Frame based Motion Detection for real-time Surveillance

OpenAIRE

Brajesh Patel; Neelam Patel

2012-01-01

In this paper a series of algorithm has been formed to track the feature of motion detection under surveillance system. In the proposed work a pixel variant plays a vital role in detection of moving object of a particular clip. If there is a little bit motion in a frame then it is detected very easily by calculating pixel variance. This algorithm detects the zero variation only when there is no motion in a real-time video sequence. It is simple and easier for motion detection in the fames of ...

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery.

Science.gov (United States)

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.

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

Online real-time reconstruction of adaptive TSENSE with commodity CPU / GPU hardware

DEFF Research Database (Denmark)

Roujol, Sebastien; de Senneville, Baudouin; Vahala, E.

2009-01-01

A real-time reconstruction for adaptive TSENSE is presented that is optimized for MR-guidance of interventional procedures. The proposed method allows high frame-rate imaging with low image latencies, even when large coil arrays are employed and can be implemented on affordable commodity hardware....

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.

Using an external surrogate for predictor model training in real-time motion management of lung tumors

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)

2014-12-15

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum

The INGV Real Time Strong Motion Database

Science.gov (United States)

Massa, Marco; D'Alema, Ezio; Mascandola, Claudia; Lovati, Sara; Scafidi, Davide; Gomez, Antonio; Carannante, Simona; Franceschina, Gianlorenzo; Mirenna, Santi; Augliera, Paolo

2017-04-01

The INGV real time strong motion data sharing is assured by the INGV Strong Motion Database. ISMD (http://ismd.mi.ingv.it) was designed in the last months of 2011 in cooperation among different INGV departments, with the aim to organize the distribution of the INGV strong-motion data using standard procedures for data acquisition and processing. The first version of the web portal was published soon after the occurrence of the 2012 Emilia (Northern Italy), Mw 6.1, seismic sequence. At that time ISMD was the first European real time web portal devoted to the engineering seismology community. After four years of successfully operation, the thousands of accelerometric waveforms collected in the archive need necessary a technological improvement of the system in order to better organize the new data archiving and to make more efficient the answer to the user requests. ISMD 2.0 was based on PostgreSQL (www.postgresql.org), an open source object- relational database. The main purpose of the web portal is to distribute few minutes after the origin time the accelerometric waveforms and related metadata of the Italian earthquakes with ML≥3.0. Data are provided both in raw SAC (counts) and automatically corrected ASCII (gal) formats. The web portal also provide, for each event, a detailed description of the ground motion parameters (i.e. Peak Ground Acceleration, Velocity and Displacement, Arias and Housner Intensities) data converted in velocity and displacement, response spectra up to 10.0 s and general maps concerning the recent and the historical seismicity of the area together with information about its seismic hazard. The focal parameters of the events are provided by the INGV National Earthquake Center (CNT, http://cnt.rm.ingv.it). Moreover, the database provides a detailed site characterization section for each strong motion station, based on geological, geomorphological and geophysical information. At present (i.e. January 2017), ISMD includes 987 (121

FPGA-based architecture for motion recovering in real-time

Science.gov (United States)

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.

Application and API for Real-time Visualization of Ground-motions and Tsunami

Science.gov (United States)

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

Online 4D ultrasound guidance for real-time motion compensation by MLC tracking.

Science.gov (United States)

Ipsen, Svenja; Bruder, Ralf; O'Brien, Rick; Keall, Paul J; Schweikard, Achim; Poulsen, Per R

2016-10-01

With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom. A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2

Real-Time Accumulative Computation Motion Detectors

Directory of Open Access Journals (Sweden)

Saturnino Maldonado-Bascón

2009-12-01

Full Text Available The neurally inspired accumulative computation (AC method and its application to motion detection have been introduced in the past years. This paper revisits the fact that many researchers have explored the relationship between neural networks and finite state machines. Indeed, finite state machines constitute the best characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. The article shows how to reach real-time performance after using a model described as a finite state machine. This paper introduces two steps towards that direction: (a A simplification of the general AC method is performed by formally transforming it into a finite state machine. (b A hardware implementation in FPGA of such a designed AC module, as well as an 8-AC motion detector, providing promising performance results. We also offer two case studies of the use of AC motion detectors in surveillance applications, namely infrared-based people segmentation and color-based people tracking, respectively.

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov (United States)

-Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution developing a system-theoretic distribution network management framework that unifies real-time voltage and Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next

Adaptive vehicle motion estimation and prediction

Science.gov (United States)

Zhao, Liang; Thorpe, Chuck E.

1999-01-01

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

Reliable 5-min real-time MR technique for left-ventricular-wall motion analysis

International Nuclear Information System (INIS)

Katoh, Marcus; Spuentrup, Elmar; Guenther, Rolf W.; Buecker, Arno; Kuehl, Harald P.; Lipke, Claudia S.A.

2007-01-01

The aim of this study was to investigate the value of a real-time magnetic resonance imaging (MRI) approach for the assessment of left-ventricular-wall motion in patients with insufficient transthoracic echocardiography in terms of accuracy and temporal expenditure. Twenty-five consecutive patients were examined on a 1.5-Tesla whole-body MR system (ACS-NT, Philips Medical Systems, Best, NL) using a real-time and ECG-gated (the current gold standard) steady-state free-precession (SSFP) sequence. Wall motion was analyzed by three observers by consensus interpretation. In addition, the preparation, scanning, and overall examination times were measured. The assessment of the wall motion demonstrated a close agreement between the two modalities resulting in a mean κ coefficient of 0.8. At the same time, each stage of the examination was significantly shortened using the real-time MR approach. Real-time imaging allows for accurate assessment of left-ventricular-wall motion with the added benefit of decreased examination time. Therefore, it may serve as a cost-efficient alternative in patients with insufficient echocardiography. (orig.)

Management of three-dimensional intrafraction motion through real-time DMLC tracking

International Nuclear Information System (INIS)

Sawant, Amit; Venkat, Raghu; Srivastava, Vikram; Carlson, David; Povzner, Sergey; Cattell, Herb; Keall, Paul

2008-01-01

Tumor tracking using a dynamic multileaf collimator (DMLC) represents a promising approach for intrafraction motion management in thoracic and abdominal cancer radiotherapy. In this work, we develop, empirically demonstrate, and characterize a novel 3D tracking algorithm for real-time, conformal, intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT)-based radiation delivery to targets moving in three dimensions. The algorithm obtains real-time information of target location from an independent position monitoring system and dynamically calculates MLC leaf positions to account for changes in target position. Initial studies were performed to evaluate the geometric accuracy of DMLC tracking of 3D target motion. In addition, dosimetric studies were performed on a clinical linac to evaluate the impact of real-time DMLC tracking for conformal, step-and-shoot (S-IMRT), dynamic (D-IMRT), and VMAT deliveries to a moving target. The efficiency of conformal and IMRT delivery in the presence of tracking was determined. Results show that submillimeter geometric accuracy in all three dimensions is achievable with DMLC tracking. Significant dosimetric improvements were observed in the presence of tracking for conformal and IMRT deliveries to moving targets. A gamma index evaluation with a 3%-3 mm criterion showed that deliveries without DMLC tracking exhibit between 1.7 (S-IMRT) and 4.8 (D-IMRT) times more dose points that fail the evaluation compared to corresponding deliveries with tracking. The efficiency of IMRT delivery, as measured in the lab, was observed to be significantly lower in case of tracking target motion perpendicular to MLC leaf travel compared to motion parallel to leaf travel. Nevertheless, these early results indicate that accurate, real-time DMLC tracking of 3D tumor motion is feasible and can potentially result in significant geometric and dosimetric advantages leading to more effective management of intrafraction motion

A graphics processing unit accelerated motion correction algorithm and modular system for real-time fMRI.

Science.gov (United States)

Scheinost, Dustin; Hampson, Michelle; Qiu, Maolin; Bhawnani, Jitendra; Constable, R Todd; Papademetris, Xenophon

2013-07-01

Real-time functional magnetic resonance imaging (rt-fMRI) has recently gained interest as a possible means to facilitate the learning of certain behaviors. However, rt-fMRI is limited by processing speed and available software, and continued development is needed for rt-fMRI to progress further and become feasible for clinical use. In this work, we present an open-source rt-fMRI system for biofeedback powered by a novel Graphics Processing Unit (GPU) accelerated motion correction strategy as part of the BioImage Suite project ( www.bioimagesuite.org ). Our system contributes to the development of rt-fMRI by presenting a motion correction algorithm that provides an estimate of motion with essentially no processing delay as well as a modular rt-fMRI system design. Using empirical data from rt-fMRI scans, we assessed the quality of motion correction in this new system. The present algorithm performed comparably to standard (non real-time) offline methods and outperformed other real-time methods based on zero order interpolation of motion parameters. The modular approach to the rt-fMRI system allows the system to be flexible to the experiment and feedback design, a valuable feature for many applications. We illustrate the flexibility of the system by describing several of our ongoing studies. Our hope is that continuing development of open-source rt-fMRI algorithms and software will make this new technology more accessible and adaptable, and will thereby accelerate its application in the clinical and cognitive neurosciences.

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...

Retrospective Reconstruction of High Temporal Resolution Cine Images from Real-Time MRI using Iterative Motion Correction

DEFF Research Database (Denmark)

Hansen, Michael Schacht; Sørensen, Thomas Sangild; Arai, Andrew

2012-01-01

acquisitions in 10 (N = 10) subjects. Acceptable image quality was obtained in all motion-corrected reconstructions, and the resulting mean image quality score was (a) Cartesian real-time: 2.48, (b) Golden Angle real-time: 1.90 (1.00–2.50), (c) Cartesian motion correction: 3.92, (d) Radial motion correction: 4...... and motion correction based on nonrigid registration and can be applied to arbitrary k-space trajectories. The method is demonstrated with real-time Cartesian imaging and Golden Angle radial acquisitions, and the motion-corrected acquisitions are compared with raw real-time images and breath-hold cine...

Real-Time Motion Management of Prostate Cancer Radiotherapy

DEFF Research Database (Denmark)

Pommer, Tobias

of this thesis is to manage prostate motion in real-time by aligning the radiation beam to the prostate using the novel dynamic multileaf collimator (DMLC) tracking method. Specifically, the delivered dose with tracking was compared to the planned dose, and the impact of treatment plan complexity and limitations...

Memory Efficient VLSI Implementation of Real-Time Motion Detection System Using FPGA Platform

Directory of Open Access Journals (Sweden)

Sanjay Singh

2017-06-01

Full Text Available Motion detection is the heart of a potentially complex automated video surveillance system, intended to be used as a standalone system. Therefore, in addition to being accurate and robust, a successful motion detection technique must also be economical in the use of computational resources on selected FPGA development platform. This is because many other complex algorithms of an automated video surveillance system also run on the same platform. Keeping this key requirement as main focus, a memory efficient VLSI architecture for real-time motion detection and its implementation on FPGA platform is presented in this paper. This is accomplished by proposing a new memory efficient motion detection scheme and designing its VLSI architecture. The complete real-time motion detection system using the proposed memory efficient architecture along with proper input/output interfaces is implemented on Xilinx ML510 (Virtex-5 FX130T FPGA development platform and is capable of operating at 154.55 MHz clock frequency. Memory requirement of the proposed architecture is reduced by 41% compared to the standard clustering based motion detection architecture. The new memory efficient system robustly and automatically detects motion in real-world scenarios (both for the static backgrounds and the pseudo-stationary backgrounds in real-time for standard PAL (720 × 576 size color video.

Adaptive Kalman filtering for real-time mapping of the visual field

Science.gov (United States)

Ward, B. Douglas; Janik, John; Mazaheri, Yousef; Ma, Yan; DeYoe, Edgar A.

2013-01-01

This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results. Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field. Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications. The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume. PMID:22100663

Real-time DSP implementation for MRF-based video motion detection.

Science.gov (United States)

Dumontier, C; Luthon, F; Charras, J P

1999-01-01

This paper describes the real time implementation of a simple and robust motion detection algorithm based on Markov random field (MRF) modeling, MRF-based algorithms often require a significant amount of computations. The intrinsic parallel property of MRF modeling has led most of implementations toward parallel machines and neural networks, but none of these approaches offers an efficient solution for real-world (i.e., industrial) applications. Here, an alternative implementation for the problem at hand is presented yielding a complete, efficient and autonomous real-time system for motion detection. This system is based on a hybrid architecture, associating pipeline modules with one asynchronous module to perform the whole process, from video acquisition to moving object masks visualization. A board prototype is presented and a processing rate of 15 images/s is achieved, showing the validity of the approach.

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

Science.gov (United States)

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Real-Time Optimization for use in a Control Allocation System to Recover from Pilot Induced Oscillations

Science.gov (United States)

Leonard, Michael W.

2013-01-01

Integration of the Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) System into the control system of a Short Takeoff and Landing Mobility Concept Vehicle simulation presents a challenge because the CAPIO formulation requires that constrained optimization problems be solved at the controller operating frequency. We present a solution that utilizes a modified version of the well-known L-BFGS-B solver. Despite the iterative nature of the solver, the method is seen to converge in real time with sufficient reliability to support three weeks of piloted runs at the NASA Ames Vertical Motion Simulator (VMS) facility. The results of the optimization are seen to be excellent in the vast majority of real-time frames. Deficiencies in the quality of the results in some frames are shown to be improvable with simple termination criteria adjustments, though more real-time optimization iterations would be required.

SU-F-303-17: Real Time Dose Calculation of MRI Guided Co-60 Radiotherapy Treatments On Free Breathing Patients, Using a Motion Model and Fast Monte Carlo Dose Calculation

International Nuclear Information System (INIS)

Thomas, D; O’Connell, D; Lamb, J; Cao, M; Yang, Y; Agazaryan, N; Lee, P; Low, D

2015-01-01

Purpose: To demonstrate real-time dose calculation of free-breathing MRI guided Co−60 treatments, using a motion model and Monte-Carlo dose calculation to accurately account for the interplay between irregular breathing motion and an IMRT delivery. Methods: ViewRay Co-60 dose distributions were optimized on ITVs contoured from free-breathing CT images of lung cancer patients. Each treatment plan was separated into 0.25s segments, accounting for the MLC positions and beam angles at each time point. A voxel-specific motion model derived from multiple fast-helical free-breathing CTs and deformable registration was calculated for each patient. 3D images for every 0.25s of a simulated treatment were generated in real time, here using a bellows signal as a surrogate to accurately account for breathing irregularities. Monte-Carlo dose calculation was performed every 0.25s of the treatment, with the number of histories in each calculation scaled to give an overall 1% statistical uncertainty. Each dose calculation was deformed back to the reference image using the motion model and accumulated. The static and real-time dose calculations were compared. Results: Image generation was performed in real time at 4 frames per second (GPU). Monte-Carlo dose calculation was performed at approximately 1frame per second (CPU), giving a total calculation time of approximately 30 minutes per treatment. Results show both cold- and hot-spots in and around the ITV, and increased dose to contralateral lung as the tumor moves in and out of the beam during treatment. Conclusion: An accurate motion model combined with a fast Monte-Carlo dose calculation allows almost real-time dose calculation of a free-breathing treatment. When combined with sagittal 2D-cine-mode MRI during treatment to update the motion model in real time, this will allow the true delivered dose of a treatment to be calculated, providing a useful tool for adaptive planning and assessing the effectiveness of gated treatments

Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

Science.gov (United States)

Du, Bing; Ruan, Chun

With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

Real-time high-speed motion blur compensation system based on back-and-forth motion control of galvanometer mirror.

Science.gov (United States)

Hayakawa, Tomohiko; Watanabe, Takanoshin; Ishikawa, Masatoshi

2015-12-14

We developed a novel real-time motion blur compensation system for the blur caused by high-speed one-dimensional motion between a camera and a target. The system consists of a galvanometer mirror and a high-speed color camera, without the need for any additional sensors. We controlled the galvanometer mirror with continuous back-and-forth oscillating motion synchronized to a high-speed camera. The angular speed of the mirror is given in real time within 10 ms based on the concept of background tracking and rapid raw Bayer block matching. Experiments demonstrated that our system captures motion-invariant images of objects moving at speeds up to 30 km/h.

The first clinical implementation of real-time image-guided adaptive radiotherapy using a standard linear accelerator.

Science.gov (United States)

Keall, Paul J; Nguyen, Doan Trang; O'Brien, Ricky; Caillet, Vincent; Hewson, Emily; Poulsen, Per Rugaard; Bromley, Regina; Bell, Linda; Eade, Thomas; Kneebone, Andrew; Martin, Jarad; Booth, Jeremy T

2018-04-01

Until now, real-time image guided adaptive radiation therapy (IGART) has been the domain of dedicated cancer radiotherapy systems. The purpose of this study was to clinically implement and investigate real-time IGART using a standard linear accelerator. We developed and implemented two real-time technologies for standard linear accelerators: (1) Kilovoltage Intrafraction Monitoring (KIM) that finds the target and (2) multileaf collimator (MLC) tracking that aligns the radiation beam to the target. Eight prostate SABR patients were treated with this real-time IGART technology. The feasibility, geometric accuracy and the dosimetric fidelity were measured. Thirty-nine out of forty fractions with real-time IGART were successful (95% confidence interval 87-100%). The geometric accuracy of the KIM system was -0.1 ± 0.4, 0.2 ± 0.2 and -0.1 ± 0.6 mm in the LR, SI and AP directions, respectively. The dose reconstruction showed that real-time IGART more closely reproduced the planned dose than that without IGART. For the largest motion fraction, with real-time IGART 100% of the CTV received the prescribed dose; without real-time IGART only 95% of the CTV would have received the prescribed dose. The clinical implementation of real-time image-guided adaptive radiotherapy on a standard linear accelerator using KIM and MLC tracking is feasible. This achievement paves the way for real-time IGART to be a mainstream treatment option. Copyright © 2018 Elsevier B.V. All rights reserved.

Three-dimensional liver motion tracking using real-time two-dimensional MRI.

Science.gov (United States)

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

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

Real-time recursive motion segmentation of video data on a programmable device

NARCIS (Netherlands)

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

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

Science.gov (United States)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Infrared wireless data transfer for real-time motion control

NARCIS (Netherlands)

Gajdusek, M.; Overboom, T.T.; Damen, A.A.H.; Bosch, van den P.P.J.

2009-01-01

In this paper several wireless solution are compared for their suitability for real-time control of a fast motion system. From the comparison, Very Fast Infrared (VFIR) communication link has been found to be an attractive solution for presented wirelessly controlled manipulator. Because standard

Adaptive cancellation of motion artifact in wearable biosensors.

Science.gov (United States)

Yousefi, Rasoul; Nourani, Mehrdad; Panahi, Issa

2012-01-01

The performance of wearable biosensors is highly influenced by motion artifact. In this paper, a model is proposed for analysis of motion artifact in wearable photoplethysmography (PPG) sensors. Using this model, we proposed a robust real-time technique to estimate fundamental frequency and generate a noise reference signal. A Least Mean Square (LMS) adaptive noise canceler is then designed and validated using our synthetic noise generator. The analysis and results on proposed technique for noise cancellation shows promising performance.

The Optimal Timing of Strategic Action – A Real Options Approach

Directory of Open Access Journals (Sweden)

Gordon G. Sollars

2012-01-01

Full Text Available he possibility of a first-mover advantage arises in a variety of strategic choices, including product introductions, business start-ups, and mergers and acquisitions. The strategic management literature reflects ambiguity regarding the likelihood that a first mover can or will capture additional value. This paper uses a real options approach to address the optimal timing of strategic moves. Previous studies have modeled real options using either a perpetual or a European financial option. With these models, a strategic choice could only be made either without respect to a time frame (perpetual or at a fixed point in time (European option. Neither case is realistic. Companies typically have strategic options with only a limited time frame due to market factors, but companies may choose to act at any time within that constraint. To reflect this reality, we adapt a method for valuing an American financial option on a dividend paying stock to the real options context. The method presented in this paper proposes a solution for the optimum value for a project that should trigger a strategic choice, and highlights the value lost by not acting optimally. We use simulation results to show that the time frame available to make a strategic choice has an important effect on both the project value for when action should be taken, as well as on the value of waiting to invest at the optimal time. The results presented in this paper help to clarify the ambiguity that is found in the strategic management literature regarding the possibility of obtaining a first-mover advantage. Indeed, a first mover that acts sub-optimally could incur losses or at least not gain any advantage. A first mover that waits to invest at the right time based on the superior information supplied by models based on real options could be better positioned to obtain the benefits that might come from the first move.

Real time microcontroller implementation of an adaptive myoelectric filter.

Science.gov (United States)

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.

ANFIS Based Time Series Prediction Method of Bank Cash Flow Optimized by Adaptive Population Activity PSO Algorithm

Directory of Open Access Journals (Sweden)

Jie-Sheng Wang

2015-06-01

Full Text Available In order to improve the accuracy and real-time of all kinds of information in the cash business, and solve the problem which accuracy and stability is not high of the data linkage between cash inventory forecasting and cash management information in the commercial bank, a hybrid learning algorithm is proposed based on adaptive population activity particle swarm optimization (APAPSO algorithm combined with the least squares method (LMS to optimize the adaptive network-based fuzzy inference system (ANFIS model parameters. Through the introduction of metric function of population diversity to ensure the diversity of population and adaptive changes in inertia weight and learning factors, the optimization ability of the particle swarm optimization (PSO algorithm is improved, which avoids the premature convergence problem of the PSO algorithm. The simulation comparison experiments are carried out with BP-LMS algorithm and standard PSO-LMS by adopting real commercial banks’ cash flow data to verify the effectiveness of the proposed time series prediction of bank cash flow based on improved PSO-ANFIS optimization method. Simulation results show that the optimization speed is faster and the prediction accuracy is higher.

Real time production optimization

Energy Technology Data Exchange (ETDEWEB)

Saputelli, Luigi; Otavio, Joao; Araujo, Turiassu; Escorcia, Alvaro [Halliburton, Houston, TX (United States). Landmark Division

2004-07-01

Production optimization encompasses various activities of measuring, analyzing, modeling, prioritizing and implementing actions to enhance productivity of a field. We present a state-of-the-art framework for optimizing production on a continuous basis as new sensor data is acquired in real time. Permanently acquired data is modeled and analyzed in order to create predictive models. A model based control strategy is used to regulate well and field instrumentation. The optimum field operating point, which changes with time, satisfies the maximum economic return. This work is a starting point for further development in automatic, intelligent reservoir technologies which get the most out of the abilities of permanent, instrumented wells and remotely activated downhole completions. The strategy, tested with history-matched data from a compartmentalised giant field, proved to reduce operating costs while increasing oil recovery by 27% in this field. (author)

Real-Time Adaptation of Influence Strategies in Online Selling

NARCIS (Netherlands)

Kaptein, M.C.; Parvinen, P.

2014-01-01

Real-time adjustments in online selling are becoming increasingly common. In this paper we describe a novel method of real-time adaptation, and introduce influence strategies as a useful level of analysis for personalization of online selling. The proposed method incorporates three perspectives on

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

Science.gov (United States)

Houck, Jacob A. (Technical Monitor); Telban, Robert J.; Cardullo, Frank M.

2005-01-01

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Real-time tracking of tumor motions and deformations along the leaf travel direction with the aid of a synchronized dynamic MLC leaf sequencer

International Nuclear Information System (INIS)

Tacke, Martin; Nill, Simeon; Oelfke, Uwe

2007-01-01

Advanced radiotherapeutical techniques like intensity-modulated radiation therapy (IMRT) are based on an accurate knowledge of the location of the radiation target. An accurate dose delivery, therefore, requires a method to account for the inter- and intrafractional target motion and the target deformation occurring during the course of treatment. A method to compensate in real time for changes in the position and shape of the target is the use of a dynamic multileaf collimator (MLC) technique which can be devised to automatically arrange the treatment field according to real-time image information. So far, various approaches proposed for leaf sequencers have had to rely on a priori known target motion data and have aimed to optimize the overall treatment time. Since for a real-time dose delivery the target motion is not known a priori, the velocity range of the leading leaves is restricted by a safety margin to c x v max while the following leaves can travel with an additional maximum speed to compensate for the respective target movements. Another aspect to be considered is the tongue and groove effect. A uniform radiation field can only be achieved if the leaf movements are synchronized. The method presented in this note is the first to combine a synchronizing sequencer and real-time tracking with a dynamic MLC. The newly developed algorithm is capable of online optimizing the leaf velocities by minimizing the overall treatment time while at the same time it synchronizes the leaf trajectories in order to avoid the tongue and groove effect. The simultaneous synchronization is performed with the help of an online-calculated mid-time leaf trajectory which is common for all leaf pairs and which takes into account the real-time target motion and deformation information. (note)

Real-time tracking of tumor motions and deformations along the leaf travel direction with the aid of a synchronized dynamic MLC leaf sequencer.

Science.gov (United States)

Tacke, Martin; Nill, Simeon; Oelfke, Uwe

2007-11-21

Advanced radiotherapeutical techniques like intensity-modulated radiation therapy (IMRT) are based on an accurate knowledge of the location of the radiation target. An accurate dose delivery, therefore, requires a method to account for the inter- and intrafractional target motion and the target deformation occurring during the course of treatment. A method to compensate in real time for changes in the position and shape of the target is the use of a dynamic multileaf collimator (MLC) technique which can be devised to automatically arrange the treatment field according to real-time image information. So far, various approaches proposed for leaf sequencers have had to rely on a priori known target motion data and have aimed to optimize the overall treatment time. Since for a real-time dose delivery the target motion is not known a priori, the velocity range of the leading leaves is restricted by a safety margin to c x v(max) while the following leaves can travel with an additional maximum speed to compensate for the respective target movements. Another aspect to be considered is the tongue and groove effect. A uniform radiation field can only be achieved if the leaf movements are synchronized. The method presented in this note is the first to combine a synchronizing sequencer and real-time tracking with a dynamic MLC. The newly developed algorithm is capable of online optimizing the leaf velocities by minimizing the overall treatment time while at the same time it synchronizes the leaf trajectories in order to avoid the tongue and groove effect. The simultaneous synchronization is performed with the help of an online-calculated mid-time leaf trajectory which is common for all leaf pairs and which takes into account the real-time target motion and deformation information.

Self-Organization in Embedded Real-Time Systems

CERN Document Server

Brinkschulte, Uwe; Rettberg, Achim

2013-01-01

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

Real-time motion analytics during brain MRI improve data quality and reduce costs.

Science.gov (United States)

Dosenbach, Nico U F; Koller, Jonathan M; Earl, Eric A; Miranda-Dominguez, Oscar; Klein, Rachel L; Van, Andrew N; Snyder, Abraham Z; Nagel, Bonnie J; Nigg, Joel T; Nguyen, Annie L; Wesevich, Victoria; Greene, Deanna J; Fair, Damien A

2017-11-01

Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

Science.gov (United States)

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

Real-time tumor motion estimation using respiratory surrogate via memory-based learning

International Nuclear Information System (INIS)

Li Ruijiang; Xing Lei; Lewis, John H; Berbeco, Ross I

2012-01-01

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95

Real-time tumor motion estimation using respiratory surrogate via memory-based learning

Science.gov (United States)

Li, Ruijiang; Lewis, John H.; Berbeco, Ross I.; Xing, Lei

2012-08-01

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95

Real-time prediction of respiratory motion based on local regression methods

International Nuclear Information System (INIS)

Ruan, D; Fessler, J A; Balter, J M

2007-01-01

Recent developments in modulation techniques enable conformal delivery of radiation doses to small, localized target volumes. One of the challenges in using these techniques is real-time tracking and predicting target motion, which is necessary to accommodate system latencies. For image-guided-radiotherapy systems, it is also desirable to minimize sampling rates to reduce imaging dose. This study focuses on predicting respiratory motion, which can significantly affect lung tumours. Predicting respiratory motion in real-time is challenging, due to the complexity of breathing patterns and the many sources of variability. We propose a prediction method based on local regression. There are three major ingredients of this approach: (1) forming an augmented state space to capture system dynamics, (2) local regression in the augmented space to train the predictor from previous observation data using semi-periodicity of respiratory motion, (3) local weighting adjustment to incorporate fading temporal correlations. To evaluate prediction accuracy, we computed the root mean square error between predicted tumor motion and its observed location for ten patients. For comparison, we also investigated commonly used predictive methods, namely linear prediction, neural networks and Kalman filtering to the same data. The proposed method reduced the prediction error for all imaging rates and latency lengths, particularly for long prediction lengths

Real-time identification of vehicle motion-modes using neural networks

Science.gov (United States)

Wang, Lifu; Zhang, Nong; Du, Haiping

2015-01-01

A four-wheel ground vehicle has three body-dominated motion-modes, that is, bounce, roll, and pitch motion-modes. Real-time identification of these motion-modes can make vehicle suspensions, in particular, active suspensions, target on the dominant motion-mode and apply appropriate control strategies to improve its performance with less power consumption. Recently, a motion-mode energy method (MEM) was developed to identify the vehicle body motion-modes. However, this method requires the measurement of full vehicle states and road inputs, which are not always available in practice. This paper proposes an alternative approach to identify vehicle primary motion-modes with acceptable accuracy by employing neural networks (NNs). The effectiveness of the trained NNs is verified on a 10-DOF full-car model under various types of excitation inputs. The results confirm that the proposed method is effective in determining vehicle primary motion-modes with comparable accuracy to the MEM method. Experimental data is further used to validate the proposed method.

Controlling the error on target motion through real-time mesh adaptation: Applications to deep brain stimulation.

Science.gov (United States)

Bui, Huu Phuoc; Tomar, Satyendra; Courtecuisse, Hadrien; Audette, Michel; Cotin, Stéphane; Bordas, Stéphane P A

2018-05-01

An error-controlled mesh refinement procedure for needle insertion simulations is presented. As an example, the procedure is applied for simulations of electrode implantation for deep brain stimulation. We take into account the brain shift phenomena occurring when a craniotomy is performed. We observe that the error in the computation of the displacement and stress fields is localised around the needle tip and the needle shaft during needle insertion simulation. By suitably and adaptively refining the mesh in this region, our approach enables to control, and thus to reduce, the error whilst maintaining a coarser mesh in other parts of the domain. Through academic and practical examples we demonstrate that our adaptive approach, as compared with a uniform coarse mesh, increases the accuracy of the displacement and stress fields around the needle shaft and, while for a given accuracy, saves computational time with respect to a uniform finer mesh. This facilitates real-time simulations. The proposed methodology has direct implications in increasing the accuracy, and controlling the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anaesthesia, or cryotherapy. Moreover, the proposed approach can be helpful in the development of robotic surgeries because the simulation taking place in the control loop of a robot needs to be accurate, and to occur in real time. Copyright © 2018 John Wiley & Sons, Ltd.

System-level power optimization for real-time distributed embedded systems

Science.gov (United States)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as

Optimization of Partitioned Architectures to Support Soft Real-Time Applications

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2014-01-01

In this paper we propose a new Tabu Search-based design optimization strategy for mixed-criticality systems implementing hard and soft real-time applications on the same platform. Our proposed strategy determined an implementation such that all hard real-time applications are schedulable and the ......In this paper we propose a new Tabu Search-based design optimization strategy for mixed-criticality systems implementing hard and soft real-time applications on the same platform. Our proposed strategy determined an implementation such that all hard real-time applications are schedulable...... and the quality of service of the soft real-time tasks is maximized. We have evaluated our strategy using an aerospace case study....

Rt-Space: A Real-Time Stochastically-Provisioned Adaptive Container Environment

Science.gov (United States)

2017-08-04

Real-Time Systems (ECRTS) Conference Location: Toulouse, France Paper Title: Multiprocessor Real-Time Locking Protocols for Replicated Resources...Conference Location: Lille, France Paper Title: A Contention-Sensitive Fine-Grained Locking Protocol for Multiprocessor Real-Time Systems Publication...On the Soft Real-Time Optimality of Global EDF on Multiprocessors: From Identical to Uniform Heterogeneous Publication Type: Conference Paper or

Optimal, real-time control--colliders

International Nuclear Information System (INIS)

Spencer, J.E.

1991-05-01

With reasonable definitions, optimal control is possible for both classical and quantal systems with new approaches called PISC(Parallel) and NISC(Neural) from analogy with RISC (Reduced Instruction Set Computing). If control equals interaction, observation and comparison to some figure of merit with interaction via external fields, then optimization comes from varying these fields to give design or operating goals. Structural stability can then give us tolerance and design constraints. But simulations use simplified models, are not in real-time and assume fixed or stationary conditions, so optimal control goes far beyond convergence rates of algorithms. It is inseparable from design and this has many implications for colliders. 12 refs., 3 figs

Three axis electronic flight motion simulator real time control system design and implementation.

Science.gov (United States)

Gao, Zhiyuan; Miao, Zhonghua; Wang, Xuyong; Wang, Xiaohua

2014-12-01

A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.

Three axis electronic flight motion simulator real time control system design and implementation

Energy Technology Data Exchange (ETDEWEB)

Gao, Zhiyuan; Miao, Zhonghua, E-mail: zhonghua-miao@163.com; Wang, Xiaohua [School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200072 (China); Wang, Xuyong [School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)

2014-12-15

A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.

Real-time spatial optimization : based on the application in wood supply chain management

International Nuclear Information System (INIS)

Scholz, J.

2010-01-01

Real-time spatial optimization - a combination of Geographical Information Science and Technology and Operations Research - is capable of generating optimized solutions to given spatial problems in real-time. The basic concepts to develop a real-time spatial optimization system are outlined in this thesis. Geographic Information Science delivers the foundations for acquiring, storing, manipulating, visualizing and analyzing spatial information. In order to develop a system that consists of several independent components the concept of Service Oriented Architectures is applied. This facilitates communication between software systems utilizing standardized services that ensure interoperability. Thus, standards in the field of Geographic Information are inevitable for real-time spatial optimization. By exploiting the ability of mobile devices to determine the own position paired with standardized services Location Based Services are created. They are of interest in order to gather real-time data from mobile devices that are of importance for the optimization process itself. To optimize a given spatial problem, the universe of discourse has to be modeled accordingly. For the problem addressed in this thesis - Wood Supply Chain management - Graph theory is used. In addition, the problem of Wood Supply Chain management can be represented by a specific mathematical problem class, the Vehicle Routing problem - specifically the Vehicle Routing Problem with Pickup and Delivery and Time Windows. To optimize this problem class, exact and approximate solution techniques exist. Exact algorithms provide optimal solutions and guarantee their optimally, whereas approximate techniques - approximation algorithms or heuristics - do not guarantee that a global optimum is found. Nevertheless, the are capable of handling large problem instances in reasonable time. For optimizing the Wood Supply Chain Adaptive Large Neighborhood Search is selected as appropriate optimization technique

Real-time sail and heading optimization for a surface sailing vessel by extremum seeking control

DEFF Research Database (Denmark)

Treichel, Kai; Jouffroy, Jerome

2010-01-01

In this paper we develop a simplified mathematical model representing the main elements of the behaviour of sailing vessels as a basis for simulation and controller design. For adaptive real-time optimization of the sail and heading angle we then apply extremum seeking control (which is a gradient...

A Dynamic Optimization Method of Indoor Fire Evacuation Route Based on Real-time Situation Awareness

Directory of Open Access Journals (Sweden)

DING Yulin

2016-12-01

Full Text Available How to provide safe and effective evacuation routes is an important safeguard to correctly guide evacuation and reduce the casualties during the fire situation rapidly evolving in complex indoor environment. The traditional static path finding method is difficult to adjust the path adaptively according to the changing fire situation, which lead to the evacuation decision-making blindness and hysteresis. This paper proposes a dynamic method which can dynamically optimize the indoor evacuation routes based on the real-time situation awareness. According to the real-time perception of fire situation parameters and the changing indoor environment information, the evacuation route is optimized dynamically. The integrated representation of multisource indoor fire monitoring sensor observations oriented fire emergency evacuation is presented at first, real-time fire threat situation information inside building is then extracted from the observation data of multi-source sensors, which is used to constrain the dynamical optimization of the topology of the evacuation route. Finally, the simulation experiments prove that this method can improve the accuracy and efficiency of indoor evacuation routing.

Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

Science.gov (United States)

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

New human-centered linear and nonlinear motion cueing algorithms for control of simulator motion systems

Science.gov (United States)

Telban, Robert J.

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input

A multiple model approach to respiratory motion prediction for real-time IGRT

International Nuclear Information System (INIS)

Putra, Devi; Haas, Olivier C L; Burnham, Keith J; Mills, John A

2008-01-01

Respiration induces significant movement of tumours in the vicinity of thoracic and abdominal structures. Real-time image-guided radiotherapy (IGRT) aims to adapt radiation delivery to tumour motion during irradiation. One of the main problems for achieving this objective is the presence of time lag between the acquisition of tumour position and the radiation delivery. Such time lag causes significant beam positioning errors and affects the dose coverage. A method to solve this problem is to employ an algorithm that is able to predict future tumour positions from available tumour position measurements. This paper presents a multiple model approach to respiratory-induced tumour motion prediction using the interacting multiple model (IMM) filter. A combination of two models, constant velocity (CV) and constant acceleration (CA), is used to capture respiratory-induced tumour motion. A Kalman filter is designed for each of the local models and the IMM filter is applied to combine the predictions of these Kalman filters for obtaining the predicted tumour position. The IMM filter, likewise the Kalman filter, is a recursive algorithm that is suitable for real-time applications. In addition, this paper proposes a confidence interval (CI) criterion to evaluate the performance of tumour motion prediction algorithms for IGRT. The proposed CI criterion provides a relevant measure for the prediction performance in terms of clinical applications and can be used to specify the margin to accommodate prediction errors. The prediction performance of the IMM filter has been evaluated using 110 traces of 4-minute free-breathing motion collected from 24 lung-cancer patients. The simulation study was carried out for prediction time 0.1-0.6 s with sampling rates 3, 5 and 10 Hz. It was found that the prediction of the IMM filter was consistently better than the prediction of the Kalman filter with the CV or CA model. There was no significant difference of prediction errors for the

Integrals of Motion for Discrete-Time Optimal Control Problems

OpenAIRE

Torres, Delfim F. M.

2003-01-01

We obtain a discrete time analog of E. Noether's theorem in Optimal Control, asserting that integrals of motion associated to the discrete time Pontryagin Maximum Principle can be computed from the quasi-invariance properties of the discrete time Lagrangian and discrete time control system. As corollaries, results for first-order and higher-order discrete problems of the calculus of variations are obtained.

Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

Energy Technology Data Exchange (ETDEWEB)

Moore, Douglas, E-mail: douglas.moore@utsouthwestern.edu; Sawant, Amit [Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Ruan, Dan [Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

2016-01-15

Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al

Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

International Nuclear Information System (INIS)

Moore, Douglas; Sawant, Amit; Ruan, Dan

2016-01-01

Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al

Development of a frameless stereotactic radiosurgery system based on real-time 6D position monitoring and adaptive head motion compensation

Energy Technology Data Exchange (ETDEWEB)

Wiersma, Rodney D; Wen Zhifei; Sadinski, Meredith; Farrey, Karl; Yenice, Kamil M [Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL 60637 (United States)], E-mail: rwiersma@uchicago.edu

2010-01-21

Stereotactic radiosurgery delivers radiation with great spatial accuracy. To achieve sub-millimeter accuracy for intracranial SRS, a head ring is rigidly fixated to the skull to create a fixed reference. For some patients, the invasiveness of the ring can be highly uncomfortable and not well tolerated. In addition, placing and removing the ring requires special expertise from a neurosurgeon, and patient setup time for SRS can often be long. To reduce the invasiveness, hardware limitations and setup time, we are developing a system for performing accurate head positioning without the use of a head ring. The proposed method uses real-time 6D optical position feedback for turning on and off the treatment beam (gating) and guiding a motor-controlled 3D head motion compensation stage. The setup consists of a central control computer, an optical patient motion tracking system and a 3D motion compensation stage attached to the front of the LINAC couch. A styrofoam head cast was custom-built for patient support and was mounted on the compensation stage. The motion feedback of the markers was processed by the control computer, and the resulting motion of the target was calculated using a rigid body model. If the target deviated beyond a preset position of 0.2 mm, an automatic position correction was performed with stepper motors to adjust the head position via the couch mount motion platform. In the event the target deviated more than 1 mm, a safety relay switch was activated and the treatment beam was turned off. The feasibility of the concept was tested using five healthy volunteers. Head motion data were acquired with and without the use of motion compensation over treatment times of 15 min. On average, test subjects exceeded the 0.5 mm tolerance 86% of the time and the 1.0 mm tolerance 45% of the time without motion correction. With correction, this percentage was reduced to 5% and 2% for the 0.5 mm and 1.0 mm tolerances, respectively.

Development of a frameless stereotactic radiosurgery system based on real-time 6D position monitoring and adaptive head motion compensation

International Nuclear Information System (INIS)

Wiersma, Rodney D; Wen Zhifei; Sadinski, Meredith; Farrey, Karl; Yenice, Kamil M

2010-01-01

Stereotactic radiosurgery delivers radiation with great spatial accuracy. To achieve sub-millimeter accuracy for intracranial SRS, a head ring is rigidly fixated to the skull to create a fixed reference. For some patients, the invasiveness of the ring can be highly uncomfortable and not well tolerated. In addition, placing and removing the ring requires special expertise from a neurosurgeon, and patient setup time for SRS can often be long. To reduce the invasiveness, hardware limitations and setup time, we are developing a system for performing accurate head positioning without the use of a head ring. The proposed method uses real-time 6D optical position feedback for turning on and off the treatment beam (gating) and guiding a motor-controlled 3D head motion compensation stage. The setup consists of a central control computer, an optical patient motion tracking system and a 3D motion compensation stage attached to the front of the LINAC couch. A styrofoam head cast was custom-built for patient support and was mounted on the compensation stage. The motion feedback of the markers was processed by the control computer, and the resulting motion of the target was calculated using a rigid body model. If the target deviated beyond a preset position of 0.2 mm, an automatic position correction was performed with stepper motors to adjust the head position via the couch mount motion platform. In the event the target deviated more than 1 mm, a safety relay switch was activated and the treatment beam was turned off. The feasibility of the concept was tested using five healthy volunteers. Head motion data were acquired with and without the use of motion compensation over treatment times of 15 min. On average, test subjects exceeded the 0.5 mm tolerance 86% of the time and the 1.0 mm tolerance 45% of the time without motion correction. With correction, this percentage was reduced to 5% and 2% for the 0.5 mm and 1.0 mm tolerances, respectively.

Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression

International Nuclear Information System (INIS)

Bukhari, W; Hong, S-M

2015-01-01

Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR + , implements a gating function without pre-specifying a particular region of the patient’s breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR + algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR + implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR + in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR + . The experimental results show that the EKF-GPR + algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR + reduces the patient-wise RMS error to 37%, 39% and 42

Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression

Science.gov (United States)

Bukhari, W.; Hong, S.-M.

2015-01-01

Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR+, implements a gating function without pre-specifying a particular region of the patient’s breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR+ algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR+ implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR+ in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR+. The experimental results show that the EKF-GPR+ algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR+ reduces the patient-wise RMS error to 37%, 39% and 42% in

Real-time prediction and gating of respiratory motion using an extended Kalman filter and Gaussian process regression.

Science.gov (United States)

Bukhari, W; Hong, S-M

2015-01-07

Motion-adaptive radiotherapy aims to deliver a conformal dose to the target tumour with minimal normal tissue exposure by compensating for tumour motion in real time. The prediction as well as the gating of respiratory motion have received much attention over the last two decades for reducing the targeting error of the treatment beam due to respiratory motion. In this article, we present a real-time algorithm for predicting and gating respiratory motion that utilizes a model-based and a model-free Bayesian framework by combining them in a cascade structure. The algorithm, named EKF-GPR(+), implements a gating function without pre-specifying a particular region of the patient's breathing cycle. The algorithm first employs an extended Kalman filter (LCM-EKF) to predict the respiratory motion and then uses a model-free Gaussian process regression (GPR) to correct the error of the LCM-EKF prediction. The GPR is a non-parametric Bayesian algorithm that yields predictive variance under Gaussian assumptions. The EKF-GPR(+) algorithm utilizes the predictive variance from the GPR component to capture the uncertainty in the LCM-EKF prediction error and systematically identify breathing points with a higher probability of large prediction error in advance. This identification allows us to pause the treatment beam over such instances. EKF-GPR(+) implements the gating function by using simple calculations based on the predictive variance with no additional detection mechanism. A sparse approximation of the GPR algorithm is employed to realize EKF-GPR(+) in real time. Extensive numerical experiments are performed based on a large database of 304 respiratory motion traces to evaluate EKF-GPR(+). The experimental results show that the EKF-GPR(+) algorithm effectively reduces the prediction error in a root-mean-square (RMS) sense by employing the gating function, albeit at the cost of a reduced duty cycle. As an example, EKF-GPR(+) reduces the patient-wise RMS error to 37%, 39% and

Analysis and Optimization of Heterogeneous Real-Time Embedded Systems

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2005-01-01

. The success of such new design methods depends on the availability of analysis and optimization techniques. In this paper, we present analysis and optimization techniques for heterogeneous real-time embedded systems. We address in more detail a particular class of such systems called multi-clusters, composed...... to frames. Optimization heuristics for frame packing aiming at producing a schedulable system are presented. Extensive experiments and a real-life example show the efficiency of the frame-packing approach....

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

Science.gov (United States)

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

2013-01-01

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

Self-Motion Perception: Assessment by Real-Time Computer Generated Animations

Science.gov (United States)

Parker, Donald E.

1999-01-01

Our overall goal is to develop materials and procedures for assessing vestibular contributions to spatial cognition. The specific objective of the research described in this paper is to evaluate computer-generated animations as potential tools for studying self-orientation and self-motion perception. Specific questions addressed in this study included the following. First, does a non- verbal perceptual reporting procedure using real-time animations improve assessment of spatial orientation? Are reports reliable? Second, do reports confirm expectations based on stimuli to vestibular apparatus? Third, can reliable reports be obtained when self-motion description vocabulary training is omitted?

Monitoring tumor motion by real time 2D/3D registration during radiotherapy.

Science.gov (United States)

Gendrin, Christelle; Furtado, Hugo; Weber, Christoph; Bloch, Christoph; Figl, Michael; Pawiro, Supriyanto Ardjo; Bergmann, Helmar; Stock, Markus; Fichtinger, Gabor; Georg, Dietmar; Birkfellner, Wolfgang

2012-02-01

In this paper, we investigate the possibility to use X-ray based real time 2D/3D registration for non-invasive tumor motion monitoring during radiotherapy. The 2D/3D registration scheme is implemented using general purpose computation on graphics hardware (GPGPU) programming techniques and several algorithmic refinements in the registration process. Validation is conducted off-line using a phantom and five clinical patient data sets. The registration is performed on a region of interest (ROI) centered around the planned target volume (PTV). The phantom motion is measured with an rms error of 2.56 mm. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is shown. Videos show a good match between X-ray and digitally reconstructed radiographs (DRR) displacement. Mean registration time is 0.5 s. We have demonstrated that real-time organ motion monitoring using image based markerless registration is feasible. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Optimal Throughput and Self-adaptability of Robust Real-Time IEEE 802.15.4 MAC for AMI Mesh Network

International Nuclear Information System (INIS)

Shabani, Hikma; Ahmed, Musse Mohamud; Khan, Sheroz; Hameed, Shahab Ahmed; Habaebi, Mohamed Hadi

2013-01-01

A smart grid refers to a modernization of the electricity system that brings intelligence, reliability, efficiency and optimality to the power grid. To provide an automated and widely distributed energy delivery, the smart grid will be branded by a two-way flow of electricity and information system between energy suppliers and their customers. Thus, the smart grid is a power grid that integrates data communication networks which provide the collected and analysed data at all levels in real time. Therefore, the performance of communication systems is so vital for the success of smart grid. Merit to the ZigBee/IEEE802.15.4std low cost, low power, low data rate, short range, simplicity and free licensed spectrum that makes wireless sensor networks (WSNs) the most suitable wireless technology for smart grid applications. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In order to improve the performance of communication systems, this paper proposes an optimal throughput and self-adaptability of ZigBee/IEEE802.15.4std for smart grid

A multi-mode real-time terrain parameter estimation method for wheeled motion control of mobile robots

Science.gov (United States)

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.

Monoamine Oxidase Inhibitory Constituents of Propolis: Kinetics and Mechanism of Inhibition of Recombinant Human MAO-A and MAO-B

Directory of Open Access Journals (Sweden)

Narayan D. Chaurasiya

2014-11-01

Full Text Available Propolis is the resinous material that bees gather from leaf buds, flowers and vegetables. Propolis extracts contain constituents with a broad spectra of pharmacological properties and are important ingredients of popular dietary supplements. Propolis extracts were evaluated in vitro for inhibition of recombinant human monoamine oxidase (MAO-A and MAO-B. The dichloromethane extract of propolis showed potent inhibition of human MAO-A and MAO-B. Further fractionation identified the most active fractions as rich in flavonoids. Galangin and apigenin were identified as the principal MAO-inhibitory constituents. Inhibition of MAO-A by galangin was about 36 times more selective than MAO-B, while apigenin selectivity for MAO-A vs. MAO-B was about 1.7 fold. Apigenin inhibited MAO-B significantly more potently than galangin. Galangin and apigenin were further evaluated for kinetic characteristics and the mechanism for the enzymes’ inhibition. Binding of galangin and apigenin with MAO-A and -B was not time-dependent and was reversible, as suggested by enzyme-inhibitor binding and dissociation-dialysis assay. The inhibition kinetics studies suggested that galangin and apigenin inhibited MAO-A and -B by a competitive mechanism. Presence of prominent MAO inhibitory constituents in propolis products suggests their potential for eliciting pharmacological effects that might be useful in depression or other neurological disorders. The results may also have important implications in drug-dietary supplement interactions.

Real-Time Motion Planning and Safe Navigation in Dynamic Multi-Robot Environments

National Research Council Canada - National Science Library

Bruce, James R

2006-01-01

.... While motion planning has been used for high level robot navigation, or limited to semi-static or single-robot domains, it has often been dismissed for the real-time low-level control of agents due...

Atomic Stretch: Optimally bounded real-time stretching and beyond

DEFF Research Database (Denmark)

Jensen, Rasmus Ramsbøl; Nielsen, Jannik Boll

2016-01-01

Atomic Stretch is a plugin for your preferred Adobe video editing tool, allowing real-time smooth and optimally bounded retarget-ting from and to any aspect ratio. The plugin allows preserving of high interest pixels through a protected region, attention redirection through color-modification, co......Atomic Stretch is a plugin for your preferred Adobe video editing tool, allowing real-time smooth and optimally bounded retarget-ting from and to any aspect ratio. The plugin allows preserving of high interest pixels through a protected region, attention redirection through color...

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.

A parallelizable real-time motion tracking algorithm with applications to ultrasonic strain imaging

International Nuclear Information System (INIS)

Jiang, J; Hall, T J

2007-01-01

Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows (registered) system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s -1 ) that exceed our previous methods

Graphics processing unit accelerated intensity-based optical coherence tomography angiography using differential frames with real-time motion correction.

Science.gov (United States)

Watanabe, Yuuki; Takahashi, Yuhei; Numazawa, Hiroshi

2014-02-01

We demonstrate intensity-based optical coherence tomography (OCT) angiography using the squared difference of two sequential frames with bulk-tissue-motion (BTM) correction. This motion correction was performed by minimization of the sum of the pixel values using axial- and lateral-pixel-shifted structural OCT images. We extract the BTM-corrected image from a total of 25 calculated OCT angiographic images. Image processing was accelerated by a graphics processing unit (GPU) with many stream processors to optimize the parallel processing procedure. The GPU processing rate was faster than that of a line scan camera (46.9 kHz). Our OCT system provides the means of displaying structural OCT images and BTM-corrected OCT angiographic images in real time.

Real-time process optimization based on grey-box neural models

Directory of Open Access Journals (Sweden)

F. A. Cubillos

2007-09-01

Full Text Available This paper investigates the feasibility of using grey-box neural models (GNM in Real Time Optimization (RTO. These models are based on a suitable combination of fundamental conservation laws and neural networks, being used in at least two different ways: to complement available phenomenological knowledge with empirical information, or to reduce dimensionality of complex rigorous physical models. We have observed that the benefits of using these simple adaptable models are counteracted by some difficulties associated with the solution of the optimization problem. Nonlinear Programming (NLP algorithms failed in finding the global optimum due to the fact that neural networks can introduce multimodal objective functions. One alternative considered to solve this problem was the use of some kind of evolutionary algorithms, like Genetic Algorithms (GA. Although these algorithms produced better results in terms of finding the appropriate region, they took long periods of time to reach the global optimum. It was found that a combination of genetic and nonlinear programming algorithms can be use to fast obtain the optimum solution. The proposed approach was applied to the Williams-Otto reactor, considering three different GNM models of increasing complexity. Results demonstrated that the use of GNM models and mixed GA/NLP optimization algorithms is a promissory approach for solving dynamic RTO problems.

SU-F-J-133: Adaptive Radiation Therapy with a Four-Dimensional Dose Calculation Algorithm That Optimizes Dose Distribution Considering Breathing Motion

Energy Technology Data Exchange (ETDEWEB)

Ali, I; Algan, O; Ahmad, S [University of Oklahoma Health Sciences, Oklahoma City, OK (United States); Alsbou, N [University of Central Oklahoma, Edmond, OK (United States)

2016-06-15

Purpose: To model patient motion and produce four-dimensional (4D) optimized dose distributions that consider motion-artifacts in the dose calculation during the treatment planning process. Methods: An algorithm for dose calculation is developed where patient motion is considered in dose calculation at the stage of the treatment planning. First, optimal dose distributions are calculated for the stationary target volume where the dose distributions are optimized considering intensity-modulated radiation therapy (IMRT). Second, a convolution-kernel is produced from the best-fitting curve which matches the motion trajectory of the patient. Third, the motion kernel is deconvolved with the initial dose distribution optimized for the stationary target to produce a dose distribution that is optimized in four-dimensions. This algorithm is tested with measured doses using a mobile phantom that moves with controlled motion patterns. Results: A motion-optimized dose distribution is obtained from the initial dose distribution of the stationary target by deconvolution with the motion-kernel of the mobile target. This motion-optimized dose distribution is equivalent to that optimized for the stationary target using IMRT. The motion-optimized and measured dose distributions are tested with the gamma index with a passing rate of >95% considering 3% dose-difference and 3mm distance-to-agreement. If the dose delivery per beam takes place over several respiratory cycles, then the spread-out of the dose distributions is only dependent on the motion amplitude and not affected by motion frequency and phase. This algorithm is limited to motion amplitudes that are smaller than the length of the target along the direction of motion. Conclusion: An algorithm is developed to optimize dose in 4D. Besides IMRT that provides optimal dose coverage for a stationary target, it extends dose optimization to 4D considering target motion. This algorithm provides alternative to motion management

Real-time physics-based 3D biped character animation using an inverted pendulum model.

Science.gov (United States)

Tsai, Yao-Yang; Lin, Wen-Chieh; Cheng, Kuangyou B; Lee, Jehee; Lee, Tong-Yee

2010-01-01

We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.

Real-Time 3D Motion capture by monocular vision and virtual rendering

OpenAIRE

Gomez Jauregui , David Antonio; Horain , Patrick

2012-01-01

International audience; Avatars in networked 3D virtual environments allow users to interact over the Internet and to get some feeling of virtual telepresence. However, avatar control may be tedious. Motion capture systems based on 3D sensors have recently reached the consumer market, but webcams and camera-phones are more widespread and cheaper. The proposed demonstration aims at animating a user's avatar from real time 3D motion capture by monoscopic computer vision, thus allowing virtual t...

Time Optimized Algorithm for Web Document Presentation Adaptation

DEFF Research Database (Denmark)

Pan, Rong; Dolog, Peter

2010-01-01

Currently information on the web is accessed through different devices. Each device has its own properties such as resolution, size, and capabilities to display information in different format and so on. This calls for adaptation of information presentation for such platforms. This paper proposes...... content-optimized and time-optimized algorithms for information presentation adaptation for different devices based on its hierarchical model. The model is formalized in order to experiment with different algorithms.......Currently information on the web is accessed through different devices. Each device has its own properties such as resolution, size, and capabilities to display information in different format and so on. This calls for adaptation of information presentation for such platforms. This paper proposes...

Robust adaptive extended Kalman filtering for real time MR-thermometry guided HIFU interventions.

Science.gov (United States)

Roujol, Sébastien; de Senneville, Baudouin Denis; Hey, Silke; Moonen, Chrit; Ries, Mario

2012-03-01

Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.

Development and operation of a real-time simulation at the NASA Ames Vertical Motion Simulator

Science.gov (United States)

Sweeney, Christopher; Sheppard, Shirin; Chetelat, Monique

1993-01-01

The Vertical Motion Simulator (VMS) facility at the NASA Ames Research Center combines the largest vertical motion capability in the world with a flexible real-time operating system allowing research to be conducted quickly and effectively. Due to the diverse nature of the aircraft simulated and the large number of simulations conducted annually, the challenge for the simulation engineer is to develop an accurate real-time simulation in a timely, efficient manner. The SimLab facility and the software tools necessary for an operating simulation will be discussed. Subsequent sections will describe the development process through operation of the simulation; this includes acceptance of the model, validation, integration and production phases.

AdaM: Adapting Multi-User Interfaces for Collaborative Environments in Real-Time

DEFF Research Database (Denmark)

Park, Seonwook; Gebhardt, Christoph; Rädle, Roman

2018-01-01

and rule-based solutions are tedious to create and do not scale to larger problems nor do they adapt to dynamic changes, such as users leaving or joining an activity. In this paper, we cast the problem of UI distribution as an assignment problem and propose to solve it using combinatorial optimization. We...... present a mixed integer programming formulation which allows real-time applications in dynamically changing collaborative settings. It optimizes the allocation of UI elements based on device capabilities, user roles, preferences, and access rights. We present a proof-of-concept designer-in-the-loop tool......Developing cross-device multi-user interfaces (UIs) is a challenging problem. There are numerous ways in which content and interactivity can be distributed. However, good solutions must consider multiple users, their roles, their preferences and access rights, as well as device capabilities. Manual...

Measuring Sea-Ice Motion in the Arctic with Real Time Photogrammetry

Science.gov (United States)

Brozena, J. M.; Hagen, R. A.; Peters, M. F.; Liang, R.; Ball, D.

2014-12-01

The U.S. Naval Research Laboratory, in coordination with other groups, has been collecting sea-ice data in the Arctic off the north coast of Alaska with an airborne system employing a radar altimeter, LiDAR and a photogrammetric camera in an effort to obtain wide swaths of measurements coincident with Cryosat-2 footprints. Because the satellite tracks traverse areas of moving pack ice, precise real-time estimates of the ice motion are needed to fly a survey grid that will yield complete data coverage. This requirement led us to develop a method to find the ice motion from the aircraft during the survey. With the advent of real-time orthographic photogrammetric systems, we developed a system that measures the sea ice motion in-flight, and also permits post-process modeling of sea ice velocities to correct the positioning of radar and LiDAR data. For the 2013 and 2014 field seasons, we used this Real Time Ice Motion Estimation (RTIME) system to determine ice motion using Applanix's Inflight Ortho software with an Applanix DSS439 system. Operationally, a series of photos were taken in the survey area. The aircraft then turned around and took more photos along the same line several minutes later. Orthophotos were generated within minutes of collection and evaluated by custom software to find photo footprints and potential overlap. Overlapping photos were passed to the correlation software, which selects a series of "chips" in the first photo and looks for the best matches in the second photo. The correlation results are then passed to a density-based clustering algorithm to determine the offset of the photo pair. To investigate any systematic errors in the photogrammetry, we flew several flight lines over a fixed point on various headings, over an area of non-moving ice in 2013. The orthophotos were run through the correlation software to find any residual offsets, and run through additional software to measure chip positions and offsets relative to the aircraft

Towards frameless maskless SRS through real-time 6DoF robotic motion compensation

Science.gov (United States)

Belcher, Andrew H.; Liu, Xinmin; Chmura, Steven; Yenice, Kamil; Wiersma, Rodney D.

2017-12-01

Stereotactic radiosurgery (SRS) uses precise dose placement to treat conditions of the CNS. Frame-based SRS uses a metal head ring fixed to the patient’s skull to provide high treatment accuracy, but patient comfort and clinical workflow may suffer. Frameless SRS, while potentially more convenient, may increase uncertainty of treatment accuracy and be physiologically confining to some patients. By incorporating highly precise robotics and advanced software algorithms into frameless treatments, we present a novel frameless and maskless SRS system where a robot provides real-time 6DoF head motion stabilization allowing positional accuracies to match or exceed those of traditional frame-based SRS. A 6DoF parallel kinematics robot was developed and integrated with a real-time infrared camera in a closed loop configuration. A novel compensation algorithm was developed based on an iterative closest-path correction approach. The robotic SRS system was tested on six volunteers, whose motion was monitored and compensated for in real-time over 15 min simulated treatments. The system’s effectiveness in maintaining the target’s 6DoF position within preset thresholds was determined by comparing volunteer head motion with and without compensation. Comparing corrected and uncorrected motion, the 6DoF robotic system showed an overall improvement factor of 21 in terms of maintaining target position within 0.5 mm and 0.5 degree thresholds. Although the system’s effectiveness varied among the volunteers examined, for all volunteers tested the target position remained within the preset tolerances 99.0% of the time when robotic stabilization was used, compared to 4.7% without robotic stabilization. The pre-clinical robotic SRS compensation system was found to be effective at responding to sub-millimeter and sub-degree cranial motions for all volunteers examined. The system’s success with volunteers has demonstrated its capability for implementation with frameless and

Towards frameless maskless SRS through real-time 6DoF robotic motion compensation.

Science.gov (United States)

Belcher, Andrew H; Liu, Xinmin; Chmura, Steven; Yenice, Kamil; Wiersma, Rodney D

2017-11-13

Stereotactic radiosurgery (SRS) uses precise dose placement to treat conditions of the CNS. Frame-based SRS uses a metal head ring fixed to the patient's skull to provide high treatment accuracy, but patient comfort and clinical workflow may suffer. Frameless SRS, while potentially more convenient, may increase uncertainty of treatment accuracy and be physiologically confining to some patients. By incorporating highly precise robotics and advanced software algorithms into frameless treatments, we present a novel frameless and maskless SRS system where a robot provides real-time 6DoF head motion stabilization allowing positional accuracies to match or exceed those of traditional frame-based SRS. A 6DoF parallel kinematics robot was developed and integrated with a real-time infrared camera in a closed loop configuration. A novel compensation algorithm was developed based on an iterative closest-path correction approach. The robotic SRS system was tested on six volunteers, whose motion was monitored and compensated for in real-time over 15 min simulated treatments. The system's effectiveness in maintaining the target's 6DoF position within preset thresholds was determined by comparing volunteer head motion with and without compensation. Comparing corrected and uncorrected motion, the 6DoF robotic system showed an overall improvement factor of 21 in terms of maintaining target position within 0.5 mm and 0.5 degree thresholds. Although the system's effectiveness varied among the volunteers examined, for all volunteers tested the target position remained within the preset tolerances 99.0% of the time when robotic stabilization was used, compared to 4.7% without robotic stabilization. The pre-clinical robotic SRS compensation system was found to be effective at responding to sub-millimeter and sub-degree cranial motions for all volunteers examined. The system's success with volunteers has demonstrated its capability for implementation with frameless and maskless SRS

Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model

Directory of Open Access Journals (Sweden)

Xin Wang

2012-01-01

Full Text Available This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.

Evolution of motion uncertainty in rectal cancer: implications for adaptive radiotherapy

Science.gov (United States)

Kleijnen, Jean-Paul J. E.; van Asselen, Bram; Burbach, Johannes P. M.; Intven, Martijn; Philippens, Marielle E. P.; Reerink, Onne; Lagendijk, Jan J. W.; Raaymakers, Bas W.

2016-01-01

Reduction of motion uncertainty by applying adaptive radiotherapy strategies depends largely on the temporal behavior of this motion. To fully optimize adaptive strategies, insight into target motion is needed. The purpose of this study was to analyze stability and evolution in time of motion uncertainty of both the gross tumor volume (GTV) and clinical target volume (CTV) for patients with rectal cancer. We scanned 16 patients daily during one week, on a 1.5 T MRI scanner in treatment position, prior to each radiotherapy fraction. Single slice sagittal cine MRIs were made at the beginning, middle, and end of each scan session, for one minute at 2 Hz temporal resolution. GTV and CTV motion were determined by registering a delineated reference frame to time-points later in time. The 95th percentile of observed motion (dist95%) was taken as a measure of motion. The stability of motion in time was evaluated within each cine-MRI separately. The evolution of motion was investigated between the reference frame and the cine-MRIs of a single scan session and between the reference frame and the cine-MRIs of several days later in the course of treatment. This observed motion was then converted into a PTV-margin estimate. Within a one minute cine-MRI scan, motion was found to be stable and small. Independent of the time-point within the scan session, the average dist95% remains below 3.6 mm and 2.3 mm for CTV and GTV, respectively 90% of the time. We found similar motion over time intervals from 18 min to 4 days. When reducing the time interval from 18 min to 1 min, a large reduction in motion uncertainty is observed. A reduction in motion uncertainty, and thus the PTV-margin estimate, of 71% and 75% for CTV and tumor was observed, respectively. Time intervals of 15 and 30 s yield no further reduction in motion uncertainty compared to a 1 min time interval.

MO-FG-BRD-00: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management

Energy Technology Data Exchange (ETDEWEB)

NONE

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-00: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management

International Nuclear Information System (INIS)

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions

Directory of Open Access Journals (Sweden)

Ahmed M. Ali

2018-02-01

Full Text Available In light of increasing alerts about limited energy sources and environment degradation, it has become essential to search for alternatives to thermal engine-based vehicles which are a major source of air pollution and fossil fuel depletion. Hybrid electric vehicles (HEVs, encompassing multiple energy sources, are a short-term solution that meets the performance requirements and contributes to fuel saving and emission reduction aims. Power management methods such as regulating efficient energy flow to the vehicle propulsion, are core technologies of HEVs. Intelligent power management methods, capable of acquiring optimal power handling, accommodating system inaccuracies, and suiting real-time applications can significantly improve the powertrain efficiency at different operating conditions. Rule-based methods are simply structured and easily implementable in real-time; however, a limited optimality in power handling decisions can be achieved. Optimization-based methods are more capable of achieving this optimality at the price of augmented computational load. In the last few years, these optimization-based methods have been under development to suit real-time application using more predictive, recognitive, and artificial intelligence tools. This paper presents a review-based discussion about these new trends in real-time optimal power management methods. More focus is given to the adaptation tools used to boost methods optimality in real-time. The contribution of this work can be identified in two points: First, to provide researchers and scholars with an overview of different power management methods. Second, to point out the state-of-the-art trends in real-time optimal methods and to highlight promising approaches for future development.

Online gaming for learning optimal team strategies in real time

Science.gov (United States)

Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

2010-04-01

This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

Real-time axial motion detection and correction for single photon emission computed tomography using a linear prediction filter

International Nuclear Information System (INIS)

Saba, V.; Setayeshi, S.; Ghannadi-Maragheh, M.

2011-01-01

We have developed an algorithm for real-time detection and complete correction of the patient motion effects during single photon emission computed tomography. The algorithm is based on a linear prediction filter (LPC). The new prediction of projection data algorithm (PPDA) detects most motions-such as those of the head, legs, and hands-using comparison of the predicted and measured frame data. When the data acquisition for a specific frame is completed, the accuracy of the acquired data is evaluated by the PPDA. If patient motion is detected, the scanning procedure is stopped. After the patient rests in his or her true position, data acquisition is repeated only for the corrupted frame and the scanning procedure is continued. Various experimental data were used to validate the motion detection algorithm; on the whole, the proposed method was tested with approximately 100 test cases. The PPDA shows promising results. Using the PPDA enables us to prevent the scanner from collecting disturbed data during the scan and replaces them with motion-free data by real-time rescanning for the corrupted frames. As a result, the effects of patient motion is corrected in real time. (author)

Real-time traffic signal optimization model based on average delay time per person

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2015-10-01

Full Text Available Real-time traffic signal control is very important for relieving urban traffic congestion. Many existing traffic control models were formulated using optimization approach, with the objective functions of minimizing vehicle delay time. To improve people’s trip efficiency, this article aims to minimize delay time per person. Based on the time-varying traffic flow data at intersections, the article first fits curves of accumulative arrival and departure vehicles, as well as the corresponding functions. Moreover, this article transfers vehicle delay time to personal delay time using average passenger load of cars and buses, employs such time as the objective function, and proposes a signal timing optimization model for intersections to achieve real-time signal parameters, including cycle length and green time. This research further implements a case study based on practical data collected at an intersection in Beijing, China. The average delay time per person and queue length are employed as evaluation indices to show the performances of the model. The results show that the proposed methodology is capable of improving traffic efficiency and is very effective for real-world applications.

Real Time Optimal Control of Supercapacitor Operation for Frequency Response

Energy Technology Data Exchange (ETDEWEB)

Luo, Yusheng; Panwar, Mayank; Mohanpurkar, Manish; Hovsapian, Rob

2016-07-01

Supercapacitors are gaining wider applications in power systems due to fast dynamic response. Utilizing supercapacitors by means of power electronics interfaces for power compensation is a proven effective technique. For applications such as requency restoration if the cost of supercapacitors maintenance as well as the energy loss on the power electronics interfaces are addressed. It is infeasible to use traditional optimization control methods to mitigate the impacts of frequent cycling. This paper proposes a Front End Controller (FEC) using Generalized Predictive Control featuring real time receding optimization. The optimization constraints are based on cost and thermal management to enhance to the utilization efficiency of supercapacitors. A rigorous mathematical derivation is conducted and test results acquired from Digital Real Time Simulator are provided to demonstrate effectiveness.

Immunity-based optimal estimation approach for a new real time group elevator dynamic control application for energy and time saving.

Science.gov (United States)

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.

Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

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.

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

Science.gov (United States)

Foo, Brian; van der Schaar, Mihaela

2010-11-01

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

Real-Time and Accurate Indoor Localization with Fusion Model of Wi-Fi Fingerprint and Motion Particle Filter

Directory of Open Access Journals (Sweden)

Xinlong Jiang

2015-01-01

Full Text Available As the development of Indoor Location Based Service (Indoor LBS, a timely localization and smooth tracking with high accuracy are desperately needed. Unfortunately, any single method cannot meet the requirement of both high accuracy and real-time ability at the same time. In this paper, we propose a fusion location framework with Particle Filter using Wi-Fi signals and motion sensors. In this framework, we use Extreme Learning Machine (ELM regression algorithm to predict position based on motion sensors and use Wi-Fi fingerprint location result to solve the error accumulation of motion sensors based location occasionally with Particle Filter. The experiments show that the trajectory is smoother as the real one than the traditional Wi-Fi fingerprint method.

WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection

Directory of Open Access Journals (Sweden)

Liangyi Gong

2015-12-01

Full Text Available With the rapid development of WLAN technology, wireless device-free passive human detection becomes a newly-developing technique and holds more potential to worldwide and ubiquitous smart applications. Recently, indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Previous wireless device-free passive human detection systems either rely on deploying specialized systems with dense transmitter-receiver links or elaborate off-line training process, which blocks rapid deployment and weakens system robustness. In the paper, we explore to research a novel fine-grained real-time calibration-free device-free passive human motion via physical layer information, which is independent of indoor scenarios and needs no prior-calibration and normal profile. We investigate sensitivities of amplitude and phase to human motion, and discover that phase feature is more sensitive to human motion, especially to slow human motion. Aiming at lightweight and robust device-free passive human motion detection, we develop two novel and practical schemes: short-term averaged variance ratio (SVR and long-term averaged variance ratio (LVR. We realize system design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve a high detection rate and low false positive rate.

WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection.

Science.gov (United States)

Gong, Liangyi; Yang, Wu; Man, Dapeng; Dong, Guozhong; Yu, Miao; Lv, Jiguang

2015-12-21

With the rapid development of WLAN technology, wireless device-free passive human detection becomes a newly-developing technique and holds more potential to worldwide and ubiquitous smart applications. Recently, indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Previous wireless device-free passive human detection systems either rely on deploying specialized systems with dense transmitter-receiver links or elaborate off-line training process, which blocks rapid deployment and weakens system robustness. In the paper, we explore to research a novel fine-grained real-time calibration-free device-free passive human motion via physical layer information, which is independent of indoor scenarios and needs no prior-calibration and normal profile. We investigate sensitivities of amplitude and phase to human motion, and discover that phase feature is more sensitive to human motion, especially to slow human motion. Aiming at lightweight and robust device-free passive human motion detection, we develop two novel and practical schemes: short-term averaged variance ratio (SVR) and long-term averaged variance ratio (LVR). We realize system design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve a high detection rate and low false positive rate.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

Science.gov (United States)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

A two-domain real-time algorithm for optimal data reduction: A case study on accelerator magnet measurements

CERN Document Server

Arpaia, P; Inglese, V

2010-01-01

A real-time algorithm of data reduction, based on the combination a two lossy techniques specifically optimized for high-rate magnetic measurements in two domains (e.g. time and space), is proposed. The first technique exploits an adaptive sampling rule based on the power estimation of the flux increments in order to optimize the information to be gathered for magnetic field analysis in real time. The tracking condition is defined by the target noise level in the Nyquist band required by post-processing procedure of magnetic analysis. The second technique uses a data reduction algorithm in order to improve the compression ratio while preserving the consistency of the measured signal. The allowed loss is set equal to the random noise level in the signal in order to force the loss and the noise to cancel rather than to add, by improving the signal-to-noise ratio. Numerical analysis and experimental results of on-field performance characterization and validation for two case studies of magnetic measurement syste...

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

DEFF Research Database (Denmark)

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

2012-01-01

In this paper, an investigation of the adaptability of available transient stability assessment methods to real-time operation and their real-time performance is carried out. Two approaches based on Lyapunov’s method and the equal area criterion are analyzed. The results allow to determine...

Inhibitors of MAO-A and MAO-B in Psychiatry and Neurology

Directory of Open Access Journals (Sweden)

John Paul Maurice Finberg

2016-10-01

Full Text Available Inhibitors of MAO-A and MAO-B are in clinical use for the treatment of psychiatric and neurological disorders respectively. Elucidation of the molecular structure of the active sites of the enzymes has enabled a precise determination of the way in which substrates and inhibitor molecules are metabolized, or inhibit metabolism of substrates, respectively. Despite the knowledge of the strong antidepressant efficacy of irreversible MAO inhibitors, their clinical use has been limited by their side effect of potentiation of the cardiovascular effects of dietary amines (cheese effect. A number of reversible MAO-A inhibitors which are devoid of cheese effect have been described in the literature, but only one, moclobemide, is currently in clinical use. The irreversible inhibitors of MAO-B, selegiline and rasagiline, are used clinically in treatment of Parkinson’s disease, and a recently introduced reversible MAO-B inhibitor, safinamide, has also been found efficacious. Modification of the pharmacokinetic characteristics of selegiline by transdermal administration has led to the development of a new drug form for treatment of depression. The clinical potential of MAO inhibitors together with detailed knowledge of the enzyme’s binding site structure should lead to future developments with these drugs.

Inhibitors of MAO-A and MAO-B in Psychiatry and Neurology.

Science.gov (United States)

Finberg, John P M; Rabey, Jose M

2016-01-01

Inhibitors of MAO-A and MAO-B are in clinical use for the treatment of psychiatric and neurological disorders respectively. Elucidation of the molecular structure of the active sites of the enzymes has enabled a precise determination of the way in which substrates and inhibitor molecules are metabolized, or inhibit metabolism of substrates, respectively. Despite the knowledge of the strong antidepressant efficacy of irreversible MAO inhibitors, their clinical use has been limited by their side effect of potentiation of the cardiovascular effects of dietary amines ("cheese effect"). A number of reversible MAO-A inhibitors which are devoid of cheese effect have been described in the literature, but only one, moclobemide, is currently in clinical use. The irreversible inhibitors of MAO-B, selegiline and rasagiline, are used clinically in treatment of Parkinson's disease, and a recently introduced reversible MAO-B inhibitor, safinamide, has also been found efficacious. Modification of the pharmacokinetic characteristics of selegiline by transdermal administration has led to the development of a new drug form for treatment of depression. The clinical potential of MAO inhibitors together with detailed knowledge of the enzyme's binding site structure should lead to future developments with these drugs.

Intelligent data management for real-time spacecraft monitoring

Science.gov (United States)

Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

1992-01-01

Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

Wavelet transform and real-time learning method for myoelectric signal in motion discrimination

International Nuclear Information System (INIS)

Liu Haihua; Chen Xinhao; Chen Yaguang

2005-01-01

This paper discusses the applicability of the Wavelet transform for analyzing an EMG signal and discriminating motion classes. In many previous works, researchers have dealt with steady EMG and have proposed suitable analyzing methods for the EMG, for example FFT and STFT. Therefore, it is difficult for the previous approaches to discriminate motions from the EMG in the different phases of muscle activity, i.e., pre-activity, in activity, postactivity phases, as well as the period of motion transition from one to another. In this paper, we introduce the Wavelet transform using the Coiflet mother wavelet into our real-time EMG prosthetic hand controller for discriminating motions from steady and unsteady EMG. A preliminary experiment to discriminate three hand motions from four channel EMG in the initial pre-activity and in activity phase is carried out to show the effectiveness of the approach. However, future research efforts are necessary to discriminate more motions much precisely

Real-time trajectory optimization on parallel processors

Science.gov (United States)

Psiaki, Mark L.

1993-01-01

A parallel algorithm has been developed for rapidly solving trajectory optimization problems. The goal of the work has been to develop an algorithm that is suitable to do real-time, on-line optimal guidance through repeated solution of a trajectory optimization problem. The algorithm has been developed on an INTEL iPSC/860 message passing parallel processor. It uses a zero-order-hold discretization of a continuous-time problem and solves the resulting nonlinear programming problem using a custom-designed augmented Lagrangian nonlinear programming algorithm. The algorithm achieves parallelism of function, derivative, and search direction calculations through the principle of domain decomposition applied along the time axis. It has been encoded and tested on 3 example problems, the Goddard problem, the acceleration-limited, planar minimum-time to the origin problem, and a National Aerospace Plane minimum-fuel ascent guidance problem. Execution times as fast as 118 sec of wall clock time have been achieved for a 128-stage Goddard problem solved on 32 processors. A 32-stage minimum-time problem has been solved in 151 sec on 32 processors. A 32-stage National Aerospace Plane problem required 2 hours when solved on 32 processors. A speed-up factor of 7.2 has been achieved by using 32-nodes instead of 1-node to solve a 64-stage Goddard problem.

The study of key issues about integration of GNSS and strong-motion records for real-time earthquake monitoring

Science.gov (United States)

Tu, Rui; Zhang, Pengfei; Zhang, Rui; Liu, Jinhai

2016-08-01

This paper has studied the key issues about integration of GNSS and strong-motion records for real-time earthquake monitoring. The validations show that the consistence of the coordinate system must be considered firstly to exclude the system bias between GNSS and strong-motion. The GNSS sampling rate is suggested about 1-5 Hz, and we should give the strong-motion's baseline shift with a larger dynamic noise as its variation is very swift. The initialization time of solving the baseline shift is less than one minute, and ambiguity resolution strategy is not greatly improved the solution. The data quality is very important for the solution, we advised to use multi-frequency and multi-system observations. These ideas give an important guide for real-time earthquake monitoring and early warning by the tight integration of GNSS and strong-motion records.

Real-Time Observation of Internal Motion within Ultrafast Dissipative Optical Soliton Molecules

Science.gov (United States)

Krupa, Katarzyna; Nithyanandan, K.; Andral, Ugo; Tchofo-Dinda, Patrice; Grelu, Philippe

2017-06-01

Real-time access to the internal ultrafast dynamics of complex dissipative optical systems opens new explorations of pulse-pulse interactions and dynamic patterns. We present the first direct experimental evidence of the internal motion of a dissipative optical soliton molecule generated in a passively mode-locked erbium-doped fiber laser. We map the internal motion of a soliton pair molecule by using a dispersive Fourier-transform imaging technique, revealing different categories of internal pulsations, including vibrationlike and phase drifting dynamics. Our experiments agree well with numerical predictions and bring insights to the analogy between self-organized states of lights and states of the matter.

Optimal time interval for induction of immunologic adaptive response

International Nuclear Information System (INIS)

Ju Guizhi; Song Chunhua; Liu Shuzheng

1994-01-01

The optimal time interval between prior dose (D1) and challenge dose (D2) for the induction of immunologic adaptive response was investigated. Kunming mice were exposed to 75 mGy X-rays at a dose rate of 12.5 mGy/min. 3, 6, 12, 24 or 60 h after the prior irradiation the mice were challenged with a dose of 1.5 Gy at a dose rate of 0.33 Gy/min. 18h after D2, the mice were sacrificed for examination of immunological parameters. The results showed that with an interval of 6 h between D1 and D2, the adaptive response of the reaction of splenocytes to LPS was induced, and with an interval of 12 h the adaptive responses of spontaneous incorporation of 3 H-TdR into thymocytes and the reaction of splenocytes to Con A and LPS were induced with 75 mGy prior irradiation. The data suggested that the optimal time intervals between D1 and D2 for the induction of immunologic adaptive response were 6 h and 12 h with a D1 of 75 mGy and a D2 of 1.5 Gy. The mechanism of immunologic adaptation following low dose radiation is discussed

Using Opaque Image Blur for Real-Time Depth-of-Field Rendering and Image-Based Motion Blur

DEFF Research Database (Denmark)

Kraus, Martin

2013-01-01

While depth of field is an important cinematographic means, its use in real-time computer graphics is still limited by the computational costs that are necessary to achieve a sufficient image quality. Specifically, color bleeding artifacts between objects at different depths are most effectively...... that the opaque image blur can also be used to add motion blur effects to images in real time....

Using real time traveler demand data to optimize commuter rail feeder systems.

Science.gov (United States)

2012-08-01

"This report focuses on real time optimization of the Commuter Rail Circulator Route Network Design Problem (CRCNDP). The route configuration of the circulator system where to stop and the route among the stops is determined on a real-time ba...

Adapting Parameterized Motions using Iterative Learning and Online Collision Detection

DEFF Research Database (Denmark)

Laursen, Johan Sund; Sørensen, Lars Carøe; Schultz, Ulrik Pagh

2018-01-01

utilizing Gaussian Process learning. This allows for motion parameters to be optimized using real world trials which incorporate all uncertainties inherent in the assembly process without requiring advanced robot and sensor setups. The result is a simple and straightforward system which helps the user...... automatically find robust and uncertainty-tolerant motions. We present experiments for an assembly case showing both detection and learning in the real world and how these combine to a robust robot system....

The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery

DEFF Research Database (Denmark)

Falk, Marianne; Larsson, Tobias; Keall, P.

2012-01-01

Purpose: Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced......-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system. The dosimetric results were evaluated using gamma index evaluation with static target measurements as reference. Results: The plan quality...

Robotic real-time translational and rotational head motion correction during frameless stereotactic radiosurgery

Energy Technology Data Exchange (ETDEWEB)

Liu, Xinmin; Belcher, Andrew H.; Grelewicz, Zachary; Wiersma, Rodney D., E-mail: rwiersma@uchicago.edu [Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, Illinois 60637 (United States)

2015-06-15

Purpose: To develop a control system to correct both translational and rotational head motion deviations in real-time during frameless stereotactic radiosurgery (SRS). Methods: A novel feedback control with a feed-forward algorithm was utilized to correct for the coupling of translation and rotation present in serial kinematic robotic systems. Input parameters for the algorithm include the real-time 6DOF target position, the frame pitch pivot point to target distance constant, and the translational and angular Linac beam off (gating) tolerance constants for patient safety. Testing of the algorithm was done using a 4D (XY Z + pitch) robotic stage, an infrared head position sensing unit and a control computer. The measured head position signal was processed and a resulting command was sent to the interface of a four-axis motor controller, through which four stepper motors were driven to perform motion compensation. Results: The control of the translation of a brain target was decoupled with the control of the rotation. For a phantom study, the corrected position was within a translational displacement of 0.35 mm and a pitch displacement of 0.15° 100% of the time. For a volunteer study, the corrected position was within displacements of 0.4 mm and 0.2° over 98.5% of the time, while it was 10.7% without correction. Conclusions: The authors report a control design approach for both translational and rotational head motion correction. The experiments demonstrated that control performance of the 4D robotic stage meets the submillimeter and subdegree accuracy required by SRS.

Robotic real-time translational and rotational head motion correction during frameless stereotactic radiosurgery

International Nuclear Information System (INIS)

Liu, Xinmin; Belcher, Andrew H.; Grelewicz, Zachary; Wiersma, Rodney D.

2015-01-01

Purpose: To develop a control system to correct both translational and rotational head motion deviations in real-time during frameless stereotactic radiosurgery (SRS). Methods: A novel feedback control with a feed-forward algorithm was utilized to correct for the coupling of translation and rotation present in serial kinematic robotic systems. Input parameters for the algorithm include the real-time 6DOF target position, the frame pitch pivot point to target distance constant, and the translational and angular Linac beam off (gating) tolerance constants for patient safety. Testing of the algorithm was done using a 4D (XY Z + pitch) robotic stage, an infrared head position sensing unit and a control computer. The measured head position signal was processed and a resulting command was sent to the interface of a four-axis motor controller, through which four stepper motors were driven to perform motion compensation. Results: The control of the translation of a brain target was decoupled with the control of the rotation. For a phantom study, the corrected position was within a translational displacement of 0.35 mm and a pitch displacement of 0.15° 100% of the time. For a volunteer study, the corrected position was within displacements of 0.4 mm and 0.2° over 98.5% of the time, while it was 10.7% without correction. Conclusions: The authors report a control design approach for both translational and rotational head motion correction. The experiments demonstrated that control performance of the 4D robotic stage meets the submillimeter and subdegree accuracy required by SRS

ADEX optimized adaptive controllers and systems from research to industrial practice

CERN Document Server

Martín-Sánchez, Juan M

2015-01-01

This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...

Real-Time Motion Capture Toolbox (RTMocap): an open-source code for recording 3-D motion kinematics to study action-effect anticipations during motor and social interactions.

Science.gov (United States)

Lewkowicz, Daniel; Delevoye-Turrell, Yvonne

2016-03-01

We present here a toolbox for the real-time motion capture of biological movements that runs in the cross-platform MATLAB environment (The MathWorks, Inc., Natick, MA). It provides instantaneous processing of the 3-D movement coordinates of up to 20 markers at a single instant. Available functions include (1) the setting of reference positions, areas, and trajectories of interest; (2) recording of the 3-D coordinates for each marker over the trial duration; and (3) the detection of events to use as triggers for external reinforcers (e.g., lights, sounds, or odors). Through fast online communication between the hardware controller and RTMocap, automatic trial selection is possible by means of either a preset or an adaptive criterion. Rapid preprocessing of signals is also provided, which includes artifact rejection, filtering, spline interpolation, and averaging. A key example is detailed, and three typical variations are developed (1) to provide a clear understanding of the importance of real-time control for 3-D motion in cognitive sciences and (2) to present users with simple lines of code that can be used as starting points for customizing experiments using the simple MATLAB syntax. RTMocap is freely available (http://sites.google.com/site/RTMocap/) under the GNU public license for noncommercial use and open-source development, together with sample data and extensive documentation.

An Optimization Framework for Dynamic, Distributed Real-Time Systems

Science.gov (United States)

Eckert, Klaus; Juedes, David; Welch, Lonnie; Chelberg, David; Bruggerman, Carl; Drews, Frank; Fleeman, David; Parrott, David; Pfarr, Barbara

2003-01-01

Abstract. This paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems .that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.

Real-time construction and visualisation of drift-free video mosaics from unconstrained camera motion

Directory of Open Access Journals (Sweden)

Mateusz Brzeszcz

2015-08-01

Full Text Available This work proposes a novel approach for real-time video mosaicking facilitating drift-free mosaic construction and visualisation, with integrated frame blending and redundancy management, that is shown to be flexible to a range of varying mosaic scenarios. The approach supports unconstrained camera motion with in-sequence loop closing, variation in camera focal distance (zoom and recovery from video sequence breaks. Real-time performance, over extended duration sequences, is realised via novel aspects of frame management within the mosaic representation and thus avoiding the high data redundancy associated with temporally dense, spatially overlapping video frame inputs. This managed set of image frames is visualised in real time using a dynamic mosaic representation of overlapping textured graphics primitives in place of the traditional globally constructed, and hence frequently reconstructed, mosaic image. Within this formulation, subsequent optimisation occurring during online construction can thus efficiency adjust relative frame positions via simple primitive position transforms. Effective visualisation is similarly facilitated by online inter-frame blending to overcome the illumination and colour variance associated with modern camera hardware. The evaluation illustrates overall robustness in video mosaic construction under a diverse range of conditions including indoor and outdoor environments, varying illumination and presence of in-scene motion on varying computational platforms.

MO-FG-BRD-02: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MV Tracking

Energy Technology Data Exchange (ETDEWEB)

Berbeco, R. [Brigham and Women’s Hospital and Dana-Farber Cancer Institute (United States)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-04: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking

Energy Technology Data Exchange (ETDEWEB)

Low, D. [University of California Los Angeles: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking (United States)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-03: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: EM Tracking

Energy Technology Data Exchange (ETDEWEB)

Keall, P. [University of Sydney (Australia)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

MO-FG-BRD-04: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MR Tracking

International Nuclear Information System (INIS)

Low, D.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

MO-FG-BRD-03: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: EM Tracking

International Nuclear Information System (INIS)

Keall, P.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

MO-FG-BRD-02: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: MV Tracking

International Nuclear Information System (INIS)

Berbeco, R.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

Three Experiments Examining the Use of Electroencephalogram,Event-Related Potentials, and Heart-Rate Variability for Real-Time Human-Centered Adaptive Automation Design

Science.gov (United States)

Prinzel, Lawrence J., III; Parasuraman, Raja; Freeman, Frederick G.; Scerbo, Mark W.; Mikulka, Peter J.; Pope, Alan T.

2003-01-01

Adaptive automation represents an advanced form of human-centered automation design. The approach to automation provides for real-time and model-based assessments of human-automation interaction, determines whether the human has entered into a hazardous state of awareness and then modulates the task environment to keep the operator in-the-loop , while maintaining an optimal state of task engagement and mental alertness. Because adaptive automation has not matured, numerous challenges remain, including what the criteria are, for determining when adaptive aiding and adaptive function allocation should take place. Human factors experts in the area have suggested a number of measures including the use of psychophysiology. This NASA Technical Paper reports on three experiments that examined the psychophysiological measures of event-related potentials, electroencephalogram, and heart-rate variability for real-time adaptive automation. The results of the experiments confirm the efficacy of these measures for use in both a developmental and operational role for adaptive automation design. The implications of these results and future directions for psychophysiology and human-centered automation design are discussed.

Heart Motion Prediction in Robotic-Assisted Beating Heart Surgery: A Nonlinear Fast Adaptive Approach

Directory of Open Access Journals (Sweden)

Fan Liang

2013-01-01

Full Text Available Off-pump Coronary Artery Bypass Graft (CABG surgery outperforms traditional on-pump surgery because the assisted robotic tools can alleviate the relative motion between the beating heart and robotic tools. Therefore, it is possible for the surgeon to operate on the beating heart and thus lessens post surgery complications for the patients. Due to the highly irregular and non-stationary nature of heart motion, it is critical that the beating heart motion is predicted in the model-based track control procedures. It is technically preferable to model heart motion in a nonlinear way because the characteristic analysis of 3D heart motion data through Bi-spectral analysis and Fourier methods demonstrates the involved nonlinearity of heart motion. We propose an adaptive nonlinear heart motion model based on the Volterra Series in this paper. We also design a fast lattice structure to achieve computational-efficiency for real-time online predictions. We argue that the quadratic term of the Volterra Series can improve the prediction accuracy by covering sharp change points and including the motion with sufficient detail. The experiment results indicate that the adaptive nonlinear heart motion prediction algorithm outperforms the autoregressive (AR and the time-varying Fourier-series models in terms of the root mean square of the prediction error and the prediction error in extreme cases.

SU-E-J-57: First Development of Adapting to Intrafraction Relative Motion Between Prostate and Pelvic Lymph Nodes Targets

Energy Technology Data Exchange (ETDEWEB)

Ge, Y; Colvill, E; O’Brien, R; Keall, P [Radiation Physics Laboratory, University of Sydney, NSW (Australia); Booth, J [Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW (Australia)

2015-06-15

Purpose Large intrafraction relative motion of multiple targets is common in advanced head and neck, lung, abdominal, gynaecological and urological cancer, jeopardizing the treatment outcomes. The objective of this study is to develop a real-time adaptation strategy, for the first time, to accurately correct for the relative motion of multiple targets by reshaping the treatment field using the multi-leaf collimator (MLC). Methods The principle of tracking the simultaneously treated but differentially moving tumor targets is to determine the new aperture shape that conforms to the shifted targets. Three dimensional volumes representing the individual targets are projected to the beam’s eye view. The leaf openings falling inside each 2D projection will be shifted according to the measured motion of each target to form the new aperture shape. Based on the updated beam shape, new leaf positions will be determined with optimized trade-off between the target underdose and healthy tissue overdose, and considerations of the physical constraints of the MLC. Taking a prostate cancer patient with pelvic lymph node involvement as an example, a preliminary dosimetric study was conducted to demonstrate the potential treatment improvement compared to the state-of- art adaptation technique which shifts the whole beam to track only one target. Results The world-first intrafraction adaptation system capable of reshaping the beam to correct for the relative motion of multiple targets has been developed. The dose in the static nodes and small bowel are closer to the planned distribution and the V45 of small bowel is decreased from 110cc to 75cc, corresponding to a 30% reduction by this technique compared to the state-of-art adaptation technique. Conclusion The developed adaptation system to correct for intrafraction relative motion of multiple targets will guarantee the tumour coverage and thus enable PTV margin reduction to minimize the high target dose to the adjacent organs

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

Science.gov (United States)

Zheng, Qiangang; Zhang, Haibo; Miao, Lizhen; Sun, Fengyong

2017-11-01

A real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection †

Science.gov (United States)

Gong, Liangyi; Yang, Wu; Man, Dapeng; Dong, Guozhong; Yu, Miao; Lv, Jiguang

2015-01-01

With the rapid development of WLAN technology, wireless device-free passive human detection becomes a newly-developing technique and holds more potential to worldwide and ubiquitous smart applications. Recently, indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Previous wireless device-free passive human detection systems either rely on deploying specialized systems with dense transmitter-receiver links or elaborate off-line training process, which blocks rapid deployment and weakens system robustness. In the paper, we explore to research a novel fine-grained real-time calibration-free device-free passive human motion via physical layer information, which is independent of indoor scenarios and needs no prior-calibration and normal profile. We investigate sensitivities of amplitude and phase to human motion, and discover that phase feature is more sensitive to human motion, especially to slow human motion. Aiming at lightweight and robust device-free passive human motion detection, we develop two novel and practical schemes: short-term averaged variance ratio (SVR) and long-term averaged variance ratio (LVR). We realize system design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve a high detection rate and low false positive rate. PMID:26703612

Adaptive Motion Compensation in Radiotherapy

CERN Document Server

Murphy, Martin J

2011-01-01

External-beam radiotherapy has long been challenged by the simple fact that patients can (and do) move during the delivery of radiation. Recent advances in imaging and beam delivery technologies have made the solution--adapting delivery to natural movement--a practical reality. Adaptive Motion Compensation in Radiotherapy provides the first detailed treatment of online interventional techniques for motion compensation radiotherapy. This authoritative book discusses: Each of the contributing elements of a motion-adaptive system, including target detection and tracking, beam adaptation, and pati

First online real-time evaluation of motion-induced 4D dose errors during radiotherapy delivery

DEFF Research Database (Denmark)

Ravkilde, Thomas; Skouboe, Simon; Hansen, Rune

2018-01-01

PURPOSE: In radiotherapy, dose deficits caused by tumor motion often far outweigh the discrepancies typically allowed in plan-specific quality assurance (QA). Yet, tumor motion is not usually included in present QA. We here present a novel method for online treatment verification by real......-time motion-including 4D dose reconstruction and dose evaluation and demonstrate its use during stereotactic body radiotherapy (SBRT) delivery with and without MLC tracking. METHODS: Five volumetric modulated arc therapy (VMAT) plans were delivered with and without MLC tracking to a motion stage carrying...... a Delta4 dosimeter. The VMAT plans have previously been used for (non-tracking) liver SBRT with intra-treatment tumor motion recorded by kilovoltage intrafraction monitoring (KIM). The motion stage reproduced the KIM-measured tumor motions in 3D while optical monitoring guided the MLC tracking. Linac...

Real-Time Demand Side Management Algorithm Using Stochastic Optimization

Directory of Open Access Journals (Sweden)

Moses Amoasi Acquah

2018-05-01

Full Text Available A demand side management technique is deployed along with battery energy-storage systems (BESS to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study, we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand.

Optimal Real-time Dispatch for Integrated Energy Systems

DEFF Research Database (Denmark)

Anvari-Moghaddam, Amjad; Guerrero, Josep M.; Rahimi-Kian, Ashkan

2016-01-01

With the emerging of small-scale integrated energy systems (IESs), there are significant potentials to increase the functionality of a typical demand-side management (DSM) strategy and typical implementation of building-level distributed energy resources (DERs). By integrating DSM and DERs...... into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems, and integrated communications architectures, it is possible to efficiently manage energy and comfort at the end-use location. In this paper, an ontology-driven multi......-agent control system with intelligent optimizers is proposed for optimal real-time dispatch of an integrated building and microgrid system considering coordinated demand response (DR) and DERs management. The optimal dispatch problem is formulated as a mixed integer nonlinear programing problem (MINLP...

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....

The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery

International Nuclear Information System (INIS)

Falk, Marianne; Larsson, Tobias; Keall, Paul; Chul Cho, Byung; Aznar, Marianne; Korreman, Stine; Poulsen, Per; Munck af Rosenschoeld, Per

2012-01-01

Purpose: Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced by using a leaf position constraint (LPC) that reduces the difference in the position of adjacent MLC leaves in the plan. The purpose of this study was to investigate the impact of the LPC on the quality of inversely optimized arc radiotherapy plans and the effect of the MLC motion pattern on the dosimetric accuracy of MLC tracking delivery. Specifically, the possibility of predicting the accuracy of MLC tracking delivery based on the plan modulation was investigated. Methods: Inversely optimized arc radiotherapy plans were created on CT-data of three lung cancer patients. For each case, five plans with a single 358 deg. arc were generated with LPC priorities of 0 (no LPC), 0.25, 0.5, 0.75, and 1 (highest possible LPC), respectively. All the plans had a prescribed dose of 2 Gy x 30, used 6 MV, a maximum dose rate of 600 MU/min and a collimator angle of 45 deg. or 315 deg. To quantify the plan modulation, an average adjacent leaf distance (ALD) was calculated by averaging the mean adjacent leaf distance for each control point. The linear relationship between the plan quality [i.e., the calculated dose distributions and the number of monitor units (MU)] and the LPC was investigated, and the linear regression coefficient as well as a two tailed confidence level of 95% was used in the evaluation. The effect of the plan modulation on the performance of MLC tracking was tested by delivering the plans to a cylindrical diode array phantom moving with sinusoidal motion in the superior-inferior direction with a peak-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system

Mao-Gilles Stabilization Algorithm

OpenAIRE

Jérôme Gilles

2013-01-01

Originally, the Mao-Gilles stabilization algorithm was designed to compensate the non-rigid deformations due to atmospheric turbulence. Given a sequence of frames affected by atmospheric turbulence, the algorithm uses a variational model combining optical flow and regularization to characterize the static observed scene. The optimization problem is solved by Bregman Iteration and the operator splitting method. The algorithm is simple, efficient, and can be easily generalized for different sce...

Real-time range acquisition by adaptive structured light.

Science.gov (United States)

Koninckx, Thomas P; Van Gool, Luc

2006-03-01

The goal of this paper is to provide a "self-adaptive" system for real-time range acquisition. Reconstructions are based on a single frame structured light illumination. Instead of using generic, static coding that is supposed to work under all circumstances, system adaptation is proposed. This occurs on-the-fly and renders the system more robust against instant scene variability and creates suitable patterns at startup. A continuous trade-off between speed and quality is made. A weighted combination of different coding cues--based upon pattern color, geometry, and tracking--yields a robust way to solve the correspondence problem. The individual coding cues are automatically adapted within a considered family of patterns. The weights to combine them are based on the average consistency with the result within a small time-window. The integration itself is done by reformulating the problem as a graph cut. Also, the camera-projector configuration is taken into account for generating the projection patterns. The correctness of the range maps is not guaranteed, but an estimation of the uncertainty is provided for each part of the reconstruction. Our prototype is implemented using unmodified consumer hardware only and, therefore, is cheap. Frame rates vary between 10 and 25 fps, dependent on scene complexity.

Evolutionary online behaviour learning and adaptation in real robots.

Science.gov (United States)

Silva, Fernando; Correia, Luís; Christensen, Anders Lyhne

2017-07-01

Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm.

Acceleration optimization of real-time equilibrium reconstruction for HL-2A tokamak discharge control

Science.gov (United States)

Rui, MA; Fan, XIA; Fei, LING; Jiaxian, LI

2018-02-01

Real-time equilibrium reconstruction is crucially important for plasma shape control in the process of tokamak plasma discharge. However, as the reconstruction algorithm is computationally intensive, it is very difficult to improve its accuracy and reduce the computation time, and some optimizations need to be done. This article describes the three most important aspects of this optimization: (1) compiler optimization; (2) some optimization for middle-scale matrix multiplication on the graphic processing unit and an algorithm which can solve the block tri-diagonal linear system efficiently in parallel; (3) a new algorithm to locate the X&O point on the central processing unit. A static test proves the correctness and a dynamic test proves the feasibility of using the new code for real-time reconstruction with 129 × 129 grids; it can complete one iteration around 575 μs for each equilibrium reconstruction. The plasma displacements from real-time equilibrium reconstruction are compared with the experimental measurements, and the calculated results are consistent with the measured ones, which can be used as a reference for the real-time control of HL-2A discharge.

Implementation of a real-time adaptive digital shaping for nuclear spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Regadío, Alberto, E-mail: aregadio@srg.aut.uah.es [Department of Computer Engineering, Space Research Group, Universidad de Alcalá, 28805 Alcalá de Henares (Spain); Electronic Technology Area, Instituto Nacional de Técnica Aeroespacial, 28850 Torrejón de Ardoz (Spain); Sánchez-Prieto, Sebastián, E-mail: ssanchez@srg.aut.uah.es [Department of Computer Engineering, Space Research Group, Universidad de Alcalá, 28805 Alcalá de Henares (Spain); Prieto, Manuel, E-mail: mprieto@srg.aut.uah.es [Department of Computer Engineering, Space Research Group, Universidad de Alcalá, 28805 Alcalá de Henares (Spain); Tabero, Jesús, E-mail: taberogj@inta.es [Electronic Technology Area, Instituto Nacional de Técnica Aeroespacial, 28850 Torrejón de Ardoz (Spain)

2014-01-21

This paper presents the structure, design and implementation of a new adaptive digital shaper for processing the pulses generated in nuclear particle detectors. The proposed adaptive algorithm has the capacity to automatically adjust the coefficients for shaping an input signal with a desired profile in real-time. Typical shapers such as triangular, trapezoidal or cusp-like ones can be generated, but more exotic unipolar shaping could also be performed. A practical prototype was designed, implemented and tested in a Field Programmable Gate Array (FPGA). Particular attention was paid to the amount of internal FPGA resources required and to the sampling rate, making the design as simple as possible in order to minimize power consumption. Lastly, its performance and capabilities were measured using simulations and a real benchmark.

Implementation of a real-time adaptive digital shaping for nuclear spectroscopy

International Nuclear Information System (INIS)

Regadío, Alberto; Sánchez-Prieto, Sebastián; Prieto, Manuel; Tabero, Jesús

2014-01-01

This paper presents the structure, design and implementation of a new adaptive digital shaper for processing the pulses generated in nuclear particle detectors. The proposed adaptive algorithm has the capacity to automatically adjust the coefficients for shaping an input signal with a desired profile in real-time. Typical shapers such as triangular, trapezoidal or cusp-like ones can be generated, but more exotic unipolar shaping could also be performed. A practical prototype was designed, implemented and tested in a Field Programmable Gate Array (FPGA). Particular attention was paid to the amount of internal FPGA resources required and to the sampling rate, making the design as simple as possible in order to minimize power consumption. Lastly, its performance and capabilities were measured using simulations and a real benchmark

Real-time SPARSE-SENSE cardiac cine MR imaging: optimization of image reconstruction and sequence validation.

Science.gov (United States)

Goebel, Juliane; Nensa, Felix; Bomas, Bettina; Schemuth, Haemi P; Maderwald, Stefan; Gratz, Marcel; Quick, Harald H; Schlosser, Thomas; Nassenstein, Kai

2016-12-01

Improved real-time cardiac magnetic resonance (CMR) sequences have currently been introduced, but so far only limited practical experience exists. This study aimed at image reconstruction optimization and clinical validation of a new highly accelerated real-time cine SPARSE-SENSE sequence. Left ventricular (LV) short-axis stacks of a real-time free-breathing SPARSE-SENSE sequence with high spatiotemporal resolution and of a standard segmented cine SSFP sequence were acquired at 1.5 T in 11 volunteers and 15 patients. To determine the optimal iterations, all volunteers' SPARSE-SENSE images were reconstructed using 10-200 iterations, and contrast ratios, image entropies, and reconstruction times were assessed. Subsequently, the patients' SPARSE-SENSE images were reconstructed with the clinically optimal iterations. LV volumetric values were evaluated and compared between both sequences. Sufficient image quality and acceptable reconstruction times were achieved when using 80 iterations. Bland-Altman plots and Passing-Bablok regression showed good agreement for all volumetric parameters. 80 iterations are recommended for iterative SPARSE-SENSE image reconstruction in clinical routine. Real-time cine SPARSE-SENSE yielded comparable volumetric results as the current standard SSFP sequence. Due to its intrinsic low image acquisition times, real-time cine SPARSE-SENSE imaging with iterative image reconstruction seems to be an attractive alternative for LV function analysis. • A highly accelerated real-time CMR sequence using SPARSE-SENSE was evaluated. • SPARSE-SENSE allows free breathing in real-time cardiac cine imaging. • For clinically optimal SPARSE-SENSE image reconstruction, 80 iterations are recommended. • Real-time SPARSE-SENSE imaging yielded comparable volumetric results as the reference SSFP sequence. • The fast SPARSE-SENSE sequence is an attractive alternative to standard SSFP sequences.

Optimized Scheduling of Smart Meter Data Access for Real-time Voltage Quality Monitoring

DEFF Research Database (Denmark)

Kemal, Mohammed Seifu; Olsen, Rasmus Løvenstein; Schwefel, Hans-Peter

2018-01-01

Abstract—Active low-voltage distribution grids that support high integration of distributed generation such as photovoltaics and wind turbines require real-time voltage monitoring. At the same time, countries in Europe such as Denmark have close to 100% rollout of smart metering infrastructure....... The metering infrastructure has limitations to provide real-time measurements with small-time granularity. This paper presents an algorithm for optimized scheduling of smart meter data access to provide real-time voltage quality monitoring. The algorithm is analyzed using a real distribution grid in Denmark...

[A review of progress of real-time tumor tracking radiotherapy technology based on dynamic multi-leaf collimator].

Science.gov (United States)

Liu, Fubo; Li, Guangjun; Shen, Jiuling; Li, Ligin; Bai, Sen

2017-02-01

While radiation treatment to patients with tumors in thorax and abdomen is being performed, further improvement of radiation accuracy is restricted by the tumor intra-fractional motion due to respiration. Real-time tumor tracking radiation is an optimal solution to tumor intra-fractional motion. A review of the progress of real-time dynamic multi-leaf collimator(DMLC) tracking is provided in the present review, including DMLC tracking method, time lag of DMLC tracking system, and dosimetric verification.

Real-time dynamic MLC tracking for inversely optimized arc radiotherapy

DEFF Research Database (Denmark)

Falk, Marianne; af Rosenschöld, Per Munck; Keall, Paul

2010-01-01

Motion compensation with MLC tracking was tested for inversely optimized arc radiotherapy with special attention to the impact of the size of the target displacements and the angle of the leaf trajectory.......Motion compensation with MLC tracking was tested for inversely optimized arc radiotherapy with special attention to the impact of the size of the target displacements and the angle of the leaf trajectory....

Performance of a Nonlinear Real-Time Optimal Control System for HEVs/PHEVs during Car Following

Directory of Open Access Journals (Sweden)

Kaijiang Yu

2014-01-01

Full Text Available This paper presents a real-time optimal control approach for the energy management problem of hybrid electric vehicles (HEVs and plug-in hybrid electric vehicles (PHEVs with slope information during car following. The new features of this study are as follows. First, the proposed method can optimize the engine operating points and the driving profile simultaneously. Second, the proposed method gives the freedom of vehicle spacing between the preceding vehicle and the host vehicle. Third, using the HEV/PHEV property, the desired battery state of charge is designed according to the road slopes for better recuperation of free braking energy. Fourth, all of the vehicle operating modes engine charge, electric vehicle, motor assist and electric continuously variable transmission, and regenerative braking, can be realized using the proposed real-time optimal control approach. Computer simulation results are shown among the nonlinear real-time optimal control approach and the ADVISOR rule-based approach. The conclusion is that the nonlinear real-time optimal control approach is effective for the energy management problem of the HEV/PHEV system during car following.

Optimal Investment Timing and Size of a Logistics Park: A Real Options Perspective

Directory of Open Access Journals (Sweden)

Dezhi Zhang

2017-01-01

Full Text Available This paper uses a real options approach to address optimal timing and size of a logistics park investment with logistics demand volatility. Two important problems are examined: when should an investment be introduced, and what size should it be? A real option model is proposed to explicitly incorporate the effect of government subsidies on logistics park investment. Logistic demand that triggers the threshold for investment in a logistics park project is explored analytically. Comparative static analyses of logistics park investment are also carried out. Our analytical results show that (1 investors will select smaller sized logistics parks and prepone the investment if government subsidies are considered; (2 the real option will postpone the optimal investment timing of logistics parks compared with net present value approach; and (3 logistic demands can significantly affect the optimal investment size and timing of logistics park investment.

SU-G-JeP4-12: Real-Time Organ Motion Monitoring Using Ultrasound and KV Fluoroscopy During Lung SBRT Delivery

International Nuclear Information System (INIS)

Omari, E; Tai, A; Li, X; Cooper, D; Lachaine, M

2016-01-01

Purpose: Real-time ultrasound monitoring during SBRT is advantageous in understanding and identifying motion irregularities which may cause geometric misses. In this work, we propose to utilize real-time ultrasound to track the diaphragm in conjunction with periodical kV fluoroscopy to monitor motion of tumor or landmarks during SBRT delivery. Methods: Transabdominal Ultrasound (TAUS) b-mode images were collected from 10 healthy volunteers using the Clarity Autoscan System (Elekta). The autoscan transducer, which has a center frequency of 5 MHz, was utilized for the scans. The acquired images were contoured using the Clarity Automatic Fusion and Contouring workstation software. Monitoring sessions of 5 minute length were observed and recorded. The position correlation between tumor and diaphragm could be established with periodic kV fluoroscopy periodically acquired during treatment with Elekta XVI. We acquired data using a tissue mimicking ultrasound phantom with embedded spheres placed on a motion stand using ultrasound and kV Fluoroscopy. MIM software was utilized for image fusion. Correlation of diaphragm and target motion was also validated using 4D-MRI and 4D-CBCT. Results: The diaphragm was visualized as a hyperechoic region on the TAUS b-mode images. Volunteer set-up can be adjusted such that TAUS probe will not interfere with treatment beams. A segment of the diaphragm was contoured and selected as our tracking structure. Successful monitoring sessions of the diaphragm were recorded. For some volunteers, diaphragm motion over 2 times larger than the initial motion has been observed during tracking. For the phantom study, we were able to register the 2D kV Fluoroscopy with the US images for position comparison. Conclusion: We demonstrated the feasibility of tracking the diaphragm using real-time ultrasound. Real-time tracking can help in identifying such irregularities in the respiratory motion which is correlated to tumor motion. We also showed the

A prototype percutaneous transhepatic cholangiography training simulator with real-time breathing motion.

Science.gov (United States)

Villard, P F; Vidal, F P; Hunt, C; Bello, F; John, N W; Johnson, S; Gould, D A

2009-11-01

We present here a simulator for interventional radiology focusing on percutaneous transhepatic cholangiography (PTC). This procedure consists of inserting a needle into the biliary tree using fluoroscopy for guidance. The requirements of the simulator have been driven by a task analysis. The three main components have been identified: the respiration, the real-time X-ray display (fluoroscopy) and the haptic rendering (sense of touch). The framework for modelling the respiratory motion is based on kinematics laws and on the Chainmail algorithm. The fluoroscopic simulation is performed on the graphic card and makes use of the Beer-Lambert law to compute the X-ray attenuation. Finally, the haptic rendering is integrated to the virtual environment and takes into account the soft-tissue reaction force feedback and maintenance of the initial direction of the needle during the insertion. Five training scenarios have been created using patient-specific data. Each of these provides the user with variable breathing behaviour, fluoroscopic display tuneable to any device parameters and needle force feedback. A detailed task analysis has been used to design and build the PTC simulator described in this paper. The simulator includes real-time respiratory motion with two independent parameters (rib kinematics and diaphragm action), on-line fluoroscopy implemented on the Graphics Processing Unit and haptic feedback to feel the soft-tissue behaviour of the organs during the needle insertion.

TH-AB-202-05: BEST IN PHYSICS (JOINT IMAGING-THERAPY): First Online Ultrasound-Guided MLC Tracking for Real-Time Motion Compensation in Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Ipsen, S; Bruder, R; Schweikard, A [University of Luebeck, Luebeck, DE (United States); O’Brien, R; Keall, P [University of Sydney, Sydney (Australia); Poulsen, P [Aarhus University Hospital, Aarhus (Denmark)

2016-06-15

Purpose: While MLC tracking has been successfully used for motion compensation of moving targets, current real-time target localization methods rely on correlation models with x-ray imaging or implanted electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging yields volumetric data in real-time (4D) without ionizing radiation. We report the first results of online 4D ultrasound-guided MLC tracking in a phantom. Methods: A real-time tracking framework was installed on a 4D ultrasound station (Vivid7 dimension, GE) and used to detect a 2mm spherical lead marker inside a water tank. The volumetric frame rate was 21.3Hz (47ms). The marker was rigidly attached to a motion stage programmed to reproduce nine tumor trajectories (five prostate, four lung). The 3D marker position from ultrasound was used for real-time MLC aperture adaption. The tracking system latency was measured and compensated by prediction for lung trajectories. To measure geometric accuracy, anterior and lateral conformal fields with 10cm circular aperture were delivered for each trajectory. The tracking error was measured as the difference between marker position and MLC aperture in continuous portal imaging. For dosimetric evaluation, 358° VMAT fields were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using a 3%/3 mm γ-test. Results: The tracking system latency was 170ms. The mean root-mean-square tracking error was 1.01mm (0.75mm prostate, 1.33mm lung). Tracking reduced the mean γ-failure rate from 13.9% to 4.6% for prostate and from 21.8% to 0.6% for lung with high-modulation VMAT plans and from 5% (prostate) and 18% (lung) to 0% with low modulation. Conclusion: Real-time ultrasound tracking was successfully integrated with MLC tracking for the first time and showed similar accuracy and latency as other methods while holding the

Real-time dose compensation methods for scanned ion beam therapy of moving tumors

International Nuclear Information System (INIS)

Luechtenborg, Robert

2012-01-01

Scanned ion beam therapy provides highly tumor-conformal treatments. So far, only tumors showing no considerable motion during therapy have been treated as tumor motion and dynamic beam delivery interfere, causing dose deteriorations. One proposed technique to mitigate these deteriorations is beam tracking (BT), which adapts the beam position to the moving tumor. Despite application of BT, dose deviations can occur in the case of non-translational motion. In this work, real-time dose compensation combined with beam tracking (RDBT) has been implemented into the control system to compensate these dose changes by adaptation of nominal particle numbers during irradiation. Compared to BT, significantly reduced dose deviations were measured using RDBT. Treatment planning studies for lung cancer patients including the increased biological effectiveness of ions revealed a significantly reduced over-dose level (3/5 patients) as well as significantly improved dose homogeneity (4/5 patients) for RDBT. Based on these findings, real-time dose compensated re-scanning (RDRS) has been proposed that potentially supersedes the technically complex fast energy adaptation necessary for BT and RDBT. Significantly improved conformity compared to re-scanning, i.e., averaging of dose deviations by repeated irradiation, was measured in film irradiations. Simulations comparing RDRS to BT revealed reduced under- and overdoses of the former method.

Three-dimensional, automated, real-time video system for tracking limb motion in brain-machine interface studies.

Science.gov (United States)

Peikon, Ian D; Fitzsimmons, Nathan A; Lebedev, Mikhail A; Nicolelis, Miguel A L

2009-06-15

Collection and analysis of limb kinematic data are essential components of the study of biological motion, including research into biomechanics, kinesiology, neurophysiology and brain-machine interfaces (BMIs). In particular, BMI research requires advanced, real-time systems capable of sampling limb kinematics with minimal contact to the subject's body. To answer this demand, we have developed an automated video tracking system for real-time tracking of multiple body parts in freely behaving primates. The system employs high-contrast markers painted on the animal's joints to continuously track the three-dimensional positions of their limbs during activity. Two-dimensional coordinates captured by each video camera are combined and converted to three-dimensional coordinates using a quadratic fitting algorithm. Real-time operation of the system is accomplished using direct memory access (DMA). The system tracks the markers at a rate of 52 frames per second (fps) in real-time and up to 100fps if video recordings are captured to be later analyzed off-line. The system has been tested in several BMI primate experiments, in which limb position was sampled simultaneously with chronic recordings of the extracellular activity of hundreds of cortical cells. During these recordings, multiple computational models were employed to extract a series of kinematic parameters from neuronal ensemble activity in real-time. The system operated reliably under these experimental conditions and was able to compensate for marker occlusions that occurred during natural movements. We propose that this system could also be extended to applications that include other classes of biological motion.

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians

Science.gov (United States)

Pang, Shengshi; Jordan, Andrew N.

2017-01-01

Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case. PMID:28276428

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians.

Science.gov (United States)

Pang, Shengshi; Jordan, Andrew N

2017-03-09

Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T 2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T 4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case.

Adaptive Monocular Visual-Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices.

Science.gov (United States)

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.

Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices

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.

Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices

Science.gov (United States)

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 two-domain real-time algorithm for optimal data reduction: a case study on accelerator magnet measurements

International Nuclear Information System (INIS)

Arpaia, Pasquale; Buzio, Marco; Inglese, Vitaliano

2010-01-01

A real-time algorithm of data reduction, based on the combination of two lossy techniques specifically optimized for high-rate magnetic measurements in two domains (e.g. time and space), is proposed. The first technique exploits an adaptive sampling rule based on the power estimation of the flux increments in order to optimize the information to be gathered for magnetic field analysis in real time. The tracking condition is defined by the target noise level in the Nyquist band required by the post-processing procedure of magnetic analysis. The second technique uses a data reduction algorithm in order to improve the compression ratio while preserving the consistency of the measured signal. The allowed loss is set equal to the random noise level in the signal in order to force the loss and the noise to cancel rather than to add, by improving the signal-to-noise ratio. Numerical analysis and experimental results of on-field performance characterization and validation for two case studies of magnetic measurement systems for testing magnets of the Large Hadron Collider at the European Organization for Nuclear Research (CERN) are reported

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

Science.gov (United States)

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

Directory of Open Access Journals (Sweden)

Dennis Akos

2011-09-01

Full Text Available Due to their weak received signal power, Global Positioning System (GPS signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs. However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU coupled with a new generation Graphics Processing Unit (GPU having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy

International Nuclear Information System (INIS)

Seppenwoolde, Yvette; Shirato, Hiroki; Kitamura, Kei; Shimizu, Shinichi; Herk, Marcel van; Lebesque, Joos V.; Miyasaka, Kazuo

2002-01-01

Purpose: In this work, three-dimensional (3D) motion of lung tumors during radiotherapy in real time was investigated. Understanding the behavior of tumor motion in lung tissue to model tumor movement is necessary for accurate (gated or breath-hold) radiotherapy or CT scanning. Methods: Twenty patients were included in this study. Before treatment, a 2-mm gold marker was implanted in or near the tumor. A real-time tumor tracking system using two fluoroscopy image processor units was installed in the treatment room. The 3D position of the implanted gold marker was determined by using real-time pattern recognition and a calibrated projection geometry. The linear accelerator was triggered to irradiate the tumor only when the gold marker was located within a certain volume. The system provided the coordinates of the gold marker during beam-on and beam-off time in all directions simultaneously, at a sample rate of 30 images per second. The recorded tumor motion was analyzed in terms of the amplitude and curvature of the tumor motion in three directions, the differences in breathing level during treatment, hysteresis (the difference between the inhalation and exhalation trajectory of the tumor), and the amplitude of tumor motion induced by cardiac motion. Results: The average amplitude of the tumor motion was greatest (12±2 mm [SD]) in the cranial-caudal direction for tumors situated in the lower lobes and not attached to rigid structures such as the chest wall or vertebrae. For the lateral and anterior-posterior directions, tumor motion was small both for upper- and lower-lobe tumors (2±1 mm). The time-averaged tumor position was closer to the exhale position, because the tumor spent more time in the exhalation than in the inhalation phase. The tumor motion was modeled as a sinusoidal movement with varying asymmetry. The tumor position in the exhale phase was more stable than the tumor position in the inhale phase during individual treatment fields. However, in many

An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU

Directory of Open Access Journals (Sweden)

Hailong Xu

2016-03-01

Full Text Available Nowadays, software-defined radio (SDR has become a common approach to evaluate new algorithms. However, in the field of Global Navigation Satellite System (GNSS adaptive array anti-jamming, previous work has been limited due to the high computational power demanded by adaptive algorithms, and often lack flexibility and configurability. In this paper, the design and implementation of an SDR-based real-time testbed for GNSS adaptive array anti-jamming accelerated by a Graphics Processing Unit (GPU are documented. This testbed highlights itself as a feature-rich and extendible platform with great flexibility and configurability, as well as high computational performance. Both Space-Time Adaptive Processing (STAP and Space-Frequency Adaptive Processing (SFAP are implemented with a wide range of parameters. Raw data from as many as eight antenna elements can be processed in real-time in either an adaptive nulling or beamforming mode. To fully take advantage of the parallelism resource provided by the GPU, a batched method in programming is proposed. Tests and experiments are conducted to evaluate both the computational and anti-jamming performance. This platform can be used for research and prototyping, as well as a real product in certain applications.

Mao-Gilles Stabilization Algorithm

Directory of Open Access Journals (Sweden)

Jérôme Gilles

2013-07-01

Full Text Available Originally, the Mao-Gilles stabilization algorithm was designed to compensate the non-rigid deformations due to atmospheric turbulence. Given a sequence of frames affected by atmospheric turbulence, the algorithm uses a variational model combining optical flow and regularization to characterize the static observed scene. The optimization problem is solved by Bregman Iteration and the operator splitting method. The algorithm is simple, efficient, and can be easily generalized for different scenarios involving non-rigid deformations.

Adaptive real-time dual-comb spectroscopy

Science.gov (United States)

Ideguchi, Takuro; Poisson, Antonin; Guelachvili, Guy; Picqué, Nathalie; Hänsch, Theodor W.

2014-01-01

The spectrum of a laser frequency comb consists of several hundred thousand equally spaced lines over a broad spectral bandwidth. Such frequency combs have revolutionized optical frequency metrology and they now hold much promise for significant advances in a growing number of applications including molecular spectroscopy. Despite an intriguing potential for the measurement of molecular spectra spanning tens of nanometres within tens of microseconds at Doppler-limited resolution, the development of dual-comb spectroscopy is hindered by the demanding stability requirements of the laser combs. Here we overcome this difficulty and experimentally demonstrate a concept of real-time dual-comb spectroscopy, which compensates for laser instabilities by electronic signal processing. It only uses free-running mode-locked lasers without any phase-lock electronics. We record spectra spanning the full bandwidth of near-infrared fibre lasers with Doppler-limited line profiles highly suitable for measurements of concentrations or line intensities. Our new technique of adaptive dual-comb spectroscopy offers a powerful transdisciplinary instrument for analytical sciences. PMID:24572636

Adaptive real-time dual-comb spectroscopy

Science.gov (United States)

Ideguchi, Takuro; Poisson, Antonin; Guelachvili, Guy; Picqué, Nathalie; Hänsch, Theodor W.

2014-02-01

The spectrum of a laser frequency comb consists of several hundred thousand equally spaced lines over a broad spectral bandwidth. Such frequency combs have revolutionized optical frequency metrology and they now hold much promise for significant advances in a growing number of applications including molecular spectroscopy. Despite an intriguing potential for the measurement of molecular spectra spanning tens of nanometres within tens of microseconds at Doppler-limited resolution, the development of dual-comb spectroscopy is hindered by the demanding stability requirements of the laser combs. Here we overcome this difficulty and experimentally demonstrate a concept of real-time dual-comb spectroscopy, which compensates for laser instabilities by electronic signal processing. It only uses free-running mode-locked lasers without any phase-lock electronics. We record spectra spanning the full bandwidth of near-infrared fibre lasers with Doppler-limited line profiles highly suitable for measurements of concentrations or line intensities. Our new technique of adaptive dual-comb spectroscopy offers a powerful transdisciplinary instrument for analytical sciences.

Real-time motion compensated patient positioning and non-rigid deformation estimation using 4-D shape priors.

Science.gov (United States)

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.

Modeling of the motion of automobile elastic wheel in real-time for creation of wheeled vehicles motion control electronic systems

Science.gov (United States)

Balakina, E. V.; Zotov, N. M.; Fedin, A. P.

2018-02-01

Modeling of the motion of the elastic wheel of the vehicle in real-time is used in the tasks of constructing different models in the creation of wheeled vehicles motion control electronic systems, in the creation of automobile stand-simulators etc. The accuracy and the reliability of simulation of the parameters of the wheel motion in real-time when rolling with a slip within the given road conditions are determined not only by the choice of the model, but also by the inaccuracy and instability of the numerical calculation. It is established that the inaccuracy and instability of the calculation depend on the size of the step of integration and the numerical method being used. The analysis of these inaccuracy and instability when wheel rolling with a slip was made and recommendations for reducing them were developed. It is established that the total allowable range of steps of integration is 0.001.0.005 s; the strongest instability is manifested in the calculation of the angular and linear accelerations of the wheel; the weakest instability is manifested in the calculation of the translational velocity of the wheel and moving of the center of the wheel; the instability is less at large values of slip angle and on more slippery surfaces. A new method of the average acceleration is suggested, which allows to significantly reduce (up to 100%) the manifesting of instability of the solution in the calculation of all parameters of motion of the elastic wheel for different braking conditions and for the entire range of steps of integration. The results of research can be applied to the selection of control algorithms in vehicles motion control electronic systems and in the testing stand-simulators

Real-Time Game Adaptation for Optimizing Player Satisfaction

DEFF Research Database (Denmark)

Yannakakis, Georgios; Hallam, John

2009-01-01

A methodology for optimizing player satisfaction in games on the "playware" physical interactive platform is demonstrated in this paper. Previously constructed artificial neural network user models, reported in the literature, map individual playing characteristics to reported entertainment...

Optimal operation of smart houses by a real-time rolling horizon algorithm

NARCIS (Netherlands)

Paterakis, N.G.; Pappi, I.N.; Catalão, J.P.S.; Erdinc, O.

2016-01-01

In this paper, a novel real-time rolling horizon optimization framework for the optimal operation of a smart household is presented. A home energy management system (HEMS) model based on mixed-integer linear programming (MILP) is developed in order to minimize the energy procurement cost considering

The post-Mao gazes: Chinese backpackers in Macau

NARCIS (Netherlands)

Ong, C.E.; Cros, du H.

2012-01-01

This paper offers insights into backpacker tourism from the People’s Republic of China. Chinese backpackers are a distinctively post-Mao reform generation growing up at a time when China shifts from Mao Zedong’s socialist policies to Deng Xiaoping’s policy explorations with capitalism. Through

MO-FG-BRD-01: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: Introduction and KV Tracking

International Nuclear Information System (INIS)

Fahimian, B.

2015-01-01

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow

MO-FG-BRD-01: Real-Time Imaging and Tracking Techniques for Intrafractional Motion Management: Introduction and KV Tracking

Energy Technology Data Exchange (ETDEWEB)

Fahimian, B. [Stanford University (United States)

2015-06-15

Intrafraction target motion is a prominent complicating factor in the accurate targeting of radiation within the body. Methods compensating for target motion during treatment, such as gating and dynamic tumor tracking, depend on the delineation of target location as a function of time during delivery. A variety of techniques for target localization have been explored and are under active development; these include beam-level imaging of radio-opaque fiducials, fiducial-less tracking of anatomical landmarks, tracking of electromagnetic transponders, optical imaging of correlated surrogates, and volumetric imaging within treatment delivery. The Joint Imaging and Therapy Symposium will provide an overview of the techniques for real-time imaging and tracking, with special focus on emerging modes of implementation across different modalities. In particular, the symposium will explore developments in 1) Beam-level kilovoltage X-ray imaging techniques, 2) EPID-based megavoltage X-ray tracking, 3) Dynamic tracking using electromagnetic transponders, and 4) MRI-based soft-tissue tracking during radiation delivery. Learning Objectives: Understand the fundamentals of real-time imaging and tracking techniques Learn about emerging techniques in the field of real-time tracking Distinguish between the advantages and disadvantages of different tracking modalities Understand the role of real-time tracking techniques within the clinical delivery work-flow.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

Science.gov (United States)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

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

OpenAIRE

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

2012-01-01

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

New pyrrole inhibitors of monoamine oxidase: synthesis, biological evaluation, and structural determinants of MAO-A and MAO-B selectivity.

Science.gov (United States)

La Regina, Giuseppe; Silvestri, Romano; Artico, Marino; Lavecchia, Antonio; Novellino, Ettore; Befani, Olivia; Turini, Paola; Agostinelli, Enzo

2007-03-08

A series of new pyrrole derivatives have been synthesized and evaluated for their monoamine oxidase (MAO) A and B inhibitory activity and selectivity. N-Methyl,N-(benzyl),N-(pyrrol-2-ylmethyl)amine (7) and N-(2-benzyl),N-(1-methylpyrrol-2-ylmethyl)amine (18) were the most selective MAO-B (7, SI = 0.0057) and MAO-A (18, SI = 12500) inhibitors, respectively. Docking and molecular dynamics simulations gave structural insights into the MAO-A and MAO-B selectivity. Compound 18 forms an H-bond with Gln215 through its protonated amino group into the MAO-A binding site. This H-bond is absent in the 7/MAO-A complex. In contrast, compound 7 places its phenyl ring into an aromatic cage of the MAO-B binding pocket, where it forms charge-transfer interactions. The slightly different binding pose of 18 into the MAO-B active site seems to be forced by a bulkier Tyr residue, which replaces a smaller Ile residue present in MAO-A.

Optimal Real-time Dispatch for Integrated Energy Systems

Energy Technology Data Exchange (ETDEWEB)

Firestone, Ryan Michael [Univ. of California, Berkeley, CA (United States)

2007-05-31

This report describes the development and application of a dispatch optimization algorithm for integrated energy systems (IES) comprised of on-site cogeneration of heat and electricity, energy storage devices, and demand response opportunities. This work is intended to aid commercial and industrial sites in making use of modern computing power and optimization algorithms to make informed, near-optimal decisions under significant uncertainty and complex objective functions. The optimization algorithm uses a finite set of randomly generated future scenarios to approximate the true, stochastic future; constraints are included that prevent solutions to this approximate problem from deviating from solutions to the actual problem. The algorithm is then expressed as a mixed integer linear program, to which a powerful commercial solver is applied. A case study of United States Postal Service Processing and Distribution Centers (P&DC) in four cities and under three different electricity tariff structures is conducted to (1) determine the added value of optimal control to a cogeneration system over current, heuristic control strategies; (2) determine the value of limited electric load curtailment opportunities, with and without cogeneration; and (3) determine the trade-off between least-cost and least-carbon operations of a cogeneration system. Key results for the P&DC sites studied include (1) in locations where the average electricity and natural gas prices suggest a marginally profitable cogeneration system, optimal control can add up to 67% to the value of the cogeneration system; optimal control adds less value in locations where cogeneration is more clearly profitable; (2) optimal control under real-time pricing is (a) more complicated than under typical time-of-use tariffs and (b) at times necessary to make cogeneration economic at all; (3) limited electric load curtailment opportunities can be more valuable as a compliment to the cogeneration system than alone; and

Real-Time Correction By Optical Tracking with Integrated Geometric Distortion Correction for Reducing Motion Artifacts in fMRI

Science.gov (United States)

Rotenberg, David J.

Artifacts caused by head motion are a substantial source of error in fMRI that limits its use in neuroscience research and clinical settings. Real-time scan-plane correction by optical tracking has been shown to correct slice misalignment and non-linear spin-history artifacts, however residual artifacts due to dynamic magnetic field non-uniformity may remain in the data. A recently developed correction technique, PLACE, can correct for absolute geometric distortion using the complex image data from two EPI images, with slightly shifted k-space trajectories. We present a correction approach that integrates PLACE into a real-time scan-plane update system by optical tracking, applied to a tissue-equivalent phantom undergoing complex motion and an fMRI finger tapping experiment with overt head motion to induce dynamic field non-uniformity. Experiments suggest that including volume by volume geometric distortion correction by PLACE can suppress dynamic geometric distortion artifacts in a phantom and in vivo and provide more robust activation maps.

A real-time dynamic-MLC control algorithm for delivering IMRT to targets undergoing 2D rigid motion in the beam's eye view

International Nuclear Information System (INIS)

McMahon, Ryan; Berbeco, Ross; Nishioka, Seiko; Ishikawa, Masayori; Papiez, Lech

2008-01-01

An MLC control algorithm for delivering intensity modulated radiation therapy (IMRT) to targets that are undergoing two-dimensional (2D) rigid motion in the beam's eye view (BEV) is presented. The goal of this method is to deliver 3D-derived fluence maps over a moving patient anatomy. Target motion measured prior to delivery is first used to design a set of planned dynamic-MLC (DMLC) sliding-window leaf trajectories. During actual delivery, the algorithm relies on real-time feedback to compensate for target motion that does not agree with the motion measured during planning. The methodology is based on an existing one-dimensional (1D) algorithm that uses on-the-fly intensity calculations to appropriately adjust the DMLC leaf trajectories in real-time during exposure delivery [McMahon et al., Med. Phys. 34, 3211-3223 (2007)]. To extend the 1D algorithm's application to 2D target motion, a real-time leaf-pair shifting mechanism has been developed. Target motion that is orthogonal to leaf travel is tracked by appropriately shifting the positions of all MLC leaves. The performance of the tracking algorithm was tested for a single beam of a fractionated IMRT treatment, using a clinically derived intensity profile and a 2D target trajectory based on measured patient data. Comparisons were made between 2D tracking, 1D tracking, and no tracking. The impact of the tracking lag time and the frequency of real-time imaging were investigated. A study of the dependence of the algorithm's performance on the level of agreement between the motion measured during planning and delivery was also included. Results demonstrated that tracking both components of the 2D motion (i.e., parallel and orthogonal to leaf travel) results in delivered fluence profiles that are superior to those that track the component of motion that is parallel to leaf travel alone. Tracking lag time effects may lead to relatively large intensity delivery errors compared to the other sources of error investigated

Real-time optical tracking for motion compensated irradiation with scanned particle beams at CNAO

Energy Technology Data Exchange (ETDEWEB)

Fattori, G., E-mail: giovanni.fattori@psi.ch [Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano (Italy); Seregni, M. [Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano (Italy); Pella, A. [Centro Nazionale di Adroterapia Oncologica (CNAO), Strada Campeggi 53, 27100 Pavia (Italy); Riboldi, M. [Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano (Italy); Capasso, L. [Istituto Nazionale di Fisica Nucleare, Section of Torino, Torino 10125 (Italy); Donetti, M. [Centro Nazionale di Adroterapia Oncologica (CNAO), Strada Campeggi 53, 27100 Pavia (Italy); Istituto Nazionale di Fisica Nucleare, Section of Torino, Torino 10125 (Italy); Ciocca, M. [Centro Nazionale di Adroterapia Oncologica (CNAO), Strada Campeggi 53, 27100 Pavia (Italy); Giordanengo, S. [Istituto Nazionale di Fisica Nucleare, Section of Torino, Torino 10125 (Italy); Pullia, M. [Centro Nazionale di Adroterapia Oncologica (CNAO), Strada Campeggi 53, 27100 Pavia (Italy); Marchetto, F. [Istituto Nazionale di Fisica Nucleare, Section of Torino, Torino 10125 (Italy); Baroni, G. [Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano (Italy); Centro Nazionale di Adroterapia Oncologica (CNAO), Strada Campeggi 53, 27100 Pavia (Italy)

2016-08-11

Purpose: We describe the interface developed at the National Center for Oncological Hadrontherapy in Pavia to provide the dose delivery systems with real time respiratory motion information captured with an optical tracking system. An experimental study is presented to assess the technical feasibility of the implemented organ motion compensation framework, by analyzing the film response when irradiated with proton beams. Methods: The motion monitoring solution is based on a commercial hardware for motion capture running in-house developed software for respiratory signal processing. As part of the integration, the latency of data transmission to the dose delivery system was experimentally quantified and accounted for by signal time prediction. A respiratory breathing phantom is presented and used to test tumor tracking based either on the optical measurement of the target position or internal-external correlation models and beam gating, as driven by external surrogates. Beam tracking was tested considering the full target motion excursion (25×18 mm), whereas it is limited to 6×2 mm in the gating window. The different motion mitigation strategies were evaluated by comparing the experimental film responses with respect to static irradiation conditions. Dose inhomogeneity (IC) and conformity (CI) are provided as main indexes for dose quality assessment considering the irradiation in static condition as reference. Results: We measured 20.6 ms overall latency for motion signal processing. Dose measurements showed that beam tracking largely preserved dose homogeneity and conformity, showing maximal IC and CI variations limited to +0.10 and −0.01 with respect to the static reference. Gating resulted in slightly larger discrepancies (ΔIC=+0.20, ΔCI=−0.13) due to uncompensated residual motion in the gating window. Conclusions: The preliminary beam tracking and gating results verified the functionality of the prototypal solution for organ motion compensation based on

Real-time optical tracking for motion compensated irradiation with scanned particle beams at CNAO

International Nuclear Information System (INIS)

Fattori, G.; Seregni, M.; Pella, A.; Riboldi, M.; Capasso, L.; Donetti, M.; Ciocca, M.; Giordanengo, S.; Pullia, M.; Marchetto, F.; Baroni, G.

2016-01-01

Purpose: We describe the interface developed at the National Center for Oncological Hadrontherapy in Pavia to provide the dose delivery systems with real time respiratory motion information captured with an optical tracking system. An experimental study is presented to assess the technical feasibility of the implemented organ motion compensation framework, by analyzing the film response when irradiated with proton beams. Methods: The motion monitoring solution is based on a commercial hardware for motion capture running in-house developed software for respiratory signal processing. As part of the integration, the latency of data transmission to the dose delivery system was experimentally quantified and accounted for by signal time prediction. A respiratory breathing phantom is presented and used to test tumor tracking based either on the optical measurement of the target position or internal-external correlation models and beam gating, as driven by external surrogates. Beam tracking was tested considering the full target motion excursion (25×18 mm), whereas it is limited to 6×2 mm in the gating window. The different motion mitigation strategies were evaluated by comparing the experimental film responses with respect to static irradiation conditions. Dose inhomogeneity (IC) and conformity (CI) are provided as main indexes for dose quality assessment considering the irradiation in static condition as reference. Results: We measured 20.6 ms overall latency for motion signal processing. Dose measurements showed that beam tracking largely preserved dose homogeneity and conformity, showing maximal IC and CI variations limited to +0.10 and −0.01 with respect to the static reference. Gating resulted in slightly larger discrepancies (ΔIC=+0.20, ΔCI=−0.13) due to uncompensated residual motion in the gating window. Conclusions: The preliminary beam tracking and gating results verified the functionality of the prototypal solution for organ motion compensation based on

Cooperating the BDS, GPS, GLONASS and strong-motion observations for real-time deformation monitoring

Science.gov (United States)

Tu, Rui; Liu, Jinhai; Lu, Cuixian; Zhang, Rui; Zhang, Pengfei; Lu, Xiaochun

2017-06-01

An approach of cooperating the BDS, GPS, GLONASS and strong-motion (SM) records for real-time deformation monitoring was presented, which was validated by the experimental data. In this approach, the Global Navigation Satellite System (GNSS) data were processed with the real-time kinematic positioning technology to retrieve the GNSS displacement, and the SM data were calibrated to acquire the raw acceleration; a Kalman filter was then applied to combine the GNSS displacement and the SM acceleration to obtain the integrated displacement, velocity and acceleration. The validation results show that the advantages of each sensor are completely complementary. For the SM, the baseline shifts are estimated and corrected, and the high-precision velocity and displacement are recovered. While the noise of GNSS can be reduced by using the SM-derived high-resolution acceleration, thus the high-precision and broad-band deformation information can be obtained in real time. The proposed method indicates a promising potential and capability in deformation monitoring of the high-building, dam, bridge and landslide.

Sparse time-frequency decomposition based on dictionary adaptation.

Science.gov (United States)

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. © 2016 The Author(s).

Sampling-based real-time motion planning under state uncertainty for autonomous micro-aerial vehicles in GPS-denied environments.

Science.gov (United States)

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-11-18

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints.

Real-Time Signal Processing for Multiantenna Systems: Algorithms, Optimization, and Implementation on an Experimental Test-Bed

Directory of Open Access Journals (Sweden)

Haustein Thomas

2006-01-01

Full Text Available A recently realized concept of a reconfigurable hardware test-bed suitable for real-time mobile communication with multiple antennas is presented in this paper. We discuss the reasons and prerequisites for real-time capable MIMO transmission systems which may allow channel adaptive transmission to increase link stability and data throughput. We describe a concept of an efficient implementation of MIMO signal processing using FPGAs and DSPs. We focus on some basic linear and nonlinear MIMO detection and precoding algorithms and their optimization for a DSP target, and a few principal steps for computational performance enhancement are outlined. An experimental verification of several real-time MIMO transmission schemes at high data rates in a typical office scenario is presented and results on the achieved BER and throughput performance are given. The different transmission schemes used either channel state information at both sides of the link or at one side only (transmitter or receiver. Spectral efficiencies of more than 20 bits/s/Hz and a throughput of more than 150 Mbps were shown with a single-carrier transmission. The experimental results clearly show the feasibility of real-time high data rate MIMO techniques with state-of-the-art hardware and that more sophisticated baseband signal processing will be an essential part of future communication systems. A discussion on implementation challenges towards future wireless communication systems supporting higher data rates (1 Gbps and beyond or high mobility concludes the paper.

LabVIEW Real-Time

CERN Multimedia

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

2003-01-01

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

Adaptive motion of animals and machines

National Research Council Canada - National Science Library

Kimura, Hiroshi

2006-01-01

... single function in a control system and mechanism. That is, adaptation in motion is induced at every level from the central nervous system to the musculoskeletal system. Thus, we organized the International Symposium on Adaptive Motion in Animals and Machines (AMAM) for scientists and engineers concerned with adaptation on various levels to be broug...

SU-F-BRCD-06: Multiple Anatomy Optimization of Accumulated Dose.

Science.gov (United States)

Watkins, W T; Moore, J A; Sharma, M; Dial, C; Xu, H; Hugo, G D; Gordon, J J; Siebers, J V

2012-06-01

Multiple anatomy optimization (MAO) utilizing deformable dose accumulation on entire 4DCT data sets is implemented to overcome ambiguity between optimal dose defined on a single anatomy and optimal accumulated dose resulting from dose delivery to moving and deforming anatomy. Six lung cancer patients are planned using two methods of radiotherapy optimization: the internal target volume (ITV) envelope method and MAO, which simultaneously optimizes a single fluence for delivery to all 10 breathing phases such that the accumulated dose satisfies the plan objectives. Target dose is constrained to 70 Gy. The ITV-plan is optimized on a single breathing phase with the planning target volume defined as the ITV; the MAO target is the moving CTV. MAO is compared to single image ITV optimization based on the accumulated dose assuming equal monitor-units to each phase. Dose-volume differences between single image estimations and 10-image accumulation are examined. Single image optimal dose distributions overestimate target V70 by 4.2%±3.1% (average, one standard deviation) and in five of six cases ipsilateral lung V20 is underestimated (1.4%±0.9%). For these five cases, MAO increases V70 by 2.8%±2.5% (maximum of 6% increase in V70) and reduces ipsilateral lung V20 by up to 3% (average decrease of 1.2%±1.3%). Contralateral lung V20, esophagus V25, and heart V30 are also reduced by up to 5%, 3%, and 3%. For the sixth case, lung tumor motion is on the order of the dose voxel size (3mm), and MAO did not improve upon the ITV plan. Dose-volume optimization on a stationary image does not ensure accumulated dose coverage to the moving CTV. Multiple anatomy optimization can remove dose ambiguity and improve plan quality. P01CA11602 and Philips Medical Systems. © 2012 American Association of Physicists in Medicine.

Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2004-01-01

We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2006-01-01

We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Unsupervised markerless 3-DOF motion tracking in real time using a single low-budget camera.

Science.gov (United States)

Quesada, Luis; León, Alejandro J

2012-10-01

Motion tracking is a critical task in many computer vision applications. Existing motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements discourage the wide spread of commercial applications based on motion tracking. In this paper, we present a novel three degrees of freedom motion tracking system that needs no knowledge on the target object and that only requires a single low-budget camera that can be found installed in most computers and smartphones. Our system estimates, in real time, the three-dimensional position of a nonmodeled unmarked object that may be nonrigid, nonconvex, partially occluded, self-occluded, or motion blurred, given that it is opaque, evenly colored, enough contrasting with the background in each frame, and that it does not rotate. Our system is also able to determine the most relevant object to track in the screen. Our proposal does not impose additional constraints, therefore it allows a market-wide implementation of applications that require the estimation of the three position degrees of freedom of an object.

Hard Real-Time Task Scheduling in Cloud Computing Using an Adaptive Genetic Algorithm

Directory of Open Access Journals (Sweden)

Amjad Mahmood

2017-04-01

Full Text Available In the Infrastructure-as-a-Service cloud computing model, virtualized computing resources in the form of virtual machines are provided over the Internet. A user can rent an arbitrary number of computing resources to meet their requirements, making cloud computing an attractive choice for executing real-time tasks. Economical task allocation and scheduling on a set of leased virtual machines is an important problem in the cloud computing environment. This paper proposes a greedy and a genetic algorithm with an adaptive selection of suitable crossover and mutation operations (named as AGA to allocate and schedule real-time tasks with precedence constraint on heterogamous virtual machines. A comprehensive simulation study has been done to evaluate the performance of the proposed algorithms in terms of their solution quality and efficiency. The simulation results show that AGA outperforms the greedy algorithm and non-adaptive genetic algorithm in terms of solution quality.

Real-time aircraft continuous descent trajectory optimization with ATC time constraints using direct collocation methods.

OpenAIRE

Verhoeven, Ronald; Dalmau Codina, Ramon; Prats Menéndez, Xavier; de Gelder, Nico

2014-01-01

1 Abstract In this paper an initial implementation of a real - time aircraft trajectory optimization algorithm is presented . The aircraft trajectory for descent and approach is computed for minimum use of thrust and speed brake in support of a “green” continuous descent and approach flight operation, while complying with ATC time constraints for maintaining runway throughput and co...

Management of threatened abortion with real-time sonography.

Science.gov (United States)

Anderson, S G

1980-02-01

Real-time sonography was used to evaluate 158 patients with threatened abortion. Fetal motion was first detected during the seventh gestational week and with increasing frequency thereafter in 73 patients with viable pregnancies continuing to term. Only 2 of 65 patients who aborted demonstrated fetal motion. The presence or absence of fetal motion was most reliable after 7 weeks' gestation for establishing a prognosis for a given pregnancy. Seventy-two of 74 pregnancies with fetal motion continued to term, whereas 63 of 64 pregnancies without fetal motion aborted. A method for using real-time sonography in the management of threatened abortion is presented.

Biphasic and region-specific MAO-B response to aging in normal human brain.

Science.gov (United States)

Saura, J; Andrés, N; Andrade, C; Ojuel, J; Eriksson, K; Mahy, N

1997-01-01

Variations of monoamine oxidases (MAO) A and B were studied during aging in 27 human subjects (age range 17-93 years) in 18 brain structures of temporal cortex, frontal gyrus, hippocampal formation, striatum, cerebellum, and brainstem. [3H]Ro41-1049 and [3H]lazabemide were used as selective radioligands to image and quantify MAO-A and MAO-B respectively by enzyme autoradiography. Postmortem delay or time of tissue storage did not affect MAO-A or MAO-B levels. There was, moreover, no evidence of sexual dimorphism. A marked age-related increase in MAO-B was observed in most structures. This increase started at the age of 50-60 years. Before this age, MAO-B levels were constant in all structures studied. MAO-B-rich senile plaques were observed in some cortical areas but they did not significantly influence the age-related MAO-B increase. Surprisingly, no age-related MAO-B changes were observed in the substantia nigra. In contrast to MAO-B, no clear age-related changes in MAO-A were observed, indicating an independent regulation of the two isoenzymes, also suggested by the cross-correlation analysis of these data.

Adaptive stimulus optimization for sensory systems neuroscience.

Science.gov (United States)

DiMattina, Christopher; Zhang, Kechen

2013-01-01

In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

Real-time simulation requirements for study and optimization of power system controls

Energy Technology Data Exchange (ETDEWEB)

Nakra, Harbans; McCallum, David; Gagnon, Charles [Institut de Recherche d` Hydro-Quebec, Quebec, PQ (Canada); Venne, Andre; Gagnon, Julien [Hydro-Quebec, Montreal, PQ (Canada)

1994-12-31

At the time of ordering for the multi-terminal dc system linking Hydro-Quebec with New England, Hydro-Quebec also ordered functionally duplicate controls of all the converters and installed these in its real time simulation laboratory. The Hydro-Quebec ac system was also simulated in detail and the testing of the controls as thus made possible in a realistic environment. Many field tests were duplicated and many additional tests were done for correction and optimization. This paper describes some of the features of the real-time simulation carried out for this purpose. (author) 3 figs.

Dynamic ADMM for Real-time Optimal Power Flow: Preprint

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-02-23

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.

A novel patterning control strategy based on real-time fingerprint recognition and adaptive wafer level scanner optimization

Science.gov (United States)

Cekli, Hakki Ergun; Nije, Jelle; Ypma, Alexander; Bastani, Vahid; Sonntag, Dag; Niesing, Henk; Zhang, Linmiao; Ullah, Zakir; Subramony, Venky; Somasundaram, Ravin; Susanto, William; Matsunobu, Masazumi; Johnson, Jeff; Tabery, Cyrus; Lin, Chenxi; Zou, Yi

2018-03-01

In addition to lithography process and equipment induced variations, processes like etching, annealing, film deposition and planarization exhibit variations, each having their own intrinsic characteristics and leaving an effect, a `fingerprint', on the wafers. With ever tighter requirements for CD and overlay, controlling these process induced variations is both increasingly important and increasingly challenging in advanced integrated circuit (IC) manufacturing. For example, the on-product overlay (OPO) requirement for future nodes is approaching process induced variance to become extremely small. Process variance control is seen as an bottleneck to further shrink which drives the need for more sophisticated process control strategies. In this context we developed a novel `computational process control strategy' which provides the capability of proactive control of each individual wafer with aim to maximize the yield, without introducing a significant impact on metrology requirements, cycle time or productivity. The complexity of the wafer process is approached by characterizing the full wafer stack building a fingerprint library containing key patterning performance parameters like Overlay, Focus, etc. Historical wafer metrology is decomposed into dominant fingerprints using Principal Component Analysis. By associating observed fingerprints with their origin e.g. process steps, tools and variables, we can give an inline assessment of the strength and origin of the fingerprints on every wafer. Once the fingerprint library is established, a wafer specific fingerprint correction recipes can be determined based on its processing history. Data science techniques are used in real-time to ensure that the library is adaptive. To realize this concept, ASML TWINSCAN scanners play a vital role with their on-board full wafer detection and exposure correction capabilities. High density metrology data is created by the scanner for each wafer and on every layer during the

System-on-chip architecture and validation for real-time transceiver optimization: APC implementation on FPGA

Science.gov (United States)

Suarez, Hernan; Zhang, Yan R.

2015-05-01

New radar applications need to perform complex algorithms and process large quantity of data to generate useful information for the users. This situation has motivated the search for better processing solutions that include low power high-performance processors, efficient algorithms, and high-speed interfaces. In this work, hardware implementation of adaptive pulse compression for real-time transceiver optimization are presented, they are based on a System-on-Chip architecture for Xilinx devices. This study also evaluates the performance of dedicated coprocessor as hardware accelerator units to speed up and improve the computation of computing-intensive tasks such matrix multiplication and matrix inversion which are essential units to solve the covariance matrix. The tradeoffs between latency and hardware utilization are also presented. Moreover, the system architecture takes advantage of the embedded processor, which is interconnected with the logic resources through the high performance AXI buses, to perform floating-point operations, control the processing blocks, and communicate with external PC through a customized software interface. The overall system functionality is demonstrated and tested for real-time operations using a Ku-band tested together with a low-cost channel emulator for different types of waveforms.

Real-time high dynamic range laser scanning microscopy

Science.gov (United States)

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-04-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Adaptive Bacterial Foraging Optimization

Directory of Open Access Journals (Sweden)

Hanning Chen

2011-01-01

Full Text Available Bacterial Foraging Optimization (BFO is a recently developed nature-inspired optimization algorithm, which is based on the foraging behavior of E. coli bacteria. Up to now, BFO has been applied successfully to some engineering problems due to its simplicity and ease of implementation. However, BFO possesses a poor convergence behavior over complex optimization problems as compared to other nature-inspired optimization techniques. This paper first analyzes how the run-length unit parameter of BFO controls the exploration of the whole search space and the exploitation of the promising areas. Then it presents a variation on the original BFO, called the adaptive bacterial foraging optimization (ABFO, employing the adaptive foraging strategies to improve the performance of the original BFO. This improvement is achieved by enabling the bacterial foraging algorithm to adjust the run-length unit parameter dynamically during algorithm execution in order to balance the exploration/exploitation tradeoff. The experiments compare the performance of two versions of ABFO with the original BFO, the standard particle swarm optimization (PSO and a real-coded genetic algorithm (GA on four widely-used benchmark functions. The proposed ABFO shows a marked improvement in performance over the original BFO and appears to be comparable with the PSO and GA.

Real-time Terrain Rendering using Smooth Hardware Optimized Level of Detail

DEFF Research Database (Denmark)

Larsen, Bent Dalgaard; Christensen, Niels Jørgen

2003-01-01

We present a method for real-time level of detail reduction that is able to display high-complexity polygonal surface data. A compact and efficient regular grid representation is used. The method is optimized for modern, low-end consumer 3D graphics cards. We avoid sudden changes of the geometry...

The preparation and corrosion behaviors of MAO coating on AZ91D with rare earth conversion precursor film

Energy Technology Data Exchange (ETDEWEB)

Cai Jingshun [Department of Chemistry, Zhejiang University, Zheda Road 38, Hangzhou, Zhejiang 310027 (China); Cao Fahe, E-mail: nelson_cao@zju.edu.cn [Department of Chemistry, Zhejiang University, Zheda Road 38, Hangzhou, Zhejiang 310027 (China); Chang Linrong; Zheng Junjun [Department of Chemistry, Zhejiang University, Zheda Road 38, Hangzhou, Zhejiang 310027 (China); Zhang Jianqing; Cao Chunan [Department of Chemistry, Zhejiang University, Zheda Road 38, Hangzhou, Zhejiang 310027 (China); State Key Laboratory for Corrosion and Protection, Institute of Metal Research, The Chinese Academy of Sciences, Shenyang 110016 (China)

2011-02-01

A novel kind of micro-arc oxidation (MAO) coating was prepared on magnesium alloy surface coated with rare earth conversion film (RE-film) in an alkaline aluminum oxidation electrolyte by AC power source. Inspection of scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared (FTIR) microspectroscopy, the structure and composition of MAO coating formed on AZ91D with RE-film under different applied voltages were investigated and the performance of the optimized MAO coating compared with the MAO coating directly formed on magnesium alloy. As the pretreatment of magnesium alloy with RE-film, the cerium oxides can be incorporated into the MAO coatings, reduce porosity of the MAO coating surface and enhance the thickness of MAO coating. These structure features and the cerium oxides incorporated into the MAO coating result in greatly improved corrosion resistance. Base on electrochemistry impedance spectroscopy (EIS) measurement, the electronic structure and composition analysis of the MAO coating, a double-layer structure, with a compact inner layer and a porous outer layer, of the coating was proposed for understanding its corrosion process.

The preparation and corrosion behaviors of MAO coating on AZ91D with rare earth conversion precursor film

International Nuclear Information System (INIS)

Cai Jingshun; Cao Fahe; Chang Linrong; Zheng Junjun; Zhang Jianqing; Cao Chunan

2011-01-01

A novel kind of micro-arc oxidation (MAO) coating was prepared on magnesium alloy surface coated with rare earth conversion film (RE-film) in an alkaline aluminum oxidation electrolyte by AC power source. Inspection of scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared (FTIR) microspectroscopy, the structure and composition of MAO coating formed on AZ91D with RE-film under different applied voltages were investigated and the performance of the optimized MAO coating compared with the MAO coating directly formed on magnesium alloy. As the pretreatment of magnesium alloy with RE-film, the cerium oxides can be incorporated into the MAO coatings, reduce porosity of the MAO coating surface and enhance the thickness of MAO coating. These structure features and the cerium oxides incorporated into the MAO coating result in greatly improved corrosion resistance. Base on electrochemistry impedance spectroscopy (EIS) measurement, the electronic structure and composition analysis of the MAO coating, a double-layer structure, with a compact inner layer and a porous outer layer, of the coating was proposed for understanding its corrosion process.

Robust Optimal Adaptive Control Method with Large Adaptive Gain

Science.gov (United States)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Real-time 2D/3D registration using kV-MV image pairs for tumor motion tracking in image guided radiotherapy.

Science.gov (United States)

Furtado, Hugo; Steiner, Elisabeth; Stock, Markus; Georg, Dietmar; Birkfellner, Wolfgang

2013-10-01

Intra-fractional respiratory motion during radiotherapy leads to a larger planning target volume (PTV). Real-time tumor motion tracking by two-dimensional (2D)/3D registration using on-board kilo-voltage (kV) imaging can allow for a reduction of the PTV though motion along the imaging beam axis cannot be resolved using only one projection image. We present a retrospective patient study investigating the impact of paired portal mega-voltage (MV) and kV images on registration accuracy. Material and methods. We used data from 10 patients suffering from non-small cell lung cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) lung treatment. For each patient we acquired a planning computed tomography (CT) and sequences of kV and MV images during treatment. We compared the accuracy of motion tracking in six degrees-of-freedom (DOF) using the anterior-posterior (AP) kV sequence or the sequence of kV-MV image pairs. Results. Motion along cranial-caudal direction could accurately be extracted when using only the kV sequence but in AP direction we obtained large errors. When using kV-MV pairs, the average error was reduced from 2.9 mm to 1.5 mm and the motion along AP was successfully extracted. Mean registration time was 188 ms. Conclusion. Our evaluation shows that using kV-MV image pairs leads to improved motion extraction in six DOF and is suitable for real-time tumor motion tracking with a conventional LINAC.

Real-time ultrasound-tagging to track the 2D motion of the common carotid artery wall in vivo

Energy Technology Data Exchange (ETDEWEB)

Zahnd, Guillaume, E-mail: g.zahnd@erasmusmc.nl [Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam 3000 CA (Netherlands); Salles, Sébastien; Liebgott, Hervé; Vray, Didier [Université de Lyon, CREATIS, CNRS UMR 5220, INSERM U1044, INSA-Lyon, Université Lyon 1, Lyon 69100 (France); Sérusclat, André [Department of Radiology, Louis Pradel Hospital, Lyon 69500 (France); Moulin, Philippe [Department of Endocrinology, Louis Pradel Hospital, Hospices Civils de Lyon, Université Lyon 1, Lyon 69100, France and INSERM UMR 1060, Lyon 69500 (France)

2015-02-15

Purpose: Tracking the motion of biological tissues represents an important issue in the field of medical ultrasound imaging. However, the longitudinal component of the motion (i.e., perpendicular to the beam axis) remains more challenging to extract due to the rather coarse resolution cell of ultrasound scanners along this direction. The aim of this study is to introduce a real-time beamforming strategy dedicated to acquire tagged images featuring a distinct pattern in the objective to ease the tracking. Methods: Under the conditions of the Fraunhofer approximation, a specific apodization function was applied to the received raw channel data, in real-time during image acquisition, in order to introduce a periodic oscillations pattern along the longitudinal direction of the radio frequency signal. Analytic signals were then extracted from the tagged images, and subpixel motion tracking of the intima–media complex was subsequently performed offline, by means of a previously introduced bidimensional analytic phase-based estimator. Results: The authors’ framework was applied in vivo on the common carotid artery from 20 young healthy volunteers and 6 elderly patients with high atherosclerosis risk. Cine-loops of tagged images were acquired during three cardiac cycles. Evaluated against reference trajectories manually generated by three experienced analysts, the mean absolute tracking error was 98 ± 84 μm and 55 ± 44 μm in the longitudinal and axial directions, respectively. These errors corresponded to 28% ± 23% and 13% ± 9% of the longitudinal and axial amplitude of the assessed motion, respectively. Conclusions: The proposed framework enables tagged ultrasound images of in vivo tissues to be acquired in real-time. Such unconventional beamforming strategy contributes to improve tracking accuracy and could potentially benefit to the interpretation and diagnosis of biomedical images.

"Real-time" disintegration analysis and D-optimal experimental design for the optimization of diclofenac sodium fast-dissolving films.

Science.gov (United States)

El-Malah, Yasser; Nazzal, Sami

2013-01-01

The objective of this work was to study the dissolution and mechanical properties of fast-dissolving films prepared from a tertiary mixture of pullulan, polyvinylpyrrolidone and hypromellose. Disintegration studies were performed in real-time by probe spectroscopy to detect the onset of film disintegration. Tensile strength and elastic modulus of the films were measured by texture analysis. Disintegration time of the films ranged from 21 to 105 seconds whereas their mechanical properties ranged from approximately 2 to 49 MPa for tensile strength and 1 to 21 MPa% for young's modulus. After generating polynomial models correlating the variables using a D-Optimal mixture design, an optimal formulation with desired responses was proposed by the statistical package. For validation, a new film formulation loaded with diclofenac sodium based on the optimized composition was prepared and tested for dissolution and tensile strength. Dissolution of the optimized film was found to commence almost immediately with 50% of the drug released within one minute. Tensile strength and young's modulus of the film were 11.21 MPa and 6, 78 MPa%, respectively. Real-time spectroscopy in conjunction with statistical design were shown to be very efficient for the optimization and development of non-conventional intraoral delivery system such as fast dissolving films.

Evaluation of adaptation to visually induced motion sickness based on the maximum cross-correlation between pulse transmission time and heart rate

Directory of Open Access Journals (Sweden)

Chiba Shigeru

2007-09-01

Full Text Available Abstract Background Computer graphics and virtual reality techniques are useful to develop automatic and effective rehabilitation systems. However, a kind of virtual environment including unstable visual images presented to wide field screen or a head mounted display tends to induce motion sickness. The motion sickness induced in using a rehabilitation system not only inhibits effective training but also may harm patients' health. There are few studies that have objectively evaluated the effects of the repetitive exposures to these stimuli on humans. The purpose of this study is to investigate the adaptation to visually induced motion sickness by physiological data. Methods An experiment was carried out in which the same video image was presented to human subjects three times. We evaluated changes of the intensity of motion sickness they suffered from by a subjective score and the physiological index ρmax, which is defined as the maximum cross-correlation coefficient between heart rate and pulse wave transmission time and is considered to reflect the autonomic nervous activity. Results The results showed adaptation to visually-induced motion sickness by the repetitive presentation of the same image both in the subjective and the objective indices. However, there were some subjects whose intensity of sickness increased. Thus, it was possible to know the part in the video image which related to motion sickness by analyzing changes in ρmax with time. Conclusion The physiological index, ρmax, will be a good index for assessing the adaptation process to visually induced motion sickness and may be useful in checking the safety of rehabilitation systems with new image technologies.

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...

Optimal transcostal high-intensity focused ultrasound with combined real-time 3D movement tracking and correction

International Nuclear Information System (INIS)

Marquet, F; Aubry, J F; Pernot, M; Fink, M; Tanter, M

2011-01-01

Recent studies have demonstrated the feasibility of transcostal high intensity focused ultrasound (HIFU) treatment in liver. However, two factors limit thermal necrosis of the liver through the ribs: the energy deposition at focus is decreased by the respiratory movement of the liver and the energy deposition on the skin is increased by the presence of highly absorbing bone structures. Ex vivo ablations were conducted to validate the feasibility of a transcostal real-time 3D movement tracking and correction mode. Experiments were conducted through a chest phantom made of three human ribs immersed in water and were placed in front of a 300 element array working at 1 MHz. A binarized apodization law introduced recently in order to spare the rib cage during treatment has been extended here with real-time electronic steering of the beam. Thermal simulations have been conducted to determine the steering limits. In vivo 3D-movement detection was performed on pigs using an ultrasonic sequence. The maximum error on the transcostal motion detection was measured to be 0.09 ± 0.097 mm on the anterior–posterior axis. Finally, a complete sequence was developed combining real-time 3D transcostal movement correction and spiral trajectory of the HIFU beam, allowing the system to treat larger areas with optimized efficiency. Lesions as large as 1 cm in diameter have been produced at focus in excised liver, whereas no necroses could be obtained with the same emitted power without correcting the movement of the tissue sample.

Optimal moving grids for time-dependent partial differential equations

Science.gov (United States)

Wathen, A. J.

1992-01-01

Various adaptive moving grid techniques for the numerical solution of time-dependent partial differential equations were proposed. The precise criterion for grid motion varies, but most techniques will attempt to give grids on which the solution of the partial differential equation can be well represented. Moving grids are investigated on which the solutions of the linear heat conduction and viscous Burgers' equation in one space dimension are optimally approximated. Precisely, the results of numerical calculations of optimal moving grids for piecewise linear finite element approximation of PDE solutions in the least-squares norm are reported.

Complexity reduction in the H.264/AVC using highly adaptive fast mode decision based on macroblock motion activity

Science.gov (United States)

Abdellah, Skoudarli; Mokhtar, Nibouche; Amina, Serir

2015-11-01

The H.264/AVC video coding standard is used in a wide range of applications from video conferencing to high-definition television according to its high compression efficiency. This efficiency is mainly acquired from the newly allowed prediction schemes including variable block modes. However, these schemes require a high complexity to select the optimal mode. Consequently, complexity reduction in the H.264/AVC encoder has recently become a very challenging task in the video compression domain, especially when implementing the encoder in real-time applications. Fast mode decision algorithms play an important role in reducing the overall complexity of the encoder. In this paper, we propose an adaptive fast intermode algorithm based on motion activity, temporal stationarity, and spatial homogeneity. This algorithm predicts the motion activity of the current macroblock from its neighboring blocks and identifies temporal stationary regions and spatially homogeneous regions using adaptive threshold values based on content video features. Extensive experimental work has been done in high profile, and results show that the proposed source-coding algorithm effectively reduces the computational complexity by 53.18% on average compared with the reference software encoder, while maintaining the high-coding efficiency of H.264/AVC by incurring only 0.097 dB in total peak signal-to-noise ratio and 0.228% increment on the total bit rate.

Molecular insights into human monoamine oxidase (MAO) inhibition by 1,4-naphthoquinone: evidences for menadione (vitamin K3) acting as a competitive and reversible inhibitor of MAO.

Science.gov (United States)

Coelho Cerqueira, Eduardo; Netz, Paulo Augusto; Diniz, Cristiane; Petry do Canto, Vanessa; Follmer, Cristian

2011-12-15

Monoamine oxidase (MAO) catalyzes the oxidative deamination of biogenic and exogenous amines and its inhibitors have therapeutic value for several conditions including affective disorders, stroke, neurodegenerative diseases and aging. The discovery of 2,3,6-trimethyl-1,4-naphthoquinone (TMN) as a nonselective and reversible inhibitor of MAO, has suggested 1,4-naphthoquinone (1,4-NQ) as a potential scaffold for designing new MAO inhibitors. Combining molecular modeling tools and biochemical assays we evaluate the kinetic and molecular details of the inhibition of human MAO by 1,4-NQ, comparing it with TMN and menadione. Menadione (2-methyl-1,4-naphthoquinone) is a multitarget drug that acts as a precursor of vitamin K and an inducer of mitochondrial permeability transition. Herein we show that MAO-B was inhibited competitively by 1,4-NQ (K(i)=1.4 μM) whereas MAO-A was inhibited by non-competitive mechanism (K(i)=7.7 μM). Contrasting with TMN and 1,4-NQ, menadione exhibited a 60-fold selectivity for MAO-B (K(i)=0.4 μM) in comparison with MAO-A (K(i)=26 μM), which makes it as selective as rasagiline. Fluorescence and molecular modeling data indicated that these inhibitors interact with the flavin moiety at the active site of the enzyme. Additionally, docking studies suggest the phenyl side groups of Tyr407 and Tyr444 (for MAO-A) or Tyr398 and Tyr435 (for MAO-B) play an important role in the interaction of the enzyme with 1,4-NQ scaffold through forces of dispersion as verified for menadione, TMN and 1,4-NQ. Taken together, our findings reveal the molecular details of MAO inhibition by 1,4-NQ scaffold and show for the first time that menadione acts as a competitive and reversible inhibitor of human MAO. Copyright © 2011 Elsevier Ltd. All rights reserved.

Adaptive real-time models of vehicle dynamics; Adaptive Echtzeitmodelle fuer die Kraftfahrzeugdynamik

Energy Technology Data Exchange (ETDEWEB)

Halfmann, C.; Holzmann, H.; Isermann, R. [Technische Univ. Darmstadt (Germany). Inst. fuer Automatisierungstechnik; Hamann, C.D.; Simm, N. [Opel (A.) AG, Ruesselsheim (Germany). Gruppe Chassis und Fahrerassistenzsysteme

1999-12-01

The application of modern simulation tools offering additional support during the vehicle development process is accepted to a large extent by most car manufacturers. Just like new model-based control strategies, these simulation investigations require very accurate - and thus very complex - models of vehicle dynamics, which can be processed in real time. As an example of such a vehicle model, this article describes a real-time vehicle simulation model which was developed at the Institute of Automatic Control at Darmstadt University of Technology, in co-operation with the ITDC of the Adam OPEL AG. By applying modern adaptation techniques, this vehicle model is able to calculate onboard the important variables describing the actual driving state even if the environmental conditions change. (orig.) [German] Der Einsatz von Simulationswerkzeugen zur Unterstuetzung der Fahrzeugentwicklung hat sich bei den meisten Automobilherstellern weitgehend durchgesetzt. Ebenso wie neuartige modellbasierte Regelstrategien verlangen diese Simulationsuntersuchungen nach immer exakteren - und damit komplexeren - fahrdynamischen Modellen, die in Echtzeit ausgewertet werden. Als Beispiel fuer ein solches Gesamtfahrzeugmodell beschreibt dieser Beitrag ein echtzeitfaehiges Modell fuer die Bewegung des Fahrzeugs um alle drei Hauptachsen, das am Institut fuer Automatisierungstechnik der TU Darmstadt in Kooperation mit dem Internationalen Technischen Entwicklungszentrum (ITEZ) der Adam Opel AG entwickelt wurde. Es ist durch den Einsatz von Adaptionsmethoden in der Lage, wichtige fahrdynamische Zustandsgroessen im Fahrzeug auch unter veraenderlichen Umgebungsbedingungen zu ermitteln. (orig.)

Recension: Mao - The Unknown Story

DEFF Research Database (Denmark)

Clausen, Søren

2005-01-01

Anmeldelse - kritisk! - til Sveriges førende Kinatidsskrift af Jung Chang & Jon Halliday's sensationelle "Mao - the Unknown Story".......Anmeldelse - kritisk! - til Sveriges førende Kinatidsskrift af Jung Chang & Jon Halliday's sensationelle "Mao - the Unknown Story"....

Update on the pharmacology of selective inhibitors of MAO-A and MAO-B: focus on modulation of CNS monoamine neurotransmitter release.

Science.gov (United States)

Finberg, John P M

2014-08-01

Inhibitors of monoamine oxidase (MAO) were initially used in medicine following the discovery of their antidepressant action. Subsequently their ability to potentiate the effects of an indirectly-acting sympathomimetic amine such as tyramine was discovered, leading to their limitation in clinical use, except for cases of treatment-resistant depression. More recently, the understanding that: a) potentiation of indirectly-acting sympathomimetic amines is caused by inhibitors of MAO-A but not by inhibitors of MAO-B, and b) that reversible inhibitors of MAO-A cause minimal tyramine potentiation, has led to their re-introduction to clinical use for treatment of depression (reversible MAO-A inhibitors and new dose form MAO-B inhibitor) and treatment of Parkinson's disease (MAO-B inhibitors). The profound neuroprotective properties of propargyl-based inhibitors of MAO-B in preclinical experiments have drawn attention to the possibility of employing these drugs for their neuroprotective effect in neurodegenerative diseases, and have raised the question of the involvement of the MAO-mediated reaction as a source of reactive free radicals. Despite the long-standing history of MAO inhibitors in medicine, the way in which they affect neuronal release of monoamine neurotransmitters is still poorly understood. In recent years, the detailed chemical structure of MAO-B and MAO-A has become available, providing new possibilities for synthesis of mechanism-based inhibitors. This review describes the latest advances in understanding the way in which MAO inhibitors affect the release of the monoamine neurotransmitters dopamine, noradrenaline and serotonin (5-HT) in the CNS, with an accent on the importance of these effects for the clinical actions of the drugs. Copyright © 2014 Elsevier Inc. All rights reserved.

Real-time animation software for customized training to use motor prosthetic systems.

Science.gov (United States)

Davoodi, Rahman; Loeb, Gerald E

2012-03-01

Research on control of human movement and development of tools for restoration and rehabilitation of movement after spinal cord injury and amputation can benefit greatly from software tools for creating precisely timed animation sequences of human movement. Despite their ability to create sophisticated animation and high quality rendering, existing animation software are not adapted for application to neural prostheses and rehabilitation of human movement. We have developed a software tool known as MSMS (MusculoSkeletal Modeling Software) that can be used to develop models of human or prosthetic limbs and the objects with which they interact and to animate their movement using motion data from a variety of offline and online sources. The motion data can be read from a motion file containing synthesized motion data or recordings from a motion capture system. Alternatively, motion data can be streamed online from a real-time motion capture system, a physics-based simulation program, or any program that can produce real-time motion data. Further, animation sequences of daily life activities can be constructed using the intuitive user interface of Microsoft's PowerPoint software. The latter allows expert and nonexpert users alike to assemble primitive movements into a complex motion sequence with precise timing by simply arranging the order of the slides and editing their properties in PowerPoint. The resulting motion sequence can be played back in an open-loop manner for demonstration and training or in closed-loop virtual reality environments where the timing and speed of animation depends on user inputs. These versatile animation utilities can be used in any application that requires precisely timed animations but they are particularly suited for research and rehabilitation of movement disorders. MSMS's modeling and animation tools are routinely used in a number of research laboratories around the country to study the control of movement and to develop and test

A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

Directory of Open Access Journals (Sweden)

He-Yuan Lin

2008-03-01

Full Text Available A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

Directory of Open Access Journals (Sweden)

Li Hsin-Te

2008-01-01

Full Text Available Abstract A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

ADAPTIVE BACKGROUND DENGAN METODE GAUSSIAN MIXTURE MODELS UNTUK REAL-TIME TRACKING

Directory of Open Access Journals (Sweden)

Silvia Rostianingsih

2008-01-01

Full Text Available Nowadays, motion tracking application is widely used for many purposes, such as detecting traffic jam and counting how many people enter a supermarket or a mall. A method to separate background and the tracked object is required for motion tracking. It will not be hard to develop the application if the tracking is performed on a static background, but it will be difficult if the tracked object is at a place with a non-static background, because the changing part of the background can be recognized as a tracking area. In order to handle the problem an application can be made to separate background where that separation can adapt to change that occur. This application is made to produce adaptive background using Gaussian Mixture Models (GMM as its method. GMM method clustered the input pixel data with pixel color value as it’s basic. After the cluster formed, dominant distributions are choosen as background distributions. This application is made by using Microsoft Visual C 6.0. The result of this research shows that GMM algorithm could made adaptive background satisfactory. This proofed by the result of the tests that succeed at all condition given. This application can be developed so the tracking process integrated in adaptive background maker process. Abstract in Bahasa Indonesia : Saat ini, aplikasi motion tracking digunakan secara luas untuk banyak tujuan, seperti mendeteksi kemacetan dan menghitung berapa banyak orang yang masuk ke sebuah supermarket atau sebuah mall. Sebuah metode untuk memisahkan antara background dan obyek yang di-track dibutuhkan untuk melakukan motion tracking. Membuat aplikasi tracking pada background yang statis bukanlah hal yang sulit, namun apabila tracking dilakukan pada background yang tidak statis akan lebih sulit, dikarenakan perubahan background dapat dikenali sebagai area tracking. Untuk mengatasi masalah tersebut, dapat dibuat suatu aplikasi untuk memisahkan background dimana aplikasi tersebut dapat

An adaptive dual-optimal path-planning technique for unmanned air vehicles

Directory of Open Access Journals (Sweden)

Whitfield Clifford A.

2016-01-01

Full Text Available A multi-objective technique for unmanned air vehicle path-planning generation through task allocation has been developed. The dual-optimal path-planning technique generates real-time adaptive flight paths based on available flight windows and environmental influenced objectives. The environmentally-influenced flight condition determines the aircraft optimal orientation within a downstream virtual window of possible vehicle destinations that is based on the vehicle’s kinematics. The intermittent results are then pursued by a dynamic optimization technique to determine the flight path. This path-planning technique is a multi-objective optimization procedure consisting of two goals that do not require additional information to combine the conflicting objectives into a single-objective. The technique was applied to solar-regenerative high altitude long endurance flight which can benefit significantly from an adaptive real-time path-planning technique. The objectives were to determine the minimum power required flight paths while maintaining maximum solar power for continual surveillance over an area of interest (AOI. The simulated path generation technique prolonged the flight duration over a sustained turn loiter flight path by approximately 2 months for a year of flight. The potential for prolonged solar powered flight was consistent for all latitude locations, including 2 months of available flight at 60° latitude, where sustained turn flight was no longer capable.

Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model.

Directory of Open Access Journals (Sweden)

Chantal Nguyen

Full Text Available Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.

Impact of optimal load response to real-time electricity price on power system constraints in Denmark

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

2010-01-01

Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift their loads from high price periods to the low price periods in order to save their energy costs. The optimal load response to a real-time electricity price...... and may represent the future of electricity markets in some ways, is chosen as the studied power system in this paper. A distribution system where wind power capacity is 126% of maximum loads is chosen as the study case. This paper presents a nonlinear load optimization method to real-time power price...... for demand side management in order to save the energy costs as much as possible. Simulation results show that the optimal load response to a real-time electricity price has some good impacts on power system constraints in a distribution system with high wind power penetrations....

Real-time sonography in obstetrics.

Science.gov (United States)

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.

Optimization of motion control laws for tether crawler or elevator systems

Science.gov (United States)

Swenson, Frank R.; Von Tiesenhausen, Georg

1988-01-01

Based on the proposal of a motion control law by Lorenzini (1987), a method is developed for optimizing motion control laws for tether crawler or elevator systems in terms of the performance measures of travel time, the smoothness of acceleration and deceleration, and the maximum values of velocity and acceleration. The Lorenzini motion control law, based on powers of the hyperbolic tangent function, is modified by the addition of a constant-velocity section, and this modified function is then optimized by parameter selections to minimize the peak acceleration value for a selected travel time or to minimize travel time for the selected peak values of velocity and acceleration. It is shown that the addition of a constant-velocity segment permits further optimization of the motion control law performance.

A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion

International Nuclear Information System (INIS)

Min Yugang; Santhanam, Anand; Ruddy, Bari H; Neelakkantan, Harini; Meeks, Sanford L; Kupelian, Patrick A

2010-01-01

In this paper, we present a graphics processing unit (GPU)-based simulation framework to calculate the delivered dose to a 3D moving lung tumor and its surrounding normal tissues, which are undergoing subject-specific lung deformations. The GPU-based simulation framework models the motion of the 3D volumetric lung tumor and its surrounding tissues, simulates the dose delivery using the dose extracted from a treatment plan using Pinnacle Treatment Planning System, Phillips, for one of the 3DCTs of the 4DCT and predicts the amount and location of radiation doses deposited inside the lung. The 4DCT lung datasets were registered with each other using a modified optical flow algorithm. The motion of the tumor and the motion of the surrounding tissues were simulated by measuring the changes in lung volume during the radiotherapy treatment using spirometry. The real-time dose delivered to the tumor for each beam is generated by summing the dose delivered to the target volume at each increase in lung volume during the beam delivery time period. The simulation results showed the real-time capability of the framework at 20 discrete tumor motion steps per breath, which is higher than the number of 4DCT steps (approximately 12) reconstructed during multiple breathing cycles.

A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion

Energy Technology Data Exchange (ETDEWEB)

Min Yugang; Santhanam, Anand; Ruddy, Bari H [University of Central Florida, FL (United States); Neelakkantan, Harini; Meeks, Sanford L [M D Anderson Cancer Center Orlando, FL (United States); Kupelian, Patrick A, E-mail: anand.santhanam@orlandohealth.co [Department of Radiation Oncology, University of California, Los Angeles, CA (United States)

2010-09-07

In this paper, we present a graphics processing unit (GPU)-based simulation framework to calculate the delivered dose to a 3D moving lung tumor and its surrounding normal tissues, which are undergoing subject-specific lung deformations. The GPU-based simulation framework models the motion of the 3D volumetric lung tumor and its surrounding tissues, simulates the dose delivery using the dose extracted from a treatment plan using Pinnacle Treatment Planning System, Phillips, for one of the 3DCTs of the 4DCT and predicts the amount and location of radiation doses deposited inside the lung. The 4DCT lung datasets were registered with each other using a modified optical flow algorithm. The motion of the tumor and the motion of the surrounding tissues were simulated by measuring the changes in lung volume during the radiotherapy treatment using spirometry. The real-time dose delivered to the tumor for each beam is generated by summing the dose delivered to the target volume at each increase in lung volume during the beam delivery time period. The simulation results showed the real-time capability of the framework at 20 discrete tumor motion steps per breath, which is higher than the number of 4DCT steps (approximately 12) reconstructed during multiple breathing cycles.

A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject-specific lung tumor motion.

Science.gov (United States)

Min, Yugang; Santhanam, Anand; Neelakkantan, Harini; Ruddy, Bari H; Meeks, Sanford L; Kupelian, Patrick A

2010-09-07

In this paper, we present a graphics processing unit (GPU)-based simulation framework to calculate the delivered dose to a 3D moving lung tumor and its surrounding normal tissues, which are undergoing subject-specific lung deformations. The GPU-based simulation framework models the motion of the 3D volumetric lung tumor and its surrounding tissues, simulates the dose delivery using the dose extracted from a treatment plan using Pinnacle Treatment Planning System, Phillips, for one of the 3DCTs of the 4DCT and predicts the amount and location of radiation doses deposited inside the lung. The 4DCT lung datasets were registered with each other using a modified optical flow algorithm. The motion of the tumor and the motion of the surrounding tissues were simulated by measuring the changes in lung volume during the radiotherapy treatment using spirometry. The real-time dose delivered to the tumor for each beam is generated by summing the dose delivered to the target volume at each increase in lung volume during the beam delivery time period. The simulation results showed the real-time capability of the framework at 20 discrete tumor motion steps per breath, which is higher than the number of 4DCT steps (approximately 12) reconstructed during multiple breathing cycles.

Time-optimal control of nuclear reactor power with adaptive proportional- integral-feedforward gains

International Nuclear Information System (INIS)

Park, Moon Ghu; Cho, Nam Zin

1993-01-01

A time-optimal control method which consists of coarse and fine control stages is described here. During the coarse control stage, the maximum control effort (time-optimal) is used to direct the system toward the switching boundary which is set near the desired power level. At this boundary, the controller is switched to the fine control stage in which an adaptive proportional-integral-feedforward (PIF) controller is used to compensate for any unmodeled reactivity feedback effects. This fine control is also introduced to obtain a constructive method for determining the (adaptive) feedback gains against the sampling effect. The feedforward control term is included to suppress the over-or undershoot. The estimation and feedback of the temperature-induced reactivity is also discussed

Noncontact optical motion sensing for real-time analysis

Science.gov (United States)

Fetzer, Bradley R.; Imai, Hiromichi

1990-08-01

The adaptation of an image dissector tube (IDT) within the OPTFOLLOW system provides high resolution displacement measurement of a light discontinuity. Due to the high speed response of the IDT and the advanced servo loop circuitry, the system is capable of real time analysis of the object under test. The image of the discontinuity may be contoured by direct or reflected light and ranges spectrally within the field of visible light. The image is monitored to 500 kHz through a lens configuration which transposes the optical image upon the photocathode of the IDT. The photoelectric effect accelerates the resultant electrons through a photomultiplier and an enhanced current is emitted from the anode. A servo loop controls the electron beam, continually centering it within the IDT using magnetic focusing of deflection coils. The output analog voltage from the servo amplifier is thereby proportional to the displacement of the target. The system is controlled by a microprocessor with a 32kbyte memory and provides a digital display as well as instructional readout on a color monitor allowing for offset image tracking and automatic system calibration.

Development of real-time motion capture system for 3D on-line games linked with virtual character

Science.gov (United States)

Kim, Jong Hyeong; Ryu, Young Kee; Cho, Hyung Suck

2004-10-01

Motion tracking method is being issued as essential part of the entertainment, medical, sports, education and industry with the development of 3-D virtual reality. Virtual human character in the digital animation and game application has been controlled by interfacing devices; mouse, joysticks, midi-slider, and so on. Those devices could not enable virtual human character to move smoothly and naturally. Furthermore, high-end human motion capture systems in commercial market are expensive and complicated. In this paper, we proposed a practical and fast motion capturing system consisting of optic sensors, and linked the data with 3-D game character with real time. The prototype experiment setup is successfully applied to a boxing game which requires very fast movement of human character.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

Science.gov (United States)

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

2018-02-01

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Applications of an alternative formulation for one-layer real time optimization

Directory of Open Access Journals (Sweden)

Schiavon Júnior A.L.

2000-01-01

Full Text Available This paper presents two applications of an alternative formulation for one-layer real time structure for control and optimization. This new formulation have arisen from predictive controller QDMC (Quadratic Dynamic Matrix Control, a type of predictive control (Model Predictive Control - MPC. At each sampling time, the values of the outputs of process are fed into the optimization-control structure which supplies the new values of the manipulated variables already considering the best conditions of process. The variables of optimization are both set-point changes and control actions. The future stationary outputs and the future stationary control actions have both a different formulation of conventional one-layer structure and they are calculated from the inverse gain matrix of the process. This alternative formulation generates a convex problem, which can be solved by less sophisticated optimization algorithms. Linear and nonlinear economic objective functions were considered. The proposed approach was applied to two linear models, one SISO (single-input/single output and the other MIMO (multiple-input/multiple-output. The results showed an excellent performance.

Decision-level adaptation in motion perception.

Science.gov (United States)

Mather, George; Sharman, Rebecca J

2015-12-01

Prolonged exposure to visual stimuli causes a bias in observers' responses to subsequent stimuli. Such adaptation-induced biases are usually explained in terms of changes in the relative activity of sensory neurons in the visual system which respond selectively to the properties of visual stimuli. However, the bias could also be due to a shift in the observer's criterion for selecting one response rather than the alternative; adaptation at the decision level of processing rather than the sensory level. We investigated whether adaptation to implied motion is best attributed to sensory-level or decision-level bias. Three experiments sought to isolate decision factors by changing the nature of the participants' task while keeping the sensory stimulus unchanged. Results showed that adaptation-induced bias in reported stimulus direction only occurred when the participants' task involved a directional judgement, and disappeared when adaptation was measured using a non-directional task (reporting where motion was present in the display, regardless of its direction). We conclude that adaptation to implied motion is due to decision-level bias, and that a propensity towards such biases may be widespread in sensory decision-making.

Evaluation of Real-Time Hand Motion Tracking Using a Range Camera and the Mean-Shift Algorithm

Science.gov (United States)

Lahamy, H.; Lichti, D.

2011-09-01

Several sensors have been tested for improving the interaction between humans and machines including traditional web cameras, special gloves, haptic devices, cameras providing stereo pairs of images and range cameras. Meanwhile, several methods are described in the literature for tracking hand motion: the Kalman filter, the mean-shift algorithm and the condensation algorithm. In this research, the combination of a range camera and the simple version of the mean-shift algorithm has been evaluated for its capability for hand motion tracking. The evaluation was assessed in terms of position accuracy of the tracking trajectory in x, y and z directions in the camera space and the time difference between image acquisition and image display. Three parameters have been analyzed regarding their influence on the tracking process: the speed of the hand movement, the distance between the camera and the hand and finally the integration time of the camera. Prior to the evaluation, the required warm-up time of the camera has been measured. This study has demonstrated the suitability of the range camera used in combination with the mean-shift algorithm for real-time hand motion tracking but for very high speed hand movement in the traverse plane with respect to the camera, the tracking accuracy is low and requires improvement.

An Adaptive Motion Estimation Scheme for Video Coding

Directory of Open Access Journals (Sweden)

Pengyu Liu

2014-01-01

Full Text Available The unsymmetrical-cross multihexagon-grid search (UMHexagonS is one of the best fast Motion Estimation (ME algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised.

Design and Performance Evaluation of an Adaptive Resource Management Framework for Distributed Real-Time and Embedded Systems

Directory of Open Access Journals (Sweden)

Chen Yingming

2008-01-01

Full Text Available Abstract Achieving end-to-end quality of service (QoS in distributed real-time embedded (DRE systems require QoS support and enforcement from their underlying operating platforms that integrates many real-time capabilities, such as QoS-enabled network protocols, real-time operating system scheduling mechanisms and policies, and real-time middleware services. As standards-based quality of service (QoS enabled component middleware automates integration and configuration activities, it is increasingly being used as a platform for developing open DRE systems that execute in environments where operational conditions, input workload, and resource availability cannot be characterized accurately a priori. Although QoS-enabled component middleware offers many desirable features, however, it historically lacked the ability to allocate resources efficiently and enable the system to adapt to fluctuations in input workload, resource availability, and operating conditions. This paper presents three contributions to research on adaptive resource management for component-based open DRE systems. First, we describe the structure and functionality of the resource allocation and control engine (RACE, which is an open-source adaptive resource management framework built atop standards-based QoS-enabled component middleware. Second, we demonstrate and evaluate the effectiveness of RACE in the context of a representative open DRE system: NASA's magnetospheric multiscale mission system. Third, we present an empirical evaluation of RACE's scalability as the number of nodes and applications in a DRE system grows. Our results show that RACE is a scalable adaptive resource management framework and yields a predictable and high-performance system, even in the face of changing operational conditions and input workload.

Design and Performance Evaluation of an Adaptive Resource Management Framework for Distributed Real-Time and Embedded Systems

Directory of Open Access Journals (Sweden)

Chenyang Lu

2008-04-01

Full Text Available Achieving end-to-end quality of service (QoS in distributed real-time embedded (DRE systems require QoS support and enforcement from their underlying operating platforms that integrates many real-time capabilities, such as QoS-enabled network protocols, real-time operating system scheduling mechanisms and policies, and real-time middleware services. As standards-based quality of service (QoS enabled component middleware automates integration and configuration activities, it is increasingly being used as a platform for developing open DRE systems that execute in environments where operational conditions, input workload, and resource availability cannot be characterized accurately a priori. Although QoS-enabled component middleware offers many desirable features, however, it historically lacked the ability to allocate resources efficiently and enable the system to adapt to fluctuations in input workload, resource availability, and operating conditions. This paper presents three contributions to research on adaptive resource management for component-based open DRE systems. First, we describe the structure and functionality of the resource allocation and control engine (RACE, which is an open-source adaptive resource management framework built atop standards-based QoS-enabled component middleware. Second, we demonstrate and evaluate the effectiveness of RACE in the context of a representative open DRE system: NASA's magnetospheric multiscale mission system. Third, we present an empirical evaluation of RACE's scalability as the number of nodes and applications in a DRE system grows. Our results show that RACE is a scalable adaptive resource management framework and yields a predictable and high-performance system, even in the face of changing operational conditions and input workload.

The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS

Science.gov (United States)

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

Real-time intensity based 2D/3D registration using kV-MV image pairs for tumor motion tracking in image guided radiotherapy

Science.gov (United States)

Furtado, H.; Steiner, E.; Stock, M.; Georg, D.; Birkfellner, W.

2014-03-01

Intra-fractional respiratorymotion during radiotherapy is one of themain sources of uncertainty in dose application creating the need to extend themargins of the planning target volume (PTV). Real-time tumormotion tracking by 2D/3D registration using on-board kilo-voltage (kV) imaging can lead to a reduction of the PTV. One limitation of this technique when using one projection image, is the inability to resolve motion along the imaging beam axis. We present a retrospective patient study to investigate the impact of paired portal mega-voltage (MV) and kV images, on registration accuracy. We used data from eighteen patients suffering from non small cell lung cancer undergoing regular treatment at our center. For each patient we acquired a planning CT and sequences of kV and MV images during treatment. Our evaluation consisted of comparing the accuracy of motion tracking in 6 degrees-of-freedom(DOF) using the anterior-posterior (AP) kV sequence or the sequence of kV-MV image pairs. We use graphics processing unit rendering for real-time performance. Motion along cranial-caudal direction could accurately be extracted when using only the kV sequence but in AP direction we obtained large errors. When using kV-MV pairs, the average error was reduced from 3.3 mm to 1.8 mm and the motion along AP was successfully extracted. The mean registration time was of 190+/-35ms. Our evaluation shows that using kVMV image pairs leads to improved motion extraction in 6 DOF. Therefore, this approach is suitable for accurate, real-time tumor motion tracking with a conventional LINAC.

Global optimization for motion estimation with applications to ultrasound videos of carotid artery plaques

Science.gov (United States)

Murillo, Sergio; Pattichis, Marios; Soliz, Peter; Barriga, Simon; Loizou, C. P.; Pattichis, C. S.

2010-03-01

Motion estimation from digital video is an ill-posed problem that requires a regularization approach. Regularization introduces a smoothness constraint that can reduce the resolution of the velocity estimates. The problem is further complicated for ultrasound videos (US), where speckle noise levels can be significant. Motion estimation using optical flow models requires the modification of several parameters to satisfy the optical flow constraint as well as the level of imposed smoothness. Furthermore, except in simulations or mostly unrealistic cases, there is no ground truth to use for validating the velocity estimates. This problem is present in all real video sequences that are used as input to motion estimation algorithms. It is also an open problem in biomedical applications like motion analysis of US of carotid artery (CA) plaques. In this paper, we study the problem of obtaining reliable ultrasound video motion estimates for atherosclerotic plaques for use in clinical diagnosis. A global optimization framework for motion parameter optimization is presented. This framework uses actual carotid artery motions to provide optimal parameter values for a variety of motions and is tested on ten different US videos using two different motion estimation techniques.

Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle

Directory of Open Access Journals (Sweden)

Linhui Li

2014-01-01

Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.

Real Time Energy Management Control Strategies for Hybrid Powertrains

Science.gov (United States)

Zaher, Mohamed Hegazi Mohamed

In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.

Visibility-based optimal path and motion planning

CERN Document Server

Wang, Paul Keng-Chieh

2015-01-01

This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...

Real-time registration of 3D to 2D ultrasound images for image-guided prostate biopsy.

Science.gov (United States)

Gillies, Derek J; Gardi, Lori; De Silva, Tharindu; Zhao, Shuang-Ren; Fenster, Aaron

2017-09-01

During image-guided prostate biopsy, needles are targeted at tissues that are suspicious of cancer to obtain specimen for histological examination. Unfortunately, patient motion causes targeting errors when using an MR-transrectal ultrasound (TRUS) fusion approach to augment the conventional biopsy procedure. This study aims to develop an automatic motion correction algorithm approaching the frame rate of an ultrasound system to be used in fusion-based prostate biopsy systems. Two modes of operation have been investigated for the clinical implementation of the algorithm: motion compensation using a single user initiated correction performed prior to biopsy, and real-time continuous motion compensation performed automatically as a background process. Retrospective 2D and 3D TRUS patient images acquired prior to biopsy gun firing were registered using an intensity-based algorithm utilizing normalized cross-correlation and Powell's method for optimization. 2D and 3D images were downsampled and cropped to estimate the optimal amount of image information that would perform registrations quickly and accurately. The optimal search order during optimization was also analyzed to avoid local optima in the search space. Error in the algorithm was computed using target registration errors (TREs) from manually identified homologous fiducials in a clinical patient dataset. The algorithm was evaluated for real-time performance using the two different modes of clinical implementations by way of user initiated and continuous motion compensation methods on a tissue mimicking prostate phantom. After implementation in a TRUS-guided system with an image downsampling factor of 4, the proposed approach resulted in a mean ± std TRE and computation time of 1.6 ± 0.6 mm and 57 ± 20 ms respectively. The user initiated mode performed registrations with in-plane, out-of-plane, and roll motions computation times of 108 ± 38 ms, 60 ± 23 ms, and 89 ± 27 ms, respectively, and corresponding

Real-time skin feature identification in a time-sequential video stream

Science.gov (United States)

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.

Learning motion concepts using real-time microcomputer-based laboratory tools

Science.gov (United States)

Thornton, Ronald K.; Sokoloff, David R.

1990-09-01

Microcomputer-based laboratory (MBL) tools have been developed which interface to Apple II and Macintosh computers. Students use these tools to collect physical data that are graphed in real time and then can be manipulated and analyzed. The MBL tools have made possible discovery-based laboratory curricula that embody results from educational research. These curricula allow students to take an active role in their learning and encourage them to construct physical knowledge from observation of the physical world. The curricula encourage collaborative learning by taking advantage of the fact that MBL tools present data in an immediately understandable graphical form. This article describes one of the tools—the motion detector (hardware and software)—and the kinematics curriculum. The effectiveness of this curriculum compared to traditional college and university methods for helping students learn basic kinematics concepts has been evaluated by pre- and post-testing and by observation. There is strong evidence for significantly improved learning and retention by students who used the MBL materials, compared to those taught in lecture.

Planning Study Comparison of Real-Time Target Tracking and Four-Dimensional Inverse Planning for Managing Patient Respiratory Motion

International Nuclear Information System (INIS)

Zhang Peng; Hugo, Geoffrey D.; Yan Di

2008-01-01

Purpose: Real-time target tracking (RT-TT) and four-dimensional inverse planning (4D-IP) are two potential methods to manage respiratory target motion. In this study, we evaluated each method using the cumulative dose-volume criteria in lung cancer radiotherapy. Methods and Materials: Respiration-correlated computed tomography scans were acquired for 4 patients. Deformable image registration was applied to generate a displacement mapping for each phase image of the respiration-correlated computed tomography images. First, the dose distribution for the organs of interest obtained from an idealized RT-TT technique was evaluated, assuming perfect knowledge of organ motion and beam tracking. Inverse planning was performed on each phase image separately. The treatment dose to the organs of interest was then accumulated from the optimized plans. Second, 4D-IP was performed using the probability density function of respiratory motion. The beam arrangement, prescription dose, and objectives were consistent in both planning methods. The dose-volume and equivalent uniform dose in the target volume, lung, heart, and spinal cord were used for the evaluation. Results: The cumulative dose in the target was similar for both techniques. The equivalent uniform dose of the lung, heart, and spinal cord was 4.6 ± 2.2, 11 ± 4.4, and 11 ± 6.6 Gy for RT-TT with a 0-mm target margin, 5.2 ± 3.1, 12 ± 5.9, and 12 ± 7.8 Gy for RT-TT with a 2-mm target margin, and 5.3 ± 2.3, 11.9 ± 5.0, and 12 ± 5.6 Gy for 4D-IP, respectively. Conclusion: The results of our study have shown that 4D-IP can achieve plans similar to those achieved by RT-TT. Considering clinical implementation, 4D-IP could be a more reliable and practical method to manage patient respiration-induced motion

Detecting changes in real-time data: a user's guide to optimal detection.

Science.gov (United States)

Johnson, P; Moriarty, J; Peskir, G

2017-08-13

The real-time detection of changes in a noisily observed signal is an important problem in applied science and engineering. The study of parametric optimal detection theory began in the 1930s, motivated by applications in production and defence. Today this theory, which aims to minimize a given measure of detection delay under accuracy constraints, finds applications in domains including radar, sonar, seismic activity, global positioning, psychological testing, quality control, communications and power systems engineering. This paper reviews developments in optimal detection theory and sequential analysis, including sequential hypothesis testing and change-point detection, in both Bayesian and classical (non-Bayesian) settings. For clarity of exposition, we work in discrete time and provide a brief discussion of the continuous time setting, including recent developments using stochastic calculus. Different measures of detection delay are presented, together with the corresponding optimal solutions. We emphasize the important role of the signal-to-noise ratio and discuss both the underlying assumptions and some typical applications for each formulation.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Real-Time Measurements for Adaptive and Cognitive Radio Systems

Directory of Open Access Journals (Sweden)

Hüseyin Arslan

2009-01-01

Full Text Available Adaptive and cognitive radios (CR have been becoming popular for optimizing mobile radio system transmission and reception. One of the most important elements of the adaptive radio and CR concepts is the ability to measure, sense, learn about, and be aware of parameters related to the radio channel characteristics, availability of spectrum and power, interference and noise temperature, operational environment of radio, user requirements and applications, available networks and infrastructures, local policies, other operating restrictions, and so on. This paper discusses some of the important measurement parameters for enabling adaptive radio and CR systems along with their relationships and impacts on the performance including relevant challenges.

Real-time parameter optimization based on neural network for smart injection molding

Science.gov (United States)

Lee, H.; Liau, Y.; Ryu, K.

2018-03-01

The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. Injection molding process has a short cycle time and high productivity. This features have been making it suitable for mass production. In addition, this process is used to produce precise parts in various industry fields such as automobiles, optics and medical devices. Injection molding process has a mixture of discrete and continuous variables. In order to optimized the quality, variables that is generated in the injection molding process must be considered. Furthermore, Optimal parameter setting is time-consuming work to predict the optimum quality of the product. Since the process parameter cannot be easily corrected during the process execution. In this research, we propose a neural network based real-time process parameter optimization methodology that sets optimal process parameters by using mold data, molding machine data, and response data. This paper is expected to have academic contribution as a novel study of parameter optimization during production compare with pre - production parameter optimization in typical studies.

A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision

Directory of Open Access Journals (Sweden)

loubna benchikhi

2017-10-01

Full Text Available Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO, reinforcement learning (RL and ant colony optimization (ACO show the efficiency of this novel method.

High-performance GPU-based rendering for real-time, rigid 2D/3D-image registration and motion prediction in radiation oncology.

Science.gov (United States)

Spoerk, Jakob; Gendrin, Christelle; Weber, Christoph; Figl, Michael; Pawiro, Supriyanto Ardjo; Furtado, Hugo; Fabri, Daniella; Bloch, Christoph; Bergmann, Helmar; Gröller, Eduard; Birkfellner, Wolfgang

2012-02-01

A common problem in image-guided radiation therapy (IGRT) of lung cancer as well as other malignant diseases is the compensation of periodic and aperiodic motion during dose delivery. Modern systems for image-guided radiation oncology allow for the acquisition of cone-beam computed tomography data in the treatment room as well as the acquisition of planar radiographs during the treatment. A mid-term research goal is the compensation of tumor target volume motion by 2D/3D Registration. In 2D/3D registration, spatial information on organ location is derived by an iterative comparison of perspective volume renderings, so-called digitally rendered radiographs (DRR) from computed tomography volume data, and planar reference x-rays. Currently, this rendering process is very time consuming, and real-time registration, which should at least provide data on organ position in less than a second, has not come into existence. We present two GPU-based rendering algorithms which generate a DRR of 512×512 pixels size from a CT dataset of 53 MB size at a pace of almost 100 Hz. This rendering rate is feasible by applying a number of algorithmic simplifications which range from alternative volume-driven rendering approaches - namely so-called wobbled splatting - to sub-sampling of the DRR-image by means of specialized raycasting techniques. Furthermore, general purpose graphics processing unit (GPGPU) programming paradigms were consequently utilized. Rendering quality and performance as well as the influence on the quality and performance of the overall registration process were measured and analyzed in detail. The results show that both methods are competitive and pave the way for fast motion compensation by rigid and possibly even non-rigid 2D/3D registration and, beyond that, adaptive filtering of motion models in IGRT. Copyright © 2011. Published by Elsevier GmbH.

High-performance GPU-based rendering for real-time, rigid 2D/3D-image registration and motion prediction in radiation oncology

Energy Technology Data Exchange (ETDEWEB)

Spoerk, Jakob; Gendrin, Christelle; Weber, Christoph [Medical University of Vienna (Austria). Center of Medical Physics and Biomedical Engineering] [and others

2012-07-01

A common problem in image-guided radiation therapy (IGRT) of lung cancer as well as other malignant diseases is the compensation of periodic and aperiodic motion during dose delivery. Modern systems for image-guided radiation oncology allow for the acquisition of cone-beam computed tomography data in the treatment room as well as the acquisition of planar radiographs during the treatment. A mid-term research goal is the compensation of tumor target volume motion by 2D/3D Registration. In 2D/3D registration, spatial information on organ location is derived by an iterative comparison of perspective volume renderings, so-called digitally rendered radiographs (DRR) from computed tomography volume data, and planar reference X-rays. Currently, this rendering process is very time consuming, and real-time registration, which should at least provide data on organ position in less than a second, has not come into existence. We present two GPU-based rendering algorithms which generate a DRR of 512 x 512 pixels size from a CT dataset of 53 MB size at a pace of almost 100 Hz. This rendering rate is feasible by applying a number of algorithmic simplifications which range from alternative volume-driven rendering approaches - namely so-called wobbled splatting - to sub-sampling of the DRR-image by means of specialized raycasting techniques. Furthermore, general purpose graphics processing unit (GPGPU) programming paradigms were consequently utilized. Rendering quality and performance as well as the influence on the quality and performance of the overall registration process were measured and analyzed in detail. The results show that both methods are competitive and pave the way for fast motion compensation by rigid and possibly even non-rigid 2D/3D registration and, beyond that, adaptive filtering of motion models in IGRT. (orig.)

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

Science.gov (United States)

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing

Advances in LWD pressure measurements: smart, time optimized pretests and on demand real-time transmission applications

Energy Technology Data Exchange (ETDEWEB)

Serafim, Robson; Ferraris, Paolo [Schlumberger, Rio de Janeiro, RJ (Brazil)

2008-07-01

The StethoScope Logging While Drilling (LWD) Pressure Measurement, introduced in Brazil in 2005, has been extensively used in deep water environment to provide reservoir pressure and mobility in real-time. In the last three years the StethoScope service was further enhanced to allow better real time monitoring using a larger transmission rate, higher RT data resolution and remote visualization. In order to guarantee stable formation pressures with a limited test duration under a wide range of conditions, Time Optimized Pretests (TOP) were developed. These tests adjust automatically drawdown and buildup parameters as a function of formation characteristics (pressure/mobility) without requiring any input from the operator. On-demand frame (ODF), an advanced telemetry triggered automatically during the pressure tests, allowed to increase equivalent transmission rate and resolution and to include quality indices computed downhole. This paper is focused on the TOP and ODF Field Test results in Brazil, which proved to be useful and reliable options for better real-time decisions together with remote monitoring visualization implemented by the RTMonitor program. (author)

Dynamic, adaptive changes in MAO-A binding after alterations in substrate availability: an in vivo [11C]-harmine positron emission tomography study

Science.gov (United States)

Sacher, Julia; Rabiner, Eugenii A; Clark, Michael; Rusjan, Pablo; Soliman, Alexandra; Boskovic, Rada; Kish, Stephen J; Wilson, Alan A; Houle, Sylvain; Meyer, Jeffrey H

2012-01-01

Monoamine oxidase A (MAO-A) is an important target in the pathophysiology and therapeutics of major depressive disorder, aggression, and neurodegenerative conditions. We measured the effect of changes in MAO-A substrate on MAO-A binding in regions implicated in affective and neurodegenerative disease with [11C]-harmine positron emission tomography in healthy volunteers. Monoamine oxidase A VT, an index of MAO-A density, was decreased (mean: 14%±9%) following tryptophan depletion in prefrontal cortex (PMAO-A in maintaining monoamine neurotransmitter homeostasis by rapidly compensating fluctuating monoamine levels. PMID:22186668

Real-time movie image enhancement in NMR

International Nuclear Information System (INIS)

Doyle, M.; Mansfield, P.

1986-01-01

Clinical NMR motion picture (movie) images can now be produced routinely in real-time by ultra-high-speed echo-planar imaging (EPI). The single-shot image quality depends on both pixel resolution and signal-to-noise ratio (S/N), both factors being intertradeable. If image S/N is sacrificed rather than resolution, it is shown that S/N may be greatly enhanced subsequently without vitiating spatial resolution or foregoing real motional effects when the object motion is periodic. This is achieved by a Fourier filtering process. Experimental results are presented which demonstrate the technique for a normal functioning heart. (author)

Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

Science.gov (United States)

Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

2017-07-01

Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

Automatic online and real-time tumour motion monitoring during stereotactic liver treatments on a conventional linac by combined optical and sparse monoscopic imaging with kilovoltage x-rays (COSMIK)

Science.gov (United States)

Bertholet, Jenny; Toftegaard, Jakob; Hansen, Rune; Worm, Esben S.; Wan, Hanlin; Parikh, Parag J.; Weber, Britta; Høyer, Morten; Poulsen, Per R.

2018-03-01

The purpose of this study was to develop, validate and clinically demonstrate fully automatic tumour motion monitoring on a conventional linear accelerator by combined optical and sparse monoscopic imaging with kilovoltage x-rays (COSMIK). COSMIK combines auto-segmentation of implanted fiducial markers in cone-beam computed tomography (CBCT) projections and intra-treatment kV images with simultaneous streaming of an external motion signal. A pre-treatment CBCT is acquired with simultaneous recording of the motion of an external marker block on the abdomen. The 3-dimensional (3D) marker motion during the CBCT is estimated from the auto-segmented positions in the projections and used to optimize an external correlation model (ECM) of internal motion as a function of external motion. During treatment, the ECM estimates the internal motion from the external motion at 20 Hz. KV images are acquired every 3 s, auto-segmented, and used to update the ECM for baseline shifts between internal and external motion. The COSMIK method was validated using Calypso-recorded internal tumour motion with simultaneous camera-recorded external motion for 15 liver stereotactic body radiotherapy (SBRT) patients. The validation included phantom experiments and simulations hereof for 12 fractions and further simulations for 42 fractions. The simulations compared the accuracy of COSMIK with ECM-based monitoring without model updates and with model updates based on stereoscopic imaging as well as continuous kilovoltage intrafraction monitoring (KIM) at 10 Hz without an external signal. Clinical real-time tumour motion monitoring with COSMIK was performed offline for 14 liver SBRT patients (41 fractions) and online for one patient (two fractions). The mean 3D root-mean-square error for the four monitoring methods was 1.61 mm (COSMIK), 2.31 mm (ECM without updates), 1.49 mm (ECM with stereoscopic updates) and 0.75 mm (KIM). COSMIK is the first combined kV/optical real-time motion

Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains

Science.gov (United States)

Zaal, P. M. T; Pool, D. M.

2014-01-01

In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

Science.gov (United States)

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Cognitive radio adaptation for power consumption minimization using biogeography-based optimization

International Nuclear Information System (INIS)

Qi Pei-Han; Zheng Shi-Lian; Yang Xiao-Niu; Zhao Zhi-Jin

2016-01-01

Adaptation is one of the key capabilities of cognitive radio, which focuses on how to adjust the radio parameters to optimize the system performance based on the knowledge of the radio environment and its capability and characteristics. In this paper, we consider the cognitive radio adaptation problem for power consumption minimization. The problem is formulated as a constrained power consumption minimization problem, and the biogeography-based optimization (BBO) is introduced to solve this optimization problem. A novel habitat suitability index (HSI) evaluation mechanism is proposed, in which both the power consumption minimization objective and the quality of services (QoS) constraints are taken into account. The results show that under different QoS requirement settings corresponding to different types of services, the algorithm can minimize power consumption while still maintaining the QoS requirements. Comparison with particle swarm optimization (PSO) and cat swarm optimization (CSO) reveals that BBO works better, especially at the early stage of the search, which means that the BBO is a better choice for real-time applications. (paper)

Modbus RTU protocol and arduino IO package: A real time implementation of a 3 finger adaptive robot gripper

Directory of Open Access Journals (Sweden)

Sadun Amirul Syafiq

2017-01-01

Full Text Available Recently, the Modbus RTU protocol has been widely accepted in the application of robotics, communications and industrial control systems due to its simplicity and reliability. With the help of the MATLAB Instrument Control Toolbox, a serial communication between Simulink and a 3 Finger Adaptive Robot Gripper can be realized to demonstrate a grasping functionality. The toolbox includes a “to instrument” and “query instrument” programming blocks that enable the users to create a serial communication with the targeted hardware/robot. Similarly, the Simulink Arduino IO package also offers a real-time feature that enabled it to act as a DAQ device. This paper establishes a real-time robot control by using Modbus RTU and Arduino IO Package for a 3 Finger Adaptive Robot Gripper. The robot communication and grasping performance were successfully implemented and demonstrated. In particular, three (3 different grasping mode via normal, wide and pinch were tested. Moreover, the robot gripper’s feedback data, such as encoder position, motor current and the grasping force were easily measured and acquired in real-time. This certainly essential for future grasping analysis of a 3 Finger Adaptive Robot Gripper.

Design Optimization of Mixed-Criticality Real-Time Embedded Systems

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2015-01-01

is allocated several time slots on a processor. Tasks of different SILs can share a partition only if they are all elevated to the highest SIL among them. Such elevation leads to increased development costs, which increase dramatically with each SIL. Tasks of higher SILs can be decomposed into redundant...... structures of lower SIL tasks. We are interested to determine (i) the mapping of tasks to processors, (ii) the assignment of tasks to partitions, (iii) the decomposition of tasks into redundant lower SIL tasks, (iv) the sequence and size of the partition time slots on each processor, and (v) the schedule...... tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real-life benchmarks....

Optimal full motion video registration with rigorous error propagation

Science.gov (United States)

Dolloff, John; Hottel, Bryant; Doucette, Peter; Theiss, Henry; Jocher, Glenn

2014-06-01

Optimal full motion video (FMV) registration is a crucial need for the Geospatial community. It is required for subsequent and optimal geopositioning with simultaneous and reliable accuracy prediction. An overall approach being developed for such registration is presented that models relevant error sources in terms of the expected magnitude and correlation of sensor errors. The corresponding estimator is selected based on the level of accuracy of the a priori information of the sensor's trajectory and attitude (pointing) information, in order to best deal with non-linearity effects. Estimator choices include near real-time Kalman Filters and batch Weighted Least Squares. Registration solves for corrections to the sensor a priori information for each frame. It also computes and makes available a posteriori accuracy information, i.e., the expected magnitude and correlation of sensor registration errors. Both the registered sensor data and its a posteriori accuracy information are then made available to "down-stream" Multi-Image Geopositioning (MIG) processes. An object of interest is then measured on the registered frames and a multi-image optimal solution, including reliable predicted solution accuracy, is then performed for the object's 3D coordinates. This paper also describes a robust approach to registration when a priori information of sensor attitude is unavailable. It makes use of structure-from-motion principles, but does not use standard Computer Vision techniques, such as estimation of the Essential Matrix which can be very sensitive to noise. The approach used instead is a novel, robust, direct search-based technique.

Real-time speckle variance swept-source optical coherence tomography using a graphics processing unit.

Science.gov (United States)

Lee, Kenneth K C; Mariampillai, Adrian; Yu, Joe X Z; Cadotte, David W; Wilson, Brian C; Standish, Beau A; Yang, Victor X D

2012-07-01

Advances in swept source laser technology continues to increase the imaging speed of swept-source optical coherence tomography (SS-OCT) systems. These fast imaging speeds are ideal for microvascular detection schemes, such as speckle variance (SV), where interframe motion can cause severe imaging artifacts and loss of vascular contrast. However, full utilization of the laser scan speed has been hindered by the computationally intensive signal processing required by SS-OCT and SV calculations. Using a commercial graphics processing unit that has been optimized for parallel data processing, we report a complete high-speed SS-OCT platform capable of real-time data acquisition, processing, display, and saving at 108,000 lines per second. Subpixel image registration of structural images was performed in real-time prior to SV calculations in order to reduce decorrelation from stationary structures induced by the bulk tissue motion. The viability of the system was successfully demonstrated in a high bulk tissue motion scenario of human fingernail root imaging where SV images (512 × 512 pixels, n = 4) were displayed at 54 frames per second.

Tumor tracking and motion compensation with an adaptive tumor tracking system (ATTS): System description and prototype testing

International Nuclear Information System (INIS)

Wilbert, Juergen; Meyer, Juergen; Baier, Kurt; Guckenberger, Matthias; Herrmann, Christian; Hess, Robin; Janka, Christian; Ma Lei; Mersebach, Torben; Richter, Anne; Roth, Michael; Schilling, Klaus; Flentje, Michael

2008-01-01

A novel system for real-time tumor tracking and motion compensation with a robotic HexaPOD treatment couch is described. The approach is based on continuous tracking of the tumor motion in portal images without implanted fiducial markers, using the therapeutic megavoltage beam, and tracking of abdominal breathing motion with optical markers. Based on the two independently acquired data sets the table movements for motion compensation are calculated. The principle of operation of the entire prototype system is detailed first. In the second part the performance of the HexaPOD couch was investigated with a robotic four-dimensional-phantom capable of simulating real patient tumor trajectories in three-dimensional space. The performance and limitations of the HexaPOD table and the control system were characterized in terms of its dynamic behavior. The maximum speed and acceleration of the HexaPOD were 8 mm/s and 34.5 mm/s 2 in the lateral direction, and 9.5 mm/s and 29.5 mm/s 2 in longitudinal and anterior-posterior direction, respectively. Base line drifts of the mean tumor position of realistic lung tumor trajectories could be fully compensated. For continuous tumor tracking and motion compensation a reduction of tumor motion up to 68% of the original amplitude was achieved. In conclusion, this study demonstrated that it is technically feasible to compensate breathing induced tumor motion in the lung with the adaptive tumor tracking system

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

Science.gov (United States)

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

Optimizing the data acquisition rate for a remotely controllable structural monitoring system with parallel operation and self-adaptive sampling

International Nuclear Information System (INIS)

Sheng, Wenjuan; Guo, Aihuang; Liu, Yang; Azmi, Asrul Izam; Peng, Gang-Ding

2011-01-01

We present a novel technique that optimizes the real-time remote monitoring and control of dispersed civil infrastructures. The monitoring system is based on fiber Bragg gating (FBG) sensors, and transfers data via Ethernet. This technique combines parallel operation and self-adaptive sampling to increase the data acquisition rate in remote controllable structural monitoring systems. The compact parallel operation mode is highly efficient at achieving the highest possible data acquisition rate for the FBG sensor based local data acquisition system. Self-adaptive sampling is introduced to continuously coordinate local acquisition and remote control for data acquisition rate optimization. Key issues which impact the operation of the whole system, such as the real-time data acquisition rate, data processing capability, and buffer usage, are investigated. The results show that, by introducing parallel operation and self-adaptive sampling, the data acquisition rate can be increased by several times without affecting the system operating performance on both local data acquisition and remote process control

Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions.

Science.gov (United States)

Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

2004-04-01

Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

Real-Time Energy Management Control for Hybrid Electric Powertrains

Directory of Open Access Journals (Sweden)

Mohamed Zaher

2013-01-01

Full Text Available This paper focuses on embedded control of a hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real-time energy management strategy. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in the opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, the motion is driven by gravitational force, or load driven. There are three main concepts for energy storing devices in hybrid vehicles: electric, hydraulic, and mechanical (flywheel. The real-time control challenge is to balance the system power demands from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle. In the worst-case scenario, only the engine is used and the hybrid system is completely disabled. A rule-based control algorithm is developed and is tuned for different work cycles and could be linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the work machine and its position via GPS and maps both of them to the gains.

Real-Time Landmine Detection with Ground-Penetrating Radar Using Discriminative and Adaptive Hidden Markov Models

Directory of Open Access Journals (Sweden)

Ho KC

2005-01-01

Full Text Available We propose a real-time software system for landmine detection using ground-penetrating radar (GPR. The system includes an efficient and adaptive preprocessing component; a hidden Markov model- (HMM- based detector; a corrective training component; and an incremental update of the background model. The preprocessing is based on frequency-domain processing and performs ground-level alignment and background removal. The HMM detector is an improvement of a previously proposed system (baseline. It includes additional pre- and postprocessing steps to improve the time efficiency and enable real-time application. The corrective training component is used to adjust the initial model parameters to minimize the number of misclassification sequences. This component could be used offline, or online through feedback to adapt an initial model to specific sites and environments. The background update component adjusts the parameters of the background model to adapt it to each lane during testing. The proposed software system is applied to data acquired from three outdoor test sites at different geographic locations, using a state-of-the-art array GPR prototype. The first collection was used as training, and the other two (contain data from more than 1200 m of simulated dirt and gravel roads for testing. Our results indicate that, on average, the corrective training can improve the performance by about 10% for each site. For individual lanes, the performance gain can reach 50%.

Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

Science.gov (United States)

Li, Xiwang

Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Moreover, it is estimated by the National Energy Technology Laboratory that more than 1/4 of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. In this study, it is envisioned that neighboring buildings will have the tendency to form a cluster, an open cyber-physical system to exploit the economic opportunities provided by a smart grid, distributed power generation, and storage devices. Through optimized demand management, these building clusters will then reduce overall primary energy consumption and peak time electricity consumption, and be more resilient to power disruptions. Therefore, this project seeks to develop a Net-zero building cluster simulation testbed and high fidelity energy forecasting models for adaptive and real-time control and decision making strategy development that can be used in a Net-zero building cluster. The following research activities are summarized in this thesis: 1) Development of a building cluster emulator for building cluster control and operation strategy assessment. 2) Development of a novel building energy forecasting methodology using active system identification and data fusion techniques. In this methodology, a systematic approach for building energy system characteristic evaluation, system excitation and model adaptation is included. The developed methodology is compared with other literature-reported building energy forecasting methods; 3) Development of the high fidelity on-line building cluster energy forecasting models, which includes energy forecasting models for buildings, PV panels, batteries and ice tank thermal storage systems 4) Small scale real building validation study to verify the performance of the developed building energy forecasting methodology. The outcomes of

Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models.

Science.gov (United States)

Yang, Chenguang; Li, Zhijun; Li, Jing

2013-02-01

In this paper, we investigate optimized adaptive control and trajectory generation for a class of wheeled inverted pendulum (WIP) models of vehicle systems. Aiming at shaping the controlled vehicle dynamics to be of minimized motion tracking errors as well as angular accelerations, we employ the linear quadratic regulation optimization technique to obtain an optimal reference model. Adaptive control has then been developed using variable structure method to ensure the reference model to be exactly matched in a finite-time horizon, even in the presence of various internal and external uncertainties. The minimized yaw and tilt angular accelerations help to enhance the vehicle rider's comfort. In addition, due to the underactuated mechanism of WIP, the vehicle forward velocity dynamics cannot be controlled separately from the pendulum tilt angle dynamics. Inspired by the control strategy of human drivers, who usually manipulate the tilt angle to control the forward velocity, we design a neural-network-based adaptive generator of implicit control trajectory (AGICT) of the tilt angle which indirectly "controls" the forward velocity such that it tracks the desired velocity asymptotically. The stability and optimal tracking performance have been rigorously established by theoretic analysis. In addition, simulation studies have been carried out to demonstrate the efficiency of the developed AGICT and optimized adaptive controller.

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control.

Science.gov (United States)

Shen, Gang; Zhu, Zhencai; Zhao, Jinsong; Zhu, Weidong; Tang, Yu; Li, Xiang

2017-03-01

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H ∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement. Copyright © 2016. Published by Elsevier Ltd.

Optimized effective potential in real time: Problems and prospects in time-dependent density-functional theory

International Nuclear Information System (INIS)

Mundt, Michael; Kuemmel, Stephan

2006-01-01

The integral equation for the time-dependent optimized effective potential (TDOEP) in time-dependent density-functional theory is transformed into a set of partial-differential equations. These equations only involve occupied Kohn-Sham orbitals and orbital shifts resulting from the difference between the exchange-correlation potential and the orbital-dependent potential. Due to the success of an analog scheme in the static case, a scheme that propagates orbitals and orbital shifts in real time is a natural candidate for an exact solution of the TDOEP equation. We investigate the numerical stability of such a scheme. An approximation beyond the Krieger-Li-Iafrate approximation for the time-dependent exchange-correlation potential is analyzed

MO-A-BRD-08: Radiosurgery Beyond Cancer: Real-Time Target Localization and Treatment Planning for Cardiac Radiosurgery Under MRI Guidance

Energy Technology Data Exchange (ETDEWEB)

Ipsen, S [University of Luebeck, Luebeck, SH (Germany); University of Sydney, Camperdown (Australia); Blanck, O [CyberKnife Zentrum Norddeutschland, Guestrow, MV (Germany); Oborn, B [Illawarra Cancer Care Centre, Wollongong, NSW (Australia); Bode, F [Medical Clinic II, Section for Electrophysiology, UKSH, Luebeck, SH (Germany); Liney, G [Ingham Institute for Applied Medical Research, Liverpool, NSW (United Kingdom); Keall, P [University of Sydney, Camperdown (Australia)

2014-06-15

Purpose: Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting >2.5M Americans and >4.5M Europeans. AF is usually treated with minimally-invasive, time consuming catheter ablation techniques. Radiosurgery of the pulmonary veins (PV) has been proposed for AF treatment, however is challenging due to the complex respiratory and cardiac motion patterns. We hypothesize that an MRI-linac could solve the difficult real-time targeting and adaptation problem. In this study we quantified target motion ranges on cardiac MRI and analyzed the dosimetric benefits of margin reduction assuming real-time MRI tracking was applied. Methods: For the motion study, four human subjects underwent real-time cardiac MRI under free breathing. The target motion on coronal and axial cine planes was analyzed using a template matching algorithm. For the planning study, an ablation line at each PV antrum was defined as target on an AF patient scheduled for catheter ablation. Various safety margins ranging from 0mm (perfect tracking) to 8mm (untracked motion) were added to the target defining the PTV. 30Gy single fraction IMRT plans were then generated. Finally, the influence of a 1T magnetic field on treatment beam delivery was calculated using the Geant4 Monte Carlo algorithm to simulate the dosimetric impact of MRI guidance. Results: The motion study showed the mean respiratory motion of the target area on MRI was 8.4mm (SI), 1.7mm (AP) and 0.3mm (LR). Cardiac motion was small (<2mm). The planning study showed that with increasing safety margins to encompass untracked motion, dose tolerances for OARs such as the esophagus and airways were exceeded by >100%. The magnetic field had little impact on the dose distribution. Conclusion: Our results indicate that real-time MRI tracking of the PVs seems feasible. Accurate image guidance for high-dose AF radiosurgery is essential since safety margins covering untracked target motion will result in unacceptable treatment plans.

Data-adaptive Harmonic Decomposition and Real-time Prediction of Arctic Sea Ice Extent

Science.gov (United States)

Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael

2017-04-01

Decline in the Arctic sea ice extent (SIE) has profound socio-economic implications and is a focus of active scientific research. Of particular interest is prediction of SIE on subseasonal time scales, i.e. from early summer into fall, when sea ice coverage in Arctic reaches its minimum. However, subseasonal forecasting of SIE is very challenging due to the high variability of ocean and atmosphere over Arctic in summer, as well as shortness of observational data and inadequacies of the physics-based models to simulate sea-ice dynamics. The Sea Ice Outlook (SIO) by Sea Ice Prediction Network (SIPN, http://www.arcus.org/sipn) is a collaborative effort to facilitate and improve subseasonal prediction of September SIE by physics-based and data-driven statistical models. Data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) techniques [Chekroun and Kondrashov, 2017], have been successfully applied to the nonlinear stochastic modeling, as well as retrospective and real-time forecasting of Multisensor Analyzed Sea Ice Extent (MASIE) dataset in key four Arctic regions. In particular, DAH-MSLM predictions outperformed most statistical models and physics-based models in real-time 2016 SIO submissions. The key success factors are associated with DAH ability to disentangle complex regional dynamics of MASIE by data-adaptive harmonic spatio-temporal patterns that reduce the data-driven modeling effort to elemental MSLMs stacked per frequency with fixed and small number of model coefficients to estimate.

An engineered approach to stem cell culture: automating the decision process for real-time adaptive subculture of stem cells.

Directory of Open Access Journals (Sweden)

Dai Fei Elmer Ker

Full Text Available Current cell culture practices are dependent upon human operators and remain laborious and highly subjective, resulting in large variations and inconsistent outcomes, especially when using visual assessments of cell confluency to determine the appropriate time to subculture cells. Although efforts to automate cell culture with robotic systems are underway, the majority of such systems still require human intervention to determine when to subculture. Thus, it is necessary to accurately and objectively determine the appropriate time for cell passaging. Optimal stem cell culturing that maintains cell pluripotency while maximizing cell yields will be especially important for efficient, cost-effective stem cell-based therapies. Toward this goal we developed a real-time computer vision-based system that monitors the degree of cell confluency with a precision of 0.791±0.031 and recall of 0.559±0.043. The system consists of an automated phase-contrast time-lapse microscope and a server. Multiple dishes are sequentially imaged and the data is uploaded to the server that performs computer vision processing, predicts when cells will exceed a pre-defined threshold for optimal cell confluency, and provides a Web-based interface for remote cell culture monitoring. Human operators are also notified via text messaging and e-mail 4 hours prior to reaching this threshold and immediately upon reaching this threshold. This system was successfully used to direct the expansion of a paradigm stem cell population, C2C12 cells. Computer-directed and human-directed control subcultures required 3 serial cultures to achieve the theoretical target cell yield of 50 million C2C12 cells and showed no difference for myogenic and osteogenic differentiation. This automated vision-based system has potential as a tool toward adaptive real-time control of subculturing, cell culture optimization and quality assurance/quality control, and it could be integrated with current and

Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

Directory of Open Access Journals (Sweden)

Zhenhao Tang

2017-01-01

Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

PRIMAS: a real-time 3D motion-analysis system

Science.gov (United States)

Sabel, Jan C.; van Veenendaal, Hans L. J.; Furnee, E. Hans

1994-03-01

The paper describes a CCD TV-camera-based system for real-time multicamera 2D detection of retro-reflective targets and software for accurate and fast 3D reconstruction. Applications of this system can be found in the fields of sports, biomechanics, rehabilitation research, and various other areas of science and industry. The new feature of real-time 3D opens an even broader perspective of application areas; animations in virtual reality are an interesting example. After presenting an overview of the hardware and the camera calibration method, the paper focuses on the real-time algorithms used for matching of the images and subsequent 3D reconstruction of marker positions. When using a calibrated setup of two cameras, it is now possible to track at least ten markers at 100 Hz. Limitations in the performance are determined by the visibility of the markers, which could be improved by adding a third camera.

Real-Time Motion Management of Prostate Cancer Radiotherapy

DEFF Research Database (Denmark)

Pommer, Tobias

, and for prostate cancer treatments, the proximity of the bladder and rectum makes radiotherapy treatment of this site a challenging task. Furthermore, the prostate may move during the radiation delivery and treatment margins are necessary to ensure that it is still receiving the intended dose. The main aim...... of the MLC on the performance of DMLC tracking were investigated. We found that for prostate motion, the main tracking error arose from the finite leaf width affecting the MLCs ability to construct the desired shape. Furthermore, we also attempted to model prostate motion using a random walk model. We found...... that for the slow and drifting motion, the model could satisfactory replicate the motion of the prostate, while the rapid and transient prostate motion observed in some cases was challenging for the model. We therefore added simulated transient motion to the random walk model, which slightly improved the results...

Real-time microscopic 3D shape measurement based on optimized pulse-width-modulation binary fringe projection

Science.gov (United States)

Hu, Yan; Chen, Qian; Feng, Shijie; Tao, Tianyang; Li, Hui; Zuo, Chao

2017-07-01

In recent years, tremendous progress has been made in 3D measurement techniques, contributing to the realization of faster and more accurate 3D measurement. As a representative of these techniques, fringe projection profilometry (FPP) has become a commonly used method for real-time 3D measurement, such as real-time quality control and online inspection. To date, most related research has been concerned with macroscopic 3D measurement, but microscopic 3D measurement, especially real-time microscopic 3D measurement, is rarely reported. However, microscopic 3D measurement plays an important role in 3D metrology and is indispensable in some applications in measuring micro scale objects like the accurate metrology of MEMS components of the final devices to ensure their proper performance. In this paper, we proposed a method which effectively combines optimized binary structured patterns with a number-theoretical phase unwrapping algorithm to realize real-time microscopic 3D measurement. A slight defocusing of our optimized binary patterns can considerably alleviate the measurement error based on four-step phase-shifting FPP, providing the binary patterns with a comparable performance to ideal sinusoidal patterns. The static measurement accuracy can reach 8 μm, and the experimental results of a vibrating earphone diaphragm reveal that our system can successfully realize real-time 3D measurement of 120 frames per second (FPS) with a measurement range of 8~\\text{mm}× 6~\\text{mm} in lateral and 8 mm in depth.

Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

International Nuclear Information System (INIS)

Pin, Francois G.

2003-01-01

Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives and modular configuration

Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

International Nuclear Information System (INIS)

Pin, Grancois G.

2004-01-01

Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives, and modular configuration

Real time polarization sensor image processing on an embedded FPGA/multi-core DSP system

Science.gov (United States)

Bednara, Marcus; Chuchacz-Kowalczyk, Katarzyna

2015-05-01

Most embedded image processing SoCs available on the market are highly optimized for typical consumer applications like video encoding/decoding, motion estimation or several image enhancement processes as used in DSLR or digital video cameras. For non-consumer applications, on the other hand, optimized embedded hardware is rarely available, so often PC based image processing systems are used. We show how a real time capable image processing system for a non-consumer application - namely polarization image data processing - can be efficiently implemented on an FPGA and multi-core DSP based embedded hardware platform.

A study of the application of singular perturbation theory. [development of a real time algorithm for optimal three dimensional aircraft maneuvers

Science.gov (United States)

Mehra, R. K.; Washburn, R. B.; Sajan, S.; Carroll, J. V.

1979-01-01

A hierarchical real time algorithm for optimal three dimensional control of aircraft is described. Systematic methods are developed for real time computation of nonlinear feedback controls by means of singular perturbation theory. The results are applied to a six state, three control variable, point mass model of an F-4 aircraft. Nonlinear feedback laws are presented for computing the optimal control of throttle, bank angle, and angle of attack. Real Time capability is assessed on a TI 9900 microcomputer. The breakdown of the singular perturbation approximation near the terminal point is examined Continuation methods are examined to obtain exact optimal trajectories starting from the singular perturbation solutions.

Directional bias of illusory stream caused by relative motion adaptation.

Science.gov (United States)

Tomimatsu, Erika; Ito, Hiroyuki

2016-07-01

Enigma is an op-art painting that elicits an illusion of rotational streaming motion. In the present study, we tested whether adaptation to various motion configurations that included relative motion components could be reflected in the directional bias of the illusory stream. First, participants viewed the center of a rotating Enigma stimulus for adaptation. There was no physical motion on the ring area. During the adaptation period, the illusory stream on the ring was mainly seen in the direction opposite to that of the physical rotation. After the physical rotation stopped, the illusory stream on the ring was mainly seen in the same direction as that of the preceding physical rotation. Moreover, adapting to strong relative motion induced a strong bias in the illusory motion direction in the subsequently presented static Enigma stimulus. The results suggest that relative motion detectors corresponding to the ring area may produce the illusory stream of Enigma. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A comparative evaluation of adaptive noise cancellation algorithms for minimizing motion artifacts in a forehead-mounted wearable pulse oximeter.

Science.gov (United States)

Comtois, Gary; Mendelson, Yitzhak; Ramuka, Piyush

2007-01-01

Wearable physiological monitoring using a pulse oximeter would enable field medics to monitor multiple injuries simultaneously, thereby prioritizing medical intervention when resources are limited. However, a primary factor limiting the accuracy of pulse oximetry is poor signal-to-noise ratio since photoplethysmographic (PPG) signals, from which arterial oxygen saturation (SpO2) and heart rate (HR) measurements are derived, are compromised by movement artifacts. This study was undertaken to quantify SpO2 and HR errors induced by certain motion artifacts utilizing accelerometry-based adaptive noise cancellation (ANC). Since the fingers are generally more vulnerable to motion artifacts, measurements were performed using a custom forehead-mounted wearable pulse oximeter developed for real-time remote physiological monitoring and triage applications. This study revealed that processing motion-corrupted PPG signals by least mean squares (LMS) and recursive least squares (RLS) algorithms can be effective to reduce SpO2 and HR errors during jogging, but the degree of improvement depends on filter order. Although both algorithms produced similar improvements, implementing the adaptive LMS algorithm is advantageous since it requires significantly less operations.

Development of a real-time monitoring system for intra-fractional motion in intracranial treatment using pressure sensors.

Science.gov (United States)

Inata, Hiroki; Araki, Fujio; Kuribayashi, Yuta; Hamamoto, Yasushi; Nakayama, Shigeki; Sodeoka, Noritaka; Kiriyama, Tetsukazu; Nishizaki, Osamu

2015-09-21

This study developed a dedicated real-time monitoring system to detect intra-fractional head motion in intracranial radiotherapy using pressure sensors. The dedicated real-time monitoring system consists of pressure sensors with a thickness of 0.6 mm and a radius of 9.1 mm, a thermoplastic mask, a vacuum pillow, and a baseplate. The four sensors were positioned at superior-inferior and right-left sides under the occipital area. The sampling rate of pressure sensors was set to 5 Hz. First, we confirmed that the relationship between the force and the displacement of the vacuum pillow follows Hook's law. Next, the spring constant for the vacuum pillow was determined from the relationship between the force given to the vacuum pillow and the displacement of the head, detected by Cyberknife target locating system (TLS) acquisitions in clinical application. Finally, the accuracy of our system was evaluated by using the 2  ×  2 confusion matrix. The regression lines between the force, y, and the displacement, x, of the vacuum pillow were given by y = 3.8x, y = 4.4x, and y = 5.0x when the degree of inner pressure was  -12 kPa,-20 kPa, and  -27 kPa, respectively. The spring constant of the vacuum pillow was 1.6 N mm(-1) from the 6D positioning data of a total of 2999 TLS acquisitions in 19 patients. Head motions of 1 mm, 1.5 mm, and 2 mm were detected in real-time with the accuracies of 67%, 84%, and 89%, respectively. Our system can detect displacement of the head continuously during every interval of TLS with a resolution of 1-2 mm without any radiation exposure.

An interdimensional correlation framework for real-time estimation of six degree of freedom target motion using a single x-ray imager during radiotherapy

Science.gov (United States)

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

Adaptive control of two-wheeled mobile balance robot capable to adapt different surfaces using a novel artificial neural network–based real-time switching dynamic controller

Directory of Open Access Journals (Sweden)

Ali Unluturk

2017-03-01

Full Text Available In this article, a novel real-time artificial neural network–based adaptable switching dynamic controller is developed and practically implemented. It will be used for real-time control of two-wheeled balance robot which can balance itself upright position on different surfaces. In order to examine the efficiency of the proposed controller, a two-wheeled mobile balance robot is designed and a test platform for experimental setup is made for balance problem on different surfaces. In a developed adaptive controller algorithm which is capable to adapt different surfaces, mean absolute target angle deviation error, mean absolute target displacement deviation error and mean absolute controller output data are employed for surface estimation by using artificial neural network. In a designed two-wheeled mobile balance robot system, robot tilt angle is estimated via Kalman filter from accelerometer and gyroscope sensor signals. Furthermore, a visual robot control interface is developed in C++ software development environment so that robot controller parameters can be changed as desired. In addition, robot balance angle, linear displacement and controller output can be observed online on personal computer. According to the real-time experimental results, the proposed novel type controller gives more effective results than the classic ones.

Optimization of incident EC wave polarization in real-time polarization scan experiments on LHD

International Nuclear Information System (INIS)

Tsujimura, Toru I.; Mizuno, Yoshinori; Makino, Ryohei

2016-01-01

Real-time polarization scan experiments were performed on the Large Helical Device (LHD) to search an optimal incident wave polarization for electron cyclotron resonance heating. The obtained optimal polarization state to maximize the power absorption to the LHD plasma is compared with the ray-tracing code that includes mode content analyses, which indicates that the calculated results are generally in good agreement with the experimental results. The analyses show that optimal coupling to plasma waves requires a fine adjustment for an incident wave polarization even for perpendicular injection due to the finite density profile and the magnetic shear at the peripheral region. (author)

Development of a scalable generic platform for adaptive optics real time control

Science.gov (United States)

Surendran, Avinash; Burse, Mahesh P.; Ramaprakash, A. N.; Parihar, Padmakar

2015-06-01

The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an Adaptive Optics (AO) system, the generation of the Deformable Mirror (DM) control voltages from the Wavefront Sensor (WFS) measurements is usually through the multiplication of the wavefront slopes with a predetermined reconstructor matrix. The ability to access several hundred hard multipliers and memories concurrently in an FPGA allows performance far beyond that of a modern CPU or GPU for tasks with a well-defined structure such as Adaptive Optics control. The target of the current project is to generate a signal for a real time wavefront correction, from the signals coming from a Wavefront Sensor, wherein the system would be flexible to accommodate all the current Wavefront Sensing techniques and also the different methods which are used for wavefront compensation. The system should also accommodate for different data transmission protocols (like Ethernet, USB, IEEE 1394 etc.) for transmitting data to and from the FPGA device, thus providing a more flexible platform for Adaptive Optics control. Preliminary simulation results for the formulation of the platform, and a design of a fully scalable slope computer is presented.

Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

Science.gov (United States)

Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

Optimizing near real time accountability for reprocessing

International Nuclear Information System (INIS)

Cipiti, Benjamin B.

2010-01-01

Near Real Time Accountability (NRTA) of actinides at high precision in reprocessing plants has been a long sought-after goal in the safeguards community. Achieving this goal is hampered by the difficulty of making precision measurements in the reprocessing environment, equipment cost, and impact to plant operations. Thus the design of future reprocessing plants requires an optimization of different approaches. The Separations and Safeguards Performance Model, developed at Sandia National Laboratories, was used to evaluate a number of NRTA strategies in a UREX+ reprocessing plant. Strategies examined include the incorporation of additional actinide measurements of internal plant vessels, more use of process monitoring data, and the option of periodic draining of inventory to key tanks. Preliminary results show that the addition of measurement technologies can increase the overall measurement uncertainty due to additional error propagation, so care must be taken when designing an advanced system. Initial results also show that relying on a combination of different NRTA techniques will likely be the best option. The model provides a platform for integrating all the data. The modeling results for the different NRTA options under various material loss conditions will be presented.

Real - time Optimization of Distributed Energy Storage System Operation Strategy Based on Peak Load Shifting

Science.gov (United States)

Wang, Qian; Lu, Guangqi; Li, Xiaoyu; Zhang, Yichi; Yun, Zejian; Bian, Di

2018-01-01

To take advantage of the energy storage system (ESS) sufficiently, the factors that the service life of the distributed energy storage system (DESS) and the load should be considered when establishing optimization model. To reduce the complexity of the load shifting of DESS in the solution procedure, the loss coefficient and the equal capacity ratio distribution principle were adopted in this paper. Firstly, the model was established considering the constraint conditions of the cycles, depth, power of the charge-discharge of the ESS, the typical daily load curves, as well. Then, dynamic programming method was used to real-time solve the model in which the difference of power Δs, the real-time revised energy storage capacity Sk and the permission error of depth of charge-discharge were introduced to optimize the solution process. The simulation results show that the optimized results was achieved when the load shifting in the load variance was not considered which means the charge-discharge of the energy storage system was not executed. In the meantime, the service life of the ESS would increase.

Study on the Forecast of Ground Motion Parameters from Real Time Earthquake Information Based on Wave Form Data at the Front Site

OpenAIRE

萩原, 由訓; 源栄, 正人; 三辻, 和弥; 野畑, 有秀; Yoshinori, HAGIWARA; Masato, MOTOSAKA; Kazuya, MITSUJI; Arihide, NOBATA; (株)大林組 技術研究所; 東北大学大学院工学研究科; 山形大学地域教育文化学部生活総合学科生活環境科学コース; (株)大林組 技術研究所; Obayashi Corporation Technical Research Institute; Graduate School of Eng., Tohoku University; Faculty of Education, Art and Science, Yamagata University

2011-01-01

The Japan Meteorological Agency(JMA) provides Earthquake Early Warnings(EEW) for advanced users from August 1, 2006. Advanced EEW users can forecaste seismic ground motion (example: Seismic Intensity, Peak Ground Acceleration) from information of the earthquake in EEW. But there are limits to the accuracy and the earliness of the forecasting. This paper describes regression equation to decrease the error and to increase rapidity of the forecast of ground motion parameters from Real Time Earth...

Dynamic Value Engineering Method Optimizing the Risk on Real Time Operating System

Directory of Open Access Journals (Sweden)

Prashant Kumar Patra

2014-04-01

Full Text Available The value engineering is the umbrella of the many more sub-system like quality assurance, quality control, quality function design and development for manufacturability. The system engineering & value engineering is two part of the coin. The value engineering is the high level of technology management for every aspect of engineering fields. The value engineering is the high utilization of System Product (i.e. Processor, Memory & Encryption key, Services, Business and Resources at minimal cost. The high end operating system providing highest services at optimal cost & time. The value engineering provides the maximum performance, accountability, reliability, integrity and availability of processor, memory, encryption key and other inter dependency sub-components. The value engineering is the ratio of the maximum functionality of individual components to the optimal cost. VE=k [(P, M, E, C, A]/optimal cost. Where k is the proportionality constant. The VE is directly proportional to performance of individual components and inversely proportional to the minimal cost. The VE is directly proportional to the risk assessment. The VE maximize the business throughput & decision process mean while minimize the risk and down time. We have to develop the dynamic value engineering model & mechanism for risk optimization over a complex real time operating system This proposed composition model definite will be resolve our objective at top high level. Product

Boat, wake, and wave real-time simulation

Science.gov (United States)

Świerkowski, Leszek; Gouthas, Efthimios; Christie, Chad L.; Williams, Owen M.

2009-05-01

We describe the extension of our real-time scene generation software VIRSuite to include the dynamic simulation of small boats and their wakes within an ocean environment. Extensive use has been made of the programmabilty available in the current generation of GPUs. We have demonstrated that real-time simulation is feasible, even including such complexities as dynamical calculation of the boat motion, wake generation and calculation of an FFTgenerated sea state.

Real-time intelligent pattern recognition algorithm for surface EMG signals

Directory of Open Access Journals (Sweden)

Jahed Mehran

2007-12-01

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

A Finite State Machine Approach to Algorithmic Lateral Inhibition for Real-Time Motion Detection †

Directory of Open Access Journals (Sweden)

María T. López

2018-05-01

Full Text Available Many researchers have explored the relationship between recurrent neural networks and finite state machines. Finite state machines constitute the best-characterized computational model, whereas artificial neural networks have become a very successful tool for modeling and problem solving. The neurally-inspired lateral inhibition method, and its application to motion detection tasks, have been successfully implemented in recent years. In this paper, control knowledge of the algorithmic lateral inhibition (ALI method is described and applied by means of finite state machines, in which the state space is constituted from the set of distinguishable cases of accumulated charge in a local memory. The article describes an ALI implementation for a motion detection task. For the implementation, we have chosen to use one of the members of the 16-nm Kintex UltraScale+ family of Xilinx FPGAs. FPGAs provide the necessary accuracy, resolution, and precision to run neural algorithms alongside current sensor technologies. The results offered in this paper demonstrate that this implementation provides accurate object tracking performance on several datasets, obtaining a high F-score value (0.86 for the most complex sequence used. Moreover, it outperforms implementations of a complete ALI algorithm and a simplified version of the ALI algorithm—named “accumulative computation”—which was run about ten years ago, now reaching real-time processing times that were simply not achievable at that time for ALI.

ELT-scale Adaptive Optics real-time control with thes Intel Xeon Phi Many Integrated Core Architecture

Science.gov (United States)

Jenkins, David R.; Basden, Alastair; Myers, Richard M.

2018-05-01

We propose a solution to the increased computational demands of Extremely Large Telescope (ELT) scale adaptive optics (AO) real-time control with the Intel Xeon Phi Knights Landing (KNL) Many Integrated Core (MIC) Architecture. The computational demands of an AO real-time controller (RTC) scale with the fourth power of telescope diameter and so the next generation ELTs require orders of magnitude more processing power for the RTC pipeline than existing systems. The Xeon Phi contains a large number (≥64) of low power x86 CPU cores and high bandwidth memory integrated into a single socketed server CPU package. The increased parallelism and memory bandwidth are crucial to providing the performance for reconstructing wavefronts with the required precision for ELT scale AO. Here, we demonstrate that the Xeon Phi KNL is capable of performing ELT scale single conjugate AO real-time control computation at over 1.0kHz with less than 20μs RMS jitter. We have also shown that with a wavefront sensor camera attached the KNL can process the real-time control loop at up to 966Hz, the maximum frame-rate of the camera, with jitter remaining below 20μs RMS. Future studies will involve exploring the use of a cluster of Xeon Phis for the real-time control of the MCAO and MOAO regimes of AO. We find that the Xeon Phi is highly suitable for ELT AO real time control.

Optimal task mapping in safety-critical real-time parallel systems

International Nuclear Information System (INIS)

Aussagues, Ch.

1998-01-01

This PhD thesis is dealing with the correct design of safety-critical real-time parallel systems. Such systems constitutes a fundamental part of high-performance systems for command and control that can be found in the nuclear domain or more generally in parallel embedded systems. The verification of their temporal correctness is the core of this thesis. our contribution is mainly in the following three points: the analysis and extension of a programming model for such real-time parallel systems; the proposal of an original method based on a new operator of synchronized product of state machines task-graphs; the validation of the approach by its implementation and evaluation. The work addresses particularly the main problem of optimal task mapping on a parallel architecture, such that the temporal constraints are globally guaranteed, i.e. the timeliness property is valid. The results incorporate also optimally criteria for the sizing and correct dimensioning of a parallel system, for instance in the number of processing elements. These criteria are connected with operational constraints of the application domain. Our approach is based on the off-line analysis of the feasibility of the deadline-driven dynamic scheduling that is used to schedule tasks inside one processor. This leads us to define the synchronized-product, a system of linear, constraints is automatically generated and then allows to calculate a maximum load of a group of tasks and then to verify their timeliness constraints. The communications, their timeliness verification and incorporation to the mapping problem is the second main contribution of this thesis. FInally, the global solving technique dealing with both task and communication aspects has been implemented and evaluated in the framework of the OASIS project in the LETI research center at the CEA/Saclay. (author)

SU-E-J-61: Monitoring Tumor Motion in Real-Time with EPID Imaging During Cervical Cancer Treatment

International Nuclear Information System (INIS)

Mao, W; Hrycushko, B; Yan, Y; Foster, R; Albuquerque, K

2015-01-01

Purpose: Traditional external beam radiotherapy for cervical cancer requires setup by external skin marks. In order to improve treatment accuracy and reduce planning margin for more conformal therapy, it is essential to monitor tumor positions interfractionally and intrafractionally. We demonstrate feasibility of monitoring cervical tumor motion online using EPID imaging from Beam’s Eye View. Methods: Prior to treatment, 1∼2 cylindrical radio opaque markers were implanted into inferior aspect of cervix tumor. During external beam treatments on a Varian 2100C by 4-field 3D plans, treatment beam images were acquired continuously by an EPID. A Matlab program was developed to locate internal markers on MV images. Based on 2D marker positions obtained from different treatment fields, their 3D positions were estimated for every treatment fraction. Results: There were 398 images acquired during different treatment fractions of three cervical cancer patients. Markers were successfully located on every frame of image at an analysis speed of about 1 second per frame. Intrafraction motions were evaluated by comparing marker positions relative to the position on the first frame of image. The maximum intrafraction motion of the markers was 1.6 mm. Interfraction motions were evaluated by comparing 3D marker positions at different treatment fractions. The maximum interfraction motion was up to 10 mm. Careful comparison found that this is due to patient positioning since the bony structures shifted with the markers. Conclusion: This method provides a cost-free and simple solution for online tumor tracking for cervical cancer treatment since it is feasible to acquire and export EPID images with fast analysis in real time. This method does not need any extra equipment or deliver extra dose to patients. The online tumor motion information will be very useful to reduce planning margins and improve treatment accuracy, which is particularly important for SBRT treatment with long

SU-E-J-61: Monitoring Tumor Motion in Real-Time with EPID Imaging During Cervical Cancer Treatment

Energy Technology Data Exchange (ETDEWEB)

Mao, W; Hrycushko, B; Yan, Y; Foster, R; Albuquerque, K [UT Southwestern Medical Center, Dallas, TX (United States)

2015-06-15

Purpose: Traditional external beam radiotherapy for cervical cancer requires setup by external skin marks. In order to improve treatment accuracy and reduce planning margin for more conformal therapy, it is essential to monitor tumor positions interfractionally and intrafractionally. We demonstrate feasibility of monitoring cervical tumor motion online using EPID imaging from Beam’s Eye View. Methods: Prior to treatment, 1∼2 cylindrical radio opaque markers were implanted into inferior aspect of cervix tumor. During external beam treatments on a Varian 2100C by 4-field 3D plans, treatment beam images were acquired continuously by an EPID. A Matlab program was developed to locate internal markers on MV images. Based on 2D marker positions obtained from different treatment fields, their 3D positions were estimated for every treatment fraction. Results: There were 398 images acquired during different treatment fractions of three cervical cancer patients. Markers were successfully located on every frame of image at an analysis speed of about 1 second per frame. Intrafraction motions were evaluated by comparing marker positions relative to the position on the first frame of image. The maximum intrafraction motion of the markers was 1.6 mm. Interfraction motions were evaluated by comparing 3D marker positions at different treatment fractions. The maximum interfraction motion was up to 10 mm. Careful comparison found that this is due to patient positioning since the bony structures shifted with the markers. Conclusion: This method provides a cost-free and simple solution for online tumor tracking for cervical cancer treatment since it is feasible to acquire and export EPID images with fast analysis in real time. This method does not need any extra equipment or deliver extra dose to patients. The online tumor motion information will be very useful to reduce planning margins and improve treatment accuracy, which is particularly important for SBRT treatment with long

Performance evaluation and modeling of a conformal filter (CF) based real-time standoff hazardous material detection sensor

Science.gov (United States)

Nelson, Matthew P.; Tazik, Shawna K.; Bangalore, Arjun S.; Treado, Patrick J.; Klem, Ethan; Temple, Dorota

2017-05-01

Hyperspectral imaging (HSI) systems can provide detection and identification of a variety of targets in the presence of complex backgrounds. However, current generation sensors are typically large, costly to field, do not usually operate in real time and have limited sensitivity and specificity. Despite these shortcomings, HSI-based intelligence has proven to be a valuable tool, thus resulting in increased demand for this type of technology. By moving the next generation of HSI technology into a more adaptive configuration, and a smaller and more cost effective form factor, HSI technologies can help maintain a competitive advantage for the U.S. armed forces as well as local, state and federal law enforcement agencies. Operating near the physical limits of HSI system capability is often necessary and very challenging, but is often enabled by rigorous modeling of detection performance. Specific performance envelopes we consistently strive to improve include: operating under low signal to background conditions; at higher and higher frame rates; and under less than ideal motion control scenarios. An adaptable, low cost, low footprint, standoff sensor architecture we have been maturing includes the use of conformal liquid crystal tunable filters (LCTFs). These Conformal Filters (CFs) are electro-optically tunable, multivariate HSI spectrometers that, when combined with Dual Polarization (DP) optics, produce optimized spectral passbands on demand, which can readily be reconfigured, to discriminate targets from complex backgrounds in real-time. With DARPA support, ChemImage Sensor Systems (CISS™) in collaboration with Research Triangle Institute (RTI) International are developing a novel, real-time, adaptable, compressive sensing short-wave infrared (SWIR) hyperspectral imaging technology called the Reconfigurable Conformal Imaging Sensor (RCIS) based on DP-CF technology. RCIS will address many shortcomings of current generation systems and offer improvements in

Design Optimization of Mixed-Criticality Real-Time Applications on Cost-Constrained Partitioned Architectures

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2011-01-01

In this paper we are interested to implement mixed-criticality hard real-time applications on a given heterogeneous distributed architecture. Applications have different criticality levels, captured by their Safety-Integrity Level (SIL), and are scheduled using static-cyclic scheduling. Mixed......-criticality tasks can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. We consider that the separation is provided by partitioning, such that applications run in separate partitions, and each partition is allocated several time slots on a processor. Tasks...... slots on each processor and (iv) the schedule tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real...

Real Time Hand Motion Reconstruction System for Trans-Humeral Amputees Using EEG and EMG

Directory of Open Access Journals (Sweden)

Jacobo Fernandez-Vargas

2016-08-01

Full Text Available Predicting a hand’s position using only biosignals is a complex problem that has not been completely solved. The only reliable solutions currently available require invasive surgery. The attempts using non-invasive technologies are rare, and usually have led to lower correlation values between the real and the reconstructed position than those required for real-world applications. In this study, we propose a solution for reconstructing the hand’s position in three dimensions using EEG and EMG to detect from the shoulder area. This approach would be valid for most trans-humeral amputees. In order to find the best solution, we tested four different architectures for the system based on artificial neural networks. Our results show that it is possible to reconstruct the hand’s motion trajectory with a correlation value up to 0.809 compared to a typical value in the literature of 0.6. We also demonstrated that both EEG and EMG contribute jointly to the motion reconstruction. Furthermore, we discovered that the system architectures do not change the results radically. In addition, our results suggest that different motions may have different brain activity patterns that could be detected through EEG. Finally, we suggest a method to study non-linear relations in the brain through the EEG signals, which may lead to a more accurate system.

A study on optimal motion for a robot manipulator amid obstacles

International Nuclear Information System (INIS)

Park, Jong Keun

1997-01-01

Optimal motion for a robot manipulator is obtained by nonlinear programming. The objective of optimal motion is minimizing energy consumption of manipulator arm with fixed traveling time in the presence of obstacles. The geometric path is not predetermined. The total trajectory is described in terms of cubic B-spline polynomials and the coefficients of them are obtained to minimize a specific performance index. Obstacle avoidance is performed by the method that the square sum of penetration growth distances between every obstacles and robot links is included in the performance index with appropriate weighting coefficient. In all examples tested here, the solutions were converged to unique optimal trajectories from different initial ones. The optimal geometric path obtained in this research can be used in minimum time trajectory planning. (author)

A Sarsa(λ)-based control model for real-time traffic light coordination.

Science.gov (United States)

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

A Sarsa(λ-Based Control Model for Real-Time Traffic Light Coordination

Directory of Open Access Journals (Sweden)

Xiaoke Zhou

2014-01-01

Full Text Available Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Fuzzy Logic Unmanned Air Vehicle Motion Planning

Directory of Open Access Journals (Sweden)

Chelsea Sabo

2012-01-01

Full Text Available There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.

Adaptive stimulus optimization and model-based experiments for sensory systems neuroscience

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Christopher eDiMattina

2013-06-01

Full Text Available In this paper we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical textit{optimal stimulus} paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the textit{iso-response} paradigm which finds sets of stimuli giving rise to constant responses, and the textit{system identification} paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of nonlinear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify nonlinear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and towards a new paradigm of real-time model estimation and comparison.

Real-time numerical shake prediction and updating for earthquake early warning

Science.gov (United States)

Wang, Tianyun; Jin, Xing; Wei, Yongxiang; Huang, Yandan

2017-12-01

Ground motion prediction is important for earthquake early warning systems, because the region's peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and precisely with limited station wave records, we propose a real-time numerical shake prediction and updating method. Our method first predicts the ground motion based on the ground motion prediction equation after P waves detection of several stations, denoted as the initial prediction. In order to correct the prediction error of the initial prediction, an updating scheme based on real-time simulation of wave propagation is designed. Data assimilation technique is incorporated to predict the distribution of seismic wave energy precisely. Radiative transfer theory and Monte Carlo simulation are used for modeling wave propagation in 2-D space, and the peak ground motion is calculated as quickly as possible. Our method has potential to predict shakemap, making the potential disaster be predicted before the real disaster happens. 2008 M S8.0 Wenchuan earthquake is studied as an example to show the validity of the proposed method.

Route around real time

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

WE-AB-303-06: Combining DAO with MV + KV Optimization to Improve Skin Dose Sparing with Real-Time Fluoroscopy

Energy Technology Data Exchange (ETDEWEB)

Grelewicz, Z; Wiersma, R [The University of Chicago, Chicago, IL (United States)

2015-06-15

Purpose: Real-time fluoroscopy may allow for improved patient positioning and tumor tracking, particularly in the treatment of lung tumors. In order to mitigate the effects of the imaging dose, previous studies have demonstrated the effect of including both imaging dose and imaging constraints into the inverse treatment planning object function. That method of combined MV+kV optimization may Result in plans with treatment beams chosen to allow for more gentle imaging beam-on times. Direct-aperture optimization (DAO) is also known to produce treatment plans with fluence maps more conducive to lower beam-on times. Therefore, in this work we demonstrate the feasibility of a combination of DAO and MV+kV optimization for further optimized real-time kV imaging. Methods: Therapeutic and imaging beams were modeled in the EGSnrc Monte Carlo environment, and applied to a patient model for a previously treated lung patient to provide dose influence matrices from DOSXYZnrc. An MV + kV IMRT DAO treatment planning system was developed to compare DAO treatment plans with and without MV+kV optimization. The objective function was optimized using simulated annealing. In order to allow for comparisons between different cases of the stochastically optimized plans, the optimization was repeated twenty times. Results: Across twenty optimizations, combined MV+kV IMRT resulted in an average of 12.8% reduction in peak skin dose. Both non-optimized and MV+kV optimized imaging beams delivered, on average, mean dose of approximately 1 cGy per fraction to the target, with peak doses to target of approximately 6 cGy per fraction. Conclusion: When using DAO, MV+kV optimization is shown to Result in improvements to plan quality in terms of skin dose, when compared to the case of MV optimization with non-optimized kV imaging. The combination of DAO and MV+kV optimization may allow for real-time imaging without excessive imaging dose. Financial support for the work has been provided in part by NIH

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

Science.gov (United States)

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Real-Time Vehicle Energy Management System Based on Optimized Distribution of Electrical Load Power

Directory of Open Access Journals (Sweden)

Yuefei Wang

2016-10-01

Full Text Available As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%.

Optimal paths of piston motion of irreversible diesel cycle for minimum entropy generation

Directory of Open Access Journals (Sweden)

Ge Yanlin

2011-01-01

Full Text Available A Diesel cycle heat engine with internal and external irreversibility’s of heat transfer and friction, in which the finite rate of combustion is considered and the heat transfer between the working fluid and the environment obeys Newton’s heat transfer law [q≈ Δ(T], is studied in this paper. Optimal piston motion trajectories for minimizing entropy generation per cycle are derived for the fixed total cycle time and fuel consumed per cycle. Optimal control theory is applied to determine the optimal piston motion trajectories for the cases of with piston acceleration constraint on each stroke and the optimal distribution of the total cycle time among the strokes. The optimal piston motion with acceleration constraint for each stroke consists of three segments, including initial maximum acceleration and final maximum deceleration boundary segments, respectively. Numerical examples for optimal configurations are provided, and the results obtained are compared with those obtained when maximizing the work output with Newton’s heat transfer law. The results also show that optimizing the piston motion trajectories could reduce engine entropy generation by more than 20%. This is primarily due to the decrease in entropy generation caused by heat transfer loss on the initial portion of the power stroke.

Validation of Energy Expenditure Prediction Models Using Real-Time Shoe-Based Motion Detectors.

Science.gov (United States)

Lin, Shih-Yun; Lai, Ying-Chih; Hsia, Chi-Chun; Su, Pei-Fang; Chang, Chih-Han

2017-09-01

This study aimed to verify and compare the accuracy of energy expenditure (EE) prediction models using shoe-based motion detectors with embedded accelerometers. Three physical activity (PA) datasets (unclassified, recognition, and intensity segmentation) were used to develop three prediction models. A multiple classification flow and these models were used to estimate EE. The "unclassified" dataset was defined as the data without PA recognition, the "recognition" as the data classified with PA recognition, and the "intensity segmentation" as the data with intensity segmentation. The three datasets contained accelerometer signals (quantified as signal magnitude area (SMA)) and net heart rate (HR net ). The accuracy of these models was assessed according to the deviation between physically measured EE and model-estimated EE. The variance between physically measured EE and model-estimated EE expressed by simple linear regressions was increased by 63% and 13% using SMA and HR net , respectively. The accuracy of the EE predicted from accelerometer signals is influenced by the different activities that exhibit different count-EE relationships within the same prediction model. The recognition model provides a better estimation and lower variability of EE compared with the unclassified and intensity segmentation models. The proposed shoe-based motion detectors can improve the accuracy of EE estimation and has great potential to be used to manage everyday exercise in real time.

MAO-A promoter polymorphism and idiopathic pulmonary arterial ...

Indian Academy of Sciences (India)

Introduction. Monoamine oxidases (MAO) are mitochondrial enzymes ... liver and later in lungs by the enzyme MAO-A, via ox- ... Diagnosis was based on WHO criteria .... treatment of pulmonary arterial hypertension of the European so-.

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

A Study on the Model of Detecting the Variation of Geomagnetic Intensity Based on an Adapted Motion Strategy

Directory of Open Access Journals (Sweden)

Hong Li

2017-12-01

Full Text Available By simulating the geomagnetic fields and analyzing thevariation of intensities, this paper presents a model for calculating the objective function ofan Autonomous Underwater Vehicle (AUVgeomagnetic navigation task. By investigating the biologically inspired strategies, the AUV successfullyreachesthe destination duringgeomagnetic navigation without using the priori geomagnetic map. Similar to the pattern of a flatworm, the proposed algorithm relies on a motion pattern to trigger a local searching strategy by detecting the real-time geomagnetic intensity. An adapted strategy is then implemented, which is biased on the specific target. The results show thereliabilityandeffectivenessofthe proposed algorithm.

Direct aperture optimization for online adaptive radiation therapy

International Nuclear Information System (INIS)

Mestrovic, Ante; Milette, Marie-Pierre; Nichol, Alan; Clark, Brenda G.; Otto, Karl

2007-01-01

This paper is the first investigation of using direct aperture optimization (DAO) for online adaptive radiation therapy (ART). A geometrical model representing the anatomy of a typical prostate case was created. To simulate interfractional deformations, four different anatomical deformations were created by systematically deforming the original anatomy by various amounts (0.25, 0.50, 0.75, and 1.00 cm). We describe a series of techniques where the original treatment plan was adapted in order to correct for the deterioration of dose distribution quality caused by the anatomical deformations. We found that the average time needed to adapt the original plan to arrive at a clinically acceptable plan is roughly half of the time needed for a complete plan regeneration, for all four anatomical deformations. Furthermore, through modification of the DAO algorithm the optimization search space was reduced and the plan adaptation was significantly accelerated. For the first anatomical deformation (0.25 cm), the plan adaptation was six times more efficient than the complete plan regeneration. For the 0.50 and 0.75 cm deformations, the optimization efficiency was increased by a factor of roughly 3 compared to the complete plan regeneration. However, for the anatomical deformation of 1.00 cm, the reduction of the optimization search space during plan adaptation did not result in any efficiency improvement over the original (nonmodified) plan adaptation. The anatomical deformation of 1.00 cm demonstrates the limit of this approach. We propose an innovative approach to online ART in which the plan adaptation and radiation delivery are merged together and performed concurrently--adaptive radiation delivery (ARD). A fundamental advantage of ARD is the fact that radiation delivery can start almost immediately after image acquisition and evaluation. Most of the original plan adaptation is done during the radiation delivery, so the time spent adapting the original plan does not

Motion-Corrected Real-Time Cine Magnetic Resonance Imaging of the Heart: Initial Clinical Experience.

Science.gov (United States)

Rahsepar, Amir Ali; Saybasili, Haris; Ghasemiesfe, Ahmadreza; Dolan, Ryan S; Shehata, Monda L; Botelho, Marcos P; Markl, Michael; Spottiswoode, Bruce; Collins, Jeremy D; Carr, James C

2018-01-01

Free-breathing real-time (RT) imaging can be used in patients with difficulty in breath-holding; however, RT cine imaging typically experiences poor image quality compared with segmented cine imaging because of low resolution. Here, we validate a novel unsupervised motion-corrected (MOCO) reconstruction technique for free-breathing RT cardiac images, called MOCO-RT. Motion-corrected RT uses elastic image registration to generate a single heartbeat of high-quality data from a free-breathing RT acquisition. Segmented balanced steady-state free precession (bSSFP) cine images and free-breathing RT images (Cartesian, TGRAPPA factor 4) were acquired with the same spatial/temporal resolution in 40 patients using clinical 1.5 T magnetic resonance scanners. The respiratory cycle was estimated using the reconstructed RT images, and nonrigid unsupervised motion correction was applied to eliminate breathing motion. Conventional segmented RT and MOCO-RT single-heartbeat cine images were analyzed to evaluate left ventricular (LV) function and volume measurements. Two radiologists scored images for overall image quality, artifact, noise, and wall motion abnormalities. Intraclass correlation coefficient was used to assess the reliability of MOCO-RT measurement. Intraclass correlation coefficient showed excellent reliability (intraclass correlation coefficient ≥ 0.95) of MOCO-RT with segmented cine in measuring LV function, mass, and volume. Comparison of the qualitative ratings indicated comparable image quality for MOCO-RT (4.80 ± 0.35) with segmented cine (4.45 ± 0.88, P = 0.215) and significantly higher than conventional RT techniques (3.51 ± 0.41, P cine (1.51 ± 0.90, P = 0.088 and 1.23 ± 0.45, P = 0.182) were not different. Wall motion abnormality ratings were comparable among different techniques (P = 0.96). The MOCO-RT technique can be used to process conventional free-breathing RT cine images and provides comparable quantitative assessment of LV function and volume

Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach

Science.gov (United States)

Zhang, Honghai; Abiose, Ademola K.; Campbell, Dwayne N.; Sonka, Milan; Martins, James B.; Wahle, Andreas

2010-03-01

Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information-gradient, intensity distributions, and regional-property terms-are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.

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)

ertCPN: The adaptations of the coloured Petri-Net theory for real-time embedded system modeling and automatic code generation

Directory of Open Access Journals (Sweden)

Wattanapong Kurdthongmee

2003-05-01

Full Text Available A real-time system is a computer system that monitors or controls an external environment. The system must meet various timing and other constraints that are imposed on it by the real-time behaviour of the external world. One of the differences between a real-time and a conventional software is that a real-time program must be both logically and temporally correct. To successfully design and implement a real-time system, some analysis is typically done to assure that requirements or designs are consistent and that they satisfy certain desirable properties that may not be immediately obvious from specification. Executable specifications, prototypes and simulation are particularly useful in real-time systems for debugging specifications. In this paper, we propose the adaptations to the coloured Petri-net theory to ease the modeling, simulation and code generation process of an embedded, microcontroller-based, real-time system. The benefits of the proposed approach are demonstrated by use of our prototype software tool called ENVisAge (an Extended Coloured Petri-Net Based Visual Application Generator Tool.

Reference-shaping adaptive control by using gradient descent optimizers.

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Baris Baykant Alagoz

Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.

Developing an optimal valve closing rule curve for real-time pressure control in pipes

Energy Technology Data Exchange (ETDEWEB)

Bazarganlari, Mohammad Reza; Afshar, Hossein [Islamic Azad University, Tehran (Iran, Islamic Republic of); Kerachian, Reza [University of Tehran, Tehran (Iran, Islamic Republic of); Bashiazghadi, Seyyed Nasser [Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

2013-01-15

Sudden valve closure in pipeline systems can cause high pressures that may lead to serious damages. Using an optimal valve closing rule can play an important role in managing extreme pressures in sudden valve closure. In this paper, an optimal closing rule curve is developed using a multi-objective optimization model and Bayesian networks (BNs) for controlling water pressure in valve closure instead of traditional step functions or single linear functions. The method of characteristics is used to simulate transient flow caused by valve closure. Non-dominated sorting genetic algorithms-II is also used to develop a Pareto front among three objectives related to maximum and minimum water pressures, and the amount of water passes through the valve during the valve-closing process. Simulation and optimization processes are usually time-consuming, thus results of the optimization model are used for training the BN. The trained BN is capable of determining optimal real-time closing rules without running costly simulation and optimization models. To demonstrate its efficiency, the proposed methodology is applied to a reservoir-pipe-valve system and the optimal closing rule curve is calculated for the valve. The results of the linear and BN-based valve closure rules show that the latter can significantly reduce the range of variations in water hammer pressures.

Comparative Analysis of Neural Network Training Methods in Real-time Radiotherapy

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Nouri S.

2017-03-01

Full Text Available Background: The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients. Objective: This study evaluates the accuracy of some artificial intelligence methods including neural network and those of combination with genetic algorithm as well as particle swarm optimization (PSO estimating tumor positions in real-time radiotherapy. Method: One hundred recorded signals of three external markers were used as input data. The signals from 3 markers thorough 10 breathing cycles of a patient treated via a cyber-knife for a lung tumor were used as data input. Then, neural network method and its combination with genetic or PSO algorithms were applied determining the tumor locations using MATLAB© software program. Results: The accuracies were obtained 0.8%, 12% and 14% in neural network, genetic and particle swarm optimization algorithms, respectively. Conclusion: The internal target volume (ITV should be determined based on the applied neural network algorithm on training steps.

Analysis of intra-fraction prostate motion and derivation of duration-dependent margins for radiotherapy using real-time 4D ultrasound

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Eric Pei Ping Pang

2018-01-01

Full Text Available Background and purpose: During radiotherapy, prostate motion changes over time. Quantifying and accounting for this motion is essential. This study aimed to assess intra-fraction prostate motion and derive duration-dependent planning margins for two treatment techniques. Material and methods: A four-dimension (4D transperineal ultrasound Clarity® system was used to track prostate motion. We analysed 1913 fractions from 60 patients undergoing volumetric-modulated arc therapy (VMAT to the prostate. The mean VMAT treatment duration was 3.4 min. Extended monitoring was conducted weekly to simulate motion during intensity-modulated radiation therapy (IMRT treatment (an additional seven minutes. A motion-time trend analysis was conducted and the mean intra-fraction motion between VMAT and IMRT treatments compared. Duration-dependent margins were calculated and anisotropic margins for VMAT and IMRT treatments were derived. Results: There were statistically significant differences in the mean intra-fraction motion between VMAT and the simulated IMRT duration in the inferior (0.1 mm versus 0.3 mm and posterior (−0.2 versus −0.4 mm directions respectively (p ≪ 0.01. An intra-fraction motion trend inferiorly and posteriorly was observed. The recommended minimum anisotropic margins are 1.7 mm/2.7 mm (superior/inferior; 0.8 mm (left/right, 1.7 mm/2.9 mm (anterior/posterior for VMAT treatments and 2.9 mm/4.3 mm (superior/inferior, 1.5 mm (left/right, 2.8 mm/4.8 mm (anterior/posterior for IMRT treatments. Smaller anisotropic margins were required for VMAT compared to IMRT (differences ranging from 1.2 to 1.6 mm superiorly/inferiorly, 0.7 mm laterally and 1.1–1.9 mm anteriorly/posteriorly. Conclusions: VMAT treatment is preferred over IMRT as prostate motion increases with time. Larger margins should be employed in the inferior and posterior directions for both treatment durations. Duration-dependent margins should

Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

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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.

Value of Information for Optimal Adaptive Routing in Stochastic Time-Dependent Traffic Networks: Algorithms and Computational Tools

Science.gov (United States)

2010-10-25

Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

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Zadeh, S. M.; Powers, D. M. W.; Sammut, K.; Yazdani, A. M.

2016-12-01

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

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Luo, Biao; Liu, Derong; Wu, Huai-Ning

2018-06-01

Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

Automatic Optimization for Large-Scale Real-Time Coastal Water Simulation

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Shunli Wang

2016-01-01

Full Text Available We introduce an automatic optimization approach for the simulation of large-scale coastal water. To solve the singular problem of water waves obtained with the traditional model, a hybrid deep-shallow-water model is estimated by using an automatic coupling algorithm. It can handle arbitrary water depth and different underwater terrain. As a certain feature of coastal terrain, coastline is detected with the collision detection technology. Then, unnecessary water grid cells are simplified by the automatic simplification algorithm according to the depth. Finally, the model is calculated on Central Processing Unit (CPU and the simulation is implemented on Graphics Processing Unit (GPU. We show the effectiveness of our method with various results which achieve real-time rendering on consumer-level computer.

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

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Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2015-05-01

Motion video analysis is a challenging task, especially in real-time applications. In most safety and security critical applications, a human observer is an obligatory part of the overall analysis system. Over the last years, substantial progress has been made in the development of automated image exploitation algorithms. Hence, we investigate how the benefits of automated video analysis can be integrated suitably into the current video exploitation systems. In this paper, a system design is introduced which strives to combine both the qualities of the human observer's perception and the automated algorithms, thus aiming to improve the overall performance of a real-time video analysis system. The system design builds on prior work where we showed the benefits for the human observer by means of a user interface which utilizes the human visual focus of attention revealed by the eye gaze direction for interaction with the image exploitation system; eye tracker-based interaction allows much faster, more convenient, and equally precise moving target acquisition in video images than traditional computer mouse selection. The system design also builds on prior work we did on automated target detection, segmentation, and tracking algorithms. Beside the system design, a first pilot study is presented, where we investigated how the participants (all non-experts in video analysis) performed in initializing an object tracking subsystem by selecting a target for tracking. Preliminary results show that the gaze + key press technique is an effective, efficient, and easy to use interaction technique when performing selection operations on moving targets in videos in order to initialize an object tracking function.

Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images

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Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun

2014-01-01

We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.

A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

International Nuclear Information System (INIS)

Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth

2015-01-01

In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. (author)

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

Science.gov (United States)

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

2014-09-30

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

Supervisory Control for Real Time Reactive Power Flow Optimization in Islanded Microgrids

DEFF Research Database (Denmark)

Milczarek, Adam; Vasquez, Juan Carlos; Malinowski, Mariusz

2013-01-01

-line measurements. Similarly to any process system, MG hierarchical control is divided into three levels. However, an additional control algorithm is required to manage power transmission between sources and loads, maximizing efficiency and minimizing transmission losses. This real-time optimization problem......A microgrid (MG) is a local energy system consisting of a number of energy sources, energy storage units and loads that operate connected to the main electrical grid or autonomously. MGs include wind, solar or other renewable energy sources. MGs provide flexibility, reduce the main electricity grid...... dependence and contribute to change the large centralized production paradigm to local and distributed generation. However, such energy systems require complex management, advanced control and optimization. Interest on MGs hierarchical control has increased due to the availability of cheap on...

Asymmetry of Drosophila ON and OFF motion detectors enhances real-world velocity estimation.