WorldWideScience

Sample records for real-time model attitude

  1. Real Time Assessment of Young Adults' Attitudes toward Tobacco Messages.

    Science.gov (United States)

    Hébert, Emily T; Vandewater, Elizabeth A; Businelle, Michael S; Harrell, Melissa B; Kelder, Steven H; Perry, Cheryl L

    2018-01-01

    We used ecological momentary assessment (EMA) to examine young adults' attitudes towards pro-tobacco messages encountered in real time and their association with intentions to use tobacco. Young adults (N = 92, ages 18-29) recorded sightings of marketing or social media related to tobacco in real time via mobile app for 28 days. Participants reported message characteristics, their attitudes towards the message, and intentions to use the depicted product for each submission. We used generalized linear mixed models to examine factors related to attitude towards message and intentions to use tobacco. Messages depicting e-cigarettes (p < .001) or hookah (p < .05) were associated with significantly more favorable attitudes compared with traditional cigarettes. Positive attitude towards the message was significantly associated with intention to use the depicted product (p < .001). Messages depicting e-cigarettes and hookah were significantly associated with higher intention to use. Message source was not significantly related to attitudes towards the message or product use intentions. Marketing featuring e-cigarettes and hookah is an important target for future regulation. Given that pro-tobacco and e-cigarette messages are prevalent online, future research should consider the Internet and social media as important venues for counter-marketing and intervention efforts.

  2. Model Checking Real-Time Systems

    DEFF Research Database (Denmark)

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

    2018-01-01

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

  3. Compiling models into real-time systems

    International Nuclear Information System (INIS)

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

    1992-08-01

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

  4. Compiling models into real-time systems

    International Nuclear Information System (INIS)

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

    1992-08-01

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

  5. Real-time modeling of heat distributions

    Science.gov (United States)

    Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas

    2018-01-02

    Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.

  6. RTMOD: Real-Time MODel evaluation

    International Nuclear Information System (INIS)

    Graziani, G; Galmarini, S.; Mikkelsen, T.

    2000-01-01

    The 1998 - 1999 RTMOD project is a system based on an automated statistical evaluation for the inter-comparison of real-time forecasts produced by long-range atmospheric dispersion models for national nuclear emergency predictions of cross-boundary consequences. The background of RTMOD was the 1994 ETEX project that involved about 50 models run in several Institutes around the world to simulate two real tracer releases involving a large part of the European territory. In the preliminary phase of ETEX, three dry runs (i.e. simulations in real-time of fictitious releases) were carried out. At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax and regular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained during the ETEX exercises suggested the development of this project. RTMOD featured a web-based user-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis of the forecasts. RTMOD has focussed on model intercomparison of concentration predictions at the nodes of a regular grid with 0.5 degrees of resolution both in latitude and in longitude, the domain grid extending from 5W to 40E and 40N to 65N. Hypothetical releases were notified around the world to the 28 model forecasters via the web on a one-day warning in advance. They then accessed the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modelers. When additional forecast data arrived, already existing statistical results would be recalculated to include the influence by all available predictions. The new web-based RTMOD concept has proven useful as a practical decision-making tool for realtime

  7. Turbine modelling for real time simulators

    International Nuclear Information System (INIS)

    Oliveira Barroso, A.C. de; Araujo Filho, F. de

    1992-01-01

    A model for vapor turbines and its peripherals has been developed. All the important variables have been included and emphasis has been given for the computational efficiency to obtain a model able to simulate all the modeled equipment. (A.C.A.S.)

  8. Real time natural object modeling framework

    International Nuclear Information System (INIS)

    Rana, H.A.; Shamsuddin, S.M.; Sunar, M.H.

    2008-01-01

    CG (Computer Graphics) is a key technology for producing visual contents. Currently computer generated imagery techniques are being developed and applied, particularly in the field of virtual reality applications, film production, training and flight simulators, to provide total composition of realistic computer graphic images. Natural objects like clouds are an integral feature of the sky without them synthetic outdoor scenes seem unrealistic. Modeling and animating such objects is a difficult task. Most systems are difficult to use, as they require adjustment of numerous, complex parameters and are non-interactive. This paper presents an intuitive, interactive system to artistically model, animate, and render visually convincing clouds using modern graphics hardware. A high-level interface models clouds through the visual use of cubes. Clouds are rendered by making use of hardware accelerated API -OpenGL. The resulting interactive design and rendering system produces perceptually convincing cloud models that can be used in any interactive system. (author)

  9. Adaptive Modeling and Real-Time Simulation

    Science.gov (United States)

    1984-01-01

    34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

  10. Real-Time Vocal Tract Modelling

    Directory of Open Access Journals (Sweden)

    K. Benkrid

    2008-03-01

    Full Text Available To date, most speech synthesis techniques have relied upon the representation of the vocal tract by some form of filter, a typical example being linear predictive coding (LPC. This paper describes the development of a physiologically realistic model of the vocal tract using the well-established technique of transmission line modelling (TLM. This technique is based on the principle of wave scattering at transmission line segment boundaries and may be used in one, two, or three dimensions. This work uses this technique to model the vocal tract using a one-dimensional transmission line. A six-port scattering node is applied in the region separating the pharyngeal, oral, and the nasal parts of the vocal tract.

  11. RTMOD: Real-Time MODel evaluation

    DEFF Research Database (Denmark)

    Graziani, G.; Galmarini, S.; Mikkelsen, Torben

    2000-01-01

    the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modellers. When additionalforecast data arrived, already existing statistical results....... At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax andregular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained...... during the ETEX exercises suggested the development of this project. RTMOD featured a web-baseduser-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis of the forecasts. RTMOD has focussed on model intercomparison of concentration...

  12. Mechatronic modeling of real-time wheel-rail contact

    CERN Document Server

    Bosso, Nicola; Gugliotta, Antonio; Somà, Aurelio

    2013-01-01

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

  13. Real-time advanced nuclear reactor core model

    International Nuclear Information System (INIS)

    Koclas, J.; Friedman, F.; Paquette, C.; Vivier, P.

    1990-01-01

    The paper describes a multi-nodal advanced nuclear reactor core model. The model is based on application of modern equivalence theory to the solution of neutron diffusion equation in real time employing the finite differences method. The use of equivalence theory allows the application of the finite differences method to cores divided into hundreds of nodes, as opposed to the much finer divisions (in the order of ten thousands of nodes) where the unmodified method is currently applied. As a result the model can be used for modelling of the core kinetics for real time full scope training simulators. Results of benchmarks, validate the basic assumptions of the model and its applicability to real-time simulation. (orig./HP)

  14. On-orbit real-time magnetometer bias determination for micro-satellites without attitude information

    Directory of Open Access Journals (Sweden)

    Zhang Zhen

    2015-10-01

    Full Text Available Due to the disadvantages such as complex calculation, low accuracy of estimation, and being non real time in present methods, a new real-time algorithm is developed for on-orbit magnetometer bias determination of micro-satellites without attitude knowledge in this paper. This method uses the differential value approach. It avoids the impact of quartic nature and uses the iterative method to satisfy real-time applications. Simulation results indicate that the new real-time algorithm is more accurate compared with other methods, which are also tested by an experiment system using real noise data. With the new real-time algorithm, a magnetometer calibration can be taken on-orbit and will reduce the demand for computing power effectively.

  15. Real-time Social Internet Data to Guide Forecasting Models

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-09-20

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

  16. Model-Checking Real-Time Control Programs

    DEFF Research Database (Denmark)

    Iversen, T. K.; Kristoffersen, K. J.; Larsen, Kim Guldstrand

    2000-01-01

    In this paper, we present a method for automatic verification of real-time control programs running on LEGO(R) RCX(TM) bricks using the verification tool UPPALL. The control programs, consisting of a number of tasks running concurrently, are automatically translated into the mixed automata model...... of UPPAAL. The fixed scheduling algorithm used by the LEGO(R) RCX(TM) processor is modeled in UPPALL, and supply of similar (sufficient) timed automata models for the environment allows analysis of the overall real-time system using the tools of UPPALL. To illustrate our technique for sorting LEGO(R) bricks...

  17. Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

    Science.gov (United States)

    Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

    2013-09-01

    In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

  18. A Model for Industrial Real-Time Systems

    DEFF Research Database (Denmark)

    Bin Waez, Md Tawhid; Wasowski, Andrzej; Dingel, Juergen

    2015-01-01

    Introducing automated formal methods for large industrial real-time systems is an important research challenge. We propose timed process automata (TPA) for modeling and analysis of time-critical systems which can be open, hierarchical, and dynamic. The model offers two essential features for large...

  19. Real time hardware-in-loop simulation of ESMO satellite attitude control system

    Directory of Open Access Journals (Sweden)

    Rune Finnset

    2006-04-01

    Full Text Available This paper studies attitude control of the ESMO satellite using six reaction thrusters. Bang-bang control with dead-zone and Pulse-Width Modulation (PWM for the modulation of the on-time of the thrusters are treated. Closed loop hardware-in-loop simulations, using themicrocontroller unit (MCU Microchip PIC18F452 for implementation of attitude control and MatLab in a standard PC for simulating satellite dynamics, are carried out. Results for real time simulation are compared with autonomous simulations. The controller gives a satisfactory performance in the real time environment.

  20. Modeling and Analyzing Real-Time Multiprocessor Systems

    NARCIS (Netherlands)

    Wiggers, M.H.; Thiele, Lothar; Lee, Edward A.; Schlieker, Simon; Bekooij, Marco Jan Gerrit

    2010-01-01

    Researchers have proposed approaches to verify that real-time multiprocessor systems meet their timeliness constraints. These approaches make assumptions on the model of computation, the load placed on the multiprocessor system, and the faults that can arise. This heterogeneous set of assumptions

  1. Modelling and analysis of real-time and hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Olivero, A

    1994-09-29

    This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.

  2. Automated Predicate Abstraction for Real-Time Models

    Directory of Open Access Journals (Sweden)

    Bahareh Badban

    2009-11-01

    Full Text Available We present a technique designed to automatically compute predicate abstractions for dense real-timed models represented as networks of timed automata. We use the CIPM algorithm in our previous work which computes new invariants for timed automata control locations and prunes the model, to compute a predicate abstraction of the model. We do so by taking information regarding control locations and their newly computed invariants into account.

  3. Real-time individualization of the unified model of performance.

    Science.gov (United States)

    Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques

    2017-12-01

    Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.

  4. Model Checking Real Time Java Using Java PathFinder

    Science.gov (United States)

    Lindstrom, Gary; Mehlitz, Peter C.; Visser, Willem

    2005-01-01

    The Real Time Specification for Java (RTSJ) is an augmentation of Java for real time applications of various degrees of hardness. The central features of RTSJ are real time threads; user defined schedulers; asynchronous events, handlers, and control transfers; a priority inheritance based default scheduler; non-heap memory areas such as immortal and scoped, and non-heap real time threads whose execution is not impeded by garbage collection. The Robust Software Systems group at NASA Ames Research Center has JAVA PATHFINDER (JPF) under development, a Java model checker. JPF at its core is a state exploring JVM which can examine alternative paths in a Java program (e.g., via backtracking) by trying all nondeterministic choices, including thread scheduling order. This paper describes our implementation of an RTSJ profile (subset) in JPF, including requirements, design decisions, and current implementation status. Two examples are analyzed: jobs on a multiprogramming operating system, and a complex resource contention example involving autonomous vehicles crossing an intersection. The utility of JPF in finding logic and timing errors is illustrated, and the remaining challenges in supporting all of RTSJ are assessed.

  5. Robust Real-Time Musculoskeletal Modeling Driven by Electromyograms.

    Science.gov (United States)

    Durandau, Guillaume; Farina, Dario; Sartori, Massimo

    2018-03-01

    Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses with biomechanical models not operating in real-time for man-machine interfacing. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human. We used electromyography (EMG)-driven musculoskeletal modeling to simulate all transformations from muscle excitation onset (EMGs) to mechanical moment production around multiple lower-limb degrees of freedom (DOFs). We developed a calibration algorithm that enables adjusting musculoskeletal model parameters specifically to an individual's anthropometry and force-generating capacity. We incorporated the modeling paradigm into a computationally efficient, generic framework that can be interfaced in real-time with any movement data collection system. The framework demonstrated the ability of computing forces in 13 lower-limb muscle-tendon units and resulting moments about three joint DOFs simultaneously in real-time. Remarkably, it was capable of extrapolating beyond calibration conditions, i.e., predicting accurate joint moments during six unseen tasks and one unseen DOF. The proposed framework can dramatically reduce evaluation latency in current clinical biomechanics and open up new avenues for establishing prompt and personalized treatments, as well as for establishing natural interfaces between patients and rehabilitation systems. The integration of EMG with numerical modeling will enable simulating realistic neuromuscular strategies in conditions including muscular/orthopedic deficit, which could not be robustly simulated via pure modeling formulations. This will enable translation to clinical settings and development of healthcare technologies including real-time bio-feedback of internal mechanical forces and direct patient-machine interfacing.

  6. Real-time Face Detection using Skin Color Model

    Institute of Scientific and Technical Information of China (English)

    LU Yao-xin; LIU Zhi-Qiang; ZHU Xiang-hua

    2004-01-01

    This paper presents a new face detection approach to real-time applications, which is based on the skin color model and the morphological filtering. First the non-skin color pixels of the input image are removed based on the skin color model in the YCrCb chrominance space, from which we extract candidate human face regions. Then a mathematical morphological filter is used to remove noisy regions and fill the holes in the candidate skin color regions. We adopt the similarity between the human face features and the candidate face regions to locate the face regions in the original image. We have implemented the algorithm in our smart media system. The experiment results show that this system is effective in real-time applications.

  7. Application of Real Time Models Updating in ABO Central Field

    International Nuclear Information System (INIS)

    Heikal, S.; Adewale, D.; Doghmi, A.; Augustine, U.

    2003-01-01

    ABO central field is the first deep offshore oil production in Nigeria located in OML 125 (ex-OPL316). The field was developed in a water depth of between 500 and 800 meters. Deep-water development requires much faster data handling and model updates in order to make the best possible technical decision. This required an easy way to incorporate the latest information and dynamic update of the reservoir model enabling real time reservoir management. The paper aims at discussing the benefits of real time static and dynamic model update and illustrates with a horizontal well example how this update was beneficial prior and during the drilling operation minimizing the project CAPEX Prior to drilling, a 3D geological model was built based on seismic and offset wells' data. The geological model was updated twice, once after the pilot hole drilling and then after reaching the landing point and prior drilling the horizontal section .Forward modeling ws made was well using the along the planned trajectory. During the drilling process both geo- steering and LWD data were loaded in real time to the 3D modeling software. The data was analyzed and compared with the predicted model. The location of markers was changed as drilling progressed and the entire 3D Geological model was rapidly updated. The target zones were revaluated in the light of the new model updates. Recommendations were communicated to the field, and the well trajectory was modified to take into account the new information. The combination of speed, flexibility and update-ability of the 3D modeling software enabled continues geological model update on which the asset team based their trajectory modification decisions throughout the drilling phase. The well was geo-steered through 7 meters thickness of sand. After the drilling, the testing showed excellent results with a productivity and fluid properties data were used to update the dynamic model reviewing the well production plateau providing optimum reservoir

  8. D Model Visualization Enhancements in Real-Time Game Engines

    Science.gov (United States)

    Merlo, A.; Sánchez Belenguer, C.; Vendrell Vidal, E.; Fantini, F.; Aliperta, A.

    2013-02-01

    This paper describes two procedures used to disseminate tangible cultural heritage through real-time 3D simulations providing accurate-scientific representations. The main idea is to create simple geometries (with low-poly count) and apply two different texture maps to them: a normal map and a displacement map. There are two ways to achieve models that fit with normal or displacement maps: with the former (normal maps), the number of polygons in the reality-based model may be dramatically reduced by decimation algorithms and then normals may be calculated by rendering them to texture solutions (baking). With the latter, a LOD model is needed; its topology has to be quad-dominant for it to be converted to a good quality subdivision surface (with consistent tangency and curvature all over). The subdivision surface is constructed using methodologies for the construction of assets borrowed from character animation: these techniques have been recently implemented in many entertainment applications known as "retopology". The normal map is used as usual, in order to shade the surface of the model in a realistic way. The displacement map is used to finish, in real-time, the flat faces of the object, by adding the geometric detail missing in the low-poly models. The accuracy of the resulting geometry is progressively refined based on the distance from the viewing point, so the result is like a continuous level of detail, the only difference being that there is no need to create different 3D models for one and the same object. All geometric detail is calculated in real-time according to the displacement map. This approach can be used in Unity, a real-time 3D engine originally designed for developing computer games. It provides a powerful rendering engine, fully integrated with a complete set of intuitive tools and rapid workflows that allow users to easily create interactive 3D contents. With the release of Unity 4.0, new rendering features have been added, including Direct

  9. Real-Time System for Water Modeling and Management

    Science.gov (United States)

    Lee, J.; Zhao, T.; David, C. H.; Minsker, B.

    2012-12-01

    Working closely with the Texas Commission on Environmental Quality (TCEQ) and the University of Texas at Austin (UT-Austin), we are developing a real-time system for water modeling and management using advanced cyberinfrastructure, data integration and geospatial visualization, and numerical modeling. The state of Texas suffered a severe drought in 2011 that cost the state $7.62 billion in agricultural losses (crops and livestock). Devastating situations such as this could potentially be avoided with better water modeling and management strategies that incorporate state of the art simulation and digital data integration. The goal of the project is to prototype a near-real-time decision support system for river modeling and management in Texas that can serve as a national and international model to promote more sustainable and resilient water systems. The system uses National Weather Service current and predicted precipitation data as input to the Noah-MP Land Surface model, which forecasts runoff, soil moisture, evapotranspiration, and water table levels given land surface features. These results are then used by a river model called RAPID, along with an error model currently under development at UT-Austin, to forecast stream flows in the rivers. Model forecasts are visualized as a Web application for TCEQ decision makers, who issue water diversion (withdrawal) permits and any needed drought restrictions; permit holders; and reservoir operation managers. Users will be able to adjust model parameters to predict the impacts of alternative curtailment scenarios or weather forecasts. A real-time optimization system under development will help TCEQ to identify optimal curtailment strategies to minimize impacts on permit holders and protect health and safety. To develop the system we have implemented RAPID as a remotely-executed modeling service using the Cyberintegrator workflow system with input data downloaded from the North American Land Data Assimilation System. The

  10. Variable slip wind generator modeling for real-time simulation

    Energy Technology Data Exchange (ETDEWEB)

    Gagnon, R.; Brochu, J.; Turmel, G. [Hydro-Quebec, Varennes, PQ (Canada). IREQ

    2006-07-01

    A model of a wind turbine using a variable slip wound-rotor induction machine was presented. The model was created as part of a library of generic wind generator models intended for wind integration studies. The stator winding of the wind generator was connected directly to the grid and the rotor was driven by the turbine through a drive train. The variable resistors was synthesized by an external resistor in parallel with a diode rectifier. A forced-commutated power electronic device (IGBT) was connected to the wound rotor by slip rings and brushes. Simulations were conducted in a Matlab/Simulink environment using SimPowerSystems blocks to model power systems elements and Simulink blocks to model the turbine, control system and drive train. Detailed descriptions of the turbine, the drive train and the control system were provided. The model's implementation in the simulator was also described. A case study demonstrating the real-time simulation of a wind generator connected at the distribution level of a power system was presented. Results of the case study were then compared with results obtained from the SimPowerSystems off-line simulation. Results showed good agreement between the waveforms, demonstrating the conformity of the real-time and the off-line simulations. The capability of Hypersim for real-time simulation of wind turbines with power electronic converters in a distribution network was demonstrated. It was concluded that hardware-in-the-loop (HIL) simulation of wind turbine controllers for wind integration studies in power systems is now feasible. 5 refs., 1 tab., 6 figs.

  11. Real-time expert systems and deep knowledge models

    International Nuclear Information System (INIS)

    Felkel, L.

    1990-01-01

    To guide operators in normal and disturbed plant conditions expert systems are feasible. These, however, must be on-line and real-time systems. The knowledge contained in such a system cannot be represented in a 'classical' role-based manner. The paper describes problems and solutions with regard to process reference models as these are important in order to provide so-called deep-knowledge for the operators. The system described is being implemented and is meant to support both diagnosis and prediction

  12. Dynamic Modeling and Real-Time Monitoring of Froth Flotation

    Directory of Open Access Journals (Sweden)

    Khushaal Popli

    2015-08-01

    Full Text Available A dynamic fundamental model was developed linking processes from the microscopic scale to the equipment scale for batch froth flotation. State estimation, fault detection, and disturbance identification were implemented using the extended Kalman filter (EKF, which reconciles real-time measurements with dynamic models. The online measurements for the EKF were obtained through image analysis of froth images that were captured and analyzed using the commercial package VisioFroth (Metsor Minerals. The extracted image features were then correlated to recovery using principal component analysis and partial least squares regression. The performance of real-time state estimation and fault detection was validated using batch flotation of pure galena at various operating conditions. The image features that were strongly representative of recovery were identified, and calibration and validation were performed against off-line measurements of recovery. The EKF successfully captured the dynamics of the process by updating the model states and parameters using the online measurements. Finally, disturbances in the air flow rate and impeller speed were introduced into the system, and the dynamic behavior of the flotation process was successfully tracked and the disturbances were identified using state estimation.

  13. A Circuit Model of Real Time Human Body Hydration.

    Science.gov (United States)

    Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H

    2016-06-01

    Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration.

  14. Designers workbench: toward real-time immersive modeling

    Science.gov (United States)

    Kuester, Falko; Duchaineau, Mark A.; Hamann, Bernd; Joy, Kenneth I.; Ma, Kwan-Liu

    2000-05-01

    This paper introduces the Designers Workbench, a semi- immersive virtual environment for two-handed modeling, sculpting and analysis tasks. The paper outlines the fundamental tools, design metaphors and hardware components required for an intuitive real-time modeling system. As companies focus on streamlining productivity to cope with global competition, the migration to computer-aided design (CAD), computer-aided manufacturing, and computer-aided engineering systems has established a new backbone of modern industrial product development. However, traditionally a product design frequently originates form a clay model that, after digitization, forms the basis for the numerical description of CAD primitives. The Designers Workbench aims at closing this technology or 'digital gap' experienced by design and CAD engineers by transforming the classical design paradigm into its fully integrate digital and virtual analog allowing collaborative development in a semi- immersive virtual environment. This project emphasizes two key components form the classical product design cycle: freeform modeling and analysis. In the freedom modeling stage, content creation in the form of two-handed sculpting of arbitrary objects using polygonal, volumetric or mathematically defined primitives is emphasized, whereas the analysis component provides the tools required for pre- and post-processing steps for finite element analysis tasks applied to the created models.

  15. Real time tracking by LOPF algorithm with mixture model

    Science.gov (United States)

    Meng, Bo; Zhu, Ming; Han, Guangliang; Wu, Zhiguo

    2007-11-01

    A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

  16. Real time traffic models, decision support for traffic management

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  17. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  18. Modelling and analysis of real-time coordination patterns

    NARCIS (Netherlands)

    Kemper, Stephanie

    2011-01-01

    Present-day embedded software systems need to support an increasing number of features and formalisms; the two most important ones being handling of real-time, and the possibility to develop the system in a modular, component-based way. To ensure that the behaviour of the final system is correct

  19. Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)

    2006-11-01

    The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensor packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging

  20. Radiation environmental real-time monitoring and dispersion modeling

    International Nuclear Information System (INIS)

    Kovacik, A.; Bartokova, I.; Omelka, J.; Melicherova, T.

    2014-01-01

    The system of real-time radiation monitoring provided by MicroStep-MIS is a turn-key solution for measurement, acquisition, processing, reporting, archiving and displaying of various radiation data. At the level of measurements, the monitoring stations can be equipped with various devices from radiation probes, measuring the actual ambient gamma dose rate, to fully automated aerosol monitors, returning analysis results of natural and manmade radionuclides concentrations in the air. Using data gathered by our radiation probes RPSG-05 integrated into monitoring network of Crisis Management of the Slovak Republic and into monitoring network of Slovak Hydrometeorological Institute, we demonstrate its reliability and long-term stability of measurements. Data from RPSG-05 probes and GammaTracer probes, both of these types are used in the SHI network, are compared. The sensitivity of RPSG-05 is documented on data where changes of dose rate are caused by precipitation. Qualities of RPSG-05 probe are illustrated also on example of its use in radiation monitoring network in the United Arab Emirates. A more detailed information about radioactivity of the atmosphere can be obtained by using spectrometric detectors (e.g. scintillation detectors) which, besides gamma dose rate values, offer also a possibility to identify different radionuclides. However, this possibility is limited by technical parameters of detector like energetic resolution and detection efficiency in given geometry of measurement. A clearer information with less doubts can be obtained from aerosol monitors with a built-in silicon detector of alpha and beta particles and with an electrically cooled HPGe detector dedicated for gamma-ray spectrometry, which is performed during the sampling. Data from a complex radiation monitoring network can be used, together with meteorological data, in radiation dispersion model by MicroStep-MIS. This model serves for simulation of atmospheric propagation of radionuclides

  1. Real-time micro-modelling of city evacuations

    Science.gov (United States)

    Löhner, Rainald; Haug, Eberhard; Zinggerling, Claudio; Oñate, Eugenio

    2018-01-01

    A methodology to integrate geographical information system (GIS) data with large-scale pedestrian simulations has been developed. Advances in automatic data acquisition and archiving from GIS databases, automatic input for pedestrian simulations, as well as scalable pedestrian simulation tools have made it possible to simulate pedestrians at the individual level for complete cities in real time. An example that simulates the evacuation of the city of Barcelona demonstrates that this is now possible. This is the first step towards a fully integrated crowd prediction and management tool that takes into account not only data gathered in real time from cameras, cell phones or other sensors, but also merges these with advanced simulation tools to predict the future state of the crowd.

  2. Radiation environmental real-time monitoring and dispersion modelling

    International Nuclear Information System (INIS)

    Kovacik, Andrej; Bartokova, Ivana; Melicherova, Terezia; Omelka, Jozef

    2015-01-01

    The MicroStep-MIS system of real-time radiation monitoring, which provides a turn-key solution for measurement, acquisition, processing, reporting, archiving and displaying of various radiation data, is described and discussed in detail. The qualities, long-term stability of measurement and sensitivity of the RPSG-05 probe are illustrated on its use within the radiation monitoring network of the Slovak Hydrometeorological Institute and within the monitoring network in the United Arab Emirates. (orig.)

  3. Real-Time Single-Frequency GPS/MEMS-IMU Attitude Determination of Lightweight UAVs

    Science.gov (United States)

    Eling, Christian; Klingbeil, Lasse; Kuhlmann, Heiner

    2015-01-01

    In this paper, a newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented. The system is intended to provide highly accurate positions and attitudes (better than 5 cm and 0.5∘) in real time, using lightweight components. The main focus of this paper is on the attitude determination with the system. This attitude determination is based on an onboard single-frequency GPS baseline, MEMS (micro-electro-mechanical systems) inertial sensor readings, magnetic field observations and a 3D position measurement. All of this information is integrated in a sixteen-state error space Kalman filter. Special attention in the algorithm development is paid to the carrier phase ambiguity resolution of the single-frequency GPS baseline observations. We aim at a reliable and instantaneous ambiguity resolution, since the system is used in urban areas, where frequent losses of the GPS signal lock occur and the GPS measurement conditions are challenging. Flight tests and a comparison to a navigation-grade inertial navigation system illustrate the performance of the developed system in dynamic situations. Evaluations show that the accuracies of the system are 0.05∘ for the roll and the pitch angle and 0.2∘ for the yaw angle. The ambiguities of the single-frequency GPS baseline can be resolved instantaneously in more than 90% of the cases. PMID:26501281

  4. Real-time probabilistic covariance tracking with efficient model update.

    Science.gov (United States)

    Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li

    2012-05-01

    The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.

  5. Applying MDA to SDR for Space to Model Real-time Issues

    Science.gov (United States)

    Blaser, Tammy M.

    2007-01-01

    NASA space communications systems have the challenge of designing SDRs with highly-constrained Size, Weight and Power (SWaP) resources. A study is being conducted to assess the effectiveness of applying the MDA Platform-Independent Model (PIM) and one or more Platform-Specific Models (PSM) specifically to address NASA space domain real-time issues. This paper will summarize our experiences with applying MDA to SDR for Space to model real-time issues. Real-time issues to be examined, measured, and analyzed are: meeting waveform timing requirements and efficiently applying Real-time Operating System (RTOS) scheduling algorithms, applying safety control measures, and SWaP verification. Real-time waveform algorithms benchmarked with the worst case environment conditions under the heaviest workload will drive the SDR for Space real-time PSM design.

  6. WCET Analysis of ARM Processors using Real-Time Model Checking

    DEFF Research Database (Denmark)

    Toft, Martin; Olesen, Mads Christian; Dalsgaard, Andreas

    2009-01-01

    This paper presents a flexible method that utilises real-time model checking to determine safe and sharp WCETs for processes running on hardware platforms featuring pipelining and caching.......This paper presents a flexible method that utilises real-time model checking to determine safe and sharp WCETs for processes running on hardware platforms featuring pipelining and caching....

  7. Real-time GIS data model and sensor web service platform for environmental data management.

    Science.gov (United States)

    Gong, Jianya; Geng, Jing; Chen, Zeqiang

    2015-01-09

    Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

  8. Real time modeling, simulation and control of dynamical systems

    CERN Document Server

    Mughal, Asif Mahmood

    2016-01-01

    This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.

  9. Real-time dispersion calculation using the Lagrange model LASAT

    International Nuclear Information System (INIS)

    Janicke, L.

    1987-01-01

    The LASAT (Lagrange Simulation of Aerosol Transport) dispersion model demonstrates pollutant transport in the atmosphere by simulating the paths of representative random samples of pollutant particles on the computer as natural as possible. The author demonstrates the generated particle paths and refers to literature for details of the model algorithm. (DG) [de

  10. A better understanding of ambulance personnel's attitude towards real-time resuscitation feedback.

    Science.gov (United States)

    Brinkrolf, Peter; Lukas, Roman; Harding, Ulf; Thies, Sebastian; Gerss, Joachim; Van Aken, Hugo; Lemke, Hans; Schniedermeier, Udo; Bohn, Andreas

    2018-03-01

    High-quality chest compressions during cardiopulmonary resuscitation (CPR) play a significant role in surviving cardiac arrest. Chest-compression quality can be measured and corrected by real-time CPR feedback devices, which are not yet commonly used. This article looks at the acceptance of such systems in comparison of equipped and unequipped personnel. Two groups of emergency medical services' (EMS) personnel were interviewed using standardized questionnaires. The survey was conducted in the German cities Dortmund and Münster. Overall, 205 persons participated in the survey: 103 paramedics and emergency physicians from the Dortmund fire service and 102 personnel from the Münster service. The staff of the Dortmund service were not equipped with real-time feedback systems. The test group of equipped personnel of the ambulance service of Münster Fire brigade uses real-time feedback systems since 2007. What is the acceptance level of real-time feedback systems? Are there differences between equipped and unequipped personnel? The total sample is receptive towards real-time feedback systems. More than 80% deem the system useful. However, this study revealed concerns and prejudices by unequipped personnel. Negative ratings are significantly lower at the Münster site that is experienced with the use of the real-time feedback system in contrast to the Dortmund site where no such experience exists-the system's use in daily routine results in better evaluation than the expectations of unequipped personnel. Real-time feedback systems receive overall positive ratings. Prejudices and concerns seem to decrease with continued use of the system.

  11. Real-time model for simulating a tracked vehicle on deformable soils

    Directory of Open Access Journals (Sweden)

    Martin Meywerk

    2016-05-01

    Full Text Available Simulation is one possibility to gain insight into the behaviour of tracked vehicles on deformable soils. A lot of publications are known on this topic, but most of the simulations described there cannot be run in real-time. The ability to run a simulation in real-time is necessary for driving simulators. This article describes an approach for real-time simulation of a tracked vehicle on deformable soils. The components of the real-time model are as follows: a conventional wheeled vehicle simulated in the Multi Body System software TRUCKSim, a geometric description of landscape, a track model and an interaction model between track and deformable soils based on Bekker theory and Janosi–Hanamoto, on one hand, and between track and vehicle wheels, on the other hand. Landscape, track model, soil model and the interaction are implemented in MATLAB/Simulink. The details of the real-time model are described in this article, and a detailed description of the Multi Body System part is omitted. Simulations with the real-time model are compared to measurements and to a detailed Multi Body System–finite element method model of a tracked vehicle. An application of the real-time model in a driving simulator is presented, in which 13 drivers assess the comfort of a passive and an active suspension of a tracked vehicle.

  12. Real Time Updating in Distributed Urban Rainfall Runoff Modelling

    DEFF Research Database (Denmark)

    Borup, Morten; Madsen, Henrik

    that are being updated from system measurements was studied. The results showed that the fact alone that it takes time for rainfall data to travel the distance between gauges and catchments has such a big negative effect on the forecast skill of updated models, that it can justify the choice of even very...... as in a real data case study. The results confirmed that the method is indeed suitable for DUDMs and that it can be used to utilise upstream as well as downstream water level and flow observations to improve model estimates and forecasts. Due to upper and lower sensor limits many sensors in urban drainage...

  13. Real-Time Optimization for Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Edlund, Kristian; Frison, Gianluca

    2012-01-01

    In this paper, we develop an efficient homogeneous and self-dual interior-point method for the linear programs arising in economic model predictive control. To exploit structure in the optimization problems, the algorithm employs a highly specialized Riccati iteration procedure. Simulations show...

  14. Reactive Aggregate Model Protecting Against Real-Time Threats

    Science.gov (United States)

    2014-09-01

    IPv4 address space. Cisco products such as Auto Secure and Adaptive Security Appliance are effective for Cisco products, but large distributed...protection capability within GINA. GINA has no published history of implementation as an IPS. A. RAMPART DECISION MODEL In order to establish a threat

  15. Method of modeling transmissions for real-time simulation

    Science.gov (United States)

    Hebbale, Kumaraswamy V.

    2012-09-25

    A transmission modeling system includes an in-gear module that determines an in-gear acceleration when a vehicle is in gear. A shift module determines a shift acceleration based on a clutch torque when the vehicle is shifting between gears. A shaft acceleration determination module determines a shaft acceleration based on at least one of the in-gear acceleration and the shift acceleration.

  16. Dynamics model for real time diagnostics of Triga RC-1 system

    International Nuclear Information System (INIS)

    Gadomski, A.M.; Nanni, V.; Meo, G.

    1988-01-01

    This paper presents dynamics model of TRIGA RC-1 reactor system. The model is dedicated to the real-time early fault detection during a reactor operation in one week exploitation cycle. The algorithms are specially suited for real-time, long time and also accelerated simulations with assumed diagnostic oriented accuracy. The approximations, modular structure, numerical methods and validation are discussed. The elaborated model will be build in the TRIGA Supervisor System and TRIGA Diagnostic Simulator

  17. Dynamics model for real time diagnostics of TRIGA RC-1 system

    International Nuclear Information System (INIS)

    Gadomski, A.M.; Nanni, V.; Meo, G.B.

    1986-01-01

    This paper presents dynamics model of TRIGA RC-1 reactor system. The model is dedicated to the real-time early fault detection during a reactor operation in one week exploitation cycle. The algorithms are specially suited for real-time, long time and also accelerated simulations with assumed diagnostic oriented accuracy. The approximations, modular structure, numerical methods and validation are discussed. The elaborated model will be build in the TRIGA Supervisory System and TRIGA Diagnostic Simulator. (author)

  18. A Comparison and Evaluation of Real-Time Software Systems Modeling Languages

    Science.gov (United States)

    Evensen, Kenneth D.; Weiss, Kathryn Anne

    2010-01-01

    A model-driven approach to real-time software systems development enables the conceptualization of software, fostering a more thorough understanding of its often complex architecture and behavior while promoting the documentation and analysis of concerns common to real-time embedded systems such as scheduling, resource allocation, and performance. Several modeling languages have been developed to assist in the model-driven software engineering effort for real-time systems, and these languages are beginning to gain traction with practitioners throughout the aerospace industry. This paper presents a survey of several real-time software system modeling languages, namely the Architectural Analysis and Design Language (AADL), the Unified Modeling Language (UML), Systems Modeling Language (SysML), the Modeling and Analysis of Real-Time Embedded Systems (MARTE) UML profile, and the AADL for UML profile. Each language has its advantages and disadvantages, and in order to adequately describe a real-time software system's architecture, a complementary use of multiple languages is almost certainly necessary. This paper aims to explore these languages in the context of understanding the value each brings to the model-driven software engineering effort and to determine if it is feasible and practical to combine aspects of the various modeling languages to achieve more complete coverage in architectural descriptions. To this end, each language is evaluated with respect to a set of criteria such as scope, formalisms, and architectural coverage. An example is used to help illustrate the capabilities of the various languages.

  19. Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

    Science.gov (United States)

    Crowell, B. W.; Bock, Y.; Squibb, M. B.

    2010-12-01

    Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

  20. Reliable real-time applications - and how to use tests to model and understand

    DEFF Research Database (Denmark)

    Jensen, Peter Krogsgaard

    Test and analysis of real-time applications, where temporal properties are inspected, analyzed, and verified in a model developed from timed traces originating from measured test result on a running application......Test and analysis of real-time applications, where temporal properties are inspected, analyzed, and verified in a model developed from timed traces originating from measured test result on a running application...

  1. Real-time sensor failure detection by dynamic modelling of a PWR plant

    International Nuclear Information System (INIS)

    Turkcan, E.; Ciftcioglu, O.

    1992-06-01

    Signal validation and sensor failure detection is an important problem in real-time nuclear power plant (NPP) surveillance. Although conventional sensor redundancy, in a way, is a solution, identification of faulty sensor is necessary for further preventive actions to be taken. A comprehensive solution for the system so that any sensory reading is verified by its model based estimated counterpart, in real-time. Such a realization is accomplished by means of dynamic system's states estimation methodology using Kalman filter modelling technique. The method is investigated by means of real-time data of the steam generator of Borssele nuclear power plant and the method has proved to be satisfactory for real-time sensor failure detection as well as model validation verification. (author). 5 refs.; 6 figs.; 1 tab

  2. A Mixed Model for Real-Time, Interactive Simulation of a Cable Passing Through Several Pulleys

    International Nuclear Information System (INIS)

    Garcia-Fernandez, Ignacio; Pla-Castells, Marta; Martinez-Dura, Rafael J.

    2007-01-01

    A model of a cable and pulleys is presented that can be used in Real Time Computer Graphics applications. The model is formulated by the coupling of a damped spring and a variable coefficient wave equation, and can be integrated in more complex mechanical models of lift systems, such as cranes, elevators, etc. with a high degree of interactivity

  3. A Mixed Model for Real-Time, Interactive Simulation of a Cable Passing Through Several Pulleys

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Fernandez, Ignacio; Pla-Castells, Marta; Martinez-Dura, Rafael J [Instituto de Robotica. Universidad de Valencia (Spain)

    2007-09-06

    A model of a cable and pulleys is presented that can be used in Real Time Computer Graphics applications. The model is formulated by the coupling of a damped spring and a variable coefficient wave equation, and can be integrated in more complex mechanical models of lift systems, such as cranes, elevators, etc. with a high degree of interactivity.

  4. Estimating marginal properties of quantitative real-time PCR data using nonlinear mixed models

    DEFF Research Database (Denmark)

    Gerhard, Daniel; Bremer, Melanie; Ritz, Christian

    2014-01-01

    A unified modeling framework based on a set of nonlinear mixed models is proposed for flexible modeling of gene expression in real-time PCR experiments. Focus is on estimating the marginal or population-based derived parameters: cycle thresholds and ΔΔc(t), but retaining the conditional mixed mod...

  5. Tool-driven Design and Automated Parameterization for Real-time Generic Drivetrain Models

    Directory of Open Access Journals (Sweden)

    Schwarz Christina

    2015-01-01

    Full Text Available Real-time dynamic drivetrain modeling approaches have a great potential for development cost reduction in the automotive industry. Even though real-time drivetrain models are available, these solutions are specific to single transmission topologies. In this paper an environment for parameterization of a solution is proposed based on a generic method applicable to all types of gear transmission topologies. This enables tool-guided modeling by non- experts in the fields of mechanic engineering and control theory leading to reduced development and testing efforts. The approach is demonstrated for an exemplary automatic transmission using the environment for automated parameterization. Finally, the parameterization is validated via vehicle measurement data.

  6. On the Designing of Model Checkers for Real-Time Distributed Systems

    Directory of Open Access Journals (Sweden)

    D. Yu. Volkanov

    2012-01-01

    Full Text Available To verify real-time properties of UML statecharts one may apply a UPPAAL, toolbox for model checking of real-time systems. One of the most suitable ways to specify an operational semantics of UML statecharts is to invoke the formal model of Hierarchical Timed Automata. Since the model language of UPPAAL is based on Networks of Timed Automata one has to provide a conversion of Hierarchical Timed Automata to Networks of Timed Automata. In this paper we describe this conversion algorithm and prove that it is correct w.r.t. UPPAAL query language which is based on the subset of Timed CTL.

  7. Real-time modeling and simulation of distribution feeder and distributed resources

    Science.gov (United States)

    Singh, Pawan

    The analysis of the electrical system dates back to the days when analog network analyzers were used. With the advent of digital computers, many programs were written for power-flow and short circuit analysis for the improvement of the electrical system. Real-time computer simulations can answer many what-if scenarios in the existing or the proposed power system. In this thesis, the standard IEEE 13-Node distribution feeder is developed and validated on a real-time platform OPAL-RT. The concept and the challenges of the real-time simulation are studied and addressed. Distributed energy resources include some of the commonly used distributed generation and storage devices like diesel engine, solar photovoltaic array, and battery storage system are modeled and simulated on a real-time platform. A microgrid encompasses a portion of an electric power distribution which is located downstream of the distribution substation. Normally, the microgrid operates in paralleled mode with the grid; however, scheduled or forced isolation can take place. In such conditions, the microgrid must have the ability to operate stably and autonomously. The microgrid can operate in grid connected and islanded mode, both the operating modes are studied in the last chapter. Towards the end, a simple microgrid controller modeled and simulated on the real-time platform is developed for energy management and protection for the microgrid.

  8. MAC-Level Communication Time Modeling and Analysis for Real-Time WSNs

    Directory of Open Access Journals (Sweden)

    STANGACIU, V.

    2016-02-01

    Full Text Available Low-level communication protocols and their timing behavior are essential to developing wireless sensor networks (WSNs able to provide the support and operating guarantees required by many current real-time applications. Nevertheless, this aspect still remains an issue in the state-of-the-art. In this paper we provide a detailed analysis of a recently proposed MAC-level communication timing model and demonstrate its usability in designing real-time protocols. The results of a large set of measurements are also presented and discussed here, in direct relation to the main time parameters of the analyzed model.

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

    Science.gov (United States)

    Ashourloo, Mojtaba

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

  10. Data-driven modeling and real-time distributed control for energy efficient manufacturing systems

    International Nuclear Information System (INIS)

    Zou, Jing; Chang, Qing; Arinez, Jorge; Xiao, Guoxian

    2017-01-01

    As manufacturers face the challenges of increasing global competition and energy saving requirements, it is imperative to seek out opportunities to reduce energy waste and overall cost. In this paper, a novel data-driven stochastic manufacturing system modeling method is proposed to identify and predict energy saving opportunities and their impact on production. A real-time distributed feedback production control policy, which integrates the current and predicted system performance, is established to improve the overall profit and energy efficiency. A case study is presented to demonstrate the effectiveness of the proposed control policy. - Highlights: • A data-driven stochastic manufacturing system model is proposed. • Real-time system performance and energy saving opportunity identification method is developed. • Prediction method for future potential system performance and energy saving opportunity is developed. • A real-time distributed feedback control policy is established to improve energy efficiency and overall system profit.

  11. Real-Time Attitude Control Algorithm for Fast Tumbling Objects under Torque Constraint

    Science.gov (United States)

    Tsuda, Yuichi; Nakasuka, Shinichi

    This paper describes a new control algorithm for achieving any arbitrary attitude and angular velocity states of a rigid body, even fast and complicated tumbling rotations, under some practical constraints. This technique is expected to be applied for the attitude motion synchronization to capture a non-cooperative, tumbling object in such missions as removal of debris from orbit, servicing broken-down satellites for repairing or inspection, rescue of manned vehicles, etc. For this objective, we have introduced a novel control algorithm called Free Motion Path Method (FMPM) in the previous paper, which was formulated as an open-loop controller. The next step of this consecutive work is to derive a closed-loop FMPM controller, and as the preliminary step toward the objective, this paper attempts to derive a conservative state variables representation of a rigid body dynamics. 6-Dimensional conservative state variables are introduced in place of general angular velocity-attitude angle representation, and how to convert between both representations are shown in this paper.

  12. Real-time volumetric deformable models for surgery simulation using finite elements and condensation

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Cotin, S.

    1996-01-01

    This paper discusses the application of SD solid volumetric Finite Element models to surgery simulation. In particular it introduces three new ideas for solving the problem of achieving real-time performance for these models. The simulation system we have developed is described and we demonstrate...

  13. Real-time PCR Machine System Modeling and a Systematic Approach for the Robust Design of a Real-time PCR-on-a-Chip System

    OpenAIRE

    Lee, Da-Sheng

    2010-01-01

    Chip-based DNA quantification systems are widespread, and used in many point-of-care applications. However, instruments for such applications may not be maintained or calibrated regularly. Since machine reliability is a key issue for normal operation, this study presents a system model of the real-time Polymerase Chain Reaction (PCR) machine to analyze the instrument design through numerical experiments. Based on model analysis, a systematic approach was developed to lower the variation of DN...

  14. Modeling of requirement specification for safety critical real time computer system using formal mathematical specifications

    International Nuclear Information System (INIS)

    Sankar, Bindu; Sasidhar Rao, B.; Ilango Sambasivam, S.; Swaminathan, P.

    2002-01-01

    Full text: Real time computer systems are increasingly used for safety critical supervision and control of nuclear reactors. Typical application areas are supervision of reactor core against coolant flow blockage, supervision of clad hot spot, supervision of undesirable power excursion, power control and control logic for fuel handling systems. The most frequent cause of fault in safety critical real time computer system is traced to fuzziness in requirement specification. To ensure the specified safety, it is necessary to model the requirement specification of safety critical real time computer systems using formal mathematical methods. Modeling eliminates the fuzziness in the requirement specification and also helps to prepare the verification and validation schemes. Test data can be easily designed from the model of the requirement specification. Z and B are the popular languages used for modeling the requirement specification. A typical safety critical real time computer system for supervising the reactor core of prototype fast breeder reactor (PFBR) against flow blockage is taken as case study. Modeling techniques and the actual model are explained in detail. The advantages of modeling for ensuring the safety are summarized

  15. Design base transient analysis using the real-time nuclear reactor simulator model

    International Nuclear Information System (INIS)

    Tien, K.K.; Yakura, S.J.; Morin, J.P.; Gregory, M.V.

    1987-01-01

    A real-time simulation model has been developed to describe the dynamic response of all major systems in a nuclear process reactor. The model consists of a detailed representation of all hydraulic components in the external coolant circulating loops consisting of piping, valves, pumps and heat exchangers. The reactor core is described by a three-dimensional neutron kinetics model with detailed representation of assembly coolant and moderator thermal hydraulics. The models have been developed to support a real-time training simulator, therefore, they reproduce system parameters characteristic of steady state normal operation with high precision. The system responses for postulated severe transients such as large pipe breaks, loss of pumping power, piping leaks, malfunctions in control rod insertion, and emergency injection of neutron absorber are calculated to be in good agreement with reference safety analyses. Restrictions were imposed by the requirement that the resulting code be able to run in real-time with sufficient spare time to allow interfacing with secondary systems and simulator hardware. Due to hardware set-up and real plant instrumentation, simplifications due to symmetry were not allowed. The resulting code represents a coarse-node engineering model in which the level of detail has been tailored to the available computing power of a present generation super-minicomputer. Results for several significant transients, as calculated by the real-time model, are compared both to actual plant data and to results generated by fine-mesh analysis codes

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

    Directory of Open Access Journals (Sweden)

    Reynaldo Iracheta-Cortez

    2017-09-01

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

  17. Design base transient analysis using the real-time nuclear reactor simulator model

    International Nuclear Information System (INIS)

    Tien, K.K.; Yakura, S.J.; Morin, J.P.; Gregory, M.V.

    1987-01-01

    A real-time simulation model has been developed to describe the dynamic response of all major systems in a nuclear process reactor. The model consists of a detailed representation of all hydraulic components in the external coolant circulating loops consisting of piping, valves, pumps and heat exchangers. The reactor core is described by a three-dimensional neutron kinetics model with detailed representation of assembly coolant and mode-rator thermal hydraulics. The models have been developed to support a real-time training simulator, therefore, they reproduce system parameters characteristic of steady state normal operation with high precision. The system responses for postulated severe transients such as large pipe breaks, loss of pumping power, piping leaks, malfunctions in control rod insertion, and emergency injection of neutron absorber are calculated to be in good agreement with reference safety analyses. Restrictions were imposed by the requirement that the resulting code be able to run in real-time with sufficient spare time to allow interfacing with secondary systems and simulator hardware. Due to hardware set-up and real plant instrumentation, simplifications due to symmetry were not allowed. The resulting code represents a coarse-node engineering model in which the level of detail has been tailored to the available computing power of a present generation super-minicomputer. Results for several significant transients, as calculated by the real-time model, are compared both to actual plant data and to results generated by fine-mesh analysis codes

  18. Real-time detection of musical onsets with linear prediction and sinusoidal modeling

    Science.gov (United States)

    Glover, John; Lazzarini, Victor; Timoney, Joseph

    2011-12-01

    Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This article provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets.

  19. Real-time monitoring/emergency response modeling workstation for a tritium facility

    International Nuclear Information System (INIS)

    Lawver, B.S.; Sims, J.M.; Baskett, R.L.

    1993-01-01

    At Lawrence Livermore National Laboratory (LLNL) we have developed a real-time system to monitor two stacks on our tritium handling facility. The monitors transmit the stack data to a workstation, which computes a three-dimensional numerical model of atmospheric dispersion. The workstation also collects surface and upper air data from meteorological towers and a sodar. The complex meteorological and terrain setting in the Livermore Valley demands more sophisticated resolution of the three-dimensional structure of the atmosphere to reliably calculate plume dispersion than afforded by Gaussian models. We experience both mountain valley and sea breeze flows. To address these complexities, we have implemented the three-dimensional diagnostic MATHEW mass-adjusted wind field and ADPIC particle-in-cell dispersion models on the workstation for use in real-time emergency response modeling. Both MATHEW and ADPIC have shown their utility in a variety of complex settings over the last 15 yr within the U.S. Department of Energy's Atmospheric Release Advisory Capability (ARAC) project. Faster workstations and real-time instruments allow utilization of more complex three-dimensional models, which provides a foundation for building a real-time monitoring and emergency response workstation for a tritium facility. The stack monitors are two ion chambers per stack

  20. Real-time distributed economic model predictive control for complete vehicle energy management

    NARCIS (Netherlands)

    Romijn, Constantijn; Donkers, Tijs; Kessels, John; Weiland, Siep

    2017-01-01

    In this paper, a real-time distributed economic model predictive control approach for complete vehicle energy management (CVEM) is presented using a receding control horizon in combination with a dual decomposition. The dual decomposition allows the CVEM optimization problem to be solved by solving

  1. Math modeling and computer mechanization for real time simulation of rotary-wing aircraft

    Science.gov (United States)

    Howe, R. M.

    1979-01-01

    Mathematical modeling and computer mechanization for real time simulation of rotary wing aircraft is discussed. Error analysis in the digital simulation of dynamic systems, such as rotary wing aircraft is described. The method for digital simulation of nonlinearities with discontinuities, such as exist in typical flight control systems and rotor blade hinges, is discussed.

  2. Real-Time Analysis and Forecasting of Multisite River Flow Using a Distributed Hydrological Model

    Directory of Open Access Journals (Sweden)

    Mingdong Sun

    2014-01-01

    Full Text Available A spatial distributed hydrological forecasting system was developed to promote the analysis of river flow dynamic state in a large basin. The research presented the real-time analysis and forecasting of multisite river flow in the Nakdong River Basin using a distributed hydrological model with radar rainfall forecast data. A real-time calibration algorithm of hydrological distributed model was proposed to investigate the particular relationship between the water storage and basin discharge. Demonstrate the approach of simulating multisite river flow using a distributed hydrological model couple with real-time calibration and forecasting of multisite river flow with radar rainfall forecasts data. The hydrographs and results exhibit that calibrated flow simulations are very approximate to the flow observation at all sites and the accuracy of forecasting flow is gradually decreased with lead times extending from 1 hr to 3 hrs. The flow forecasts are lower than the flow observation which is likely caused by the low estimation of radar rainfall forecasts. The research has well demonstrated that the distributed hydrological model is readily applicable for multisite real-time river flow analysis and forecasting in a large basin.

  3. Feasibility analysis of real-time physical modeling using WaveCore processor technology on FPGA

    NARCIS (Netherlands)

    Verstraelen, Martinus Johannes Wilhelmina; Pfeifle, Florian; Bader, Rolf

    2015-01-01

    WaveCore is a scalable many-core processor technology. This technology is specifically developed and optimized for real-time acoustical modeling applications. The programmable WaveCore soft-core processor is silicon-technology independent and hence can be targeted to ASIC or FPGA technologies. The

  4. Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

    Science.gov (United States)

    Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L

    2016-08-01

    Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.

  5. An Innovative Real-time Environment for Unified Deterministic and Stochastic Groundwater Modeling

    Science.gov (United States)

    Li, S.; Liu, Q.

    2003-12-01

    Despite an exponential growth of computational capability over the last two decades-one that has allowed computational science and engineering to become a unique, powerful tool for scientific discovery-the extreme cost of groundwater modeling continues to limit its use. This occurs primarily because the modeling paradigm that has been employed for decades limits our ability to take full advantage of recent developments in computer, communication, graphic, and visualization technologies. In this presentation we introduce an innovative and sophisticated computational environment for groundwater modeling that promises to eliminate the current bottleneck and greatly expand the utility of computational tools for scientific discovery related to groundwater. Based on a set of efficient and robust computational algorithms, the new software system, called Interactive Groundwater (IGW), allows simulating complex flow and transport in aquifers subject to both systematic and "randomly" varying stresses and geological and chemical heterogeneity. Adopting a new paradigm, IGW eliminates a major bottleneck inherent in the traditional fragmented modeling technologies and enables real-time modeling, real-time visualization, real-time analysis, and real-time presentation. IGW functions as a "numerical laboratory" in which a researcher can freely explore in real-time: creating visually an aquifer of desired configurations, interactively imposing desired stresses, and then immediately investigating and visualizing the geology and the processes of flow and contaminant transport and transformation. A modeler can pause to edit at any time and interact on-line with any aspects (e.g., conceptual and numerical representation, boundary conditions, model solvers, and ways of visualization and analysis) of the integrated modeling process; he/she can initiate or stop, whenever needed, particle tracking, plume modeling, subscale modeling, cross-sectional modeling, stochastic modeling, monitoring

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

    International Nuclear Information System (INIS)

    Fakory, M.R.; Seifaee, F.

    1987-01-01

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

  7. A practical MGA-ARIMA model for forecasting real-time dynamic rain-induced attenuation

    Science.gov (United States)

    Gong, Shuhong; Gao, Yifeng; Shi, Houbao; Zhao, Ge

    2013-05-01

    novel and practical modified genetic algorithm (MGA)-autoregressive integrated moving average (ARIMA) model for forecasting real-time dynamic rain-induced attenuation has been established by combining genetic algorithm ideas with the ARIMA model. It is proved that due to the introduction of MGA into the ARIMA(1,1,7) model, the MGA-ARIMA model has the potential to be conveniently applied in every country or area by creating a parameter database used by the ARIMA(1,1,7) model. The parameter database is given in this paper based on attenuation data measured in Xi'an, China. The methods to create the parameter databases in other countries or areas are offered, too. Based on the experimental results, the MGA-ARIMA model has been proved practical for forecasting dynamic rain-induced attenuation in real time. The novel model given in this paper is significant for developing adaptive fade mitigation technologies at millimeter wave bands.

  8. Real-time PCR Machine System Modeling and a Systematic Approach for the Robust Design of a Real-time PCR-on-a-Chip System

    Directory of Open Access Journals (Sweden)

    Da-Sheng Lee

    2010-01-01

    Full Text Available Chip-based DNA quantification systems are widespread, and used in many point-of-care applications. However, instruments for such applications may not be maintained or calibrated regularly. Since machine reliability is a key issue for normal operation, this study presents a system model of the real-time Polymerase Chain Reaction (PCR machine to analyze the instrument design through numerical experiments. Based on model analysis, a systematic approach was developed to lower the variation of DNA quantification and achieve a robust design for a real-time PCR-on-a-chip system. Accelerated lift testing was adopted to evaluate the reliability of the chip prototype. According to the life test plan, this proposed real-time PCR-on-a-chip system was simulated to work continuously for over three years with similar reproducibility in DNA quantification. This not only shows the robustness of the lab-on-a-chip system, but also verifies the effectiveness of our systematic method for achieving a robust design.

  9. Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

    Science.gov (United States)

    Chen, Jinduan; Boccelli, Dominic L.

    2018-02-01

    Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.

  10. Functional Fault Modeling Conventions and Practices for Real-Time Fault Isolation

    Science.gov (United States)

    Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

    2010-01-01

    The purpose of this paper is to present the conventions, best practices, and processes that were established based on the prototype development of a Functional Fault Model (FFM) for a Cryogenic System that would be used for real-time Fault Isolation in a Fault Detection, Isolation, and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using a suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FFMs were created offline but would eventually be used by a real-time reasoner to isolate faults in a Cryogenic System. Through their development and review, a set of modeling conventions and best practices were established. The prototype FFM development also provided a pathfinder for future FFM development processes. This paper documents the rationale and considerations for robust FFMs that can easily be transitioned to a real-time operating environment.

  11. A Model for Real-Time Data Reputation Via Cyber Telemetry

    Science.gov (United States)

    2016-06-01

    methodology which focuses on iterative cycles, known as sprints, to produce the capabilities of the system. Traditional waterfall models do not allow for...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited A MODEL FOR REAL...Master’s Thesis 4. TITLE AND SUBTITLE A MODEL FOR REAL-TIME DATA REPUTATION VIA CYBER TELEMETRY 5. FUNDING NUMBERS 6. AUTHOR(S) Beau M

  12. Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting

    Directory of Open Access Journals (Sweden)

    Hua-pu Lu

    2015-01-01

    Full Text Available This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.

  13. An improved grey model for the prediction of real-time GPS satellite clock bias

    Science.gov (United States)

    Zheng, Z. Y.; Chen, Y. Q.; Lu, X. S.

    2008-07-01

    In real-time GPS precise point positioning (PPP), real-time and reliable satellite clock bias (SCB) prediction is a key to implement real-time GPS PPP. It is difficult to hold the nuisance and inenarrable performance of space-borne GPS satellite atomic clock because of its high-frequency, sensitivity and impressionable, it accords with the property of grey model (GM) theory, i. e. we can look on the variable process of SCB as grey system. Firstly, based on limits of quadratic polynomial (QP) and traditional GM to predict SCB, a modified GM (1,1) is put forward to predict GPS SCB in this paper; and then, taking GPS SCB data for example, we analyzed clock bias prediction with different sample interval, the relationship between GM exponent and prediction accuracy, precision comparison of GM to QP, and concluded the general rule of different type SCB and GM exponent; finally, to test the reliability and validation of the modified GM what we put forward, taking IGS clock bias ephemeris product as reference, we analyzed the prediction precision with the modified GM, It is showed that the modified GM is reliable and validation to predict GPS SCB and can offer high precise SCB prediction for real-time GPS PPP.

  14. Real-time modelling of the diesel engine combustion process; Echtzeitfaehige Modellierung des dieselmotorischen Verbrennungsprozesses

    Energy Technology Data Exchange (ETDEWEB)

    Merz, B.

    2008-07-01

    The publication investigates single-zone models of diesel engine combustion which are capable, in addition to pre-injection and main injection, to represent post-injection processes on a physical basis. These must function in real time as they are used in ''hardware-in-the-loop'' test stands. Methods to adapt the models to other engine types are explained. Validation is made across the whole characteristic field on the basis of measured data provided by two serial engines. For assessing pollutant production, models are integrated that are capable of calculating NOx and soot formation. These, too, are calculated in real time using appropriate hardware systems. A runtime analysis compares the computing times of the models. (orig.)

  15. Modeling real-time balancing power demands in wind power systems using stochastic differential equations

    International Nuclear Information System (INIS)

    Olsson, Magnus; Perninge, Magnus; Soeder, Lennart

    2010-01-01

    The inclusion of wind power into power systems has a significant impact on the demand for real-time balancing power due to the stochastic nature of wind power production. The overall aim of this paper is to present probabilistic models of the impact of large-scale integration of wind power on the continuous demand in MW for real-time balancing power. This is important not only for system operators, but also for producers and consumers since they in most systems through various market solutions provide balancing power. Since there can occur situations where the wind power variations cancel out other types of deviations in the system, models on an hourly basis are not sufficient. Therefore the developed model is in continuous time and is based on stochastic differential equations (SDE). The model can be used within an analytical framework or in Monte Carlo simulations. (author)

  16. A real-time prediction model for post-irradiation malignant cervical lymph nodes.

    Science.gov (United States)

    Lo, W-C; Cheng, P-W; Shueng, P-W; Hsieh, C-H; Chang, Y-L; Liao, L-J

    2018-04-01

    To establish a real-time predictive scoring model based on sonographic characteristics for identifying malignant cervical lymph nodes (LNs) in cancer patients after neck irradiation. One-hundred forty-four irradiation-treated patients underwent ultrasonography and ultrasound-guided fine-needle aspirations (USgFNAs), and the resultant data were used to construct a real-time and computerised predictive scoring model. This scoring system was further compared with our previously proposed prediction model. A predictive scoring model, 1.35 × (L axis) + 2.03 × (S axis) + 2.27 × (margin) + 1.48 × (echogenic hilum) + 3.7, was generated by stepwise multivariate logistic regression analysis. Neck LNs were considered to be malignant when the score was ≥ 7, corresponding to a sensitivity of 85.5%, specificity of 79.4%, positive predictive value (PPV) of 82.3%, negative predictive value (NPV) of 83.1%, and overall accuracy of 82.6%. When this new model and the original model were compared, the areas under the receiver operating characteristic curve (c-statistic) were 0.89 and 0.81, respectively (P real-time sonographic predictive scoring model was constructed to provide prompt and reliable guidance for USgFNA biopsies to manage cervical LNs after neck irradiation. © 2017 John Wiley & Sons Ltd.

  17. A real-time computational model for estimating kinematics of ankle ligaments.

    Science.gov (United States)

    Zhang, Mingming; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Quan

    2016-01-01

    An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot-ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.

  18. Estimating DSGE model parameters in a small open economy: Do real-time data matter?

    Directory of Open Access Journals (Sweden)

    Capek Jan

    2015-03-01

    Full Text Available This paper investigates the differences between parameters estimated using real-time and those estimated with revised data. The models used are New Keynesian DSGE models of the Czech, Polish, Hungarian, Swiss, and Swedish small open economies in interaction with the euro area. The paper also offers an analysis of data revisions of GDP growth and inflation and trend revisions of interest rates.

  19. Control-Oriented Models for Real-Time Simulation of Automotive Transmission Systems

    Directory of Open Access Journals (Sweden)

    Cavina N.

    2015-01-01

    Full Text Available A control-oriented model of a Dual Clutch Transmission (DCT was developed for real-time Hardware In the Loop (HIL applications, to support model-based development of the DCT controller and to systematically test its performance. The model is an innovative attempt to reproduce the fast dynamics of the actuation system while maintaining a simulation step size large enough for real-time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models. As the oil circulating in the system has a large bulk modulus, the pressure dynamics are very fast, possibly causing instability in a real-time simulation; the same challenge involves the servo valves dynamics, due to the very small masses of the moving elements. Therefore, the hydraulic circuit model has been modified and simplified without losing physical validity, in order to adapt it to the real-time simulation requirements. The results of offline simulations have been compared to on-board measurements to verify the validity of the developed model, which was then implemented in a HIL system and connected to the Transmission Control Unit (TCU. Several tests have been performed on the HIL simulator, to verify the TCU performance: electrical failure tests on sensors and actuators, hydraulic and mechanical failure tests on hydraulic valves, clutches and synchronizers, and application tests comprehending all the main features of the control actions performed by the TCU. Being based on physical laws, in every condition the model simulates a plausible reaction of the system. A test automation procedure has finally been developed to permit the execution of a pattern of tests without the interaction of the user; perfectly repeatable tests can be performed for non-regression verification, allowing the testing of new software releases in fully automatic mode.

  20. Computational model for real-time determination of tritium inventory in a detritiation installation

    International Nuclear Information System (INIS)

    Bornea, Anisia; Stefanescu, Ioan; Zamfirache, Marius; Stefan, Iuliana; Sofalca, Nicolae; Bidica, Nicolae

    2008-01-01

    Full text: At ICIT Rm.Valcea an experimental pilot plant was built having as main objective the development of a technology for detritiation of heavy water processed in the CANDU-type reactors of the nuclear power plant at Cernavoda, Romania. The aspects related to safeguards and safety for such a detritiation installation being of great importance, a complex computational model has been developed. The model allows real-time calculation of tritium inventory in a working installation. The applied detritiation technology is catalyzed isotopic exchange coupled with cryogenic distillation. Computational models for non-steady working conditions have been developed for each process of isotopic exchange. By coupling these processes tritium inventory can be determined in real-time. The computational model was developed based on the experience gained on the pilot installation. The model uses a set of parameters specific to isotopic exchange processes. These parameters were experimentally determined in the pilot installation. The model is included in the monitoring system and uses as input data the parameters acquired in real-time from automation system of the pilot installation. A friendly interface has been created to visualize the final results as data or graphs. (authors)

  1. Near-real-time regional troposphere models for the GNSS precise point positioning technique

    International Nuclear Information System (INIS)

    Hadas, T; Kaplon, J; Bosy, J; Sierny, J; Wilgan, K

    2013-01-01

    The GNSS precise point positioning (PPP) technique requires high quality product (orbits and clocks) application, since their error directly affects the quality of positioning. For real-time purposes it is possible to utilize ultra-rapid precise orbits and clocks which are disseminated through the Internet. In order to eliminate as many unknown parameters as possible, one may introduce external information on zenith troposphere delay (ZTD). It is desirable that the a priori model is accurate and reliable, especially for real-time application. One of the open problems in GNSS positioning is troposphere delay modelling on the basis of ground meteorological observations. Institute of Geodesy and Geoinformatics of Wroclaw University of Environmental and Life Sciences (IGG WUELS) has developed two independent regional troposphere models for the territory of Poland. The first one is estimated in near-real-time regime using GNSS data from a Polish ground-based augmentation system named ASG-EUPOS established by Polish Head Office of Geodesy and Cartography (GUGiK) in 2008. The second one is based on meteorological parameters (temperature, pressure and humidity) gathered from various meteorological networks operating over the area of Poland and surrounding countries. This paper describes the methodology of both model calculation and verification. It also presents results of applying various ZTD models into kinematic PPP in the post-processing mode using Bernese GPS Software. Positioning results were used to assess the quality of the developed models during changing weather conditions. Finally, the impact of model application to simulated real-time PPP on precision, accuracy and convergence time is discussed. (paper)

  2. 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.

  3. Time Extensions of Petri Nets for Modelling and Verification of Hard Real-Time Systems

    Directory of Open Access Journals (Sweden)

    Tomasz Szmuc

    2002-01-01

    Full Text Available The main aim ofthe paper is a presentation of time extensions of Petri nets appropriate for modelling and analysis of hard real-time systems. It is assumed, that the extensions must provide a model of time flow an ability to force a transition to fire within a stated timing constraint (the so-called the strong firing rule, and timing constraints represented by intervals. The presented survey includes extensions of classical Place/Transition Petri nets, as well as the ones applied to high-level Petri nets. An expressiveness of each time extension is illustrated using simple hard real-time system. The paper includes also a brief description of analysis and veryication methods related to the extensions, and a survey of software tools supporting modelling and analysis ofthe considered Petri nets.

  4. Real-time monitoring of a microbial electrolysis cell using an electrical equivalent circuit model.

    Science.gov (United States)

    Hussain, S A; Perrier, M; Tartakovsky, B

    2018-04-01

    Efforts in developing microbial electrolysis cells (MECs) resulted in several novel approaches for wastewater treatment and bioelectrosynthesis. Practical implementation of these approaches necessitates the development of an adequate system for real-time (on-line) monitoring and diagnostics of MEC performance. This study describes a simple MEC equivalent electrical circuit (EEC) model and a parameter estimation procedure, which enable such real-time monitoring. The proposed approach involves MEC voltage and current measurements during its operation with periodic power supply connection/disconnection (on/off operation) followed by parameter estimation using either numerical or analytical solution of the model. The proposed monitoring approach is demonstrated using a membraneless MEC with flow-through porous electrodes. Laboratory tests showed that changes in the influent carbon source concentration and composition significantly affect MEC total internal resistance and capacitance estimated by the model. Fast response of these EEC model parameters to changes in operating conditions enables the development of a model-based approach for real-time monitoring and fault detection.

  5. Real Time Radioactivity Monitoring and its Interface with predictive atmospheric transport modelling

    International Nuclear Information System (INIS)

    Raes, F.

    1990-01-01

    After the Chernobyl accident, a programme was initiated at the Joint Research Centre of the Commission of the European Communities named 'Radioactivity Environmental Monitoring' (REM). The main aspects considered in REM are: data handling, atmospheric modelling and data quality control related to radioactivity in the environment. The first REM workshop was held in December 1987: 'Aerosol Measurements and Nuclear Accidents: A Reconsideration'. (CEC EUR 11755 EN). These are the proceedings of the second REM workshop, held in December 1989, dealing with real-time radioactivity monitoring and its interface with predictive atmospheric models. Atmospheric transport models, in applications extending over time scales of the order of a day or more become progressively less reliable to the extent that an interface with real-time radiological field data becomes highly desirable. Through international arrangements for early exchange of information in the event of a nuclear accident (European Community, IAEA) such data might become available on a quasi real-time basis. The question is how best to use such information to improve our predictive capabilities. During the workshop the present status of on-line monitoring networks for airborne radioactivity in the EC Member States has been reviewed. Possibilities were discussed to use data from such networks as soon as they become available, in order to update predictions made with long range transport models. This publication gives the full text of 13 presentations and a report of the Round Table Discussion held afterwards

  6. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  7. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  8. Integration of InfraMAP with Near-Real-Time Atmospheric Characterizations and Applications to Infrasound Modeling

    National Research Council Canada - National Science Library

    Gibson, Robert

    2003-01-01

    .... Of particular interest herein is the recently developed capability to incorporate near-real-time atmospheric updates, such as the output from numerical weather prediction models, to supplement...

  9. 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.

  10. IGBT Switching Characteristic Curve Embedded Half-Bridge MMC Modelling and Real Time Simulation Realization

    Science.gov (United States)

    Zhengang, Lu; Hongyang, Yu; Xi, Yang

    2017-05-01

    The Modular Multilevel Converter (MMC) is one of the most attractive topologies in recent years for medium or high voltage industrial applications, such as high voltage dc transmission (HVDC) and medium voltage varying speed motor drive. The wide adoption of MMCs in industry is mainly due to its flexible expandability, transformer-less configuration, common dc bus, high reliability from redundancy, and so on. But, when the sub module number of MMC is more, the test of MMC controller will cost more time and effort. Hardware in the loop test based on real time simulator will save a lot of time and money caused by the MMC test. And due to the flexible of HIL, it becomes more and more popular in the industry area. The MMC modelling method remains an important issue for the MMC HIL test. Specifically, the VSC model should realistically reflect the nonlinear device switching characteristics, switching and conduction losses, tailing current, and diode reverse recovery behaviour of a realistic converter. In this paper, an IGBT switching characteristic curve embedded half-bridge MMC modelling method is proposed. This method is based on the switching curve referring and sample circuit calculation, and it is sample for implementation. Based on the proposed method, a FPGA real time simulation is carried out with 200ns sample time. The real time simulation results show the proposed method is correct.

  11. Real-time modelling of a ventilation system for a power plant simulator

    International Nuclear Information System (INIS)

    Kocher, P.; Welfonder, E.

    1992-01-01

    This paper describes how to simulate in real-time the ventilation system of a nuclear power plant. The simulation is made under difficult computing time conditions. The ventilation system program is part of a simulator which simulates the whole nuclear power plant process in realtime. Therefore the ventilation system is split up into several smaller units. For each of these process units a real-time module has been developed, being as simple as possible but nevertheless coming close enough to the real dynamic behaviour. After that the simple real-time modules are linked together to form the total dynamic model ''ventilation system''. The continuous dynamic model developed is numerically integrated by the Euler method. The stability of this explicit method is maintained by special modelling measures such as the increasing of too low flow resistances or the limitation of too high gain factors. At the end of the paper some curves, recorded at the simulator, illustrate the behaviour of the ventilation system in the case of an accident. (author)

  12. Real-time control data wrangling for development of mathematical control models of technological processes

    Science.gov (United States)

    Vasilyeva, N. V.; Koteleva, N. I.; Fedorova, E. R.

    2018-05-01

    The relevance of the research is due to the need to stabilize the composition of the melting products of copper-nickel sulfide raw materials in the Vanyukov furnace. The goal of this research is to identify the most suitable methods for the aggregation of the real time data for the development of a mathematical model for control of the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace. Statistical methods of analyzing the historical data of the real technological object and the correlation analysis of process parameters are described. Factors that exert the greatest influence on the main output parameter (copper content in matte) and ensure the physical-chemical transformations are revealed. An approach to the processing of the real time data for the development of a mathematical model for control of the melting process is proposed. The stages of processing the real time information are considered. The adopted methodology for the aggregation of data suitable for the development of a control model for the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace allows us to interpret the obtained results for their further practical application.

  13. Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

    Science.gov (United States)

    Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; W. Rieger, Sebastian; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank

    2013-01-01

    Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual–spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. PMID:23668967

  14. Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

    Science.gov (United States)

    Baskaran, Subbiah; Noever, D.

    1999-01-01

    Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

  15. Fast And Flexible Modelling Of Real-Time Systems With Rtcp-Nets

    Directory of Open Access Journals (Sweden)

    Marcin Szpyrka

    2004-01-01

    Full Text Available A large number of formalisms has been proposed for real-time systems modelling. However, formal methods are not widely used in industrial software development. Such a situation could be treated as a result of a lack of suitable tools for fast designing of a model, its analysis and modification. RTCP-nets have been defined to facilitate fast modelling of embedded systems incorporating rule-based systems. Computer tools that are being developed for RTCP-nets, use a template mechanism to allow users to design models and manipulate its properties fast and effectively. Both theoretical and practical aspects of RTCP-nets are presented in the paper.

  16. Fast and Flexible Modelling of Real-Time Systems with RTCP-Nets

    Directory of Open Access Journals (Sweden)

    Marcin Szpyrka

    2004-01-01

    Full Text Available A large number of formalisms has been proposed for real-time systems modelling. However, formal methods are not widely used in industrial software development. Such a situation could be treated as a result of a lack of suitable tools for fast designing of a model, its analysis and modification. RTCP-nets have been defined to facilitate fast modelling of embedded systems incorporating rule-based systems. Computer tools that are being developed for RTCP-nets, use a template mechanism to allow users to design models and manipulate its properties fast and effectively. Both theoretical and practical aspects of RTCP-nets are presented in the paper.

  17. Logic Model Checking of Time-Periodic Real-Time Systems

    Science.gov (United States)

    Florian, Mihai; Gamble, Ed; Holzmann, Gerard

    2012-01-01

    In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.

  18. Real Time Systems

    DEFF Research Database (Denmark)

    Christensen, Knud Smed

    2000-01-01

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

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

    Science.gov (United States)

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

    2010-04-01

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

  20. Evaluation of HVDC interconnection models for considering its impact in real-time voltage stability assessment

    DEFF Research Database (Denmark)

    Perez, Angel; Jóhannsson, Hjörtur; Lund, P.

    2015-01-01

    An approach to evaluate the HVDC interconnectionsmodels to be used in real-time voltage stability assessment is proposed.The existing models for the HVDC interconnections, thatare based on voltage source converter, were studied selecting theones that are suitable for its application in Thevenin...... equivalent ´methods for voltage stability assessment. The proposed methodis to evaluate the validity of the models by using synthetizedPMU measurements from simulations and from PMUs connectedto the danish system. Wide-area measurements are used toestimate the HVDC model parameters which are needed...

  1. Real-time modelling and simulation of an active power filter

    Energy Technology Data Exchange (ETDEWEB)

    Beaulieu, S.; Ouhrouche, M. [Quebec Univ., Chicoutimi, PQ (Canada); Dufour, C.; Allaire, P.F. [Opal RT Technologies Inc., Montreal, PQ (Canada)

    2007-07-01

    Power electronics converters generate harmonics and cause electromagnetic compatibility problems. Active power filter (APF) technology has advanced to the point that it can compensate for harmonics in electrical networks and provide reactive power and neutral current in AC networks. This paper presented a contribution in the design of a shunt APF for harmonics compensation in real-time simulation using the RT-LAB software package running on a simple personal computer. Real-time simulations were performed to validate the effectiveness of the proposed model. Several high-tech industries have adopted this tool for rapid control prototyping and for Hardware-in-the-Loop applications. The switching signals of the APF are determined by the hysteresis band current controller. The suitable current reference signals were determined by the algorithm based on synchronous reference frame. Real-time simulation runs showed good performance in harmonics compensation, thus satisfying the requirements of IEEE Standard 519-1992. The rate of total harmonic distortion for the source current decreased from 30 to 5 per cent. 12 refs., 1 tab., 9 figs.

  2. CD-SEM real time bias correction using reference metrology based modeling

    Science.gov (United States)

    Ukraintsev, V.; Banke, W.; Zagorodnev, G.; Archie, C.; Rana, N.; Pavlovsky, V.; Smirnov, V.; Briginas, I.; Katnani, A.; Vaid, A.

    2018-03-01

    Accuracy of patterning impacts yield, IC performance and technology time to market. Accuracy of patterning relies on optical proximity correction (OPC) models built using CD-SEM inputs and intra die critical dimension (CD) control based on CD-SEM. Sub-nanometer measurement uncertainty (MU) of CD-SEM is required for current technologies. Reported design and process related bias variation of CD-SEM is in the range of several nanometers. Reference metrology and numerical modeling are used to correct SEM. Both methods are slow to be used for real time bias correction. We report on real time CD-SEM bias correction using empirical models based on reference metrology (RM) data. Significant amount of currently untapped information (sidewall angle, corner rounding, etc.) is obtainable from SEM waveforms. Using additional RM information provided for specific technology (design rules, materials, processes) CD extraction algorithms can be pre-built and then used in real time for accurate CD extraction from regular CD-SEM images. The art and challenge of SEM modeling is in finding robust correlation between SEM waveform features and bias of CD-SEM as well as in minimizing RM inputs needed to create accurate (within the design and process space) model. The new approach was applied to improve CD-SEM accuracy of 45 nm GATE and 32 nm MET1 OPC 1D models. In both cases MU of the state of the art CD-SEM has been improved by 3x and reduced to a nanometer level. Similar approach can be applied to 2D (end of line, contours, etc.) and 3D (sidewall angle, corner rounding, etc.) cases.

  3. A real-time crash prediction model for the ramp vicinities of urban expressways

    Directory of Open Access Journals (Sweden)

    Moinul Hossain

    2013-07-01

    Full Text Available Ramp vicinities are arguably the known black-spots on urban expressways. There, while maintaining high speed, drivers need to respond to several complex events such as maneuvering, reading road signs, route planning and maintaining safe distance from other maneuvering vehicles simultaneously which demand higher level of cognitive response to ensure safety. Therefore, any additional discomfort caused by traffic dynamics may induce driving error resulting in a crash. This manuscript presents a methodology for identifying these dynamically forming hazardous traffic conditions near the ramp vicinities with high resolution real-time traffic flow data. It separates the ramp vicinities into four zones – upstream and downstream of entrance and exit ramps, and builds four separate real-time crash prediction models. Around two year (December 2007 to October 2009 crash data as well as their matching traffic sensor data from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited have been utilized for this research. Random multinomial logit, a forest of multinomial logit models, has been used to identify the most important variables. Finally, a real-time modeling method, Bayesian belief net (BBN, has been employed to build the four models using ramp flow, flow and congestion index in the upstream and flow and speed in the downstream of the ramp location as variables. The newly proposed models could predict 50%, 42%, 43% and 55% of the future crashes with around 10% false alarm for the downstream of entrance, downstream of exit, upstream of entrance and upstream of exit ramps respectively. The models can be utilized in combination with various traffic smoothing measures such as ramp metering, variable speed limit, warning messages through variable message signs, etc. to enhance safety near the ramp vicinities.

  4. Real-time Pipeline for Object Modeling and Grasping Pose Selection via Superquadric Functions

    Directory of Open Access Journals (Sweden)

    Giulia Vezzani

    2017-11-01

    Full Text Available This work provides a novel real-time pipeline for modeling and grasping of unknown objects with a humanoid robot. Such a problem is of great interest for the robotic community, since conventional approaches fail when the shape, dimension, or pose of the objects are missing. Our approach reconstructs in real-time a model for the object under consideration and represents the robot hand both with proper and mathematically usable models, i.e., superquadric functions. The volume graspable by the hand is represented by an ellipsoid and is defined a priori, because the shape of the hand is known in advance. The superquadric representing the object is obtained in real-time from partial vision information instead, e.g., one stereo view of the object under consideration, and provides an approximated 3D full model. The optimization problem we formulate for the grasping pose computation is solved online by using the Ipopt software package and, thus, does not require off-line computation or learning. Even though our approach is for a generic humanoid robot, we developed a complete software architecture for executing this approach on the iCub humanoid robot. Together with that, we also provide a tutorial on how to use this framework. We believe that our work, together with the available code, is of a strong utility for the iCub community for three main reasons: object modeling and grasping are relevant problems for the robotic community, our code can be easily applied on every iCub, and the modular structure of our framework easily allows extensions and communications with external code.

  5. Nonlinear modeling and identification of a DC motor for bidirectional operation with real time experiments

    International Nuclear Information System (INIS)

    Kara, Tolgay; Eker, Ilyas

    2004-01-01

    Modeling and identification of mechanical systems constitute an essential stage in practical control design and applications. Controllers commanding systems that operate at varying conditions or require high precision operation raise the need for a nonlinear approach in modeling and identification. Most mechanical systems used in industry are composed of masses moving under the action of position and velocity dependent forces. These forces exhibit nonlinear behavior in certain regions of operation. For a multi-mass rotational system, the nonlinearities, like Coulomb friction and dead zone, significantly influence the system operation when the rotation changes direction. The paper presents nonlinear modeling and identification of a DC motor rotating in two directions together with real time experiments. Linear and nonlinear models for the system are obtained for identification purposes, and the major nonlinearities in the system, such as Coulomb friction and dead zone, are investigated and integrated in the nonlinear model. The Hammerstein nonlinear system approach is used for identification of the nonlinear system model. Online identification of the linear and nonlinear system models is performed using the recursive least squares method. Results of the real time experiments are graphically and numerically presented, and the advantages of the nonlinear identification approach are revealed

  6. TRSM-a thermal-hydraulic real-time simulation model for PWR

    International Nuclear Information System (INIS)

    Zhou Weichang

    1997-01-01

    TRSM (a Thermal-hydraulic Real-time Simulation Model) has been developed for PWR real-time simulation and best-estimate prediction of normal operating and abnormal accident conditions. It is a non-equilibrium two phase flow thermal-hydraulic model based on five basic conservation equations. A drift flux model is used to account for the unequal velocities of liquid and gaseous mixture, with or without the presence of the noncondensibles. Critical flow models are applied for break flow and valve flow calculations. A 5-regime two phase heat convection model is applied for clad-to-coolant as well as fluid-to-tubing heat transfer. A rigorous reactor coolant pump model is used to calculate the pressure drop and rise for the suction and discharge ends with complete pump characteristics curves included. The TRSM model has been adapted in the full-scale training simulator of Qinshan Nuclear Power Plant 300 MW unit to simulate the thermal-hydraulic performance of the NSSS. The simulation results of a cold leg LOCA and a steam generator tube rupture (SGTR) accident are presented

  7. 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.)

  8. The elastic body model: a pedagogical approach integrating real time measurements and modelling activities

    International Nuclear Information System (INIS)

    Fazio, C; Guastella, I; Tarantino, G

    2007-01-01

    In this paper, we describe a pedagogical approach to elastic body movement based on measurements of the contact times between a metallic rod and small bodies colliding with it and on modelling of the experimental results by using a microcomputer-based laboratory and simulation tools. The experiments and modelling activities have been built in the context of the laboratory of mechanical wave propagation of the two-year graduate teacher education programme of Palermo's University. Some considerations about observed modifications in trainee teachers' attitudes in utilizing experiments and modelling are discussed

  9. A real-time PUFF-model for accidental releases in complex terrain

    International Nuclear Information System (INIS)

    Thykier-Nielsen, S.; Mikkelsen, T.; Larsen, S.E.; Troen, I.; Baas, A.F. de; Kamada, R.; Skupniewicz, C.; Schacher, G.

    1990-01-01

    LINCOM-RIMPUFF, a combined flow/puff model, was developed at Riso National Laboratory for the Vandenberg AFB Meteorology and Plume Dispersion Handbook and is suitable as is for real time response to emergency spills and vents of gases and radionuclides. LINCOM is a linear, diagnostic, spectral, potential flow model which extends the Jackson-Hunt theory of non-hydrostatic, adiabatic wind flow over hills to the mesoscale domain. It is embedded in a weighted objective analysis (WOA) of real-time Vandenberg tower winds and may be used in ultra-high speed lookup table mode. The mesoscale dispersion model RIMPUFF is a flexible Gaussian puff model equipped with computer-time effective features for terrain and stability-dependent dispersion parameterization, plume rise formulas, inversion and ground-level reflection capabilities and wet/dry (source) depletion. It can treat plume bifurcation in complex terrain by using a puff-splitting scheme. It allows the flow-model to compute the larger scale wind field, reserving turbulent diffusion calculations for the sub-grid scale. In diagnostic mode toxic exposure are well assessed via the release of a single initial puff. With optimization, processing time for RIMPUFF should be on the order of 2 CPU minutes or less on a PC-system. In prognostic mode with shifting winds, multiple puff releases may become necessary, thereby lengthening processing time

  10. Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

    Science.gov (United States)

    Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

    2009-11-01

    In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

  11. Detection of Common Problems in Real-Time and Multicore Systems Using Model-Based Constraints

    Directory of Open Access Journals (Sweden)

    Raphaël Beamonte

    2016-01-01

    Full Text Available Multicore systems are complex in that multiple processes are running concurrently and can interfere with each other. Real-time systems add on top of that time constraints, making results invalid as soon as a deadline has been missed. Tracing is often the most reliable and accurate tool available to study and understand those systems. However, tracing requires that users understand the kernel events and their meaning. It is therefore not very accessible. Using modeling to generate source code or represent applications’ workflow is handy for developers and has emerged as part of the model-driven development methodology. In this paper, we propose a new approach to system analysis using model-based constraints, on top of userspace and kernel traces. We introduce the constraints representation and how traces can be used to follow the application’s workflow and check the constraints we set on the model. We then present a number of common problems that we encountered in real-time and multicore systems and describe how our model-based constraints could have helped to save time by automatically identifying the unwanted behavior.

  12. Hybrid Modeling of Intra-DCT Coefficients for Real-Time Video Encoding

    Directory of Open Access Journals (Sweden)

    Li Jin

    2008-01-01

    Full Text Available Abstract The two-dimensional discrete cosine transform (2-D DCT and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This paper proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT coefficients for intratransform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better real-time performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for DCT and quantization. This is particularly suitable for processors in portable devices where multiplications consume more power than additions. Computational reduction implies longer battery lifetime and energy economy.

  13. Adaptation of the MAST passive current simulation model for real-time plasma control

    International Nuclear Information System (INIS)

    McArdle, G.J.; Taylor, D.

    2008-01-01

    Successful equilibrium reconstruction on MAST depends on a reliable estimate of the passive current induced in the thick vacuum vessel (which also acts as the load assembly) and other toroidally continuous internal support structures. For the EFIT reconstruction code, a pre-processing program takes the measured plasma and PF coil current evolution and uses a sectional model of the passive structure to solve the ODEs for electromagnetic induction. The results are written to a file, which is treated by EFIT as a set of virtual measurements of the passive current in each section. However, when a real-time version of EFIT was recently installed in the MAST plasma control system, a similar function was required for real-time estimation of the instantaneous passive current. This required several adaptation steps for the induction model to reduce the computational overhead to the absolute minimum, whilst preserving accuracy of the result. These include: ·conversion of the ODE to use an auxiliary variable, avoiding the need to calculate the time derivative of current; ·minimise the order of the system via model reduction techniques with a state-space representation of the problem; ·transformation to eigenmode form, to diagonalise the main matrix for faster computation; ·discretisation of the ODE; ·hand-optimisation to use vector instruction extensions in the real-time processor; ·splitting the task into two parts: the time-critical feedback part, and the next cycle pre-calculation part. After these optimisations, the algorithm was successfully implemented at a cost of just 65 μs per 500 μs control cycle, with only 27 μs added to the control latency. The results show good agreement with the original off-line version. Some of these optimisations have also been used subsequently to improve the performance of the off-line version

  14. Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

    Science.gov (United States)

    Vaccaro, James M.; Yaworsky, Paul S.

    1999-06-01

    Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

  15. Real-time slicing algorithm for Stereolithography (STL) CAD model applied in additive manufacturing industry

    Science.gov (United States)

    Adnan, F. A.; Romlay, F. R. M.; Shafiq, M.

    2018-04-01

    Owing to the advent of the industrial revolution 4.0, the need for further evaluating processes applied in the additive manufacturing application particularly the computational process for slicing is non-trivial. This paper evaluates a real-time slicing algorithm for slicing an STL formatted computer-aided design (CAD). A line-plane intersection equation was applied to perform the slicing procedure at any given height. The application of this algorithm has found to provide a better computational time regardless the number of facet in the STL model. The performance of this algorithm is evaluated by comparing the results of the computational time for different geometry.

  16. 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.

  17. 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.

  18. The Research of Car-Following Model Based on Real-Time Maximum Deceleration

    Directory of Open Access Journals (Sweden)

    Longhai Yang

    2015-01-01

    Full Text Available This paper is concerned with the effect of real-time maximum deceleration in car-following. The real-time maximum acceleration is estimated with vehicle dynamics. It is known that an intelligent driver model (IDM can control adaptive cruise control (ACC well. The disadvantages of IDM at high and constant speed are analyzed. A new car-following model which is applied to ACC is established accordingly to modify the desired minimum gap and structure of the IDM. We simulated the new car-following model and IDM under two different kinds of road conditions. In the first, the vehicles drive on a single road, taking dry asphalt road as the example in this paper. In the second, vehicles drive onto a different road, and this paper analyzed the situation in which vehicles drive from a dry asphalt road onto an icy road. From the simulation, we found that the new car-following model can not only ensure driving security and comfort but also control the steady driving of the vehicle with a smaller time headway than IDM.

  19. FPGA-Based Real Time, Multichannel Emulated-Digital Retina Model Implementation

    Directory of Open Access Journals (Sweden)

    Zsolt Vörösházi

    2009-01-01

    Full Text Available The function of the low-level image processing that takes place in the biological retina is to compress only the relevant visual information to a manageable size. The behavior of the layers and different channels of the neuromorphic retina has been successfully modeled by cellular neural/nonlinear networks (CNNs. In this paper, we present an extended, application-specific emulated-digital CNN-universal machine (UM architecture to compute the complex dynamic of this mammalian retina in video real time. The proposed emulated-digital implementation of multichannel retina model is compared to the previously developed models from three key aspects, which are processing speed, number of physical cells, and accuracy. Our primary aim was to build up a simple, real-time test environment with camera input and display output in order to mimic the behavior of retina model implementation on emulated digital CNN by using low-cost, moderate-sized field-programmable gate array (FPGA architectures.

  20. A real-time monitoring/emergency response modeling workstation for a tritium facility

    International Nuclear Information System (INIS)

    Lawver, B.S.; Sims, J.M.; Baskett, R.L.

    1993-07-01

    At Lawrence Livermore National Laboratory (LLNL) we developed a real-time system to monitor two stacks on our tritium handling facility. The monitors transmit the stack data to a workstation which computes a 3D numerical model of atmospheric dispersion. The workstation also collects surface and upper air data from meteorological towers and a sodar. The complex meteorological and terrain setting in the Livermore Valley demands more sophisticated resolution of the three-dimensional structure of the atmosphere to reliably calculate plume dispersion than afforded by Gaussian models. We experience both mountain valley and sea breeze flows. To address these complexities, we have implemented the three-dimensional diagnostic MATHEW mass-adjusted wind field and ADPIC particle-in-cell dispersion models on the workstation for use in real-time emergency response modeling. Both MATHEW and ADPIC have shown their utility in a variety of complex settings over the last 15 years within the Department of Energy's Atmospheric Release Advisory Capability (ARAC[1,2]) project

  1. Tailored motivational message generation: A model and practical framework for real-time physical activity coaching.

    Science.gov (United States)

    Op den Akker, Harm; Cabrita, Miriam; Op den Akker, Rieks; Jones, Valerie M; Hermens, Hermie J

    2015-06-01

    This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Systematic evaluation of fault trees using real-time model checker UPPAAL

    International Nuclear Information System (INIS)

    Cha, Sungdeok; Son, Hanseong; Yoo, Junbeom; Jee, Eunkyung; Seong, Poong Hyun

    2003-01-01

    Fault tree analysis, the most widely used safety analysis technique in industry, is often applied manually. Although techniques such as cutset analysis or probabilistic analysis can be applied on the fault tree to derive further insights, they are inadequate in locating flaws when failure modes in fault tree nodes are incorrectly identified or when causal relationships among failure modes are inaccurately specified. In this paper, we demonstrate that model checking technique is a powerful tool that can formally validate the accuracy of fault trees. We used a real-time model checker UPPAAL because the system we used as the case study, nuclear power emergency shutdown software named Wolsong SDS2, has real-time requirements. By translating functional requirements written in SCR-style tabular notation into timed automata, two types of properties were verified: (1) if failure mode described in a fault tree node is consistent with the system's behavioral model; and (2) whether or not a fault tree node has been accurately decomposed. A group of domain engineers with detailed technical knowledge of Wolsong SDS2 and safety analysis techniques developed fault tree used in the case study. However, model checking technique detected subtle ambiguities present in the fault tree

  3. Simulation model for transcervical laryngeal injection providing real-time feedback.

    Science.gov (United States)

    Ainsworth, Tiffiny A; Kobler, James B; Loan, Gregory J; Burns, James A

    2014-12-01

    This study aimed to develop and evaluate a model for teaching transcervical laryngeal injections. A 3-dimensional printer was used to create a laryngotracheal framework based on de-identified computed tomography images of a human larynx. The arytenoid cartilages and intrinsic laryngeal musculature were created in silicone from clay casts and thermoplastic molds. The thyroarytenoid (TA) muscle was created with electrically conductive silicone using metallic filaments embedded in silicone. Wires connected TA muscles to an electrical circuit incorporating a cell phone and speaker. A needle electrode completed the circuit when inserted in the TA during simulated injection, providing real-time feedback of successful needle placement by producing an audible sound. Face validation by the senior author confirmed appropriate tactile feedback and anatomical realism. Otolaryngologists pilot tested the model and completed presimulation and postsimulation questionnaires. The high-fidelity simulation model provided tactile and audio feedback during needle placement, simulating transcervical vocal fold injections. Otolaryngology residents demonstrated higher comfort levels with transcervical thyroarytenoid injection on postsimulation questionnaires. This is the first study to describe a simulator for developing transcervical vocal fold injection skills. The model provides real-time tactile and auditory feedback that aids in skill acquisition. Otolaryngologists reported increased confidence with transcervical injection after using the simulator. © The Author(s) 2014.

  4. Model-based framework for multi-axial real-time hybrid simulation testing

    Science.gov (United States)

    Fermandois, Gaston A.; Spencer, Billie F.

    2017-10-01

    Real-time hybrid simulation is an efficient and cost-effective dynamic testing technique for performance evaluation of structural systems subjected to earthquake loading with rate-dependent behavior. A loading assembly with multiple actuators is required to impose realistic boundary conditions on physical specimens. However, such a testing system is expected to exhibit significant dynamic coupling of the actuators and suffer from time lags that are associated with the dynamics of the servo-hydraulic system, as well as control-structure interaction (CSI). One approach to reducing experimental errors considers a multi-input, multi-output (MIMO) controller design, yielding accurate reference tracking and noise rejection. In this paper, a framework for multi-axial real-time hybrid simulation (maRTHS) testing is presented. The methodology employs a real-time feedback-feedforward controller for multiple actuators commanded in Cartesian coordinates. Kinematic transformations between actuator space and Cartesian space are derived for all six-degrees-offreedom of the moving platform. Then, a frequency domain identification technique is used to develop an accurate MIMO transfer function of the system. Further, a Cartesian-domain model-based feedforward-feedback controller is implemented for time lag compensation and to increase the robustness of the reference tracking for given model uncertainty. The framework is implemented using the 1/5th-scale Load and Boundary Condition Box (LBCB) located at the University of Illinois at Urbana- Champaign. To demonstrate the efficacy of the proposed methodology, a single-story frame subjected to earthquake loading is tested. One of the columns in the frame is represented physically in the laboratory as a cantilevered steel column. For realtime execution, the numerical substructure, kinematic transformations, and controllers are implemented on a digital signal processor. Results show excellent performance of the maRTHS framework when six

  5. Real-time remote sensing driven river basin modeling using radar altimetry

    Directory of Open Access Journals (Sweden)

    S. J. Pereira-Cardenal

    2011-01-01

    Full Text Available Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS data have been recognized as an alternative to in-situ hydrometeorological data in remote and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models.

    In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modeling approach based entirely on RS and reanalysis data: precipitation was obtained from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA, temperature from the European Centre for Medium-Range Weather Forecast's (ECMWF Operational Surface Analysis dataset and reference evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat measurements of reservoir water levels. The modeling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several large reservoirs and scarce hydrometeorological data that is located in Central Asia and shared between 4 countries with conflicting water management interests.

    The modeling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar altimetry data significantly improved the performance of the hydrological model. Without assimilation of radar altimetry data, model performance was limited, probably because of the size and complexity of the model domain, simplifications inherent in model design, and the uncertainty of RS and reanalysis data. Altimetry data assimilation reduced the mean absolute error of the simulated reservoir water levels from 4.7 to 1.9 m, and

  6. Control-oriented modeling of the plasma particle density in tokamaks and application to real-time density profile reconstruction

    NARCIS (Netherlands)

    Blanken, T.C.; Felici, F.; Rapson, C.J.; de Baar, M.R.; Heemels, W.P.M.H.

    2018-01-01

    A model-based approach to real-time reconstruction of the particle density profile in tokamak plasmas is presented, based on a dynamic state estimator. Traditionally, the density profile is reconstructed in real-time by solving an ill-conditioned inversion problem using a measurement at a single

  7. 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.

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

    International Nuclear Information System (INIS)

    Sui Zhe; Sun Jun; Ma Yuanle; Zhang Ruipeng

    2013-01-01

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

  9. Analytical model for real time, noninvasive estimation of blood glucose level.

    Science.gov (United States)

    Adhyapak, Anoop; Sidley, Matthew; Venkataraman, Jayanti

    2014-01-01

    The paper presents an analytical model to estimate blood glucose level from measurements made non-invasively and in real time by an antenna strapped to a patient's wrist. Some promising success has been shown by the RIT ETA Lab research group that an antenna's resonant frequency can track, in real time, changes in glucose concentration. Based on an in-vitro study of blood samples of diabetic patients, the paper presents a modified Cole-Cole model that incorporates a factor to represent the change in glucose level. A calibration technique using the input impedance technique is discussed and the results show a good estimation as compared to the glucose meter readings. An alternate calibration methodology has been developed that is based on the shift in the antenna resonant frequency using an equivalent circuit model containing a shunt capacitor to represent the shift in resonant frequency with changing glucose levels. Work under progress is the optimization of the technique with a larger sample of patients.

  10. A hybrid condenser model for real-time applications in performance monitoring, control and optimization

    International Nuclear Information System (INIS)

    Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun; Zhang Guiqing

    2009-01-01

    In this paper, a simple, yet accurate hybrid modeling technique for condensers is presented. The method starts with fundamental physical principles but captures only few key operational characteristic parameters to predict the system performances. The advantages of the methods lie that linear or non-linear least-squares methods can be directly used to determine no more than four key operational characteristic parameters in the model, which can significantly reduce the computational burden. The developed model is verified with the experimental data taken from a pilot system. The testing results confirm that the proposed model can predict accurately the performance of the real-time operating condenser with the maximum error of less than ±10%. The model technique proposed will have wide applications not only in condenser operating optimization, but also in performance assessment and fault detection and diagnosis.

  11. Real-time modeling of complex atmospheric releases in urban areas

    International Nuclear Information System (INIS)

    Baskett, R.L.; Ellis, J.S.; Sullivan, T.J.

    1994-08-01

    If a nuclear installation in or near an urban area has a venting, fire, or explosion, airborne radioactivity becomes the major concern. Dispersion models are the immediate tool for estimating the dose and contamination. Responses in urban areas depend on knowledge of the amount of the release, representative meteorological data, and the ability of the dispersion model to simulate the complex flows as modified by terrain or local wind conditions. A centralized dispersion modeling system can produce realistic assessments of radiological accidents anywhere in a country within several minutes if it is computer-automated. The system requires source-term, terrain, mapping and dose-factor databases, real-time meteorological data acquisition, three-dimensional atmospheric transport and dispersion models, and experienced staff. Experience with past responses in urban areas by the Atmospheric Release Advisory Capability (ARAC) program at Lawrence Livermore National Laboratory illustrate the challenges for three-dimensional dispersion models

  12. Real-time modelling of complex atmospheric releases in urban areas

    International Nuclear Information System (INIS)

    Baskett, R.L.; Ellis, J.S.; Sullivan, T.J.

    2000-01-01

    If a nuclear installation in or near an urban area has a venting, fire, or explosion, airborne radioactivity becomes the major concern. Dispersion models are the immediate tool for estimating the dose and contamination. Responses in urban areas depend on knowledge of the amount of the release, representative meteorological data, and the ability of the dispersion model to simulate the complex flows as modified by terrain or local wind conditions. A centralised dispersion modelling system can produce realistic assessments of radiological accidents anywhere in a country within several minutes if it is computer-automated. The system requires source-term, terrain, mapping and dose-factor databases, real-time meteorological data acquisition, three-dimensional atmospheric transport and dispersion models, and experienced staff. Experience with past responses in urban areas by the Atmospheric Release Advisory Capability (ARAC) program at Lawrence Livermore National Laboratory illustrate the challenges for three-dimensional dispersion models. (author)

  13. Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

    Science.gov (United States)

    Aulov, O.; Halem, M.; Lary, D. J.

    2011-12-01

    We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

  14. Lie group model neuromorphic geometric engine for real-time terrain reconstruction from stereoscopic aerial photos

    Science.gov (United States)

    Tsao, Thomas R.; Tsao, Doris

    1997-04-01

    In the 1980's, neurobiologist suggested a simple mechanism in primate visual cortex for maintaining a stable and invariant representation of a moving object. The receptive field of visual neurons has real-time transforms in response to motion, to maintain a stable representation. When the visual stimulus is changed due to motion, the geometric transform of the stimulus triggers a dual transform of the receptive field. This dual transform in the receptive fields compensates geometric variation in the stimulus. This process can be modelled using a Lie group method. The massive array of affine parameter sensing circuits will function as a smart sensor tightly coupled to the passive imaging sensor (retina). Neural geometric engine is a neuromorphic computing device simulating our Lie group model of spatial perception of primate's primal visual cortex. We have developed the computer simulation and experimented on realistic and synthetic image data, and performed a preliminary research of using analog VLSI technology for implementation of the neural geometric engine. We have benchmark tested on DMA's terrain data with their result and have built an analog integrated circuit to verify the computational structure of the engine. When fully implemented on ANALOG VLSI chip, we will be able to accurately reconstruct a 3D terrain surface in real-time from stereoscopic imagery.

  15. 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.

  16. Real-Time Aircraft Cosmic Ray Radiation Exposure Predictions from the NAIRAS Model

    Science.gov (United States)

    Mertens, C. J.; Tobiska, W.; Kress, B. T.; Xu, X.

    2012-12-01

    The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. There is also interest in extending NAIRAS to the LEO environment to address radiation hazard issues for the emerging commercial spaceflight industry. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. Real-time observations are required at a variety of locations within the geospace environment. The NAIRAS model is driven by real-time input data from ground-, atmospheric-, and space-based platforms. During the development of the NAIRAS model, new science questions and observational data gaps were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. The focus of this talk is to present the current capabilities of the NAIRAS model, discuss future developments in aviation radiation modeling and instrumentation, and propose strategies and methodologies of bridging known gaps in current modeling and observational capabilities.

  17. Aggregate modeling of fast-acting demand response and control under real-time pricing

    International Nuclear Information System (INIS)

    Chassin, David P.; Rondeau, Daniel

    2016-01-01

    Highlights: • Demand elasticity for fast-acting demand response load under real-time pricing. • Validated first-principles logistic demand curve matches random utility model. • Logistic demand curve suitable for diversified aggregate loads market-based transactive control systems. - Abstract: This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

  18. Investigation Model for DDoS Attack Detection in Real-Time

    Directory of Open Access Journals (Sweden)

    Abdulghani Ali Ahmed

    2015-02-01

    Full Text Available Investigating traffic of distributed denial of services (DDoS attack requires extra overhead which mostly results in network performance degradation. This study proposes an investigation model for detecting DDoS attack in real-time without causing negative degradation against network performance. The model investigates network traffic in a scalable way to detect user violations on quality of service regulations. Traffic investigation is triggered only when the network is congested; at that exact moment, burst gateways actually generate a congestion notification to misbehaving users. The misbehaving users are thus further investigated by measuring their consumption ratios of bandwidth. By exceeding the service level agreement bandwidth ratio, user traffic is filtered as DDoS traffic. Simulation results demonstrate that the proposed model efficiently monitors intrusive traffic and precisely detects DDoS attack.

  19. Real time polymer nanocomposites-based physical nanosensors: theory and modeling

    Science.gov (United States)

    Bellucci, Stefano; Shunin, Yuri; Gopeyenko, Victor; Lobanova-Shunina, Tamara; Burlutskaya, Nataly; Zhukovskii, Yuri

    2017-09-01

    Functionalized carbon nanotubes and graphene nanoribbons nanostructures, serving as the basis for the creation of physical pressure and temperature nanosensors, are considered as tools for ecological monitoring and medical applications. Fragments of nanocarbon inclusions with different morphologies, presenting a disordered system, are regarded as models for nanocomposite materials based on carbon nanoсluster suspension in dielectric polymer environments (e.g., epoxy resins). We have formulated the approach of conductivity calculations for carbon-based polymer nanocomposites using the effective media cluster approach, disordered systems theory and conductivity mechanisms analysis, and obtained the calibration dependences. Providing a proper description of electric responses in nanosensoring systems, we demonstrate the implementation of advanced simulation models suitable for real time control nanosystems. We also consider the prospects and prototypes of the proposed physical nanosensor models providing the comparisons with experimental calibration dependences.

  20. Speech Silicon: An FPGA Architecture for Real-Time Hidden Markov-Model-Based Speech Recognition

    Directory of Open Access Journals (Sweden)

    Schuster Jeffrey

    2006-01-01

    Full Text Available This paper examines the design of an FPGA-based system-on-a-chip capable of performing continuous speech recognition on medium sized vocabularies in real time. Through the creation of three dedicated pipelines, one for each of the major operations in the system, we were able to maximize the throughput of the system while simultaneously minimizing the number of pipeline stalls in the system. Further, by implementing a token-passing scheme between the later stages of the system, the complexity of the control was greatly reduced and the amount of active data present in the system at any time was minimized. Additionally, through in-depth analysis of the SPHINX 3 large vocabulary continuous speech recognition engine, we were able to design models that could be efficiently benchmarked against a known software platform. These results, combined with the ability to reprogram the system for different recognition tasks, serve to create a system capable of performing real-time speech recognition in a vast array of environments.

  1. Speech Silicon: An FPGA Architecture for Real-Time Hidden Markov-Model-Based Speech Recognition

    Directory of Open Access Journals (Sweden)

    Alex K. Jones

    2006-11-01

    Full Text Available This paper examines the design of an FPGA-based system-on-a-chip capable of performing continuous speech recognition on medium sized vocabularies in real time. Through the creation of three dedicated pipelines, one for each of the major operations in the system, we were able to maximize the throughput of the system while simultaneously minimizing the number of pipeline stalls in the system. Further, by implementing a token-passing scheme between the later stages of the system, the complexity of the control was greatly reduced and the amount of active data present in the system at any time was minimized. Additionally, through in-depth analysis of the SPHINX 3 large vocabulary continuous speech recognition engine, we were able to design models that could be efficiently benchmarked against a known software platform. These results, combined with the ability to reprogram the system for different recognition tasks, serve to create a system capable of performing real-time speech recognition in a vast array of environments.

  2. Dynamic modelling and real-time leak detection for NGL pipelines

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-07-01

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

  3. Applications For Real Time NOMADS At NCEP To Disseminate NOAA's Operational Model Data Base

    Science.gov (United States)

    Alpert, J. C.; Wang, J.; Rutledge, G.

    2007-05-01

    A wide range of environmental information, in digital form, with metadata descriptions and supporting infrastructure is contained in the NOAA Operational Modeling Archive Distribution System (NOMADS) and its Real Time (RT) project prototype at the National Centers for Environmental Prediction (NCEP). NOMADS is now delivering on its goal of a seamless framework, from archival to real time data dissemination for NOAA's operational model data holdings. A process is under way to make NOMADS part of NCEP's operational production of products. A goal is to foster collaborations among the research and education communities, value added retailers, and public access for science and development. In the National Research Council's "Completing the Forecast", Recommendation 3.4 states: "NOMADS should be maintained and extended to include (a) long-term archives of the global and regional ensemble forecasting systems at their native resolution, and (b) re-forecast datasets to facilitate post-processing." As one of many participants of NOMADS, NCEP serves the operational model data base using data application protocol (Open-DAP) and other services for participants to serve their data sets and users to obtain them. Using the NCEP global ensemble data as an example, we show an Open-DAP (also known as DODS) client application that provides a request-and-fulfill mechanism for access to the complex ensemble matrix of holdings. As an example of the DAP service, we show a client application which accesses the Global or Regional Ensemble data set to produce user selected weather element event probabilities. The event probabilities are easily extended over model forecast time to show probability histograms defining the future trend of user selected events. This approach insures an efficient use of computer resources because users transmit only the data necessary for their tasks. Data sets are served by OPeN-DAP allowing commercial clients such as MATLAB or IDL as well as freeware clients

  4. A Spatial Reference Grid for Real-Time Autonomous Underwater Modeling using 3-D Sonar

    Energy Technology Data Exchange (ETDEWEB)

    Auran, P.G.

    1996-12-31

    The offshore industry has recognized the need for intelligent underwater robotic vehicles. This doctoral thesis deals with autonomous underwater vehicles (AUVs) and concentrates on a data representation for real-time image formation and analysis. Its main objective is to develop a 3-D image representation suitable for autonomous perception objectives underwater, assuming active sonar as the main sensor for perception. The main contributions are: (1) A dynamical image representation for 3-D range data, (2) A basic electronic circuit and software system for 3-D sonar sampling and amplitude thresholding, (3) A model for target reliability, (4) An efficient connected components algorithm for 3-D segmentation, (5) A method for extracting general 3-D geometrical representations from segmented echo clusters, (6) Experimental results of planar and curved target modeling. 142 refs., 120 figs., 10 tabs.

  5. Dynamics of symmetry breaking during quantum real-time evolution in a minimal model system.

    Science.gov (United States)

    Heyl, Markus; Vojta, Matthias

    2014-10-31

    One necessary criterion for the thermalization of a nonequilibrium quantum many-particle system is ergodicity. It is, however, not sufficient in cases where the asymptotic long-time state lies in a symmetry-broken phase but the initial state of nonequilibrium time evolution is fully symmetric with respect to this symmetry. In equilibrium, one particular symmetry-broken state is chosen as a result of an infinitesimal symmetry-breaking perturbation. From a dynamical point of view the question is: Can such an infinitesimal perturbation be sufficient for the system to establish a nonvanishing order during quantum real-time evolution? We study this question analytically for a minimal model system that can be associated with symmetry breaking, the ferromagnetic Kondo model. We show that after a quantum quench from a completely symmetric state the system is able to break its symmetry dynamically and discuss how these features can be observed experimentally.

  6. Wave optics modeling of real-time holographic wavefront compensation systems using OSSim

    Science.gov (United States)

    Carbon, Margarita A.; Guthals, Dennis M.; Logan, Jerry D.

    2005-08-01

    OSSim (Optical System Simulation) is a wave-optics, time-domain simulation toolbox with both optical and data processing components developed for adaptive optics (AO) systems. Diffractive wavefront control elements have recently been added that accurately model optically and electrically addressed spatial light modulators as real time holographic (RTH) devices in diffractive wavefront control systems. The developed RTH toolbox has found multiple applications for a variety of Boeing programs in solving problems of AO system analysis and design. Several complex diffractive wavefront control systems have been modeled for compensation of static and dynamic aberrations such as imperfect segmented primary mirrors and atmospheric and boundary layer turbulence. The results of OSSim simulations of RTH wavefront compensation show very good agreement with available experimental data.

  7. Dynamical modeling procedure of a Li-ion battery pack suitable for real-time applications

    International Nuclear Information System (INIS)

    Castano, S.; Gauchia, L.; Voncila, E.; Sanz, J.

    2015-01-01

    Highlights: • Dynamical modeling of a 50 A h battery pack composed of 56 cells. • Detailed analysis of SOC tests at realistic performance range imposed by BMS. • We propose an electrical circuit that improves how the battery capacity is modeled. • The model is validated in the SOC range using a real-time experimental setup. - Abstract: This paper presents the modeling of a 50 A h battery pack composed of 56 cells, taking into account real battery performance conditions imposed by the BMS control. The modeling procedure starts with a detailed analysis of experimental charge and discharge SOC tests. Results from these tests are used to obtain the battery model parameters at a realistic performance range (20–80% SOC). The model topology aims to better describe the finite charge contained in a battery pack. The model has been validated at three different SOC values in order to verify the model response at real battery pack operation conditions. The validation tests show that the battery pack model is able to simulate the real battery response with excellent accuracy in the range tested. The proposed modeling procedure is fully applicable to any Li-ion battery pack, regardless of the number of series or parallel cells or its rated capacity

  8. Cure modeling in real-time prediction: How much does it help?

    Science.gov (United States)

    Ying, Gui-Shuang; Zhang, Qiang; Lan, Yu; Li, Yimei; Heitjan, Daniel F

    2017-08-01

    Various parametric and nonparametric modeling approaches exist for real-time prediction in time-to-event clinical trials. Recently, Chen (2016 BMC Biomedical Research Methodology 16) proposed a prediction method based on parametric cure-mixture modeling, intending to cover those situations where it appears that a non-negligible fraction of subjects is cured. In this article we apply a Weibull cure-mixture model to create predictions, demonstrating the approach in RTOG 0129, a randomized trial in head-and-neck cancer. We compare the ultimate realized data in RTOG 0129 to interim predictions from a Weibull cure-mixture model, a standard Weibull model without a cure component, and a nonparametric model based on the Bayesian bootstrap. The standard Weibull model predicted that events would occur earlier than the Weibull cure-mixture model, but the difference was unremarkable until late in the trial when evidence for a cure became clear. Nonparametric predictions often gave undefined predictions or infinite prediction intervals, particularly at early stages of the trial. Simulations suggest that cure modeling can yield better-calibrated prediction intervals when there is a cured component, or the appearance of a cured component, but at a substantial cost in the average width of the intervals. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. 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.

  10. Enabling Real-time Water Decision Support Services Using Model as a Service

    Science.gov (United States)

    Zhao, T.; Minsker, B. S.; Lee, J. S.; Salas, F. R.; Maidment, D. R.; David, C. H.

    2014-12-01

    Through application of computational methods and an integrated information system, data and river modeling services can help researchers and decision makers more rapidly understand river conditions under alternative scenarios. To enable this capability, workflows (i.e., analysis and model steps) are created and published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, has been implemented as a workflow and published as a Web application. This allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. The model service and Web application has been prototyped in the San Antonio and Guadalupe River Basin in Texas, with input from university and agency partners. In the future, optimization model workflows will be developed to link with the RAPID model workflow to provide real-time water allocation decision support services.

  11. 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.

  12. Reliability modeling of a hard real-time system using the path-space approach

    International Nuclear Information System (INIS)

    Kim, Hagbae

    2000-01-01

    A hard real-time system, such as a fly-by-wire system, fails catastrophically (e.g. losing stability) if its control inputs are not updated by its digital controller computer within a certain timing constraint called the hard deadline. To assess and validate those systems' reliabilities by using a semi-Markov model that explicitly contains the deadline information, we propose a path-space approach deriving the upper and lower bounds of the probability of system failure. These bounds are derived by using only simple parameters, and they are especially suitable for highly reliable systems which should recover quickly. Analytical bounds are derived for both exponential and Wobble failure distributions encountered commonly, which have proven effective through numerical examples, while considering three repair strategies: repair-as-good-as-new, repair-as-good-as-old, and repair-better-than-old

  13. Modeling Optical Spectra of Large Organic Systems Using Real-Time Propagation of Semiempirical Effective Hamiltonians.

    Science.gov (United States)

    Ghosh, Soumen; Andersen, Amity; Gagliardi, Laura; Cramer, Christopher J; Govind, Niranjan

    2017-09-12

    We present an implementation of a time-dependent semiempirical method (INDO/S) in NWChem using real-time (RT) propagation to address, in principle, the entire spectrum of valence electronic excitations. Adopting this model, we study the UV/vis spectra of medium-sized systems such as P3B2 and f-coronene, and in addition much larger systems such as ubiquitin in the gas phase and the betanin chromophore in the presence of two explicit solvents (water and methanol). RT-INDO/S provides qualitatively and often quantitatively accurate results when compared with RT- TDDFT or experimental spectra. Even though we only consider the INDO/S Hamiltonian in this work, our implementation provides a framework for performing electron dynamics in large systems using semiempirical Hartree-Fock Hamiltonians in general.

  14. Real-time source deformation modeling through GNSS permanent stations at Merapi volcano (Indonesia

    Science.gov (United States)

    Beauducel, F.; Nurnaning, A.; Iguchi, M.; Fahmi, A. A.; Nandaka, M. A.; Sumarti, S.; Subandriyo, S.; Metaxian, J. P.

    2014-12-01

    Mt. Merapi (Java, Indonesia) is one of the most active and dangerous volcano in the world. A first GPS repetition network was setup and periodically measured since 1993, allowing detecting a deep magma reservoir, quantifying magma flux in conduit and identifying shallow discontinuities around the former crater (Beauducel and Cornet, 1999;Beauducel et al., 2000, 2006). After the 2010 centennial eruption, when this network was almost completely destroyed, Indonesian and Japanese teams installed a new continuous GPS network for monitoring purpose (Iguchi et al., 2011), consisting of 3 stations located at the volcano flanks, plus a reference station at the Yogyakarta Observatory (BPPTKG).In the framework of DOMERAPI project (2013-2016) we have completed this network with 5 additional stations, which are located on the summit area and volcano surrounding. The new stations are 1-Hz sampling, GNSS (GPS + GLONASS) receivers, and near real-time data streaming to the Observatory. An automatic processing has been developed and included in the WEBOBS system (Beauducel et al., 2010) based on GIPSY software computing precise daily moving solutions every hour, and for different time scales (2 months, 1 and 5 years), time series and velocity vectors. A real-time source modeling estimation has also been implemented. It uses the depth-varying point source solution (Mogi, 1958; Williams and Wadge, 1998) in a systematic inverse problem model exploration that displays location, volume variation and 3-D probability map.The operational system should be able to better detect and estimate the location and volume variations of possible magma sources, and to follow magma transfer towards the surface. This should help monitoring and contribute to decision making during future unrest or eruption.

  15. Automatic dataflow model extraction from modal real-time stream processing applications

    NARCIS (Netherlands)

    Geuns, S.J.; Hausmans, J.P.H.M.; Bekooij, Marco Jan Gerrit

    2013-01-01

    Many real-time stream processing applications are initially described as a sequential application containing while-loops, which execute for an unknown number of iterations. These modal applications have to be executed in parallel on an MPSoC system in order to meet their real-time throughput

  16. Unified and Modular Modeling and Functional Verification Framework of Real-Time Image Signal Processors

    Directory of Open Access Journals (Sweden)

    Abhishek Jain

    2016-01-01

    Full Text Available In VLSI industry, image signal processing algorithms are developed and evaluated using software models before implementation of RTL and firmware. After the finalization of the algorithm, software models are used as a golden reference model for the image signal processor (ISP RTL and firmware development. In this paper, we are describing the unified and modular modeling framework of image signal processing algorithms used for different applications such as ISP algorithms development, reference for hardware (HW implementation, reference for firmware (FW implementation, and bit-true certification. The universal verification methodology- (UVM- based functional verification framework of image signal processors using software reference models is described. Further, IP-XACT based tools for automatic generation of functional verification environment files and model map files are described. The proposed framework is developed both with host interface and with core using virtual register interface (VRI approach. This modeling and functional verification framework is used in real-time image signal processing applications including cellphone, smart cameras, and image compression. The main motivation behind this work is to propose the best efficient, reusable, and automated framework for modeling and verification of image signal processor (ISP designs. The proposed framework shows better results and significant improvement is observed in product verification time, verification cost, and quality of the designs.

  17. Real-time management of a multipurpose water reservoir with a heteroscedastic inflow model

    Science.gov (United States)

    Pianosi, F.; Soncini-Sessa, R.

    2009-10-01

    Stochastic dynamic programming has been extensively used as a method for designing optimal regulation policies for water reservoirs. However, the potential of this method is dramatically reduced by its computational burden, which often forces to introduce strong approximations in the model of the system, especially in the description of the reservoir inflow. In this paper, an approach to partially remedy this problem is proposed and applied to a real world case study. It foresees solving the management problem on-line, using a reduced model of the system and the inflow forecast provided by a dynamic model. By doing so, all the hydrometeorological information that is available in real-time is fully exploited. The model here proposed for the inflow forecasting is a nonlinear, heteroscedastic model that provides both the expected value and the standard deviation of the inflow through dynamic relations. The effectiveness of such model for the purpose of the reservoir regulation is evaluated through simulation and comparison with the results provided by conventional homoscedastic inflow models.

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

    Directory of Open Access Journals (Sweden)

    Gergely Takács

    2014-01-01

    Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

  19. On the Correctness of Real-Time Modular Computer Systems Modeling with Stopwatch Automata Networks

    Directory of Open Access Journals (Sweden)

    Alevtina B. Glonina

    2018-01-01

    Full Text Available In this paper, we consider a schedulability analysis problem for real-time modular computer systems (RT MCS. A system configuration is called schedulable if all the jobs finish within their deadlines. The authors propose a stopwatch automata-based general model of RT MCS operation. A model instance for a given RT MCS configuration is a network of stopwatch automata (NSA and it can be built automatically using the general model. A system operation trace, which is necessary for checking the schedulability criterion, can be obtained from the corresponding NSA trace. The paper substantiates the correctness of the proposed approach. A set of correctness requirements to models of system components and to the whole system model were derived from RT MCS specifications. The authors proved that if all models of system components satisfy the corresponding requirements, the whole system model built according to the proposed approach satisfies its correctness requirements and is deterministic (i.e. for a given configuration a trace generated by the corresponding model run is uniquely determined. The model determinism implies that any model run can be used for schedulability analysis. This fact is crucial for the approach efficiency, as the number of possible model runs grows exponentially with the number of jobs in a system. Correctness requirements to models of system components models can be checked automatically by a verifier using observer automata approach. The authors proved by using UPPAAL verifier that all the developed models of system components satisfy the corresponding requirements. User-defined models of system components can be also used for system modeling if they satisfy the requirements.

  20. IPS – A SYSTEM FOR REAL-TIME NAVIGATION AND 3D MODELING

    Directory of Open Access Journals (Sweden)

    D. Grießbach

    2012-07-01

    Full Text Available fdaReliable navigation and 3D modeling is a necessary requirement for any autonomous system in real world scenarios. German Aerospace Center (DLR developed a system providing precise information about local position and orientation of a mobile platform as well as three-dimensional information about its environment in real-time. This system, called Integral Positioning System (IPS can be applied for indoor environments and outdoor environments. To achieve high precision, reliability, integrity and availability a multi-sensor approach was chosen. The important role of sensor data synchronization, system calibration and spatial referencing is emphasized because the data from several sensors has to be fused using a Kalman filter. A hardware operating system (HW-OS is presented, that facilitates the low-level integration of different interfaces. The benefit of this approach is an increased precision of synchronization at the expense of additional engineering costs. It will be shown that the additional effort is leveraged by the new design concept since the HW-OS methodology allows a proven, flexible and fast design process, a high re-usability of common components and consequently a higher reliability within the low-level sensor fusion. Another main focus of the paper is on IPS software. The DLR developed, implemented and tested a flexible and extensible software concept for data grabbing, efficient data handling, data preprocessing (e.g. image rectification being essential for thematic data processing. Standard outputs of IPS are a trajectory of the moving platform and a high density 3D point cloud of the current environment. This information is provided in real-time. Based on these results, information processing on more abstract levels can be executed.

  1. Real time wave forecasting using wind time history and numerical model

    Science.gov (United States)

    Jain, Pooja; Deo, M. C.; Latha, G.; Rajendran, V.

    Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired.

  2. On the choice of the demand and hydraulic modeling approach to WDN real-time simulation

    Science.gov (United States)

    Creaco, Enrico; Pezzinga, Giuseppe; Savic, Dragan

    2017-07-01

    This paper aims to analyze two demand modeling approaches, i.e., top-down deterministic (TDA) and bottom-up stochastic (BUA), with particular reference to their impact on the hydraulic modeling of water distribution networks (WDNs). In the applications, the hydraulic modeling is carried out through the extended period simulation (EPS) and unsteady flow modeling (UFM). Taking as benchmark the modeling conditions that are closest to the WDN's real operation (UFM + BUA), the analysis showed that the traditional use of EPS + TDA produces large pressure head and water discharge errors, which can be attenuated only when large temporal steps (up to 1 h in the case study) are used inside EPS. The use of EPS + BUA always yields better results. Indeed, EPS + BUA already gives a good approximation of the WDN's real operation when intermediate temporal steps (larger than 2 min in the case study) are used for the simulation. The trade-off between consistency of results and computational burden makes EPS + BUA the most suitable tool for real-time WDN simulation, while benefitting from data acquired through smart meters for the parameterization of demand generation models.

  3. 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.

  4. Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

    Science.gov (United States)

    Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

    2017-01-01

    The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

  5. Ovation Prime Real-Time

    Data.gov (United States)

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

  6. Creating wavelet-based models for real-time synthesis of perceptually convincing environmental sounds

    Science.gov (United States)

    Miner, Nadine Elizabeth

    1998-09-01

    This dissertation presents a new wavelet-based method for synthesizing perceptually convincing, dynamic sounds using parameterized sound models. The sound synthesis method is applicable to a variety of applications including Virtual Reality (VR), multi-media, entertainment, and the World Wide Web (WWW). A unique contribution of this research is the modeling of the stochastic, or non-pitched, sound components. This stochastic-based modeling approach leads to perceptually compelling sound synthesis. Two preliminary studies conducted provide data on multi-sensory interaction and audio-visual synchronization timing. These results contributed to the design of the new sound synthesis method. The method uses a four-phase development process, including analysis, parameterization, synthesis and validation, to create the wavelet-based sound models. A patent is pending for this dynamic sound synthesis method, which provides perceptually-realistic, real-time sound generation. This dissertation also presents a battery of perceptual experiments developed to verify the sound synthesis results. These experiments are applicable for validation of any sound synthesis technique.

  7. Source modeling and inversion with near real-time GPS: a GITEWS perspective for Indonesia

    Science.gov (United States)

    Babeyko, A. Y.; Hoechner, A.; Sobolev, S. V.

    2010-07-01

    We present the GITEWS approach to source modeling for the tsunami early warning in Indonesia. Near-field tsunami implies special requirements to both warning time and details of source characterization. To meet these requirements, we employ geophysical and geological information to predefine a maximum number of rupture parameters. We discretize the tsunamigenic Sunda plate interface into an ordered grid of patches (150×25) and employ the concept of Green's functions for forward and inverse rupture modeling. Rupture Generator, a forward modeling tool, additionally employs different scaling laws and slip shape functions to construct physically reasonable source models using basic seismic information only (magnitude and epicenter location). GITEWS runs a library of semi- and fully-synthetic scenarios to be extensively employed by system testing as well as by warning center personnel teaching and training. Near real-time GPS observations are a very valuable complement to the local tsunami warning system. Their inversion provides quick (within a few minutes on an event) estimation of the earthquake magnitude, rupture position and, in case of sufficient station coverage, details of slip distribution.

  8. Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

    Science.gov (United States)

    Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

    2017-09-01

    Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

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

    Science.gov (United States)

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

    2015-07-01

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

  10. Use of flood propagation models in real time hydrologic forecast: experiences at Segura River

    International Nuclear Information System (INIS)

    Valverde, Angel Luis Aldana; Beato, Ana Martinez Perez

    2004-01-01

    In this paper a case study related to flood propagation forecast in the Segura River in Spain is presented along with the application that was developed for that purpose. Simulation and forecast models ease the work carry out by the watershed organism personnel and may be essential to understand the complexity of some of the propagation phenomena that take place at specific locations such as the study area, a man-made channel at the downstream end of the Segura River (from Contraparada to Guardamar), including the tributaries along the stream. Three different models were used in the previous studies: a steady state numerical model (Hec-Ras), a physical model and two unsteady state numerical models (ISIS and HMS). Also, historical time series were analyzed and some topography works were carried out along the stream. PROC Segura model was conceived for real time flood propagation forecast in the mentioned area using the data collected by the SAIH. A simplified model was developed based on the following methods: Muskingum, Muskingum-Cunge and Modified Puls. To overcome some of these models limitations, such as the one to one discharge-water surface relationships and the impossibility of reproducing downstream backwater, doubled input rating curves were used to estimate the discharge at some of the gauging stations located at the tributaries, i.e. Merancho and Rambia del Derramador, which may be affected by the water level in the Segura River. The advantages of using these simplified models versus a dynamic wave model were studied and reported as well. In general, it can be stated that when several solutions are provided to solve the same problem, the simplest solution is usually the best one.(Author)

  11. Earthquake and failure forecasting in real-time: A Forecasting Model Testing Centre

    Science.gov (United States)

    Filgueira, Rosa; Atkinson, Malcolm; Bell, Andrew; Main, Ian; Boon, Steven; Meredith, Philip

    2013-04-01

    Across Europe there are a large number of rock deformation laboratories, each of which runs many experiments. Similarly there are a large number of theoretical rock physicists who develop constitutive and computational models both for rock deformation and changes in geophysical properties. Here we consider how to open up opportunities for sharing experimental data in a way that is integrated with multiple hypothesis testing. We present a prototype for a new forecasting model testing centre based on e-infrastructures for capturing and sharing data and models to accelerate the Rock Physicist (RP) research. This proposal is triggered by our work on data assimilation in the NERC EFFORT (Earthquake and Failure Forecasting in Real Time) project, using data provided by the NERC CREEP 2 experimental project as a test case. EFFORT is a multi-disciplinary collaboration between Geoscientists, Rock Physicists and Computer Scientist. Brittle failure of the crust is likely to play a key role in controlling the timing of a range of geophysical hazards, such as volcanic eruptions, yet the predictability of brittle failure is unknown. Our aim is to provide a facility for developing and testing models to forecast brittle failure in experimental and natural data. Model testing is performed in real-time, verifiably prospective mode, in order to avoid selection biases that are possible in retrospective analyses. The project will ultimately quantify the predictability of brittle failure, and how this predictability scales from simple, controlled laboratory conditions to the complex, uncontrolled real world. Experimental data are collected from controlled laboratory experiments which includes data from the UCL Laboratory and from Creep2 project which will undertake experiments in a deep-sea laboratory. We illustrate the properties of the prototype testing centre by streaming and analysing realistically noisy synthetic data, as an aid to generating and improving testing methodologies in

  12. Real-time characterization of partially observed epidemics using surrogate models.

    Energy Technology Data Exchange (ETDEWEB)

    Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia; Crary, David (Applied Research Associates, Arlington, VA); Sargsyan, Khachik; Cheng, Karen (Applied Research Associates, Arlington, VA)

    2011-09-01

    We present a statistical method, predicated on the use of surrogate models, for the 'real-time' characterization of partially observed epidemics. Observations consist of counts of symptomatic patients, diagnosed with the disease, that may be available in the early epoch of an ongoing outbreak. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information on the dynamics of the etiologic agent in the affected population e.g., the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and epidemiological parameters are estimated as distributions using a Markov chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. In some cases, the inverse problem can be computationally expensive, primarily due to the epidemic simulator used inside the inversion algorithm. We present a method, based on replacing the epidemiological model with computationally inexpensive surrogates, that can reduce the computational time to minutes, without a significant loss of accuracy. The surrogates are created by projecting the output of an epidemiological model on a set of polynomial chaos bases; thereafter, computations involving the surrogate model reduce to evaluations of a polynomial. We find that the epidemic characterizations obtained with the surrogate models is very close to that obtained with the original model. We also find that the number of projections required to construct a surrogate model is O(10)-O(10{sup 2}) less than the number of samples required by the MCMC to construct a stationary posterior distribution; thus, depending upon the epidemiological models in question, it may be possible to omit the offline creation and caching of surrogate models, prior to their use in an inverse problem. The technique is demonstrated on synthetic data as well as

  13. An accurate real-time model of maglev planar motor based on compound Simpson numerical integration

    Directory of Open Access Journals (Sweden)

    Baoquan Kou

    2017-05-01

    Full Text Available To realize the high-speed and precise control of the maglev planar motor, a more accurate real-time electromagnetic model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems for the stator, mover and corner coil are established. The coil is divided into two segments, the straight coil segment and the corner coil segment, in order to obtain a complete electromagnetic model. When only take the first harmonic of the flux density distribution of a Halbach magnet array into account, the integration method can be carried out towards the two segments according to Lorenz force law. The force and torque analysis formula of the straight coil segment can be derived directly from Newton-Leibniz formula, however, this is not applicable to the corner coil segment. Therefore, Compound Simpson numerical integration method is proposed in this paper to solve the corner segment. With the validation of simulation and experiment, the proposed model has high accuracy and can realize practical application easily.

  14. An accurate real-time model of maglev planar motor based on compound Simpson numerical integration

    Science.gov (United States)

    Kou, Baoquan; Xing, Feng; Zhang, Lu; Zhou, Yiheng; Liu, Jiaqi

    2017-05-01

    To realize the high-speed and precise control of the maglev planar motor, a more accurate real-time electromagnetic model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems for the stator, mover and corner coil are established. The coil is divided into two segments, the straight coil segment and the corner coil segment, in order to obtain a complete electromagnetic model. When only take the first harmonic of the flux density distribution of a Halbach magnet array into account, the integration method can be carried out towards the two segments according to Lorenz force law. The force and torque analysis formula of the straight coil segment can be derived directly from Newton-Leibniz formula, however, this is not applicable to the corner coil segment. Therefore, Compound Simpson numerical integration method is proposed in this paper to solve the corner segment. With the validation of simulation and experiment, the proposed model has high accuracy and can realize practical application easily.

  15. A deformable surface model for real-time water drop animation.

    Science.gov (United States)

    Zhang, Yizhong; Wang, Huamin; Wang, Shuai; Tong, Yiying; Zhou, Kun

    2012-08-01

    A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.

  16. Modelling real-time control of WWTP influent flow under data scarcity.

    Science.gov (United States)

    Kroll, Stefan; Dirckx, Geert; Donckels, Brecht M R; Van Dorpe, Mieke; Weemaes, Marjoleine; Willems, Patrick

    2016-01-01

    In order to comply with effluent standards, wastewater operators need to avoid hydraulic overloading of the wastewater treatment plant (WWTP), as this can result in the washout of activated sludge from secondary settling tanks. Hydraulic overloading can occur in a systematic way, for instance when sewer network connections are extended without increasing the WWTP's capacity accordingly. This study demonstrates the use of rule-based real-time control (RTC) to reduce the load to the WWTP while restricting the overall overflow volume of the sewer system to a minimum. Further, it shows the added value of RTC despite the limited availability of monitoring data and information on the catchment through a parsimonious simulation approach, using relocation of spatial system boundaries and creating required input data through reverse modelling. Focus was hereby on the accurate modelling of pump hydraulics and control. Finally, two different methods of global sensitivity analysis were employed to verify the influence of parameters of both the model and the implemented control algorithm. Both methods show the importance of good knowledge of the system properties, but that monitoring errors play a minor role.

  17. On Modelling Real-time and Security properties of Distributed Systems

    NARCIS (Netherlands)

    Corin, Ricardo; Etalle, Sandro; Hartel, Pieter H.; Mader, Angelika H.

    2003-01-01

    We discuss a simplified version of the timing attack to illustrate a connection between security and real-time properties of distributed systems. We suggest several avenues for further research on this and similar connections.

  18. Improved Strategies and Optimization of Calibration Models for Real-time PCR Absolute Quantification

    Science.gov (United States)

    Real-time PCR absolute quantification applications rely on the use of standard curves to make estimates of DNA target concentrations in unknown samples. Traditional absolute quantification approaches dictate that a standard curve must accompany each experimental run. However, t...

  19. Real-Time Gesture-Controlled Physical Modelling Music Synthesis with Tactile Feedback

    Directory of Open Access Journals (Sweden)

    David M. Howard

    2004-06-01

    Full Text Available Electronic sound synthesis continues to offer huge potential possibilities for the creation of new musical instruments. The traditional approach is, however, seriously limited in that it incorporates only auditory feedback and it will typically make use of a sound synthesis model (e.g., additive, subtractive, wavetable, and sampling that is inherently limited and very often nonintuitive to the musician. In a direct attempt to challenge these issues, this paper describes a system that provides tactile as well as acoustic feedback, with real-time synthesis that invokes a more intuitive response from players since it is based upon mass-spring physical modelling. Virtual instruments are set up via a graphical user interface in terms of the physical properties of basic well-understood sounding objects such as strings, membranes, and solids. These can be interconnected to form complex integrated structures. Acoustic excitation can be applied at any point mass via virtual bowing, plucking, striking, specified waveform, or from any external sound source. Virtual microphones can be placed at any point masses to deliver the acoustic output. These aspects of the instrument are described along with the nature of the resulting acoustic output.

  20. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

    Science.gov (United States)

    Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

    2016-08-15

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

    International Nuclear Information System (INIS)

    Teng, S.; Tebby, C.; Barcellini-Couget, S.; De Sousa, G.; Brochot, C.; Rahmani, R.; Pery, A.R.R.

    2016-01-01

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

  2. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

    Energy Technology Data Exchange (ETDEWEB)

    Teng, S.; Tebby, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Barcellini-Couget, S. [ODESIA Neosciences, Sophia Antipolis, 400 route des chappes, 06903 Sophia Antipolis (France); De Sousa, G. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Brochot, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Rahmani, R. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Pery, A.R.R., E-mail: alexandre.pery@agroparistech.fr [AgroParisTech, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France); INRA, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France)

    2016-08-15

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

  3. A Human Sensor Network Framework in Support of Near Real Time Situational Geophysical Modeling

    Science.gov (United States)

    Aulov, O.; Price, A.; Smith, J. A.; Halem, M.

    2013-12-01

    The area of Disaster Management is well established among Federal Agencies such as FEMA, EPA, NOAA and NASA. These agencies have well formulated frameworks for response and mitigation based on near real time satellite and conventional observing networks for assimilation into geophysical models. Forecasts from these models are used to communicate with emergency responders and the general public. More recently, agencies have started using social media to broadcast warnings and alerts to potentially affected communities. In this presentation, we demonstrate the added benefits of mining and assimilating the vast amounts of social media data available from heterogeneous hand held devices and social networks into established operational geophysical modeling frameworks as they apply to the five cornerstones of disaster management - Prevention, Mitigation, Preparedness, Response and Recovery. Often, in situations of extreme events, social media provide the earliest notification of adverse extreme events. However, various forms of social media data also can provide useful geolocated and time stamped in situ observations, complementary to directly sensed conventional observations. We use the concept of a Human Sensor Network where one views social media users as carrying field deployed "sensors" whose posts are the remotely "sensed instrument measurements.' These measurements can act as 'station data' providing the resolution and coverage needed for extreme event specific modeling and validation. Here, we explore the use of social media through the use of a Human Sensor Network (HSN) approach as another data input source for assimilation into geophysical models. Employing the HSN paradigm can provide useful feedback in near real-time, but presents software challenges for rapid access, quality filtering and transforming massive social media data into formats consistent with the operational models. As a use case scenario, we demonstrate the value of HSN for disaster management

  4. Real-time systems

    OpenAIRE

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

    1992-01-01

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

  5. Modeling solvation effects in real-space and real-time within density functional approaches

    Energy Technology Data Exchange (ETDEWEB)

    Delgado, Alain [Istituto Nanoscienze - CNR, Centro S3, via Campi 213/A, 41125 Modena (Italy); Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear, Calle 30 # 502, 11300 La Habana (Cuba); Corni, Stefano; Pittalis, Stefano; Rozzi, Carlo Andrea [Istituto Nanoscienze - CNR, Centro S3, via Campi 213/A, 41125 Modena (Italy)

    2015-10-14

    The Polarizable Continuum Model (PCM) can be used in conjunction with Density Functional Theory (DFT) and its time-dependent extension (TDDFT) to simulate the electronic and optical properties of molecules and nanoparticles immersed in a dielectric environment, typically liquid solvents. In this contribution, we develop a methodology to account for solvation effects in real-space (and real-time) (TD)DFT calculations. The boundary elements method is used to calculate the solvent reaction potential in terms of the apparent charges that spread over the van der Waals solute surface. In a real-space representation, this potential may exhibit a Coulomb singularity at grid points that are close to the cavity surface. We propose a simple approach to regularize such singularity by using a set of spherical Gaussian functions to distribute the apparent charges. We have implemented the proposed method in the OCTOPUS code and present results for the solvation free energies and solvatochromic shifts for a representative set of organic molecules in water.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-07-01

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

  7. Double point source W-phase inversion: Real-time implementation and automated model selection

    Science.gov (United States)

    Nealy, Jennifer; Hayes, Gavin

    2015-01-01

    Rapid and accurate characterization of an earthquake source is an extremely important and ever evolving field of research. Within this field, source inversion of the W-phase has recently been shown to be an effective technique, which can be efficiently implemented in real-time. An extension to the W-phase source inversion is presented in which two point sources are derived to better characterize complex earthquakes. A single source inversion followed by a double point source inversion with centroid locations fixed at the single source solution location can be efficiently run as part of earthquake monitoring network operational procedures. In order to determine the most appropriate solution, i.e., whether an earthquake is most appropriately described by a single source or a double source, an Akaike information criterion (AIC) test is performed. Analyses of all earthquakes of magnitude 7.5 and greater occurring since January 2000 were performed with extended analyses of the September 29, 2009 magnitude 8.1 Samoa earthquake and the April 19, 2014 magnitude 7.5 Papua New Guinea earthquake. The AIC test is shown to be able to accurately select the most appropriate model and the selected W-phase inversion is shown to yield reliable solutions that match published analyses of the same events.

  8. Scientists in the Classroom Mentor Model Program - Bringing real time science into the K - 12 classroom

    Science.gov (United States)

    Worssam, J. B.

    2017-12-01

    Field research finally within classroom walls, data driven, hands on with students using a series of electronic projects to show evidence of scientific mentor collaboration. You do not want to miss this session in which I will be sharing the steps to develop an interactive mentor program between scientists in the field and students in the classroom. Using next generation science standards and common core language skills you will be able to blend scientific exploration with scientific writing and communication skills. Learn how to make connections in your own community with STEM businesses, agencies and organizations. Learn how to connect with scientists across the globe to make your classroom instruction interactive and live for all students. Scientists, you too will want to participate, see how you can reach out and be a part of the K-12 educational system with students learning about YOUR science, a great component for NSF grants! "Scientists in the Classroom," a model program for all, bringing real time science, data and knowledge into the classroom.

  9. A model system using confocal fluorescence microscopy for examining real-time intracellular sodium ion regulation.

    Science.gov (United States)

    Lee, Jacqueline A; Collings, David A; Glover, Chris N

    2016-08-15

    The gills of euryhaline fish are the ultimate ionoregulatory tissue, achieving ion homeostasis despite rapid and significant changes in external salinity. Cellular handling of sodium is not only critical for salt and water balance but is also directly linked to other essential functions such as acid-base homeostasis and nitrogen excretion. However, although measurement of intracellular sodium ([Na(+)]i) is important for an understanding of gill transport function, it is challenging and subject to methodological artifacts. Using gill filaments from a model euryhaline fish, inanga (Galaxias maculatus), the suitability of the fluorescent dye CoroNa Green as a probe for measuring [Na(+)]i in intact ionocytes was confirmed via confocal microscopy. Cell viability was verified, optimal dye loading parameters were determined, and the dye-ion dissociation constant was measured. Application of the technique to freshwater- and 100% seawater-acclimated inanga showed salinity-dependent changes in branchial [Na(+)]i, whereas no significant differences in branchial [Na(+)]i were determined in 50% seawater-acclimated fish. This technique facilitates the examination of real-time changes in gill [Na(+)]i in response to environmental factors and may offer significant insight into key homeostatic functions associated with the fish gill and the principles of sodium ion transport in other tissues and organisms. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. A meshless EFG-based algorithm for 3D deformable modeling of soft tissue in real-time.

    Science.gov (United States)

    Abdi, Elahe; Farahmand, Farzam; Durali, Mohammad

    2012-01-01

    The meshless element-free Galerkin method was generalized and an algorithm was developed for 3D dynamic modeling of deformable bodies in real time. The efficacy of the algorithm was investigated in a 3D linear viscoelastic model of human spleen subjected to a time-varying compressive force exerted by a surgical grasper. The model remained stable in spite of the considerably large deformations occurred. There was a good agreement between the results and those of an equivalent finite element model. The computational cost, however, was much lower, enabling the proposed algorithm to be effectively used in real-time applications.

  11. 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

  12. Patterns for automatic generation of soft real-time system models

    NARCIS (Netherlands)

    Florescu, O.; Voeten, J.P.M.; Theelen, B.D.; Corporaal, H.

    2009-01-01

    Worst-case assumptions about the timing of systems are often too conservative when analyzing distributed soft real-time systems as they lead to over-dimensioned and expensive products. For these systems, a certain percentage of deadline misses is often affordable. Instead of a binary answer

  13. Atmospheric dispersion models and pre-processing of meteorological data for real-time application

    DEFF Research Database (Denmark)

    Mikkelsen, T.; Desiato, F.

    1993-01-01

    RODOS is a real-time and on-line decision support system for assisting emergency response in the case of a nuclear emergency. The system is presently under development within the CEC Radiation Protection Programme as a joint venture between several European institutes. This paper identifies, ranks...

  14. Performance model for “Just-in-Time” problems in real-time multimedia applications

    NARCIS (Netherlands)

    R.D. van der Mei (Rob); F.J. Seinstra; G.M. Koole (Ger); R. Yang (Ran); D. Roubos; H. Bal

    2008-01-01

    htmlabstractOver the last few years, the use of large-scale multimedia data applications has been growing tremendously, and this growth is not likely to slow down in the near future. Many multimedia applications operate in a real-time environment (e.g., surveillance cameras, iris scans), which

  15. Model Checking Process Algebra of Communicating Resources for Real-time Systems

    DEFF Research Database (Denmark)

    Boudjadar, Jalil; Kim, Jin Hyun; Larsen, Kim Guldstrand

    2014-01-01

    This paper presents a new process algebra, called PACOR, for real-time systems which deals with resource constrained timed behavior as an improved version of the ACSR algebra. We define PACOR as a Process Algebra of Communicating Resources which allows to express preemptiveness, urgent ness...

  16. Model checking process algebra of communicating resources for real-time systems

    DEFF Research Database (Denmark)

    Boudjadar, Jalil; Kim, Jin Hyun; Larsen, Kim Guldstrand

    2014-01-01

    This paper presents a new process algebra, called PACoR, for real-time systems which deals with resource- constrained timed behavior as an improved version of the ACSR algebra. We define PACoR as a Process Algebra of Communicating Resources which allows to explicitly express preemptiveness...

  17. T-UPPAAL: Online Model-based Testing of Real-Time Systems

    DEFF Research Database (Denmark)

    Mikucionis, Marius; Larsen, Kim Guldstrand; Nielsen, Brian

    2004-01-01

    The goal of testing is to gain confidence in a physical computer based system by means of executing it. More than one third of typical project resources is spent on testing embedded and real-time systems, but still it remains ad-hoc, based on heuristics, and error-prone. Therefore systematic...

  18. Validation of an intermediate heat exchanger model for real time analysis

    International Nuclear Information System (INIS)

    Tzanos, C.P.

    1986-11-01

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

  19. Real time damage detection using recursive principal components and time varying auto-regressive modeling

    Science.gov (United States)

    Krishnan, M.; Bhowmik, B.; Hazra, B.; Pakrashi, V.

    2018-02-01

    experiments performed on a cantilever beam subjected to earthquake excitation; a two-storey benchscale model with a TMD and, data from recorded responses of UCLA factor building demonstrate the efficacy of the proposed methodology as an ideal candidate for real time, reference free structural health monitoring.

  20. Radiation environmental real-time monitoring and dispersion modeling: A comprehensive solution

    International Nuclear Information System (INIS)

    Kovacik, A.; Bartokova, I.; Omelka, J.; Melicherova, T.

    2014-01-01

    The system of real-time radiation monitoring provided by MicroStep-MIS is a turn-key solution for measurement, acquisition, processing, reporting, archiving and displaying of various radiation data. At the level of measurements, the monitoring stations can be equipped with various devices from radiation probes, measuring the actual ambient gamma dose rate, to fully automated aerosol monitors, returning analysis results of natural and manmade radionuclides concentrations in the air. Using data gathered by our radiation probes RPSG-05 integrated into monitoring network of Crisis Management of the Slovak Republic and into monitoring network of Slovak Hydrometeorological Institute, we demonstrate its reliability and long-term stability of measurements. Data from RPSG-05 probes and GammaTracer probes, both of these types are used in the SHI network, are compared. The sensitivity of RPSG-05 is documented on data where changes of dose rate are caused by precipitation. Qualities of RPSG-05 probe are illustrated also on example of its use in radiation monitoring network in the United Arab Emirates. A more detailed information about radioactivity of the atmosphere can be obtained by using spectrometric detectors (e.g. scintillation detectors) which, besides gamma dose rate values, offer also a possibility to identify different radionuclides. However, this possibility is limited by technical parameters of detector like energetic resolution and detection efficiency in given geometry of measurement. A clearer information with less doubts can be obtained from aerosol monitors with a built-in silicon detector of alpha and beta particles and with an electrically cooled HPGe detector dedicated for gamma-ray spectrometry, which is performed during the sampling. Data from a complex radiation monitoring network can be used, together with meteorological data, in radiation dispersion model by MicroStep-MIS. This model serves for simulation of atmospheric propagation of radionuclides

  1. Modeling and analysis of real-time and embedded systems with UML and MARTE developing cyber-physical systems

    CERN Document Server

    Selic, Bran

    2013-01-01

    Modeling and Analysis of Real-Time and Embedded Systems with UML and MARTE explains how to apply the complex MARTE standard in practical situations. This approachable reference provides a handy user guide, illustrating with numerous examples how you can use MARTE to design and develop real-time and embedded systems and software. Expert co-authors Bran Selic and Sébastien Gérard lead the team that drafted and maintain the standard and give you the tools you need apply MARTE to overcome the limitations of cyber-physical systems. The functional sophistication required of modern cyber-physical

  2. A Computational Model for Real-Time Calculation of Electric Field due to Transcranial Magnetic Stimulation in Clinics

    Directory of Open Access Journals (Sweden)

    Alessandra Paffi

    2015-01-01

    Full Text Available The aim of this paper is to propose an approach for an accurate and fast (real-time computation of the electric field induced inside the whole brain volume during a transcranial magnetic stimulation (TMS procedure. The numerical solution implements the admittance method for a discretized realistic brain model derived from Magnetic Resonance Imaging (MRI. Results are in a good agreement with those obtained using commercial codes and require much less computational time. An integration of the developed code with neuronavigation tools will permit real-time evaluation of the stimulated brain regions during the TMS delivery, thus improving the efficacy of clinical applications.

  3. Combined electrochemical, heat generation, and thermal model for large prismatic lithium-ion batteries in real-time applications

    Science.gov (United States)

    Farag, Mohammed; Sweity, Haitham; Fleckenstein, Matthias; Habibi, Saeid

    2017-08-01

    Real-time prediction of the battery's core temperature and terminal voltage is very crucial for an accurate battery management system. In this paper, a combined electrochemical, heat generation, and thermal model is developed for large prismatic cells. The proposed model consists of three sub-models, an electrochemical model, heat generation model, and thermal model which are coupled together in an iterative fashion through physicochemical temperature dependent parameters. The proposed parameterization cycles identify the sub-models' parameters separately by exciting the battery under isothermal and non-isothermal operating conditions. The proposed combined model structure shows accurate terminal voltage and core temperature prediction at various operating conditions while maintaining a simple mathematical structure, making it ideal for real-time BMS applications. Finally, the model is validated against both isothermal and non-isothermal drive cycles, covering a broad range of C-rates, and temperature ranges [-25 °C to 45 °C].

  4. Modelling, Simulation, Animation, and Real-Time Control (Mosart) for a Class of Electromechanical Systems: A System-Theoretic Approach

    Science.gov (United States)

    Rodriguez, Armando A.; Metzger, Richard P.; Cifdaloz, Oguzhan; Dhirasakdanon, Thanate; Welfert, Bruno

    2004-01-01

    This paper describes an interactive modelling, simulation, animation, and real-time control (MoSART) environment for a class of 'cart-pendulum' electromechanical systems that may be used to enhance learning within differential equations and linear algebra classes. The environment is useful for conveying fundamental mathematical/systems concepts…

  5. Forecast generation for real-time control of urban drainage systems using greybox modelling and radar rainfall

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2012-01-01

    We present stochastic flow forecasts to be used in a real-time control setup for urban drainage systems. The forecasts are generated using greybox models with rain gauge and radar rainfall observations as input. Predictions are evaluated as intervals rather than just mean values. We obtain...

  6. Advances in real-time technology assessment and emergency response: Close-in atmospheric dispersion modeling and exposure estimation

    International Nuclear Information System (INIS)

    Sims, J.; Lee, R.; McCallen, R.; Lawver, B.; Clark, J.; Rueppel, D.; Sullivan, T.

    1992-07-01

    We have developed a stand-alone, real-time emergency response system to assess and predict the offsite dispersion of particulate releases. We have also developed advanced modeling tools that win expand the capability of the emergency response system to predict nearfield dispersion over complex terrain and around buildings

  7. Combining driveline and suspension models for real-time simulations / Kombination von Antriebs- und Fahrwerksmodellen zur Echtzeit-Simulation

    NARCIS (Netherlands)

    Vis, M.A.; Venne, J.W.C.M. van de; Vink, W.J.; Steen, M. van der; Lupker, H.A.

    2000-01-01

    A Modular Vehicle (MoVe) library is presented, containing driveline and vehicle dynamics component models. The library is built in Matlab\\Simulink, taking advantage of its modular capabilities and real-time application possibilities. Its use is demonstrated with the construction of a 4-wheel car,

  8. REAL-TIME MEASUREMENT OF AIRWAY RESPONSES TO SULOFUR DIOXIDE (SO2) IN AN INTACT, AWAKE GUINEA PIG MODEL

    Science.gov (United States)

    Real-time measurment of airway responses to Sulfur Dioxide (SO2) in an intact, awake guinea pig model. J Stanek1,2, Q Krantz2, J Nolan2, D Winsett2, W Watkinson2, and D Costa2. 1College of Veterinary Medicine, NCSU, Raleigh, NC, USA; 2Pulmonary Toxicology Branch, ETD, NHEERL, US...

  9. Atmospheric dispersion models for real-time application in the decision support system being developed within the CEC

    International Nuclear Information System (INIS)

    Mikkelsen, T.

    1992-01-01

    A number of Commission of the European Communities member states are presently coordinating their research and development of a ''Real-time On-line DecisiOn Support'' (RODOS) for emergency assistance in the event of nuclear accident. In addition to atmospheric dispersion, the system involves multiple other radiological disciplines. The ability to estimate a specific atmospheric dispersion scenarios in real-time becomes a first-priority task and is of uttermost importance for the subsequent success or failure of such a comprehensive decision support system to guide off-site emergency situations. No single dispersion model is at present able to cover all possible release-types and scales of dispersion. A hierarchy of atmospheric flow and dispersion models is presently being ranked for suitability to real-time calculate air and integrated-air concentrations. Starting at the short-range scale, models are discriminated with respect to principle, adequacy and flexibility, CPU-time constraints, experimental evaluation record, instantaneous or short-time release handling, deposition measures (wet and dry), input and output data flexibility and uncertainty-handling and model-interpretation. Additional features of particular importance are: Robustness in schemes for meteorological preprocessing of meteorological input data, and on-line backfitting and data-assimilation procedures. Models demonstrating practical and operational use, including real-time operational experience, have in this context the highest priority, as opposed to the more sophisticated and theoretical ''development-type'' models. Real-time methods founded on our present knowledge and data concerning flow and dispersion in the atmospheric boundary layer, are of primary interest. (au) (18 refs.)

  10. Exploring inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video

    Science.gov (United States)

    Li, Jia; Tian, Yonghong; Gao, Wen

    2008-01-01

    In recent years, the amount of streaming video has grown rapidly on the Web. Often, retrieving these streaming videos offers the challenge of indexing and analyzing the media in real time because the streams must be treated as effectively infinite in length, thus precluding offline processing. Generally speaking, captions are important semantic clues for video indexing and retrieval. However, existing caption detection methods often have difficulties to make real-time detection for streaming video, and few of them concern on the differentiation of captions from scene texts and scrolling texts. In general, these texts have different roles in streaming video retrieval. To overcome these difficulties, this paper proposes a novel approach which explores the inter-frame correlation analysis and wavelet-domain modeling for real-time caption detection in streaming video. In our approach, the inter-frame correlation information is used to distinguish caption texts from scene texts and scrolling texts. Moreover, wavelet-domain Generalized Gaussian Models (GGMs) are utilized to automatically remove non-text regions from each frame and only keep caption regions for further processing. Experiment results show that our approach is able to offer real-time caption detection with high recall and low false alarm rate, and also can effectively discern caption texts from the other texts even in low resolutions.

  11. Draft Forecasts from Real-Time Runs of Physics-Based Models - A Road to the Future

    Science.gov (United States)

    Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

    2008-01-01

    The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. After consultations with NOAA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

  12. Dynamic average modeling of a bidirectional solid state transformer for feasibility studies and real-time implementation

    OpenAIRE

    Martínez Velasco, Juan Antonio; Alepuz Menéndez, Salvador; Gonzalez Molina, Francisco; Martín Arnedo, Jacinto

    2014-01-01

    Detailed switching models of power electronics devices often lead to long computing times, limiting the size of the system to be simulated. This drawback is especially important when the goal is to implement the model in a real-time simulation platform. An alternative is to use dynamic average models (DAM) for analyzing the dynamic behavior of power electronic devices. This paper presents the development of a DAM for a bidirectional solid-state transformer and its implementation in a real-tim...

  13. Accounting for large deformations in real-time simulations of soft tissues based on reduced-order models.

    Science.gov (United States)

    Niroomandi, S; Alfaro, I; Cueto, E; Chinesta, F

    2012-01-01

    Model reduction techniques have shown to constitute a valuable tool for real-time simulation in surgical environments and other fields. However, some limitations, imposed by real-time constraints, have not yet been overcome. One of such limitations is the severe limitation in time (established in 500Hz of frequency for the resolution) that precludes the employ of Newton-like schemes for solving non-linear models as the ones usually employed for modeling biological tissues. In this work we present a technique able to deal with geometrically non-linear models, based on the employ of model reduction techniques, together with an efficient non-linear solver. Examples of the performance of the technique over some examples will be given. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  14. Real-time dynamic hydraulic model for water distribution networks: steady state modelling

    CSIR Research Space (South Africa)

    Osman, Mohammad S

    2016-09-01

    Full Text Available equipment (pipes, reservoirs, pumps, valves, etc.) was used as a pilot WDN. Further information of the various other DHM components has been published [1]. The steady-state hydraulic model calculates the network hydraulic variables at a particular... from the abstraction point to the two low-level concrete reservoirs. On this pipeline there is a 2” tie-off to an alternate consumer as well as another 2” tie-off (5 m length) to the pump station sump. Water from the pump station is pumped to two...

  15. The European tracer experiment ETEX: a real-time long range atmospheric dispersion model exercise in different weather conditions

    International Nuclear Information System (INIS)

    Graziani, G.; )

    1998-01-01

    Two long-range tracer experiments were conducted. An inert, non-depositing tracer was being released at Rennes in France for 12 hours. The 168 sampling ground stations were run by the National Meteorological Services. Twenty-four institutions took part in the real-time forecasting of the cloud evolution using 28 long-range dispersion models. The horizontal projection of the cloud evolution over Europe was combined with real-time aerial chemical analysis. The results of the comparison indicate that a limited group of models (7-8) were capable of obtaining a good reproduction of the cloud movement throughout Europe for the first release. Large differences were, however, found in the predicted tracer concentration at a particular location. For the second release, there were large differences between the measured and calculated cloud, particularly after a front passage, which indicates that some efforts have still to be spent before consensus on the model reliability is achieved. (P.A.)

  16. 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

  17. Cloud Computing: A model Construct of Real-Time Monitoring for Big Dataset Analytics Using Apache Spark

    Science.gov (United States)

    Alkasem, Ameen; Liu, Hongwei; Zuo, Decheng; Algarash, Basheer

    2018-01-01

    The volume of data being collected, analyzed, and stored has exploded in recent years, in particular in relation to the activity on the cloud computing. While large-scale data processing, analysis, storage, and platform model such as cloud computing were previously and currently are increasingly. Today, the major challenge is it address how to monitor and control these massive amounts of data and perform analysis in real-time at scale. The traditional methods and model systems are unable to cope with these quantities of data in real-time. Here we present a new methodology for constructing a model for optimizing the performance of real-time monitoring of big datasets, which includes a machine learning algorithms and Apache Spark Streaming to accomplish fine-grained fault diagnosis and repair of big dataset. As a case study, we use the failure of Virtual Machines (VMs) to start-up. The methodology proposition ensures that the most sensible action is carried out during the procedure of fine-grained monitoring and generates the highest efficacy and cost-saving fault repair through three construction control steps: (I) data collection; (II) analysis engine and (III) decision engine. We found that running this novel methodology can save a considerate amount of time compared to the Hadoop model, without sacrificing the classification accuracy or optimization of performance. The accuracy of the proposed method (92.13%) is an improvement on traditional approaches.

  18. Assessment of surface solar irradiance derived from real-time modelling techniques and verification with ground-based measurements

    Science.gov (United States)

    Kosmopoulos, Panagiotis G.; Kazadzis, Stelios; Taylor, Michael; Raptis, Panagiotis I.; Keramitsoglou, Iphigenia; Kiranoudis, Chris; Bais, Alkiviadis F.

    2018-02-01

    This study focuses on the assessment of surface solar radiation (SSR) based on operational neural network (NN) and multi-regression function (MRF) modelling techniques that produce instantaneous (in less than 1 min) outputs. Using real-time cloud and aerosol optical properties inputs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation (MSG) satellite and the Copernicus Atmosphere Monitoring Service (CAMS), respectively, these models are capable of calculating SSR in high resolution (1 nm, 0.05°, 15 min) that can be used for spectrally integrated irradiance maps, databases and various applications related to energy exploitation. The real-time models are validated against ground-based measurements of the Baseline Surface Radiation Network (BSRN) in a temporal range varying from 15 min to monthly means, while a sensitivity analysis of the cloud and aerosol effects on SSR is performed to ensure reliability under different sky and climatological conditions. The simulated outputs, compared to their common training dataset created by the radiative transfer model (RTM) libRadtran, showed median error values in the range -15 to 15 % for the NN that produces spectral irradiances (NNS), 5-6 % underestimation for the integrated NN and close to zero errors for the MRF technique. The verification against BSRN revealed that the real-time calculation uncertainty ranges from -100 to 40 and -20 to 20 W m-2, for the 15 min and monthly mean global horizontal irradiance (GHI) averages, respectively, while the accuracy of the input parameters, in terms of aerosol and cloud optical thickness (AOD and COT), and their impact on GHI, was of the order of 10 % as compared to the ground-based measurements. The proposed system aims to be utilized through studies and real-time applications which are related to solar energy production planning and use.

  19. The utilization of real time models as a decision aid following a large release of radionuclides into the atmosphere

    International Nuclear Information System (INIS)

    1994-02-01

    In 1986, following the Chernobyl accident, the International Nuclear Safety Advisory Group (INSAG) recommended, in Safety Series No. 75-INSAG-1, inter alia (recommendation B.2(10)), that ''the IAEA should develop technical guidance on the use of real-time models able to accept actual meteorological and radiological monitoring system data in predicting the radiological consequences of a nuclear accident for persons and the environment and in determining what protective measures are necessary''. 24 refs, 21 figs, 2 tabs

  20. Bayesian Algorithm Implementation in a Real Time Exposure Assessment Model on Benzene with Calculation of Associated Cancer Risks

    OpenAIRE

    Sarigiannis, Dimosthenis A.; Karakitsios, Spyros P.; Gotti, Alberto; Papaloukas, Costas L.; Kassomenos, Pavlos A.; Pilidis, Georgios A.

    2009-01-01

    The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based...

  1. Development of a cross-section methodology and a real-time core model for VVER-1000 simulator application

    Energy Technology Data Exchange (ETDEWEB)

    Georgieva, Emiliya Lyudmilova

    2016-06-06

    The novel academic contributions are summarized as follows. A) A cross-section modelling methodology and a cycle-specific cross-section update procedure are developed to meet fidelity requirements applicable to a cycle-specific reactor core simulation, as well as particular customer needs and practices supporting VVER-1000 operation and safety. B) A real-time version of the Nodal Expansion Method code is developed and implemented into Kozloduy 6 full-scope replica control room simulator.

  2. Development of fast scattering model of complex shape target for seminatural tests of onboard proximity radars in real time mode

    Directory of Open Access Journals (Sweden)

    Likhoedenko Andrei K.

    2016-01-01

    Full Text Available Problems of creation of models of real time of complex shape targets on the basis of use of their polygonal models are considered. Formulas for radar cross section of multipoint model of target and power of input signal of onboard radar are described. Technique of semi-natural tests of onboard radar detector on the base of multipoint model of target is proposed. Results of digital simulation of input signals of the onboard radar detector of the target from the aerodynamic target on the basis of their multipoint models are given.

  3. Real-time interferometric monitoring and measuring of photopolymerization based stereolithographic additive manufacturing process: sensor model and algorithm

    International Nuclear Information System (INIS)

    Zhao, X; Rosen, D W

    2017-01-01

    As additive manufacturing is poised for growth and innovations, it faces barriers of lack of in-process metrology and control to advance into wider industry applications. The exposure controlled projection lithography (ECPL) is a layerless mask-projection stereolithographic additive manufacturing process, in which parts are fabricated from photopolymers on a stationary transparent substrate. To improve the process accuracy with closed-loop control for ECPL, this paper develops an interferometric curing monitoring and measuring (ICM and M) method which addresses the sensor modeling and algorithms issues. A physical sensor model for ICM and M is derived based on interference optics utilizing the concept of instantaneous frequency. The associated calibration procedure is outlined for ICM and M measurement accuracy. To solve the sensor model, particularly in real time, an online evolutionary parameter estimation algorithm is developed adopting moving horizon exponentially weighted Fourier curve fitting and numerical integration. As a preliminary validation, simulated real-time measurement by offline analysis of a video of interferograms acquired in the ECPL process is presented. The agreement between the cured height estimated by ICM and M and that measured by microscope indicates that the measurement principle is promising as real-time metrology for global measurement and control of the ECPL process. (paper)

  4. Towards real-time communication between in vivo neurophysiological data sources and simulator-based brain biomimetic models.

    Science.gov (United States)

    Lee, Giljae; Matsunaga, Andréa; Dura-Bernal, Salvador; Zhang, Wenjie; Lytton, William W; Francis, Joseph T; Fortes, José Ab

    2014-11-01

    Development of more sophisticated implantable brain-machine interface (BMI) will require both interpretation of the neurophysiological data being measured and subsequent determination of signals to be delivered back to the brain. Computational models are the heart of the machine of BMI and therefore an essential tool in both of these processes. One approach is to utilize brain biomimetic models (BMMs) to develop and instantiate these algorithms. These then must be connected as hybrid systems in order to interface the BMM with in vivo data acquisition devices and prosthetic devices. The combined system then provides a test bed for neuroprosthetic rehabilitative solutions and medical devices for the repair and enhancement of damaged brain. We propose here a computer network-based design for this purpose, detailing its internal modules and data flows. We describe a prototype implementation of the design, enabling interaction between the Plexon Multichannel Acquisition Processor (MAP) server, a commercial tool to collect signals from microelectrodes implanted in a live subject and a BMM, a NEURON-based model of sensorimotor cortex capable of controlling a virtual arm. The prototype implementation supports an online mode for real-time simulations, as well as an offline mode for data analysis and simulations without real-time constraints, and provides binning operations to discretize continuous input to the BMM and filtering operations for dealing with noise. Evaluation demonstrated that the implementation successfully delivered monkey spiking activity to the BMM through LAN environments, respecting real-time constraints.

  5. Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

    Science.gov (United States)

    Fontaine, Reid Griffith; Dodge, Kenneth A

    2006-11-01

    Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

  6. Interactive Mapping on Virtual Terrain Models Using RIMS (Real-time, Interactive Mapping System)

    Science.gov (United States)

    Bernardin, T.; Cowgill, E.; Gold, R. D.; Hamann, B.; Kreylos, O.; Schmitt, A.

    2006-12-01

    Recent and ongoing space missions are yielding new multispectral data for the surfaces of Earth and other planets at unprecedented rates and spatial resolution. With their high spatial resolution and widespread coverage, these data have opened new frontiers in observational Earth and planetary science. But they have also precipitated an acute need for new analytical techniques. To address this problem, we have developed RIMS, a Real-time, Interactive Mapping System that allows scientists to visualize, interact with, and map directly on, three-dimensional (3D) displays of georeferenced texture data, such as multispectral satellite imagery, that is draped over a surface representation derived from digital elevation data. The system uses a quadtree-based multiresolution method to render in real time high-resolution (3 to 10 m/pixel) data over large (800 km by 800 km) spatial areas. It allows users to map inside this interactive environment by generating georeferenced and attributed vector-based elements that are draped over the topography. We explain the technique using 15 m ASTER stereo-data from Iraq, P.R. China, and other remote locations because our particular motivation is to develop a technique that permits the detailed (10 m to 1000 m) neotectonic mapping over large (100 km to 1000 km long) active fault systems that is needed to better understand active continental deformation on Earth. RIMS also includes a virtual geologic compass that allows users to fit a plane to geologic surfaces and thereby measure their orientations. It also includes tools that allow 3D surface reconstruction of deformed and partially eroded surfaces such as folded bedding planes. These georeferenced map and measurement data can be exported to, or imported from, a standard GIS (geographic information systems) file format. Our interactive, 3D visualization and analysis system is designed for those who study planetary surfaces, including neotectonic geologists, geomorphologists, marine

  7. Modeling and control for a magnetic levitation system based on SIMLAB platform in real time

    Directory of Open Access Journals (Sweden)

    Mundher H.A. Yaseen

    2018-03-01

    Full Text Available Magnetic Levitation system becomes a hot topic of study due to the minimum friction and low energy consumption which regards as very important issues. This paper proposed a new magnetic levitation system using real-time control simulink feature of (SIMLAB microcontroller. The control system of the maglev transportation system is verified by simulations with experimental results, and its superiority is indicated in comparison with previous literature and conventional control strategies. In addition, the proposed system was implemented under effect of three controller types which are Linear–quadratic regulator (LQR, proportional–integral–derivative controller (PID and Lead compensation. As well, the controller system performance was compared in term of three parameters Peak overshoot, Settling time and Rise time. The findings prove the agreement of simulation with experimental results obtained. Moreover, the LQR controller produced a great stability and homogeneous response than other controllers used. For experimental results, the LQR brought a 14.6%, 0.199 and 0.064 for peak overshoot, Setting time and Rise time respectively. Keywords: Magnetic levitation system, Linear Quadratic Regulator (LQR, PID control, Lead compensation

  8. Simultaneous real-time control of the current and pressure profiles in JET: experiments and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Mazon, D.; Laborde, L.; Litaudon, X.; Moreau, D.; Zabeo, L.; Joffrin, E. [Association Euratom-CEA Cadarache (DSM/DRFC), 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee; Murari, A. [Consorzio RFX Association Euratom-ENEA, Padova (Italy); Ariola, M.; Albanese, R.; Tommasi, G. de; Pironti, A. [Association Euratom-ENEA, CREATE, Napoly (Italy); Moreau, D. [EFDA-JET CSU, Culham Science Centre, Abingdon, OX (United Kingdom); Tala, T. [Euratom-Tekes Association, VTT Processes (Finland); Crisanti, F.; Pericoli-Ridolfini, V.; Tuccillo, A. [Association Euratom-ENEA, C.R. Frascati (Italy); Baar, M. de; Vries, P. de [Euratom-FOM Association, TEC Cluster, Nieuwegein (Netherlands); De la Luna, E. [Euratom-Ciemat Association (Spain); Felton, R.; Corrigan, G. [Euratom-UKAEA Association, Culham Science Centre, Abingdon (United Kingdom)

    2004-07-01

    Real-time control of the plasma profiles (current density, pressure and flow) is one of the major issues for sustaining internal transport barriers (ITB) in a high performance plasma, with a large bootstrap current fraction. We have recently investigated the experimental and numerical aspects of the simultaneous control of the current and pressure profiles in JET ITB discharges. The current density and the electron temperature were successfully controlled via the safety factor profile (or via its inverse the tau-profile) and the {rho}{sup *}{sub Te} profile respectively. The results of these new studies are presented. With only a limited number of actuators, the technique aims at minimizing an integral square error signal which combines the 2 profiles, rather than attempting to control plasma parameters at some given radii with great precision. The resulting fuzziness of the control scheme allows the plasma to relax towards a physically accessible non-linear state which may not be accurately known in advance, but is close enough to the requested one to provide the required plasma performance. Closed loop experiments have allow to reach different target q and {rho}{sup *}{sub Te} profiles, and to some degree, to displace the region of maximum electron temperature gradient. The control has also shown some robustness in front of rapid transients.

  9. Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

    Science.gov (United States)

    Chou, Chien-Ming; Wang, Ru-Yih

    2004-04-01

    This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

  10. Real-Time Simulation Technique of a Microgrid Model for DER Penetration

    Directory of Open Access Journals (Sweden)

    Konstantina Mentesidi

    2014-12-01

    Full Text Available Comprehensive analysis of Distributed Energy Resources (DER integration requires tools that provide computational power and flexibility. In this context, throughout this paper PHIL simulations are performed to emulate the energy management system of a real microgrid including a diesel synchronous machine and inverter-based sources. Moreover, conventional frequency and voltage droops were incorporated into the respective inverters. The results were verified at the real microgrid installation in the Centre for Renewable Energy Sources (CRES premises. This research work is divided into two steps: A Real time in RSCAD/RTDS and Power Hardware-in-the-Loop (PHIL simulations where the diesel generator´s active power droop control is evaluated, the battery inverter´s droop curves are simulated and the load sharing for parallel operation of the system´s generation units is examined. B microgrid experiments during which various tests were executed concerning the diesel generator and the battery inverters in order to examine their dynamic operation within the LV islanded power system.

  11. Modeling and control for a magnetic levitation system based on SIMLAB platform in real time

    Science.gov (United States)

    Yaseen, Mundher H. A.; Abd, Haider J.

    2018-03-01

    Magnetic Levitation system becomes a hot topic of study due to the minimum friction and low energy consumption which regards as very important issues. This paper proposed a new magnetic levitation system using real-time control simulink feature of (SIMLAB) microcontroller. The control system of the maglev transportation system is verified by simulations with experimental results, and its superiority is indicated in comparison with previous literature and conventional control strategies. In addition, the proposed system was implemented under effect of three controller types which are Linear-quadratic regulator (LQR), proportional-integral-derivative controller (PID) and Lead compensation. As well, the controller system performance was compared in term of three parameters Peak overshoot, Settling time and Rise time. The findings prove the agreement of simulation with experimental results obtained. Moreover, the LQR controller produced a great stability and homogeneous response than other controllers used. For experimental results, the LQR brought a 14.6%, 0.199 and 0.064 for peak overshoot, Setting time and Rise time respectively.

  12. A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

    Science.gov (United States)

    Tonutti, Michele; Gras, Gauthier; Yang, Guang-Zhong

    2017-07-01

    Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augmented reality (AR) applications. Current deformation models are characterised by a trade-off between accuracy and computational speed. We propose an approach to derive a patient-specific deformation model for brain pathologies by combining the results of pre-computed finite element method (FEM) simulations with machine learning algorithms. The models can be computed instantaneously and offer an accuracy comparable to FEM models. A brain tumour is used as the subject of the deformation model. Load-driven FEM simulations are performed on a tetrahedral brain mesh afflicted by a tumour. Forces of varying magnitudes, positions, and inclination angles are applied onto the brain's surface. Two machine learning algorithms-artificial neural networks (ANNs) and support vector regression (SVR)-are employed to derive a model that can predict the resulting deformation for each node in the tumour's mesh. The tumour deformation can be predicted in real time given relevant information about the geometry of the anatomy and the load, all of which can be measured instantly during a surgical operation. The models can predict the position of the nodes with errors below 0.3mm, beyond the general threshold of surgical accuracy and suitable for high fidelity AR systems. The SVR models perform better than the ANN's, with positional errors for SVR models reaching under 0.2mm. The results represent an improvement over existing deformation models for real time applications, providing smaller errors and high patient-specificity. The proposed approach addresses the current needs of image-guided surgical systems and has the potential to be employed to model the deformation of any type of soft tissue. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Agent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market

    Directory of Open Access Journals (Sweden)

    Sh. Yousefi

    2011-09-01

    Full Text Available In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offered real time prices, an hourly acceptance function is proposed in order to represent the hourly changes in the customer’s effective demand according to the prices. Here, Q-learning (QL approach is applied in day-ahead real time pricing for the customers enabling the REP agent to discover which price yields the most benefit through a trial-and-error search. Numerical studies are presented based on New England day-ahead market data which include comparing the results of RTP based on QL approach with that of genetic-based pricing.

  14. Real-time prediction of extreme ambient carbon monoxide concentrations due to vehicular exhaust emissions using univariate linear stochastic models

    International Nuclear Information System (INIS)

    Sharma, P.; Khare, M.

    2000-01-01

    Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box-Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India. (author)

  15. A Real-Time Recording Model of Key Indicators for Energy Consumption and Carbon Emissions of Sustainable Buildings

    Directory of Open Access Journals (Sweden)

    Weiwei Wu

    2014-05-01

    Full Text Available Buildings’ sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability.

  16. Modeling and real time simulation of an HVDC inverter feeding a weak AC system based on commutation failure study.

    Science.gov (United States)

    Mankour, Mohamed; Khiat, Mounir; Ghomri, Leila; Chaker, Abdelkader; Bessalah, Mourad

    2018-06-01

    This paper presents modeling and study of 12-pulse HVDC (High Voltage Direct Current) based on real time simulation where the HVDC inverter is connected to a weak AC system. In goal to study the dynamic performance of the HVDC link, two serious kind of disturbance are applied at HVDC converters where the first one is the single phase to ground AC fault and the second one is the DC link to ground fault. The study is based on two different mode of analysis, which the first is to test the performance of the DC control and the second is focalized to study the effect of the protection function on the system behavior. This real time simulation considers the strength of the AC system to witch is connected and his relativity with the capacity of the DC link. The results obtained are validated by means of RT-lab platform using digital Real time simulator Hypersim (OP-5600), the results carried out show the effect of the DC control and the influence of the protection function to reduce the probability of commutation failures and also for helping inverter to take out from commutation failure even while the DC control fails to eliminate them. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  17. A Real-Time Recording Model of Key Indicators for Energy Consumption and Carbon Emissions of Sustainable Buildings

    Science.gov (United States)

    Wu, Weiwei; Yang, Huanjia; Chew, David; Hou, Yanhong; Li, Qiming

    2014-01-01

    Buildings' sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID)-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability. PMID:24831109

  18. Benchmarking flood models from space in near real-time: accommodating SRTM height measurement errors with low resolution flood imagery

    Science.gov (United States)

    Schumann, G.; di Baldassarre, G.; Alsdorf, D.; Bates, P. D.

    2009-04-01

    In February 2000, the Shuttle Radar Topography Mission (SRTM) measured the elevation of most of the Earth's surface with spatially continuous sampling and an absolute vertical accuracy greater than 9 m. The vertical error has been shown to change with topographic complexity, being less important over flat terrain. This allows water surface slopes to be measured and associated discharge volumes to be estimated for open channels in large basins, such as the Amazon. Building on these capabilities, this paper demonstrates that near real-time coarse resolution radar imagery of a recent flood event on a 98 km reach of the River Po (Northern Italy) combined with SRTM terrain height data leads to a water slope remarkably similar to that derived by combining the radar image with highly accurate airborne laser altimetry. Moreover, it is shown that this space-borne flood wave approximation compares well to a hydraulic model and thus allows the performance of the latter, calibrated on a previous event, to be assessed when applied to an event of different magnitude in near real-time. These results are not only of great importance to real-time flood management and flood forecasting but also support the upcoming Surface Water and Ocean Topography (SWOT) mission that will routinely provide water levels and slopes with higher precision around the globe.

  19. Processor core for real time background identification of HD video based on OpenCV Gaussian mixture model algorithm

    Science.gov (United States)

    Genovese, Mariangela; Napoli, Ettore

    2013-05-01

    The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  1. A fast surrogate model tailor-made for real time control

    DEFF Research Database (Denmark)

    Borup, Morten; Thrysøe, Cecilie; Arnbjerg-Nielsen, Karsten

    A surrogate model of a detailed hydraulic urban drainage model is created for supplying inflow forecasts to an MPC model for 31 separate locations. The original model is subdivided into 66 relationships extracted from the original model. The surrogate model is 9000 times faster than the original...... model, with just a minor deviation from the original model results....

  2. Real Time Text Analysis

    Science.gov (United States)

    Senthilkumar, K.; Ruchika Mehra Vijayan, E.

    2017-11-01

    This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language

  3. Modeling of RFID-Enabled Real-Time Manufacturing Execution System in Mixed-Model Assembly Lines

    Directory of Open Access Journals (Sweden)

    Zhixin Yang

    2015-01-01

    Full Text Available To quickly respond to the diverse product demands, mixed-model assembly lines are well adopted in discrete manufacturing industries. Besides the complexity in material distribution, mixed-model assembly involves a variety of components, different process plans and fast production changes, which greatly increase the difficulty for agile production management. Aiming at breaking through the bottlenecks in existing production management, a novel RFID-enabled manufacturing execution system (MES, which is featured with real-time and wireless information interaction capability, is proposed to identify various manufacturing objects including WIPs, tools, and operators, etc., and to trace their movements throughout the production processes. However, being subject to the constraints in terms of safety stock, machine assignment, setup, and scheduling requirements, the optimization of RFID-enabled MES model for production planning and scheduling issues is a NP-hard problem. A new heuristical generalized Lagrangian decomposition approach has been proposed for model optimization, which decomposes the model into three subproblems: computation of optimal configuration of RFID senor networks, optimization of production planning subjected to machine setup cost and safety stock constraints, and optimization of scheduling for minimized overtime. RFID signal processing methods that could solve unreliable, redundant, and missing tag events are also described in detail. The model validity is discussed through algorithm analysis and verified through numerical simulation. The proposed design scheme has important reference value for the applications of RFID in multiple manufacturing fields, and also lays a vital research foundation to leverage digital and networked manufacturing system towards intelligence.

  4. Hydrological real-time modelling in the Zambezi river basin using satellite-based soil moisture and rainfall data

    Directory of Open Access Journals (Sweden)

    P. Meier

    2011-03-01

    Full Text Available Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. For the management of ecological releases even discharge forecasts with moderate accuracy can be beneficial. Sequential data assimilation using the Ensemble Kalman Filter provides a tool that is both efficient and robust for a real-time modelling framework. One key parameter in a hydrological system is the soil moisture, which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by a radar scatterometer. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modelling framework yields good results in watersheds where soil storage is an important factor. The lead time of the forecast is dependent on the size and the retention capacity of the watershed. For the largest watershed a forecast over 40 days can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In a watershed with little soil storage and a quick response to rainfall events, the performance is relatively poor and the lead time is as short as 10 days only.

  5. The stomatogastric nervous system as a model for studying sensorimotor interactions in real-time closed-loop conditions

    Directory of Open Access Journals (Sweden)

    Nelly eDaur

    2012-03-01

    Full Text Available The perception of proprioceptive signals that report the internal state of the body is one of the essential tasks of the nervous system and helps to continuously adapt body movements to changing circumstances. Despite the impact of proprioceptive feedback on motor activity it has rarely been studied in conditions in which motor output and sensory activity interact as they do in behaving animals, i.e. in closed-loop conditions. The interaction of motor and sensory activities, however, can create emergent properties that may govern the functional characteristics of the system. We here demonstrate the use of a well-characterized model system for central pattern generation, the stomatogastric nervous system, for studying these properties in vitro. We created a real-time computer model of a single-cell muscle tendon organ in the gastric mill of the crab foregut that uses intracellular current injections to control the activity of the biological proprioceptor. The resulting motor output of a gastric mill motor neuron is then recorded intracellularly and fed into a simple muscle model consisting of a series of low-pass filters. The muscle output is used to activate a one-dimensional Hodgkin-Huxley type model of the muscle tendon organ in real-time, allowing closed-loop conditions. Model properties were either hand-tuned to achieve the best match with data from semi-intact muscle preparations, or an exhaustive search was performed to determine the best set of parameters. We report the real-time capabilities of our models, its performance and its interaction with the biological motor system.

  6. USE OF AN AUTOMATON MODEL FOR THE DESIGNING OF REAL-TIME INFORMATION SYSTEMS IN THE RAILWAY STATIONS

    Directory of Open Access Journals (Sweden)

    Igor ZHUKOVYTS’KYY

    2017-12-01

    Full Text Available The author proposes to develop special models that are built based on finite-state machine, Mealy, in order to display information about technological processes at railway stations. The input alphabet of such machines is represented by the real signals (from the floor equipment, the related information systems and the dispatch office personnel. This representation allows one to formalize the software design process of real-time information management systems for these technological processes. The article demonstrates the possibility of formal transition from the automaton model to the software algorithms. The proposed approach was tested when designing the information system for Nizhnedneprovsk junction railway yard.

  7. A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation

    Directory of Open Access Journals (Sweden)

    Jianzhong Zhou

    2017-12-01

    Full Text Available Model simulation and control of pumped storage unit (PSU are essential to improve the dynamic quality of power station. Only under the premise of the PSU models reflecting the actual transient process, the novel control method can be properly applied in the engineering. The contributions of this paper are that (1 a real-time accurate equivalent circuit model (RAECM of PSU via error compensation is proposed to reconcile the conflict between real-time online simulation and accuracy under various operating conditions, and (2 an adaptive predicted fuzzy PID controller (APFPID based on RAECM is put forward to overcome the instability of conventional control under no-load conditions with low water head. Respectively, all hydraulic factors in pipeline system are fully considered based on equivalent lumped-circuits theorem. The pretreatment, which consists of improved Suter-transformation and BP neural network, and online simulation method featured by two iterative loops are synthetically proposed to improve the solving accuracy of the pump-turbine. Moreover, the modified formulas for compensating error are derived with variable-spatial discretization to improve the accuracy of the real-time simulation further. The implicit RadauIIA method is verified to be more suitable for PSUGS owing to wider stable domain. Then, APFPID controller is constructed based on the integration of fuzzy PID and the model predictive control. Rolling prediction by RAECM is proposed to replace rolling optimization with its computational speed guaranteed. Finally, the simulation and on-site measurements are compared to prove trustworthy of RAECM under various running conditions. Comparative experiments also indicate that APFPID controller outperforms other controllers in most cases, especially low water head conditions. Satisfying results of RAECM have been achieved in engineering and it provides a novel model reference for PSUGS.

  8. Bayesian Algorithm Implementation in a Real Time Exposure Assessment Model on Benzene with Calculation of Associated Cancer Risks

    Directory of Open Access Journals (Sweden)

    Pavlos A. Kassomenos

    2009-02-01

    Full Text Available The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural. Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations.

  9. Bayesian algorithm implementation in a real time exposure assessment model on benzene with calculation of associated cancer risks.

    Science.gov (United States)

    Sarigiannis, Dimosthenis A; Karakitsios, Spyros P; Gotti, Alberto; Papaloukas, Costas L; Kassomenos, Pavlos A; Pilidis, Georgios A

    2009-01-01

    The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural). Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations.

  10. The impact of real-time, Internet experiments versus interactive, asynchronous replays of experiments on high school students science concepts and attitudes

    Science.gov (United States)

    Kubasko, Dennis S., Jr.

    The purpose of this study was to investigate whether students' learning experiences were similar or different with an interactive, live connection via the Internet in real-time to an Atomic Force Microscope (AFM) versus a stored replay of AFM experiments. Did the two treatments influence students' attitudes towards the learning experience? Are there differences in students' understandings of viruses and science investigations? In addition, this study investigated treatment effects on students' understandings of the nature of science. The present study drew upon the research that examined students' attitudes toward science, students' views of the nature of science, instructional technology in education, and prior research on the nanoManipulator. Specific efforts have been made to address reform efforts in science education throughout the literature review. Eighty-five high school biology students participated in the nanoManipulator experience (44 males, 41 females, 64 Euro-American, 16 African-American, and 5 of other ethnicities). Two high school classes were randomly selected and administered the interactive, real-time treatment. Two different high school classes were randomly selected and administered the limited-interaction, experimental replay treatment. The intervention occurred over a one-week period. Qualitative and quantitative measures were used to examine the differences between two treatment conditions. Experiential, affective, cognitive, and the nature of science domains were assessed. Findings show that the questions and statements made in synchronous time by the live treatment group were significantly different than students' questions and statements in asynchronous communication. Students in the replay treatment made more statements about what they learned or knew about the experience than did students in the live experience. Students in both groups showed significant gains in understanding viruses (particularly viral dimensionality and shape

  11. Real Time Revisited

    Science.gov (United States)

    Allen, Phillip G.

    1985-12-01

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

  12. 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)

  13. 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%.

  14. Modelling and real-time simulation of continuous-discrete systems in mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Lindow, H. [Rostocker, Magdeburg (Germany)

    1996-12-31

    This work presents a methodology for simulation and modelling of systems with continuous - discrete dynamics. It derives hybrid discrete event models from Lagrange`s equations of motion. This method combines continuous mechanical, electrical and thermodynamical submodels on one hand with discrete event models an the other hand into a hybrid discrete event model. This straight forward software development avoids numeric overhead.

  15. Real-Time Measurements and Modelling on Dynamic Behaviour of SonoVue Bubbles Based on Light Scattering Technology

    International Nuclear Information System (INIS)

    Juan, Tu; Rongjue, Wei; Guan, J. F.; Matula, T. J.; Crum, L. A.

    2008-01-01

    The dynamic behaviour of SonoVue microbubbles, a new generation ultrasound contrast agent, is investigated in real time with light scattering method. Highly diluted SonoVue microbubbles are injected into a diluted gel made of xanthan gum and water. The responses of individual SonoVue bubbles to driven ultrasound pulses are measured. Both linear and nonlinear bubble oscillations are observed and the results suggest that SonoVue microbubbles can generate strong nonlinear responses. By fitting the experimental data of individual bubble responses with Sarkar's model, the shell coating parameter of the bubbles and dilatational viscosity is estimated to be 7.0 nm·s·Pa

  16. Study of the application of a near-real-time materials accountancy system for a model plutonium conversion plants

    International Nuclear Information System (INIS)

    Ihara, Hitoshi; Ikawa, Koji

    1986-11-01

    An assessment was done on the potential capability of a Near-Real-Time materials accountancy system for a model plutonium conversion plant. To this end, a computer simulation system, DYSAS-C, has been developed and evaluated through this assessment study. This study showed that N.R.T.A system could be used not only as a good operator's accounting system but also as a useful inspectorate's system to detect an abrupt diversion. It also showed, however, that more elaborated NRTA system which have not yet evaluated in this study should be considerered when we wish to improve of detecting protracted diversion. (author)

  17. A Real-Time Application of the ADCIRC-2DDI Hydrodynamic Model at Camp Pendleton, California

    National Research Council Canada - National Science Library

    Blain, Cheryl

    1998-01-01

    ...) off the coast of southern California 16-23 Jul 1997. A modeling strategy is designed for Camp Pendleton coastal waters and appropriate sensitivity analyses are conducted to assess initial model performance...

  18. Predictive modeling in Clostridium acetobutylicum fermentations employing Raman spectroscopy and multivariate data analysis for real-time culture monitoring

    Science.gov (United States)

    Zu, Theresah N. K.; Liu, Sanchao; Germane, Katherine L.; Servinsky, Matthew D.; Gerlach, Elliot S.; Mackie, David M.; Sund, Christian J.

    2016-05-01

    The coupling of optical fibers with Raman instrumentation has proven to be effective for real-time monitoring of chemical reactions and fermentations when combined with multivariate statistical data analysis. Raman spectroscopy is relatively fast, with little interference from the water peak present in fermentation media. Medical research has explored this technique for analysis of mammalian cultures for potential diagnosis of some cancers. Other organisms studied via this route include Escherichia coli, Saccharomyces cerevisiae, and some Bacillus sp., though very little work has been performed on Clostridium acetobutylicum cultures. C. acetobutylicum is a gram-positive anaerobic bacterium, which is highly sought after due to its ability to use a broad spectrum of substrates and produce useful byproducts through the well-known Acetone-Butanol-Ethanol (ABE) fermentation. In this work, real-time Raman data was acquired from C. acetobutylicum cultures grown on glucose. Samples were collected concurrently for comparative off-line product analysis. Partial-least squares (PLS) models were built both for agitated cultures and for static cultures from both datasets. Media components and metabolites monitored include glucose, butyric acid, acetic acid, and butanol. Models were cross-validated with independent datasets. Experiments with agitation were more favorable for modeling with goodness of fit (QY) values of 0.99 and goodness of prediction (Q2Y) values of 0.98. Static experiments did not model as well as agitated experiments. Raman results showed the static experiments were chaotic, especially during and shortly after manual sampling.

  19. Real time adjustment of slow changing flow components in distributed urban runoff models

    DEFF Research Database (Denmark)

    Borup, Morten; Grum, M.; Mikkelsen, Peter Steen

    2011-01-01

    In many urban runoff systems infiltrating water contributes with a substantial part of the total inflow and therefore most urban runoff modelling packages include hydrological models for simulating the infiltrating inflow. This paper presents a method for deterministic updating of the hydrological...... improvements for regular simulations as well as up to 10 hour forecasts. The updating method reduces the impact of non-representative precipitation estimates as well as model structural errors and leads to better overall modelling results....

  20. Reachability and Real-Time Actuation Strategies for the Active SLIP Model

    Science.gov (United States)

    2015-06-01

    time. In gen- eral, animals’ anatomy is far more complex than what the SLIP model captures, due to the presence of joints, ankles , knees, hips, leg...strategies for locomotion. These strategies can then be applied to an anchor , a more complex and realistic model to mimic the animal’s morphology and...model. As clearly explained in [1], the ideal SLIP model is a template that can then be ” anchored ” to systems with more complex dynamics. The prototype

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  2. 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

  3. Prototyping real-time systems

    OpenAIRE

    Clynch, Gary

    1994-01-01

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

  4. A computationally efficient electricity price forecasting model for real time energy markets

    International Nuclear Information System (INIS)

    Feijoo, Felipe; Silva, Walter; Das, Tapas K.

    2016-01-01

    Highlights: • A fast hybrid forecast model for electricity prices. • Accurate forecast model that combines K-means and machine learning techniques. • Low computational effort by elimination of feature selection techniques. • New benchmark results by using market data for year 2012 and 2015. - Abstract: Increased significance of demand response and proliferation of distributed energy resources will continue to demand faster and more accurate models for forecasting locational marginal prices. This paper presents such a model (named K-SVR). While yielding prediction accuracy comparable with the best known models in the literature, K-SVR requires a significantly reduced computational time. The computational reduction is attained by eliminating the use of a feature selection process, which is commonly used by the existing models in the literature. K-SVR is a hybrid model that combines clustering algorithms, support vector machine, and support vector regression. K-SVR is tested using Pennsylvania–New Jersey–Maryland market data from the periods 2005–6, 2011–12, and 2014–15. Market data from 2006 has been used to measure performance of many of the existing models. Authors chose these models to compare performance and demonstrate strengths of K-SVR. Results obtained from K-SVR using the market data from 2012 and 2015 are new, and will serve as benchmark for future models.

  5. Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware.

    Science.gov (United States)

    Rast, Alexander; Galluppi, Francesco; Davies, Sergio; Plana, Luis; Patterson, Cameron; Sharp, Thomas; Lester, David; Furber, Steve

    2011-11-01

    Dedicated hardware is becoming increasingly essential to simulate emerging very-large-scale neural models. Equally, however, it needs to be able to support multiple models of the neural dynamics, possibly operating simultaneously within the same system. This may be necessary either to simulate large models with heterogeneous neural types, or to simplify simulation and analysis of detailed, complex models in a large simulation by isolating the new model to a small subpopulation of a larger overall network. The SpiNNaker neuromimetic chip is a dedicated neural processor able to support such heterogeneous simulations. Implementing these models on-chip uses an integrated library-based tool chain incorporating the emerging PyNN interface that allows a modeller to input a high-level description and use an automated process to generate an on-chip simulation. Simulations using both LIF and Izhikevich models demonstrate the ability of the SpiNNaker system to generate and simulate heterogeneous networks on-chip, while illustrating, through the network-scale effects of wavefront synchronisation and burst gating, methods that can provide effective behavioural abstractions for large-scale hardware modelling. SpiNNaker's asynchronous virtual architecture permits greater scope for model exploration, with scalable levels of functional and temporal abstraction, than conventional (or neuromorphic) computing platforms. The complete system illustrates a potential path to understanding the neural model of computation, by building (and breaking) neural models at various scales, connecting the blocks, then comparing them against the biology: computational cognitive neuroscience. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. Real-time deformation of human soft tissues: A radial basis meshless 3D model based on Marquardt's algorithm.

    Science.gov (United States)

    Zhou, Jianyong; Luo, Zu; Li, Chunquan; Deng, Mi

    2018-01-01

    When the meshless method is used to establish the mathematical-mechanical model of human soft tissues, it is necessary to define the space occupied by human tissues as the problem domain and the boundary of the domain as the surface of those tissues. Nodes should be distributed in both the problem domain and on the boundaries. Under external force, the displacement of the node is computed by the meshless method to represent the deformation of biological soft tissues. However, computation by the meshless method consumes too much time, which will affect the simulation of real-time deformation of human tissues in virtual surgery. In this article, the Marquardt's Algorithm is proposed to fit the nodal displacement at the problem domain's boundary and obtain the relationship between surface deformation and force. When different external forces are applied, the deformation of soft tissues can be quickly obtained based on this relationship. The analysis and discussion show that the improved model equations with Marquardt's Algorithm not only can simulate the deformation in real-time but also preserve the authenticity of the deformation model's physical properties. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Performance of overlapped shield tunneling through an integrated physical model tests, numerical simulations and real-time field monitoring

    Directory of Open Access Journals (Sweden)

    Junlong Yang

    2017-03-01

    Full Text Available In this work, deformations and internal forces of an existing tunnel subjected to a closely overlapped shield tunneling are monitored and analyzed using a series of physical model experiments and numerical simulations. Effects of different excavation sequences and speeds are explicitly considered in the analysis. The results of the physical model experiments show that the bottom-up tunneling procedure is better than the top-down tunneling procedure. The incurred deformations and internal forces of the existing tunnel increase with the excavation speed and the range of influence areas also increase accordingly. For construction process control, real-time monitoring of the power tunnel is used. The monitoring processes feature full automation, adjustable frequency, real-time monitor and dynamic feedback, which are used to guide the construction to achieve micro-disturbance control. In accordance with the situation of crossing construction, a numerical study on the performance of power tunnel is carried out. Construction control measures are given for the undercrossing construction, which helps to accomplish the desired result and meet protection requirements of the existing tunnel structure. Finally, monitoring data and numerical results are compared, and the displacement and joint fracture change models in the power tunnel subject to the overlapped shield tunnel construction are analyzed. Keywords: Overlapped tunnel, Automatic monitoring, Micro-disturbance control

  8. Improving long-range dispersion predictions with ETEX real-time and a-posteriori model evaluations

    International Nuclear Information System (INIS)

    Desiato, F.

    1997-01-01

    The Italian environmental Protection Agency (ANPA), which is responsible for the evaluation of the consequences of accidental releases into the atmosphere, has participated to both the real-time (phase-1) and a-posteriori (phase-2) ETEX model evaluations. The double benchmark actually constituted an invaluable experience for better understanding the skill and limits of the present long-range dispersion modelling capabilities. In particular, the strong difference between phase-1 and phase-2 model performance emphasised the opportunity to modify, improve or tune a number of specific aspects of the overall simulation. ETEX model runs were carried out with the Lagrangian particle model APOLLO. The meteorological input was constituted by ECMWF fields. Three-hourly average concentrations paired in space and time and time-integrated concentrations were used in the evaluation of the results, based on a set of statistical indexes and concentration contour lines and scatter diagrams

  9. Model-based schedulability analysis of safety critical hard real-time Java programs

    DEFF Research Database (Denmark)

    Bøgholm, Thomas; Kragh-Hansen, Henrik; Olsen, Petur

    2008-01-01

    verifiable by the Uppaal model checker [23]. Schedulability analysis is reduced to a simple reachability question, checking for deadlock freedom. Model-based schedulability analysis has been developed by Amnell et al. [2], but has so far only been applied to high level specifications, not actual...

  10. Rule-based approach to cognitive modeling of real-time decision making

    International Nuclear Information System (INIS)

    Thorndyke, P.W.

    1982-01-01

    Recent developments in the fields of cognitive science and artificial intelligence have made possible the creation of a new class of models of complex human behavior. These models, referred to as either expert or knowledge-based systems, describe the high-level cognitive processing undertaken by a skilled human to perform a complex, largely mental, task. Expert systems have been developed to provide simulations of skilled performance of a variety of tasks. These include problems of data interpretation, system monitoring and fault isolation, prediction, planning, diagnosis, and design. In general, such systems strive to produce prescriptive (error-free) behavior, rather than model descriptively the typical human's errorful behavior. However, some research has sought to develop descriptive models of human behavior using the same theoretical frameworks adopted by expert systems builders. This paper presents an overview of this theoretical framework and modeling approach, and indicates the applicability of such models to the development of a model of control room operators in a nuclear power plant. Such a model could serve several beneficial functions in plant design, licensing, and operation

  11. Model reduction for dynamic real-time optimization of chemical processes

    NARCIS (Netherlands)

    Van den Berg, J.

    2005-01-01

    The value of models in process industries becomes apparent in practice and literature where numerous successful applications are reported. Process models are being used for optimal plant design, simulation studies, for off-line and online process optimization. For online optimization applications

  12. Universal Capacitance Model for Real-Time Biomass in Cell Culture

    Directory of Open Access Journals (Sweden)

    Viktor Konakovsky

    2015-09-01

    Full Text Available Capacitance probes have the potential to revolutionize bioprocess control due to their safe and robust use and ability to detect even the smallest capacitors in the form of biological cells. Several techniques have evolved to model biomass statistically, however, there are problems with model transfer between cell lines and process conditions. Errors of transferred models in the declining phase of the culture range for linear models around +100% or worse, causing unnecessary delays with test runs during bioprocess development. The goal of this work was to develop one single universal model which can be adapted by considering a potentially mechanistic factor to estimate biomass in yet untested clones and scales. The novelty of this work is a methodology to select sensitive frequencies to build a statistical model which can be shared among fermentations with an error between 9% and 38% (mean error around 20% for the whole process, including the declining phase. A simple linear factor was found to be responsible for the transferability of biomass models between cell lines, indicating a link to their phenotype or physiology.

  13. The sound of friction: Real-time models, playability and musical applications

    Science.gov (United States)

    Serafin, Stefania

    Friction, the tangential force between objects in contact, in most engineering applications needs to be removed as a source of noise and instabilities. In musical applications, friction is a desirable component, being the sound production mechanism of different musical instruments such as bowed strings, musical saws, rubbed bowls and any other sonority produced by interactions between rubbed dry surfaces. The goal of the dissertation is to simulate different instrument whose main excitation mechanism is friction. An efficient yet accurate model of a bowed string instrument, which combines the latest results in violin acoustics with the efficient digital waveguide approach, is provided. In particular, the bowed string physical model proposed uses a thermodynamic friction model in which the finite width of the bow is taken into account; this solution is compared to the recently developed elasto-plastic friction models used in haptics and robotics. Different solutions are also proposed to model the body of the instrument. Other less common instruments driven by friction are also proposed, and the elasto-plastic model is used to provide audio-visual simulations of everyday friction sounds such as squeaking doors and rubbed wine glasses. Finally, playability evaluations and musical applications in which the models have been used are discussed.

  14. Real-time economic optimization for a fermentation process using Model Predictive Control

    DEFF Research Database (Denmark)

    Petersen, Lars Norbert; Jørgensen, John Bagterp

    2014-01-01

    Fermentation is a widely used process in production of many foods, beverages, and pharmaceuticals. The main goal of the control system is to maximize profit of the fermentation process, and thus this is also the main goal of this paper. We present a simple dynamic model for a fermentation process...... and demonstrate its usefulness in economic optimization. The model is formulated as an index-1 differential algebraic equation (DAE), which guarantees conservation of mass and energy in discrete form. The optimization is based on recent advances within Economic Nonlinear Model Predictive Control (E......-NMPC), and also utilizes the index-1 DAE model. The E-NMPC uses the single-shooting method and the adjoint method for computation of the optimization gradients. The process constraints are relaxed to soft-constraints on the outputs. Finally we derive the analytical solution to the economic optimization problem...

  15. Real-Time Model Based Process Monitoring of Enzymatic Biodiesel Production

    DEFF Research Database (Denmark)

    Price, Jason Anthony; Nordblad, Mathias; Woodley, John

    2015-01-01

    In this contribution we extend our modelling work on the enzymatic production of biodiesel where we demonstrate the application of a Continuous-Discrete Extended Kalman Filter (a state estimator). The state estimator is used to correct for mismatch between the process data and the process model...... for Fed-batch production of biodiesel. For the three process runs investigated, using a single tuning parameter, qx=2 x 10-2 which represents the uncertainty in the process model, it was possible over the entire course of the reaction to reduce the overall mean and standard deviation of the error between......, there was over a ten-fold decrease in the overall mean error for the state estimator prediction compared with the predictions from the pure model simulations. It is also shown that the state estimator can be used as a tool for detection of outliers in the measurement data. For the enzymatic biodiesel process...

  16. Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control

    Directory of Open Access Journals (Sweden)

    RATOI, M.

    2010-05-01

    Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.

  17. Finite Element Methods for real-time Haptic Feedback of Soft-Tissue Models in Virtual Reality Simulators

    Science.gov (United States)

    Frank, Andreas O.; Twombly, I. Alexander; Barth, Timothy J.; Smith, Jeffrey D.; Dalton, Bonnie P. (Technical Monitor)

    2001-01-01

    We have applied the linear elastic finite element method to compute haptic force feedback and domain deformations of soft tissue models for use in virtual reality simulators. Our results show that, for virtual object models of high-resolution 3D data (>10,000 nodes), haptic real time computations (>500 Hz) are not currently possible using traditional methods. Current research efforts are focused in the following areas: 1) efficient implementation of fully adaptive multi-resolution methods and 2) multi-resolution methods with specialized basis functions to capture the singularity at the haptic interface (point loading). To achieve real time computations, we propose parallel processing of a Jacobi preconditioned conjugate gradient method applied to a reduced system of equations resulting from surface domain decomposition. This can effectively be achieved using reconfigurable computing systems such as field programmable gate arrays (FPGA), thereby providing a flexible solution that allows for new FPGA implementations as improved algorithms become available. The resulting soft tissue simulation system would meet NASA Virtual Glovebox requirements and, at the same time, provide a generalized simulation engine for any immersive environment application, such as biomedical/surgical procedures or interactive scientific applications.

  18. A real-time monitoring/emergency response workstation using a 3-D numerical model initialized with SODAR

    International Nuclear Information System (INIS)

    Lawver, B.S.; Sullivan, T.J.; Baskett, R.L.

    1993-01-01

    Many workstation based emergency response dispersion modeling systems provide simple Gaussian models driven by single meteorological tower inputs to estimate the downwind consequences from accidental spills or stack releases. Complex meteorological or terrain settings demand more sophisticated resolution of the three-dimensional structure of the atmosphere to reliably calculate plume dispersion. Mountain valleys and sea breeze flows are two common examples of such settings. To address these complexities, we have implemented the three-dimensional-diagnostic MATHEW mass-adjusted wind field and ADPIC particle-in-cell dispersion models on a workstation for use in real-time emergency response modeling. Both MATHEW and ADPIC have shown their utility in a variety of complex settings over the last 15 years within the Department of Energy's Atmospheric Release Advisory Capability project

  19. Real-time nonlinear feedback control of pattern formation in (bio)chemical reaction-diffusion processes: a model study.

    Science.gov (United States)

    Brandt-Pollmann, U; Lebiedz, D; Diehl, M; Sager, S; Schlöder, J

    2005-09-01

    Theoretical and experimental studies related to manipulation of pattern formation in self-organizing reaction-diffusion processes by appropriate control stimuli become increasingly important both in chemical engineering and cellular biochemistry. In a model study, we demonstrate here exemplarily the application of an efficient nonlinear model predictive control (NMPC) algorithm to real-time optimal feedback control of pattern formation in a bacterial chemotaxis system modeled by nonlinear partial differential equations. The corresponding drift-diffusion model type is representative for many (bio)chemical systems involving nonlinear reaction dynamics and nonlinear diffusion. We show how the computed optimal feedback control strategy exploits the system inherent physical property of wave propagation to achieve desired control aims. We discuss various applications of our approach to optimal control of spatiotemporal dynamics.

  20. Development of the Real-time Core and Thermal-Hydraulic Models for Kori-1 Simulator

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Jin Hyuk; Lee, Myeong Soo; Hwang, Do Hyun; Byon, Soo Jin [KEPRI, Daejeon (Korea, Republic of)

    2010-10-15

    The operation of the Kori-Unit 1 (1723.5MWt) is expanded to additional 10 years with upgrades of the Main Control Room (MCR). Therefore, the revision of the procedures, performance tests and works related with the exchange of the Main Control Board (MCB) are currently carried out. And as a part of it, the fullscope simulator for the Kori-1 is being developed for the purpose of the pre-operation and emergence response capability for the operators. The purpose of this paper is to report on the performance of the developed neutronics and thermal-hydraulic (TH) models of Kori Unit 1 simulator. The neutronics model is based on the NESTLE code and TH model based on the RELAP5/MOD3 thermal-hydraulics analysis code which was funded as FY-93 LDRD Project 7201 and is running on the commercial simulator environment tool (the 3KeyMaster{sup TM} of the WSC). As some examples for the verification of the developed neutronics and TH models, some figures are provided. The outputs of the developed neutronics and TH models are in accord with the Nuclear Design Report (NDR) and Final Safety Analysis Report (FSAR) of the reference plant

  1. Model-predictive control and real-time optimization of a cat cracker unit

    Directory of Open Access Journals (Sweden)

    Stig Strand

    1997-04-01

    Full Text Available A project for control and optimization of the Residual Catalytic Cracking Process at the Mongstad refinery is near completion. Four model-predictive control applications have been successfully implemented, using the IDCOM control software from Setpoint Inc. The most attractive feature of the controller is the well-defined control prioritizing hierarchy, and the linear impulse-response models have proved to give satisfactory performance on this process. Excitation and identification of the dynamic models proved to be a difficult task, and careful design and monitoring of the tests was mandatory in order to produce good results. Multi-variable Pseudo Random Binary Test Sequences were used for the excitation. Technical performance and operator acceptance of the new control functions have been good, but it is realized that a continuing effort is needed to fine-tune and maintain such functions.

  2. Making Digital Elevation ModelsAccessible, Comprehensible, and Engaging through Real-Time Visualization

    DEFF Research Database (Denmark)

    Kjeldsen, Thomas Kim; Mikkelsen, Peter Trier; Mosegaard, Jesper

    2015-01-01

    In this paper we present our initial experiments with the new high quality digital elevation model, “Danmarks Højdemodel-2015” (DHM) exposed as an interactive 3D visualization on web and in virtual reality. We argue that such data has great opportunities to spawn new business and new insight...

  3. Real-time resource model updating in continuous mining environment utilizing online sensor data

    NARCIS (Netherlands)

    Yüksel, C.

    2017-01-01

    In mining, modelling of the deposit geology is the basis for many actions to be taken in the future, such as predictions of quality attributes, mineral resources and ore reserves, as well as mine design and long-term production planning. The essential knowledge about the raw materialproduct is based

  4. Real-time remote sensing driven river basin modeling using radar altimetry

    DEFF Research Database (Denmark)

    Pereira Cardenal, Silvio Javier; Riegels, Niels; Bauer-Gottwein, Peter

    2011-01-01

    Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS) data have been recognized as an alternative to in-situ hydrometeorological data in remote...

  5. Continuous hydrological modelling in the context of real time flood forecasting in alpine Danube tributary catchments

    International Nuclear Information System (INIS)

    Stanzel, Ph; Kahl, B; Haberl, U; Herrnegger, M; Nachtnebel, H P

    2008-01-01

    A hydrological modelling framework applied within operational flood forecasting systems in three alpine Danube tributary basins, Traisen, Salzach and Enns, is presented. A continuous, semi-distributed rainfall-runoff model, accounting for the main hydrological processes of snow accumulation and melt, interception, evapotranspiration, infiltration, runoff generation and routing is set up. Spatial discretization relies on the division of watersheds into subbasins and subsequently into hydrologic response units based on spatial information on soil types, land cover and elevation bands. The hydrological models are calibrated with meteorological ground measurements and with meteorological analyses incorporating radar information. Operationally, each forecasting sequence starts with the re-calculation of the last 24 to 48 hours. Errors between simulated and observed runoff are minimized by optimizing a correction factor for the input to provide improved system states. For the hydrological forecast quantitative 48 or 72 hour forecast grids of temperature and precipitation - deterministic and probabilistic - are used as input. The forecasted hydrograph is corrected with an autoregressive model. The forecasting sequences are repeated each 15 minutes. First evaluations of resulting hydrological forecasts are presented and reliability of forecasts with different lead times is discussed.

  6. Experimental real-time multi-model ensemble (MME) prediction of ...

    Indian Academy of Sciences (India)

    calibration (training) has to be of good quality. Otherwise, it might degrade the MME results. Early works by ... ECMWF ensemble data (Evans et al 2000), and they showed the superiority of the multi-model system over the ..... eral idea of the quality of rainfall forecasts in terms of error statistics for monsoon for the member.

  7. Real-time Modelling, Diagnostics and Optimised MPPT for Residential PV Systems

    DEFF Research Database (Denmark)

    Sera, Dezso

    responsible for yield-reduction of residential photovoltaic systems. Combining the model calculations with measurements, a method to detect changes in the panels’ series resistance based on the slope of the I − V curve in the vicinity of open-circuit conditions and scaled to Standard Test Conditions (STC......The work documented in the thesis has been focused into two main sections. The first part is centred around Maximum Power Point Tracking (MPPT) techniques for photovoltaic arrays, optimised for fast-changing environmental conditions, and is described in Chapter 2. The second part is dedicated...... to diagnostic functions as an additional tool to maximise the energy yield of photovoltaic arrays (Chapter 4). Furthermore, mathematical models of PV panels and arrays have been developed and built (detailed in Chapter 3) for testing MPPT algorithms, and for diagnostic purposes. In Chapter 2 an overview...

  8. [Real-time detection of quality of Chinese materia medica: strategy of NIR model evaluation].

    Science.gov (United States)

    Wu, Zhi-sheng; Shi, Xin-yuan; Xu, Bing; Dai, Xing-xing; Qiao, Yan-jiang

    2015-07-01

    The definition of critical quality attributes of Chinese materia medica ( CMM) was put forward based on the top-level design concept. Nowadays, coupled with the development of rapid analytical science, rapid assessment of critical quality attributes of CMM was firstly carried out, which was the secondary discipline branch of CMM. Taking near infrared (NIR) spectroscopy as an example, which is a rapid analytical technology in pharmaceutical process over the past decade, systematic review is the chemometric parameters in NIR model evaluation. According to the characteristics of complexity of CMM and trace components analysis, a multi-source information fusion strategy of NIR model was developed for assessment of critical quality attributes of CMM. The strategy has provided guideline for NIR reliable analysis in critical quality attributes of CMM.

  9. Wavelet Compressed PCA Models for Real-Time Image Registration in Augmented Reality Applications

    OpenAIRE

    Christopher Cooper; Kent Wise; John Cooper; Makarand Deo

    2015-01-01

    The use of augmented reality (AR) has shown great promise in enhancing medical training and diagnostics via interactive simulations. This paper presents a novel method to perform accurate and inexpensive image registration (IR) utilizing a pre-constructed database of reference objects in conjunction with a principal component analysis (PCA) model. In addition, a wavelet compression algorithm is utilized to enhance the speed of the registration process. The proposed method is used to perform r...

  10. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

    Science.gov (United States)

    Chen, Feng; Chen, Suren; Ma, Xiaoxiang

    2018-06-01

    Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

  11. Real-Time Model-Based Leak-Through Detection within Cryogenic Flow Systems

    Science.gov (United States)

    Walker, M.; Figueroa, F.

    2015-01-01

    The timely detection of leaks within cryogenic fuel replenishment systems is of significant importance to operators on account of the safety and economic impacts associated with material loss and operational inefficiencies. Associated loss in control of pressure also effects the stability and ability to control the phase of cryogenic fluids during replenishment operations. Current research dedicated to providing Prognostics and Health Management (PHM) coverage of such cryogenic replenishment systems has focused on the detection of leaks to atmosphere involving relatively simple model-based diagnostic approaches that, while effective, are unable to isolate the fault to specific piping system components. The authors have extended this research to focus on the detection of leaks through closed valves that are intended to isolate sections of the piping system from the flow and pressurization of cryogenic fluids. The described approach employs model-based detection of leak-through conditions based on correlations of pressure changes across isolation valves and attempts to isolate the faults to specific valves. Implementation of this capability is enabled by knowledge and information embedded in the domain model of the system. The approach has been used effectively to detect such leak-through faults during cryogenic operational testing at the Cryogenic Testbed at NASA's Kennedy Space Center.

  12. A nonlinear 3D real-time model for simulation of BWR nuclear power plants

    International Nuclear Information System (INIS)

    Ercan, Y.

    1982-02-01

    A nonlinear transient model for BWR nuclear power plants which consists of a 3D-core (subdivided into a number of superboxes, and with parallel flow and subcooled boiling), a top plenum, steam removal and feed water systems and main coolant recirculation pumps is given. The model describes the local core and global plant transient situation as dependent on both the inherent core dynamics and external control actions, i.e., disturbances such as motions of control rod banks, changes of mass flow rates of coolant, feed water and steam outlet. The case of a pressure-controlled reactor operation is also considered. The model which forms the basis for the digital code GARLIC-B (Er et al. 82) is aimed to be used on an on-site process computer in parallel to the actual reactor process (or even in predictive mode). Thus, special measures had to be taken into account in order to increase the computational speed and reduce the necessary computer storage. This could be achieved by - separating the neutron and power kinetics from the xenon-iodine dynamics, - treating the neutron kinetics and most of the thermodynamics and hydrodynamics in a pseudostationary way, - developing a special coupling coefficient concept to describe the neutron diffusion, calculating the coupling coefficients from a basic neutron kinetics code, - combining coarse mesh elements into superboxes, taking advantage of the symmetry properties of the core and - applying a sparse matrix technique for solving the resulting algebraic power equation system. (orig.) [de

  13. Integrating Real-Time Room Acoustics Simulation into a CAD Modeling Software to Enhance the Architectural Design Process

    Directory of Open Access Journals (Sweden)

    Sönke Pelzer

    2014-04-01

    Full Text Available For architects, real-time 3D visual rendering of CAD-models is a valuable tool. The architect usually perceives the visual appearance of the building interior in a natural and realistic way during the design process. Unfortunately this only emphasizes the role of the visual appearance of a building, while the acoustics often remain disregarded. Controlling the room acoustics is not integrated into most architects’ workflows—due to a lack of tools. The present contribution describes a newly developed plug-in for adding an adequate 3D-acoustics feedback to the architect. To present intuitively the acoustical effect of the current design project, the plug-in uses real-time audio rendering and 3D-reproduction. The room acoustics of the design can be varied by modifying structural shapes as well as by changing the material selection. In addition to the audio feedback, also a visualization of important room acoustics qualities is provided by displaying color-coded maps inside the CAD software.

  14. Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models

    Directory of Open Access Journals (Sweden)

    Nouar AlDahoul

    2018-01-01

    Full Text Available Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly susceptible to dynamical events such as illumination changes, camera jitter, and variations in object sizes. On the other hand, the proposed feature learning approaches are cheaper and easier because highly abstract and discriminative features can be produced automatically without the need of expert knowledge. In this paper, we utilize automatic feature learning methods which combine optical flow and three different deep models (i.e., supervised convolutional neural network (S-CNN, pretrained CNN feature extractor, and hierarchical extreme learning machine for human detection in videos captured using a nonstatic camera on an aerial platform with varying altitudes. The models are trained and tested on the publicly available and highly challenging UCF-ARG aerial dataset. The comparison between these models in terms of training, testing accuracy, and learning speed is analyzed. The performance evaluation considers five human actions (digging, waving, throwing, walking, and running. Experimental results demonstrated that the proposed methods are successful for human detection task. Pretrained CNN produces an average accuracy of 98.09%. S-CNN produces an average accuracy of 95.6% with soft-max and 91.7% with Support Vector Machines (SVM. H-ELM has an average accuracy of 95.9%. Using a normal Central Processing Unit (CPU, H-ELM’s training time takes 445 seconds. Learning in S-CNN takes 770 seconds with a high performance Graphical Processing Unit (GPU.

  15. FPGA implementation for real-time background subtraction based on Horprasert model.

    Science.gov (United States)

    Rodriguez-Gomez, Rafael; Fernandez-Sanchez, Enrique J; Diaz, Javier; Ros, Eduardo

    2012-01-01

    Background subtraction is considered the first processing stage in video surveillance systems, and consists of determining objects in movement in a scene captured by a static camera. It is an intensive task with a high computational cost. This work proposes an embedded novel architecture on FPGA which is able to extract the background on resource-limited environments and offers low degradation (produced because of the hardware-friendly model modification). In addition, the original model is extended in order to detect shadows and improve the quality of the segmentation of the moving objects. We have analyzed the resource consumption and performance in Spartan3 Xilinx FPGAs and compared to others works available on the literature, showing that the current architecture is a good trade-off in terms of accuracy, performance and resources utilization. With less than a 65% of the resources utilization of a XC3SD3400 Spartan-3A low-cost family FPGA, the system achieves a frequency of 66.5 MHz reaching 32.8 fps with resolution 1,024 × 1,024 pixels, and an estimated power consumption of 5.76 W.

  16. Combining multiple earthquake models in real time for earthquake early warning

    Science.gov (United States)

    Minson, Sarah E.; Wu, Stephen; Beck, James L; Heaton, Thomas H.

    2017-01-01

    The ultimate goal of earthquake early warning (EEW) is to provide local shaking information to users before the strong shaking from an earthquake reaches their location. This is accomplished by operating one or more real‐time analyses that attempt to predict shaking intensity, often by estimating the earthquake’s location and magnitude and then predicting the ground motion from that point source. Other EEW algorithms use finite rupture models or may directly estimate ground motion without first solving for an earthquake source. EEW performance could be improved if the information from these diverse and independent prediction models could be combined into one unified, ground‐motion prediction. In this article, we set the forecast shaking at each location as the common ground to combine all these predictions and introduce a Bayesian approach to creating better ground‐motion predictions. We also describe how this methodology could be used to build a new generation of EEW systems that provide optimal decisions customized for each user based on the user’s individual false‐alarm tolerance and the time necessary for that user to react.

  17. FPGA Implementation for Real-Time Background Subtraction Based on Horprasert Model

    Directory of Open Access Journals (Sweden)

    Eduardo Ros

    2012-01-01

    Full Text Available Background subtraction is considered the first processing stage in video surveillance systems, and consists of determining objects in movement in a scene captured by a static camera. It is an intensive task with a high computational cost. This work proposes an embedded novel architecture on FPGA which is able to extract the background on resource-limited environments and offers low degradation (produced because of the hardware-friendly model modification. In addition, the original model is extended in order to detect shadows and improve the quality of the segmentation of the moving objects. We have analyzed the resource consumption and performance in Spartan3 Xilinx FPGAs and compared to others works available on the literature, showing that the current architecture is a good trade-off in terms of accuracy, performance and resources utilization. With less than a 65% of the resources utilization of a XC3SD3400 Spartan-3A low-cost family FPGA, the system achieves a frequency of 66.5 MHz reaching 32.8 fps with resolution 1,024 x 1,024 pixels, and an estimated power consumption of 5.76 W.

  18. NOAA Operational Model Archive Distribution System (NOMADS): High Availability Applications for Reliable Real Time Access to Operational Model Data

    Science.gov (United States)

    Alpert, J. C.; Wang, J.

    2009-12-01

    To reduce the impact of natural hazards and environmental changes, the National Centers for Environmental Prediction (NCEP) provide first alert and a preferred partner for environmental prediction services, and represents a critical national resource to operational and research communities affected by climate, weather and water. NOMADS is now delivering high availability services as part of NOAA’s official real time data dissemination at its Web Operations Center (WOC) server. The WOC is a web service used by organizational units in and outside NOAA, and acts as a data repository where public information can be posted to a secure and scalable content server. A goal is to foster collaborations among the research and education communities, value added retailers, and public access for science and development efforts aimed at advancing modeling and GEO-related tasks. The user (client) executes what is efficient to execute on the client and the server efficiently provides format independent access services. Client applications can execute on the server, if it is desired, but the same program can be executed on the client side with no loss of efficiency. In this way this paradigm lends itself to aggregation servers that act as servers of servers listing, searching catalogs of holdings, data mining, and updating information from the metadata descriptions that enable collections of data in disparate places to be simultaneously accessed, with results processed on servers and clients to produce a needed answer. The services used to access the operational model data output are the Open-source Project for a Network Data Access Protocol (OPeNDAP), implemented with the Grid Analysis and Display System (GrADS) Data Server (GDS), and applications for slicing, dicing and area sub-setting the large matrix of real time model data holdings. This approach insures an efficient use of computer resources because users transmit/receive only the data necessary for their tasks including

  19. 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

  20. A Distributed Web-based Solution for Ionospheric Model Real-time Management, Monitoring, and Short-term Prediction

    Science.gov (United States)

    Kulchitsky, A.; Maurits, S.; Watkins, B.

    2006-12-01

    With the widespread availability of the Internet today, many people can monitor various scientific research activities. It is important to accommodate this interest providing on-line access to dynamic and illustrative Web-resources, which could demonstrate different aspects of ongoing research. It is especially important to explain and these research activities for high school and undergraduate students, thereby providing more information for making decisions concerning their future studies. Such Web resources are also important to clarify scientific research for the general public, in order to achieve better awareness of research progress in various fields. Particularly rewarding is dissemination of information about ongoing projects within Universities and research centers to their local communities. The benefits of this type of scientific outreach are mutual, since development of Web-based automatic systems is prerequisite for many research projects targeting real-time monitoring and/or modeling of natural conditions. Continuous operation of such systems provide ongoing research opportunities for the statistically massive validation of the models, as well. We have developed a Web-based system to run the University of Alaska Fairbanks Polar Ionospheric Model in real-time. This model makes use of networking and computational resources at the Arctic Region Supercomputing Center. This system was designed to be portable among various operating systems and computational resources. Its components can be installed across different computers, separating Web servers and computational engines. The core of the system is a Real-Time Management module (RMM) written Python, which facilitates interactions of remote input data transfers, the ionospheric model runs, MySQL database filling, and PHP scripts for the Web-page preparations. The RMM downloads current geophysical inputs as soon as they become available at different on-line depositories. This information is processed to

  1. Uncertainty modelling of real-time observation of a moving object: photogrammetric measurements

    Science.gov (United States)

    Ulrich, Thomas

    2015-04-01

    Photogrametric systems are widely used in the field of industrial metrology to measure kinematic tasks such as tracking robot movements. In order to assess spatiotemporal deviations of a kinematic movement, it is crucial to have a reliable uncertainty of the kinematic measurements. Common methods to evaluate the uncertainty in kinematic measurements include approximations specified by the manufactures, various analytical adjustment methods and Kalman filters. Here a hybrid system estimator in conjunction with a kinematic measurement model is applied. This method can be applied to processes which include various types of kinematic behaviour, constant velocity, variable acceleration or variable turn rates. Additionally, it has been shown that the approach is in accordance with GUM (Guide to the Expression of Uncertainty in Measurement). The approach is compared to the Kalman filter using simulated data to achieve an overall error calculation. Furthermore, the new approach is used for the analysis of a rotating system as this system has both a constant and a variable turn rate. As the new approach reduces overshoots it is more appropriate for analysing kinematic processes than the Kalman filter. In comparison with the manufacturer’s approximations, the new approach takes account of kinematic behaviour, with an improved description of the real measurement process. Therefore, this approach is well-suited to the analysis of kinematic processes with unknown changes in kinematic behaviour.

  2. Development of the Real Time Situation Identification Model for Adaptive Service Support in Vehicular Communication Networks Domain

    Directory of Open Access Journals (Sweden)

    Mindaugas Kurmis

    2013-01-01

    Full Text Available The article discusses analyses and assesses the key proposals how to deal with the situation identification for the heterogeneous service support in vehicular cooperation environment. This is one of the most important topics of the pervasive computing. Without the solution it is impossible to adequately respond to the user's needs and to provide needed services in the right place at the right moment and in the right way. In this work we present our developed real time situation identification model for adaptive service support in vehicular communication networks domain. Our solution is different from the others as it uses additional virtual context information source - information from other vehicles which for our knowledge is not addressed in the past. The simulation results show the promising context exchange rate between vehicles. The other vehicles provided additional context source in our developed model helps to increase situations identification level.

  3. Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

    Science.gov (United States)

    van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

    2015-04-01

    In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

  4. LANL* V1.0: a radiation belt drift shell model suitable for real-time and reanalysis applications

    Energy Technology Data Exchange (ETDEWEB)

    Koller, Josep [Los Alamos National Laboratory; Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory

    2008-01-01

    Space weather modeling, forecasts, and predictions, especially for the radiation belts in the inner magnetosphere, require detailed information about the Earth's magnetic field. Results depend on the magnetic field model and the L* (pron. L-star) values which are used to describe particle drift shells. Space wather models require integrating particle motions along trajectories that encircle the Earth. Numerical integration typically takes on the order of 10{sup 5} calls to a magnetic field model which makes the L* calculations very slow, in particular when using a dynamic and more accurate magnetic field model. Researchers currently tend to pick simplistic models over more accurate ones but also risking large inaccuracies and even wrong conclusions. For example, magnetic field models affect the calculation of electron phase space density by applying adiabatic invariants including the drift shell value L*. We present here a new method using a surrogate model based on a neural network technique to replace the time consuming L* calculations made with modern magnetic field models. The advantage of surrogate models (or meta-models) is that they can compute the same output in a fraction of the time while adding only a marginal error. Our drift shell model LANL* (Los Alamos National Lab L-star) is based on L* calculation using the TSK03 model. The surrogate model has currently been tested and validated only for geosynchronous regions but the method is generally applicable to any satellite orbit. Computations with the new model are several million times faster compared to the standard integration method while adding less than 1% error. Currently, real-time applications for forecasting and even nowcasting inner magnetospheric space weather is limited partly due to the long computing time of accurate L* values. Without them, real-time applications are limited in accuracy. Reanalysis application of past conditions in the inner magnetosphere are used to understand

  5. LANL* V1.0: a radiation belt drift shell model suitable for real-time and reanalysis applications

    International Nuclear Information System (INIS)

    Koller, Josep; Reeves, Geoffrey D.; Friedel, Reiner H.W.

    2008-01-01

    Space weather modeling, forecasts, and predictions, especially for the radiation belts in the inner magnetosphere, require detailed information about the Earth's magnetic field. Results depend on the magnetic field model and the L* (pron. L-star) values which are used to describe particle drift shells. Space wather models require integrating particle motions along trajectories that encircle the Earth. Numerical integration typically takes on the order of 10 5 calls to a magnetic field model which makes the L* calculations very slow, in particular when using a dynamic and more accurate magnetic field model. Researchers currently tend to pick simplistic models over more accurate ones but also risking large inaccuracies and even wrong conclusions. For example, magnetic field models affect the calculation of electron phase space density by applying adiabatic invariants including the drift shell value L*. We present here a new method using a surrogate model based on a neural network technique to replace the time consuming L* calculations made with modern magnetic field models. The advantage of surrogate models (or meta-models) is that they can compute the same output in a fraction of the time while adding only a marginal error. Our drift shell model LANL* (Los Alamos National Lab L-star) is based on L* calculation using the TSK03 model. The surrogate model has currently been tested and validated only for geosynchronous regions but the method is generally applicable to any satellite orbit. Computations with the new model are several million times faster compared to the standard integration method while adding less than 1% error. Currently, real-time applications for forecasting and even nowcasting inner magnetospheric space weather is limited partly due to the long computing time of accurate L* values. Without them, real-time applications are limited in accuracy. Reanalysis application of past conditions in the inner magnetosphere are used to understand physical

  6. Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

    Energy Technology Data Exchange (ETDEWEB)

    Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Drohmann, Martin [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Tuminaro, Raymond S. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Computational Mathematics; Boggs, Paul T. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Quantitative Modeling and Analysis; van Bloemen Waanders, Bart Gustaaf [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Optimization and Uncertainty Estimation

    2014-10-01

    Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model

  7. Real-time distributed simulation using the Modular Modeling System interfaced to a Bailey NETWORK 90 system

    International Nuclear Information System (INIS)

    Edwards, R.M.; Turso, J.A.; Garcia, H.E.; Ghie, M.H.; Dharap, S.; Lee, S.

    1991-01-01

    The Modular Modeling System was adapted for real-time simulation testing of diagnostic expert systems in 1987. The early approach utilized an available general purpose mainframe computer which operated the simulation and diagnostic program in the multitasking environment of the mainframe. That research program was subsequently expanded to intelligent distributed control applications incorporating microprocessor based controllers with the aid of an equipment grant from the National Science Foundation (NSF). The Bailey NETWORK 90 microprocessor-based control system, acquired with the NSF grant, has been operational since April of 1990 and has been interfaced to both VAX mainframe and PC simulations of power plant processes in order to test and demonstrate advanced control and diagnostic concepts. This paper discusses the variety of techniques that have been used and which are under development to interface simulations and other distributed control functions to the Penn State Bailey system

  8. Real-time shadows

    CERN Document Server

    Eisemann, Elmar; Assarsson, Ulf; Wimmer, Michael

    2011-01-01

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

  9. Developing Near Real-time Data-assimilative Models and Tools for the Space Environment, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The IDA4D and AMIE data assimilation methods are currently of limited use for real-time space weather applications because either they don't run in real-time (IDA4D)...

  10. 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

  11. Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems

    International Nuclear Information System (INIS)

    Su, Yan; Chan, Lai-Cheong; Shu, Lianjie; Tsui, Kwok-Leung

    2012-01-01

    Highlights: ► We develop online prediction models for solar photovoltaic system performance. ► The proposed prediction models are simple but with reasonable accuracy. ► The maximum monthly average minutely efficiency varies 10.81–12.63%. ► The average efficiency tends to be slightly higher in winter months. - Abstract: This paper develops new real time prediction models for output power and energy efficiency of solar photovoltaic (PV) systems. These models were validated using measured data of a grid-connected solar PV system in Macau. Both time frames based on yearly average and monthly average are considered. It is shown that the prediction model for the yearly/monthly average of the minutely output power fits the measured data very well with high value of R 2 . The online prediction model for system efficiency is based on the ratio of the predicted output power to the predicted solar irradiance. This ratio model is shown to be able to fit the intermediate phase (9 am to 4 pm) very well but not accurate for the growth and decay phases where the system efficiency is near zero. However, it can still serve as a useful purpose for practitioners as most PV systems work in the most efficient manner over this period. It is shown that the maximum monthly average minutely efficiency varies over a small range of 10.81% to 12.63% in different months with slightly higher efficiency in winter months.

  12. Nowcasting, forecasting and hindcasting Harvey and Irma inundation in near-real time using a continental 2D hydrodynamic model

    Science.gov (United States)

    Sampson, C. C.; Wing, O.; Quinn, N.; Smith, A.; Neal, J. C.; Schumann, G.; Bates, P.

    2017-12-01

    During an ongoing natural disaster data are required on: (1) the current situation (nowcast); (2) its likely immediate evolution (forecast); and (3) a consistent view post-event of what actually happened (hindcast or reanalysis). We describe methods used to achieve all three tasks for flood inundation during the Harvey and Irma events using a continental scale 2D hydrodynamic model (Wing et al., 2017). The model solves the local inertial form of the Shallow Water equations over a regular grid of 1 arcsecond ( 30m). Terrain data are taken from the USGS National Elevation Dataset with known flood defences represented using the U.S. Army Corps of Engineers National Levee Dataset. Channels are treated as sub-grid scale features using the HydroSHEDS global hydrography data set. The model is driven using river flows, rainfall and coastal water levels. It simulates river flooding in basins > 50 km2, and fluvial and coastal flooding everywhere. Previous wide area validation tests show this model to be capable of matching FEMA maps and USGS local models built with bespoke data with hit rates of 86% and 92% respectively (Wing et al., 2017). Boundary conditions were taken from NOAA QPS data to produce nowcast and forecast simulations in near real time, before updating with NOAA observations to produce the hindcast. During the event simulation results were supplied to major insurers and multi-nationals who used them to estimate their likely capital exposure and to mitigate flood damage to their infrastructure whilst the event was underway. Simulations were validated against modelled flood footprints computed by FEMA and USACE, and composite satellite imagery produced by the Dartmouth Flood Observatory. For the Harvey event, hit rates ranged from 60-84% against these data sources, but a lack of metadata meant it was difficult to perform like-for-like comparisons. The satellite data also appeared to miss known flooding in urban areas that was picked up in the models. Despite

  13. Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU.

    Science.gov (United States)

    Doulgerakis, Matthaios; Eggebrecht, Adam; Wojtkiewicz, Stanislaw; Culver, Joseph; Dehghani, Hamid

    2017-12-01

    Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25  s/excitation source. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  14. Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU

    Science.gov (United States)

    Doulgerakis, Matthaios; Eggebrecht, Adam; Wojtkiewicz, Stanislaw; Culver, Joseph; Dehghani, Hamid

    2017-12-01

    Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ˜600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ˜0.25 s/excitation source.

  15. Real time expert systems

    International Nuclear Information System (INIS)

    Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

    1992-01-01

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

  16. Effective Solar Indices for Ionospheric Modeling: A Review and a Proposal for a Real-Time Regional IRI

    Science.gov (United States)

    Pignalberi, A.; Pezzopane, M.; Rizzi, R.; Galkin, I.

    2018-01-01

    The first part of this paper reviews methods using effective solar indices to update a background ionospheric model focusing on those employing the Kriging method to perform the spatial interpolation. Then, it proposes a method to update the International Reference Ionosphere (IRI) model through the assimilation of data collected by a European ionosonde network. The method, called International Reference Ionosphere UPdate (IRI UP), that can potentially operate in real time, is mathematically described and validated for the period 9-25 March 2015 (a time window including the well-known St. Patrick storm occurred on 17 March), using IRI and IRI Real Time Assimilative Model (IRTAM) models as the reference. It relies on foF2 and M(3000)F2 ionospheric characteristics, recorded routinely by a network of 12 European ionosonde stations, which are used to calculate for each station effective values of IRI indices IG_{12} and R_{12} (identified as IG_{{12{eff}}} and R_{{12{eff}}}); then, starting from this discrete dataset of values, two-dimensional (2D) maps of IG_{{12{eff}}} and R_{{12{eff}}} are generated through the universal Kriging method. Five variogram models are proposed and tested statistically to select the best performer for each effective index. Then, computed maps of IG_{{12{eff}}} and R_{{12{eff}}} are used in the IRI model to synthesize updated values of foF2 and hmF2. To evaluate the ability of the proposed method to reproduce rapid local changes that are common under disturbed conditions, quality metrics are calculated for two test stations whose measurements were not assimilated in IRI UP, Fairford (51.7°N, 1.5°W) and San Vito (40.6°N, 17.8°E), for IRI, IRI UP, and IRTAM models. The proposed method turns out to be very effective under highly disturbed conditions, with significant improvements of the foF2 representation and noticeable improvements of the hmF2 one. Important improvements have been verified also for quiet and moderately disturbed

  17. 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.

  18. A Novel Non-Iterative Method for Real-Time Parameter Estimation of the Fricke-Morse Model

    Directory of Open Access Journals (Sweden)

    SIMIC, M.

    2016-11-01

    Full Text Available Parameter estimation of Fricke-Morse model of biological tissue is widely used in bioimpedance data processing and analysis. Complex nonlinear least squares (CNLS data fitting is often used for parameter estimation of the model, but limitations such as high processing time, converging into local minimums, need for good initial guess of model parameters and non-convergence have been reported. Thus, there is strong motivation to develop methods which can solve these flaws. In this paper a novel real-time method for parameter estimation of Fricke-Morse model of biological cells is presented. The proposed method uses the value of characteristic frequency estimated from the measured imaginary part of bioimpedance, whereupon the Fricke-Morse model parameters are calculated using the provided analytical expressions. The proposed method is compared with CNLS in frequency ranges of 1 kHz to 10 MHz (beta-dispersion and 10 kHz to 100 kHz, which is more suitable for low-cost microcontroller-based bioimpedance measurement systems. The obtained results are promising, and in both frequency ranges, CNLS and the proposed method have accuracies suitable for most electrical bioimpedance (EBI applications. However, the proposed algorithm has significantly lower computation complexity, so it was 20-80 times faster than CNLS.

  19. Numerical modeling in real-time assessment of dispersal of radionuclides beyond ten to twenty kilometres from an accidental release

    International Nuclear Information System (INIS)

    ApSimon, H.M.; Wilson, J.J.N.

    1990-01-01

    The Chernobyl accident has demonstrated the need for capabilities to assess transport and contamination out to considerable distances and across national frontiers in the event of a nuclear accident. For real-time assessment close to the source, the transport, dilution and deposition of material are usually based on simple Gaussian plume or puff techniques. At greater distances, usually beyond 10 or 20 km., changing meteorological conditions and topographical features become increasingly important and may require rather different modelling techniques. At yet longer distances synoptic scale weather patterns and their evolution govern where material will travel, and regions where precipitation may potentially yield higher deposition of critical nuclides such as I-131 and Cs-137. This paper will consider the questions to be addressed by numerical models during a nuclear emergency, and how such models may be incorporated in an overall assessment system for emergency procedures, extending to span the European Continent. The appropriate modelling techniques available for simulating transport over mesoscale distances (out to a few hundred kilometres), and for the synoptic scale (out to a few thousand kilometres) will be reviewed. The radiological measurements which would be of the greatest use for checking and revising model calculations in an emergency situation will also be discussed, and the importance of international exchange of such information emphasized

  20. Evaluation of multiple hydraulic models in generating design/near-real time flood inundation extents under various geophysical settings

    Science.gov (United States)

    Liu, Z.; Rajib, M. A.; Jafarzadegan, K.; Merwade, V.

    2015-12-01

    Application of land surface/hydrologic models within an operational flood forecasting system can provide probable time of occurrence and magnitude of streamflow at specific locations along a stream. Creating time-varying spatial extent of flood inundation and depth requires the use of a hydraulic or hydrodynamic model. Models differ in representing river geometry and surface roughness which can lead to different output depending on the particular model being used. The result from a single hydraulic model provides just one possible realization of the flood extent without capturing the uncertainty associated with the input or the model parameters. The objective of this study is to compare multiple hydraulic models toward generating ensemble flood inundation extents. Specifically, relative performances of four hydraulic models, including AutoRoute, HEC-RAS, HEC-RAS 2D, and LISFLOOD are evaluated under different geophysical conditions in several locations across the United States. By using streamflow output from the same hydrologic model (SWAT in this case), hydraulic simulations are conducted for three configurations: (i) hindcasting mode by using past observed weather data at daily time scale in which models are being calibrated against USGS streamflow observations, (ii) validation mode using near real-time weather data at sub-daily time scale, and (iii) design mode with extreme streamflow data having specific return periods. Model generated inundation maps for observed flood events both from hindcasting and validation modes are compared with remotely sensed images, whereas the design mode outcomes are compared with corresponding FEMA generated flood hazard maps. The comparisons presented here will give insights on probable model-specific nature of biases and their relative advantages/disadvantages as components of an operational flood forecasting system.

  1. Combining UML2 Application and SystemC Platform Modelling for Performance Evaluation of Real-Time Embedded Systems

    Directory of Open Access Journals (Sweden)

    Qu Yang

    2008-01-01

    Full Text Available Abstract Future mobile devices will be based on heterogeneous multiprocessing platforms accommodating several stand-alone applications. The network-on-chip communication and device networking combine the design challenges of conventional distributed systems and resource constrained real-time embedded systems. Interoperable design space exploration for both the application and platform development is required. Application designer needs abstract platform models to rapidly check the feasibility of a new feature or application. Platform designer needs abstract application models for defining platform computation and communication capacities. We propose a layered UML application/workload and SystemC platform modelling approach that allow application and platform to be modelled at several levels of abstraction, which enables early performance evaluation of the resulting system. The overall approach has been experimented with a mobile video player case study, while different load extraction methods have been validated by applying them to MPEG-4 encoder, Quake2 3D game, and MP3 decoder case studies previously.

  2. Model-driven requirements engineering (MDRE) for real-time ultra-wide instantaneous bandwidth signal simulation

    Science.gov (United States)

    Chang, Daniel Y.; Rowe, Neil C.

    2013-05-01

    While conducting a cutting-edge research in a specific domain, we realize that (1) requirements clarity and correctness are crucial to our success [1], (2) hardware is hard to change, most work is in software requirements development, coding and testing [2], (3) requirements are constantly changing, so that configurability, reusability, scalability, adaptability, modularity and testability are important non-functional attributes [3], (4) cross-domain knowledge is necessary for complex systems [4], and (5) if our research is successful, the results could be applied to other domains with similar problems. In this paper, we propose to use model-driven requirements engineering (MDRE) to model and guide our requirements/development, since models are easy to understand, execute, and modify. The domain for our research is Electronic Warfare (EW) real-time ultra-wide instantaneous bandwidth (IBW1) signal simulation. The proposed four MDRE models are (1) Switch-and-Filter architecture, (2) multiple parallel data bit streams alignment, (3) post-ADC and pre-DAC bits re-mapping, and (4) Discrete Fourier Transform (DFT) filter bank. This research is unique since the instantaneous bandwidth we are dealing with is in gigahertz range instead of conventional megahertz.

  3. A near-real-time material accountancy model and its preliminary demonstration in the Tokai reprocessing plant

    International Nuclear Information System (INIS)

    Ikawa, K.; Ihara, H.; Nishimura, H.; Tsutsumi, M.; Sawahata, T.

    1983-01-01

    The study of a near-real-time (n.r.t.) material accountancy system as applied to small or medium-sized spent fuel reprocessing facilities has been carried out since 1978 under the TASTEX programme. In this study, a model of the n.r.t. accountancy system, called the ten-day-detection-time model, was developed and demonstrated in the actual operating plant. The programme was closed on May 1981, but the study has been extended. The effectiveness of the proposed n.r.t. accountancy model was evaluated by means of simulation techniques. The results showed that weekly material balances covering the entire process MBA could provide sufficient information to satisfy the IAEA guidelines for small or medium-sized facilities. The applicability of the model to the actual plant has been evaluated by a series of field tests which covered four campaigns. In addition to the material accountancy data, many valuable operational data with regard to additional locations for an in-process inventory, the time needed for an in-process inventory, etc., have been obtained. A CUMUF (cumulative MUF) chart of the resulting MUF data in the C-1 and C-2 campaigns clearly showed that there had been a measurement bias across the process MBA. This chart gave a dramatic picture of the power of the n.r.t. accountancy concept by showing the nature of this bias, which was not clearly shown in the conventional material accountancy data. (author)

  4. Development of real-time core monitoring system models with accuracy-enhanced neural network and its application

    International Nuclear Information System (INIS)

    Koo, Bon Hyun

    1994-02-01

    In a complicated system like pressurized water reactor, a number of key safety parameters need to be selected to represent the reactor systems safety. It could be more effective for the reactor safety to make the key safety parameters in real-time available directly to the reactor operator. Direct representation of key safety parameters is also desirable in the view of reactor core design since it could reduce unnecessary margins for various components of uncertainties. In this thesis, real-time core monitoring system models have been developed with use of artificial neural networks for the prediction of nuclear hot channel factor (HCF) and core departure from nucleate boiling ratio (DNBR) which are known to be the fundamental core safety parameters for pressurized water reactors. Artificial neural network algorithm, has been shown to be successful for the conservative and accurate prediction of the HCF and DNBR. For the development of system models, training patterns were generated using the FLAIR and COBRAIV-i computer codes for the HCF and DNBR. The selected input variables were the core power, reactor coolant flow, temperature, pressure, power distribution, boron concentration, and rod position. The developed system models could replace the existing core monitoring systems and then afford a better efficiency by using the additional margin which otherwise needs to be reserved for various unidentified uncertainties. Several variations of the neural network technique have been proposed and compared based on numerical experiments. The neural network can be augmented by use of a functional link to improve the performance of the network model. The functional link is found to be very effective especially when the relationship between the input parameters and the output parameters is overly complicated such as in the core HCF and DNBR. For the further enhancement of DNBR accuracy, two-fold weight sets were used. The coarse weight set can provide a quick and

  5. SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

    Science.gov (United States)

    Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

    2018-01-01

    Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Evaluation Study of the Tactical Atmospheric Modeling System/Real-Time (TAMS-RT) at NPMOC San Diego

    National Research Council Canada - National Science Library

    Reiss, Arthur

    1999-01-01

    ...) has been developed by the Naval Research Lab in Monterey, California to meet this task. A forecast system employing COAMPS, called the Tactical Atmospheric Mesoscale System- Real Time (TAMS-RT...

  7. Exploring and modelling impacts of third molar experience on quality of life: a real-time qualitative study using Twitter.

    Science.gov (United States)

    Hanna, Kamal; Sambrook, Paul; Armfield, Jason M; Brennan, David S

    2017-10-01

    This study had two objectives: (i) to explore and model domains describing the real-time impact of third molars (TMs) on quality of life (QoL); and (ii) to assess the percentage coverage, in some generic health-related quality of life (HRQoL) and oral health-related quality of life (OHRQoL) instruments, of the TM QoL domains identified in this study. A global cross-sectional sample of tweets containing 'wisdom tooth' over a 1-week period retrieved 3,537 tweets. After random quota sampling, classification and filtering, only 843 tweets were included in the thematic analysis. A TM QoL model was constructed based on the associations of the identified domains. Domains for the selected generic HRQoL and OHRQoL instruments were plotted against the domains identified in the study to calculate the percentage coverage for each. The QoL domains identified were pain (n = 348, 41%), mood (n = 173, 20%), anxiety and fear (n = 54, 7%), enjoying food (n = 41, 4%), coping (n = 37, 4%), daily activities (n = 34, 4%), sleep (n = 24, 2%), social life (n = 19, 2%), physical health (n = 17, 2%), ability to think (n = 9, 1%), self-care (n = 8, 1%) and sporting & recreation (n = 2, <1%). The Assessment Quality of Life instrument (AQoL-8D) covers 87% of the TM QoL domains, while the rest of the HRQoL and OHRQoL instruments cover 33-60%. This study shows how Twitter can be used to obtain real-time QoL data, which might be used to model how TMs impact on QoL. The TM QoL domains identified in the study were generally under-represented among the generic OHRQoL instruments assessed while, the HRQoL AQoL-8D covered most of the TM QoL domains. The QoL domains identified in the study might be used to develop a new OHRQoL measure for TMs. © 2017 FDI World Dental Federation.

  8. Real-Time Spatial Monitoring of Vehicle Vibration Data as a Model for TeleGeoMonitoring Systems

    OpenAIRE

    Robidoux, Jeff

    2005-01-01

    This research presents the development and proof of concept of a TeleGeoMonitoring (TGM) system for spatially monitoring and analyzing, in real-time, data derived from vehicle-mounted sensors. In response to the concern for vibration related injuries experienced by equipment operators in surface mining and construction operations, the prototype TGM system focuses on spatially monitoring vehicle vibration in real-time. The TGM vibration system consists of 3 components: (1) Data Acquisition ...

  9. Process modeling and control applied to real-time monitoring of distillation processes by near-infrared spectroscopy.

    Science.gov (United States)

    de Oliveira, Rodrigo R; Pedroza, Ricardo H P; Sousa, A O; Lima, Kássio M G; de Juan, Anna

    2017-09-08

    A distillation device that acquires continuous and synchronized measurements of temperature, percentage of distilled fraction and NIR spectra has been designed for real-time monitoring of distillation processes. As a process model, synthetic commercial gasoline batches produced in Brazil, which contain mixtures of pure gasoline blended with ethanol have been analyzed. The information provided by this device, i.e., distillation curves and NIR spectra, has served as initial information for the proposal of new strategies of process modeling and multivariate statistical process control (MSPC). Process modeling based on PCA batch analysis provided global distillation trajectories, whereas multiset MCR-ALS analysis is proposed to obtain a component-wise characterization of the distillation evolution and distilled fractions. Distillation curves, NIR spectra or compressed NIR information under the form of PCA scores and MCR-ALS concentration profiles were tested as the seed information to build MSPC models. New on-line PCA-based MSPC approaches, some inspired on local rank exploratory methods for process analysis, are proposed and work as follows: a) MSPC based on individual process observation models, where multiple local PCA models are built considering the sole information in each observation point; b) Fixed Size Moving Window - MSPC, in which local PCA models are built considering a moving window of the current and few past observation points; and c) Evolving MSPC, where local PCA models are built with an increasing window of observations covering all points since the beginning of the process until the current observation. Performance of different approaches has been assessed in terms of sensitivity to fault detection and number of false alarms. The outcome of this work will be of general use to define strategies for on-line process monitoring and control and, in a more specific way, to improve quality control of petroleum derived fuels and other substances submitted

  10. A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

    Science.gov (United States)

    Yondo, Raul; Andrés, Esther; Valero, Eusebio

    2018-01-01

    Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi-objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective functions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the introduction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial

  11. 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

  12. Real-time radiography

    International Nuclear Information System (INIS)

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

    1981-01-01

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

  13. Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

    Science.gov (United States)

    Chang, Ya-Ting; Chang, Li-Chiu; Chang, Fi-John

    2005-04-01

    To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input-output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.

  14. Simultaneous fitting of real-time PCR data with efficiency of amplification modeled as Gaussian function of target fluorescence

    Directory of Open Access Journals (Sweden)

    Lazar Andreas

    2008-02-01

    Full Text Available Abstract Background In real-time PCR, it is necessary to consider the efficiency of amplification (EA of amplicons in order to determine initial target levels properly. EAs can be deduced from standard curves, but these involve extra effort and cost and may yield invalid EAs. Alternatively, EA can be extracted from individual fluorescence curves. Unfortunately, this is not reliable enough. Results Here we introduce simultaneous non-linear fitting to determine – without standard curves – an optimal common EA for all samples of a group. In order to adjust EA as a function of target fluorescence, and still to describe fluorescence as a function of cycle number, we use an iterative algorithm that increases fluorescence cycle by cycle and thus simulates the PCR process. A Gauss peak function is used to model the decrease of EA with increasing amplicon accumulation. Our approach was validated experimentally with hydrolysis probe or SYBR green detection with dilution series of 5 different targets. It performed distinctly better in terms of accuracy than standard curve, DART-PCR, and LinRegPCR approaches. Based on reliable EAs, it was possible to detect that for some amplicons, extraordinary fluorescence (EA > 2.00 was generated with locked nucleic acid hydrolysis probes, but not with SYBR green. Conclusion In comparison to previously reported approaches that are based on the separate analysis of each curve and on modelling EA as a function of cycle number, our approach yields more accurate and precise estimates of relative initial target levels.

  15. Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

    Science.gov (United States)

    Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

    2018-03-29

    Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

  16. Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

    Science.gov (United States)

    Shafer, Jaclyn A.; Watson, Leela R.

    2015-01-01

    Customer: NASA's Launch Services Program (LSP), Ground Systems Development and Operations (GSDO), and Space Launch System (SLS) programs. NASA's LSP, GSDO, SLS and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). For example, to determine if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 kilometer Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the AMU high-resolution WRF Environmental Modeling System (EMS) model (Watson 2013) in real-time. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The model was set up with a triple-nested grid configuration over KSC/CCAFS based on previous AMU work (Watson 2013). The outer domain (D01) has 12-kilometer grid spacing, the middle domain (D02) has 4-kilometer grid spacing, and the inner domain (D03) has 1.33-kilometer grid spacing. The model runs a 12-hour forecast every hour, D01 and D02 domain outputs are available once an hour and D03 is every 15 minutes during the forecast period. The AMU assessed the WRF-EMS 1

  17. Interactive Online Real-time Groundwater Model for Irrigation Water Allocation in the Heihe Mid-reaches, China

    Science.gov (United States)

    Pedrazzini, G.; Kinzelbach, W.

    2016-12-01

    In the Heihe Basin and many other semi-arid regions in the world the ongoing introduction of smart meter IC-card systems on farmers' pumping wells will soon allow monitoring and control of abstractions with the goal of preventing further depletion of the resource. In this regard, a major interest of policy makers concerns the development of new and the improvement of existing legislation on pricing schemes and groundwater/surface water quotas. Predictive knowledge on the development of groundwater levels for different allocation schemes or climatic change scenarios is required to support decision-makers in this task. In the past groundwater models have been a static component of investigations and their results delivered in the form of reports. We set up and integrated a groundwater model into a user-friendly web-based environment, allowing direct and easy access to the novice user. Through operating sliders the user can select an irrigation district, change irrigation patterns such as partitioning of surface- and groundwater, size of irrigation area, irrigation efficiency, as well as a number of climate related parameters. Reactive handles allow to display the results in real-time. The implemented software is all license free. The tool is currently being introduced to irrigation district managers in the project area. Findings will be available after some practical experience to be expected in a given time. The accessibility via a web-interface is a novelty in the context of groundwater models. It allows delivering a product accessible from everywhere and from any device. The maintenance and if necessary updating of model or software can occur remotely. Feedback mechanisms between reality and prediction will be introduced and the model periodically updated through data assimilation as new data becomes available. This will render the model a dynamic tool steadily available and evolving over time.

  18. EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

    Science.gov (United States)

    MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

    2017-12-01

    Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

  19. Inverse modelling for real-time estimation of radiological consequences in the early stage of an accidental radioactivity release.

    Science.gov (United States)

    Pecha, Petr; Šmídl, Václav

    2016-11-01

    A stepwise sequential assimilation algorithm is proposed based on an optimisation approach for recursive parameter estimation and tracking of radioactive plume propagation in the early stage of a radiation accident. Predictions of the radiological situation in each time step of the plume propagation are driven by an existing short-term meteorological forecast and the assimilation procedure manipulates the model parameters to match the observations incoming concurrently from the terrain. Mathematically, the task is a typical ill-posed inverse problem of estimating the parameters of the release. The proposed method is designated as a stepwise re-estimation of the source term release dynamics and an improvement of several input model parameters. It results in a more precise determination of the adversely affected areas in the terrain. The nonlinear least-squares regression methodology is applied for estimation of the unknowns. The fast and adequately accurate segmented Gaussian plume model (SGPM) is used in the first stage of direct (forward) modelling. The subsequent inverse procedure infers (re-estimates) the values of important model parameters from the actual observations. Accuracy and sensitivity of the proposed method for real-time forecasting of the accident propagation is studied. First, a twin experiment generating noiseless simulated "artificial" observations is studied to verify the minimisation algorithm. Second, the impact of the measurement noise on the re-estimated source release rate is examined. In addition, the presented method can be used as a proposal for more advanced statistical techniques using, e.g., importance sampling. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Energy-based method for near-real time modeling of sound field in complex urban environments.

    Science.gov (United States)

    Pasareanu, Stephanie M; Remillieux, Marcel C; Burdisso, Ricardo A

    2012-12-01

    Prediction of the sound field in large urban environments has been limited thus far by the heavy computational requirements of conventional numerical methods such as boundary element (BE) or finite-difference time-domain (FDTD) methods. Recently, a considerable amount of work has been devoted to developing energy-based methods for this application, and results have shown the potential to compete with conventional methods. However, these developments have been limited to two-dimensional (2-D) studies (along street axes), and no real description of the phenomena at issue has been exposed. Here the mathematical theory of diffusion is used to predict the sound field in 3-D complex urban environments. A 3-D diffusion equation is implemented by means of a simple finite-difference scheme and applied to two different types of urban configurations. This modeling approach is validated against FDTD and geometrical acoustic (GA) solutions, showing a good overall agreement. The role played by diffraction near buildings edges close to the source is discussed, and suggestions are made on the possibility to predict accurately the sound field in complex urban environments, in near real time simulations.

  1. Comparison of methods of DNA extraction for real-time PCR in a model of pleural tuberculosis.

    Science.gov (United States)

    Santos, Ana; Cremades, Rosa; Rodríguez, Juan Carlos; García-Pachón, Eduardo; Ruiz, Montserrat; Royo, Gloria

    2010-01-01

    Molecular methods have been reported to have different sensitivities in the diagnosis of pleural tuberculosis and this may in part be caused by the use of different methods of DNA extraction. Our study compares nine DNA extraction systems in an experimental model of pleural tuberculosis. An inoculum of Mycobacterium tuberculosis was added to 23 pleural liquid samples with different characteristics. DNA was subsequently extracted using nine different methods (seven manual and two automatic) for analysis with real-time PCR. Only two methods were able to detect the presence of M. tuberculosis DNA in all the samples: extraction using columns (Qiagen) and automated extraction with the TNAI system (Roche). The automatic method is more expensive, but requires less time. Almost all the false negatives were because of the difficulty involved in extracting M. tuberculosis DNA, as in general, all the methods studied are capable of eliminating inhibitory substances that block the amplification reaction. The method of M. tuberculosis DNA extraction used affects the results of the diagnosis of pleural tuberculosis by molecular methods. DNA extraction systems that have been shown to be effective in pleural liquid should be used.

  2. Direct Observation of Long-Range Transport Using Continuously Sounding Balloons and Near-Real-Time Trajectory Modeling

    Science.gov (United States)

    Voss, P. B.; Zaveri, R. A.; Berkowitz, C. M.

    2009-12-01

    Controlled Meteorological (CMET) balloons have been used in several recent studies to measure long-range transport over periods as long as 30 hours and distances up to 1000 kilometers. By repeatedly performing shallow soundings as they drift, CMET balloons can quantify evolving atmospheric structure, mixing events, shear advection, and dispersion during transport. In addition, the quasi-Lagrangian wind profiles can be used to drive a multi-layer trajectory model in which the advected air parcels follow the underlying terrain, or are constrained by altitude, potential temperature, or tracer concentration. Data from a coordinated balloon-aircraft study of long range transport over Texas (SETTS 2005) show that the reconstructed trajectories accurately track residual-layer urban outflow (and at times even its fine-scale structure) over distances of many hundreds of kilometers. The reconstructed trajectories and evolving profile visualizations are increasingly being made available in near-real time during balloon flights, supporting data-driven flight planning and sophisticated process studies relevant to atmospheric chemistry and climate. Multilayer trajectories (black grids) derived from CMET balloon flight paths (grey lines) for a transport event across Texas in 2005.

  3. Real-time temperature estimation and monitoring of HIFU ablation through a combined modeling and passive acoustic mapping approach

    International Nuclear Information System (INIS)

    Jensen, C R; Cleveland, R O; Coussios, C C

    2013-01-01

    Passive acoustic mapping (PAM) has been recently demonstrated as a method of monitoring focused ultrasound therapy by reconstructing the emissions created by inertially cavitating bubbles (Jensen et al 2012 Radiology 262 252–61). The published method sums energy emitted by cavitation from the focal region within the tissue and uses a threshold to determine when sufficient energy has been delivered for ablation. The present work builds on this approach to provide a high-intensity focused ultrasound (HIFU) treatment monitoring software that displays both real-time temperature maps and a prediction of the ablated tissue region. This is achieved by determining heat deposition from two sources: (i) acoustic absorption of the primary HIFU beam which is calculated via a nonlinear model, and (ii) absorption of energy from bubble acoustic emissions which is estimated from measurements. The two sources of heat are used as inputs to the bioheat equation that gives an estimate of the temperature of the tissue as well as estimates of tissue ablation. The method has been applied to ex vivo ox liver samples and the estimated temperature is compared to the measured temperature and shows good agreement, capturing the effect of cavitation-enhanced heating on temperature evolution. In conclusion, it is demonstrated that by using PAM and predictions of heating it is possible to produce an evolving estimate of cell death during exposure in order to guide treatment for monitoring ablative HIFU therapy. (paper)

  4. GIS model-based real-time hydrological forecasting and operation management system for the Lake Balaton and its watershed

    Science.gov (United States)

    Adolf Szabó, János; Zoltán Réti, Gábor; Tóth, Tünde

    2017-04-01

    Today, the most significant mission of the decision makers on integrated water management issues is to carry out sustainable management for sharing the resources between a variety of users and the environment under conditions of considerable uncertainty (such as climate/land-use/population/etc. change) conditions. In light of this increasing water management complexity, we consider that the most pressing needs is to develop and implement up-to-date GIS model-based real-time hydrological forecasting and operation management systems for aiding decision-making processes to improve water management. After years of researches and developments the HYDROInform Ltd. has developed an integrated, on-line IT system (DIWA-HFMS: DIstributed WAtershed - Hydrologyc Forecasting & Modelling System) which is able to support a wide-ranging of the operational tasks in water resources management such as: forecasting, operation of lakes and reservoirs, water-control and management, etc. Following a test period, the DIWA-HFMS has been implemented for the Lake Balaton and its watershed (in 500 m resolution) at Central-Transdanubian Water Directorate (KDTVIZIG). The significant pillars of the system are: - The DIWA (DIstributed WAtershed) hydrologic model, which is a 3D dynamic water-balance model that distributed both in space and its parameters, and which was developed along combined principles but its mostly based on physical foundations. The DIWA integrates 3D soil-, 2D surface-, and 1D channel-hydraulic components as well. - Lakes and reservoir-operating component; - Radar-data integration module; - fully online data collection tools; - scenario manager tool to create alternative scenarios, - interactive, intuitive, highly graphical user interface. In Vienna, the main functions, operations and results-management of the system will be presented.

  5. Using Agent-Based Modeling to Enhance System-Level Real-time Control of Urban Stormwater Systems

    Science.gov (United States)

    Rimer, S.; Mullapudi, A. M.; Kerkez, B.

    2017-12-01

    The ability to reduce combined-sewer overflow (CSO) events is an issue that challenges over 800 U.S. municipalities. When the volume of a combined sewer system or wastewater treatment plant is exceeded, untreated wastewater then overflows (a CSO event) into nearby streams, rivers, or other water bodies causing localized urban flooding and pollution. The likelihood and impact of CSO events has only exacerbated due to urbanization, population growth, climate change, aging infrastructure, and system complexity. Thus, there is an urgent need for urban areas to manage CSO events. Traditionally, mitigating CSO events has been carried out via time-intensive and expensive structural interventions such as retention basins or sewer separation, which are able to reduce CSO events, but are costly, arduous, and only provide a fixed solution to a dynamic problem. Real-time control (RTC) of urban drainage systems using sensor and actuator networks has served as an inexpensive and versatile alternative to traditional CSO intervention. In particular, retrofitting individual stormwater elements for sensing and automated active distributed control has been shown to significantly reduce the volume of discharge during CSO events, with some RTC models demonstrating a reduction upwards of 90% when compared to traditional passive systems. As more stormwater elements become retrofitted for RTC, system-level RTC across complete watersheds is an attainable possibility. However, when considering the diverse set of control needs of each of these individual stormwater elements, such system-level RTC becomes a far more complex problem. To address such diverse control needs, agent-based modeling is employed such that each individual stormwater element is treated as an autonomous agent with a diverse decision making capabilities. We present preliminary results and limitations of utilizing the agent-based modeling computational framework for the system-level control of diverse, interacting

  6. Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix models

    Science.gov (United States)

    Almog, Assaf; Garlaschelli, Diego

    2014-09-01

    The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons, respectively. While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relations between binary and non-binary properties of financial time series. These relations are a novel quantification of the fact that extreme price increments occur more often when most stocks move in the same direction. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices and their mapping to spin models in statistical physics, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to accurately replicate, and mathematically characterize, the observed binary/non-binary relations. We also obtain a phase diagram allowing us to identify, based only on the instantaneous aggregate return of a set of multiple time series, a regime where the so-called ‘market mode’ has an optimal interpretation in terms of collective (endogenous) effects, a regime where it is parsimoniously explained by pure noise, and a regime where it can be regarded as a combination of endogenous and exogenous factors. Our approach allows us to connect spin models, simple stochastic processes, and ensembles of time series inferred from partial information.

  7. Bioeffects of albumin-encapsulated microbubbles and real-time myocardial contrast echocardiography in an experimental canine model

    Directory of Open Access Journals (Sweden)

    P.M.M. Dourado

    2006-06-01

    Full Text Available Myocardial contrast echocardiography has been used for assessing myocardial perfusion. Some concerns regarding its safety still remain, mainly regarding the induction of microvascular alterations. We sought to determine the bioeffects of microbubbles and real-time myocardial contrast echocardiography (RTMCE in a closed-chest canine model. Eighteen mongrel dogs were randomly assigned to two groups. Nine were submitted to continuous intravenous infusion of perfluorocarbon-exposed sonicated dextrose albumin (PESDA plus continuous imaging using power pulse inversion RTMCE for 180 min, associated with manually deflagrated high-mechanical index impulses. The control group consisted of 3 dogs submitted to continuous imaging using RTMCE without PESDA, 3 dogs received PESDA alone, and 3 dogs were sham-operated. Hemodynamics and cardiac rhythm were monitored continuously. Histological analysis was performed on cardiac and pulmonary tissues. No hemodynamic changes or cardiac arrhythmias were observed in any group. Normal left ventricular ejection fraction and myocardial perfusion were maintained throughout the protocol. Frequency of mild and focal microhemorrhage areas in myocardial and pulmonary tissue was similar in PESDA plus RTMCE and control groups. The percentages of positive microscopical fields in the myocardium were 0.4 and 0.7% (P = NS in the PESDA plus RTMCE and control groups, respectively, and in the lungs they were 2.1 and 1.1%, respectively (P = NS. In this canine model, myocardial perfusion imaging obtained with PESDA and RTMCE was safe, with no alteration in cardiac rhythm or left ventricular function. Mild and focal myocardial and pulmonary microhemorrhages were observed in both groups, and may be attributed to surgical tissue manipulation.

  8. Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix models

    International Nuclear Information System (INIS)

    Almog, Assaf; Garlaschelli, Diego

    2014-01-01

    The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons, respectively. While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relations between binary and non-binary properties of financial time series. These relations are a novel quantification of the fact that extreme price increments occur more often when most stocks move in the same direction. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices and their mapping to spin models in statistical physics, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to accurately replicate, and mathematically characterize, the observed binary/non-binary relations. We also obtain a phase diagram allowing us to identify, based only on the instantaneous aggregate return of a set of multiple time series, a regime where the so-called ‘market mode’ has an optimal interpretation in terms of collective (endogenous) effects, a regime where it is parsimoniously explained by pure noise, and a regime where it can be regarded as a combination of endogenous and exogenous factors. Our approach allows us to connect spin models, simple stochastic processes, and ensembles of time series inferred from partial information. (paper)

  9. A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

    DEFF Research Database (Denmark)

    Jiang, Yuewen; Chen, Meisen; You, Shi

    2017-01-01

    In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase...... in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view...... of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO) is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle...

  10. LANL* V1.0: a radiation belt drift shell model suitable for real-time and reanalysis applications

    Directory of Open Access Journals (Sweden)

    J. Koller

    2009-07-01

    applications to real-time radiation belt forecasting, analysis of data sets involving tens of satellite-years of observations, and other problems in space weather.

  11. Real time falling leaves

    OpenAIRE

    Vázquez Alcocer, Pere Pau; Balsa, Marcos

    2007-01-01

    There is a growing interest in simulating natural phenomena in computer graphics applications. Animating natural scenes in real time is one of the most challenging problems due to the inherent complexity of their structure, formed by millions of geometric entities, and the interactions that happen within. An example of natural scenario that is needed for games or simulation programs are forests. Forests are difficult to render because the huge amount of geometric entities and the large amount...

  12. Real Time Strategy Language

    OpenAIRE

    Hayes, Roy; Beling, Peter; Scherer, William

    2014-01-01

    Real Time Strategy (RTS) games provide complex domain to test the latest artificial intelligence (AI) research. In much of the literature, AI systems have been limited to playing one game. Although, this specialization has resulted in stronger AI gaming systems it does not address the key concerns of AI researcher. AI researchers seek the development of AI agents that can autonomously interpret learn, and apply new knowledge. To achieve human level performance, current AI systems rely on game...

  13. Real Time Processing

    CERN Multimedia

    CERN. Geneva; ANDERSON, Dustin James; DOGLIONI, Caterina

    2015-01-01

    The LHC provides experiments with an unprecedented amount of data. Experimental collaborations need to meet storage and computing requirements for the analysis of this data: this is often a limiting factor in the physics program that would be achievable if the whole dataset could be analysed. In this talk, I will describe the strategies adopted by the LHCb, CMS and ATLAS collaborations to overcome these limitations and make the most of LHC data: data parking, data scouting, and real-time analysis.

  14. Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Meng Xiong

    2015-08-01

    Full Text Available Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long- and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.

  15. Modeling Just-in-Time Communication On the Optimal Resource Utilization in Distributed Real-Time Multimedia Applications

    NARCIS (Netherlands)

    R. Yang (Ran); R.D. van der Mei (Rob); D. Roubos; F.J. Seinstra; H. Bal

    2012-01-01

    htmlabstractThe applications of multimedia content analysis (MMCA) operating in real-time environments must run under extremely strict time constraints. To meet these requirements, large-scale multimedia applications are typically executed on Grid systems consisting of large collections of

  16. Modeling Just-in-Time Communication On the Optimal Resource Utilization in Distributed Real-Time Multimedia Applications

    NARCIS (Netherlands)

    R. Yang (Ran); R.D. van der Mei (Rob); D. Roubos; F.J. Seinstra; H. Bal

    2011-01-01

    htmlabstractThe applications of multimedia content analysis (MMCA) operating in real-time environments must run under extremely strict time constraints. To meet these requirements, large-scale multimedia applications are typically executed on Grid systems consisting of large collections of

  17. Induced tauopathy in a novel 3D-culture model mediates neurodegenerative processes: a real-time study on biochips.

    Directory of Open Access Journals (Sweden)

    Diana Seidel

    Full Text Available Tauopathies including Alzheimer's disease represent one of the major health problems of aging population worldwide. Therefore, a better understanding of tau-dependent pathologies and consequently, tau-related intervention strategies is highly demanded. In recent years, several tau-focused therapies have been proposed with the aim to stop disease progression. However, to develop efficient active pharmaceutical ingredients for the broad treatment of Alzheimer's disease patients, further improvements are necessary for understanding the detailed neurodegenerative processes as well as the mechanism and side effects of potential active pharmaceutical ingredients (API in the neuronal system. In this context, there is a lack of suitable complex in vitro cell culture models recapitulating major aspects of taupathological degenerative processes in sufficient time and reproducible manner.Herewith, we describe a novel 3D SH-SY5Y cell-based, tauopathy model that shows advanced characteristics of matured neurons in comparison to monolayer cultures without the need of artificial differentiation promoting agents. Moreover, the recombinant expression of a novel highly pathologic fourfold mutated human tau variant lead to a fast and emphasized degeneration of neuritic processes. The neurodegenerative effects could be analyzed in real time and with high sensitivity using our unique microcavity array-based impedance spectroscopy measurement system. We were able to quantify a time- and concentration-dependent relative impedance decrease when Alzheimer's disease-like tau pathology was induced in the neuronal 3D cell culture model. In combination with the collected optical information, the degenerative processes within each 3D-culture could be monitored and analyzed. More strikingly, tau-specific regenerative effects caused by tau-focused active pharmaceutical ingredients could be quantitatively monitored by impedance spectroscopy.Bringing together our novel complex 3

  18. Modeling of Phenoxy Acid Herbicide Mineralization and Growth of Microbial Degraders in 15 Soils Monitored by Quantitative Real-Time PCR of the Functional tfdA Gene

    DEFF Research Database (Denmark)

    Bælum, Jacob; Prestat, Emmanuel; David, Maude M.

    2012-01-01

    continents. The mineralization patterns were fitted by zero/linear or exponential growth forms of the three-half-order models and by logarithmic (log), first-order, or zero-order kinetic models. Prior and subsequent to the mineralization event, tfdA genes were quantified using real-time PCR to estimate...

  19. Research in Distributed Real-Time Systems

    Science.gov (United States)

    Mukkamala, R.

    1997-01-01

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

  20. Real-time specifications

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  1. Real time Faraday spectrometer

    Science.gov (United States)

    Smith, Jr., Tommy E.; Struve, Kenneth W.; Colella, Nicholas J.

    1991-01-01

    This invention uses a dipole magnet to bend the path of a charged particle beam. As the deflected particles exit the magnet, they are spatially dispersed in the bend-plane of the magnet according to their respective momenta and pass to a plurality of chambers having Faraday probes positioned therein. Both the current and energy distribution of the particles is then determined by the non-intersecting Faraday probes located along the chambers. The Faraday probes are magnetically isolated from each other by thin metal walls of the chambers, effectively providing real time current-versus-energy particle measurements.

  2. Real time Faraday spectrometer

    International Nuclear Information System (INIS)

    Smith, T.E.; Struve, K.W.; Colella, N.J.

    1991-01-01

    This patent describes an invention which uses a dipole magnet to bend the path of a charged particle beam. As the deflected particles exit the magnet, they are spatially dispersed in the bend-plane of the magnet according to their respective momenta and pass to a plurality of chambers having Faraday probes positioned therein. Both the current and energy distribution of the particles is then determined by the non-intersecting Faraday probes located along the chambers. The Faraday probes are magnetically isolated from each other by thin metal walls of the chambers, effectively providing real time current-versus-energy particle measurements

  3. Using MathWorks' Simulink® and Real-Time Workshop® Code Generator to Produce Attitude Control Test and Flight Code

    OpenAIRE

    Salada, Mark; Dellinger, Wayne

    1998-01-01

    This paper describes the use of a commercial product, MathWorks' RealTime Workshop® (RTW), to generate actual flight code for NASA's Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics (TIMED) mission. The Johns Hopkins University Applied Physics Laboratory is handling the design and construction of this satellite for NASA. As TIMED is scheduled to launch in May of the year 2000, software development for both ground and flight systems are well on their way. However, based on experien...

  4. Development of a High Resolution, Real Time, Distribution-Level Metering System and Associated Visualization, Modeling, and Data Analysis Functions

    Energy Technology Data Exchange (ETDEWEB)

    Bank, J.; Hambrick, J.

    2013-05-01

    NREL is developing measurement devices and a supporting data collection network specifically targeted at electrical distribution systems to support research in this area. This paper describes the measurement network which is designed to apply real-time and high speed (sub-second) measurement principles to distribution systems that are already common for the transmission level in the form of phasor measurement units and related technologies.

  5. VERSE - Virtual Equivalent Real-time Simulation

    Science.gov (United States)

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

    2005-01-01

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

  6. Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

    Science.gov (United States)

    Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

    2014-01-01

    Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

  7. Reference genes for real-time PCR quantification of messenger RNAs and microRNAs in mouse model of obesity.

    Science.gov (United States)

    Matoušková, Petra; Bártíková, Hana; Boušová, Iva; Hanušová, Veronika; Szotáková, Barbora; Skálová, Lenka

    2014-01-01

    Obesity and metabolic syndrome is increasing health problem worldwide. Among other ways, nutritional intervention using phytochemicals is important method for treatment and prevention of this disease. Recent studies have shown that certain phytochemicals could alter the expression of specific genes and microRNAs (miRNAs) that play a fundamental role in the pathogenesis of obesity. For study of the obesity and its treatment, monosodium glutamate (MSG)-injected mice with developed central obesity, insulin resistance and liver lipid accumulation are frequently used animal models. To understand the mechanism of phytochemicals action in obese animals, the study of selected genes expression together with miRNA quantification is extremely important. For this purpose, real-time quantitative PCR is a sensitive and reproducible method, but it depends on proper normalization entirely. The aim of present study was to identify the appropriate reference genes for mRNA and miRNA quantification in MSG mice treated with green tea catechins, potential anti-obesity phytochemicals. Two sets of reference genes were tested: first set contained seven commonly used genes for normalization of messenger RNA, the second set of candidate reference genes included ten small RNAs for normalization of miRNA. The expression stability of these reference genes were tested upon treatment of mice with catechins using geNorm, NormFinder and BestKeeper algorithms. Selected normalizers for mRNA quantification were tested and validated on expression of quinone oxidoreductase, biotransformation enzyme known to be modified by catechins. The effect of selected normalizers for miRNA quantification was tested on two obesity- and diabetes- related miRNAs, miR-221 and miR-29b, respectively. Finally, the combinations of B2M/18S/HPRT1 and miR-16/sno234 were validated as optimal reference genes for mRNA and miRNA quantification in liver and 18S/RPlP0/HPRT1 and sno234/miR-186 in small intestine of MSG mice. These

  8. Real-time optical modelling and investigation of inorganic nano-layer growth onto flexible polymeric substrates

    International Nuclear Information System (INIS)

    Laskarakis, A.; Georgiou, D.; Logothetidis, S.

    2010-01-01

    A major factor for the achievement of the desirable performance, efficiency and lifetime of flexible organic electronic devices is the optimization of the encapsulation layers that protect the device active layers by atmospheric gas molecule permeation. The active layers consisted of small molecule and/or polymer organic semiconductors as well as the organic conductors need to be encapsulated into a transparent medium that will provide the necessary protection and maintain their charge generation and transport characteristics. The encapsulation layers are generally consisted of inorganic thin films (silicon oxide-SiO x and aluminium oxide-AlO x ) deposited onto the polymeric substrates, such as PolyEthylene Terephthalate (PET). In this work, in situ and real-time Spectroscopic Ellipsometry in the ultraviolet spectral region has been implemented in order to investigate the growth of inorganic SiO x and AlO x nano-layers onto PET flexible polymeric substrates as well as the PET/inorganic interface effects during the early stages of growth. The analysis of the pseudodielectric function that was measured in real-time in very short time scales (in the order of hundreds of ms) has provided detailed information on the time evolution of the thickness and deposition rate of the inorganic nano-layers during their growth process as well as on their optical and electronic properties. This work proposes a methodology for using real-time optical monitoring technique with the aim to tailor and control the functionality of these materials for application in flexible electronic devices.

  9. Real-time temperature monitoring during radiofrequency treatments on ex-vivo animal model by fiber Bragg grating sensors

    Science.gov (United States)

    Palumbo, Giovanna; Tosi, Daniele; Schena, Emiliano; Massaroni, Carlo; Ippolito, Juliet; Verze, Paolo; Carlomagno, Nicola; Tammaro, Vincenzo; Iadicicco, Agostino; Campopiano, Stefania

    2017-05-01

    Fiber Bragg Grating (FBG) sensors applied to bio-medical procedures such as surgery and rehabilitation are a valid alternative to traditional sensing techniques due to their unique characteristics. Herein we propose the use of FBG sensor arrays for accurate real-time temperature measurements during multi-step RadioFrequency Ablation (RFA) based thermal tumor treatment. Real-time temperature monitoring in the RF-applied region represents a valid feedback for the success of the thermo-ablation procedure. In order to create a thermal multi-point map around the tumor area to be treated, a proper sensing configuration was developed. In particular, the RF probe of a commercial medical instrumentation, has been equipped with properly packaged FBGs sensors. Moreover, in order to discriminate the treatment areas to be ablated as precisely as possible, a second array 3.5 cm long, made by several FBGs was used. The results of the temperature measurements during the RFA experiments conducted on ex-vivo animal liver and kidney tissues are presented herein. The proposed FBGs based solution has proven to be capable of distinguish different and consecutive discharges and for each of them, to measure the temperature profile with a resolution of 0.1 °C and a minimum spatial resolution of 5mm. Based upon our experiments, it is possible to confirm that the temperature decreases with distance from a RF peak ablation, in accordance with RF theory. The proposed solution promises to be very useful for the surgeon because a real-time temperature feedback allows for the adaptation of RFA parameters during surgery and better delineates the area under treatment.

  10. Real time spectrum analysis

    International Nuclear Information System (INIS)

    Blunden, A.; O'Prey, D.G.; Tait, W.H.

    1983-01-01

    A method is described for the separation of a composite pulse-height spectrum into its unresolved component parts, which belong to a set of measured library spectra. The method allows real-time estimation giving running estimates during acquisition of the spectrum, minimises computation space, especially for a number of parallel calculations, estimates in advance the rms errors, and produces a significance measure for the hypothesis that the composite contains only the library spectra. Least squares curve-fitting, and other methods, can be compared, with the formalism developed, allowing analytical comparison of the effect of detector energy resolution and detection efficiency. A rational basis for the choice between the various methods of spectrum analysis follows from the theory, minimising rms estimation errors. The method described is applicable for very low numbers of counts and poor resolution. (orig.)

  11. Real time urbanism

    Directory of Open Access Journals (Sweden)

    Ana Ruiz Varona

    2012-12-01

    Full Text Available Nowadays, given the technological revolution of the society of information, the administrative management of the cities faces a new problem not as related to the projection of the urban space as to the capacity of controlling and measuring the process of direct and centralized production of the cities by part of some non-homogeneous social multitudes, in a hyper-accelerated time towards instantaneity. Against libertarian apologies of the new “participative urbanisms”, the article puts forward a discourse that shows the lost associated to the new problem of temporal instantaneity. In this regard we claim new process of mediation that allow administrations and urbanist monitoring the production of the city. To that end, a previous and necessary step will be the redefinition of the role of a new real time urbanist.

  12. A Real-Time Computation Model of the Electromagnetic Force and Torque for a Maglev Planar Motor with the Concentric Winding

    Directory of Open Access Journals (Sweden)

    Baoquan Kou

    2017-01-01

    Full Text Available The traditional model of the electromagnetic force and torque does not take the coil corners into account, which is the major cause for the motor fluctuation. To reduce the fluctuation, a more accurate real-time computation model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems respectively for the stator, the mover, and the corner are established. The first harmonic of the magnetic flux density distribution of a Halbach magnet array is taken into account in this model. The coil is divided into the straight coil segment and the corner coil segment based on its structure. For the straight coil segment, the traditional Lorenz force method can be used to compute its electromagnetic force and torque, which is a function of the mover position. For the corner coil segment, however, the numerical calculation method can be used to get its respective electromagnetic force and torque. Based on the above separate analysis, an electromagnetic model can be derived, which is suitable for practical application. Compared with the well-known harmonic model, the proposed real-time computation model is found to have less model inaccuracy. Additionally, the real-time ability of the maglev planar motor model and the decoupling computation is validated by NI PXI platform (Austin, TX, USA.

  13. An integrated modeling framework for real-time irrigation scheduling: the benefit of spectroscopy and weather forecasts

    Science.gov (United States)

    Brook, Anna; Polinova, Maria; Housh, Mashor

    2016-04-01

    ). These studies have only incorporated short-term (weekly) forecasts, missing the potential benefit of the mid-term (seasonal) climate forecasts The latest progress in new data acquisition technologies (mainly in the field of Earth observation by remote sensing and imaging spectroscopy systems) as well as the state-of-the-art achievements in the fields of geographical information systems (GIS), computer science and climate and climate impact modelling enable to develop both integrated modelling and realistic spatial simulations. The present method is the use of field spectroscopy technology to keep constant monitoring of the field. The majority of previously developed decision support systems use satellite remote sensing data that provide very limited capabilities (conventional and basic parameters). The alternative is to use a more progressive technology of hyperspectral airborne or ground-based imagery data that provide an exhaustive description of the field. Nevertheless, this alternative is known to be very costly and complex. As such, we will present a low-cost imaging spectroscopy technology supported by detailed and fine-resolution field spectroscopy as a cost effective option for near field real-time monitoring tool. In order to solve the soil water balance and to predict the water irrigation volume a pedological survey is realized in the evaluation study areas.The remote sensing and field spectroscopy were applied to integrate continuous feedbacks from the field (e.g. soil moisture, organic/inorganic carbon, nitrogen, salinity, fertilizers, sulphur acid, texture; crop water-stress, plant stage, LAI , chlorophyll, biomass, yield prediction applying PROSPECT+SILT ; Fraction of Absorbed Photosynthetically Active Radiation FAPAR) estimated based on remote sensing information to minimize the errors associated with crop simulation process. A stochastic optimization model will be formulated that take into account both mid-term seasonal probabilistic climate prediction

  14. Modeling and simulation of tumor-influenced high resolution real-time physics-based breast models for model-guided robotic interventions

    Science.gov (United States)

    Neylon, John; Hasse, Katelyn; Sheng, Ke; Santhanam, Anand P.

    2016-03-01

    Breast radiation therapy is typically delivered to the patient in either supine or prone position. Each of these positioning systems has its limitations in terms of tumor localization, dose to the surrounding normal structures, and patient comfort. We envision developing a pneumatically controlled breast immobilization device that will enable the benefits of both supine and prone positioning. In this paper, we present a physics-based breast deformable model that aids in both the design of the breast immobilization device as well as a control module for the device during every day positioning. The model geometry is generated from a subject's CT scan acquired during the treatment planning stage. A GPU based deformable model is then generated for the breast. A mass-spring-damper approach is then employed for the deformable model, with the spring modeled to represent a hyperelastic tissue behavior. Each voxel of the CT scan is then associated with a mass element, which gives the model its high resolution nature. The subject specific elasticity is then estimated from a CT scan in prone position. Our results show that the model can deform at >60 deformations per second, which satisfies the real-time requirement for robotic positioning. The model interacts with a computer designed immobilization device to position the breast and tumor anatomy in a reproducible location. The design of the immobilization device was also systematically varied based on the breast geometry, tumor location, elasticity distribution and the reproducibility of the desired tumor location.

  15. Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

    International Nuclear Information System (INIS)

    Stanzel, Ph; Haberl, U; Nachtnebel, H P

    2008-01-01

    Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

  16. Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Stanzel, Ph; Haberl, U; Nachtnebel, H P [Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Muthgasse 18, 1190 Vienna (Austria)], E-mail: philipp.stanzel@boku.ac.at

    2008-11-01

    Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

  17. A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time.

    Science.gov (United States)

    Martínez-Martínez, F; Rupérez-Moreno, M J; Martínez-Sober, M; Solves-Llorens, J A; Lorente, D; Serrano-López, A J; Martínez-Sanchis, S; Monserrat, C; Martín-Guerrero, J D

    2017-11-01

    This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely randomized trees and random forest). Two different experimental setups were designed to validate and study the performance of these models under different conditions. The mean 3D Euclidean distance between nodes predicted by the models and those extracted from the FE simulations was calculated to assess the performance of the models in the validation set. The experiments proved that extremely randomized trees performed better than the other two models. The mean error committed by the three models in the prediction of the nodal displacements was under 2 mm, a threshold usually set for clinical applications. The time needed for breast compression prediction is sufficiently short to allow its use in real-time (<0.2 s). Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Statistical Real-time Model for Performance Prediction of Ship Detection from Microsatellite Electro-Optical Imagers

    Directory of Open Access Journals (Sweden)

    Lapierre FabianD

    2010-01-01

    Full Text Available Abstract For locating maritime vessels longer than 45 meters, such vessels are required to set up an Automatic Identification System (AIS used by vessel traffic services. However, when a boat is shutting down its AIS, there are no means to detect it in open sea. In this paper, we use Electro-Optical (EO imagers for noncooperative vessel detection when the AIS is not operational. As compared to radar sensors, EO sensors have lower cost, lower payload, and better computational processing load. EO sensors are mounted on LEO microsatellites. We propose a real-time statistical methodology to estimate sensor Receiver Operating Characteristic (ROC curves. It does not require the computation of the entire image received at the sensor. We then illustrate the use of this methodology to design a simple simulator that can help sensor manufacturers in optimizing the design of EO sensors for maritime applications.

  19. Flexible automated systems of real time mining operation management: concepts, architecture, models of network engineering for data transmission and processing

    Energy Technology Data Exchange (ETDEWEB)

    Markhasin, A.B.

    1987-11-01

    Since the mid 1960's considerable effort has been invested by the mining industry and its research institutions and by universities to create real time mining management automation systems. Some of the shortcomings which still persist in realizing the efficiency such systems can offer are due to objective and subjective factors within and outside the management systems: the creation of the component base, automation equipment, and computer technology, on the one hand, and the organization, process, engineering, and coordination of mining work on the other. This review addresses several of these shortcomings with recommendations for their solution in a primary and systematic way and suggests methods for the implementation of microprocessors and a network of flexible data transmission and processing facilities for both surface and underground mining.

  20. 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.

  1. Real-time stereo matching architecture based on 2D MRF model: a memory-efficient systolic array

    Directory of Open Access Journals (Sweden)

    Park Sungchan

    2011-01-01

    Full Text Available Abstract There is a growing need in computer vision applications for stereopsis, requiring not only accurate distance but also fast and compact physical implementation. Global energy minimization techniques provide remarkably precise results. But they suffer from huge computational complexity. One of the main challenges is to parallelize the iterative computation, solving the memory access problem between the big external memory and the massive processors. Remarkable memory saving can be obtained with our memory reduction scheme, and our new architecture is a systolic array. If we expand it into N's multiple chips in a cascaded manner, we can cope with various ranges of image resolutions. We have realized it using the FPGA technology. Our architecture records 19 times smaller memory than the global minimization technique, which is a principal step toward real-time chip implementation of the various iterative image processing algorithms with tiny and distributed memory resources like optical flow, image restoration, etc.

  2. Application of WRF - SWAT OpenMI 2.0 based models integration for real time hydrological modelling and forecasting

    Science.gov (United States)

    Bugaets, Andrey; Gonchukov, Leonid

    2014-05-01

    Intake of deterministic distributed hydrological models into operational water management requires intensive collection and inputting of spatial distributed climatic information in a timely manner that is both time consuming and laborious. The lead time of the data pre-processing stage could be essentially reduced by coupling of hydrological and numerical weather prediction models. This is especially important for the regions such as the South of the Russian Far East where its geographical position combined with a monsoon climate affected by typhoons and extreme heavy rains caused rapid rising of the mountain rivers water level and led to the flash flooding and enormous damage. The objective of this study is development of end-to-end workflow that executes, in a loosely coupled mode, an integrated modeling system comprised of Weather Research and Forecast (WRF) atmospheric model and Soil and Water Assessment Tool (SWAT 2012) hydrological model using OpenMI 2.0 and web-service technologies. Migration SWAT into OpenMI compliant involves reorganization of the model into a separate initialization, performing timestep and finalization functions that can be accessed from outside. To save SWAT normal behavior, the source code was separated from OpenMI-specific implementation into the static library. Modified code was assembled into dynamic library and wrapped into C# class implemented the OpenMI ILinkableComponent interface. Development of WRF OpenMI-compliant component based on the idea of the wrapping web-service clients into a linkable component and seamlessly access to output netCDF files without actual models connection. The weather state variables (precipitation, wind, solar radiation, air temperature and relative humidity) are processed by automatic input selection algorithm to single out the most relevant values used by SWAT model to yield climatic data at the subbasin scale. Spatial interpolation between the WRF regular grid and SWAT subbasins centroid (which are

  3. Development of a real-time fuel cell stack modelling solution with integrated test rig interface for the generic fuel cell modelling environment (GenFC) software

    Energy Technology Data Exchange (ETDEWEB)

    Fraser, S.D.; Monsberger, M.; Hacker, V. [Graz Univ. of Technology, Graz (Austria). Christian Doppler Laboratory for Fuel Cell Systems; Gubner, A.; Reimer, U. [Forschungszentrum Julich, Julich (Germany)

    2007-07-01

    Since the late 1980s, numerous FC models have been developed by scientists and engineers worldwide to design, control and optimize fuel cells (FCs) and fuel cell (FC) power systems. However, state-of-the-art FC models have only a small range of applications within the versatile field of FC modelling. As fuel cell technology approaches commercialization, the scientific community is faced with the challenge of providing robust fuel cell models that are compatible with established processes in industrial product development. One such process, known as Hardware in the Loop (HiL), requires real-time modelling capability. HiL is used for developing and testing hardware components by adding the complexity of the related dynamic systems with mathematical representations. Sensors and actuators are used to interface simulated and actual hardware components. As such, real-time fuel cell models are among the key elements in the development of the Generic Fuel Cell Modelling Environment (GenFC) software. Six European partners are developing GenFC under the support of the Sixth European Framework Programme for Research and Technological Development (FP6). GenFC is meant to increase the use of fuel cell modelling for systems design and to enable cost- and time-efficient virtual experiments for optimizing operating parameters. This paper presented an overview of the GenFC software and the GenFC HiL functionality. It was concluded that GenFC is going to be an extendable software tool providing FC modelling techniques and solutions to a wide range of different FC modelling applications. By combining the flexibility of the GenFC software with this HiL-specific functionality, GenFC is going to promote the use of FC model-based HiL technology in FC system development. 9 figs.

  4. A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

    Directory of Open Access Journals (Sweden)

    Yuewen Jiang

    2017-04-01

    Full Text Available In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle swarm algorithm (QPSO. Finally, the impacts of associated parameters on the separate trading and unified trading model are analyzed to verify the superiority of the proposed model and algorithm.

  5. Real-time forecasting of an epidemic using a discrete time stochastic model: a case study of pandemic influenza (H1N1-2009

    Directory of Open Access Journals (Sweden)

    Nishiura Hiroshi

    2011-02-01

    Full Text Available Abstract Background Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. Methods A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009 in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. Results The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Conclusions Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance.

  6. Real time programming environment for Windows

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-04-01

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

  7. Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agent’s Location Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Cédric Beaulac

    2017-01-01

    Full Text Available We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.

  8. Updating long-range transport model predictions using real-time monitoring data in case of nuclear accidents with release to the atmosphere

    International Nuclear Information System (INIS)

    Raes, Frank; Tassone, Caterina; Grippa, Gianni; Zarimpas, Nicolas; Graziani, Giovanni

    1991-01-01

    A procedure is developed to reduce the uncertainties of long-range transport model predictions, in case of a large scale nuclear accident. It is based on the availability in 'real time' of the concentrations of airborne radioactive aerosols from automatic on-line monitors, which are presently being installed throughout Europe. Essentially, the procedure consists of: (1) constructing new (area) source terms from the measured field data as they become available; and (2) restart the prediction with these sources, rather than with the original (point) source. The procedure is applied to the Chernobyl accident. It is shown that the procedure is feasible and might result in an improvement of the prediction of the location of the cloud by several hundreds of kilometers and the actual levels with an order of magnitude. The weak point is the treatment of the vertical structure and transport of the cloud, which can only be solved when 'real-time' upper air observations are also available. (author)

  9. Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Chamana, Manohar; Prabakar, Kumaraguru; Palmintier, Bryan; Baggu, Murali M.

    2017-04-11

    A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source to enable use by others.

  10. Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator

    Energy Technology Data Exchange (ETDEWEB)

    Chamana, Manohar; Prabakar, Kumaraguru; Palmintier, Bryan; Baggu, Murali M.

    2017-05-11

    A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source to enable use by others.

  11. Modeling and Implementing Two-Stage AdaBoost for Real-Time Vehicle License Plate Detection

    Directory of Open Access Journals (Sweden)

    Moon Kyou Song

    2014-01-01

    Full Text Available License plate (LP detection is the most imperative part of the automatic LP recognition system. In previous years, different methods, techniques, and algorithms have been developed for LP detection (LPD systems. This paper proposes to automatical detection of car LPs via image processing techniques based on classifier or machine learning algorithms. In this paper, we propose a real-time and robust method for LPD systems using the two-stage adaptive boosting (AdaBoost algorithm combined with different image preprocessing techniques. Haar-like features are used to compute and select features from LP images. The AdaBoost algorithm is used to classify parts of an image within a search window by a trained strong classifier as either LP or non-LP. Adaptive thresholding is used for the image preprocessing method applied to those images that are of insufficient quality for LPD. This method is of a faster speed and higher accuracy than most of the existing methods used in LPD. Experimental results demonstrate that the average LPD rate is 98.38% and the computational time is approximately 49 ms.

  12. Aerodynamic Modeling of NREL 5-MW Wind Turbine for Nonlinear Control System Design: A Case Study Based on Real-Time Nonlinear Receding Horizon Control

    Directory of Open Access Journals (Sweden)

    Pedro A. Galvani

    2016-08-01

    Full Text Available The work presented in this paper has two major aspects: (i investigation of a simple, yet efficient model of the NREL (National Renewable Energy Laboratory 5-MW reference wind turbine; (ii nonlinear control system development through a real-time nonlinear receding horizon control methodology with application to wind turbine control dynamics. In this paper, the results of our simple wind turbine model and a real-time nonlinear control system implementation are shown in comparison with conventional control methods. For this purpose, the wind turbine control problem is converted into an optimization problem and is directly solved by the nonlinear backwards sweep Riccati method to generate the control protocol, which results in a non-iterative algorithm. One main contribution of this paper is that we provide evidence through simulations, that such an advanced control strategy can be used for real-time control of wind turbine dynamics. Examples are provided to validate and demonstrate the effectiveness of the presented scheme.

  13. A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm.

    Science.gov (United States)

    Feng, Kaiqiang; Li, Jie; Zhang, Xiaoming; Shen, Chong; Bi, Yu; Zheng, Tao; Liu, Jun

    2017-09-19

    In order to reduce the computational complexity, and improve the pitch/roll estimation accuracy of the low-cost attitude heading reference system (AHRS) under conditions of magnetic-distortion, a novel linear Kalman filter, suitable for nonlinear attitude estimation, is proposed in this paper. The new algorithm is the combination of two-step geometrically-intuitive correction (TGIC) and the Kalman filter. In the proposed algorithm, the sequential two-step geometrically-intuitive correction scheme is used to make the current estimation of pitch/roll immune to magnetic distortion. Meanwhile, the TGIC produces a computed quaternion input for the Kalman filter, which avoids the linearization error of measurement equations and reduces the computational complexity. Several experiments have been carried out to validate the performance of the filter design. The results demonstrate that the mean time consumption and the root mean square error (RMSE) of pitch/roll estimation under magnetic disturbances are reduced by 45.9% and 33.8%, respectively, when compared with a standard filter. In addition, the proposed filter is applicable for attitude estimation under various dynamic conditions.

  14. Rapid modeling of complex multi-fault ruptures with simplistic models from real-time GPS: Perspectives from the 2016 Mw 7.8 Kaikoura earthquake

    Science.gov (United States)

    Crowell, B.; Melgar, D.

    2017-12-01

    The 2016 Mw 7.8 Kaikoura earthquake is one of the most complex earthquakes in recent history, rupturing across at least 10 disparate faults with varying faulting styles, and exhibiting intricate surface deformation patterns. The complexity of this event has motivated the need for multidisciplinary geophysical studies to get at the underlying source physics to better inform earthquake hazards models in the future. However, events like Kaikoura beg the question of how well (or how poorly) such earthquakes can be modeled automatically in real-time and still satisfy the general public and emergency managers. To investigate this question, we perform a retrospective real-time GPS analysis of the Kaikoura earthquake with the G-FAST early warning module. We first perform simple point source models of the earthquake using peak ground displacement scaling and a coseismic offset based centroid moment tensor (CMT) inversion. We predict ground motions based on these point sources as well as simple finite faults determined from source scaling studies, and validate against true recordings of peak ground acceleration and velocity. Secondly, we perform a slip inversion based upon the CMT fault orientations and forward model near-field tsunami maximum expected wave heights to compare against available tide gauge records. We find remarkably good agreement between recorded and predicted ground motions when using a simple fault plane, with the majority of disagreement in ground motions being attributable to local site effects, not earthquake source complexity. Similarly, the near-field tsunami maximum amplitude predictions match tide gauge records well. We conclude that even though our models for the Kaikoura earthquake are devoid of rich source complexities, the CMT driven finite fault is a good enough "average" source and provides useful constraints for rapid forecasting of ground motion and near-field tsunami amplitudes.

  15. Integrating a Typhoon Event Database with an Optimal Flood Operation Model on the Real-Time Flood Control of the Tseng-Wen Reservoir

    Science.gov (United States)

    Chen, Y. W.; Chang, L. C.

    2012-04-01

    Typhoons which normally bring a great amount of precipitation are the primary natural hazard in Taiwan during flooding season. Because the plentiful rainfall quantities brought by typhoons are normally stored for the usage of the next draught period, the determination of release strategies for flood operation of reservoirs which is required to simultaneously consider not only the impact of reservoir safety and the flooding damage in plain area but also for the water resource stored in the reservoir after typhoon becomes important. This study proposes a two-steps study process. First, this study develop an optimal flood operation model (OFOM) for the planning of flood control and also applies the OFOM on Tseng-wun reservoir and the downstream plain related to the reservoir. Second, integrating a typhoon event database with the OFOM mentioned above makes the proposed planning model have ability to deal with a real-time flood control problem and names as real-time flood operation model (RTFOM). Three conditions are considered in the proposed models, OFOM and RTFOM, include the safety of the reservoir itself, the reservoir storage after typhoons and the impact of flooding in the plain area. Besides, the flood operation guideline announced by government is also considered in the proposed models. The these conditions and the guideline can be formed as an optimization problem which is solved by the genetic algorithm (GA) in this study. Furthermore, a distributed runoff model, kinematic-wave geomorphic instantaneous unit hydrograph (KW-GIUH), and a river flow simulation model, HEC-RAS, are used to simulate the river water level of Tseng-wun basin in the plain area and the simulated level is shown as an index of the impact of flooding. Because the simulated levels are required to re-calculate iteratively in the optimization model, applying a recursive artificial neural network (recursive ANN) instead of the HEC-RAS model can significantly reduce the computational burden of

  16. Risk-based technical specifications: Development and application of an approach to the generation of a plant specific real-time risk model

    International Nuclear Information System (INIS)

    Puglia, B.; Gallagher, D.; Amico, P.; Atefi, B.

    1992-10-01

    This report describes a process developed to convert an existing PRA into a model amenable to real time, risk-based technical specification calculations. In earlier studies (culminating in NUREG/CR-5742), several risk-based approaches to technical specification were evaluated. A real-time approach using a plant specific PRA capable of modeling plant configurations as they change was identified as the most comprehensive approach to control plant risk. A master fault tree logic model representative of-all of the core damage sequences was developed. Portions of the system fault trees were modularized and supercomponents comprised of component failures with similar effects were developed to reduce the size of the model and, quantification times. Modifications to the master fault tree logic were made to properly model the effect of maintenance and recovery actions. Fault trees representing several actuation systems not modeled in detail in the existing PRA were added to the master fault tree logic. This process was applied to the Surry NUREG-1150 Level 1 PRA. The master logic mode was confirmed. The model was then used to evaluate frequency associated with several plant configurations using the IRRAS code. For all cases analyzed computational time was less than three minutes. This document Volume 2, contains appendices A, B, and C. These provide, respectively: Surry Technical Specifications Model Database, Surry Technical Specifications Model, and a list of supercomponents used in the Surry Technical Specifications Model

  17. Real time analysis under EDS

    International Nuclear Information System (INIS)

    Schneberk, D.

    1985-07-01

    This paper describes the analysis component of the Enrichment Diagnostic System (EDS) developed for the Atomic Vapor Laser Isotope Separation Program (AVLIS) at Lawrence Livermore National Laboratory (LLNL). Four different types of analysis are performed on data acquired through EDS: (1) absorption spectroscopy on laser-generated spectral lines, (2) mass spectrometer analysis, (3) general purpose waveform analysis, and (4) separation performance calculations. The information produced from this data includes: measures of particle density and velocity, partial pressures of residual gases, and overall measures of isotope enrichment. The analysis component supports a variety of real-time modeling tasks, a means for broadcasting data to other nodes, and a great degree of flexibility for tailoring computations to the exact needs of the process. A particular data base structure and program flow is common to all types of analysis. Key elements of the analysis component are: (1) a fast access data base which can configure all types of analysis, (2) a selected set of analysis routines, (3) a general purpose data manipulation and graphics package for the results of real time analysis. Each of these components are described with an emphasis upon how each contributes to overall system capability. 3 figs

  18. Translating Activity Diagram from Duration Calculus for Modeling of Real-Time Systems and its Formal Verification using UPPAAL and DiVinE

    Directory of Open Access Journals (Sweden)

    Muhammad Abdul Basit Ur Rehman

    2016-01-01

    Full Text Available The RTS (Real-Time Systems are widely used in industry, home appliances, life saving systems, aircrafts, and automatic weapons. These systems need more accuracy, safety, and reliability. An accurate graphical modeling and verification of such systems is really challenging. The formal methods made it possible to model such systems with more accuracy. In this paper, we envision a strategy to overcome the inadequacy of SysML (System Modeling Language for modeling and verification of RTS, and illustrate the framework by applying it on a case study of fuel filling machine. We have defined DC (Duration Calculus implementaion based formal semantics to specify the functionality of RTS. The activity diagram in then generated from these semantics. Finally, the graphical model is verified using UPPAAL and DiVinE model checkers for validation of timed and untimed properties with accelerated verification speed. Our results suggest the use of methodology for modeling and verification of large scale real-time systems with reduced verification cost.

  19. Translating activity diagram from duration calculus for modeling of real-time systems and its formal verification using UPPAAL and DiVinE

    International Nuclear Information System (INIS)

    Rahim, M.A.B.U.; Arif, F.

    2016-01-01

    The RTS (Real-Time Systems) are widely used in industry, home appliances, life saving systems, aircrafts, and automatic weapons. These systems need more accuracy, safety, and reliability. An accurate graphical modeling and verification of such systems is really challenging. The formal methods made it possible to model such systems with more accuracy. In this paper, we envision a strategy to overcome the inadequacy of SysML (System Modeling Language) for modeling and verification of RTS, and illustrate the framework by applying it on a case study of fuel filling machine. We have defined DC (Duration Calculus) implementation based formal semantics to specify the functionality of RTS. The activity diagram in then generated from these semantics. Finally, the graphical model is verified using UPPAAL and DiVinE model checkers for validation of timed and untimed properties with accelerated verification speed. Our results suggest the use of methodology for modeling and verification of large scale real-time systems with reduced verification cost. (author)

  20. Dependable Real-Time Systems

    Science.gov (United States)

    1991-09-30

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

  1. An integrated technique for developing real-time systems

    NARCIS (Netherlands)

    Hooman, J.J.M.; Vain, J.

    1995-01-01

    The integration of conceptual modeling techniques, formal specification, and compositional verification is considered for real time systems within the knowledge engineering context. We define constructive transformations from a conceptual meta model to a real time specification language and give

  2. Monitoring diesel particulate matter and calculating diesel particulate densities using Grimm model 1.109 real-time aerosol monitors in underground mines.

    Science.gov (United States)

    Kimbal, Kyle C; Pahler, Leon; Larson, Rodney; VanDerslice, Jim

    2012-01-01

    Currently, there is no Mine Safety and Health Administration (MSHA)-approved sampling method that provides real-time results for ambient concentrations of diesel particulates. This study investigated whether a commercially available aerosol spectrometer, the Grimm Portable Aerosol Spectrometer Model 1.109, could be used during underground mine operations to provide accurate real-time diesel particulate data relative to MSHA-approved cassette-based sampling methods. A subset was to estimate size-specific diesel particle densities to potentially improve the diesel particulate concentration estimates using the aerosol monitor. Concurrent sampling was conducted during underground metal mine operations using six duplicate diesel particulate cassettes, according to the MSHA-approved method, and two identical Grimm Model 1.109 instruments. Linear regression was used to develop adjustment factors relating the Grimm results to the average of the cassette results. Statistical models using the Grimm data produced predicted diesel particulate concentrations that highly correlated with the time-weighted average cassette results (R(2) = 0.86, 0.88). Size-specific diesel particulate densities were not constant over the range of particle diameters observed. The variance of the calculated diesel particulate densities by particle diameter size supports the current understanding that diesel emissions are a mixture of particulate aerosols and a complex host of gases and vapors not limited to elemental and organic carbon. Finally, diesel particulate concentrations measured by the Grimm Model 1.109 can be adjusted to provide sufficiently accurate real-time air monitoring data for an underground mining environment.

  3. Multiprocessor scheduling for real-time systems

    CERN Document Server

    Baruah, Sanjoy; Buttazzo, Giorgio

    2015-01-01

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

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

    International Nuclear Information System (INIS)

    Finesso, Roberto; Spessa, Ezio

    2014-01-01

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

  5. The effects of residential real-time pricing contracts on transco loads, pricing, and profitability: Simulations using the N-ABLE trademark agent-based model

    International Nuclear Information System (INIS)

    Ehlen, Mark A.; Scholand, Andrew J.; Stamber, Kevin L.

    2007-01-01

    An agent-based model is constructed in which a demand aggregator sells both uniform-price and real-time price (RTP) contracts to households as means for adding price elasticity in residential power use sectors, particularly during peak-price hours of the day. Simulations suggest that RTP contracts help a demand aggregator (1) shift its long-term contracts toward off-peak hours, thereby reducing its cost of power and (2) increase its short-run profits if it is one of the first aggregators to have large numbers of RTP contracts; but (3) create susceptibilities to short-term market demand and price volatilities. (author)

  6. Modeling L2,3-Edge X-ray Absorption Spectroscopy with Real-Time Exact Two-Component Relativistic Time-Dependent Density Functional Theory.

    Science.gov (United States)

    Kasper, Joseph M; Lestrange, Patrick J; Stetina, Torin F; Li, Xiaosong

    2018-04-10

    X-ray absorption spectroscopy is a powerful technique to probe local electronic and nuclear structure. There has been extensive theoretical work modeling K-edge spectra from first principles. However, modeling L-edge spectra directly with density functional theory poses a unique challenge requiring further study. Spin-orbit coupling must be included in the model, and a noncollinear density functional theory is required. Using the real-time exact two-component method, we are able to variationally include one-electron spin-orbit coupling terms when calculating the absorption spectrum. The abilities of different basis sets and density functionals to model spectra for both closed- and open-shell systems are investigated using SiCl 4 and three transition metal complexes, TiCl 4 , CrO 2 Cl 2 , and [FeCl 6 ] 3- . Although we are working in the real-time framework, individual molecular orbital transitions can still be recovered by projecting the density onto the ground state molecular orbital space and separating contributions to the time evolving dipole moment.

  7. From advance exploration to real time steering of TBMs: A review on pertinent research in the Collaborative Research Center “Interaction Modeling in Mechanized Tunneling”

    Directory of Open Access Journals (Sweden)

    G. Meschke

    2018-03-01

    Full Text Available This paper reports on planning and construction related results from research performed at the Collaborative Research Center “Interaction Modeling in Mechanized Tunneling” at Ruhr-University Bochum, Germany. Research covers a broad spectrum of topics relevant for mechanized tunneling in soft soil conditions. This includes inverse numerical methods for advance exploration and models for the characterization of the in situ ground conditions, the interaction of the face support and the tail gap grouting with the porous soil, multi-scale models for the design of fiber reinforced segmental linings with enhanced robustness, computational methods for the numerical simulation of the tunnel advancement, the soil excavation and the material transport in the pressure chamber, logistics processes and risk analysis in urban tunneling. Targeted towards the continuous support of the construction process, a concept for real-time steering support of tunnel boring machines in conjunction with model update procedures and methods of uncertainty quantification is addressed. Keywords: Mechanized tunneling, Computational simulation, Tunnel reconnaissance, Tunnel linings, Face support, Tail void grouting, Real-time analysis, Abrasion, Process simulation

  8. Low-level profiling and MARTE-compatible modeling of software components for real-time systems

    NARCIS (Netherlands)

    Triantafyllidis, K.; Bondarev, E.; With, de P.H.N.

    2012-01-01

    In this paper, we present a method for (a) profiling of individual components at high accuracy level, (b) modeling of the components with the accurate data obtained from profiling, and (c) model conversion to the MARTE profile. The resulting performance models of individual components are used at

  9. Characterizing the Severe Turbulence Environments Associated With Commercial Aviation Accidents: A Real-Time Turbulence Model (RTTM) Designed for the Operational Prediction of Hazardous Aviation Turbulence Environments

    Science.gov (United States)

    Kaplan, Michael L.; Lux, Kevin M.; Cetola, Jeffrey D.; Huffman, Allan W.; Riordan, Allen J.; Slusser, Sarah W.; Lin, Yuh-Lang; Charney, Joseph J.; Waight, Kenneth T.

    2004-01-01

    Real-time prediction of environments predisposed to producing moderate-severe aviation turbulence is studied. We describe the numerical model and its postprocessing system designed for said prediction of environments predisposed to severe aviation turbulence as well as presenting numerous examples of its utility. The numerical model is MASS version 5.13, which is integrated over three different grid matrices in real time on a university work station in support of NASA Langley Research Center s B-757 turbulence research flight missions. The postprocessing system includes several turbulence-related products, including four turbulence forecasting indices, winds, streamlines, turbulence kinetic energy, and Richardson numbers. Additionally, there are convective products including precipitation, cloud height, cloud mass fluxes, lifted index, and K-index. Furthermore, soundings, sounding parameters, and Froude number plots are also provided. The horizontal cross-section plot products are provided from 16 000 to 46 000 ft in 2000-ft intervals. Products are available every 3 hours at the 60- and 30-km grid interval and every 1.5 hours at the 15-km grid interval. The model is initialized from the NWS ETA analyses and integrated two times a day.

  10. Expansion of the Real-Time SPoRT-Land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

    Science.gov (United States)

    Case, Jonathan L; White, Kristopher D.

    2014-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014.This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations.

  11. Development of three-dimensional patient face model that enables real-time collision detection and cutting operation for a dental simulator.

    Science.gov (United States)

    Yamaguchi, Satoshi; Yamada, Yuya; Yoshida, Yoshinori; Noborio, Hiroshi; Imazato, Satoshi

    2012-01-01

    The virtual reality (VR) simulator is a useful tool to develop dental hand skill. However, VR simulations with reactions of patients have limited computational time to reproduce a face model. Our aim was to develop a patient face model that enables real-time collision detection and cutting operation by using stereolithography (STL) and deterministic finite automaton (DFA) data files. We evaluated dependence of computational cost and constructed the patient face model using the optimum condition for combining STL and DFA data files, and assessed the computational costs for operation in do-nothing, collision, cutting, and combination of collision and cutting. The face model was successfully constructed with low computational costs of 11.3, 18.3, 30.3, and 33.5 ms for do-nothing, collision, cutting, and collision and cutting, respectively. The patient face model could be useful for developing dental hand skill with VR.

  12. Error estimates for near-Real-Time Satellite Soil Moisture as Derived from the Land Parameter Retrieval Model

    NARCIS (Netherlands)

    Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.

    2011-01-01

    A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from

  13. Dynamic, in vivo, real-time detection of retinal oxidative status in a model of elevated intraocular pressure using a novel, reversibly responsive, profluorescent nitroxide probe.

    Science.gov (United States)

    Rayner, Cassie L; Gole, Glen A; Bottle, Steven E; Barnett, Nigel L

    2014-12-01

    Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

    Science.gov (United States)

    Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

    2017-12-01

    Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

  15. Modeling and simulation of soft sensor design for real-time speed estimation, measurement and control of induction motor.

    Science.gov (United States)

    Etien, Erik

    2013-05-01

    This paper deals with the design of a speed soft sensor for induction motor. The sensor is based on the physical model of the motor. Because the validation step highlight the fact that the sensor cannot be validated for all the operating points, the model is modified in order to obtain a fully validated sensor in the whole speed range. An original feature of the proposed approach is that the modified model is derived from stability analysis using automatic control theory. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters

    OpenAIRE

    Fusco, Francesco; Ringwood, John

    2010-01-01

    Time domain control of wave energy converters requires knowledge of future incident wave elevation in order to approach conditions for optimal energy extraction. Autoregressive models revealed to be a promising approach to the prediction of future values of the wave elevation only from its past history. Results on real wave observations from different ocean locations show that AR models allow to achieve very good predictions for more than one wave period in the future if ...

  17. WRF model for precipitation simulation and its application in real-time flood forecasting in the Jinshajiang River Basin, China

    Science.gov (United States)

    Zhou, Jianzhong; Zhang, Hairong; Zhang, Jianyun; Zeng, Xiaofan; Ye, Lei; Liu, Yi; Tayyab, Muhammad; Chen, Yufan

    2017-07-01

    An accurate flood forecasting with long lead time can be of great value for flood prevention and utilization. This paper develops a one-way coupled hydro-meteorological modeling system consisting of the mesoscale numerical weather model Weather Research and Forecasting (WRF) model and the Chinese Xinanjiang hydrological model to extend flood forecasting lead time in the Jinshajiang River Basin, which is the largest hydropower base in China. Focusing on four typical precipitation events includes: first, the combinations and mode structures of parameterization schemes of WRF suitable for simulating precipitation in the Jinshajiang River Basin were investigated. Then, the Xinanjiang model was established after calibration and validation to make up the hydro-meteorological system. It was found that the selection of the cloud microphysics scheme and boundary layer scheme has a great impact on precipitation simulation, and only a proper combination of the two schemes could yield accurate simulation effects in the Jinshajiang River Basin and the hydro-meteorological system can provide instructive flood forecasts with long lead time. On the whole, the one-way coupled hydro-meteorological model could be used for precipitation simulation and flood prediction in the Jinshajiang River Basin because of its relatively high precision and long lead time.

  18. Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

    Science.gov (United States)

    Vicente, Gilberto A.

    An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

  19. Laboratory Load Model Based on 150 kVA Power Frequency Converter and Simulink Real-Time – Concept, Implementation, Experiments

    Directory of Open Access Journals (Sweden)

    Robert Małkowski

    2016-09-01

    Full Text Available First section of the paper provides technical specification of laboratory load model basing on 150 kVA power frequency converter and Simulink Real-Time platform. Assumptions, as well as control algorithm structure is presented. Theoretical considerations based on criteria which load types may be simulated using discussed laboratory setup, are described. As described model contains transformer with thyristor-controlled tap changer, wider scope of device capabilities is presented. Paper lists and describes tunable parameters, both: tunable during device operation and changed only before starting the experiment. Implementation details are given in second section of paper. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Third section describes performed laboratory tests. Different load configurations are described and experimental results are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area and arbitrary active and reactive power regulation basing on defined schedule. Different operation modes of control algorithm are described: apparent power control, active and reactive power control, active and reactive current RMS value control.

  20. On the real-time estimation of the wheel-rail contact force by means of a new nonlinear estimator design model

    Science.gov (United States)

    Strano, Salvatore; Terzo, Mario

    2018-05-01

    The dynamics of the railway vehicles is strongly influenced by the interaction between the wheel and the rail. This kind of contact is affected by several conditioning factors such as vehicle speed, wear, adhesion level and, moreover, it is nonlinear. As a consequence, the modelling and the observation of this kind of phenomenon are complex tasks but, at the same time, they constitute a fundamental step for the estimation of the adhesion level or for the vehicle condition monitoring. This paper presents a novel technique for the real time estimation of the wheel-rail contact forces based on an estimator design model that takes into account the nonlinearities of the interaction by means of a fitting model functional to reproduce the contact mechanics in a wide range of slip and to be easily integrated in a complete model based estimator for railway vehicle.

  1. Model-Assisted Control of Flow Front in Resin Transfer Molding Based on Real-Time Estimation of Permeability/Porosity Ratio

    Directory of Open Access Journals (Sweden)

    Bai-Jian Wei

    2016-09-01

    Full Text Available Resin transfer molding (RTM is a popular manufacturing technique that produces fiber reinforced polymer (FRP composites. In this paper, a model-assisted flow front control system is developed based on real-time estimation of permeability/porosity ratio using the information acquired by a visualization system. In the proposed control system, a radial basis function (RBF network meta-model is utilized to predict the position of the future flow front by inputting the injection pressure, the current position of flow front, and the estimated ratio. By conducting optimization based on the meta-model, the value of injection pressure to be implemented at each step is obtained. Moreover, a cascade control structure is established to further improve the control performance. Experiments show that the developed system successfully enhances the performance of flow front control in RTM. Especially, the cascade structure makes the control system robust to model mismatch.

  2. Real-time kinetic modeling of YSZ thin film roughness deposited by e-beam evaporation technique

    International Nuclear Information System (INIS)

    Galdikas, A.; Cerapaite-Trusinskiene, R.; Laukaitis, G.; Dudonis, J.

    2008-01-01

    In the present study, the process of yttrium-stabilized zirconia (YSZ) thin films deposition on optical quartz (SiO 2 ) substrates using e-beam deposition technique controlling electron gun power is analyzed. It was found that electron gun power influences the non-monotonous kinetics of YSZ film surface roughness. The evolution of YSZ thin film surface roughness was analyzed by a kinetic model. The model is based on the rate equations and includes processes of surface diffusion of the adatoms and the clusters, nucleation, growth and coalescence of islands in the case of thin film growth in Volmer-Weber mode. The analysis of the experimental results done by modeling explains non-monotonous kinetics and dependence of the surface roughness on the electron gun power. A good quantitative agreement with experimental results is obtained taking into account the initial roughness of the substrate surface and the amount of the clusters in the flux of evaporated material.

  3. The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting

    Science.gov (United States)

    Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Brocca, Luca; Todini, Ezio

    2017-08-01

    This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts: the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.

  4. Temporal Specification and Verification of Real-Time Systems.

    Science.gov (United States)

    1991-08-30

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

  5. Modeling and simulation of soft sensor design for real-time speed and position estimation of PMSM.

    Science.gov (United States)

    Omrane, Ines; Etien, Erik; Dib, Wissam; Bachelier, Olivier

    2015-07-01

    This paper deals with the design of a speed soft sensor for permanent magnet synchronous motor. At high speed, model-based soft sensor is used and it gives excellent results. However, it fails to deliver satisfactory performance at zero or very low speed. High-frequency soft sensor is used at low speed. We suggest to use a model-based soft sensor together with the high-frequency soft sensor to overcome the limitations of the first one at low speed range. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  6. ROSMOD: A Toolsuite for Modeling, Generating, Deploying, and Managing Distributed Real-time Component-based Software using ROS

    Directory of Open Access Journals (Sweden)

    Pranav Srinivas Kumar

    2016-09-01

    Full Text Available This paper presents the Robot Operating System Model-driven development tool suite, (ROSMOD an integrated development environment for rapid prototyping component-based software for the Robot Operating System (ROS middleware. ROSMOD is well suited for the design, development and deployment of large-scale distributed applications on embedded devices. We present the various features of ROSMOD including the modeling language, the graphical user interface, code generators, and deployment infrastructure. We demonstrate the utility of this tool with a real-world case study: an Autonomous Ground Support Equipment (AGSE robot that was designed and prototyped using ROSMOD for the NASA Student Launch competition, 2014–2015.

  7. Application of Recent Advances in Forward Modeling of Emissions from Boreal and Temperate Wildfires to Real-time Forecasting of Aerosol and Trace Gas Concentrations

    Science.gov (United States)

    Hyer, E. J.; Reid, J. S.; Kasischke, E. S.; Allen, D. J.

    2005-12-01

    The magnitude of trace gas and aerosol emissions from wildfires is a scientific problem with important implications for atmospheric composition, and is also integral to understanding carbon cycling in terrestrial ecosystems. Recent ecological research on modeling wildfire emissions has integrated theoretical advances derived from ecological fieldwork with improved spatial and temporal databases to produce "post facto" estimates of emissions with high spatial and temporal resolution. These advances have been shown to improve agreement with atmospheric observations at coarse scales, but can in principle be applied to applications, such as forecasting, at finer scales. However, several of the approaches employed in these forward models are incompatible with the requirements of real-time forecasting, requiring modification of data inputs and calculation methods. Because of the differences in data inputs used for real-time and "post-facto" emissions modeling, the key uncertainties in the forward problem are not necessarily the same for these two applications. However, adaptation of these advances in forward modeling to forecasting applications has the potential to improve air quality forecasts, and also to provide a large body of experimental data which can be used to constrain crucial uncertainties in current conceptual models of wildfire emissions. This talk describes a forward modeling method developed at the University of Maryland and its application to the Fire Locating and Modeling of Burning Emissions (FLAMBE) system at the Naval Research Laboratory. Methods for applying the outputs of the NRL aerosol forecasting system to the inverse problem of constraining emissions will also be discussed. The system described can use the feedback supplied by atmospheric observations to improve the emissions source description in the forecasting model, and can also be used for hypothesis testing regarding fire behavior and data inputs.

  8. Model predictive control of urban drainage systems: A review and perspective towards smart real-time water management

    DEFF Research Database (Denmark)

    Lund, Nadia Schou Vorndran; Falk, Anne Katrine Vinther; Borup, Morten

    2018-01-01

    Model predictive control (MPC) can be used to manage combined urban drainage systems more efficiently for protection of human health and the environment, but examples of operational implementations are rare. This paper reviews more than 30 years of partly heterogeneous research on the topic. We...... propose a terminology for MPC of urban drainage systems and a hierarchical categorization where we emphasize four overall components: the “receding horizon principle”, the “optimization model”, the “optimization solver”, and the “internal MPC model”. Most of the reported optimization models share...... of the components in the receding horizon principle. The large number of MPC formulations and evaluation approaches makes it problematic to compare different MPC methods. This review highlights methods, challenges, and research gaps in order to make MPC of urban drainage systems accessible for researchers...

  9. Real-time imaging and detection of intracranial haemorrhage by electrical impedance tomography in a piglet model.

    Science.gov (United States)

    Xu, C H; Wang, L; Shi, X T; You, F S; Fu, F; Liu, R G; Dai, M; Zhao, Z W; Gao, G D; Dong, X Z

    2010-01-01

    The aim of this study was to use electrical impedance tomography (EIT) to detect and image acute intracranial haemorrhage (ICH) in an animal model. Blood was infused into the frontal lobe of the brains of anaesthetized piglets and impedance was measured using 16 electrodes placed in a circle on the scalp. The EIT images were constructed using a filtered back-projection algorithm. The mean of all the pixel intensities within a region of interest--the mean resistivity value (MRV)--was used to evaluate the relative impedance changes in the target region. A symmetrical index (SI), reflecting the relative impedance on both sides of the brain, was also calculated. Changes in MRV and SI were associated with the injection of blood, demonstrating that EIT can successfully detect ICH in this animal model. The unique features of EIT may be beneficial for diagnosing ICH early in patients after cranial surgery, thereby reducing the risk of complications and mortality.

  10. Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm

    OpenAIRE

    Dura-Bernal, Salvador; Chadderdon, George L; Neymotin, Samuel A; Francis, Joseph T; Lytton, William W

    2014-01-01

    Brain-machine interfaces can greatly improve the performance of prosthetics. Utilizing biomimetic neuronal modeling in brain machine interfaces (BMI) offers the possibility of providing naturalistic motor-control algorithms for control of a robotic limb. This will allow finer control of a robot, while also giving us new tools to better understand the brain’s use of electrical signals. However, the biomimetic approach presents challenges in integrating technologies across multiple hardware and...

  11. Mapping urban air quality in near real-time using observations from low-cost sensors and model information.

    Science.gov (United States)

    Schneider, Philipp; Castell, Nuria; Vogt, Matthias; Dauge, Franck R; Lahoz, William A; Bartonova, Alena

    2017-09-01

    The recent emergence of low-cost microsensors measuring various air pollutants has significant potential for carrying out high-resolution mapping of air quality in the urban environment. However, the data obtained by such sensors are generally less reliable than that from standard equipment and they are subject to significant data gaps in both space and time. In order to overcome this issue, we present here a data fusion method based on geostatistics that allows for merging observations of air quality from a network of low-cost sensors with spatial information from an urban-scale air quality model. The performance of the methodology is evaluated for nitrogen dioxide in Oslo, Norway, using both simulated datasets and real-world measurements from a low-cost sensor network for January 2016. The results indicate that the method is capable of producing realistic hourly concentration fields of urban nitrogen dioxide that inherit the spatial patterns from the model and adjust the prior values using the information from the sensor network. The accuracy of the data fusion method is dependent on various factors including the total number of observations, their spatial distribution, their uncertainty (both in terms of systematic biases and random errors), as well as the ability of the model to provide realistic spatial patterns of urban air pollution. A validation against official data from air quality monitoring stations equipped with reference instrumentation indicates that the data fusion method is capable of reproducing city-wide averaged official values with an R 2 of 0.89 and a root mean squared error of 14.3 μg m -3 . It is further capable of reproducing the typical daily cycles of nitrogen dioxide. Overall, the results indicate that the method provides a robust way of extracting useful information from uncertain sensor data using only a time-invariant model dataset and the knowledge contained within an entire sensor network. Copyright © 2017 The Authors. Published

  12. Inverse modelling for real-time estimation of radiological consequences in the early stage of an accidental radioactivity release

    Czech Academy of Sciences Publication Activity Database

    Pecha, Petr; Šmídl, Václav

    2016-01-01

    Roč. 164, č. 1 (2016), s. 377-394 ISSN 0265-931X R&D Projects: GA MŠk(CZ) 7F14287; GA MV VG20102013018 Institutional support: RVO:67985556 Keywords : Inverse modelling * recursive radioactive plume tracking * Improvement of population protection * monitoring network capability Subject RIV: AQ - Safety, Health Protection, Human - Machine Impact factor: 2.310, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/pecha-0460631.pdf

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

    Science.gov (United States)

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

    2018-05-01

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

  14. A Real-Time Construction Safety Monitoring System for Hazardous Gas Integrating Wireless Sensor Network and Building Information Modeling Technologies.

    Science.gov (United States)

    Cheung, Weng-Fong; Lin, Tzu-Hsuan; Lin, Yu-Cheng

    2018-02-02

    In recent years, many studies have focused on the application of advanced technology as a way to improve management of construction safety management. A Wireless Sensor Network (WSN), one of the key technologies in Internet of Things (IoT) development, enables objects and devices to sense and communicate environmental conditions; Building Information Modeling (BIM), a revolutionary technology in construction, integrates database and geometry into a digital model which provides a visualized way in all construction lifecycle management. This paper integrates BIM and WSN into a unique system which enables the construction site to visually monitor the safety status via a spatial, colored interface and remove any hazardous gas automatically. Many wireless sensor nodes were placed on an underground construction site and to collect hazardous gas level and environmental condition (temperature and humidity) data, and in any region where an abnormal status is detected, the BIM model will alert the region and an alarm and ventilator on site will start automatically for warning and removing the hazard. The proposed system can greatly enhance the efficiency in construction safety management and provide an important reference information in rescue tasks. Finally, a case study demonstrates the applicability of the proposed system and the practical benefits, limitations, conclusions, and suggestions are summarized for further applications.

  15. Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV

    Directory of Open Access Journals (Sweden)

    Izaskun Garrido

    2016-08-01

    Full Text Available Plasma stability is one of the obstacles in the path to the successful operation of fusion devices. Numerical control-oriented codes as it is the case of the widely accepted RZIp may be used within Tokamak simulations. The novelty of this article relies in the hierarchical development of a dynamic control loop. It is based on a current profile Model Predictive Control (MPC algorithm within a multiloop structure, where a MPC is developed at each step so as to improve the Proportional Integral Derivative (PID global scheme. The inner control loop is composed of a PID-based controller that acts over the Multiple Input Multiple Output (MIMO system resulting from the RZIp plasma model of the Tokamak à Configuration Variable (TCV. The coefficients of this PID controller are initially tuned using an eigenmode reduction over the passive structure model. The control action corresponding to the state of interest is then optimized in the outer MPC loop. For the sake of comparison, both the traditionally used PID global controller as well as the multiloop enhanced MPC are applied to the same TCV shot. The results show that the proposed control algorithm presents a superior performance over the conventional PID algorithm in terms of convergence. Furthermore, this enhanced MPC algorithm contributes to extend the discharge length and to overcome the limited power availability restrictions that hinder the performance of advanced tokamaks.

  16. Real-time synchrotron x-ray observations of equiaxed solidification of aluminium alloys and implications for modelling

    Science.gov (United States)

    Prasad, A.; Liotti, E.; McDonald, S. D.; Nogita, K.; Yasuda, H.; Grant, P. S.; StJohn, D. H.

    2015-06-01

    Recently, in-situ observations were carried out by synchrotron X-ray radiography to observe the nucleation and growth in Al alloys during solidification. The nucleation and grain formation of a range of Al-Si and Al-Cu binary alloys were studied. When grain refiner was added to the alloys, the location of the nucleation events was readily observed. Once nucleation began it continued to occur in a wave of events with the movement of the temperature gradient across the field of view due to cooling. Other features observed were the settling of the primary phase grains in the Al-Si alloys and floating in the Al-Cu alloys, the effects of convection with marked fluctuation of the growth rate of the solid-liquid interface in the Al-Si alloys, and an absence of fragmentation. The microstructures are typical of those produced in the equiaxed zone of actual castings. These observations are compared with predictions arising from the Interdependence model. The results from this comparison have implications for further refinement of the model and simulation and modelling approaches in general. These implications will be discussed.

  17. Physics-electrical hybrid model for real time impedance matching and remote plasma characterization in RF plasma sources.

    Science.gov (United States)

    Sudhir, Dass; Bandyopadhyay, M; Chakraborty, A

    2016-02-01

    Plasma characterization and impedance matching are an integral part of any radio frequency (RF) based plasma source. In long pulse operation, particularly in high power operation where plasma load may vary due to different reasons (e.g. pressure and power), online tuning of impedance matching circuit and remote plasma density estimation are very useful. In some cases, due to remote interfaces, radio activation and, due to maintenance issues, power probes are not allowed to be incorporated in the ion source design for plasma characterization. Therefore, for characterization and impedance matching, more remote schemes are envisaged. Two such schemes by the same authors are suggested in these regards, which are based on air core transformer model of inductive coupled plasma (ICP) [M. Bandyopadhyay et al., Nucl. Fusion 55, 033017 (2015); D. Sudhir et al., Rev. Sci. Instrum. 85, 013510 (2014)]. However, the influence of the RF field interaction with the plasma to determine its impedance, a physics code HELIC [D. Arnush, Phys. Plasmas 7, 3042 (2000)] is coupled with the transformer model. This model can be useful for both types of RF sources, i.e., ICP and helicon sources.

  18. 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.

  19. 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.

  20. 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.

  1. Real-time bladder volume monitoring by the application of a new implantable bladder volume sensor for a small animal model

    Directory of Open Access Journals (Sweden)

    Dong Sup Lee

    2011-04-01

    Full Text Available Although real-time monitoring of bladder volume together with intravesical pressure can provide more information for understanding the functional changes of the urinary bladder, it still entails difficulties in the accurate prediction of real-time bladder volume in urodynamic studies with small animal models. We studied a new implantable bladder volume monitoring device with eight rats. During cystometry, microelectrodes prepared by the microelectromechanical systems process were placed symmetrically on both lateral walls of the bladder, and the expanded bladder volume was calculated. Immunohistological study was done after 1 week and after 4 weeks to evaluate the biocompatibility of the microelectrode. From the point that infused saline volume into the bladder was higher than 0.6 mL, estimated bladder volume was statistically correlated with the volume of saline injected (p<0.01. Additionally, the microelectromechanical system microelectrodes used in this study showed reliable biocompatibility. Therefore, the device can be used to evaluate changes in bladder volume in studies with small animals, and it may help to provide more information about functional changes in the bladder in laboratory studies. Furthermore, owing to its biocompatibility, the device could be chronically implanted in conscious ambulating animals, thus allowing a novel longitudinal study to be performed for a specific purpose.

  2. Real-Time Flood Control by Tree-Based Model Predictive Control Including Forecast Uncertainty: A Case Study Reservoir in Turkey

    Directory of Open Access Journals (Sweden)

    Gökçen Uysal

    2018-03-01

    Full Text Available Optimal control of reservoirs is a challenging task due to conflicting objectives, complex system structure, and uncertainties in the system. Real time control decisions suffer from streamflow forecast uncertainty. This study aims to use Probabilistic Streamflow Forecasts (PSFs having a lead-time up to 48 h as input for the recurrent reservoir operation problem. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC. Deterministic Streamflow Forecasts (DSFs are provided by applying random perturbations on perfect data. PSFs are synthetically generated from DSFs by a new approach which explicitly presents dynamic uncertainty evolution. We assessed different variables in the generation of stochasticity and compared the results using different scenarios. The developed real-time hourly flood control was applied to a test case which had limited reservoir storage and restricted downstream condition. According to hindcasting closed-loop experiment results, TB-MPC outperforms the deterministic counterpart in terms of decreased downstream flood risk according to different independent forecast scenarios. TB-MPC was also tested considering different number of tree branches, forecast horizons, and different inflow conditions. We conclude that using synthetic PSFs in TB-MPC can provide more robust solutions against forecast uncertainty by resolution of uncertainty in trees.

  3. A dynamic real time in vivo and static ex vivo analysis of granulomonocytic cell migration in the collagen-induced arthritis model.

    Directory of Open Access Journals (Sweden)

    Ruth Byrne

    Full Text Available Neutrophilic granulocytes and monocytes (granulomonocytic cells; GMC drive the inflammatory process at the earliest stages of rheumatoid arthritis (RA. The migratory behavior and functional properties of GMC within the synovial tissue are, however, only incompletely characterized. Here we have analyzed GMC in the murine collagen-induced arthritis (CIA model of RA using multi-photon real time in vivo microscopy together with ex vivo analysis of GMC in tissue sections.GMC were abundant as soon as clinical arthritis was apparent. GMC were motile and migrated randomly through the synovial tissue. In addition, we observed the frequent formation of cell clusters consisting of both neutrophilic granulocytes and monocytes that actively contributed to the inflammatory process of arthritis. Treatment of animals with a single dose of prednisolone reduced the mean velocity of cell migration and diminished the overall immigration of GMC.In summary, our study shows that the combined application of real time in vivo microscopy together with elaborate static post-mortem analysis of GMC enables the description of dynamic migratory characteristics of GMC together with their precise location in a complex anatomical environment. Moreover, this approach is sensitive enough to detect subtle therapeutic effects within a very short period of time.

  4. Novel real-time feedback and integrated simulation model for teaching and evaluating ultrasound-guided regional anesthesia skills in pediatric anesthesia trainees.

    Science.gov (United States)

    Moore, David L; Ding, Lili; Sadhasivam, Senthilkumar

    2012-09-01

    To assess, teach, and improve core competencies and skills sets associated with ultrasound-guided regional anesthesia (UGRA) of pediatric anesthesia trainees. To effectively assess and improve UGRA-associated cognitive and technical skills and proficiency of pediatric anesthesia trainees using simulators and real-time feedback. Ultrasound usage has been increasingly adopted by anesthesiologists to perform regional anesthesia. Pediatric UGRA performance significantly lags behind adult UGRA practice. Lack of effective UGRA training is the major reason for this unfortunate lag. Integration of ultrasound imaging, target location, and needling skills are crucial in safely performing UGRA. However, there are no standards to ensure proficiency in practice, nor in training. We implemented an UGRA instructional program for all trainees, in two parts. First, we used a unique training model for initial assessment and training of technical skills. Second, we used an instructional program that encompasses UGRA and equipment-associated cognitive skills. After baseline assessment at 0 months, we retested these trainees at 6 and 12 months to identify progression of proficiency over time. Cognitive and technical UGRA skills of trainees improved significantly over the course of time. UGRA performance average accuracy improved to 79% at 12 months from the baseline accuracy of 57%. Cognitive UGRA-related skills of trainees improved from baseline results of 52.5-79.2% at 12 months. Implementing a multifaceted assessment and real-time feedback-based training has significantly improved UGRA-related cognitive and technical skills and proficiency of pediatric anesthesia trainees. © 2012 Blackwell Publishing Ltd.

  5. iFLOOD: A Real Time Flood Forecast System for Total Water Modeling in the National Capital Region

    Science.gov (United States)

    Sumi, S. J.; Ferreira, C.

    2017-12-01

    Extreme flood events are the costliest natural hazards impacting the US and frequently cause extensive damages to infrastructure, disruption to economy and loss of lives. In 2016, Hurricane Matthew brought severe damage to South Carolina and demonstrated the importance of accurate flood hazard predictions that requires the integration of riverine and coastal model forecasts for total water prediction in coastal and tidal areas. The National Weather Service (NWS) and the National Ocean Service (NOS) provide flood forecasts for almost the entire US, still there are service-gap areas in tidal regions where no official flood forecast is available. The National capital region is vulnerable to multi-flood hazards including high flows from annual inland precipitation events and surge driven coastal inundation along the tidal Potomac River. Predicting flood levels on such tidal areas in river-estuarine zone is extremely challenging. The main objective of this study is to develop the next generation of flood forecast systems capable of providing accurate and timely information to support emergency management and response in areas impacted by multi-flood hazards. This forecast system is capable of simulating flood levels in the Potomac and Anacostia River incorporating the effects of riverine flooding from the upstream basins, urban storm water and tidal oscillations from the Chesapeake Bay. Flood forecast models developed so far have been using riverine data to simulate water levels for Potomac River. Therefore, the idea is to use forecasted storm surge data from a coastal model as boundary condition of this system. Final output of this validated model will capture the water behavior in river-estuary transition zone far better than the one with riverine data only. The challenge for this iFLOOD forecast system is to understand the complex dynamics of multi-flood hazards caused by storm surges, riverine flow, tidal oscillation and urban storm water. Automated system

  6. Comparative studies of the ITU-T prediction model for radiofrequency radiation emission and real time measurements at some selected mobile base transceiver stations in Accra, Ghana

    International Nuclear Information System (INIS)

    Obeng, S. O

    2014-07-01

    Recent developments in the electronics industry have led to the widespread use of radiofrequency (RF) devices in various areas including telecommunications. The increasing numbers of mobile base station (BTS) as well as their proximity to residential areas have been accompanied by public health concerns due to the radiation exposure. The main objective of this research was to compare and modify the ITU- T predictive model for radiofrequency radiation emission for BTS with measured data at some selected cell sites in Accra, Ghana. Theoretical and experimental assessment of radiofrequency exposures due to mobile base station antennas have been analysed. The maximum and minimum average power density measured from individual base station in the town was 1. 86µW/m2 and 0.00961µW/m2 respectively. The ITU-T Predictive model power density ranged between 6.40mW/m 2 and 0.344W/m 2 . Results obtained showed a variation between measured power density levels and the ITU-T predictive model. The ITU-T model power density levels decrease with increase in radial distance while real time measurements do not due to fluctuations during measurement. The ITU-T model overestimated the power density levels by a factor l0 5 as compared to real time measurements. The ITU-T model was modified to reduce the level of overestimation. The result showed that radiation intensity varies from one base station to another even at the same distance. Occupational exposure quotient ranged between 5.43E-10 and 1.89E-08 whilst general public exposure quotient ranged between 2.72E-09 and 9.44E-08. From the results, it shows that the RF exposure levels in Accra from these mobile phone base station antennas are below the permitted RF exposure limit to the general public recommended by the International Commission on Non-Ionizing Radiation Protection. (au)

  7. Real-Time Parameter Identification

    Data.gov (United States)

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

  8. High Availability Applications for NOMADS at the NOAA Web Operations Center Aimed at Providing Reliable Real Time Access to Operational Model Data

    Science.gov (United States)

    Alpert, J. C.; Rutledge, G.; Wang, J.; Freeman, P.; Kang, C. Y.

    2009-05-01

    The NOAA Operational Modeling Archive Distribution System (NOMADS) is now delivering high availability services as part of NOAA's official real time data dissemination at its Web Operations Center (WOC). The WOC is a web service used by all organizational units in NOAA and acts as a data repository where public information can be posted to a secure and scalable content server. A goal is to foster collaborations among the research and education communities, value added retailers, and public access for science and development efforts aimed at advancing modeling and GEO-related tasks. The services used to access the operational model data output are the Open-source Project for a Network Data Access Protocol (OPeNDAP), implemented with the Grid Analysis and Display System (GrADS) Data Server (GDS), and applications for slicing, dicing and area sub-setting the large matrix of real time model data holdings. This approach insures an efficient use of computer resources because users transmit/receive only the data necessary for their tasks including metadata. Data sets served in this way with a high availability server offer vast possibilities for the creation of new products for value added retailers and the scientific community. New applications to access data and observations for verification of gridded model output, and progress toward integration with access to conventional and non-conventional observations will be discussed. We will demonstrate how users can use NOMADS services to repackage area subsets either using repackaging of GRIB2 files, or values selected by ensemble component, (forecast) time, vertical levels, global horizontal location, and by variable, virtually a 6- Dimensional analysis services across the internet.

  9. Development of a real-time prediction model of driver behavior at intersections using kinematic time series data.

    Science.gov (United States)

    Tan, Yaoyuan V; Elliott, Michael R; Flannagan, Carol A C

    2017-09-01

    As connected autonomous vehicles (CAVs) enter the fleet, there will be a long period when these vehicles will have to interact with human drivers. One of the challenges for CAVs is that human drivers do not communicate their decisions well. Fortunately, the kinematic behavior of a human-driven vehicle may be a good predictor of driver intent within a short time frame. We analyzed the kinematic time series data (e.g., speed) for a set of drivers making left turns at intersections to predict whether the driver would stop before executing the turn. We used principal components analysis (PCA) to generate independent dimensions that explain the variation in vehicle speed before a turn. These dimensions remained relatively consistent throughout the maneuver, allowing us to compute independent scores on these dimensions for different time windows throughout the approach to the intersection. We then linked these PCA scores to whether a driver would stop before executing a left turn using the random intercept Bayesian additive regression trees. Five more road and observable vehicle characteristics were included to enhance prediction. Our model achieved an area under the receiver operating characteristic curve (AUC) of 0.84 at 94m away from the center of an intersection and steadily increased to 0.90 by 46m away from the center of an intersection. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. GPU-based parallel computing in real-time modeling of atmospheric transport and diffusion of radioactive material

    International Nuclear Information System (INIS)

    Santos, Marcelo C. dos; Pereira, Claudio M.N.A.; Schirru, Roberto; Pinheiro, André; Coordenacao de Pos-Graduacao e Pesquisa de Engenharia

    2017-01-01

    Atmospheric radionuclide dispersion systems (ARDS) are essential mechanisms to predict the consequences of unexpected radioactive releases from nuclear power plants. Considering, that during an eventuality of an accident with a radioactive material release, an accurate forecast is vital to guide the evacuation plan of the possible affected areas. However, in order to predict the dispersion of the radioactive material and its impact on the environment, the model must process information about source term (radioactive materials released, activities and location), weather condition (wind, humidity and precipitation) and geographical characteristics (topography). Furthermore, ARDS is basically composed of 4 main modules: Source Term, Wind Field, Plume Dispersion and Doses Calculations. The Wind Field and Plume Dispersion modules are the ones that require a high computational performance to achieve accurate results within an acceptable time. Taking this into account, this work focuses on the development of a GPU-based parallel Plume Dispersion module, focusing on the radionuclide transport and diffusion calculations, which use a given wind field and a released source term as parameters. The program is being developed using the C ++ programming language, allied with CUDA libraries. In comparative case study between a parallel and sequential version of the slower function of the Plume Dispersion module, a speedup of 11.63 times could be observed. (author)

  11. Modeling and Validating Time, Buffering, and Utilization of a Large-Scale, Real-Time Data Acquisition System

    CERN Document Server

    AUTHOR|(SzGeCERN)756497; The ATLAS collaboration; Garcia Garcia, Pedro Javier; Vandelli, Wainer; Froening, Holger

    2017-01-01

    Data acquisition systems for large-scale high-energy physics experiments have to handle hundreds of gigabytes per second of data, and are typically realized as specialized data centers that connect a very large number of front-end electronics devices to an event detection and storage system. The design of such systems is often based on many assumptions, small-scale experiments and a substantial amount of over-provisioning. In this work, we introduce a discrete event-based simulation tool that models the data flow of the current ATLAS data acquisition system, with the main goal to be accurate with regard to the main operational characteristics. We measure buffer occupancy counting the number of elements in buffers, resource utilization measuring output bandwidth and counting the number of active processing units, and their time evolution by comparing data over many consecutive and small periods of time. We perform studies on the error of simulation when comparing the results to a large amount of real-world ope...

  12. Modeling and Validating Time, Buffering, and Utilization of a Large-Scale, Real-Time Data Acquisition System

    CERN Document Server

    AUTHOR|(SzGeCERN)756497; The ATLAS collaboration; Garcia Garcia, Pedro Javier; Vandelli, Wainer; Froening, Holger

    2017-01-01

    Data acquisition systems for large-scale high-energy physics experiments have to handle hundreds of gigabytes per second of data, and are typically implemented as specialized data centers that connect a very large number of front-end electronics devices to an event detection and storage system. The design of such systems is often based on many assumptions, small-scale experiments and a substantial amount of over-provisioning. In this paper, we introduce a discrete event-based simulation tool that models the dataflow of the current ATLAS data acquisition system, with the main goal to be accurate with regard to the main operational characteristics. We measure buffer occupancy counting the number of elements in buffers; resource utilization measuring output bandwidth and counting the number of active processing units, and their time evolution by comparing data over many consecutive and small periods of time. We perform studies on the error in simulation when comparing the results to a large amount of real-world ...

  13. GPU-based parallel computing in real-time modeling of atmospheric transport and diffusion of radioactive material

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Marcelo C. dos; Pereira, Claudio M.N.A.; Schirru, Roberto; Pinheiro, André, E-mail: jovitamarcelo@gmail.com, E-mail: cmnap@ien.gov.br, E-mail: schirru@lmp.ufrj.br, E-mail: apinheiro99@gmail.com [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear

    2017-07-01

    Atmospheric radionuclide dispersion systems (ARDS) are essential mechanisms to predict the consequences of unexpected radioactive releases from nuclear power plants. Considering, that during an eventuality of an accident with a radioactive material release, an accurate forecast is vital to guide the evacuation plan of the possible affected areas. However, in order to predict the dispersion of the radioactive material and its impact on the environment, the model must process information about source term (radioactive materials released, activities and location), weather condition (wind, humidity and precipitation) and geographical characteristics (topography). Furthermore, ARDS is basically composed of 4 main modules: Source Term, Wind Field, Plume Dispersion and Doses Calculations. The Wind Field and Plume Dispersion modules are the ones that require a high computational performance to achieve accurate results within an acceptable time. Taking this into account, this work focuses on the development of a GPU-based parallel Plume Dispersion module, focusing on the radionuclide transport and diffusion calculations, which use a given wind field and a released source term as parameters. The program is being developed using the C ++ programming language, allied with CUDA libraries. In comparative case study between a parallel and sequential version of the slower function of the Plume Dispersion module, a speedup of 11.63 times could be observed. (author)

  14. Real-time ultrasound imaging of irreversible electroporation in a porcine liver model adequately characterizes the zone of cellular necrosis.

    Science.gov (United States)

    Schmidt, Carl R; Shires, Peter; Mootoo, Mary

    2012-02-01

      Irreversible electroporation (IRE) is a largely non-thermal method for the ablation of solid tumours. The ability of ultrasound (US) to measure the size of the IRE ablation zone was studied in a porcine liver model.   Three normal pig livers were treated in vivo with a total of 22 ablations using IRE. Ultrasound was used within minutes after ablation and just prior to liver harvest at either 6 h or 24 h after the procedure. The area of cellular necrosis was measured after staining with nitroblue tetrazolium and the percentage of cell death determined by histomorphometry.   Visible changes in the hepatic parenchyma were apparent by US after all 22 ablations using IRE. The mean maximum diameter of the ablation zone measured by US during the procedure was 20.1 ± 2.7 mm. This compared with a mean cellular necrosis zone maximum diameter of 20.3 ± 2.9 mm as measured histologically. The mean percentage of dead cells within the ablation zone was 77% at 6 h and 98% at 24 h after ablation.   Ultrasound is a useful modality for measuring the ablation zone within minutes of applying IRE to normal liver tissue. The area of parenchymal change measured by US correlates with the area of cellular necrosis. © 2011 International Hepato-Pancreato-Biliary Association.

  15. Augmenting real-time video with virtual models for enhanced visualization for simulation, teaching, training and guidance

    Science.gov (United States)

    Potter, Michael; Bensch, Alexander; Dawson-Elli, Alexander; Linte, Cristian A.

    2015-03-01

    In minimally invasive surgical interventions direct visualization of the target area is often not available. Instead, clinicians rely on images from various sources, along with surgical navigation systems for guidance. These spatial localization and tracking systems function much like the Global Positioning Systems (GPS) that we are all well familiar with. In this work we demonstrate how the video feed from a typical camera, which could mimic a laparoscopic or endoscopic camera used during an interventional procedure, can be used to identify the pose of the camera with respect to the viewed scene and augment the video feed with computer-generated information, such as rendering of internal anatomy not visible beyond the imaged surface, resulting in a simple augmented reality environment. This paper describes the software and hardware environment and methodology for augmenting the real world with virtual models extracted from medical images to provide enhanced visualization beyond the surface view achieved using traditional imaging. Following intrinsic and extrinsic camera calibration, the technique was implemented and demonstrated using a LEGO structure phantom, as well as a 3D-printed patient-specific left atrial phantom. We assessed the quality of the overlay according to fiducial localization, fiducial registration, and target registration errors, as well as the overlay offset error. Using the software extensions we developed in conjunction with common webcams it is possible to achieve tracking accuracy comparable to that seen with significantly more expensive hardware, leading to target registration errors on the order of 2 mm.

  16. Real-time vision systems

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-11-15

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

  17. Expansion of the Real-time Sport-land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

    Science.gov (United States)

    Case, Jonathan L.

    2014-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has been running a real-time version of the Land Information System (LIS) since summer 2010 (hereafter, SPoRTLIS). The real-time SPoRT-LIS runs the Noah land surface model (LSM) in an offline capacity apart from a numerical weather prediction model, using input atmospheric and precipitation analyses (i.e., "forcings") to drive the Noah LSM integration at 3-km resolution. Its objectives are to (1) produce local-scale information about the soil state for NOAA/National Weather Service (NWS) situational awareness applications such as drought monitoring and assessing flood potential, and (2) provide land surface initialization fields for local modeling initiatives. The current domain extent has been limited by the input atmospheric analyses that drive the Noah LSM integration within SPoRT-LIS, specifically the National Centers for Environmental Prediction (NCEP) Stage IV precipitation analyses. Due to the nature of the geographical edges of the Stage IV precipitation grid and its limitations in the western U.S., the SPoRT-LIS was originally confined to a domain fully nested within the Stage IV grid, over the southeastern half of the Conterminous United States (CONUS). In order to expand the real-time SPoRT-LIS to a full CONUS domain, alternative precipitation forcing datasets were explored in year-long, offline comparison runs of the Noah LSM. Based on results of these comparison simulations, we chose to implement the radar/gauge-based precipitation analyses from the National Severe Storms Laboratory as a replacement to the Stage IV product. The Multi-Radar Multi-Sensor (MRMS; formerly known as the National Mosaic and multi-sensor Quantitative precipitation estimate) product has full CONUS coverage at higher-resolution, thereby providing better coverage and greater detail than that of the Stage IV product. This paper will describe the expanded/upgraded SPoRT-LIS, present comparisons between the

  18. On Real-Time Systems Using Local Area Networks.

    Science.gov (United States)

    1987-07-01

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

  19. 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

  20. Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07

    Science.gov (United States)

    Oden, Timothy D.; Asquith, William H.; Milburn, Matthew S.

    2009-01-01

    In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the

  1. A Real-Time Joint Estimator for Model Parameters and State of Charge of Lithium-Ion Batteries in Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Jianping Gao

    2015-08-01

    Full Text Available Accurate state of charge (SoC estimation of batteries plays an important role in promoting the commercialization of electric vehicles. The main work to be done in accurately determining battery SoC can be summarized in three parts. (1 In view of the model-based SoC estimation flow diagram, the n-order resistance-capacitance (RC battery model is proposed and expected to accurately simulate the battery’s major time-variable, nonlinear characteristics. Then, the mathematical equations for model parameter identification and SoC estimation of this model are constructed. (2 The Akaike information criterion is used to determine an optimal tradeoff between battery model complexity and prediction precision for the n-order RC battery model. Results from a comparative analysis show that the first-order RC battery model is thought to be the best based on the Akaike information criterion (AIC values. (3 The real-time joint estimator for the model parameter and SoC is constructed, and the application based on two battery types indicates that the proposed SoC estimator is a closed-loop identification system where the model parameter identification and SoC estimation are corrected mutually, adaptively and simultaneously according to the observer values. The maximum SoC estimation error is less than 1% for both battery types, even against the inaccurate initial SoC.

  2. Failure analysis of real-time systems

    International Nuclear Information System (INIS)

    Jalashgar, A.; Stoelen, K.

    1998-01-01

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

  3. Non performing loans (NPLs) in a crisis economy: Long-run equilibrium analysis with a real time VEC model for Greece (2001-2015)

    Science.gov (United States)

    Konstantakis, Konstantinos N.; Michaelides, Panayotis G.; Vouldis, Angelos T.

    2016-06-01

    As a result of domestic and international factors, the Greek economy faced a severe crisis which is directly comparable only to the Great Recession. In this context, a prominent victim of this situation was the country's banking system. This paper attempts to shed light on the determining factors of non-performing loans in the Greek banking sector. The analysis presents empirical evidence from the Greek economy, using aggregate data on a quarterly basis, in the time period 2001-2015, fully capturing the recent recession. In this work, we use a relevant econometric framework based on a real time Vector Autoregressive (VAR)-Vector Error Correction (VEC) model, which captures the dynamic interdependencies among the variables used. Consistent with international evidence, the empirical findings show that both macroeconomic and financial factors have a significant impact on non-performing loans in the country. Meanwhile, the deteriorating credit quality feeds back into the economy leading to a self-reinforcing negative loop.

  4. Using a Bayesian Probabilistic Forecasting Model to Analyze the Uncertainty in Real-Time Dynamic Control of the Flood Limiting Water Level for Reservoir Operation

    DEFF Research Database (Denmark)

    Liu, Dedi; Li, Xiang; Guo, Shenglian

    2015-01-01

    Dynamic control of the flood limiting water level (FLWL) is a valuable and effective way to maximize the benefits from reservoir operation without exceeding the design risk. In order to analyze the impacts of input uncertainty, a Bayesian forecasting system (BFS) is adopted. Applying quantile water...... inflow values and their uncertainties obtained from the BFS, the reservoir operation results from different schemes can be analyzed in terms of benefits, dam safety, and downstream impacts during the flood season. When the reservoir FLWL dynamic control operation is implemented, there are two fundamental......, also deterministic water inflow was tested. The proposed model in the paper emphasizes the importance of analyzing the uncertainties of the water inflow forecasting system for real-time dynamic control of the FLWL for reservoir operation. For the case study, the selected quantile inflow from...

  5. Galactomannan enzyme immunoassay and quantitative Real Time PCR as tools to evaluate the exposure and response in a rat model of aspergillosis after posaconazole prophylaxis.

    Science.gov (United States)

    Cendejas-Bueno, Emilio; Forastiero, Agustina; Ruiz, Isabel; Mellado, Emilia; Buitrago, María José; Gavaldà, Joan; Gomez-Lopez, Alicia

    2016-11-01

    A steroid-immunosuppressed rat model of invasive pulmonary aspergillosis was use to examine the usefulness of galactomannan enzyme immunoassay (GM) and quantitative real time PCR (RT-PCR) in evaluating the association between response and exposure after a high dose of prophylactic posaconazole. Two different strains of Aspergillus fumigatus with different in vitro posaconazole susceptibility were used. Serum concentrations demonstrated similar posaconazole exposure for all treated animals. However, response to posaconazole relied on the in vitro susceptibility of the infecting strain. After prophylaxis, galactomannan index and fungal burden only decreased in those animals infected with the most susceptible strain. This study demonstrated that both biomarkers may be useful tools for predicting efficacy of antifungal compounds in prophylaxis. Copyright © 2015 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  6. Model documentation for relations between continuous real-time and discrete water-quality constituents in Cheney Reservoir near Cheney, Kansas, 2001--2009

    Science.gov (United States)

    Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

    2013-01-01

    Cheney Reservoir, located in south-central Kansas, is one of the primary water supplies for the city of Wichita, Kansas. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station in Cheney Reservoir since 2001; continuously measured physicochemical properties include specific conductance, pH, water temperature, dissolved oxygen, turbidity, fluorescence (wavelength range 650 to 700 nanometers; estimate of total chlorophyll), and reservoir elevation. Discrete water-quality samples were collected during 2001 through 2009 and analyzed for sediment, nutrients, taste-and-odor compounds, cyanotoxins, phytoplankton community composition, actinomycetes bacteria, and other water-quality measures. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physicochemical properties to compute concentrations of constituents that are not easily measured in real time. The water-quality information in this report is important to the city of Wichita because it allows quantification and characterization of potential constituents of concern in Cheney Reservoir. This report updates linear regression models published in 2006 that were based on data collected during 2001 through 2003. The update uses discrete and continuous data collected during May 2001 through December 2009. Updated models to compute dissolved solids, sodium, chloride, and suspended solids were similar to previously published models. However, several other updated models changed substantially from previously published models. In addition to updating relations that were previously developed, models also were developed for four new constituents, including magnesium, dissolved phosphorus, actinomycetes bacteria, and the cyanotoxin microcystin. In addition, a conversion factor of 0.74 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI

  7. Testing Real-Time Systems Using UPPAAL

    DEFF Research Database (Denmark)

    Hessel, Anders; Larsen, Kim Guldstrand; Mikucionis, Marius

    2008-01-01

    This chapter presents principles and techniques for model-based black-box conformance testing of real-time systems using the Uppaal model-checking tool-suite. The basis for testing is given as a network of concurrent timed automata specified by the test engineer. Relativized input...

  8. Real-time monitoring of bacterial infection in vivo: development of bioluminescent staphylococcal foreign-body and deep-thigh-wound mouse infection models.

    Science.gov (United States)

    Kuklin, Nelly A; Pancari, Gregory D; Tobery, Timothy W; Cope, Leslie; Jackson, Jesse; Gill, Charles; Overbye, Karen; Francis, Kevin P; Yu, Jun; Montgomery, Donna; Anderson, Annaliesa S; McClements, William; Jansen, Kathrin U

    2003-09-01

    Staphylococcal infections associated with catheter and prosthetic implants are difficult to eradicate and often lead to chronic infections. Development of novel antibacterial therapies requires simple, reliable, and relevant models for infection. Using bioluminescent Staphylococcus aureus, we have adapted the existing foreign-body and deep-wound mouse models of staphylococcal infection to allow real-time monitoring of the bacterial colonization of catheters or tissues. This approach also enables kinetic measurements of bacterial growth and clearance in each infected animal. Persistence of infection was observed throughout the course of the study until termination of the experiment at day 16 in a deep-wound model and day 21 in the foreign-body model, providing sufficient time to test the effects of antibacterial compounds. The usefulness of both animal models was assessed by using linezolid as a test compound and comparing bioluminescent measurements to bacterial counts. In the foreign-body model, a three-dose antibiotic regimen (2, 5, and 24 h after infection) resulted in a decrease in both luminescence and bacterial counts recovered from the implant compared to those of the mock-treated infected mice. In addition, linezolid treatment prevented the formation of subcutaneous abscesses, although it did not completely resolve the infection. In the thigh model, the same treatment regimen resulted in complete resolution of the luminescent signal, which correlated with clearance of the bacteria from the thighs.

  9. Towards Real-Time Argumentation

    Directory of Open Access Journals (Sweden)

    Vicente JULIÁN

    2016-07-01

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

  10. Skill of real-time operational forecasts with the APCC multi-model ensemble prediction system during the period 2008-2015

    Science.gov (United States)

    Min, Young-Mi; Kryjov, Vladimir N.; Oh, Sang Myeong; Lee, Hyun-Ju

    2017-12-01

    This paper assesses the real-time 1-month lead forecasts of 3-month (seasonal) mean temperature and precipitation on a monthly basis issued by the Asia-Pacific Economic Cooperation Climate Center (APCC) for 2008-2015 (8 years, 96 forecasts). It shows the current level of the APCC operational multi-model prediction system performance. The skill of the APCC forecasts strongly depends on seasons and regions that it is higher for the tropics and boreal winter than for the extratropics and boreal summer due to direct effects and remote teleconnections from boundary forcings. There is a negative relationship between the forecast skill and its interseasonal variability for both variables and the forecast skill for precipitation is more seasonally and regionally dependent than that for temperature. The APCC operational probabilistic forecasts during this period show a cold bias (underforecasting of above-normal temperature and overforecasting of below-normal temperature) underestimating a long-term warming trend. A wet bias is evident for precipitation, particularly in the extratropical regions. The skill of both temperature and precipitation forecasts strongly depends upon the ENSO strength. Particularly, the highest forecast skill noted in 2015/2016 boreal winter is associated with the strong forcing of an extreme El Nino event. Meanwhile, the relatively low skill is associated with the transition and/or continuous ENSO-neutral phases of 2012-2014. As a result the skill of real-time forecast for boreal winter season is higher than that of hindcast. However, on average, the level of forecast skill during the period 2008-2015 is similar to that of hindcast.

  11. Modelling, simulation and experimental verification for renewable agents connected to a distorted utility grid using a Real-Time Digital Simulation Platform

    International Nuclear Information System (INIS)

    Guerrero-Rodríguez, N.F.; Rey-Boué, Alexis B.

    2014-01-01

    Highlights: • A MSOGI-FLL is used to detect the frequency. • A PR harmonic-compensator is used. • Grid-connected PV system insensitive to harmonic pollution. • RTDS reinforced the final validation of the control algorithms. • Several algorithms are combined in this paper. - Abstract: The large number of Photovoltaic plants and its utilization as agents of a Distributed Generation Systems justified the increasing efforts towards the optimal design of the overall grid-connected System. In a Distributed Generation environment the low voltage 3-phase utility grid could be affected by some disturbances such as voltage unbalanced, variations of frequency and harmonics distortion and it is mandatory that the control algorithms used in the inverter can be able to maintain the power flow between the renewable agent and the low voltage 3-phase utility grid; in addition a unitary power factor must be attained. A Proportional-Resonant regulator is used to performance a current control with the output current of the inverter and a Multiple Second Order Generalized Integrator Frequency-Locked Loop (MSOGI-FLL) is used to detect the frequency of the low voltage 3-phase utility grid. Some low order harmonics are introduced in the low voltage 3-phase utility grid in order to see the effect of the harmonic compensator. In order to validate the model of the Photovoltaic Renewable agent, the synchronization algorithm and the inverter control algorithm, some simulations using MATLAB/SIMULINK from The MathWorks, Inc. are shown firstly, and secondly, some Real-Time Digital Simulation tests using a Real-Time Digital Simulation (RTDS) Platform are carried out

  12. Demonstration of a very inexpensive, turbidimetric, real-time, RT-LAMP detection platform using shrimp Laem-Singh virus (LSNV as a model.

    Directory of Open Access Journals (Sweden)

    Narong Arunrut

    Full Text Available Rapid and accurate detection of pathogens under field laboratory conditions is necessary for effective control of veterinary pathogens. Here we describe a prototype, portable, pathogen detection device developed for single tube, real-time, reverse transcription, loop-mediated isothermal amplification (RT-LAMP using Laem-Singh virus (LSNV as a model. LSNV is an RNA virus and a component cause of growth retardation in black tiger shrimp. We chose its RNA-dependent RNA polymerase (RdRp gene as the target for our tests. The basis for detection was measurement of turbidity arising from formation of a white, insoluble magnesium pyrophosphate precipitate byproduct upon amplification of the RdRp target sequence from 100 ng template RNA extracted from shrimp. The measurement device consisted of a heating block to maintain constant temperature in the RT-LAMP reaction for 8 Eppindorf sample tubes, a light-emitting diode (LED light source providing red light emission at 650 nm wavelength to pass through sample tubes, a light dependent resistance (LDR photo-detector and a software program to report turbidity events and could potentially be marketed for under US$3000. The device was connected to a computer to display real-time results in a variety of formats. The optimized protocol for LSNV detection consisted of incubation of the sample tubes at 65 °C for 1 h during which turbidity was continuously measured, and quantitative results could be obtained by reaction time measurement. The sensitivity of detection was comparable to that of conventional nested RT-PCR and there was no cross reaction with other common shrimp viruses. The device was used for quantitative measurement of relative copy numbers of LSNV RdRp in 8 shrimp tissues and they were found to be highest in the gills followed in order by the lymphoid organ and hemolymph (p ≤ 0.05. This platform can be easily adapted for detection of other pathogens under field laboratory settings.

  13. Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

    Science.gov (United States)

    Adams, Matthew D; Kanaroglou, Pavlos S

    2016-03-01

    Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved

  14. A novel mouse model of soft-tissue infection using bioluminescence imaging allows noninvasive, real-time monitoring of bacterial growth.

    Science.gov (United States)

    Yoshioka, Kenji; Ishii, Ken; Kuramoto, Tetsuya; Nagai, Shigenori; Funao, Haruki; Ishihama, Hiroko; Shiono, Yuta; Sasaki, Aya; Aizawa, Mamoru; Okada, Yasunori; Koyasu, Shigeo; Toyama, Yoshiaki; Matsumoto, Morio

    2014-01-01

    Musculoskeletal infections, including surgical-site and implant-associated infections, often cause progressive inflammation and destroy areas of the soft tissue. Treating infections, especially those caused by multi-antibiotic resistant bacteria such as methicillin-resistant Staphylococcus aureus (MRSA) remains a challenge. Although there are a few animal models that enable the quantitative evaluation of infection in soft tissues, these models are not always reproducible or sustainable. Here, we successfully established a real-time, in vivo, quantitative mouse model of soft-tissue infection in the superficial gluteus muscle (SGM) using bioluminescence imaging. A bioluminescent strain of MRSA was inoculated into the SGM of BALB/c adult male mice, followed by sequential measurement of bacterial photon intensity and serological and histological analyses of the mice. The mean photon intensity in the mice peaked immediately after inoculation and remained stable until day 28. The serum levels of interleukin-6, interleukin-1 and C-reactive protein at 12 hours after inoculation were significantly higher than those prior to inoculation, and the C-reactive protein remained significantly elevated until day 21. Histological analyses showed marked neutrophil infiltration and abscesses containing necrotic and fibrous tissues in the SGM. With this SGM mouse model, we successfully visualized and quantified stable bacterial growth over an extended period of time with bioluminescence imaging, which allowed us to monitor the process of infection without euthanizing the experimental animals. This model is applicable to in vivo evaluations of the long-term efficacy of novel antibiotics or antibacterial implants.

  15. Real time automatic scene classification

    NARCIS (Netherlands)

    Verbrugge, R.; Israël, Menno; Taatgen, N.; van den Broek, Egon; van der Putten, Peter; Schomaker, L.; den Uyl, Marten J.

    2004-01-01

    This work has been done as part of the EU VICAR (IST) project and the EU SCOFI project (IAP). The aim of the first project was to develop a real time video indexing classification annotation and retrieval system. For our systems, we have adapted the approach of Picard and Minka [3], who categorized

  16. Real time freeway incident detection.

    Science.gov (United States)

    2014-04-01

    The US Department of Transportation (US-DOT) estimates that over half of all congestion : events are caused by highway incidents rather than by rush-hour traffic in big cities. Real-time : incident detection on freeways is an important part of any mo...

  17. Real Time Conference 2016 Overview

    Science.gov (United States)

    Luchetta, Adriano

    2017-06-01

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

  18. Designing Real Time Assistive Technologies

    DEFF Research Database (Denmark)

    Sonne, To