Real-Time Head Pose Estimation on Mobile Platforms
Directory of Open Access Journals (Sweden)
Jianfeng Ren
2010-06-01
Full Text Available Many computer vision applications such as augmented reality require head pose estimation. As far as the real-time implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to satisfy real-time constraints while maintaining reasonable head pose estimation accuracy. The introduced head pose estimation approach in this paper is an attempt to meet this objective. The approach consists of the following components: Viola-Jones face detection, color-based face tracking using an online calibration procedure, and head pose estimation using Hu moment features and Fisher linear discriminant. Experimental results running on an actual mobile device are reported exhibiting both the real- time and accuracy aspects of the developed approach.
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
Tsunami Amplitude Estimation from Real-Time GNSS.
Jeffries, C.; MacInnes, B. T.; Melbourne, T. I.
2017-12-01
Tsunami early warning systems currently comprise modeling of observations from the global seismic network, deep-ocean DART buoys, and a global distribution of tide gauges. While these tools work well for tsunamis traveling teleseismic distances, saturation of seismic magnitude estimation in the near field can result in significant underestimation of tsunami excitation for local warning. Moreover, DART buoy and tide gauge observations cannot be used to rectify the underestimation in the available time, typically 10-20 minutes, before local runup occurs. Real-time GNSS measurements of coseismic offsets may be used to estimate finite faulting within 1-2 minutes and, in turn, tsunami excitation for local warning purposes. We describe here a tsunami amplitude estimation algorithm; implemented for the Cascadia subduction zone, that uses continuous GNSS position streams to estimate finite faulting. The system is based on a time-domain convolution of fault slip that uses a pre-computed catalog of hydrodynamic Green's functions generated with the GeoClaw shallow-water wave simulation software and maps seismic slip along each section of the fault to points located off the Cascadia coast in 20m of water depth and relies on the principle of the linearity in tsunami wave propagation. The system draws continuous slip estimates from a message broker, convolves the slip with appropriate Green's functions which are then superimposed to produce wave amplitude at each coastal location. The maximum amplitude and its arrival time are then passed into a database for subsequent monitoring and display. We plan on testing this system using a suite of synthetic earthquakes calculated for Cascadia whose ground motions are simulated at 500 existing Cascadia GPS sites, as well as real earthquakes for which we have continuous GNSS time series and surveyed runup heights, including Maule, Chile 2010 and Tohoku, Japan 2011. This system has been implemented in the CWU Geodesy Lab for the Cascadia
Real-time gaze estimation via pupil center tracking
Directory of Open Access Journals (Sweden)
Cazzato Dario
2018-02-01
Full Text Available Automatic gaze estimation not based on commercial and expensive eye tracking hardware solutions can enable several applications in the fields of human computer interaction (HCI and human behavior analysis. It is therefore not surprising that several related techniques and methods have been investigated in recent years. However, very few camera-based systems proposed in the literature are both real-time and robust. In this work, we propose a real-time user-calibration-free gaze estimation system that does not need person-dependent calibration, can deal with illumination changes and head pose variations, and can work with a wide range of distances from the camera. Our solution is based on a 3-D appearance-based method that processes the images from a built-in laptop camera. Real-time performance is obtained by combining head pose information with geometrical eye features to train a machine learning algorithm. Our method has been validated on a data set of images of users in natural environments, and shows promising results. The possibility of a real-time implementation, combined with the good quality of gaze tracking, make this system suitable for various HCI applications.
RealCalc : a real time Java calculation tool. Application to HVSR estimation
Hloupis, G.; Vallianatos, F.
2009-04-01
Java computation platform is not a newcomer in the seismology field. It is mainly used for applications regarding collecting, requesting, spreading and visualizing seismological data because it is productive, safe and has low maintenance costs. Although it has very attractive characteristics for the engineers, Java didn't used frequently in real time applications where prediction and reliability required as a reaction to real world events. The main reasons for this are the absence of priority support (such as priority ceiling or priority inversion) and the use of an automated memory management (called garbage collector). To overcome these problems a number of extensions have been proposed with the Real Time Specification for Java (RTSJ) being the most promising and used one. In the current study we used the RTSJ to build an application that receives data continuously and provides estimations in real time. The application consists of four main modules: incoming data, preprocessing, estimation and publication. As an application example we present real time HVSR estimation. Microtremors recordings are collected continuously from the incoming data module. The preprocessing module consists of a window selector tool based on wavelets which is applied on the incoming data stream in order derive the most stationary parts. The estimation module provides all the necessary calculations according to user specifications. Finally the publication module except the results presentation it also calculates attributes and relevant statistics for each site (temporal variations, HVSR stability). Acknowledgements This work is partially supported by the Greek General Secretariat of Research and Technology in the frame of Crete Regional Project 2000- 2006 (M1.2): "TALOS: An integrated system of seismic hazard monitoring and management in the front of the Hellenic Arc", CRETE PEP7 (KP_7).
Aircraft Fault Detection Using Real-Time Frequency Response Estimation
Grauer, Jared A.
2016-01-01
A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.
An Embedded Device for Real-Time Noninvasive Intracranial Pressure Estimation.
Matthews, Jonathan M; Fanelli, Andrea; Heldt, Thomas
2018-01-01
The monitoring of intracranial pressure (ICP) is indicated for diagnosing and guiding therapy in many neurological conditions. Current monitoring methods, however, are highly invasive, limiting their use to the most critically ill patients only. Our goal is to develop and test an embedded device that performs all necessary mathematical operations in real-time for noninvasive ICP (nICP) estimation based on a previously developed model-based approach that uses cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP) waveforms. The nICP estimation algorithm along with the required preprocessing steps were implemented on an NXP LPC4337 microcontroller unit (MCU). A prototype device using the MCU was also developed, complete with display, recording functionality, and peripheral interfaces for ABP and CBFV monitoring hardware. The device produces an estimate of mean ICP once per minute and performs the necessary computations in 410 ms, on average. Real-time nICP estimates differed from the original batch-mode MATLAB implementation of theestimation algorithm by 0.63 mmHg (root-mean-square error). We have demonstrated that real-time nICP estimation is possible on a microprocessor platform, which offers the advantages of low cost, small size, and product modularity over a general-purpose computer. These attributes take a step toward the goal of real-time nICP estimation at the patient's bedside in a variety of clinical settings.
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...
Seasonal adjustment methods and real time trend-cycle estimation
Bee Dagum, Estela
2016-01-01
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportat...
Soft sensor for real-time cement fineness estimation.
Stanišić, Darko; Jorgovanović, Nikola; Popov, Nikola; Čongradac, Velimir
2015-03-01
This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Ab initio quantum-enhanced optical phase estimation using real-time feedback control
DEFF Research Database (Denmark)
Berni, Adriano; Gehring, Tobias; Nielsen, Bo Melholt
2015-01-01
of a quantum-enhanced and fully deterministic ab initio phase estimation protocol based on real-time feedback control. Using robust squeezed states of light combined with a real-time Bayesian adaptive estimation algorithm, we demonstrate deterministic phase estimation with a precision beyond the quantum shot...... noise limit. The demonstrated protocol opens up new opportunities for quantum microscopy, quantum metrology and quantum information processing....
Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery.
Rottmann, Joerg; Keall, Paul; Berbeco, Ross
2013-09-01
To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.
Continuous Fine-Fault Estimation with Real-Time GNSS
Norford, B. B.; Melbourne, T. I.; Szeliga, W. M.; Santillan, V. M.; Scrivner, C.; Senko, J.; Larsen, D.
2017-12-01
Thousands of real-time telemetered GNSS stations operate throughout the circum-Pacific that may be used for rapid earthquake characterization and estimation of local tsunami excitation. We report on the development of a GNSS-based finite-fault inversion system that continuously estimates slip using real-time GNSS position streams from the Cascadia subduction zone and which is being expanded throughout the circum-Pacific. The system uses 1 Hz precise point position streams computed in the ITRF14 reference frame using clock and satellite orbit corrections from the IGS. The software is implemented as seven independent modules that filter time series using Kalman filters, trigger and estimate coseismic offsets, invert for slip using a non-negative least squares method developed by Lawson and Hanson (1974) and elastic half-space Green's Functions developed by Okada (1985), smooth the results temporally and spatially, and write the resulting streams of time-dependent slip to a RabbitMQ messaging server for use by downstream modules such as tsunami excitation modules. Additional fault models can be easily added to the system for other circum-Pacific subduction zones as additional real-time GNSS data become available. The system is currently being tested using data from well-recorded earthquakes including the 2011 Tohoku earthquake, the 2010 Maule earthquake, the 2015 Illapel earthquake, the 2003 Tokachi-oki earthquake, the 2014 Iquique earthquake, the 2010 Mentawai earthquake, the 2016 Kaikoura earthquake, the 2016 Ecuador earthquake, the 2015 Gorkha earthquake, and others. Test data will be fed to the system and the resultant earthquake characterizations will be compared with published earthquake parameters. Seismic events will be assumed to occur on major faults, so, for example, only the San Andreas fault will be considered in Southern California, while the hundreds of other faults in the region will be ignored. Rake will be constrained along each subfault to be
Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery
International Nuclear Information System (INIS)
Rottmann, Joerg; Berbeco, Ross; Keall, Paul
2013-01-01
Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient.Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps.Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm.Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time
Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery
Energy Technology Data Exchange (ETDEWEB)
Rottmann, Joerg; Berbeco, Ross [Brigham and Women' s Hospital, Dana Farber-Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Keall, Paul [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney NSW 2006 (Australia)
2013-09-15
Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient.Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps.Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm.Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.
REAL TIME SPEED ESTIMATION FROM MONOCULAR VIDEO
Directory of Open Access Journals (Sweden)
M. S. Temiz
2012-07-01
Full Text Available In this paper, detailed studies have been performed for developing a real time system to be used for surveillance of the traffic flow by using monocular video cameras to find speeds of the vehicles for secure travelling are presented. We assume that the studied road segment is planar and straight, the camera is tilted downward a bridge and the length of one line segment in the image is known. In order to estimate the speed of a moving vehicle from a video camera, rectification of video images is performed to eliminate the perspective effects and then the interest region namely the ROI is determined for tracking the vehicles. Velocity vectors of a sufficient number of reference points are identified on the image of the vehicle from each video frame. For this purpose sufficient number of points from the vehicle is selected, and these points must be accurately tracked on at least two successive video frames. In the second step, by using the displacement vectors of the tracked points and passed time, the velocity vectors of those points are computed. Computed velocity vectors are defined in the video image coordinate system and displacement vectors are measured by the means of pixel units. Then the magnitudes of the computed vectors in the image space are transformed to the object space to find the absolute values of these magnitudes. The accuracy of the estimated speed is approximately ±1 – 2 km/h. In order to solve the real time speed estimation problem, the authors have written a software system in C++ programming language. This software system has been used for all of the computations and test applications.
Real-time measurements and their effects on state estimation of distribution power system
DEFF Research Database (Denmark)
Han, Xue; You, Shi; Thordarson, Fannar
2013-01-01
between the estimated values (voltage and injected power) and the measurements are applied to evaluate the accuracy of the estimated grid states. Eventually, some suggestions are provided for the distribution grid operators on placing the real-time meters in the distribution grid.......This paper aims at analyzing the potential value of using different real-time metering and measuring instruments applied in the low voltage distribution networks for state-estimation. An algorithm is presented to evaluate different combinations of metering data using a tailored state estimator....... It is followed by a case study based on the proposed algorithm. A real distribution grid feeder with different types of meters installed either in the cabinets or at the customer side is selected for simulation and analysis. Standard load templates are used to initiate the state estimation. The deviations...
Power System Real-Time Monitoring by Using PMU-Based Robust State Estimation Method
DEFF Research Database (Denmark)
Zhao, Junbo; Zhang, Gexiang; Das, Kaushik
2016-01-01
Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions...... the system real-time states with good robustness and can address several kinds of BD.......-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track...
Li, Yuankai; Ding, Liang; Zheng, Zhizhong; Yang, Qizhi; Zhao, Xingang; Liu, Guangjun
2018-05-01
For motion control of wheeled planetary rovers traversing on deformable terrain, real-time terrain parameter estimation is critical in modeling the wheel-terrain interaction and compensating the effect of wheel slipping. A multi-mode real-time estimation method is proposed in this paper to achieve accurate terrain parameter estimation. The proposed method is composed of an inner layer for real-time filtering and an outer layer for online update. In the inner layer, sinkage exponent and internal frictional angle, which have higher sensitivity than that of the other terrain parameters to wheel-terrain interaction forces, are estimated in real time by using an adaptive robust extended Kalman filter (AREKF), whereas the other parameters are fixed with nominal values. The inner layer result can help synthesize the current wheel-terrain contact forces with adequate precision, but has limited prediction capability for time-variable wheel slipping. To improve estimation accuracy of the result from the inner layer, an outer layer based on recursive Gauss-Newton (RGN) algorithm is introduced to refine the result of real-time filtering according to the innovation contained in the history data. With the two-layer structure, the proposed method can work in three fundamental estimation modes: EKF, REKF and RGN, making the method applicable for flat, rough and non-uniform terrains. Simulations have demonstrated the effectiveness of the proposed method under three terrain types, showing the advantages of introducing the two-layer structure.
A multi-camera system for real-time pose estimation
Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin
2007-04-01
This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.
Dynamic state estimation and prediction for real-time control and operation
Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.
2013-01-01
Real-time control and operation are crucial to deal with increasing complexity of modern power systems. To effectively enable those functions, it is required a Dynamic State Estimation (DSE) function to provide accurate network state variables at the right moment and predict their trends ahead. This
Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng
2018-02-01
Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.
Analytical model for real time, noninvasive estimation of blood glucose level.
Adhyapak, Anoop; Sidley, Matthew; Venkataraman, Jayanti
2014-01-01
The paper presents an analytical model to estimate blood glucose level from measurements made non-invasively and in real time by an antenna strapped to a patient's wrist. Some promising success has been shown by the RIT ETA Lab research group that an antenna's resonant frequency can track, in real time, changes in glucose concentration. Based on an in-vitro study of blood samples of diabetic patients, the paper presents a modified Cole-Cole model that incorporates a factor to represent the change in glucose level. A calibration technique using the input impedance technique is discussed and the results show a good estimation as compared to the glucose meter readings. An alternate calibration methodology has been developed that is based on the shift in the antenna resonant frequency using an equivalent circuit model containing a shunt capacitor to represent the shift in resonant frequency with changing glucose levels. Work under progress is the optimization of the technique with a larger sample of patients.
Towards real-time body pose estimation for presenters in meeting environments
Poppe, Ronald Walter; Heylen, Dirk K.J.; Nijholt, Antinus; Poel, Mannes
2005-01-01
This paper describes a computer vision-based approach to body pose estimation. The algorithm can be executed in real-time and processes low resolution, monocular image sequences. A silhouette is extracted and matched against a projection of a 16 DOF human body model. In addition, skin color is used
Multi-processor system for real-time deconvolution and flow estimation in medical ultrasound
DEFF Research Database (Denmark)
Jensen, Jesper Lomborg; Jensen, Jørgen Arendt; Stetson, Paul F.
1996-01-01
of the algorithms. Many of the algorithms can only be properly evaluated in a clinical setting with real-time processing, which generally cannot be done with conventional equipment. This paper therefore presents a multi-processor system capable of performing 1.2 billion floating point operations per second on RF...... filter is used with a second time-reversed recursive estimation step. Here it is necessary to perform about 70 arithmetic operations per RF sample or about 1 billion operations per second for real-time deconvolution. Furthermore, these have to be floating point operations due to the adaptive nature...... interfaced to our previously-developed real-time sampling system that can acquire RF data at a rate of 20 MHz and simultaneously transmit the data at 20 MHz to the processing system via several parallel channels. These two systems can, thus, perform real-time processing of ultrasound data. The advantage...
Real-time estimation of small-area populations with human biomarkers in sewage
International Nuclear Information System (INIS)
Daughton, Christian G.
2012-01-01
urine dilution), the biomarker with the most potential for the SCIM concept for real-time measurement of population was determined to be coprostanol - the major sterol produced by microbial reduction of cholesterol in the colon. - Highlights: ► New concept proposed for estimating small-area human populations. ► Sewage Chemical-Information Mining (SCIM) measures biomarkers in sewage. ► Real-time estimation of populations (accommodating influx and efflux) is possible. ► Coprostanol is identified as a candidate biomarker for estimating population size. ► Composite biomarkers having complementary properties could improve accuracy.
DEFF Research Database (Denmark)
Pertl, Michael; Douglass, Philip James; Heussen, Kai
2018-01-01
network approach for voltage estimation in active distribution grids by means of measured data from two feeders of a real low voltage distribution grid. The approach enables a real-time voltage estimation at locations in the distribution grid, where otherwise only non-real-time measurements are available......The installation of measurements in distribution grids enables the development of data driven methods for the power system. However, these methods have to be validated in order to understand the limitations and capabilities for their use. This paper presents a systematic validation of a neural...
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
account for urine dilution), the biomarker with the most potential for the SCIM concept for real-time measurement of population was determined to be coprostanol - the major sterol produced by microbial reduction of cholesterol in the colon. - Highlights: Black-Right-Pointing-Pointer New concept proposed for estimating small-area human populations. Black-Right-Pointing-Pointer Sewage Chemical-Information Mining (SCIM) measures biomarkers in sewage. Black-Right-Pointing-Pointer Real-time estimation of populations (accommodating influx and efflux) is possible. Black-Right-Pointing-Pointer Coprostanol is identified as a candidate biomarker for estimating population size. Black-Right-Pointing-Pointer Composite biomarkers having complementary properties could improve accuracy.
An anti-disturbing real time pose estimation method and system
Zhou, Jian; Zhang, Xiao-hu
2011-08-01
Pose estimation relating two-dimensional (2D) images to three-dimensional (3D) rigid object need some known features to track. In practice, there are many algorithms which perform this task in high accuracy, but all of these algorithms suffer from features lost. This paper investigated the pose estimation when numbers of known features or even all of them were invisible. Firstly, known features were tracked to calculate pose in the current and the next image. Secondly, some unknown but good features to track were automatically detected in the current and the next image. Thirdly, those unknown features which were on the rigid and could match each other in the two images were retained. Because of the motion characteristic of the rigid object, the 3D information of those unknown features on the rigid could be solved by the rigid object's pose at the two moment and their 2D information in the two images except only two case: the first one was that both camera and object have no relative motion and camera parameter such as focus length, principle point, and etc. have no change at the two moment; the second one was that there was no shared scene or no matched feature in the two image. Finally, because those unknown features at the first time were known now, pose estimation could go on in the followed images in spite of the missing of known features in the beginning by repeating the process mentioned above. The robustness of pose estimation by different features detection algorithms such as Kanade-Lucas-Tomasi (KLT) feature, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) were compared and the compact of the different relative motion between camera and the rigid object were discussed in this paper. Graphic Processing Unit (GPU) parallel computing was also used to extract and to match hundreds of features for real time pose estimation which was hard to work on Central Processing Unit (CPU). Compared with other pose estimation methods, this new
Real-time data for estimating a forward-looking interest rate rule of the ECB
Directory of Open Access Journals (Sweden)
Tilman Bletzinger
2017-12-01
Full Text Available The purpose of the data presented in this article is to use it in ex post estimations of interest rate decisions by the European Central Bank (ECB, as it is done by Bletzinger and Wieland (2017 [1]. The data is of quarterly frequency from 1999 Q1 until 2013 Q2 and consists of the ECB's policy rate, inflation rate, real output growth and potential output growth in the euro area. To account for forward-looking decision making in the interest rate rule, the data consists of expectations about future inflation and output dynamics. While potential output is constructed based on data from the European Commission's annual macro-economic database, inflation and real output growth are taken from two different sources both provided by the ECB: the Survey of Professional Forecasters and projections made by ECB staff. Careful attention was given to the publication date of the collected data to ensure a real-time dataset only consisting of information which was available to the decision makers at the time of the decision. Keywords: Interest rate rule estimation, Real-time data, Forward-looking data
Dynamic temperature estimation and real time emergency rating of transmission cables
DEFF Research Database (Denmark)
Olsen, R. S.; Holboll, J.; Gudmundsdottir, Unnur Stella
2012-01-01
enables real time emergency ratings, such that the transmission system operator can make well-founded decisions during faults. Hereunder is included the capability of producing high resolution loadability vs. time schedules within few minutes, such that the TSO can safely control the system.......). It is found that the calculated temperature estimations are fairly accurate — within 1.5oC of the finite element method (FEM) simulation to which it is compared — both when looking at the temperature profile (time dependent) and the temperature distribution (geometric dependent). The methodology moreover...
Graffigna, Victoria
2017-01-01
The TOmographic Model of the IONospheric electron content (TOMION) software implements a simultaneous precise geodetic and ionospheric modeling, which can be used to test new approaches for real-time precise GNSS modeling (positioning, ionospheric and tropospheric delays, clock errors, among others). In this work, the software is used to estimate the Zenith Tropospheric Delay (ZTD) emulating real time and its performance is evaluated through a comparative analysis with a built-in GIPSY estima...
Real-Time Tropospheric Delay Estimation using IGS Products
Stürze, Andrea; Liu, Sha; Söhne, Wolfgang
2014-05-01
The Federal Agency for Cartography and Geodesy (BKG) routinely provides zenith tropospheric delay (ZTD) parameter for the assimilation in numerical weather models since more than 10 years. Up to now the results flowing into the EUREF Permanent Network (EPN) or E-GVAP (EUMETNET EIG GNSS water vapour programme) analysis are based on batch processing of GPS+GLONASS observations in differential network mode. For the recently started COST Action ES1206 about "Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate" (GNSS4SWEC), however, rapid updates in the analysis of the atmospheric state for nowcasting applications require changing the processing strategy towards real-time. In the RTCM SC104 (Radio Technical Commission for Maritime Services, Special Committee 104) a format combining the advantages of Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) is under development. The so-called State Space Representation approach is defining corrections, which will be transferred in real-time to the user e.g. via NTRIP (Network Transport of RTCM via Internet Protocol). Meanwhile messages for precise orbits, satellite clocks and code biases compatible to the basic PPP mode using IGS products are defined. Consequently, the IGS Real-Time Service (RTS) was launched in 2013 in order to extend the well-known precise orbit and clock products by a real-time component. Further messages e.g. with respect to ionosphere or phase biases are foreseen. Depending on the level of refinement, so different accuracies up to the RTK level shall be reachable. In co-operation of BKG and the Technical University of Darmstadt the real-time software GEMon (GREF EUREF Monitoring) is under development. GEMon is able to process GPS and GLONASS observation and RTS product data streams in PPP mode. Furthermore, several state-of-the-art troposphere models, for example based on numerical weather prediction data, are implemented. Hence, it
Morales, Rafael; Rincón, Fernando; Gazzano, Julio Dondo; López, Juan Carlos
2014-01-01
Time derivative estimation of signals plays a very important role in several fields, such as signal processing and control engineering, just to name a few of them. For that purpose, a non-asymptotic algebraic procedure for the approximate estimation of the system states is used in this work. The method is based on results from differential algebra and furnishes some general formulae for the time derivatives of a measurable signal in which two algebraic derivative estimators run simultaneously, but in an overlapping fashion. The algebraic derivative algorithm presented in this paper is computed online and in real-time, offering high robustness properties with regard to corrupting noises, versatility and ease of implementation. Besides, in this work, we introduce a novel architecture to accelerate this algebraic derivative estimator using reconfigurable logic. The core of the algorithm is implemented in an FPGA, improving the speed of the system and achieving real-time performance. Finally, this work proposes a low-cost platform for the integration of hardware in the loop in MATLAB. PMID:24859033
DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING
National Aeronautics and Space Administration — DYNAMIC STRAIN MAPPING AND REAL-TIME DAMAGE STATE ESTIMATION UNDER BIAXIAL RANDOM FATIGUE LOADING SUBHASISH MOHANTY*, ADITI CHATTOPADHYAY, JOHN N. RAJADAS, AND CLYDE...
DEFF Research Database (Denmark)
Støvring, Henrik; Pottegård, Anton; Hallas, Jesper
2017-01-01
Purpose: To introduce the reverse waiting time distribution (WTD) and show how it can be used to estimate stopping fractions and real-time prevalence of treatment in pharmacoepidemiological studies. Methods: The reverse WTD is the distribution of time from the last dispensed prescription of each......-hoc decision rules for automated implementations, and it yields estimates of real-time prevalence....... patient within a time window to the end of it. It is a mirrored version of the ordinary WTD, which considers the first dispensed prescription of patients within a time window. Based on renewal process theory, the reverse WTD can be analyzed as an ordinary WTD with maximum likelihood estimation. Based...
Real time bayesian estimation of the epidemic potential of emerging infectious diseases.
Directory of Open Access Journals (Sweden)
Luís M A Bettencourt
Full Text Available BACKGROUND: Fast changes in human demographics worldwide, coupled with increased mobility, and modified land uses make the threat of emerging infectious diseases increasingly important. Currently there is worldwide alert for H5N1 avian influenza becoming as transmissible in humans as seasonal influenza, and potentially causing a pandemic of unprecedented proportions. Here we show how epidemiological surveillance data for emerging infectious diseases can be interpreted in real time to assess changes in transmissibility with quantified uncertainty, and to perform running time predictions of new cases and guide logistics allocations. METHODOLOGY/PRINCIPAL FINDINGS: We develop an extension of standard epidemiological models, appropriate for emerging infectious diseases, that describes the probabilistic progression of case numbers due to the concurrent effects of (incipient human transmission and multiple introductions from a reservoir. The model is cast in terms of surveillance observables and immediately suggests a simple graphical estimation procedure for the effective reproductive number R (mean number of cases generated by an infectious individual of standard epidemics. For emerging infectious diseases, which typically show large relative case number fluctuations over time, we develop a bayesian scheme for real time estimation of the probability distribution of the effective reproduction number and show how to use such inferences to formulate significance tests on future epidemiological observations. CONCLUSIONS/SIGNIFICANCE: Violations of these significance tests define statistical anomalies that may signal changes in the epidemiology of emerging diseases and should trigger further field investigation. We apply the methodology to case data from World Health Organization reports to place bounds on the current transmissibility of H5N1 influenza in humans and establish a statistical basis for monitoring its evolution in real time.
Real-time fault-tolerant moving horizon air data estimation for the RECONFIGURE benchmark
Wan, Y.; Keviczky, T.
2018-01-01
This paper proposes a real-time fault-tolerant estimation approach for combined sensor fault diagnosis and air data reconstruction. Due to simultaneous influence of winds and latent faults on monitored sensors, it is challenging to address the tradeoff between robustness to wind disturbances and
Directory of Open Access Journals (Sweden)
CHEN Liang
2017-05-01
Full Text Available GNSS satellite-based differential augment system is based on real-time orbit and clock augment message. The multi-GNSS real-time precise clock error estimation model is studied, and then the parameters estimated in traditional un-difference model are optimized and a high-efficient real-time clock simplified model is proposed and realized. The real-time orbit data processing based on PANDA is also analyzed. The results indicate that the real-time orbit radial accuracy of GPS, BeiDou MEO and Galileo is 1~5 cm, and the radial accuracy of the BeiDou GEO/IGSO satellite is about 10 cm. It is found that the optimized real-time clock simplified model is more efficient in one epoch than un-difference model and can be applied to high-frequency (such as 1 Hz updating of real-time clock augment message. The results show that the real-time clock error obtained by this model is absolute value and there is no constant bias. Based on the real-time orbit, the GPS real-time clock precision of the simplified model is about 0.24 ns, BeiDou GEO is about 0.50 ns, IGSO/MEO is about 0.22 ns and Galileo is about 0.32 ns. Using the multi-GNSS real-time data stream in GFZ, a multi-GNSS real-time augment prototype system is built and the real-time augment message is being broadcasted on the Internet. The real-time PPP centimeter-level service and meter-level navigation service based on pseudorange are realized based on this prototype system.
Real-time moving horizon estimation for a vibrating active cantilever
Abdollahpouri, Mohammad; Takács, Gergely; Rohaľ-Ilkiv, Boris
2017-03-01
Vibrating structures may be subject to changes throughout their operating lifetime due to a range of environmental and technical factors. These variations can be considered as parameter changes in the dynamic model of the structure, while their online estimates can be utilized in adaptive control strategies, or in structural health monitoring. This paper implements the moving horizon estimation (MHE) algorithm on a low-cost embedded computing device that is jointly observing the dynamic states and parameter variations of an active cantilever beam in real time. The practical behavior of this algorithm has been investigated in various experimental scenarios. It has been found, that for the given field of application, moving horizon estimation converges faster than the extended Kalman filter; moreover, it handles atypical measurement noise, sensor errors or other extreme changes, reliably. Despite its improved performance, the experiments demonstrate that the disadvantage of solving the nonlinear optimization problem in MHE is that it naturally leads to an increase in computational effort.
Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air
Martos, Borja; Morelli, Eugene A.
2012-01-01
The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.
Estimating marginal properties of quantitative real-time PCR data using nonlinear mixed models
DEFF Research Database (Denmark)
Gerhard, Daniel; Bremer, Melanie; Ritz, Christian
2014-01-01
A unified modeling framework based on a set of nonlinear mixed models is proposed for flexible modeling of gene expression in real-time PCR experiments. Focus is on estimating the marginal or population-based derived parameters: cycle thresholds and ΔΔc(t), but retaining the conditional mixed mod...
Hyer, E. J.; Schmidt, C. C.; Hoffman, J.; Giglio, L.; Peterson, D. A.
2013-12-01
Polar and geostationary satellites are used operationally for fire detection and smoke source estimation by many near-real-time operational users, including operational forecast centers around the globe. The input satellite radiance data are processed by data providers to produce Level-2 and Level -3 fire detection products, but processing these data into spatially and temporally consistent estimates of fire activity requires a substantial amount of additional processing. The most significant processing steps are correction for variable coverage of the satellite observations, and correction for conditions that affect the detection efficiency of the satellite sensors. We describe a system developed by the Naval Research Laboratory (NRL) that uses the full raster information from the entire constellation to diagnose detection opportunities, calculate corrections for factors such as angular dependence of detection efficiency, and generate global estimates of fire activity at spatial and temporal scales suitable for atmospheric modeling. By incorporating these improved fire observations, smoke emissions products, such as NRL's FLAMBE, are able to produce improved estimates of global emissions. This talk provides an overview of the system, demonstrates the achievable improvement over older methods, and describes challenges for near-real-time implementation.
Energy Technology Data Exchange (ETDEWEB)
Zeng, L., E-mail: zeng@fusion.gat.com; Doyle, E. J.; Rhodes, T. L.; Wang, G.; Sung, C.; Peebles, W. A. [Physics and Astronomy Department, University of California, Los Angeles, California 90095 (United States); Bobrek, M. [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6006 (United States)
2016-11-15
A new model-based technique for fast estimation of the pedestal electron density gradient has been developed. The technique uses ordinary mode polarization profile reflectometer time delay data and does not require direct profile inversion. Because of its simple data processing, the technique can be readily implemented via a Field-Programmable Gate Array, so as to provide a real-time density gradient estimate, suitable for use in plasma control systems such as envisioned for ITER, and possibly for DIII-D and Experimental Advanced Superconducting Tokamak. The method is based on a simple edge plasma model with a linear pedestal density gradient and low scrape-off-layer density. By measuring reflectometer time delays for three adjacent frequencies, the pedestal density gradient can be estimated analytically via the new approach. Using existing DIII-D profile reflectometer data, the estimated density gradients obtained from the new technique are found to be in good agreement with the actual density gradients for a number of dynamic DIII-D plasma conditions.
Real-Time Personalized Monitoring to Estimate Occupational Heat Stress in Ambient Assisted Working
Directory of Open Access Journals (Sweden)
Pablo Pancardo
2015-07-01
Full Text Available Ambient Assisted Working (AAW is a discipline aiming to provide comfort and safety in the workplace through customization and technology. Workers’ comfort may be compromised in many labor situations, including those depending on environmental conditions, like extremely hot weather conduces to heat stress. Occupational heat stress (OHS happens when a worker is in an uninterrupted physical activity and in a hot environment. OHS can produce strain on the body, which leads to discomfort and eventually to heat illness and even death. Related ISO standards contain methods to estimate OHS and to ensure the safety and health of workers, but they are subjective, impersonal, performed a posteriori and even invasive. This paper focuses on the design and development of real-time personalized monitoring for a more effective and objective estimation of OHS, taking into account the individual user profile, fusing data from environmental and unobtrusive body sensors. Formulas employed in this work were taken from different domains and joined in the method that we propose. It is based on calculations that enable continuous surveillance of physical activity performance in a comfortable and healthy manner. In this proposal, we found that OHS can be estimated by satisfying the following criteria: objective, personalized, in situ, in real time, just in time and in an unobtrusive way. This enables timely notice for workers to make decisions based on objective information to control OHS.
Estimating DSGE model parameters in a small open economy: Do real-time data matter?
Directory of Open Access Journals (Sweden)
Capek Jan
2015-03-01
Full Text Available This paper investigates the differences between parameters estimated using real-time and those estimated with revised data. The models used are New Keynesian DSGE models of the Czech, Polish, Hungarian, Swiss, and Swedish small open economies in interaction with the euro area. The paper also offers an analysis of data revisions of GDP growth and inflation and trend revisions of interest rates.
Near-real-time and scenario earthquake loss estimates for Mexico
Wyss, M.; Zuñiga, R.
2017-12-01
The large earthquakes of 8 September 2017, M8.1, and 19 September 2017, M7.1 have focused attention on the dangers of Mexican seismicity. The near-real-time alerts by QLARM estimated 10 to 300 fatalities and 0 to 200 fatalities, respectively. At the time of this submission the reported death tolls are 96 and 226, respectively. These alerts were issued within 96 and 57 minutes of the occurrence times. For the M8.1 earthquake the losses due to a line model could be calculated. The line with length L=110 km extended from the initial epicenter to the NE, where the USGS had reported aftershocks. On September 19, no aftershocks were available in near-real-time, so a point source had to be used for the quick calculation of likely casualties. In both cases, the casualties were at least an order of magnitude smaller than what they could have been because on 8 September the source was relatively far offshore and on 19 September the hypocenter was relatively deep. The largest historic earthquake in Mexico occurred on 28 March 1787 and likely had a rupture length of 450 km and M8.6. Based on this event, and after verifying our tool for Mexico, we estimated the order of magnitude of a disaster, given the current population, in a maximum credible earthquake along the Pacific coast. In the countryside along the coast we expect approximately 27,000 fatalities and 480,000 injured. In the special case of Mexico City the casualties in a worst possible earthquake along the Pacific plate boundary would likely be counted as five digit numbers. The large agglomerate of the capital with its lake bed soil attracts most attention. Nevertheless, one should pay attention to the fact that the poor, rural segment of society, living in buildings of weak resistance to shaking, are likely to sustain a mortality rate about 20% larger than the population in cities on average soil.
International Nuclear Information System (INIS)
Lim, KaiChin; Bastawrous, Hany Ayad; Duong, Van-Huan; See, Khay Wai; Zhang, Peng; Dou, Shi Xue
2016-01-01
Highlights: • Real-time battery model parameters and SoC estimation with novel method is proposed. • Cascading filtering stages are used for parameters identification and SoC estimation. • Optimized fading Kalman filter is implemented for SoC estimation. • Accurate SoC estimation is validated in UDDS load profile experiment. • This approach is suitable for BMS in EV applications due to its simplicity. - Abstract: A novel online estimation technique for estimating the state of charge (SoC) of a lithium iron phosphate (LiFePO_4) battery has been developed. Based on a simplified model, the open circuit voltage (OCV) of the battery is estimated through two cascaded linear filtering stages. A recursive least squares filter is employed in the first stage to dynamically estimate the battery model parameters in real-time, and then, a fading Kalman filter (FKF) is used to estimate the OCV from these parameters. FKF can avoid the possibility of large estimation errors, which may occur with a conventional Kalman filter, due to its capability to compensate any modeling error through a fading factor. By optimizing the value of the fading factor in the set of recursion equations of FKF with genetic algorithms, the errors in estimating the battery’s SoC in urban dynamometer driving schedules-based experiments and real vehicle driving cycle experiments were below 3% compared to more than 9% in the case of using an ordinary Kalman filter. The proposed method with its simplified model provides the simplicity and feasibility required for real-time application with highly accurate SoC estimation.
Lubey, D.; Scheeres, D.
Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal
Real-Time Aerodynamic Parameter Estimation without Air Flow Angle Measurements
Morelli, Eugene A.
2010-01-01
A technique for estimating aerodynamic parameters in real time from flight data without air flow angle measurements is described and demonstrated. The method is applied to simulated F-16 data, and to flight data from a subscale jet transport aircraft. Modeling results obtained with the new approach using flight data without air flow angle measurements were compared to modeling results computed conventionally using flight data that included air flow angle measurements. Comparisons demonstrated that the new technique can provide accurate aerodynamic modeling results without air flow angle measurements, which are often difficult and expensive to obtain. Implications for efficient flight testing and flight safety are discussed.
Son, Sanghyun; Baek, Yunju
2015-08-18
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.
Directory of Open Access Journals (Sweden)
Sanghyun Son
2015-08-01
Full Text Available As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.
George, Daniel; Huerta, E. A.
2018-03-01
The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of multimessenger astrophysics. To enhance the scope of this emergent field of science, we pioneered the use of deep learning with convolutional neural networks, that take time-series inputs, for rapid detection and characterization of gravitational wave signals. This approach, Deep Filtering, was initially demonstrated using simulated LIGO noise. In this article, we present the extension of Deep Filtering using real data from LIGO, for both detection and parameter estimation of gravitational waves from binary black hole mergers using continuous data streams from multiple LIGO detectors. We demonstrate for the first time that machine learning can detect and estimate the true parameters of real events observed by LIGO. Our results show that Deep Filtering achieves similar sensitivities and lower errors compared to matched-filtering while being far more computationally efficient and more resilient to glitches, allowing real-time processing of weak time-series signals in non-stationary non-Gaussian noise with minimal resources, and also enables the detection of new classes of gravitational wave sources that may go unnoticed with existing detection algorithms. This unified framework for data analysis is ideally suited to enable coincident detection campaigns of gravitational waves and their multimessenger counterparts in real-time.
Kernel density estimation-based real-time prediction for respiratory motion
International Nuclear Information System (INIS)
Ruan, Dan
2010-01-01
Effective delivery of adaptive radiotherapy requires locating the target with high precision in real time. System latency caused by data acquisition, streaming, processing and delivery control necessitates prediction. Prediction is particularly challenging for highly mobile targets such as thoracic and abdominal tumors undergoing respiration-induced motion. The complexity of the respiratory motion makes it difficult to build and justify explicit models. In this study, we honor the intrinsic uncertainties in respiratory motion and propose a statistical treatment of the prediction problem. Instead of asking for a deterministic covariate-response map and a unique estimate value for future target position, we aim to obtain a distribution of the future target position (response variable) conditioned on the observed historical sample values (covariate variable). The key idea is to estimate the joint probability distribution (pdf) of the covariate and response variables using an efficient kernel density estimation method. Then, the problem of identifying the distribution of the future target position reduces to identifying the section in the joint pdf based on the observed covariate. Subsequently, estimators are derived based on this estimated conditional distribution. This probabilistic perspective has some distinctive advantages over existing deterministic schemes: (1) it is compatible with potentially inconsistent training samples, i.e., when close covariate variables correspond to dramatically different response values; (2) it is not restricted by any prior structural assumption on the map between the covariate and the response; (3) the two-stage setup allows much freedom in choosing statistical estimates and provides a full nonparametric description of the uncertainty for the resulting estimate. We evaluated the prediction performance on ten patient RPM traces, using the root mean squared difference between the prediction and the observed value normalized by the
Energy Technology Data Exchange (ETDEWEB)
Kulisek, J.A., E-mail: Jonathan.Kulisek@pnnl.gov; Schweppe, J.E.; Stave, S.C.; Bernacki, B.E.; Jordan, D.V.; Stewart, T.N.; Seifert, C.E.; Kernan, W.J.
2015-06-01
Helicopter-mounted gamma-ray detectors can provide law enforcement officials the means to quickly and accurately detect, identify, and locate radiological threats over a wide geographical area. The ability to accurately distinguish radiological threat-generated gamma-ray signatures from background gamma radiation in real time is essential in order to realize this potential. This problem is non-trivial, especially in urban environments for which the background may change very rapidly during flight. This exacerbates the challenge of estimating background due to the poor counting statistics inherent in real-time airborne gamma-ray spectroscopy measurements. To address this challenge, we have developed a new technique for real-time estimation of background gamma radiation from aerial measurements without the need for human analyst intervention. The method can be calibrated using radiation transport simulations along with data from previous flights over areas for which the isotopic composition need not be known. Over the examined measured and simulated data sets, the method generated accurate background estimates even in the presence of a strong, {sup 60}Co source. The potential to track large and abrupt changes in background spectral shape and magnitude was demonstrated. The method can be implemented fairly easily in most modern computing languages and environments.
The real-time price elasticity of electricity
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
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
A Real-Time Systems Symposium Preprint.
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,
Energy Technology Data Exchange (ETDEWEB)
Garrigos, Ausias; Blanes, Jose M.; Carrasco, Jose A. [Area de Tecnologia Electronica, Universidad Miguel Hernandez de Elche, Avda. de la Universidad s/n, 03202 Elche, Alicante (Spain); Ejea, Juan B. [Departamento de Ingenieria Electronica, Universidad de Valencia, Avda. Dr Moliner 50, 46100 Valencia, Valencia (Spain)
2007-05-15
In this paper, an approximate curve fitting method for photovoltaic modules is presented. The operation is based on solving a simple solar cell electrical model by a microcontroller in real time. Only four voltage and current coordinates are needed to obtain the solar module parameters and set its operation at maximum power in any conditions of illumination and temperature. Despite its simplicity, this method is suitable for low cost real time applications, as control loop reference generator in photovoltaic maximum power point circuits. The theory that supports the estimator together with simulations and experimental results are presented. (author)
Real-Time Parameter Identification
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 Forecasting Revisited: Letting the Data Decide
Jackson Kitchen; John Kitchen
2013-01-01
Real-time GDP forecasting, also often known as “nowcasting,” produces estimates for current-quarter real GDP growth, typically based on a centered value from a set of estimates from incoming indicators. These real-time measures are usually intended to be data-based and to not be based on forecaster judgment or add factors. Even so, estimation methodologies in this research area—and prior versions of the system we use—typically have been constrained by using various “fixed” relationships, such...
Real-time geometric scene estimation for RGBD images using a 3D box shape grammar
Willis, Andrew R.; Brink, Kevin M.
2016-06-01
This article describes a novel real-time algorithm for the purpose of extracting box-like structures from RGBD image data. In contrast to conventional approaches, the proposed algorithm includes two novel attributes: (1) it divides the geometric estimation procedure into subroutines having atomic incremental computational costs, and (2) it uses a generative "Block World" perceptual model that infers both concave and convex box elements from detection of primitive box substructures. The end result is an efficient geometry processing engine suitable for use in real-time embedded systems such as those on an UAVs where it is intended to be an integral component for robotic navigation and mapping applications.
Accurate estimation of camera shot noise in the real-time
Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Starikov, Rostislav S.
2017-10-01
Nowadays digital cameras are essential parts of various technological processes and daily tasks. They are widely used in optics and photonics, astronomy, biology and other various fields of science and technology such as control systems and video-surveillance monitoring. One of the main information limitations of photo- and videocameras are noises of photosensor pixels. Camera's photosensor noise can be divided into random and pattern components. Temporal noise includes random noise component while spatial noise includes pattern noise component. Temporal noise can be divided into signal-dependent shot noise and signal-nondependent dark temporal noise. For measurement of camera noise characteristics, the most widely used methods are standards (for example, EMVA Standard 1288). It allows precise shot and dark temporal noise measurement but difficult in implementation and time-consuming. Earlier we proposed method for measurement of temporal noise of photo- and videocameras. It is based on the automatic segmentation of nonuniform targets (ASNT). Only two frames are sufficient for noise measurement with the modified method. In this paper, we registered frames and estimated shot and dark temporal noises of cameras consistently in the real-time. The modified ASNT method is used. Estimation was performed for the cameras: consumer photocamera Canon EOS 400D (CMOS, 10.1 MP, 12 bit ADC), scientific camera MegaPlus II ES11000 (CCD, 10.7 MP, 12 bit ADC), industrial camera PixeLink PL-B781F (CMOS, 6.6 MP, 10 bit ADC) and video-surveillance camera Watec LCL-902C (CCD, 0.47 MP, external 8 bit ADC). Experimental dependencies of temporal noise on signal value are in good agreement with fitted curves based on a Poisson distribution excluding areas near saturation. Time of registering and processing of frames used for temporal noise estimation was measured. Using standard computer, frames were registered and processed during a fraction of second to several seconds only. Also the
Strano, Salvatore; Terzo, Mario
2018-05-01
The dynamics of the railway vehicles is strongly influenced by the interaction between the wheel and the rail. This kind of contact is affected by several conditioning factors such as vehicle speed, wear, adhesion level and, moreover, it is nonlinear. As a consequence, the modelling and the observation of this kind of phenomenon are complex tasks but, at the same time, they constitute a fundamental step for the estimation of the adhesion level or for the vehicle condition monitoring. This paper presents a novel technique for the real time estimation of the wheel-rail contact forces based on an estimator design model that takes into account the nonlinearities of the interaction by means of a fitting model functional to reproduce the contact mechanics in a wide range of slip and to be easily integrated in a complete model based estimator for railway vehicle.
Fu, Deqian; Gao, Lisheng; Jhang, Seong Tae
2012-04-01
The mobile computing device has many limitations, such as relative small user interface and slow computing speed. Usually, augmented reality requires face pose estimation can be used as a HCI and entertainment tool. As far as the realtime implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to face different constraints while leaving enough face pose estimation accuracy. The proposed face pose estimation method met this objective. Experimental results running on a testing Android mobile device delivered satisfactory performing results in the real-time and accurately.
A Comparison of Iterative 2D-3D Pose Estimation Methods for Real-Time Applications
DEFF Research Database (Denmark)
Grest, Daniel; Krüger, Volker; Petersen, Thomas
2009-01-01
This work compares iterative 2D-3D Pose Estimation methods for use in real-time applications. The compared methods are available for public as C++ code. One method is part of the openCV library, namely POSIT. Because POSIT is not applicable for planar 3Dpoint congurations, we include the planar P...
Real-time data for estimating a forward-looking interest rate rule of the ECB.
Bletzinger, Tilman; Wieland, Volker
2017-12-01
The purpose of the data presented in this article is to use it in ex post estimations of interest rate decisions by the European Central Bank (ECB), as it is done by Bletzinger and Wieland (2017) [1]. The data is of quarterly frequency from 1999 Q1 until 2013 Q2 and consists of the ECB's policy rate, inflation rate, real output growth and potential output growth in the euro area. To account for forward-looking decision making in the interest rate rule, the data consists of expectations about future inflation and output dynamics. While potential output is constructed based on data from the European Commission's annual macro-economic database, inflation and real output growth are taken from two different sources both provided by the ECB: the Survey of Professional Forecasters and projections made by ECB staff. Careful attention was given to the publication date of the collected data to ensure a real-time dataset only consisting of information which was available to the decision makers at the time of the decision.
Real-time estimation of wildfire perimeters from curated crowdsourcing
Zhong, Xu; Duckham, Matt; Chong, Derek; Tolhurst, Kevin
2016-04-01
Real-time information about the spatial extents of evolving natural disasters, such as wildfire or flood perimeters, can assist both emergency responders and the general public during an emergency. However, authoritative information sources can suffer from bottlenecks and delays, while user-generated social media data usually lacks the necessary structure and trustworthiness for reliable automated processing. This paper describes and evaluates an automated technique for real-time tracking of wildfire perimeters based on publicly available “curated” crowdsourced data about telephone calls to the emergency services. Our technique is based on established data mining tools, and can be adjusted using a small number of intuitive parameters. Experiments using data from the devastating Black Saturday wildfires (2009) in Victoria, Australia, demonstrate the potential for the technique to detect and track wildfire perimeters automatically, in real time, and with moderate accuracy. Accuracy can be further increased through combination with other authoritative demographic and environmental information, such as population density and dynamic wind fields. These results are also independently validated against data from the more recent 2014 Mickleham-Dalrymple wildfires.
Menegaldo, Luciano L
2017-12-01
State-space control of myoelectric devices and real-time visualization of muscle forces in virtual rehabilitation require measuring or estimating muscle dynamic states: neuromuscular activation, tendon force and muscle length. This paper investigates whether regular (KF) and extended Kalman filters (eKF), derived directly from Hill-type muscle mechanics equations, can be used as real-time muscle state estimators for isometric contractions using raw electromyography signals (EMG) as the only available measurement. The estimators' amplitude error, computational cost, filtering lags and smoothness are compared with usual EMG-driven analysis, performed offline, by integrating the nonlinear Hill-type muscle model differential equations (offline simulations-OS). EMG activity of the three triceps surae components (soleus, gastrocnemius medialis and gastrocnemius lateralis), in three torque levels, was collected for ten subjects. The actualization interval (AI) between two updates of the KF and eKF was also varied. The results show that computational costs are significantly reduced (70x for KF and 17[Formula: see text] for eKF). The filtering lags presented sharp linear relationships with the AI (0-300 ms), depending on the state and activation level. Under maximum excitation, amplitude errors varied in the range 10-24% for activation, 5-8% for tendon force and 1.4-1.8% for muscle length, reducing linearly with the excitation level. Smoothness, measured by the ratio between the average standard variations of KF/eKF and OS estimations, was greatly reduced for activation but converged exponentially to 1 for the other states by increasing AI. Compared to regular KF, extended KF does not seem to improve estimation accuracy significantly. Depending on the particular application requirements, the most appropriate KF actualization interval can be selected.
Kropivnitskaya, Yelena; Tiampo, Kristy F.; Qin, Jinhui; Bauer, Michael A.
2017-06-01
Earthquake intensity is one of the key components of the decision-making process for disaster response and emergency services. Accurate and rapid intensity calculations can help to reduce total loss and the number of casualties after an earthquake. Modern intensity assessment procedures handle a variety of information sources, which can be divided into two main categories. The first type of data is that derived from physical sensors, such as seismographs and accelerometers, while the second type consists of data obtained from social sensors, such as witness observations of the consequences of the earthquake itself. Estimation approaches using additional data sources or that combine sources from both data types tend to increase intensity uncertainty due to human factors and inadequate procedures for temporal and spatial estimation, resulting in precision errors in both time and space. Here we present a processing approach for the real-time analysis of streams of data from both source types. The physical sensor data is acquired from the U.S. Geological Survey (USGS) seismic network in California and the social sensor data is based on Twitter user observations. First, empirical relationships between tweet rate and observed Modified Mercalli Intensity (MMI) are developed using data from the M6.0 South Napa, CAF earthquake that occurred on August 24, 2014. Second, the streams of both data types are analyzed together in simulated real-time to produce one intensity map. The second implementation is based on IBM InfoSphere Streams, a cloud platform for real-time analytics of big data. To handle large processing workloads for data from various sources, it is deployed and run on a cloud-based cluster of virtual machines. We compare the quality and evolution of intensity maps from different data sources over 10-min time intervals immediately following the earthquake. Results from the joint analysis shows that it provides more complete coverage, with better accuracy and higher
Real Time Radiation Monitoring Using Nanotechnology
Li, Jing (Inventor); Hanratty, James J. (Inventor); Wilkins, Richard T. (Inventor); Lu, Yijiang (Inventor)
2016-01-01
System and method for monitoring receipt and estimating flux value, in real time, of incident radiation, using two or more nanostructures (NSs) and associated terminals to provide closed electrical paths and to measure one or more electrical property change values .DELTA.EPV, associated with irradiated NSs, during a sequence of irradiation time intervals. Effects of irradiation, without healing and with healing, of the NSs, are separately modeled for first order and second order healing. Change values.DELTA.EPV are related to flux, to cumulative dose received by NSs, and to radiation and healing effectivity parameters and/or.mu., associated with the NS material and to the flux. Flux and/or dose are estimated in real time, based on EPV change values, using measured .DELTA.EPV values. Threshold dose for specified changes of biological origin (usually undesired) can be estimated. Effects of time-dependent radiation flux are analyzed in pre-healing and healing regimes.
Litt, Jonathan S.; Simo, Donald L.
2007-01-01
This paper presents a preliminary demonstration of an automated health assessment tool, capable of real-time on-board operation using existing engine control hardware. The tool allows operators to discern how rapidly individual turboshaft engines are degrading. As the compressor erodes, performance is lost, and with it the ability to generate power. Thus, such a tool would provide an instant assessment of the engine s fitness to perform a mission, and would help to pinpoint any abnormal wear or performance anomalies before they became serious, thereby decreasing uncertainty and enabling improved maintenance scheduling. The research described in the paper utilized test stand data from a T700-GE-401 turboshaft engine that underwent sand-ingestion testing to scale a model-based compressor efficiency degradation estimation algorithm. This algorithm was then applied to real-time Health Usage and Monitoring System (HUMS) data from a T700-GE-701C to track compressor efficiency on-line. The approach uses an optimal estimator called a Kalman filter. The filter is designed to estimate the compressor efficiency using only data from the engine s sensors as input.
An MCMC Algorithm for Target Estimation in Real-Time DNA Microarrays
Directory of Open Access Journals (Sweden)
Vikalo Haris
2010-01-01
Full Text Available DNA microarrays detect the presence and quantify the amounts of nucleic acid molecules of interest. They rely on a chemical attraction between the target molecules and their Watson-Crick complements, which serve as biological sensing elements (probes. The attraction between these biomolecules leads to binding, in which probes capture target analytes. Recently developed real-time DNA microarrays are capable of observing kinetics of the binding process. They collect noisy measurements of the amount of captured molecules at discrete points in time. Molecular binding is a random process which, in this paper, is modeled by a stochastic differential equation. The target analyte quantification is posed as a parameter estimation problem, and solved using a Markov Chain Monte Carlo technique. In simulation studies where we test the robustness with respect to the measurement noise, the proposed technique significantly outperforms previously proposed methods. Moreover, the proposed approach is tested and verified on experimental data.
NUI framework based on real-time head pose estimation and hand gesture recognition
Directory of Open Access Journals (Sweden)
Kim Hyunduk
2016-01-01
Full Text Available The natural user interface (NUI is used for the natural motion interface without using device or tool such as mice, keyboards, pens and markers. In this paper, we develop natural user interface framework based on two recognition module. First module is real-time head pose estimation module using random forests and second module is hand gesture recognition module, named Hand gesture Key Emulation Toolkit (HandGKET. Using the head pose estimation module, we can know where the user is looking and what the user’s focus of attention is. Moreover, using the hand gesture recognition module, we can also control the computer using the user’s hand gesture without mouse and keyboard. In proposed framework, the user’s head direction and hand gesture are mapped into mouse and keyboard event, respectively.
Huo, Ming-Xia; Li, Ying
2017-12-01
Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.
Zakharchenko, V. D.; Kovalenko, I. G.
2014-05-01
A new method for the line-of-sight velocity estimation of a high-speed near-Earth object (asteroid, meteorite) is suggested. The method is based on the use of fractional, one-half order derivative of a Doppler signal. The algorithm suggested is much simpler and more economical than the classical one, and it appears preferable for use in orbital weapon systems of threat response. Application of fractional differentiation to quick evaluation of mean frequency location of the reflected Doppler signal is justified. The method allows an assessment of the mean frequency in the time domain without spectral analysis. An algorithm structure for the real-time estimation is presented. The velocity resolution estimates are made for typical asteroids in the X-band. It is shown that the wait time can be shortened by orders of magnitude compared with similar value in the case of a standard spectral processing.
Hládek, Ľuboš; Porr, Bernd; Brimijoin, W Owen
2018-01-01
The manuscript proposes and evaluates a real-time algorithm for estimating eye gaze angle based solely on single-channel electrooculography (EOG), which can be obtained directly from the ear canal using conductive ear moulds. In contrast to conventional high-pass filtering, we used an algorithm that calculates absolute eye gaze angle via statistical analysis of detected saccades. The estimated eye positions of the new algorithm were still noisy. However, the performance in terms of Pearson product-moment correlation coefficients was significantly better than the conventional approach in some instances. The results suggest that in-ear EOG signals captured with conductive ear moulds could serve as a basis for light-weight and portable horizontal eye gaze angle estimation suitable for a broad range of applications. For instance, for hearing aids to steer the directivity of microphones in the direction of the user's eye gaze.
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...
The IPERMOB System for Effective Real-Time Road Travel Time Measurement and Prediction
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...
Geomagnetic Observatory Data for Real-Time Applications
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
Hauschild, L; Lovatto, P A; Pomar, J; Pomar, C
2012-07-01
The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation
Directory of Open Access Journals (Sweden)
Ľuboš Hládek
Full Text Available The manuscript proposes and evaluates a real-time algorithm for estimating eye gaze angle based solely on single-channel electrooculography (EOG, which can be obtained directly from the ear canal using conductive ear moulds. In contrast to conventional high-pass filtering, we used an algorithm that calculates absolute eye gaze angle via statistical analysis of detected saccades. The estimated eye positions of the new algorithm were still noisy. However, the performance in terms of Pearson product-moment correlation coefficients was significantly better than the conventional approach in some instances. The results suggest that in-ear EOG signals captured with conductive ear moulds could serve as a basis for light-weight and portable horizontal eye gaze angle estimation suitable for a broad range of applications. For instance, for hearing aids to steer the directivity of microphones in the direction of the user's eye gaze.
Caprio, M.; Lancieri, M.; Cua, G. B.; Zollo, A.; Wiemer, S.
2011-01-01
We present an evolutionary approach for magnitude estimation for earthquake early warning based on real-time inversion of displacement spectra. The Spectrum Inversion (SI) method estimates magnitude and its uncertainty by inferring the shape of the entire displacement spectral curve based on the part of the spectra constrained by available data. The method consists of two components: 1) estimating seismic moment by finding the low frequency plateau Ω0, the corner frequency fc and attenuation factor (Q) that best fit the observed displacement spectra assuming a Brune ω2 model, and 2) estimating magnitude and its uncertainty based on the estimate of seismic moment. A novel characteristic of this method is that is does not rely on empirically derived relationships, but rather involves direct estimation of quantities related to the moment magnitude. SI magnitude and uncertainty estimates are updated each second following the initial P detection. We tested the SI approach on broadband and strong motion waveforms data from 158 Southern California events, and 25 Japanese events for a combined magnitude range of 3 ≤ M ≤ 7. Based on the performance evaluated on this dataset, the SI approach can potentially provide stable estimates of magnitude within 10 seconds from the initial earthquake detection.
Energy Technology Data Exchange (ETDEWEB)
Magaña Suarez, M.
2016-07-01
In this paper we will develop a methodology for estimating the percentage of free parking spaces available in the area of the city where a user is interested through a real-time query in a mobile app. The smartphone screen will provide a colour-coded map of the requested area that indicates the saturation state of the parking spaces. (Author)
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)
Real time freeway incident detection.
2014-04-01
The US Department of Transportation (US-DOT) estimates that over half of all congestion : events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time : incident detection on freeways is an important part of any mo...
A Novel Non-Iterative Method for Real-Time Parameter Estimation of the Fricke-Morse Model
Directory of Open Access Journals (Sweden)
SIMIC, M.
2016-11-01
Full Text Available Parameter estimation of Fricke-Morse model of biological tissue is widely used in bioimpedance data processing and analysis. Complex nonlinear least squares (CNLS data fitting is often used for parameter estimation of the model, but limitations such as high processing time, converging into local minimums, need for good initial guess of model parameters and non-convergence have been reported. Thus, there is strong motivation to develop methods which can solve these flaws. In this paper a novel real-time method for parameter estimation of Fricke-Morse model of biological cells is presented. The proposed method uses the value of characteristic frequency estimated from the measured imaginary part of bioimpedance, whereupon the Fricke-Morse model parameters are calculated using the provided analytical expressions. The proposed method is compared with CNLS in frequency ranges of 1 kHz to 10 MHz (beta-dispersion and 10 kHz to 100 kHz, which is more suitable for low-cost microcontroller-based bioimpedance measurement systems. The obtained results are promising, and in both frequency ranges, CNLS and the proposed method have accuracies suitable for most electrical bioimpedance (EBI applications. However, the proposed algorithm has significantly lower computation complexity, so it was 20-80 times faster than CNLS.
Mesin, Luca
2015-02-01
Developing a real time method to estimate generation, extinction and propagation of muscle fibre action potentials from bi-dimensional and high density surface electromyogram (EMG). A multi-frame generalization of an optical flow technique including a source term is considered. A model describing generation, extinction and propagation of action potentials is fit to epochs of surface EMG. The algorithm is tested on simulations of high density surface EMG (inter-electrode distance equal to 5mm) from finite length fibres generated using a multi-layer volume conductor model. The flow and source term estimated from interference EMG reflect the anatomy of the muscle, i.e. the direction of the fibres (2° of average estimation error) and the positions of innervation zone and tendons under the electrode grid (mean errors of about 1 and 2mm, respectively). The global conduction velocity of the action potentials from motor units under the detection system is also obtained from the estimated flow. The processing time is about 1 ms per channel for an epoch of EMG of duration 150 ms. A new real time image processing algorithm is proposed to investigate muscle anatomy and activity. Potential applications are proposed in prosthesis control, automatic detection of optimal channels for EMG index extraction and biofeedback. Copyright © 2014 Elsevier Ltd. All rights reserved.
The Implementation of a Real-Time Polyphase Filter
Adámek, Karel; Novotný, Jan; Armour, Wes
2014-01-01
In this article we study the suitability of dierent computational accelerators for the task of real-time data processing. The algorithm used for comparison is the polyphase filter, a standard tool in signal processing and a well established algorithm. We measure performance in FLOPs and execution time, which is a critical factor for real-time systems. For our real-time studies we have chosen a data rate of 6.5GB/s, which is the estimated data rate for a single channel on the SKAs Low Frequenc...
Estimating Net Realizable Value for Distressed Real Estate
James D. Shilling; John D. Benjamin; C.F. Sirmans
1990-01-01
This paper provides a framework for adjusting distressed real estate properties for liquidating discounts. We estimate the probability of receiving an offer on a property in any particular short interval of time. Our empirical evidence allows us to predict the average rate at which offers will occur in any particular interval of time. Further, it allows us to arrive at an estimate of net realizable value, adjusted for selling expenses.
Real-time video quality monitoring
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.
Liu, Kaizhan; Ye, Yunming; Li, Xutao; Li, Yan
2018-04-01
In recent years Convolutional Neural Network (CNN) has been widely used in computer vision field and makes great progress in lots of contents like object detection and classification. Even so, combining Convolutional Neural Network, which means making multiple CNN frameworks working synchronously and sharing their output information, could figure out useful message that each of them cannot provide singly. Here we introduce a method to real-time estimate speed of object by combining two CNN: YOLOv2 and FlowNet. In every frame, YOLOv2 provides object size; object location and object type while FlowNet providing the optical flow of whole image. On one hand, object size and object location help to select out the object part of optical flow image thus calculating out the average optical flow of every object. On the other hand, object type and object size help to figure out the relationship between optical flow and true speed by means of optics theory and priori knowledge. Therefore, with these two key information, speed of object can be estimated. This method manages to estimate multiple objects at real-time speed by only using a normal camera even in moving status, whose error is acceptable in most application fields like manless driving or robot vision.
Directory of Open Access Journals (Sweden)
Cédric Beaulac
2017-01-01
Full Text Available We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.
Real-time knee adduction moment feedback training using an elliptical trainer.
Kang, Sang Hoon; Lee, Song Joo; Ren, Yupeng; Zhang, Li-Qun
2014-03-01
The external knee adduction moment (EKAM) is associated with knee osteoarthritis (OA) in many aspects including presence, progression, and severity of knee OA. Despite of its importance, there is a lack of EKAM estimation methods that can provide patients with knee OA real-time EKAM biofeedback for training and clinical evaluations without using a motion analysis laboratory. A practical real-time EKAM estimation method, which utilizes kinematics measured by a simple six degree-of-freedom goniometer and kinetics measured by a multi-axis force sensor underneath the foot, was developed to provide real-time feedback of the EKAM to the patients during stepping on an elliptical trainer, which can potentially be used to control and alter the EKAM. High reliability (ICC(2,1): 0.9580) of the real-time EKAM estimation method was verified through stepping trials of seven subjects without musculoskeletal disorders. Combined with advantages of elliptical trainers including functional weight-bearing stepping and mitigation of impulsive forces, the real-time EKAM estimation method is expected to help patients with knee OA better control frontal plane knee loading and reduce knee OA development and progression.
Directory of Open Access Journals (Sweden)
Joseph T Wu
2011-10-01
Full Text Available In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR and severity.We tested 14,766 sera collected during the first wave of the 2009 pandemic in Hong Kong using viral microneutralization. We estimated IAR and infection-hospitalization probability (IHP from the serial cross-sectional serologic data and hospitalization data. Had our serologic data been available weekly in real time, we would have obtained reliable IHP estimates 1 wk after, 1-2 wk before, and 3 wk after epidemic peak for individuals aged 5-14 y, 15-29 y, and 30-59 y. The ratio of IAR to pre-existing seroprevalence, which decreased with age, was a major determinant for the timeliness of reliable estimates. If we began sero-surveillance 3 wk after community transmission was confirmed, with 150, 350, and 500 specimens per week for individuals aged 5-14 y, 15-19 y, and 20-29 y, respectively, we would have obtained reliable IHP estimates for these age groups 4 wk before the peak. For 30-59 y olds, even 800 specimens per week would not have generated reliable estimates until the peak because the ratio of IAR to pre-existing seroprevalence for this age group was low. The performance of serial cross-sectional sero-surveillance substantially deteriorates if test specificity is not near 100% or pre-existing seroprevalence is not near zero. These potential limitations could be mitigated by choosing a higher titer cutoff for seropositivity. If the epidemic doubling time is longer than 6 d, then serial cross-sectional sero-surveillance with 300 specimens per week would yield reliable estimates when IAR reaches around 6%-10%.Serial cross-sectional serologic data together with clinical surveillance data can allow reliable real-time estimates of IAR and
The use of best estimate codes to improve the simulation in real time
International Nuclear Information System (INIS)
Rivero, N.; Esteban, J. A.; Lenhardt, G.
2007-01-01
Best estimate codes are assumed to be the technology solution providing the most realistic and accurate response. Best estimate technology provides a complementary solution to the conservative simulation technology usually applied to determine plant safety margins and perform security related studies. Tecnatom in the early 90's, within the MAS project, pioneered the initiative to implement best estimate code in its training simulators. Result of this project was the implementation of the first six-equations thermal hydraulic code worldwide (TRAC R T), running in a training environment. To meet real time and other specific training requirements, it was necessary to overcome important difficulties. Tecnatom has just adapted the Global Nuclear Fuel core Design code: PANAC 11, and is about to complete the General Electric TRACG04 thermal hydraulic code adaptation. This technology features a unique solution for nuclear plants aiming at providing the highest fidelity in simulation, enabling to consider the simulator as a multipurpose: engineering and training, simulation platform. Besides, a visual environment designed to optimize the models life cycle, covering both pre and post-processing activities, is in its late development phase. (Author)
Erdogan, Eren; Schmidt, Michael; Seitz, Florian; Durmaz, Murat
2017-02-01
Although the number of terrestrial global navigation satellite system (GNSS) receivers supported by the International GNSS Service (IGS) is rapidly growing, the worldwide rather inhomogeneously distributed observation sites do not allow the generation of high-resolution global ionosphere products. Conversely, with the regionally enormous increase in highly precise GNSS data, the demands on (near) real-time ionosphere products, necessary in many applications such as navigation, are growing very fast. Consequently, many analysis centers accepted the responsibility of generating such products. In this regard, the primary objective of our work is to develop a near real-time processing framework for the estimation of the vertical total electron content (VTEC) of the ionosphere using proper models that are capable of a global representation adapted to the real data distribution. The global VTEC representation developed in this work is based on a series expansion in terms of compactly supported B-spline functions, which allow for an appropriate handling of the heterogeneous data distribution, including data gaps. The corresponding series coefficients and additional parameters such as differential code biases of the GNSS satellites and receivers constitute the set of unknown parameters. The Kalman filter (KF), as a popular recursive estimator, allows processing of the data immediately after acquisition and paves the way of sequential (near) real-time estimation of the unknown parameters. To exploit the advantages of the chosen data representation and the estimation procedure, the B-spline model is incorporated into the KF under the consideration of necessary constraints. Based on a preprocessing strategy, the developed approach utilizes hourly batches of GPS and GLONASS observations provided by the IGS data centers with a latency of 1 h in its current realization. Two methods for validation of the results are performed, namely the self consistency analysis and a comparison
Real-time sonography in obstetrics.
Anderson, S G
1978-03-01
Three hundred fifty real-time scans were performed on pregnant women for various indications. Placental localization was satisfactorily obtained in 173 of 174 studies. Estimates of fetal gestation from directly measured biparietal diameter were +/-2 weeks of actual gestation in 153 of 172 (88.9%) measurements. The presence or absence of fetal motion and cardiac activity established a diagnosis of fetal viability or fetal death in 32 patients after the first trimester. Accurate diagnosis was made in 52 of 57 patients with threatened abortions, and two of these errors occurred in scans performed before completion of the eighth postmenstrual week. Because of the ability to demonstrate fetal motion, real-time sonography should have many applications in obstetrics.
Output gap uncertainty and real-time monetary policy
Directory of Open Access Journals (Sweden)
Francesco Grigoli
2015-12-01
Full Text Available Output gap estimates are subject to a wide range of uncertainty owing principally to the difficulty in distinguishing between cycle and trend in real time. We show that country desks tend to overestimate economic slack, especially during recessions, and that uncertainty in initial output gap estimates persists several years. Only a small share of output gap revisions is predictable based on output dynamics, data quality, and policy frameworks. We also show that for a group of Latin American inflation targeters the prescriptions from monetary policy rules are subject to large changes due to revised output gap estimates. These explain a sizable proportion of the deviation of inflation from target, suggesting this information is not accounted for in real-time policy decisions.
International Nuclear Information System (INIS)
Blunden, A.; O'Prey, D.G.; Tait, W.H.
1983-01-01
A method is described for the separation of a composite pulse-height spectrum into its unresolved component parts, which belong to a set of measured library spectra. The method allows real-time estimation giving running estimates during acquisition of the spectrum, minimises computation space, especially for a number of parallel calculations, estimates in advance the rms errors, and produces a significance measure for the hypothesis that the composite contains only the library spectra. Least squares curve-fitting, and other methods, can be compared, with the formalism developed, allowing analytical comparison of the effect of detector energy resolution and detection efficiency. A rational basis for the choice between the various methods of spectrum analysis follows from the theory, minimising rms estimation errors. The method described is applicable for very low numbers of counts and poor resolution. (orig.)
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.
Criticality: static profiling for real-time programs
DEFF Research Database (Denmark)
Brandner, Florian; Hepp, Stefan; Jordan, Alexander
2014-01-01
With the increasing performance demand in real-time systems it becomes more and more important to provide feedback to programmers and software development tools on the performance-relevant code parts of a real-time program. So far, this information was limited to an estimation of the worst....... Experiments using well-established real-time benchmark programs show an interesting distribution of the criticality values, revealing considerable amounts of highly critical as well as uncritical code. The metric thus provides ideal information to programmers and software development tools to optimize...... view covering the entire code base, tools in the spirit of program profiling are required. This work proposes an efficient approach to compute worst-case timing information for all code parts of a program using a complementary metric, called criticality. Every statement of a program is assigned...
Oden, Timothy D.; Asquith, William H.; Milburn, Matthew S.
2009-01-01
In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the
Ying Ouyang; Theodor D. Leininger; Jeff Hatten
2013-01-01
Elevated phosphorus (P) in surface waters can cause eutrophication of aquatic ecosystems and can impair water for drinking, industry, agriculture, and recreation. Currently, no effort has been devoted to estimating real-time variation and load of total P (TP) in surface waters due to the lack of suitable and/or cost-effective wireless sensors. However, when considering...
Real-time reactor coolant system pressure/temperature limit system
International Nuclear Information System (INIS)
Newton, D.G.; Schemmel, R.R.; Van Scooter, W.E. Jr.
1991-01-01
This patent describes an system, used in controlling the operating of a nuclear reactor coolant system, which automatically calculates and displays allowable reactor coolant system pressure/temperature limits within the nuclear reactor coolant system based upon real-time inputs. It comprises: means for producing signals representative of real-time operating parameters of the nuclear reactor cooling system; means for developing pressure and temperature limits relating the real-time operating parameters of the nuclear reactor coolant system, for normal and emergency operation thereof; means for processing the signals representative of real-time operating parameters of the nuclear reactor coolant system to perform calculations of a best estimate of signals, check manual inputs against permissible valves and test data acquisition hardware for validity and over/under range; and means for comparing the representative signals with limits for the real-time operating parameters to produce a signal for a real-time display of the pressure and temperature limits and of the real-time operating parameters use an operator in controlling the operation of the nuclear reactor coolant system
Real Time Precise Point Positioning: Preliminary Results for the Brazilian Region
Marques, Haroldo; Monico, João.; Hirokazu Shimabukuro, Milton; Aquino, Marcio
2010-05-01
GNSS positioning can be carried out in relative or absolute approach. In the last years, more attention has been driven to the real time precise point positioning (PPP). To achieve centimeter accuracy with this method in real time it is necessary to have available the satellites precise coordinates as well as satellites clocks corrections. The coordinates can be used from the predicted IGU ephemeris, but the satellites clocks must be estimated in a real time. It can be made from a GNSS network as can be seen from EUREF Permanent Network. The infra-structure to realize the PPP in real time is being available in Brazil through the Brazilian Continuous Monitoring Network (RBMC) together with the Sao Paulo State GNSS network which are transmitting GNSS data using NTRIP (Networked Transport of RTCM via Internet Protocol) caster. Based on this information it was proposed a PhD thesis in the Univ. Estadual Paulista (UNESP) aiming to investigate and develop the methodology to estimate the satellites clocks and realize PPP in real time. Then, software is being developed to process GNSS data in the real time PPP mode. A preliminary version of the software was called PPP_RT and is able to process GNSS code and phase data using precise ephemeris and satellites clocks. The PPP processing can be accomplished considering the absolute satellite antenna Phase Center Variation (PCV), Ocean Tide Loading (OTL), Earth Body Tide, among others. The first order ionospheric effects can be eliminated or minimized by ion-free combination or parameterized in the receiver-satellite direction using a stochastic process, e.g. random walk or white noise. In the case of ionosphere estimation, a pseudo-observable is introduced in the mathematical model for each satellite and the initial value can be computed from Klobuchar model or from Global Ionospheric Map (GIM). The adjustment is realized in the recursive mode and the DIA (Detection Identification and Adaptation) is used for quality control. In
Progress in using real-time GPS for seismic monitoring of the Cascadia megathrust
Szeliga, W. M.; Melbourne, T. I.; Santillan, V. M.; Scrivner, C.; Webb, F.
2014-12-01
We report on progress in our development of a comprehensive real-time GPS-based seismic monitoring system for the Cascadia subduction zone. This system is based on 1 Hz point position estimates computed in the ITRF08 reference frame. Convergence from phase and range observables to point position estimates is accelerated using a Kalman filter based, on-line stream editor. Positions are estimated using a short-arc approach and algorithms from JPL's GIPSY-OASIS software with satellite clock and orbit products from the International GNSS Service (IGS). The resulting positions show typical RMS scatter of 2.5 cm in the horizontal and 5 cm in the vertical with latencies below 2 seconds. To facilitate the use of these point position streams for applications such as seismic monitoring, we broadcast real-time positions and covariances using custom-built streaming software. This software is capable of buffering 24-hour streams for hundreds of stations and providing them through a REST-ful web interface. To demonstrate the power of this approach, we have developed a Java-based front-end that provides a real-time visual display of time-series, vector displacement, and contoured peak ground displacement. We have also implemented continuous estimation of finite fault slip along the Cascadia megathrust using an NIF approach. The resulting continuous slip distributions are combined with pre-computed tsunami Green's functions to generate real-time tsunami run-up estimates for the entire Cascadia coastal margin. This Java-based front-end is available for download through the PANGA website. We currently analyze 80 PBO and PANGA stations along the Cascadia margin and are gearing up to process all 400+ real-time stations operating in the Pacific Northwest, many of which are currently telemetered in real-time to CWU. These will serve as milestones towards our over-arching goal of extending our processing to include all of the available real-time streams from the Pacific rim. In addition
International Nuclear Information System (INIS)
Tehrani, Joubin Nasehi; O’Brien, Ricky T; Keall, Paul; Poulsen, Per Rugaard
2013-01-01
Previous studies have shown that during cancer radiotherapy a small translation or rotation of the tumor can lead to errors in dose delivery. Current best practice in radiotherapy accounts for tumor translations, but is unable to address rotation due to a lack of a reliable real-time estimate. We have developed a method based on the iterative closest point (ICP) algorithm that can compute rotation from kilovoltage x-ray images acquired during radiation treatment delivery. A total of 11 748 kilovoltage (kV) images acquired from ten patients (one fraction for each patient) were used to evaluate our tumor rotation algorithm. For each kV image, the three dimensional coordinates of three fiducial markers inside the prostate were calculated. The three dimensional coordinates were used as input to the ICP algorithm to calculate the real-time tumor rotation and translation around three axes. The results show that the root mean square error was improved for real-time calculation of tumor displacement from a mean of 0.97 mm with the stand alone translation to a mean of 0.16 mm by adding real-time rotation and translation displacement with the ICP algorithm. The standard deviation (SD) of rotation for the ten patients was 2.3°, 0.89° and 0.72° for rotation around the right–left (RL), anterior–posterior (AP) and superior–inferior (SI) directions respectively. The correlation between all six degrees of freedom showed that the highest correlation belonged to the AP and SI translation with a correlation of 0.67. The second highest correlation in our study was between the rotation around RL and rotation around AP, with a correlation of −0.33. Our real-time algorithm for calculation of rotation also confirms previous studies that have shown the maximum SD belongs to AP translation and rotation around RL. ICP is a reliable and fast algorithm for estimating real-time tumor rotation which could create a pathway to investigational clinical treatment studies requiring
Real-time systems design and analysis
Laplante, Phillip A
2004-01-01
"Real-Time Systems Design and Analysis, Third Edition is essential for students and practicing software engineers who want improved designs, faster computation, and ultimate cost savings. Chapters discuss hardware considerations and software requirements, software systems design, the software production process, performance estimation and optimization, and engineering considerations."--Jacket.
Parameter Estimation in Continuous Time Domain
Directory of Open Access Journals (Sweden)
Gabriela M. ATANASIU
2016-12-01
Full Text Available This paper will aim to presents the applications of a continuous-time parameter estimation method for estimating structural parameters of a real bridge structure. For the purpose of illustrating this method two case studies of a bridge pile located in a highly seismic risk area are considered, for which the structural parameters for the mass, damping and stiffness are estimated. The estimation process is followed by the validation of the analytical results and comparison with them to the measurement data. Further benefits and applications for the continuous-time parameter estimation method in civil engineering are presented in the final part of this paper.
Real-Time Tropospheric Product Establishment and Accuracy Assessment in China
Chen, M.; Guo, J.; Wu, J.; Song, W.; Zhang, D.
2018-04-01
Tropospheric delay has always been an important issue in Global Navigation Satellite System (GNSS) processing. Empirical tropospheric delay models are difficult to simulate complex and volatile atmospheric environments, resulting in poor accuracy of the empirical model and difficulty in meeting precise positioning demand. In recent years, some scholars proposed to establish real-time tropospheric product by using real-time or near-real-time GNSS observations in a small region, and achieved some good results. This paper uses real-time observing data of 210 Chinese national GNSS reference stations to estimate the tropospheric delay, and establishes ZWD grid model in the country wide. In order to analyze the influence of tropospheric grid product on wide-area real-time PPP, this paper compares the method of taking ZWD grid product as a constraint with the model correction method. The results show that the ZWD grid product estimated based on the national reference stations can improve PPP accuracy and convergence speed. The accuracy in the north (N), east (E) and up (U) direction increase by 31.8 %,15.6 % and 38.3 %, respectively. As with the convergence speed, the accuracy of U direction experiences the most improvement.
Real-time stylistic prediction for whole-body human motions.
Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun
2012-01-01
The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Silvia Barbetta
2016-10-01
Full Text Available This work presents the application of the multi-temporal approach of the Model Conditional Processor (MCP-MT for predictive uncertainty (PU estimation in the Godavari River basin, India. MCP-MT is developed for making probabilistic Bayesian decision. It is the most appropriate approach if the uncertainty of future outcomes is to be considered. It yields the best predictive density of future events and allows determining the probability that a critical warning threshold may be exceeded within a given forecast time. In Bayesian decision-making, the predictive density represents the best available knowledge on a future event to address a rational decision-making process. MCP-MT has already been tested for case studies selected in Italian river basins, showing evidence of improvement of the effectiveness of operative real-time flood forecasting systems. The application of MCP-MT for two river reaches selected in the Godavari River basin, India, is here presented and discussed by considering the stage forecasts provided by a deterministic model, STAFOM-RCM, and hourly dataset based on seven monsoon seasons in the period 2001–2010. The results show that the PU estimate is useful for finding the exceedance probability for a given hydrometric threshold as function of the forecast time up to 24 h, demonstrating the potential usefulness for supporting real-time decision-making. Moreover, the expected value provided by MCP-MT yields better results than the deterministic model predictions, with higher Nash–Sutcliffe coefficients and lower error on stage forecasts, both in term of mean error and standard deviation and root mean square error.
Estimation of total bacteria by real-time PCR in patients with periodontal disease.
Brajović, Gavrilo; Popović, Branka; Puletić, Miljan; Kostić, Marija; Milasin, Jelena
2016-01-01
Periodontal diseases are associated with the presence of elevated levels of bacteria within the gingival crevice. The aim of this study was to evaluate a total amount of bacteria in subgingival plaque samples in patients with a periodontal disease. A quantitative evaluation of total bacteria amount using quantitative real-time polymerase chain reaction (qRT-PCR) was performed on 20 samples of patients with ulceronecrotic periodontitis and on 10 samples of healthy subjects. The estimation of total bacterial amount was based on gene copy number for 16S rRNA that was determined by comparing to Ct values/gene copy number of the standard curve. A statistically significant difference between average gene copy number of total bacteria in periodontal patients (2.55 x 10⁷) and healthy control (2.37 x 10⁶) was found (p = 0.01). Also, a trend of higher numbers of the gene copy in deeper periodontal lesions (> 7 mm) was confirmed by a positive value of coefficient of correlation (r = 0.073). The quantitative estimation of total bacteria based on gene copy number could be an important additional tool in diagnosing periodontitis.
Real-time approaches to the estimation of local wind velocity for a fixed-wing unmanned air vehicle
International Nuclear Information System (INIS)
Chan, W L; Lee, C S; Hsiao, F B
2011-01-01
Three real-time approaches to estimating local wind velocity for a fixed-wing unmanned air vehicle are presented in this study. All three methods work around the navigation equations with added wind components. The first approach calculates the local wind speed by substituting the ground speed and ascent rate data given by the Global Positioning System (GPS) into the navigation equations. The second and third approaches utilize the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), respectively. The results show that, despite the nonlinearity of the navigation equations, the EKF performance is proven to be on a par with the UKF. A time-varying noise estimation method based on the Wiener filter is also discussed. Results are compared with the average wind speed measured on the ground. All three approaches are proven to be reliable with stated advantages and disadvantages
Real time loss detection for SNM in process
International Nuclear Information System (INIS)
Candy, J.V.; Dunn, D.R.; Gavel, D.T.
1980-01-01
This paper discusses the basis of a design for real time special nuclear material (SNM) loss detectors. The design utilizes process measurements and signal processing techniques to produce a timely estimate of material loss. A state estimator is employed as the primary signal processing algorithm. Material loss is indicated by changes in the states or process innovations (residuals). The design philosophy is discussed in the context of these changes
Baygin, Mehmet; Karakose, Mehmet
2013-01-01
Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.
Directory of Open Access Journals (Sweden)
Mehmet Baygin
2013-01-01
Full Text Available Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.
Directory of Open Access Journals (Sweden)
Liang Gong
2013-01-01
Full Text Available Online monitoring of the instantaneous resistance variation during the A.C. resistance spot welding is of paramount importance for the weld quality control. On the basis of the welding transformer circuit model, a new method is proposed to measure the transformer primary-side signal for estimating the secondary-side resistance in each 1/4 cycle. The tailored computing system ensures that the measuring method possesses a real-time computational capacity with satisfying accuracy. Since the dynamic resistance cannot be represented via an explicit function with respect to measurable parameters from the primary side of the welding transformer, an offline trained embedded artificial neural network (ANN successfully realizes the real-time implicit function calculation or estimation. A DSP-based resistance spot welding monitoring system is developed to perform ANN computation. Experimental results indicate that the proposed method is applicable for measuring the dynamic resistance in single-phase, half-wave controlled rectifier circuits.
Real-time sensor failure detection by dynamic modelling of a PWR plant
International Nuclear Information System (INIS)
Turkcan, E.; Ciftcioglu, O.
1992-06-01
Signal validation and sensor failure detection is an important problem in real-time nuclear power plant (NPP) surveillance. Although conventional sensor redundancy, in a way, is a solution, identification of faulty sensor is necessary for further preventive actions to be taken. A comprehensive solution for the system so that any sensory reading is verified by its model based estimated counterpart, in real-time. Such a realization is accomplished by means of dynamic system's states estimation methodology using Kalman filter modelling technique. The method is investigated by means of real-time data of the steam generator of Borssele nuclear power plant and the method has proved to be satisfactory for real-time sensor failure detection as well as model validation verification. (author). 5 refs.; 6 figs.; 1 tab
Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation
Directory of Open Access Journals (Sweden)
Gergely Takács
2014-01-01
Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.
Accurate estimation of indoor travel times
DEFF Research Database (Denmark)
Prentow, Thor Siiger; Blunck, Henrik; Stisen, Allan
2014-01-01
The ability to accurately estimate indoor travel times is crucial for enabling improvements within application areas such as indoor navigation, logistics for mobile workers, and facility management. In this paper, we study the challenges inherent in indoor travel time estimation, and we propose...... the InTraTime method for accurately estimating indoor travel times via mining of historical and real-time indoor position traces. The method learns during operation both travel routes, travel times and their respective likelihood---both for routes traveled as well as for sub-routes thereof. InTraTime...... allows to specify temporal and other query parameters, such as time-of-day, day-of-week or the identity of the traveling individual. As input the method is designed to take generic position traces and is thus interoperable with a variety of indoor positioning systems. The method's advantages include...
Multivariate performance reliability prediction in real-time
International Nuclear Information System (INIS)
Lu, S.; Lu, H.; Kolarik, W.J.
2001-01-01
This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique
A real-time computational model for estimating kinematics of ankle ligaments.
Zhang, Mingming; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Quan
2016-01-01
An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot-ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.
Near-real-time Estimation and Forecast of Total Precipitable Water in Europe
Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.
2013-12-01
Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so
Methodology for Time-Domain Estimation of Storm-Time Electric Fields Using the 3D Earth Impedance
Kelbert, A.; Balch, C. C.; Pulkkinen, A. A.; Egbert, G. D.; Love, J. J.; Rigler, E. J.; Fujii, I.
2016-12-01
Magnetic storms can induce geoelectric fields in the Earth's electrically conducting interior, interfering with the operations of electric-power grid industry. The ability to estimate these electric fields at Earth's surface in close to real-time and to provide local short-term predictions would improve the ability of the industry to protect their operations. At any given time, the electric field at the Earth's surface is a function of the time-variant magnetic activity (driven by the solar wind), and the local electrical conductivity structure of the Earth's crust and mantle. For this reason, implementation of an operational electric field estimation service requires an interdisciplinary, collaborative effort between space science, real-time space weather operations, and solid Earth geophysics. We highlight in this talk an ongoing collaboration between USGS, NOAA, NASA, Oregon State University, and the Japan Meteorological Agency, to develop algorithms that can be used for scenario analyses and which might be implemented in a real-time, operational setting. We discuss the development of a time domain algorithm that employs discrete time domain representation of the impedance tensor for a realistic 3D Earth, known as the discrete time impulse response (DTIR), convolved with the local magnetic field time series, to estimate the local electric field disturbances. The algorithm is validated against measured storm-time electric field data collected in the United States and Japan. We also discuss our plans for operational real-time electric field estimation using 3D Earth impedances.
Real-time motion-adaptive-optimization (MAO) in TomoTherapy
Energy Technology Data Exchange (ETDEWEB)
Lu Weiguo; Chen Mingli; Ruchala, Kenneth J; Chen Quan; Olivera, Gustavo H [TomoTherapy Inc., 1240 Deming Way, Madison, WI (United States); Langen, Katja M; Kupelian, Patrick A [MD Anderson Cancer Center-Orlando, Orlando, FL (United States)], E-mail: wlu@tomotherapy.com
2009-07-21
IMRT delivery follows a planned leaf sequence, which is optimized before treatment delivery. However, it is hard to model real-time variations, such as respiration, in the planning procedure. In this paper, we propose a negative feedback system of IMRT delivery that incorporates real-time optimization to account for intra-fraction motion. Specifically, we developed a feasible workflow of real-time motion-adaptive-optimization (MAO) for TomoTherapy delivery. TomoTherapy delivery is characterized by thousands of projections with a fast projection rate and ultra-fast binary leaf motion. The technique of MAO-guided delivery calculates (i) the motion-encoded dose that has been delivered up to any given projection during the delivery and (ii) the future dose that will be delivered based on the estimated motion probability and future fluence map. These two pieces of information are then used to optimize the leaf open time of the upcoming projection right before its delivery. It consists of several real-time procedures, including 'motion detection and prediction', 'delivered dose accumulation', 'future dose estimation' and 'projection optimization'. Real-time MAO requires that all procedures are executed in time less than the duration of a projection. We implemented and tested this technique using a TomoTherapy (registered) research system. The MAO calculation took about 100 ms per projection. We calculated and compared MAO-guided delivery with two other types of delivery, motion-without-compensation delivery (MD) and static delivery (SD), using simulated 1D cases, real TomoTherapy plans and the motion traces from clinical lung and prostate patients. The results showed that the proposed technique effectively compensated for motion errors of all test cases. Dose distributions and DVHs of MAO-guided delivery approached those of SD, for regular and irregular respiration with a peak-to-peak amplitude of 3 cm, and for medium and large
Real-time motion-adaptive-optimization (MAO) in TomoTherapy
International Nuclear Information System (INIS)
Lu Weiguo; Chen Mingli; Ruchala, Kenneth J; Chen Quan; Olivera, Gustavo H; Langen, Katja M; Kupelian, Patrick A
2009-01-01
IMRT delivery follows a planned leaf sequence, which is optimized before treatment delivery. However, it is hard to model real-time variations, such as respiration, in the planning procedure. In this paper, we propose a negative feedback system of IMRT delivery that incorporates real-time optimization to account for intra-fraction motion. Specifically, we developed a feasible workflow of real-time motion-adaptive-optimization (MAO) for TomoTherapy delivery. TomoTherapy delivery is characterized by thousands of projections with a fast projection rate and ultra-fast binary leaf motion. The technique of MAO-guided delivery calculates (i) the motion-encoded dose that has been delivered up to any given projection during the delivery and (ii) the future dose that will be delivered based on the estimated motion probability and future fluence map. These two pieces of information are then used to optimize the leaf open time of the upcoming projection right before its delivery. It consists of several real-time procedures, including 'motion detection and prediction', 'delivered dose accumulation', 'future dose estimation' and 'projection optimization'. Real-time MAO requires that all procedures are executed in time less than the duration of a projection. We implemented and tested this technique using a TomoTherapy (registered) research system. The MAO calculation took about 100 ms per projection. We calculated and compared MAO-guided delivery with two other types of delivery, motion-without-compensation delivery (MD) and static delivery (SD), using simulated 1D cases, real TomoTherapy plans and the motion traces from clinical lung and prostate patients. The results showed that the proposed technique effectively compensated for motion errors of all test cases. Dose distributions and DVHs of MAO-guided delivery approached those of SD, for regular and irregular respiration with a peak-to-peak amplitude of 3 cm, and for medium and large prostate motions. The results conceptually
Energy Technology Data Exchange (ETDEWEB)
Lee, Jung Uk [Samsung Electroics, Suwon (Korea, Republic of); Sun, Ju Young; Won, Mooncheol [Chungnam Nat' l Univ., Daejeon (Korea, Republic of)
2013-12-15
In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner.
International Nuclear Information System (INIS)
Lee, Jung Uk; Sun, Ju Young; Won, Mooncheol
2013-01-01
In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner
Upgrade of the COMPASS tokamak real-time control system
Energy Technology Data Exchange (ETDEWEB)
Janky, F., E-mail: filip.janky.work@gmail.com [Institute of Plasma Physics, AS CR, v.v.i., Association EURATOM/IPP.CR, Za Slovankou 3, 18200 Prague (Czech Republic); Charles University in Prague, Faculty of Mathematics and Physics, V Holesovickach 2, 18000 Prague (Czech Republic); Havlicek, J. [Institute of Plasma Physics, AS CR, v.v.i., Association EURATOM/IPP.CR, Za Slovankou 3, 18200 Prague (Czech Republic); Charles University in Prague, Faculty of Mathematics and Physics, V Holesovickach 2, 18000 Prague (Czech Republic); Batista, A.J.N. [Associação EURATOM/IST, Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade Técnica de Lisboa, 1049-001 Lisboa (Portugal); Kudlacek, O.; Seidl, J. [Institute of Plasma Physics, AS CR, v.v.i., Association EURATOM/IPP.CR, Za Slovankou 3, 18200 Prague (Czech Republic); Neto, A.C. [Associação EURATOM/IST, Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade Técnica de Lisboa, 1049-001 Lisboa (Portugal); Pipek, J.; Hron, M. [Institute of Plasma Physics, AS CR, v.v.i., Association EURATOM/IPP.CR, Za Slovankou 3, 18200 Prague (Czech Republic); Mikulin, O. [Institute of Plasma Physics, AS CR, v.v.i., Association EURATOM/IPP.CR, Za Slovankou 3, 18200 Prague (Czech Republic); Czech Technical University, Faculty of Nuclear Sciences and Physical Engineering, V Holesovickach 2, 18000 Prague (Czech Republic); and others
2014-03-15
Highlights: • An upgrade of the COMPASS real-time system has been made to generally improve the plasma performance. • Stability of discharges in SNT configuration has been increased. • Plasma flat-top phase length has been extended. • Central solenoid protection has been developed. • Plasma position estimation has been improved. - Abstract: The COMPASS plasma control system is based on the MARTe real-time framework. Thanks to MARTe modularity and flexibility new algorithms have been developed for plasma diagnostic (plasma position calculation), control (shaping field control), and protection systems (central solenoid protection). Moreover, the MARTe framework itself was modified to broaden the communication capabilities via Aurora. This paper presents the recent upgrades and improvements made to the COMPASS real-time plasma control system, focusing on the issues related to precision of the real-time calculations, and discussing the improvements in terms of discharge parameters and stability. In particular, the new real-time system has given the possibility to analyze and to minimize the transport delays of each control loop.
Real-Time Audio Processing on the T-CREST Multicore Platform
DEFF Research Database (Denmark)
Ausin, Daniel Sanz; Pezzarossa, Luca; Schoeberl, Martin
2017-01-01
of the audio signal. This paper presents a real-time multicore audio processing system based on the T-CREST platform. T-CREST is a time-predictable multicore processor for real-time embedded systems. Multiple audio effect tasks have been implemented, which can be connected together in different configurations...... forming sequential and parallel effect chains, and using a network-onchip for intercommunication between processors. The evaluation of the system shows that real-time processing of multiple effect configurations is possible, and that the estimation and control of latency ensures real-time behavior.......Multicore platforms are nowadays widely used for audio processing applications, due to the improvement of computational power that they provide. However, some of these systems are not optimized for temporally constrained environments, which often leads to an undesired increase in the latency...
Novel Real-Time Flight Envelope Monitoring System, Phase II
National Aeronautics and Space Administration — The proposed innovation is an aircraft flight envelope monitoring system that will provide real-time in-cockpit estimations of aircraft flight envelope boundaries....
A real-time BWR stability measurement system
International Nuclear Information System (INIS)
March-Leuba, J.; King, W.T.
1988-01-01
This paper describes the characteristics of a portable, real-time system used for nonperturbational measurements of stability in boiling water reactors. The algorithm used in this system estimates the closed-loop asymptotic decay ratio using only the naturally occurring neutron noise and it is based on the univariate autoregressive methodology. (author)
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
Real time microcontroller implementation of an adaptive myoelectric filter.
Bagwell, P J; Chappell, P H
1995-03-01
This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.
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
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
Wang, Yearnchee Curtis; Chan, Terence Chee-Hung; Sahakian, Alan Varteres
2018-01-04
Radiofrequency ablation (RFA), a method of inducing thermal ablation (cell death), is often used to destroy tumours or potentially cancerous tissue. Current techniques for RFA estimation (electrical impedance tomography, Nakagami ultrasound, etc.) require long compute times (≥ 2 s) and measurement devices other than the RFA device. This study aims to determine if a neural network (NN) can estimate ablation lesion depth for control of bipolar RFA using complex electrical impedance - since tissue electrical conductivity varies as a function of tissue temperature - in real time using only the RFA therapy device's electrodes. Three-dimensional, cubic models comprised of beef liver, pork loin or pork belly represented target tissue. Temperature and complex electrical impedance from 72 data generation ablations in pork loin and belly were used for training the NN (403 s on Xeon processor). NN inputs were inquiry depth, starting complex impedance and current complex impedance. Training-validation-test splits were 70%-0%-30% and 80%-10%-10% (overfit test). Once the NN-estimated lesion depth for a margin reached the target lesion depth, RFA was stopped for that margin of tissue. The NN trained to 93% accuracy and an NN-integrated control ablated tissue to within 1.0 mm of the target lesion depth on average. Full 15-mm depth maps were calculated in 0.2 s on a single-core ARMv7 processor. The results show that a NN could make lesion depth estimations in real-time using less in situ devices than current techniques. With the NN-based technique, physicians could deliver quicker and more precise ablation therapy.
Real-Time Rotational Activity Detection in Atrial Fibrillation
Ríos-Muñoz, Gonzalo R.; Arenal, Ángel; Artés-Rodríguez, Antonio
2018-01-01
Rotational activations, or spiral waves, are one of the proposed mechanisms for atrial fibrillation (AF) maintenance. We present a system for assessing the presence of rotational activity from intracardiac electrograms (EGMs). Our system is able to operate in real-time with multi-electrode catheters of different topologies in contact with the atrial wall, and it is based on new local activation time (LAT) estimation and rotational activity detection methods. The EGM LAT estimation method is based on the identification of the highest sustained negative slope of unipolar signals. The method is implemented as a linear filter whose output is interpolated on a regular grid to match any catheter topology. Its operation is illustrated on selected signals and compared to the classical Hilbert-Transform-based phase analysis. After the estimation of the LAT on the regular grid, the detection of rotational activity in the atrium is done by a novel method based on the optical flow of the wavefront dynamics, and a rotation pattern match. The methods have been validated using in silico and real AF signals. PMID:29593566
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)
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....
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.)
Real-time LMR control parameter generation using advanced adaptive synthesis
International Nuclear Information System (INIS)
King, R.W.; Mott, J.E.
1990-01-01
The reactor ''delta T'', the difference between the average core inlet and outlet temperatures, for the liquid-sodium-cooled Experimental Breeder Reactor 2 is empirically synthesized in real time from, a multitude of examples of past reactor operation. The real-time empirical synthesis is based on reactor operation. The real-time empirical synthesis is based on system state analysis (SSA) technology embodied in software on the EBR 2 data acquisition computer. Before the real-time system is put into operation, a selection of reactor plant measurements is made which is predictable over long periods encompassing plant shutdowns, core reconfigurations, core load changes, and plant startups. A serial data link to a personal computer containing SSA software allows the rapid verification of the predictability of these plant measurements via graphical means. After the selection is made, the real-time synthesis provides a fault-tolerant estimate of the reactor delta T accurate to +/-1%. 5 refs., 7 figs
Determination of Uncalibrated Phase Delays for Real-Time PPP
Hinterberger, Fabian; Weber, Robert; Huber, Katrin; Lesjak, Roman
2014-05-01
Today PPP is a well-known technique of GNSS based positioning used for a wide range of post-processing applications. Using observations of a single GNSS receiver and applying precise orbit and clock information derived from global GNSS networks highly precise positions can be obtained. The atmospheric delays are usually mitigated by linear combination (ionosphere) and parameter estimation (troposphere). Within the last years also the demand for real-time PPP increased. In 2012, the IGS real-time working group started a pilot project to broadcast real-time precise orbits and clock correction streams. Nevertheless, real-time PPP is in its starting phase and currently only few applications make use of the technique although SSR-Messages are already implemented in RTCM3.1. The problems of still limited accuracy compared to Network-RTK as well as long convergence times might be solved by almost instantaneous integer ambiguity resolution at zero-difference level which is a major topic of current scientific investigations. Therefore a national consortium has carried out over the past 2 years the research project PPP-Serve (funded by the Austrian Research Promotion Agency - FFG), which aimed at the development of appropriate algorithms for real-time PPP with special emphasis on the ambiguity resolution of zero-difference observations. We have established a module which calculates based on GPS-reference station data-streams of a dense network (obtained from IGS via BKG) so-called wide-lane and narrow-lane satellite specific calibration phase delays. While the wide-lane phase delays are almost stable over longer periods, the estimation of narrow-lane phase delays has to be re-established every 24 hours. These phase-delays are submitted via a real-time module to the rover where they are used for point positioning via a PPP-model. This presentation deals with the process and obstacles of calculating the wide-lane and narrow-lane phase-delays (based on SD -observations between
Real Time MRI Motion Correction with Markerless Tracking
DEFF Research Database (Denmark)
Benjaminsen, Claus; Jensen, Rasmus Ramsbøl; Wighton, Paul
Prospective motion correction for MRI neuroimaging has been demonstrated using MR navigators and external tracking systems using markers. The drawbacks of these two motion estimation methods include prolonged scan time plus lack of compatibility with all image acquisitions, and difficulties...... validating marker attachment resulting in uncertain estimation of the brain motion respectively. We have developed a markerless tracking system, and in this work we demonstrate the use of our system for prospective motion correction, and show that despite being computationally demanding, markerless tracking...... can be implemented for real time motion correction....
Towards Real-Time, Nonintrusive Estimation of Driver Workload: A Simulator Study
van Gent, P.; Farah, H.; Nes, Nicole Van; van Arem, B.
2017-01-01
The aim of this research is to work towards building an open-source, platform-independent algorithm capable of predicting driver workload in real-time and in a non-intrusive way. To work towards a system that can also be implemented in on-road settings, we aimed at using off-the-shelf, non-intrusive
Resolving Peak Ground Displacements in Real-Time GNSS PPP Solutions
Hodgkinson, K. M.; Mencin, D.; Mattioli, G. S.; Sievers, C.; Fox, O.
2017-12-01
The goal of early earthquake warning (EEW) systems is to provide warning of impending ground shaking to the public, infrastructure managers, and emergency responders. Shaking intensity can be estimated using Ground Motion Prediction Equations (GMPEs), but only if site characteristics, hypocentral distance and event magnitude are known. In recent years work has been done analyzing the first few seconds of the seismic P wave to derive event location and magnitude. While initial rupture locations seem to be sufficiently constrained, it has been shown that P-wave magnitude estimates tend to saturate at M>7. Regions where major and great earthquakes occur may therefore be vulnerable to an underestimation of shaking intensity if only P waves magnitudes are used. Crowell et al., (2013) first demonstrated that Peak Ground Displacement (PGD) from long-period surface waves recorded by GNSS receivers could provide a source-scaling relation that does not saturate with event magnitude. GNSS PGD derived magnitudes could improve the accuracy of EEW GMPE calculations. If such a source-scaling method were to be implemented in EEW algorithms it is critical that the noise levels in real-time GNSS processed time-series are low enough to resolve long-period surface waves. UNAVCO currently operates 770 real-time GNSS sites, most of which are located along the North American-Pacific Plate Boundary. In this study, we present an analysis of noise levels observed in the GNSS Precise Point Positioning (PPP) solutions generated and distributed in real-time by UNAVCO for periods from seconds to hours. The analysis is performed using the 770 sites in the real-time network and data collected through July 2017. We compare noise levels determined from various monument types and receiver-antenna configurations. This analysis gives a robust estimation of noise levels in PPP solutions because the solutions analyzed are those that were generated in real-time and thus contain all the problems observed
Real-Time Tracking of Knee Adduction Moment in Patients with Knee Osteoarthritis
Kang, Sang Hoon; Lee, Song Joo; Zhang, Li-Qun
2014-01-01
Background The external knee adduction moment (EKAM) is closely associated with the presence, progression, and severity of knee osteoarthritis (OA). However, there is a lack of convenient and practical method to estimate and track in real-time the EKAM of patients with knee OA for clinical evaluation and gait training, especially outside of gait laboratories. New Method A real-time EKAM estimation method was developed and applied to track and investigate the EKAM and other knee moments during stepping on an elliptical trainer in both healthy subjects and a patient with knee OA. Results Substantial changes were observed in the EKAM and other knee moments during stepping in the patient with knee OA. Comparison with Existing Method(s) This is the first study to develop and test feasibility of real-time tracking method of the EKAM on patients with knee OA using 3-D inverse dynamics. Conclusions The study provides us an accurate and practical method to evaluate in real-time the critical EKAM associated with knee OA, which is expected to help us to diagnose and evaluate patients with knee OA and provide the patients with real-time EKAM feedback rehabilitation training. PMID:24361759
Wasza, Jakob; Bauer, Sebastian; Hornegger, Joachim
2012-01-01
Over the last years, range imaging (RI) techniques have been proposed for patient positioning and respiration analysis in motion compensation. Yet, current RI based approaches for patient positioning employ rigid-body transformations, thus neglecting free-form deformations induced by respiratory motion. Furthermore, RI based respiration analysis relies on non-rigid registration techniques with run-times of several seconds. In this paper we propose a real-time framework based on RI to perform respiratory motion compensated positioning and non-rigid surface deformation estimation in a joint manner. The core of our method are pre-procedurally obtained 4-D shape priors that drive the intra-procedural alignment of the patient to the reference state, simultaneously yielding a rigid-body table transformation and a free-form deformation accounting for respiratory motion. We show that our method outperforms conventional alignment strategies by a factor of 3.0 and 2.3 in the rotation and translation accuracy, respectively. Using a GPU based implementation, we achieve run-times of 40 ms.
Directory of Open Access Journals (Sweden)
Jianping Gao
2015-08-01
Full Text Available Accurate state of charge (SoC estimation of batteries plays an important role in promoting the commercialization of electric vehicles. The main work to be done in accurately determining battery SoC can be summarized in three parts. (1 In view of the model-based SoC estimation flow diagram, the n-order resistance-capacitance (RC battery model is proposed and expected to accurately simulate the battery’s major time-variable, nonlinear characteristics. Then, the mathematical equations for model parameter identification and SoC estimation of this model are constructed. (2 The Akaike information criterion is used to determine an optimal tradeoff between battery model complexity and prediction precision for the n-order RC battery model. Results from a comparative analysis show that the first-order RC battery model is thought to be the best based on the Akaike information criterion (AIC values. (3 The real-time joint estimator for the model parameter and SoC is constructed, and the application based on two battery types indicates that the proposed SoC estimator is a closed-loop identification system where the model parameter identification and SoC estimation are corrected mutually, adaptively and simultaneously according to the observer values. The maximum SoC estimation error is less than 1% for both battery types, even against the inaccurate initial SoC.
Comprehensive seismic monitoring of the Cascadia megathrust with real-time GPS
Melbourne, T. I.; Szeliga, W. M.; Santillan, V. M.; Scrivner, C. W.; Webb, F.
2013-12-01
We have developed a comprehensive real-time GPS-based seismic monitoring system for the Cascadia subduction zone based on 1- and 5-second point position estimates computed within the ITRF08 reference frame. A Kalman filter stream editor that uses a geometry-free combination of phase and range observables to speed convergence while also producing independent estimation of carrier phase biases and ionosphere delay pre-cleans raw satellite measurements. These are then analyzed with GIPSY-OASIS using satellite clock and orbit corrections streamed continuously from the International GNSS Service (IGS) and the German Aerospace Center (DLR). The resulting RMS position scatter is less than 3 cm, and typical latencies are under 2 seconds. Currently 31 coastal Washington, Oregon, and northern California stations from the combined PANGA and PBO networks are analyzed. We are now ramping up to include all of the remaining 400+ stations currently operating throughout the Cascadia subduction zone, all of which are high-rate and telemetered in real-time to CWU. These receivers span the M9 megathrust, M7 crustal faults beneath population centers, several active Cascades volcanoes, and a host of other hazard sources. To use the point position streams for seismic monitoring, we have developed an inter-process client communication package that captures, buffers and re-broadcasts real-time positions and covariances to a variety of seismic estimation routines running on distributed hardware. An aggregator ingests, re-streams and can rebroadcast up to 24 hours of point-positions and resultant seismic estimates derived from the point positions to application clients distributed across web. A suite of seismic monitoring applications has also been written, which includes position time series analysis, instantaneous displacement vectors, and peak ground displacement contouring and mapping. We have also implemented a continuous estimation of finite-fault slip along the Cascadia megathrust
Real-time interactive treatment planning
International Nuclear Information System (INIS)
Otto, Karl
2014-01-01
The goal of this work is to develop an interactive treatment planning platform that permits real-time manipulation of dose distributions including DVHs and other dose metrics. The hypothesis underlying the approach proposed here is that the process of evaluating potential dose distribution options and deciding on the best clinical trade-offs may be separated from the derivation of the actual delivery parameters used for the patient’s treatment. For this purpose a novel algorithm for deriving an Achievable Dose Estimate (ADE) was developed. The ADE algorithm is computationally efficient so as to update dose distributions in effectively real-time while accurately incorporating the limits of what can be achieved in practice. The resulting system is a software environment for interactive real-time manipulation of dose that permits the clinician to rapidly develop a fully customized 3D dose distribution. Graphical navigation of dose distributions is achieved by a sophisticated method of identifying contributing fluence elements, modifying those elements and re-computing the entire dose distribution. 3D dose distributions are calculated in ∼2–20 ms. Including graphics processing overhead, clinicians may visually interact with the dose distribution (e.g. ‘drag’ a DVH) and display updates of the dose distribution at a rate of more than 20 times per second. Preliminary testing on various sites shows that interactive planning may be completed in ∼1–5 min, depending on the complexity of the case (number of targets and OARs). Final DVHs are derived through a separate plan optimization step using a conventional VMAT planning system and were shown to be achievable within 2% and 4% in high and low dose regions respectively. With real-time interactive planning trade-offs between Target(s) and OARs may be evaluated efficiently providing a better understanding of the dosimetric options available to each patient in static or adaptive RT. (paper)
Process algebra with timing : real time and discrete time
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
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
Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.
2013-01-01
The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.
Seo, Dong-Jun; Siddique, Ridwan; Zhang, Yu; Kim, Dongsoo
2014-11-01
A new technique for gauge-only precipitation analysis for improved estimation of heavy-to-extreme precipitation is described and evaluated. The technique is based on a novel extension of classical optimal linear estimation theory in which, in addition to error variance, Type-II conditional bias (CB) is explicitly minimized. When cast in the form of well-known kriging, the methodology yields a new kriging estimator, referred to as CB-penalized kriging (CBPK). CBPK, however, tends to yield negative estimates in areas of no or light precipitation. To address this, an extension of CBPK, referred to herein as extended conditional bias penalized kriging (ECBPK), has been developed which combines the CBPK estimate with a trivial estimate of zero precipitation. To evaluate ECBPK, we carried out real-world and synthetic experiments in which ECBPK and the gauge-only precipitation analysis procedure used in the NWS's Multisensor Precipitation Estimator (MPE) were compared for estimation of point precipitation and mean areal precipitation (MAP), respectively. The results indicate that ECBPK improves hourly gauge-only estimation of heavy-to-extreme precipitation significantly. The improvement is particularly large for estimation of MAP for a range of combinations of basin size and rain gauge network density. This paper describes the technique, summarizes the results and shares ideas for future research.
Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application
Chen, Jinduan; Boccelli, Dominic L.
2018-02-01
Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.
Open-circuit respirometry: real-time, laboratory-based systems.
Ward, Susan A
2018-05-04
This review explores the conceptual and technological factors integral to the development of laboratory-based, automated real-time open-circuit mixing-chamber and breath-by-breath (B × B) gas-exchange systems, together with considerations of assumptions and limitations. Advances in sensor technology, signal analysis, and digital computation led to the emergence of these technologies in the mid-20th century, at a time when investigators were beginning to recognise the interpretational advantages of nonsteady-state physiological-system interrogation in understanding the aetiology of exercise (in)tolerance in health, sport, and disease. Key milestones include the 'Auchincloss' description of an off-line system to estimate alveolar O 2 uptake B × B during exercise. This was followed by the first descriptions of real-time automated O 2 uptake and CO 2 output B × B measurement by Beaver and colleagues and by Linnarsson and Lindborg, and mixing-chamber measurement by Wilmore and colleagues. Challenges to both approaches soon emerged: e.g., the influence of mixing-chamber washout kinetics on mixed-expired gas concentration determination, and B × B alignment of gas-concentration signals with respired flow. The challenging algorithmic and technical refinements required for gas-exchange estimation at the alveolar level have also been extensively explored. In conclusion, while the technology (both hardware and software) underpinning real-time automated gas-exchange measurement has progressively advanced, there are still concerns regarding accuracy especially under the challenging conditions of changing metabolic rate.
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
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.
Energy Technology Data Exchange (ETDEWEB)
Laurent, J.
2002-12-15
Today, power and energy consumption have become, as time and area, an important constraint when you design a system. Indeed modern applications use more and more processing and memory resources so these lead a significant increase of consumption. Furthermore, embedded software impact is preponderant in real time system so the code optimisation has a great impact onto the consumption constraint. Several research teams have already developed estimation methodologies for processor but almost are at instruction level (ILPA). With this kind of method you have to measure the consumption of each instruction of the instruction set and also the inter-instruction consumption overhead. For complex architecture, this kind of methodology is not adapted due to the prohibitive number of consumption measures. So the characterisation time of this kind of architecture is too important furthermore with this method is very difficult to take into account the external environment. For actual architecture another method is needed to reduce the characterisation time while preserving the accuracy. The reduction of the characterisation time have to be realized by increasing the abstraction level. So, we propose here a new approach based on a functional and architectural analysis of the target in consumption point of view (FLPA). Our methodology has two steps: the first one is a modeling step and the second is estimation step. (author)
Real-time estimation of differential piston at the LBT
Böhm, Michael; Pott, Jörg-Uwe; Sawodny, Oliver; Herbst, Tom; Kürster, Martin
2014-07-01
In this paper, we present and compare different strategies to minimize the effects of telescope vibrations to the differential piston (OPD) for LINC/NIRVANA at the LBT using an accelerometer feedforward compensation approach. We summarize why this technology is of importance for LINC/NIRVANA, but also for future telescopes and instruments. We outline the estimation problem in general and its specifics at the LBT. Model based estimation and broadband filtering techniques can be used to solve the estimation task, each having its own advantages and disadvantages, which will be discussed. Simulation results and measurements at the LBT are shown to motivate and support our choice of the estimation algorithm for the instrument LINC/NIRVANA. We explain our laboratory setup aimed at imitating the vibration behaviour at the LBT in general, and the M2 as main contributor in particular, and we demonstrate the controller's ability to suppress vibrations in the frequency range of 8 Hz to 60 Hz. In this range, telescope vibrations are the most dominant disturbance to the optical path. For our measurements, we introduce a disturbance time series which has a frequency spectrum comparable to what can be measured at the LBT on a typical night. We show promising experimental results, indicating the ability to suppress differential piston induced by telescope vibrations by a factor of about 5 (RMS), which is significantly better than any currently commissioned system.
On-orbit real-time magnetometer bias determination for micro-satellites without attitude information
Directory of Open Access Journals (Sweden)
Zhang Zhen
2015-10-01
Full Text Available Due to the disadvantages such as complex calculation, low accuracy of estimation, and being non real time in present methods, a new real-time algorithm is developed for on-orbit magnetometer bias determination of micro-satellites without attitude knowledge in this paper. This method uses the differential value approach. It avoids the impact of quartic nature and uses the iterative method to satisfy real-time applications. Simulation results indicate that the new real-time algorithm is more accurate compared with other methods, which are also tested by an experiment system using real noise data. With the new real-time algorithm, a magnetometer calibration can be taken on-orbit and will reduce the demand for computing power effectively.
FPGA-based architecture for motion recovering in real-time
Arias-Estrada, Miguel; Maya-Rueda, Selene E.; Torres-Huitzil, Cesar
2002-03-01
A key problem in the computer vision field is the measurement of object motion in a scene. The main goal is to compute an approximation of the 3D motion from the analysis of an image sequence. Once computed, this information can be used as a basis to reach higher level goals in different applications. Motion estimation algorithms pose a significant computational load for the sequential processors limiting its use in practical applications. In this work we propose a hardware architecture for motion estimation in real time based on FPGA technology. The technique used for motion estimation is Optical Flow due to its accuracy, and the density of velocity estimation, however other techniques are being explored. The architecture is composed of parallel modules working in a pipeline scheme to reach high throughput rates near gigaflops. The modules are organized in a regular structure to provide a high degree of flexibility to cover different applications. Some results will be presented and the real-time performance will be discussed and analyzed. The architecture is prototyped in an FPGA board with a Virtex device interfaced to a digital imager.
Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Todini, Ezio
2015-04-01
-Curve Model in Real Time (RCM-RT) (Barbetta and Moramarco, 2014) are used to this end. Both models without considering rainfall information explicitly considers, at each time of forecast, the estimate of lateral contribution along the river reach for which the stage forecast is performed at downstream end. The analysis is performed for several reaches using different lead times according to the channel length. Barbetta, S., Moramarco, T., Brocca, L., Franchini, M. and Melone, F. 2014. Confidence interval of real-time forecast stages provided by the STAFOM-RCM model: the case study of the Tiber River (Italy). Hydrological Processes, 28(3),729-743. Barbetta, S. and Moramarco, T. 2014. Real-time flood forecasting by relating local stage and remote discharge. Hydrological Sciences Journal, 59(9 ), 1656-1674. Coccia, G. and Todini, E. 2011. Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach. Hydrology and Earth System Sciences, 15, 3253-3274. doi:10.5194/hess-15-3253-2011. Krzysztofowicz, R. 1999. Bayesian theory of probabilistic forecasting via deterministic hydrologic model, Water Resour. Res., 35, 2739-2750. Todini, E. 2004. Role and treatment of uncertainty in real-time flood forecasting. Hydrological Processes 18(14), 2743_2746. Todini, E. 2008. A model conditional processor to assess predictive uncertainty in flood forecasting. Intl. J. River Basin Management, 6(2): 123-137.
Memory controllers for real-time embedded systems predictable and composable real-time systems
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...
Estimate of the real-time respiratory simulation system in cyberknife image-guided radiosurgery
International Nuclear Information System (INIS)
Min, Chul Kee; Chung, Weon Kuu; Lee, Suk
2010-01-01
The purpose of this study was to evaluate the target accuracy according to the movement with respiration of an actual patient in a quantitative way by developing a real-time respiratory simulation system (RRSS), including a patient customized 3D moving phantom. The real-time respiratory simulation system (RRSS) consists of two robots in order to implement both the movement of body surfaces and the movement of internal organs caused by respiration. The quantitative evaluation for the 3D movement of the RRSS was performed using a real-time laser displacement sensor for each axis. The average difference in the static movement of the RRSS was about 0.01 ∼ 0.06 mm. Also, in the evaluation of the dynamic movement by producing a formalized sine wave with the phase of four seconds per cycle, the difference between the measured and the calculated values for each cycle length in the robot that was in charge of body surfaces and the robot that was in charge of the movement of internal tumors showed 0.10 ∼ 0.55 seconds, and the correlation coefficients between the calculated and the measured values were 0.998 ∼ 0.999. The differences between the maximum and the minimum amplitudes were 0.01 ∼ 0.06 mm, and the reproducibility was within ±0.5 mm. In the case of the application and non-application of respiration, the target errors were -0.05 ∼ 1.05 mm and -0.13 ∼ 0.74 mm, respectively, and the entire target errors were 1.30 mm and 0.79 mm, respectively. Based on the accuracy in the RRSS system, various respiration patterns of patients can be reproduced in real-time. Also, this system can be used as an optimal tool for applying patient customized accuracy management in image-guided radiosurgery.
Estimate of the real-time respiratory simulation system in cyberknife image-guided radiosurgery
Energy Technology Data Exchange (ETDEWEB)
Min, Chul Kee [Konyang Univ. Hospital, Daejeon (Korea, Republic of); Kyonggi University, Seoul (Korea, Republic of); Chung, Weon Kuu [Konyang Univ. Hospital, Daejeon (Korea, Republic of); Lee, Suk [Korea University, Seoul (Korea, Republic of); and others
2010-01-15
The purpose of this study was to evaluate the target accuracy according to the movement with respiration of an actual patient in a quantitative way by developing a real-time respiratory simulation system (RRSS), including a patient customized 3D moving phantom. The real-time respiratory simulation system (RRSS) consists of two robots in order to implement both the movement of body surfaces and the movement of internal organs caused by respiration. The quantitative evaluation for the 3D movement of the RRSS was performed using a real-time laser displacement sensor for each axis. The average difference in the static movement of the RRSS was about 0.01 {approx} 0.06 mm. Also, in the evaluation of the dynamic movement by producing a formalized sine wave with the phase of four seconds per cycle, the difference between the measured and the calculated values for each cycle length in the robot that was in charge of body surfaces and the robot that was in charge of the movement of internal tumors showed 0.10 {approx} 0.55 seconds, and the correlation coefficients between the calculated and the measured values were 0.998 {approx} 0.999. The differences between the maximum and the minimum amplitudes were 0.01 {approx} 0.06 mm, and the reproducibility was within {+-}0.5 mm. In the case of the application and non-application of respiration, the target errors were -0.05 {approx} 1.05 mm and -0.13 {approx} 0.74 mm, respectively, and the entire target errors were 1.30 mm and 0.79 mm, respectively. Based on the accuracy in the RRSS system, various respiration patterns of patients can be reproduced in real-time. Also, this system can be used as an optimal tool for applying patient customized accuracy management in image-guided radiosurgery.
Real-time yield estimation based on deep learning
Rahnemoonfar, Maryam; Sheppard, Clay
2017-05-01
Crop yield estimation is an important task in product management and marketing. Accurate yield prediction helps farmers to make better decision on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on the manual counting of fruits is very time consuming and expensive process and it is not practical for big fields. Robotic systems including Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), provide an efficient, cost-effective, flexible, and scalable solution for product management and yield prediction. Recently huge data has been gathered from agricultural field, however efficient analysis of those data is still a challenging task. Computer vision approaches currently face diffident challenges in automatic counting of fruits or flowers including occlusion caused by leaves, branches or other fruits, variance in natural illumination, and scale. In this paper a novel deep convolutional network algorithm was developed to facilitate the accurate yield prediction and automatic counting of fruits and vegetables on the images. Our method is robust to occlusion, shadow, uneven illumination and scale. Experimental results in comparison to the state-of-the art show the effectiveness of our algorithm.
MonoSLAM: real-time single camera SLAM.
Davison, Andrew J; Reid, Ian D; Molton, Nicholas D; Stasse, Olivier
2007-06-01
We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to Structure from Motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera.
TerraSAR-X precise orbit determination with real-time GPS ephemerides
Wermuth, Martin; Hauschild, Andre; Montenbruck, Oliver; Kahle, Ralph
TerraSAR-X is a German Synthetic Aperture Radar (SAR) satellite, which was launched in June 2007 from Baikonour. Its task is to acquire radar images of the Earth's surface. In order to locate the radar data takes precisely, the satellite is equipped with a high-quality dual-frequency GPS receiver -the Integrated Geodetic and Occultation Receiver (IGOR) provided by the GeoForschungsZentrum Potsdam (GFZ). Using GPS observations from the IGOR instrument in a reduced dynamic precise orbit determination (POD), the German Space Operations Center (DLR/GSOC) is computing rapid and science orbit products on a routine basis. The rapid orbit products arrive with a latency of about one hour after data reception with an accuracy of 10-20 cm. Science orbit products are computed with a latency of five days achieving an accuracy of about 5cm (3D-RMS). For active and future Earth observation missions, the availability of near real-time precise orbit information is becoming more and more important. Other applications of near real-time orbit products include the processing of GNSS radio occulation measurements for atmospheric sounding as well as altimeter measurements of ocean surface heights, which are nowadays employed in global weather and ocean circulation models with short latencies. For example after natural disasters it is necessary to evaluate the damage by satellite images as soon as possible. The latency and quality of POD results is mainly driven by the availability of precise GPS ephemerides. In order to have high-quality GPS ephemerides available at real-time, GSOC has developed the real-time clock estimation system RETICLE. The system receives NTRIP-data streams with GNSS observations from the global tracking network of IGS in real-time. Using the known station position, RETICLE estimates precise GPS satellite clock offsets and drifts based on the most recent available IGU predicted orbits. The clock offset estimates have an accuracy of better than 0.3 ns and are
Pecha, Petr; Šmídl, Václav
2016-11-01
A stepwise sequential assimilation algorithm is proposed based on an optimisation approach for recursive parameter estimation and tracking of radioactive plume propagation in the early stage of a radiation accident. Predictions of the radiological situation in each time step of the plume propagation are driven by an existing short-term meteorological forecast and the assimilation procedure manipulates the model parameters to match the observations incoming concurrently from the terrain. Mathematically, the task is a typical ill-posed inverse problem of estimating the parameters of the release. The proposed method is designated as a stepwise re-estimation of the source term release dynamics and an improvement of several input model parameters. It results in a more precise determination of the adversely affected areas in the terrain. The nonlinear least-squares regression methodology is applied for estimation of the unknowns. The fast and adequately accurate segmented Gaussian plume model (SGPM) is used in the first stage of direct (forward) modelling. The subsequent inverse procedure infers (re-estimates) the values of important model parameters from the actual observations. Accuracy and sensitivity of the proposed method for real-time forecasting of the accident propagation is studied. First, a twin experiment generating noiseless simulated "artificial" observations is studied to verify the minimisation algorithm. Second, the impact of the measurement noise on the re-estimated source release rate is examined. In addition, the presented method can be used as a proposal for more advanced statistical techniques using, e.g., importance sampling. Copyright © 2016 Elsevier Ltd. All rights reserved.
Real-time video analysis for retail stores
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.
Essays in real-time forecasting
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...
Meral Ozel, N.; Kusmezer, A.
2012-04-01
The Converging Grid Search (CGS) algorithm was tested on broadband waveforms data from large aftershocks of the October 23, Van earthquake with the hypocentral distances within 0-300 km over a magnitude range of 4.0≤M≤5.6.Observed displacement spectra were virtually well adapted to the Brune's source model in the whole frequency range for many waveforms.The estimated Mw solutions were compared to global CMT catalogue solutions, and were seen to be in good agreement. To estimate Mw from a shear-wave displacement spectrum, an automatic routine named as CGS was applied to attempt to test and develop a method for stable moment magnitude estimation to be used as a real-time operation.The spectra were corrected for average an elastic attenuation and geometrical spreading factors and then were scaled to compute moment at the long period asymptote where the spectral plateau for 0 Hz is flat.For this aim, an automatic procedure was utilized: 1)calculating the displacement spectra for vertical components at a given station, 2)estimating corner frequency and seismic moment using CGS which is based on minimizing the differences between observed and synthetic source spectra, 3)calculating moment magnitude from seismic moment for each station separately, and then are averaged to give the mean values of each event. The best fitting iteration of these parameters was obtained after a few seconds. The noise spectrum was also computed to suggest a comparison between signals to noise ratio before performing the inversion.Weak events with low SNR were excluded from the computations. The method examined on the Van earthquake aftershock dataset proved that it is applicable to have stable and reliable estimates of magnitude for the routine processing within a few seconds from the initial P wave detection though the location estimation is necessary.This allows a fast determination of Mw magnitude and assist to measure physical quantities of the source available for the real time
FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation
Directory of Open Access Journals (Sweden)
Irineo Torres-Pacheco
2010-09-01
Full Text Available Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities.
FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation
Millan-Almaraz, Jesus Roberto; de Jesus Romero-Troncoso, Rene; Guevara-Gonzalez, Ramon Gerardo; Contreras-Medina, Luis Miguel; Carrillo-Serrano, Roberto Valentin; Osornio-Rios, Roque Alfredo; Duarte-Galvan, Carlos; Rios-Alcaraz, Miguel Angel; Torres-Pacheco, Irineo
2010-01-01
Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities. PMID:22163656
Nguyen, D. T.; Bertholet, J.; Kim, J.-H.; O'Brien, R.; Booth, J. T.; Poulsen, P. R.; Keall, P. J.
2018-01-01
Increasing evidence suggests that intrafraction tumour motion monitoring needs to include both 3D translations and 3D rotations. Presently, methods to estimate the rotation motion require the 3D translation of the target to be known first. However, ideally, translation and rotation should be estimated concurrently. We present the first method to directly estimate six-degree-of-freedom (6DoF) motion from the target’s projection on a single rotating x-ray imager in real-time. This novel method is based on the linear correlations between the superior-inferior translations and the motion in the other five degrees-of-freedom. The accuracy of the method was evaluated in silico with 81 liver tumour motion traces from 19 patients with three implanted markers. The ground-truth motion was estimated using the current gold standard method where each marker’s 3D position was first estimated using a Gaussian probability method, and the 6DoF motion was then estimated from the 3D positions using an iterative method. The 3D position of each marker was projected onto a gantry-mounted imager with an imaging rate of 11 Hz. After an initial 110° gantry rotation (200 images), a correlation model between the superior-inferior translations and the five other DoFs was built using a least square method. The correlation model was then updated after each subsequent frame to estimate 6DoF motion in real-time. The proposed algorithm had an accuracy (±precision) of -0.03 ± 0.32 mm, -0.01 ± 0.13 mm and 0.03 ± 0.52 mm for translations in the left-right (LR), superior-inferior (SI) and anterior-posterior (AP) directions respectively; and, 0.07 ± 1.18°, 0.07 ± 1.00° and 0.06 ± 1.32° for rotations around the LR, SI and AP axes respectively on the dataset. The first method to directly estimate real-time 6DoF target motion from segmented marker positions on a 2D imager was devised. The algorithm was evaluated using 81
International Nuclear Information System (INIS)
Sciare, J.; Sarda-Esteve, R.; Favez, O.; Cachier, H.; Aymoz, G.; Laj, P.
2008-01-01
Real-time analyzers of selected chemical components (sulfate, nitrate, Black Carbon) and integrative aerosol parameters (particulate matter and light scattering coefficient) were implemented for a 2-week campaign (November-December 2005) in a suburban area of Clermont-Ferrand (France) in order to document fast changes in the chemical composition of submicron aerosols. Measurements of particulate organic matter (POM) were not available in the field but were indirectly estimated from time-resolved (3-min) reconstruction of the light scattering coefficient. This methodology offered the opportunity to investigate almost real-time and artifact-free POM concentrations even at low concentrations (typically below 0.1 mu g m(-3)). The overall uncertainties associated with this POM calculation were of the order of 20%, which are comparable to those commonly referred in literature for POM calculation or measurements. A chemical mass balance (CMB) of PM1 was performed using the derived POM concentrations and showed a very good correlation (slope = 0.93; r(2) = 0.91, N = 663) with real-time PM1 measurements obtained from R and P TEOM-FDMS, demonstrating the consistency of our approach. Important diurnal variations were observed in POM concentrations, with a dominant contribution of POM from fossil fuel origin during daytime and a dominant contribution of POM from residential wood burning at night. POM was calculated to contribute as much as 70% of PM1 during our study, pointing out the major role of carbonaceous aerosols at this period of the year at our residential area. (authors)
REAL - Ensemble radar precipitation estimation for hydrology in a mountainous region
Germann, Urs; Berenguer Ferrer, Marc; Sempere Torres, Daniel; Zappa, Massimiliano
2009-01-01
An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall–runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisati...
Boundary Correct Real-Time Soft Shadows
DEFF Research Database (Denmark)
Jacobsen, Bjarke; Christensen, Niels Jørgen; Larsen, Bent Dalgaard
2004-01-01
This paper describes a method to determine correct shadow boundaries from an area light source using umbra and penumbra volumes. The light source is approximated by a circular disk as this gives a fast way to extrude the volumes. The method also gives a crude estimate of the visibility of the are...... for implementation on most programmable hardware. Though some crude approximations are used in the visibility function, the method can be used to produce soft shadows with correct boundaries in real time....
Real time control of the flexible dynamics of orbital launch vehicles
Bos, van den J.; Steinbuch, M.; Gutierrez, H.M.
2011-01-01
During this traineeship the flexible dynamics of orbital launch vehicles are estimated and controlled in real time, using distributed fiber-Bragg sensor arrays for motion estimation and cold gas thrusters for control. The use of these cold-gas thrusters to actively control flexible modes is the main
LTE delay assessment for real-time management of future smart grids
Jorguseski, L.; Zhang, H.; Chrysalos, M.; Golinski, M.; Toh, Y.
2017-01-01
This study investigates the feasibility of using Long Term Evolution (LTE), for the real-time state estimation of the smart grids. This enables monitoring and control of future smart grids. The smart grid state estimation requires measurement reports from different nodes in the smart grid and
Computing moment to moment BOLD activation for real-time neurofeedback
Hinds, Oliver; Ghosh, Satrajit; Thompson, Todd W.; Yoo, Julie J.; Whitfield-Gabrieli, Susan; Triantafyllou, Christina; Gabrieli, John D.E.
2013-01-01
Estimating moment to moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment to moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment to moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI timeseries, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method. PMID:20682350
PEANO, a toolbox for real-time process signal validation and estimation
International Nuclear Information System (INIS)
Fantoni, Paolo F.; Figedy, Stefan; Racz, Attila
1998-02-01
PEANO (Process Evaluation and Analysis by Neural Operators), a toolbox for real time process signal validation and condition monitoring has been developed. This system analyses the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. The system is based on neuro-fuzzy techniques. Artificial Neural Networks and Fuzzy Logic models can be combined to exploit learning and generalisation capability of the first technique with the approximate reasoning embedded in the second approach. Real-time process signal validation is an application field where the use of this technique can improve the diagnosis of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process has to be performed. The possibilistic approach (rather than probabilistic) allows a ''don't know'' classification that results in a fast detection of unforeseen plant conditions or outliers. Specialised Artificial Neural Networks are used for the validation process, one for each fuzzy cluster in which the operating map has been divided. There are two main advantages in using this technique: the accuracy and generalisation capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This model has been tested in a simulated environment on a French PWR, to monitor safety-related reactor variables over the entire power-flow operating map. (author)
PEANO, a toolbox for real-time process signal validation and estimation
Energy Technology Data Exchange (ETDEWEB)
Fantoni, Paolo F.; Figedy, Stefan; Racz, Attila
1998-02-01
PEANO (Process Evaluation and Analysis by Neural Operators), a toolbox for real time process signal validation and condition monitoring has been developed. This system analyses the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. The system is based on neuro-fuzzy techniques. Artificial Neural Networks and Fuzzy Logic models can be combined to exploit learning and generalisation capability of the first technique with the approximate reasoning embedded in the second approach. Real-time process signal validation is an application field where the use of this technique can improve the diagnosis of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process has to be performed. The possibilistic approach (rather than probabilistic) allows a ''don't know'' classification that results in a fast detection of unforeseen plant conditions or outliers. Specialised Artificial Neural Networks are used for the validation process, one for each fuzzy cluster in which the operating map has been divided. There are two main advantages in using this technique: the accuracy and generalisation capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This model has been tested in a simulated environment on a French PWR, to monitor safety-related reactor variables over the entire power-flow operating map. (author)
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...
Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay
International Nuclear Information System (INIS)
Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.
2008-01-01
This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.
Multi-processor system for real-time flow estimation in medical ultrasound imaging
DEFF Research Database (Denmark)
Stetson, Paul F.; Jensen, Jesper Lomborg; Antonius, Peter
1997-01-01
the processed data. The generous bandwidth of the links makes it easy to balance the computational load among the processors.In order to manage the shared system memory and to make use of the parallel processing capabilities of the system, a real-time multitasking kernel has been developed. The kernel uses...
Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Welch, Gregory Francis [UNC-Chapel Hill/University of Central Florida; Zhang, Jinghe [UNC-Chapel Hill/Virginia Tech
2014-06-10
Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuities caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.
VERSE - Virtual Equivalent Real-time Simulation
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.
On the fast estimation of transit times application to BWR simulated data
International Nuclear Information System (INIS)
Antonopoulos-Domis, M.; Marseguerra, M.; Padovani, E.
1996-01-01
Real time estimators of transit times are proposed. BWR noise is simulated including a global component due to rod vibration. The time obtained form the simulation is used to investigate the robustness and noise immunity of the estimators. It is found that, in presence of a coincident (global) signal, the cross-correlation function is the worst estimator. (authors)
Topological transitions at finite temperatures: A real-time numerical approach
International Nuclear Information System (INIS)
Grigoriev, D.Yu.; Rubakov, V.A.; Shaposhnikov, M.E.
1989-01-01
We study topological transitions at finite temperatures within the (1+1)-dimensional abelian Higgs model by a numerical simulation in real time. Basic ideas of the real-time approach are presented and some peculiarities of the Metropolis technique are discussed. It is argued that the processes leading to topological transitions are of classical origin; the transitions can be observed by solving the classical field equations in real time. We show that the topological transitions actually pass via the sphaleron configuration. The transition rate as a function of temperature is found to be in good agreement with the analytical predictions. No extra suppression of the rate is observed. The conditions of applicability of our approach are discussed. The temperature interval where the low-temperature broken phase persists is estimated. (orig.)
Combining instruction prefetching with partial cache locking to improve WCET in real-time systems.
Directory of Open Access Journals (Sweden)
Fan Ni
Full Text Available Caches play an important role in embedded systems to bridge the performance gap between fast processor and slow memory. And prefetching mechanisms are proposed to further improve the cache performance. While in real-time systems, the application of caches complicates the Worst-Case Execution Time (WCET analysis due to its unpredictable behavior. Modern embedded processors often equip locking mechanism to improve timing predictability of the instruction cache. However, locking the whole cache may degrade the cache performance and increase the WCET of the real-time application. In this paper, we proposed an instruction-prefetching combined partial cache locking mechanism, which combines an instruction prefetching mechanism (termed as BBIP with partial cache locking to improve the WCET estimates of real-time applications. BBIP is an instruction prefetching mechanism we have already proposed to improve the worst-case cache performance and in turn the worst-case execution time. The estimations on typical real-time applications show that the partial cache locking mechanism shows remarkable WCET improvement over static analysis and full cache locking.
Combining instruction prefetching with partial cache locking to improve WCET in real-time systems.
Ni, Fan; Long, Xiang; Wan, Han; Gao, Xiaopeng
2013-01-01
Caches play an important role in embedded systems to bridge the performance gap between fast processor and slow memory. And prefetching mechanisms are proposed to further improve the cache performance. While in real-time systems, the application of caches complicates the Worst-Case Execution Time (WCET) analysis due to its unpredictable behavior. Modern embedded processors often equip locking mechanism to improve timing predictability of the instruction cache. However, locking the whole cache may degrade the cache performance and increase the WCET of the real-time application. In this paper, we proposed an instruction-prefetching combined partial cache locking mechanism, which combines an instruction prefetching mechanism (termed as BBIP) with partial cache locking to improve the WCET estimates of real-time applications. BBIP is an instruction prefetching mechanism we have already proposed to improve the worst-case cache performance and in turn the worst-case execution time. The estimations on typical real-time applications show that the partial cache locking mechanism shows remarkable WCET improvement over static analysis and full cache locking.
Directory of Open Access Journals (Sweden)
Plebankiewicz E.
2015-09-01
Full Text Available The article presents briefly several methods of working time estimation. However, three methods of task duration assessment have been selected to investigate working time in a real construction project using the data collected from observing workers laying terrazzo flooring in staircases. The first estimation has been done by calculating a normal and a triangular function. The next method, which is the focus of greatest attention here, is PERT. The article presents a way to standardize the results and the procedure algorithm allowing determination of the characteristic values for the method. Times to perform every singular component sub-task as well as the whole task have been defined for the collected data with the reliability level of 85%. The completion time of the same works has also been calculated with the use of the KNR. The obtained result is much higher than the actual time needed for execution of the task calculated with the use of the previous method. The authors argue that PERT is the best method of all three, because it takes into account the randomness of the entire task duration and it can be based on the actual execution time known from research.
Highway travel time estimation with data fusion
Soriguera Martí, Francesc
2016-01-01
This monograph presents a simple, innovative approach for the measurement and short-term prediction of highway travel times based on the fusion of inductive loop detector and toll ticket data. The methodology is generic and not technologically captive, allowing it to be easily generalized for other equivalent types of data. The book shows how Bayesian analysis can be used to obtain fused estimates that are more reliable than the original inputs, overcoming some of the drawbacks of travel-time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) from the available data, without recurrent and costly requirements for additional data. The application of the algorithms to empirical testing in the AP-7 toll highway in Barcelona proves that it is possible to develop an accurate real-time, travel-time information system on closed-toll highways with the existing surveillance equipment, suggesting that highway operators might provide...
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
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
Kelbert, Anna; Balch, Christopher C.; Pulkkinen, Antti; Egbert, Gary D.; Love, Jeffrey J.; Rigler, E. Joshua; Fujii, Ikuko
2017-07-01
Geoelectric fields at the Earth's surface caused by magnetic storms constitute a hazard to the operation of electric power grids and related infrastructure. The ability to estimate these geoelectric fields in close to real time and provide local predictions would better equip the industry to mitigate negative impacts on their operations. Here we report progress toward this goal: development of robust algorithms that convolve a magnetic storm time series with a frequency domain impedance for a realistic three-dimensional (3-D) Earth, to estimate the local, storm time geoelectric field. Both frequency domain and time domain approaches are presented and validated against storm time geoelectric field data measured in Japan. The methods are then compared in the context of a real-time application.
Dynamic Modeling and Real-Time Monitoring of Froth Flotation
Directory of Open Access Journals (Sweden)
Khushaal Popli
2015-08-01
Full Text Available A dynamic fundamental model was developed linking processes from the microscopic scale to the equipment scale for batch froth flotation. State estimation, fault detection, and disturbance identification were implemented using the extended Kalman filter (EKF, which reconciles real-time measurements with dynamic models. The online measurements for the EKF were obtained through image analysis of froth images that were captured and analyzed using the commercial package VisioFroth (Metsor Minerals. The extracted image features were then correlated to recovery using principal component analysis and partial least squares regression. The performance of real-time state estimation and fault detection was validated using batch flotation of pure galena at various operating conditions. The image features that were strongly representative of recovery were identified, and calibration and validation were performed against off-line measurements of recovery. The EKF successfully captured the dynamics of the process by updating the model states and parameters using the online measurements. Finally, disturbances in the air flow rate and impeller speed were introduced into the system, and the dynamic behavior of the flotation process was successfully tracked and the disturbances were identified using state estimation.
Indoor Localization of a Quadrotor Based on WSN: A Real-Time Application
Directory of Open Access Journals (Sweden)
Jose L. Rullan-Lara
2013-01-01
Full Text Available A real-time localization algorithm is presented in this paper. The algorithm presented here uses an extended Kalman filter and is based on Time Difference Of Arrivals (TDOA measurements of radio signal. The position and velocity of an Unmanned Aerial Vehicle (UAV are successfully estimated in closed-loop in real-time, both in hover and path following flights. Relatively small position errors obtained from the experiments prove the good performance of the proposed algorithm.
Achieving Real-Time Tracking Mobile Wireless Sensors Using SE-KFA
Kadhim Hoomod, Haider, Dr.; Al-Chalabi, Sadeem Marouf M.
2018-05-01
Nowadays, Real-Time Achievement is very important in different fields, like: Auto transport control, some medical applications, celestial body tracking, controlling agent movements, detections and monitoring, etc. This can be tested by different kinds of detection devices, which named "sensors" as such as: infrared sensors, ultrasonic sensor, radars in general, laser light sensor, and so like. Ultrasonic Sensor is the most fundamental one and it has great impact and challenges comparing with others especially when navigating (as an agent). In this paper, concerning to the ultrasonic sensor, sensor(s) detecting and delimitation by themselves then navigate inside a limited area to estimating Real-Time using Speed Equation with Kalman Filter Algorithm as an intelligent estimation algorithm. Then trying to calculate the error comparing to the factual rate of tracking. This paper used Ultrasonic Sensor HC-SR04 with Arduino-UNO as Microcontroller.
Almiron Bonnin, Rubens Eduardo
The development of an experimental synchrophasors network and application of synchrophasors for real-time transmission line parameter monitoring are presented in this thesis. In the laboratory setup, a power system is simulated in a RTDS real-time digital simulator, and the simulated voltages and currents are input to hardware phasor measurement units (PMUs) through the analog outputs of the simulator. Time synchronizing signals for the PMU devices are supplied from a common GPS clock. The real time data collected from PMUs are sent to a phasor data concentrator (PDC) through Ethernet using the TCP/IP protocol. A real-time transmission line parameter monitoring application program that uses the synchrophasor data provided by the PDC is implemented and validated. The experimental synchrophasor network developed in this thesis is expected to be used in research on synchrophasor applications as well as in graduate and undergraduate teaching.
A real-time Global Warming Index.
Haustein, K; Allen, M R; Forster, P M; Otto, F E L; Mitchell, D M; Matthews, H D; Frame, D J
2017-11-13
We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.
Energy Technology Data Exchange (ETDEWEB)
Rivero, N.; Esteban, J. A.; Lenhardt, G.
2007-07-01
Best estimate codes are assumed to be the technology solution providing the most realistic and accurate response. Best estimate technology provides a complementary solution to the conservative simulation technology usually applied to determine plant safety margins and perform security related studies. Tecnatom in the early 90's, within the MAS project, pioneered the initiative to implement best estimate code in its training simulators. Result of this project was the implementation of the first six-equations thermal hydraulic code worldwide (TRAC{sub R}T), running in a training environment. To meet real time and other specific training requirements, it was necessary to overcome important difficulties. Tecnatom has just adapted the Global Nuclear Fuel core Design code: PANAC 11, and is about to complete the General Electric TRACG04 thermal hydraulic code adaptation. This technology features a unique solution for nuclear plants aiming at providing the highest fidelity in simulation, enabling to consider the simulator as a multipurpose: engineering and training, simulation platform. Besides, a visual environment designed to optimize the models life cycle, covering both pre and post-processing activities, is in its late development phase. (Author)
Real-time monitoring of a microbial electrolysis cell using an electrical equivalent circuit model.
Hussain, S A; Perrier, M; Tartakovsky, B
2018-04-01
Efforts in developing microbial electrolysis cells (MECs) resulted in several novel approaches for wastewater treatment and bioelectrosynthesis. Practical implementation of these approaches necessitates the development of an adequate system for real-time (on-line) monitoring and diagnostics of MEC performance. This study describes a simple MEC equivalent electrical circuit (EEC) model and a parameter estimation procedure, which enable such real-time monitoring. The proposed approach involves MEC voltage and current measurements during its operation with periodic power supply connection/disconnection (on/off operation) followed by parameter estimation using either numerical or analytical solution of the model. The proposed monitoring approach is demonstrated using a membraneless MEC with flow-through porous electrodes. Laboratory tests showed that changes in the influent carbon source concentration and composition significantly affect MEC total internal resistance and capacitance estimated by the model. Fast response of these EEC model parameters to changes in operating conditions enables the development of a model-based approach for real-time monitoring and fault detection.
Merged Real Time GNSS Solutions for the READI System
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
Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System
Directory of Open Access Journals (Sweden)
Jun-Ming Lu
2011-07-01
Full Text Available This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.
Volumetric ambient occlusion for real-time rendering and games.
Szirmay-Kalos, L; Umenhoffer, T; Toth, B; Szecsi, L; Sbert, M
2010-01-01
This new algorithm, based on GPUs, can compute ambient occlusion to inexpensively approximate global-illumination effects in real-time systems and games. The first step in deriving this algorithm is to examine how ambient occlusion relates to the physically founded rendering equation. The correspondence stems from a fuzzy membership function that defines what constitutes nearby occlusions. The next step is to develop a method to calculate ambient occlusion in real time without precomputation. The algorithm is based on a novel interpretation of ambient occlusion that measures the relative volume of the visible part of the surface's tangent sphere. The new formula's integrand has low variation and thus can be estimated accurately with a few samples.
Ahmed, F.; Teferle, F. N.; Bingley, R. M.
2012-04-01
Since September 2011 the University of Luxembourg in collaboration with the University of Nottingham has been setting up two near real-time processing systems for ground-based GNSS data for the provision of zenith total delay (ZTD) and integrated water vapour (IWV) estimates. Both systems are based on Bernese v5.0, use the double-differenced network processing strategy and operate with a 1-hour (NRT1h) and 15-minutes (NRT15m) update cycle. Furthermore, the systems follow the approach of the E-GVAP METO and IES2 systems in that the normal equations for the latest data are combined with those from the previous four updates during the estimation of the ZTDs. NRT1h currently takes the hourly data from over 130 GNSS stations in Europe whereas NRT15m is primarily using the real-time streams of EUREF-IP. Both networks include additional GNSS stations in Luxembourg, Belgium and France. The a priori station coordinates for all of these stem from a moving average computed over the last 20 to 50 days and are based on the precise point positioning processing strategy. In this study we present the first ZTD and IWV estimates obtained from the NRT1h and NRT15m systems in development at the University of Luxembourg. In a preliminary evaluation we compare their performance to the IES2 system at the University of Nottingham and find the IWV estimates to agree at the sub-millimetre level.
A real-time architecture for time-aware agents.
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.
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.
Yin, Lucy; Andrews, Jennifer; Heaton, Thomas
2018-05-01
Earthquake parameter estimations using nearest neighbor searching among a large database of observations can lead to reliable prediction results. However, in the real-time application of Earthquake Early Warning (EEW) systems, the accurate prediction using a large database is penalized by a significant delay in the processing time. We propose to use a multidimensional binary search tree (KD tree) data structure to organize large seismic databases to reduce the processing time in nearest neighbor search for predictions. We evaluated the performance of KD tree on the Gutenberg Algorithm, a database-searching algorithm for EEW. We constructed an offline test to predict peak ground motions using a database with feature sets of waveform filter-bank characteristics, and compare the results with the observed seismic parameters. We concluded that large database provides more accurate predictions of the ground motion information, such as peak ground acceleration, velocity, and displacement (PGA, PGV, PGD), than source parameters, such as hypocenter distance. Application of the KD tree search to organize the database reduced the average searching process by 85% time cost of the exhaustive method, allowing the method to be feasible for real-time implementation. The algorithm is straightforward and the results will reduce the overall time of warning delivery for EEW.
Demonstration of near-real-time accounting: the AGNS 1980-81 miniruns
International Nuclear Information System (INIS)
Dayem, H.A.; Baker, A.L.; Cobb, D.D.; Hakkila, E.A.; Ostenak, C.A.
1984-01-01
Near-real-time nuclear materials accounting was demonstrated in a series of experiments at the Allied-General Nuclear Services (AGNS) Barnwell Nuclear Fuels Plant. For each experiment, the second and third plutonium cycles were operated continuously for 1 wk processing uranium solutions. Process data were collected in near-real time by the AGNS computerized nuclear materials control and accounting system and were analyzed for uranium removals using decision analysis techniques. Although the measurement system primarily consisted of process-monitoring measurements that were not optimized for near-real-time accounting, the results of uranium-removal tests showed that removals and unexpected losses from the process area can be detected. Los Alamos used process-grade measurements to close hourly materials balances. Loss-detection sensitivities for 1 day of between 4 and 18 kg of uranium, at 50% detection probability and 2.5% false-alarm probability, were calculated for selected accounting areas. Using pulsed-column inventory estimators, we calculated a total four-column inventory that was within 10% of column dump measurements. Loss-detection sensitivity could be improved by incorporating online waste stream measurements, improving laboratory measurements for process streams, and refining the pulsed-column inventory estimates
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.
Allstadt, Kate E.; Thompson, Eric M.; Wald, David J.; Hamburger, Michael W.; Godt, Jonathan W.; Knudsen, Keith L.; Jibson, Randall W.; Jessee, M. Anna; Zhu, Jing; Hearne, Michael; Baise, Laurie G.; Tanyas, Hakan; Marano, Kristin D.
2016-03-30
The U.S. Geological Survey (USGS) Earthquake Hazards and Landslide Hazards Programs are developing plans to add quantitative hazard assessments of earthquake-triggered landsliding and liquefaction to existing real-time earthquake products (ShakeMap, ShakeCast, PAGER) using open and readily available methodologies and products. To date, prototype global statistical models have been developed and are being refined, improved, and tested. These models are a good foundation, but much work remains to achieve robust and defensible models that meet the needs of end users. In order to establish an implementation plan and identify research priorities, the USGS convened a workshop in Golden, Colorado, in October 2015. This document summarizes current (as of early 2016) capabilities, research and operational priorities, and plans for further studies that were established at this workshop. Specific priorities established during the meeting include (1) developing a suite of alternative models; (2) making use of higher resolution and higher quality data where possible; (3) incorporating newer global and regional datasets and inventories; (4) reducing barriers to accessing inventory datasets; (5) developing methods for using inconsistent or incomplete datasets in aggregate; (6) developing standardized model testing and evaluation methods; (7) improving ShakeMap shaking estimates, particularly as relevant to ground failure, such as including topographic amplification and accounting for spatial variability; and (8) developing vulnerability functions for loss estimates.
An In-Home Digital Network Architecture for Real-Time and Non-Real-Time Communication
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
MARTe: A Multiplatform Real-Time Framework
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.
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.
Accurate Estimation of Low Fundamental Frequencies from Real-Valued Measurements
DEFF Research Database (Denmark)
Christensen, Mads Græsbøll
2013-01-01
In this paper, the difficult problem of estimating low fundamental frequencies from real-valued measurements is addressed. The methods commonly employed do not take the phenomena encountered in this scenario into account and thus fail to deliver accurate estimates. The reason for this is that the......In this paper, the difficult problem of estimating low fundamental frequencies from real-valued measurements is addressed. The methods commonly employed do not take the phenomena encountered in this scenario into account and thus fail to deliver accurate estimates. The reason...... for this is that they employ asymptotic approximations that are violated when the harmonics are not well-separated in frequency, something that happens when the observed signal is real-valued and the fundamental frequency is low. To mitigate this, we analyze the problem and present some exact fundamental frequency estimators...
Real time monitoring of moment magnitude by waveform inversion
Lee, J.; Friederich, W.; Meier, T.
2012-01-01
An instantaneous measure of the moment magnitude (Mw) of an ongoing earthquake is estimated from the moment rate function (MRF) determined in real-time from available seismic data using waveform inversion. Integration of the MRF gives the moment function from which an instantaneous Mw is derived. By repeating the inversion procedure at regular intervals while seismic data are coming in we can monitor the evolution of seismic moment and Mw with time. The final size and duration of a strong earthquake can be obtained within 12 to 15 minutes after the origin time. We show examples of Mw monitoring for three large earthquakes at regional distances. The estimated Mw is only weakly sensitive to changes in the assumed source parameters. Depending on the availability of seismic stations close to the epicenter, a rapid estimation of the Mw as a prerequisite for the assessment of earthquake damage potential appears to be feasible.
Real-Time Prognostics of a Rotary Valve Actuator
Daigle, Matthew
2015-01-01
Valves are used in many domains and often have system-critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and prediction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remaining useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.
A Dynamic Travel Time Estimation Model Based on Connected Vehicles
Directory of Open Access Journals (Sweden)
Daxin Tian
2015-01-01
Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.
Shelf Life of Food Products: From Open Labeling to Real-Time Measurements.
Corradini, Maria G
2018-03-25
The labels currently used on food and beverage products only provide consumers with a rough guide to their expected shelf lives because they assume that a product only experiences a limited range of predefined handling and storage conditions. These static labels do not take into consideration conditions that might shorten a product's shelf life (such as temperature abuse), which can lead to problems associated with food safety and waste. Advances in shelf-life estimation have the potential to improve the safety, reliability, and sustainability of the food supply. Selection of appropriate kinetic models and data-analysis techniques is essential to predict shelf life, to account for variability in environmental conditions, and to allow real-time monitoring. Novel analytical tools to determine safety and quality attributes in situ coupled with modern tracking technologies and appropriate predictive tools have the potential to provide accurate estimations of the remaining shelf life of a food product in real time. This review summarizes the necessary steps to attain a transition from open labeling to real-time shelf-life measurements.
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...
Three-dimensional liver motion tracking using real-time two-dimensional MRI.
Brix, Lau; Ringgaard, Steffen; Sørensen, Thomas Sangild; Poulsen, Per Rugaard
2014-04-01
Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (or tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Axial, sagittal, and coronal 2D MRI series
Three-dimensional liver motion tracking using real-time two-dimensional MRI
Energy Technology Data Exchange (ETDEWEB)
Brix, Lau, E-mail: lau.brix@stab.rm.dk [Department of Procurement and Clinical Engineering, Region Midt, Olof Palmes Allé 15, 8200 Aarhus N, Denmark and MR Research Centre, Aarhus University Hospital, Skejby, Brendstrupgaardsvej 100, 8200 Aarhus N (Denmark); Ringgaard, Steffen [MR Research Centre, Aarhus University Hospital, Skejby, Brendstrupgaardsvej 100, 8200 Aarhus N (Denmark); Sørensen, Thomas Sangild [Department of Computer Science, Aarhus University, Aabogade 34, 8200 Aarhus N, Denmark and Department of Clinical Medicine, Aarhus University, Brendstrupgaardsvej 100, 8200 Aarhus N (Denmark); Poulsen, Per Rugaard [Department of Clinical Medicine, Aarhus University, Brendstrupgaardsvej 100, 8200 Aarhus N, Denmark and Department of Oncology, Aarhus University Hospital, Nørrebrogade 44, 8000 Aarhus C (Denmark)
2014-04-15
Purpose: Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. Methods: The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (or tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Results: Axial, sagittal
Three-dimensional liver motion tracking using real-time two-dimensional MRI
International Nuclear Information System (INIS)
Brix, Lau; Ringgaard, Steffen; Sørensen, Thomas Sangild; Poulsen, Per Rugaard
2014-01-01
Purpose: Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. Methods: The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (or tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Results: Axial, sagittal
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
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
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.
High-Resolution Near Real-Time Drought Monitoring in South Asia
Aadhar, S.; Mishra, V.
2017-12-01
Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.
Directory of Open Access Journals (Sweden)
Bai-Jian Wei
2016-09-01
Full Text Available Resin transfer molding (RTM is a popular manufacturing technique that produces fiber reinforced polymer (FRP composites. In this paper, a model-assisted flow front control system is developed based on real-time estimation of permeability/porosity ratio using the information acquired by a visualization system. In the proposed control system, a radial basis function (RBF network meta-model is utilized to predict the position of the future flow front by inputting the injection pressure, the current position of flow front, and the estimated ratio. By conducting optimization based on the meta-model, the value of injection pressure to be implemented at each step is obtained. Moreover, a cascade control structure is established to further improve the control performance. Experiments show that the developed system successfully enhances the performance of flow front control in RTM. Especially, the cascade structure makes the control system robust to model mismatch.
International Nuclear Information System (INIS)
Jensen, C R; Cleveland, R O; Coussios, C C
2013-01-01
Passive acoustic mapping (PAM) has been recently demonstrated as a method of monitoring focused ultrasound therapy by reconstructing the emissions created by inertially cavitating bubbles (Jensen et al 2012 Radiology 262 252–61). The published method sums energy emitted by cavitation from the focal region within the tissue and uses a threshold to determine when sufficient energy has been delivered for ablation. The present work builds on this approach to provide a high-intensity focused ultrasound (HIFU) treatment monitoring software that displays both real-time temperature maps and a prediction of the ablated tissue region. This is achieved by determining heat deposition from two sources: (i) acoustic absorption of the primary HIFU beam which is calculated via a nonlinear model, and (ii) absorption of energy from bubble acoustic emissions which is estimated from measurements. The two sources of heat are used as inputs to the bioheat equation that gives an estimate of the temperature of the tissue as well as estimates of tissue ablation. The method has been applied to ex vivo ox liver samples and the estimated temperature is compared to the measured temperature and shows good agreement, capturing the effect of cavitation-enhanced heating on temperature evolution. In conclusion, it is demonstrated that by using PAM and predictions of heating it is possible to produce an evolving estimate of cell death during exposure in order to guide treatment for monitoring ablative HIFU therapy. (paper)
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 ...
Software Design Methods for Real-Time Systems
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...
Absolute estimation of initial concentrations of amplicon in a real-time RT-PCR process
Directory of Open Access Journals (Sweden)
Kohn Michael
2007-10-01
Full Text Available Abstract Background Since real time PCR was first developed, several approaches to estimating the initial quantity of template in an RT-PCR reaction have been tried. While initially only the early thermal cycles corresponding to exponential duplication were used, lately there has been an effort to use all of the cycles in a PCR. The efforts have included both fitting empirical sigmoid curves and more elaborate mechanistic models that explore the chemical reactions taking place during each cycle. The more elaborate mechanistic models require many more parameters than can be fit from a single amplification, while the empirical models provide little insight and are difficult to tailor to specific reactants. Results We directly estimate the initial amount of amplicon using a simplified mechanistic model based on chemical reactions in the annealing step of the PCR. The basic model includes the duplication of DNA with the digestion of Taqman probe and the re-annealing between previously synthesized DNA strands of opposite orientation. By modelling the amount of Taqman probe digested and matching that with the observed fluorescence, the conversion factor between the number of fluorescing dye molecules and observed fluorescent emission can be estimated, along with the absolute initial amount of amplicon and the rate parameter for re-annealing. The model is applied to several PCR reactions with known amounts of amplicon and is shown to work reasonably well. An expanded version of the model allows duplication of amplicon without release of fluorescent dye, by adding 1 more parameter to the model. The additional process is helpful in most cases where the initial primer concentration exceeds the initial probe concentration. Software for applying the algorithm to data may be downloaded at http://www.niehs.nih.gov/research/resources/software/pcranalyzer/ Conclusion We present proof of the principle that a mechanistically based model can be fit to observations
Distributed, Embedded and Real-time Java Systems
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...
Research of real-time communication software
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.
Smooth time-dependent receiver operating characteristic curve estimators.
Martínez-Camblor, Pablo; Pardo-Fernández, Juan Carlos
2018-03-01
The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, two main extensions have been proposed: the cumulative/dynamic receiver operating characteristic curve and the incident/dynamic receiver operating characteristic curve. In both cases, the main problem for developing appropriate estimators is the estimation of the joint distribution of the variables time-to-event and marker. As usual, different approximations lead to different estimators. In this article, the authors explore the use of a bivariate kernel density estimator which accounts for censored observations in the sample and produces smooth estimators of the time-dependent receiver operating characteristic curves. The performance of the resulting cumulative/dynamic and incident/dynamic receiver operating characteristic curves is studied by means of Monte Carlo simulations. Additionally, the influence of the choice of the required smoothing parameters is explored. Finally, two real-applications are considered. An R package is also provided as a complement to this article.
Damiano, Diane L.; Bulea, Thomas C.
2016-01-01
Individuals with cerebral palsy frequently exhibit crouch gait, a pathological walking pattern characterized by excessive knee flexion. Knowledge of the knee joint moment during crouch gait is necessary for the design and control of assistive devices used for treatment. Our goal was to 1) develop statistical models to estimate knee joint moment extrema and dynamic stiffness during crouch gait, and 2) use the models to estimate the instantaneous joint moment during weight-acceptance. We retrospectively computed knee moments from 10 children with crouch gait and used stepwise linear regression to develop statistical models describing the knee moment features. The models explained at least 90% of the response value variability: peak moment in early (99%) and late (90%) stance, and dynamic stiffness of weight-acceptance flexion (94%) and extension (98%). We estimated knee extensor moment profiles from the predicted dynamic stiffness and instantaneous knee angle. This approach captured the timing and shape of the computed moment (root-mean-squared error: 2.64 Nm); including the predicted early-stance peak moment as a correction factor improved model performance (root-mean-squared error: 1.37 Nm). Our strategy provides a practical, accurate method to estimate the knee moment during crouch gait, and could be used for real-time, adaptive control of robotic orthoses. PMID:27101612
Real-time 3-D space numerical shake prediction for earthquake early warning
Wang, Tianyun; Jin, Xing; Huang, Yandan; Wei, Yongxiang
2017-12-01
In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake prediction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.
A real-time BWR [boiling water reactor] stability measurement system
International Nuclear Information System (INIS)
March-Leuba, J.; King, W.T.
1987-01-01
This paper describes the characteristics of a portable, real-time system used for nonperturbational measurements of stability in boiling water reactors. The algorithm used in this system estimates the closed-loop asymptotic decay ratio using only the naturally occurring neutron noise and it is based on the univariate autoregressive methodology
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
Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability
Mandal, Tanmay Kumar
Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of
Co-simulation for real time safety verification of nuclear power plants
International Nuclear Information System (INIS)
Boafo, E.K.; Zhang, L.; Nasimi, E.; Gabbar, H.A.
2015-01-01
Small and major accidents and near misses are still occurring in nuclear power plants (NPPs). Risk level has increased with the degradation of NPP equipment and instrumentations. In order to achieve NPP safety, it is important to continuously evaluate risk for all potential hazard and fault propagation scenarios and map protection layers to fault / failure / hazard propagation scenarios to be able to evaluate and verify safety level during NPP operation. There are major limitations in current real time safety verification tools, as it is mainly offline and with no integration to NPP simulation tools. The main goal of this research is to develop real time safety verification with co-simulation tool to be integrated with plant operation support systems. This includes the development of static and dynamic fault semantic network (FSN) to model all possible fault propagation scenarios and the interrelationships among associated process variables. Safety and protection layers along with their reliability are mapped to FSN so that safety levels can be verified during plant operation. Errors between multiphysics models and real time data are modeled to accurately and dynamically tune FSN for each fault propagation scenario. The detailed methodology will show how to integrate process models, construction of static FSN with fault propagation scenarios, and evaluation and tuning of dynamic FSN with probabilistic and process variable interaction values. Principle Component Analysis method is used reduce dimensionality and reduce process variables associated with each fault scenario. Then map independent protection layers (IPL) to FSN with estimated reliability measures of each protection layer to accurately verify safety for different operational scenarios. Intelligent algorithms is used with multivariate techniques to accurate define the interrelation among process variables, in terms of signal strength and time delay, using Genetic Programming (GP), which will provide basis
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.
Koshimura, S.; Hino, R.; Ohta, Y.; Kobayashi, H.; Musa, A.; Murashima, Y.
2014-12-01
With use of modern computing power and advanced sensor networks, a project is underway to establish a new system of real-time tsunami inundation forecasting, damage estimation and mapping to enhance society's resilience in the aftermath of major tsunami disaster. The system consists of fusion of real-time crustal deformation monitoring/fault model estimation by Ohta et al. (2012), high-performance real-time tsunami propagation/inundation modeling with NEC's vector supercomputer SX-ACE, damage/loss estimation models (Koshimura et al., 2013), and geo-informatics. After a major (near field) earthquake is triggered, the first response of the system is to identify the tsunami source model by applying RAPiD Algorithm (Ohta et al., 2012) to observed RTK-GPS time series at GEONET sites in Japan. As performed in the data obtained during the 2011 Tohoku event, we assume less than 10 minutes as the acquisition time of the source model. Given the tsunami source, the system moves on to running tsunami propagation and inundation model which was optimized on the vector supercomputer SX-ACE to acquire the estimation of time series of tsunami at offshore/coastal tide gauges to determine tsunami travel and arrival time, extent of inundation zone, maximum flow depth distribution. The implemented tsunami numerical model is based on the non-linear shallow-water equations discretized by finite difference method. The merged bathymetry and topography grids are prepared with 10 m resolution to better estimate the tsunami inland penetration. Given the maximum flow depth distribution, the system performs GIS analysis to determine the numbers of exposed population and structures using census data, then estimates the numbers of potential death and damaged structures by applying tsunami fragility curve (Koshimura et al., 2013). Since the tsunami source model is determined, the model is supposed to complete the estimation within 10 minutes. The results are disseminated as mapping products to
Storm real-time processing cookbook
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.
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.
Research in Distributed Real-Time Systems
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
Unmanned airborne system in real-time radiological monitoring
International Nuclear Information System (INIS)
Zafrir, H.; Pernick, A.; Yaffe, U.; Grushka, A.
1993-01-01
The unmanned airborne vehicle (UAV) platform, equipped with an appropriate payload and capable of carrying a variety of modular sensors, is an effective tool for real-time control of environmental disasters of different types (e.g. nuclear or chemical accidents). The suggested payloads consist of a miniaturised self-collimating nuclear spectrometry sensor and electro-optical sensors for day and night imagery. The system provides means of both real-time field data acquisition in an endangered environment and on-line hazard assessment computation from the down link raw data. All the processing, including flight planning using an expert system, is performed by a dedicated microcomputer located in a Mobile Ground Control Station (MGCS) situated outside the hazardous area. The UAV equipment is part of a system designed especially for the critically important early phase of emergency response. Decisions by the Emergency Response Manager (ERM) are also based on the ability to estimate the potential dose to individuals and the mitigation of dose when protection measures are implemented. (author)
A framework for predicting three-dimensional prostate deformation in real time
Jahya, Alex; Herink, Mark; Misra, Sarthak
2013-01-01
Background Surgical simulation systems can be used to estimate soft tissue deformation during pre- and intra-operative planning. Such systems require a model that can accurately predict the deformation in real time. In this study, we present a back-propagation neural network for predicting
Making real-time reactive systems reliable
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.
Directory of Open Access Journals (Sweden)
Yifan Wang
2014-05-01
Full Text Available A control method based on real-time operational reliability evaluation for space manipulator is presented for improving the success rate of a manipulator during the execution of a task. In this paper, a method for quantitative analysis of operational reliability is given when manipulator is executing a specified task; then a control model which could control the quantitative operational reliability is built. First, the control process is described by using a state space equation. Second, process parameters are estimated in real time using Bayesian method. Third, the expression of the system's real-time operational reliability is deduced based on the state space equation and process parameters which are estimated using Bayesian method. Finally, a control variable regulation strategy which considers the cost of control is given based on the Theory of Statistical Process Control. It is shown via simulations that this method effectively improves the operational reliability of space manipulator control system.
A Preliminary Examination of the Second Generation CMORPH Real-time Production
Joyce, R.; Xie, P.; Wu, S.
2017-12-01
The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05olat/lon grid over the entire globe, from pole-to-pole. The CMORPH2 is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) and LEO platforms, and precipitation simulations from the NCEP operational global forecast system (GFS). Inputs from the various sources are first inter-calibrated to ensure quantitative consistencies in representing precipitation events of different intensities through PDF calibration against a common reference standard. The inter-calibrated PMW retrievals and IR-based precipitation estimates are then propagated from their respective observation times to the target analysis time along the motion vectors of the precipitating clouds. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the GFS precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. The propagated PMW and IR based precipitation estimates are finally integrated into a single field of global precipitation through the Kalman Filter framework. A set of procedures have been established to examine the performance of the CMORPH2 real-time production. CMORPH2 satellite precipitation estimates are compared against the CPC daily gauge analysis, Stage IV radar precipitation over the CONUS, and numerical model forecasts to discover potential shortcomings and quantify improvements against the first generation CMORPH. Special attention has been focused on the CMORPH behavior over high-latitude areas beyond the coverage of the first
Real-time earthquake source imaging: An offline test for the 2011 Tohoku earthquake
Zhang, Yong; Wang, Rongjiang; Zschau, Jochen; Parolai, Stefano; Dahm, Torsten
2014-05-01
In recent decades, great efforts have been expended in real-time seismology aiming at earthquake and tsunami early warning. One of the most important issues is the real-time assessment of earthquake rupture processes using near-field seismogeodetic networks. Currently, earthquake early warning systems are mostly based on the rapid estimate of P-wave magnitude, which contains generally large uncertainties and the known saturation problem. In the case of the 2011 Mw9.0 Tohoku earthquake, JMA (Japan Meteorological Agency) released the first warning of the event with M7.2 after 25 s. The following updates of the magnitude even decreased to M6.3-6.6. Finally, the magnitude estimate stabilized at M8.1 after about two minutes. This led consequently to the underestimated tsunami heights. By using the newly developed Iterative Deconvolution and Stacking (IDS) method for automatic source imaging, we demonstrate an offline test for the real-time analysis of the strong-motion and GPS seismograms of the 2011 Tohoku earthquake. The results show that we had been theoretically able to image the complex rupture process of the 2011 Tohoku earthquake automatically soon after or even during the rupture process. In general, what had happened on the fault could be robustly imaged with a time delay of about 30 s by using either the strong-motion (KiK-net) or the GPS (GEONET) real-time data. This implies that the new real-time source imaging technique is helpful to reduce false and missing warnings, and therefore should play an important role in future tsunami early warning and earthquake rapid response systems.
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.
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 forecasting of the April 11, 2012 Sumatra tsunami
Wang, Dailin; Becker, Nathan C.; Walsh, David; Fryer, Gerard J.; Weinstein, Stuart A.; McCreery, Charles S.; ,
2012-01-01
The April 11, 2012, magnitude 8.6 earthquake off the northern coast of Sumatra generated a tsunami that was recorded at sea-level stations as far as 4800 km from the epicenter and at four ocean bottom pressure sensors (DARTs) in the Indian Ocean. The governments of India, Indonesia, Sri Lanka, Thailand, and Maldives issued tsunami warnings for their coastlines. The United States' Pacific Tsunami Warning Center (PTWC) issued an Indian Ocean-wide Tsunami Watch Bulletin in its role as an Interim Service Provider for the region. Using an experimental real-time tsunami forecast model (RIFT), PTWC produced a series of tsunami forecasts during the event that were based on rapidly derived earthquake parameters, including initial location and Mwp magnitude estimates and the W-phase centroid moment tensor solutions (W-phase CMTs) obtained at PTWC and at the U. S. Geological Survey (USGS). We discuss the real-time forecast methodology and how successive, real-time tsunami forecasts using the latest W-phase CMT solutions improved the accuracy of the forecast.
Locally-adaptive Myriad Filters for Processing ECG Signals in Real Time
Directory of Open Access Journals (Sweden)
Nataliya Tulyakova
2017-03-01
Full Text Available The locally adaptive myriad filters to suppress noise in electrocardiographic (ECG signals in almost in real time are proposed. Statistical estimates of efficiency according to integral values of such criteria as mean square error (MSE and signal-to-noise ratio (SNR for the test ECG signals sampled at 400 Hz embedded in additive Gaussian noise with different values of variance are obtained. Comparative analysis of adaptive filters is carried out. High efficiency of ECG filtering and high quality of signal preservation are demonstrated. It is shown that locally adaptive myriad filters provide higher degree of suppressing additive Gaussian noise with possibility of real time implementation.
Experimental verification of a real-time power curve for downregulated offshore wind power plants
Giebel, Gregor; Göcmen Bozkurt, Tuhfe; Sørensen, Poul; Rajczyk Skjelmose, Mads; Runge Kristoffersen, Jesper
2015-04-01
Wind farm scale experiments with wakes under downregulation have been initiated in Horns Rev wind farm in the frame of the PossPOW project (see posspow.dtu.dk). The experiments will be compared with the results of the calibrated GCLarsen wake model for real-time which is used not only to obtain real-time power curve but also to estimate the available power in wind farm level. Available (or Possible) Power is the power that a down-regulated (or curtailed) turbine or a wind power plant would produce if it were to operate in normal operational conditions and it is becoming more of particular interest due to increasing number of curtailment periods. Currently, the Transmission System Operators (TSOs) have no real way to determine exactly the available power of a down-regulated wind farm and the PossPOW project is addressing that need. What makes available power calculation interesting at the wind farm level is the change in the wake characteristics for different operational states. Even though the single turbine level available power is easily estimated, the sum of those signals from all turbines in a wind farm overestimates the power since the wake losses significantly decrease during curtailment. In order to calculate that effect, the turbine wind speed is estimated real-time from the produced power, the pitch angle and the rotor speed using a proximate Cp curve. A real-time wake estimation of normal operation is then performed and advected to the next downstream turbine, and so on until the entire wind farm is calculated. The estimation of the rotor effective wind speed, the parameterization of the GCLarsen wake model for real-time use (i.e., 1-sec data from Horns Rev and Thanet) and the details of the advection are the topic can be found in Göcmen et al. [1] Here we plan to describe the experiments using the Horns Rev wind farm and hopefully present the first validation results. Assuming similarity of the wind speeds between neighbouring rows of turbines, the
Real-Time MENTAT programming language and architecture
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
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.
Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks
Aquino, Andre Luiz Lins; Nakamura, Eduardo Freire
2009-01-01
This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness. PMID:22303145
Run-time middleware to support real-time system scenarios
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
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.
Real Time Seismic Loss Estimation in Italy
Goretti, A.; Sabetta, F.
2009-04-01
By more than 15 years the Seismic Risk Office is able to perform a real-time evaluation of the earthquake potential loss in any part of Italy. Once the epicentre and the magnitude of the earthquake are made available by the National Institute for Geophysiscs and Volca-nology, the model, based on the Italian Geographic Information Sys-tems, is able to evaluate the extent of the damaged area and the consequences on the built environment. In recent years the model has been significantly improved with new methodologies able to conditioning the uncertainties using observa-tions coming from the fields during the first days after the event. However it is reputed that the main challenges in loss analysis are related to the input data, more than to methodologies. Unlike the ur-ban scenario, where the missing data can be collected with enough accuracy, the country-wise analysis requires the use of existing data bases, often collected for other purposed than seismic scenario evaluation, and hence in some way lacking of completeness and homogeneity. Soil properties, building inventory and population dis-tribution are the main input data that are to be known in any site of the whole Italian territory. To this end the National Census on Popu-lation and Dwellings has provided information on the residential building types and the population that lives in that building types. The critical buildings, such as Hospital, Fire Brigade Stations, Schools, are not included in the inventory, since the national plan for seismic risk assessment of critical buildings is still under way. The choice of a proper soil motion parameter, its attenuation with distance and the building type fragility are important ingredients of the model as well. The presentation will focus on the above mentioned issues, highlight-ing the different data sets used and their accuracy, and comparing the model, input data and results when geographical areas with dif-ferent extent are considered: from the urban scenarios
Archtecture of distributed real-time systems
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...
Real-time individualization of the unified model of performance.
Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques
2017-12-01
Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.
Hippocampus activation related to 'real-time' processing of visuospatial change.
Beudel, M; Leenders, K L; de Jong, B M
2016-12-01
The delay associated with cerebral processing time implies a lack of real-time representation of changes in the observed environment. To bridge this gap for motor actions in a dynamical environment, the brain uses predictions of the most plausible future reality based on previously provided information. To optimise these predictions, adjustments to actual experiences are necessary. This requires a perceptual memory buffer. In our study we gained more insight how the brain treats (real-time) information by comparing cerebral activations related to judging past-, present- and future locations of a moving ball, respectively. Eighteen healthy subjects made these estimations while fMRI data was obtained. All three conditions evoked bilateral dorsal-parietal and premotor activations, while judgment of the location of the ball at the moment of judgment showed increased bilateral posterior hippocampus activation relative to making both future and past judgments at the one-second time-sale. Since the condition of such 'real-time' judgments implied undistracted observation of the ball's actual movements, the associated hippocampal activation is consistent with the concept that the hippocampus participates in a top-down exerted sensory gating mechanism. In this way, it may play a role in novelty (saliency) detection. Copyright © 2016 Elsevier B.V. All rights reserved.
Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream
Ding, Yulin; Lin, Hui; Li, Rongrong
2016-06-01
Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led
CHANGE SEMANTIC CONSTRAINED ONLINE DATA CLEANING METHOD FOR REAL-TIME OBSERVATIONAL DATA STREAM
Directory of Open Access Journals (Sweden)
Y. Ding
2016-06-01
Full Text Available Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment’s status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events caused by various effects produced by the environment they are monitoring. The “big but dirty” real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational
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...
Zhe Cao; Shaojie Su; Hao Tang; Yixin Zhou; Zhihua Wang; Hong Chen
2017-07-01
With the aging of population, the number of Total Hip Replacement Surgeries (THR) increased year by year. In THR, inaccurate position of the implanted prosthesis may lead to the failure of the operation. In order to reduce the failure rate and acquire the real-time pose of Anterior Pelvic Plane (APP), we propose a measurement system in this paper. The measurement system includes two parts: Initial Pose Measurement Instrument (IPMI) and Real-time Pose Measurement Instrument (RPMI). IPMI is used to acquire the initial pose of the APP, and RPMI is used to estimate the real-time pose of the APP. Both are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. To estimate the attitude of the measurement system, the Extended Kalman Filter (EKF) is adopted in this paper. The real-time pose of the APP could be acquired together with the algorithm designed in the paper. The experiment results show that the Root Mean Square Error (RMSE) is within 1.6 degrees, which meets the requirement of THR operations.
Real-time markerless tracking for augmented reality: the virtual visual servoing framework.
Comport, Andrew I; Marchand, Eric; Pressigout, Muriel; Chaumette, François
2006-01-01
Tracking is a very important research subject in a real-time augmented reality context. The main requirements for trackers are high accuracy and little latency at a reasonable cost. In order to address these issues, a real-time, robust, and efficient 3D model-based tracking algorithm is proposed for a "video see through" monocular vision system. The tracking of objects in the scene amounts to calculating the pose between the camera and the objects. Virtual objects can then be projected into the scene using the pose. Here, nonlinear pose estimation is formulated by means of a virtual visual servoing approach. In this context, the derivation of point-to-curves interaction matrices are given for different 3D geometrical primitives including straight lines, circles, cylinders, and spheres. A local moving edges tracker is used in order to provide real-time tracking of points normal to the object contours. Robustness is obtained by integrating an M-estimator into the visual control law via an iteratively reweighted least squares implementation. This approach is then extended to address the 3D model-free augmented reality problem. The method presented in this paper has been validated on several complex image sequences including outdoor environments. Results show the method to be robust to occlusion, changes in illumination, and mistracking.
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.
Real-time skin feature identification in a time-sequential video stream
Kramberger, Iztok
2005-04-01
Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.
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...
Vicente, Gilberto A.
An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.
Application of XML in real-time data warehouse
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".
Deepwater Horizon - Estimating surface oil volume distribution in real time
Lehr, B.; Simecek-Beatty, D.; Leifer, I.
2011-12-01
Spill responders to the Deepwater Horizon (DWH) oil spill required both the relative spatial distribution and total oil volume of the surface oil. The former was needed on a daily basis to plan and direct local surface recovery and treatment operations. The latter was needed less frequently to provide information for strategic response planning. Unfortunately, the standard spill observation methods were inadequate for an oil spill this size, and new, experimental, methods, were not ready to meet the operational demands of near real-time results. Traditional surface oil estimation tools for large spills include satellite-based sensors to define the spatial extent (but not thickness) of the oil, complemented with trained observers in small aircraft, sometimes supplemented by active or passive remote sensing equipment, to determine surface percent coverage of the 'thick' part of the slick, where the vast majority of the surface oil exists. These tools were also applied to DWH in the early days of the spill but the shear size of the spill prevented synoptic information of the surface slick through the use small aircraft. Also, satellite images of the spill, while large in number, varied considerably in image quality, requiring skilled interpretation of them to identify oil and eliminate false positives. Qualified staff to perform this task were soon in short supply. However, large spills are often events that overcome organizational inertia to the use of new technology. Two prime examples in DWH were the application of hyper-spectral scans from a high-altitude aircraft and more traditional fixed-wing aircraft using multi-spectral scans processed by use of a neural network to determine, respectively, absolute or relative oil thickness. But, with new technology, come new challenges. The hyper-spectral instrument required special viewing conditions that were not present on a daily basis and analysis infrastructure to process the data that was not available at the command
Mixed - mode Operating System for Real - time Performance
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...
LATENCY DETERMINATION AND COMPENSATION IN REAL-TIME GNSS/INS INTEGRATED NAVIGATION SYSTEMS
Directory of Open Access Journals (Sweden)
P. D. Solomon
2012-09-01
Full Text Available Unmanned Aerial Vehicle (UAV technology is now commonplace in many defence and civilian environments. However, the high cost of owning and operating a sophisticated UAV has slowed their adoption in many commercial markets. Universities and research groups are actively experimenting with UAVs to further develop the technology, particularly for automated flying operations. The two main UAV platforms used are fixed-wing and helicopter. Helicopter-based UAVs offer many attractive features over fixed-wing UAVs, including vertical take-off, the ability to loiter, and highly dynamic flight. However the control and navigation of helicopters are significantly more demanding than those of fixed-wing UAVs and as such require a high bandwidth real-time Position, Velocity, Attitude (PVA navigation system. In practical Real-Time Navigation Systems (RTNS there are delays in the processing of the GNSS data prior to the fusion of the GNSS data with the INS measurements. This latency must be compensated for otherwise it degrades the solution of the navigation filter. This paper investigates the effect of latency in the arrival time of the GNSS data in a RTNS. Several test drives and flights were conducted with a low-cost RTNS, and compared with a high quality GNSS/INS solution. A technique for the real-time, automated and accurate estimation of the GNSS latency in low-cost systems was developed and tested. The latency estimates were then verified through cross-correlation with the time-stamped measurements from the reference system. A delayed measurement Extended Kalman Filter was then used to allow for the real-time fusing of the delayed measurements, and then a final system developed for on-the-fly measurement and compensation of GNSS latency in a RTNS.
Latency Determination and Compensation in Real-Time Gnss/ins Integrated Navigation Systems
Solomon, P. D.; Wang, J.; Rizos, C.
2011-09-01
Unmanned Aerial Vehicle (UAV) technology is now commonplace in many defence and civilian environments. However, the high cost of owning and operating a sophisticated UAV has slowed their adoption in many commercial markets. Universities and research groups are actively experimenting with UAVs to further develop the technology, particularly for automated flying operations. The two main UAV platforms used are fixed-wing and helicopter. Helicopter-based UAVs offer many attractive features over fixed-wing UAVs, including vertical take-off, the ability to loiter, and highly dynamic flight. However the control and navigation of helicopters are significantly more demanding than those of fixed-wing UAVs and as such require a high bandwidth real-time Position, Velocity, Attitude (PVA) navigation system. In practical Real-Time Navigation Systems (RTNS) there are delays in the processing of the GNSS data prior to the fusion of the GNSS data with the INS measurements. This latency must be compensated for otherwise it degrades the solution of the navigation filter. This paper investigates the effect of latency in the arrival time of the GNSS data in a RTNS. Several test drives and flights were conducted with a low-cost RTNS, and compared with a high quality GNSS/INS solution. A technique for the real-time, automated and accurate estimation of the GNSS latency in low-cost systems was developed and tested. The latency estimates were then verified through cross-correlation with the time-stamped measurements from the reference system. A delayed measurement Extended Kalman Filter was then used to allow for the real-time fusing of the delayed measurements, and then a final system developed for on-the-fly measurement and compensation of GNSS latency in a RTNS.
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.
New Near-Real Time Monitoring of the Ionosphere over Europe Available On-line
Chevalier, J. M.; Bergeot, N.; Bruyninx, C.; Pottiaux, E.; Aerts, W.; Baire, Q.; Legrand, J.; Defraigne, P.
2012-04-01
With the beginning of the 24th Solar cycle, the increased Solar activity requires having a close eye on the ionosphere for better understanding Space Weather physics and its effects on radio communications. In that frame, near-real time ionospheric models over Europe are now routinely generated at the Royal Observatory of Belgium (ROB). These models are made available to the public through new interactive web pages at the web site of the GNSS team (www.gnss.be) and the Solar Influences Data Analysis Center (www.sidc.be) of ROB. The models are ionospheric Vertical Total Electron Content (VTEC) maps estimated every 15 minutes on a 0.5°x0.5° grid. They use the high-rate GPS observations of the real-time stations in the EUREF Permanent Network (EPN) provided by the ROB NTRIP broadcaster. The maps are published on the ROB web site with a latency of 7-15 minutes with respect to the last GPS measurement included in the 15-minute observation files. In a first step, this paper presents the processing strategy used to generate the VTEC maps: input data, parameter estimation, data cleaning and interpolation method. In addition, the tools developed to further exploit the product are introduced, e.g. on-demand animated VTEC maps. In a second step, the VTEC maps are compared with external ionospheric products and models such as Global Ionospheric Maps and IRI 2011. These new near-real time VTEC maps will allow any user within the geographical scope of the maps to estimate in near-real time the ionospheric delay induced along the signal of any observed satellite. In the future, the web site will continuously be updated in response to evolving user needs. This paper opens doors to discussions with the user community to target their needs.
Tracking errors in a prototype real-time tumour tracking system
International Nuclear Information System (INIS)
Sharp, Gregory C; Jiang, Steve B; Shimizu, Shinichi; Shirato, Hiroki
2004-01-01
In motion-compensated radiation therapy, radio-opaque markers can be implanted in or near a tumour and tracked in real-time using fluoroscopic imaging. Tracking these implanted markers gives highly accurate position information, except when tracking fails due to poor or ambiguous imaging conditions. This study investigates methods for automatic detection of tracking errors, and assesses the frequency and impact of tracking errors on treatments using the prototype real-time tumour tracking system. We investigated four indicators for automatic detection of tracking errors, and found that the distance between corresponding rays was most effective. We also found that tracking errors cause a loss of gating efficiency of between 7.6 and 10.2%. The incidence of treatment beam delivery during tracking errors was estimated at between 0.8% and 1.25%
Real-time software for multi-isotopic source term estimation
International Nuclear Information System (INIS)
Goloubenkov, A.; Borodin, R.; Sohier, A.
1996-01-01
Consideration is given to development of software for one of crucial components of the RODOS - assessment of the source rate (SR) from indirect measurements. Four components of the software are described in the paper. First component is a GRID system, which allow to prepare stochastic meteorological and radioactivity fields using measured data. Second part is a model of atmospheric transport which can be adapted for emulation of practically any gamma dose/spectrum detectors. The third one is a method which allows space-time and quantitative discrepancies in measured and modelled data to be taken into account simultaneously. It bases on the preference scheme selected by an expert. Last component is a special optimization method for calculation of multi-isotopic SR and its uncertainties. Results of a validation of the software using tracer experiments data and Chernobyl source estimation for main dose-forming isotopes are enclosed in the paper
The Estimation of the Equilibrium Real Exchange Rate for Romania
Bogdan Andrei Dumitrescu; Vasile Dedu
2009-01-01
This paper aims to estimate the equilibrium real exchange rate for Romania, respectively the real exchange rate consistent with the macroeconomic balance, which is achieved when the economy is operating at full employment and low inflation (internal balance) and has a current account that is sustainable (external balance). This equilibrium real exchange rate is very important for an economy because deviations of the real exchange rate from its equilibrium value can affect the competitiveness ...
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
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.
Uncertainty Quantification of the Real-Time Reserves for Offshore Wind Power Plants
DEFF Research Database (Denmark)
Göçmen, Tuhfe; Giebel, Gregor; Réthoré, Pierre-Elouan
In order to retain the system stability, the wind power plants are required to provide ancillary services. One of those services is reserve power. Here in this study, we focus on the real-time reserves which can be traded in the balancing markets and are currently used for compensation under...... mandatory downregulation stated by the transmission system operators (TSOs). The PossPOW project (Possible Power of down-regulated Offshore Wind power plants) developed a real-time power curve of available power for offshore wind farms for use during down-regulation. The follow-up Concert project......(control and uncertainties in real-time power curves of offshore wind power plants) aims to quantify and finally reduce the uncertainty in reserve power, bringing the PossPOW algorithm and the state of the art forecasting methods together. The experiments designed to test the available power estimated by the Poss...
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)
Comprehensive evaluation of attitude and orbit estimation using real earth magnetic field data
Deutschmann, Julie; Bar-Itzhack, Itzhack
1997-01-01
A single, augmented extended Kalman filter (EKF) which simultaneously and autonomously estimates spacecraft attitude and orbit was developed and tested with simulated and real magnetometer and rate data. Since the earth's magnetic field is a function of time and position, and since time is accurately known, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft's orbit, are a function of orbit and attitude errors. These differences can be used to estimate the orbit and attitude. The test results of the EKF with magnetometer and gyro data from three NASA satellites are presented and evaluated.
Senior, Lisa A.
2017-09-15
Several streams used for recreational activities, such as fishing, swimming, and boating, in Chester County, Pennsylvania, are known to have periodic elevated concentrations of fecal coliform bacteria, a type of bacteria used to indicate the potential presence of fecally related pathogens that may pose health risks to humans exposed through water contact. The availability of near real-time continuous stream discharge, turbidity, and other water-quality data for some streams in the county presents an opportunity to use surrogates to estimate near real-time concentrations of fecal coliform (FC) bacteria and thus provide some information about associated potential health risks during recreational use of streams.The U.S. Geological Survey (USGS), in cooperation with the Chester County Health Department (CCHD) and the Chester County Water Resources Authority (CCWRA), has collected discrete stream samples for analysis of FC concentrations during March–October annually at or near five gaging stations where near real-time continuous data on stream discharge, turbidity, and water temperature have been collected since 2007 (or since 2012 at 2 of the 5 stations). In 2014, the USGS, in cooperation with the CCWRA and CCHD, began to develop regression equations to estimate FC concentrations using available near real-time continuous data. Regression equations included possible explanatory variables of stream discharge, turbidity, water temperature, and seasonal factors calculated using Julian Day with base-10 logarithmic (log) transformations of selected variables.The regression equations were developed using the data from 2007 to 2015 (101–106 discrete bacteria samples per site) for three gaging stations on Brandywine Creek (West Branch Brandywine Creek at Modena, East Branch Brandywine Creek below Downingtown, and Brandywine Creek at Chadds Ford) and from 2012 to 2015 (37–38 discrete bacteria samples per site) for one station each on French Creek near Phoenixville and
Real-time estimation of FLE for point-based registration
Wiles, Andrew D.; Peters, Terry M.
2009-02-01
In image-guide surgery, optimizing the accuracy in localizing the surgical tools within the virtual reality environment or 3D image is vitally important, significant effort has been spent reducing the measurement errors at the point of interest or target. This target registration error (TRE) is often defined by a root-mean-square statistic which reduces the vector data to a single term that can be minimized. However, lost in the data reduction is the directionality of the error which, can be modelled using a 3D covariance matrix. Recently, we developed a set of expressions that modeled the TRE statistics for point-based registrations as a function of the fiducial marker geometry, target location and the fiducial localizer error (FLE). Unfortunately, these expressions are only as good as the definition of the FLE. In order to close the gap, we have subsequently developed a closed form expression that estimates the FLE as a function of the estimated fiducial registration error (FRE, the error between the measured fiducials and the best fit locations of those fiducials). The FRE covariance matrix is estimated using a sliding window technique and used as input into the closed form expression to estimate the FLE. The estimated FLE can then used to estimate the TRE which, can be given to the surgeon to permit the procedure to be designed such that the errors associated with the point-based registrations are minimized.
Heterogeneous Embedded Real-Time Systems Environment
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
Demonstration of real-time control for poloidal beta in KSTAR
Energy Technology Data Exchange (ETDEWEB)
Han, Hyunsun, E-mail: hyunsun@nfri.re.kr [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Hahn, S.H.; Bak, J.G. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Hyatt, A.; Johnson, R. [General Atomics, San Diego, CA (United States); Woo, M.H.; Kim, J.S.; Bae, Y.S. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of)
2015-06-15
Highlights: • Real time control system for poloidal beta has been designed in KSTAR. • Poloidal beta has been calculated based on the diamagnetic loop signals. • The neutral beam Injector plays a role as the actuator. • The control system has been validated in the KSTAR experiments. - Abstract: Sustaining the plasma in a stable and a high performance condition is one of the important control issues for future steady state tokamaks. In the 2014 KSTAR campaign, we have developed a real-time poloidal beta (β{sub p}) control technique and carried out preliminary experiments to identify its feasibility. In the control system, the β{sub p} is calculated in real time using the measured diamagnetic loop signal, and compared with the target value leading to the change of the neutral beam (NB) heating power using a feedback PID control algorithm. To match the requested power of NB which is operated with constant voltage, the on-time periods of the intervals were adjusted as the ratio of the required power to the maximum achievable one. This paper will present the overall procedures of the β{sub p} control, the β{sub p} estimation process and NB operation scheme implemented in the plasma control system (PCS), and the analysis on the preliminary experimental results.
Demonstration of real-time control for poloidal beta in KSTAR
International Nuclear Information System (INIS)
Han, Hyunsun; Hahn, S.H.; Bak, J.G.; Hyatt, A.; Johnson, R.; Woo, M.H.; Kim, J.S.; Bae, Y.S.
2015-01-01
Highlights: • Real time control system for poloidal beta has been designed in KSTAR. • Poloidal beta has been calculated based on the diamagnetic loop signals. • The neutral beam Injector plays a role as the actuator. • The control system has been validated in the KSTAR experiments. - Abstract: Sustaining the plasma in a stable and a high performance condition is one of the important control issues for future steady state tokamaks. In the 2014 KSTAR campaign, we have developed a real-time poloidal beta (β p ) control technique and carried out preliminary experiments to identify its feasibility. In the control system, the β p is calculated in real time using the measured diamagnetic loop signal, and compared with the target value leading to the change of the neutral beam (NB) heating power using a feedback PID control algorithm. To match the requested power of NB which is operated with constant voltage, the on-time periods of the intervals were adjusted as the ratio of the required power to the maximum achievable one. This paper will present the overall procedures of the β p control, the β p estimation process and NB operation scheme implemented in the plasma control system (PCS), and the analysis on the preliminary experimental results
Lee, Michael T.; Asquith, William H.; Oden, Timothy D.
2012-01-01
In December 2005, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (Escherichia coli and total coliform), atrazine, and suspended sediment at two USGS streamflow-gaging stations that represent watersheds contributing to Lake Houston (08068500 Spring Creek near Spring, Tex., and 08070200 East Fork San Jacinto River near New Caney, Tex.). Data from the discrete water-quality samples collected during 2005–9, in conjunction with continuously monitored real-time data that included streamflow and other physical water-quality properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), were used to develop regression models for the estimation of concentrations of water-quality constituents of substantial source watersheds to Lake Houston. The potential explanatory variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, and time (to account for seasonal variations inherent in some water-quality data). The response variables (the selected constituents) at each site were nitrite plus nitrate nitrogen, total phosphorus, total organic carbon, E. coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities to serve as potential surrogate variables to estimate concentrations of the selected constituents through statistical regression. Statistical regression also facilitates accompanying estimates of uncertainty in the form of prediction intervals. Each regression model potentially can be used to estimate concentrations of a given constituent in real time. Among other regression diagnostics, the diagnostics used as indicators of general model reliability and reported herein include the adjusted R-squared, the residual standard error, residual plots, and p-values. Adjusted R-squared values for the Spring Creek models ranged
Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.
2015-06-01
The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.
Temporal Proof Methodologies for Real-Time Systems,
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
Deep neural networks to enable real-time multimessenger astrophysics
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 communication protocols: an overview
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
Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach
Miran, Sina; Akram, Sahar; Sheikhattar, Alireza; Simon, Jonathan Z.; Zhang, Tao; Babadi, Behtash
2018-01-01
Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach). To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1) Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2) Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3) Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our proposed
Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach
Directory of Open Access Journals (Sweden)
Sina Miran
2018-05-01
Full Text Available Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG and electroencephalography (EEG. To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach or vice versa (the encoding approach. To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1 Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2 Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3 Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our
Self-Organization in Embedded Real-Time Systems
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
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.
Zhao, Kaiguang
LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of
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...
Real-time image restoration for iris recognition systems.
Kang, Byung Jun; Park, Kang Ryoung
2007-12-01
In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower recognition performance, since iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time iris image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: 1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input iris images; 2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; 3) because the PSF parameter can be obtained by using a predetermined equation, iris image restoration can be done in real-time; 4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and 5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of image blurring. Experimental results showed that iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous iris-restoration methods.
Real-time analysis of water movement in plant sample
International Nuclear Information System (INIS)
Yokota, Harumi; Furukawa, Jun; Tanoi, Keitaro
2000-01-01
To know the effect of drought stress on two cultivars of cowpea, drought tolerant (DT) and drought sensitive (DS), and to estimate vanadium treatment on plant activity, we performed real time 18 F labeled water uptake measurement by PETIS. Fluoride-18 was produced by bombarding a cubic ice target with 50 MeV protons using TIARA AVF cyclotron. Then 18 F labeled water was applied to investigate water movement in a cowpea plant. Real time water uptake manner could be monitored by PETIS. After the analysis by PETIS, we also measured the distribution of 18 F in a whole plant by BAS. When a cowpea plant was treated with drought stress, there was a difference in water uptake manner between DT and DS cultivar. When a cowpea plant was treated with V for 20 hours before the water uptake experiment, the total amount of 18 F labeled water absorption was found to be drastically decreased. (author)
Real-time analysis of water movement in plant sample
Energy Technology Data Exchange (ETDEWEB)
Yokota, Harumi; Furukawa, Jun; Tanoi, Keitaro [Graduate School, Tokyo Univ. (Japan)
2000-07-01
To know the effect of drought stress on two cultivars of cowpea, drought tolerant (DT) and drought sensitive (DS), and to estimate vanadium treatment on plant activity, we performed real time{sup 18}F labeled water uptake measurement by PETIS. Fluoride-18 was produced by bombarding a cubic ice target with 50 MeV protons using TIARA AVF cyclotron. Then {sup 18}F labeled water was applied to investigate water movement in a cowpea plant. Real time water uptake manner could be monitored by PETIS. After the analysis by PETIS, we also measured the distribution of {sup 18}F in a whole plant by BAS. When a cowpea plant was treated with drought stress, there was a difference in water uptake manner between DT and DS cultivar. When a cowpea plant was treated with V for 20 hours before the water uptake experiment, the total amount of {sup 18}F labeled water absorption was found to be drastically decreased. (author)
Real Time In-circuit Condition Monitoring of MOSFET in Power Converters
Directory of Open Access Journals (Sweden)
Shakeb A. Khan
2015-03-01
Full Text Available Abstract:This paper presents simple and low-cost, real time in-circuit condition monitoring of MOSFET in power electronic converters. Design metrics requirements like low cost, small size, high power factor, low percentage of total harmonic distortion etc. requires the power electronic systems to operate at high frequencies and at high power density. Failures of power converters are attributed largely by aging of power MOSFETs at high switching frequencies. Therefore, real time in-circuit prognostic of MOSFET needs to be done before their selection for power system design. Accelerated aging tests are performed in different circuits to determine the wear out failure of critical components based on their parametric degradation. In this paper, the simple and low-cost test beds are designed for real time in-circuit prognostics of power MOSFETs. The proposed condition monitoring scheme helps in estimating the condition of MOSFETs at their maximum rated operating condition and will aid the system designers to test their reliability and benchmark them before selecting in power converters.
Real time material accountability in a chemical reprocessing unit
International Nuclear Information System (INIS)
Morrison, G.W.; Blakeman, E.D.
1979-01-01
Real time material accountability for a pulse column in a chemical reprocessing plant has been investigated using a simple two state Kalman Filter. Operation of the pulse column was simulated by the SEPHIS-MOD4 code. Noisy measurements of the column inventory were obtained from two neutron detectors with various simulated counting errors. Various loss scenarios were simulated and analyzed by the Kalman Filter. In all cases considered the Kalman Filter was a superior estimator of material loss
Real-time recursive motion segmentation of video data on a programmable device
Wittebrood, R.B; Haan, de G.
2001-01-01
We previously reported on a recursive algorithm enabling real-time object-based motion estimation (OME) of standard definition video on a digital signal processor (DSP). The algorithm approximates the motion of the objects in the image with parametric motion models and creates a segmentation mask by
Blanken, T.C.; Felici, F.; Rapson, C.J.; de Baar, M.R.; Heemels, W.P.M.H.
2018-01-01
A model-based approach to real-time reconstruction of the particle density profile in tokamak plasmas is presented, based on a dynamic state estimator. Traditionally, the density profile is reconstructed in real-time by solving an ill-conditioned inversion problem using a measurement at a single
Real-Time Multi-Target Localization from Unmanned Aerial Vehicles
Directory of Open Access Journals (Sweden)
Xuan Wang
2016-12-01
Full Text Available In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1 the real-time zoom lens distortion correction method; (2 a recursive least squares (RLS filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.
IMPLEMENTATION OF A REAL-TIME STACKING ALGORITHM IN A PHOTOGRAMMETRIC DIGITAL CAMERA FOR UAVS
Directory of Open Access Journals (Sweden)
A. Audi
2017-08-01
Full Text Available In the recent years, unmanned aerial vehicles (UAVs have become an interesting tool in aerial photography and photogrammetry activities. In this context, some applications (like cloudy sky surveys, narrow-spectral imagery and night-vision imagery need a longexposure time where one of the main problems is the motion blur caused by the erratic camera movements during image acquisition. This paper describes an automatic real-time stacking algorithm which produces a high photogrammetric quality final composite image with an equivalent long-exposure time using several images acquired with short-exposure times. Our method is inspired by feature-based image registration technique. The algorithm is implemented on the light-weight IGN camera, which has an IMU sensor and a SoC/FPGA. To obtain the correct parameters for the resampling of images, the presented method accurately estimates the geometrical relation between the first and the Nth image, taking into account the internal parameters and the distortion of the camera. Features are detected in the first image by the FAST detector, than homologous points on other images are obtained by template matching aided by the IMU sensors. The SoC/FPGA in the camera is used to speed up time-consuming parts of the algorithm such as features detection and images resampling in order to achieve a real-time performance as we want to write only the resulting final image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images, as well as block diagrams of the described architecture. The resulting stacked image obtained on real surveys doesn’t seem visually impaired. Timing results demonstrate that our algorithm can be used in real-time since its processing time is less than the writing time of an image in the storage device. An interesting by-product of this algorithm is the 3D rotation
On Real-Time Systems Using Local Area Networks.
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
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.
Improved Strategies and Optimization of Calibration Models for Real-time PCR Absolute Quantification
Real-time PCR absolute quantification applications rely on the use of standard curves to make estimates of DNA target concentrations in unknown samples. Traditional absolute quantification approaches dictate that a standard curve must accompany each experimental run. However, t...
Mixed-mode Operating System for Real-time Performance
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...
Real-time long term measurement using integrated framework for ubiquitous smart monitoring
Heo, Gwanghee; Lee, Giu; Lee, Woosang; Jeon, Joonryong; Kim, Pil-Joong
2007-04-01
Ubiquitous monitoring combining internet technologies and wireless communication is one of the most promising technologies of infrastructure health monitoring against the natural of man-made hazards. In this paper, an integrated framework of the ubiquitous monitoring is developed for real-time long term measurement in internet environment. This framework develops a wireless sensor system based on Bluetooth technology and sends measured acceleration data to the host computer through TCP/IP protocol. And it is also designed to respond to the request of web user on real time basis. In order to verify this system, real time monitoring tests are carried out on a prototype self-anchored suspension bridge. Also, wireless measurement system is analyzed to estimate its sensing capacity and evaluate its performance for monitoring purpose. Based on the evaluation, this paper proposes the effective strategies for integrated framework in order to detect structural deficiencies and to design an early warning system.
Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold
2004-01-01
Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.
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
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
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....
Towards exascale real-time RFI mitigation
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,
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...
Interfacing real-time information with OILMAP
International Nuclear Information System (INIS)
Howlett, E.; Jayko, K.; Spaulding, M.
1993-01-01
OILMAP is a state-of-the-art, microcomputer-based oil spill response system applicable to oil spill contingency planning and real-time response for any location in the world. OILMAP has a graphic user interface and was designed in a modular framework so that different spill models could be incorporated into the system, as well as a suite of sophisticated data management tools, without increasing the complexity of the user interface. The basic OILMAP configuration contains a surface trajectory model intended for rapid, first-order estimates of spill movement. A variety of additional models are available within the OILMAP shell to address issues such as weathering, cleanup activities, and probabilities of oiling. A simplified geographic information system (GIS) allows display and manipulation of point, line, and area data geographically referenced to the spill domain. The GIS can import raster data so that images collected by satellite and aerial photography may be displayed. Several new capabilities have been implemented for OILMAP that allow real-time data to be integrated. These features include linking with the OILTRACKER free-floating buoys via a global positioning system, linking of hydrodynamic data from the Ocean Data and Information Network, the Harvard ocean forecasting system, and SeaSonde radar, and the capability of importing spill observations from any remotely sensed data. A further link between OILMAP's GIS and spill models has been developed which allows model predictions to be corrected to observed oil locations while the model runs. 13 refs., 6 figs
A revealed-preference study of behavioural impacts of real-time traffic information
Knockaert, J.S.A.; Tseng, Y.; Verhoef, E.T.
2013-01-01
In the present study, we investigate the impact of real-time traffic information on traveller behaviour by using repeated day-to-day revealed-preference (RP) observations from a reward experiment. We estimate a trip scheduling model of morning peak behaviour that allows us to determine the impact of
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
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
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.
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
[Real time 3D echocardiography
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.
The potential role of real-time geodetic observations in tsunami early warning
Tinti, Stefano; Armigliato, Alberto
2016-04-01
Tsunami warning systems (TWS) have the final goal to launch a reliable alert of an incoming dangerous tsunami to coastal population early enough to allow people to flee from the shore and coastal areas according to some evacuation plans. In the last decade, especially after the catastrophic 2004 Boxing Day tsunami in the Indian Ocean, much attention has been given to filling gaps in the existing TWSs (only covering the Pacific Ocean at that time) and to establishing new TWSs in ocean regions that were uncovered. Typically, TWSs operating today work only on earthquake-induced tsunamis. TWSs estimate quickly earthquake location and size by real-time processing seismic signals; on the basis of some pre-defined "static" procedures (either based on decision matrices or on pre-archived tsunami simulations), assess the tsunami alert level on a large regional scale and issue specific bulletins to a pre-selected recipients audience. Not unfrequently these procedures result in generic alert messages with little value. What usually operative TWSs do not do, is to compute earthquake focal mechanism, to calculate the co-seismic sea-floor displacement, to assess the initial tsunami conditions, to input these data into tsunami simulation models and to compute tsunami propagation up to the threatened coastal districts. This series of steps is considered nowadays too time consuming to provide the required timely alert. An equivalent series of steps could start from the same premises (earthquake focal parameters) and reach the same result (tsunami height at target coastal areas) by replacing the intermediate steps of real-time tsunami simulations with proper selection from a large archive of pre-computed tsunami scenarios. The advantage of real-time simulations and of archived scenarios selection is that estimates are tailored to the specific occurring tsunami and alert can be more detailed (less generic) and appropriate for local needs. Both these procedures are still at an
Application and API for Real-time Visualization of Ground-motions and Tsunami
Aoi, S.; Kunugi, T.; Suzuki, W.; Kubo, T.; Nakamura, H.; Azuma, H.; Fujiwara, H.
2015-12-01
Due to the recent progress of seismograph and communication environment, real-time and continuous ground-motion observation becomes technically and economically feasible. K-NET and KiK-net, which are nationwide strong motion networks operated by NIED, cover all Japan by about 1750 stations in total. More than half of the stations transmit the ground-motion indexes and/or waveform data in every second. Traditionally, strong-motion data were recorded by event-triggering based instruments with non-continues telephone line which is connected only after an earthquake. Though the data from such networks mainly contribute to preparations for future earthquakes, huge amount of real-time data from dense network are expected to directly contribute to the mitigation of ongoing earthquake disasters through, e.g., automatic shutdown plants and helping decision-making for initial response. By generating the distribution map of these indexes and uploading them to the website, we implemented the real-time ground motion monitoring system, Kyoshin (strong-motion in Japanese) monitor. This web service (www.kyoshin.bosai.go.jp) started in 2008 and anyone can grasp the current ground motions of Japan. Though this service provides only ground-motion map in GIF format, to take full advantage of real-time strong-motion data to mitigate the ongoing disasters, digital data are important. We have developed a WebAPI to provide real-time data and related information such as ground motions (5 km-mesh) and arrival times estimated from EEW (earthquake early warning). All response data from this WebAPI are in JSON format and are easy to parse. We also developed Kyoshin monitor application for smartphone, 'Kmoni view' using the API. In this application, ground motions estimated from EEW are overlapped on the map with the observed one-second-interval indexes. The application can playback previous earthquakes for demonstration or disaster drill. In mobile environment, data traffic and battery are
Real-time quasi-3D tomographic reconstruction
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.
Zardad, Asma; Mohsin, Asma; Zaman, Khalid
2013-12-01
The purpose of this study is to investigate the factors that affect real exchange rate volatility for Pakistan through the co-integration and error correction model over a 30-year time period, i.e. between 1980 and 2010. The study employed the autoregressive conditional heteroskedasticity (ARCH), generalized autoregressive conditional heteroskedasticity (GARCH) and Vector Error Correction model (VECM) to estimate the changes in the volatility of real exchange rate series, while an error correction model was used to determine the short-run dynamics of the system. The study is limited to a few variables i.e., productivity differential (i.e., real GDP per capita relative to main trading partner); terms of trade; trade openness and government expenditures in order to manage robust data. The result indicates that real effective exchange rate (REER) has been volatile around its equilibrium level; while, the speed of adjustment is relatively slow. VECM results confirm long run convergence of real exchange rate towards its equilibrium level. Results from ARCH and GARCH estimation shows that real shocks volatility persists, so that shocks die out rather slowly, and lasting misalignment seems to have occurred.
The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS
Li, Xingxing; Ge, Maorong; Zhang, Hongping; Nischan, Thomas; Wickert, Jens
2013-03-01
Motivated by the IGS real-time Pilot Project, GFZ has been developing its own real-time precise positioning service for various applications. An operational system at GFZ is now broadcasting real-time orbits, clocks, global ionospheric model, uncalibrated phase delays and regional atmospheric corrections for standard PPP, PPP with ambiguity fixing, single-frequency PPP and regional augmented PPP. To avoid developing various algorithms for different applications, we proposed a uniform algorithm and implemented it into our real-time software. In the new processing scheme, we employed un-differenced raw observations with atmospheric delays as parameters, which are properly constrained by real-time derived global ionospheric model or regional atmospheric corrections and by the empirical characteristics of the atmospheric delay variation in time and space. The positioning performance in terms of convergence time and ambiguity fixing depends mainly on the quality of the received atmospheric information and the spatial and temporal constraints. The un-differenced raw observation model can not only integrate PPP and NRTK into a seamless positioning service, but also syncretize these two techniques into a unique model and algorithm. Furthermore, it is suitable for both dual-frequency and sing-frequency receivers. Based on the real-time data streams from IGS, EUREF and SAPOS reference networks, we can provide services of global precise point positioning (PPP) with 5-10 cm accuracy, PPP with ambiguity-fixing of 2-5 cm accuracy, PPP using single-frequency receiver with accuracy of better than 50 cm and PPP with regional augmentation for instantaneous ambiguity resolution of 1-3 cm accuracy. We adapted the system for current COMPASS to provide PPP service. COMPASS observations from a regional network of nine stations are used for precise orbit determination and clock estimation in simulated real-time mode, the orbit and clock products are applied for real-time precise point
An algorithm for learning real-time automata
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
Real-time Loudspeaker Distance Estimation with Stereo Audio
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Gaubitch, Nikolay; Heusdens, Richard
2015-01-01
Knowledge on how a number of loudspeakers are positioned relative to a listening position can be used to enhance the listening experience. Usually, these loudspeaker positions are estimated using calibration signals, either audible or psycho-acoustically hidden inside the desired audio signal...
De toekomst van Real Time Intelligence
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 process algebra with time-dependent conditions
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
Numerical simulation of a cabin ventilation subsystem in a space station oriented real-time system
Directory of Open Access Journals (Sweden)
Zezheng QIU
2017-12-01
Full Text Available An environment control and life support system (ECLSS is an important system in a space station. The ECLSS is a typical complex system, and the real-time simulation technology can help to accelerate its research process by using distributed hardware in a loop simulation system. An implicit fixed time step numerical integration method is recommended for a real-time simulation system with time-varying parameters. However, its computational efficiency is too low to satisfy the real-time data interaction, especially for the complex ECLSS system running on a PC cluster. The instability problem of an explicit method strongly limits its application in the ECLSS real-time simulation although it has a high computational efficiency. This paper proposes an improved numerical simulation method to overcome the instability problem based on the explicit Euler method. A temperature and humidity control subsystem (THCS is firstly established, and its numerical stability is analyzed by using the eigenvalue estimation theory. Furthermore, an adaptive operator is proposed to avoid the potential instability problem. The stability and accuracy of the proposed method are investigated carefully. Simulation results show that this proposed method can provide a good way for some complex time-variant systems to run their real-time simulation on a PC cluster. Keywords: Numerical integration method, Real-time simulation, Stability, THCS, Time-variant system
Real-Time Energy Management System for a Hybrid AC/DC Residential Microgrid
DEFF Research Database (Denmark)
Diaz, Enrique Rodriguez; Palacios-Garcia, Emilio J.; Anvari-Moghaddam, Amjad
2017-01-01
This paper proposes real-time Energy Management System (EMS) for a residential hybrid ac/dc microgrid. The residential microgrid is organized in two different distribution systems. A dc distribution bus which interconnect the renewable energy sources (RES), energy storage systems (ESS...... buildings. This architecture increases the overall efficiency of the distribution by interconnecting the RES and ESS thorough a dc distribution bus, and therefore avoiding unnecessary dc/ac conversion stages. The real-time EMS performs an 24 hours ahead optimization in order to schedule the charge...... setup. The results shown how the operational costs of the system are effectively decreased by 28%, even with non-accurate estimation of the RES generation or building parameters....
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
International Nuclear Information System (INIS)
Mukherjee, Bhaskar.
2002-01-01
Large activities of short-lived positron emitting radiopharmaceuticals are routinely manufactured by modern Medical Cyclotron facilities for positron emission tomography (PET) applications. During radiochemical processing, a substantial fraction of the volatile positron emitting radiopharmaceuticals are released into the atmosphere. An inexpensive, fast response positron detector using a simple positron-annihilation chamber has been developed for real-time assessment of the stack release of positron emitting effluents at the Australian National Medical Cyclotron. The positron detector was calibrated by using a 3.0 ml (1.50 MBq) aliquot of 18 FDG and interfaced to an industrial standard datalogger for the real-time acquisition of stack release data
Real Time Linux - The RTOS for Astronomy?
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
Forecasting surface water flooding hazard and impact in real-time
Cole, Steven J.; Moore, Robert J.; Wells, Steven C.
2016-04-01
Across the world, there is increasing demand for more robust and timely forecast and alert information on Surface Water Flooding (SWF). Within a UK context, the government Pitt Review into the Summer 2007 floods provided recommendations and impetus to improve the understanding of SWF risk for both off-line design and real-time forecasting and warning. Ongoing development and trial of an end-to-end real-time SWF system is being progressed through the recently formed Natural Hazards Partnership (NHP) with delivery to the Flood Forecasting Centre (FFC) providing coverage over England & Wales. The NHP is a unique forum that aims to deliver coordinated assessments, research and advice on natural hazards for governments and resilience communities across the UK. Within the NHP, a real-time Hazard Impact Model (HIM) framework has been developed that includes SWF as one of three hazards chosen for initial trialling. The trial SWF HIM system uses dynamic gridded surface-runoff estimates from the Grid-to-Grid (G2G) hydrological model to estimate the SWF hazard. National datasets on population, infrastructure, property and transport are available to assess impact severity for a given rarity of SWF hazard. Whilst the SWF hazard footprint is calculated in real-time using 1, 3 and 6 hour accumulations of G2G surface runoff on a 1 km grid, it has been possible to associate these with the effective rainfall design profiles (at 250m resolution) used as input to a detailed flood inundation model (JFlow+) run offline to produce hazard information resolved to 2m resolution. This information is contained in the updated Flood Map for Surface Water (uFMfSW) held by the Environment Agency. The national impact datasets can then be used with the uFMfSW SWF hazard dataset to assess impacts at this scale and severity levels of potential impact assigned at 1km and for aggregated county areas in real-time. The impact component is being led by the Health and Safety Laboratory (HSL) within the NHP
A Programmable Microkernel for Real-Time Systems
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
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
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.
International Nuclear Information System (INIS)
Gladstone, D.J.; Chin, L.M.
1995-01-01
This report presents the first real-time measurement of absorbed radiation dose during radioimmunotherapy in mice. Dose rate and total dose at the center of the tumor were measured after administration of 90 Y-labeled antibodies using a miniature metal oxide semiconductor field-effect transistor radiation dosimeter probe which was inserted into the center of the tumor volume. Continuous real-time measurements were made for as long as 23 h after injection of the radiolabeled antibodies. Comparison of the real-time dose-rate measurements with estimates based on the MIRD formalism indicates good agreement. The real-time measurements are further compared to measurements made in a second experiment in which groups of mice were sacrificed at individual times after injection of the same radiolabeled antibodies. The real-time measurements agree well with the measurements in excised tumors. The real-time measurements have greater time resolution and are much more efficient than traditional uptake measurements. 17 refs., 2 figs
Estimation of real-time N load in surface water using dynamic data driven application system
Y. Ouyang; S.M. Luo; L.H. Cui; Q. Wang; J.E. Zhang
2011-01-01
Agricultural, industrial, and urban activities are the major sources for eutrophication of surface water ecosystems. Currently, determination of nutrients in surface water is primarily accomplished by manually collecting samples for laboratory analysis, which requires at least 24 h. In other words, little to no effort has been devoted to monitoring real-time variations...
Picozzi, M.; Bindi, D.; Pittore, M.; Kieling, K.; Parolai, S.
2013-04-01
Earthquake early warning systems (EEWS) are considered to be an effective, pragmatic, and viable tool for seismic risk reduction in cities. While standard EEWS approaches focus on the real-time estimation of an earthquake's location and magnitude, innovative developments in EEWS include the capacity for the rapid assessment of damage. Clearly, for all public authorities that are engaged in coordinating emergency activities during and soon after earthquakes, real-time information about the potential damage distribution within a city is invaluable. In this work, we present a first attempt to design an early warning and rapid response procedure for real-time risk assessment. In particular, the procedure uses typical real-time information (i.e., P-wave arrival times and early waveforms) derived from a regional seismic network for locating and evaluating the size of an earthquake, information which in turn is exploited for extracting a risk map representing the potential distribution of damage from a dataset of predicted scenarios compiled for the target city. A feasibility study of the procedure is presented for the city of Bishkek, the capital of Kyrgyzstan, which is surrounded by the Kyrgyz seismic network by mimicking the ground motion associated with two historical events that occurred close to Bishkek, namely the 1911 Kemin ( M = 8.2; ±0.2) and the 1885 Belovodsk ( M = 6.9; ±0.5) earthquakes. Various methodologies from previous studies were considered when planning the implementation of the early warning and rapid response procedure for real-time risk assessment: the Satriano et al. (Bull Seismol Soc Am 98(3):1482-1494, 2008) approach to real-time earthquake location; the Caprio et al. (Geophys Res Lett 38:L02301, 2011) approach for estimating moment magnitude in real time; the EXSIM method for ground motion simulation (Motazedian and Atkinson, Bull Seismol Soc Am 95:995-1010, 2005); the Sokolov (Earthquake Spectra 161: 679-694, 2002) approach for estimating
Shape based kinetic outlier detection in real-time PCR
Directory of Open Access Journals (Sweden)
D'Atri Mario
2010-04-01
Full Text Available Abstract Background Real-time PCR has recently become the technique of choice for absolute and relative nucleic acid quantification. The gold standard quantification method in real-time PCR assumes that the compared samples have similar PCR efficiency. However, many factors present in biological samples affect PCR kinetic, confounding quantification analysis. In this work we propose a new strategy to detect outlier samples, called SOD. Results Richards function was fitted on fluorescence readings to parameterize the amplification curves. There was not a significant correlation between calculated amplification parameters (plateau, slope and y-coordinate of the inflection point and the Log of input DNA demonstrating that this approach can be used to achieve a "fingerprint" for each amplification curve. To identify the outlier runs, the calculated parameters of each unknown sample were compared to those of the standard samples. When a significant underestimation of starting DNA molecules was found, due to the presence of biological inhibitors such as tannic acid, IgG or quercitin, SOD efficiently marked these amplification profiles as outliers. SOD was subsequently compared with KOD, the current approach based on PCR efficiency estimation. The data obtained showed that SOD was more sensitive than KOD, whereas SOD and KOD were equally specific. Conclusion Our results demonstrated, for the first time, that outlier detection can be based on amplification shape instead of PCR efficiency. SOD represents an improvement in real-time PCR analysis because it decreases the variance of data thus increasing the reliability of quantification.
Mechatronic modeling of real-time wheel-rail contact
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.
Osada, Y.; Ohta, Y.; Demachi, T.; Kido, M.; Fujimoto, H.; Azuma, R.; Hino, R.
2013-12-01
Large interplate earthquake repeatedly occurred in Japan Trench. Recently, the detail crustal deformation revealed by the nation-wide inland GPS network called as GEONET by GSI. However, the maximum displacement region for interplate earthquake is mainly located offshore region. GPS/Acoustic seafloor geodetic observation (hereafter GPS/A) is quite important and useful for understanding of shallower part of the interplate coupling between subducting and overriding plates. We typically conduct GPS/A in specific ocean area based on repeated campaign style using research vessel or buoy. Therefore, we cannot monitor the temporal variation of seafloor crustal deformation in real time. The one of technical issue on real time observation is kinematic GPS analysis because kinematic GPS analysis based on reference and rover data. If the precise kinematic GPS analysis will be possible in the offshore region, it should be promising method for real time GPS/A with USV (Unmanned Surface Vehicle) and a moored buoy. We assessed stability, precision and accuracy of StarFireTM global satellites based augmentation system. We primarily tested for StarFire in the static condition. In order to assess coordinate precision and accuracy, we compared 1Hz StarFire time series and post-processed precise point positioning (PPP) 1Hz time series by GIPSY-OASIS II processing software Ver. 6.1.2 with three difference product types (ultra-rapid, rapid, and final orbits). We also used difference interval clock information (30 and 300 seconds) for the post-processed PPP processing. The standard deviation of real time StarFire time series is less than 30 mm (horizontal components) and 60 mm (vertical component) based on 1 month continuous processing. We also assessed noise spectrum of the estimated time series by StarFire and post-processed GIPSY PPP results. We found that the noise spectrum of StarFire time series is similar pattern with GIPSY-OASIS II processing result based on JPL rapid orbit
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...
Automated real-time software development
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.
Real time n/γ discrimination for the JET neutron profile monitor
Energy Technology Data Exchange (ETDEWEB)
Riva, M., E-mail: marco.riva@enea.it [Associazione EURATOM-ENEA sulla Fusione, C.P. 65, Frascati I-00044, Roma (Italy); Esposito, B.; Marocco, D.; Belli, F. [Associazione EURATOM-ENEA sulla Fusione, C.P. 65, Frascati I-00044, Roma (Italy); Syme, B. [EURATOM/CCFE Fusion Association, OX14 3DB Abingdon (United Kingdom); Giacomelli, L. [Dipartimento di Fisica, Università degli Studi di Milano-Bicocca (Italy); Istituto di Fisica del Plasma, Associazione EURATOM-ENEA-CNR, 20100 Milano (Italy); JET-EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)
2013-10-15
Highlights: ► Development of a pulse oriented acquisition system able for the JET neutron profile monitor to separate neutron and gamma pulses. ► Description of the FPGA hardware architecture. ► Comparison between the off-line and real time neutron count rates from the last JET experimental campaign. ► Estimate of the maximum sustainable count rate of the system. ► Statistical analysis of neutron measurements from JET neutron profile monitor and neutron monitors. -- Abstract: The JET neutron profile monitor provides the measurement of the neutron flux along 19 collimated lines of sight from which the neutron emissivity profile can be obtained through reconstruction based on inversion methods. The neutron detectors are liquid organic scintillators featuring n/γ pulse shape discrimination. A recent digital upgrade of the neutron profile monitor acquisition system (200 MSamples/s sampling rate per channel, 14 bit resolution) offers new real-time capabilities. An algorithm performing real-time n/γ discrimination by means of the charge comparison method is implemented in the acquisition system FPGA. The algorithm produces two distinct count rates (n and γ) that are sent to the JET real time network ready for control applications and are simultaneously stored into the JET archive together with all the samples of each pulse. The paper describes the architecture of the FPGA implementation and reports the analysis of data collected during the 2011–2012 JET campaigns. The comparison between the real-time and post-processed (off-line) neutron count rates shows an agreement within 5% for all 19 detectors. Moreover, it is shown that the maximum count rate sustainable by the acquisition system when storing raw data (∼900 kHz as evaluated in laboratory tests) can be extended up to 5 MHz when using the real-time implementation with no local data storage. Finally, a statistical analysis of the ratio between the line-integrated measurements from the neutron profile
Si, Liang; Baier, Horst
2015-07-08
For the future design of smart aerospace structures, the development and application of a reliable, real-time and automatic monitoring and diagnostic technique is essential. Thus, with distributed sensor networks, a real-time automatic structural health monitoring (SHM) technique is designed and investigated to monitor and predict the locations and force magnitudes of unforeseen foreign impacts on composite structures and to estimate in real time mode the structural state when impacts occur. The proposed smart impact visualization inspection (IVI) technique mainly consists of five functional modules, which are the signal data preprocessing (SDP), the forward model generator (FMG), the impact positioning calculator (IPC), the inverse model operator (IMO) and structural state estimator (SSE). With regard to the verification of the practicality of the proposed IVI technique, various structure configurations are considered, which are a normal CFRP panel and another CFRP panel with "orange peel" surfaces and a cutout hole. Additionally, since robustness against several background disturbances is also an essential criterion for practical engineering demands, investigations and experimental tests are carried out under random vibration interfering noise (RVIN) conditions. The accuracy of the predictions for unknown impact events on composite structures using the IVI technique is validated under various structure configurations and under changing environmental conditions. The evaluated errors all fall well within a satisfactory limit range. Furthermore, it is concluded that the IVI technique is applicable for impact monitoring, diagnosis and assessment of aerospace composite structures in complex practical engineering environments.
Real-time earthquake data feasible
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.
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.
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
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
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?
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…
Directory of Open Access Journals (Sweden)
Maryam M Shanechi
Full Text Available Real-time brain-machine interfaces (BMI have focused on either estimating the continuous movement trajectory or target intent. However, natural movement often incorporates both. Additionally, BMIs can be modeled as a feedback control system in which the subject modulates the neural activity to move the prosthetic device towards a desired target while receiving real-time sensory feedback of the state of the movement. We develop a novel real-time BMI using an optimal feedback control design that jointly estimates the movement target and trajectory of monkeys in two stages. First, the target is decoded from neural spiking activity before movement initiation. Second, the trajectory is decoded by combining the decoded target with the peri-movement spiking activity using an optimal feedback control design. This design exploits a recursive Bayesian decoder that uses an optimal feedback control model of the sensorimotor system to take into account the intended target location and the sensory feedback in its trajectory estimation from spiking activity. The real-time BMI processes the spiking activity directly using point process modeling. We implement the BMI in experiments consisting of an instructed-delay center-out task in which monkeys are presented with a target location on the screen during a delay period and then have to move a cursor to it without touching the incorrect targets. We show that the two-stage BMI performs more accurately than either stage alone. Correct target prediction can compensate for inaccurate trajectory estimation and vice versa. The optimal feedback control design also results in trajectories that are smoother and have lower estimation error. The two-stage decoder also performs better than linear regression approaches in offline cross-validation analyses. Our results demonstrate the advantage of a BMI design that jointly estimates the target and trajectory of movement and more closely mimics the sensorimotor control system.
Academic Training: Real Time Process Control - Lecture series
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
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.
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.
Real-Time Inhibitor Recession Measurements in the Space Shuttle Reusable Solid Rocket Motors
McWhorter, Bruce B.; Ewing, Mark E.; McCool, Alex (Technical Monitor)
2001-01-01
Real-time char line recession measurements were made on propellant inhibitors of the Space Shuttle Reusable Solid Rocket Motor (RSRM). The RSRM FSM-8 static test motor propellant inhibitors (composed of a rubber insulation material) were successfully instrumented with eroding potentiometers and thermocouples. The data was used to establish inhibitor recession versus time relationships. Normally, pre-fire and post-fire insulation thickness measurements establish the thermal performance of an ablating insulation material. However, post-fire inhibitor decomposition and recession measurements are complicated by the fact that most of the inhibitor is back during motor operation. It is therefore a difficult task to evaluate the thermal protection offered by the inhibitor material. Real-time measurements would help this task. The instrumentation program for this static test motor marks the first time that real-time inhibitors. This report presents that data for the center and aft field joint forward facing inhibitors. The data was primarily used to measure char line recession of the forward face of the inhibitors which provides inhibitor thickness reduction versus time data. The data was also used to estimate the inhibitor height versus time relationship during motor operation.
Virtual timers in hierarchical real-time systems
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
Real-time Volcanic Cloud Products and Predictions for Aviation Alerts
Krotkov, N. A.; Hughes, E. J.; da Silva, A. M., Jr.; Seftor, C. J.; Brentzel, K. W.; Hassinen, S.; Heinrichs, T. A.; Schneider, D. J.; Hoffman, R.; Myers, T.; Flynn, L. E.; Niu, J.; Theys, N.; Brenot, H. H.
2016-12-01
We will discuss progress of the NASA ASP project, which promotes the use of satellite volcanic SO2 (VSO2) and Ash (VA) data, and forecasting tools that enhance VA Decision Support Systems (DSS) at the VA Advisory Centers (VAACs) for prompt aviation warnings. The goals are: (1) transition NASA algorithms to NOAA for global NRT processing and integration into DSS at Washington VAAC for operational users and public dissemination; (2) Utilize Direct Broadcast capability of the Aura and SNPP satellites to process Direct Readout (DR) data at two high latitude locations in Finland and Fairbanks, Alaska to enhance VA DSS in Europe and at USGS's Alaska Volcano Observatory (AVO) and Alaska-VAAC; (3) Improve global Eulerian model-based VA/VSO2 forecasting and risk/cost assessments with Metron Aviation. Our global NRT OMI and OMPS data have been fully integrated into European Support to Aviation Control Service and NOAA operational web sites. We are transitioning OMPS processing to our partners at NOAA/NESDIS to integrate into operational processing environment. NASA's Suomi NPP Ozone Science Team, in conjunction with GSFC's Direct Readout Laboratory (DRL), have implemented Version 2 of the OMPS real-time DR processing package to generate VSO2 and VA products at the Geographic Information Network of Alaska (GINA) and the Finnish Meteorological Institute (FMI). The system provides real-time coverage over some of the most congested airspace and over many of the most active volcanoes in the world. The OMPS real time capability is now publicly available via DRL's IPOPP package. We use satellite observations to define volcanic source term estimates in the NASA GOES-5 model, which was updated allowing for the simulation of VA and VSO2 clouds. Column SO2 observations from SNPP/OMPS provide an initial estimate of the total cloud SO2 mass, and are used with backward transport analysis to make an initial cloud height estimate. Later VSO2 observations are used to "nudge" the SO2 mass
Creation and clinical application of real-time dose monitor using dose area product meter
International Nuclear Information System (INIS)
Matsubara, Kosuke; Uoyama, Yoshinori; Iida, Hiroji; Mizushima, Takashi
2004-01-01
The management of patient dose has become more of an issue in recent years. Dose can be determined non-invasively and in real time through the use of a dose area product meter, but it is the area dose value that is obtained. Therefore, we created a program that estimates entrance skin dose (ESD) in real time from area dose values obtained during procedures. We used Microsoft Visual C++ 6.0 (Standard Edition) for the programming language and C language for the programming environment. The value was a maximum 285.4 mGy at ileus tube insertion when measuring ESD for radiography of the digestive organ and non-vascular type interventional radiology (IVR) using the created program and seeking the average according to the procedures. The program that we created can be considered valid for monitoring ESD correctly and in real time. (author)
A method for real-time three-dimensional vector velocity imaging
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt; Nikolov, Svetoslav
2003-01-01
The paper presents an approach for making real-time three-dimensional vector flow imaging. Synthetic aperture data acquisition is used, and the data is beamformed along the flow direction to yield signals usable for flow estimation. The signals are cross-related to determine the shift in position...... are done using 16 × 16 = 256 elements at a time and the received signals from the same elements are sampled. Access to the individual elements is done through 16-to-1 multiplexing, so that only a 256 channels transmitting and receiving system are needed. The method has been investigated using Field II...
Reactivity estimation using digital nonlinear H∞ estimator for VHTRC experiment
International Nuclear Information System (INIS)
Suzuki, Katsuo; Nabeshima, Kunihiko; Yamane, Tsuyoshi
2003-01-01
On-line and real-time estimation of time-varying reactivity in a nuclear reactor in necessary for early detection of reactivity anomaly and safe operation. Using a digital nonlinear H ∞ estimator, an experiment of real-time dynamic reactivity estimation was carried out in the Very High Temperature Reactor Critical Assembly (VHTRC) of Japan Atomic Energy Research Institute. Some technical issues of the experiment are described, such as reactivity insertion, data sampling frequency, anti-aliasing filter, experimental circuit and digitalising nonlinear H ∞ reactivity estimator, and so on. Then, we discussed the experimental results obtained by the digital nonlinear H ∞ estimator with sampled data of the nuclear instrumentation signal for the power responses under various reactivity insertions. Good performances of estimated reactivity were observed, with almost no delay to the true reactivity and sufficient accuracy between 0.05 cent and 0.1 cent. The experiment shows that real-time reactivity for data sampling period of 10 ms can be certainly realized. From the results of the experiment, it is concluded that the digital nonlinear H ∞ reactivity estimator can be applied as on-line real-time reactivity meter for actual nuclear plants. (author)
Real-time video compressing under DSP/BIOS
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.
Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation
International Nuclear Information System (INIS)
Siohansi, Ramteen
2010-01-01
One of the costs associated with integrating wind generation into a power system is the cost of redispatching the system in real-time due to day-ahead wind resource forecast errors. One possible way of reducing these redispatch costs is to introduce demand response in the form of real-time pricing (RTP), which could allow electricity demand to respond to actual real-time wind resource availability using price signals. A day-ahead unit commitment model with day-ahead wind forecasts and a real-time dispatch model with actual wind resource availability is used to estimate system operations in a high wind penetration scenario. System operations are compared to a perfect foresight benchmark, in which actual wind resource availability is known day-ahead. The results show that wind integration costs with fixed demands can be high, both due to real-time redispatch costs and lost load. It is demonstrated that introducing RTP can reduce redispatch costs and eliminate loss of load events. Finally, social surplus with wind generation and RTP is compared to a system with neither and the results demonstrate that introducing wind and RTP into a market can result in superadditive surplus gains.
Design and implementation of real-time multi-sensor vision systems
Popovic, Vladan; Cogal, Ömer; Akin, Abdulkadir; Leblebici, Yusuf
2017-01-01
This book discusses the design of multi-camera systems and their application to fields such as the virtual reality, gaming, film industry, medicine, automotive industry, drones, etc.The authors cover the basics of image formation, algorithms for stitching a panoramic image from multiple cameras, and multiple real-time hardware system architectures, in order to have panoramic videos. Several specific applications of multi-camera systems are presented, such as depth estimation, high dynamic range imaging, and medical imaging.
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.
2010-03-01
Incidents account for a large portion of all congestion and a need clearly exists for tools to predict and estimate incident effects. This study examined (1) congestion back propagation to estimate the length of the queue and travel time from upstrea...
Real-Time Analysis and Forecasting of Multisite River Flow Using a Distributed Hydrological Model
Directory of Open Access Journals (Sweden)
Mingdong Sun
2014-01-01
Full Text Available A spatial distributed hydrological forecasting system was developed to promote the analysis of river flow dynamic state in a large basin. The research presented the real-time analysis and forecasting of multisite river flow in the Nakdong River Basin using a distributed hydrological model with radar rainfall forecast data. A real-time calibration algorithm of hydrological distributed model was proposed to investigate the particular relationship between the water storage and basin discharge. Demonstrate the approach of simulating multisite river flow using a distributed hydrological model couple with real-time calibration and forecasting of multisite river flow with radar rainfall forecasts data. The hydrographs and results exhibit that calibrated flow simulations are very approximate to the flow observation at all sites and the accuracy of forecasting flow is gradually decreased with lead times extending from 1 hr to 3 hrs. The flow forecasts are lower than the flow observation which is likely caused by the low estimation of radar rainfall forecasts. The research has well demonstrated that the distributed hydrological model is readily applicable for multisite real-time river flow analysis and forecasting in a large basin.
Real-time underwater object detection based on an electrically scanned high-resolution sonar
DEFF Research Database (Denmark)
Henriksen, Lars
1994-01-01
The paper describes an approach to real time detection and tracking of underwater objects, using image sequences from an electrically scanned high-resolution sonar. The use of a high resolution sonar provides a good estimate of the location of the objects, but strains the computers on board, beca...
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.
Piao, Jin-Chun; Kim, Shin-Dug
2017-11-07
Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.
Directory of Open Access Journals (Sweden)
Jin-Chun Piao
2017-11-01
Full Text Available Simultaneous localization and mapping (SLAM is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.
Piao, Jin-Chun; Kim, Shin-Dug
2017-01-01
Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method. PMID:29112143
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.
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
Real Time Earthquake Information System in Japan
Doi, K.; Kato, T.
2003-12-01
An early earthquake notification system in Japan had been developed by the Japan Meteorological Agency (JMA) as a governmental organization responsible for issuing earthquake information and tsunami forecasts. The system was primarily developed for prompt provision of a tsunami forecast to the public with locating an earthquake and estimating its magnitude as quickly as possible. Years after, a system for a prompt provision of seismic intensity information as indices of degrees of disasters caused by strong ground motion was also developed so that concerned governmental organizations can decide whether it was necessary for them to launch emergency response or not. At present, JMA issues the following kinds of information successively when a large earthquake occurs. 1) Prompt report of occurrence of a large earthquake and major seismic intensities caused by the earthquake in about two minutes after the earthquake occurrence. 2) Tsunami forecast in around three minutes. 3) Information on expected arrival times and maximum heights of tsunami waves in around five minutes. 4) Information on a hypocenter and a magnitude of the earthquake, the seismic intensity at each observation station, the times of high tides in addition to the expected tsunami arrival times in 5-7 minutes. To issue information above, JMA has established; - An advanced nationwide seismic network with about 180 stations for seismic wave observation and about 3,400 stations for instrumental seismic intensity observation including about 2,800 seismic intensity stations maintained by local governments, - Data telemetry networks via landlines and partly via a satellite communication link, - Real-time data processing techniques, for example, the automatic calculation of earthquake location and magnitude, the database driven method for quantitative tsunami estimation, and - Dissemination networks, via computer-to-computer communications and facsimile through dedicated telephone lines. JMA operationally
Autoregressive-model-based missing value estimation for DNA microarray time series data.
Choong, Miew Keen; Charbit, Maurice; Yan, Hong
2009-01-01
Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.
IMPROVED REAL-TIME SCAN MATCHING USING CORNER FEATURES
Directory of Open Access Journals (Sweden)
H. A. Mohamed
2016-06-01
Full Text Available The automation of unmanned vehicle operation has gained a lot of research attention, in the last few years, because of its numerous applications. The vehicle localization is more challenging in indoor environments where absolute positioning measurements (e.g. GPS are typically unavailable. Laser range finders are among the most widely used sensors that help the unmanned vehicles to localize themselves in indoor environments. Typically, automatic real-time matching of the successive scans is performed either explicitly or implicitly by any localization approach that utilizes laser range finders. Many accustomed approaches such as Iterative Closest Point (ICP, Iterative Matching Range Point (IMRP, Iterative Dual Correspondence (IDC, and Polar Scan Matching (PSM handles the scan matching problem in an iterative fashion which significantly affects the time consumption. Furthermore, the solution convergence is not guaranteed especially in cases of sharp maneuvers or fast movement. This paper proposes an automated real-time scan matching algorithm where the matching process is initialized using the detected corners. This initialization step aims to increase the convergence probability and to limit the number of iterations needed to reach convergence. The corner detection is preceded by line extraction from the laser scans. To evaluate the probability of line availability in indoor environments, various data sets, offered by different research groups, have been tested and the mean numbers of extracted lines per scan for these data sets are ranging from 4.10 to 8.86 lines of more than 7 points. The set of all intersections between extracted lines are detected as corners regardless of the physical intersection of these line segments in the scan. To account for the uncertainties of the detected corners, the covariance of the corners is estimated using the extracted lines variances. The detected corners are used to estimate the transformation parameters
Real Time Surface Registration for PET Motion Tracking
DEFF Research Database (Denmark)
Wilm, Jakob; Olesen, Oline Vinter; Paulsen, Rasmus Reinhold
2011-01-01
to create point clouds representing parts of the patient's face. The movement is estimated by a rigid registration of the point clouds. The registration should be done using a robust algorithm that can handle partial overlap and ideally operate in real time. We present an optimized Iterative Closest Point......Head movement during high resolution Positron Emission Tomography brain studies causes blur and artifacts in the images. Therefore, attempts are being made to continuously monitor the pose of the head and correct for this movement. Specifically, our method uses a structured light scanner system...... algorithm that operates at 10 frames per second on partial human face surfaces. © 2011 Springer-Verlag....
Energy Technology Data Exchange (ETDEWEB)
Despalatovic, Marin; Jadric, Martin; Terzic, Bozo [FESB University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, R. Boskovica bb, 21000 Split (Croatia)
2008-11-15
This paper presents a new method for the real-time power angle determination of the salient-pole synchronous machines. This method is based on the terminal voltage and air gap measurements, which are the common features of the hydroturbine generator monitoring system. The raw signal of the air gap sensor is used to detect the rotor displacement with reference to the fundamental component of the terminal voltage. First, the algorithm developed for the real-time power angle determination is tested using the synthetic data obtained by the standard machine model simulation. Thereafter, the experimental investigation is carried out on the 26 MVA utility generator. The validity of the method is verified by comparing with another method, which is based on a tooth gear mounted on the rotor shaft. The proposed real-time algorithm has an adequate accuracy and needs a very short processing time. For applications that do not require real-time processing, such as the estimation of the synchronous machine parameters, the accuracy is additionally increased by applying an off-line data-processing algorithm. (author)
Real-time holographic endoscopy
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.
Real-time computational photon-counting LiDAR
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.
Real time magnetic resonance guided endomyocardial local delivery
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
Prototyping Real-Time Control in the SPS
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
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
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.
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.
An Analysis of Input/Output Paradigms for Real-Time Systems
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
Vintage errors: do real-time economic data improve election forecasts?
Directory of Open Access Journals (Sweden)
Mark Andreas Kayser
2015-07-01
Full Text Available Economic performance is a key component of most election forecasts. When fitting models, however, most forecasters unwittingly assume that the actual state of the economy, a state best estimated by the multiple periodic revisions to official macroeconomic statistics, drives voter behavior. The difference in macroeconomic estimates between revised and original data vintages can be substantial, commonly over 100% (two-fold for economic growth estimates, making the choice of which data release to use important for the predictive validity of a model. We systematically compare the predictions of four forecasting models for numerous US presidential elections using real-time and vintage data. We find that newer data are not better data for election forecasting: forecasting error increases with data revisions. This result suggests that voter perceptions of economic growth are influenced more by media reports about the economy, which are based on initial economic estimates, than by the actual state of the economy.
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
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.
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.
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...
DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays.
Li, Jianfeng; Wang, Feng; Jiang, Defu
2017-03-20
A fast direction of arrival (DOA) estimation method using a real-valued cross-correlation matrix (CCM) of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS) method and estimation of signal parameter via rotational invariance (ESPRIT) based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach.
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
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
-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 Kalman filter: Cooling of an optically levitated nanoparticle
Setter, Ashley; Toroš, Marko; Ralph, Jason F.; Ulbricht, Hendrik
2018-03-01
We demonstrate that a Kalman filter applied to estimate the position of an optically levitated nanoparticle, and operated in real-time within a field programmable gate array, is sufficient to perform closed-loop parametric feedback cooling of the center-of-mass motion to sub-Kelvin temperatures. The translational center-of-mass motion along the optical axis of the trapped nanoparticle has been cooled by 3 orders of magnitude, from a temperature of 300 K to a temperature of 162 ±15 mK.
Real-time Kalman filter: cooling of an optically levitated nanoparticle
Setter, Ashley; Toros, Marko; Ralph, Jason; Ulbricht, Hendrik
2018-01-01
We demonstrate that a Kalman filter applied to estimate the position of an optically levitated nanoparticle, and operated in real-time within a Field Programmable Gate Array (FPGA), is sufficient to perform closed-loop parametric feedback cooling of the centre of mass motion to sub-Kelvin temperatures. The translational centre of mass motion along the optical axis of the trapped nanoparticle has been cooled by three orders of magnitude, from a temperature of 300K to a temperature of 162 +/- 1...
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
Efficient Implementation of a Symbol Timing Estimator for Broadband PLC.
Nombela, Francisco; García, Enrique; Mateos, Raúl; Hernández, Álvaro
2015-08-21
Broadband Power Line Communications (PLC) have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless, the use of these multi-carrier modulations, such as Wavelet-OFDM, requires a highly accurate symbol timing estimation for reliably recovering of transmitted data. Furthermore, the PLC channel presents some particularities that prevent the direct use of previous synchronization algorithms proposed in wireless communication systems. Therefore more research effort should be involved in the design and implementation of novel and robust synchronization algorithms for PLC, thus enabling real-time synchronization. This paper proposes a symbol timing estimator for broadband PLC based on cross-correlation with multilevel complementary sequences or Zadoff-Chu sequences and its efficient implementation in a FPGA; the obtained results show a 90% of success rate in symbol timing estimation for a certain PLC channel model and a reduced resource consumption for its implementation in a Xilinx Kyntex FPGA.
Efficient Implementation of a Symbol Timing Estimator for Broadband PLC
Directory of Open Access Journals (Sweden)
Francisco Nombela
2015-08-01
Full Text Available Broadband Power Line Communications (PLC have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless, the use of these multi-carrier modulations, such as Wavelet-OFDM, requires a highly accurate symbol timing estimation for reliably recovering of transmitted data. Furthermore, the PLC channel presents some particularities that prevent the direct use of previous synchronization algorithms proposed in wireless communication systems. Therefore more research effort should be involved in the design and implementation of novel and robust synchronization algorithms for PLC, thus enabling real-time synchronization. This paper proposes a symbol timing estimator for broadband PLC based on cross-correlation with multilevel complementary sequences or Zadoff-Chu sequences and its efficient implementation in a FPGA; the obtained results show a 90% of success rate in symbol timing estimation for a certain PLC channel model and a reduced resource consumption for its implementation in a Xilinx Kyntex FPGA.
Real-time unmanned aircraft systems surveillance video mosaicking using GPU
Camargo, Aldo; Anderson, Kyle; Wang, Yi; Schultz, Richard R.; Fevig, Ronald A.
2010-04-01
Digital video mosaicking from Unmanned Aircraft Systems (UAS) is being used for many military and civilian applications, including surveillance, target recognition, border protection, forest fire monitoring, traffic control on highways, monitoring of transmission lines, among others. Additionally, NASA is using digital video mosaicking to explore the moon and planets such as Mars. In order to compute a "good" mosaic from video captured by a UAS, the algorithm must deal with motion blur, frame-to-frame jitter associated with an imperfectly stabilized platform, perspective changes as the camera tilts in flight, as well as a number of other factors. The most suitable algorithms use SIFT (Scale-Invariant Feature Transform) to detect the features consistent between video frames. Utilizing these features, the next step is to estimate the homography between two consecutives video frames, perform warping to properly register the image data, and finally blend the video frames resulting in a seamless video mosaick. All this processing takes a great deal of resources of resources from the CPU, so it is almost impossible to compute a real time video mosaic on a single processor. Modern graphics processing units (GPUs) offer computational performance that far exceeds current CPU technology, allowing for real-time operation. This paper presents the development of a GPU-accelerated digital video mosaicking implementation and compares it with CPU performance. Our tests are based on two sets of real video captured by a small UAS aircraft; one video comes from Infrared (IR) and Electro-Optical (EO) cameras. Our results show that we can obtain a speed-up of more than 50 times using GPU technology, so real-time operation at a video capture of 30 frames per second is feasible.
Real-time monitoring of capacity loss for vanadium redox flow battery
Wei, Zhongbao; Bhattarai, Arjun; Zou, Changfu; Meng, Shujuan; Lim, Tuti Mariana; Skyllas-Kazacos, Maria
2018-06-01
The long-term operation of the vanadium redox flow battery is accompanied by ion diffusion across the separator and side reactions, which can lead to electrolyte imbalance and capacity loss. The accurate online monitoring of capacity loss is therefore valuable for the reliable and efficient operation of vanadium redox flow battery system. In this paper, a model-based online monitoring method is proposed to detect capacity loss in the vanadium redox flow battery in real time. A first-order equivalent circuit model is built to capture the dynamics of the vanadium redox flow battery. The model parameters are online identified from the onboard measureable signals with the recursive least squares, in seeking to keep a high modeling accuracy and robustness under a wide range of working scenarios. Based on the online adapted model, an observer is designed with the extended Kalman Filter to keep tracking both the capacity and state of charge of the battery in real time. Experiments are conducted on a lab-scale battery system. Results suggest that the online adapted model is able to simulate the battery behavior with high accuracy. The capacity loss as well as the state of charge can be estimated accurately in a real-time manner.
International Nuclear Information System (INIS)
Terrier, Francois
1996-01-01
The greater and greater autonomy and complexity asked to the control and command systems lead to work on introducing techniques such as Artificial Intelligence or concurrent object programming in industrial applications. However, while the critical feature of these systems impose to control the dynamics of the proposed solutions, their complexity often imposes a high adaptability to a partially modelled environment. The studies presented start from low level control and command systems to more complex applications at higher levels, such as 'supervision systems'. Techniques such as temporal reasoning and uncertainty management are proposed for the first studies, while the second are tackled with programming techniques based on the real time object paradigm. The outcomes of this itinerary crystallize on the ACCORD project which targets to manage - on the whole life cycle of a real time application - these two problematics, sometimes antagonistic: control of the dynamics and adaptivity. (author) [fr
Real-time image dehazing using local adaptive neighborhoods and dark-channel-prior
Valderrama, Jesus A.; Díaz-Ramírez, Víctor H.; Kober, Vitaly; Hernandez, Enrique
2015-09-01
A real-time algorithm for single image dehazing is presented. The algorithm is based on calculation of local neighborhoods of a hazed image inside a moving window. The local neighborhoods are constructed by computing rank-order statistics. Next the dark-channel-prior approach is applied to the local neighborhoods to estimate the transmission function of the scene. By using the suggested approach there is no need for applying a refining algorithm to the estimated transmission such as the soft matting algorithm. To achieve high-rate signal processing the proposed algorithm is implemented exploiting massive parallelism on a graphics processing unit (GPU). Computer simulation results are carried out to test the performance of the proposed algorithm in terms of dehazing efficiency and speed of processing. These tests are performed using several synthetic and real images. The obtained results are analyzed and compared with those obtained with existing dehazing algorithms.
Recent achievements in real-time computational seismology in Taiwan
Lee, S.; Liang, W.; Huang, B.
2012-12-01
Real-time computational seismology is currently possible to be achieved which needs highly connection between seismic database and high performance computing. We have developed a real-time moment tensor monitoring system (RMT) by using continuous BATS records and moment tensor inversion (CMT) technique. The real-time online earthquake simulation service is also ready to open for researchers and public earthquake science education (ROS). Combine RMT with ROS, the earthquake report based on computational seismology can provide within 5 minutes after an earthquake occurred (RMT obtains point source information ROS completes a 3D simulation real-time now. For more information, welcome to visit real-time computational seismology earthquake report webpage (RCS).
iShadow: Design of a Wearable, Real-Time Mobile Gaze Tracker.
Mayberry, Addison; Hu, Pan; Marlin, Benjamin; Salthouse, Christopher; Ganesan, Deepak
2014-06-01
Continuous, real-time tracking of eye gaze is valuable in a variety of scenarios including hands-free interaction with the physical world, detection of unsafe behaviors, leveraging visual context for advertising, life logging, and others. While eye tracking is commonly used in clinical trials and user studies, it has not bridged the gap to everyday consumer use. The challenge is that a real-time eye tracker is a power-hungry and computation-intensive device which requires continuous sensing of the eye using an imager running at many tens of frames per second, and continuous processing of the image stream using sophisticated gaze estimation algorithms. Our key contribution is the design of an eye tracker that dramatically reduces the sensing and computation needs for eye tracking, thereby achieving orders of magnitude reductions in power consumption and form-factor. The key idea is that eye images are extremely redundant, therefore we can estimate gaze by using a small subset of carefully chosen pixels per frame. We instantiate this idea in a prototype hardware platform equipped with a low-power image sensor that provides random access to pixel values, a low-power ARM Cortex M3 microcontroller, and a bluetooth radio to communicate with a mobile phone. The sparse pixel-based gaze estimation algorithm is a multi-layer neural network learned using a state-of-the-art sparsity-inducing regularization function that minimizes the gaze prediction error while simultaneously minimizing the number of pixels used. Our results show that we can operate at roughly 70mW of power, while continuously estimating eye gaze at the rate of 30 Hz with errors of roughly 3 degrees.
iShadow: Design of a Wearable, Real-Time Mobile Gaze Tracker
Mayberry, Addison; Hu, Pan; Marlin, Benjamin; Salthouse, Christopher; Ganesan, Deepak
2015-01-01
Continuous, real-time tracking of eye gaze is valuable in a variety of scenarios including hands-free interaction with the physical world, detection of unsafe behaviors, leveraging visual context for advertising, life logging, and others. While eye tracking is commonly used in clinical trials and user studies, it has not bridged the gap to everyday consumer use. The challenge is that a real-time eye tracker is a power-hungry and computation-intensive device which requires continuous sensing of the eye using an imager running at many tens of frames per second, and continuous processing of the image stream using sophisticated gaze estimation algorithms. Our key contribution is the design of an eye tracker that dramatically reduces the sensing and computation needs for eye tracking, thereby achieving orders of magnitude reductions in power consumption and form-factor. The key idea is that eye images are extremely redundant, therefore we can estimate gaze by using a small subset of carefully chosen pixels per frame. We instantiate this idea in a prototype hardware platform equipped with a low-power image sensor that provides random access to pixel values, a low-power ARM Cortex M3 microcontroller, and a bluetooth radio to communicate with a mobile phone. The sparse pixel-based gaze estimation algorithm is a multi-layer neural network learned using a state-of-the-art sparsity-inducing regularization function that minimizes the gaze prediction error while simultaneously minimizing the number of pixels used. Our results show that we can operate at roughly 70mW of power, while continuously estimating eye gaze at the rate of 30 Hz with errors of roughly 3 degrees. PMID:26539565
Bekooij, Marco; Bekooij, Marco Jan Gerrit; Wiggers, M.H.; van Meerbergen, Jef
2007-01-01
Soft real-time applications that process data streams can often be intuitively described as dataflow process networks. In this paper we present a novel analysis technique to compute conservative estimates of the required buffer capacities in such process networks. With the same analysis technique
Uncertainty evaluation of a regional real-time system for rain-induced landslides
Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni
2015-04-01
A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.
Proceedings of the Real-Time Systems Engineering Workshop
2001-08-01
real - time systems engineering. The workshop was held as part of the SEI Symposium in...Washington, DC, during September 2000. The objective of the workshop was to identify key issues and obtain feedback from attendees concerning real - time systems engineering...and interoperability. This report summarizes the workshop in terms of foundation, management, and technical topics, and it contains a discussion related to developing a community of interest for real - time systems
Estimating the contributions of mobile sources of PAH to urban air using real-time PAH monitoring.
Dunbar, J C; Lin, C I; Vergucht, I; Wong, J; Duran, J L
2001-11-12
basis, buses and trucks--the majority of which run on diesel fuel--emitted greater amounts of particle-bound PAH than passenger vehicles. Overall, we found that real-time photoelectric aerosol sensing (in combination with video photography) is useful for estimating the contributions of airborne PAB from different vehicle types. Due to the physical constraints of our monitoring site and the high volumes of traffic, however, it was not possible to uniquely attribute PAS signals to individual vehicles.
Validation of RNAi by real time PCR
DEFF Research Database (Denmark)
Josefsen, Knud; Lee, Ying Chiu
2011-01-01
Real time PCR is the analytic tool of choice for quantification of gene expression, while RNAi is concerned with downregulation of gene expression. Together, they constitute a powerful approach in any loss of function studies of selective genes. We illustrate here the use of real time PCR to verify...
Real Time Deconvolution of In-Vivo Ultrasound Images
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt
2013-01-01
and two wavelengths. This can be improved by deconvolution, which increase the bandwidth and equalizes the phase to increase resolution under the constraint of the electronic noise in the received signal. A fixed interval Kalman filter based deconvolution routine written in C is employed. It uses a state...... resolution has been determined from the in-vivo liver image using the auto-covariance function. From the envelope of the estimated pulse the axial resolution at Full-Width-Half-Max is 0.581 mm corresponding to 1.13 l at 3 MHz. The algorithm increases the resolution to 0.116 mm or 0.227 l corresponding...... to a factor of 5.1. The basic pulse can be estimated in roughly 0.176 seconds on a single CPU core on an Intel i5 CPU running at 1.8 GHz. An in-vivo image consisting of 100 lines of 1600 samples can be processed in roughly 0.1 seconds making it possible to perform real-time deconvolution on ultrasound data...
Transferability and robustness of real-time freeway crash risk assessment.
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.
Wyss, M.
2012-12-01
Estimating human losses within less than an hour worldwide requires assumptions and simplifications. Earthquake for which losses are accurately recorded after the event provide clues concerning the influence of error sources. If final observations and real time estimates differ significantly, data and methods to calculate losses may be modified or calibrated. In the case of the earthquake in the Emilia Romagna region with M5.9 on May 20th, the real time epicenter estimates of the GFZ and the USGS differed from the ultimate location by the INGV by 6 and 9 km, respectively. Fatalities estimated within an hour of the earthquake by the loss estimating tool QLARM, based on these two epicenters, numbered 20 and 31, whereas 7 were reported in the end, and 12 would have been calculated if the ultimate epicenter released by INGV had been used. These four numbers being small, do not differ statistically. Thus, the epicenter errors in this case did not appreciably influence the results. The QUEST team of INGV has reported intensities with I ≥ 5 at 40 locations with accuracies of 0.5 units and QLARM estimated I > 4.5 at 224 locations. The differences between the observed and calculated values at the 23 common locations show that the calculation in the 17 instances with significant differences were too high on average by one unit. By assuming higher than average attenuation within standard bounds for worldwide loss estimates, the calculated intensities model the observed ones better: For 57% of the locations, the difference was not significant; for the others, the calculated intensities were still somewhat higher than the observed ones. Using a generic attenuation law with higher than average attenuation, but not tailored to the region, the number of estimated fatalities becomes 12 compared to 7 reported ones. Thus, attenuation in this case decreased the discrepancy between observed and reported death by approximately a factor of two. The source of the fatalities is
SignalR real time application development
Ingebrigtsen, Einar
2013-01-01
This step-by-step guide gives you practical advice, tips, and tricks that will have you writing real-time apps quickly and easily.If you are a .NET developer who wants to be at the cutting edge of development, then this book is for you. Real-time application development is made simple in this guide, so as long as you have basic knowledge of .NET, a copy of Visual Studio, and NuGet installed, you are ready to go.
Real time monitoring of electron processors
International Nuclear Information System (INIS)
Nablo, S.V.; Kneeland, D.R.; McLaughlin, W.L.
1995-01-01
A real time radiation monitor (RTRM) has been developed for monitoring the dose rate (current density) of electron beam processors. The system provides continuous monitoring of processor output, electron beam uniformity, and an independent measure of operating voltage or electron energy. In view of the device's ability to replace labor-intensive dosimetry in verification of machine performance on a real-time basis, its application to providing archival performance data for in-line processing is discussed. (author)
Limited Preemptive Scheduling in Real-time Systems
Thekkilakattil, Abhilash
2016-01-01
Preemptive and non-preemptive scheduling paradigms typically introduce undesirable side effects when scheduling real-time tasks, mainly in the form of preemption overheads and blocking, that potentially compromise timeliness guarantees. The high preemption overheads in preemptive real-time scheduling may imply high resource utilization, often requiring significant over-provisioning, e.g., pessimistic Worst Case Execution Time (WCET) approximations. Non-preemptive scheduling, on the other hand...
Real time sensor for therapeutic radiation delivery
International Nuclear Information System (INIS)
Bliss, M.; Craig, R.A.; Reeder, P.L.
1998-01-01
The invention is a real time sensor for therapeutic radiation. A probe is placed in or near the patient that senses in real time the dose at the location of the probe. The strength of the dose is determined by either an insertion or an exit probe. The location is determined by a series of vertical and horizontal sensing elements that gives the operator a real time read out dose location relative to placement of the patient. The increased accuracy prevents serious tissue damage to the patient by preventing overdose or delivery of a dose to a wrong location within the body. 14 figs
Coordinating Transit Transfers in Real Time
2016-05-06
Transfers are a major source of travel time variability for transit passengers. Coordinating transfers between transit routes in real time can reduce passenger waiting times and travel time variability, but these benefits need to be contrasted with t...
Timing organization of a real-time multicore processor
DEFF Research Database (Denmark)
Schoeberl, Martin; Sparsø, Jens
2017-01-01
Real-time systems need a time-predictable computing platform. Computation, communication, and access to shared resources needs to be time-predictable. We use time division multiplexing to statically schedule all computation and communication resources, such as access to main memory or message...... passing over a network-on-chip. We use time-driven communication over an asynchronous network-on-chip to enable time division multiplexing even in a globally asynchronous, locally synchronous multicore architecture. Using time division multiplexing at all levels of the architecture yields in a time...
Real-time logo detection and tracking in video
George, M.; Kehtarnavaz, N.; Rahman, M.; Carlsohn, M.
2010-05-01
This paper presents a real-time implementation of a logo detection and tracking algorithm in video. The motivation of this work stems from applications on smart phones that require the detection of logos in real-time. For example, one application involves detecting company logos so that customers can easily get special offers in real-time. This algorithm uses a hybrid approach by initially running the Scale Invariant Feature Transform (SIFT) algorithm on the first frame in order to obtain the logo location and then by using an online calibration of color within the SIFT detected area in order to detect and track the logo in subsequent frames in a time efficient manner. The results obtained indicate that this hybrid approach allows robust logo detection and tracking to be achieved in real-time.
A reliable information management for real-time systems
International Nuclear Information System (INIS)
Nishihara, Takuo; Tomita, Seiji
1995-01-01
In this paper, we propose a system configuration suitable for the hard realtime systems in which integrity and durability of information are important. On most hard real-time systems, where response time constraints are critical, the data which program access are volatile, and may be lost in case the systems are down. But for some real-time systems, the value-added intelligent network (IN) systems, e.g., integrity and durability of the stored data are very important. We propose a distributed system configuration for such hard real-time systems, comprised of service control modules and data management modules. The service control modules process transactions and responses based on deadline control, and the data management modules deal the stored data based on information recovery schemes well-restablished in fault real-time systems. (author)
Improving Timeliness in Real-Time Secure Database Systems
National Research Council Canada - National Science Library
Son, Sang H; David, Rasikan; Thuraisingham, Bhavani
2006-01-01
.... In addition to real-time requirements, security is usually required in many applications. Multilevel security requirements introduce a new dimension to transaction processing in real-time database systems...
Model-Checking Real-Time Control Programs
DEFF Research Database (Denmark)
Iversen, T. K.; Kristoffersen, K. J.; Larsen, Kim Guldstrand
2000-01-01
In this paper, we present a method for automatic verification of real-time control programs running on LEGO(R) RCX(TM) bricks using the verification tool UPPALL. The control programs, consisting of a number of tasks running concurrently, are automatically translated into the mixed automata model...... of UPPAAL. The fixed scheduling algorithm used by the LEGO(R) RCX(TM) processor is modeled in UPPALL, and supply of similar (sufficient) timed automata models for the environment allows analysis of the overall real-time system using the tools of UPPALL. To illustrate our technique for sorting LEGO(R) bricks...
Cloud-Hosted Real-time Data Services for the Geosciences (CHORDS)
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.
Time-critical multirate scheduling using contemporary real-time operating system services
Eckhardt, D. E., Jr.
1983-01-01
Although real-time operating systems provide many of the task control services necessary to process time-critical applications (i.e., applications with fixed, invariant deadlines), it may still be necessary to provide a scheduling algorithm at a level above the operating system in order to coordinate a set of synchronized, time-critical tasks executing at different cyclic rates. The scheduling requirements for such applications and develops scheduling algorithms using services provided by contemporary real-time operating systems.
Optimized quantum sensing with a single electron spin using real-time adaptive measurements
Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.
2016-03-01
Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.
Mahmmod, Yasser S; Toft, Nils; Katholm, Jørgen; Grønbæk, Carsten; Klaas, Ilka C
2013-11-01
Danish farmers can order a real-time PCR mastitis diagnostic test on routinely taken cow-level samples from milk recordings. Validation of its performance in comparison to conventional mastitis diagnostics under field conditions is essential for efficient control of intramammary infections (IMI) with Staphylococcus aureus (S. aureus). Therefore, the objective of this study was to estimate the sensitivity (Se) and specificity (Sp) of real-time PCR, bacterial culture (BC) and California mastitis test (CMT) for the diagnosis of the naturally occurring IMI with S. aureus in routinely collected milk samples using latent class analysis (LCA) to avoid the assumption of a perfect reference test. Using systematic random sampling, a total of 609 lactating dairy cows were selected from 6 dairy herds with bulk tank milk PCR cycle threshold (Ct) value ≤39 for S. aureus. At routine milk recordings, automatically obtained cow-level (composite) milk samples were analyzed by PCR and at the same milking, 2436 quarter milk samples were collected aseptically for BC and CMT. Results showed that 140 cows (23%) were positive for S. aureus IMI by BC while 170 cows (28%) were positive by PCR. Estimates of Se and Sp for PCR were higher than test estimates of BC and CMT. SeCMT was higher than SeBC however, SpBC was higher than SpCMT. SePCR was 91%, while SeBC was 53%, and SeCMT was 61%. SpPCR was 99%, while SpBC was 89%, and SpCMT was 65%. In conclusion, PCR has a higher performance than the conventional diagnostic tests (BC and CMT) suggesting its usefulness as a routine test for accurate diagnosis of S. aureus IMI from dairy cows at routine milk recordings. The use of LCA provided estimates of the test characteristics for two currently diagnostic tests (BC, CMT) and a novel technique (real-time PCR) for diagnosing S. aureus IMI under field conditions at routine milk recordings in Denmark. Copyright © 2013 Elsevier B.V. All rights reserved.
Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.
Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan
2017-12-06
Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.
DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays
Directory of Open Access Journals (Sweden)
Jianfeng Li
2017-03-01
Full Text Available A fast direction of arrival (DOA estimation method using a real-valued cross-correlation matrix (CCM of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS method and estimation of signal parameter via rotational invariance (ESPRIT based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach.
International Nuclear Information System (INIS)
Tsurutani, B.T.; Baker, D.N.
1979-01-01
Prediction of geomagnetic substorms and storms would be of great scientific and commercial interest. A real-time ISEE data system directed toward this purpose is discussed in detail. 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. 6 figures, 1 table
Automated Real-Time Clearance Analyzer (ARCA), Phase I
National Aeronautics and Space Administration — The Automated Real-Time Clearance Analyzer (ARCA) addresses the future safety need for Real-Time System-Wide Safety Assurance (RSSA) in aviation and progressively...
Online Estimation of Time-Varying Volatility Using a Continuous-Discrete LMS Algorithm
Directory of Open Access Journals (Sweden)
Jacques Oksman
2008-09-01
Full Text Available The following paper addresses a problem of inference in financial engineering, namely, online time-varying volatility estimation. The proposed method is based on an adaptive predictor for the stock price, built from an implicit integration formula. An estimate for the current volatility value which minimizes the mean square prediction error is calculated recursively using an LMS algorithm. The method is then validated on several synthetic examples as well as on real data. Throughout the illustration, the proposed method is compared with both UKF and offline volatility estimation.
Directory of Open Access Journals (Sweden)
Yong Zhang
2017-05-01
Full Text Available The real-time estimation of the wide-lane and narrow-lane Uncalibrated Phase Delay (UPD of satellites is realized by real-time data received from regional reference station networks; The properties of the real-time UPD product and its influence on real-time precise point positioning ambiguity resolution (RTPPP-AR are experimentally analyzed according to real-time data obtained from the regional Continuously Operating Reference Stations (CORS network located in Tianjin, Shanghai, Hong Kong, etc. The results show that the real-time wide-lane and narrow-lane UPD products differ significantly from each other in time-domain characteristics; the wide-lane UPDs have daily stability, with a change rate of less than 0.1 cycle/day, while the narrow-lane UPDs have short-term stability, with significant change in one day. The UPD products generated by different regional networks have obvious spatial characteristics, thus significantly influencing RTPPP-AR: the adoption of real-time UPD products employing the sparse stations in the regional network for estimation is favorable for improving the regional RTPPP-AR up to 99%; the real-time UPD products of different regional networks slightly influence PPP-AR positioning accuracy. After ambiguities are successfully fixed, the real-time dynamic RTPPP-AR positioning accuracy is better than 3 cm in the plane and 8 cm in the upward direction.
Shiinoki, Takehiro; Onizuka, Ryota; Kawahara, Daisuke; Suzuki, Tatsuhiko; Yuasa, Yuki; Fujimoto, Koya; Uehara, Takuya; Hanazawa, Hideki; Shibuya, Keiko
2018-03-01
Purpose: To quantify the patient-specific imaging dose for real-time tumour monitoring in the lung during respiratory-gated stereotactic body radiotherapy (SBRT) in clinical cases using SyncTraX. Methods and Materials: Ten patients who underwent respiratory-gated SBRT with SyncTraX were enrolled in this study. The imaging procedure for real-time tumour monitoring using SyncTraX was simulated using Monte Carlo. We evaluated the dosimetric effect of a real-time tumour monitoring in a critical organ at risk (OAR) and the planning target volume (PTV) over the course of treatment. The relationship between skin dose and gating efficiency was also investigated. Results: For all patients, the mean D50 to the PTV, ipsilateral lung, liver, heart, spinal cord and skin was 118.3 (21.5–175.9), 31.9 (9.5–75.4), 15.4 (1.1–31.6), 10.1 (1.3–18.1), 25.0 (1.6–101.8), and 3.6 (0.9–7.1) mGy, respectively. The mean D2 was 352.0 (26.5–935.8), 146.4 (27.3–226.7), 90.7 (3.6–255.0), 42.2 (4.8–82.7), 88.0 (15.4–248.5), and 273.5 (98.3–611.6) mGy, respectively. The D2 of the skin dose was found to increase as the gating efficiency decreased. Conclusions: The additional dose to the PTV was at most 1.9% of the prescribed dose over the course of treatment for real-time tumour monitoring. For OARs, we could confirm the high dose region, which may not be susceptible to radiation toxicity. However, to reduce the skin dose from SyncTraX, it is necessary to increase the gating efficiency.
Three-dimensional localization of low activity gamma-ray sources in real-time scenarios
Energy Technology Data Exchange (ETDEWEB)
Sharma, Manish K., E-mail: mksrkf@mst.edu; Alajo, Ayodeji B.; Lee, Hyoung K.
2016-03-21
Radioactive source localization plays an important role in tracking radiation threats in homeland security tasks. Its real-time application requires computationally efficient and reasonably accurate algorithms even with limited data to support detection with minimum uncertainty. This paper describes a statistic-based grid-refinement method for backtracing the position of a gamma-ray source in a three-dimensional domain in real-time. The developed algorithm used measurements from various known detector positions to localize the source. This algorithm is based on an inverse-square relationship between source intensity at a detector and the distance from the source to the detector. The domain discretization was developed and implemented in MATLAB. The algorithm was tested and verified from simulation results of an ideal case of a point source in non-attenuating medium. Subsequently, an experimental validation of the algorithm was performed to determine the suitability of deploying this scheme in real-time scenarios. Using the measurements from five known detector positions and for a measurement time of 3 min, the source position was estimated with an accuracy of approximately 53 cm. The accuracy improved and stabilized to approximately 25 cm for higher measurement times. It was concluded that the error in source localization was primarily due to detection uncertainties. In verification and experimental validation of the algorithm, the distance between {sup 137}Cs source and any detector position was between 0.84 m and 1.77 m. The results were also compared with the least squares method. Since the discretization algorithm was validated with a weak source, it is expected that it can localize the source of higher activity in real-time. It is believed that for the same physical placement of source and detectors, a source of approximate activity 0.61–0.92 mCi can be localized in real-time with 1 s of measurement time and same accuracy. The accuracy and computational
Real-time statistical quality control and ARM
International Nuclear Information System (INIS)
Blough, D.K.
1992-05-01
An important component of the Atmospheric Radiation Measurement (ARM) Program is real-time quality control of data obtained from meteorological instruments. It is the goal of the ARM program to enhance the predictive capabilities of global circulation models by incorporating in them more detailed information on the radiative characteristics of the earth's atmosphere. To this end, a number of Cloud and Radiation Testbeds (CART's) will be built at various locations worldwide. Each CART will consist of an array of instruments designed to collect radiative data. The large amount of data obtained from these instruments necessitates real-time processing in order to flag outliers and possible instrument malfunction. The Bayesian dynamic linear model (DLM) proves to be an effective way of monitoring the time series data which each instrument generates. It provides a flexible yet powerful approach to detecting in real-time sudden shifts in a non-stationary multivariate time series. An application of these techniques to data arising from a remote sensing instrument to be used in the CART is provided. Using real data from a wind profiler, the ability of the DLM to detect outliers is studied. 5 refs
Explaining How to Play Real-Time Strategy Games
Metoyer, Ronald; Stumpf, Simone; Neumann, Christoph; Dodge, Jonathan; Cao, Jill; Schnabel, Aaron
Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.
Correspondence between imaginary-time and real-time finite-temperature field theory
International Nuclear Information System (INIS)
Kobes, R.
1990-01-01
It is known that one-particle-irreducible graphs found using the imaginary-time formalism of finite-temperature field theory differ in general with those of the real-time formalism. Here it is shown that within the real-time formalism one can consider a sum of graphs, motivated by causality arguments, which at least in a number of simple examples agree with the corresponding analytically continued imaginary-time result. The occurrence of multiple statistical factors in this sum of graphs is discussed
Refactoring Real-Time Java Profiles
DEFF Research Database (Denmark)
Søndergaard, Hans; Thomsen, Bent; Ravn, Anders Peter
2011-01-01
Just like other software, Java profiles benefits from refactoring when they have been used and have evolved for some time. This paper presents a refactoring of the Real-Time Specification for Java (RTSJ) and the Safety Critical Java (SCJ) profile (JSR-302). It highlights core concepts and makes...
Li, M.; Huang, X.; Li, J.; Song, Y.
2012-04-01
Because of the high emission intensity and reactivity, biogenic volatile organic compounds (BVOCs) play a significant role in the terrestrial ecosystems, human health, secondary pollution, global climate change and the global carbon cycle. Past estimations of BVOC emissions in China were based on outdated algorithms and limited meteorological data, and there have been significant inconsistences between the land surface parameters of dynamic models and those of BVOC estimation models, leading to large inaccuracies in the estimated results. To refine BVOC emission estimations for China and to further explore the role of BVOCs in atmospheric chemical processes, we used the latest algorithms of MEGAN (Model of Emissions of Gases and Aerosols from Nature) with MM5 (the Fifth-Generation Mesoscale Model) providing highly resolved meteorological data, to estimate the biogenic emissions of isoprene (C5H8) and seven monoterpene species (C10H16) in 2006. Real-time MODIS (Moderate Resolution Imaging Spectroradiometer) data were introduced to update the land surface parameters and improve the simulation performance of MM5, and to modify the influence of leaf area index (LAI) and leaf age deviation from standard conditions. In this study, the annual BVOC emissions for the whole country totaled 12.97 Tg C, a relevant value much lower than that given in global estimations but higher than the past estimations in China. Therein, the most important individual contributor was isoprene (9.36 Tg C), followed by α-pinene (1.24 Tg C yr-1) and β-pinene (0.84 Tg C yr-1). Due to the considerable regional disparity in plant distributions and meteorological conditions across China, BVOC emissions presented significant spatial-temporal variations. Spatially, isoprene emission was concentrated in South China, which is covered by large areas of broadleaf forests and shrubs. On the other hand, Southeast China was the top-ranking contributor of monoterpenes, in which the dominant vegetation
Compilation and synthesis for real-time embedded controllers
DEFF Research Database (Denmark)
Fränzle, Martin; Müller-Olm, Markus
1999-01-01
This article provides an overview over two constructive approaches to provably correct hard real-time code generation where hard real-time code is generated from abstract requirements rather than verified against the timing requirements a posteriori. The first, more pragmatic approach is concerne......-time systems at a very high level of abstraction....
Real-time advanced nuclear reactor core model
International Nuclear Information System (INIS)
Koclas, J.; Friedman, F.; Paquette, C.; Vivier, P.
1990-01-01
The paper describes a multi-nodal advanced nuclear reactor core model. The model is based on application of modern equivalence theory to the solution of neutron diffusion equation in real time employing the finite differences method. The use of equivalence theory allows the application of the finite differences method to cores divided into hundreds of nodes, as opposed to the much finer divisions (in the order of ten thousands of nodes) where the unmodified method is currently applied. As a result the model can be used for modelling of the core kinetics for real time full scope training simulators. Results of benchmarks, validate the basic assumptions of the model and its applicability to real-time simulation. (orig./HP)
TRSM-a thermal-hydraulic real-time simulation model for PWR
International Nuclear Information System (INIS)
Zhou Weichang
1997-01-01
TRSM (a Thermal-hydraulic Real-time Simulation Model) has been developed for PWR real-time simulation and best-estimate prediction of normal operating and abnormal accident conditions. It is a non-equilibrium two phase flow thermal-hydraulic model based on five basic conservation equations. A drift flux model is used to account for the unequal velocities of liquid and gaseous mixture, with or without the presence of the noncondensibles. Critical flow models are applied for break flow and valve flow calculations. A 5-regime two phase heat convection model is applied for clad-to-coolant as well as fluid-to-tubing heat transfer. A rigorous reactor coolant pump model is used to calculate the pressure drop and rise for the suction and discharge ends with complete pump characteristics curves included. The TRSM model has been adapted in the full-scale training simulator of Qinshan Nuclear Power Plant 300 MW unit to simulate the thermal-hydraulic performance of the NSSS. The simulation results of a cold leg LOCA and a steam generator tube rupture (SGTR) accident are presented
First Trial of Real-time Poloidal Beta Control in KSTAR
Han, Hyunsun; Hahn, S. H.; Bak, J. G.; Walker, M. L.; Woo, M. H.; Kim, J. S.; Kim, Y. J.; Bae, Y. S.; KSTAR Team
2014-10-01
Sustaining the plasma in a stable and a high performance condition is one of the important control issues for future steady state tokamaks. In the 2014 KSTAR campaign, we have developed a real-time poloidal beta (βp) control technique and carried out preliminary experiments to identify its feasibility. In the control system, the βp is calculated in real time using the measured diamagnetic loop signal (DLM03) with coil pickup corrections, and compared with the target value leading to the change of the neutral beam (NB) heating power using a feedback PID control algorithm. To match the required power of NB which is operated with constant voltage, the duty cycles of the modulation were adjusted as the ratio of the required power to the maximum achievable one. This paper will present the overall procedures of the βp control, the βp estimation process implemented in the plasma control system, and the analysis on the preliminary experimental results. This work is supported by the KSTAR research project funded by the Ministry of Science, ICT & Future Planning of Korea.
Progress on RTSS simulation-based analysis for real-time systems development at two laboratories
International Nuclear Information System (INIS)
Shu, Y.; Jia, M.; Fei, Y.; Zhang, Y.; Liu, G.; Yang, S.; Chen, Y.
1996-01-01
A new object-oriented Real Time System Simulator (RTSS) with the capability for simulation graphics and animation, has been developed and used for modeling the distributed data acquisition and processing systems at JET and ASIPP. Simulation allows estimates of response time, throughput and resource utilization for a variety of configurations to be investigated. Performance measurements, simulation and analysis are used together to calibrate and validate each other
Hardware locks for a real-time Java chip multiprocessor
DEFF Research Database (Denmark)
Strøm, Torur Biskopstø; Puffitsch, Wolfgang; Schoeberl, Martin
2016-01-01
A software locking mechanism commonly protects shared resources for multithreaded applications. This mechanism can, especially in chip-multiprocessor systems, result in a large synchronization overhead. For real-time systems in particular, this overhead increases the worst-case execution time....... This improvement can allow a larger number of real-time tasks to be reliably scheduled on a multiprocessor real-time platform....
Hard Real-Time Linux for Off-The-Shelf Multicore Architectures
Radder, Dirk
2015-01-01
This document describes the research results that were obtained from the development of a real-time extension for the Linux operating system. The paper describes a full extension of the kernel, which enables hard real-time performance on a 64-bit x86 architecture. In the first part of this study, real-time systems are categorized and concepts of real-time operating systems are introduced to the reader. In addition, numerous well-known real-time operating systems are considered. QNX Neutrino, ...
Accurate Lithium-ion battery parameter estimation with continuous-time system identification methods
International Nuclear Information System (INIS)
Xia, Bing; Zhao, Xin; Callafon, Raymond de; Garnier, Hugues; Nguyen, Truong; Mi, Chris
2016-01-01
Highlights: • Continuous-time system identification is applied in Lithium-ion battery modeling. • Continuous-time and discrete-time identification methods are compared in detail. • The instrumental variable method is employed to further improve the estimation. • Simulations and experiments validate the advantages of continuous-time methods. - Abstract: The modeling of Lithium-ion batteries usually utilizes discrete-time system identification methods to estimate parameters of discrete models. However, in real applications, there is a fundamental limitation of the discrete-time methods in dealing with sensitivity when the system is stiff and the storage resolutions are limited. To overcome this problem, this paper adopts direct continuous-time system identification methods to estimate the parameters of equivalent circuit models for Lithium-ion batteries. Compared with discrete-time system identification methods, the continuous-time system identification methods provide more accurate estimates to both fast and slow dynamics in battery systems and are less sensitive to disturbances. A case of a 2"n"d-order equivalent circuit model is studied which shows that the continuous-time estimates are more robust to high sampling rates, measurement noises and rounding errors. In addition, the estimation by the conventional continuous-time least squares method is further improved in the case of noisy output measurement by introducing the instrumental variable method. Simulation and experiment results validate the analysis and demonstrate the advantages of the continuous-time system identification methods in battery applications.
Combining Real-Time Seismic and GPS Data for Earthquake Early Warning (Invited)
Boese, M.; Heaton, T. H.; Hudnut, K. W.
2013-12-01
Scientists at Caltech, UC Berkeley, the Univ. of SoCal, the Univ. of Washington, the US Geological Survey, and ETH Zurich have developed an earthquake early warning (EEW) demonstration system for California and the Pacific Northwest. To quickly determine the earthquake magnitude and location, 'ShakeAlert' currently processes and interprets real-time data-streams from ~400 seismic broadband and strong-motion stations within the California Integrated Seismic Network (CISN). Based on these parameters, the 'UserDisplay' software predicts and displays the arrival and intensity of shaking at a given user site. Real-time ShakeAlert feeds are currently shared with around 160 individuals, companies, and emergency response organizations to educate potential users about EEW and to identify needs and applications of EEW in a future operational warning system. Recently, scientists at the contributing institutions have started to develop algorithms for ShakeAlert that make use of high-rate real-time GPS data to improve the magnitude estimates for large earthquakes (M>6.5) and to determine slip distributions. Knowing the fault slip in (near) real-time is crucial for users relying on or operating distributed systems, such as for power, water or transportation, especially if these networks run close to or across large faults. As shown in an earlier study, slip information is also useful to predict (in a probabilistic sense) how far a fault rupture will propagate, thus enabling more robust probabilistic ground-motion predictions at distant locations. Finally, fault slip information is needed for tsunami warning, such as in the Cascadia subduction-zone. To handle extended fault-ruptures of large earthquakes in real-time, Caltech and USGS Pasadena are currently developing and testing a two-step procedure that combines seismic and geodetic data; in the first step, high-frequency strong-motion amplitudes are used to rapidly classify near-and far-source stations. Then, the location and
Processor tradeoffs in distributed real-time systems
Krishna, C. M.; Shin, Kang G.; Bhandari, Inderpal S.
1987-01-01
The problem of the optimization of the design of real-time distributed systems is examined with reference to a class of computer architectures similar to the continuously reconfigurable multiprocessor flight control system structure, CM2FCS. Particular attention is given to the impact of processor replacement and the burn-in time on the probability of dynamic failure and mean cost. The solution is obtained numerically and interpreted in the context of real-time applications.
Aoi, S.; Yamamoto, N.; Suzuki, W.; Hirata, K.; Nakamura, H.; Kunugi, T.; Kubo, T.; Maeda, T.
2015-12-01
In the 2011 Tohoku earthquake, in which huge tsunami claimed a great deal of lives, the initial tsunami forecast based on hypocenter information estimated using seismic data on land were greatly underestimated. From this lesson, NIED is now constructing S-net (Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench) which consists of 150 ocean bottom observatories with seismometers and pressure gauges (tsunamimeters) linked by fiber optic cables. To take full advantage of S-net, we develop a new methodology of real-time tsunami inundation forecast using ocean bottom observation data and construct a prototype system that implements the developed forecasting method for the Pacific coast of Chiba prefecture (Sotobo area). We employ a database-based approach because inundation is a strongly non-linear phenomenon and its calculation costs are rather heavy. We prepare tsunami scenario bank in advance, by constructing the possible tsunami sources, and calculating the tsunami waveforms at S-net stations, coastal tsunami heights and tsunami inundation on land. To calculate the inundation for target Sotobo area, we construct the 10-m-mesh precise elevation model with coastal structures. Based on the sensitivities analyses, we construct the tsunami scenario bank that efficiently covers possible tsunami scenarios affecting the Sotobo area. A real-time forecast is carried out by selecting several possible scenarios which can well explain real-time tsunami data observed at S-net from tsunami scenario bank. An advantage of our method is that tsunami inundations are estimated directly from the actual tsunami data without any source information, which may have large estimation errors. In addition to the forecast system, we develop Web services, APIs, and smartphone applications and brush them up through social experiments to provide the real-time tsunami observation and forecast information in easy way to understand toward urging people to evacuate.
Developments in architecture for real-time data systems
International Nuclear Information System (INIS)
Heath, R.L.; Myers, W.R.
1975-01-01
Real-time data systems typically operate at two levels: a fast-response instrument-oriented level for data acquisition and control, and a slow human-oriented level for interaction and computation. Traditional minicomputer data systems support real-time applications by implementation of background/foreground software. Recent developments in computer technology including microprocessors enable the functional organization of hardware in distributed or hierarchical form to provide new system structures for real-time requirements. Examples of systems with distributed architecture will be discussed in detail
Specification and Automated Verification of Real-Time Behaviour
DEFF Research Database (Denmark)
Kristensen, C.H.; Andersen, J.H.; Skou, A.
1995-01-01
In this paper we sketch a method for specification and automatic verification of real-time software properties.......In this paper we sketch a method for specification and automatic verification of real-time software properties....
Specification and Automated Verification of Real-Time Behaviour
DEFF Research Database (Denmark)
Andersen, J.H.; Kristensen, C.H.; Skou, A.
1996-01-01
In this paper we sketch a method for specification and automatic verification of real-time software properties.......In this paper we sketch a method for specification and automatic verification of real-time software properties....