessly transmitted from the WGAS to a near-by PC for real-time gait data collection and analysis. In order to perform successful classification of patients vs. normal subjects, we used several different classification algorithms, such as the back propagation artificial neural network (BP-ANN, support vector machine (SVM, k-nearest neighbors (KNN and binary decision trees (BDT, based on features extracted from the raw gait data of the gyroscopes and accelerometers. When the range was used as the input feature, the overall classification accuracy obtained is 100% with BP-ANN, 98% with SVM, 96% with KNN and 94% using BDT. Similar high classification accuracy results were also achieved when the standard deviation or other values were used as input features to these classifiers. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real time using various classifiers, the success of which may eventually lead to accurate and objective diagnosis of abnormal human gaits and their underlying etiologies in the future, as more patient data are being collected.

Transient simulation for a real-time operator advisor expert system

International Nuclear Information System (INIS)

Jakubowski, T.; Hajek, B.K.; Miller, D.W.; Bhatnagar, R.

1990-01-01

An Operator Advisor (OA) consisting of four integrated expert systems has been under development at The Ohio State University since 1985. The OA, designed for a General Electric BWR-6 plant, has used the Perry Nuclear Power Plants full scope simulator near Cleveland, Ohio (USA) as the reference plant. The primary goal of this development has been to provide a single system which not only performs monitoring and diagnosis functions, but also provides fault mitigation procedures to the operator, monitors the performance of these procedures and provides backup procudures should the initial ones fail. To test the system off line, a transient event simulation methodology has been developed. The simulator employs event scenarios from the Perry simulator. Scenarios are selected to test both inter- and intra-modular system behavior and response and to verify the consistency and accuracy of the knowledge base. This paper describes the OA architecture and design and the transient simulation. A discussion of a sample scenario test, including the rationale for scenario selection, is included as an example. The results of the testing demonstrate the value of off line transient simulations in that they verify system operation and help to identify characteristics requiring further improvements

Real-time transient stabilization and voltage regulation of power generators with unknown mechanical power input

International Nuclear Information System (INIS)

Kenne, Godpromesse; Goma, Raphael; Nkwawo, Homere; Lamnabhi-Lagarrigue, Francoise; Arzande, Amir; Vannier, Jean Claude

2010-01-01

A nonlinear adaptive excitation controller is proposed to enhance the transient stability and voltage regulation of synchronous generators with unknown power angle and mechanical power input. The proposed method is based on a standard third-order model of a synchronous generator which requires only information about the physical available measurements of relative angular speed, active electric power, infinite bus and generator terminal voltages. The operating conditions are computed online using the above physical available measurements, the terminal voltage reference value and the estimate of the mechanical power input. The proposed design is therefore capable of providing satisfactory voltage in the presence of unknown variations of the power system operating conditions. Using the concept of sliding mode equivalent control techniques, a robust decentralized adaptive controller which insures the exponential convergence of the outputs to the desired ones, is obtained. Real-time experimental results are reported, comparing the performance of the proposed adaptive nonlinear control scheme to one of the conventional AVR/PSS controller. The high simplicity of the overall adaptive control scheme and its robustness with respect to line impedance variation including critical unbalanced operating condition and temporary turbine fault, constitute the main positive features of the proposed approach.

Real-time transient stabilization and voltage regulation of power generators with unknown mechanical power input

Energy Technology Data Exchange (ETDEWEB)

Kenne, Godpromesse, E-mail: gokenne@yahoo.co [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Goma, Raphael, E-mail: raphael.goma@lss.supelec.f [Laboratoire des Signaux et Systemes (L2S), CNRS-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Nkwawo, Homere, E-mail: homere.nkwawo@iutv.univ-paris13.f [Departement GEII, Universite Paris XIII, 99 Avenue Jean Baptiste Clement, 93430 Villetaneuse (France); Lamnabhi-Lagarrigue, Francoise, E-mail: lamnabhi@lss.supelec.f [Laboratoire des Signaux et Systemes (L2S), CNRS-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir, E-mail: Amir.arzande@supelec.f [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Vannier, Jean Claude, E-mail: Jean-claude.vannier@supelec.f [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)

2010-01-15

A nonlinear adaptive excitation controller is proposed to enhance the transient stability and voltage regulation of synchronous generators with unknown power angle and mechanical power input. The proposed method is based on a standard third-order model of a synchronous generator which requires only information about the physical available measurements of relative angular speed, active electric power, infinite bus and generator terminal voltages. The operating conditions are computed online using the above physical available measurements, the terminal voltage reference value and the estimate of the mechanical power input. The proposed design is therefore capable of providing satisfactory voltage in the presence of unknown variations of the power system operating conditions. Using the concept of sliding mode equivalent control techniques, a robust decentralized adaptive controller which insures the exponential convergence of the outputs to the desired ones, is obtained. Real-time experimental results are reported, comparing the performance of the proposed adaptive nonlinear control scheme to one of the conventional AVR/PSS controller. The high simplicity of the overall adaptive control scheme and its robustness with respect to line impedance variation including critical unbalanced operating condition and temporary turbine fault, constitute the main positive features of the proposed approach.

Timing of transients: quantifying reaching times and transient behavior in complex systems

Science.gov (United States)

Kittel, Tim; Heitzig, Jobst; Webster, Kevin; Kurths, Jürgen

2017-08-01

In dynamical systems, one may ask how long it takes for a trajectory to reach the attractor, i.e. how long it spends in the transient phase. Although for a single trajectory the mathematically precise answer may be infinity, it still makes sense to compare different trajectories and quantify which of them approaches the attractor earlier. In this article, we categorize several problems of quantifying such transient times. To treat them, we propose two metrics, area under distance curve and regularized reaching time, that capture two complementary aspects of transient dynamics. The first, area under distance curve, is the distance of the trajectory to the attractor integrated over time. It measures which trajectories are ‘reluctant’, i.e. stay distant from the attractor for long, or ‘eager’ to approach it right away. Regularized reaching time, on the other hand, quantifies the additional time (positive or negative) that a trajectory starting at a chosen initial condition needs to approach the attractor as compared to some reference trajectory. A positive or negative value means that it approaches the attractor by this much ‘earlier’ or ‘later’ than the reference, respectively. We demonstrated their substantial potential for application with multiple paradigmatic examples uncovering new features.

Real time simulator for material testing reactor

Energy Technology Data Exchange (ETDEWEB)

Takemoto, Noriyuki; Imaizumi, Tomomi; Izumo, Hironobu; Hori, Naohiko; Suzuki, Masahide [Japan Atomic Energy Agency, Oarai Research and Development Center, Oarai, Ibaraki (Japan); Ishitsuka, Tatsuo; Tamura, Kazuo [ITOCHU Techno-Solutions Corp., Tokyo (Japan)

2012-03-15

Japan Atomic Energy Agency (JAEA) is now developing a real time simulator for a material testing reactor based on Japan Materials Testing Reactor (JMTR). The simulator treats reactor core system, primary and secondary cooling system, electricity system and irradiation facility systems. Possible simulations are normal reactor operation, unusual transient operation and accidental operation. The developed simulator also contains tool to revise/add facility in it for the future development. (author)

Real time simulator for material testing reactor

International Nuclear Information System (INIS)

Takemoto, Noriyuki; Imaizumi, Tomomi; Izumo, Hironobu; Hori, Naohiko; Suzuki, Masahide; Ishitsuka, Tatsuo; Tamura, Kazuo

2012-01-01

Japan Atomic Energy Agency (JAEA) is now developing a real time simulator for a material testing reactor based on Japan Materials Testing Reactor (JMTR). The simulator treats reactor core system, primary and secondary cooling system, electricity system and irradiation facility systems. Possible simulations are normal reactor operation, unusual transient operation and accidental operation. The developed simulator also contains tool to revise/add facility in it for the future development. (author)

Automatic classification of time-variable X-ray sources

Energy Technology Data Exchange (ETDEWEB)

Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M. [Sydney Institute for Astronomy, School of Physics, The University of Sydney, Sydney, NSW 2006 (Australia)

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ∼97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7–500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

Automatic classification of time-variable X-ray sources

International Nuclear Information System (INIS)

Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M.

2014-01-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ∼97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7–500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS)

Science.gov (United States)

Daniels, M. D.; Graves, S. J.; Vernon, F.; Kerkez, B.; Chandra, C. V.; Keiser, K.; Martin, C.

2014-12-01

Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS) Access, utilization and management of real-time data continue to be challenging for decision makers, as well as researchers in several scientific fields. This presentation will highlight infrastructure aimed at addressing some of the gaps in handling real-time data, particularly in increasing accessibility of these data to the scientific community through cloud services. The Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS) system addresses the ever-increasing importance of real-time scientific data, particularly in mission critical scenarios, where informed decisions must be made rapidly. Advances in the distribution of real-time data are leading many new transient phenomena in space-time to be observed, however real-time decision-making is infeasible in many cases that require streaming scientific data as these data are locked down and sent only to proprietary in-house tools or displays. This lack of accessibility to the broader scientific community prohibits algorithm development and workflows initiated by these data streams. As part of NSF's EarthCube initiative, CHORDS proposes to make real-time data available to the academic community via cloud services. The CHORDS infrastructure will enhance the role of real-time data within the geosciences, specifically expanding the potential of streaming data sources in enabling adaptive experimentation and real-time hypothesis testing. Adherence to community data and metadata standards will promote the integration of CHORDS real-time data with existing standards-compliant analysis, visualization and modeling tools.

Connecting real-time data to algorithms and databases: EarthCube's Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS)

Science.gov (United States)

Daniels, M. D.; Graves, S. J.; Kerkez, B.; Chandrasekar, V.; Vernon, F.; Martin, C. L.; Maskey, M.; Keiser, K.; Dye, M. J.

2015-12-01

The Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS) project was funded under the National Science Foundation's EarthCube initiative. CHORDS addresses the ever-increasing importance of real-time scientific data in the geosciences, particularly in mission critical scenarios, where informed decisions must be made rapidly. Access to constant streams of real-time data also allow many new transient phenomena in space-time to be observed, however, much of these streaming data are either completely inaccessible or only available to proprietary in-house tools or displays. Small research teams do not have the resources to develop tools for the broad dissemination of their unique real-time data and require an easy to use, scalable, cloud-based solution to facilitate this access. CHORDS will make these diverse streams of real-time data available to the broader geosciences community. This talk will highlight a recently developed CHORDS portal tools and processing systems which address some of the gaps in handling real-time data, particularly in the provisioning of data from the "long-tail" scientific community through a simple interface that is deployed in the cloud, is scalable and is able to be customized by research teams. A running portal, with operational data feeds from across the nation, will be presented. The processing within the CHORDS system will expose these real-time streams via standard services from the Open Geospatial Consortium (OGC) in a way that is simple and transparent to the data provider, while maximizing the usage of these investments. The ingestion of high velocity, high volume and diverse data has allowed the project to explore a NoSQL database implementation. Broad use of the CHORDS framework by geoscientists will help to facilitate adaptive experimentation, model assimilation and real-time hypothesis testing.

Imaging gene expression in real-time using aptamers

Energy Technology Data Exchange (ETDEWEB)

Shin, Il Chung [Iowa State Univ., Ames, IA (United States)

2011-01-01

Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

Imaging gene expression in real-time using aptamers

Energy Technology Data Exchange (ETDEWEB)

Shin, Ilchung [Iowa State Univ., Ames, IA (United States)

2012-01-01

Signal transduction pathways are usually activated by external stimuli and are transient. The downstream changes such as transcription of the activated genes are also transient. Real-time detection of promoter activity is useful for understanding changes in gene expression, especially during cell differentiation and in development. A simple and reliable method for viewing gene expression in real time is not yet available. Reporter proteins such as fluorescent proteins and luciferase allow for non-invasive detection of the products of gene expression in living cells. However, current reporter systems do not provide for real-time imaging of promoter activity in living cells. This is because of the long time period after transcription required for fluorescent protein synthesis and maturation. We have developed an RNA reporter system for imaging in real-time to detect changes in promoter activity as they occur. The RNA reporter uses strings of RNA aptamers that constitute IMAGEtags (Intracellular MultiAptamer GEnetic tags), which can be expressed from a promoter of choice. The tobramycin, neomycin and PDC RNA aptamers have been utilized for this system and expressed in yeast from the GAL1 promoter. The IMAGEtag RNA kinetics were quantified by RT-qPCR. In yeast precultured in raffinose containing media the GAL1 promoter responded faster than in yeast precultured in glucose containing media. IMAGEtag RNA has relatively short half-life (5.5 min) in yeast. For imaging, the yeast cells are incubated with their ligands that are labeled with fluorescent dyes. To increase signal to noise, ligands have been separately conjugated with the FRET (Förster resonance energy transfer) pairs, Cy3 and Cy5. With these constructs, the transcribed aptamers can be imaged after activation of the promoter by galactose. FRET was confirmed with three different approaches, which were sensitized emission, acceptor photobleaching and donor lifetime by FLIM (fluorescence lifetime imaging

Value of real-time shear wave elastography in evaluating classification of liver fibrosis: a Meta-analysis

Directory of Open Access Journals (Sweden)

WU Yue

2017-09-01

Full Text Available ObjectiveTo investigate the diagnostic value of real-time shear wave elastography (SWE technique in evaluating classification of liver fibrosis. MethodsPubMed, CNKI, CBM, VIP, and Wanfang Data were searched for Chinese and English articles on SWE for evaluating classification of liver fibrosis published from January 2010 to December 2016, and these articles were screened and evaluated. Meta-disc 1.4 software was used for the meta-analysis of the data in the articles included. ResultsA total of 11 English articles were included, with 1560 cases in total. In the ≥F2 group, SWE had a pooled sensitivity of 0.85 (95% confidence interval ［CI］：0.82-0.87, a specificity of 0.79 (95%CI：0.76-0.82, and a diagnostic odds ratio (DOR of 30.81 (95%CI: 16.55-57.34. In the ≥F3 group, SWE had a pooled sensitivity of 0.87 (95%CI：0.84-0.91, a specificity of 0.84 (95%CI：0.82-0.87, and a DOR of 41.45 (95%CI：18.25-94.45. In the F4 group, SWE had a pooled sensitivity of 0.88 (95%CI：0.83-0.91, a specificity of 0.91 (95%CI：0.89-092, and a DOR of 67.18 (95%CI：30.03-150.31. The areas under the receiver operating characteristic curve for these three groups were 0.914 7, 0.922 3, and 0.952 0, respectively. ConclusionSWE has a high diagnostic value in evaluating the classification of liver fibrosis and can be used to determine liver fibrosis stage in clinical practice.

Deciding between compensated volume balance and real time transient models for pipeline leak detection system

Energy Technology Data Exchange (ETDEWEB)

Baptista, Renan Martins [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas. Div. de Explotacao]. E-mail: renan@cenpes.petrobras.com.br

2000-07-01

This paper describes a technical procedure to assess a software based leak detection system (LDS), by deciding between a simpler low cost, less effective product, having a fast installation and tuning, and a complex one with high cost and efficiency, which however takes a long time to be properly installed. This is a common decision among the pipeline operating companies, considering that the majority of the lines are short, with single phase liquid flow (which may include batches), basic communication system and instrumentation. Service companies offer realistic solutions for liquid flow, but usually designed to big pipeline networks, flowing multiple batches and allowing multiple fluid entrances and deliveries. Those solutions are sometimes impractical to short pipelines, due to its high cost, as well as long tuning procedures, complex instrumentation, communication and computer requirements. It is intended to approach here the best solution according to its cost. In a practical sense, it means to differentiate the various LDS techniques. Those techniques are available in a considerable number, and they are still spreading, according to the different scenarios. However, two most known and worldwide implemented techniques hold the majority of the market: the Compensated Volume Balance (CVB), which is less accurate, reliable and robust, but cheaper, simpler and faster to install, and the Real Time Transient Model (RTTM), which is very reliable, accurate and robust, but expensive and complex. This work will describe a way to define whether one can use or not a CVB in a pipeline. (author)

Feasibility of transient elastography versus real-time two-dimensional shear wave elastography in difficult-to-scan patients.

Science.gov (United States)

Staugaard, Benjamin; Christensen, Peer Brehm; Mössner, Belinda; Hansen, Janne Fuglsang; Madsen, Bjørn Stæhr; Søholm, Jacob; Krag, Aleksander; Thiele, Maja

2016-11-01

Transient elastography (TE) is hampered in some patients by failures and unreliable results. We hypothesized that real time two-dimensional shear wave elastography (2D-SWE), the FibroScan XL probe, and repeated TE exams, could be used to obtain reliable liver stiffness measurements in patients with an invalid TE examination. We reviewed 1975 patients with 5764 TE exams performed between 2007 and 2014, to identify failures and unreliable exams. Fifty-four patients with an invalid TE at their latest appointment entered a comparative feasibility study of TE vs. 2D-SWE. The initial TE exam was successful in 93% (1835/1975) of patients. Success rate increased from 89% to 96% when the XL probe became available (OR: 1.07, 95% CI 1.06-1.09). Likewise, re-examining those with a failed or unreliable TE led to a reliable TE in 96% of patients. Combining availability of the XL probe with TE re-examination resulted in a 99.5% success rate on a per-patient level. When comparing the feasibility of TE vs. 2D-SWE, 96% (52/54) of patients obtained a reliable TE, while 2D-SWE was reliable in 63% (34/54, p < 0.001). The odds of a successful 2D-SWE exam decreased with higher skin-capsule distance (OR = 0.77, 95% CI 0.67-0.98). Transient elastography can be accomplished in nearly all patients by use of the FibroScan XL probe and repeated examinations. In difficult-to-scan patients, the feasibility of TE is superior to 2D-SWE.

Understanding chemical-potential-related transient pore-pressure response to improve real-time borehole (in)stability predictions

Energy Technology Data Exchange (ETDEWEB)

Tare, U.A.; Mody, F.K.; Mese, A.I. [Halliburton Energy Services, Cairo (Egypt)

2000-11-01

Experimental studies were conducted to explain the concept of a real-time wellbore (in)stability logging methodology. The role of the chemical potential of drilling fluids on transient pore pressure and time-dependent rock property alterations of shale formations was examined by providing details about a pore pressure transmission (PPT) test. The PPT experiments exposed formation (shale) cores under simulated downhole conditions to various salt solutions and drilling fluids. The main objective was to translate the results of the PPT tests to actual drilling conditions. A 20 per cent w/w calcium chloride solution was exposed to a Pierre II shale under high pressure in the PPT apparatus. The PPT test was used to estimate the impact of a drilling fluid on shale pore pressure. The efficiency of the salt solution/shale system was also estimated. Estimates of the dynamic rock properties were made based on the obtained acoustic data. It was determined that in order to accurately model time-dependent wellbore (in)stability in the field, it is important to calibrate representative shale core response to drilling fluids under realistic in-situ conditions. The 20 per cent w/w calcium chloride solution showed very low membrane efficiency of 4.45 per cent. It was concluded that changes in the shale dynamic rock properties as a function of test fluid exposure can be obtained from the simultaneous acquisition of sonic compression and shear wave velocity data. 12 refs., 5 figs.

Human Activity Recognition in Real-Times Environments using Skeleton Joints

Directory of Open Access Journals (Sweden)

Ajay Kumar

2016-06-01

Full Text Available In this research work, we proposed a most effective noble approach for Human activity recognition in real-time environments. We recognize several distinct dynamic human activity actions using kinect. A 3D skeleton data is processed from real-time video gesture to sequence of frames and getter skeleton joints (Energy Joints, orientation, rotations of joint angles from selected setof frames. We are using joint angle and orientations, rotations information from Kinect therefore less computation required. However, after extracting the set of frames we implemented several classification techniques Principal Component Analysis (PCA with several distance based classifiers and Artificial Neural Network (ANN respectively with some variants for classify our all different gesture models. However, we conclude that use very less number of frame (10-15% for train our system efficiently from the entire set of gesture frames. Moreover, after successfully completion of our classification methods we clinch an excellent overall accuracy 94%, 96% and 98% respectively. We finally observe that our proposed system is more useful than comparing to other existing system, therefore our model is best suitable for real-time application such as in video games for player action/gesture recognition.

Implementation of the frequency dependent line model in a real-time power system simulator

Directory of Open Access Journals (Sweden)

Reynaldo Iracheta-Cortez

2017-09-01

Full Text Available In this paper is described the implementation of the frequency-dependent line model (FD-Line in a real-time digital power system simulator. The main goal with such development is to describe a general procedure to incorporate new realistic models of power system components in modern real-time simulators based on the Electromagnetic Transients Program (EMTP. In this procedure are described, firstly, the steps to obtain the time domain solution of the differential equations that models the electromagnetic behavior in multi-phase transmission lines with frequency dependent parameters. After, the algorithmic solution of the FD-Line model is implemented in Simulink environment, through an S-function programmed in C language, for running off-line simulations of electromagnetic transients. This implementation allows the free assembling of the FD Line model with any element of the Power System Blockset library and also, it can be used to build any network topology. The main advantage of having a power network built in Simulink is that can be executed in real-time by means of the commercial eMEGAsim simulator. Finally, several simulation cases are presented to validate the accuracy and the real-time performance of the FD-Line model.

Real-time systems

OpenAIRE

Badr, Salah M.; Bruztman, Donald P.; Nelson, Michael L.; Byrnes, Ronald Benton

1992-01-01

This paper presents an introduction to the basic issues involved in real-time systems. Both real-time operating sys and real-time programming languages are explored. Concurrent programming and process synchronization and communication are also discussed. The real-time requirements of the Naval Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real-time operating system, real-time programming language, real-time sy...

Improvements to the transient solution in the PANTHER space-time code

International Nuclear Information System (INIS)

Kutt, P.K.; Knight, M.P.

1993-01-01

The three dimensional, two-group, nodal diffusion code PANTHER has been developed for the analysis of almost all thermal reactor types [pressurized water reactor (PWR), boiling water reactor, VVER, RBMK, advanced gas-cooled reactor, MAGNOX]. It can perform a comprehensive range of calculations for fuel management, operational support including on-line application, and transient analysis. Transient results for a number of light water reactor (LWR) benchmark problems have been reported previously. This paper outlines some recent developments of the transient solution in PANTHER, showing results for two LWR benchmark problems. Recently, PANTHER results have been accepted as the reference solutions for a Nuclear Energy Agency Committee on Reactor Physics (NEACRP) rod ejection benchmark Unlike previous simplified rod ejection benchmarks, it represents a real PWR with a detailed thermal model and cross sections dependent on boron, fuel temperature, and water density and temperature. This reference solution was computed with fine time steps

Real time implementation and control validation of the wind energy conversion system

Science.gov (United States)

Sattar, Adnan

The purpose of the thesis is to analyze dynamic and transient characteristics of wind energy conversion systems including the stability issues in real time environment using the Real Time Digital Simulator (RTDS). There are different power system simulation tools available in the market. Real time digital simulator (RTDS) is one of the powerful tools among those. RTDS simulator has a Graphical User Interface called RSCAD which contains detail component model library for both power system and control relevant analysis. The hardware is based upon the digital signal processors mounted in the racks. RTDS simulator has the advantage of interfacing the real world signals from the external devices, hence used to test the protection and control system equipments. Dynamic and transient characteristics of the fixed and variable speed wind turbine generating systems (WTGSs) are analyzed, in this thesis. Static Synchronous Compensator (STATCOM) as a flexible ac transmission system (FACTS) device is used to enhance the fault ride through (FRT) capability of the fixed speed wind farm. Two level voltage source converter based STATCOM is modeled in both VSC small time-step and VSC large time-step of RTDS. The simulation results of the RTDS model system are compared with the off-line EMTP software i.e. PSCAD/EMTDC. A new operational scheme for a MW class grid-connected variable speed wind turbine driven permanent magnet synchronous generator (VSWT-PMSG) is developed. VSWT-PMSG uses fully controlled frequency converters for the grid interfacing and thus have the ability to control the real and reactive powers simultaneously. Frequency converters are modeled in the VSC small time-step of the RTDS and three phase realistic grid is adopted with RSCAD simulation through the use of optical analogue digital converter (OADC) card of the RTDS. Steady state and LVRT characteristics are carried out to validate the proposed operational scheme. Simulation results show good agreement with real

Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application

Directory of Open Access Journals (Sweden)

Molina Gary N Garcia

2003-01-01

Full Text Available Brain-computer interface is a growing field of interest in human-computer interaction with diverse applications ranging from medicine to entertainment. In this paper, we present a system which allows for classification of mental tasks based on a joint time-frequency-space decorrelation, in which mental tasks are measured via electroencephalogram (EEG signals. The efficiency of this approach was evaluated by means of real-time experimentations on two subjects performing three different mental tasks. To do so, a number of protocols for visualization, as well as training with and without feedback, were also developed. Obtained results show that it is possible to obtain good classification of simple mental tasks, in view of command and control, after a relatively small amount of training, with accuracies around 80%, and in real time.

Real-time ultrasonic weld evaluation system

Science.gov (United States)

Katragadda, Gopichand; Nair, Satish; Liu, Harry; Brown, Lawrence M.

1996-11-01

Ultrasonic testing techniques are currently used as an alternative to radiography for detecting, classifying,and sizing weld defects, and for evaluating weld quality. Typically, ultrasonic weld inspections are performed manually, which require significant operator expertise and time. Thus, in recent years, the emphasis is to develop automated methods to aid or replace operators in critical weld inspections where inspection time, reliability, and operator safety are major issues. During this period, significant advances wee made in the areas of weld defect classification and sizing. Very few of these methods, however have found their way into the market, largely due to the lack of an integrated approach enabling real-time implementation. Also, not much research effort was directed in improving weld acceptance criteria. This paper presents an integrated system utilizing state-of-the-art techniques for a complete automation of the weld inspection procedure. The modules discussed include transducer tracking, classification, sizing, and weld acceptance criteria. Transducer tracking was studied by experimentally evaluating sonic and optical position tracking techniques. Details for this evaluation are presented. Classification is obtained using a multi-layer perceptron. Results from different feature extraction schemes, including a new method based on a combination of time and frequency-domain signal representations are given. Algorithms developed to automate defect registration and sizing are discussed. A fuzzy-logic acceptance criteria for weld acceptance is presented describing how this scheme provides improved robustness compared to the traditional flow-diagram standards.

Dynamic thermal signature prediction for real-time scene generation

Science.gov (United States)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

2013-05-01

At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

Real-time measurement and control at Jet. Experiment Control

International Nuclear Information System (INIS)

Felton, R.; Zabeo, L.; Sartori, F.; Piccolo, F.; Farthing, J.; Budd, T.; Dorling, S.; McCullen, P.; Harling, J.; Dalley, S.; Goodyear, A.; Stephen, A.; Card, P.; Bright, M.; Lucock, R.; Jones, E.; Griph, S.; Hogben, C.; Beldishevski, M.; Buckley, M.; Davis, J.; Young, I.; Hemming, O.; Wheatley, M.; Heesterman, P.; Lloyd, G.; Walters, M.; Bridge, R.; Leggate, H.; Howell, D.; Zastrow, K.D.; Giroud, C.; Coffey, I.; Hawkes, N.; Stamp, M.; Barnsley, R.; Edlington, T.; Guenther, K.; Gowers, C.; Popovichef, S.; Huber, A.; Ingesson, C.; Joffrin, E.; Mazon, D.; Moreau, D.; Murari, A.; Riva, M.; Barana, O.; Bolzonella, T.; Valisa, M.; Innocente, P.; Zerbini, M.; Bosak, K.; Blum, J.; Vitale, E.; Crisanti, F.; La Luna, E. de; Sanchez, J.

2004-01-01

Over the past few ears, the preparation of ITER-relevant plasma scenarios has been the main focus experimental activity on tokamaks. The development of integrated, simultaneous, real-time controls of plasma shape, current, pressure, temperature, radiation, neutron profiles, and also impurities, ELMs (edge localized modes) and MHD are now seen to be essential for further development of quasi-steady state conditions with feedback, or the stabilisation of transient phenomena with event-driven actions. For this thrust, the EFDA JET Real Time Project has developed a set of real-time plasma measurements, experiment control, and communication facilities. The Plasma Diagnostics used for real-time experiments are Far Infra Red interferometry, polarimetry, visible, UV and X-ray spectroscopy, LIDAR, bolometry, neutron and magnetics. Further analysis systems produce integrated results such as temperature profiles on geometry derived from MHD equilibrium solutions. The Actuators include toroidal, poloidal and divertor coils, gas and pellet fuelling, neutral beam injection, radiofrequency (ICRH) waves and microwaves (LH). The Heating/Fuelling Operators can either define a power or gas request waveform or select the real-time instantaneous power/gas request from the Real Time Experiment Central Control (RTCC) system. The Real Time Experiment Control system provides both a high-level, control-programming environment and interlocks with the actuators. A MATLAB facility is being developed for the development of more complex controllers. The plasma measurement, controller and plant control systems communicate in ATM network. The EFDA Real Time project is essential groundwork for future reactors such as ITER. It involves many staff from several institutions. The facility is now frequently used in experiments. (authors)

Classification versus inference learning contrasted with real-world categories.

Science.gov (United States)

Jones, Erin L; Ross, Brian H

2011-07-01

Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

A Real-Time Simulation Platform for Power System Operation

DEFF Research Database (Denmark)

Cha, Seung-Tae; Østergaard, Jacob; Wu, Qiuwei

2010-01-01

This paper describes the real-time digital simulation platform that can be used for power system operation, analysis, and power system modeling. This particular platform gives grid operators, planners and researchers the opportunity to observe how a power system behaves and can be used...... in real time. Various phenomena commonly encountered when dealing with the two-area system is studied. Despite its small size, it mimics very closely the behavior of typical systems in actual operation. The electromagnetic transient type of simulation made in RSCAD enables the study of fast and detailed...... phenomena like single-phase faults in the two-area network and to observe their effects on a larger time scale. Also, the case study of 11 bus system with 5 generators has been also used and the results are presented....

Real-time Social Internet Data to Guide Forecasting Models

Energy Technology Data Exchange (ETDEWEB)

Del Valle, Sara Y. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-09-20

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.

Improving the Robustness of Real-Time Myoelectric Pattern Recognition against Arm Position Changes in Transradial Amputees

Directory of Open Access Journals (Sweden)

Yanjuan Geng

2017-01-01

Full Text Available Previous studies have showed that arm position variations would significantly degrade the classification performance of myoelectric pattern-recognition-based prosthetic control, and the cascade classifier (CC and multiposition classifier (MPC have been proposed to minimize such degradation in offline scenarios. However, it remains unknown whether these proposed approaches could also perform well in the clinical use of a multifunctional prosthesis control. In this study, the online effect of arm position variation on motion identification was evaluated by using a motion-test environment (MTE developed to mimic the real-time control of myoelectric prostheses. The performance of different classifier configurations in reducing the impact of arm position variation was investigated using four real-time metrics based on dataset obtained from transradial amputees. The results of this study showed that, compared to the commonly used motion classification method, the CC and MPC configurations improved the real-time performance across seven classes of movements in five different arm positions (8.7% and 12.7% increments of motion completion rate, resp.. The results also indicated that high offline classification accuracy might not ensure good real-time performance under variable arm positions, which necessitated the investigation of the real-time control performance to gain proper insight on the clinical implementation of EMG-pattern-recognition-based controllers for limb amputees.

Development of a real time activity monitoring Android application utilizing SmartStep.

Science.gov (United States)

Hegde, Nagaraj; Melanson, Edward; Sazonov, Edward

2016-08-01

Footwear based activity monitoring systems are becoming popular in academic research as well as consumer industry segments. In our previous work, we had presented developmental aspects of an insole based activity and gait monitoring system-SmartStep, which is a socially acceptable, fully wireless and versatile insole. The present work describes the development of an Android application that captures the SmartStep data wirelessly over Bluetooth Low energy (BLE), computes features on the received data, runs activity classification algorithms and provides real time feedback. The development of activity classification methods was based on the the data from a human study involving 4 participants. Participants were asked to perform activities of sitting, standing, walking, and cycling while they wore SmartStep insole system. Multinomial Logistic Discrimination (MLD) was utilized in the development of machine learning model for activity prediction. The resulting classification model was implemented in an Android Smartphone. The Android application was benchmarked for power consumption and CPU loading. Leave one out cross validation resulted in average accuracy of 96.9% during model training phase. The Android application for real time activity classification was tested on a human subject wearing SmartStep resulting in testing accuracy of 95.4%.

MTF analysis of the near-real time neutron radiography facility at MURR

International Nuclear Information System (INIS)

Lindsay, J.T.; Alger, D.M.; Bull, S.R.; Miller, W.H.

1983-01-01

Several neutron radiography systems designed to view transient processes on a real-time basis have been developed. With the advent of these different real-time systems comes the necessity to develop a means to quantitatively evaluate and compare these systems. A suitable method for measuring the resolution capabilities of the image-forming system is the determination of the modulation transfer function (MTF). The MTF is a measure of an imaging system's ability to reproduce the spatial frequencies present in an image. The system in use at the University of Missouri Research Reactor is described. (Auth.)

Detecting EUV transients in near real time with ALEXIS

Energy Technology Data Exchange (ETDEWEB)

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

1995-12-31

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

Energy-Aware Synthesis of Fault-Tolerant Schedules for Real-Time Distributed Embedded Systems

DEFF Research Database (Denmark)

Poulsen, Kåre Harbo; Pop, Paul; Izosimov, Viacheslav

2007-01-01

This paper presents a design optimisation tool for distributed embedded real-time systems that 1) decides mapping, fault-tolerance policy and generates a fault-tolerant schedule, 2) is targeted for hard real-time, 3) has hard reliability goal, 4) generates static schedule for processes and messages......, 5) provides fault-tolerance for k transient/soft faults, 6) optimises for minimal energy consumption, while considering impact of lowering voltages on the probability of faults, 7) uses constraint logic programming (CLP) based implementation....

Online Synchrophasor-Based Dynamic State Estimation using Real-Time Digital Simulator

DEFF Research Database (Denmark)

Khazraj, Hesam; Adewole, Adeyemi Charles; Udaya, Annakkage

2018-01-01

Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real-...... using the RTDS (real-time digital simulator). The dynamic state variables of multi-machine systems are monitored and measured for the study on the transient behavior of power systems.......Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real......-time digital simulator (RTDS). The dynamic state variables of the system are the rotor angle and speed of the generators. The performance of the UKF method is tested with PMU measurements as inputs using the IEEE 14-bus test system. This test system was modeled in the RSCAD software and tested in real time...

Validation of an intermediate heat exchanger model for real time analysis

International Nuclear Information System (INIS)

Tzanos, C.P.

1986-11-01

A new method was presented for LMFBR intermediate heat exchanger (IHX) analysis in real time for purposes of continuous on-line data validation, plant state verification and fault identification. For the validation of this methodology the EBR-II IHX transient during Test 8A was analyzed. This paper presents the results of this analysis

Self-organization comprehensive real-time state evaluation model for oil pump unit on the basis of operating condition classification and recognition

Science.gov (United States)

Liang, Wei; Yu, Xuchao; Zhang, Laibin; Lu, Wenqing

2018-05-01

In oil transmission station, the operating condition (OC) of an oil pump unit sometimes switches accordingly, which will lead to changes in operating parameters. If not taking the switching of OCs into consideration while performing a state evaluation on the pump unit, the accuracy of evaluation would be largely influenced. Hence, in this paper, a self-organization Comprehensive Real-Time State Evaluation Model (self-organization CRTSEM) is proposed based on OC classification and recognition. However, the underlying model CRTSEM is built through incorporating the advantages of Gaussian Mixture Model (GMM) and Fuzzy Comprehensive Evaluation Model (FCEM) first. That is to say, independent state models are established for every state characteristic parameter according to their distribution types (i.e. the Gaussian distribution and logistic regression distribution). Meanwhile, Analytic Hierarchy Process (AHP) is utilized to calculate the weights of state characteristic parameters. Then, the OC classification is determined by the types of oil delivery tasks, and CRTSEMs of different standard OCs are built to constitute the CRTSEM matrix. On the other side, the OC recognition is realized by a self-organization model that is established on the basis of Back Propagation (BP) model. After the self-organization CRTSEM is derived through integration, real-time monitoring data can be inputted for OC recognition. At the end, the current state of the pump unit can be evaluated by using the right CRTSEM. The case study manifests that the proposed self-organization CRTSEM can provide reasonable and accurate state evaluation results for the pump unit. Besides, the assumption that the switching of OCs will influence the results of state evaluation is also verified.

Spectroscopic Classification of Nine Optical Transients with the 2.5-m du Pont Telescope

Science.gov (United States)

Bose, Subhash; Holoien, Tom; Prieto, Jose L.; Dong, Subo; Chen, P.; Stanek, K. Z.

2018-04-01

We report spectroscopic observations and classifications of optical transients using the du Pont 2.5-m telescope (+ WFCCD) at Las Campanas Observatory. Targets were discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN, Shappee et al. 2014) (ATel #11391, ATel #11343, ATel #11459), Gaia Alerts (http://gsaweb.ast.cam.ac.uk/alerts/alertsindex) and A. Rest et al. (for 2018agk).

Real-time Human Activity Recognition

Science.gov (United States)

Albukhary, N.; Mustafah, Y. M.

2017-11-01

The traditional Closed-circuit Television (CCTV) system requires human to monitor the CCTV for 24/7 which is inefficient and costly. Therefore, there’s a need for a system which can recognize human activity effectively in real-time. This paper concentrates on recognizing simple activity such as walking, running, sitting, standing and landing by using image processing techniques. Firstly, object detection is done by using background subtraction to detect moving object. Then, object tracking and object classification are constructed so that different person can be differentiated by using feature detection. Geometrical attributes of tracked object, which are centroid and aspect ratio of identified tracked are manipulated so that simple activity can be detected.

Material Classification Using Raw Time-of-Flight Measurements

KAUST Repository

Su, Shuochen

2016-12-13

We propose a material classification method using raw time-of-flight (ToF) measurements. ToF cameras capture the correlation between a reference signal and the temporal response of material to incident illumination. Such measurements encode unique signatures of the material, i.e. the degree of subsurface scattering inside a volume. Subsequently, it offers an orthogonal domain of feature representation compared to conventional spatial and angular reflectance-based approaches. We demonstrate the effectiveness, robustness, and efficiency of our method through experiments and comparisons of real-world materials.

Real Time Revisited

Science.gov (United States)

Allen, Phillip G.

1985-12-01

The call for abolishing photo reconnaissance in favor of real time is once more being heard. Ten years ago the same cries were being heard with the introduction of the Charge Coupled Device (CCD). The real time system problems that existed then and stopped real time proliferation have not been solved. The lack of an organized program by either DoD or industry has hampered any efforts to solve the problems, and as such, very little has happened in real time in the last ten years. Real time is not a replacement for photo, just as photo is not a replacement for infra-red or radar. Operational real time sensors can be designed only after their role has been defined and improvements made to the weak links in the system. Plodding ahead on a real time reconnaissance suite without benefit of evaluation of utility will allow this same paper to be used ten years from now.

Genetic and neural approaches to nuclear transient identification

International Nuclear Information System (INIS)

Almeida, Jose Carlos Soares de; Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu; Lapa, Celso Marcelo Franklin

2005-01-01

This work presents two approaches for pattern recognition to the same set of reactor signals. The first one describes a possibilistic approach optimized by genetic algorithm. The use of a possibilistic classification provides a natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know' response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical, since wrong or not reliable classifications can be catastrophic. Application of the proposed approach to a nuclear transient identification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. The second one uses two multilayer neural networks (NN). The first NN is responsible for the dynamic identification. This NN uses, as input, a short set (in a moving time window) of recent measurements of each variable avoiding the necessity of using starting events. The second NN is used to validate the instantaneous identification (from the first net) through the validation of each variable. This net is responsible for allowing the system to provide a 'don't know' response. In order to validate both methods, a Nuclear Power Plant (NPP) transient identification problem comprising postulated accidents, simulated for a pressurized water reactor, was proposed in the validation process it has been considered noisy data in order to evaluate the method robustness. Obtained results reveal the ability of the methods in dealing with both dynamic identification of transients and correct 'don't know' response. (author)

Toward transient finite element simulation of thermal deformation of machine tools in real-time

Science.gov (United States)

Naumann, Andreas; Ruprecht, Daniel; Wensch, Joerg

2018-01-01

Finite element models without simplifying assumptions can accurately describe the spatial and temporal distribution of heat in machine tools as well as the resulting deformation. In principle, this allows to correct for displacements of the Tool Centre Point and enables high precision manufacturing. However, the computational cost of FE models and restriction to generic algorithms in commercial tools like ANSYS prevents their operational use since simulations have to run faster than real-time. For the case where heat diffusion is slow compared to machine movement, we introduce a tailored implicit-explicit multi-rate time stepping method of higher order based on spectral deferred corrections. Using the open-source FEM library DUNE, we show that fully coupled simulations of the temperature field are possible in real-time for a machine consisting of a stock sliding up and down on rails attached to a stand.

Real-time video analysis for retail stores

Science.gov (United States)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

Impact of Model Detail of Synchronous Machines on Real-time Transient Stability Assessment

DEFF Research Database (Denmark)

Weckesser, Johannes Tilman Gabriel; Jóhannsson, Hjörtur; Østergaard, Jacob

2013-01-01

In this paper, it is investigated how detailed the model of a synchronous machine needs to be in order to assess transient stability using a Single Machine Equivalent (SIME). The results will show how the stability mechanism and the stability assessment are affected by the model detail. In order...... of the machine models is varied. Analyses of the results suggest that a 4th-order model may be sufficient to represent synchronous machines in transient stability studies....

Transient analysis of a grid connected wind driven induction generator using a real-time simulation platform

Energy Technology Data Exchange (ETDEWEB)

Ouhrouche, Mohand [Department of Applied Sciences, University of Quebec at Chicoutimi, Quebec, G7H2B1 (Canada)

2009-03-15

Due to its simple construction, ruggedness and low cost, the induction generator driven by a wind turbine and feeding power to the grid appears to be an attractive solution to the problem of growing energy demand in the context of environmental issues. This paper investigates the integration of such a system into the main utility using RT-Lab trademark (Trademark of Opal-RT Technologies) software package running on a simple off-the-shelf PC. This real-time simulation platform is now adopted by many high-tech industries as a real-time laboratory package for rapid control prototyping and for Hardware-in-the-Loop applications. Real-time digital simulation results obtained during contingencies, such as islanding and unbalanced faults are presented and analysed. (author)

A possibilistic approach for transient identification with 'don't know' response capability optimized by genetic algorithm

International Nuclear Information System (INIS)

Almeida, Jose Carlos S. de; Schirru, Roberto; Pereira, Claudio M.N.A.; Universidade Federal, Rio de Janeiro, RJ

2002-01-01

This work describes a possibilistic approach for transient identification based on the minimum centroids set method, proposed in previous work, optimized by genetic algorithm. The idea behind this method is to split the complex classification problem into small and simple ones, so that the performance in the classification can be increased. In order to accomplish that, a genetic algorithm is used to learn, from realistic simulated data, the optimized time partitions, which the robustness and correctness in the classification are maximized. The use of a possibilistic classification approach propitiates natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know 'response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical. Application of the proposed approach to a nuclear transient indentification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. Obtained results are shown and commented. (author)

Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors.

Science.gov (United States)

Belkacem, Abdelkader Nasreddine; Saetia, Supat; Zintus-art, Kalanyu; Shin, Duk; Kambara, Hiroyuki; Yoshimura, Natsue; Berrached, Nasreddine; Koike, Yasuharu

2015-01-01

EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control.

Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

International Nuclear Information System (INIS)

Canedo Medeiros, Jose Antonio Carlos; Schirru, Roberto

2008-01-01

In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results

Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Canedo Medeiros, Jose Antonio Carlos [Universidade Federal do Rio de Janeiro, PEN/COPPE, UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: canedo@lmp.ufrj.br; Schirru, Roberto [Universidade Federal do Rio de Janeiro, PEN/COPPE, UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: schirru@lmp.ufrj.br

2008-04-15

In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results.

Real time thermal hydraulic model for high temperature gas-cooled reactor core

International Nuclear Information System (INIS)

Sui Zhe; Sun Jun; Ma Yuanle; Zhang Ruipeng

2013-01-01

A real-time thermal hydraulic model of the reactor core was described and integrated into the simulation system for the high temperature gas-cooled pebble bed reactor nuclear power plant, which was developed in the vPower platform, a new simulation environment for nuclear and fossil power plants. In the thermal hydraulic model, the helium flow paths were established by the flow network tools in order to obtain the flow rates and pressure distributions. Meanwhile, the heat structures, representing all the solid heat transfer elements in the pebble bed, graphite reflectors and carbon bricks, were connected by the heat transfer network in order to solve the temperature distributions in the reactor core. The flow network and heat transfer network were coupled and calculated in real time. Two steady states (100% and 50% full power) and two transients (inlet temperature step and flow step) were tested that the quantitative comparisons of the steady results with design data and qualitative analysis of the transients showed the good applicability of the present thermal hydraulic model. (authors)

Comparison of transient arterial occlusion and muscle exercise provocation for assessment of perfusion reserve in skeletal muscle with real-time contrast-enhanced ultrasound

International Nuclear Information System (INIS)

Krix, Martin; Krakowski-Roosen, Holger; Armarteifio, Erick; Fuerstenberger, Susanne; Delorme, Stefan; Kauczor, Hans-Ulrich; Weber, Marc-Andre

2011-01-01

Objective: Contrast-enhanced ultrasound (CEUS) is able to quantify muscle perfusion and changes in perfusion due to muscle exercise in real-time. However, reliable measurement of standardized muscle exercise is difficult to perform in clinical examinations. We compared perfusion reserve assessed by CEUS after transient arterial occlusion and exercise to find the most suitable measurement for clinical application. Methods: Contrast pulse sequencing (7 MHz) during continuous IV infusion of SonoVue (4.8 mL/300 s) was used in 8 healthy volunteers to monitor muscle perfusion of the gastrocnemius muscle during transient (1 min) arterial occlusion produced by a thigh cuff of a venous occlusion plethysmograph. Isometric muscle exercise (50% of individual maximum strength for 20 s) was subsequently performed during the same examination, and several CEUS parameters obtained from ultrasound-signal-intensity-time curves and its calculation errors were compared. Results: The mean maximum local blood volume after occlusion was 13.9 [∼mL] (range, 4.5-28.8 [∼mL]), and similar values were measured after sub-maximum exercise 13.8 [∼mL], (range, 4.6-22.2 [∼mL]. The areas under the curve during reperfusion vs. recovery were also similar (515.2 ± 257.5 compared to 482.2 ± 187.5 [∼mL s]) with a strong correlation (r = 0.65), as were the times to maximum (15.3 s vs. 15.9 s), with a significantly smaller variation for the occlusion method (±2.1 s vs. ±9.0 s, p = 0.03). The mean errors for all calculated CEUS parameters were lower for the occlusion method than for the exercise test. Conclusions: CEUS muscle perfusion measurements can be easily performed after transient arterial occlusion. It delivers data which are comparable to CEUS measurements after muscle exercise but with a higher robustness. This method can be easily applied in clinical examination of patients with e.g. PAOD or diabetic microvessel diseases to assess perfusion reserve.

Instrument response during overpower transients at TREAT

International Nuclear Information System (INIS)

Meek, C.C.; Bauer, T.H.; Hill, D.J.; Froehle, P.H.; Klickman, A.E.; Tylka, J.P.; Doerner, R.C.; Wright, A.E.

1982-01-01

A program to empirically analyze data residuals or noise to determine instrument response that occurs during in-pile transient tests is out-lined. As an example, thermocouple response in the Mark III loop during a severe overpower transient in TREAT is studied both in frequency space and in real-time. Time intervals studied included both constant power and burst portions of the power transient. Thermocouple time constants were computed. Benefits and limitations of the method are discussed

Real-time speech-driven animation of expressive talking faces

Science.gov (United States)

Liu, Jia; You, Mingyu; Chen, Chun; Song, Mingli

2011-05-01

In this paper, we present a real-time facial animation system in which speech drives mouth movements and facial expressions synchronously. Considering five basic emotions, a hierarchical structure with an upper layer of emotion classification is established. Based on the recognized emotion label, the under-layer classification at sub-phonemic level has been modelled on the relationship between acoustic features of frames and audio labels in phonemes. Using certain constraint, the predicted emotion labels of speech are adjusted to gain the facial expression labels which are combined with sub-phonemic labels. The combinations are mapped into facial action units (FAUs), and audio-visual synchronized animation with mouth movements and facial expressions is generated by morphing between FAUs. The experimental results demonstrate that the two-layer structure succeeds in both emotion and sub-phonemic classifications, and the synthesized facial sequences reach a comparative convincing quality.

Etiological classifications of transient ischemic attacks: subtype classification by TOAST, CCS and ASCO--a pilot study.

Science.gov (United States)

Amort, Margareth; Fluri, Felix; Weisskopf, Florian; Gensicke, Henrik; Bonati, Leo H; Lyrer, Philippe A; Engelter, Stefan T

2012-01-01

In patients with transient ischemic attacks (TIA), etiological classification systems are not well studied. The Trial of ORG 10172 in Acute Stroke Treatment (TOAST), the Causative Classification System (CCS), and the Atherosclerosis Small Vessel Disease Cardiac Source Other Cause (ASCO) classification may be useful to determine the underlying etiology. We aimed at testing the feasibility of each of the 3 systems. Furthermore, we studied and compared their prognostic usefulness. In a single-center TIA registry prospectively ascertained over 2 years, we applied 3 etiological classification systems. We compared the distribution of underlying etiologies, the rates of patients with determined versus undetermined etiology, and studied whether etiological subtyping distinguished TIA patients with versus without subsequent stroke or TIA within 3 months. The 3 systems were applicable in all 248 patients. A determined etiology with the highest level of causality was assigned similarly often with TOAST (35.9%), CCS (34.3%), and ASCO (38.7%). However, the frequency of undetermined causes differed significantly between the classification systems and was lowest for ASCO (TOAST: 46.4%; CCS: 37.5%; ASCO: 18.5%; p CCS, and ASCO, cardioembolism (19.4/14.5/18.5%) was the most common etiology, followed by atherosclerosis (11.7/12.9/14.5%). At 3 months, 33 patients (13.3%, 95% confidence interval 9.3-18.2%) had recurrent cerebral ischemic events. These were strokes in 13 patients (5.2%; 95% confidence interval 2.8-8.8%) and TIAs in 20 patients (8.1%, 95% confidence interval 5.0-12.2%). Patients with a determined etiology (high level of causality) had higher rates of subsequent strokes than those without a determined etiology [TOAST: 6.7% (95% confidence interval 2.5-14.1%) vs. 4.4% (95% confidence interval 1.8-8.9%); CSS: 9.3% (95% confidence interval 4.1-17.5%) vs. 3.1% (95% confidence interval 1.0-7.1%); ASCO: 9.4% (95% confidence interval 4.4-17.1%) vs. 2.6% (95% confidence interval

Real-time interactive three-dimensional display of CT and MR imaging volume data

International Nuclear Information System (INIS)

Yla-Jaaski, J.; Kubler, O.; Kikinis, R.

1987-01-01

Real-time reconstruction of surfaces from CT and MR imaging volume data is demonstrated using a new algorithm and implementation in a parallel computer system. The display algorithm accepts noncubic 16-bit voxels directly as input. Operations such as interpolation, classification by thresholding, depth coding, simple lighting effects, and removal of parts of the volume by clipping planes are all supported on-line. An eight-processor implementation of the algorithm renders surfaces from typical CT data sets in real time to allow interactive rotation of the volume

Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors

Directory of Open Access Journals (Sweden)

Abdelkader Nasreddine Belkacem

2015-01-01

Full Text Available EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control.

Classification of Pulse Waveforms Using Edit Distance with Real Penalty

Directory of Open Access Journals (Sweden)

Zhang Dongyu

2010-01-01

Full Text Available Abstract Advances in sensor and signal processing techniques have provided effective tools for quantitative research in traditional Chinese pulse diagnosis (TCPD. Because of the inevitable intraclass variation of pulse patterns, the automatic classification of pulse waveforms has remained a difficult problem. In this paper, by referring to the edit distance with real penalty (ERP and the recent progress in -nearest neighbors (KNN classifiers, we propose two novel ERP-based KNN classifiers. Taking advantage of the metric property of ERP, we first develop an ERP-induced inner product and a Gaussian ERP kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The experimental results show that the proposed classifiers are effective for accurate classification of pulse waveform.

Incipient multiple fault diagnosis in real time with applications to large-scale systems

International Nuclear Information System (INIS)

Chung, H.Y.; Bien, Z.; Park, J.H.; Seon, P.H.

1994-01-01

By using a modified signed directed graph (SDG) together with the distributed artificial neutral networks and a knowledge-based system, a method of incipient multi-fault diagnosis is presented for large-scale physical systems with complex pipes and instrumentations such as valves, actuators, sensors, and controllers. The proposed method is designed so as to (1) make a real-time incipient fault diagnosis possible for large-scale systems, (2) perform the fault diagnosis not only in the steady-state case but also in the transient case as well by using a concept of fault propagation time, which is newly adopted in the SDG model, (3) provide with highly reliable diagnosis results and explanation capability of faults diagnosed as in an expert system, and (4) diagnose the pipe damage such as leaking, break, or throttling. This method is applied for diagnosis of a pressurizer in the Kori Nuclear Power Plant (NPP) unit 2 in Korea under a transient condition, and its result is reported to show satisfactory performance of the method for the incipient multi-fault diagnosis of such a large-scale system in a real-time manner

Summary: Experimental validation of real-time fault-tolerant systems

Science.gov (United States)

Iyer, R. K.; Choi, G. S.

1992-01-01

Testing and validation of real-time systems is always difficult to perform since neither the error generation process nor the fault propagation problem is easy to comprehend. There is no better substitute to results based on actual measurements and experimentation. Such results are essential for developing a rational basis for evaluation and validation of real-time systems. However, with physical experimentation, controllability and observability are limited to external instrumentation that can be hooked-up to the system under test. And this process is quite a difficult, if not impossible, task for a complex system. Also, to set up such experiments for measurements, physical hardware must exist. On the other hand, a simulation approach allows flexibility that is unequaled by any other existing method for system evaluation. A simulation methodology for system evaluation was successfully developed and implemented and the environment was demonstrated using existing real-time avionic systems. The research was oriented toward evaluating the impact of permanent and transient faults in aircraft control computers. Results were obtained for the Bendix BDX 930 system and Hamilton Standard EEC131 jet engine controller. The studies showed that simulated fault injection is valuable, in the design stage, to evaluate the susceptibility of computing sytems to different types of failures.

Evaluation of classifier topologies for the real-time classification of simultaneous limb motions.

Science.gov (United States)

Ortiz-Catalan, Max; Branemark, Rickard; Hakansson, Bo

2013-01-01

The prediction of motion intent through the decoding of myoelectric signals has the potential to improve the functionally of limb prostheses. Considerable research on individual motion classifiers has been done to exploit this idea. A drawback with the individual prediction approach, however, is its limitation to serial control, which is slow, cumbersome, and unnatural. In this work, different classifier topologies suitable for the decoding of mixed classes, and thus capable of predicting simultaneous motions, were investigated in real-time. These topologies resulted in higher offline accuracies than previously achieved, but more importantly, positive indications of their suitability for real-time systems were found. Furthermore, in order to facilitate further development, benchmarking, and cooperation, the algorithms and data generated in this study are freely available as part of BioPatRec, an open source framework for the development of advanced prosthetic control strategies.

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

Science.gov (United States)

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.

Skipping the real world: Classification of PolSAR images without explicit feature extraction

Science.gov (United States)

Hänsch, Ronny; Hellwich, Olaf

2018-06-01

The typical processing chain for pixel-wise classification from PolSAR images starts with an optional preprocessing step (e.g. speckle reduction), continues with extracting features projecting the complex-valued data into the real domain (e.g. by polarimetric decompositions) which are then used as input for a machine-learning based classifier, and ends in an optional postprocessing (e.g. label smoothing). The extracted features are usually hand-crafted as well as preselected and represent (a somewhat arbitrary) projection from the complex to the real domain in order to fit the requirements of standard machine-learning approaches such as Support Vector Machines or Artificial Neural Networks. This paper proposes to adapt the internal node tests of Random Forests to work directly on the complex-valued PolSAR data, which makes any explicit feature extraction obsolete. This approach leads to a classification framework with a significantly decreased computation time and memory footprint since no image features have to be computed and stored beforehand. The experimental results on one fully-polarimetric and one dual-polarimetric dataset show that, despite the simpler approach, accuracy can be maintained (decreased by only less than 2 % for the fully-polarimetric dataset) or even improved (increased by roughly 9 % for the dual-polarimetric dataset).

Real-Time Model and Simulation Architecture for Half- and Full-Bridge Modular Multilevel Converters

Science.gov (United States)

Ashourloo, Mojtaba

This work presents an equivalent model and simulation architecture for real-time electromagnetic transient analysis of either half-bridge or full-bridge modular multilevel converter (MMC) with 400 sub-modules (SMs) per arm. The proposed CPU/FPGA-based architecture is optimized for the parallel implementation of the presented MMC model on the FPGA and is beneficiary of a high-throughput floating-point computational engine. The developed real-time simulation architecture is capable of simulating MMCs with 400 SMs per arm at 825 nanoseconds. To address the difficulties of the sorting process implementation, a modified Odd-Even Bubble sorting is presented in this work. The comparison of the results under various test scenarios reveals that the proposed real-time simulator is representing the system responses in the same way of its corresponding off-line counterpart obtained from the PSCAD/EMTDC program.

Real-time shadows

CERN Document Server

Eisemann, Elmar; Assarsson, Ulf; Wimmer, Michael

2011-01-01

Important elements of games, movies, and other computer-generated content, shadows are crucial for enhancing realism and providing important visual cues. In recent years, there have been notable improvements in visual quality and speed, making high-quality realistic real-time shadows a reachable goal. Real-Time Shadows is a comprehensive guide to the theory and practice of real-time shadow techniques. It covers a large variety of different effects, including hard, soft, volumetric, and semi-transparent shadows.The book explains the basics as well as many advanced aspects related to the domain

Dependable Real-Time Systems

Science.gov (United States)

1991-09-30

0196 or 413 545-0720 PI E-mail Address: krithi@nirvan.cs.umass.edu, stankovic(ocs.umass.edu Grant or Contract Title: Dependable Real - Time Systems Grant...Dependable Real - Time Systems " Grant or Contract Number: N00014-85-k-0398 L " Reporting Period: 1 Oct 87 - 30 Sep 91 , 2. Summary of Accomplishments ’ 2.1 Our...in developing a sound approach to scheduling tasks in complex real - time systems , (2) developed a real-time operating system kernel, a preliminary

LabVIEW Real-Time

CERN Multimedia

CERN. Geneva; Flockhart, Ronald Bruce; Seppey, P

2003-01-01

With LabVIEW Real-Time, you can choose from a variety of RT Series hardware. Add a real-time data acquisition component into a larger measurement and automation system or create a single stand-alone real-time solution with data acquisition, signal conditioning, motion control, RS-232, GPIB instrumentation, and Ethernet connectivity. With the various hardware options, you can create a system to meet your precise needs today, while the modularity of the system means you can add to the solution as your system requirements grow. If you are interested in Reliable and Deterministic systems for Measurement and Automation, you will profit from this seminar. Agenda: Real-Time Overview LabVIEW RT Hardware Platforms - Linux on PXI Programming with LabVIEW RT Real-Time Operating Systems concepts Timing Applications Data Transfer

Concepts of real time and semi-real time material control

International Nuclear Information System (INIS)

Lovett, J.E.

1975-01-01

After a brief consideration of the traditional material balance accounting on an MBA basis, this paper explores the basic concepts of real time and semi-real time material control, together with some of the major problems to be solved. Three types of short-term material control are discussed: storage, batch processing, and continuous processing. (DLC)

Mining the Sky for Explosive Optical Transients with Both Eyes Open

International Nuclear Information System (INIS)

Vestrand, W.T.; Casperson, D.J.; Davis, H.; Fenimore, E.; Galassi, M.; White, R.R.; Wren, J.; Borozdin, K.; Davidoff, S.; McGowan, K.; Starr, D.; Wozniak, P.

2004-01-01

While it has been known for centuries that the optical sky is variable, monitoring the sky for optical transients with durations as short as a minute is an area of astronomical research that remains largely unexplored. Prompt follow-up observations of Gamma Ray Bursts have shown that bright, explosive, optical transients exist. However, there are many reasons to suspect the existence of explosive optical transients that cannot be located through sky monitoring by high-energy satellites. The RAPTOR sky monitoring system is an autonomous system of telescope arrays at Los Alamos National Laboratory that identifies fast optical transients as short as a minute and makes follow-up observations in real time. The core of the RAPTOR system is composed of two arrays of telescopes, separated by 38 kilometers, that stereoscopically monitor a field of about 1300 square degrees for transients down to about 12.5th magnitude in 30 seconds. Both arrays are coupled to real-time data analysis pipelines that are designed to identify transients on timescales of seconds. Each telescope array also contains a more sensitive higher resolution 'fovea' telescope, capable of both measuring the light curve at a faster cadence and providing color information. In a manner analogous to human vision, each array is mounted on a rapidly slewing mount so that the 'fovea' of the array can be rapidly directed for real-time follow-up observations of any interesting transient identified by the wide-field system. We discuss the first results from RAPTOR and show that stereoscopic imaging and the absence of measurable parallax is a powerful tool for distinguishing real celestial transients in the 'forest' of false positives

Real Time Systems

DEFF Research Database (Denmark)

Christensen, Knud Smed

2000-01-01

Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems.......Describes fundamentals of parallel programming and a kernel for that. Describes methods for modelling and checking parallel problems. Real time problems....

Real time expert systems

International Nuclear Information System (INIS)

Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

1992-01-01

Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

Dynamic Beam Solutions for Real-Time Simulation and Control Development of Flexible Rockets

Science.gov (United States)

Su, Weihua; King, Cecilia K.; Clark, Scott R.; Griffin, Edwin D.; Suhey, Jeffrey D.; Wolf, Michael G.

2016-01-01

In this study, flexible rockets are structurally represented by linear beams. Both direct and indirect solutions of beam dynamic equations are sought to facilitate real-time simulation and control development for flexible rockets. The direct solution is completed by numerically integrate the beam structural dynamic equation using an explicit Newmark-based scheme, which allows for stable and fast transient solutions to the dynamics of flexile rockets. Furthermore, in the real-time operation, the bending strain of the beam is measured by fiber optical sensors (FOS) at intermittent locations along the span, while both angular velocity and translational acceleration are measured at a single point by the inertial measurement unit (IMU). Another study in this paper is to find the analytical and numerical solutions of the beam dynamics based on the limited measurement data to facilitate the real-time control development. Numerical studies demonstrate the accuracy of these real-time solutions to the beam dynamics. Such analytical and numerical solutions, when integrated with data processing and control algorithms and mechanisms, have the potential to increase launch availability by processing flight data into the flexible launch vehicle's control system.

Real Time Facial Expression Recognition Using Webcam and SDK Affectiva

Directory of Open Access Journals (Sweden)

Martin Magdin

2018-06-01

Full Text Available Facial expression is an essential part of communication. For this reason, the issue of human emotions evaluation using a computer is a very interesting topic, which has gained more and more attention in recent years. It is mainly related to the possibility of applying facial expression recognition in many fields such as HCI, video games, virtual reality, and analysing customer satisfaction etc. Emotions determination (recognition process is often performed in 3 basic phases: face detection, facial features extraction, and last stage - expression classification. Most often you can meet the so-called Ekman’s classification of 6 emotional expressions (or 7 - neutral expression as well as other types of classification - the Russell circular model, which contains up to 24 or the Plutchik’s Wheel of Emotions. The methods used in the three phases of the recognition process have not only improved over the last 60 years, but new methods and algorithms have also emerged that can determine the ViolaJones detector with greater accuracy and lower computational demands. Therefore, there are currently various solutions in the form of the Software Development Kit (SDK. In this publication, we point to the proposition and creation of our system for real-time emotion classification. Our intention was to create a system that would use all three phases of the recognition process, work fast and stable in real time. That’s why we’ve decided to take advantage of existing Affectiva SDKs. By using the classic webcamera we can detect facial landmarks on the image automatically using the Software Development Kit (SDK from Affectiva. Geometric feature based approach is used for feature extraction. The distance between landmarks is used as a feature, and for selecting an optimal set of features, the brute force method is used. The proposed system uses neural network algorithm for classification. The proposed system recognizes 6 (respectively 7 facial expressions

A Multifeature Fusion Approach for Power System Transient Stability Assessment Using PMU Data

Directory of Open Access Journals (Sweden)

Yang Li

2015-01-01

Full Text Available Taking full advantage of synchrophasors provided by GPS-based wide-area measurement system (WAMS, a novel VBpMKL-based transient stability assessment (TSA method through multifeature fusion is proposed in this paper. First, a group of classification features reflecting the transient stability characteristics of power systems are extracted from synchrophasors, and according to the different stages of the disturbance process they are broken into three nonoverlapped subsets; then a VBpMKL-based TSA model is built using multifeature fusion through combining feature spaces corresponding to each feature subset; and finally application of the proposed model to the IEEE 39-bus system and a real-world power system is demonstrated. The novelty of the proposed approach is that it improves the classification accuracy and reliability of TSA using multifeature fusion with synchrophasors. The application results on the test systems verify the effectiveness of the proposal.

Process algebra with timing : real time and discrete time

NARCIS (Netherlands)

Baeten, J.C.M.; Middelburg, C.A.; Bergstra, J.A.; Ponse, A.J.; Smolka, S.A.

2001-01-01

We present real time and discrete time versions of ACP with absolute timing and relative timing. The starting-point is a new real time version with absolute timing, called ACPsat, featuring urgent actions and a delay operator. The discrete time versions are conservative extensions of the discrete

Process algebra with timing: Real time and discrete time

NARCIS (Netherlands)

Baeten, J.C.M.; Middelburg, C.A.

1999-01-01

We present real time and discrete time versions of ACP with absolute timing and relative timing. The startingpoint is a new real time version with absolute timing, called ACPsat , featuring urgent actions and a delay operator. The discrete time versions are conservative extensions of the discrete

Classification of the linear canonical transformation and its associated real symplectic matrix

NARCIS (Netherlands)

Bastiaans, M.J.; Alieva, T.

2007-01-01

Based on the eigenvalues of the real symplectic ABCD-matrix that characterizes the linear canonical integral transformation, a classification of this transformation and the associated ABCD-system is proposed and some nuclei (i.e. elementary members) in each class are described. In the

PC-Reactor-core transient simulation code

International Nuclear Information System (INIS)

Nakata, H.

1989-10-01

PC-REATOR, a reactor core transient simulation code has been developed for the real-time operator training on a IBM-PC microcomputer. The program presents capabilities for on-line exchange of the operating parameters during the transient simulation, by friendly keyboard instructions. The model is based on the point-kinetics approximation, with 2 delayed neutron percursors and up to 11 decay power generating groups. (author) [pt

Real-time radiography

International Nuclear Information System (INIS)

Bossi, R.H.; Oien, C.T.

1981-01-01

Real-time radiography is used for imaging both dynamic events and static objects. Fluorescent screens play an important role in converting radiation to light, which is then observed directly or intensified and detected. The radiographic parameters for real-time radiography are similar to conventional film radiography with special emphasis on statistics and magnification. Direct-viewing fluoroscopy uses the human eye as a detector of fluorescent screen light or the light from an intensifier. Remote-viewing systems replace the human observer with a television camera. The remote-viewing systems have many advantages over the direct-viewing conditions such as safety, image enhancement, and the capability to produce permanent records. This report reviews real-time imaging system parameters and components

Real-time vision systems

Energy Technology Data Exchange (ETDEWEB)

Johnson, R.; Hernandez, J.E.; Lu, Shin-yee [Lawrence Livermore National Lab., CA (United States)

1994-11-15

Many industrial and defence applications require an ability to make instantaneous decisions based on sensor input of a time varying process. Such systems are referred to as `real-time systems` because they process and act on data as it occurs in time. When a vision sensor is used in a real-time system, the processing demands can be quite substantial, with typical data rates of 10-20 million samples per second. A real-time Machine Vision Laboratory (MVL) was established in FY94 to extend our years of experience in developing computer vision algorithms to include the development and implementation of real-time vision systems. The laboratory is equipped with a variety of hardware components, including Datacube image acquisition and processing boards, a Sun workstation, and several different types of CCD cameras, including monochrome and color area cameras and analog and digital line-scan cameras. The equipment is reconfigurable for prototyping different applications. This facility has been used to support several programs at LLNL, including O Division`s Peacemaker and Deadeye Projects as well as the CRADA with the U.S. Textile Industry, CAFE (Computer Aided Fabric Inspection). To date, we have successfully demonstrated several real-time applications: bullet tracking, stereo tracking and ranging, and web inspection. This work has been documented in the ongoing development of a real-time software library.

Effectiveness of Multivariate Time Series Classification Using Shapelets

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

OpenAIRE

Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

OpenAIRE

Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Classification of acoustic emission signals for drive systems coupling crack detection in semi-real time

International Nuclear Information System (INIS)

Godinez, V.; Shu, F.; Finlayson, R.; O'Donnell, B.; Anastasopoulos, A.; Tsimogiannis, A.

2004-01-01

Early detection of mechanical failure in helicopter drive train components is a key safety and economical issue with both military and civil sectors of aviation. Of these components, couplings are particularly critical. The objective of this work is to demonstrate the feasibility of designing and developing a reliable, real time monitoring methodology based on Supervised Pattern Recognition (SPR) for early detection of cracks in couplings used in helicopter and engine drive systems. Within this framework, a portable Acoustic Emission (AE) system was used, equipped with a semi-real time SPR software package. Results from AE tests performed in a gearbox-testing bench at different speeds and different torque values are presented. These results indicate that the energy content of different frequency bands in the AE signals power spectra is strongly correlated with the introduction of EDM notches in the main gear. Further tests indicate that a strong shift in the frequency of the AE signals is observed after spalling occurred in the pinion gear. The variation of displacement and velocity between signal classes are discussed as a potential feature in characterizing crack severity. Finally, a scope of the work for optimizing the methodology in detecting and evaluating coupling cracking in real time will be presented. (author)

Mining Outlier Data in Mobile Internet-Based Large Real-Time Databases

Directory of Open Access Journals (Sweden)

Xin Liu

2018-01-01

Full Text Available Mining outlier data guarantees access security and data scheduling of parallel databases and maintains high-performance operation of real-time databases. Traditional mining methods generate abundant interference data with reduced accuracy, efficiency, and stability, causing severe deficiencies. This paper proposes a new mining outlier data method, which is used to analyze real-time data features, obtain magnitude spectra models of outlier data, establish a decisional-tree information chain transmission model for outlier data in mobile Internet, obtain the information flow of internal outlier data in the information chain of a large real-time database, and cluster data. Upon local characteristic time scale parameters of information flow, the phase position features of the outlier data before filtering are obtained; the decision-tree outlier-classification feature-filtering algorithm is adopted to acquire signals for analysis and instant amplitude and to achieve the phase-frequency characteristics of outlier data. Wavelet transform threshold denoising is combined with signal denoising to analyze data offset, to correct formed detection filter model, and to realize outlier data mining. The simulation suggests that the method detects the characteristic outlier data feature response distribution, reduces response time, iteration frequency, and mining error rate, improves mining adaptation and coverage, and shows good mining outcomes.

Memory controllers for real-time embedded systems predictable and composable real-time systems

CERN Document Server

Akesson, Benny

2012-01-01

  Verification of real-time requirements in systems-on-chip becomes more complex as more applications are integrated. Predictable and composable systems can manage the increasing complexity using formal verification and simulation.  This book explains the concepts of predictability and composability and shows how to apply them to the design and analysis of a memory controller, which is a key component in any real-time system. This book is generally intended for readers interested in Systems-on-Chips with real-time applications.   It is especially well-suited for readers looking to use SDRAM memories in systems with hard or firm real-time requirements. There is a strong focus on real-time concepts, such as predictability and composability, as well as a brief discussion about memory controller architectures for high-performance computing. Readers will learn step-by-step how to go from an unpredictable SDRAM memory, offering highly variable bandwidth and latency, to a predictable and composable shared memory...

Floor Covering and Surface Identification for Assistive Mobile Robotic Real-Time Room Localization Application

Directory of Open Access Journals (Sweden)

Michael Gillham

2013-12-01

Full Text Available Assistive robotic applications require systems capable of interaction in the human world, a workspace which is highly dynamic and not always predictable. Mobile assistive devices face the additional and complex problem of when and if intervention should occur; therefore before any trajectory assistance is given, the robotic device must know where it is in real-time, without unnecessary disruption or delay to the user requirements. In this paper, we demonstrate a novel robust method for determining room identification from floor features in a real-time computational frame for autonomous and assistive robotics in the human environment. We utilize two inexpensive sensors: an optical mouse sensor for straightforward and rapid, texture or pattern sampling, and a four color photodiode light sensor for fast color determination. We show how data relating floor texture and color obtained from typical dynamic human environments, using these two sensors, compares favorably with data obtained from a standard webcam. We show that suitable data can be extracted from these two sensors at a rate 16 times faster than a standard webcam, and that these data are in a form which can be rapidly processed using readily available classification techniques, suitable for real-time system application. We achieved a 95% correct classification accuracy identifying 133 rooms’ flooring from 35 classes, suitable for fast coarse global room localization application, boundary crossing detection, and additionally some degree of surface type identification.

Real-Time RT-PCR for the Detection of Lyssavirus Species

Directory of Open Access Journals (Sweden)

A. Deubelbeiss

2014-01-01

Full Text Available The causative agents of rabies are single-stranded, negative-sense RNA viruses in the genus Lyssavirus of Rhabdoviridae, consisting of twelve classified and three as yet unclassified species including classical rabies virus (RABV. Highly neurotropic RABV causes rapidly progressive encephalomyelitis with nearly invariable fatal outcome. Rapid and reliable diagnosis of rabies is highly relevant for public and veterinary health. Due to growing variety of the genus Lyssavirus observed, the development of suitable molecular assays for diagnosis and differentiation is challenging. This work focused on the establishment of a suitable real-time RT-PCR technique for rabies diagnosis as a complement to fluorescent antibody test and rabies tissue culture infection test as gold standard for diagnosis and confirmation. The real-time RT-PCR was adapted with the goal to detect the whole spectrum of lyssavirus species, for nine of which synthesized DNA fragments were used. For the detection of species, seven probes were developed. Serial dilutions of the rabies virus strain CVS-11 showed a 100-fold higher sensitivity of real-time PCR compared to heminested RT-PCR. Using a panel of thirty-one lyssaviruses representing four species, the suitability of the protocol could be shown. Phylogenetic analysis of the sequences obtained by heminested PCR allowed correct classification of all viruses used.

A framework for software fault tolerance in real-time systems

Science.gov (United States)

Anderson, T.; Knight, J. C.

1983-01-01

A classification scheme for errors and a technique for the provision of software fault tolerance in cyclic real-time systems is presented. The technique requires that the process structure of a system be represented by a synchronization graph which is used by an executive as a specification of the relative times at which they will communicate during execution. Communication between concurrent processes is severely limited and may only take place between processes engaged in an exchange. A history of error occurrences is maintained by an error handler. When an error is detected, the error handler classifies it using the error history information and then initiates appropriate recovery action.

Evolutionary Algorithms For Neural Networks Binary And Real Data Classification

Directory of Open Access Journals (Sweden)

Dr. Hanan A.R. Akkar

2015-08-01

Full Text Available Artificial neural networks are complex networks emulating the way human rational neurons process data. They have been widely used generally in prediction clustering classification and association. The training algorithms that used to determine the network weights are almost the most important factor that influence the neural networks performance. Recently many meta-heuristic and Evolutionary algorithms are employed to optimize neural networks weights to achieve better neural performance. This paper aims to use recently proposed algorithms for optimizing neural networks weights comparing these algorithms performance with other classical meta-heuristic algorithms used for the same purpose. However to evaluate the performance of such algorithms for training neural networks we examine such algorithms to classify four opposite binary XOR clusters and classification of continuous real data sets such as Iris and Ecoli.

A point implicit time integration technique for slow transient flow problems

Energy Technology Data Exchange (ETDEWEB)

Kadioglu, Samet Y., E-mail: kadioglu@yildiz.edu.tr [Department of Mathematical Engineering, Yildiz Technical University, 34210 Davutpasa-Esenler, Istanbul (Turkey); Berry, Ray A., E-mail: ray.berry@inl.gov [Idaho National Laboratory, P.O. Box 1625, MS 3840, Idaho Falls, ID 83415 (United States); Martineau, Richard C. [Idaho National Laboratory, P.O. Box 1625, MS 3840, Idaho Falls, ID 83415 (United States)

2015-05-15

Highlights: • This new method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods. • It is unconditionally stable, as a fully implicit method would be. • It exhibits the simplicity of implementation of an explicit method. • It is specifically designed for slow transient flow problems of long duration such as can occur inside nuclear reactor coolant systems. • Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust. - Abstract: We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very

A point implicit time integration technique for slow transient flow problems

International Nuclear Information System (INIS)

Kadioglu, Samet Y.; Berry, Ray A.; Martineau, Richard C.

2015-01-01

Highlights: • This new method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods. • It is unconditionally stable, as a fully implicit method would be. • It exhibits the simplicity of implementation of an explicit method. • It is specifically designed for slow transient flow problems of long duration such as can occur inside nuclear reactor coolant systems. • Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust. - Abstract: We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very

Merged Real Time GNSS Solutions for the READI System

Science.gov (United States)

Santillan, V. M.; Geng, J.

2014-12-01

Real-time measurements from increasingly dense Global Navigational Satellite Systems (GNSS) networks located throughout the western US offer a substantial, albeit largely untapped, contribution towards the mitigation of seismic and other natural hazards. Analyzed continuously in real-time, currently over 600 instruments blanket the San Andreas and Cascadia fault systems of the North American plate boundary and can provide on-the-fly characterization of transient ground displacements highly complementary to traditional seismic strong-motion monitoring. However, the utility of GNSS systems depends on their resolution, and merged solutions of two or more independent estimation strategies have been shown to offer lower scatter and higher resolution. Towards this end, independent real time GNSS solutions produced by Scripps Inst. of Oceanography and Central Washington University (PANGA) are now being formally combined in pursuit of NASA's Real-Time Earthquake Analysis for Disaster Mitigation (READI) positioning goals. CWU produces precise point positioning (PPP) solutions while SIO produces ambiguity resolved PPP solutions (PPP-AR). The PPP-AR solutions have a ~5 mm RMS scatter in the horizontal and ~10mm in the vertical, however PPP-AR solutions can take tens of minutes to re-converge in case of data gaps. The PPP solutions produced by CWU use pre-cleaned data in which biases are estimated as non-integer ambiguities prior to formal positioning with GIPSY 6.2 using a real time stream editor developed at CWU. These solutions show ~20mm RMS scatter in the horizontal and ~50mm RMS scatter in the vertical but re-converge within 2 min. or less following cycle-slips or data outages. We have implemented the formal combination of the CWU and SCRIPPS ENU displacements using the independent solutions as input measurements to a simple 3-element state Kalman filter plus white noise. We are now merging solutions from 90 stations, including 30 in Cascadia, 39 in the Bay Area, and 21

Essays in real-time forecasting

OpenAIRE

Liebermann, Joelle

2012-01-01

This thesis contains three essays in the field of real-time econometrics, and more particularlyforecasting.The issue of using data as available in real-time to forecasters, policymakers or financialmarkets is an important one which has only recently been taken on board in the empiricalliterature. Data available and used in real-time are preliminary and differ from ex-postrevised data, and given that data revisions may be quite substantial, the use of latestavailable instead of real-time can s...

Real-Time Classification of Seagrass Meadows on Flat Bottom with Bathymetric Data Measured by a Narrow Multibeam Sonar System

Directory of Open Access Journals (Sweden)

Masahiro Hamana

2016-01-01

Full Text Available Seagrass meadows, one of the most important habitats for many marine species, provide essential ecological services. Thus, society must conserve seagrass beds as part of their sustainable development efforts. Conserving these ecosystems requires information on seagrass distribution and relative abundance, and an efficient, accurate monitoring system. Although narrow multibeam sonar systems (NMBSs are highly effective in resolving seagrass beds, post-processing methods are required to extract key data. The purpose of this study was to develop a simple method capable of detecting seagrass meadows and estimating their relative abundance in real time using an NMBS. Because most seagrass meadows grow on sandy seafloors, we proposed a way of discriminating seagrass meadows from the sand bed. We classify meadows into three categories of relative seagrass abundance using the 95% confidence level of beam depths and the depth range of the beam depth. These are respectively two times the standard deviation of beam depths, and the difference between the shallowest and the deepest depths in a 0.5 × 0.5 m grid cell sampled with several narrow beams. We examined Zostera caulescens Miki, but this simple NMBS method of seagrass classification can potentially be used to map seagrass meadows with longer shoots of other species, such as Posidonia, as both have gas filled cavities.

Ovation Prime Real-Time

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Ovation Prime Real-Time (OPRT) product is a real-time forecast and nowcast model of auroral power and is an operational implementation of the work by Newell et...

Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry.

Science.gov (United States)

Bandura, Dmitry R; Baranov, Vladimir I; Ornatsky, Olga I; Antonov, Alexei; Kinach, Robert; Lou, Xudong; Pavlov, Serguei; Vorobiev, Sergey; Dick, John E; Tanner, Scott D

2009-08-15

A novel instrument for real time analysis of individual biological cells or other microparticles is described. The instrument is based on inductively coupled plasma time-of-flight mass spectrometry and comprises a three-aperture plasma-vacuum interface, a dc quadrupole turning optics for decoupling ions from neutral components, an rf quadrupole ion guide discriminating against low-mass dominant plasma ions, a point-to-parallel focusing dc quadrupole doublet, an orthogonal acceleration reflectron analyzer, a discrete dynode fast ion detector, and an 8-bit 1 GHz digitizer. A high spectrum generation frequency of 76.8 kHz provides capability for collecting multiple spectra from each particle-induced transient ion cloud, typically of 200-300 micros duration. It is shown that the transients can be resolved and characterized individually at a peak frequency of 1100 particles per second. Design considerations and optimization data are presented. The figures of merit of the instrument are measured under standard inductively coupled plasma (ICP) operating conditions ( 900 for m/z = 159, the sensitivity with a standard sample introduction system of >1.4 x 10(8) ion counts per second per mg L(-1) of Tb and an abundance sensitivity of (6 x 10(-4))-(1.4 x 10(-3)) (trailing and leading masses, respectively) are shown. The mass range (m/z = 125-215) and abundance sensitivity are sufficient for elemental immunoassay with up to 60 distinct available elemental tags. When 500) can be used, which provides >2.4 x 10(8) cps per mg L(-1) of Tb, at (1.5 x 10(-3))-(5.0 x 10(-3)) abundance sensitivity. The real-time simultaneous detection of multiple isotopes from individual 1.8 microm polystyrene beads labeled with lanthanides is shown. A real time single cell 20 antigen expression assay of model cell lines and leukemia patient samples immuno-labeled with lanthanide-tagged antibodies is presented.

Neural network recognition of nuclear power plant transients

International Nuclear Information System (INIS)

Bartlett, E.B.; Danofsky, R.; Adams, J.; AlJundi, T.; Basu, A.; Dhanwada, C.; Kerr, J.; Kim, K.; Lanc, T.

1993-01-01

The objective of this report is to describe results obtained during the first year of funding that will lead to the development of an artificial neural network (ANN) fault - diagnostic system for the real - time classification of operational transients at nuclear power plants. The ultimate goal of this three-year project is to design, build, and test a prototype diagnostic adviser for use in the control room or technical support center at Duane Arnold Energy Center (DAEC); such a prototype could be integrated into the plant process computer or safety - parameter display system. The adviser could then warn and inform plant operators and engineers of plant component failures in a timely manner. This report describes the work accomplished in the first of three scheduled years for the project. Included herein is a summary of the first year's results as, well as individual descriptions of each of the major topics undertaken by the researchers. Also included are reprints of the articles written under this funding as well as those that were published during the funded period

Real-time Holographic Display Based on a Super Fast Response Thin Film

International Nuclear Information System (INIS)

Gao, Hongyue; Li, Xiao; He, Zhenghong; Su, Yikai; Poon, Ting-Chung

2013-01-01

Real-time dynamic holographic display is obtained with super fast response in a thin film without any applied electric field. Holograms can be refreshed in the order of a millisecond and there is no cross talk between the recorded holograms because the hologram formed in the film is transient and can be completely self erased, and the hologram formation time and self-erasure time are both ∼1 ms. Holographic video display is achieved, which shows the real-time holographic image display capability of the thin film, and its much higher resolution than those of commercially available spatial light modulators. Furthermore, multiplexed hologram display using two polarization directions of a recorded light and multiple color holographic display at different laser wavelengths are presented, which demonstrate the feasibility of a RGB color holographic three-dimensional display with the thin film. Because the sample is easy to be fabricated into a large size screen and needs no external applied electric field, we think that the film can be developed into a large-size, dynamic, and color holographic three-dimensional display in the future.

Development of a transient identification and classification system to an integral pressurized water reactor

International Nuclear Information System (INIS)

Aronne, Ivan Dionysio

2009-01-01

The demand for energy in the modern world is growing, particularly in the developing countries. The nuclear options has been deserving prominence for their qualities of not impacting the environment through emissions of greenhouse gases and nor to demand great areas.. However society requests improvement in the safety of new reactors and the utilities request larger availability of the power plants. The IRIS project of an integral nuclear pressurized water reactor proposes to fulfill those requirements. A system for identification and classification of transients would help to improve the safety and to increase the availability of the IRIS increasing its competitiveness. In order to contribute to the development o such a system it was developed in this work a System for Identification and Classification of Transients - SDICT - capable of monitoring the operation of the reactor and of providing information on its operational state. SICT was developed using the technique of neural networks, more specifically the Self-Organizing Maps. Results of IRIS simulation with RELAP5 code were used to train the neural network of SICT. To demonstrate the correctness of the methodology of using simulations results, whose values have characteristics different from the measured ones, it was made a version of SICT for an experimental installation, the The Circuit no. 1 - CT1. Experiments were run in this test facility and simulations of its operation were done with RELAP5. This CT1 version of SICT was then checked against the simulation and experimental data validating the methodology. As a result of the activities to develop SICT, it is now available for futures studies: the developed application, SICT, a database of experiments in CT1, a validate nodalization of CT1, a database of results of CT1 simulations , a nodalization of the IRIS tested for several normal and abnormal transients and a database with the results of IRIS simulations. Attached to this thesis is a CD with the

International and Domestic Development Trends of Electromagnetic Transient Analysis Programs for Power Systems

Science.gov (United States)

Noda, Taku

Nowadays, there is quite high demand for electromagnetic transient (EMT) analysis programs and real-time simulators for power systems. In addition to the conventional demand such as overvoltage, over-current and oscillation simulations, the new demand that includes simulations of power-electronics circuits and power quality is increasing. With this background, development groups of EMT programs and real-time simulators have made progress in terms of computational performance and user experience. In Japan, Central Research Institute of Electric Power Industry has newly developed an EMT analysis program called XTAP (eXpandable Transient Analysis Program). This article overviews these international and domestic development trends of EMT analysis programs and real-time simulators.

VERSE - Virtual Equivalent Real-time Simulation

Science.gov (United States)

Zheng, Yang; Martin, Bryan J.; Villaume, Nathaniel

2005-01-01

Distributed real-time simulations provide important timing validation and hardware in the- loop results for the spacecraft flight software development cycle. Occasionally, the need for higher fidelity modeling and more comprehensive debugging capabilities - combined with a limited amount of computational resources - calls for a non real-time simulation environment that mimics the real-time environment. By creating a non real-time environment that accommodates simulations and flight software designed for a multi-CPU real-time system, we can save development time, cut mission costs, and reduce the likelihood of errors. This paper presents such a solution: Virtual Equivalent Real-time Simulation Environment (VERSE). VERSE turns the real-time operating system RTAI (Real-time Application Interface) into an event driven simulator that runs in virtual real time. Designed to keep the original RTAI architecture as intact as possible, and therefore inheriting RTAI's many capabilities, VERSE was implemented with remarkably little change to the RTAI source code. This small footprint together with use of the same API allows users to easily run the same application in both real-time and virtual time environments. VERSE has been used to build a workstation testbed for NASA's Space Interferometry Mission (SIM PlanetQuest) instrument flight software. With its flexible simulation controls and inexpensive setup and replication costs, VERSE will become an invaluable tool in future mission development.

The psychophysiology of real-time financial risk processing.

Science.gov (United States)

Lo, Andrew W; Repin, Dmitry V

2002-04-01

A longstanding controversy in economics and finance is whether financial markets are governed by rational forces or by emotional responses. We study the importance of emotion in the decision-making process of professional securities traders by measuring their physiological characteristics (e.g., skin conductance, blood volume pulse, etc.) during live trading sessions while simultaneously capturing real-time prices from which market events can be detected. In a sample of 10 traders, we find statistically significant differences in mean electrodermal responses during transient market events relative to no-event control periods, and statistically significant mean changes in cardiovascular variables during periods of heightened market volatility relative to normal-volatility control periods. We also observe significant differences in these physiological responses across the 10 traders that may be systematically related to the traders' levels of experience.

Time series classification using k-Nearest neighbours, Multilayer Perceptron and Learning Vector Quantization algorithms

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2012-01-01

Full Text Available We are presenting results comparison of three artificial intelligence algorithms in a classification of time series derived from musical excerpts in this paper. Algorithms were chosen to represent different principles of classification – statistic approach, neural networks and competitive learning. The first algorithm is a classical k-Nearest neighbours algorithm, the second algorithm is Multilayer Perceptron (MPL, an example of artificial neural network and the third one is a Learning Vector Quantization (LVQ algorithm representing supervised counterpart to unsupervised Self Organizing Map (SOM.After our own former experiments with unlabelled data we moved forward to the data labels utilization, which generally led to a better accuracy of classification results. As we need huge data set of labelled time series (a priori knowledge of correct class which each time series instance belongs to, we used, with a good experience in former studies, musical excerpts as a source of real-world time series. We are using standard deviation of the sound signal as a descriptor of a musical excerpts volume level.We are describing principle of each algorithm as well as its implementation briefly, giving links for further research. Classification results of each algorithm are presented in a confusion matrix showing numbers of misclassifications and allowing to evaluate overall accuracy of the algorithm. Results are compared and particular misclassifications are discussed for each algorithm. Finally the best solution is chosen and further research goals are given.

ISTTOK real-time architecture

Energy Technology Data Exchange (ETDEWEB)

Carvalho, Ivo S., E-mail: ivoc@ipfn.ist.utl.pt; Duarte, Paulo; Fernandes, Horácio; Valcárcel, Daniel F.; Carvalho, Pedro J.; Silva, Carlos; Duarte, André S.; Neto, André; Sousa, Jorge; Batista, António J.N.; Hekkert, Tiago; Carvalho, Bernardo B.

2014-03-15

Highlights: • All real-time diagnostics and actuators were integrated in the same control platform. • A 100 μs control cycle was achieved under the MARTe framework. • Time-windows based control with several event-driven control strategies implemented. • AC discharges with exception handling on iron core flux saturation. • An HTML discharge configuration was developed for configuring the MARTe system. - Abstract: The ISTTOK tokamak was upgraded with a plasma control system based on the Advanced Telecommunications Computing Architecture (ATCA) standard. This control system was designed to improve the discharge stability and to extend the operational space to the alternate plasma current (AC) discharges as part of the ISTTOK scientific program. In order to accomplish these objectives all ISTTOK diagnostics and actuators relevant for real-time operation were integrated in the control system. The control system was programmed in C++ over the Multi-threaded Application Real-Time executor (MARTe) which provides, among other features, a real-time scheduler, an interrupt handler, an intercommunications interface between code blocks and a clearly bounded interface with the external devices. As a complement to the MARTe framework, the BaseLib2 library provides the foundations for the data, code introspection and also a Hypertext Transfer Protocol (HTTP) server service. Taking advantage of the modular nature of MARTe, the algorithms of each diagnostic data processing, discharge timing, context switch, control and actuators output reference generation, run on well-defined blocks of code named Generic Application Module (GAM). This approach allows reusability of the code, simplified simulation, replacement or editing without changing the remaining GAMs. The ISTTOK control system GAMs run sequentially each 100 μs cycle on an Intel{sup ®} Q8200 4-core processor running at 2.33 GHz located in the ATCA crate. Two boards (inside the ATCA crate) with 32 analog

ISTTOK real-time architecture

International Nuclear Information System (INIS)

Carvalho, Ivo S.; Duarte, Paulo; Fernandes, Horácio; Valcárcel, Daniel F.; Carvalho, Pedro J.; Silva, Carlos; Duarte, André S.; Neto, André; Sousa, Jorge; Batista, António J.N.; Hekkert, Tiago; Carvalho, Bernardo B.

2014-01-01

Highlights: • All real-time diagnostics and actuators were integrated in the same control platform. • A 100 μs control cycle was achieved under the MARTe framework. • Time-windows based control with several event-driven control strategies implemented. • AC discharges with exception handling on iron core flux saturation. • An HTML discharge configuration was developed for configuring the MARTe system. - Abstract: The ISTTOK tokamak was upgraded with a plasma control system based on the Advanced Telecommunications Computing Architecture (ATCA) standard. This control system was designed to improve the discharge stability and to extend the operational space to the alternate plasma current (AC) discharges as part of the ISTTOK scientific program. In order to accomplish these objectives all ISTTOK diagnostics and actuators relevant for real-time operation were integrated in the control system. The control system was programmed in C++ over the Multi-threaded Application Real-Time executor (MARTe) which provides, among other features, a real-time scheduler, an interrupt handler, an intercommunications interface between code blocks and a clearly bounded interface with the external devices. As a complement to the MARTe framework, the BaseLib2 library provides the foundations for the data, code introspection and also a Hypertext Transfer Protocol (HTTP) server service. Taking advantage of the modular nature of MARTe, the algorithms of each diagnostic data processing, discharge timing, context switch, control and actuators output reference generation, run on well-defined blocks of code named Generic Application Module (GAM). This approach allows reusability of the code, simplified simulation, replacement or editing without changing the remaining GAMs. The ISTTOK control system GAMs run sequentially each 100 μs cycle on an Intel ® Q8200 4-core processor running at 2.33 GHz located in the ATCA crate. Two boards (inside the ATCA crate) with 32 analog

Pornography classification: The hidden clues in video space-time.

Science.gov (United States)

Moreira, Daniel; Avila, Sandra; Perez, Mauricio; Moraes, Daniel; Testoni, Vanessa; Valle, Eduardo; Goldenstein, Siome; Rocha, Anderson

2016-11-01

As web technologies and social networks become part of the general public's life, the problem of automatically detecting pornography is into every parent's mind - nobody feels completely safe when their children go online. In this paper, we focus on video-pornography classification, a hard problem in which traditional methods often employ still-image techniques - labeling frames individually prior to a global decision. Frame-based approaches, however, ignore significant cogent information brought by motion. Here, we introduce a space-temporal interest point detector and descriptor called Temporal Robust Features (TRoF). TRoF was custom-tailored for efficient (low processing time and memory footprint) and effective (high classification accuracy and low false negative rate) motion description, particularly suited to the task at hand. We aggregate local information extracted by TRoF into a mid-level representation using Fisher Vectors, the state-of-the-art model of Bags of Visual Words (BoVW). We evaluate our original strategy, contrasting it both to commercial pornography detection solutions, and to BoVW solutions based upon other space-temporal features from the scientific literature. The performance is assessed using the Pornography-2k dataset, a new challenging pornographic benchmark, comprising 2000 web videos and 140h of video footage. The dataset is also a contribution of this work and is very assorted, including both professional and amateur content, and it depicts several genres of pornography, from cartoon to live action, with diverse behavior and ethnicity. The best approach, based on a dense application of TRoF, yields a classification error reduction of almost 79% when compared to the best commercial classifier. A sparse description relying on TRoF detector is also noteworthy, for yielding a classification error reduction of over 69%, with 19× less memory footprint than the dense solution, and yet can also be implemented to meet real-time requirements

Food for Thought: Cross-Classification and Category Organization in a Complex Real-World Domain.

Science.gov (United States)

Ross, Brian H.; Murphy, Gregory L.

1999-01-01

Seven studies involving 256 undergraduates examined how people represent, access, and make inferences about the real-world category domain, foods. Results give a detailed picture of the use of cross-classification in a complex domain. (SLD)

Real-time single-molecule co-immunoprecipitation analyses reveal cancer-specific Ras signalling dynamics

Science.gov (United States)

Lee, Hong-Won; Kyung, Taeyoon; Yoo, Janghyun; Kim, Tackhoon; Chung, Chaeuk; Ryu, Ji Young; Lee, Hanki; Park, Kihyun; Lee, Sangkyu; Jones, Walton D.; Lim, Dae-Sik; Hyeon, Changbong; Do Heo, Won; Yoon, Tae-Young

2013-01-01

Co-immunoprecipitation (co-IP) has become a standard technique, but its protein-band output provides only static, qualitative information about protein–protein interactions. Here we demonstrate a real-time single-molecule co-IP technique that generates real-time videos of individual protein–protein interactions as they occur in unpurified cell extracts. By analysing single Ras–Raf interactions with a 50-ms time resolution, we have observed transient intermediates of the protein–protein interaction and determined all the essential kinetic rates. Using this technique, we have quantified the active fraction of native Ras proteins in xenograft tumours, normal tissue and cancer cell lines. We demonstrate that the oncogenic Ras mutations selectively increase the active-Ras fraction by one order of magnitude, without affecting total Ras levels or single-molecule signalling kinetics. Our approach allows us to probe the previously hidden, dynamic aspects of weak protein–protein interactions. It also suggests a path forward towards precision molecular diagnostics at the protein–protein interaction level. PMID:23422673

Analysis of core uncovery time in Kuosheng station blackout transient with MELCOR

International Nuclear Information System (INIS)

Wang, S.J.; Chien, C.S.

1996-01-01

The MELCOR code, developed by the Sandia National Laboratories, is capable of simulating severe accident phenomena of nuclear power plants. Core uncovery time is an important parameter in the probabilistic risk assessment. However, many MELCOR users do not generate the initial conditions in a station blackout (SBO) transient analysis. Thus, achieving reliable core uncovery time is difficult. The core uncovery time for the Kuosheng nuclear power plant during an SBO transient is analyzed. First, full-power steady-state conditions are generated with the application of a developed self-initialization algorithm. Then the response of the SBO transient up to core uncovery is simulated. The effects of key parameters including the initialization process and the reactor feed pump (RFP) coastdown time on the core uncovery time are analyzed. The initialization process is the most important parameter that affects the core uncovery time. Because SBO transient analysis, the correct initial conditions must be generated to achieve a reliable core uncovery time. The core uncovery time is also sensitive to the RFP coastdown time. A correct time constant is required

Nuclear power plant transient diagnostics using artificial neural networks that allow ''don't-know'' classifications

International Nuclear Information System (INIS)

Bartal, Y.; Lin, J.; Uhrig, R.E.

1995-01-01

A nuclear power plant's (NPP's) status is usually monitored by a human operator. Any classifier system used to enhance the operator's capability to diagnose a safety-critical system like an NPP should classify a novel transient as ''don't-know'' if it is not contained within its accumulated knowledge base. In particular, the classifier needs some kind of proximity measure between the new data and its training set. Artificial neural networks have been proposed as NPP classifiers, the most popular ones being the multilayered perceptron (MLP) type. However, MLPs do not have a proximity measure, while learning vector quantization, probabilistic neural networks (PNNs), and some others do. This proximity measure may also serve as an explanation to the classifier's decision in the way that case-based-reasoning expert systems do. The capability of a PNN network as a classifier is demonstrated using simulator data for the three-loop 436-MW(electric) Westinghouse San Onofre unit 1 pressurized water reactor. A transient's classification history is used in an ''evidence accumulation'' technique to enhance a classifier's accuracy as well as its consistency

simulation of electromagnetic transients in power systems

African Journals Online (AJOL)

Dr Obe

1996-09-01

Sep 1, 1996 ... Transients in power systems are initiated by abrupt changes to otherwise steady operating conditions. These changes would .... The method is applicable both to single transmission in real time. The method is applicable both ...

A real-time expert system for nuclear power plant failure diagnosis and operational guide

International Nuclear Information System (INIS)

Naito, N.; Sakuma, A.; Shigeno, K.; Mori, N.

1987-01-01

A real-time expert system (DIAREX) has been developed to diagnose plant failure and to offer a corrective operational guide for boiling water reactor (BWR) power plants. The failure diagnosis model used in DIAREX was systematically developed, based mainly on deep knowledge, to cover heuristics. Complex paradigms for knowledge representation were adopted, i.e., the process representation language and the failure propagation tree. The system is composed of a knowledge base, knowledge base editor, preprocessor, diagnosis processor, and display processor. The DIAREX simulation test has been carried out for many transient scenarios, including multiple failures, using a real-time full-scope simulator modeled after the 1100-MW(electric) BWR power plant. Test results showed that DIAREX was capable of diagnosing a plant failure quickly and of providing a corrective operational guide with a response time fast enough to offer valuable information to plant operators

Classification of brain tumours using short echo time 1H MR spectra

Science.gov (United States)

Devos, A.; Lukas, L.; Suykens, J. A. K.; Vanhamme, L.; Tate, A. R.; Howe, F. A.; Majós, C.; Moreno-Torres, A.; van der Graaf, M.; Arús, C.; Van Huffel, S.

2004-09-01

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas ( n = 87), meningiomas ( n = 57), metastases ( n = 39), and astrocytomas grade II ( n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

Real-Time Shear Wave versus Transient Elastography for Predicting Fibrosis: Applicability, and Impact of Inflammation and Steatosis. A Non-Invasive Comparison.

Science.gov (United States)

Poynard, Thierry; Pham, Tam; Perazzo, Hugo; Munteanu, Mona; Luckina, Elena; Elaribi, Djamel; Ngo, Yen; Bonyhay, Luminita; Seurat, Noemie; Legroux, Muriel; Ngo, An; Deckmyn, Olivier; Thabut, Dominique; Ratziu, Vlad; Lucidarme, Olivier

2016-01-01

Real-time shear wave elastography (2D-SWE) is a two-dimensional transient elastography and a competitor as a biomarker of liver fibrosis in comparison with the standard reference transient elastography by M probe (TE-M). The aims were to compare several criteria of applicability, and to assess inflammation and steatosis impact on elasticity values, two unmet needs. We took FibroTest as the fibrosis reference and ActiTest and SteatoTest as quantitative estimates of inflammation and steatosis. After standardization of estimates, analyses used curve fitting, quantitative Lin concordance coefficient [LCC], and multivariate logistic regression. A total of 2,251 consecutive patients were included. We validated the predetermined 0.2 kPa cut-off as a too low minimal elasticity value identifying not-reliable 2D-SWE results (LCC with FibroTest = 0.0281[-0.119;0.175]. Other criteria, elasticity CV, body mass index and depth of measures were not sufficiently discriminant. The applicability of 2D-SWE (95%CI) 89.6%(88.2-90.8), was significantly higher than that of TE, 85.6%(84.0-87.0; P<0.0001). In patients with non-advanced fibrosis (METAVIR F0F1F2), elasticity values estimated by 2D-SWE was less impacted by inflammation and steatosis than elasticity value estimated by TE-M: LCC (95%CI) 0.039 (0.021;0.058) vs 0.090 (0.068;0.112;P<0.01) and 0.105 (0.068;0.141) vs 0.192 (0.153;0.230; P<0.01) respectively. The three analyses methods gave similar results. Elasticity results including very low minimal signal in the region of interest should be considered not reliable. 2D-SWE had a higher applicability than TE, the reference elastography, with less impact of inflammation and steatosis especially in patients with non-advanced fibrosis, as presumed by blood tests. ClinicalTrials.gov NCT01927133.

Real-Time Shear Wave versus Transient Elastography for Predicting Fibrosis: Applicability, and Impact of Inflammation and Steatosis. A Non-Invasive Comparison.

Directory of Open Access Journals (Sweden)

Thierry Poynard

Full Text Available Real-time shear wave elastography (2D-SWE is a two-dimensional transient elastography and a competitor as a biomarker of liver fibrosis in comparison with the standard reference transient elastography by M probe (TE-M. The aims were to compare several criteria of applicability, and to assess inflammation and steatosis impact on elasticity values, two unmet needs.We took FibroTest as the fibrosis reference and ActiTest and SteatoTest as quantitative estimates of inflammation and steatosis. After standardization of estimates, analyses used curve fitting, quantitative Lin concordance coefficient [LCC], and multivariate logistic regression.A total of 2,251 consecutive patients were included. We validated the predetermined 0.2 kPa cut-off as a too low minimal elasticity value identifying not-reliable 2D-SWE results (LCC with FibroTest = 0.0281[-0.119;0.175]. Other criteria, elasticity CV, body mass index and depth of measures were not sufficiently discriminant. The applicability of 2D-SWE (95%CI 89.6%(88.2-90.8, was significantly higher than that of TE, 85.6%(84.0-87.0; P<0.0001. In patients with non-advanced fibrosis (METAVIR F0F1F2, elasticity values estimated by 2D-SWE was less impacted by inflammation and steatosis than elasticity value estimated by TE-M: LCC (95%CI 0.039 (0.021;0.058 vs 0.090 (0.068;0.112;P<0.01 and 0.105 (0.068;0.141 vs 0.192 (0.153;0.230; P<0.01 respectively. The three analyses methods gave similar results.Elasticity results including very low minimal signal in the region of interest should be considered not reliable. 2D-SWE had a higher applicability than TE, the reference elastography, with less impact of inflammation and steatosis especially in patients with non-advanced fibrosis, as presumed by blood tests.ClinicalTrials.gov NCT01927133.

A real-time architecture for time-aware agents.

Science.gov (United States)

Prouskas, Konstantinos-Vassileios; Pitt, Jeremy V

2004-06-01

This paper describes the specification and implementation of a new three-layer time-aware agent architecture. This architecture is designed for applications and environments where societies of humans and agents play equally active roles, but interact and operate in completely different time frames. The architecture consists of three layers: the April real-time run-time (ART) layer, the time aware layer (TAL), and the application agents layer (AAL). The ART layer forms the underlying real-time agent platform. An original online, real-time, dynamic priority-based scheduling algorithm is described for scheduling the computation time of agent processes, and it is shown that the algorithm's O(n) complexity and scalable performance are sufficient for application in real-time domains. The TAL layer forms an abstraction layer through which human and agent interactions are temporally unified, that is, handled in a common way irrespective of their temporal representation and scale. A novel O(n2) interaction scheduling algorithm is described for predicting and guaranteeing interactions' initiation and completion times. The time-aware predicting component of a workflow management system is also presented as an instance of the AAL layer. The described time-aware architecture addresses two key challenges in enabling agents to be effectively configured and applied in environments where humans and agents play equally active roles. It provides flexibility and adaptability in its real-time mechanisms while placing them under direct agent control, and it temporally unifies human and agent interactions.

Towards Real-Time Argumentation

Directory of Open Access Journals (Sweden)

Vicente JULIÁN

2016-07-01

Full Text Available In this paper, we deal with the problem of real-time coordination with the more general approach of reaching real-time agreements in MAS. Concretely, this work proposes a real-time argumentation framework in an attempt to provide agents with the ability of engaging in argumentative dialogues and come with a solution for their underlying agreement process within a bounded period of time. The framework has been implemented and evaluated in the domain of a customer support application. Concretely, we consider a society of agents that act on behalf of a group of technicians that must solve problems in a Technology Management Centre (TMC within a bounded time. This centre controls every process implicated in the provision of technological and customer support services to private or public organisations by means of a call centre. The contract signed between the TCM and the customer establishes penalties if the specified time is exceeded.

REAL-TIME EMISSION CHARACTERIZATION OF ORGANIC AIR TOXIC POLLUTANTS DURING STEADY STATE AND TRANSIENT OPERATION OF A MEDIUM DUTY DIESEL ENGINE

Science.gov (United States)

An on-line monitoring method, jet resonance-enhanced multi-photon ionization (REMPI) with time-of-flight mass spectrometry (TOFMS) was used to measure emissions of organic air toxics from a medium-duty (60 kW)diesel generator during transient and steady state operations. Emission...

Real-time PCR in virology.

Science.gov (United States)

Mackay, Ian M; Arden, Katherine E; Nitsche, Andreas

2002-03-15

The use of the polymerase chain reaction (PCR) in molecular diagnostics has increased to the point where it is now accepted as the gold standard for detecting nucleic acids from a number of origins and it has become an essential tool in the research laboratory. Real-time PCR has engendered wider acceptance of the PCR due to its improved rapidity, sensitivity, reproducibility and the reduced risk of carry-over contamination. There are currently five main chemistries used for the detection of PCR product during real-time PCR. These are the DNA binding fluorophores, the 5' endonuclease, adjacent linear and hairpin oligoprobes and the self-fluorescing amplicons, which are described in detail. We also discuss factors that have restricted the development of multiplex real-time PCR as well as the role of real-time PCR in quantitating nucleic acids. Both amplification hardware and the fluorogenic detection chemistries have evolved rapidly as the understanding of real-time PCR has developed and this review aims to update the scientist on the current state of the art. We describe the background, advantages and limitations of real-time PCR and we review the literature as it applies to virus detection in the routine and research laboratory in order to focus on one of the many areas in which the application of real-time PCR has provided significant methodological benefits and improved patient outcomes. However, the technology discussed has been applied to other areas of microbiology as well as studies of gene expression and genetic disease.

Classification of Real and Imagined Sounds in Early Visual Cortex

Directory of Open Access Journals (Sweden)

Petra Vetter

2011-10-01

Full Text Available Early visual cortex has been thought to be mainly involved in the detection of low-level visual features. Here we show that complex natural sounds can be decoded from early visual cortex activity, in the absence of visual stimulation and both when sounds are actually displayed and when they are merely imagined. Blindfolded subjects listened to three complex natural sounds (bird singing, people talking, traffic noise; Exp. 1 or received word cues (“forest”, “people”, “traffic”; Exp 2 to imagine the associated scene. fMRI BOLD activation patterns from retinotopically defined early visual areas were fed into a multivariate pattern classification algorithm (a linear support vector machine. Actual sounds were discriminated above chance in V2 and V3 and imagined sounds were decoded in V1. Also cross-classification, ie, training the classifier to real sounds and testing it to imagined sounds and vice versa, was successful. Two further experiments showed that an orthogonal working memory task does not interfere with sound classification in early visual cortex (Exp. 3, however, an orthogonal visuo-spatial imagery task does (Exp. 4. These results demonstrate that early visual cortex activity contains content-specific information from hearing and from imagery, challenging the view of a strict modality-specific function of early visual cortex.

Quest for the real-time for the safety analysis code Cathare 2 used in the post-accident simulator Sipa

International Nuclear Information System (INIS)

Ruby, A.; Antoni, O.; Rose, Ch.; Iffenecker, F.

2003-01-01

The aim of the SCAR project is to use the CATHARE French thermal-hydraulic accident code in the SIPA simulator (Post-Accident Simulator) and extend SIPA to reactor cold shutdown states. The quest for real-time has been one of the key themes of the project since it began in 1997. The required CPU time depends on the computing power and on the ability of CATHARE to converge as fast as possible on the solution. Three main tasks have been scheduled to contain the lag between the simulation and the real-time: -1) Parallelism in CATHARE has been developed with shared-memory model (using OPEN MP). Standardized and adapted to the numerical method and the structure of CATHARE, it has enabled parallel tasks in 95% of the code with efficient parallel loops on the elements, and an optimized but limited parallelism in the solver. Validation has been carried out all along the task, ensuring the binary identity of results for 10 representative accident transients, whatever the number of processors used on each computer of the SCAR project. -2) Convergence has been improved for 20 CATHARE transients, ranging from the 100% full power state to cold-shutdown for maintenance state. A method based on the definition of maximum lag criteria in function of an estimated power of computers has been developed, revealing coding errors and leading to numerical improvements without any regression of physical law validation. A second phase has started in 2003 on another series of 25 transients within the simulator. -3) A techno-watch policy (using benchmarking) has allowed to keep up to date with progress in computer power throughout the duration of the project. It has consisted in comparing the performance of computers for 12 standard CATHARE input decks using an elementary time relevant of the computing machines for a given modeling of plant series. Furthermore, development validation and performance assessment tools have been developed at the same time. As a result of these three tasks

Quest for the real-time for the safety analysis code Cathare 2 used in the post-accident simulator Sipa

Energy Technology Data Exchange (ETDEWEB)

Ruby, A.; Antoni, O. [CEA Grenoble, 38 (France). Dept. de Thermohydraulique et de Physique; Creach, V.; Dufeil, Ph. [Institut de Radioprotection et de Surete Nucleaire (IRSN), 92 - Clamart (France); Rose, Ch.; Iffenecker, F. [Electricite de France, 75 - Paris (France)

2003-07-01

The aim of the SCAR project is to use the CATHARE French thermal-hydraulic accident code in the SIPA simulator (Post-Accident Simulator) and extend SIPA to reactor cold shutdown states. The quest for real-time has been one of the key themes of the project since it began in 1997. The required CPU time depends on the computing power and on the ability of CATHARE to converge as fast as possible on the solution. Three main tasks have been scheduled to contain the lag between the simulation and the real-time: -1) Parallelism in CATHARE has been developed with shared-memory model (using OPEN MP). Standardized and adapted to the numerical method and the structure of CATHARE, it has enabled parallel tasks in 95% of the code with efficient parallel loops on the elements, and an optimized but limited parallelism in the solver. Validation has been carried out all along the task, ensuring the binary identity of results for 10 representative accident transients, whatever the number of processors used on each computer of the SCAR project. -2) Convergence has been improved for 20 CATHARE transients, ranging from the 100% full power state to cold-shutdown for maintenance state. A method based on the definition of maximum lag criteria in function of an estimated power of computers has been developed, revealing coding errors and leading to numerical improvements without any regression of physical law validation. A second phase has started in 2003 on another series of 25 transients within the simulator. -3) A techno-watch policy (using benchmarking) has allowed to keep up to date with progress in computer power throughout the duration of the project. It has consisted in comparing the performance of computers for 12 standard CATHARE input decks using an elementary time relevant of the computing machines for a given modeling of plant series. Furthermore, development validation and performance assessment tools have been developed at the same time. As a result of these three tasks

Real time programming environment for Windows

Energy Technology Data Exchange (ETDEWEB)

LaBelle, D.R. [LaBelle (Dennis R.), Clifton Park, NY (United States)

1998-04-01

This document provides a description of the Real Time Programming Environment (RTProE). RTProE tools allow a programmer to create soft real time projects under general, multi-purpose operating systems. The basic features necessary for real time applications are provided by RTProE, leaving the programmer free to concentrate efforts on his specific project. The current version supports Microsoft Windows{trademark} 95 and NT. The tasks of real time synchronization and communication with other programs are handled by RTProE. RTProE includes a generic method for connecting a graphical user interface (GUI) to allow real time control and interaction with the programmer`s product. Topics covered in this paper include real time performance issues, portability, details of shared memory management, code scheduling, application control, Operating System specific concerns and the use of Computer Aided Software Engineering (CASE) tools. The development of RTProE is an important step in the expansion of the real time programming community. The financial costs associated with using the system are minimal. All source code for RTProE has been made publicly available. Any person with access to a personal computer, Windows 95 or NT, and C or FORTRAN compilers can quickly enter the world of real time modeling and simulation.

An In-Home Digital Network Architecture for Real-Time and Non-Real-Time Communication

NARCIS (Netherlands)

Scholten, Johan; Jansen, P.G.; Hanssen, F.T.Y.; Hattink, Tjalling

2002-01-01

This paper describes an in-home digital network architecture that supports both real-time and non-real-time communication. The architecture deploys a distributed token mechanism to schedule communication streams and to offer guaranteed quality-ofservice. Essentially, the token mechanism prevents

A real-time heat strain risk classifier using heart rate and skin temperature

International Nuclear Information System (INIS)

Buller, Mark J; Latzka, William A; Yokota, Miyo; Tharion, William J; Moran, Daniel S

2008-01-01

Heat injury is a real concern to workers engaged in physically demanding tasks in high heat strain environments. Several real-time physiological monitoring systems exist that can provide indices of heat strain, e.g. physiological strain index (PSI), and provide alerts to medical personnel. However, these systems depend on core temperature measurement using expensive, ingestible thermometer pills. Seeking a better solution, we suggest the use of a model which can identify the probability that individuals are 'at risk' from heat injury using non-invasive measures. The intent is for the system to identify individuals who need monitoring more closely or who should apply heat strain mitigation strategies. We generated a model that can identify 'at risk' (PSI ≥ 7.5) workers from measures of heart rate and chest skin temperature. The model was built using data from six previously published exercise studies in which some subjects wore chemical protective equipment. The model has an overall classification error rate of 10% with one false negative error (2.7%), and outperforms an earlier model and a least squares regression model with classification errors of 21% and 14%, respectively. Additionally, the model allows the classification criteria to be adjusted based on the task and acceptable level of risk. We conclude that the model could be a valuable part of a multi-faceted heat strain management system. (note)

CATALisp - an expert system for real-time diagnosis of multiple-failure transients in pressurized water reactors

International Nuclear Information System (INIS)

Martin, R.P.; Nassersharif, B.

1988-01-01

The state of the art in artificial intelligence (AI) and expert system (ES) technology has matured to a degree that the potential development of a computer-aided/automated diagnostic and transient mitigation system in the area of nuclear reactor operation can be considered. Since traditional methods cannot handle complex systems efficiently, AI techniques provide a means to emulate an expert reactor operator rather than follow mechanistic methods. Computer-aided transient analysis coded in LISP (CATA-Lisp) is a confidence level based expert system written in Common LISP on the SYMBOLICS 3640 computer system. New versions are being developed in Common LISP for the Texas Instruments (TI) Explorer and the Sun microsystems machines, CATALisp manipulates both a knowledge base of transient identifier patterns (tree structured to allow for zooming in diagnostics) and a knowledge base containing a qualitative model of a nuclear power plant. The interference engine used by CATALisp uses the information stored in both knowledge bases to arrive at confidence level values that are used to infer particular plant states

MARTe: A Multiplatform Real-Time Framework

Science.gov (United States)

Neto, André C.; Sartori, Filippo; Piccolo, Fabio; Vitelli, Riccardo; De Tommasi, Gianmaria; Zabeo, Luca; Barbalace, Antonio; Fernandes, Horacio; Valcarcel, Daniel F.; Batista, Antonio J. N.

2010-04-01

Development of real-time applications is usually associated with nonportable code targeted at specific real-time operating systems. The boundary between hardware drivers, system services, and user code is commonly not well defined, making the development in the target host significantly difficult. The Multithreaded Application Real-Time executor (MARTe) is a framework built over a multiplatform library that allows the execution of the same code in different operating systems. The framework provides the high-level interfaces with hardware, external configuration programs, and user interfaces, assuring at the same time hard real-time performances. End-users of the framework are required to define and implement algorithms inside a well-defined block of software, named Generic Application Module (GAM), that is executed by the real-time scheduler. Each GAM is reconfigurable with a set of predefined configuration meta-parameters and interchanges information using a set of data pipes that are provided as inputs and required as output. Using these connections, different GAMs can be chained either in series or parallel. GAMs can be developed and debugged in a non-real-time system and, only once the robustness of the code and correctness of the algorithm are verified, deployed to the real-time system. The software also supplies a large set of utilities that greatly ease the interaction and debugging of a running system. Among the most useful are a highly efficient real-time logger, HTTP introspection of real-time objects, and HTTP remote configuration. MARTe is currently being used to successfully drive the plasma vertical stabilization controller on the largest magnetic confinement fusion device in the world, with a control loop cycle of 50 ?s and a jitter under 1 ?s. In this particular project, MARTe is used with the Real-Time Application Interface (RTAI)/Linux operating system exploiting the new ?86 multicore processors technology.

Real-Time and Real-Fast Performance of General-Purpose and Real-Time Operating Systems in Multithreaded Physical Simulation of Complex Mechanical Systems

Directory of Open Access Journals (Sweden)

Carlos Garre

2014-01-01

Full Text Available Physical simulation is a valuable tool in many fields of engineering for the tasks of design, prototyping, and testing. General-purpose operating systems (GPOS are designed for real-fast tasks, such as offline simulation of complex physical models that should finish as soon as possible. Interfacing hardware at a given rate (as in a hardware-in-the-loop test requires instead maximizing time determinism, for which real-time operating systems (RTOS are designed. In this paper, real-fast and real-time performance of RTOS and GPOS are compared when simulating models of high complexity with large time steps. This type of applications is usually present in the automotive industry and requires a good trade-off between real-fast and real-time performance. The performance of an RTOS and a GPOS is compared by running a tire model scalable on the number of degrees-of-freedom and parallel threads. The benchmark shows that the GPOS present better performance in real-fast runs but worse in real-time due to nonexplicit task switches and to the latency associated with interprocess communication (IPC and task switch.

Simulating transient dynamics of the time-dependent time fractional Fokker–Planck systems

Energy Technology Data Exchange (ETDEWEB)

Kang, Yan-Mei, E-mail: ymkang@mail.xjtu.edu.cn

2016-09-16

For a physically realistic type of time-dependent time fractional Fokker–Planck (FP) equation, derived as the continuous limit of the continuous time random walk with time-modulated Boltzmann jumping weight, a semi-analytic iteration scheme based on the truncated (generalized) Fourier series is presented to simulate the resultant transient dynamics when the external time modulation is a piece-wise constant signal. At first, the iteration scheme is demonstrated with a simple time-dependent time fractional FP equation on finite interval with two absorbing boundaries, and then it is generalized to the more general time-dependent Smoluchowski-type time fractional Fokker–Planck equation. The numerical examples verify the efficiency and accuracy of the iteration method, and some novel dynamical phenomena including polarized motion orientations and periodic response death are discussed. - Highlights: • An iteration method is proposed for the transient dynamics of time-dependent time fractional Fokker–Planck equations. • The method is based on Fourier Series solution and the multi-step transition probability formula. • With the time-modulated subdiffusion on finite interval as example, the polarized motion orientation is disclosed. • With the time-modulated subdiffusion within a confined potential as example, the death of dynamic response is observed.

Simulating transient dynamics of the time-dependent time fractional Fokker–Planck systems

International Nuclear Information System (INIS)

Kang, Yan-Mei

2016-01-01

For a physically realistic type of time-dependent time fractional Fokker–Planck (FP) equation, derived as the continuous limit of the continuous time random walk with time-modulated Boltzmann jumping weight, a semi-analytic iteration scheme based on the truncated (generalized) Fourier series is presented to simulate the resultant transient dynamics when the external time modulation is a piece-wise constant signal. At first, the iteration scheme is demonstrated with a simple time-dependent time fractional FP equation on finite interval with two absorbing boundaries, and then it is generalized to the more general time-dependent Smoluchowski-type time fractional Fokker–Planck equation. The numerical examples verify the efficiency and accuracy of the iteration method, and some novel dynamical phenomena including polarized motion orientations and periodic response death are discussed. - Highlights: • An iteration method is proposed for the transient dynamics of time-dependent time fractional Fokker–Planck equations. • The method is based on Fourier Series solution and the multi-step transition probability formula. • With the time-modulated subdiffusion on finite interval as example, the polarized motion orientation is disclosed. • With the time-modulated subdiffusion within a confined potential as example, the death of dynamic response is observed.

GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

Science.gov (United States)

Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

2018-01-01

Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm

Real-time reflectance-difference spectroscopy of GaAs molecular beam epitaxy homoepitaxial growth

Energy Technology Data Exchange (ETDEWEB)

Lastras-Martínez, A., E-mail: alm@cactus.iico.uaslp.mx, E-mail: alastras@gmail.com; Ortega-Gallegos, J.; Guevara-Macías, L. E.; Nuñez-Olvera, O.; Balderas-Navarro, R. E.; Lastras-Martínez, L. F. [Instituto de Investigación en Comunicación Optica, Universidad Autónoma de San Luis Potosí, Alvaro Obregón 64, San Luis Potosí, SLP 78000 (Mexico); Lastras-Montaño, L. A. [IBM T. J. Watson Research Center, Yorktown Heights, New York 10598 (United States); Lastras-Montaño, M. A. [Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, California 93106 (United States)

2014-03-01

We report on real time-resolved Reflectance-difference (RD) spectroscopy of GaAs(001) grown by molecular beam epitaxy, with a time-resolution of 500 ms per spectrum within the 2.3–4.0 eV photon energy range. Through the analysis of transient RD spectra we demonstrated that RD line shapes are comprised of two components with different physical origins and determined their evolution during growth. Such components were ascribed to the subsurface strain induced by surface reconstruction and to surface stoichiometry. Results reported in this paper render RD spectroscopy as a powerful tool for the study of fundamental processes during the epitaxial growth of zincblende semiconductors.

Scalable Real-Time Negotiation Toolkit

National Research Council Canada - National Science Library

Lesser, Victor

2004-01-01

... to implement an adaptive distributed sensor network. These activities involved the development of a distributed soft, real-time heuristic resource allocation protocol, the development of a domain-independent soft, real time agent architecture...

Model Checking Real-Time Systems

DEFF Research Database (Denmark)

Bouyer, Patricia; Fahrenberg, Uli; Larsen, Kim Guldstrand

2018-01-01

This chapter surveys timed automata as a formalism for model checking real-time systems. We begin with introducing the model, as an extension of finite-state automata with real-valued variables for measuring time. We then present the main model-checking results in this framework, and give a hint...

Modular specification of real-time systems

DEFF Research Database (Denmark)

Inal, Recep

1994-01-01

Duration Calculus, a real-time interval logic, has been embedded in the Z specification language to provide a notation for real-time systems that combines the modularisation and abstraction facilities of Z with a logic suitable for reasoning about real-time properties. In this article the notation...

Hard Real-Time Networking on Firewire

NARCIS (Netherlands)

Zhang, Yuchen; Orlic, Bojan; Visser, Peter; Broenink, Jan

2005-01-01

This paper investigates the possibility of using standard, low-cost, widely used FireWire as a new generation fieldbus medium for real-time distributed control applications. A real-time software subsys- tem, RT-FireWire was designed that can, in combination with Linux-based real-time operating

Multiprocessor scheduling for real-time systems

CERN Document Server

Baruah, Sanjoy; Buttazzo, Giorgio

2015-01-01

This book provides a comprehensive overview of both theoretical and pragmatic aspects of resource-allocation and scheduling in multiprocessor and multicore hard-real-time systems.  The authors derive new, abstract models of real-time tasks that capture accurately the salient features of real application systems that are to be implemented on multiprocessor platforms, and identify rules for mapping application systems onto the most appropriate models.  New run-time multiprocessor scheduling algorithms are presented, which are demonstrably better than those currently used, both in terms of run-time efficiency and tractability of off-line analysis.  Readers will benefit from a new design and analysis framework for multiprocessor real-time systems, which will translate into a significantly enhanced ability to provide formally verified, safety-critical real-time systems at a significantly lower cost.

Delay time and tunneling transient phenomena

International Nuclear Information System (INIS)

Garcia-Calderon, Gaston; Villavicencio, Jorge

2002-01-01

Analytic solutions to the time-dependent Schroedinger equation for cutoff wave initial conditions are used to investigate the time evolution of the transmitted probability density for tunneling. For a broad range of values of the potential barrier opacity α, we find that the probability density exhibits two evolving structures. One refers to the propagation of a forerunner related to a time domain resonance [Phys. Rev. A 64, 0121907 (2001)], while the other consists of a semiclassical propagating wave front. We find a regime where the forerunners are absent, corresponding to positive time delays, and show that this regime is characterized by opacities α c . The critical opacity α c is derived from the analytical expression for the delay time, which reflects a link between transient effects in tunneling and the delay time

Robust real-time change detection in high jitter.

Energy Technology Data Exchange (ETDEWEB)

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.

Transient effects in friction fractal asperity creep

CERN Document Server

Goedecke, Andreas

2013-01-01

Transient friction effects determine the behavior of a wide class of mechatronic systems. Classic examples are squealing brakes, stiction in robotic arms, or stick-slip in linear drives. To properly design and understand mechatronic systems of this type, good quantitative models of transient friction effects are of primary interest. The theory developed in this book approaches this problem bottom-up, by deriving the behavior of macroscopic friction surfaces from the microscopic surface physics. The model is based on two assumptions: First, rough surfaces are inherently fractal, exhibiting roughness on a wide range of scales. Second, transient friction effects are caused by creep enlargement of the real area of contact between two bodies. This work demonstrates the results of extensive Finite Element analyses of the creep behavior of surface asperities, and proposes a generalized multi-scale area iteration for calculating the time-dependent real contact between two bodies. The toolset is then demonstrated both...

Comparative Study of Time-Frequency Decomposition Techniques for Fault Detection in Induction Motors Using Vibration Analysis during Startup Transient

Directory of Open Access Journals (Sweden)

Paulo Antonio Delgado-Arredondo

2015-01-01

Full Text Available Induction motors are critical components for most industries and the condition monitoring has become necessary to detect faults. There are several techniques for fault diagnosis of induction motors and analyzing the startup transient vibration signals is not as widely used as other techniques like motor current signature analysis. Vibration analysis gives a fault diagnosis focused on the location of spectral components associated with faults. Therefore, this paper presents a comparative study of different time-frequency analysis methodologies that can be used for detecting faults in induction motors analyzing vibration signals during the startup transient. The studied methodologies are the time-frequency distribution of Gabor (TFDG, the time-frequency Morlet scalogram (TFMS, multiple signal classification (MUSIC, and fast Fourier transform (FFT. The analyzed vibration signals are one broken rotor bar, two broken bars, unbalance, and bearing defects. The obtained results have shown the feasibility of detecting faults in induction motors using the time-frequency spectral analysis applied to vibration signals, and the proposed methodology is applicable when it does not have current signals and only has vibration signals. Also, the methodology has applications in motors that are not fed directly to the supply line, in such cases the analysis of current signals is not recommended due to poor current signal quality.

High-speed railway real-time localization auxiliary method based on deep neural network

Science.gov (United States)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

Prototyping real-time systems

OpenAIRE

Clynch, Gary

1994-01-01

The traditional software development paradigm, the waterfall life cycle model, is defective when used for developing real-time systems. This thesis puts forward an executable prototyping approach for the development of real-time systems. A prototyping system is proposed which uses ESML (Extended Systems Modelling Language) as a prototype specification language. The prototyping system advocates the translation of non-executable ESML specifications into executable LOOPN (Language of Object ...

Transient analysis for Laguna Verde nuclear power plant

International Nuclear Information System (INIS)

Ramos Pablos, J.C. et.al.

1991-01-01

Relationship between transients analysis and safety of Laguna Verde nuclear power plant is described a general panorama of safety thermal limits of a nuclear station, as well as transients classification and events simulation codes are exposed. Activities of a group of transients analysis of electrical research institute are also mentioned (Author)

Software Design Methods for Real-Time Systems

Science.gov (United States)

1989-12-01

This module describes the concepts and methods used in the software design of real time systems . It outlines the characteristics of real time systems , describes...the role of software design in real time system development, surveys and compares some software design methods for real - time systems , and

Real-time Pricing in Power Markets

DEFF Research Database (Denmark)

Boom, Anette; Schwenen, Sebastian

We examine welfare e ects of real-time pricing in electricity markets. Before stochastic energy demand is known, competitive retailers contract with nal consumers who exogenously do not have real-time meters. After demand is realized, two electricity generators compete in a uniform price auction...... to satisfy demand from retailers acting on behalf of subscribed customers and from consumers with real-time meters. Increasing the number of consumers on real-time pricing does not always increase welfare since risk-averse consumers dislike uncertain and high prices arising through market power...

Real-time Pricing in Power Markets

DEFF Research Database (Denmark)

Boom, Anette; Schwenen, Sebastian

We examine welfare eects of real-time pricing in electricity markets. Before stochastic energy demand is known, competitive retailers contract with nal consumers who exogenously do not have real-time meters. After demand is realized, two electricity generators compete in a uniform price auction...... to satisfy demand from retailers acting on behalf of subscribed customers and from consumers with real-time meters. Increasing the number of consumers on real-time pricing does not always increase welfare since risk-averse consumers dislike uncertain and high prices arising through market power...

Distributed, Embedded and Real-time Java Systems

CERN Document Server

Wellings, Andy

2012-01-01

Research on real-time Java technology has been prolific over the past decade, leading to a large number of corresponding hardware and software solutions, and frameworks for distributed and embedded real-time Java systems.  This book is aimed primarily at researchers in real-time embedded systems, particularly those who wish to understand the current state of the art in using Java in this domain.  Much of the work in real-time distributed, embedded and real-time Java has focused on the Real-time Specification for Java (RTSJ) as the underlying base technology, and consequently many of the Chapters in this book address issues with, or solve problems using, this framework. Describes innovative techniques in: scheduling, memory management, quality of service and communication systems supporting real-time Java applications; Includes coverage of multiprocessor embedded systems and parallel programming; Discusses state-of-the-art resource management for embedded systems, including Java’s real-time garbage collect...

Computationally determining the salience of decision points for real-time wayfinding support

Directory of Open Access Journals (Sweden)

Makoto Takemiya

2012-06-01

Full Text Available This study introduces the concept of computational salience to explain the discriminatory efficacy of decision points, which in turn may have applications to providing real-time assistance to users of navigational aids. This research compared algorithms for calculating the computational salience of decision points and validated the results via three methods: high-salience decision points were used to classify wayfinders; salience scores were used to weight a conditional probabilistic scoring function for real-time wayfinder performance classification; and salience scores were correlated with wayfinding-performance metrics. As an exploratory step to linking computational and cognitive salience, a photograph-recognition experiment was conducted. Results reveal a distinction between algorithms useful for determining computational and cognitive saliences. For computational salience, information about the structural integration of decision points is effective, while information about the probability of decision-point traversal shows promise for determining cognitive salience. Limitations from only using structural information and motivations for future work that include non-structural information are elicited.

Research of real-time communication software

Science.gov (United States)

Li, Maotang; Guo, Jingbo; Liu, Yuzhong; Li, Jiahong

2003-11-01

Real-time communication has been playing an increasingly important role in our work, life and ocean monitor. With the rapid progress of computer and communication technique as well as the miniaturization of communication system, it is needed to develop the adaptable and reliable real-time communication software in the ocean monitor system. This paper involves the real-time communication software research based on the point-to-point satellite intercommunication system. The object-oriented design method is adopted, which can transmit and receive video data and audio data as well as engineering data by satellite channel. In the real-time communication software, some software modules are developed, which can realize the point-to-point satellite intercommunication in the ocean monitor system. There are three advantages for the real-time communication software. One is that the real-time communication software increases the reliability of the point-to-point satellite intercommunication system working. Second is that some optional parameters are intercalated, which greatly increases the flexibility of the system working. Third is that some hardware is substituted by the real-time communication software, which not only decrease the expense of the system and promotes the miniaturization of communication system, but also aggrandizes the agility of the system.

A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

Science.gov (United States)

Foo, Brian; van der Schaar, Mihaela

2010-11-01

In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

Real time monitoring of water distribution in an operando fuel cell during transient states

Science.gov (United States)

Martinez, N.; Peng, Z.; Morin, A.; Porcar, L.; Gebel, G.; Lyonnard, S.

2017-10-01

The water distribution of an operating proton exchange membrane fuel cell (PEMFC) was monitored in real time by using Small Angle Neutron Scattering (SANS). The formation of liquid water was obtained simultaneously with the evolution of the water content inside the membrane. Measurements were performed when changing current with a time resolution of 10 s, providing insights on the kinetics of water management prior to the stationary phase. We confirmed that water distribution is strongly heterogeneous at the scale at of the whole Membrane Electrode Assembly. As already reported, at the local scale there is no straightforward link between the amounts of water present inside and outside the membrane. However, we show that the temporal evolutions of these two parameters are strongly correlated. In particular, the local membrane water content is nearly instantaneously correlated to the total liquid water content, whether it is located at the anode or cathode side. These results can help in optimizing 3D stationary diphasic models used to predict PEMFC water distribution.

Noninvasive Strategy Based on Real-Time in Vivo Cataluminescence Monitoring for Clinical Breath Analysis.

Science.gov (United States)

Zhang, Runkun; Huang, Wanting; Li, Gongke; Hu, Yufei

2017-03-21

The development of noninvasive methods for real-time in vivo analysis is of great significant, which provides powerful tools for medical research and clinical diagnosis. In the present work, we described a new strategy based on cataluminescence (CTL) for real-time in vivo clinical breath analysis. To illustrate such strategy, a homemade real-time CTL monitoring system characterized by coupling an online sampling device with a CTL sensor for sevoflurane (SVF) was designed, and a real-time in vivo method for the monitoring of SVF in exhaled breath was proposed. The accuracy of the method was evaluated by analyzing the real exhaled breath samples, and the results were compared with those obtained by GC/MS. The measured data obtained by the two methods were in good agreement. Subsequently, the method was applied to real-time monitoring of SVF in exhaled breath from rat models of the control group to investigate elimination pharmacokinetics. In order to further probe the potential of the method for clinical application, the elimination pharmacokinetics of SVF from rat models of control group, liver fibrosis group alcohol liver group, and nonalcoholic fatty liver group were monitored by the method. The raw data of pharmacokinetics of different groups were normalized and subsequently subjected to linear discriminant analysis (LDA). These data were transformed to canonical scores which were visualized as well-clustered with the classification accuracy of 100%, and the overall accuracy of leave-one-out cross-validation procedure is 88%, thereby indicating the utility of the potential of the method for liver disease diagnosis. Our strategy undoubtedly opens up a new door for real-time clinical analysis in a pain-free and noninvasive way and also guides a promising development direction for CTL.

Perceptual Real-Time 2D-to-3D Conversion Using Cue Fusion.

Science.gov (United States)

Leimkuhler, Thomas; Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Seidel, Hans-Peter

2018-06-01

We propose a system to infer binocular disparity from a monocular video stream in real-time. Different from classic reconstruction of physical depth in computer vision, we compute perceptually plausible disparity, that is numerically inaccurate, but results in a very similar overall depth impression with plausible overall layout, sharp edges, fine details and agreement between luminance and disparity. We use several simple monocular cues to estimate disparity maps and confidence maps of low spatial and temporal resolution in real-time. These are complemented by spatially-varying, appearance-dependent and class-specific disparity prior maps, learned from example stereo images. Scene classification selects this prior at runtime. Fusion of prior and cues is done by means of robust MAP inference on a dense spatio-temporal conditional random field with high spatial and temporal resolution. Using normal distributions allows this in constant-time, parallel per-pixel work. We compare our approach to previous 2D-to-3D conversion systems in terms of different metrics, as well as a user study and validate our notion of perceptually plausible disparity.

A New Methodology Based on Imbalanced Classification for Predicting Outliers in Electricity Demand Time Series

Directory of Open Access Journals (Sweden)

Francisco Javier Duque-Pintor

2016-09-01

Full Text Available The occurrence of outliers in real-world phenomena is quite usual. If these anomalous data are not properly treated, unreliable models can be generated. Many approaches in the literature are focused on a posteriori detection of outliers. However, a new methodology to a priori predict the occurrence of such data is proposed here. Thus, the main goal of this work is to predict the occurrence of outliers in time series, by using, for the first time, imbalanced classification techniques. In this sense, the problem of forecasting outlying data has been transformed into a binary classification problem, in which the positive class represents the occurrence of outliers. Given that the number of outliers is much lower than the number of common values, the resultant classification problem is imbalanced. To create training and test sets, robust statistical methods have been used to detect outliers in both sets. Once the outliers have been detected, the instances of the dataset are labeled accordingly. Namely, if any of the samples composing the next instance are detected as an outlier, the label is set to one. As a study case, the methodology has been tested on electricity demand time series in the Spanish electricity market, in which most of the outliers were properly forecast.

Feature Space Dimensionality Reduction for Real-Time Vision-Based Food Inspection

Directory of Open Access Journals (Sweden)

Mai Moussa CHETIMA

2009-03-01

Full Text Available Machine vision solutions are becoming a standard for quality inspection in several manufacturing industries. In the processed-food industry where the appearance attributes of the product are essential to customer’s satisfaction, visual inspection can be reliably achieved with machine vision. But such systems often involve the extraction of a larger number of features than those actually needed to ensure proper quality control, making the process less efficient and difficult to tune. This work experiments with several feature selection techniques in order to reduce the number of attributes analyzed by a real-time vision-based food inspection system. Identifying and removing as much irrelevant and redundant information as possible reduces the dimensionality of the data and allows classification algorithms to operate faster. In some cases, accuracy on classification can even be improved. Filter-based and wrapper-based feature selectors are experimentally evaluated on different bakery products to identify the best performing approaches.

Asynchronous data-driven classification of weapon systems

International Nuclear Information System (INIS)

Jin, Xin; Mukherjee, Kushal; Gupta, Shalabh; Ray, Asok; Phoha, Shashi; Damarla, Thyagaraju

2009-01-01

This communication addresses real-time weapon classification by analysis of asynchronous acoustic data, collected from microphones on a sensor network. The weapon classification algorithm consists of two parts: (i) feature extraction from time-series data using symbolic dynamic filtering (SDF), and (ii) pattern classification based on the extracted features using the language measure (LM) and support vector machine (SVM). The proposed algorithm has been tested on field data, generated by firing of two types of rifles. The results of analysis demonstrate high accuracy and fast execution of the pattern classification algorithm with low memory requirements. Potential applications include simultaneous shooter localization and weapon classification with soldier-wearable networked sensors. (rapid communication)

Integration of MDSplus in real-time systems

International Nuclear Information System (INIS)

Luchetta, A.; Manduchi, G.; Taliercio, C.

2006-01-01

RFX-mod makes extensive usage of real-time systems for feedback control and uses MDSplus to interface them to the main Data Acquisition system. For this purpose, the core of MDSplus has been ported to VxWorks, the operating system used for real-time control in RFX. Using this approach, it is possible to integrate real-time systems, but MDSplus is used only for non-real-time tasks, i.e. those tasks which are executed before and after the pulse and whose performance does not affect the system time constraints. More extensive use of MDSplus in real-time systems is foreseen, and a real-time layer for MDSplus is under development, which will provide access to memory-mapped pulse files, shared by the tasks running on the same CPU. Real-time communication will also be integrated in the MDSplus core to provide support for distributed memory-mapped pulse files

Dense time discretization technique for verification of real time systems

International Nuclear Information System (INIS)

Makackas, Dalius; Miseviciene, Regina

2016-01-01

Verifying the real-time system there are two different models to control the time: discrete and dense time based models. This paper argues a novel verification technique, which calculates discrete time intervals from dense time in order to create all the system states that can be reached from the initial system state. The technique is designed for real-time systems specified by a piece-linear aggregate approach. Key words: real-time system, dense time, verification, model checking, piece-linear aggregate

Storm real-time processing cookbook

CERN Document Server

Anderson, Quinton

2013-01-01

A Cookbook with plenty of practical recipes for different uses of Storm.If you are a Java developer with basic knowledge of real-time processing and would like to learn Storm to process unbounded streams of data in real time, then this book is for you.

Real-time reflectance-difference spectroscopy of GaAs molecular beam epitaxy homoepitaxial growth

Directory of Open Access Journals (Sweden)

A. Lastras-Martínez

2014-03-01

Full Text Available We report on real time-resolved Reflectance-difference (RD spectroscopy of GaAs(001 grown by molecular beam epitaxy, with a time-resolution of 500 ms per spectrum within the 2.3–4.0 eV photon energy range. Through the analysis of transient RD spectra we demonstrated that RD line shapes are comprised of two components with different physical origins and determined their evolution during growth. Such components were ascribed to the subsurface strain induced by surface reconstruction and to surface stoichiometry. Results reported in this paper render RD spectroscopy as a powerful tool for the study of fundamental processes during the epitaxial growth of zincblende semiconductors.

Mixed - mode Operating System for Real - time Performance

Directory of Open Access Journals (Sweden)

Hasan M. M.

2017-11-01

Full Text Available The purpose of the mixed-mode system research is to handle devices with the accuracy of real-time systems and at the same time, having all the benefits and facilities of a matured Graphic User Interface(GUIoperating system which is typicallynon-real-time. This mixed-mode operating system comprising of a real-time portion and a non-real-time portion was studied and implemented to identify the feasibilities and performances in practical applications (in the context of scheduled the real-time events. In this research an i8751 microcontroller-based hardware was used to measure the performance of the system in real-time-only as well as non-real-time-only configurations. The real-time portion is an 486DX-40 IBM PC system running under DOS-based real-time kernel and the non-real-time portion is a Pentium IIIbased system running under Windows NT. It was found that mixed-mode systems performed as good as a typical real-time system and in fact, gave many additional benefits such as simplified/modular programming and load tolerance.

Comparison of real-time classification systems for arrhythmia detection on Android-based mobile devices.

Science.gov (United States)

Leutheuser, Heike; Gradl, Stefan; Kugler, Patrick; Anneken, Lars; Arnold, Martin; Achenbach, Stephan; Eskofier, Bjoern M

2014-01-01

The electrocardiogram (ECG) is a key diagnostic tool in heart disease and may serve to detect ischemia, arrhythmias, and other conditions. Automatic, low cost monitoring of the ECG signal could be used to provide instantaneous analysis in case of symptoms and may trigger the presentation to the emergency department. Currently, since mobile devices (smartphones, tablets) are an integral part of daily life, they could form an ideal basis for automatic and low cost monitoring solution of the ECG signal. In this work, we aim for a realtime classification system for arrhythmia detection that is able to run on Android-based mobile devices. Our analysis is based on 70% of the MIT-BIH Arrhythmia and on 70% of the MIT-BIH Supraventricular Arrhythmia databases. The remaining 30% are reserved for the final evaluation. We detected the R-peaks with a QRS detection algorithm and based on the detected R-peaks, we calculated 16 features (statistical, heartbeat, and template-based). With these features and four different feature subsets we trained 8 classifiers using the Embedded Classification Software Toolbox (ECST) and compared the computational costs for each classification decision and the memory demand for each classifier. We conclude that the C4.5 classifier is best for our two-class classification problem (distinction of normal and abnormal heartbeats) with an accuracy of 91.6%. This classifier still needs a detailed feature selection evaluation. Our next steps are implementing the C4.5 classifier for Android-based mobile devices and evaluating the final system using the remaining 30% of the two used databases.

SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging

Energy Technology Data Exchange (ETDEWEB)

Yan, H [Capital Medical University, Beijing, Beijing (China); Chen, Z [Yale New Haven Hospital, New Haven, CT (United States); Nath, R; Liu, W [Yale University School of Medicine, New Haven, CT (United States)

2016-06-15

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the

SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging

International Nuclear Information System (INIS)

Yan, H; Chen, Z; Nath, R; Liu, W

2016-01-01

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the

SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

International Nuclear Information System (INIS)

Kumar, S.; Gezari, S.; Heinis, S.; Chornock, R.; Berger, E.; Soderberg, A.; Stubbs, C. W.; Kirshner, R. P.; Rest, A.; Huber, M. E.; Narayan, G.; Marion, G. H.; Burgett, W. S.; Foley, R. J.; Scolnic, D.; Riess, A. G.; Lawrence, A.; Smartt, S. J.; Smith, K.; Wood-Vasey, W. M.

2015-01-01

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g P1 , r P1 , i P1 , and z P1 . We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to

Off-line and real-time monitoring of acetaminophen photodegradation by an electrochemical sensor.

Science.gov (United States)

Berto, Silvia; Carena, Luca; Chiavazza, Enrico; Marletti, Matteo; Fin, Andrea; Giacomino, Agnese; Malandrino, Mery; Barolo, Claudia; Prenesti, Enrico; Vione, Davide

2018-08-01

The photochemistry of N-acetyl-para-aminophenol (acetaminophen, APAP) is here investigated by using differential pulse voltammetry (DPV) analysis to monitor APAP photodegradation upon steady-state irradiation. The purpose of this work is to assess the applicability of DPV to monitor the photochemical behaviour of xenobiotics, along with the development of an electrochemical set-up for the real-time monitoring of APAP photodegradation. We here investigated the APAP photoreactivity towards the main photogenerated reactive transients species occurring in sunlit surface waters (hydroxyl radical HO, carbonate radical CO 3 - , excited triplet state of anthraquinone-2-sulfonate used as proxy of the chromophoric DOM, and singlet oxygen 1 O 2 ), and determined relevant kinetic parameters. A standard procedure based on UV detection coupled with liquid chromatography (HPLC-UV) was used under identical experimental conditions to compare and verify the DPV-based results. The latter were in agreement with HPLC data, with the exception of the triplet-sensitized processes. In the other cases, DPV could be used as an alternative to the well-tested but more costly and time-consuming HPLC-UV technique. We have also assessed the reaction rate constant between APAP and HO by real-time DPV, which allowed for the monitoring of APAP photodegradation inside the irradiation chamber. Unfortunately, real-time DPV measurements are likely to be affected by temperature variations of the irradiated samples. Overall, DPV appeared as a fast, cheap and reasonably reliable technique when used for the off-line monitoring of APAP photodegradation. When a suitable real-time procedure is developed, it could become a very straightforward method to study the photochemical behaviour of electroactive xenobiotics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Research in Distributed Real-Time Systems

Science.gov (United States)

Mukkamala, R.

1997-01-01

This document summarizes the progress we have made on our study of issues concerning the schedulability of real-time systems. Our study has produced several results in the scalability issues of distributed real-time systems. In particular, we have used our techniques to resolve schedulability issues in distributed systems with end-to-end requirements. During the next year (1997-98), we propose to extend the current work to address the modeling and workload characterization issues in distributed real-time systems. In particular, we propose to investigate the effect of different workload models and component models on the design and the subsequent performance of distributed real-time systems.

Real-time data access layer for MDSplus

International Nuclear Information System (INIS)

Manduchi, G.; Luchetta, A.; Taliercio, C.; Fredian, T.; Stillerman, J.

2008-01-01

Recent extensions to MDSplus allow data handling in long discharges and provide a real-time data access and communication layer. The real-time data access layer is an additional component of MDSplus: it is possible to use the traditional MDSplus API during normal operation, and to select a subset of data items to be used in real time. Real-time notification is provided by a communication layer using a publish-subscribe pattern. The notification covers processes sharing the same data items even running on different machines, thus allowing the implementation of distributed control systems. The real-time data access layer has been developed for Windows, Linux, and VxWorks; it is currently being ported to Linux RTAI. In order to quantify the fingerprint of the presented system, the performance of the real-time access layer approach is compared with that of an ad hoc, manually optimized program in a sample real-time application

Benefits of real-time gas management

International Nuclear Information System (INIS)

Nolty, R.; Dolezalek, D. Jr.

1994-01-01

In today's competitive gas gathering, processing, storage and transportation business environment, the requirements to do business are continually changing. These changes arise from government regulations such as the amendments to the Clean Air Act concerning the environment and FERC Order 636 concerning business practices. Other changes are due to advances in technology such as electronic flow measurement (EFM) and real-time communications capabilities within the gas industry. Gas gathering, processing, storage and transportation companies must be flexible in adapting to these changes to remain competitive. These dynamic requirements can be met with an open, real-time gas management computer information system. Such a system provides flexible services with a variety of software applications. Allocations, nominations management and gas dispatching are examples of applications that are provided on a real-time basis. By providing real-time services, the gas management system enables operations personnel to make timely adjustments within the current accounting period. Benefits realized from implementing a real-time gas management system include reduced unaccountable gas, reduced imbalance penalties, reduced regulatory violations, improved facility operations and better service to customers. These benefits give a company the competitive edge. This article discusses the applications provided, the benefits from implementing a real-time gas management system, and the definition of such a system

Making real-time reactive systems reliable

Science.gov (United States)

Marzullo, Keith; Wood, Mark

1990-01-01

A reactive system is characterized by a control program that interacts with an environment (or controlled program). The control program monitors the environment and reacts to significant events by sending commands to the environment. This structure is quite general. Not only are most embedded real time systems reactive systems, but so are monitoring and debugging systems and distributed application management systems. Since reactive systems are usually long running and may control physical equipment, fault tolerance is vital. The research tries to understand the principal issues of fault tolerance in real time reactive systems and to build tools that allow a programmer to design reliable, real time reactive systems. In order to make real time reactive systems reliable, several issues must be addressed: (1) How can a control program be built to tolerate failures of sensors and actuators. To achieve this, a methodology was developed for transforming a control program that references physical value into one that tolerates sensors that can fail and can return inaccurate values; (2) How can the real time reactive system be built to tolerate failures of the control program. Towards this goal, whether the techniques presented can be extended to real time reactive systems is investigated; and (3) How can the environment be specified in a way that is useful for writing a control program. Towards this goal, whether a system with real time constraints can be expressed as an equivalent system without such constraints is also investigated.

Real-time intelligent pattern recognition algorithm for surface EMG signals

Directory of Open Access Journals (Sweden)

Jahed Mehran

2007-12-01

Full Text Available Abstract Background Electromyography (EMG is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP and least mean square (LMS is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD and time-frequency representation (TFR. Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal

An investigation of loads generated by temperature transients in pipes

International Nuclear Information System (INIS)

Maneschy, C.E.

1988-12-01

An analysis is presented of the effect of a transient temperature on the stress distribution due to a fluid flowing through a pipe, is analytically determined using the definition of a variable called in this paper as ''shifted time''. This variable, which is related to the axial coordinate, the average fluid velocity and the real time, is defined to make the transient thermal problem one-dimensional. The stresses are then calculated from the temperature solution using the linear theory of viscoelasticity. (author) [pt

Space Weather and Real-Time Monitoring

Directory of Open Access Journals (Sweden)

S Watari

2009-04-01

Full Text Available Recent advance of information and communications technology enables to collect a large amount of ground-based and space-based observation data in real-time. The real-time data realize nowcast of space weather. This paper reports a history of space weather by the International Space Environment Service (ISES in association with the International Geophysical Year (IGY and importance of real-time monitoring in space weather.

Research Directions in Real-Time Systems.

Science.gov (United States)

1996-09-01

This report summarizes a survey of published research in real time systems . Material is presented that provides an overview of the topic, focusing on...communications protocols and scheduling techniques. It is noted that real - time systems deserve special attention separate from other areas because of...formal tools for design and analysis of real - time systems . The early work on applications as well as notable theoretical advances are summarized

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

Science.gov (United States)

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.

Real-Time MENTAT programming language and architecture

Science.gov (United States)

Grimshaw, Andrew S.; Silberman, Ami; Liu, Jane W. S.

1989-01-01

Real-time MENTAT, a programming environment designed to simplify the task of programming real-time applications in distributed and parallel environments, is described. It is based on the same data-driven computation model and object-oriented programming paradigm as MENTAT. It provides an easy-to-use mechanism to exploit parallelism, language constructs for the expression and enforcement of timing constraints, and run-time support for scheduling and exciting real-time programs. The real-time MENTAT programming language is an extended C++. The extensions are added to facilitate automatic detection of data flow and generation of data flow graphs, to express the timing constraints of individual granules of computation, and to provide scheduling directives for the runtime system. A high-level view of the real-time MENTAT system architecture and programming language constructs is provided.

Real Time Conference 2016 Overview

Science.gov (United States)

Luchetta, Adriano

2017-06-01

This is a special issue of the IEEE Transactions on Nuclear Science containing papers from the invited, oral, and poster presentation of the 20th Real Time Conference (RT2016). The conference was held June 6-10, 2016, at Centro Congressi Padova “A. Luciani,” Padova, Italy, and was organized by Consorzio RFX (CNR, ENEA, INFN, Università di Padova, Acciaierie Venete SpA) and the Istituto Nazionale di Fisica Nucleare. The Real Time Conference is multidisciplinary and focuses on the latest developments in real-time techniques in high-energy physics, nuclear physics, astrophysics and astroparticle physics, nuclear fusion, medical physics, space instrumentation, nuclear power instrumentation, general radiation instrumentation, and real-time security and safety. Taking place every second year, it is sponsored by the Computer Application in Nuclear and Plasma Sciences technical committee of the IEEE Nuclear and Plasma Sciences Society. RT2016 attracted more than 240 registrants, with a large proportion of young researchers and engineers. It had an attendance of 67 students from many countries.

Transient selection in multicellular immune networks

Science.gov (United States)

Ivanchenko, M. V.

2011-03-01

We analyze the dynamics of a multi-clonotype naive T-cell population competing for survival signals from antigen-presenting cells. We find that this competition provides with an efficacious selection of clonotypes, making the less able and more repetitive get extinct. We uncover the scaling principles for large systems the extinction rate obeys and calibrate the model parameters to their experimental counterparts. For the first time, we estimate the physiological values of the T-cell receptor-antigen presentation profile recognition probability and T-cell clonotypes niche overlap. We demonstrate that, while the ultimate state is a stable fixed point, sequential transients dominate the dynamics over large timescales that may span over years, if not decades, in real time. We argue that what is currently viewed as "homeostasis" is a complex sequential transient process, while being quasi-stationary in the total number of T-cells only. The discovered type of sequential transient dynamics in large random networks is a novel alternative to the stable heteroclinic channel mechanism.

Study of water flowrate using time transient and cross-correlation techniques with 82Br radiotracer

International Nuclear Information System (INIS)

Salgado, William L.; Brandao, Luiz E.B.

2013-01-01

This paper aims to determinate the water flowrate using Time Transient and Cross-Correlation techniques. The detection system uses two NaI (T1) detectors adequately positioned on the outside of pipe and a gamma-ray source ( 82 Br radiotracer). The water flowrate measurements using Time Transient and Cross-Correlation techniques were compared to invasive conventional measurements of the flowrate previously installed in pipeline. Discrepancies between Time Transient and Cross-Correlation techniques flowmeter previously installed in pipeline. Discrepancies between Time Transient and Cross-Correlation techniques flowrate values were found to be less than 3% in relation to conventional ones. (author)

Run-time middleware to support real-time system scenarios

NARCIS (Netherlands)

Goossens, K.; Koedam, M.; Sinha, S.; Nelson, A.; Geilen, M.

2015-01-01

Systems on Chip (SOC) are powerful multiprocessor systems capable of running multiple independent applications, often with both real-time and non-real-time requirements. Scenarios exist at two levels: first, combinations of independent applications, and second, different states of a single

Advanced real-time manipulation of video streams

CERN Document Server

Herling, Jan

2014-01-01

Diminished Reality is a new fascinating technology that removes real-world content from live video streams. This sensational live video manipulation actually removes real objects and generates a coherent video stream in real-time. Viewers cannot detect modified content. Existing approaches are restricted to moving objects and static or almost static cameras and do not allow real-time manipulation of video content. Jan Herling presents a new and innovative approach for real-time object removal with arbitrary camera movements.

Collection and evaluation of salt mixing data with the real time data acquisition system. [LMFBR

Energy Technology Data Exchange (ETDEWEB)

Glazer, S.; Chiu, C.; Todreas, N.E.

1977-09-01

A minicomputer based real time data acquisition system was designed and built to facilitate data collection during salt mixing tests in mock ups of LMFBR rod bundles. The system represents an expansion of data collection capabilities over previous equipment. It performs steady state and transient monitoring and recording of up to 512 individual electrical resistance probes. Extensive real time software was written to govern all phases of the data collection procedure, including probe definition, probe calibration, salt mixing test data acquisition and storage, and data editing. Offline software was also written to permit data examination and reduction to dimensionless salt concentration maps. Finally, the computer program SUPERENERGY was modified to permit rapid extraction of parameters from dimensionless salt concentration maps. The document describes the computer system, and includes circuit diagrams of all custom built components. It also includes descriptions and listings of all software written, as well as extensive user instructions.

CONTROLLED CONDENSATION IN K-NN AND ITS APPLICATION FOR REAL TIME COLOR IDENTIFICATION

Directory of Open Access Journals (Sweden)

Carmen Villar Patiño

2017-04-01

Full Text Available k-NN algorithms are frequently used in statistical classification. They are accurate and distribution free. Despite these advantages, k-NN algorithms imply a high computational cost. To find efficient ways to implement them is an important challenge in pattern recognition. In this article, an improved version of the k-NN Controlled Condensation algorithm is introduced. Its potential for instantaneous color identification in real time is also analyzed. This algorithm is based on the representation of data in terms of a reduced set of informative prototypes. It includes two parameters to control the balance between speed and precision. This gives us the opportunity to achieve a convenient percentage of condensation without incurring in an important loss of accuracy. We test our proposal in an instantaneous color identification exercise in video images. We achieve the real time identification by using k-NN Controlled Condensation executed through multi-threading programming methods. The results are encouraging.

Large-scale machine learning and evaluation platform for real-time traffic surveillance

Science.gov (United States)

Eichel, Justin A.; Mishra, Akshaya; Miller, Nicholas; Jankovic, Nicholas; Thomas, Mohan A.; Abbott, Tyler; Swanson, Douglas; Keller, Joel

2016-09-01

In traffic engineering, vehicle detectors are trained on limited datasets, resulting in poor accuracy when deployed in real-world surveillance applications. Annotating large-scale high-quality datasets is challenging. Typically, these datasets have limited diversity; they do not reflect the real-world operating environment. There is a need for a large-scale, cloud-based positive and negative mining process and a large-scale learning and evaluation system for the application of automatic traffic measurements and classification. The proposed positive and negative mining process addresses the quality of crowd sourced ground truth data through machine learning review and human feedback mechanisms. The proposed learning and evaluation system uses a distributed cloud computing framework to handle data-scaling issues associated with large numbers of samples and a high-dimensional feature space. The system is trained using AdaBoost on 1,000,000 Haar-like features extracted from 70,000 annotated video frames. The trained real-time vehicle detector achieves an accuracy of at least 95% for 1/2 and about 78% for 19/20 of the time when tested on ˜7,500,000 video frames. At the end of 2016, the dataset is expected to have over 1 billion annotated video frames.

Improving Music Genre Classification by Short-Time Feature Integration

DEFF Research Database (Denmark)

Meng, Anders; Ahrendt, Peter; Larsen, Jan

2005-01-01

Many different short-time features, using time windows in the size of 10-30 ms, have been proposed for music segmentation, retrieval and genre classification. However, often the available time frame of the music to make the actual decision or comparison (the decision time horizon) is in the range...... of seconds instead of milliseconds. The problem of making new features on the larger time scale from the short-time features (feature integration) has only received little attention. This paper investigates different methods for feature integration and late information fusion for music genre classification...

Archtecture of distributed real-time systems

OpenAIRE

Wing Leung, Cheuk

2013-01-01

CRAFTERS (Constraint and Application Driven Framework for Tailoring Embedded Real-time System) project aims to address the problem of uncertainty and heterogeneity in a distributed system by providing seamless, portable connectivity and middleware. This thesis contributes to the project by investigating the techniques that can be used in a distributed real-time embedded system. The conclusion is that, there is a list of specifications to be meet in order to provide a transparent and real-time...

A wearable smartphone-based platform for real-time cardiovascular disease detection via electrocardiogram processing.

Science.gov (United States)

Oresko, Joseph J; Duschl, Heather; Cheng, Allen C

2010-05-01

Cardiovascular disease (CVD) is the single leading cause of global mortality and is projected to remain so. Cardiac arrhythmia is a very common type of CVD and may indicate an increased risk of stroke or sudden cardiac death. The ECG is the most widely adopted clinical tool to diagnose and assess the risk of arrhythmia. ECGs measure and display the electrical activity of the heart from the body surface. During patients' hospital visits, however, arrhythmias may not be detected on standard resting ECG machines, since the condition may not be present at that moment in time. While Holter-based portable monitoring solutions offer 24-48 h ECG recording, they lack the capability of providing any real-time feedback for the thousands of heart beats they record, which must be tediously analyzed offline. In this paper, we seek to unite the portability of Holter monitors and the real-time processing capability of state-of-the-art resting ECG machines to provide an assistive diagnosis solution using smartphones. Specifically, we developed two smartphone-based wearable CVD-detection platforms capable of performing real-time ECG acquisition and display, feature extraction, and beat classification. Furthermore, the same statistical summaries available on resting ECG machines are provided.

A Literature Survey of Early Time Series Classification and Deep Learning

OpenAIRE

Santos, Tiago; Kern, Roman

2017-01-01

This paper provides an overview of current literature on time series classification approaches, in particular of early time series classification. A very common and effective time series classification approach is the 1-Nearest Neighbor classier, with different distance measures such as the Euclidean or dynamic time warping distances. This paper starts by reviewing these baseline methods. More recently, with the gain in popularity in the application of deep neural networks to the eld of...

Dynamic modelling and real-time leak detection for NGL pipelines

Energy Technology Data Exchange (ETDEWEB)

Young, B.R.; Svrcek, W.Y. [Calgary Univ., AB (Canada). Dept. of Chemical and Petroleum Engineering; Cooke, J.G.; Daye, R.E. [Rangeland Engineering Ltd., Calgary, AB (Canada)

2004-07-01

This paper presented newly developed steady-state and dynamic models commissioned for natural gas liquids (NGL) pipelines near Empress, Alberta. The work demonstrates a unique university-industry collaboration for solving the challenge of reliable pipeline leak detection. The flexible, custom real-time leak detection system was tested on the dynamic simulation. It was successfully used to replace a volume balance system for NGL pipelines at Empress in March 2003. A custom pipeline monitoring system was also developed to integrate with the existing pipeline supervisory control and data acquisition (SCADA) system. Simulation results enabled a change in the control scheme of the pipelines that resulted in less transient operation. The premise of the leak detection system is a rigorous thermodynamics and dynamic mass balance calculation based on real-time information from field flow, pressure and temperature sensors. The application of the system makes it possible to minimize or eliminate false or nuisance alarms, which is critical to the confidence of the monitoring system. The volumetric and mass imbalance formulae permit the system to cross check the calculation and then make important decisions regarding the sounding of alarms. The custom solution offers flexibility for use in a wide variety of conditions and applications. In addition, it is cost effective and locally supported. 8 refs., 4 tabs., 5 figs.

The real-time price elasticity of electricity

NARCIS (Netherlands)

Lijesen, M.G.

2007-01-01

The real-time price elasticity of electricity contains important information on the demand response of consumers to the volatility of peak prices. Despite the importance, empirical estimates of the real-time elasticity are hardly available. This paper provides a quantification of the real-time

Real-time stability in power systems techniques for early detection of the risk of blackout

CERN Document Server

Savulescu, Savu

2014-01-01

This pioneering volume has been updated and enriched to reflect the state-of-the-art in blackout prediction and prevention. It documents and explains background and algorithmic aspects of the most successful steady-state, transient and voltage stability solutions available today in real-time. It also describes new, cutting-edge stability applications of synchrophasor technology, and captures industry acceptance of metrics and visualization tools that quantify and monitor the distance to instability. Expert contributors review a broad spectrum of additionally available techniques, such as traje

Implementing Run-Time Evaluation of Distributed Timing Constraints in a Real-Time Environment

DEFF Research Database (Denmark)

Kristensen, C. H.; Drejer, N.

1994-01-01

In this paper we describe a solution to the problem of implementing run-time evaluation of timing constraints in distributed real-time environments......In this paper we describe a solution to the problem of implementing run-time evaluation of timing constraints in distributed real-time environments...

Research on photodiode detector-based spatial transient light detection and processing system

Science.gov (United States)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

Applications of PCA and SVM-PSO Based Real-Time Face Recognition System

Directory of Open Access Journals (Sweden)

Ming-Yuan Shieh

2014-01-01

Full Text Available This paper incorporates principal component analysis (PCA with support vector machine-particle swarm optimization (SVM-PSO for developing real-time face recognition systems. The integrated scheme aims to adopt the SVM-PSO method to improve the validity of PCA based image recognition systems on dynamically visual perception. The face recognition for most human-robot interaction applications is accomplished by PCA based method because of its dimensionality reduction. However, PCA based systems are only suitable for processing the faces with the same face expressions and/or under the same view directions. Since the facial feature selection process can be considered as a problem of global combinatorial optimization in machine learning, the SVM-PSO is usually used as an optimal classifier of the system. In this paper, the PSO is used to implement a feature selection, and the SVMs serve as fitness functions of the PSO for classification problems. Experimental results demonstrate that the proposed method simplifies features effectively and obtains higher classification accuracy.

Y2K issues for real time computer systems for fast breeder test reactor

International Nuclear Information System (INIS)

Swaminathan, P.

1999-01-01

Presentation shows the classification of real time systems related to operation, control and monitoring of the fast breeder test reactor. Software life cycle includes software requirement specification, software design description, coding, commissioning, operation and management. A software scheme in supervisory computer of fast breeder test rector is described with the twenty years of experience in design, development, installation, commissioning, operation and maintenance of computer based supervision control system for nuclear installation with a particular emphasis on solving the Y2K problem

The TEX-I real-time expert system, applied to situation assessment for the SNR-300 reactor

International Nuclear Information System (INIS)

Schmal, N.; Leder, H.J.; Schade, H.J.

1988-01-01

Interatom, a subsidiary company of Siemens, is developing expert systems for the technical domain. These systems are operating in various industrial applications like flexible manufacturing or plant configuration, based on a domain-specific expert system shell, developed by Interatom. Additional projects are focusing on real-time diagnostics, e.g., for nuclear power plants. The authors report in this paper about a diagnosis expert system for the liquid-metal fast breeder reactor SNR-300, which uses new real-time tools, developed within the German TEX-I project (technical expert systems for data interpretation, diagnosis, and process control). The purpose of the system is to support the reactor operators in assessing plant status in real time, based on readings from many sensors. By on-line connection to the process control computer, it can monitor all incoming signal values, check the consistency of data, continuously diagnose the current plant status, detect unusual trends prior to accidents, localize faulty components, and recommended operator response in abnormal conditions. In the present knowledge acquisition and test phase, the expert system is connected to a real-time simulation of the reactor. The simulator is based on a thermohydraulic code for simulation of the transient behavior of temperatures and flow rates in the reactor core, plena, pipes, pumps, valves, intermediate heat exchangers, and cooling components. Additionally, the system's response to an asynchronous operator interaction can be simulated

Real-time recording and classification of eye movements in an immersive virtual environment.

Science.gov (United States)

Diaz, Gabriel; Cooper, Joseph; Kit, Dmitry; Hayhoe, Mary

2013-10-10

Despite the growing popularity of virtual reality environments, few laboratories are equipped to investigate eye movements within these environments. This primer is intended to reduce the time and effort required to incorporate eye-tracking equipment into a virtual reality environment. We discuss issues related to the initial startup and provide algorithms necessary for basic analysis. Algorithms are provided for the calculation of gaze angle within a virtual world using a monocular eye-tracker in a three-dimensional environment. In addition, we provide algorithms for the calculation of the angular distance between the gaze and a relevant virtual object and for the identification of fixations, saccades, and pursuit eye movements. Finally, we provide tools that temporally synchronize gaze data and the visual stimulus and enable real-time assembly of a video-based record of the experiment using the Quicktime MOV format, available at http://sourceforge.net/p/utdvrlibraries/. This record contains the visual stimulus, the gaze cursor, and associated numerical data and can be used for data exportation, visual inspection, and validation of calculated gaze movements.

REAL TIME SYSTEM OPERATIONS 2006-2007

Energy Technology Data Exchange (ETDEWEB)

Eto, Joseph H.; Parashar, Manu; Lewis, Nancy Jo

2008-08-15

The Real Time System Operations (RTSO) 2006-2007 project focused on two parallel technical tasks: (1) Real-Time Applications of Phasors for Monitoring, Alarming and Control; and (2) Real-Time Voltage Security Assessment (RTVSA) Prototype Tool. The overall goal of the phasor applications project was to accelerate adoption and foster greater use of new, more accurate, time-synchronized phasor measurements by conducting research and prototyping applications on California ISO's phasor platform - Real-Time Dynamics Monitoring System (RTDMS) -- that provide previously unavailable information on the dynamic stability of the grid. Feasibility assessment studies were conducted on potential application of this technology for small-signal stability monitoring, validating/improving existing stability nomograms, conducting frequency response analysis, and obtaining real-time sensitivity information on key metrics to assess grid stress. Based on study findings, prototype applications for real-time visualization and alarming, small-signal stability monitoring, measurement based sensitivity analysis and frequency response assessment were developed, factory- and field-tested at the California ISO and at BPA. The goal of the RTVSA project was to provide California ISO with a prototype voltage security assessment tool that runs in real time within California ISO?s new reliability and congestion management system. CERTS conducted a technical assessment of appropriate algorithms, developed a prototype incorporating state-of-art algorithms (such as the continuation power flow, direct method, boundary orbiting method, and hyperplanes) into a framework most suitable for an operations environment. Based on study findings, a functional specification was prepared, which the California ISO has since used to procure a production-quality tool that is now a part of a suite of advanced computational tools that is used by California ISO for reliability and congestion management.

A software framework for real-time multi-modal detection of microsleeps.

Science.gov (United States)

Knopp, Simon J; Bones, Philip J; Weddell, Stephen J; Jones, Richard D

2017-09-01

A software framework is described which was designed to process EEG, video of one eye, and head movement in real time, towards achieving early detection of microsleeps for prevention of fatal accidents, particularly in transport sectors. The framework is based around a pipeline structure with user-replaceable signal processing modules. This structure can encapsulate a wide variety of feature extraction and classification techniques and can be applied to detecting a variety of aspects of cognitive state. Users of the framework can implement signal processing plugins in C++ or Python. The framework also provides a graphical user interface and the ability to save and load data to and from arbitrary file formats. Two small studies are reported which demonstrate the capabilities of the framework in typical applications: monitoring eye closure and detecting simulated microsleeps. While specifically designed for microsleep detection/prediction, the software framework can be just as appropriately applied to (i) other measures of cognitive state and (ii) development of biomedical instruments for multi-modal real-time physiological monitoring and event detection in intensive care, anaesthesiology, cardiology, neurosurgery, etc. The software framework has been made freely available for researchers to use and modify under an open source licence.

A study of real-time content marketing : formulating real-time content marketing based on content, search and social media

OpenAIRE

Nguyen, Thi Kim Duyen

2015-01-01

The primary objective of this research is to understand profoundly the new concept of content marketing – real-time content marketing on the aspect of the digital marketing experts. Particularly, the research will focus on the real-time content marketing theories and how to build real-time content marketing strategy based on content, search and social media. It also finds out how marketers measure and keep track of conversion rates of their real-time content marketing plan. Practically, th...

Real-Life/Real-Time Elderly Fall Detection with a Triaxial Accelerometer.

Science.gov (United States)

Sucerquia, Angela; López, José David; Vargas-Bonilla, Jesús Francisco

2018-04-05

The consequences of a fall on an elderly person can be reduced if the accident is attended by medical personnel within the first hour. Independent elderly people often stay alone for long periods of time, being in more risk if they suffer a fall. The literature offers several approaches for detecting falls with embedded devices or smartphones using a triaxial accelerometer. Most of these approaches have not been tested with the target population or cannot be feasibly implemented in real-life conditions. In this work, we propose a fall detection methodology based on a non-linear classification feature and a Kalman filter with a periodicity detector to reduce the false positive rate. This methodology requires a sampling rate of only 25 Hz; it does not require large computations or memory and it is robust among devices. We tested our approach with the SisFall dataset achieving 99.4% of accuracy. We then validated it with a new round of simulated activities with young adults and an elderly person. Finally, we give the devices to three elderly persons for full-day validations. They continued with their normal life and the devices behaved as expected.

Real-time odor discrimination using a bioelectronic sensor array based on the insect electroantennogram

International Nuclear Information System (INIS)

Myrick, A J; Hetling, J R; Park, K-C; Baker, T C

2008-01-01

Current trends in artificial nose research are strongly influenced by knowledge of biological olfactory systems. Insects have evolved over millions of years to detect and maneuver toward a food source or mate, or away from predators. The insect olfactory system is able to identify volatiles on a time scale that matches their ability to maneuver. Here, biological olfactory sense organs, insect antennae, have been exploited in a hybrid-device biosensor, demonstrating the ability to identify individual strands of odor in a plume passing over the sensor on a sub-second time scale. A portable system was designed to utilize the electrophysiological responses recorded from a sensor array composed of male or female antennae from four or eight different species of insects (a multi-channel electroantennogram, EAG). A computational analysis strategy that allows discrimination between odors in real time is described in detail. Following a training period, both semi-parametric and k-nearest neighbor (k-NN) classifiers with the ability to discard ambiguous responses are applied toward the classification of up to eight odors. EAG responses to individual strands in an odor plume are classified or discarded as ambiguous with a delay (sensor response to classification report) on the order of 1 s. The dependence of classification error rate on several parameters is described. Finally, the performance of the approach is compared to that of a minimal conditional risk classifier

Application of XML in real-time data warehouse

Science.gov (United States)

Zhao, Yanhong; Wang, Beizhan; Liu, Lizhao; Ye, Su

2009-07-01

At present, XML is one of the most widely-used technologies of data-describing and data-exchanging, and the needs for real-time data make real-time data warehouse a popular area in the research of data warehouse. What effects can we have if we apply XML technology to the research of real-time data warehouse? XML technology solves many technologic problems which are impossible to be addressed in traditional real-time data warehouse, and realize the integration of OLAP (On-line Analytical Processing) and OLTP (Online transaction processing) environment. Then real-time data warehouse can truly be called "real time".

Mixed - mode Operating System for Real - time Performance

OpenAIRE

Hasan M. M.; Sultana S.; Foo C.K.

2017-01-01

The purpose of the mixed-mode system research is to handle devices with the accuracy of real-time systems and at the same time, having all the benefits and facilities of a matured Graphic User Interface(GUI)operating system which is typicallynon-real-time. This mixed-mode operating system comprising of a real-time portion and a non-real-time portion was studied and implemented to identify the feasibilities and performances in practical applications (in the context of scheduled the real-time e...

A real time zero-dimensional diagnostic model for the calculation of in-cylinder temperatures, HRR and nitrogen oxides in diesel engines

International Nuclear Information System (INIS)

Finesso, Roberto; Spessa, Ezio

2014-01-01

Highlights: • Real-time zero-dimensional three-zone diagnostic combustion model. • Capable of evaluating in-cylinder temperatures, HRR and NOx in DI diesel engines. • Able to be integrated in the engine ECU for control applications. • Able to be integrated in the test bed acquisition software for calibration tasks. • Tested under both steady state and fast transient conditions. - Abstract: A real-time zero-dimensional diagnostic combustion model has been developed and assessed to evaluate in-cylinder temperatures, HRR (heat release rate) and NOx (nitrogen oxides) in DI (Direct Injection) diesel engines under steady state and transient conditions. The approach requires very little computational time, that is, of the order of a few milliseconds, and is therefore suitable for real-time applications. It could, for example, be implemented in an ECU (Engine Control Unit) for the on-board diagnostics of combustion and emission formation processes, or it could be integrated in acquisition software installed on an engine test bench for indicated analysis. The model could also be used for post-processing analysis of previously acquired experimental data. The methodology is based on a three-zone thermodynamic model: the combustion chamber is divided into a fuel zone, an unburned gas zone and a stoichiometric burned gas zone, to which the energy and mass conservation equations are applied. The main novelty of the proposed method is that the equations can be solved in closed form, thus making the approach suitable for real-time applications. The evaluation of the temperature of burned gases allows the in-cylinder NOx concentration to be calculated, on the basis of prompt and Zeldovich thermal mechanisms. The procedure also takes into account the NOx level in the intake charge, and is therefore suitable for engines equipped with traditional short-route EGR (Exhaust Gas Recirculation) systems, and engines equipped with SCR (Selective Catalytic Reduction) and long

Adaptive pattern recognition in real-time video-based soccer analysis

DEFF Research Database (Denmark)

Schlipsing, Marc; Salmen, Jan; Tschentscher, Marc

2017-01-01

are taken into account. Our contribution is twofold: (1) the deliberate use of machine learning and pattern recognition techniques allows us to achieve high classification accuracy in varying environments. We systematically evaluate combinations of image features and learning machines in the given online......Computer-aided sports analysis is demanded by coaches and the media. Image processing and machine learning techniques that allow for "live" recognition and tracking of players exist. But these methods are far from collecting and analyzing event data fully autonomously. To generate accurate results......, human interaction is required at different stages including system setup, calibration, supervision of classifier training, and resolution of tracking conflicts. Furthermore, the real-time constraints are challenging: in contrast to other object recognition and tracking applications, we cannot treat data...

Mixed-mode Operating System for Real-time Performance

Directory of Open Access Journals (Sweden)

M.M. Hasan

2017-11-01

Full Text Available The purpose of the mixed-mode system research is to handle devices with the accuracy of real-time systems and at the same time, having all the benefits and facilities of a matured Graphic User Interface (GUI operating system which is typically nonreal-time. This mixed-mode operating system comprising of a real-time portion and a non-real-time portion was studied and implemented to identify the feasibilities and performances in practical applications (in the context of scheduled the real-time events. In this research an i8751 microcontroller-based hardware was used to measure the performance of the system in real-time-only as well as non-real-time-only configurations. The real-time portion is an 486DX-40 IBM PC system running under DOS-based realtime kernel and the non-real-time portion is a Pentium III based system running under Windows NT. It was found that mixed-mode systems performed as good as a typical realtime system and in fact, gave many additional benefits such as simplified/modular programming and load tolerance.

PWR plant transient analyses using TRAC-PF1

International Nuclear Information System (INIS)

Ireland, J.R.; Boyack, B.E.

1984-01-01

This paper describes some of the pressurized water reactor (PWR) transient analyses performed at Los Alamos for the US Nuclear Regulatory Commission using the Transient Reactor Analysis Code (TRAC-PF1). Many of the transient analyses performed directly address current PWR safety issues. Included in this paper are examples of two safety issues addressed by TRAC-PF1. These examples are pressurized thermal shock (PTS) and feed-and-bleed cooling for Oconee-1. The calculations performed were plant specific in that details of both the primary and secondary sides were modeled in addition to models of the plant integrated control systems. The results of these analyses show that for these two transients, the reactor cores remained covered and cooled at all times posing no real threat to the reactor system nor to the public

Testing of real-time-software

International Nuclear Information System (INIS)

Friesland, G.; Ovenhausen, H.

1975-05-01

The situation in the area of testing real-time-software is unsatisfactory. During the first phase of the project PROMOTE (prozessorientiertes Modul- und Gesamttestsystem) an analysis of the momentary situation took place, results of which are summarized in the following study about some user interviews and an analysis of relevant literature. 22 users (industry, software-houses, hardware-manufacturers, and institutes) have been interviewed. Discussions were held about reliability of real-time software with special interest to error avoidance, testing, and debugging. Main aims of the analysis of the literature were elaboration of standard terms, comparison of existing test methods and -systems, and the definition of boundaries to related areas. During the further steps of this project some means and techniques will be worked out to systematically test real-time software. (orig.) [de

Validation and Assessment of Multi-GNSS Real-Time Precise Point Positioning in Simulated Kinematic Mode Using IGS Real-Time Service

Directory of Open Access Journals (Sweden)

Liang Wang

2018-02-01

Full Text Available Precise Point Positioning (PPP is a popular technology for precise applications based on the Global Navigation Satellite System (GNSS. Multi-GNSS combined PPP has become a hot topic in recent years with the development of multiple GNSSs. Meanwhile, with the operation of the real-time service (RTS of the International GNSS Service (IGS agency that provides satellite orbit and clock corrections to broadcast ephemeris, it is possible to obtain the real-time precise products of satellite orbits and clocks and to conduct real-time PPP. In this contribution, the real-time multi-GNSS orbit and clock corrections of the CLK93 product are applied for real-time multi-GNSS PPP processing, and its orbit and clock qualities are investigated, first with a seven-day experiment by comparing them with the final multi-GNSS precise product ‘GBM’ from GFZ. Then, an experiment involving real-time PPP processing for three stations in the Multi-GNSS Experiment (MGEX network with a testing period of two weeks is conducted in order to evaluate the convergence performance of real-time PPP in a simulated kinematic mode. The experimental result shows that real-time PPP can achieve a convergence performance of less than 15 min for an accuracy level of 20 cm. Finally, the real-time data streams from 12 globally distributed IGS/MGEX stations for one month are used to assess and validate the positioning accuracy of real-time multi-GNSS PPP. The results show that the simulated kinematic positioning accuracy achieved by real-time PPP on different stations is about 3.0 to 4.0 cm for the horizontal direction and 5.0 to 7.0 cm for the three-dimensional (3D direction.

The FERMI-Elettra distributed real-time framework

International Nuclear Information System (INIS)

Pivetta, L.; Gaio, G.; Passuello, R.; Scalamera, G.

2012-01-01

FERMI-Elettra is a Free Electron Laser (FEL) based on a 1.5 GeV linac. The pulsed operation of the accelerator and the necessity to characterize and control each electron bunch requires synchronous acquisition of the beam diagnostics together with the ability to drive actuators in real-time at the linac repetition rate. The Adeos/Xenomai real-time extensions have been adopted in order to add real-time capabilities to the Linux based control system computers running the Tango software. A software communication protocol based on Gigabit Ethernet and known as Network Reflective Memory (NRM) has been developed to implement a shared memory across the whole control system, allowing computers to communicate in real-time. The NRM architecture, the real-time performance and the integration in the control system are described. (authors)

Real-time video quality monitoring

Science.gov (United States)

Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

2011-12-01

The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

Towards an unbiased, full-sky clustering search with IceCube in real time

Energy Technology Data Exchange (ETDEWEB)

Bernardini, Elisa; Franckowiak, Anna; Kintscher, Thomas; Kowalski, Marek; Stasik, Alexander [DESY, Zeuthen (Germany); Collaboration: IceCube-Collaboration

2016-07-01

The IceCube neutrino observatory is a 1 km{sup 3} detector for Cherenkov light in the ice at the South Pole. Having observed the presence of a diffuse astrophysical neutrino flux, static point source searches have come up empty handed. Thus, transient and variable objects emerge as promising, detectable source candidates. An unbiased, full-sky clustering search - run in real time - can find neutrino events with close temporal and spatial proximity. The most significant of these clusters serve as alerts to third-party observatories in order to obtain a complete picture of cosmic accelerators. The talk showcases the status and prospects of this project.

Heterogeneous Embedded Real-Time Systems Environment

Science.gov (United States)

2003-12-01

AFRL-IF-RS-TR-2003-290 Final Technical Report December 2003 HETEROGENEOUS EMBEDDED REAL - TIME SYSTEMS ENVIRONMENT Integrated...HETEROGENEOUS EMBEDDED REAL - TIME SYSTEMS ENVIRONMENT 6. AUTHOR(S) Cosmo Castellano and James Graham 5. FUNDING NUMBERS C - F30602-97-C-0259

Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes

International Nuclear Information System (INIS)

Ortigosa, Nuria; Fernández, Carmen; Galbis, Antonio; Cano, Óscar

2015-01-01

Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and patient classification is done afterwards, when its clinical course is available. In this paper we present a comparison of classification performances when differentiating paroxysmal and persistent atrial fibrillation episodes by means of support vector machines. We analyze short surface electrocardiogram recordings by extracting modulus and phase features from several time-frequency transforms: short-time Fourier transform, Wigner–Ville, Choi–Williams, Stockwell transform, and general Fourier-family transform. Overall, accuracy higher than 81% is obtained when classifying phase information features of real test ECGs from a heterogeneous cohort of patients (in terms of progression of the arrhythmia and antiarrhythmic treatment) recorded in a tertiary center. Therefore, phase features can facilitate the clinicians’ choice of the most appropriate treatment for each patient by means of a non-invasive technique (the surface ECG). (paper)

Real-time estimation of small-area populations with human biomarkers in sewage

International Nuclear Information System (INIS)

Daughton, Christian G.

2012-01-01

A new approach is conceptualized for measuring small-area human populations by using biomarkers in sewage. The basis for the concept (SCIM: Sewage Chemical-Information Mining) is supported by a comprehensive examination and synthesis of data published across several disciplines, including medicine, microbiology, clinical chemistry, and environmental science. Accurate measures of human populations are fundamental to numerous disciplines, including economics, marketing, politics, sociology, public health and safety (e.g., disease management; assessment of natural hazards; disaster prevention and response), quality of life, and the environment. Knowing the size, distribution, and flow of a small-area (local) population facilitates understanding the numerous and complex linkages and interactions between humans and the environment. Examples include material-flow (substance-flow) analysis, determining the magnitude of per capita contribution of pollutant loadings to watersheds, or forecasting future impacts of local populations on the environment or a population's demands on resources. While no definitive approach exists for measuring small-area populations, census-taking is a long-established convention. No approach exists, however, for gauging small-area populations in real-time, as none is able to capture population dynamics, which involve transient changes (e.g., daily influx and efflux) and lasting changes (e.g., births, deaths, change in residence). Accurate measurement of small-area populations in real time has never been possible but is essential for facilitating the design of more sustainable communities. Real-time measurement would provide communities the capability of testing what-if scenarios in design and policy decisions. After evaluation of a range of biomarkers (including the nitrogenous waste product creatinine, which has been long used in clinical chemistry as a parameter to normalize the concentrations of other urinary excretion products to account for

Temporal Proof Methodologies for Real-Time Systems,

Science.gov (United States)

1990-09-01

real time systems that communicate either through shared variables or by message passing and real time issues such as time-outs, process priorities (interrupts) and process scheduling. The authors exhibit two styles for the specification of real - time systems . While the first approach uses bounded versions of temporal operators the second approach allows explicit references to time through a special clock variable. Corresponding to two styles of specification the authors present and compare two fundamentally different proof

Could We Realize the Fully Flexible System by Real-Time Computing with Thin-Film Transistors?

Directory of Open Access Journals (Sweden)

Qin Li

2017-11-01

Full Text Available Flexible electronic devices, such as the typical thin-film transistors, are widely adopted in the area of sensors, displayers, wearable equipment, and such large-area applications, for their features of bending and stretching; additionally, in some applications of lower-resolution data converters recently, where a trend appears that implementing more parts of system with flexible devices to realize the fully flexible system. Nevertheless, relatively fewer works on the computation parts with flexible electronic devices are reported, due to their poor carrier mobility, which blocks the way to realize the fully flexible systems with uniform manufacturing process. In this paper, a novel circuit architecture for image processing accelerator using Oxide Thin-film transistor (TFT, which could realize real-time image pre-processing and classification in the analog domain, is proposed, where the performance and fault-tolerance of image signal processing is exploited. All of the computation is done in the analog signal domain and no clock signal is needed. Therefore, certain weaknesses of flexible electronic devices, such as low carrier mobility, could be remedied dramatically. In this paper, Simulations based on Oxide TFT device model have demonstrated that the flexible computing parts could perform 5 × 5 Gaussian convolution operation at a speed of 3.3 MOPS/s with the energy efficiency of 1.83 TOPS/J, and realize image classification at a speed of 10 k fps, with the energy efficiency of 5.25 GOPS/J, which means that the potential applications to realize real-time computing parts of complex algorithms with flexible electronic devices, as well as the future fully flexible systems containing sensors, data converters, energy suppliers, and real-time signal processing modules, all with flexible devices.

Real-time communication protocols: an overview

NARCIS (Netherlands)

Hanssen, F.T.Y.; Jansen, P.G.

2003-01-01

This paper describes several existing data link layer protocols that provide real-time capabilities on wired networks, focusing on token-ring and Carrier Sense Multiple Access based networks. Existing modifications to provide better real-time capabilities and performance are also described. Finally

Self-Organization in Embedded Real-Time Systems

CERN Document Server

Brinkschulte, Uwe; Rettberg, Achim

2013-01-01

This book describes the emerging field of self-organizing, multicore, distributed and real-time embedded systems.  Self-organization of both hardware and software can be a key technique to handle the growing complexity of modern computing systems. Distributed systems running hundreds of tasks on dozens of processors, each equipped with multiple cores, requires self-organization principles to ensure efficient and reliable operation. This book addresses various, so-called Self-X features such as self-configuration, self-optimization, self-adaptation, self-healing and self-protection. Presents open components for embedded real-time adaptive and self-organizing applications; Describes innovative techniques in: scheduling, memory management, quality of service, communications supporting organic real-time applications; Covers multi-/many-core embedded systems supporting real-time adaptive systems and power-aware, adaptive hardware and software systems; Includes case studies of open embedded real-time self-organizi...

Real-time systems scheduling fundamentals

CERN Document Server

Chetto, Maryline

2014-01-01

Real-time systems are used in a wide range of applications, including control, sensing, multimedia, etc.  Scheduling is a central problem for these computing/communication systems since responsible of software execution in a timely manner. This book provides state of knowledge in this domain with special emphasis on the key results obtained within the last decade. This book addresses foundations as well as the latest advances and findings in Real-Time Scheduling, giving all references to important papers. But nevertheless the chapters will be short and not overloaded with confusing details.

Field transients of coherent terahertz synchrotron radiation accessed via time-resolving and correlation techniques

Energy Technology Data Exchange (ETDEWEB)

Pohl, A.; Hübers, H.-W. [Humboldt-Universität zu Berlin, Institute of Physics, Newtonstraße 15, 12489 Berlin (Germany); Institute of Optical Sensor Systems, German Aerospace Center (DLR), Rutherfordstrasse 29, 12489 Berlin (Germany); Semenov, A. [Institute of Optical Sensor Systems, German Aerospace Center (DLR), Rutherfordstrasse 29, 12489 Berlin (Germany); Hoehl, A.; Ulm, G. [Physikalisch-Technische Bundesanstalt (PTB), Abbestraße 2-12, 10587 Berlin (Germany); Ries, M.; Wüstefeld, G. [Helmholz-Zentrum Berlin, Albert-Einstein-Str. 15, 12489 Berlin (Germany); Ilin, K.; Thoma, P.; Siegel, M. [Institute of Micro- and Nanoelectronic Systems, Karlsruhe Institute of Technology (KIT), Hertzstrasse 16, 76187 Karlsruhe (Germany)

2016-03-21

Decaying oscillations of the electric field in repetitive pulses of coherent synchrotron radiation in the terahertz frequency range was evaluated by means of time-resolving and correlation techniques. Comparative analysis of real-time voltage transients of the electrical response and interferograms, which were obtained with an ultrafast zero-bias Schottky diode detector and a Martin-Puplett interferometer, delivers close values of the pulse duration. Consistent results were obtained via the correlation technique with a pair of Golay Cell detectors and a pair of resonant polarisation-sensitive superconducting detectors integrated on one chip. The duration of terahertz synchrotron pulses does not closely correlate with the duration of single-cycle electric field expected for the varying size of electron bunches. We largely attribute the difference to the charge density oscillations in electron bunches and to the low-frequency spectral cut-off imposed by both the synchrotron beamline and the coupling optics of our detectors.

The real time mass evaluation system as a tool for detection of undeclared cascade operation at GCEPs

OpenAIRE

Delbeke, J.F.A.; Howell, J.; Eklund, G.; Peerani, P.; Janssens, W.

2008-01-01

Given the flexibility of current cascade designs a real time mass monitoring system is preferred for safeguarding Gas Centrifuge Enrichment Plants. However, if such a system is to be installed in a GCEP it must not impinge on plant operation or be intrusive. Since load cells are already part of the operational process and located outside the cascade hall their exploitation for safeguards purposes is an obvious development. The paper describes, through dynamic simulations, how transients would...

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions.

Directory of Open Access Journals (Sweden)

Vasanthan Maruthapillai

Full Text Available In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face and change in marker distance (change in distance between the original and new marker positions, were used to extract three statistical features (mean, variance, and root mean square from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions.

Science.gov (United States)

Maruthapillai, Vasanthan; Murugappan, Murugappan

2016-01-01

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.

Binary nucleation kinetics. III. Transient behavior and time lags

International Nuclear Information System (INIS)

Wyslouzil, B.E.; Wilemski, G.

1996-01-01

Transient binary nucleation is more complex than unary because of the bidimensionality of the cluster formation kinetics. To investigate this problem qualitatively and quantitatively, we numerically solved the birth-death equations for vapor-to-liquid phase transitions. Our previous work showed that the customary saddle point and growth path approximations are almost always valid in steady state gas phase nucleation and only fail if the nucleated solution phase is significantly nonideal. Now, we demonstrate that in its early transient stages, binary nucleation rarely, if ever, occurs via the saddle point. This affects not only the number of particles forming but their composition and may be important for nucleation in glasses and other condensed mixtures for which time scales are very long. Before reaching the state of saddle point nucleation, most binary systems pass through a temporary stage in which the region of maximum flux extends over a ridge on the free energy surface. When ridge crossing nucleation is the steady state solution, it thus arises quite naturally as an arrested intermediate state that normally occurs in the development of saddle point nucleation. While the time dependent and steady state distributions of the fluxes and concentrations for each binary system are strongly influenced by the gas composition and species impingement rates, the ratio of nonequilibrium to equilibrium concentrations has a quasiuniversal behavior that is determined primarily by the thermodynamic properties of the liquid mixture. To test our quantitive results of the transient behavior, we directly calculated the time lag for the saddle point flux and compared it with the available analytical predictions. Although the analytical results overestimate the time lag by factors of 1.2-5, they should be adequate for purposes of planning experiments. We also found that the behavior of the saddle point time lag can indicate when steady state ridge crossing nucleation will occur

Real-time specifications

DEFF Research Database (Denmark)

David, A.; Larsen, K.G.; Legay, A.

2015-01-01

A specification theory combines notions of specifications and implementations with a satisfaction relation, a refinement relation, and a set of operators supporting stepwise design. We develop a specification framework for real-time systems using Timed I/O Automata as the specification formalism......, with the semantics expressed in terms of Timed I/O Transition Systems. We provide constructs for refinement, consistency checking, logical and structural composition, and quotient of specifications-all indispensable ingredients of a compositional design methodology. The theory is implemented in the new tool Ecdar...

Connection with seismic networks and construction of real time earthquake monitoring system

Energy Technology Data Exchange (ETDEWEB)

Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

2000-12-15

It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system.

Connection with seismic networks and construction of real time earthquake monitoring system

International Nuclear Information System (INIS)

Chi, Heon Cheol; Lee, H. I.; Shin, I. C.; Lim, I. S.; Park, J. H.; Lee, B. K.; Whee, K. H.; Cho, C. S.

2000-12-01

It is natural to use the nuclear power plant seismic network which have been operated by KEPRI(Korea Electric Power Research Institute) and local seismic network by KIGAM(Korea Institute of Geology, Mining and Material). The real time earthquake monitoring system is composed with monitoring module and data base module. Data base module plays role of seismic data storage and classification and the other, monitoring module represents the status of acceleration in the nuclear power plant area. This research placed the target on the first, networking the KIN's seismic monitoring system with KIGAM and KEPRI seismic network and the second, construction the KIN's Independent earthquake monitoring system

On Real-Time Systems Using Local Area Networks.

Science.gov (United States)

1987-07-01

87-35 July, 1987 CS-TR-1892 On Real - Time Systems Using Local Area Networks*I VShem-Tov Levi Department of Computer Science Satish K. Tripathit...1892 On Real - Time Systems Using Local Area Networks* Shem-Tov Levi Department of Computer Science Satish K. Tripathit Department of Computer Science...constraints and the clock systems that feed the time to real - time systems . A model for real-time system based on LAN communication is presented in

Development of a Real-Time Virtual Nitric Oxide Sensor for Light-Duty Diesel Engines

Directory of Open Access Journals (Sweden)

Seungha Lee

2017-03-01

Full Text Available This study describes the development of a semi-physical, real-time nitric oxide (NO prediction model that is capable of cycle-by-cycle prediction in a light-duty diesel engine. The model utilizes the measured in-cylinder pressure and information obtained from the engine control unit (ECU. From the inputs, the model takes into account the pilot injection burning and mixing, which affects the in-cylinder mixture formation. The representative in-cylinder temperature for NO formation was determined from the mixture composition calculation. The selected temperature and mixture composition was substituted using a simplified form of the NO formation rate equation for the cycle-by-cycle estimation. The reactive area and the duration of NO formation were assumed to be limited by the fuel quantity. The model predictability was verified not only using various steady-state conditions, including the variation of the EGR rate, the boost pressure, the rail pressure, and the injection timing, but also using transient conditions, which represent the worldwide harmonized light vehicles test procedure (WLTC. The WLTC NO prediction results produced less than 3% error with the measured value. In addition, the proposed model maintained its reliability in terms of hardware aging, the changing and artificial perturbations during steady-state and transient engine operations. The model has been shown to require low computational effort because of the cycle-by-cycle, engine-out NO emission prediction and control were performed simultaneously in an embedded system for the automotive application. We expect that the developed NO prediction model can be helpful in emission calibration during the engine design stage or in the real-time controlling of the exhaust NO emission for improving fuel consumption while satisfying NO emission legislation.

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

Science.gov (United States)

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. Copyright © 2014 Elsevier B.V. All rights reserved.

Real-time detection and discrimination of visual perception using electrocorticographic signals

Science.gov (United States)

Kapeller, C.; Ogawa, H.; Schalk, G.; Kunii, N.; Coon, W. G.; Scharinger, J.; Guger, C.; Kamada, K.

2018-06-01

Objective. Several neuroimaging studies have demonstrated that the ventral temporal cortex contains specialized regions that process visual stimuli. This study investigated the spatial and temporal dynamics of electrocorticographic (ECoG) responses to different types and colors of visual stimulation that were presented to four human participants, and demonstrated a real-time decoder that detects and discriminates responses to untrained natural images. Approach. ECoG signals from the participants were recorded while they were shown colored and greyscale versions of seven types of visual stimuli (images of faces, objects, bodies, line drawings, digits, and kanji and hiragana characters), resulting in 14 classes for discrimination (experiment I). Additionally, a real-time system asynchronously classified ECoG responses to faces, kanji and black screens presented via a monitor (experiment II), or to natural scenes (i.e. the face of an experimenter, natural images of faces and kanji, and a mirror) (experiment III). Outcome measures in all experiments included the discrimination performance across types based on broadband γ activity. Main results. Experiment I demonstrated an offline classification accuracy of 72.9% when discriminating among the seven types (without color separation). Further discrimination of grey versus colored images reached an accuracy of 67.1%. Discriminating all colors and types (14 classes) yielded an accuracy of 52.1%. In experiment II and III, the real-time decoder correctly detected 73.7% responses to face, kanji and black computer stimuli and 74.8% responses to presented natural scenes. Significance. Seven different types and their color information (either grey or color) could be detected and discriminated using broadband γ activity. Discrimination performance maximized for combined spatial-temporal information. The discrimination of stimulus color information provided the first ECoG-based evidence for color-related population

Mixed-mode Operating System for Real-time Performance

OpenAIRE

M.M. Hasan; S. Sultana; C.K. Foo

2017-01-01

The purpose of the mixed-mode system research is to handle devices with the accuracy of real-time systems and at the same time, having all the benefits and facilities of a matured Graphic User Interface (GUI) operating system which is typically nonreal-time. This mixed-mode operating system comprising of a real-time portion and a non-real-time portion was studied and implemented to identify the feasibilities and performances in practical applications (in the context of scheduled the real-time...

Linux real-time framework for fusion devices

Energy Technology Data Exchange (ETDEWEB)

Neto, Andre [Associacao Euratom-IST, Instituto de Plasmas e Fusao Nuclear, Av. Rovisco Pais, 1049-001 Lisboa (Portugal)], E-mail: andre.neto@cfn.ist.utl.pt; Sartori, Filippo; Piccolo, Fabio [Euratom-UKAEA, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Barbalace, Antonio [Euratom-ENEA Association, Consorzio RFX, 35127 Padova (Italy); Vitelli, Riccardo [Dipartimento di Informatica, Sistemi e Produzione, Universita di Roma, Tor Vergata, Via del Politecnico 1-00133, Roma (Italy); Fernandes, Horacio [Associacao Euratom-IST, Instituto de Plasmas e Fusao Nuclear, Av. Rovisco Pais, 1049-001 Lisboa (Portugal)

2009-06-15

A new framework for the development and execution of real-time codes is currently being developed and commissioned at JET. The foundations of the system are Linux, the Real Time Application Interface (RTAI) and a wise exploitation of the new i386 multi-core processors technology. The driving motivation was the need to find a real-time operating system for the i386 platform able to satisfy JET Vertical Stabilisation Enhancement project requirements: 50 {mu}s cycle time. Even if the initial choice was the VxWorks operating system, it was decided to explore an open source alternative, mostly because of the costs involved in the commercial product. The work started with the definition of a precise set of requirements and milestones to achieve: Linux distribution and kernel versions to be used for the real-time operating system; complete characterization of the Linux/RTAI real-time capabilities; exploitation of the multi-core technology; implementation of all the required and missing features; commissioning of the system. Latency and jitter measurements were compared for Linux and RTAI in both user and kernel-space. The best results were attained using the RTAI kernel solution where the time to reschedule a real-time task after an external interrupt is of 2.35 {+-} 0.35 {mu}s. In order to run the real-time codes in the kernel-space, a solution to provide user-space functionalities to the kernel modules had to be designed. This novel work provided the most common functions from the standard C library and transparent interaction with files and sockets to the kernel real-time modules. Kernel C++ support was also tested, further developed and integrated in the framework. The work has produced very convincing results so far: complete isolation of the processors assigned to real-time from the Linux non real-time activities, high level of stability over several days of benchmarking operations and values well below 3 {mu}s for task rescheduling after external interrupt. From

Linux real-time framework for fusion devices

International Nuclear Information System (INIS)

Neto, Andre; Sartori, Filippo; Piccolo, Fabio; Barbalace, Antonio; Vitelli, Riccardo; Fernandes, Horacio

2009-01-01

A new framework for the development and execution of real-time codes is currently being developed and commissioned at JET. The foundations of the system are Linux, the Real Time Application Interface (RTAI) and a wise exploitation of the new i386 multi-core processors technology. The driving motivation was the need to find a real-time operating system for the i386 platform able to satisfy JET Vertical Stabilisation Enhancement project requirements: 50 μs cycle time. Even if the initial choice was the VxWorks operating system, it was decided to explore an open source alternative, mostly because of the costs involved in the commercial product. The work started with the definition of a precise set of requirements and milestones to achieve: Linux distribution and kernel versions to be used for the real-time operating system; complete characterization of the Linux/RTAI real-time capabilities; exploitation of the multi-core technology; implementation of all the required and missing features; commissioning of the system. Latency and jitter measurements were compared for Linux and RTAI in both user and kernel-space. The best results were attained using the RTAI kernel solution where the time to reschedule a real-time task after an external interrupt is of 2.35 ± 0.35 μs. In order to run the real-time codes in the kernel-space, a solution to provide user-space functionalities to the kernel modules had to be designed. This novel work provided the most common functions from the standard C library and transparent interaction with files and sockets to the kernel real-time modules. Kernel C++ support was also tested, further developed and integrated in the framework. The work has produced very convincing results so far: complete isolation of the processors assigned to real-time from the Linux non real-time activities, high level of stability over several days of benchmarking operations and values well below 3 μs for task rescheduling after external interrupt. From being the

Static Schedulers for Embedded Real-Time Systems

Science.gov (United States)

1989-12-01

Because of the need for having efficient scheduling algorithms in large scale real time systems , software engineers put a lot of effort on developing...provide static schedulers for he Embedded Real Time Systems with single processor using Ada programming language. The independent nonpreemptable...support the Computer Aided Rapid Prototyping for Embedded Real Time Systems so that we determine whether the system, as designed, meets the required

Real-time motional Stark effect in jet

International Nuclear Information System (INIS)

Alves, D.; Stephen, A.; Hawkes, N.; Dalley, S.; Goodyear, A.; Felton, R.; Joffrin, E.; Fernandes, H.

2004-01-01

The increasing importance of real-time measurements and control systems in JET experiments, regarding e.g. Internal Transport Barrier (ITB) and q-profile control, has motivated the development of a real-time motional Stark effect (MSE) system. The MSE diagnostic allows the measurement of local magnetic fields in different locations along the neutral beam path providing, therefore, local measurement of the current and q-profiles. Recently in JET, an upgrade of the MSE diagnostic has been implemented, incorporating a totally new system which allows the use of this diagnostic as a real-time control tool as well as an extended data source for off-line analysis. This paper will briefly describe the technical features of the real-time diagnostic with main focus on the system architecture, which consists of a VME crate hosting three PowerPC processor boards and a fast ADC, all connected via Front Panel Data Port (FPDP). The DSP algorithm implements a lockin-amplifier required to demodulate the JET MSE signals. Some applications for the system will be covered such as: feeding the real-time equilibrium reconstruction code (EQUINOX) and allowing the full coverage analysis of the Neutral Beam time window. A brief comparison between the real-time MSE analysis and the off-line analysis will also be presented

A control-oriented real-time semi-empirical model for the prediction of NOx emissions in diesel engines

International Nuclear Information System (INIS)

D’Ambrosio, Stefano; Finesso, Roberto; Fu, Lezhong; Mittica, Antonio; Spessa, Ezio

2014-01-01

Highlights: • New semi-empirical correlation to predict NOx emissions in diesel engines. • Based on a real-time three-zone diagnostic combustion model. • The model is of fast application, and is therefore suitable for control-oriented applications. - Abstract: The present work describes the development of a fast control-oriented semi-empirical model that is capable of predicting NOx emissions in diesel engines under steady state and transient conditions. The model takes into account the maximum in-cylinder burned gas temperature of the main injection, the ambient gas-to-fuel ratio, the mass of injected fuel, the engine speed and the injection pressure. The evaluation of the temperature of the burned gas is based on a three-zone real-time diagnostic thermodynamic model that has recently been developed by the authors. Two correlations have also been developed in the present study, in order to evaluate the maximum burned gas temperature during the main combustion phase (derived from the three-zone diagnostic model) on the basis of significant engine parameters. The model has been tuned and applied to two diesel engines that feature different injection systems of the indirect acting piezoelectric, direct acting piezoelectric and solenoid type, respectively, over a wide range of steady-state operating conditions. The model has also been validated in transient operation conditions, over the urban and extra-urban phases of an NEDC. It has been shown that the proposed approach is capable of improving the predictive capability of NOx emissions, compared to previous approaches, and is characterized by a very low computational effort, as it is based on a single-equation correlation. It is therefore suitable for real-time applications, and could also be integrated in the engine control unit for closed-loop or feed-forward control tasks

Scala for Real-Time Systems?

DEFF Research Database (Denmark)

Schoeberl, Martin

2015-01-01

Java served well as a general-purpose language. However, during its two decades of constant change it has gotten some weight and legacy in the language syntax and the libraries. Furthermore, Java's success for real-time systems is mediocre. Scala is a modern object-oriented and functional language...... with interesting new features. Although a new language, it executes on a Java virtual machine, reusing that technology. This paper explores Scala as language for future real-time systems....

Improved Transient Performance of a Fuzzy Modified Model Reference Adaptive Controller for an Interacting Coupled Tank System Using Real-Coded Genetic Algorithm

Directory of Open Access Journals (Sweden)

Asan Mohideen Khansadurai

2014-01-01

Full Text Available The main objective of the paper is to design a model reference adaptive controller (MRAC with improved transient performance. A modification to the standard direct MRAC called fuzzy modified MRAC (FMRAC is used in the paper. The FMRAC uses a proportional control based Mamdani-type fuzzy logic controller (MFLC to improve the transient performance of a direct MRAC. The paper proposes the application of real-coded genetic algorithm (RGA to tune the membership function parameters of the proposed FMRAC offline so that the transient performance of the FMRAC is improved further. In this study, a GA based modified MRAC (GAMMRAC, an FMRAC, and a GA based FMRAC (GAFMRAC are designed for a coupled tank setup in a hybrid tank process and their transient performances are compared. The results show that the proposed GAFMRAC gives a better transient performance than the GAMMRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient performance for the control of nonlinear processes.

Analysis of Time n Frequency EEG Feature Extraction Methods for Mental Task Classification

Directory of Open Access Journals (Sweden)

Caglar Uyulan

2017-01-01

Full Text Available Many endogenous and external components may affect the physiological, mental and behavioral states in humans. Monitoring tools are required to evaluate biomarkers, identify biological events, and predict their outcomes. Being one of the valuable indicators, brain biomarkers derived from temporal or spectral electroencephalography (EEG signals processing, allow for the classification of mental disorders and mental tasks. An EEG signal has a nonstationary nature and individual frequency feature, hence it can be concluded that each subject has peculiar timing and data to extract unique features. In order to classify data, which are collected by performing four mental task (reciting the alphabet backwards, imagination of rotation of a cube, imagination of right hand movements (open/close and performing mathematical operations, discriminative features were extracted using four competitive time-frequency techniques; Wavelet Packet Decomposition (WPD, Morlet Wavelet Transform (MWT, Short Time Fourier Transform (STFT and Wavelet Filter Bank (WFB, respectively. The extracted features using both time and frequency domain information were then reduced using a principal component analysis for subset reduction. Finally, the reduced subsets were fed into a multi-layer perceptron neural network (MP-NN trained with back propagation (BP algorithm to generate a predictive model. This study mainly focuses on comparing the relative performance of time-frequency feature extraction methods that are used to classify mental tasks. The real-time (RT conducted experimental results underlined that the WPD feature extraction method outperforms with 92% classification accuracy compared to three other aforementioned methods for four different mental tasks.

[Research progress on real-time deformable models of soft tissues for surgery simulation].

Science.gov (United States)

Xu, Shaoping; Liu, Xiaoping; Zhang, Hua; Luo, Jie

2010-04-01

Biological tissues generally exhibit nonlinearity, anisotropy, quasi-incompressibility and viscoelasticity about material properties. Simulating the behaviour of elastic objects in real time is one of the current objectives of virtual surgery simulation which is still a challenge for researchers to accurately depict the behaviour of human tissues. In this paper, we present a classification of the different deformable models that have been developed. We present the advantages and disadvantages of each one. Finally, we make a comparison of deformable models and perform an evaluation of the state of the art and the future of deformable models.

Towards exascale real-time RFI mitigation

NARCIS (Netherlands)

van Nieuwpoort, R.V.

2016-01-01

We describe the design and implementation of an extremely scalable real-time RFI mitigation method, based on the offline AOFlagger. All algorithms scale linearly in the number of samples. We describe how we implemented the flagger in the LOFAR real-time pipeline, on both CPUs and GPUs. Additionally,

Transient diagnosis system using quantum-inspired computing and Minkowski distance

Energy Technology Data Exchange (ETDEWEB)

Nicolau, Andressa dos Santos; Schirru, Roberto, E-mail: andressa@lmp.ufrj.b, E-mail: schirru@lmp.ufrj.b [Federal University of Rio de Janeiro (PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Nuclear Engineering Program

2011-07-01

This paper proposes a diagnosis system model for identification of transient in a PWR nuclear power plant, optimized by the Quantum Inspired Evolutionary Algorithm - QEA in order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition. This method was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the nuclear power plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). This System compares the similarly distance between the set of variables of the anomalous event, in a given time t, and the centroids of the design-basis transient variables. The lower similarly distance indicates the class of the transient to which the anomalous event belongs. The QEA was then used to find the best position of the centroids of each class of the selected transients. Such positions maximize the number of the correct classifications. Unlike the diagnosis system proposed in the literature, Minkowski distance was employed to calculate the similarity distance. The signatures of four transients were submitted to 1% and 2% of noise, and tested with prototype vector found by QEA. The results showed that the present transient diagnostic system was successfully implemented in the nuclear accident identification problem and was compatible with the techniques presented in the literature. (author)

Transient diagnosis system using quantum-inspired computing and Minkowski distance

International Nuclear Information System (INIS)

Nicolau, Andressa dos Santos; Schirru, Roberto

2011-01-01

This paper proposes a diagnosis system model for identification of transient in a PWR nuclear power plant, optimized by the Quantum Inspired Evolutionary Algorithm - QEA in order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition. This method was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the nuclear power plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). This System compares the similarly distance between the set of variables of the anomalous event, in a given time t, and the centroids of the design-basis transient variables. The lower similarly distance indicates the class of the transient to which the anomalous event belongs. The QEA was then used to find the best position of the centroids of each class of the selected transients. Such positions maximize the number of the correct classifications. Unlike the diagnosis system proposed in the literature, Minkowski distance was employed to calculate the similarity distance. The signatures of four transients were submitted to 1% and 2% of noise, and tested with prototype vector found by QEA. The results showed that the present transient diagnostic system was successfully implemented in the nuclear accident identification problem and was compatible with the techniques presented in the literature. (author)

Time-Optimal Real-Time Test Case Generation using UPPAAL

DEFF Research Database (Denmark)

Hessel, Anders; Larsen, Kim Guldstrand; Nielsen, Brian

2004-01-01

Testing is the primary software validation technique used by industry today, but remains ad hoc, error prone, and very expensive. A promising improvement is to automatically generate test cases from formal models of the system under test. We demonstrate how to automatically generate real...... test purposes or generated automatically from various coverage criteria of the model.......-time conformance test cases from timed automata specifications. Specifically we demonstrate how to fficiently generate real-time test cases with optimal execution time i.e test cases that are the fastest possible to execute. Our technique allows time optimal test cases to be generated using manually formulated...

A Lyapunov Function Based Remedial Action Screening Tool Using Real-Time Data

Energy Technology Data Exchange (ETDEWEB)

Mitra, Joydeep [Michigan State Univ., East Lansing, MI (United States); Ben-Idris, Mohammed [Univ. of Nevada, Reno, NV (United States); Faruque, Omar [Florida State Univ., Tallahassee, FL (United States); Backhaus, Scott [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Deb, Sidart [LCG Consulting, Los Altos, CA (United States)

2016-03-30

This report summarizes the outcome of a research project that comprised the development of a Lyapunov function based remedial action screening tool using real-time data (L-RAS). The L-RAS is an advanced computational tool that is intended to assist system operators in making real-time redispatch decisions to preserve power grid stability. The tool relies on screening contingencies using a homotopy method based on Lyapunov functions to avoid, to the extent possible, the use of time domain simulations. This enables transient stability evaluation at real-time speed without the use of massively parallel computational resources. The project combined the following components. 1. Development of a methodology for contingency screening using a homotopy method based on Lyapunov functions and real-time data. 2. Development of a methodology for recommending remedial actions based on the screening results. 3. Development of a visualization and operator interaction interface. 4. Testing of screening tool, validation of control actions, and demonstration of project outcomes on a representative real system simulated on a Real-Time Digital Simulator (RTDS) cluster. The project was led by Michigan State University (MSU), where the theoretical models including homotopy-based screening, trajectory correction using real-time data, and remedial action were developed and implemented in the form of research-grade software. Los Alamos National Laboratory (LANL) contributed to the development of energy margin sensitivity dynamics, which constituted a part of the remedial action portfolio. Florida State University (FSU) and Southern California Edison (SCE) developed a model of the SCE system that was implemented on FSU's RTDS cluster to simulate real-time data that was streamed over the internet to MSU where the L-RAS tool was executed and remedial actions were communicated back to FSU to execute stabilizing controls on the simulated system. LCG Consulting developed the visualization

Performance evaluation of near-real-time accounting systems

International Nuclear Information System (INIS)

Anon.

1981-01-01

Examples are given illustrating the application of near-real-time accounting concepts and principles to actual nuclear facilities. Experience with prototypical systems at the AGNS reprocessing plant and the Los Alamos plutonium facility is described using examples of actual data to illustrate the performance and effectiveness of near-real-time systems. The purpose of the session is to enable participants to: (1) identify the major components of near-real-time accounting systems; (2) describe qualitatively the advantages, limitations, and performance of such systems in real nuclear facilities; (3) identify process and facility design characteristics that affect the performance of near-real-time systems; and (4) describe qualitatively the steps necessary to implement a near-real-time accounting and control system in a nuclear facility

Distributed Issues for Ada Real-Time Systems

Science.gov (United States)

1990-07-23

NUMBERS Distributed Issues for Ada Real - Time Systems MDA 903-87- C- 0056 S. AUTHOR(S) Thomas E. Griest 7. PERFORMING ORGANiZATION NAME(S) AND ADORESS(ES) 8...considerations. I Adding to the problem of distributed real - time systems is the issue of maintaining a common sense of time among all of the processors...because -omeone is waiting for the final output of a very large set of computations. However in real - time systems , consistent meeting of short-term

Design Specifications for Adaptive Real-Time Systems

Science.gov (United States)

1991-12-01

TICfl \\ E CT E Design Specifications for JAN’\\ 1992 Adaptive Real - Time Systems fl Randall W. Lichota U, Alice H. Muntz - December 1991 \\ \\\\/ 0 / r...268-2056 Technical Report CMU/SEI-91-TR-20 ESD-91-TR-20 December 1991 Design Specifications for Adaptive Real - Time Systems Randall W. Lichota Hughes...Design Specifications for Adaptive Real - Time Systems Abstract: The design specification method described in this report treats a software

Design Recovery Technology for Real-Time Systems.

Science.gov (United States)

1995-10-01

RL-TR-95-208 Final Technical Report October 1995 DESIGN RECOVERY TECHNOLOGY FOR REAL TIME SYSTEMS The MITRE Corporation Lester J. Holtzblatt...92 - Jan 95 4. TTTLE AND SUBTITLE DESIGN RECOVERY TECHNOLOGY FOR REAL - TIME SYSTEMS 6. AUTHOR(S) Lester J. Holtzblatt, Richard Piazza, and Susan...behavior of real - time systems in general, our initial efforts have centered on recovering this information from one system in particular, the Modular

SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

Energy Technology Data Exchange (ETDEWEB)

Kumar, S.; Gezari, S.; Heinis, S. [Department of Astronomy, University of Maryland, Stadium Drive, College Park, MD 21224 (United States); Chornock, R.; Berger, E.; Soderberg, A.; Stubbs, C. W.; Kirshner, R. P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Rest, A. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Huber, M. E.; Narayan, G.; Marion, G. H.; Burgett, W. S. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Foley, R. J. [Astronomy Department, University of Illinois at Urbana-Champaign, 1002 West Green Street, Urbana, IL 61801 (United States); Scolnic, D.; Riess, A. G. [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Lawrence, A. [Institute for Astronomy, University of Edinburgh Scottish Universities Physics Alliance, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); Smartt, S. J.; Smith, K. [Astrophysics Research Centre, School of Mathematics and Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Wood-Vasey, W. M. [Pittsburgh Particle Physics, Astrophysics, and Cosmology Center, Department of Physics and Astronomy, University of Pittsburgh, 3941 O' Hara Street, Pittsburgh, PA 15260 (United States); and others

2015-03-20

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g {sub P1}, r {sub P1}, i {sub P1}, and z {sub P1}. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host

A low-cost single-board solution for real-time, unsupervised waveform classification of multineuron recordings.

Science.gov (United States)

Kreiter, A K; Aertsen, A M; Gerstein, G L

1989-10-01

We describe a low-cost single-board system for unsupervised, real-time spike sorting of recordings from a number of neurons on a single microelectrode. The maximum number of spike classes depends on the quality of the recording; it will typically be between 2 and 5. The spike sorter communicates with a conventional microcomputer through a standard serial port (RS232). For typical firing rates as measured in the mammalian central nervous system, this set-up will accommodate up to some 10 parallel spike sorters for as many separate microelectrodes.

Deep-HiTS: Rotation Invariant Convolutional Neural Network for Transient Detection

Science.gov (United States)

Cabrera-Vives, Guillermo; Reyes, Ignacio; Förster, Francisco; Estévez, Pablo A.; Maureira, Juan-Carlos

2017-02-01

We introduce Deep-HiTS, a rotation-invariant convolutional neural network (CNN) model for classifying images of transient candidates into artifacts or real sources for the High cadence Transient Survey (HiTS). CNNs have the advantage of learning the features automatically from the data while achieving high performance. We compare our CNN model against a feature engineering approach using random forests (RFs). We show that our CNN significantly outperforms the RF model, reducing the error by almost half. Furthermore, for a fixed number of approximately 2000 allowed false transient candidates per night, we are able to reduce the misclassified real transients by approximately one-fifth. To the best of our knowledge, this is the first time CNNs have been used to detect astronomical transient events. Our approach will be very useful when processing images from next generation instruments such as the Large Synoptic Survey Telescope. We have made all our code and data available to the community for the sake of allowing further developments and comparisons at https://github.com/guille-c/Deep-HiTS. Deep-HiTS is licensed under the terms of the GNU General Public License v3.0.

[Real time 3D echocardiography

Science.gov (United States)

Bauer, F.; Shiota, T.; Thomas, J. D.

2001-01-01

Three-dimensional representation of the heart is an old concern. Usually, 3D reconstruction of the cardiac mass is made by successive acquisition of 2D sections, the spatial localisation and orientation of which require complex guiding systems. More recently, the concept of volumetric acquisition has been introduced. A matricial emitter-receiver probe complex with parallel data processing provides instantaneous of a pyramidal 64 degrees x 64 degrees volume. The image is restituted in real time and is composed of 3 planes (planes B and C) which can be displaced in all spatial directions at any time during acquisition. The flexibility of this system of acquisition allows volume and mass measurement with greater accuracy and reproducibility, limiting inter-observer variability. Free navigation of the planes of investigation allows reconstruction for qualitative and quantitative analysis of valvular heart disease and other pathologies. Although real time 3D echocardiography is ready for clinical usage, some improvements are still necessary to improve its conviviality. Then real time 3D echocardiography could be the essential tool for understanding, diagnosis and management of patients.

Real-time communication for distributed plasma control systems

Energy Technology Data Exchange (ETDEWEB)

Luchetta, A. [Consorzio RFX, Associazione Euratom-ENEA sulla Fusione, Corso Stati Uniti 4, Padova 35127 (Italy)], E-mail: adriano.luchetta@igi.cnr.it; Barbalace, A.; Manduchi, G.; Soppelsa, A.; Taliercio, C. [Consorzio RFX, Associazione Euratom-ENEA sulla Fusione, Corso Stati Uniti 4, Padova 35127 (Italy)

2008-04-15

Real-time control applications will benefit in the near future from the enhanced performance provided by multi-core processor architectures. Nevertheless real-time communication will continue to be critical in distributed plasma control systems where the plant under control typically is distributed over a wide area. At RFX-mod real-time communication is crucial for hard real-time plasma control, due to the distributed architecture of the system, which consists of several VMEbus stations. The system runs under VxWorks and uses Gigabit Ethernet for sub-millisecond real-time communication. To optimize communication in the system, a set of detailed measurements has been carried out on the target platforms (Motorola MVME5100 and MVME5500) using either the VxWorks User Datagram Protocol (UDP) stack or raw communication based on the data link layer. Measurements have been carried out also under Linux, using its UDP stack or, in alternative, RTnet, an open source hard real-time network protocol stack. RTnet runs under Xenomai or RTAI, two popular real-time extensions based on the Linux kernel. The paper reports on the measurements carried out and compares the results, showing that the performance obtained by using open source code is suitable for sub-millisecond real-time communication in plasma control.

Acoustic transient classification with a template correlation processor.

Science.gov (United States)

Edwards, R T

1999-10-01

I present an architecture for acoustic pattern classification using trinary-trinary template correlation. In spite of its computational simplicity, the algorithm and architecture represent a method which greatly reduces bandwidth of the input, storage requirements of the classifier memory, and power consumption of the system without compromising classification accuracy. The linear system should be amenable to training using recently-developed methods such as Independent Component Analysis (ICA), and we predict that behavior will be qualitatively similar to that of structures in the auditory cortex.

Gold nanoparticle-based RT-PCR and real-time quantitative RT-PCR assays for detection of Japanese encephalitis virus

International Nuclear Information System (INIS)

Huang, S-H; Tsai, M-H; Lin, C-W; Yang, T-C; Chuang, P-H; Tsai, I-S; Lu, H-C; Wan Lei; Lin, Y-J; Lai, C-H

2008-01-01

Virus isolation and antibody detection are routinely used for diagnosis of Japanese encephalitis virus (JEV) infection, but the low level of transient viremia in some JE patients makes JEV isolation from clinical and surveillance samples very difficult. We describe the use of gold nanoparticle-based RT-PCR and real-time quantitative RT-PCR assays for detection of JEV from its RNA genome. We tested the effect of gold nanoparticles on four different PCR systems, including conventional PCR, reverse-transcription PCR (RT-PCR), and SYBR green real-time PCR and RT-PCR assays for diagnosis in the acute phase of JEV infection. Gold nanoparticles increased the amplification yield of the PCR product and shortened the PCR time compared to the conventional reaction. In addition, nanogold-based real-time RT-PCR showed a linear relationship between Ct and template amount using ten-fold dilutions of JEV. The nanogold-based RT-PCR and real-time quantitative RT-PCR assays were able to detect low levels (1-10 000 copies) of the JEV RNA genomes extracted from culture medium or whole blood, providing early diagnostic tools for the detection of low-level viremia in the acute-phase infection. The assays described here were simple, sensitive, and rapid approaches for detection and quantitation of JEV in tissue cultured samples as well as clinical samples

Software fault detection and recovery in critical real-time systems: An approach based on loose coupling

International Nuclear Information System (INIS)

Alho, Pekka; Mattila, Jouni

2014-01-01

Highlights: •We analyze fault tolerance in mission-critical real-time systems. •Decoupled architectural model can be used to implement fault tolerance. •Prototype implementation for remote handling control system and service manager. •Recovery from transient faults by restarting services. -- Abstract: Remote handling (RH) systems are used to inspect, make changes to, and maintain components in the ITER machine and as such are an example of mission-critical system. Failure in a critical system may cause damage, significant financial losses and loss of experiment runtime, making dependability one of their most important properties. However, even if the software for RH control systems has been developed using best practices, the system might still fail due to undetected faults (bugs), hardware failures, etc. Critical systems therefore need capability to tolerate faults and resume operation after their occurrence. However, design of effective fault detection and recovery mechanisms poses a challenge due to timeliness requirements, growth in scale, and complex interactions. In this paper we evaluate effectiveness of service-oriented architectural approach to fault tolerance in mission-critical real-time systems. We use a prototype implementation for service management with an experimental RH control system and industrial manipulator. The fault tolerance is based on using the high level of decoupling between services to recover from transient faults by service restarts. In case the recovery process is not successful, the system can still be used if the fault was not in a critical software module

Software fault detection and recovery in critical real-time systems: An approach based on loose coupling

Energy Technology Data Exchange (ETDEWEB)

Alho, Pekka, E-mail: pekka.alho@tut.fi; Mattila, Jouni

2014-10-15

Highlights: •We analyze fault tolerance in mission-critical real-time systems. •Decoupled architectural model can be used to implement fault tolerance. •Prototype implementation for remote handling control system and service manager. •Recovery from transient faults by restarting services. -- Abstract: Remote handling (RH) systems are used to inspect, make changes to, and maintain components in the ITER machine and as such are an example of mission-critical system. Failure in a critical system may cause damage, significant financial losses and loss of experiment runtime, making dependability one of their most important properties. However, even if the software for RH control systems has been developed using best practices, the system might still fail due to undetected faults (bugs), hardware failures, etc. Critical systems therefore need capability to tolerate faults and resume operation after their occurrence. However, design of effective fault detection and recovery mechanisms poses a challenge due to timeliness requirements, growth in scale, and complex interactions. In this paper we evaluate effectiveness of service-oriented architectural approach to fault tolerance in mission-critical real-time systems. We use a prototype implementation for service management with an experimental RH control system and industrial manipulator. The fault tolerance is based on using the high level of decoupling between services to recover from transient faults by service restarts. In case the recovery process is not successful, the system can still be used if the fault was not in a critical software module.

Online decoding of object-based attention using real-time fMRI.

Science.gov (United States)

Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J

2014-01-01

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Real-time quasi-3D tomographic reconstruction

Science.gov (United States)

Buurlage, Jan-Willem; Kohr, Holger; Palenstijn, Willem Jan; Joost Batenburg, K.

2018-06-01

Developments in acquisition technology and a growing need for time-resolved experiments pose great computational challenges in tomography. In addition, access to reconstructions in real time is a highly demanded feature but has so far been out of reach. We show that by exploiting the mathematical properties of filtered backprojection-type methods, having access to real-time reconstructions of arbitrarily oriented slices becomes feasible. Furthermore, we present , software for visualization and on-demand reconstruction of slices. A user of can interactively shift and rotate slices in a GUI, while the software updates the slice in real time. For certain use cases, the possibility to study arbitrarily oriented slices in real time directly from the measured data provides sufficient visual and quantitative insight. Two such applications are discussed in this article.

An algorithm for learning real-time automata

NARCIS (Netherlands)

Verwer, S.E.; De Weerdt, M.M.; Witteveen, C.

2007-01-01

We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe

EEG Eye State Identification Using Incremental Attribute Learning with Time-Series Classification

Directory of Open Access Journals (Sweden)

Ting Wang

2014-01-01

Full Text Available Eye state identification is a kind of common time-series classification problem which is also a hot spot in recent research. Electroencephalography (EEG is widely used in eye state classification to detect human's cognition state. Previous research has validated the feasibility of machine learning and statistical approaches for EEG eye state classification. This paper aims to propose a novel approach for EEG eye state identification using incremental attribute learning (IAL based on neural networks. IAL is a novel machine learning strategy which gradually imports and trains features one by one. Previous studies have verified that such an approach is applicable for solving a number of pattern recognition problems. However, in these previous works, little research on IAL focused on its application to time-series problems. Therefore, it is still unknown whether IAL can be employed to cope with time-series problems like EEG eye state classification. Experimental results in this study demonstrates that, with proper feature extraction and feature ordering, IAL can not only efficiently cope with time-series classification problems, but also exhibit better classification performance in terms of classification error rates in comparison with conventional and some other approaches.

De toekomst van Real Time Intelligence

NARCIS (Netherlands)

Broek, J. van den; Berg, C.H. van den

2013-01-01

Al direct vanaf de start van de Nationale Politie is gewerkt aan het opzetten van tien real-time intelligence centra in Nederland. Van daaruit worden 24 uur per dag en zeven dagen in de week agenten op straat actief ondersteund met real-time informatie bij de melding waar ze op af gaan. In de visie

Real-Time Parameter Identification

Data.gov (United States)

National Aeronautics and Space Administration — Armstrong researchers have implemented in the control room a technique for estimating in real time the aerodynamic parameters that describe the stability and control...

Real time process algebra with time-dependent conditions

NARCIS (Netherlands)

Baeten, J.C.M.; Middelburg, C.A.

We extend the main real time version of ACP presented in [6] with conditionals in which the condition depends on time. This extension facilitates flexible dependence of proccess behaviour on initialization time. We show that the conditions concerned generalize the conditions introduced earlier

Compiling models into real-time systems

International Nuclear Information System (INIS)

Dormoy, J.L.; Cherriaux, F.; Ancelin, J.

1992-08-01

This paper presents an architecture for building real-time systems from models, and model-compiling techniques. This has been applied for building a real-time model-based monitoring system for nuclear plants, called KSE, which is currently being used in two plants in France. We describe how we used various artificial intelligence techniques for building it: a model-based approach, a logical model of its operation, a declarative implementation of these models, and original knowledge-compiling techniques for automatically generating the real-time expert system from those models. Some of those techniques have just been borrowed from the literature, but we had to modify or invent other techniques which simply did not exist. We also discuss two important problems, which are often underestimated in the artificial intelligence literature: size, and errors. Our architecture, which could be used in other applications, combines the advantages of the model-based approach with the efficiency requirements of real-time applications, while in general model-based approaches present serious drawbacks on this point

Compiling models into real-time systems

International Nuclear Information System (INIS)

Dormoy, J.L.; Cherriaux, F.; Ancelin, J.

1992-08-01

This paper presents an architecture for building real-time systems from models, and model-compiling techniques. This has been applied for building a real-time model-base monitoring system for nuclear plants, called KSE, which is currently being used in two plants in France. We describe how we used various artificial intelligence techniques for building it: a model-based approach, a logical model of its operation, a declarative implementation of these models, and original knowledge-compiling techniques for automatically generating the real-time expert system from those models. Some of those techniques have just been borrowed from the literature, but we had to modify or invent other techniques which simply did not exist. We also discuss two important problems, which are often underestimated in the artificial intelligence literature: size, and errors. Our architecture, which could be used in other applications, combines the advantages of the model-based approach with the efficiency requirements of real-time applications, while in general model-based approaches present serious drawbacks on this point

Revisiting Bragg's X-ray microscope: Scatter based optical transient grating detection of pulsed ionising radiation

International Nuclear Information System (INIS)

Fullagar, Wilfred K.; Paganin, David M.; Hall, Chris J.

2011-01-01

Transient optical gratings for detecting ultrafast signals are routine for temporally resolved photochemical investigations. Many processes can contribute to the formation of such gratings; we indicate use of optically scattering centres that can be formed with highly variable latencies in different materials and devices using ionising radiation. Coherent light scattered by these centres can form the short-wavelength-to-optical-wavelength, incoherent-to-coherent basis of a Bragg X-ray microscope, with inherent scope for optical phasing. Depending on the dynamics of the medium chosen, the way is open to both ultrafast pulsed and integrating measurements. For experiments employing brief pulses, we discuss high-dynamic-range short-wavelength diffraction measurements with real-time optical reconstructions. Applications to optical real-time X-ray phase-retrieval are considered. -- Research highlights: → It is timely that the concept of Bragg's X-ray microscope be revisited. → Transient gratings can be used for X-ray all-optical information processing. → Applications to optical real-time X-ray phase-retrieval are considered.

Real Time Linux - The RTOS for Astronomy?

Science.gov (United States)

Daly, P. N.

The BoF was attended by about 30 participants and a free CD of real time Linux-based upon RedHat 5.2-was available. There was a detailed presentation on the nature of real time Linux and the variants for hard real time: New Mexico Tech's RTL and DIAPM's RTAI. Comparison tables between standard Linux and real time Linux responses to time interval generation and interrupt response latency were presented (see elsewhere in these proceedings). The present recommendations are to use RTL for UP machines running the 2.0.x kernels and RTAI for SMP machines running the 2.2.x kernel. Support, both academically and commercially, is available. Some known limitations were presented and the solutions reported e.g., debugging and hardware support. The features of RTAI (scheduler, fifos, shared memory, semaphores, message queues and RPCs) were described. Typical performance statistics were presented: Pentium-based oneshot tasks running > 30kHz, 486-based oneshot tasks running at ~ 10 kHz, periodic timer tasks running in excess of 90 kHz with average zero jitter peaking to ~ 13 mus (UP) and ~ 30 mus (SMP). Some detail on kernel module programming, including coding examples, were presented showing a typical data acquisition system generating simulated (random) data writing to a shared memory buffer and a fifo buffer to communicate between real time Linux and user space. All coding examples were complete and tested under RTAI v0.6 and the 2.2.12 kernel. Finally, arguments were raised in support of real time Linux: it's open source, free under GPL, enables rapid prototyping, has good support and the ability to have a fully functioning workstation capable of co-existing hard real time performance. The counter weight-the negatives-of lack of platforms (x86 and PowerPC only at present), lack of board support, promiscuous root access and the danger of ignorance of real time programming issues were also discussed. See ftp://orion.tuc.noao.edu/pub/pnd/rtlbof.tgz for the StarOffice overheads

Simulating transient dynamics of the time-dependent time fractional Fokker-Planck systems

Science.gov (United States)

Kang, Yan-Mei

2016-09-01

For a physically realistic type of time-dependent time fractional Fokker-Planck (FP) equation, derived as the continuous limit of the continuous time random walk with time-modulated Boltzmann jumping weight, a semi-analytic iteration scheme based on the truncated (generalized) Fourier series is presented to simulate the resultant transient dynamics when the external time modulation is a piece-wise constant signal. At first, the iteration scheme is demonstrated with a simple time-dependent time fractional FP equation on finite interval with two absorbing boundaries, and then it is generalized to the more general time-dependent Smoluchowski-type time fractional Fokker-Planck equation. The numerical examples verify the efficiency and accuracy of the iteration method, and some novel dynamical phenomena including polarized motion orientations and periodic response death are discussed.

The real-time price elasticity of electricity

International Nuclear Information System (INIS)

Lijesen, Mark G.

2007-01-01

The real-time price elasticity of electricity contains important information on the demand response of consumers to the volatility of peak prices. Despite the importance, empirical estimates of the real-time elasticity are hardly available. This paper provides a quantification of the real-time relationship between total peak demand and spot market prices. We find a low value for the real-time price elasticity, which may partly be explained from the fact that not all users observe the spot market price. If we correct for this phenomenon, we find the elasticity to be fairly low for consumers currently active in the spot market. If this conclusion applies to all users, this would imply a limited scope for government intervention in supply security issues. (Author)

A Programmable Microkernel for Real-Time Systems

Science.gov (United States)

2003-06-01

A Programmable Microkernel for Real - Time Systems Christoph M. Kirsch Thomas A. Henzinger Marco A.A. Sanvido Report No. UCB/CSD-3-1250 June 2003...TITLE AND SUBTITLE A Programmable Microkernel for Real - Time Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 A Programmable Microkernel for Real - Time Systems ∗ Christoph M

Sow-activity classification from acceleration patterns

DEFF Research Database (Denmark)

Escalante, Hugo Jair; Rodriguez, Sara V.; Cordero, Jorge

2013-01-01

sow-activity classification can be approached with standard machine learning methods for pattern classification. Individual predictions for elements of times series of arbitrary length are combined to classify it as a whole. An extensive comparison of representative learning algorithms, including......This paper describes a supervised learning approach to sow-activity classification from accelerometer measurements. In the proposed methodology, pairs of accelerometer measurements and activity types are considered as labeled instances of a usual supervised classification task. Under this scenario...... neural networks, support vector machines, and ensemble methods, is presented. Experimental results are reported using a data set for sow-activity classification collected in a real production herd. The data set, which has been widely used in related works, includes measurements from active (Feeding...

Transient thermal camouflage and heat signature control

Science.gov (United States)

Yang, Tian-Zhi; Su, Yishu; Xu, Weikai; Yang, Xiao-Dong

2016-09-01

Thermal metamaterials have been proposed to manipulate heat flux as a new way to cloak or camouflage objects in the infrared world. To date, however, thermal metamaterials only operate in the steady-state and exhibit detectable, transient heat signatures. In this letter, the theoretical basis for a thermal camouflaging technique with controlled transient diffusion is presented. This technique renders an object invisible in real time. More importantly, the thermal camouflaging device instantaneously generates a pre-designed heat signature and behaves as a perfect thermal illusion device. A metamaterial coating with homogeneous and isotropic thermal conductivity, density, and volumetric heat capacity was fabricated and very good camouflaging performance was achieved.

Real-time object-oriented programming: studies and proposals

International Nuclear Information System (INIS)

Fouquier, Gilles

1996-01-01

This thesis contributes to the introduction of real-time features in object-oriented programming. Object-oriented programming favours modularity and reusability. Therefore, its application to real-time introduces many theoretical and conceptual problems. To deal with these problems, a new real-time object-oriented programming model is presented. This model is based on the active object model which allows concurrence and maintains the encapsulation property. The real-time aspect is treated by replacing the concept of task by the concept of method processing and by associating a real-time constraint to each message (priority or deadline). The set of all the running methods is scheduled. This model, called ATOME, contains several sub-models to deal with the usual concurrence control integrating their priority and deadline processing. The classical HPF and EDF scheduling avoid priority or deadline inversion. This model and its variants are new proposals to program real-time applications in the object-oriented way, therefore easing reusability and code writing. The feasibility of this approach is demonstrated by extending and existing active object-based language to real-time, in using the rules defined in the ATOME model. (author) [fr

Real-time simulation of large-scale floods

Science.gov (United States)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

Data Mining and Machine Learning in Time-Domain Discovery and Classification

Science.gov (United States)

Bloom, Joshua S.; Richards, Joseph W.

2012-03-01

-domain aspect of the data and the objects of interest presents some unique challenges. First, any collection, storage, transport, and computational framework for processing the streaming data must be able to keep up with the dataflow. This is not necessarily true, for instance, with static sky science, where metrics of interest can be computed off-line and on a timescale much longer than the time required to obtain the data. Second, many types of transient (one-off) events evolve quickly in time and require more observations to fully understand the nature of the events. This demands that time-changing events are quickly discovered, classified, and broadcast to other follow-up facilities. All of this must happen robustly with, in some cases, very limited data. Last, the process of discovery and classification must be calibrated to the available resources for computation and follow-up. That is, the precision of classification must be weighed against the computational cost of producing that level of precision. Likewise, the cost of being wrong about the classification of some sorts of sources must be balanced against the scientific gains about being right about the classification of other types of sources. Quantifying these trade-offs, especially in the presence of a limited amount of follow-up resources (such as the availability of larger telescope observations) is not straightforward and inheres domain-specific imperatives that will, in general, differ from astronomer to astronomer. This chapter presents an overview of the current directions in ML and data-mining techniques in the context of time-domain astronomy. Ultimately the goal - if not just the necessity given the data rates and the diversity of questions to be answered - is to abstract the traditional role of astronomer in the entire scientific process. In some sense, this takes us full circle from the pre modern view of the scientific pursuit presented in Vermeer's "The Astronomer" (Figure 6.2): in broad daylight, he

Mechatronic modeling of real-time wheel-rail contact

CERN Document Server

Bosso, Nicola; Gugliotta, Antonio; Somà, Aurelio

2013-01-01

Real-time simulations of the behaviour of a rail vehicle require realistic solutions of the wheel-rail contact problem which can work in a real-time mode. Examples of such solutions for the online mode have been well known and are implemented within standard and commercial tools for the simulation codes for rail vehicle dynamics. This book is the result of the research activities carried out by the Railway Technology Lab of the Department of Mechanical and Aerospace Engineering at Politecnico di Torino. This book presents work on the project for the development of a real-time wheel-rail contact model and provides the simulation results obtained with dSpace real-time hardware. Besides this, the implementation of the contact model for the development of a real-time model for the complex mechatronic system of a scaled test rig is presented in this book and may be useful for the further validation of the real-time contact model with experiments on a full scale test rig.

Tradeoff analysis for Dependable Real-Time Embedded Systems during the Early Design Phases

DEFF Research Database (Denmark)

Gan, Junhe

Embedded systems are becoming increasingly complex and have tight competing constraints in terms of performance, cost, energy consumption, dependability, flexibility, security, etc. The objective of this thesis is to propose design methods and tools for supporting the tradeoff analysis of competing...... to processing elements, as well as the processor voltage and frequency levels for executing each task, such that transient faults are tolerated, the real-time constraints of the application are satisfied, and the energy consumed is minimized. In this thesis, we target the early design phases, when decisions...... have a high impact on the subsequent implementation choices. However, due to a lack of information, the early design phases are characterized by uncertainties, e.g., in the worst-case execution times (WCETs), in the functionality requirements, or in the hardware component costs. In this context, we...

Internet-accessible real-time weather information system

Digital Repository Service at National Institute of Oceanography (India)

Desai, R.G.P.; Joseph, A.; Desa, E.; Mehra, P.; Desa, E.; Gouveia, A.D.

An internet-accessible real-time weather information system has been developed. This system provides real-time accessibility to weather information from a multitude of spatially distributed weather stations. The Internet connectivity also offers...

An Empirical Overview of the No Free Lunch Theorem and Its Effect on Real-World Machine Learning Classification.

Science.gov (United States)

Gómez, David; Rojas, Alfonso

2016-01-01

A sizable amount of research has been done to improve the mechanisms for knowledge extraction such as machine learning classification or regression. Quite unintuitively, the no free lunch (NFL) theorem states that all optimization problem strategies perform equally well when averaged over all possible problems. This fact seems to clash with the effort put forth toward better algorithms. This letter explores empirically the effect of the NFL theorem on some popular machine learning classification techniques over real-world data sets.

Automated real-time software development

Science.gov (United States)

Jones, Denise R.; Walker, Carrie K.; Turkovich, John J.

1993-01-01

A Computer-Aided Software Engineering (CASE) system has been developed at the Charles Stark Draper Laboratory (CSDL) under the direction of the NASA Langley Research Center. The CSDL CASE tool provides an automated method of generating source code and hard copy documentation from functional application engineering specifications. The goal is to significantly reduce the cost of developing and maintaining real-time scientific and engineering software while increasing system reliability. This paper describes CSDL CASE and discusses demonstrations that used the tool to automatically generate real-time application code.

Geomagnetic Observatory Data for Real-Time Applications

Science.gov (United States)

Love, J. J.; Finn, C. A.; Rigler, E. J.; Kelbert, A.; Bedrosian, P.

2015-12-01

The global network of magnetic observatories represents a unique collective asset for the scientific community. Historically, magnetic observatories have supported global magnetic-field mapping projects and fundamental research of the Earth's interior and surrounding space environment. More recently, real-time data streams from magnetic observatories have become an important contributor to multi-sensor, operational monitoring of evolving space weather conditions, especially during magnetic storms. In this context, the U.S. Geological Survey (1) provides real-time observatory data to allied space weather monitoring projects, including those of NOAA, the U.S. Air Force, NASA, several international agencies, and private industry, (2) collaborates with Schlumberger to provide real-time geomagnetic data needed for directional drilling for oil and gas in Alaska, (3) develops products for real-time evaluation of hazards for the electric-power grid industry that are associated with the storm-time induction of geoelectric fields in the Earth's conducting lithosphere. In order to implement strategic priorities established by the USGS Natural Hazards Mission Area and the National Science and Technology Council, and with a focus on developing new real-time products, the USGS is (1) leveraging data management protocols already developed by the USGS Earthquake Program, (2) developing algorithms for mapping geomagnetic activity, a collaboration with NASA and NOAA, (3) supporting magnetotelluric surveys and developing Earth conductivity models, a collaboration with Oregon State University and the NSF's EarthScope Program, (4) studying the use of geomagnetic activity maps and Earth conductivity models for real-time estimation of geoelectric fields, (5) initiating geoelectric monitoring at several observatories, (6) validating real-time estimation algorithms against historical geomagnetic and geoelectric data. The success of these long-term projects is subject to funding constraints

Real-time earthquake data feasible

Science.gov (United States)

Bush, Susan

Scientists agree that early warning devices and monitoring of both Hurricane Hugo and the Mt. Pinatubo volcanic eruption saved thousands of lives. What would it take to develop this sort of early warning and monitoring system for earthquake activity?Not all that much, claims a panel assigned to study the feasibility, costs, and technology needed to establish a real-time earthquake monitoring (RTEM) system. The panel, drafted by the National Academy of Science's Committee on Seismology, has presented its findings in Real-Time Earthquake Monitoring. The recently released report states that “present technology is entirely capable of recording and processing data so as to provide real-time information, enabling people to mitigate somewhat the earthquake disaster.” RTEM systems would consist of two parts—an early warning system that would give a few seconds warning before severe shaking, and immediate postquake information within minutes of the quake that would give actual measurements of the magnitude. At this time, however, this type of warning system has not been addressed at the national level for the United States and is not included in the National Earthquake Hazard Reduction Program, according to the report.

Transferability and robustness of real-time freeway crash risk assessment.

Science.gov (United States)

Shew, Cameron; Pande, Anurag; Nuworsoo, Cornelius

2013-09-01

This study examines the data from single loop detectors on northbound (NB) US-101 in San Jose, California to estimate real-time crash risk assessment models. The classification tree and neural network based crash risk assessment models developed with data from NB US-101 are applied to data from the same freeway, as well as to the data from nearby segments of the SB US-101, NB I-880, and SB I-880 corridors. The performance of crash risk assessment models on these nearby segments is the focus of this research. The model applications show that it is in fact possible to use the same model for multiple freeways, as the underlying relationships between traffic data and crash risk remain similar. The framework provided here may be helpful to authorities for freeway segments with newly installed traffic surveillance apparatuses, since the real-time crash risk assessment models from nearby freeways with existing infrastructure would be able to provide a reasonable estimate of crash risk. The robustness of the model output is also assessed by location, time of day, and day of week. The analysis shows that on some locations the models may require further learning due to higher than expected false positive (e.g., the I-680/I-280 interchange on US-101 NB) or false negative rates. The approach for post-processing the results from the model provides ideas to refine the model prior to or during the implementation. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Development of sustainable performance indicators to assess the benefits of real-time monitoring in mechanised underground mining

OpenAIRE

Govindan, Rajesh; Cao, Wenzhuo; Korre, Anna; Durucan, Sevket; Graham, Peter; Simon, Clara; Barlow, Glenn; Pemberton, Ross

2018-01-01

This paper presents the development and quantification of a catalogue of Sustainable Performance Indicators (SPIs) for the assessment of the benefits real-time mining can offer in small and complex mechanised underground mining operations. The SPIs investigated in detail include: ‒ grade accuracy and error of the resource model, ‒ high/low grade ore classification accuracy and error, ‒ additional high grade ore identified per unit volume, ‒ profit expected per unit volume, ‒ or...

Verifying real-time systems against scenario-based requirements

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Li, Shuhao; Nielsen, Brian

2009-01-01

We propose an approach to automatic verification of real-time systems against scenario-based requirements. A real-time system is modeled as a network of Timed Automata (TA), and a scenario-based requirement is specified as a Live Sequence Chart (LSC). We define a trace-based semantics for a kernel...... subset of the LSC language. By equivalently translating an LSC chart into an observer TA and then non-intrusively composing this observer with the original system model, the problem of verifying a real-time system against a scenario-based requirement reduces to a classical real-time model checking...

Real-time UNIX in HEP data acquisition

International Nuclear Information System (INIS)

Buono, S.; Gaponenko, I.; Jones, R.; Mapelli, L.; Mornacchi, G.; Prigent, D.; Sanchez-Corral, E.; Skiadelli, M.; Toppers, A.; Duval, P.Y.; Ferrato, D.; Le Van Suu, A.; Qian, Z.; Rondot, C.; Ambrosini, G.; Fumagalli, G.; Aguer, M.; Huet, M.

1994-01-01

Today's experimentation in high energy physics is characterized by an increasing need for sensitivity to rare phenomena and complex physics signatures, which require the use of huge and sophisticated detectors and consequently a high performance readout and data acquisition. Multi-level triggering, hierarchical data collection and an always increasing amount of processing power, distributed throughout the data acquisition layers, will impose a number of features on the software environment, especially the need for a high level of standardization. Real-time UNIX seems, today, the best solution for the platform independence, operating system interface standards and real-time features necessary for data acquisition in HEP experiments. We present the results of the evaluation, in a realistic application environment, of a Real-Time UNIX operating system: the EP/LX real-time UNIX system. ((orig.))

Temporal Specification and Verification of Real-Time Systems.

Science.gov (United States)

1991-08-30

of concrete real - time systems can be modeled adequately. Specification: We present two conservative extensions of temporal logic that allow for the...logic. We present both model-checking algorithms for the automatic verification of finite-state real - time systems and proof methods for the deductive verification of real - time systems .

ClockWork: a Real-Time Feasibility Analysis Tool

NARCIS (Netherlands)

Jansen, P.G.; Hanssen, F.T.Y.; Mullender, Sape J.

ClockWork shows that we can improve the flexibility and efficiency of real-time kernels. We do this by proposing methods for scheduling based on so-called Real-Time Transactions. ClockWork uses Real-Time Transactions which allow scheduling decisions to be taken by the system. A programmer does not

Exploring transient X-ray sky with Einstein Probe

Science.gov (United States)

Yuan, W.; Zhang, C.; Ling, Z.; Zhao, D.; Chen, Y.; Lu, F.; Zhang, S.

2017-10-01

The Einstein Probe is a small satellite in time-domain astronomy to monitor the soft X-ray sky. It is a small mission in the space science programme of the Chinese Academy of Sciences. It will carry out systematic survey and characterisation of high-energy transients at unprecedented sensitivity, spatial resolution, Grasp and monitoring cadence. Its wide-field imaging capability is achieved by using established technology of micro-pore lobster-eye X-ray focusing optics. Complementary to this is X-ray follow-up capability enabled by a narrow-field X-ray telescope. It is capable of on-board triggering and real time downlink of transient alerts, in order to trigger fast follow-up observations at multi-wavelengths. Its scientific goals are concerned with discovering and characterising diverse types of X-ray transients, including tidal disruption events, supernova shock breakouts, high-redshift GRBs, and of particular interest, X-ray counterparts of gravitational wave events.

Failure analysis of real-time systems

International Nuclear Information System (INIS)

Jalashgar, A.; Stoelen, K.

1998-01-01

This paper highlights essential aspects of real-time software systems that are strongly related to the failures and their course of propagation. The significant influence of means-oriented and goal-oriented system views in the description, understanding and analysing of those aspects is elaborated. The importance of performing failure analysis prior to reliability analysis of real-time systems is equally addressed. Problems of software reliability growth models taking the properties of such systems into account are discussed. Finally, the paper presents a preliminary study of a goal-oriented approach to model the static and dynamic characteristics of real-time systems, so that the corresponding analysis can be based on a more descriptive and informative picture of failures, their effects and the possibility of their occurrence. (author)

Can Real-Time Data Also Be Climate Quality?

Science.gov (United States)

Brewer, M.; Wentz, F. J.

2015-12-01

GMI, AMSR-2 and WindSat herald a new era of highly accurate and timely microwave data products. Traditionally, there has been a large divide between real-time and re-analysis data products. What if these completely separate processing systems could be merged? Through advanced modeling and physically based algorithms, Remote Sensing Systems (RSS) has narrowed the gap between real-time and research-quality. Satellite microwave ocean products have proven useful for a wide array of timely Earth science applications. Through cloud SST capabilities have enormously benefited tropical cyclone forecasting and day to day fisheries management, to name a few. Oceanic wind vectors enhance operational safety of shipping and recreational boating. Atmospheric rivers are of import to many human endeavors, as are cloud cover and knowledge of precipitation events. Some activities benefit from both climate and real-time operational data used in conjunction. RSS has been consistently improving microwave Earth Science Data Records (ESDRs) for several decades, while making near real-time data publicly available for semi-operational use. These data streams have often been produced in 2 stages: near real-time, followed by research quality final files. Over the years, we have seen this time delay shrink from months or weeks to mere hours. As well, we have seen the quality of near real-time data improve to the point where the distinction starts to blur. We continue to work towards better and faster RFI filtering, adaptive algorithms and improved real-time validation statistics for earlier detection of problems. Can it be possible to produce climate quality data in real-time, and what would the advantages be? We will try to answer these questions…

Academic Training: Real Time Process Control - Lecture series

CERN Multimedia

Françoise Benz

2004-01-01

ACADEMIC TRAINING LECTURE REGULAR PROGRAMME 7, 8 and 9 June From 11:00 hrs to 12:00 hrs - Main Auditorium bldg. 500 Real Time Process Control T. Riesco / CERN-TS What exactly is meant by Real-time? There are several definitions of real-time, most of them contradictory. Unfortunately the topic is controversial, and there does not seem to be 100% agreement over the terminology. Real-time applications are becoming increasingly important in our daily lives and can be found in diverse environments such as the automatic braking system on an automobile, a lottery ticket system, or robotic environmental samplers on a space station. These lectures will introduce concepts and theory like basic concepts timing constraints, task scheduling, periodic server mechanisms, hard and soft real-time.ENSEIGNEMENT ACADEMIQUE ACADEMIC TRAINING Françoise Benz 73127 academic.training@cern.ch

Real-time estimation of small-area populations with human biomarkers in sewage

Energy Technology Data Exchange (ETDEWEB)

Daughton, Christian G., E-mail: daughton.christian@epa.gov

2012-01-01

A new approach is conceptualized for measuring small-area human populations by using biomarkers in sewage. The basis for the concept (SCIM: Sewage Chemical-Information Mining) is supported by a comprehensive examination and synthesis of data published across several disciplines, including medicine, microbiology, clinical chemistry, and environmental science. Accurate measures of human populations are fundamental to numerous disciplines, including economics, marketing, politics, sociology, public health and safety (e.g., disease management; assessment of natural hazards; disaster prevention and response), quality of life, and the environment. Knowing the size, distribution, and flow of a small-area (local) population facilitates understanding the numerous and complex linkages and interactions between humans and the environment. Examples include material-flow (substance-flow) analysis, determining the magnitude of per capita contribution of pollutant loadings to watersheds, or forecasting future impacts of local populations on the environment or a population's demands on resources. While no definitive approach exists for measuring small-area populations, census-taking is a long-established convention. No approach exists, however, for gauging small-area populations in real-time, as none is able to capture population dynamics, which involve transient changes (e.g., daily influx and efflux) and lasting changes (e.g., births, deaths, change in residence). Accurate measurement of small-area populations in real time has never been possible but is essential for facilitating the design of more sustainable communities. Real-time measurement would provide communities the capability of testing what-if scenarios in design and policy decisions. After evaluation of a range of biomarkers (including the nitrogenous waste product creatinine, which has been long used in clinical chemistry as a parameter to normalize the concentrations of other urinary excretion products to

Detection of Histoplasma capsulatum from clinical specimens by cycling probe-based real-time PCR and nested real-time PCR.

Science.gov (United States)

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. © The Author 2015. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Reviewing real-time performance of nuclear reactor safety systems

International Nuclear Information System (INIS)

Preckshot, G.G.

1993-08-01

The purpose of this paper is to recommend regulatory guidance for reviewers examining real-time performance of computer-based safety systems used in nuclear power plants. Three areas of guidance are covered in this report. The first area covers how to determine if, when, and what prototypes should be required of developers to make a convincing demonstration that specific problems have been solved or that performance goals have been met. The second area has recommendations for timing analyses that will prove that the real-time system will meet its safety-imposed deadlines. The third area has description of means for assessing expected or actual real-time performance before, during, and after development is completed. To ensure that the delivered real-time software product meets performance goals, the paper recommends certain types of code-execution and communications scheduling. Technical background is provided in the appendix on methods of timing analysis, scheduling real-time computations, prototyping, real-time software development approaches, modeling and measurement, and real-time operating systems

Reviewing real-time performance of nuclear reactor safety systems

Energy Technology Data Exchange (ETDEWEB)

Preckshot, G.G. [Lawrence Livermore National Lab., CA (United States)

1993-08-01

The purpose of this paper is to recommend regulatory guidance for reviewers examining real-time performance of computer-based safety systems used in nuclear power plants. Three areas of guidance are covered in this report. The first area covers how to determine if, when, and what prototypes should be required of developers to make a convincing demonstration that specific problems have been solved or that performance goals have been met. The second area has recommendations for timing analyses that will prove that the real-time system will meet its safety-imposed deadlines. The third area has description of means for assessing expected or actual real-time performance before, during, and after development is completed. To ensure that the delivered real-time software product meets performance goals, the paper recommends certain types of code-execution and communications scheduling. Technical background is provided in the appendix on methods of timing analysis, scheduling real-time computations, prototyping, real-time software development approaches, modeling and measurement, and real-time operating systems.

Real-Time Video Convolutional Face Finder on Embedded Platforms

Directory of Open Access Journals (Sweden)

Mamalet Franck

2007-01-01

Full Text Available A high-level optimization methodology is applied for implementing the well-known convolutional face finder (CFF algorithm for real-time applications on mobile phones, such as teleconferencing, advanced user interfaces, image indexing, and security access control. CFF is based on a feature extraction and classification technique which consists of a pipeline of convolutions and subsampling operations. The design of embedded systems requires a good trade-off between performance and code size due to the limited amount of available resources. The followed methodology copes with the main drawbacks of the original implementation of CFF such as floating-point computation and memory allocation, in order to allow parallelism exploitation and perform algorithm optimizations. Experimental results show that our embedded face detection system can accurately locate faces with less computational load and memory cost. It runs on a 275 MHz Starcore DSP at 35 QCIF images/s with state-of-the-art detection rates and very low false alarm rates.

Real-Time Video Convolutional Face Finder on Embedded Platforms

Directory of Open Access Journals (Sweden)

Franck Mamalet

2007-03-01

Full Text Available A high-level optimization methodology is applied for implementing the well-known convolutional face finder (CFF algorithm for real-time applications on mobile phones, such as teleconferencing, advanced user interfaces, image indexing, and security access control. CFF is based on a feature extraction and classification technique which consists of a pipeline of convolutions and subsampling operations. The design of embedded systems requires a good trade-off between performance and code size due to the limited amount of available resources. The followed methodology copes with the main drawbacks of the original implementation of CFF such as floating-point computation and memory allocation, in order to allow parallelism exploitation and perform algorithm optimizations. Experimental results show that our embedded face detection system can accurately locate faces with less computational load and memory cost. It runs on a 275 MHz Starcore DSP at 35 QCIF images/s with state-of-the-art detection rates and very low false alarm rates.

Virtual timers in hierarchical real-time systems

NARCIS (Netherlands)

Heuvel, van den M.M.H.P.; Holenderski, M.J.; Cools, W.A.; Bril, R.J.; Lukkien, J.J.; Zhu, D.

2009-01-01

Hierarchical scheduling frameworks (HSFs) provide means for composing complex real-time systems from welldefined subsystems. This paper describes an approach to provide hierarchically scheduled real-time applications with virtual event timers, motivated by the need for integrating priority

Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

Science.gov (United States)

Majumdar, Alok K.; Ravindran, S. S.

2017-01-01

Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

Science.gov (United States)

Fachrurrozi, Muhammad; Saparudin; Erwin

2017-04-01

Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments

Directory of Open Access Journals (Sweden)

Gannot Sharon

2003-01-01

Full Text Available We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs. The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptively updated online, based on hypothesis test results. The noise canceller is updated only during stationary noise frames, and the ATF identification is carried out only when desired source components have been detected. The hypothesis testing is based on the nonstationarity of the signals and the transient power ratio between the beamformer primary output and its reference noise signals. Following the beamforming and the hypothesis testing, estimates for the signal presence probability and for the noise power spectral density are derived. Subsequently, an optimal spectral gain function that minimizes the mean square error of the log-spectral amplitude (LSA is applied. Experimental results demonstrate the usefulness of the proposed system in nonstationary noise environments.

Real-time video compressing under DSP/BIOS

Science.gov (United States)

Chen, Qiu-ping; Li, Gui-ju

2009-10-01

This paper presents real-time MPEG-4 Simple Profile video compressing based on the DSP processor. The programming framework of video compressing is constructed using TMS320C6416 Microprocessor, TDS510 simulator and PC. It uses embedded real-time operating system DSP/BIOS and the API functions to build periodic function, tasks and interruptions etcs. Realize real-time video compressing. To the questions of data transferring among the system. Based on the architecture of the C64x DSP, utilized double buffer switched and EDMA data transfer controller to transit data from external memory to internal, and realize data transition and processing at the same time; the architecture level optimizations are used to improve software pipeline. The system used DSP/BIOS to realize multi-thread scheduling. The whole system realizes high speed transition of a great deal of data. Experimental results show the encoder can realize real-time encoding of 768*576, 25 frame/s video images.

Real-time ISEE data system

Science.gov (United States)

Tsurutani, B. T.; Baker, D. N.

1979-01-01

A real-time ISEE data system directed toward predicting geomagnetic substorms and storms is discussed. Such a system may allow up to 60+ minutes advance warning of magnetospheric substorms and up to 30 minute warnings of geomagnetic storms (and other disturbances) induced by high-speed streams and solar flares. The proposed system utilizes existing capabilities of several agencies (NASA, NOAA, USAF), and thereby minimizes costs. This same concept may be applicable to data from other spacecraft, and other NASA centers; thus, each individual experimenter can receive quick-look data in real time at his or her base institution.

The stretch to stray on time: Resonant length of random walks in a transient

Science.gov (United States)

Falcke, Martin; Friedhoff, Victor Nicolai

2018-05-01

First-passage times in random walks have a vast number of diverse applications in physics, chemistry, biology, and finance. In general, environmental conditions for a stochastic process are not constant on the time scale of the average first-passage time or control might be applied to reduce noise. We investigate moments of the first-passage time distribution under an exponential transient describing relaxation of environmental conditions. We solve the Laplace-transformed (generalized) master equation analytically using a novel method that is applicable to general state schemes. The first-passage time from one end to the other of a linear chain of states is our application for the solutions. The dependence of its average on the relaxation rate obeys a power law for slow transients. The exponent ν depends on the chain length N like ν = - N / ( N + 1 ) to leading order. Slow transients substantially reduce the noise of first-passage times expressed as the coefficient of variation (CV), even if the average first-passage time is much longer than the transient. The CV has a pronounced minimum for some lengths, which we call resonant lengths. These results also suggest a simple and efficient noise control strategy and are closely related to the timing of repetitive excitations, coherence resonance, and information transmission by noisy excitable systems. A resonant number of steps from the inhibited state to the excitation threshold and slow recovery from negative feedback provide optimal timing noise reduction and information transmission.

Real-time dynamics of RNA Polymerase II clustering in live human cells

Science.gov (United States)

Cisse, Ibrahim

2014-03-01

Transcription is the first step in the central dogma of molecular biology, when genetic information encoded on DNA is made into messenger RNA. How this fundamental process occurs within living cells (in vivo) is poorly understood,[1] despite extensive biochemical characterizations with isolated biomolecules (in vitro). For high-order organisms, like humans, transcription is reported to be spatially compartmentalized in nuclear foci consisting of clusters of RNA Polymerase II, the enzyme responsible for synthesizing all messenger RNAs. However, little is known of when these foci assemble or their relative stability. We developed an approach based on photo-activation localization microscopy (PALM) combined with a temporal correlation analysis, which we refer to as tcPALM. The tcPALM method enables the real-time characterization of biomolecular spatiotemporal organization, with single-molecule sensitivity, directly in living cells.[2] Using tcPALM, we observed that RNA Polymerase II clusters form transiently, with an average lifetime of 5.1 (+/- 0.4) seconds. Stimuli affecting transcription regulation yielded orders of magnitude changes in the dynamics of the polymerase clusters, implying that clustering is regulated and plays a role in the cells ability to effect rapid response to external signals. Our results suggest that the transient crowding of enzymes may aid in rate-limiting steps of genome regulation.

Real-time image processing for label-free enrichment of Actinobacteria cultivated in picolitre droplets.

Science.gov (United States)

Zang, Emerson; Brandes, Susanne; Tovar, Miguel; Martin, Karin; Mech, Franziska; Horbert, Peter; Henkel, Thomas; Figge, Marc Thilo; Roth, Martin

2013-09-21

The majority of today's antimicrobial therapeutics is derived from secondary metabolites produced by Actinobacteria. While it is generally assumed that less than 1% of Actinobacteria species from soil habitats have been cultivated so far, classic screening approaches fail to supply new substances, often due to limited throughput and frequent rediscovery of already known strains. To overcome these restrictions, we implement high-throughput cultivation of soil-derived Actinobacteria in microfluidic pL-droplets by generating more than 600,000 pure cultures per hour from a spore suspension that can subsequently be incubated for days to weeks. Moreover, we introduce triggered imaging with real-time image-based droplet classification as a novel universal method for pL-droplet sorting. Growth-dependent droplet sorting at frequencies above 100 Hz is performed for label-free enrichment and extraction of microcultures. The combination of both cultivation of Actinobacteria in pL-droplets and real-time detection of growing Actinobacteria has great potential in screening for yet unknown species as well as their undiscovered natural products.

Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

Science.gov (United States)

Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

2014-09-30

This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

Science.gov (United States)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

Real-time Java simulations of multiple interference dielectric filters

Science.gov (United States)

Kireev, Alexandre N.; Martin, Olivier J. F.

2008-12-01

An interactive Java applet for real-time simulation and visualization of the transmittance properties of multiple interference dielectric filters is presented. The most commonly used interference filters as well as the state-of-the-art ones are embedded in this platform-independent applet which can serve research and education purposes. The Transmittance applet can be freely downloaded from the site http://cpc.cs.qub.ac.uk. Program summaryProgram title: Transmittance Catalogue identifier: AEBQ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBQ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5778 No. of bytes in distributed program, including test data, etc.: 90 474 Distribution format: tar.gz Programming language: Java Computer: Developed on PC-Pentium platform Operating system: Any Java-enabled OS. Applet was tested on Windows ME, XP, Sun Solaris, Mac OS RAM: Variable Classification: 18 Nature of problem: Sophisticated wavelength selective multiple interference filters can include some tens or even hundreds of dielectric layers. The spectral response of such a stack is not obvious. On the other hand, there is a strong demand from application designers and students to get a quick insight into the properties of a given filter. Solution method: A Java applet was developed for the computation and the visualization of the transmittance of multilayer interference filters. It is simple to use and the embedded filter library can serve educational purposes. Also, its ability to handle complex structures will be appreciated as a useful research and development tool. Running time: Real-time simulations

Experimental Study of Real-Time Classification of 17 Voluntary Movements for Multi-Degree Myoelectric Prosthetic Hand

Directory of Open Access Journals (Sweden)

Trongmun Jiralerspong

2017-11-01

Full Text Available The myoelectric prosthetic hand is a powerful tool developed to help people with upper limb loss restore the functions of a biological hand. Recognizing multiple hand motions from only a few electromyography (EMG sensors is one of the requirements for the development of prosthetic hands with high level of usability. This task is highly challenging because both classification rate and misclassification rate worsen with additional hand motions. This paper presents a signal processing technique that uses spectral features and an artificial neural network to classify 17 voluntary movements from EMG signals. The main highlight will be on the use of a small set of low-cost EMG sensor for classification of a reasonably large number of hand movements. The aim of this work is to extend the capabilities to recognize and produce multiple movements beyond what is currently feasible. This work will also show and discuss about how tailoring the number of hand motions for a specific task can help develop a more reliable prosthetic hand system. Online classification experiments have been conducted on seven male and five female participants to evaluate the validity of the proposed method. The proposed algorithm achieves an overall correct classification rate of up to 83%, thus, demonstrating the potential to classify 17 movements from 6 EMG sensors. Furthermore, classifying 9 motions using this method could achieve an accuracy of up to 92%. These results show that if the prosthetic hand is intended for a specific task, limiting the number of motions can significantly increase the performance and usability.

A Process For Performance Evaluation Of Real-Time Systems

Directory of Open Access Journals (Sweden)

Andrew J. Kornecki

2003-12-01

Full Text Available Real-time developers and engineers must not only meet the system functional requirements, but also the stringent timing requirements. One of the critical decisions leading to meeting these timing requirements is the selection of an operating system under which the software will be developed and run. Although there is ample documentation on real-time systems performance and evaluation, little can be found that combines such information into an efficient process for use by developers. As the software industry moves towards clearly defined processes, creation of appropriate guidelines describing a process for performance evaluation of real-time system would greatly benefit real-time developers. This technology transition research focuses on developing such a process. PROPERT (PROcess for Performance Evaluation of Real Time systems - the process described in this paper - is based upon established techniques for evaluating real-time systems. It organizes already existing real-time performance criteria and assessment techniques in a manner consistent with a well-formed process, based on the Personal Software Process concepts.

Quantitative (real-time) PCR

International Nuclear Information System (INIS)

Denman, S.E.; McSweeney, C.S.

2005-01-01

Many nucleic acid-based probe and PCR assays have been developed for the detection tracking of specific microbes within the rumen ecosystem. Conventional PCR assays detect PCR products at the end stage of each PCR reaction, where exponential amplification is no longer being achieved. This approach can result in different end product (amplicon) quantities being generated. In contrast, using quantitative, or real-time PCR, quantification of the amplicon is performed not at the end of the reaction, but rather during exponential amplification, where theoretically each cycle will result in a doubling of product being created. For real-time PCR, the cycle at which fluorescence is deemed to be detectable above the background during the exponential phase is termed the cycle threshold (Ct). The Ct values obtained are then used for quantitation, which will be discussed later

Potential barrier classification by short-time measurement

International Nuclear Information System (INIS)

Granot, Er'el; Marchewka, Avi

2006-01-01

We investigate the short-time dynamics of a delta-function potential barrier on an initially confined wave packet. There are mainly two conclusions: (A) At short times the probability density of the first particles that passed through the barrier is unaffected by it. (B) When the barrier is absorptive (i.e., its potential is imaginary) it affects the transmitted wave function at shorter times than a real potential barrier. Therefore, it is possible to distinguish between an imaginary and a real potential barrier by measuring its effect at short times only on the transmitting wave function

Potential barrier classification by short-time measurement

Science.gov (United States)

Granot, Er'El; Marchewka, Avi

2006-03-01

We investigate the short-time dynamics of a delta-function potential barrier on an initially confined wave packet. There are mainly two conclusions: (A) At short times the probability density of the first particles that passed through the barrier is unaffected by it. (B) When the barrier is absorptive (i.e., its potential is imaginary) it affects the transmitted wave function at shorter times than a real potential barrier. Therefore, it is possible to distinguish between an imaginary and a real potential barrier by measuring its effect at short times only on the transmitting wave function.

Real-time holographic endoscopy

Science.gov (United States)

Smigielski, Paul; Albe, Felix; Dischli, Bernard

1992-08-01

Some new experiments concerning holographic endoscopy are presented. The quantitative measurements of deformations of objects are obtained by the double-exposure and double- reference beam method, using either a cw-laser or a pulsed laser. Qualitative experiments using an argon laser with time-average holographic endoscopy are also presented. A video film on real-time endoscopic holographic interferometry was recorded with the help of a frequency-doubled YAG-laser working at 25 Hz for the first time.

Measurement and analysis of workload effects on fault latency in real-time systems

Science.gov (United States)

Woodbury, Michael H.; Shin, Kang G.

1990-01-01

The authors demonstrate the need to address fault latency in highly reliable real-time control computer systems. It is noted that the effectiveness of all known recovery mechanisms is greatly reduced in the presence of multiple latent faults. The presence of multiple latent faults increases the possibility of multiple errors, which could result in coverage failure. The authors present experimental evidence indicating that the duration of fault latency is dependent on workload. A synthetic workload generator is used to vary the workload, and a hardware fault injector is applied to inject transient faults of varying durations. This method makes it possible to derive the distribution of fault latency duration. Experimental results obtained from the fault-tolerant multiprocessor at the NASA Airlab are presented and discussed.

A Permanent Automated Real-Time Passive Acoustic Monitoring System for Bottlenose Dolphin Conservation in the Mediterranean Sea.

Directory of Open Access Journals (Sweden)

Marco Brunoldi

Full Text Available Within the framework of the EU Life+ project named LIFE09 NAT/IT/000190 ARION, a permanent automated real-time passive acoustic monitoring system for the improvement of the conservation status of the transient and resident population of bottlenose dolphin (Tursiops truncatus has been implemented and installed in the Portofino Marine Protected Area (MPA, Ligurian Sea. The system is able to detect the simultaneous presence of dolphins and boats in the area and to give their position in real time. This information is used to prevent collisions by diffusing warning messages to all the categories involved (tourists, professional fishermen and so on. The system consists of two gps-synchronized acoustic units, based on a particular type of marine buoy (elastic beacon, deployed about 1 km off the Portofino headland. Each one is equipped with a four-hydrophone array and an onboard acquisition system which can record the typical social communication whistles emitted by the dolphins and the sound emitted by boat engines. Signals are pre-filtered, digitized and then broadcast to the ground station via wi-fi. The raw data are elaborated to get the direction of the acoustic target to each unit, and hence the position of dolphins and boats in real time by triangulation.

Real-time computational photon-counting LiDAR

Science.gov (United States)

Edgar, Matthew; Johnson, Steven; Phillips, David; Padgett, Miles

2018-03-01

The availability of compact, low-cost, and high-speed MEMS-based spatial light modulators has generated widespread interest in alternative sampling strategies for imaging systems utilizing single-pixel detectors. The development of compressed sensing schemes for real-time computational imaging may have promising commercial applications for high-performance detectors, where the availability of focal plane arrays is expensive or otherwise limited. We discuss the research and development of a prototype light detection and ranging (LiDAR) system via direct time of flight, which utilizes a single high-sensitivity photon-counting detector and fast-timing electronics to recover millimeter accuracy three-dimensional images in real time. The development of low-cost real time computational LiDAR systems could have importance for applications in security, defense, and autonomous vehicles.

Investigating the impact of in-vehicle transients on diesel soot emissions

Directory of Open Access Journals (Sweden)

Filipi Zoran

2008-01-01

Full Text Available This paper describes development of a test cell setup for concurrent running of a real engine and a simulation of the vehicle system, and its use for investigating highly-dynamic engine-in-vehicle operation and its effect on diesel engine emissions. Running an engine in the test cell under conditions experienced in the vehicle enables acquiring detailed insight into dynamic interactions between power train sub-systems, and the impact of it on fuel consumption and transient emissions. This type of data may otherwise be difficult and extremely costly to obtain from a vehicle prototype test. In particular, engine system response during critical transients and the effect of transient excursions on emissions are investigated using advanced, fast-response test instrumentation and emissions analyzers. Main enablers of the work include the highly dynamic AC electric dynamometer with the accompanying computerized control system and the computationally efficient simulation of the driveline/vehicle system. The latter is developed through systematic energy-based proper modeling that tailors the virtual model to capture critical powertrain transients while running in real time. Coupling the real engine with the virtual driveline/vehicle offers a chance to easily modify vehicle parameters, and even study different power train configurations. In particular, the paper describes the engine-in-the-loop study of a V-8, 6l engine coupled to a virtual 4´4 off road vehicle. This engine is considered as a high-performance option for this truck and the real prototype of the complete vehicle does not exist yet. The results shed light on critical transients in a conventional powertrain and their effect on NOx and soot emissions. Measurements demonstrate very large spikes of particulate concentration at the initiation of vehicle acceleration events. Characterization of transients and their effect on particulate emission provides a basis for devising engine-level or

Tightly coupled transient analysis of EBR-II

International Nuclear Information System (INIS)

Makowitz, H.; Lehto, W.K.; Sackett, J.I.

1988-01-01

A Tightly Coupled transient analysis system for the Experimental Breeder Reactor-II (EBR-II) is currently being tested. The system consists of a faster than real time high fidelity reactor simulation, advanced graphics displays, expert system coupling, and real time data coupling via the EBR-II data acquisition system to and from the plant and the control system. The base, first generation software has been developed and is presently being tested. Various subsystem couplings and the total system integration are being checked out. This system should enhance the diagnostic and prognostic capability of EBR-II in the near term and provide automatic control during startup and power maneuvering in the future, as well as serve as a testbed for new control system development for advanced reactors

Cluster Computing For Real Time Seismic Array Analysis.

Science.gov (United States)

Martini, M.; Giudicepietro, F.

A seismic array is an instrument composed by a dense distribution of seismic sen- sors that allow to measure the directional properties of the wavefield (slowness or wavenumber vector) radiated by a seismic source. Over the last years arrays have been widely used in different fields of seismological researches. In particular they are applied in the investigation of seismic sources on volcanoes where they can be suc- cessfully used for studying the volcanic microtremor and long period events which are critical for getting information on the volcanic systems evolution. For this reason arrays could be usefully employed for the volcanoes monitoring, however the huge amount of data produced by this type of instruments and the processing techniques which are quite time consuming limited their potentiality for this application. In order to favor a direct application of arrays techniques to continuous volcano monitoring we designed and built a small PC cluster able to near real time computing the kinematics properties of the wavefield (slowness or wavenumber vector) produced by local seis- mic source. The cluster is composed of 8 Intel Pentium-III bi-processors PC working at 550 MHz, and has 4 Gigabytes of RAM memory. It runs under Linux operating system. The developed analysis software package is based on the Multiple SIgnal Classification (MUSIC) algorithm and is written in Fortran. The message-passing part is based upon the LAM programming environment package, an open-source imple- mentation of the Message Passing Interface (MPI). The developed software system includes modules devote to receiving date by internet and graphical applications for the continuous displaying of the processing results. The system has been tested with a data set collected during a seismic experiment conducted on Etna in 1999 when two dense seismic arrays have been deployed on the northeast and the southeast flanks of this volcano. A real time continuous acquisition system has been simulated by

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Kun-Ching Wang

2015-01-01

Full Text Available The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI. In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII. The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

Real-time PCR systems targeting giant viruses of amoebae and their virophages.

Science.gov (United States)

Ngounga, Tatsiana; Pagnier, Isabelle; Reteno, Dorine-Gaelle Ikanga; Raoult, Didier; La Scola, Bernard; Colson, Philippe

2013-01-01

Giant viruses that infect amoebae, including mimiviruses and marseilleviruses, were first described in 2003. Virophages were subsequently described that infect mimiviruses. Culture isolation with Acanthamoeba spp. and metagenomic studies have shown that these giant viruses are common inhabitants of our biosphere and have enabled the recent detection of these viruses in human samples. However, the genomes of these viruses display substantial genetic diversity, making it a challenge to examine their presence in environmental and clinical samples using conventional and real-time PCR. We designed and evaluated the performance of PCR systems capable of detecting all currently isolated mimiviruses, marseilleviruses and virophages to assess their prevalence in various samples. Our real-time PCR assays accurately detected all or most of the members of the currently delineated lineages of giant viruses infecting acanthamoebae as well as the mimivirus virophages, and enabled accurate classification of the mimiviruses of amoebae in lineages A, B or C. We were able to detect four new mimiviruses directly from environmental samples and correctly classified these viruses within mimivirus lineage C. This was subsequently confirmed by culture on amoebae followed by partial Sanger sequencing. PCR systems such as those implemented here may contribute to an improved understanding of the prevalence of mimiviruses, their virophages and marseilleviruses in humans.

Real time magnetic resonance guided endomyocardial local delivery

Science.gov (United States)

Corti, R; Badimon, J; Mizsei, G; Macaluso, F; Lee, M; Licato, P; Viles-Gonzalez, J F; Fuster, V; Sherman, W

2005-01-01

Objective: To investigate the feasibility of targeting various areas of left ventricle myocardium under real time magnetic resonance (MR) imaging with a customised injection catheter equipped with a miniaturised coil. Design: A needle injection catheter with a mounted resonant solenoid circuit (coil) at its tip was designed and constructed. A 1.5 T MR scanner with customised real time sequence combined with in-room scan running capabilities was used. With this system, various myocardial areas within the left ventricle were targeted and injected with a gadolinium-diethylenetriaminepentaacetic acid (DTPA) and Indian ink mixture. Results: Real time sequencing at 10 frames/s allowed clear visualisation of the moving catheter and its transit through the aorta into the ventricle, as well as targeting of all ventricle wall segments without further image enhancement techniques. All injections were visualised by real time MR imaging and verified by gross pathology. Conclusion: The tracking device allowed real time in vivo visualisation of catheters in the aorta and left ventricle as well as precise targeting of myocardial areas. The use of this real time catheter tracking may enable precise and adequate delivery of agents for tissue regeneration. PMID:15710717

Transient space-time surface waves characterization using Gabor analysis

Energy Technology Data Exchange (ETDEWEB)

Martinez, L; Wilkie-Chancellier, N; Caplain, E [Universite de Cergy Pontoise, ENS Cachan, UMR CNRS 8029, Laboratoire Systemes et Applications des Techniques de l' Information et de l' Energie (SATIE), 5 mail Gay-Lussac, F 9500 Cergy-Pontoise (France); Glorieux, C; Sarens, B, E-mail: nicolas.wilkie-chancellier@u-cergy.f [Katholieke Universiteit Leuven, Laboratorium voor Akoestiek en Thermische Fysica (LATF), Celestijnenlaan 200D, B-3001 Leuven (Belgium)

2009-11-01

Laser ultrasonics allow the observation of transient surface waves along their propagation media and their interaction with encountered objects like cracks, holes, borders. In order to characterize and localize these transient aspects in the Space-Time-Wave number-Frequency domains, the 1D, 2D and 3D Gabor transforms are presented. The Gabor transform enables the identification of several properties of the local wavefronts such as their shape, wavelength, frequency, attenuation, group velocity and the full conversion sequence along propagation. The ability of local properties identification by Gabor transform is illustrated by two experimental studies: Lamb waves generated by an annular source on a circular quartz and Lamb wave interaction with a fluid droplet. In both cases, results obtained with Gabor transform enable ones to identify the observed local waves.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

Science.gov (United States)

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prototyping Real-Time Control in the SPS

CERN Document Server

Andersson, J; Jensen, L; Jones, R; Lamont, M; Wenninger, J; Wijnands, Thijs; CERN. Geneva. AB Department

2003-01-01

Real-time control of beam related parameters will be required in the LHC. In order to gain experience of the issues involved in implementing distributed real-time control over large distances, a prototype local orbit feedback system is being developed in the SPS. This will use 6 pickups, each equipped with the full LHC acquisition electronics chain and linked to a real-time communication and feedback system. This reports summarises the .rst tests performed with this system in October 2002, where the data from four pickups was successfully acquired and displayed at 10 Hz in the control room.

Formal methods for dependable real-time systems

Science.gov (United States)

Rushby, John

1993-01-01

The motivation for using formal methods to specify and reason about real time properties is outlined and approaches that were proposed and used are sketched. The formal verifications of clock synchronization algorithms are concluded as showing that mechanically supported reasoning about complex real time behavior is feasible. However, there was significant increase in the effectiveness of verification systems since those verifications were performed, at it is to be expected that verifications of comparable difficulty will become fairly routine. The current challenge lies in developing perspicuous and economical approaches to the formalization and specification of real time properties.

Real time detecting system for turning force

Energy Technology Data Exchange (ETDEWEB)

Xiaobin, Yue [China Academy of Engineering Physics, Mianyang (China). Inst. of Machinery Manufacturing Technology

2001-07-01

How to get the real-time value of forces dropped on the tool in the course of processing by piezoelectric sensors is introduced. First, the analog signals of the cutting force were achieved by these sensors, amplified and transferred into digital signals by A/D transferring card. Then real-time software reads the information, put it into its own coordinate, drew the curve of forces, displayed it on the screen by the real time and saved it for the technicians to analyze the situation of the tool. So the cutting parameter can be optimized to improve surface quality of the pieces.

Real Time Grid Reliability Management 2005

Energy Technology Data Exchange (ETDEWEB)

Eto, Joe; Eto, Joe; Lesieutre, Bernard; Lewis, Nancy Jo; Parashar, Manu

2008-07-07

The increased need to manage California?s electricity grid in real time is a result of the ongoing transition from a system operated by vertically-integrated utilities serving native loads to one operated by an independent system operator supporting competitive energy markets. During this transition period, the traditional approach to reliability management -- construction of new transmission lines -- has not been pursued due to unresolved issues related to the financing and recovery of transmission project costs. In the absence of investments in new transmission infrastructure, the best strategy for managing reliability is to equip system operators with better real-time information about actual operating margins so that they can better understand and manage the risk of operating closer to the edge. A companion strategy is to address known deficiencies in offline modeling tools that are needed to ground the use of improved real-time tools. This project: (1) developed and conducted first-ever demonstrations of two prototype real-time software tools for voltage security assessment and phasor monitoring; and (2) prepared a scoping study on improving load and generator response models. Additional funding through two separate subsequent work authorizations has already been provided to build upon the work initiated in this project.

Real-time systems scheduling 2 focuses

CERN Document Server

Chetto, Maryline

2014-01-01

Real-time systems are used in a wide range of applications, including control, sensing, multimedia, etc. Scheduling is a central problem for these computing/communication systems since it is responsible for software execution in a timely manner. This book, the second of two volumes on the subject, brings together knowledge on specific topics and discusses the recent advances for some of them.  It addresses foundations as well as the latest advances and findings in real-time scheduling, giving comprehensive references to important papers, but the chapters are short and not overloaded with co

Real-time Avatar Animation from a Single Image.

Science.gov (United States)

Saragih, Jason M; Lucey, Simon; Cohn, Jeffrey F

2011-01-01

A real time facial puppetry system is presented. Compared with existing systems, the proposed method requires no special hardware, runs in real time (23 frames-per-second), and requires only a single image of the avatar and user. The user's facial expression is captured through a real-time 3D non-rigid tracking system. Expression transfer is achieved by combining a generic expression model with synthetically generated examples that better capture person specific characteristics. Performance of the system is evaluated on avatars of real people as well as masks and cartoon characters.

Do Magnetic Fields drive high-energy explosive transients?

OpenAIRE

Mundell, Carole

2017-01-01

I will review the current state-of-the-art in real-time, rapid response optical imaging and polarimetric followup of transient sources such as Gamma Ray Bursts. I will interpret current results within the context of the external shock model and present predictions for future mm- and cm-wave radio observatories. Recent observational results from new radio pilot studies will also be presented.

Do Magnetic Fields Drive High-Energy Explosive Transients?

Science.gov (United States)

Mundell, Carole

2017-10-01

I will review the current state-of-the-art in real-time, rapid response optical imaging and polarimetric followup of transient sources such as Gamma Ray Bursts. I will interpret current results within the context of the external shock model and present predictions for future mm- and cm-wave radio observatories. Recent observational results from new radio pilot studies will also be presented.

An Analysis of Input/Output Paradigms for Real-Time Systems

Science.gov (United States)

1990-07-01

timing and concurrency aspects of real - time systems . This paper illustrates how to build a mathematical model of the schedulability of a real-time...various design alternatives. The primary characteristic that distinguishes real-time system from non- real - time systems is the importance of time. The

Location and Classification of Moving Fruits in Real Time with a Single Color Camera Localización y Clasificación de Frutas Móviles en Tiempo Real con una Cámara Individual a Color

Directory of Open Access Journals (Sweden)

José F Reyes

2009-06-01

Full Text Available Quality control of fruits to satisfy increasingly competitive food markets requires the implementation of automatic servovisual systems in fruit processing operations to cope with market challenges. A new and fast method for identifying and classifying moving fruits by processing single color images from a static camera in real time was developed and tested. Two algorithms were combined to classify and track moving fruits on image plane using representative color features. The method allows classifying the fruit by color segmentation and estimating its position on the image plane, which provides a reliable algorithm to be implemented in robotic manipulation of fruits. To evaluate the methodology an experimental real time system simulating a conveyor belt and real fruit was used. Testing of the system indicates that with natural lighting conditions and proper calibration of the system a minimum error of 2% in classification of fruits is feasible. The methodology allows for very simple implementation, and although operational results are promising, even higher accuracy may be possible if structured illumination is used.El control de calidad en frutas y hortalizas para satisfacer mercados cada vez mas exigentes, requiere la implementación de sistemas automáticos servo visuales en operaciones de de procesamiento de frutas para responder a estos desafíos de mercado. En está trabajo se desarrollo y evaluó un nuevo método para identificar y clasificar frutas en movimiento mediante el procesamiento en tiempo real imágenes a color capturadas por una cámara individual estática. Se combinaron dos algoritmos para clasificar y rastrear frutas en movimiento en el plano de imagen utilizando aspectos representativos de color. El método permite clasificar las frutas en base a segmentación de color y estimar su posición en el plano de imagen, lo cual proporciona un algoritmo confiable para ser implementado en un brazo robótico.de manipulación de

Spying on real-time computers to improve performance

International Nuclear Information System (INIS)

Taff, L.M.

1975-01-01

The sampled program-counter histogram, an established technique for shortening the execution times of programs, is described for a real-time computer. The use of a real-time clock allows particularly easy implementation. (Auth.)

PERTS: A Prototyping Environment for Real-Time Systems

Science.gov (United States)

Liu, Jane W. S.; Lin, Kwei-Jay; Liu, C. L.

1993-01-01

PERTS is a prototyping environment for real-time systems. It is being built incrementally and will contain basic building blocks of operating systems for time-critical applications, tools, and performance models for the analysis, evaluation and measurement of real-time systems and a simulation/emulation environment. It is designed to support the use and evaluation of new design approaches, experimentations with alternative system building blocks, and the analysis and performance profiling of prototype real-time systems.

Real-time multiple image manipulations

International Nuclear Information System (INIS)

Arenson, J.S.; Shalev, S.; Legris, J.; Goertzen, Y.

1984-01-01

There are many situations in which it is desired to manipulate two or more images under real-time operator control. The authors have investigated a number of such cases in order to determine their value and applicability in clinical medicine and laboratory research. Several examples are presented in detail. The DICOM-8 video image computer system was used due to its capability of storing two 512 x 512 x 8 bit images and operating on them, and/or an incoming video frame, with any of a number of real time operations including addition, subtraction, inversion, averaging, logical AND, NAND, OR, NOR, NOT, XOR and XNOR, as well as combinations of these. Some applications involve manipulations of or among the stored images. In others, a stored image is used as a mask or template for positioning or adjusting a second image to be grabbed via a video camera. The accuracy of radiotherapy treatment is verified by comparing port films with the original radiographic planning film, which is previously digitized and stored. Moving the port film on the light box while viewing the real-time subtraction image allows for adjustments of zoom, translation and rotation, together with contrast and edge enhancement

Real-time position reconstruction with hippocampal place cells.

Science.gov (United States)

Guger, Christoph; Gener, Thomas; Pennartz, Cyriel M A; Brotons-Mas, Jorge R; Edlinger, Günter; Bermúdez I Badia, S; Verschure, Paul; Schaffelhofer, Stefan; Sanchez-Vives, Maria V

2011-01-01

Brain-computer interfaces (BCI) are using the electroencephalogram, the electrocorticogram and trains of action potentials as inputs to analyze brain activity for communication purposes and/or the control of external devices. Thus far it is not known whether a BCI system can be developed that utilizes the states of brain structures that are situated well below the cortical surface, such as the hippocampus. In order to address this question we used the activity of hippocampal place cells (PCs) to predict the position of an rodent in real-time. First, spike activity was recorded from the hippocampus during foraging and analyzed off-line to optimize the spike sorting and position reconstruction algorithm of rats. Then the spike activity was recorded and analyzed in real-time. The rat was running in a box of 80 cm × 80 cm and its locomotor movement was captured with a video tracking system. Data were acquired to calculate the rat's trajectories and to identify place fields. Then a Bayesian classifier was trained to predict the position of the rat given its neural activity. This information was used in subsequent trials to predict the rat's position in real-time. The real-time experiments were successfully performed and yielded an error between 12.2 and 17.4% using 5-6 neurons. It must be noted here that the encoding step was done with data recorded before the real-time experiment and comparable accuracies between off-line (mean error of 15.9% for three rats) and real-time experiments (mean error of 14.7%) were achieved. The experiment shows proof of principle that position reconstruction can be done in real-time, that PCs were stable and spike sorting was robust enough to generalize from the training run to the real-time reconstruction phase of the experiment. Real-time reconstruction may be used for a variety of purposes, including creating behavioral-neuronal feedback loops or for implementing neuroprosthetic control.

The IPERMOB System for Effective Real-Time Road Travel Time Measurement and Prediction

OpenAIRE

Martelli, Francesca; Renda, Maria Elena; Santi, Paolo

2010-01-01

Accurate, real-time measurement and estimation of road travel time is considered a central problem in the design of advanced Intelligent Transportation Systems. In particular, whether eective, real-time collection of travel time measurements in a urban area is possible is, to the best of our knowledge, still an open problem. In this paper, we introduce the IPERMOB system for efficient, real-time collection of travel time measurements in urban areas through vehicular networks. We demonstrate t...

Games and Scenarios for Real-Time System Validation

DEFF Research Database (Denmark)

Li, Shuhao

This thesis presents research on the validation of real-time embedded software systems in the context of model-based development. The thesis proposes scenario-based and game-theoretic approaches to system analysis, verification, synthesis and testing to address the challenges that arise from....... By linking our prototype translators with existing model checker Uppaal and game solver Uppaal-Tiga, we show that these methods contribute to the interaction correctness and timeliness of early system designs. The thesis also shows that testing a real-time reactive system can be viewed as playing a timed...... communicating real-time systems can be modeled and specified with LSC. By translating LSC to timed automata (TAs), we reduce scenario-based model consistency checking and property verification to CTL real-time model checking problems, and reduce scenario-based synthesis to a timed game solving problem...

Real time refractive index measurement by ESPI

International Nuclear Information System (INIS)

Torroba, R.; Joenathan, C.

1991-01-01

In this paper a method to measure refractive index variations in real time is reported. A technique to introduce reference fringes in real time is discussed. Both the theoretical and experimental results are presented and an example with phase shifting is given. (author). 8 refs, 5 figs

The Synthesis of Intelligent Real-Time Systems

Science.gov (United States)

1990-11-09

Synthesis of Intelligent Real - Time Systems . The purpose of the effort was to develop and extend theories and techniques that facilitate the design and...implementation of intelligent real - time systems . In particular, Teleos has extended situated-automata theory to apply to situations in which the system has

Real-time software for the COMPASS tokamak plasma control

International Nuclear Information System (INIS)

Valcarcel, D.F.; Duarte, A.S.; Neto, A.; Carvalho, I.S.; Carvalho, B.B.; Fernandes, H.; Sousa, J.; Sartori, F.; Janky, F.; Cahyna, P.; Hron, M.; Panek, R.

2010-01-01

The COMPASS tokamak has started its operation recently in Prague and to meet the necessary operation parameters its real-time system, for data processing and control, must be designed for both flexibility and performance, allowing the easy integration of code from several developers and to guarantee the desired time cycle. For this purpose an Advanced Telecommunications Computing Architecture based real-time system has been deployed with a solution built on a multi-core x86 processor. It makes use of two software components: the BaseLib2 and the MARTe (Multithreaded Application Real-Time executor) real-time frameworks. The BaseLib2 framework is a generic real-time library with optimized objects for the implementation of real-time algorithms. This allowed to build a library of modules that process the acquired data and execute control algorithms. MARTe executes these modules in kernel space Real-Time Application Interface allowing to attain the required cycle time and a jitter of less than 1.5 μs. MARTe configuration and data storage are accomplished through a Java hardware client that connects to the FireSignal control and data acquisition software. This article details the implementation of the real-time system for the COMPASS tokamak, in particular the organization of the control code, the design and implementation of the communications with the actuators and how MARTe integrates with the FireSignal software.

Real-time software for the COMPASS tokamak plasma control

Energy Technology Data Exchange (ETDEWEB)

Valcarcel, D.F., E-mail: danielv@ipfn.ist.utl.p [Associacao EURATOM/IST, Instituto de Plasmas e Fusao Nuclear - Laboratorio Associado, Instituto Superior Tecnico, P-1049-001 Lisboa (Portugal); Duarte, A.S.; Neto, A.; Carvalho, I.S.; Carvalho, B.B.; Fernandes, H.; Sousa, J. [Associacao EURATOM/IST, Instituto de Plasmas e Fusao Nuclear - Laboratorio Associado, Instituto Superior Tecnico, P-1049-001 Lisboa (Portugal); Sartori, F. [Euratom-UKAEA, Culham Science Centre, Abingdon, OX14 3DB Oxon (United Kingdom); Janky, F.; Cahyna, P.; Hron, M.; Panek, R. [Institute of Plasma Physics AS CR, v.v.i., Association EURATOM/IPP.CR, Za Slovankou 3, 182 00 Prague (Czech Republic)

2010-07-15

The COMPASS tokamak has started its operation recently in Prague and to meet the necessary operation parameters its real-time system, for data processing and control, must be designed for both flexibility and performance, allowing the easy integration of code from several developers and to guarantee the desired time cycle. For this purpose an Advanced Telecommunications Computing Architecture based real-time system has been deployed with a solution built on a multi-core x86 processor. It makes use of two software components: the BaseLib2 and the MARTe (Multithreaded Application Real-Time executor) real-time frameworks. The BaseLib2 framework is a generic real-time library with optimized objects for the implementation of real-time algorithms. This allowed to build a library of modules that process the acquired data and execute control algorithms. MARTe executes these modules in kernel space Real-Time Application Interface allowing to attain the required cycle time and a jitter of less than 1.5 {mu}s. MARTe configuration and data storage are accomplished through a Java hardware client that connects to the FireSignal control and data acquisition software. This article details the implementation of the real-time system for the COMPASS tokamak, in particular the organization of the control code, the design and implementation of the communications with the actuators and how MARTe integrates with the FireSignal software.

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov (United States)

-Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution developing a system-theoretic distribution network management framework that unifies real-time voltage and Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next

Real time psychrometric data collection

International Nuclear Information System (INIS)

McDaniel, K.H.

1996-01-01

Eight Mine Weather Stations (MWS) installed at the Waste Isolation Pilot Plant (WIPP) to monitor the underground ventilation system are helping to simulate real-time ventilation scenarios. Seasonal weather extremes can result in variations of Natural Ventilation Pressure (NVP) which can significantly effect the ventilation system. The eight MWS(s) (which previously collected and stored temperature, barometric pressure and relative humidity data for subsequent NVP calculations) were upgraded to provide continuous real-time data to the site wide Central monitoring System. This data can now be utilized by the ventilation engineer to create realtime ventilation simulations and trends which assist in the prediction and mitigation of NVP and psychrometric related events

Acquisition of a Multi-Domain Advanced Real-Time Simulator to Support DoD-focused Interdisciplinary Research at CSUB

Science.gov (United States)